Medicine, Faculty of
Medicine, Department of
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UBCV
Michalski, Christina
Doctor of Philosophy - PhD
University of British Columbia
Premature birth is a major contributor to under-five mortality, causing approximately 1 million deaths every year. This vulnerability stems from the high susceptibility of neonates, particularly those born prematurely, to severe life-threatening infections. The overarching goal of my thesis work was to study the immunological basis for preterm neonates’ vulnerability to infections. It was previously known that monocytes isolated from preterm cord blood show suppressed responses to innate immune activation. In Chapter 2, we employed untargeted transcriptomics comparing monocytes at rest and after LPS stimulation, from neonates born preterm (<33 weeks gestation), at term (>37 weeks gestation) and from adults. Results establish cellular energy metabolism as a major regulator of innate immune responsiveness during fetal life, perhaps to purposely limit overt inflammation in utero. Additionally, our experiments suggested a central role for mTORC1, and its negative regulator DDIT4L in suppressing innate immune responses in preterm monocytes. In Chapter 3, I developed a monocytic cell line model to study the impact of DDIT4L on innate immune function. DDIT4L overexpression limited protein synthesis, cellular proliferation and LPS-induced cytokine production. Additionally, experiments in primary neonatal monocytes revealed developmental changes in mitochondrial function. Lastly, data linking reduced DDIT4L expression to more severe inflammatory lung disease in preterm neonates point towards a putative role in preventing inflammatory-mediated tissue damage in neonates. Beyond the immediate postnatal period, preterm infants remain particularly vulnerable to respiratory viral infections. In Chapter 4, I studied infants at high-risk for respiratory syncytial virus (RSV) infections. I showed that most infants have been exposed to RSV, as evidenced by increased IgM titers, Fc receptor binding and antibody-mediated phagocytosis by the end of their first winter season. Overall, my study suggests that most high-risk preterm infants develop antibody responses against RSV by one year of age, in the absence of overt clinical signs. This challenges the dogma that preterm infants are unable to fight respiratory illnesses without getting sick and provide insights into the highest period of vulnerability to these viruses. In sum, my work provides fundamental insights into the maturation of immune responses in the first year of life in premature babies.
PREMATURE BIRTH: IMPLICATIONS FOR EARLY LIFE IMMUNITY by Christina Michalski M.S., Rutgers University, 2015 B.Sc., Marburg University, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2021 © Christina Michalski, 2021 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Premature Birth: Implications for Immunity in Early Life submitted by Christina Michalski in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Experimental Medicine Examining Committee: Dr. Pascal Lavoie, Associate Professor, Department of Pediatrics, UBC Supervisor Dr. Laura Sly, Professor, Department of Pediatrics, UBC Supervisory Committee Member Dr. Fumio Takei, Professor, Department of Pathology & Laboratory Medicine, UBC University Examiner Dr. Helene Cote, Professor, Department of Pathology & Laboratory Medicine, UBC University Examiner Additional Supervisory Committee Members: Dr. Eric Jan, Professor, Department of Biochemistry & Molecular Biology, UBC Supervisory Committee Member Dr. Dan Luciani, Associate Professor, Department of Surgery, UBC Supervisory Committee Member iii Abstract Premature birth is a major contributor to under-five mortality, causing approximately 1 million deaths every year. This vulnerability stems from the high susceptibility of neonates, particularly those born prematurely, to severe life-threatening infections. The overarching goal of my thesis work was to study the immunological basis for preterm neonates’ vulnerability to infections. It was previously known that monocytes isolated from preterm cord blood show suppressed responses to innate immune activation. In Chapter 2, we employed untargeted transcriptomics comparing monocytes at rest and after LPS stimulation, from neonates born preterm (<33 weeks gestation), at term (>37 weeks gestation) and from adults. Results establish cellular energy metabolism as a major regulator of innate immune responsiveness during fetal life, perhaps to purposely limit overt inflammation in utero. Additionally, our experiments suggested a central role for mTORC1, and its negative regulator DDIT4L in suppressing innate immune responses in preterm monocytes. In Chapter 3, I developed a monocytic cell line model to study the impact of DDIT4L on innate immune function. DDIT4L overexpression limited protein synthesis, cellular proliferation and LPS-induced cytokine production. Additionally, experiments in primary neonatal monocytes revealed developmental changes in mitochondrial function. Lastly, data linking reduced DDIT4L expression to more severe inflammatory lung disease in preterm neonates point towards a putative role in preventing inflammatory-mediated tissue damage in neonates. Beyond the immediate postnatal period, preterm infants remain particularly vulnerable to respiratory viral infections. In Chapter 4, I studied infants at high-risk for respiratory syncytial virus (RSV) infections. I showed that most infants have been exposed to RSV, as evidenced by increased IgM titers, Fc receptor binding and antibody-mediated phagocytosis by the end of their first winter season. Overall, my study suggests that most high-risk preterm infants develop antibody responses iv against RSV by one year of age, in the absence of overt clinical signs. This challenges the dogma that preterm infants are unable to fight respiratory illnesses without getting sick and provide insights into the highest period of vulnerability to these viruses. In sum, my work provides fundamental insights into the maturation of immune responses in the first year of life in premature babies. v Lay Summary Babies born too early are much more likely to develop infections in early life compared to adults or full-term babies. This thesis aims to understand why premature newborns are susceptible to infections. I found that immune cells from premature babies have low energy metabolism limiting their response to bacteria. Interestingly, my data support that preterm immune cells may purposely do this to avoid excessive inflammation that could be more damaging to their fragile body early in development. I also studied how premature babies respond to respiratory viruses immunologically and found that most produce strong antibody responses to common cold viruses. These findings suggest that contrary to the immediate period after birth, most premature infants successfully fight infections in their first year of life. Together, my thesis work sheds light into the mechanisms underlying premature babies’ vulnerability to infections. vi Preface Experiments in this thesis were designed and conducted by me with exceptions detailed below. PM Lavoie supervised the work, helped design experiments and provided input throughout. Chapter 1: Figure 1.1 was reprinted with permission from Springer Nature (license number 5112600712123) from Nakazawa, M. S., Keith, B., & Simon, M. C. (2016). Oxygen availability and metabolic adaptations. Nature Reviews. Cancer, 16(10), 663–673. doi:10.1038/nrc.2016.84 Chapter 2: Parts of chapter 2 have been published as: Kan B & Michalski C, Fu H, et al. Cellular metabolism constrains innate immune responses in early human ontogeny. Nat Commun. 2018;9(1):4822. doi:10.1038/s41467-018-07215-9, licensed under a Creative Commons Attribution 4.0 International License. Apart from the figures, figure legends and the methods section, no text has been copied from the publication. The figures from the aforementioned publication are furthermore part of B Kan’s PhD thesis, doi: 10.14288/1.0365287, licensed under Creative Commons Attribution 4.0 International License. Experiments presented in this thesis were designed by me, B Kan and PM Lavoie. Microarray samples were collected by B Kan and K Lee. The microarray was run by F Miao under the supervision of CJ Ross. The original microarray analysis was done by B Kan who also created Figure 2.2a. All other microarray analyses and figures were generated by me. The ELISA presented in Fig. 2.1d was performed by K Lee and B Kan who also produced the graph. 35S-Met/Cys pulse labeling (Fig. 2.3a,b) was performed by me, B Kan and HT Au with input from E Jan. Polysome profiling (Fig. 2.3d-f) was conducted by me with help from HT Au and E Jan. B Kan performed the qPCR. B Kan collected samples and performed Western Blot and flow cytometry analysis for MALT1, Bcl10 and Dectin 1 (Fig. 2.3g-vii i) and mTOR (Fig. 2.6c). Cytokine secretion after 2-DG blocking (Fig. 2.4a) was quantified by me and B Kan. Lactate secretion presented in Fig. 2.4d-e was measured by me using samples collected by B Kan. Seahorse experiments were conducted by B Kan, me and M Cheng under my supervision. M Aharoni-Simon and DS Luciani provided input in experimental design. The phagocytosis assay (Fig. 2.5e) was designed and carried out by B Kan and H Fu. P Tilley provided the clinical C. albicans strains. Fig. 2.3c and 2.6a were created by PM Lavoie. M Cheng assisted with sample preparation for Fig. 2.5a-c under my supervision. EA Marchant helped with clinical data collection. Chapter 3: Experiments were designed by me with input from PM Lavoie, RI Klein-Geltink and AA Sharma. Seahorse assays (Fig. 3.8b, d-g) were performed by me with help from E Ackermann (under my supervision), J Oh, A Patterson and RI Klein-Geltink. Under my supervision, R Da Silva assisted with RNA isolation and cDNA synthesis for Fig. 3.1d. The lentiviral construct was designed by PC Orban who also provided support with the cloning strategy. The construct was generated, and viral particles were produced by me and CR Popescu. Experiments presented in Fig. 3.3, 3.4, 3.5 and 3.8 were performed together with C Cheung under my supervision. CJ Lim provided the CRISPR construct and helped with the KO strategy. The DNA isolation and PCR purification for CRISPR clone screening was done by F Reicherz, O Xu, C Cheng and me. A Majdoubi helped with siRNA experiments discussed in Chapter 5. Chapter 4: The study presented in Chapter 4 was a collaboration between the laboratories of Drs. Lavoie, Alter (Harvard), Sekaly (Emory) and Haddad (Drexel) who also conceived of the initial study design. Participant recruitment was coordinated in collaboration with E Cawthorne, J Wong, viii C Christopherson and E Alonso-Prieto. Q Lai and Z Cieslak recruited patients at the Royal Columbia Hospital and A Chacko recruited patients at Surrey Memorial Hospital with help from KK Ramesh. The samples were processed by me with occasional assistance from R Da Silva, E Ackermann, Z Sharafian and EA Marchant. The systems serology experiments were designed and conducted by CM Boudreau with assistance from JS Burke under the supervision of G Alter. HR Razzaghian performed the neutralization assays with input from N Marr; results were analyzed by me. The palivizumab ELISA was run by me with assistance from F Reicherz following a protocol provided by V Demeurs-Mathieu. The mesoscale assay was run by AA Sharma with assistance from G Sanchez. E Phung, T Ruckwardt (both under the supervision of B Graham) and AA Sharma provided input for the B cell phenotyping experimental design. AA Sharma also provided the script for Phenograph analysis on which Fig. 4.2c-g are based. M Fu gave statistical advice and A Solimano and CR Popescu provided clinical relevance. All data was analyzed and graphed by me with the exception of Figure 4.1 which was created by CM Boudreau. CM Boudreau also wrote the methods description of the systems serology assays. Ethics approval for studies conducted in this thesis was obtained from the UBC Children’s & Women’s and Fraser Health Research Ethics Boards (H07-02681 for work conducted in Chapter 2 &3 and H18-01724 for work conducted in Chapter 4). Informed consent was obtained from all participants except for some of the preterm cord blood samples for which consent was unobtainable (e.g. due to patient transfer to another hospital). In accordance with local ethics protocols, those samples were used without any patient information collected besides gestational age at birth. All studies were conducted in accordance with the declaration of Helsinki. ix Table of Contents Abstract ................................................................................................................................... iii Lay Summary ............................................................................................................................ v Preface ...................................................................................................................................... vi Table of Contents ..................................................................................................................... ix List of Tables .......................................................................................................................... xiv List of Figures.......................................................................................................................... xv List of Abbreviations ............................................................................................................. xvii Acknowledgements ................................................................................................................. xxi Chapter 1: Introduction ............................................................................................................ 1 1.1 Preterm birth – impacts on infant immunity .................................................................1 1.1.1 Neonatal sepsis ........................................................................................................2 1.1.2 Infections during the infant period ...........................................................................3 1.1.3 Clinical inflammation syndromes in preterm newborns ............................................4 1.1.3.1 Necrotizing enterocolitis ..................................................................................4 1.1.3.2 Bronchopulmonary dysplasia ...........................................................................5 1.1.4 Contributing factors to high infection risk in preterm neonates .................................5 1.1.5 Characteristics of the preterm immune system .........................................................6 1.2 Regulation of neonatal monocyte responses .................................................................9 1.2.1 Myeloid cell development in utero ...........................................................................9 1.2.2 Monocytes in the preterm neonate .......................................................................... 10 1.2.3 Metabolic regulation of cytokine production .......................................................... 12 x 1.2.4 The role of mTOR in shaping innate immune responses ......................................... 15 1.2.5 The negative mTOR regulators DDIT4 and DDIT4L ............................................. 19 1.3 Respiratory viral infections in infants ......................................................................... 21 1.3.1 B cell development during fetal life and the postnatal period .................................. 21 1.3.2 The role of antibodies in infant immunity ............................................................... 22 1.3.3 Respiratory syncytial virus infections in infants ..................................................... 24 1.3.4 Influenza infections in infants ................................................................................ 28 1.4 Thesis rationale and objectives................................................................................... 29 Chapter 2: Reduced glycolysis and protein synthesis limit pro-inflammatory responses in preterm monocytes .................................................................................................................. 31 2.1 Introduction ............................................................................................................... 31 2.2 Materials and Methods ............................................................................................... 32 2.2.1 Human subjects...................................................................................................... 32 2.2.2 Cells ...................................................................................................................... 33 2.2.3 Reagents ................................................................................................................ 33 2.2.4 Cytokine stimulation .............................................................................................. 34 2.2.5 Flow cytometry ...................................................................................................... 34 2.2.6 Phagocytosis assay ................................................................................................. 35 2.2.7 Western blots ......................................................................................................... 35 2.2.8 Polysome profiling ................................................................................................. 36 2.2.9 Real-time qPCR ..................................................................................................... 36 2.2.10 Pulse-labelling experiments................................................................................ 37 2.2.11 Metabolic assays ................................................................................................ 37 xi 2.2.12 Microarray analyses ........................................................................................... 38 2.2.13 Statistical analysis .............................................................................................. 39 2.3 Results ....................................................................................................................... 40 2.3.1 Transcriptomic analysis of preterm monocytes reveals remodeling of metabolic and ribosomal pathways ........................................................................................................... 40 2.3.2 Protein synthesis is dampened in preterm monocytes ............................................. 43 2.3.3 Preterm monocytes have reduced glycolytic activity .............................................. 45 2.3.4 Glycolysis-dependent immune responses are diminished in preterm monocytes ..... 46 2.3.5 mTOR pathway activity is low in preterm monocytes ............................................ 48 2.4 Discussion ................................................................................................................. 50 Chapter 3: DDIT4L limits innate immune activation in fetal monocytes ............................. 56 3.1 Introduction ............................................................................................................... 56 3.2 Materials and Methods ............................................................................................... 58 3.2.1 Human subjects...................................................................................................... 58 3.2.2 Cells ...................................................................................................................... 59 3.2.3 Lentiviral transduction ........................................................................................... 59 3.2.4 CRISPR-Cas9 generation of DDIT4L knockout cells ............................................. 60 3.2.5 Flow cytometry ...................................................................................................... 60 3.2.6 Metabolic assays – primary cells ............................................................................ 61 3.2.7 DDIT4L gene expression analysis .......................................................................... 62 3.2.8 Western blot .......................................................................................................... 62 3.2.9 Cell proliferation assays ......................................................................................... 63 3.2.10 Cytokine production assays ................................................................................ 64 xii 3.2.11 Assessment of protein stability ........................................................................... 64 3.2.12 Protein synthesis assay ....................................................................................... 64 3.2.13 Bioinformatic analyses ....................................................................................... 65 3.2.14 Statistical analyses ............................................................................................. 65 3.3 Results ....................................................................................................................... 66 3.3.1 DDIT4L expression is upregulated in metabolically limiting conditions in LPS-stimulated neonatal monocytes .......................................................................................... 66 3.3.2 DDIT4L overexpression “on-demand” using a lentivirus inducible system ............ 67 3.3.3 DDIT4L overexpression limits LPS-induced cytokine responses ............................ 69 3.3.4 DDIT4L protein levels are rapidly degraded in normoxia and hypoxia ................... 72 3.3.5 DDIT4L overexpression limits cell proliferation and protein synthesis ................... 73 3.3.6 DDIT4L overexpression remodels mitochondrial metabolism ................................ 76 3.3.7 Preterm monocytes have low mitochondrial capacity ............................................. 76 3.3.8 DDIT4L may limit severity of Bronchopulmonary Dysplasia ................................. 79 3.4 Discussion ................................................................................................................. 80 Chapter 4: Pathogen-specific development of humoral immunity to respiratory viruses in at-risk infants .......................................................................................................................... 84 4.1 Introduction ............................................................................................................... 84 4.2 Materials and Methods ............................................................................................... 85 4.2.1 British Columbia RSV Program ............................................................................. 85 4.2.2 Study design .......................................................................................................... 86 4.2.3 Blood samples ....................................................................................................... 86 4.2.4 Clinical outcomes .................................................................................................. 87 xiii 4.2.5 Systems serology assays ........................................................................................ 87 4.2.6 Palivizumab assay .................................................................................................. 90 4.2.7 Neutralizing anti-RSV antibody assay .................................................................... 90 4.2.8 Plasma cytokine measurement ............................................................................... 91 4.2.9 Flow cytometry ...................................................................................................... 91 4.2.10 Statistical methods ............................................................................................. 92 4.3 Results ....................................................................................................................... 93 4.3.1 Study population .................................................................................................... 93 4.3.2 Maternal antibodies drive protection in early life ................................................... 94 4.3.3 Endogenous anti-RSV antibodies mature functionally in the first year of life ......... 95 4.3.4 Postnatal age is the main driver of humoral immunity in early life ......................... 99 4.3.5 Responses to influenza antigens are weak in at-risk infants .................................. 100 4.3.6 Serological responses to RSV develop independently from those to influenza ...... 102 4.4 Discussion ............................................................................................................... 103 Chapter 5: Conclusion .......................................................................................................... 108 5.1 Summary of findings ............................................................................................... 108 5.2 Future directions ...................................................................................................... 117 References.............................................................................................................................. 124 xiv List of Tables Table 2.1 List of primers used in Chapter 2 ............................................................................... 37 Table 3.1 List of flow cytometry antibodies used in Chapter 3................................................... 61 Table 3.2 List of qPCR primers used in Chapter 3 ..................................................................... 62 Table 4.1 List of flow cytometry antibodies used in Chapter 4................................................... 92 Table 4.2 Clinical characteristics of infants ............................................................................... 94 xv List of Figures Figure 1.1 Regulation of mTORC1 and mTORC2 ..................................................................... 16 Figure 2.1 The transcriptomic response to LPS is conserved in preterm monocytes. .................. 41 Figure 2.2 Metabolic and ribosomal pathways are transcriptionally altered in preterm monocytes ................................................................................................................................................. 42 Figure 2.3 Decreased protein translation in preterm monocytes. ................................................ 44 Figure 2.4 Reduced glycolysis in preterm monocytes. ............................................................... 46 Figure 2.5 Inhibition of glycolysis leads to reduced MALT1 protein expression. ....................... 47 Figure 2.6 Altered mTOR signaling in preterm monocytes. ....................................................... 49 Figure 2.7 Summary model for Chapter 2 .................................................................................. 50 Figure 3.1 Metabolic limiting conditions induce DDIT4L. ........................................................ 67 Figure 3.2 U937 cells express negligible levels of DDIT4L. ...................................................... 68 Figure 3.3 DDIT4L limits pro-inflammatory cytokine responses. .............................................. 70 Figure 3.4 DDIT4L effects are maintained in hypoxia. .............................................................. 71 Figure 3.5 DDIT4L is rapidly degraded in normoxia and hypoxia ............................................. 72 Figure 3.6 DDIT4L limits functions of cellular growth and proliferation ................................... 75 Figure 3.7 Cytokine production is reduced in metabolic limiting conditions. ............................. 77 Figure 3.8 Preterm monocytes display reduced mitochondrial capacity. .................................... 78 Figure 3.9 DDIT4L may limit severity of Bronchopulmonary Dysplasia ................................... 80 Figure 4.1 Blockage of palivizumab in systems serology assays ................................................ 89 Figure 4.2 High RSV neutralization in early postnatal life and after palivizumab administration ................................................................................................................................................. 95 Figure 4.3 Endogenous anti-RSV antibodies develop with increasing postnatal age ................... 96 xvi Figure 4.4 Anti-RSV antibody functions mature throughout the first year of life. ...................... 98 Figure 4.5 Postnatal development of humoral immunity is largely independent of gestational age. ............................................................................................................................................... 100 Figure 4.6 Responses to influenza antigens are weak in at-risk infants. .................................... 101 Figure 4.7 Functional maturation of RSV and influenza responses occurs independently. ........ 103 xvii List of Abbreviations 2-DG 2-deoxy-D-glucose 2-NBDG 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose 4E-BP1 eukaryotic translation initiation factor 4E (eIF4E)-binding protein 1 Ab antibody ACTB beta actin ADCP antibody-mediated cellular phagocytosis ADNP antibody-mediated neutrophil phagocytosis ARTI acute respiratory tract infection ATP adenosine triphosphate BC British Columbia BCL10 B-cell lymphoma/leukemia 10 BCR B cell receptor BFA brefeldin A BH Benjamini-Hochberg BPD brochnopulmonary dysplasia C. albicans Candida albicans CARD9 caspase recruitment domain family member 9 CBMC cord blood mononuclear cells CCL C-C motif chemokine ligand CD cluster of differentiation ChIP-Seq chromatin immunoprecipitation sequencing chx cycloheximide CLEC7A C-type lectin domain containing 7A CX3CR1 C-X3-C motif chemokine receptor 1 DAMP danger associated molecular pattern DDIT4 DNA damage inducible transcript 4 DDIT4L DNA damage inducible transcript 4 like DEPTOR DEP domain-containing mTOR-interacting protein DNA desoxyribonucleic acid E. coli Escherichia coli ECAR extracellular acidification rate ELISA enzyme-linked immunosorbent assay EOS early onset sepsis ERK extracellular signal-regulated kinases ETC electron transport chain xviii EV empty vector Fab antigen-binding fragment FAD flavin adenine dinucleotide FBS fetal bovine serum FCCP trifluoromethoxy carbonylcyanide phenylhydrazone FcR Fc (fragment crystallizable) receptor FcRn neonatal Fc (fragment crystallizable) receptor FDR false discovery rate FMO fluorescence minus one GA gestational age GAPDH glyceraldehyde 3-phosphate dehydrogenase GBS group B streptococcus GDP guanosine diphosphate GLUT1 glucose transporter 1 GO gene ontology GRP75 glucose-regulated protein 75 GSEA gene set enrichment analysis GTP guanosine triphosphate HIF hypoxia inducible factor HLA human leukocyte antigen HPG L-homopropargylglycine IFN interferon Ig immunoglobulin IL interleukin IQR interquartile range IRAK1 interleukin 1 receptor associated kinase 1 IVIG intravenous immunoglobulin KEGG Kyoto encyclopedia of genes and genomes LARP1 La-related protein 1 LDL low-density lipoprotein LMIC low- and middle-income countries LOS late onset sepsis LPS lipopolysaccharide LRTI lower respiratory tract infections MALT1 mucosa-associated lymphoid tissue lymphoma translocation protein 1 MdM monocyte-derived-macrophage MDSC myeloid-derived suppressor cell xix MFI median fluorescence intensity MLST8 mammalian lethal with SEC13 protein 8 MTG mitotracker green mRNA messenger RNA mROS mitochondrial reactive oxygen species mTOR mammalian target of rapamycin MyD88 myeloid differentiation primary response 88 nAb neutralizing antibody NAD nicotinamide adenine dinucleotide NEC necrotizing enterocolitis NF-κB nuclear factor kappa-light-chain-enhancer of activated B cells NICU neonatal intensive care unit NK natural killer NLRP3 NOD-, LRR- and pyrin domain-containing protein 3 NT95 neutralizing titer with 95% reduction OCR oxygen consumption rate OXPHOS oxidative phosphorylation PAMP pathogen associated molecular pattern PBMC peripheral blood mononuclear cells PBS phosphate buffered saline PC principal component PCR polymerase chain reaction pDC plasmacytoid dendritic cell PMA phorbol myristate acetate postF postfusion F protein PP2A protein phosphatase 2 PPAR peroxisome proliferator-activated receptor PRAS40 proline-rich Akt substrate of 40 kDa preF prefusion F protein PRR pathogen recognition receptor PVDF polyvinylidene difluoride pvz palivizumab qPCR quantitative polymerase chain reaction R848 resiquimod RAPTOR regulatory-associated protein of mTOR RBC red blood cell REDD regulated in development and disease xx RET reverse electron transport rh recombinant human Rheb Ras homolog enriched in brain RICTOR RPTOR (regulatory associated protein of mTOR complex 1) independent companion of mTOR complex 2 RNA ribonucleid acid ROS reactive oxygen species RSV Respiratory Syncytial Virus S. Staphylococcus S6K1 ribosomal protein S6 kinase beta-1 scRNA-Seq single cell RNA sequencing siRNA small interfering RNA SREBP1 sterol regulatory element-binding protein 1 TCA tricarboxylic acid TCR T cell receptor TGF-β transforming growth factor beta Th T helper TISU translation initiator of short 5′ UTR TLR toll like receptor TMRE tetramethylrhodamine, ethyl ester TNF tumor necrosis factor TOP terminal oligopyrimidine TRAF6 tumor necrosis factor receptor associated factor 6 Treg regulatory T cell TSC tuberous sclerosis complex UTR untranslated region xxi Acknowledgements I would like to acknowledge that research presented in this thesis was conducted at the BC Children’s Hospital, operating on the traditional, ancestral, and unceded territory of the Coast Salish peoples — xʷməθkʷəy̓əm (Musqueam), Sḵwx̱wú7mesh (Squamish), and Səl̓ílwətaʔ/Selilwitulh (Tsleil-Waututh) Nations. I am also grateful for the funding provided by the Canadian Institutes of Health Research (CIHR), National Institutes of Health (NIH) and the BC Children’s Hospital in forms of scholarships to me or grants to Dr. Lavoie. I would like to thank my supervisor Dr. Pascal Lavoie for giving me the opportunity to work on and lead a wide array of projects allowing me to develop a portfolio in both wet lab techniques as well as in bioinformatics. Thank you for being excited about the projects, being always available for questions and for letting me explore many different avenues – this diversity has been one of the most enjoyable parts of my PhD. I would also like to thank Drs. Laura Sly, Eric Jan and Dan Luciani for providing support and guidance throughout my doctoral studies by serving on my supervisory committee and always being available for discussions. Throughout my PhD, I have been extremely fortunate to mentor many very talented undergraduate students. Shannon, Grace, Nikita, Maye, Rachel and Emma, thank you for your enthusiasm for science and your help in the lab. Claire, thank you so much for extending your co-op term again and again – it is a true pleasure to work with you. Moreover, I am grateful for all members of the Lavoie lab, past and present, for creating a pleasant work environment, particularly Bernard for getting me started in the lab and working together on preterm monocytes – I have learned a lot. Elizabeth for always lending a helping hand or ear and reading an early draft of my thesis. I would xxii also like to thank other trainees, staff and PIs at BCCHR, especially Mehul for his optimism and help with trouble shooting. These days, science is rarely practiced in isolation. Indeed, the projects outlined in my thesis have only been possible through collaborations, be it within our institute or with other labs around the world. This scientific exchange has been a wonderful source of inspiration and I immensely enjoyed learning from different points of view. I would also like to thank Ashton and the entire British Columbia Children’s BioBank – it’s been a pleasure to work together and create the Preemie BioBank. Last but not least, I would like to thank my family and friends for their support throughout this journey and for understanding that it is entirely possible to be “almost done” a PhD for many years. A special thanks goes to Ashish, who has contributed to this thesis as collaborator but more importantly, as my partner, has been a constant source of moral support. 1 Chapter 1: Introduction 1.1 Preterm birth – impacts on infant immunity Premature birth, defined as delivery before 37 weeks of gestation, is a major risk factor for morbidity and mortality1. With 878,000 neonatal deaths due to preterm birth related complications in 2017, prematurity is the leading cause of neonatal mortality worldwide2. Rates of preterm birth vary between countries but are consistently around 10% of all deliveries, making preterm birth a major global health issue3. Preterm birth can be iatrogenic, i.e. medically induced due to fetal or maternal complications such as intrauterine growth restriction or preeclampsia, or spontaneous due to premature onset of labor4,5. Among known risk factors for preterm birth are intrauterine infection, low maternal socio-economic status, and multi-fetal pregnancy. However, the precise etiology of preterm delivery is unknown in many cases5, complicating the development of effective prevention strategies. In Canada, preterm infants have a comparatively much higher chance of survival than in low- and middle-income countries where medical staff and equipment are limited. Nevertheless, preterm birth and associated complications negatively impact long term health outcomes in North America: a third of all deaths occurring in the first year of life are linked to prematurity in the United States6 and 46% of infants born before 29 weeks in Canada display neurodevelopmental impairment at two years of age7. Unsurprisingly, the risk for morbidity and mortality increases with lower gestational age, so that in the United States, infants born before 28 weeks of completed gestation are 183 times more likely to die in their first year of life than those born at full term6. One of the main reasons why premature newborns are more likely to die in early life is related to the immaturity of developing organs such as the brain or the lungs at time of preterm birth, but 2 also impacted by adverse events in the neonatal period. Indeed, premature newborns have a significantly greater risk to succumb to infections within their first months of life compared to full-term neonates8. Why premature newborns are so vulnerable to infections remains an area of active investigation. In the next sections, I will discuss infections commonly occurring in premature neonates and how an immature immune system may contribute to this susceptibility. 1.1.1 Neonatal sepsis Sepsis is a multi-organ syndrome, caused by an aberrant immune response to blood stream infections. Patients can die during the initial phase of infection due to organ damage caused by overt inflammation. More frequently, patients succumb later in the disease course during the so-called immunoparalysis phase, where (innate) immune cells become unresponsive to pathogen recognition receptor (PRR) stimulation, facilitating rapid, uncontrolled pathogen growth9. Research into immunostimulatory approaches to treat sepsis has gained considerable traction over the past decade but has mainly been explored in adults9. Sepsis is a major contributor to global mortality and the risk is high in neonates10,11, particularly in those born prematurely12. Early onset sepsis (EOS; defined as presenting within 72 h of birth) often originates from in utero infections manifesting as chorioamnionitis and may be causally linked to premature birth. Accordingly, rates of EOS are about 30 times higher in neonates born before 28 weeks of gestation compared to term newborns8. Late-onset sepsis (LOS) is defined as sepsis presenting after day 3 but before day 120 of life. While improved clinical practices have led to a reduction in LOS, the rate of infants presenting with EOS in Canada have increased over the last two decades13. In North America, E.coli and Group B streptococcus (GBS) are the most common causative agents of neonatal sepsis12,14, but in very preterm neonates, fungal pathogens such as Candida albicans can also lead 3 to sepsis15. With the advent of prophylactic antibiotic use during the intrapartum period, the rates of GBS-caused EOS have significantly declined16,17. However, excessive prophylactic antibiotic use has led to concerns about the emergence of multi-drug resistant pathogens and elicited calls for a more targeted antibiotic use. In addition to the risk of antibiotic resistance, needless antibiotic use can disrupt the developing intestinal microbiome, leading to gut dysbiosis. Indeed, prolonged antibiotic treatment after birth has been associated with increased antibiotic resistance and overall mortality18,19. 1.1.2 Infections during the infant period While the first month of life is inarguably the most vulnerable period for premature newborns, the elevated risk to infections persists well into infancy and remains elevated throughout childhood20–22. As in the neonatal period, the increase in infection rates is negatively associated with gestational age, with infants born before 30 weeks of gestation having a four times higher risk for hospitalization due to lower respiratory tract infections (LRTI) than infants born at full term20,22. The main causative pathogens of LRTI in infancy are influenza and Respiratory Syncytial Virus (RSV) which will be discussed in more detail later in this Chapter. Severe manifestation of these infections has been associated with impacts on long-term health outcomes, such as the development of asthma or recurrent wheezing23, further highlighting the far-reaching implications of preterm birth24. Interestingly, the risk of respiratory viral infections in early life may not be different in term and preterm infants but rather a result of increased disease severity in those born prematurely, leading to significantly higher rates of hospitalization25. 4 1.1.3 Clinical inflammation syndromes in preterm newborns While hypo-inflammatory responses facilitate infections such as sepsis in the neonatal period, inflammatory pathologies occur frequently in the first four weeks of life after preterm birth with bronchopulmonary dysplasia (BPD) and necrotizing enterocolitis (NEC) being the most common26. This suggests that the preterm immune system is easily dysregulated and that any perturbation towards insufficient or excessive inflammation during this period of development can easily have major clinical consequences. The following few sections will discuss specific diseases that have been linked to overt immune responses in the developing preterm infant during the neonatal period. 1.1.3.1 Necrotizing enterocolitis NEC is characterized by intestinal inflammation, tissue necrosis and bowel perforation in severe cases. Frequency is high in very low birth weight infants (~7%) and associated with considerable morbidity and mortality27,28. The exact etiology is unknown, but gut immaturity contributes to disease development. The preterm gut is characterized by high intestinal permeability and low gut motility, which can facilitate bacterial translocation and overgrowth instead of development of a healthy gut microbiome29. Additionally, high TLR4 expression in the preterm neonatal intestine is thought to promote recruitment of IL-17 producing T cells and induce pro-inflammatory cytokine production by the intestinal epithelium30. In the absence of specific therapeutics, strategies for NEC prevention and management include promotion of breastfeeding, use of probiotics and surgical removal of necrotic tissue28. Technological advances have led to a resurgence of interest in mechanistic studies on NEC, establishing hope that more targeted therapies will become available within the next decade31,32. 5 1.1.3.2 Bronchopulmonary dysplasia Like NEC, a chronic lung disease in preterm neonates known as BPD is characterized by imbalanced inflammatory responses33. Human lungs mature late during pregnancy, necessitating extensive respiratory support in preterm neonates. However, maintaining supplemental oxygen saturation at optimal levels is notoriously difficult, especially in premature newborns where the respiratory drive is immature. This leads to periods of intermittent hypoxia and hyperoxia, causing oxidative stress and scarring of the developing lung epithelium. This phenomenon is exacerbated by the fact that premature neonates have poor anti-oxidant defense mechanisms and imbalanced immune responses34,35. In fact, many studies have not only linked inflammation to BPD severity but demonstrated that inflammatory episodes precede BPD symptom onset36,37. BPD can have severe long-term impacts on infants’ health as it has been shown to predispose to asthma and exacerbate respiratory viral infections in childhood33. 1.1.4 Contributing factors to high infection risk in preterm neonates Incomplete organ development at birth, an immune system geared towards suppressed inflammatory responses in utero and a greater exposure to medical procedures in early life altogether explain the increased risk of infection for premature newborns38. In the following paragraphs, I will discuss the impact of medical interventions on the risk of infection in premature neonates before presenting characteristics of the neonatal immune system in a separate section. The epidermis and mucosa provide the first line of defense against infections by serving as a barrier against pathogens. During their stay in the neonatal intensive care unit (NICU), premature neonates undergo an extensive number of medical procedures every day, frequently involving breakage of 6 skin for example when inserting intravenous lines39. While these interventions are essential for survival, they further erode epithelial barrier function and may directly introduce pathogens into the bloodstream. Following this line of thought, it is important to consider the impact of routine blood testing. For example, preterm infants usually have multiple blood draws per day so that neonates born <28 weeks of gestation can lose up to a third of their total blood volume in the first month of life40. To prevent anemia, neonates often receive red blood cell (RBC) transfusion during their NICU stay. Recent research in animal models has demonstrated that phlebotomy-induced anemia by itself is sufficient to induce intestinal inflammation and loss of gut barrier integrity41. In a neonatal mouse model, RBC transfusions further increased immune cell infiltration and intestinal injury42. These results may explain the long-known correlation between anemia, blood-transfusions and NEC development in humans. Other medical interventions that have significantly improved preterm survival but are also linked to disease development include early life antibiotic use and mechanical ventilation as discussed above. Factors associated with improved neonatal outcomes include strict adherence to hygienic practices to reduce microbial exposure, early use of surfactant to boost lung development and promotion of breastfeeding and skin-to-skin care43. More recently, administration of pre- and probiotics has also shown promising results in improving health outcomes of preterm neonates44. 1.1.5 Characteristics of the preterm immune system The neonatal immune system has received considerable attention over the last years and several excellent reviews discuss its properties and host-pathogen interactions35,45,46. The following paragraphs will instead highlight specific characteristics unique to preterm infants. 7 The fetal immune system undergoes dramatic changes throughout pregnancy, pivoting from a tolerant, immunosuppressive state before birth to an immunoreactive state after birth. When premature birth occurs, these developmental stages are not yet completed and an immune system that is optimally adapted to the in utero environment unexpectedly finds itself faced by stimuli that it was not supposed to encounter for several more weeks. The preterm immune system is hence often described as immature. Immaturity here does not signify “non-functional”, it merely indicates that certain developmentally regulated adaptations in preparation for the ex utero environment have not yet been achieved. Indeed, the fetal environment starkly differs from the conditions faced after birth. In the womb, the fetus is encapsulated by the amniotic sac, providing physical separation from external pathogens. Supply of nutrients and oxygen is ensured through the placenta. Additionally, maternal immunoglobulin G (IgG) is selectively transferred through the placenta through attachment to the neonatal Fc receptor (FcRn). These antibodies provide passive immunity to the infant within the first months after birth. This transfer largely occurs in the third trimester, leaving preterm infants with significantly lower levels of maternal IgG at birth47. After birth, maternal immunity is passed on to newborns through breastfeeding in the form of IgA and leukocytes. These antibodies and cells can increase protection in early life and also enhance development of infant immunity48,49. At time of preterm delivery however, feeding skills may be immature and medical complications in the neonate may impede breastfeeding50. Additionally, milk composition is affected by gestational age, including the amount of immune proteins such as TGF-β51,52. At birth, full-term neonates are coated in vernix caseosa, a lipid-rich hydrophobic biofilm, impeding penetration by microbes. Preterm neonates lack this layer of protection as production 8 occurs late in the third trimester53. Additionally, their epithelial layer is substantially thinner, facilitating entry of pathogens54. As the exposure to pathogens is limited in utero, neonates have a comparatively low number of memory lymphocytes55,56. Although memory B and T cell development rapidly increases in the first weeks of life57,58, both pre- and full-term neonates heavily rely on their innate immune system in the early postnatal period. Neutrophil numbers are low at time of birth, especially in premature neonates. Granulocyte and monocyte numbers in circulation quickly rise within a week after birth58,59 but preterm neonates remain prone to neutropenia in the neonatal period owing to limited bone marrow reserves60. Moreover, neutrophil functions such as chemotaxis or NETosis are decreased in preterm cord blood60–62. Monocytes and macrophages play a crucial role in tissue remodeling during fetal growth. Accordingly, phagocytic capacity is high while PRR responses are generally dampened as will be discussed in further detail later in this Chapter. To prevent rejection of maternal tissues and limit overt inflammatory responses in utero, neonates have an impressive arsenal of immunoregulatory cells. Examples include high levels of regulatory B and T cells, immature CD71+ erythrocytes and myeloid-derived suppressor cells (MDSCs) which suppress T cell proliferation and promote anti-inflammatory properties in macrophages, e.g. through nitric oxide production and IL-10 secretion63–66. Preterm neonates often have lower levels of these immunosuppressive cells and indeed low levels of MDSCs have been associated with inflammatory diseases prevalent in neonates like NEC65,67. On the other hand, preterm neonates have higher levels of regulatory T cells (Tregs) and preterm Tregs show increased suppressive capacity compared with full-term Tregs68,69. 9 1.2 Regulation of neonatal monocyte responses 1.2.1 Myeloid cell development in utero Monocytes are a subset of myeloid cells that comprise between 5-20 % of peripheral blood mononuclear cells in healthy adults. These cells circulate through the bloodstream and quickly egress into tissues upon pathogenic insults. While less efficient than macrophages, monocytes perform very similar functions, namely phagocytosis of pathogens or dysfunctional cells, antigen presentation to T cells and production of cytokines to recruit further immune cells to the site of insult. In healthy adults, about 90% of the circulating monocytes are classical CD14highCD16neg cells70 which have a very short half-life and quickly die or differentiate; they can develop into macrophages or monocyte-derived dendritic cells when egressing into tissues or they can differentiate into intermediate monocytes within the blood stream70,71. Intermediate monocytes express high levels of both the LPS-coreceptor CD14 and the Fcγ III receptor CD16 and can in turn differentiate into non-classical monocytes (CD14lowCD16high)70,71. Numbers of circulating intermediate and non-classical monocytes are usually low but can increase in individuals with acute or chronic inflammatory diseases71,72. While all three subsets perform the above described myeloid functions, they vary slightly in their roles with classical monocytes considered to be mainly phagocytic and antimicrobial through high production of reactive oxygen species (ROS). Intermediate monocytes are specialized in antigen-presentation and the non-classical subset are important in wound-healing [reviewed in 73]. In humans, myeloid cell development begins around three weeks after conception, with primitive hematopoiesis in the yolk sac, including generation of embryonic macrophages. Later, the production of these cells shifts to the fetal liver before the bone marrow becomes the predominant 10 source of leukocytes, including myeloid cells, around 22 weeks of gestation74,75. Macrophages are critical throughout pregnancy due to their tissue remodeling capacity. Additionally, monocytes seed a variety of organs during embryonic development, where they develop into site-specific tissue resident macrophages, such as alveolar macrophages in the lung or microglia in the brain. While circulating monocytes can egress into tissues in adulthood, especially in the context of infection or injury, the majority of tissue-resident macrophages is estimated to stem from seeding during embryonic development76,77. 1.2.2 Monocytes in the preterm neonate Circulating myeloid cell counts change throughout pregnancy. Low gestational age is associated with higher total monocyte levels at time of birth and in the first week of life78. Within the monocyte compartment, both non-classical and intermediate phenotypes are enriched in neonates at the expense of classical monocytes79–81. Additionally, HLA-DR expression is reduced in all three subsets79–81 – suggesting decreased capacity for antigen presentation – but quickly increases in the postnatal period82. Phagocytosis has been assessed in many studies and – depending on the pathogen and assay used – has been shown to be lower, comparable or improved in preterm monocytes compared to full term and adult counterparts81,83,84. Numerous studies have demonstrated decreased pro-inflammatory cytokine production (e.g. IL-1β, IL-6, TNF-α) in response to PRR stimulation by preterm monocytes59,80,81,85. The underlying molecular mechanisms have been the subject of many research studies: While some papers show reduced TLR4 levels, most studies agree on comparable expression of PRRs such as TLR4 or TLR2 and stimulation induced upregulation of surface activation markers (e.g. CD80 and CD86) 11 between preterm, full term and adult monocytes81,84,86. Additionally, LPS or lipoteichoic acid leads to phosphorylation of canonical downstream signaling molecules such as NF-κB and ERK, albeit at reduced levels compared to adult monocytes81,84. In line with preserved signaling downstream of PRRs, it was recently shown that transcriptomic responses to E.coli or S.aureus are largely conserved in preterm monocytes87. This however prompts the question why are cytokine protein levels significantly reduced? Work detailed in Chapter 2 of this thesis was initiated long before the paper by de Jong et al. was published87 and more thoroughly evaluates the implications of the disconnect between transcriptomic and proteomic cytokine responses. Epigenetic studies on preterm monocytes are rare but suggest that a large proportion of cells still display markers of fetal liver origin88. Additionally, ChIP-Seq studies provide evidence for a global reduction of the activating histone modification H3K4me3 in preterm monocytes, which increases throughout pregnancy, including at promoter sites for the pro-inflammatory cytokine genes IL1B and IL6. Interestingly, about 60% of H3K4me3 peaks are associated with metabolic pathways in adult monocytes, in contrast to only comprising about 10% in very preterm neonates, where a large number of peaks are associated with developmental pathways89. Altogether, these epigenetic and phenotypic alterations are in line with the physiological requirements at this developmental stage, consisting mainly of tissue remodeling whereas the need for pro-inflammatory cytokine production is thought to be limited if not even detrimental. However, preterm birth places infants in an environment starkly different from the in utero milieu. Ex utero, the exposure to microorganisms necessitates an appropriate immune response to prevent infection. Accordingly, failure to upregulate inflammatory pathways in the postnatal period has 12 been associated with increased rates of sepsis90. Interestingly, the hypo-inflammatory phenotype of neonatal monocytes resembles alterations seen in sepsis patients during the immunoparalytic phase9,91. In the context of preterm birth, immunoparalysis could be induced through in utero PRR activation, such as that observed in chorioamnionitis, a common cause for preterm birth92. Indeed, chorioamnionitis impacts preterm monocytes on the transcriptional and epigenetic level93,94. Like sepsis, where several studies have shown promising results of immunoparalysis reversal by the administration of IFN-γ95–97, Tissieres et al. showed heightened pro-inflammatory cytokine production in response to PRR stimulation after preterm cord blood was pre-cultured with IFN-γ98. While further studies are needed, this may offer new avenues for therapeutic intervention. 1.2.3 Metabolic regulation of cytokine production Although Warburg described aerobic glycolysis in cancer cells a century ago, research into the role of metabolic regulation in immune responses has seen a renaissance in the past two decades. To summarize the entire state of knowledge in this field is beyond the scope of this thesis and the reader is referred to several excellent reviews (see 99–101). Below, I will instead highlight metabolic pathways and molecules important in shaping monocyte responses, with particular focus on the regulation of cytokine production. Cells utilize various metabolic pathways to generate sufficient energy in the form of adenosine triphosphate (ATP) and metabolic intermediates required for enzymatic function, biogenesis and signaling purposes. In the mitochondria, often called the powerhouse of eukaryotic cells, the tricarboxylic acid (TCA) cycle uses fatty acids, pyruvate (the end product of glycolysis) or amino acids to generate reducing agents NADH and FADH2 that serve as electron carriers to fuel the 13 electron transport chain (ETC). Here, oxidative phosphorylation (OXPHOS) occurs through establishment of a proton gradient across the inner mitochondrial membrane allowing ATP production. This process plays a major role in cellular energy production due to its high efficiency (~36 ATP/glucose). With only four molecules of ATP per molecule of glucose generated, aerobic glycolysis is much less energy efficient than oxidative phosphorylation, however it may provide energy faster than increasing mitochondrial mass to a level sufficient for sustaining elevated energy needs. At rest, monocytes heavily rely on oxidative phosphorylation for ATP production. Upon stimulation with PRR ligands, glycolytic flux quickly increases102–104. The elevated glucose to pyruvate conversion serves multiple purposes, namely (1) rapid production of ATP through conversion of pyruvate into lactate, (2) increased supply of pyruvate to the mitochondria to fuel the TCA cycle and (3) production of glycolysis intermediates that serve immunoregulatory function. The latter includes increased flux through the pentose phosphate pathway to generate nucleotides to sustain increased transcription. Additionally, several metabolic enzymes have “moonlighting” functions outside of their traditional role in metabolic processes105. A well-studied example is the ability of GAPDH in mediating TNF-α production in myeloid cells: when cellular glucose import is low, only a proportion of cellular GAPDH is engaged in glycolysis while other GAPDH molecules bind to the AU-rich 3’UTR of TNF-α mRNA, effectively sequestering the mRNA and preventing its translation106. Once glycolytic flux increases, GAPDH gets malonylated, releasing the TNF-α mRNA and allowing its translation while GAPDH is returned to its role in glyolysis107. Multiple studies have shown that the increase in glycolysis is indeed essential for 14 adequate responses to PRR stimulation as blockage with the glucose analogue 2-deoxy-D-glucose (2-DG) significantly impairs inflammatory function such as cytokine production102,104,108. Mitochondria also play a major role in shaping myeloid cell responses: concomitant with the increase in glycolysis upon PRR stimulation, TCA cycle activity increases. Interestingly though, it is the production of TCA intermediates and not energy production per se that is modulating inflammatory responses [reviewed in 109,110]. As such, TCA cycle activity does not merely increase, instead significant functional remodeling takes place leading to a “broken” TCA cycle in PRR-activated macrophages. Through transcriptional repression and post-translational modifications of isocitrate dehydrogenase, citrate levels accumulate promoting cytosolic Acetyl-CoA production, which in turn increases pro-inflammatory cytokine transcription through epigenetic remodeling and may also increase their translation through acetylation of GAPDH (reviewed in 111). Similarly, succinate levels increase, fueling the electron transport chain108,112. Intriguingly, activated myeloid cells display reverse electron transport (RET), where – as the name implies – electrons are shuttled from complex II to complex I, boosting mitochondrial reactive oxygen species (mROS) production112. Besides their direct bactericidal activity, mROS support generation of pro-inflammatory cytokines such as IL-1β113. Indeed, inhibiting complex II (by targeting one of its succinate dehydrogenase subunits) limits RET and dampens pro-inflammatory cytokine production in macrophages, particularly reducing IL-1β levels112,114. Metabolic signals also regulate inflammasome activity115–117. For example, β-hydroxybutyrate, which is elevated during ketogenic diet, reduces caspase-1 activity118 and glycolysis induced hexokinase 1 expression can activate NLRP3117,119. This is particularly interesting in the context of this thesis, as our lab has shown previously that preterm monocytes have dampened caspase-1 15 activity80. Whether altered cellular metabolism is responsible for this developmental particularity remains to be determined. On the other hand, oxidative damage and excess ROS production can activate inflammasomes116, which could mediate the damaging properties of imbalanced oxygen metabolism during preterm neonates’ stay in the NICU. Very limited knowledge exists on the metabolic activity of neonatal myeloid cells. Dreschers et al. studied monocyte-derived-macrophages (MdMs) from adults and full-term cord blood and observed significantly lower utilization of glycolysis and mitochondrial respiration in the neonatal cells, both at baseline as well as after stimulation with E.coli 120,121. This is corroborated by findings from O´ Maoldomhnaigh et al., showing that a reduction in oxidative phosphorylation observed in adult MdMs following stimulation with LPS or Mycobacterium tuberculosis is absent in full-term cord blood MdMs122. 1.2.4 The role of mTOR in shaping innate immune responses In myeloid cells, the rapid increase in glycolysis upon PRR stimulation is mediated through activation of mTORC1102. This paragraph will briefly summarize the regulation of mammalian target of rapamycin (mTOR), before highlighting its role in myeloid cell responses. For further details on mTOR biology, the reader is referred to several excellent reviews (see 123,124). The serine threonine kinase mTOR associates with RAPTOR, DEPTOR, MLST8 and PRAS40 to form a protein complex called mTORC1, a multi-protein signaling hub regulating proliferation, metabolic processes and mRNA translation among others123 (Fig. 1.1). Phosphorylation of mTOR on Ser2448 in mTORC1 leads to phosphorylation of downstream targets such as 4E-BP1 and S6K1, thereby promoting mRNA translation. This is especially true for mRNAs containing terminal 16 oligopyrimidine (TOP) motifs or translation initiator of short 5′ UTR (TISU) elements in their 5’UTR which are often found in mRNAs coding for ribosomal or mitochondrial proteins respectively125. The following paragraphs will mainly focus on mTORC1 but it is worth noting that mTOR can also interact with RICTOR and other proteins to form mTORC2. In this context, phosphorylation of mTOR on Ser2481 mediates changes in cellular metabolism and cytoskeletal biology123. Many upstream signals indicating the need for reduced cellular growth and metabolic Figure 1.1 Regulation of mTORC1 and mTORC2 Hypoxia upregulates DDIT4 and DDIT4L (indicated with their alternative names REDD1 and REDD2 in this figure). This promotes TSC1/2 mediated inhibition of mTORC1 activity. mTORC1 and mTORC2 activity is also modulated by growth factors through Akt phosphorylation. Reprinted with permission from Nakazawa et al. doi.10.1038/nrc.2016.84 17 rate converge on mTOR. Examples include hypoxia, low amino acid abundance or DNA damage. Mechanistically, the tuberous sclerosis complex proteins (TSC1 and TSC2) integrate signals of nutrient availability to modulate the extent of mTORC1 phosphorylation. Low nutrient availability or stress signals lead to dephosphorylation of TSC2, promoting its localization to the lysosome. Here, it promotes hydrolysis of Rheb-bound GTP to GDP, limiting mTORC1 activation. Under nutrient replete conditions however, Rheb retains GTP. This allows binding to mTOR, inducing a conformational change and subsequent activation of mTORC1. Besides regulating cellular growth, mTORC1 is intricately involved in modulation of immune responses126,127. In myeloid cells, PRR stimulation generally leads to a rapid increase in mTORC1 activation and phosphorylation of downstream targets. This serves multiple purposes: (1) Increased protein synthesis to facilitate rapid expression of immune response genes such as cytokines, (2) increased rates of glycolysis to fuel translation and generate metabolic intermediates as detailed in the prior section, (3) heightened lipid biosynthesis through SREBP1 activation. This is important for inflammasome activation and to provide sufficient building blocks for membrane remodeling128,129. Accordingly, mTOR inhibition in vitro has been shown to decrease pro-inflammatory cytokine production such as IL-1β in human and murine myeloid cells95,119,130,131. Additionally, mTOR inhibitors have long been used clinically to prevent graft rejection in transplant recipients. However, many other studies suggest that mTOR inhibition can in fact promote inflammatory responses and limit pathogen growth132,133. For example, a recent study showed that butyrate treatment limited mTORC1 activity in macrophages, facilitating antimicrobial responses through increased autophagy134. These contradictory results may seem difficult to reconcile but it is worth keeping in mind that requirements for mTORC1 certainly vary 18 in the early and later phase of stimulation. Additionally, rapamycin is a commonly used mTOR inhibitor. While mTORC1 is preferentially inhibited, prolonged treatment with rapamycin can also lead to mTORC2 inhibition. Undoubtedly, further studies are required for a thorough understanding of mTOR in innate immune function. Suffice to say that mTORC1 can play activating or inhibitory roles depending on the system studied. While mTORC1 is essential for hematopoietic stem and progenitor cell (HSC and HPC respectively) expansion, excessive mTORC1 activity has been shown to lead to ROS production, HSC hyperproliferation and exhaustion, resulting in HSC depletion [reviewed in 135]. Little is known about the activity of mTOR in neonatal myeloid cells, with one group showing low mTOR levels and reduced phosphorylation in MdMs from full term cord blood compared to those from adults. Interestingly, in vitro supplementation with leucine augmented mTOR activity and partially restored glycolysis and OXPHOS rates closer to adult levels120,121. Low capacity to increase mTOR phosphorylation upon stimulation has also been observed in neutrophils from preterms compared to adults and full terms136. From mouse models, we know that autophagy is sparsely used during embryogenesis but quickly upregulated after birth, presumably to prevent neonatal death from starvation due to the drastic change in environment137. This upregulation is mediated through inhibition of mTORC1 within hours after birth and knockout mice that lack components to induce autophagy or have constitutively active mTORC1 rapidly die after birth137,138. To what extent the same phenomenon is true in human neonates and whether this pathway is imbalanced in preterms is unknown. 19 1.2.5 The negative mTOR regulators DDIT4 and DDIT4L DNA damage inducible transcript 4 (DDIT4, also known as regulated in development and DNA damage responses 1, REDD1) is a negative regulator of mTORC1. Its paralogue DDIT4L (DDIT4 like, or REDD2) is less well studied but proposed to function in a similar manner139. Expression of both proteins has been shown to diminish phosphorylation of mTORC1 and its downstream targets S6 and 4E-BP1140,141. The exact mechanism of action of DDIT4(L) on mTOR is unknown, but data suggest that DDIT4 functions upstream of the TSC1/TSC2 complex141. Potential modes of action have been reviewed previously139,142,143 and are summarized here: A hypothetical model of action for DDIT4(L) includes direct binding to members of the 14-3-3 scaffolding protein family which would impede their interaction with TSC1, thereby permitting formation of a functional TSC1/TSC2 complex. However, direct protein-protein interaction between DDIT4(L) and 14-3-3 has not been demonstrated and appears unlikely according to 3D modeling despite the presence of a 14-3-3 binding motif in DDIT4(L). Another model suggests binding of DDIT4(L) to PP2A leading to dephosphorylation and subsequent inhibition of Akt. Yet another theory proposes disruption of ER-mitochondrial interaction by binding of DDIT4(L) to GRP75, a key component of the mitochondria associated membrane139,143,144. Further studies are required to validate these models and potentially identify cell type and context-specific mechanisms. DDIT4(L) is a sensor of cellular stress and its expression can be induced in a variety of cell types, particularly – as the name suggests – in response to cellular stresses such as DNA damage, hypoxia, glycemia, serum starvation or arsenite [reviewed in 139,144]. DDIT4 and DDIT4L are best studied in skeletal muscle tissue142 and DDIT4 has also received considerable attention relating to its role in cancer and diabetes144. Through inhibition of mTOR, DDIT4 has been demonstrated to remodel 20 cellular metabolism, generally increasing autophagy and mitochondrial activity while reducing glycolytic pathways139,143,144. It should be noted that other studies have observed diminished cellular oxygen consumption upon DDIT4 overexpression145. With regard to immune function, results are also mixed, particularly concerning the questions whether DDIT4 promotes or in fact limits ROS production130,146,147. In murine macrophages, LPS induces DDIT4 expression and ablation of DDIT4 through siRNA or generation of knockout mice leads to reduction in LPS-induced NLRP3 inflammasome activation and pro-inflammatory cytokine production147,148. Ruslan Medzhitov’s group however observed increased inflammasome activity and IL-1β production in their DDIT4 knockout mice130. Altogether, these data suggest that like mTORC1, DDIT4 may have different roles depending on the system studied, including cell type, the kinetics of DDIT4 expression (prolonged vs acute) and culture conditions (e.g. hypoxia vs normoxia). Extrapolating from our knowledge that DDIT4 can remodel cellular metabolism in murine bone marrow derived macrophages towards more mitochondrial activity130,149, it is tempting to speculate that DDIT4L may be able to perform similar functions. However, while DDIT4 is ubiquitously expressed, including in T and B lymphocytes, macrophages and granulocytes, DDIT4L levels are generally very low in hematopoietic cells150,151. Nevertheless, a few studies have examined DDIT4L function in macrophage cell lines, demonstrating its induction by hypoxia or oxidized LDL. Overexpression of DDIT4L in macrophages increased ROS production and cell death, particularly necrosis in response to oxidized LDL152,153. Another study showed upregulation of DDIT4L after LPS or zymosan stimulation of rainbow trout macrophages154, perhaps eluding to an evolutionarily conserved role. Indeed, homologues to DDIT4 and DDIT4L have been found in a variety of species, spanning from drosophila to cattle to mice140,155. Despite this conserved expression of DDIT4L, its exact role in physiology is largely unknown. 21 1.3 Respiratory viral infections in infants 1.3.1 B cell development during fetal life and the postnatal period As part of the adaptive immune system, B cells respond in an antigen-specific manner and retain memory. Antigen-specificity is mediated through the B cell receptor (BCR), which is initially expressed on the cell surface but can be secreted upon activation to release copious amounts of antibodies into the blood stream. Antibodies come in different isotypes affecting interaction with pathogens and immune cells whilst maintaining the same antigen specificity. In humans, class switching occurs in the following order: IgM > IgD > IgG3 > IgG1 > IgA1 > IgG2 > IgG4 > IgE > IgA2. Mature naïve B cells express IgM and IgD on their surface and subsequent class switching is initiated upon antigen exposure. Further diversification of humoral responses is achieved through affinity maturation: portions of the complementarity-determining regions (the DNA region coding for the antigen-binding sequence) are randomly mutated, followed by selection of strongly binding clones over weakly binding clones in the germinal centers of the lymph node. These processes, also known as somatic hypermutation and clonal selection, refine B cell responses and increase antibody specificity and avidity156. Besides their antibody production capacity, B cells are also professional antigen-presenting cells and modulate immune responses through cytokine secretion157. In humans, B cells develop early on and can be found in the fetal liver by week 7 of gestation158. Circulating B cell numbers and BCR repertoire diversity increase throughout gestation but lymphoproliferation is limited in utero159. Accordingly, absolute B cell numbers are slightly lower in preterm than full term neonates160–162. However, comparable B cell activation status is seen in 22 cord blood from neonates born between 30-34 weeks and full term neonates55 and peripheral blood B cell counts are similar between very preterm, late preterm and full term infants during the first three months of life163. Total B cell levels rise dramatically after the neonatal period, with B cell numbers in infancy surpassing adult levels57,82,161. At birth, about 90 % of the circulating B cells are naïve, in both preterm and full term neonates55 but the number of class-switched memory B cells quickly increases postnatally57. Cord blood is rich in CD24highCD38high, so called transitional B lymphocytes – cells that have exited the bone marrow into the periphery but not yet developed into mature, naïve B cells. These cells are characterized by expression of CD5, CD10 and high levels of IgM and numbers decline quickly within the first years of life164–166. Infants also have elevated levels of regulatory B cells (Bregs) that promote anti-inflammatory immune responses through IL-10 secretion and direct cell-to-cell contact167–169. While T cell receptor (TCR) diversity continues to rise in the last trimester, at around 22-26 weeks GA, BCR clonal diversity is comparable to that observed in full term neonates and adults159,165,170. Somatic hypermutation and class-switching are apparent within the first trimester of pregnancy, suggesting functionality of B lymphocytes. However, the somatic hypermutation rate is reduced and the complementary determining region is shorter in cord blood from preterm infants compared to term controls171. In conclusion, B cell function is established early on in human development and largely comparable in preterm and full-term neonates. 1.3.2 The role of antibodies in infant immunity Antibodies are important in preventing and clearing infections, especially those occurring at mucosal surfaces like the pulmonary tract. Indeed, individuals with hypogammaglobulinemia 23 often suffer from recurring respiratory infections and while intravenous immunoglobulin (IVIG) treatment improves overall health outcomes for affected patients, IgA deficiency remains a significant risk factor for respiratory and gastrointestinal tract infections172–174. A main function of antibodies in protecting against viral infection is direct neutralization of virions. Hence, neutralizing antibody (nAbs) titers are often used as a correlate of protection in ex vivo assays, epidemiological studies or vaccine trials. For certain pathogens, however, nAbs levels only moderately correlate with clinical protection, suggesting a greater importance for T cell mediated immunity and non-neutralizing antibody functions. These include antibody-mediated neutrophil or cellular (monocyte) phagocytosis (ADNP and ADCP respectively), NK cell activation (antibody-dependent cellular cytotoxicity; ADCC) and complement deposition (ADCD). To assert these functions, the constant region of antibodies can interact with Fc receptors expressed on immune cells such as macrophages and NK cells [reviewed in 175,176]. In a similar manner, the neonatal Fc receptor transports maternal IgG across the placenta to the fetus177. Antibodies are heavily glycosylated and these glycan modifications are highly malleable. Changes in glycosylation patterns can fine-tune binding affinity to Fc receptors thereby shaping effector cell function178. For example, digalactosylated antibodies are preferentially transferred across the placenta, thereby selecting for antibodies with high NK cell activation capacity179. As the vast majority of B cells at birth are naïve, the amount of antibodies that is endogenously produced is limited in early life. Transplacental transfer of maternal IgG antibodies can partially compensate for this physiological hypogammaglobulinemia so that cord serum IgG levels are comparable to, if not exceeding maternal titers179,180. Observations made of patients with primary agammaglobulinemia, caused by damaging mutations in genes important for B cell maturation, 24 have shown that maternal antibody levels quickly decline within the first three months after birth and have disappeared almost completely by six months of age173,181. Consistently, these patients do not display a disease phenotype in the first three months of life but are severely susceptible to infections once maternal antibodies have waned181. In healthy infants however, immunoglobulin production gradually increases in the postnatal period so that – combining maternal and endogenous antibodies – a nadir is reached around six months of age for IgG1, IgG2 and IgG4 while IgG3 levels increase earlier, around three months after birth57,182. IgM and IgA do not cross the placenta and hence rely on infant production with serum levels steadily increasing in the first year of life57,183,184. Transplacental antibody transfer commences in the late second trimester, but rates only significantly increase in the middle of the third trimester, so that preterm infants have received considerably lower amounts of IgG at the time of birth180,185. In the postnatal period, breastfeeding can also promote humoral immunity through transfer of maternal IgA and, to a lesser extent, IgM and IgG. These antibodies mostly remain at mucosal surfaces of the respiratory and intestinal tract and do not significantly contribute to systemic immunity186. 1.3.3 Respiratory syncytial virus infections in infants Respiratory syncytial virus is a negative-sense single-stranded RNA virus causing yearly epidemics of respiratory infections in a seasonal pattern. Two main subtypes of RSV are endemic to most regions in the world, RSV A and RSV B. While one may dominate in any given season, both subtypes usually occur in parallel187,188. Due to high sequence similarity, memory responses, including antibodies, are often cross-protective189,190. However, memory responses are generally weak and diminish quickly, evidenced by a seasonal rise and decline in antibody levels191,192. This 25 allows frequent reinfection even in healthy adults, impeding vaccine design and herd immunity formation. RSV has two main lipoproteins on its surface: The glycoprotein (“G”) is important for attachment to host cells by engaging with receptors such as CX3CR1 while the fusion (“F”) protein mediates viral entry193. Many vaccine strategies currently in development are focused on the F protein due to its high immunogenicity, sequence conservation between strains and ability for generating neutralizing antibodies194. The F protein is initially expressed in a pre-fusion conformation (preF) which however is metastable and quickly switches into a post-fusion state (postF), necessary for interaction with receptors on host cells193. Several epitopes are shared by both conformations, but some become masked or only exposed after the conformational switch. In adults, most RSV neutralizing antibodies target antigenic sites Ø and V, accessible exclusively in the pre-fusion conformation189,190. These antibodies are highly neutralizing as they lock the F protein in the pre-fusion state, preventing attachment to viral entry receptors on host epithelial cells195. Recent efforts to generate a stabilized RSV preF protein for use as vaccine antigen have shown promise in early clinical trials196. The G protein has received less attention from the research community but can also elicit formation of neutralizing antibodies, with a recent study suggesting that about 40% of RSV-targeting B cells are G protein specific197. Lower respiratory tract infections (LRTI) caused by RSV are a major concern in infants under five years of age188,198. Due to its ubiquitous nature, most infants are exposed to RSV within their first two years of life, often causing only mild symptoms, a seasonal “cold”. However, infection can lead to severe morbidity and mortality, especially in infants born prematurely or those who have 26 congenital heart or chronic lung diseases199,200. Worldwide, RSV causes 3 million hospitalizations and an estimated 120,000 deaths in infants every year188. These numbers may be severely underestimated as it has been suggested that many RSV-related deaths occur after hospital discharge in low- and middle-income countries (LMIC)188. RSV infections have a significant economic impact on healthcare systems and present an emotional burden for families, warranting the development of preventative strategies. Several promising vaccines are in development196,201–203, but are yet to be licensed for patient use, so prophylaxis currently relies on monoclonal antibody therapy, mainly with palivizumab. Palivizumab is a humanized murine IgG1 antibody binding to the antigenic site II of the RSV F protein204. This epitope is accessible both in the pre- as well as post-fusion conformation and highly conserved between RSV A and B, leading to viral neutralization and prevention of fusion with host cells204. Since clinical trials in the 1990s have shown that palivizumab prophylaxis during the winter season reduces RSV infection by about 50 % in at risk infants, many countries have implemented palivizumab dosing205. During the viral winter season, palivizumab is administered intramuscularly at 15 mg/kg every month206. To the best of our knowledge, with the exception of British Columbia (BC), jurisdictions around the world follow the recommendation for five doses throughout the season. In BC, an abbreviated regimen of four doses is used during the six-month long winter season, with no impact on palivizumab prophylaxis effectiveness207–209. However, several challenges remain: due to its high price, the treatment is only cost-effective in infants presenting with known risk factors such as extreme prematurity, respiratory comorbidities (e.g. BPD) or congenital heart disease, even though the majority of cases occurs in healthy, full 27 term infants198. Additionally, 30 million at-risk infants in LMIC are left unprotected188. Lastly, palivizumab provides only partial protection, reducing hospitalization by about 50-60%. Neutralizing antibodies efficiently protect against severe RSV210–212. Transplacentally transferred maternal antibodies can confer protection after birth with maternal anti-RSV antibody titers or cord blood RSV-neutralizing antibody levels being predictive of RSV infection in the first three months of life210,211,213. In line with waning of maternal antibodies, most studies show a gradual decline in RSV-targeting IgG titers within the first year of life214. Preterm infants, who are at highest risk of severe RSV infection, generally have low levels of this maternal antibody protection, as placental antibody transfer largely occurs during the third trimester of pregnancy. Indeed, RSV-specific IgGs are significantly lower in cord blood from preterm infants than those born at full term, concomitant with reduced neutralizing activity215. Thus, preterm infants depend heavily on their capacity for generating their own natural humoral immunity for protection beyond the neonatal period. Serological studies in term infants presenting with RSV infection show that they can mount efficient antiviral responses as evidenced by higher titers after recovery compared to the acute phase of infection. However, rates of somatic hypermutation are low, especially in very young infants. Consequently, infants younger than 4 months largely depend on maternal antibodies for protection216–220. Possible reasons for low humoral responses in young infants may include hindrance by high maternal antibody levels221,222 or immaturity of the infant immune system, including B cell responses167,200. Most studies examining anti-RSV antibodies in the first year of life assess levels in RSV-infected infants and measure IgG levels, preventing distinction of 28 maternal from actively acquired infant antibody responses. Large scale studies suggest that by three years of age, most infants have anti-RSV titers comparable to adults, without overt clinical infection in many cases223. Previously, we proposed that a majority of at-risk infants acquire neutralizing, non-palivizumab related antibodies in their first months of life208. As that study did not directly quantify antibody titers, it is however still unclear if and how endogenous antibodies to RSV are produced in at-risk infants in absence of clinically manifesting LRTI. Additionally, it is not well understood how the postnatal development of natural immunity is affected by premature birth, where only low levels of maternal antibodies have been transferred through the placenta. 1.3.4 Influenza infections in infants Like RSV, influenza are negative-sense single-stranded RNA viruses causing LRTI with particularly high morbidity in infants and the elderly224. To protect against overt infection, vaccination is recommended for children > 6 months of age and adults225. Memory responses to influenza are long lasting but the virus exhibits significant rates of antigenic drift. Accordingly, the vaccine formula is adjusted yearly, based on predictions of which strains will be circulating in the upcoming season. Hence, while previous influenza vaccinations may provide partial immunity through cross-reactive antibodies and T cell responses, it is important to receive the vaccine every year to be adequately protected226. Per current guidelines, infants below six months of age are not eligible to receive the vaccine, so that strategies to limit infection in this age group consist of maternal immunization during pregnancy (to confer protection to the infant through placental antibody transfer) and immunization of family members during the winter season (to reduce exposure risk)227. Unexpectedly, the first year of life remains the period in which infants are most 29 susceptible to influenza infection and morbidity228. For the same reasons as discussed above for RSV, this is especially true for premature infants229. Influenza vaccination of mothers during pregnancy is safe, provides protection to the mother and roughly reduces the risk for influenza infection in the infant by half230,231. However, this protection is mainly effective in the first eight weeks of life and quickly diminishes in step with waning of maternal antibodies232. Surprisingly little is known about immunogenicity to the influenza vaccine in infants but available data suggest that the vaccine is safe and effective in this age group233,234. Even less is known if and how responses differ between preterm and full-term infants. One study examining vaccine responses to the pandemic influenza A/H1N1 vaccine found that while antibody levels were lower in infants born <32 weeks GA compared to full term infants, both before and one month after vaccine administration, the fold change in antibody titers was in fact higher in preterm infants. Additionally, after the second vaccine dose, 100 % of infants showed seroprotection, in all age groups235. For non-pandemic vaccines, responses in preterm infants have been shown to be comparable if not even better than in full term infants236,237. 1.4 Thesis rationale and objectives Premature birth significantly increases the risk for severe infection in early life. Developmental alterations in preterm neonates’ immune responses have been proposed to contribute to this increased susceptibility. Over the past decades, studies have shown repeatedly that at birth, preterm immune cells are hyporesponsive to various stimulations in vitro. When I started my thesis, we however lacked an understanding of the basic mechanisms underlying the innate immune unresponsiveness in these cells. We knew that several immune pathways were affected but could 30 not reconcile the mechanism affected upstream of these pathways. Additionally, we lacked an understanding on how well preterm immune responses develop beyond the immediate neonatal period and how this influences susceptibility to respiratory viral infections in the first year of life. My thesis aimed to address these knowledge gaps through the following objectives: • Objective 1 (Chapter 2): To determine the molecular pathways underlying functional immunological differences between preterm, term and adult innate immune cells, focusing on monocytes as a model. • Objective 2 (Chapter 3): To determine the function of DDIT4L – a negative mTOR regulator highly expressed in preterm monocytes – on myeloid cell function, including LPS responses and cellular metabolism. • Objective 3 (Chapter 4): To characterize the development of humoral immunity to RSV in infants at high risk of respiratory viral infections. 31 Chapter 2: Reduced glycolysis and protein synthesis limit pro-inflammatory responses in preterm monocytes 2.1 Introduction Despite advances in medical care, very preterm newborns (born <33 weeks of gestational age) remain at a significantly elevated risk for infections during the neonatal period13,238,239. Alongside physiological immaturity, an altered immune response has long been considered a contributor to disease susceptibility35,45,240. Over the past two decades, numerous research studies on myeloid cell function in this age group have shown dampened immune reactivity as evidenced by low pro-inflammatory cytokine production and antigen-presentation after activation [reviewed in 84]. This is true for a variety of PRRs and ligands, including LPS, R848, and flagellin as well as whole pathogens such as Group B Streptococcus and S. epidermis80,81,85,94,241,242. While this lack of pro-inflammatory responses may be beneficial in utero to limit rejection of maternal tissues, preterm birth leaves these neonates ill-adapted to adequately respond to microbial stimulation ex utero. Indeed, several studies have demonstrated that hypo-responsiveness persists in the early postnatal period and increases the risk for sepsis development59,90,243. These findings suggest the existence of a developmental phenotype in preterm monocytes, globally different from adult and even full-term monocytes. What this phenotype looks like on a molecular level and how it can globally alter immune responsiveness is however incompletely understood. In this study, we employed an unbiased transcriptomic approach to identify regulatory mechanisms distinguishing monocytes from preterm and term neonates to adults. Surprisingly, the transcriptomic response to LPS was largely conserved in preterm monocytes. Instead, our results 32 suggested metabolic remodeling and low ribosomal activity. Through functional in vitro assays, we showed that cytokine production, a glycolysis-dependent process, is dampened in preterm monocytes, while phagocytosis does not rely on glycolysis and is fully functional in preterm cells. Finally, our results suggest that glycolysis and protein synthesis are attenuated in preterm monocytes as a result of low mTORC1 activity, potentially due to high expression of the negative mTOR regulator DDIT4L. Together, our results provide important insights into human myeloid development and pinpoint to potential therapeutic targets for neonates born prematurely. 2.2 Materials and Methods 2.2.1 Human subjects This study was conducted according to the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans244. Cord blood was obtained from preterm infants (<33 weeks) born by Caesarean section or vaginal delivery and term infants (37 – 41 weeks) born by elective caesarean section in absence of labor, and peripheral blood was obtained from healthy adult volunteers recruited at the BC Children’s Hospital Research Institute. All blood samples were collected in sodium heparin vacutainers. The cord blood samples were collected following delayed cord clamping in line with clinical standards, and after the placenta was detached from the infant. Written consent was obtained from all participants, except for preterm cases where parents were unavailable/non-reachable, in person or by phone. In these cases, no clinical data except for gestational age was obtained and completely de-identified cord blood samples were used, in accordance with a waiver of consent approved by the University of British Columbia Children’s & Women’s Research Ethics Board (UBC C&W REB). The study complied with and was approved by the UBC C&W REB (#H07-01698). 33 2.2.2 Cells Mononuclear cells (MNCs) were isolated from whole blood by density centrifugation using Lymphoprep™ (STEMCELL Technologies, #07861). Monocytes were purified from MNCs generally from at least 1 mL of whole blood, using an EasySep™ positive CD14 selection kit (STEMCELL Technologies, #18058) and EDTA 1 mM to prevent cell clumping. Monocyte purity was regularly determined by flow cytometry (FSC/SSC plus staining for CD14 surface expression) throughout the study and confirmed to have >95 % purity for microarray studies. 2.2.3 Reagents Pediatric clinical isolates of Candida albicans, identified by mass spectrometry (Bruker Daltonics, Billerica, MA) were obtained from the BC Children’s Hospital Microbiology Lab (Vancouver, Canada). We used fixed Candida spp. yeast particles which are closer antigenically to yeast forms245. Fungi were grown over 4 days at 30°C in BHI (Brain-Heart Infusion) broth (Oxoid, Nepean, ON). Yeast in exponential growth phase were harvested after 4 days, centrifuged and fixed in 10 % paraformaldehyde. To ensure reproducibility, batches of Candida particles were prepared and used throughout the study. Curdlan (β-1,3-glucan from Alcaligenes faecalis), a dectin-1 specific agonist, was obtained from Wako (#032-09902) and used at 10 µg/ml in cytokine studies. Lipopolysaccharide (LPS), a TLR-4 agonist purified from Escherichia coli, was obtained from InvivoGen (#tlrl-eblps) and used at 10 ng/ml. The following anti-target antibodies were used for Western blots (source): MALT1 (Cell Signaling Tech., #2494S), BCL10 (Cell Signaling Tech., #4237S), phospho mTOR (Cell Signaling Tech., #5536P), mTOR (Cell Signaling Tech., #4517S), 4E-BP1 (Cell Signaling Tech., #9644P), β-actin (Abcam, #Ab75186), goat anti-mouse (LI-COR Odyssey, #926-68070) and anti-rabbit antibodies (#926-32213). Primary antibodies were used at 34 a 1:1000 dilution and secondary antibodies were used at a 1:10,000 dilution. For MALT1 protein detection by flow cytometry, we used a Phycoerythrin-labeled anti-MALT1 antibody at a 1:100 dilution [EP603Y] (Abcam, #Ab210982). Cell viability was measured using a Fixable Viability Dye eFluor™ 780 (eBioscience; #65-0865-14; 1:100 dilution). 2.2.4 Cytokine stimulation MNCs or monocytes were cultured in RPMI 1640 (Roswell Park Memorial Institute medium) supplemented with 2 mM L-glutamine (Gibco, #25030), 10% human AB serum (Gibco #11875-093) and Pen-strep (Gibco, #15140-122) (referred to as complete RPMI medium, or cRPMI). MNCs were stimulated in round-bottom 96-well plate (Corning Life Sciences, #3799) with fixed Candida (multiplicity of infection, MOI=5), LPS (10 ng/ml) or Curdlan (10 µg/ml) for 24 h unless otherwise specified. For enzyme-linked immunosorbent assays, supernatants were stored at -80°C and analyzed in batches for IL-1β and IL-6 (eBioscience, #88-7261-76), or using a multiplex enzyme-linked immunosorbent assay (ELISA) for IL-1α, IL-1β, IL-1RA, IL-6, TNF-α and IL-10 (R&D Systems) as per manufacturer’s instructions. 2.2.5 Flow cytometry MNCs were washed three times in phosphate buffered saline (PBS) and stained for surface expression of CD14 (eBioscience #25-0149; 1:100 dilution), and dectin-1 (AbD Serotec, #MCA4661A488; 1:100 dilution) as indicated. Native mTOR expression and phosphorylation was performed on cryopreserved mononuclear cells, in batches in order to reduce variability. In brief, MNCs were thawed, washed in cRPMI (3x) and rested for 1 h. 500,000 cells were stimulated with LPS for 30 min. CD14 antibody (eBioscience, #48-0149-42, 1:100 dilution) was added during the 35 last 15 min of incubation. Incubation was stopped and cells were stained intracellularly using the Transcription Factor Phospho Buffer Set (BD Biosciences, #565575) for native (Cell Signaling Technology, #5043S, 1:50 dilution) and phospho mTOR (Ser2448, Thermo Fisher Scientific, #501123458, 1:50 dilution). Cells were washed 3x in PBS before acquisition. Cells were analyzed on a BD Fortessa or a BD LSRII flow cytometer. Data were analyzed using FlowJo v10 (FlowJo, LLC, Ashling OR). Live cells were gated on singlets. 2.2.6 Phagocytosis assay MNCs were incubated in 96-well plates in the presence of Candida strains pre-stained for 15 min with DAPI (Biolegend, #422801) at room temperature. After a 1 h incubation with Candida species, cells were quenched in Trypan Blue/PBS of any residual fluorescence of non-phagocytized Candida spp, and then washed once in PBS before staining with a CD14 PE-Cy7-conjugated antibody (eBioscience, #25-0149, 1:100 dilution). Cells treated with cytochalasin D (10 µg/ml, Sigma-Aldrich) were used as negative controls. Samples were analyzed on an Amnis Image Stream Imager. Results are presented as the percentage of monocytes (CD14-expressing cells) that have phagocytosed at least one Candida particle. Data was analyzed using IDEAS software (v.5.0.343.0) 2.2.7 Western blots After stimulation (LPS or curdlan), monocytes were washed, and then lysed in RIPA buffer in presence of phosphatase/protease inhibitors (Santa Cruz Biotechnology, #sc-24948). Protein quantification was performed using a Pierce 660 nm protein assay (Thermo Fisher Scientific). Lysates boiled in 4X Laemmeli buffer (Bio-Rad) supplemented with 2-mercaptoethanol were ran 36 on 4-20% mini-PROTEAN TGX gradient gels (Bio-Rad), transferred to polyvinylidene difluoride (PVDF) membranes, and incubated with primary and secondary antibodies. Blots were imaged on a LI-COR Odyssey 9120. Images were acquired using Studio ver. 5.2 and adjusted for brightness. 2.2.8 Polysome profiling For polysome profiling experiments, a minimum of 3x106 monocytes were pre-cultured with cycloheximide (100 μg/ml) for 10 min at 37°C, washed once in PBS/cycloheximide and lysed in polysome lysis buffer (Mammalian ARTseq™ Ribosome Profiling Kit, Illumina, #RPHMR12126). Lysates were layered onto 10 to 50% sucrose gradients in buffer (0.3M NaCl, 15mM Tris-Cl pH 7.5, 15mM MgCl2, 100 μg/ml cycloheximide) in the presence of heparin (1 mg/ml) and spun in an ultracentrifuge (SW41, Beckman Coulter) for 3.5 h at 4°C (35,000 rpm) in order to separate RNA strands based upon ribosomal occupancy. After fractionation, purified, in vitro transcribed dsRED RNA was proportionally spiked into pooled monosome, disome, or heavy or light polysome fractions as internal control. 2.2.9 Real-time qPCR Total RNA was isolated using TRIzol LS (Thermo Fisher Scientific) followed by chloroform extraction and cleaned using RNeasy Mini spin columns (Qiagen) followed by ethanol precipitation. mRNA was reverse transcribed using SuperScript® III First-Strand Synthesis SuperMix (Thermo Fisher Scientific, #18080400), and qPCR experiments were carried out in triplicates on a ViiA 7 system (Applied Biosystems) using both Power SYBR® Green (Thermo Fisher Scientific, #4368706) or TaqMan. Data were normalized on dsRED (ΔCt method) as detailed in246. Briefly, ΔCt was calculated for each fraction against dsRED. 2-ΔCt was then 37 calculated, and the sum of all fractions determined. Gene expression (mRNA) was expressed as 2ΔCt x 100)/sum of each fraction. The following primer sequences were used for the qPCR: Table 2.1 List of primers used in Chapter 2 Gene/primer name Direction Sequence CLEC7A (Dectin-1 receptor) forward 5’- TCGACTCTCAAAGCAATACCAG -3’ reverse 5’- CCACAGCTATCACCAGTATTACC -3’ MALT1 forward 5’-AGGCTATGGAACACACTGAAG-3’ reverse 5’-ACCACTGATATTGAACAAAAGGATG-3’ CARD9 forward 5’-CACCCAGCTCTCAGACAAAG-3’ reverse 5’-CTTAACAAACGGCCCCAATG-3’ BCL10 forward 5’-GAAATATAAAACTAGAACATCTGAAAGGAC-3’ reverse 5’-TGGTACATGACAGTGGATGC-3’ ACTB forward 5’-CCTTGCACATGCCGGAG-3’ reverse 5’-ACAGAGCCTCGCCTTTG-3’ dsRED forward 5’- TGAAGCTGAAGGTGACCAAG-3’ reverse 5’- GGACAGCTTCTTGTAGTCG-3’ 2.2.10 Pulse-labelling experiments Monocytes were stimulated for 2.5 h and pulsed with 35S-methionine/cysteine for the last 30 min of the experiment. Cells were washed with PBS and lysed in RIPA (Santa Cruz Biotechnology); equivalent amounts of protein were loaded on polyacrylamide gel. Blots were imaged on film. 2.2.11 Metabolic assays Glucose uptake in monocytes was measured by flow cytometry. Cryopreserved MNCs were rested for 1 h at 37°C in cRPMI after gentle thawing, and then counted before stimulation for 2 h and 40 min in presence of LPS (10 ng/mL), with 2-(N-[7-Nitrobenz-2-oxa-1,3-diazol-4-yl]Amino)-2-Deoxyglucose (2-NBDG, 15 µM) added for the last 40 min. Cells were stained with CD14 (eBioscience #25-0149; 1:100 dilution) and CD16 (eBioscience #48-0168; 1:100 dilution) at the 38 beginning of LPS stimulation. Cells were washed twice before acquisition on an LSR Fortessa™ flow cytometer (Becton Dickinson). Data was analyzed using FlowJo® (FlowJo, LLC). For extracellular flux analyses, monocytes were plated on Cell-Tak™ (Corning, #354240)-coated XF96 Cell Culture Microplates. Cells were rested in a non-CO2 incubator, and glycolysis stress test was performed as per manufacturer protocol (Agilent Seahorse, #103020-100) using the Seahorse XFe96 Analyzer. Extracellular acidification rate (ECAR) was normalized to protein content. L-lactate was measured by colorimetry (Abcam, #ab65331). 2.2.12 Microarray analyses Total RNA from purified CD14+ monocytes was extracted using the MagJET RNA purification kit (ThermoFisher Scientific). RNA was quantified using NanoDrop™ 1000 spectrophotometer, and its integrity was determined using the Agilent 2100 Bioanalyzer. Samples were hybridized onto an Illumina HumanHT-12 v4 Expression BeadChip and scanned with an Illumina iScan System (Illumina, San Diego, CA, USA). Data were analyzed using R. Data was preprocessed by quantile normalization and log2 transformation. Probes that were non-expressed (based on their detection p-values) were removed. For differential gene analyses, linear models were fit using limma247. Probes with false discovery rate (FDR) ≤ 0.05 calculated using the Benjamini-Hochberg method were considered differentially expressed. For ClueGO pathway analyses, genes that were differentially expressed by two-fold or more when compared to adult or term samples were included. P-values were adjusted for multiple comparisons using the Bonferonni step-down method. Gene ontology (GO) biological-processes ontology was used. Degree of functional enrichment was determined by sorting enriched terms based on a p-value threshold of <0.001. We used GO tree intervals between levels 3 and 8 and Kappa Score Threshold of 0.04. Gene Ontology 39 analysis and Network images were generated using the ClueGO 2.3.3 plugin for Cytoscape 3.5.1 (references 248,249). Heatmaps for metabolic pathways were generated based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Gene expression shown in heatmaps represents Z score normalized values. Principal component analysis was performed using the prcomp function in R with zero-centered and scaled variables. The microarray data has been deposited in GEO under accession code GSE104510. 2.2.13 Statistical analysis For each experiment, sample size was estimated based on the variance from 3 to 5 replicates in any age group (assuming comparable variance between age groups). To avoid a selection bias, we balanced distribution of adult, term and preterm samples in batch experiments over time. GraphPad Prism v6.07 was used for graphs and statistical analyses. To simplify the figures, we present p values only when indicated by the data. Differences between groups were analyzed using 2-tailed t tests, ANOVA (for groups) or as otherwise specified. Normality of data was assumed in most statistical testing, unless grossly skewed. In cases of non-normal distribution, a Mann-Whitney U test or a Kruskal-Wallis test were performed. Statistical significance was considered at p values of <0.05. Except for the microarray analyses, adjustment for multiple comparisons was not performed to capture all possible associations. When data is shown in boxes and whiskers, boxes are spanning from the first quartile to the third quartile, with the center line depicting the median. Whiskers are extending from min to max. 40 2.3 Results 2.3.1 Transcriptomic analysis of preterm monocytes reveals remodeling of metabolic and ribosomal pathways To better understand molecular mechanisms underlying the reduced inflammatory activity of preterm monocytes, we employed an unbiased transcriptomic approach. Gene expression of CD14+ monocytes from healthy term neonates and very preterm neonates (both purified from cord blood) was analyzed by microarray after stimulation for 5 h with the bacterial cell wall component LPS. As a control, monocytes from healthy adults (peripheral blood) were processed in parallel. Interestingly, the main driver of variability between the samples was the stimulation condition (LPS vs untreated; principal component 1 (PC1), 28% of variance), while separation by age group was of secondary importance indicated by separation on PC2, comprising 9.3% of the variance (Fig. 2.1a). Additionally, of the 11,697 genes affected by LPS stimulation, 6067 were the same across all age groups and a further 3975 were common to adults and full terms (Fig. 2.1b), suggesting a conserved transcriptomic response to TLR4 stimulation in monocytes regardless of age. Surprisingly, even the upregulation of inflammatory cytokine genes such as IL1B and IL6 was preserved in all age groups (Fig. 2.1c) despite significantly reduced secretion of the corresponding proteins by preterm monocytes (Fig. 2.1d). To identify processes that could 41 potentially account for the disconnect between gene and protein expression, we performed pathway analysis. At an FDR cutoff of 1 %, processes mapping to mRNA translation and oxidative phosphorylation were dampened in the preterm group (Fig. 2.2a). Specifically, genes coding for large and small ribosomal subunit proteins were strongly downregulated in preterm monocytes Figure 2.1 The transcriptomic response to LPS is conserved in preterm monocytes. CD14+ monocytes from healthy adults, full term and preterm neonates were stimulated for 5 h with 10 ng/mL LPS and assessed by microarray. (a) Principal component analysis of all probes above signal threshold. (b) Venn diagram showing probes significantly changed with LPS (FDR < 5%) and their overlap between the age groups. (c) Gene expression of selected cytokine genes based on the microarray data as represented on a Z score scale. (d) Their corresponding protein expression were measured by ELISA after a 24 h LPS stimulation of mononuclear cells. Effect of age was assessed by Kruskal-Wallis test (mean ± SD; n= 3 to 6 subjects per age group). 42 (Fig. 2.2b). Additionally, genes involved in glycolysis showed a different expression pattern between the age groups, while oxidative phosphorylation and PPAR signaling pathways (a hallmark for fatty acid metabolism) were generally down- and up-regulated respectively in preterm monocytes (Fig. 2.2c). Interestingly, comparing neonatal to adult monocytes, preterm and term Figure 2.2 Metabolic and ribosomal pathways are transcriptionally altered in preterm monocytes Pathway analysis of microarray data presented in Fig. 2.1. (a) Gene ontology analysis comparing unstimulated preterm to unstimulated term and adult samples (combined for analysis) using FDR < 0.01. (b) Heatmap depicting gene expression of the KEGG ribosome pathway for unstimulated samples. (c) Heatmap representing the top 15 up- and downregulated genes in each of the depicted pathways in the unstimulated and LPS stimulated samples comparing neonates to adults. Genes that are significantly different between the age groups (FDR < 0.01) are marked by an asterisk. Color scales represent log fold changes compared to adult monocytes. 43 cells generally showed the same trend with a more pronounced phenotype in the preterm group. This suggests that the observed alterations may be characteristic for fetal development and gradually attenuate throughout the last trimester of pregnancy, progressively increasing metabolic activity and mRNA translation towards term delivery. 2.3.2 Protein synthesis is dampened in preterm monocytes To validate the findings from our bioinformatic analyses, we performed a series of functional experiments. First, we aimed to understand whether reduced expression of ribosomal genes resulted in lower rates of protein synthesis in preterm monocytes: Purified CD14+ cells were stimulated with LPS for 2 h and subsequently pulse-labelled for 30 min with 35S-Met/Cys. We observed globally dampened methionine incorporation in preterm cells, both in resting and in LPS-stimulated conditions, suggesting reduced translation (Fig. 2.3a, b). To determine whether this reduction was mainly driven by low translation of immune response genes, we examined signaling molecules important in antifungal immunity. Fungal pathogens such as Candida albicans are a common cause of neonatal sepsis in preterms and the risk for infection increases with lower gestational age250. Previous data from our lab had shown that monocytes from preterm infants produce only marginal levels of pro-inflammatory cytokines when stimulated in vitro with fungal pathogen associated molecular patterns (PAMPs) or whole Candida particles251. Dectin-1 is a pathogen recognition receptor mediating antifungal immunity by binding to β-glucan, a fungal cell wall component consisting of glucose polymers. We hence examined CLEC7A (the gene coding for the Dectin-1 receptor) as well as the signalosome components MALT1, BCL10 and CARD9 activated downstream of Dectin-1 (Fig. 2.3c) by polysome profiling. We observed no changes in global translation initiation between preterm, term and adult monocytes as evidenced by the 44 comparable shape of polysome traces (Fig. 2.3d). No overt differences in polysomal occupation of the target mRNAs were observed between the age groups (Fig. 2.3e) which may however have been masked by substantial interindividual variability. Despite comparable mRNA levels between the age groups (Fig. 2.3f), protein expression starkly differed with MALT1 and Bcl10 protein levels being severely reduced in preterm monocytes (Fig. 2.3g, h). Interestingly, expression of the receptor Dectin-1 was not affected by age (Fig. 2.3i). Together, these data suggest that preterm Figure 2.3 Decreased protein translation in preterm monocytes. (a) S35 pulse labeling of monocytes stimulated for 2.5 h with LPS and quantified in (b) from three independent experiments. (c) Schematic of Dectin-1 dependent activation of the CARD9-Bcl10-MALT1 signalosome. (d) Polysome profiles of adult, term and preterm CD14+ monocytes and (e) corresponding quantification of Dectin-1 signaling cascade genes. Data are from 4 subjects per age group (boxes and whiskers; RQ = relative quantification). (f) Quantification of the signalosome genes by qPCR in CD14+ cells (4 to 5 subjects/age group; mean ± SD). The protein for each assessed gene was confirmed by (g) Western blot for MALT1 and Bcl10 after 0 – 60 min LPS stimulation, with quantification (h) from 4 independent experiments (mean ± SD) and by (i) flow cytometry for Dectin-1 (unstimulated mononuclear cells, gated on CD14-expressing cells; data pooled from 10 to 23 subjects per age group; boxes and whiskers). 45 monocytes do not respond to fungal stimulation in vitro due to the absence of the required signalosome machinery that is potentially regulated on the translational level. 2.3.3 Preterm monocytes have reduced glycolytic activity Our bioinformatic analysis hinted at differences in glucose metabolism in preterm monocytes (Fig. 2.2c). Over the last years, the role of glycolysis in shaping innate immune responses has become increasingly appreciated252, prompting us to investigate its role in regulating preterm immunity. In line with data from the literature showing a requirement for increased glycolytic flux to mediate cytokine production upon stimulation, blocking glycolysis using the glucose analogue 2-deoxy-glucose (2-DG) led to significantly reduced IL-1β and IL-6 production in adult monocytes stimulated with LPS or curdlan (Fig. 2.4a). Accordingly, we observed increased uptake of the fluorescent glucose analogue 2-NBDG with LPS stimulation (Fig. 2.4b, c). While preterm monocytes also increased their glucose uptake after activation, their uptake levels (both at baseline and after 2 h LPS stimulation) were significantly lower than in adult or term monocytes. In addition to low glucose uptake, we also showed reduced secretion of lactate (Fig. 2.4d), the end product of aerobic glycolysis. Lactate levels correlated with IL-1β and IL-6 secretion in adult cells, supporting the notion that glycolysis is important for pro-inflammatory cytokine production (Fig. 2.4e). Lastly, we employed real-time extracellular flux measurements to further assess the preterm metabolic phenotype. When cultured in glucose-free media, the extracellular acidification rate of preterm monocytes was slightly lower at baseline compared to their adult and term counterparts. As expected, addition of glucose led to a significant increase in glycolytic rate in adult and term monocytes. Notably, this upregulation of glycolysis was significantly abrogated in preterm cells, 46 suggesting low glycolytic capacity. Altogether, our results support the idea of reduced glucose utilization in preterm monocytes (Fig. 2.4f,g). 2.3.4 Glycolysis-dependent immune responses are diminished in preterm monocytes mRNA translation comes at high energetic cost, consuming about 45 % of cellular ATP253. In immune cells, PRR stimulation induces a rapid response, including upregulation of mRNA translation254,255, requiring a considerable amount of energy. The stimulation-induced increase in glycolysis has often been suggested to fulfill this demand256. We hence assessed whether the low levels of cytokine and signalosome proteins could be due to restrained glycolysis in preterm Figure 2.4 Reduced glycolysis in preterm monocytes. (a) Cytokine production with blockage of glycolysis in mononuclear cells stimulated with LPS or curdlan for 24 h (Wilcoxon matched-pairs signed rank test; boxes and whiskers; 4 to 9 samples per condition; 2-DG= 2-deoxy-d-glucose). (b) Representative plot of one adult sample for 2-NBDG uptake experiment quantified in (c): mononuclear cells were incubated for 30 min with 2-NBDG (Fluorescent 2-(N-[7-Nitrobenz-2-oxa-1,3-diazol-4-yl]Amino)-2-Deoxyglucose), uptake was quantified by flow cytometry, gating on CD14+CD16- cells; P values represents difference between groups using a Kolmogorov-Smirnov test (n=5-7 per age group). (d) Lactate secretion by LPS stimulated (24 h) mononuclear cells. Data are from 9-10 subjects per age group (boxes and whiskers; p value= effect of age by 2-way ANOVA). (e) Correlation of lactate secretion with cytokine production in adult mononuclear cells (Spearman’ r; *p < 0.05; with dotted regression line); 8 subjects. (f) Representative graph of Seahorse glycolytic stress assay in CD14+ cells with quantification of glycolytic capacity in (g) from 3 independent experiments (3–9 subjects per age group; mean ± SD; p value by Mann–Whitney U test). 47 monocytes. We cultured adult monocytes in the presence of 2-DG to block glycolysis or cycloheximide to block protein synthesis and quantified MALT1 protein expression at different time points. Indeed, MALT1 protein levels rapidly declined with 2-DG treatment, while increasing in untreated cells (Fig. 2.5a). This was unlikely due to increased cell death as differences in MALT1 levels were evident 16 h post 2-DG treatment when cell viability remained high in all conditions (Fig. 2.5b, c). Direct blocking of translation elongation with cycloheximide nearly completely abolished MALT1 expression, supporting the idea that 2-DG blocks de novo translation required to maintain MALT1 protein levels. We also assessed whether the low MALT1 levels could influence glycolytic rate: While MALT1 inhibition reduced cytokine production as expected, it did not have any effect on lactate secretion (Fig. 2.5d). Together, this data supports the notion that glycolysis is required for sustained MALT1 expression whereas glycolysis is Figure 2.5 Inhibition of glycolysis leads to reduced MALT1 protein expression. (a) MALT1 protein expression in adult mononuclear cells treated with 2-DG and cycloheximide (CHX) quantified by flow cytometry with gating on CD14+ cells. (b) corresponding viability over time and (c) MFI quantified at 16 h (MFI mean fluorescence intensity; dotted line: signal for fluorescence-minus-one staining control MFI level; boxes and whiskers with a paired 2-sided t-test in c; mean ± SD in a and b, n=6). (d) Cytokine and lactate secretion after MALT1 inhibition in LPS stimulated (24 h) adult mononuclear cells (boxes and whiskers with 2-sided paired t-tests, n=8). (e) Impact of 2-DG or CHX treatment on phagocytosis of C. albicans (Ca) by adult monocytes (n=3) and comparison of phagocytosis levels in adult, term and preterm monocytes. 48 independent of MALT1 protein levels. Next, we asked whether other arms of the immune response might be equally regulated by low glycolytic flux in preterm monocytes. Phagocytosis is one innate immune function that is generally thought to be conserved in preterm monocytes84. Interestingly, blocking glycolysis with 2-DG or translation with cycloheximide in adult monocytes did not have any influence on their ability to phagocytose C. albicans (Fig. 2.5e). Additionally, phagocytic capacity did not differ between adult, term and preterm monocytes (Fig. 2.5e). In summary, glycolysis-dependent immune responses were diminished in preterm monocytes while glycolysis-independent responses were intact, suggesting that reduced glycolysis may be a main modulator in restraining fetal immune responses. 2.3.5 mTOR pathway activity is low in preterm monocytes We next aimed to identify potential upstream mechanisms that could create the phenotype we observed in preterm monocytes. The kinase mTOR is an important signaling node regulating both glycolysis and protein synthesis (Fig. 2.6a). Indeed, further inspection of the microarray data revealed age-specific differences in expression of mTOR as well as of upstream regulators and downstream targets of this kinase (Fig. 2.6b). Western blot and flow cytometry analysis demonstrated that mTOR protein levels were reduced in an age-dependent manner (Fig. 2.6c, d). Additionally, while stimulation with LPS led to an increase in mTOR phosphorylation in all three age groups, baseline and stimulation-induced levels were significantly lower in neonatal monocytes, especially those from preterms (Fig. 2.6e). mTOR phosphorylation strongly correlated with cytokine production in adults, however, this connection was lost in preterm cells (Fig. 2.6f), potentially due to their low levels of mTOR phosphorylation. Collectively, these data support low 49 mTOR activity in preterm monocytes, leading to reduced glycolytic activity and mRNA translation, finally resulting in dampened inflammatory cytokine production (Fig. 2.7). Figure 2.6 Altered mTOR signaling in preterm monocytes. (a) Schematic of PRR dependent mTOR activation. (b) Gene expression of mTOR pathway genes in the microarray data (6–12 per age group; boxes and whiskers; 2-way ANOVA across age groups, only significant p values are shown). (c) mTOR quantification by Western blot in monocytes. (d) Native mTOR levels in mononuclear cells (quantified by flow cytometry with gating on CD14+ cells; MFI=median fluorescence intensity, 2-sided unpaired t test) and (e) phosphorylated mTOR levels normalized to unstimulated adult cells in the same samples after 30 min LPS stimulation (5 to 8 subjects per age group; age-related effect by 2-way ANOVA). (f) Linear regression between LPS-induced mTOR phosphorylation and cytokine production (with goodness of fit R2 and p value). 50 2.4 Discussion Monocytes isolated from cord blood of preterm neonates produce low levels pro-inflammatory cytokines in response to stimulation. This comparative “unresponsiveness” has been observed for a variety of PRRs59,81,85,242, suggesting global age-specific changes in upstream regulatory mechanisms. Here, we show that the transcriptomic response to LPS is conserved to a surprising extent in preterm, full term and adult monocytes, including transcription of pro-inflammatory cytokine genes. Instead, preterm monocytes are characterized by a unique metabolic phenotype with alterations in glycolytic, mitochondrial and fatty acid metabolism on the transcriptomic level. We functionally validate that glycolysis rates are low in preterm monocytes and cytokine production, a glycolysis-dependent process, is limited. Metabolic control of inflammatory responses is increasingly better understood and offers attractive therapeutic avenues through dietary interventions or metabolic reprogramming drugs in a variety Figure 2.7 Summary model for Chapter 2 51 of disease contexts257. It is interesting to contemplate if or how the unique metabolic in utero environment contributes to the observed preterm monocyte phenotype. Due to their rapid growth, fetal energy requirements are tremendous and mostly met by glucose, facilitated by high placental expression of the glucose transporter GLUT1258. After birth, the metabolic supply is dramatically altered and nutrients are supplied through breastmilk, mostly in form of lactose and fatty acids. Numerous studies have demonstrated immunomodulatory capacity of breastmilk or its components48 and future studies specifically examining its impact on myeloid cell metabolism should provide useful insights into postnatal immune development. These considerations are especially important in the context of preterm birth where placental nutrient supply is prematurely switched to exogenous feeding. As such, preterm infants have low levels of glycogen and fat storage, predisposing them to hypoglycemia in early life259. Therefore, exogenous glucose is sometimes administered in their first week after birth, increasing the risk for hyperglycemia259. How this imbalance in systemic glucose metabolism influences immune reactivity remains to be determined but it can be speculated that – as in in diabetes patients where low glycemic control is associated with NF-κB activation260 – improper glucose balance may contribute to the heightened immune reactivity and oxidative stress observed in the neonatal period. A rise in glycolytic flux upon PRR stimulation not only increases the production of metabolic intermediates required for production of inflammatory molecules, it also rapidly provides ATP to fuel the increased demand for protein synthesis. As our bioinformatic analysis suggested reduced expression of ribosomal proteins in preterm monocytes, we aimed to functionally characterize mRNA translation in these cells and to investigate a potential impact of low glycolytic flux on translation of immune response genes. Indeed, post-transcriptional regulation, including ribosomal 52 activity, is increasingly appreciated as a major modulator of immune responses255,261,262. Employing pulse labeling and polysome profiling, we provide evidence of markedly reduced global translation rates but similar translation initiation for the subset of genes examined. Our conclusions from these experiments are limited by the small sample size and the low number of preterm monocytes available. Polysome profiling is generally conducted with about 100 million cells. Due to the small cord blood volume generally obtainable from a preterm placenta, we were unable to isolate a large number of CD14+ cells and had to work with less than 10 million cells per sample. As a result, the amount of RNA per fraction was comparatively low, prompting us to consolidate fractions into monosome, disome, light polysome and heavy polysome groups, potentially limiting our ability to observe age-specific modulation of translation initiation. Importantly however, we provide further evidence for a role of protein synthesis inhibition in the preterm phenotype by assessing protein expression of the signalosome component MALT1 under glucose limiting conditions. Treatment with 2-DG rapidly decreased MALT1 expression, suggesting a dependency on glycolytic metabolism. Together, our data suggest that the low glycolytic activity of preterm monocytes may limit mRNA translation rates, but further studies will be required to confirm this model. Besides globally reduced ribosomal activity, translation may be more selectively regulated and limited to pro-inflammatory genes. Conserved UTR motifs or mRNA specific sequences can modulate translation through sequestration of mRNAs or protein degradation, often mediated by interaction with RNA binding proteins or non-coding RNAs261,263. Intriguingly, several metabolic enzymes have been reported to exert moonlighting functions as RNA binding proteins105,264. For example, GAPDH can bind to TNFA and IFNG mRNAs preventing their translation. Increased 53 availability of glucose recruits GAPDH to its canonical role in glycolysis, in turn permitting translation of TNFA and IFNG106,265. Such mechanisms offer an interesting addition to the potential role of glycolysis in facilitating translation of immune responses genes and could contribute to the disconnect of cytokine transcript and protein levels observed in preterm monocytes. A well-studied example of non-coding RNAs in immunity is the miR-146a family whose targets include the signaling molecules IRAK1 and TRAF6 downstream of MyD88266. Induction of miR-146a during PRR activation is essential to prevent overt inflammation through a negative feedback loop. While changes in myeloid miRNA levels have been reported in full term neonates (including higher LPS-induced miR-146a levels compared to adults)267,268 and in pregnant women undergoing spontaneous preterm labor269, to the best of my knowledge, no study has systematically evaluated expression and activity of non-coding RNAs in premature neonates. In addition to endogenous production of non-coding RNAs, the monocyte phenotype in utero could also be maintained by secretion of miRNAs by the placenta270. Indeed, placentally-derived extracellular vesicles have immunomodulatory capacity, for example promoting IL-10 production by myeloid cells271 and studies in other disease contexts have shown that extracellular vesicle-derived miRNAs can modulate myeloid cells272. Potential contribution of placentally-derived miRNAs on fetal immune reactivity is an intriguing hypothesis as it presents an explanation for hyperinflammatory responses observed in the neonatal period: following abrupt removal from the immunosuppressive in utero environment, including extracellular vesicle-derived miRNAs, preterm myeloid cells may overtly react to PRR stimulation in the absence of repressive signals. The data presented here suggests that future studies examining maternal and fetal derived miRNAs may provide useful insights in the regulation of fetal immune responses. 54 Our data also demonstrate low phosphorylation of mTOR. As a central regulator of catabolic and anabolic cellular processes, careful balancing of mTOR activity is essential for optimal function in most mammalian cell types123. In myeloid cells, exact requirements substantially differ depending on the kinetics post stimulation, but mTOR activation has been generally shown to be essential for induction of PRR responses including cytokine production127. mTOR phosphorylation was significantly reduced in preterm monocytes compared to adults, with full term monocytes displaying an intermediate pattern. Of note, the negative mTOR regulator DDIT4L was strongly overexpressed in preterm cells, even more so after LPS stimulation. This not only provides a possible explanation for the low mTOR phosphorylation observed but makes an interesting point about the preterm monocyte response to LPS: these cells do not only passively “neglect” to produce cytokines, they instead seem to actively prevent such pro-inflammatory responses. This suggests that preterm monocytes are not inert and uncapable of responding to PRR stimulation but are instead perfectly suited for the in utero environment: The amniotic sac is comparatively sterile foregoing the need for strong pro-inflammatory responses. Besides saving ATP that would be required to produce copious amounts of inflammatory cytokines, it may even be essential to curb inflammation to prevent rejection of maternal tissues. Additionally, we demonstrate that phagocytic capacity is not limited in preterm monocytes in line with their essential role in tissue remodeling of the rapidly growing fetus, further corroborating the preterm monocytes are fully functional. Since our results were published in 2018, other studies have confirmed some of our findings. Dreschers et al. have shown low mTOR activity, glycolytic capacity and mitochondrial respiration in macrophages derived from full term neonates compared to adults120,121. While preterm samples 55 were not included in their studies, it is reasonable to speculate that their phenotype may be similar to full-term derived macrophages but more pronounced, as observed in our experiments. Interestingly, low mTOR activity may not be limited to monocytes but potentially a feature of preterm myeloid cells more generally as Campbell et al. have reported reduced mTOR phosphorylation in preterm neutrophils136. In conclusion, our data significantly enhance our understanding of preterm monocytes and point to potential new therapeutic avenues such as metabolic reprogramming to modulate inflammatory responses in the neonatal period. 56 Chapter 3: DDIT4L limits innate immune activation in fetal monocytes 3.1 Introduction The innate immune system matures during the third trimester of gestation in humans46. In utero, tight regulation of innate immune activity appears essential to ensure tolerance to both maternal and self-antigens, and may not be desirable until the fetus is viable35. Indeed, ex vivo LPS-stimulated fetal monocytes secrete relatively little pro-inflammatory cytokines compared to adult monocytes81,251, but cytokine production increases as the pregnancy advances, so that cells isolated from cord blood at full term have more comparable PRR responses to their adult counterparts59. Little is known about the basic mechanisms that limit innate immune activation at this stage, except for studies suggesting that this may be in part due to high levels of anti-inflammatory modulators such as adenosine35. Additionally, intrinsic immunosuppressive properties of fetal immune cells exist but are largely uncharacterized. Previously, we reported selective upregulation of DNA damage inducible transcript 4-like (DDIT4L) as well as low mTORC1 activity in fetal monocytes compared to adults (Chapter 2, published in reference 251). Independently, Dreschers et al. reported reduced mTORC1 activity in neonatal monocyte derived macrophages120, warranting further evaluation of these pathways in fetal myeloid cells. Evidence suggests that DDIT4L is a negative regulator of mTORC1140,152, resulting in reduced translation initiation of specific genes. Additionally, knockout of DDIT4, a more functionally characterized paralog of DDIT4L, has been shown to reprogram murine bone marrow derived macrophages towards a more glycolytic phenotype, increasing LPS-induced IL-1β production130. Altogether, these data suggest a link between DDIT4L upregulation and changes in metabolic activity and responsiveness we measured in preterm immune cells. However, in order 57 to understand the role of DDIT4L during fetal development, we need to first consider the distinct bioenergetics characteristics of the fetal environment. Myeloid cell reactivity is modulated by metabolic substrate availability and usage, with inflammatory phenotypes often characterized by glycolysis while quiescent, anti-inflammatory cells rely more on fatty acid oxidation and oxidative phosphorylation100. In utero, immune cells are exposed to reduced oxygen levels compared to the postnatal environment. Activation of monocytes and their egress from the bloodstream into tissues necessitates an increase in anaerobic glycolysis, allowing the development of inflammatory macrophages in the comparatively hypoxic tissues during infection273. This switch from energy-efficient oxidative phosphorylation to hypoxia-induced anaerobic glycolysis drastically reduces ATP production, necessitating selective changes in mRNA translation rates to reduce energy expenditure274. Mechanistically, these changes are regulated by mTORC1, which governs cell proliferation and protein synthesis, in addition to cellular energy metabolism. A key sensor of hypoxia is the transcription factor HIF-1α, which induces expression of glycolytic genes such as GLUT1 and lactate dehydrogenase275. Knockout of HIF subunits is embryonically lethal276, suggesting that HIF is crucial to maintain anaerobic glycolysis in the physiologically hypoxic fetal environment. Accordingly, (hematopoietic) stem cells require a hypoxic niche to maintain quiescence and pluripotency277, but how hypoxia affects circulating, matured myeloid cell function in the periphery during fetal development is unknown. In this study, we had two main specific objectives: First, we aimed to characterize the expression of DDIT4L during LPS stimulation of primary human neonatal monocytes. We show that DDIT4L was rapidly induced by LPS, and that its expression was further increased by hypoxia in neonatal, but not in adult monocytes. Second, we aimed to determine the effect of DDIT4L overexpression 58 on LPS responses in a monocyte cell line model. Here, we hypothesized that DDIT4L upregulation limits LPS responsiveness through inhibiting mTOR activity. Using a unique monocytic cell line model where DDIT4L expression can be upregulated “on-demand”, we demonstrate that DDIT4L reduced mTORC1 activity, S6K phosphorylation and global mRNA translation in these cells. Additionally, DDIT4L overexpression significantly limited LPS-induced pro-inflammatory cytokine secretion. Lastly, we provide evidence that low DDIT4L expression in alveolar macrophages was associated with worsened bronchopulmonary dysplasia severity, potentially indicating a physiological role for DDIT4L in early postnatal life. 3.2 Materials and Methods 3.2.1 Human subjects Peripheral blood was collected from healthy adults. Cord blood was collected at the term of gestation (37 to 41 weeks of gestation, after Caesarean section delivery), or before 33 weeks of gestation (hereafter referred to as preterm samples, Caesarean or vaginal delivery) at the BC Children’s and Women’s Hospital. All blood samples were collected in sodium heparinized vacutainers and processed within two hours of collection. This study was approved by the University of British Columbia Children’s & Women’s Research Ethics Board. All studies were performed in accordance with the declaration of Helsinki. Informed consent was sought from adult participants and most parents of neonatal subjects. De-identified preterm cord blood samples were also used following a waiver of consent in selected cases where parents were not reachable, according to privacy procedures approved by our ethics review board. 59 3.2.2 Cells Peripheral or cord blood mononuclear cells were isolated by density gradient centrifugation. Briefly, blood was diluted 1:1 with PBS (or 1:2 for cord blood) and layered on top of 30 mL Lymphoprep (Stemcell #07861). After centrifugation for 20 min at 2300 rpm without brake, mononuclear cell layer was extracted and washed twice with PBS before immediate usage of cells for experiments or cryogenic storage. Where indicated, monocytes were extracted using the CD14+ purification kit II (Stemcell #17858) as per manufacturer’s instructions. Mononuclear cells or CD14+ cells were cultured in cRPMI (RPMI with 10 % human AB serum (Gibco #11875-093), 1 % sodium pyruvate, 1 % penicillin/streptomycin). U937 cells were grown in R10 (RPMI supplemented with 10 % FBS (Thermo Fisher Scientific #26140079), 1% sodium pyruvate, 1% penicillin/streptomycin) and seeded at 0.1 million cells per mL every 2-3 days. For lentivirally transduced cells, 1 µg/mL puromycin (Sigma #P8833-10MG) was added to the culture media. DDIT4L overexpression was induced by addition of 100 ng/mL doxycycline (Peprotech #2431450) for indicated times. 3.2.3 Lentiviral transduction Luciferase was removed from pCW57.1-Luciferase (Addgene #99283) and replaced with the DDIT4L open reading frame or ligated to generate pCW57.1-DDIT4L and pCW57.1-EV respectively. Lentiviral particles were generated using calcium chloride transfection of HEK 293T cells grown in IMDM with 10 % FBS, 1 % sodium pyruvate and 1 % penicillin/streptomycin as described previously278. Supernatant was harvested two days after transfection and concentrated by ultracentrifugation. U937 cells were transduced by spinoculation (60 min at 800 x g at 32°C) in the presence of 8 µg/mL polybrene (Millipore Sigma #TR-1003-G). Media was changed the 60 next morning and puromycin was added at 2 µg/ml on day two post transduction. After two weeks of antibiotic selection, EV or DDIT4L transduced cells were single cell sorted to obtain clones. 3.2.4 CRISPR-Cas9 generation of DDIT4L knockout cells To generate DDIT4L knockout cells, wildtype U937 cells were transfected with pX458 containing DDIT4L guide RNA (5’-ATTTCAGAATTGCTGGACTG-3’ or 5’- CAAACTGCCAGTTGCA-ACCA-3’) and Cas9-2A-GFP. Following nucleofection (Lonza 4D Nucleofector, 1 million cells in 100 µl SF solution, program code FF100), cells were rested overnight before single cell sorting of GFP+ 7-AAD- cells. Recovered clones were screened for knockout by PCR. Clones with sequences diverging from the reference genome were assessed for DDIT4L expression by flow cytometry. 3.2.5 Flow cytometry Surface staining was performed in 50 μL PBS for 15 min at room temperature in the dark. For intracellular staining, the FOXP3 transcription buffer kit was used (Thermo Fisher #00-5523-00). Cells were fixed in 100 μL 1x fix buffer for 15 min at room temperature in the dark. After washing with 100 μL 1X permeabilization buffer, antibodies were added in 25 μL or 50 μL permeabilization buffer for 15 min staining at room temperature in the dark. Subsequently, cells were washed twice and stored in 2 % PFA in PBS at 4 °C until acquisition on a BD LSR II or Fortessa X-20. Antibodies were used at the following concentrations: 61 Table 3.1 List of flow cytometry antibodies used in Chapter 3 Flow cytometry data was analyzed using FlowJo version 10. Viability stains (7-AAD or fixable viability dye in eF506 or eF780) were included in all assays. Analysis was performed on single, viable cells. 3.2.6 Metabolic assays – primary cells 200,000 CD14+ cells were analyzed on a Seahorse XF reader (Agilent) by performing the mitochondrial stress test according to manufacturer’s instructions. For baseline mitochondrial volume assessment, 500,000 mononuclear cells were plated in 200 μL cRPMI in round-bottom 96-well plates and incubated with 100 nM MitoTracker Green (Thermo Fisher Scientific #M7514) for 30 min at 37 °C. Cells were washed three times prior to surface staining with CD14 as described above. After staining, cells were kept on ice and acquired within 2 h. For metabolic assessment of the cell line clones, U937 cells were cultured overnight in the presence of 100 ng/mL doxycycline, 10 ng/mL rapamycin or DMSO. Next, cells were stained with TMRE (Cayman #21426, final conc. Target Clone Fluorochrome Company Cat # Dilution used Viability dye - 7-AAD Biolegend 420404 1:20 Fixable viability dye - eF506 Thermo Fisher Scientific 65-0866-14 1:1000 Fixable viability dye - eF780 Thermo Fisher Scientific 65-0865-14 1:1000 CD14 HCD14 BV421 Biolegend 325628 1:100 p-mTOR (Ser2448) MRRBY PE-Cy7 Thermo Fisher Scientific 25-9718-41 1:50 p-S6 (Ser235, Ser236) cupk43k eF450 Thermo Fisher Scientific 48-9007-41 1:100 p-4E-BP1 (Thr36, Thr45) V3NTY24 eF660 Thermo Fisher Scientific 50-9107-41 1:100 DDIT4L DDIT-03 PE Thermo Fisher Scientific MA5-28628 1:25 62 50 nM), and Mitotracker Green (final conc. 100 nM) for 15 min at 37 °C, 5 % CO2. Cells were washed twice, 7-AAD was added and cells were acquired immediately. 3.2.7 DDIT4L gene expression analysis 250,000 monocytes were plated in 200 μL cRPMI in round-bottom 96 well plates with 250 μM CoCl2 or 10 mM 2-DG (Fisher Scientific #ac111980050) where indicated. Cells were stimulated with 10 ng/mL LPS (Invivogen, #tlrl-eblps) for 5 h before being harvested into TRIzol (Thermo Fisher #15596-026) for RNA extraction according to manufacturer’s protocol. Purified RNA was transcribed into cDNA using the AB cDNA synthesis kit (Thermo Fisher Scientific #4368814). qPCR was performed in triplicates using SybrGreen (Thermo Fisher Scientific #4368706) on a ViiA 7 instrument (Applied Biosystems). Data are represented as 2-∆∆Ct. Table 3.2 List of qPCR primers used in Chapter 3 Gene/primer name Direction Sequence DDIT4L (total) forward 5’-GTTTGAGCAGCAAGAACCCG-3’ reverse 5’-AGTCAAAATCACTTAGCAGGCTC-3’ DDIT4L (endogenous) forward 5’-AGGAAACAGAGCCGTTGACC-3’ reverse 5’-AGTCAAAATCACTTAGCAGGCTC-3’ (same as DDIT4L total reverse primer) ACTB forward 5’-CCTTGCACATGCCGGAG-3’ reverse 5’-ACAGAGCCTCGCCTTTG-3’ 3.2.8 Western blot 200,000 monocytes were washed with PBS and lysed in RIPA buffer supplemented with sodium orthovanadate, PMSF and protease inhibitor (Santa Cruz #sc-24948). Following three rapid freeze-thaw cycles (dry ice to 37 °C water bath), lysates were spun at 21 000 x g for 15 min. Cleared lysates were transferred to new pre-chilled tubes and stored at -80 °C. Lysates were combined with 63 Laemmli buffer and incubated for 5 min at 40 °C before loading on 4 – 20% Tris-Glycine gels (Thermo Fisher Scientific # XP04202BOX). PVDF membranes were blocked with 5% BSA for 2 h before incubation with OXPHOS antibody cocktail (Abcam # ab110413) and β-Tubulin (Abcam #ab6046) at 1:1000 dilution overnight. Incubation with secondary antibodies was performed for 1 h (IRDye 680RD Goat anti-Mouse IgG and IRDye 800CW Donkey Anti-Rabbit IgG, Licor Biosciences # 925-68070 and #925-32213, both at 1:10,000). Blots were imaged on a LI-COR Odyssey 9120 and analyzed using Image Studio version 5.2. 3.2.9 Cell proliferation assays Cells were seeded at 100,000 cells in 5 mL R10 plus DMSO (vehicle control), 10 ng/mL rapamycin or 100 µg/mL doxycycline and cultured for 72 h in six well plates. Cells were transferred to 15 mL tubes and centrifuged (1500 rpm for 4 min) to remove media. Next, cells were divided between the following experiments: DDIT4L expression, cell count/viability measurement and cell cycle phase assessment. For DDIT4L expression, cells were stained as described in the flow cytometry section. For the cell count quantification, a known amount of liquid counting beads (BD Biosciences #335925) was added to quantify cell numbers. Viability (7-AAD staining), cell counts and cell volume (FSC-A) were assessed in the same vial. Cell cycle phase proportions were quantified using propidium iodide staining: Cells were fixed and lysed in 400 µl ice-cold PBS and 800 µl ice-cold 100% ethanol at 4 °C for 2 h. Cells were centrifuged, liquid was removed, and the pellet resuspended in 200 µl staining mix (40 µl propidium iodide (Stemcell # 75002), 1 μL RNase (final concentration of 100 ng/mL), 159 µl PBS) and incubated at 37 °C in the dark for 25 min before acquisition on the flow cytometer. 64 3.2.10 Cytokine production assays 200,000 U937 cells were differentiated with 100 ng/mL PMA (Millipore Sigma #P1585-1MG) in 1 mL R10 in 24 well plates for 48 h. Then, media was replaced with 200 μL fresh R10 and stimulated with 100 ng/mL LPS for 5 h. The night before LPS stimulation, DMSO, rapamycin, doxycycline or CoCl2 were added where indicated. Reagent concentration was maintained when changing the media for LPS stimulation. For the hypoxia experiments, cells were transferred to a 1 % O2 chamber at this time. Following 5 h LPS stimulation, supernatants and cells were harvested. Cells were trypsinized and stained for DDIT4L, IL-8, TNF-α or p-mTOR, p-S6 and p-4E-BP1 as described in the flow cytometry methods section. Supernatants were stored at -80 °C until cytokine quantification was performed by ELISA (Thermo Fisher Scientific #88-8086-88 and #88734686) following manufacturer’s protocol. 3.2.11 Assessment of protein stability 200,000 U937 cells were treated overnight with DMSO (veh) or doxycycline (dox) in normoxia or hypoxia (1% O2). Following overnight pretreatment, all cells were moved to normoxia. The proteasome inhibitor MG-132 (Millipore Sigma #474787) was added at a concentration of 5 µM for 30 min where indicated. Subsequently, cycloheximide (100 μg/ml) was added for indicated time points. Cells were harvested and stained for DDIT4L quantification by flow cytometry as described above. 3.2.12 Protein synthesis assay To assess nascent protein synthesis, 200,000 U937 cells were incubated overnight in the presence of DMSO, rapamycin or doxycycline as well as fixable viability dye eF506. Next, cells were 65 centrifuged, washed with PBS and incubated in 200 µl methionine-free RPMI (Thermo Fisher Scientific # A1451701) with DMSO, rapamycin or doxycycline at 37 °C for 30 min. The Click-iT™ HPG Alexa Fluor 488 Protein Synthesis Assay Kit (Thermo Fisher Scientific #C10428) was used according to manufacturer’s instruction. Buffers from the FOXP3 transcription buffer kit were used for staining (Thermo Fisher #00-5523-00). 3.2.13 Bioinformatic analyses The data presented includes the microarray dataset described in Chapter 2 (GSE104510) and the publicly available dataset GSE149490 (accessed through GEO). Heatmaps were generated using the pheatmap package in R studio version 1.1.463 using R version 3.6.3. For assessment of genes co-expressed with DDIT4L, spearman correlation was performed between DDIT4L and all other probes in the LPS stimulated preterm samples. The spearman rho value was used as input for a pre-ranked Gene Set Enrichment Analysis using the GSEA software version 4.0.3 from the Broad Institute. 3.2.14 Statistical analyses Data was graphed and analyzed using GraphPad version 9. Statistical tests used are indicated in the figure legends. P < 0.05 was considered statistically significant. When data is represented as boxes and whiskers, boxes represent the 25th to 75th quartile with the median indicated by the solid line. Whiskers extend from min to max. 66 3.3 Results 3.3.1 DDIT4L expression is upregulated in metabolically limiting conditions in LPS-stimulated neonatal monocytes In the previous chapter, we have shown selective DDIT4L upregulation in fetal monocytes upon LPS stimulation (Fig. 2.6b, shown again for clarity in Fig. 3.1a). In more extensive kinetic experiments, we determined that DDIT4L expression of the DDIT4L transcript peaked around 5-8 hours post LPS stimulation (Fig. 3.1b). The promoter region of DDIT4L contains binding sites for transcription factors sensing hypoxia (HIF-1α binding to the hypoxia responsive element (HRE)) and glucose restriction (Serum Response Factor binding to the CArG box) (Fig. 3.1c). To determine whether expression of DDIT4L increases in primary immune cells exposed to reduced oxygen levels, cord blood monocytes from neonates born at full term (37-41 weeks) as well as from adult peripheral blood were exposed to pharmacological conditions mimicking glucose or oxygen deprivation. As shown in Figure 3.1d, DDIT4L expression increased in neonatal monocytes exposed to CoCl2–induced cellular hypoxia, both at baseline and after LPS stimulation. In contrast, DDIT4L gene expression remained low in adult monocytes exposed to hypoxia. Limiting glycolytic flux with the non-metabolizable glucose analogue 2-DG similarly increased DDIT4L expression in neonatal, but not in adult monocytes, in agreement with the characterization of DDIT4L as a more general sensor of metabolic stress not limited to hypoxia. A link between DDIT4L expression and cellular metabolism was further suggested by a Gene Set Enrichment Analysis (GSEA). This analysis performed on LPS-stimulated preterm monocytes (n = 8) using the KEGG database showed that DDIT4L expression negatively correlated with expression of genes involved in oxidative phosphorylation and translation (Fig. 3.1e, f). 67 3.3.2 DDIT4L overexpression “on-demand” using a lentivirus inducible system To study the role of DDIT4L in myeloid cells, we aimed to generate a suitable cell line model. Endogenous expression of DDIT4L is generally low in U937 cells (data not shown and 151). However, in our experiments, we consistently detected background staining using a DDIT4L-Figure 3.1 Metabolic limiting conditions induce DDIT4L. (a) DDIT4L gene expression in adult, term and preterm monocytes after 5 h LPS stimulation by microarray. (b) Kinetics of DDIT4L gene expression in LPS stimulated full-term monocytes. Data shown as median with interquartile range. n=4-8 per time point. (c) Schematic representation of the DDIT4L promoter region. (d) DDIT4L gene expression in monocytes from adults or full-term neonates stimulated with LPS for 5 h in the presence of 2-deoxy-glucose (2-DG) or cobalt chloride (CoCl2). (e) Gene Set Enrichment Analysis of genes co-expressed with DDIT4L in LPS stimulated preterm monocytes. Normalized Enrichment Scores (NES) shown for KEGG pathways with FDR adjusted q-values < 0.05. (f) Corresponding expression of leading edge genes of the KEGG Ribosome and Oxidative Phosphorylation pathways. P values indicate results of Dunnett’s multiple comparisons test following a 2-way ANOVA. Only significant values comparing LPS stimulated conditions with LPS plus 2-DG or CoCl2 are shown. (* = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001). Data is represented as boxes (25th to 75th percentile) and whiskers (min to max) with solid line indicating the median. 68 specific detection antibody, by flow cytometry but not in Western blot (not shown). To ensure that U937 cells express negligible levels of endogenous DDIT4L, we generated knockout clones by electroporation of a Cas9 - DDIT4L guide RNA containing plasmid followed by single cell sorting (Fig. 3.2a). We constructed two different guide RNAs, selected for their predicted efficiency and specificity, both targeting exon 1 of DDIT4L. Out of 113 screened clones, only one was a complete knockout and five were monoallelic knockouts. Importantly, despite a complete out-of-frame disruption of the DDIT4L gene using this approach, no difference in DDIT4L protein expression was observed by flow cytometry comparing the monoallelic knockout clones to clones with 100 % sequence alignment to the reference genome (Fig. 3.2b). Therefore, this experiment excluded that the background detected using the DDIT4L antibody is specific to the DDIT4L protein itself. In terms of the low knock-out efficiency obtained in these experiments, we speculate that the DDIT4L locus might be tightly packed in chromatin resulting in inactivation of DDIT4L transcription in U937 cells and limiting accessibility for Cas9. To study the effect of DDIT4L overexpression during innate immune activation, we generated a cell line model that can express the DDIT4L gene “on-demand” using lentiviral transduction of the gene driven by a doxycycline-inducible promotor, in monocytic U937 cells (Fig. 3.3a). After selection of successfully transduced cells with puromycin, only a small percentage of cells showed Figure 3.2 U937 cells express negligible levels of DDIT4L. (a) Strategy for generating KO clones using CRISPR with flow cytometry staining of select generated clones depicted in (b) 69 visible induction of DDIT4L protein expression upon doxycycline treatment. To address this problem, DDIT4L-transduced cells were sorted to generate clonal cell lines expressing high DDIT4L levels. DDIT4L expression was strongly induced after three days of doxycycline treatment in DDIT4L-transduced clones, but not in clones transduced with an empty vector (Fig. 3.3b). These clones were used in the subsequent experiments detailed below. 3.3.3 DDIT4L overexpression limits LPS-induced cytokine responses To determine the impact of DDIT4L overexpression on cytokine production, we first differentiated the U937 cells with PMA to achieve a macrophage-like phenotype that is responsive to LPS. After PMA differentiation of cells, we confirmed that all selected DDIT4L-transduced U937 clones, but not empty vector-transduced U937 cells showed upregulation of DDIT4L upon treatment with doxycycline (Fig. 3.3c). As a control we treated cells with rapamycin, a known mTORC1 inhibitor. Rapamycin significantly reduced IL-8 and TNF-α levels, thus confirming that LPS-induced cytokine responses in U937 cells are mTORC1-dependent (Fig. 3.3d). Using this system, we determined the effect of DDIT4L upregulation on LPS-induced cytokine production. DDIT4L overexpression significantly decreased production of IL-8 and showed a trend towards reduced TNF-α production (Fig. 3.3d)1. DDIT4L overexpression also reduced mTOR phosphorylation at Ser2448 (Fig. 3.3e), and reduced mTORC1 activity, as confirmed by reduced phosphorylation of its downstream target S6 but not the translation initiator protein 4E-BP1. Similar, albeit more pronounced, changes were observed with rapamycin treatment in EV and DDIT4L clones. 1 Since the initial submission of this thesis for external examination, the inhibitory effect of DDIT4L on IL-8 and TNF-α production has been confirmed in independently generated clones. 70 Treatment with doxycycline did modestly reduce mTOR and S6 phosphorylation in the EV clones as well. However, the effect was more pronounced in the DDIT4L clones, suggesting a DDIT4L-specific dampening of mTOR activity. Of note, cytokine production was higher in U937 clones transduced with an empty vector lentivirus treated with doxycycline compared to non-Figure 3.3 DDIT4L limits pro-inflammatory cytokine responses. (a) Schematic representation of generation of DDIT4L overexpressing U937 clones. (b) U937 clones were cultured for 72 h in the presence of DMSO (veh), rapamycin (rap) or doxycycline (dox). DDIT4L expression was determined by flow cytometry. (c) U937 clones were differentiated with PMA for 48 h followed by 5 h LPS stimulation. Cells were treated the night before LPS addition with DMSO (veh), rapamycin (rap) or doxycycline (dox). DDIT4L levels quantified by flow cytometry and (d) matched cytokine release measured by ELISA. (e) mTOR and mTORC1 target phosphorylation quantified by flow cytometry. Data is normalized to the LPS treated vehicle control and represented as boxes (25th to 75th percentile) and whiskers (min to max) with solid line indicating the median. p values indicate results from one sample t tests. Unstimulated, DMSO treated samples are included as negative control and shown for visualization purposes but not included in the analyses. (* = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001). 71 doxycycline-treated empty-vector-transduced cells (Fig. 3.3d). This suggests that doxycycline increases cytokine production in itself in U937 cells. As a result, the effect of DDIT4L on cytokine responses may be underestimated when comparing doxycycline-treated versus doxycycline-untreated DDIT4L-transduced cells. As DDIT4L is transcriptionally upregulated in hypoxia, we aimed to assess its properties under low oxygen conditions. Culturing U937 DDIT4L clones in continuous hypoxia (1% O2) or switching them between hypoxia and normoxia increased the levels of overexpressed DDIT4L (Fig. 3.4a). The inhibitory effect of DDIT4L on LPS-induced IL-8 and TNF-α production was increased in hypoxic conditions (Fig. 3.4b). mTOR and S6 phosphorylation was reduced in the Figure 3.4 DDIT4L effects are maintained in hypoxia. U937 clones were differentiated with PMA for 48 h followed by 5 h LPS stimulation. Cells were treated the night before LPS addition with DMSO (veh) or doxycycline (dox). At the time of doxycycline addition, cells were kept in normoxia or transferred to hypoxia (1% O2). At the time of LPS stimulation, cells were either kept in normoxia (N-N), kept in hypoxia (H-H) or transferred from hypoxia to normoxia (H-N). Only LPS stimulated conditions are shown as cytokine production was minimal in unstimulated DMSO conditions. DDIT4L expression (a) was quantified by flow cytometry. IL-8 and TNF-α levels (b) were measured by ELISA. Flow cytometry was used to determine levels of mTOR, S6 and 4E-BP1 phosphorylation (c). P values were calculated using paired t tests except for cytokine data where data are represented as percentage of the DMSO LPS condition. One sample t tests were used for these experiments. (* = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001). 72 hypoxia-normoxia condition but not in continuous hypoxia (Fig. 3.4c), perhaps owing to the fact that hypoxia itself limited mTOR activity (data not shown). 3.3.4 DDIT4L protein levels are rapidly degraded in normoxia and hypoxia When U937 cells were experimented in hypoxia, we also noticed that inducible DDIT4L levels were significantly augmented in reduced oxygen concentration in the cell clones overexpressing DDIT4L. When returning the cells to normoxia after overnight hypoxic culture, DDIT4L protein levels remained elevated for at least five hours (Fig. 3.5a). To address the possibility that DDIT4L expression was post-transcriptionally regulated during hypoxia, DDIT4L expression was studied, Figure 3.5 DDIT4L is rapidly degraded in normoxia and hypoxia U937 clones were treated overnight with DMSO (veh) or doxycycline (dox) in normoxia or hypoxia (1% O2). Following overnight pretreatment, all cells were moved to normoxia. Proteasome inhibitor MG-132 was added for 30 min followed by cycloheximide (CHX) addition. DDIT4L protein expression was quantified by flow cytometry at 0, 30 and 120 min post CHX addition. Results in (a) only represent samples without MG-132 treatment. Normalized DDIT4L levels at 120 min post CHX addition are shown in (b). (c) qPCR for total and endogenous DDIT4L levels after overnight treatment with veh or dox in normoxia or hypoxia. Relationship with corresponding protein expression is shown in (d). 73 in the presence of inhibitors of protein synthesis or protein degradation. Blocking translation initiation (using cycloheximide) or proteasomal degradation (using MG-132) allowed to estimate that the half-life of the DDIT4L protein in this model was relatively short (< 30 min) and required constant translation in order to maintain its level (Fig. 3.5a). Unexpectedly, the rate of degradation was comparable in hypoxic and normoxic conditions, suggesting that hypoxia has negligible effect on DDIT4L protein stability (Fig. 3.5b). Another possibility is that hypoxia increased transcription, rather than translation of the DDIT4L gene. To assess this, I designed qPCR primers that would only amplify the endogenous but not the inducible DDIT4L mRNA by constructing a primer binding to the 5’UTR (the lentivirus only contains the open reading frame). Inducible DDIT4L gene expression was significantly increased when cells were subjected to hypoxia, but not expression of endogenous DDIT4L (Fig. 3.5c). Moreover, total DDIT4L protein expression was strongly correlated with expression of its corresponding gene in either normoxia and hypoxia (Fig. 3.5d). These experiments suggested that the hypoxia-mediated increase in DDIT4L is driven by an increase in gene expression rather than a change in DDIT4L protein synthesis or degradation. As the lentiviral construct only contains the DDIT4L open reading frame and is lacking its endogenous promoter, these data were puzzling to us. At this point, we do not know the precise mechanism for the increased expression of the lentivirus-encoded DDIT4L gene, which will require further experiments. 3.3.5 DDIT4L overexpression limits cell proliferation and protein synthesis Next, we aimed to examine whether DDIT4L limits other mTORC1 dependent functions, such as cellular growth and mRNA translation. First, we showed that DDIT4L overexpression 74 significantly limited cell proliferation and growth, as shown by a reduction in cell number and cell size after 3 days of doxycycline treatment in DDIT4L-transduced but not in empty vector-transduced U937 cell clones (Fig. 3.6a, b). Reassuringly, DDIT4L overexpression had little effect on overall cell viability, suggesting the observed results were not due to DDIT4L-mediated toxicity (Fig. 3.6c). In line with reduced cell proliferation, we observed a moderate increase in the percentage of cells in the G2/M phase with DDIT4L overexpression (Fig. 3.6d). Second, we determined the effect of DDIT4L on protein synthesis. To this end, we opted to treat U937 cell clones for 16 hours with rapamycin or doxycycline to disentangle the effects of DDIT4L on protein synthesis directly or indirectly through limiting cell growth. Following overnight treatment with rapamycin or doxycycline, we pulsed cells for 30 min with L-homopropargylglycine (HPG), a non-radioactively labelled methionine analogue, which could then be quantified by flow cytometry. As a positive control, we treated cells for 30 min with cycloheximide, a protein synthesis initiation inhibitor, prior to HPG addition. As expected, cycloheximide treatment drastically limited HPG incorporation (Fig. 3.6e). Additionally, rapamycin significantly reduced the HPG signal in both empty vector and DDIT4L clones, suggesting reduced protein synthesis rates. DDIT4L overexpression through doxycycline treatment had an effect of similar magnitude to rapamycin. Together, these data suggest that DDIT4L moderately reduces mRNA translation rates and cellular proliferation. 75 Figure 3.6 DDIT4L limits functions of cellular growth and proliferation U937 clones were cultured for 72 h in the presence of DMSO (veh), rapamycin (rap) or doxycycline (dox). (a) Cell count, (b) cell size and (c) viability were determined by flow cytometry. (d) Cell cycle phase proportions were quantified by flow cytometry using propidium iodide staining. (e) U937 clones were treated overnight with veh, rap or dox. Cycloheximide (chx) was added for 30 min the next morning. Subsequently, HPG incorporation during a 30 min pulse was quantified by flow cytometry. (f) Cells were treated overnight with veh, rap, dox. Mitochondrial mass and membrane potential were quantified by flow cytometry. Results are shown normalized to the vehicle control. P values were calculated using paired t tests, except for (e&f) where a one-sided t test was used. Data is represented as boxes (25th to 75th percentile) and whiskers (min to max) with solid line indicating the median. 76 3.3.6 DDIT4L overexpression remodels mitochondrial metabolism Next, we determined the effect of DDIT4L on mitochondrial remodeling. To help answer this question, mitochondrial mass was assessed in U937 cell clones following upregulation of DDIT4L overnight using doxycycline. DDIT4L overexpression significantly reduced mitochondrial volume in a manner comparable to rapamycin (Fig. 3.6f). Determination of mitochondrial activity through TMRE staining proved challenging, as doxycycline treatment significantly reduced the mitochondrial membrane potential in empty vector and DDIT4L clones alike (data not shown), preventing detection of major specific effects of DDIT4L. Looking at normalized values, we observed that rapamycin treatment increased the mitochondrial activity to mass ratio (TMRE/MTG). Doxycycline treated DDIT4L clones showed a similar trend, while the TMRE/MTG ratio was significantly reduced in doxycycline treated EV clones. While further data are needed to more granularly assess the role of DDIT4L in regulating cellular metabolism, our results suggest remodeling of mitochondrial and translation function by DDIT4L, resulting in reduced cellular growth and reduced cell cycle progression. 3.3.7 Preterm monocytes have low mitochondrial capacity Stimulation of either neonatal or adult monocytes with LPS in the presence of CoCl2 or 2-DG significantly reduced their ability to produce IL-6 or IL-8 (Fig. 3.7), highlighting the need for sufficient cellular energy to produce a robust innate immune activation. Considering that PRR stimulation elicits limited inflammatory responses in preterm monocytes, we speculated that mitochondrial plasticity is dampened in fetal myeloid cells due to the limited oxygen supply in utero. Using the microarray dataset described in Chapter 2, we assessed expression of genes in the Hallmark hypoxia and ROS pathways. Unsupervised clustering analysis demonstrated altered 77 expression of hypoxia genes in preterm monocytes compared to full term and adults (Fig. 3.8a). However, the transcriptomic response to LPS stimulation was largely conserved with regards to hypoxia genes. Additionally, preterm monocytes had lower expression of antioxidant genes such as Microsomal Glutathione S-Transferase 1 (MGST1), Peroxiredoxin 4 (PRDX4) and Superoxide Dismutase (SOD1), suggesting that preterm monocytes may be experiencing oxidative stress (Fig. 3.8a). Next, we aimed to functionally examine mitochondrial activity in primary monocytes. At rest, oxidative phosphorylation capacity of cells was comparable between preterm, term and adult monocytes, as shown by comparable oxygen consumption rates (OCR) (Fig. 3.8b). However, mitochondrial volume, as measured by MitoTracker Green staining, was significantly elevated in full term monocytes (Fig. 3.8c), so that oxygen consumption was significantly more efficient in adult than neonatal monocytes when normalized to mitochondrial mass (Fig. 3.8d). Figure 3.7 Cytokine production is reduced in metabolic limiting conditions. (a) Production of IL-6 and (b) IL-8 by the monocytes stimulated for 5 h with LPS. P values indicate results of Dunnett’s multiple comparisons test following a 2-way ANOVA. Only significant values comparing LPS stimulated conditions with LPS plus 2-DG or CoCl2 are shown. (* = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001). Data is represented as boxes (25th to 75th percentile) and whiskers (min to max) with solid line indicating the median. 78 To examine mitochondrial capacity, we blocked complex V of the electron transport chain (ETC), followed by treatment with the ionophore FCCP. This uncoupling led to increased OCR in all age groups as expected, although the spare respiratory capacity was significantly lower in preterm monocytes (Fig. 3.8e, f). Normalization to mitochondrial volume suggested that adult Figure 3.8 Preterm monocytes display reduced mitochondrial capacity. (a) Expression of genes in the Hallmark Hypoxia Geneset in CD14+ monocytes from adult, term and preterm (microarray data). (b) Basal oxygen consumption rate (OCR) in monocytes from adult, term and preterm. (c) Mitochondrial volume assessed by Mitotracker Green (MTG) staining. (d) Basal OCR divided by MTG MFI for individuals in which matched samples were available. (e) Mito Stress Test with (f) quantification of spare respiratory capacity (SRC). (g) SRC divided by MTG MFI for individuals in which matched samples were available. Protein expression of electron transport chain components by Western Blot. Representative blot in (h) with quantified results of five blots in (i). Data was analyzed using unpaired, two-sided t tests. Data is represented as boxes (25th to 75th percentile) and whiskers (min to max) with solid line indicating the median. (* = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001). 79 mitochondria are considerably more efficient than their preterm and term neonatal counterparts (Fig. 3.8g). In full term neonates, an increase in mitochondrial mass may compensate for this reduced efficiency while preterm monocytes have low capacity for oxidative phosphorylation augmentation. To confirm that this was not due to reduced expression of electron transport chain complexes, we quantified ETC components by Western blot (Fig. 3.8h, i). The expression for the selected ETC components was comparable between the three age groups. Together, these results show that preterm monocytes have low capacity for augmented respiration and reveal important developmental changes in mitochondrial functions in myeloid cells during ontogeny. 3.3.8 DDIT4L may limit severity of Bronchopulmonary Dysplasia Our results suggested a direct role of DDIT4L in limiting cellular bioenergetics and inflammatory cytokine responses during development in myeloid cells. Fetal monocytes display a metabolic phenotype consistent with hypoxia and limited mitochondrial activity, promoting DDIT4L expression. Therefore, we reasoned that DDIT4L may be important to prevent overt, potentially organ damaging inflammation in neonates born prematurely. To address this, we analyzed a publicly available transcriptomic dataset of macrophages from lung aspirates in premature newborns during their first weeks of life to examine a potential relationship between DDIT4L expression and BPD development. Interestingly, DDIT4L expression increased within the first two weeks of life, potentially owing to antigen exposure following birth (Fig. 3.9a). Compared to infants that would later develop severe BPD, lung macrophages from infants with no or mild BPD had significantly higher DDIT4L expression. High DDIT4L levels correlated with low gene expression of pro-inflammatory cytokine genes such as IL1B and IL6 while anti-inflammatory cytokines such as CCL18 (mediates chemotactic attraction of Tregs) were positively correlated 80 (Fig. 3.9b). This data suggests that DDIT4L may limit overt inflammation in the neonatal lung, potentially ameliorating BPD severity. 3.4 Discussion In this Chapter, we provide evidence that DDIT4L limits mTOR-dependent monocyte function during fetal life. Interestingly, adult monocytes had minimal expression of DDIT4L, suggesting that this may be a developmentally regulated gene. Using primary neonatal monocytes, we show that LPS activation rapidly induces DDIT4L expression in neonatal monocytes, especially in chemical hypoxia. Using an experimental, genetically modified monocyte cell line model, we demonstrate that DDIT4L limits cytokine responses and mTOR function during innate immune activation as well as more downstream functions like cellular proliferation and mRNA translation. DDIT4L has scarcely been studied but available data suggest that it limits mTORC1 activity akin to its paralogue DDIT4. Our results are in line with a study published by Ip et al. in 2017 that Figure 3.9 DDIT4L may limit severity of Bronchopulmonary Dysplasia (a) DDIT4L gene expression in a publicly available microarray dataset of lung macrophages collected from a cohort of premature neonates. Data is stratified by day of life and severity of BPD developed in these patients. (b) Matched cytokine and chemokine expression on day of life 7. Samples are ordered by magnitude of their DDIT4L expression. Color scale represents Z scores. 81 demonstrated that DDIT4 knockout increases IL-1β production through heightened caspase 1 activity in murine bone-marrow derived macrophages130. As U937 cells only make minimal amounts of IL-1β in response to LPS, we did not assess the impact of DDIT4L overexpression on its production. Future studies in primary cells may be helpful to investigate a potential role of DDIT4L on inflammasome activity, especially since caspase-1 activity is known to be restricted in preterm monocytes80. Although DDIT4L overexpression significantly reduced LPS-induced cytokine responses, the effects observed were very modest, even in hypoxic conditions. While our data suggests DDIT4L may modulate neonatal immune function, it certainly does not constitute the only developmental adaptation. A limitation of our study is the use of a cell line model, which may not entirely reflect the conditions occurring in primary cells. As cancer cells, U937 have a high metabolic rate, potentially limiting sensitivity to mTOR inhibition and are certainly different from metabolic activity in primary monocytes. Despite my best attempts to experimentally manipulate primary neonatal monocytes during my PhD, this approached proved to be impossible in part because of the fact that primary monocytes stop proliferating and differentiate rapidly in culture after <24 h making it extremely difficult to genetically modify those cells. Further studies, ideally using different model systems, are required to fully elucidate the role of DDIT4L in neonatal monocytes. Our data suggest a possible link between DDIT4L expression and clinically relevant limitation of inflammation in the context of BPD severity. This poses the question whether the DDIT4L-mTOR axis may provide a suitable therapeutic target in preterm neonates. Indeed, therapeutic inhibition of mTOR using rapamycin (also known as sirolimus) has significantly improved survival in 82 transplantation by reducing graft rejection279. Additionally, rapamycin and other mTOR inhibitors are currently in clinical trials for a variety of other inflammatory conditions such as systemic lupus erythematosus or viral infections including influenza and COVID-19280. To the best of our knowledge, mTOR inhibition has not been trialed in the neonatal population, for obvious safety reasons. Rather, we suggest that our data supports the rationale for optimizing therapeutic use of more physiologic agents such as probiotics or short-chain fatty acids. These could adequately remodel the metabolic environment in the newborn gut and promote balanced myeloid cell responses. Butyrate, for example, has been shown to limit inflammatory properties of macrophages through mTOR inhibition while maintaining their antimicrobial properties134,281. Probiotics can increase short-chain fatty acid levels in the gut282 and have shown promise in neonatal sepsis44. Whether this may have occurred through remodeling of myeloid cell metabolism and whether similar approaches could be applied in the setting of BPD remains unknown. Undoubtedly, our understanding of the interplay between metabolism and (lung) immunity is still limited, especially in neonates and we are looking forward to exciting new findings in the coming years. Preterm birth is a significant risk factor for developing systemic infections in the neonatal period. Immature immune responses have long been thought to be a contributing factor to this disease susceptibility. Indeed, whole blood from premature neonates who later developed sepsis showed lower cytokine production when stimulated ex vivo with S. epidermis than neonates that did not develop sepsis90. On the other hand, many diseases experienced by preterms in the neonatal period are characterized by excessive inflammation, shaping the idea that conditions such as BPD and necrotizing enterocolitis reflect the inability of the preterm immune system to properly balance inflammatory responses in a way that is safe to their developing organs283. Metabolic 83 reprogramming, perhaps at least partially mediated through DDIT4L expression, may help maintain pro- and anti-inflammatory immune responses in equilibrium in the neonatal period. In conclusion the data presented in this Chapter provide further evidence that major developmental changes in fundamental bioenergetic pathways shape preterm immunity. 84 Chapter 4: Pathogen-specific development of humoral immunity to respiratory viruses in at-risk infants 4.1 Introduction RSV accounts for over 3 million hospitalizations and 50,000 in-hospital deaths in children under five years of age, worldwide every year, with nearly half of these hospitalizations and deaths occurring in infants younger than six months188. Maternal RSV-specific antibodies transferred through the placenta protect neonates at birth and in the early postnatal period191,210,211. These antibodies gradually wane, reaching a nadir by three to six months of age. This leaves infants most vulnerable as endogenous antibody titers are still comparatively low at this time214,284,285. However, by one year of age, most infants have developed their own neutralizing antibodies to RSV likely due to a direct exposure. Indeed, term infants can mount efficient antibody responses upon RSV infection as evidenced by higher antibody titers after recovery compared to the acute phase of infection216,217,220. In infants younger than 4 months of age, this antibody response may be more limited216,217,220, possibly due to hindrance from maternal antibodies221 or due to increased suppressive regulatory B cell responses early in life167. Infants born preterm are at a highest risk of severe acute respiratory tract infection (ARTI)286. This is partially attributed to low levels of maternal antibodies215,287, as placental IgG transfer largely occurs during the third trimester of gestation. Hence, these infants can receive monthly administration of palivizumab (pvz), a monoclonal antibody targeting the RSV F protein, during the winter season, reducing the risk of hospitalization by about 50 - 80 % 205,288. However, there is a lack of data on the natural acquisition of RSV immunity in these infants. In fact, most studies examining RSV antibody responses in the 85 first year of life were conducted in term infants after clinically apparent infections and measured IgGs without distinction of naturally acquired from passive maternal antibody responses. Here, we used a systems serology approach to study a cohort of infants at high-risk for severe ARTI in their first winter season. We found gestational age-dependent levels of maternal RSV-specific IgGs that gradually waned by 6 months of age. Concomitantly, almost all infants developed their own natural immunity against RSV by the end of the winter season, as evidenced by increased RSV-specific IgMs, Fc-receptor binding, antibody-mediated phagocytosis, and neutralization activity, despite lack of apparent clinical disease. Therefore, we conclude that most high-risk infants naturally develop their own antibody immunity against common respiratory viruses by the end of their first winter season despite the lack of overt clinical symptoms. However, the protection afforded by palivizumab appears essential during the highest vulnerability period and until infants can develop their own adaptive immunity. Strategies promoting endogenous antibody production may have important implications towards both pre- and postnatal immunization interventions. 4.2 Materials and Methods 4.2.1 British Columbia RSV Program This study included a subgroup of the 418 and 453 infants at high risk for severe RSV infections who were followed in the British Columbia RSV Immunoprophylaxis clinical program, during the 2018-2019 and 2019-2020 winter seasons, respectively. In BC, the high-risk period for RSV cases extends from early November to the end of March (so-called “RSV” season). The BC RSV Immunoprophylaxis Program follows all infants under 2 years of age who receive palivizumab. 86 Infants receive monthly palivizumab during the RSV season, with the first dose at the beginning of November and the last dose before March 31 at maximal dose intervals of 28 days after the first dose and 35 days after the second and any subsequent doses. The details of the eligibility criteria for the BC RSV Immunoprophylaxis Program can be found in their administrative manual289. 4.2.2 Study design This was a prospective descriptive cohort study. Infants enrolled in the BC RSV Program in the 2018-2019 and 2019-2020 winter seasons who were close to discharge from the hospital after birth were approached for enrollment in this study if they were less than one year old and had not received immunoglobulins. Recruitment proceeded across three sites in the Vancouver Metro Area: BC Children’s Hospital, Surrey Memorial Hospital and Royal Columbia Hospital. Altogether, these hospitals see about 45 % of all infants in the BC RSV Program. The study was approved by the UBC Children’s & Women’s and Fraser Health Research Ethics Boards (H18-01724). Written informed consent was obtained from parent/legal guardian in all cases. The study was conducted in accordance with the declaration of Helsinki. 4.2.3 Blood samples Infants were sampled for peripheral blood at two different time points: shortly prior to discharge home from the birth hospital and before their first palivizumab dose (preseason sample) and after March 31st of the corresponding season (postseason sample). 2 mL blood were collected in sodium heparin anticoagulated Vacutainers (BD Bioscience) and processed within 5 h. Blood samples were centrifuged for 10 min at 500 x g to obtain plasma, followed by centrifugation for 5 min at 500 x g to remove residual cells. To reduce the number of platelets, plasma samples were 87 centrifuged a third time at 1500 x g for 30 min and stored in multiple aliquots at -80 °C until analyses. For flow cytometry, the cellular fraction obtained after the first centrifugation step was combined with 5 mL of 1X FACS Lysing solution (BD Bioscience, #349202) and inverted 10 times. After 10 min incubation at room temperature, samples were stored at -80 °C until analyses. 4.2.4 Clinical outcomes The following clinical data were collected for all infants: month of birth, gestational age, birth weight, sex, eligibility criteria for the BC RSV Program, palivizumab doses (number of doses received, dates), clinical encounters and hospitalizations for ARTI (with dates, final diagnosis and results of any viral testing done). The following data was also collected by questionnaire at the time of the second postseason visit: duration of breastfeeding (start/end dates), number of siblings at home, use of daycare, influenza vaccination history for mother and infant. ARTI-related hospitalizations and medical encounters that did not require hospitalizations were systematically captured by reviewing infants’ health records, BC RSV Program’s monthly clinic encounter data and also by asking parents at the postseason study visit. 4.2.5 Systems serology assays The following antigens were coupled to fluorescently barcoded magnetic microspheres (Luminex Corp, location, USA) by covalent NHS-ester linkages: • RSV antigens (RSV A DS-cav1 pre-fusion F, RSV A post-fusion F, RSV B DS-cav1 pre-fusion F, and RSV B post-fusion F), courtesy of Dr. Barney Graham, National Institutes of Health (NIH). 88 • Influenza hemagglutinin (HA) season-matched antigens (H1 A/Michigan/45/ 2015, H3 A/Singapore/INFIMH/16-0019/2016, HA B/Colorado/06/2017, HA B/Phuket/3073/2013, H1 A/Brisbane/59/2007, H3 A/Wisconsin/67/X-161/2005, HA B/Brisbane/60/2008, HA B/Florida/4/2006) obtained from Immune Technology Corp (location, USA). As some studies have indicated that external antibodies (be they maternal or exogenously administered such as palivizumab) can hamper development of infant humoral responses290, we were interested in quantifying palivizumab-independent antibody titers over the course of the winter season. To that end, we blocked pvz detection in all systems serology assays by incubating infant plasma with purified palivizumab Fab prior to analysis (Fig. 4.1a). Palivizumab Fab was obtained by incubating the commercial antibody drug product (obtained from BC Children’s Hospital pharmacy and originally purchased from Abbvie, St-Laurent, QC) with an excess of Endoproteinase LysC (New England Biolabs) to cleave at the hinge of IgG1. The resulting Fc was then purified using Protein A/G agarose (ThermoFisher). Fab purity was confirmed by fast protein liquid chromatography. For IgG1 isotyping and FCGR IgG binding assays, microspheres were blocked with palivizumab Fab at a concentration of 125 μg/ml for 30 min prior to incubation with plasma, as pre-determined by running a competitive dilution curve assay (Fig. 4.1b). For antibody-dependent cellular phagocytosis (ADCP) and antibody-dependent neutrophil phagocytosis (ADNP), pre-fusion RSV A and RSV B F antigens, post-fusion RSV A and RSV B F antigens or influenza HAs from H1 A/Michigan/45/2015, H3 A/Singapore/INFIMH/16-0019/2016, HA B/Colorado/06/2017, HA B/Phuket/3037/2013 were separately pooled at a 1:1 ratio. Pooled antigens were biotinylated and adsorbed onto fluorescent NeutrAvidin microspheres 89 (ThermoFisher). RSV Pre- and Post-fusion antigen beads were blocked by incubation with 100 µg/mL and 50 µg/mL palivizumab Fab, respectively. Influenza-coupled beads were not blocked with any palivizumab Fab. For Ig subclassing/isotyping and FcR binding assays, RSV and influenza antigen-coated microspheres were incubated with diluted plasma (1:500 for IgG1 and FCGRs, 1:100 for other isotypes) overnight in non-binding 384-well plates (Greiner Bio-One), followed by washing and incubated with isotype-specific PE-conjugated secondary antibodies (Southern Biotech, FCGRS produced by Duke Protein Production Core and conjugated to streptavidin-PE [Prozyme] at a molar ratio of 4:1). After incubation, microspheres were washed again prior to analysis. For antibody-dependent cellular phagocytosis (ADCP), RSV or influenza antigen-coated microspheres were incubated with a 1:200 dilution of plasma. Resulting immune Figure 4.1 Blockage of palivizumab in systems serology assays 90 complexes were incubated after washing, with THP-1 monocytes (ATCC, location, USA) for 16 h. For antibody-dependent neutrophil phagocytosis (ADNP), RSV or influenza antigen-coated microspheres were incubated with a 1:50 dilution of plasma. Resulting immune complexes were incubated after washing, with primary human leukocytes isolated from healthy donors using ammonium-chloride potassium (ACK) lysis. Cells were surface stained for neutrophils with a fluorescent-conjugated CD66b antibody, fixed and analyzed. All cells and microspheres were analyzed on an iQue Screener Plus (Intellicyt). All systems serology assays were performed as independent duplicates. 4.2.6 Palivizumab assay Palivizumab levels in plasma were measured by ELISA, based on a protocol described by Demers-Mathieu et al291. Briefly, 1:200 diluted plasma samples were assayed in duplicates using HCA261 and HCA262P (both BioRad) as capture and detection antibodies, respectively. 4.2.7 Neutralizing anti-RSV antibody assay The day before infection, HEp-2 cells were seeded at 20,000 cells per well in flat bottom 96 well plates in MEM supplemented with non-essential amino acids, 2 mM L-glutamine, 1 mM sodium pyruvate and 1% penicillin/streptomycin and 10 % FBS. On the day of infection, patient plasma was heat-inactivated for 30 min at 56 °C. rgRSV30 (expressing GFP) was quickly thawed and diluted in MEM supplemented as above but without FBS to reach a concentration of 4 x 103 pfu/mL. Equal volumes of 2-fold serially diluted plasma (beginning at 1:4) and rgRSV30 were combined and incubated for 60 min at 37 °C before being added to HEp-2 cells. After exactly 2 h of incubation at 37 °C, plasma/virus mixture was removed from cells and replaced with fresh 91 MEM, supplemented as above including 10 % FBS. 2 days post infection, number of syncytia was counted by fluorescence microscopy. NT95 was calculated as the plasma dilution where <5 syncytia were observed. All samples were assayed in duplicates. Virus back-titration and serially diluted palivizumab were included as controls. 4.2.8 Plasma cytokine measurement Plasma cytokine levels were quantified by MesoScale Discovery electrochemiluminescence assay according to the manufacturer’s protocol. Briefly, 25 µl of plasma were combined with the biotinylated antibody plus the assigned linked and the SULFO-TAG conjugated detection antibody and quantified on a MesoScale instrument. The plasma cytokine values (pg/mL) were interpolated from the standard curve of each specific analyte. 4.2.9 Flow cytometry The cellular fraction of whole blood was stored in FACSLyse as described in 4.2.3. On the day of the assay, aliquots were quickly thawed at 37 °C and washed three times with PBS to remove excess RBCs. Samples were stained with antibody mix (Table 4.1) for 20 min at room temperature in the dark in a V-bottom plate. Unbound antibody was washed out 3 times with PBS and cells were fixed in 2 % PFA/PBS before acquisition on a Fortessa X-20 (BD). After gating on single (FSC-A vs FSC-H) lymphocytes (FSC-A vs SSC-A), compensation was applied. B cells were defined as CD19+ CD3- CD14- CD56- CD235-. Manual gating was applied to identify RSV-specific B cells. While excellent staining was observed for a positive control sample (RSV vaccine trial participant after inoculation with RSV PreF), the low number of memory B cells precluded quantification of RSV-specific cells in the infant samples (data not shown). To identify B cell 92 subsets, unbiased clustering analysis (Phenograph) was used. Up to 5000 cells per sample were included (some samples have less than 5000 B cells, so the entire population was used). The following markers were used for clustering: CD5, CD10, CD21, CD24, CD27, CD38, CX3CR1, IgM, IgD, IgG, IgA (= all markers except CD19, dump, PreF, PostF). Table 4.1 List of flow cytometry antibodies used in Chapter 4 4.2.10 Statistical methods Data analysis was performed in GraphPad Prism version 9 and in R studio using R version 3.6. Semi-quantitative NT95 titers were log2 transformed, systems serology data was log10 transformed prior to statistical analysis. Where indicated in the figure legends, data was Z-score normalized for visualization purposes. For correlation analyses, NT95 data, systems serology data Target Fluorochrome Clone Company Cat # Dilution used CD19 BV650 HIB19 BioLegend 302238 1 in 100 IgM BV785 MHM-88 BioLegend 314544 1 in 100 CD5 BV605 L17F12 BioLegend 364019 1 in 100 CD10 BV510 HI10a BioLegend 312219 1 in 100 PostF BV421 custom-made probe by Dr. Graham’s lab 0.5 in 100 CD27 PE O323 BioLegend 302808 1 in 100 CD21 PE-Dazzle-594 Bu32 BioLegend 354922 1 in 100 CX3CR1 PE-Cy7 2A9-1 BioLegend 341611 1 in 100 IgA FITC IS11-8E10 Miltenyi Biotec 130-113-475 1 in 100 CD3 PerCP-Cy5.5 OKT3 BioLegend 317336 1 in 100 CD14 PerCP-Cy5.5 HCD14 BioLegend 325622 1 in 100 CD56 PerCP-Cy5.5 HCD56 BioLegend 318322 1 in 100 CD235 PerCP-Cy5.5 HIR2 BioLegend 306614 1 in 100 PreF APC custom-made probe by Dr. Graham’s lab 1 in 100 CD24 APC-Cy7 ML5 BioLegend 311132 1 in 100 IgG BUV805 G18-145 BD 742041 3 in 100 IgD BUV395 IA6-2 BD 566243 1 in 100 CD38 BUV661 HIT2 BD 612970 1 in 100 93 and clinical variables were assessed using Spearman correlation. Correction for multiple testing was performed using Benjamini-Hochberg adjustment where indicated. Spearman rho and p values are indicated in the figures. The following R packages were used: “dplyr” and “tidyr” for data organization, “psych” for correltion, “ppccor” for partial correlation, “PCAtools” for PCA, “RColorBrewer”, “pheatmap”, “ggplot2” and “cowplot” for data visualization. Pre- and postseason antibody titers were compared using Wilcoxon tests. Significance of fold changes in Fc receptor binding and antibody mediated phagocytosis was assessed using Wilcoxon signed-rank test with 1 as hypothetical median. P values are indicated in the figures, P<0.05 was considered significant. 4.3 Results 4.3.1 Study population To study the development of humoral immunity against respiratory viruses in at-risk infants, we enrolled infants from the BC RSV prophylaxis program between 2018 and 2020 (Fig. 4.2a). A total of 105 infants were enrolled in the study, but two were excluded from this analysis after consent as they were deemed ineligible, because they were more than one year old at the time of the first blood draw and one was withdrawn prior to the first draw upon parental request, so 102 infants were finally included in the analysis. Most (93%) infants were born preterm (n = 95 infants born <37 weeks), including 59 (58%) who were born below 29 weeks of gestation (Table 4.2). Other risk factors included congenital heart disease and Down syndrome, among others. As most of the infants required intensive medical care in the early postnatal period, the age at discharge from hospital and accordingly the age at the first 94 blood sampling (“preseason” sample) ranged between 1 and 31 weeks of postnatal age (Fig. 4.2b). Of the 102 infants, 79 (77%) completed a 2nd blood sample after March 31st (“postseason”), of which only one had a documented RSV infection. Between the pre- and postseason blood sampling, infants received palivizumab as per standard medical care (median = 3 doses, IQR = 2-4 doses). 4.3.2 Maternal antibodies drive protection in early life To characterize development of RSV-specific humoral immunity, we assessed RSV neutralization capacity pre- and postseason. Neutralizing titers (NT95) were highly variable between infants at both time points: while some had levels comparable to adults, others showed very low neutralization titers (Fig. 4.2c). Preseason RSV neutralization was strongly correlated with increasing gestational age and decreasing postnatal age, while no significant association with sex was detected (Fig. 4.2d, e). This is in line with the assumption that a large proportion of antibodies will be maternally derived early after birth and wane during the postnatal period. Post season, plasma palivizumab levels strongly correlated with NT95 titers, while low postnatal age remained significantly associated with neutralizing capacity even after adjusting for gestational and postnatal age (Fig. 4.2d, f). Palivizumab levels remained protective (>40 µg/ml, see ref 204) for at least 50 days after the last palivizumab dose, in line with pharmacokinetic data (Fig. 4.2f). Total n = 102 N with data Gestational age (wks), mean ± SD 28.8 ± 4.3 102 Birth weight (g), mean ± SD 1341 ± 755 102 % male/female 55/45 102 Breastfeeding, n (%) 73 (92%) 79 Siblings at home, n (%) 41 (53%) 78 Daycare attendance, n (%) 3 (3.8%) 78 Number of palivizumab doses received, median (IQR) 3 (2-4) 102 Received at least one dose of influenza, n (%) 26 (33%) 79 Table 4.2 Clinical characteristics of infants 95 Figure 4.2 High RSV neutralization in early postnatal life and after palivizumab administration (a) Overview of study design and sample collection schedule. (b) Gestational age and postnatal age at time of the first blood draw. (c) Neutralizing capacity against RSV A was measured in infant and adult plasma samples. Neutralizing titers (NT95) pre and post the winter season as well as in adults are shown (n = 102 for preseason, n = 79 for postseason and n = 18 for adults). P values represent results from Kruskal-Wallis test with Dunn’s multiple comparisons test. (d) – (f) Infant NT95s were correlated with gestational age (GA), sex, postnatal age (PNA) and palivizumab levels. For significant correlations (p<0.05), partial correlations to adjust for confounding factors was performed. Shown are spearman rho values and the corresponding relationships are visualized in (e) for preseason and (f) for postseason. 4.3.3 Endogenous anti-RSV antibodies mature functionally in the first year of life Employing systems serology, we measured plasma levels of RSV-specific IgM, IgA and IgG subclasses as well as their Fc receptor binding and phagocytic capacity. To distinguish endogenous antibodies and palivizumab, detection of palivizumab was blocked in all subsequent assays. IgG and IgA levels decreased within the first 4 to 6 months of life with the most significant declines seen in IgG1, IgG2 and IgA2 (Fig. 4.3a). In parallel, RSV-specific IgM levels increased during 96 Figure 4.3 Endogenous anti-RSV antibodies develop with increasing postnatal age (a) Infant plasma antibody levels were measured against the RSV F protein in its pre- and post-fusion conformation by systems serology. Both RSV subtype A and B were assessed. Antibody levels against the F protein are shown by postnatal age. Preseason samples (in red) and postseason samples (in blue) are connected by a line for each infant. Overlaid are loess regression lines (span=0.8) with 95% confidence intervals. Dotted lines represent IVIG (available for IgG1 only) and solid lines represent PBS. (b) Spearman correlation of antibody levels in the infant preseason samples with gestational age (GA) and postnatal age (PNA) are shown. To adjust for the confounding relationship in GA and PNA, partial correlation correcting for each other was performed. Non-significant correlations (p>0.05 after adjustment for multiple comparison by BH) are labelled grey. 97 this period (Fig. 4.3a), likely indicative of active immunization of most infants. An increase in IgM titers during the winter season occurred even in the youngest children, indicating functional humoral responses early after birth. During the later postnatal period, we also observed an increase in IgG2 and to some extent IgG1 titers (Fig. 4.3a), likely a result of class-switching of infant antibodies. In line with the expectation that a large proportion of early life IgG is maternally-derived, we observed an inverse relationship between postnatal age and IgG1/IgG2 titers (Fig. 4.3b). Interestingly, at the preseason timepoint IgA2 titers also negatively correlated with postnatal age, perhaps owing to transfer of IgA through breastfeeding. Gestational age had more limited effects but positively correlated with IgG2 and IgA2 titers (Fig. 4.3b). Besides their neutralizing function, antibodies play a central role in activating host immune cells, for example through binding to their Fc gamma receptors (FcγR)175. As IgG1 is the most potent FcγR activator, we expected to see a decline in FcγR binding with increasing postnatal age, paralleling the IgG1 titers. However, FcγR binding increased over time for most infants and only dropped or remained constant in some of the very young infants (Fig. 4.4a). Similarly, RSV-specific antibody-dependent cellular and neutrophil phagocytosis also increased in nearly all infants by the end of the season, suggesting functional maturation of the antibody repertoire (Fig. 4.4b). Although postnatal age was a main driver of antibody titers and functional responses, certain features exhibited significant changes between pre- and postseason after correcting for postnatal age (Fig. 4.4c). This included FcγR binding, antibody mediated phagocytosis as well as 98 IgG2 titers against the postfusion F protein. Potentially, this could be due to increased RSV antigen exposure during the winter season, mediating functional maturation of α-RSV antibodies. Figure 4.4 Anti-RSV antibody functions mature throughout the first year of life. (a) Fc receptor binding of RSV-specific antibodies plotted by postnatal age in weeks. (b) Antibody-dependent cellular phagocytosis (ADCP; THP-1 cells) and antibody-dependent neutrophil phagocytosis (ADNP) of infant antibodies targeting the RSV F protein in pre- or post-fusion conformation. A mixture of RSV A and RSV B was used for the phagocytosis assays. Preseason samples (in red) and postseason samples (in blue) are connected by a line for each infant. Overlaid are loess regression lines (span=0.8) with 95% confidence intervals. Dotted lines represent IVIG and solid lines represent PBS. (c) Ancova estimating the effect of season after correcting for postnatal age. Heatmap shows F statistic coefficient. Asterisks indicate FDR values after adjustment for multiple testing using BH method. ∗p<0.05, ∗∗p<0.005, ∗∗∗p<0.0005, ∗∗∗∗p<0.0001 99 4.3.4 Postnatal age is the main driver of humoral immunity in early life Unsupervised clustering analysis of the systems serology data indicated a strong relationship with postnatal age (Fig. 4.5a, b). In line with the univariate analyses, gestational age impacted preseason immunity but had no impact post season. Breastfeeding and month of collection also modestly correlated with preseason serology while no significant effect of sex was observed. To expand our observation that gestational age had limited influence on development of humoral immunity beyond the first weeks of life, we phenotyped B cell subsets in a subgroup of infants (those recruited in the 2019-2020 season) using cord blood and adult peripheral blood as comparison. High-parameter flow cytometry coupled with dimensionality reduction revealed distinct clusters for each age group, including separation of pre- and postseason timepoints for the infant cohort (Fig. 4.5c). Populations of immature/transitional B cells (CD38hiCD24hiIgM+IgD+) declined with postnatal age while clusters of class-switched, mature B cells (CD38loCD5-IgM-IgD-) were enriched in older infants and adults (Fig. 4.5d). Next, we performed unsupervised clustering using Phenograph and linked cluster frequencies to clinical variables. Within the infant samples, postnatal age significantly correlated with several clusters, while gestational age proved to be a poor correlate (Fig. 4.5e). Cluster #9 was strongly correlated with postnatal age at both pre- and postseason time point. Cells within this cluster represented class-switched, IgA+ cells and their frequency gradually increased in the first year of life (Fig. 4.5f, g). Overall, this increase in class-100 switched B cells indicates antigen exposure and gradually improved humoral immunity during infancy. 4.3.5 Responses to influenza antigens are weak in at-risk infants As a comparison, we measured influenza-specific antibody responses, quantifying antibody levels and function against hemagglutinin antigens from the four influenza strains included in the 2018-2019 season vaccine, as well as four strains circulating in previous seasons. Like RSV, influenza-specific IgG levels declined between the pre- and postseason samples and an increase in IgM was observed for several of the antigens, albeit to a much lesser extent than for the RSV antigens Figure 4.5 Postnatal development of humoral immunity is largely independent of gestational age. Principal component analysis on (a) preseason and (b) postseason systems serology samples with respective correlation of selected metavariables (∗FDR<0.05, ∗∗FDR<0.01, ∗∗∗ FDR<0.001, ∗∗∗∗ FDR<0.0001 spearman correlation, adjusted for multiple comparison by BH). (c) UMAP visualization of CD19+ B cells from cord blood (n=8), infant pre- and postseason (n=38 and 41, respectively) and adult peripheral blood (n=9). (d) Projection of manually gated transitional B cells (CD38hiCD24hiIgM+IgD+) and class-switched, mature B cells (CD38loCD5-IgM-IgD-). (e) Spearman correlation of B cell cluster frequency with gestational age and postnatal age with adjustment for postnatal and gestational age respectively. Non-significant correlations (FDR< 0.05, adjusted for multiple comparison by BH) were left grey. (f) IgA expression per cluster (g) Cluster #9 frequency for each sample shown by age. Inset shows location of cluster #9 on the UMAP visualization. 101 (Fig. 4.6a). As the influenza vaccine is recommended for infants above 6 months of age, several infants in our cohort had been vaccinated during the study as per standard medical care. For some but not all of the vaccinated infants, IgG titers significantly increased against strains included in the 2018/19 vaccine (Fig. 4.6, top row). These infants also showed increased postseason responses against HA B/Brisbane08 and HA B/Florida (Fig. 4.6, bottom row) which were not included in the Figure 4.6 Responses to influenza antigens are weak in at-risk infants. (a) Infant plasma antibody levels were measured against hemagglutinin antigens from various influenza A and B strains. Log MFI values are shown. Orange color circles indicate preseason samples and blue indicate postseason samples. ∗p<0.05, ∗∗p<0.005 calculated by Wilcoxon test with BH correction for multiple testing. (b) IgG1 responses to influenza antigens plotted by postnatal age. For each infant, pre- and postseason samples are connected by a line. Infants that did receive the 2018/2019 influenza vaccine are marked in red. (c) Z-score normalized postseason plasma cytokine levels are shown for each infant. Postseason IgG1 titers against H1 A/Michigan/45/2015, postnatal age at postseason visit and gestational age at birth are displayed at top. 102 vaccine received, potentially due to cross-reactivity with the HA B/Phuket strain. Vaccine responders and non-responders did not differ in postnatal or gestational age. Interestingly though, vaccine non-responders had a more inflammatory plasma cytokine milieu than responders (Fig. 4.6c), which is in line with the notion that baseline chronic low-grade inflammation may hamper strong vaccine responsiveness292. Altogether, these data indicate that preterm infants can develop strong responses against influenza HA antigens but interindividual differences in vaccine responsiveness exist, warranting further investigation. 4.3.6 Serological responses to RSV develop independently from those to influenza Lastly, we compared the maturation of antibody responses between the two pathogens assessed. At the preseason timepoint, influenza and RSV serological responses strongly correlated (Fig. 4.7a). Interestingly though, at the postseason time point, the correlations were mostly lost, except for a strong association between IgM and IgG3. Together, these results suggest that postnatal antibody development against RSV and influenza initially occurs in parallel, but maturation progresses independently in an antigen-specific manner. In line with this hypothesis, we also observed minimal average increases in antibody-mediated phagocytosis and FcγR binding for influenza compared to several fold enhanced responses for RSV (Fig. 4.7b-d). These results suggest that exposure to RSV occurs independently from an exposure to influenza in these infants, which is consistent with low reported rates of co-infections in clinical studies293,294. 103 4.4 Discussion In this study, we investigated antibody responses that naturally develop against two main respiratory pathogens – RSV and influenza – during the first year of life in at-risk infants. We found that while anti-RSV IgG levels declined in the first two months after birth, IgM titers increased in most infants during the study period, suggesting a waning of maternal antibodies accompanied by a natural immunization in almost all infants despite the lack of overt clinical disease. While we knew that most healthy term infants become exposed in their first year, little data existed previously on infants at highest risk of RSV or influenza related ARTI, which are Figure 4.7 Functional maturation of RSV and influenza responses occurs independently. (a) Serological responses against RSV and influenza antigens were correlated and corrected for multiple testing using the BH method. Shown are the spearman rho values. Non-significant correlations (p>0.05) were left blank. Fold changes in FcGR2A binding (b), antibody-mediated cellular phagocytosis (c) and antibody-mediated neutrophil phagocytosis (d) were calculated from pre- to postseason for all antigens assayed. P values indicate results of Wilcoxon signed-rank tests with 1 as hypothetical median. Only significant p values are shown. 104 presumably less exposed due to increased vigilance from parents. These results indicate that even in this age group, the rate of RSV infection is likely much underestimated. A corollary to this is that RSV must circulate much more than previously suspected and most infected infants are asymptomatic despite being at high-risk of disease. These data have major clinical implications in terms of prevention and protection programs in this population. ARTI continue to be a major health concern in infants under five, especially those born preterm. The first six months of life are the window of greatest vulnerability and no vaccine for RSV nor influenza, two major causes of ARTI, exist for this age group. Understanding if and how these two pathogens can induce immunological responses in early life is useful in designing age-specific therapeutics. Although infants with strong humoral responses had higher gestational age and lower postnatal age, indicating high levels of maternal antibodies, we observed maturation in functional antibody responses such as antibody-dependent phagocytosis during the winter season, independent of age. Interestingly, this was not recapitulated for humoral responses against influenza where little functional maturation or increases in IgM titers were observed. Taken together, these data strongly suggest that even very preterm infants can develop endogenous antibodies against RSV and that these developments are independent from responses against other pathogens such as influenza. Plasma IgA responses towards RSV were generally low and may not accurately reflect mucosal titers, in line with data previously published for healthy term infants223. Interestingly, only one of the infants in our cohort presented with RSV+ ARTI (not part of the samples assessed by systems serology) and none had influenza+ ARTI requiring medical assistance during the study period, suggesting that subclinical exposure may be sufficient for antibody development against respiratory viruses. While the reasons for divergent humoral 105 responses to RSV and influenza are unknown, we speculate that the ubiquitous nature of RSV leads to persistent subclinical exposure whereas strain-specific influenza antigens may be encountered less often. Additionally, while both RSV and influenza are respiratory, enveloped single-stranded negative-sense RNA viruses, the host response qualitatively differs between the two pathogens295. For example, interferon production required to initiate innate and adaptive immunity is mainly mediated by plasmacytoid dendritic cells (pDCs) for influenza, whereas in RSV, alveolar macrophages play a major role295. Indeed, interferon-α production is limited in neonatal PRR-stimulated pDCs296. Whether alveolar macrophages can compensate for this low cytokine production in early life is unknown and warrants further study. While palivizumab is undoubtedly effective and safe, its administration comes with theoretical concerns about unwanted side effects. Sub-neutralizing levels of antibodies can not only increase the risk for infection but also lead to increased disease severity as was evidenced by failed RSV vaccine trials in the 1960s where vaccinated infants experienced more RSV morbidity, resulting in the death of two participants297. This antibody mediated disease enhancement has hampered further vaccine development and while several promising approaches are now undergoing clinical trials, a vaccine is not yet available. Another potential concern with the administration of monoclonal antibodies is the possibility that this may hamper development of endogenous immune responses which would leave infants more susceptible during subsequent seasons. A previous study in mice suggested that this may not be a concern for RSV and that monoclonal antibody treatment may allow for antigen exposure sufficient to induce humoral responses while protecting from clinically manifesting infection298. Other studies have even suggested, that monoclonal antibody therapy can not only protect from infection through virus neutralization but also educate 106 the host immune system and induce long lasting immune responses299. In a mouse model of RSV, a monoclonal antibody targeting the RSV G protein did shift the immune response from Th2 to Th1, which would be beneficial in infants300. However, to the best of our knowledge, this question has not been directly assessed in infants receiving palivizumab. Our results support the conclusion that palivizumab administration does not prevent the development of humoral responses in recipients. Whether palivizumab positively influences T cell immunity or other host responses can unfortunately not be answered with our study design and will require further investigation. From a practical point of view, monthly palivizumab dosing comes with significant disadvantages such as high cost, making it available to only the most at-risk infants in high income countries. Currently, two major lines of research are trying to overcome this limitation: development of a vaccine and development of monoclonal antibodies with increased efficacy and half-life. Our results suggest that a single dose of an anti-RSV monoclonal antibody with extended half-life such as Nirsevimab301 may provide protection beyond its expected pharmacokinetic duration as infant antibody responses develop in parallel. Additionally, our data provide reassurance that an RSV vaccine, once developed, has potential to induce immunogenicity even in very preterm infants. For influenza, a vaccine exists but it is not recommended to be administered in infants younger than six months, leaving this risk group unprotected. Whether infants can mount efficient humoral responses to the influenza vaccine is not well understood although studies suggest that preterms have comparable responses to full-term infants237. In our cohort, some vaccinated infants did display a strong increase in their IgG1 titers from pre- to postseason, suggesting that even preterms can respond to the influenza vaccine. In line with studies in adults showing a negative impact of 107 underlying inflammation on vaccine responsiveness292, infants who showed significant elevation of influenza-specific IgG titers after vaccination tended to have lower levels of plasma pro-inflammatory cytokines. Unfortunately, the small sample size and lack of a proper control group precludes further conclusion of why some infants responded better than others and warrants further studies. This study has limitations. The relative rarity of hospitalization even in this cohort, and sample size precludes any correlation with clinical outcomes. Larger cohorts assessing functional antibody responses in at-risk infants could help define correlates of protection. This may not only allow identification of infants who would benefit most from monoclonal antibody therapy but also guide vaccine design for this patient group. Also, the small proportion of term infants precluded direct comparison of antibody responses with preterm infants. We addressed this limitation by assessing gestational age as a continuous variable. Additionally, this study was not designed for and is hence not powered to directly assess influenza vaccine responses, neither maternal nor infant vaccination. Finally, although we examined cellular responses such as antibody-mediated phagocytosis, we did not investigate other forms of cellular immunity, including T cell immunity that is also important against RSV. We find that antibody levels, neutralizing capacity and ADCP correlate well at the preseason time point, i.e., prior to overt antigen exposure. Interestingly, RSV functional responses increased in most infants during the study period which was not necessarily reflected in antibody titers. The importance of non-neutralizing antibody functions is increasingly being recognized. For example, antibody-mediated NK cell activation was significantly reduced in RSV infected children compared to healthy controls302 and further studies on this topic should be very insightful.108 Chapter 5: Conclusion 5.1 Summary of findings The overarching goal of this thesis was to identify drivers of infection susceptibility of premature neonates by examining their immune system at birth and beyond. The perinatal period is one of the most challenging in a human’s life, by virtue of the major physiological adaptations that need to occur. The immune system is not exempt from challenges during this transition from the postnatal environment that suddenly exposes the newborn to a myriad of microbes – a stark contrast to the comparatively sterile amniotic sac. Additionally, nutrient supply is abruptly shifting from continuous, transplacental transfer of glucose and oxygen to intermittent feeding in the form of breastmilk rich in lipids and proteins. How this change in substrate availability affects the function of the neonatal immune system and the ability of immune cells to respond to pathogens is not well understood. We do know however that carefully balancing appropriate pathogen responses while allowing colonization of commensals is essential to set infants on a trajectory of life-long health. Indeed, disruption of healthy microbiome establishment in the early postnatal period (e.g. through excessive antibiotic use) has been linked to adverse health outcomes such as asthma development303. In preparation for the ex utero environment after birth, the first fetal immune cells appear early in gestation and layered immune development continues throughout pregnancy35,45. Birth before the term of gestation prematurely exposes the developing immune system to microorganisms, at a time where fetal immune cells are still expected to be in a sterile environment. This disruption of the intricate balance between immunotolerance in utero versus the need for immunoreactive responses after birth has been speculated to contribute to the high risk for infection and inflammatory diseases in preterm neonates91,304. Specifically, it has long been recognized that monocytes from preterm cord blood are hypo-responsive to PRR stimulation, 109 producing only minimal levels of pro-inflammatory cytokines59,81,85. Originally interpreted as “deficiency”, the research community is increasingly recognizing the preterm immune system simply as a developmental stage, perfectly adapted to the in utero milieu45,240. Indeed, immune cells do not act in isolation but are significantly impacted by their environment. It is this plasticity that allows myeloid cells to perform organ specific functions such as synaptic pruning by microglia in the brain305,306. Additionally, quick responses to subtle changes in the cytokine milieu allow myeloid cells to initially drive anti-microbial responses while promoting resolution of inflammation during later stages of infection306. It is expected that the need for pro-inflammatory responses is limited in utero and may even be detrimental by leading to rejection of maternal tissues. On the other hand, phagocytic responses (to aid in tissue remodeling), antigen-presentation (to educate T lymphocytes) and secretion of anti-inflammatory cytokines (to promote fetal-maternal tolerance) should be preserved during fetal development. In this thesis, I provided support for the hypothesis that the fetal immune system is not impaired but instead globally reprogrammed to prevent overt inflammation in the in utero environment. Studying cord blood monocytes ex vivo, I showed that cellular metabolism is altered in preterm monocytes as they are less glycolytic than their term and adult counterparts. Such a metabolic profile is reminiscent of an anti-inflammatory macrophage phenotype which rely more heavily on oxidative phosphorylation and fatty acid oxidation307. Accordingly, mitochondrial respiration was comparable between the age groups at baseline. However, the capacity to increase OXPHOS was limited in preterm monocytes perhaps suggesting that these cells are not simply anti-inflammatory but more generally metabolically restricted to prevent overt activation. Such global metabolic limitation has also been observed in monocytes from adult sepsis patients95. As such, one could 110 argue that the metabolic alterations observed in preterm monocytes may be a consequence of in utero pathogen exposure which may have led to premature delivery. Indeed, chorioamnionitis is a major risk factor for preterm birth and the whole blood and monocyte transcriptome of affected neonates is distinguishable from neonates born premature for other reasons94,308,309. However, the studies presented in this thesis were conducted on a large number of preterm samples with a variety of preterm birth etiologies. This would argue that metabolic reprogramming is developmentally regulated and not the result from specific perinatal conditions. In line with this thought, previous studies from our lab have shown that gestational age is a much stronger predictor of PAMP-induced cytokine responses than chorioamnionitis59,85. Still, it would be of interest in the future to compare cord blood responses between iatrogenic and spontaneous preterm deliveries. In Chapter 3 of this thesis, I investigated the role of DDIT4L on innate immune responsiveness. Our lab has extensive experience working with primary human monocytes, which are notoriously difficult to genetically manipulate. However, there are a number of well-characterized monocytic cell lines that can be used to this end. THP-1 and U937 cells are monocyte-like transformed cells that can be differentiated with PMA to enhance their LPS responsiveness, while they adopt a more macrophage-like phenotype. The use of a cell line represented a major advantage as it allowed us to specifically study the direct effect of DDIT4L experimentally using multiple complementary approaches. A major portion of my thesis efforts was spent developing a suitable model to study the role of DDIT4L, deserving a discussion in the following paragraphs about the approach that led me to the final results presented in Chapter 3. 111 Initial attempts to study DDIT4L in THP-1 cells involved plasmid nucleofection. However, high levels of cell death precluded me from studying downstream effects of DDIT4L. The high rates of cell death were likely induced by the nucleofection itself and not by DDIT4L as low viability was observed in empty vector transfected cells as well. However, other groups had suggested that DDIT4L could promote myeloid cell death, so considering this possibility, we switched to lentiviral transduction of THP-1 cells with a vector encoding DDIT4L under the control of a doxycycline inducible promoter. This allowed generation of stable cell lines and even differentiation into macrophages without expression of DDIT4L. After successful construction of the DDIT4L vector and transduction of cells using lentiviruses followed by selection with puromycin, DDIT4L inducibility with doxycycline remained low, prompting the need to generate single cell clones. Screening of clones allowed me to produce a range of low, medium and high-expressing cell lines which were used in functional assays. Unfortunately, it turned out that in THP-1 cells, cytokine production is uncoupled from mTOR activity as rapamycin treatment did not impact IL-8 or TNF-α secretion, making it an unsuitable model to study the effects of DDIT4L on cytokine production. With this model, I could however show that DDIT4L overexpression in THP-1 cells limited functions of cellular growth such as proliferation (unpublished work not presented in this thesis). Next, I decided to repeat the lentiviral transduction and single cell cloning approach using U937 cells after confirming that LPS responses in this model are mTOR-dependent, as shown by a dose-dependently reduction in cytokine secretion when exposing LPS-stimulated cells to rapamycin. Using the U937 clones, I could reproduce the finding that DDIT4L overexpression limited cell cycle progression and proliferation, in addition to showing a modest impact on mTOR-dependent 112 cytokine production. This major finding supported my initial hypothesis that DDIT4L plays a role limiting cytokine responses in primary preterm monocytes. However, using a cell line model, especially in the case of single cell clones, comes with limitations. U937 cells are immortalized leukemic cell and do not represent primary monocytes. Particularly, as cancer cells, these cells have high metabolic activity and unlimited growth potential, which is in contrast to the metabolically restricted phenotype of preterm monocytes. A cell line model can also not capture the inter-individual variability seen in humans. In addition, single cell cloning required a (metabolic) phenotype that could survive single cell culture, perhaps unknowingly selecting for cells with altered mTOR activity. Lastly, doxycycline itself has been shown to affect cellular activity, including mitochondrial metabolism, albeit at concentrations higher than used in this thesis310. To mitigate the limitations, I ensured that experiments were performed on multiple single cell clones per experiment and compared DDIT4L transduced cells to empty vector controls generated in the same manner. In a second approach, I aimed to reproduce findings in primary human monocytes. To this end, we designed a strategy to knockdown DDIT4L in primary neonatal monocytes using siRNA. We were able to obtain good uptake of the siRNA by term monocytes (> 99 % using a fluorescently labeled siRNA) and reduced expression of DDIT4L after 24 h LPS stimulation if the siRNA was added immediately after monocyte purification together with the LPS. However, a major limitation of this approach was that primary neonatal monocytes rapidly differentiate in culture after less than 12 hours, resulting in the loss of DDIT4L inducibility. Unfortunately, due to the need to immediately knockdown DDIT4L, investigating the effect of DDIT4L directly in primary human cells turned out not to be feasible. Indeed, adding the siRNA 113 and LPS simultaneously did not sufficiently reduce DDIT4L expression by 5 h, when peak cytokine production occurs. Future approaches to address this limitation could involve simultaneous addition of siRNA and LPS immediately after monocyte isolation but quantification of cytokine production after 24 h, for example using brefeldin treatment and intracellular cytokine detection at that time. In addition, we are currently working on overexpressing DDIT4L in primary adult monocytes using lentiviral transduction. As of now, the transduction efficiency is too low to assess outcomes and this will require further optimization. Another open question is the exact mechanism of action of DDIT4L. Our results are in line with the literature suggesting that DDIT4L limits mTORC1 activity, upstream of TSC1/2. Michel et al. identified a discontinuous motif present in DDIT4 and DDIT4L that was required to mediate mTORC1 inhibition, however, as described in this thesis’s introduction, the direct interaction partners of DDIT4L remain unknown311. DDIT4 possesses an N-terminal extension that is required for its localization to the plasma membrane and its degradation by the ubiquitin ligase HUWE1, but this N-terminal domain is lacking in DDIT4L311,312. Further studies are required to identify binding partner of DDIT4 and DDIT4L which would also help understand their mechanism of action. Our results in Chapter 2 and 3 argue for a role of post-transcriptional regulation via mTORC1 in preterm monocyte responses. mTORC1 is a major signaling hub for a variety of cell growth related pathways and as such finely tuned by metabolic substrate availability. When energy levels are high, active mTORC1 promotes phosphorylation of its downstream targets S6K and 4E-BP1, thereby promoting translation initiation. mRNAs containing 5’TOP motifs are particularly sensitive to mTORC1-dependent protein synthesis regulation. Recently, this specificity has been shown to be mediated by La-related protein 1 (LARP1). In its hypo-phosphorylated state, LARP1 114 binds to the m7Gppp cap and the 5’TOP motif of specific mRNAs, thereby preventing their translation. Following mTORC1 activation, mTOR phosphorylates LARP1, releasing the bound mRNAs which is followed by increased translation313. Currently, no phospho-LARP1 antibody exists but, in the future, it may be useful to examine LARP1 activity in preterm monocytes. In the context of this thesis, it may also be interesting to consider ribosome profiling, a technique where mRNA fragments bound by actively translating ribosomes are subjected to RNA sequencing to identify actively translated mRNAs314. This would perhaps allow us to characterize translation alterations in preterm monocytes more granularly, including assessment of 5’ or 3’ UTR motifs of preferentially translated genes. More recently, a protocol to specifically study mitochondrial translation has been published315, however, the low amount of mitoribosomes together with the low number of preterm monocytes available probably makes this a less useful strategy in the near future. In Chapter 2, we performed polysome profiling to assess translation rates of MALT1 signalosome genes. Surprisingly, the ribosomal occupancy was largely comparable between the age group perhaps owing to limited sensitivity of this assay with low cell numbers. It could also suggest that mRNA translation in preterm monocytes is regulated after initial polysome assembly. For example, it is possible that the cytokine mRNA-ribosome complexes get sequestered in stress granules or p-bodies which would prevent translation elongation. Stress granules are dynamic, cytoplasmic aggregates containing untranslated messenger ribonucleoproteins and stress granule proteins316 and their formation plays an important role in antiviral immunity317. Interestingly, stress granules inhibit the NLRP3 inflammasome318 which mirrors low inflammasome activity in preterm80. Future studies examining stress granule formation may help elucidate a potential role for this form of posttranscriptional regulation in preterm monocytes. 115 In addition to examining monocytes at birth, in Chapter 4 of this thesis, I provide evidence that postnatal lymphocyte development is comparable in preterm and term infants. I confirmed that antibody responses in the early postnatal period were directly related to gestational age, presumably mainly due to the levels of maternal antibodies. Accordingly, antibody levels and functionality were comparable across gestational ages in the later postnatal period and B cell subset composition was not affected by age at birth. Our results are in line with recent studies demonstrating a rapid convergence of preterm and term immune responses within three months after birth243. A limitation of the results presented in Chapter 4 is the focus on high-risk infants. Although several infants born > 37 weeks were included in our cohort, these all presented with comorbidities prompting prophylactic palivizumab administration. Further studies directly comparing infants from different gestational age groups, including healthy, full-term neonates and late preterms not receiving palivizumab would be helpful to corroborate our findings. Our results also provide important insights into the development of humoral immunity against respiratory viruses. We observed increases in IgM titers and Fc binding capacity during the first year of life in the absence of clinical RSV infection. This suggests that RSV circulates much more in preterm infants than clinically detected and that most preterm infants become exposed sub-clinically to RSV by the end of their first winter season. Most infants in my cohort received palivizumab (a monoclonal IgG antibody). A strength of our study is the use of systems serology assays in which blocking of palivizumab detection was achieved by prior incubation with its Fab fragment. In addition to an increase in IgM titers, we furthermore detected increases in IgG3 and IgG2 levels in older infants. This can also not be explained by incomplete palivizumab blocking (palivizumab is an IgG1 antibody) and hence is most likely the result of class-switching in response 116 to repeated antigen exposure. Interestingly, we observed improved binding of RSV-specific antibodies to Fcγ receptors at the postseason time point compared to preseason. This increase remained statistically significant after adjusting for postnatal age, suggesting that it is not merely a developmental change but perhaps related to antigen exposure during the winter season. This seems plausible as repeated interaction with antigens can fine-tune antibody function, for example through glycan modifications which can modulate FcR binding178. Glycan modifications are malleable, change considerably in the first years of life and specific patterns have been associated with respiratory tract infections in children302,319,320. A recent study showed that cord blood is enriched in digalactosylated antibodies enhancing FcRn binding and antibody-mediated NK cell activation179. It would have been interesting to characterize glycan modifications pre- and postseason in our cohort. In contrast to high binding capacity to Fcγ receptors, we observed low levels of binding to FcRn. This may seem surprising, as binding to FcRn is essential for mediating transplacental antibody transfer177. Interaction with FcRn is sensitive to pH, so perhaps we might have observed increasing binding if the assay would have been performed under acidic conditions, more accurately representing the physiological environment321. It would be interesting to investigate whether the increased binding capacity by antibodies is mirrored in age-dependent changes in Fc receptor expression on immune cells. My results deserve a discussion about the limitations of the chosen approach. To what extent antibody responses measured in infants in this cohort are related to the risk of severe, or even clinically apparent infection is unknown, as our cohort size was too small to identify correlates of protection. Moreover, we did not examine maturation of T cells or innate immune cells despite their well-known role in respiratory immunity322. Additional collection of nasal swabs or 117 bronchoalveolar lavages to characterize immunity in the respiratory tract may also have been helpful. Future studies, perhaps employing lung organoids or air-liquid interface cultures, may help to better understand the immune-epithelial cell crosstalk in respiratory viral infection and pinpoint to causes for disease susceptibility in infants. 5.2 Future directions In this thesis, I demonstrated reduced glycolytic activity and mitochondrial capacity in monocytes from preterm cord blood. Due to its central role in immune cell modulation, it is plausible to hypothesize that similar metabolic remodeling may occur in other fetal immune cells such as neutrophils or T cells. Similarly, it is tempting to ask the question: Is dampening of fetal immune reactivity by DDIT4L limited to monocytes? It is plausible that other myeloid cells such as neutrophils may employ similar mechanisms. One group performed transcriptomics on preterm, term and adult neutrophils62 but unfortunately the data was not made publicly available so that a potential role of DDIT4L in neonatal granulocytes remains mere speculation. With regards to lymphocytes, it seems that DDIT4L is barely expressed in naïve CD4 T cells from adults and healthy term neonates (microarray data from our lab, not shown). This could suggest that DDIT4L does not play a role in CD4 lymphocytes or, similarly to our observations in monocytes, DDIT4L levels may increase upon stimulation. Studying metabolic changes in T cells will be important in the future, as a model to understand how it can modulate adaptive responses in early life. Neonatal naïve CD4 T cells are skewed in their differentiation potential in that they preferably develop into Tregs and Th2 cells rather than Th1 and Th17 cells323. Necrotizing enterocolitis has been associated with high levels of intestinal 118 Th17 cells, suggesting that skewed differentiation may be essential to maintain tolerance in utero and allow microbial colonization in the neonatal period30. From mechanistic studies in adult T cells or mice, we know that cellular metabolism affects T helper cell development324. Long-chain fatty acids promote development of Th1 and Th17 cells while short-chain fatty acids (SCFAs) facilitate Treg differentiation and IL-10 production by Th1 cells through activation of mTORC1, collectively improving intestinal homeostasis325. In light of my findings, it is interesting to speculate about a potential role of nutrition in modulating inflammatory conditions through alteration in neonatal immune cells’ responsiveness. A recent study by Petter Brodin’s group provides evidence that fecal water from infants consuming breastmilk supplemented with Bifidobacteria shifted CD4 T cell differentiation towards Th1 rather than Th2 compared to infants consuming unsupplemented breastmilk58. While the authors suggested increasing human milk oligosaccharide breakdown as explanation, more mechanistic studies are needed to understand how breastmilk influence neonatal lymphocytes on a molecular level. Besides assessing human milk oligosaccharides, it would be extremely interesting to study the impact of breastmilk lipid composition on naïve CD4 T cells. Such studies may also open pathways to swift translation into the clinic as dietary supplementation may be more achievable than pharmacological interventions. Indeed, pre- and probiotics (which could increase SCFA levels through promoting bacterial fermentation) have shown promising results in preventing neonatal sepsis44. In addition to studying the effect of breastmilk or neonatal intestinal metabolites on T cells, it may also prove insightful to study the baseline metabolism of neonatal CD4 and CD8 lymphocytes in comparison to their adult counterparts. A recent study using mice showed that neonatal CD8 T cells are more glycolytic than their adult counterpart326 but human neonatal T cell metabolism has scarcely been studied. Following this line of thought, it may also be worthwhile to examine neonatal B cell metabolism. 119 High frequencies of Bregs are observed in cord blood and it may be speculated that the unique metabolic environment the fetus resides in could contribute. For example, low oxygen tension in utero could lead to stabilization of HIF-1α in B cells, which has been shown to promote their IL-10 production327. Besides governing cellular metabolism, mTORC1 is a crucial regulator of autophagy. Under energy-limiting conditions, mTOR phosphorylation is low, promoting autophagy by allowing ULK complex formation. Autophagy mediates recycling of cellular components that are damaged and providing metabolic building blocks when nutrient supply is limited328. In macrophages, inhibition of mitophagy, a specialized form of autophagy involving degradation of mitochondria, has been shown to promote pro-inflammatory responses through mitochondrial ROS production329. Autophagy is essential to prevent starvation in the immediate hours after birth137 but, to the best of my knowledge, autophagy has not been assessed in preterm white blood cells. Our microarray offers little insight as the mRNA levels of most autophagy genes are not statistically significantly different between the age groups although preterm monocytes tend to express higher levels of canonical autophagy genes like Atg7 or Ulk1. Interestingly, one of the genes most significantly affected by the interaction of age and LPS stimulation is VTRNA1-3. Vault RNAs are non-coding RNAs associated with the vault organelle, a cytoplasmic ribonucleoprotein complex of mostly unknown function. While its role remains to be further characterized, it has been associated with increased pro-inflammatory responses and reduced autophagy330. Based on our microarray data, LPS strongly induces VTRNA1-3 in adult and term monocytes while minimal induction is observed in preterm cells. Future studies are required to assess autophagy in preterm monocytes and a potential role for vault RNAs. 120 Preterm neonates of female sex have significantly better outcomes than their male counterparts and the molecular mechanisms are largely unknown331. In the RSV cohort described in Chapter 4, I did not detect any significant impact of sex on humoral immune development. Due to small sample sizes, I was unfortunately unable to assess the impact of sex in the cord blood experiments presented in Chapter 2 and 3. Studies examining sex differences in neonatal immune cells are urgently needed and may provide insight into molecular mechanisms governing neonatal immunity, hopefully improving outcomes for males and females alike. Besides obvious candidates that could explain the sex dimorphism (classical sex hormones such as estrogens or androgens have known immunomodulatory function; many immune genes are X-linked such as Foxp3, the master transcription factor for Tregs)332, leptin is an interesting candidate in the context of this thesis. Leptin is a pleiotropic hormone involved in metabolic control and the leptin receptor is ubiquitously expressed, including on immune cells. In our microarray data, leptin receptor expression is significantly higher in preterm monocytes compared to adults, with term monocytes displaying an intermediate phenotype. Leptin can increase mTOR phosphorylation through activation of PI3K promoting pro-inflammatory responses such as cytokine production by macrophages333. Interestingly, leptin levels are low in cord blood from premature neonates and significantly lower in male than female newborns334. Whether leptin plays a role in modulating neonatal monocyte responses and whether it contributes to the sex differences in neonatal sepsis will require further study. At the time of writing this thesis, we have just experienced a year marked by the COVID-19 pandemic. Extensive social distancing, mask wearing, and reduced international travel introduced 121 during this time have not only curbed the spread of SARS-CoV-2 but led to a dramatic decline in cases of RSV and influenza. Where British Columbia usually reports thousands of cases during the winter season, the 2020-21 season only saw 239 positive cases335. This is unlikely due to underdiagnosis as the number of tests performed has been stable. In fact, the absence of RSV cases was so striking that the BC RSV prophylaxis program decided to pause palivizumab administration for the remainder of the season. While other jurisdictions did not halt palivizumab prophylaxis for fear of RSV resurgence, the relative absence of RSV and influenza cases has truly been a global phenomenon336,337. At first sight, the low number of influenza and RSV infections gives cause for optimism as a presumably significant number of deaths has been averted. It also underlines the importance of hygiene and masks in limiting exposure of at-risk individuals which will hopefully guide future outbreak management. However, several regions now report an extra-seasonal surge in RSV cases337,338, prompting the US CDC to issue a health advisory in June 2021 (ref 339). It is unknown how RSV cases will present over the next year(s) but it is speculated that the lack of exposure during 2020-21 will have left a comparatively large number of infants immunologically naïve and promoted waning of immunity in adults, potentially increasing the incidence and severity of RSV infections for the next winter season335,340. From a scientific point of view, this situation is an ideal setting to delineate the development of respiratory viral immunity and more accurately estimate the role of subclinical antigen exposure. The small size and fragility of neonates has limited the number of studies assessing immune responses in this age group. Especially for preterm neonates, peripheral blood volumes are low, precluding isolation of specific immune cell subsets in numbers sufficient for many molecular biology experiments. Hence, cord blood is often used as an easily accessible model of neonatal 122 immune cells. While responses in cord blood may not be representative of in vivo responses during the neonatal period59,243, cord blood has been an invaluable tool providing insight into human immune development. The advent of small sample volume, high-throughput methods has fueled a resurged interest in human fetal and neonatal immunology. Examples include single cell sequencing to characterize fetal liver hematopoiesis75, CyTOF to assess development of leukocyte subsets in the postnatal period243 or systems serology to characterize cord blood antibody function179. Additionally, advances in organoid cultures and microfluidic culture devices mimicking human organs (“Organ-on-chip”) now allow us to study immune cells in more physiological niches and will potentially facilitate characterization of newborn mucosal immunity. Preterm birth is associated with neurodevelopmental delays, partially attributed to damage caused by excessive inflammation in the neonatal period. To better understand the underlying molecular mechanism, it might be interesting to perform next generation sequencing or proteomics on neonatal cerebrospinal fluid samples (routinely taken in cases of suspected meningitis) as a window into the developing peripheral nervous system. Moreover, it might be interesting to grow brain organoids or iPSC-derived microglia in the presence of newborn serum. This would help to identify soluble molecules which could penetrate the blood-brain-barrier and induce inflammation in the brain. Similar approaches could be employed using gut organoids or air-liquid interface cultures to study NEC and BPD development respectively. Additional technologies with untapped potential include single cell sequencing of cord and peripheral blood from (pre)term neonates which could easily be coupled with BCR or TCR sequencing to characterize repertoire diversity or PathSeq to study host-microbiome interactions in the perinatal period. PathSeq is a comparatively new method in which high throughput 123 sequencing is performed on cell-free, liquid biopsies (most often plasma) to infer microbial presence from non-human nucleic acid reads. While pathogens are not abundant in blood, their presence can increase in sepsis or in disease states where gut microbial translocation is high, such as HIV341,342. It would be very interesting to perform PathSeq on preterm cord blood to assess potential transplacental transfer of pathogens during chorioamnionitis and predict early onset sepsis. Additionally, PathSeq on plasma samples in the postnatal period might indicate events of gut dysbiosis and help identify neonates at risk for NEC. 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Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Lavoie, Pascal M.
Premature birth : implications for early life immunity
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