Arts and Social Sciences, Irving K. Barber Faculty of (Okanagan)
Biochemistry and Molecular Biology, Department of
DSpace
UBCO
Gates, Ellen Joan
Master of Science - MSc
University of British Columbia
Neuroinflammation is a key pathophysiological feature of neurodegenerative disorders including Alzheimer’s disease. Neuroinflammation occurs when microglia, brain immune cells, become chronically activated and excessively secrete inflammatory molecules, such as reactive oxygen and nitrogen species, tumour necrosis factor (TNF)-α, and monocyte chemoattractant protein (MCP)-1. This overactivation of the brain immune system can lead to damage and death of healthy neurons. Identifying the mediators that regulate microglial activation in the central nervous system (CNS) is imperative for the development of new therapies that treat or prevent neuroinflammation. Recent evidence shows that bacteria that inhabit the gut are key players in the communication between the gut and brain and may mediate neuroinflammation. Therefore, the bacterial metabolites D-serine, trimethylamine N-oxide (TMAO), formate, and valerate, as well as the related endogenous signaling molecule Interleukin (IL)-2, were tested for their ability to modulate select microglial functions. To test this hypothesis, the cell-mediated neurotoxicity assay was used to determine the toxic effects of human microglia-like cells towards human SH-SY5Y neuronal cells. Enzyme-linked immunosorbent assays were utilized to determine the secretion levels of TNF-α and MCP-1 by microglia-like cells. The Griess assay and chemiluminescence were used to quantify the secretion of reactive nitrogen and oxygen species, respectively, by microglia-like cells and the phagocytosis assay was utilized to quantify the phagocytic activity of microglia-like cells. It was determined that formate and valerate inhibited secretion of TNF-α and MCP-1 by microglia-like cells and decreased their toxicity towards SH-SY5Y neurons. D-Serine, TMAO, and IL-2 had no effects on these parameters. D-Serine, formate, and IL-2 inhibited the secretion of reactive oxygen species by microglia-like cells, while valerate and TMAO showed no effect. D-Serine, formate and valerate modulated the phagocytic activity of microglia-like cells while TMAO and IL-2 had no effect. None of the tested compounds had any effect on the secretion of reactive nitrogen species by murine microglia. This study demonstrated that four different bacterial metabolites and the related endogenous signaling molecule IL-2 modulated select microglial functions. These data provide insight into the signaling mechanisms between gut bacteria and brain immune cells and may provide alternate therapeutic approaches for targeting neuroinflammation.
i Signaling Between Gut Microbiota and Brain Immune Cells by Ellen Joan Gates B.Sc., The University of Saskatchewan, 2017 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Biochemistry and Molecular Biology) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) October 2020 © Ellen Joan Gates, 2020 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: SIGNALING BETWEEN GUT MICROBIOTA AND BRAIN IMMUNE CELLS submitted by Ellen Gates in partial fulfillment of the requirements of the degree of Master of Science . Dr. Andis Klegeris; Irving K. Barber Faculty of Science Supervisor Dr. Bruce Mathieson; Irving K. Barber Faculty of Science Supervisory Committee Member Dr. Mark Rheault; Irving K. Barber Faculty of Science Supervisory Committee Member Dr. Robert Godin; Irving K. Barber Faculty of Science University Examiner iii Abstract Neuroinflammation is a key pathophysiological feature of neurodegenerative disorders including Alzheimer’s disease. Neuroinflammation occurs when microglia, brain immune cells, become chronically activated and excessively secrete inflammatory molecules, such as reactive oxygen and nitrogen species, tumour necrosis factor (TNF)-α, and monocyte chemoattractant protein (MCP)-1. This overactivation of the brain immune system can lead to damage and death of healthy neurons. Identifying the mediators that regulate microglial activation in the central nervous system (CNS) is imperative for the development of new therapies that treat or prevent neuroinflammation. Recent evidence shows that bacteria that inhabit the gut are key players in the communication between the gut and brain and may mediate neuroinflammation. Therefore, the bacterial metabolites D-serine, trimethylamine N-oxide (TMAO), formate, and valerate, as well as the related endogenous signaling molecule Interleukin (IL)-2, were tested for their ability to modulate select microglial functions. To test this hypothesis, the cell-mediated neurotoxicity assay was used to determine the toxic effects of human microglia-like cells towards human SH-SY5Y neuronal cells. Enzyme-linked immunosorbent assays were utilized to determine the secretion levels of TNF-α and MCP-1 by microglia-like cells. The Griess assay and chemiluminescence were used to quantify the secretion of reactive nitrogen and oxygen species, respectively, by microglia-like cells and the phagocytosis assay was utilized to quantify the phagocytic activity of microglia-like cells. It was determined that formate and valerate inhibited secretion of TNF-α and MCP-1 by microglia-like cells and decreased their toxicity towards SH-SY5Y neurons. iv D-Serine, TMAO, and IL-2 had no effects on these parameters. D-Serine, formate, and IL-2 inhibited the secretion of reactive oxygen species by microglia-like cells, while valerate and TMAO showed no effect. D-Serine, formate and valerate modulated the phagocytic activity of microglia-like cells while TMAO and IL-2 had no effect. None of the tested compounds had any effect on the secretion of reactive nitrogen species by murine microglia. This study demonstrated that four different bacterial metabolites and the related endogenous signaling molecule IL-2 modulated select microglial functions. These data provide insight into the signaling mechanisms between gut bacteria and brain immune cells and may provide alternate therapeutic approaches for targeting neuroinflammation in neurodegenerative disorders. v Lay Summary Neurodegenerative diseases, like Alzheimer’s disease, are one of the leading causes of death worldwide. Current treatments remain ineffective and the discovery of new therapeutic options is imperative. Recent studies show that the bacteria that inhabit the gut are key regulators in the communication between the gut and the brain and may play a pivotal role in the mechanisms that underly neurodegenerative disease. Little is known about how gut bacteria communicate with the brain immune system and my research aims to bridge this gap in knowledge. I tested whether the gut bacterial metabolites D-serine, trimethylamine N-oxide (TMAO), formate, valerate, and the related endogenous molecule interleukin (IL)-2 could modulate the functions of microglia, the resident brain immune cells. I determined that D-serine, formate, valerate and IL-2, but not TMAO, can modulate select functions of microglial-like cells. These molecules should be further studied for their involvement in gut-brain interactions that occur during neurodegenerative diseases. vi Preface I was responsible for the design, experimental work, and data analysis described in this thesis. All experiments were conducted by myself, with the exception of the microglia-mediated neurotoxicity assays and enzyme-linked immunosorbent assays testing the biological activity of formate and valerate, which were performed by Tyler Wenzel. Athena Ranger and Seamus McRae assisted with producing experimental replicates with the cell-mediated neurotoxicity and Griess assays. Seamus also assisted with blinded microscopy image analysis. I either authored or co-authored the following publications during my M.Sc. studies: 1. Leitner G, Wenzel TJ, Marshall N, Gates E, Klegeris A. (2019). Targeting toll-like receptor 4 to modulate neuroinflammation in central nervous system disorders. Expert Opin. Ther. Targets. 23 (10): 865-82. https://doi.org/10.1080/14728222.2019.1676416 2. Wenzel, T. J., Gates, E. J., Ranger, A. L., & Klegeris, A. (2020). Short-chain fatty acids (SCFAs) alone or in combination regulate select immune functions of microglia-like cells. Molecular and Cellular Neuroscience, 105, 103493. https://doi.org/10.1016/j.mcn.2020.103493 vii Table of Contents Abstract ........................................................................................................................... iii Lay Summary .................................................................................................................. v Preface ............................................................................................................................vi Table of Contents ........................................................................................................... vii List of Tables ................................................................................................................... x List of Figures ..................................................................................................................xi List of Abbreviations ...................................................................................................... xiv Acknowledgements ....................................................................................................... xvi Dedication .................................................................................................................... xvii Chapter 1: Introduction .................................................................................................... 1 1.1 Cell types of the central nervous system ............................................................... 1 1.2 Neuroinflammation in neurodegenerative disease ................................................ 3 1.3 Gut microbiota-brain axis in neuroinflammation and neurodegenerative disease . 4 1.4 D-Serine ................................................................................................................ 5 1.5 Trimethylamine N-oxide (TMAO) ........................................................................... 7 1.6 Short-chain fatty acids (SCFAs): formate and valerate ......................................... 9 1.7 Interleukin-2 (IL-2) ............................................................................................... 10 1.8 Modelling brain immune cell activation ................................................................ 12 1.9 Research Overview and Hypothesis ................................................................... 14 Chapter 2: Materials and methods ................................................................................ 16 2.1 Chemicals and reagents ...................................................................................... 16 2.2 Equipment and supplies ...................................................................................... 17 2.3 Cell lines and maintenance ................................................................................. 17 viii 2.4 Microglia-mediated cytotoxicity ............................................................................ 18 2.4.1 Seeding, treating and stimulating human THP-1 microglia-like cells ............ 19 2.4.2 Seeding and treating human SH-SY5Y neurons .......................................... 20 2.4.3 Cell viability assay: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) .............................................................................................................. 21 2.5 NO secretion by microglia ................................................................................... 21 2.5.1 Seeding, treating and stimulating murine BV-2 microglia cells ..................... 22 2.5.2 Griess Assay ................................................................................................ 23 2.6 Secretion of TNF-α and MCP-1 by microglia ....................................................... 24 2.6.1 Enzyme-linked immunosorbent assay (ELISA) ............................................. 25 2.7 ROS secretion by Human HL-60 cells ................................................................. 27 2.7.1 Seeding and treatment of human HL-60 cells .............................................. 27 2.7.2 Respiratory burst assay ................................................................................ 29 2.8 Phagocytosis by microglia ................................................................................... 29 2.8.1 Seeding, treating, and stimulating THP-1 microglia-like cells ....................... 30 2.8.2 Phagocytosis assay ...................................................................................... 31 2.9 Statistical analyses .............................................................................................. 31 Chapter 3: Results......................................................................................................... 32 3.1 Cytotoxicity of immune-stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells ................................................................................................................ 32 3.1.1 D-Serine, TMAO and IL-2 do not affect the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells ......................................................................................... 32 3.1.2 Formate and valerate reduce the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells ................................................................................................. 37 3.2 Secretion of inflammatory mediators by immune-stimulated microglia-like cells . 38 ix 3.2.1 D-Serine, TMAO, valerate and IL-2 do not affect the concentration of nitrite in the supernatant of immune-stimulated BV-2 murine microglia ...................................... 39 3.2.2 Formate may affect the concentration of nitrite in the supernatant of immune-stimulated BV-2 murine microglia .................................................................................. 44 3.2.3 D-Serine, TMAO and IL-2 do not affect the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 cells ......................................................................... 46 3.2.4 Formate and valerate inhibit the secretion of TNF-α and MCP-1 by immune-stimulated THP-1 cells .................................................................................................. 50 3.2.5 TMAO and valerate do not affect ROS secretion by immune-stimulated HL-60 cells ............................................................................................................................... 52 3.2.6 D-Serine, formate and IL-2 inhibit the secretion of ROS by immune-stimulated HL-60 cells ................................................................................................... 54 3.3 Phagocytic activity of immune-stimulated THP-1 microglia-like cells .................. 57 3.3.1 TMAO and IL-2 do not affect the phagocytic activity of THP-1 cells ............. 58 3.3.2 D-Serine, formate and valerate modulate the phagocytic activity of THP-1 cells ............................................................................................................................... 60 Chapter 4: Discussion ................................................................................................... 64 4.1 Microglia-modulating effects of D-serine ............................................................. 64 4.2 Microglia-modulating effects of TMAO ................................................................ 66 4.3 Microglia-modulating effects of formate and valerate .......................................... 68 4.4 Microglia-modulating effects of IL-2 ..................................................................... 71 Chapter 5: Summary and conclusions........................................................................... 73 5.1 Hypotheses addressed ........................................................................................ 73 5.2 Future directions .................................................................................................. 74 5.3 Study limitations .................................................................................................. 75 5.4 Research Significance ......................................................................................... 77 Literature Cited .............................................................................................................. 79 x List of Tables Table 1. Concentrations of D-serine in control and AD patients. ..................................... 6 Table 2. Concentrations of TMAO in CSF and plasma of PD and AD patients, and control subjects. .............................................................................................................. 9 Table 3. Concentrations of IL-2 in CSF, plasma and blood in control subjects, MCI, PD, and AD patients. ............................................................................................................ 12 Table 4. Summary of results ......................................................................................... 73 xi List of Figures Figure 1. The chronic secretion of inflammatory molecules by activated microglia leads to neuron degeneration. .................................................................................................. 4 Figure 2. D-Serine did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells.. ................................................................................ 34 Figure 3. TMAO did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells.. ................................................................................ 35 Figure 4. IL-2 did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells.. ................................................................................ 36 Figure 5. Formate and valerate decreased the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells.. ............................................................................................... 38 Figure 6. D-Serine did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells.. ........................................................................ 40 Figure 7. TMAO did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells.. ........................................................................ 41 Figure 8. Valerate did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells.. ........................................................................ 42 Figure 9. IL-2 did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells.. ......................................................................................... 43 Figure 10. Formate altered the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells.. ......................................................................................... 45 xii Figure 11. D-Serine did not affect the secretion of TNF-α or MCP-1 by lipopolysaccharide (LPS) plus interferon (IFN)-ɣ-stimulated THP-1 microglia-like cells. 47 Figure 12. TMAO did not affect the secretion of TNF-α or MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells.. ........................................................................... 48 Figure 13. IL-2 did not affect the secretion of TNF-α or MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells.. ........................................................................... 49 Figure 14. Formate inhibited the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells.. ........................................................................... 51 Figure 15. Valerate inhibited the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ stimulated THP-1 microglia-like cells.. ........................................................................... 52 Figure 16. TMAO did not affect the secretion of ROS by LPS-primed plus N-formylmethione-leucyl-phenylalanine (FMLP)-stimulated HL-60 microglia-like cells.. ... 53 Figure 17. Valerate did not affect the secretion of ROS by LPS-primed and FMLP-stimulated HL-60 microglia-like cells.. ........................................................................... 54 Figure 18. D-Serine inhibited the secretion of ROS by LPS-primed and FMLP-stimulated HL-60 microglia-like cells. ............................................................................................. 55 Figure 19. Formate inhibited the secretion of ROS by LPS-primed and FMLP-stimulated HL-60 microglia-like cells.. ............................................................................................ 56 Figure 20. IL-2 inhibited the secretion of ROS by LPS-primed and FMLP-stimulated HL-60 microglia-like cells.. .................................................................................................. 57 Figure 21. TMAO did not affect the phagocytic activity of THP-1 microglia-like cells. ... 59 Figure 22. IL-2 did not affect the phagocytic activity of THP-1 microglia-like cells. ....... 60 Figure 23. D-Serine modulated the phagocytic activity of THP-1 microglia-like cells. ... 61 xiii Figure 24. Formate inhibited the phagocytic activity of stimulated THP-1 microglia-like cells. .............................................................................................................................. 62 Figure 25. Valerate inhibited the phagocytic activity of THP-1 microglia-like cells. ....... 63 xiv List of Abbreviations Aβ Amyloid beta protein AD Alzheimer’s disease ANOVA Analysis of variance BBB Blood-brain barrier BSA Bovine serum albumin CBS Calf bovine serum CD Cluster of differentiation CHL Chemiluminescence CSF Cerebrospinal fluid CNS Central nervous system diH2O Deionized H2O DMEM Dulbecco’s modified Eagle medium: F12/Ham DMF Dimethylformamide DMSO Dimethyl sulfoxide EDTA Ethylenediaminetetraacetic acid ELISA Enzyme-linked immunosorbent assay FFARs free-fatty acid receptors FI Fluorescence intensity FMLP N-Formylmethionine-leucyl-phenylalanine FMO3 Flavin-containing monooxygenase F2 DMEM/F12 supplemented with 2% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) F5 DMEM/F12 supplemented with 5% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) F10 DMEM/F12 supplemented with 10% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) GSH Glutathione xv IFN Interferon IL Interleukin LOD Limit of detection LPS Lipopolysaccharide LSD Least significant difference MCI Mild cognitive impairment MCP Monocyte chemoattractant protein MS Multiple sclerosis mTOR Mammalian target of rapamycin MTT 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide NADPH Reduced nicotinamide adenine dinucleotide phosphate NMDA N-Methyl D-aspartate NO Nitric oxide OD Optical density PBS Phosphate-buffered saline PD Parkinson’s disease PI Propidium iodide ROS Reactive oxygen species SCFAs Short-chain fatty acids SDS Sodium dodecyl sulfate SR Scavenger receptor SRR Serine racemase STDEV Standard deviation TLR Toll-like receptor TMAO Trimethylamine N-oxide TMB 3,3′,5,5′-Tetramethylbenzidine TNF Tumor necrosis factor xvi Acknowledgements The completion of my Master of Science degree would not have been possible without the support of my coworkers, friends and family. While it is impossible to list everyone that has helped me through this process, I would like to extend thanks to everyone that has helped me in one way or another, no matter how small of a role you may have played. Firstly, I would like to thank my supervisor Dr. Klegeris for taking a chance on me, mentoring me and encouraging me to be the best scientist that I can be. You have taught me the power of teachable moments, and I will carry this knowledge forward into my scientific career. I would like to thank current and former members of the Laboratory of Cellular and Molecular Pharmacology for training me, helping me with experiments, writing, edits, and offering advice and support. I’d like to especially thank Jessica Lowry and Tyler Wenzel for not only being excellent teachers but friends throughout this process. I would like to thank my committee members Drs. Rheault and Mathieson for challenging me, providing invaluable insight, and guiding me throughout my studies. Thank you to the members of the Barker lab for training me on proper microscopy use and offering your expertise when needed. To my wonderful partner, thank you for listening to me, encouraging me, and helping me transition into the post-grad life. Most importantly, I would like to thank my parents. You have showed unwavering support in multiple ways and without you, this would not have been possible. Words cannot express my sincerest gratitude. Thank you for encouraging me, being patient with me, and believing in me when I did not believe in myself. xvii For my parents 1 Chapter 1: Introduction 1.1 Cell types of the central nervous system The central nervous system (CNS) is a complex network of electrochemical signalling pathways found within the brain and spinal cord. The CNS is responsible for responding to external stimuli, maintaining homeostatic functions of the body and coordinating signals that manage muscle movements, memory, emotion and cognition (Sousa, Meyer, Santpere, Gulden, & Sestan, 2017). The main cellular unit responsible for modulating these physiological functions is the neuron, a specialized excitable cell type that can undergo drastic morphological modifications to facilitate the unique needs of the area in which it resides. Neurons associate with other neighbouring neurons and glia to form complexes that can respond to chemical stimuli, such as neurotransmitters and hormones, and elicit effector organ activity (Millet & Gillette, 2012). Damage to neurons from trauma, stroke or chronic illness can result in the loss of motor function and cognitive impairments (Al-Qazzaz, Ali, Ahmad, Islam, & Mohamad, 2014; Walker & Tesco, 2013). Glia are cells found within the CNS that perform homeostatic functions to support neurons (Jessen, 2004). Oligodendrocytes are glial cells that are closely associated with neurons and their axons. They are responsible for producing the myelin sheath that surrounds and protects axons and assists in electrochemical signal propagation (Saab & Nave, 2017). Damage to oligodendrocytes and the myelin sheath can lead to impaired neuronal signalling, which is often associated with multiple sclerosis (MS) pathology (Fox, 2004). 2 Astrocytes are a type of glial cell that manage the molecular environment of neurons. Astrocytes have important roles in neurotransmitter recycling, regulation of ion balance, and possess phagocytic activity to clear pathogens and cellular debris (Jessen, 2004; Jung & Chung, 2018). Astrocytes assist in the clearance of senescent neuron synapses and dying neurons. This helps to eliminate cell debris and toxins released by damaged neurons; however, over-elimination of synapses may negatively impact neural plasticity and disease recovery (Jung & Chung, 2018; Pekny & Pekna, 2014, 2016; Wakida et al., 2018). Microglia, another type of glial cell and the main immune cells of the brain, have multiple regulatory roles in the CNS. Microglia are phagocytes that aid in synaptic remodelling, initiate immune responses to pathogens, and help clear cellular debris (Hanisch & Kettenmann, 2007). The activation of microglia within the CNS is a normal and healthy process to maintain brain homeostasis; however, if prolonged, it can lead to overactive immune responses and induce a sustained state of inflammation. Chronically activated microglia secrete neurotoxic molecules and inflammatory cytokines (Stephenson, Nutma, van der Valk, & Amor, 2018). Furthermore, dysregulated microglia can develop inappropriate phagocytic responses towards live neurons, leading to neurodegeneration (Brown & Neher, 2014). The dysregulation and overactivation of microglia are hallmarks of neuroinflammation in neurodegenerative disease (Stephenson et al., 2018); therefore, microglia are the main cell type studied throughout this thesis. 3 1.2 Neuroinflammation in neurodegenerative disease Neurodegeneration is the progressive loss of viable neurons, resulting from trauma, stroke, or chronic illness, such as Alzheimer’s diseases (AD), Parkinson’s disease (PD) and MS. Neurodegenerative processes can lead to motor skill and peripheral nerve impairment, dementia and death (Dugger & Dickson, 2017). While the etiologies of neurodegenerative diseases, such as AD, PD and MS, are different, similar pathological processes and symptoms are often present. Chronic neuroinflammation is a hallmark of neurodegenerative diseases and is the process of prolonged immune activation within the CNS (Stephenson et al., 2018). While transient neuroinflammation is required for the clearance of pathogens and cell debris, sustained inflammation in the CNS can lead to the damage and death of neurons (Jung & Chung, 2018). When microglia in the CNS become chronically activated, they acquire a phagocytic phenotype and release inflammatory and cytotoxic molecules, such as tumour necrosis factor (TNF)-α, monocyte chemoattractant protein (MCP)-1, and reactive oxygen and nitrogen species (Fig 1.). These molecules, if secreted at high concentrations, lead to the damage and death of surrounding cells including neurons and glia (Brown & Neher, 2014; Stephenson et al., 2018). 4 Figure 1. The chronic secretion of inflammatory molecules by activated microglia leads to neuron degeneration. 1.3 Gut microbiota-brain axis in neuroinflammation and neurodegenerative disease The gut microbiota-brain axis is a well-accepted and researched concept. This crosstalk between the gut and brain is bidirectional, involving several distinct mechanisms. Gut microbiota play a significant role in gut communication with the brain either by engaging the enteric nervous system or through the passage of bacterial 5 metabolites into the circulatory system to interact with the blood brain barrier (BBB) or brain cells directly (Cryan et al., 2019). Within the past decade, research has shown that gut bacteria may modulate the progression and severity of neurogenerative diseases. AD, PD and MS patients have altered gut microbial communities and studies using animal models have shown that modulating gut microbiota, either through probiotic or antibiotic administration, alters the disease progression and symptoms in these models (Kobayashi et al., 2017; Mowry & Glenn, 2018; Sampson et al., 2016; Sun & Shen, 2018; Vogt et al., 2017). Identifying the signalling molecules involved in the communication between gut microbiota and brain immune cells may offer more direct targets for preventing or ameliorating neurodegenerative diseases, such as AD, PD and MS. My studies focussed on the microglia-modulating abilities of the following gut microbiota-related molecules: D-serine, trimethylamine N-oxide (TMAO), formate, valerate and interleukin (IL)-2. These specific bacteria related molecules have previously been shown to have peripheral immune cell modulating abilities, or their levels have been shown to be altered throughout the progression of neurodegenerative disease. Their role in neuroinflammation, however, has yet to be studied. These molecules will be further discussed below. 1.4 D-Serine D-Serine is a co-agonist at the N-methyl D-aspartate (NMDA) receptor and a bacterial metabolite that mimics the role of glycine at the receptor’s NR1 subunit on neurons (Miller, 2004). D-Serine can also be made de novo in the brain from L-serine through the action of serine racemase in both glial and neuronal cells (Van Horn, Sild, & 6 Ruthazer, 2013). While mice studies using germ-free animals have shown the critical role of the gut microbiota in modulating brain D-serine levels, human studies have not explored whether gut microbiota are the main source of D-serine in the brain (Kawase et al., 2017). Because D-serine has no known role in human metabolism, it is believed to have evolved with gut microbiota to have a modulatory function in the CNS during development and learning. D-Serine is required for synaptic plasticity, as well as memory consolidation, and plays a supportive role for neurons (Schell, 2004). Activation of murine microglial NMDA receptors has been shown to promote an inflammatory state (Wu et al., 2018). Furthermore, the NMDA receptor has been shown to work collaboratively with toll-like receptors (TLRs) on microglia (Cui, Yu, Li, Li, & Liu, 2018). The activation of TLRs on microglia, by compounds such as the bacterial endotoxin lipopolysaccharide (LPS), also promotes inflammatory responses (Wu et al., 2018). Whether increased levels of D-serine play a role in the overactivation of microglia in neurodegenerative disease has yet to be determined. While contradictory evidence on the circulating concentrations of D-serine in AD exists, one study has shown that D-serine is elevated in the brains of AD patients (Table1). It will be important to determine if the increased levels of D-serine in the AD brain contribute to the progression of the disease. Table 1: Concentrations of D-serine in control and AD patients. Location Concentration Health status Reference Hippocampus 17 nmol/g WT Control, post-mortem (Madeira et al., 2015) Hippocampus 35 nmol/g WT AD, post-mortem (Madeira et al., 2015) 7 Parietal cortex 14 nmol/g WT Control, post-mortem (Madeira et al., 2015) Parietal cortex 31 nmol/g WT AD, post-mortem (Madeira et al., 2015) Serum 1.98 µM Control (Hashimoto et al., 2004) Serum 1.77 µM Probable AD (Hashimoto et al., 2004) Serum 0.30 µM Control (Lin et al., 2019) Serum 0.57 µM Probable AD (Lin et al., 2019) AD: Alzheimer’s disease, WT: Wet tissue 1.5 Trimethylamine N-oxide (TMAO) Trimethylamine is an organic compound that can be acquired by humans directly through the diet or through the bacterial metabolism of choline and L-carnitine in the gut. Trimethylamine is converted by the liver flavin-containing monooxygenase 3 (FMO3) to the biologically active molecule TMAO, and then released into the circulatory system (Ufnal, Zadlo, & Ostaszewski, 2015). TMAO is a protein-stabilizing chaperone molecule that supports enzymatic activity through resisting protein degeneration from influences such as changes in pH or osmolyte concentrations (Zou, Bennion, Daggett, & Murphy, 2002). Increased serum and cerebrospinal fluid (CSF) concentrations of this molecule are associated with aging and neurodegenerative diseases, such as AD and PD (Table 2). While FMO3 activity has been detected in the human brain, it has not yet been determined whether TMAO is locally produced or drawn into the CNS through the BBB (Cashman & Zhang, 2006; Del et al., 2017). A recent study showed that TMAO can compromise vascular integrity by inducing endothelial expression of high-mobility 8 group box 1, an inflammatory molecule capable of disrupting cell-to-cell junctions in endothelial tissues. Increased vascular permeability may promote the passage of TMAO, and other molecules, into the CNS (Singh, Zhang, Boini, & Koka, 2019). Another study, using a human microphysiology system model that mimics organ-to-organ molecule transport, showed that TMAO can pass through the BBB; however, the mechanism used by TMAO for its passage was not investigated (Vernetti et al., 2017). The role of TMAO in neurodegenerative pathology remains uncertain as it may have both adverse and protective effects. Studies show that TMAO may promote the aggregation of neurotoxic amyloid beta protein (Aβ); however, TMAO may also promote tau-induced tubulin assembly, resisting filamentous pathology (Smith, Crowther, & Goedert, 2000; Tseng & Graves, 1998). Animal models of aging and AD showed that ingestion of TMAO impaired both memory and cognitive abilities, and promoted hippocampal neuron senescence, most likely through the inhibition of mammalian target of rapamycin (mTOR) signaling. The inhibition of mTOR signaling by TMAO led to the destruction of chemical synapses and reduced synaptic plasticity (Li et al., 2018). TMAO also compromised hippocampal neuron metabolic functions through altering mitochondria and rough endoplasmic reticulum functioning, which was most likely the cause for the observed increase in oxidative stress (Li et al., 2018). Although TMAO has been shown to cause neurodegeneration in animal models, its possible involvement in microglial dysfunction has yet to be studied. 9 Table 2: Concentrations of TMAO in CSF and plasma of PD and AD patients, and control subjects. Location Concentration Health status Reference CSF 76 ng/ml Control (Sankowski et al., 2020) CSF 108 ng/ml PD (Sankowski et al., 2020) Plasma 136 ng/ml Control (Sankowski et al., 2020) Plasma 300 ng/ml PD (Sankowski et al., 2020) CSF 1.3 SIU Control (Vogt et al., 2018) CSF 2.8 SIU Probable AD (Vogt et al., 2018) AD: Alzheimer’s disease, CSF: Cerebrospinal fluid, PD: Parkinson’s disease, SIU: Scaled intensity units 1.6 Short-chain fatty acids (SCFAs): formate and valerate Formate and valerate are short chain fatty acids (SCFAs) produced by bacteria in the large intestine of animals and humans through the fermentation of dietary fiber (Topping & Clifton, 2001). SCFAs, mainly acetate, butyrate, and propionate, have been well researched and are known for their peripheral health benefits through their anti-inflammatory activity (Ji et al., 2016; Nastasi et al., 2015; Tan et al., 2014). SCFAs interact with free fatty acid receptors (FFARs), located on peripheral immune cells and neurons and glia in the brain (Uhlen et al., 2015). SCFAs can use monocarboxylate transporters found on endothelial cells to pass through the BBB into the brain where they can then directly interact with brain cells (Dalile, Van Oudenhove, Vervliet, & Verbeke, 2019). Human and mouse plasma concentrations of the SCFAs formate, 10 valerate, propionate, butyrate and acetate vary from 1-300 µM, and several studies have reported brain levels ranging from 1-20 pmol/g (Bachmann, Colombo, & Berüter, 1979; Cummings, Pomare, Branch, Naylor, & MacFarlane, 1987; Dalile et al., 2019). Alterations in peripheral tissue and brain levels of SCFAs in neurogenerative disease have yet to be studied. Previous research performed in our laboratory (Fig. 5 & 14-15) showed that SCFAs inhibit microglia-mediated neurotoxicity in vitro, most likely through the attenuation of inflammatory molecule secretion. These studies also showed that formate and valerate, either independently or in a cocktail with other SCFAs, modulated microglia-like cell functions in vitro. For these reasons, formate and valerate have been further studied throughout this thesis. 1.7 Interleukin-2 (IL-2) IL-2 is a cytokine that is produced by activated T-cells. IL-2 is best known for its role in the clonal expansion of antigen-activated T-cells. In the periphery, IL-2 production and IL-2 receptor expression are dependent on T-cell activation (Hanisch & Quirion, 1995). It is believed that IL-2 and IL-2 receptor expression in the CNS are also dependent on reactive stimuli. A study that used microglia extracted from healthy, non-inflamed rodent brains showed no IL-2 receptor staining until cells were treated with LPS (Sawada, Suzumura, & Marunouchi, 1995). IL-2 increased the viability of murine microglia following LPS treatment, compared to microglia treated with LPS alone, further confirming that the effects elicited by IL-2 depend on co-stimulation (Sawada, 11 Suzumura, & Marunouchi, 1995). The exact role of IL-2 in neuroinflammation and support of neuronal viability remains relatively unknown. IL-2 was one of the upregulated cytokines in the brains of Crohn’s disease and ulcerative colitis model mice (unpublished data, collaborative study with Dr. Gibson’s lab at UBC Okanagan). The same mice showed no alteration in serum concentrations of IL-2, suggesting that IL-2 was made locally in the brain in response to gut inflammation. Furthermore, when the mice were administered a specific probiotic formulation, consisting of beneficial bacteria, brain IL-2 concentrations returned to normal, suggesting gut bacteria involvement in modulating IL-2 brain levels (unpublished data, collaborative study with Dr. Gibson’s lab at UBC Okanagan). A different study that used AD model mice showed that these animals benefited from an intraperitoneal injection of IL-2, resulting in improved memory and reduced amyloid pathology (Alves et al., 2017). Clinical data show that patients with AD or PD have altered IL-2 circulating levels; however, these levels may be dependent on disease progression. Early stages of the diseases (mild cognitive impairment, MCI) are correlated with high blood levels of IL-2, while more progressed cases of the diseases have normal circulating IL-2 levels (see King et al., 2018, Table 3). Furthermore, a study exploring the brain concentration of IL-2 in patients with advanced AD, showed a two-fold decrease in IL-2 protein concentration, as determined by western blot analysis of post-mortem hippocampal brain samples (Alves et al., 2017). Due to the regulatory role of IL-2 in peripheral immunity and inflammation, research into the possible microglia-modulating effects of IL-2 may identify a mechanism for indirect regulation of neuroinflammation by gut bacteria. 12 Table 3: Concentrations of IL-2 in CSF, plasma and blood in control subjects, MCI, PD, and AD patients. Location Concentration Health status reference CSF 11 pg/ml Control (Blum-Degena et al., 1995) CSF 11 pg/ml PD (Blum-Degena et al., 1995) CSF 11.5 pg/ml AD (Blum-Degena et al., 1995) Plasma 13.5 pg/ml Control (Blum-Degena et al., 1995) Plasma 13.5 pg/ml PD (Blum-Degena et al., 1995) Plasma 14 pg/ml AD (Blum-Degena et al., 1995) Blood 0.38 pg/ml Control (King et al., 2018) Blood 0.34 pg/ml DLB (King et al., 2018) Blood 0.39 pg/ml AD (King et al., 2018) Blood 3.68 pg/ml MCI-LB (King et al., 2018) Blood 3.56 pg/ml MCI-AD (King et al., 2018) AD: Alzheimer’s disease, CSF: cerebrospinal fluid, DLB: Dementia with Lewy bodies, MCI; Mild cognitive impairment, MCI-AD: Mild cognitive impairment with probable Alzheimer’s disease, MCI-LB: mild cognitive impairment with Lewy bodies, PD: Parkinson’s disease 1.8 Modelling brain immune cell activation The studies described throughout this thesis utilized human THP-1 monocytic cells, human HL-60 promyelocytic cells and murine BV-2 cells to model microglia. Human SH-SY5Y neuroblastoma cells were used to model neurons. THP-1 cells are widely recognized for their ability to perform several physiological processes that mimic the actions of microglia, such as an increased phagocytic response and release of 13 neurotoxic molecules in response to immune stimuli (Klegeris, Bissonnette, & McGeer, 2005; Kurynina et al., 2018; Sharif, Bolshakov, Raines, Newham, & Perkins, 2007). For these reasons, THP-1 cells were used to model the toxicity of reactive microglia toward SH-SY5Y cells. Furthermore, THP-1 cells were used in the enzyme-linked immunosorbent assay (ELISA) and phagocytosis assay to measure their secretion of inflammatory molecules and phagocytic activity in response to immune stimuli. HL-60 cells can be differentiated to acquire a macrophage-like phenotype. Unlike THP-1 cells, HL-60 cells, much like microglia, express subunits of the nicotinamide adenine dinucleotide phosphate (NADPH)-dependent oxidase, which is required for the generation of a respiratory burst in response to immune stimuli. When stimulated, HL-60 cells respond with a respiratory burst that leads to the production of reactive oxygen species (ROS) (Levy, Rotrosen, Nagauker, Leto, & Malech, 1990; Thomas, 2017). When secreted in large amounts, ROS become toxic to surrounding neurons and thus, the respiratory burst assay was used to detect the secretion of ROS by immune-stimulated HL-60 cells (Benakis, Garcia-Bonilla, Iadecola, & Anrather, 2014). When induced by immune or chemical stimuli, BV-2 microglia express inducible nitric oxide synthase, which produces nitric oxide (NO) (Henn et al., 2009). NO is an important physiological signaling molecule in both the periphery and CNS (Calabrese et al., 2007; Ignarro, Cirino, Casini, & Napoli, 1999); however, when overproduced in the brain, it can be transformed into neurotoxic reactive nitrogen species (Chen, Chen, Xu, & Shen, 2012). Nitrite, a metabolic product of NO, has been traditionally used as a biomarker of adverse microglial activation as NO is unstable and rapidly biotransforms to nitrite (Bryan & Grisham, 2007; V. A. Vincent, Tilders, & Van Dam, 1998). The Griess 14 assay was used to measure nitrite concentrations in the supernatant of immune-stimulated BV-2 cells. 1.9 Research Overview and Hypothesis Neuroinflammation is a hallmark of neurodegenerative diseases and can be triggered by the dysregulation and overactivation of immune cells in the CNS (Banati, Gehrmann, Schubert, & Kreutzberg, 1993; Wyss-Coray & Rogers, 2012). Microglia, the main immune cells of the brain, become activated and phagocytic when clearing cellular debris and pathogens within sites of injury (Kraft & Harry, 2011; Streit, Walter, & Pennell, 1999). When microglia become dysregulated, they contribute to the onset and progression of neurodegenerative diseases by chronically secreting toxic molecules that can lead to neuron death (Spielman, Little, & Klegeris, 2014). Microglia have been shown to participate in the bidirectional communication that occurs between the gut and healthy brain. Disruptions in the gut-brain axis have been associated with brain inflammation (Cryan et al., 2019). Recent evidence shows that bacteria that inhabit the gut are able to communicate with the brain indirectly through interactions with the enteric nervous system and vagus nerve, or directly through the production of signalling molecules that reach the brain by entering the systemic circulation and crossing BBB (Cryan et al., 2019). It is not well-known which molecules are responsible for the communication between gut bacteria and the brain. My thesis work addressed this knowledge gap by studying effects of several bacteria-related compounds on select functions of microglia in vitro. This work provides insight into the role these compounds 15 play in modulating neuroinflammation and may provide novel therapeutic targets for preventing or ameliorating neurodegeneration. I hypothesized that the gut bacterial metabolites D-serine, TMAO, formate and valerate, and the related endogenous immune factor IL-2 modulate select microglial neuroinflammatory functions. This hypothesis was tested in vitro using human and murine immortalized cell lines as microglial cell models. The three main research objectives of my thesis work were: 1) To determine if D-serine, TMAO, formate, valerate and IL-2 modulate microglia-mediated neurotoxicity, 2) To determine if D-serine, TMAO, formate, valerate and IL-2 modulate the secretion of inflammatory mediators by microglia. i) Determine if D-serine, TMAO, formate, valerate and IL-2 modulate the secretion of NO by microglia. ii) Determine if D-serine, TMAO, formate, valerate and IL-2 modulate the secretion of TNF-α and MCP-1 by microglia. iii) Determine if D-serine, TMAO, formate, valerate and IL-2 modulate the secretion of ROS by microglia. 3) To determine if D-serine, TMAO, formate, valerate or IL-2 modulate the phagocytic activity of microglia 16 Chapter 2: Materials and methods 2.1 Chemicals and reagents The following reagents were supplied by Thermo Fisher Scientific (Ottawa, ON, Canada): Bovine serum albumin (BSA), calf bovine serum (CBS), Dulbecco's modified Eagle medium: nutrient mixture F12/Ham (DMEM/F12), phenol red-free DMEM/F12, antibiotic solution containing penicillin G (10000 U/ml), streptomycin (10 mg/ml) and amphotericin B (25 µg/ml), 0.05% and 0.025% trypsin with ethylenediaminetetraacetic acid (EDTA), dimethylformamide (DMF), sodium dodecyl sulfate (SDS), Tween 20, and one-step slow 3,3′,5,5′-tetramethylbenzidine (TMB)- ELISA substrate solution. Sigma Aldrich (Oakville, ON, Canada) supplied the following reagents: D-serine, dimethyl sulfoxide (DMSO), N-formylmethionine-leucyl-phenylalanine (FMLP), luminol sodium salt, lipopolysaccharide (LPS), Triton® X-100, phosphate-buffered saline (PBS) tablets, propidium iodide (PI) and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). Externally-labelled fluorescein isothiocyanate, one µm unopsonized fluorescent latex beads were purchased from Bangs Laboratories (Fishers, Indiana, USA). Human recombinant interferon (IFN)-ɣ, interleukin (IL)-2 and the ELISA kits for tumour necrosis factor (TNF)-α and monocyte chemoattractant protein (MCP)-1 were purchased from PeproTech (Embrun, ON, Canada). Trimethylamine N-oxide, sodium butyrate and sodium acetate were purchased from Cayman Chemicals (Ann Arbor, Michigan, USA). Sodium formate and sodium propionate were purchased from Alfa Aesar (Ward Hill, Massachusetts, USA). Sodium valerate was purchased from Bide Pharmatech (Yangpu, Shanghai China). Membrite Texas red was purchased from Biotium (Fremont, CA, USA). 17 2.2 Equipment and supplies A class 2, type IIA biological safety cabinet was used for cell culture experiments. Sterile 24-well plastic cell culture plates (Corning, NY, USA) were used for seeding THP-1, SH-SY5Y and HL-60 cells for the microglia-mediated cytotoxicity, MTT, PI and respiratory burst assays. 96-well plates (Corning) were utilized during the MTT and respiratory burst assays, as well as the ELISAs. Sterile four-well glass-bottomed culturing dishes (Greiner Bio-one, Frickenhausen, Germany) were used for the phagocytosis assay. Sterile 10 cm tissue culture plates (ThermoFisher Scientific) were used for HL-60 cell differentiation. All cells were grown in T-75 flasks (Sarstedt, Montreal, QC, Canada) placed in a Steri-Cycle High-Efficiency Particulate Air Class 100 CO2 incubator (Model #370, ThermoFisher Scientific). Cells were counted by a hemocytometer (ChangeBioscience, Castro Valley, CA, USA). Sorvall RT1 and Legend Micro 17 centrifuges (ThermoFisher Scientific) were used to centrifuge cell suspensions. Spectrophotometric, chemiluminescent and fluorescent measurements were performed using the FLUOstar Omega microplate reader (BMG Labtech, Nepean, ON, Canada). 2.3 Cell lines and maintenance Human HL-60 promyelocytic, human THP-1 monocytic and murine BV-2 microglia cells were used as microglia models. Human SH-SY5Y neuroblastoma cells were used to model neuronal cells. The HL-60 and THP-1 cells were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA) and the BV-2 cells 18 were donated by Dr. G. Garden (Department of Neurology, University of Washington, Seattle, WA, USA). The SH-SY5Y cells were donated by Dr. R. Ross (Department of Biological Sciences, Fordham University, Bronx, NY, USA). All cells were stored in 1.2 ml cryovials (ThermoFisher Scientific) in liquid nitrogen. The vials contained DMEM/F12 media, supplemented with 20% CBS and 10 % DMSO, penicillin (100 U/ml), streptomycin (100 µg/ml) and amphotericin B (250 ng/ml). Once thawed, cells were grown in T-75 flasks containing DMEM/F12 with 10% CBS, penicillin (100 U/ml), streptomycin (100 µg/ml) and amphotericin B (250 ng/ml). Flasks were kept, and experimental cell cultures incubated, at 37OC in humidified five % CO2 and 95% air atmosphere, unless otherwise stated. 2.4 Microglia-mediated cytotoxicity To assess the cytotoxicity of microglia towards neurons, the microglia-mediated cytotoxicity assay was utilized. Once activated, microglia secrete an abundance of inflammatory mediators which can be toxic to surrounding neurons. In the microglia-mediated cytotoxicity assay, supernatant from immune-stimulated microglia is transferred onto a monoculture of neurons, which induces their death. Cell viability assays have previously been used to quantify the extent of neuron death that is induced by microglia supernatant (Wenzel et al., 2020). 19 2.4.1 Seeding, treating and stimulating human THP-1 microglia-like cells Human THP-1 microglia-like cells were used to model the cytotoxic effects of stimulated microglia towards neurons. Cells were collected from T-75 flasks, counted using a hemocytometer, and centrifuged at 400 g for seven min at room temperature. Following centrifugation, supernatant was removed, and cells were resuspended in DMEM/F12 supplemented with 5% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) (F5) to a final concentration of 0.5 million cells/ml. THP-1 cell suspensions were seeded into a 24-well sterile plate at one ml per well. Following 30 min incubation, cells were treated by adding 2.5 µl of one of the following in duplicate for a final concentration of: 1) D-Serine: 0 µM (just solvent; PBS) and 0.01-100 μM, 2) TMAO: 0 μM (just solvent; PBS) and 0.01-100 μM, 3) IL-2: 0 ng/ml (just solvent; four mM acetic acid) and 1-100 ng/ml 4) Formate 0 μM [just solvent; deionized water (diH2O)] and 15-500 μM, 5) Valerate 0 μM (just solvent; diH2O) and 15-500 μM Cells were treated with D-serine, TMAO or IL-2 and their respective solvent for either 15 min or 24 h. Cells in one of the duplicate wells were stimulated with 200 ng/ml LPS plus 150 U/ml IFN-ɣ, while cells in the other duplicate wells were left unstimulated. Cells were then incubated for 48 h. Cells were treated with formate or valerate, or their solvent, for 15 min. Cells in one of the duplicate wells were stimulated with 20 ng/ml LPS plus 150 U/ml IFN-ɣ, while cells in the other duplicate wells were left unstimulated. After 48 h incubation, cell-free 20 supernatant was collected for further testing as described in sections 2.4.2 and 2.6.1 and viability of THP-1 cells was quantified by the MTT and PI assays as described in sections 2.4.3 and 2.4.4. 2.4.2 Seeding and treating human SH-SY5Y neurons Human SH-SY5Y neuroblastoma cells were used to model neuron death elicited by the cytotoxic secretions of activated microglia. SH-SY5Y cells were detached from T-75 flasks using 0.05% trypsin-EDTA solution. Once unadhered, cells were resuspended in DMEM/F12 supplemented with 10% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) (F10), counted using a hemocytometer, and centrifuged at 400 g for seven min at room temperature. Supernatant was removed and cells were resuspended to a final concentration of 0.6 million cells/ml. SH-SY5Y cell suspensions were seeded into a 24-well sterile plate at 0.5 ml per well. The plate was placed into an incubator for 24 h to allow cell adherence and repair. Supernatant from SH-SY5Y cells was removed and replaced with 400 µl supernatant from stimulated and unstimulated THP-1 cells treated as described in section 2.4.1. After 72 h incubation, viability of SH-SY5Y cells was determined by the MTT and PI assays, as described in sections 2.4.3 and 2.4.4. 21 2.4.3 Cell viability assay: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) To measure cell viability, the MTT assay was utilized. In this assay, MTT tetrazolium salt is reduced by various mitochondrial enzymes to form insoluble purple formazan crystals. Metabolic activity levels can be used as an indirect measurement for cell viability. An increased production of formazan crystals is an indicator of more active, viable cells which can then be quantified colourimetrically (Ferrari, Fornasiero, & Isetta, 1990; Gerlier & Thomasset, 1986; Liu, Peterson, Kimura, & Schubert, 1997). Cells were treated with MTT at a final concentration of 500 µg/ml for one h. Cells were then lysed with SDS-DMF (20 % SDS, 50 % DMF in H2O) solution in a 1:1 SDS-DMF:supernatant volume ratio and then incubated for three h. 100 µl of thoroughly mixed well contents were transferred from each well of the 24-well plate to a 96-well plate, and optical density (OD) was measured at 570 nm using the FLUOstar omega plate reader. Percent cell viability was calculated according to the following formula: Cell viability = ODsample - ODlysisODlive-ODlysis ×100 Where ODsample = Optical density of cells with respective treatment; ODlysis = Optical density of lysed cells; ODlive = Optical density of unstimulated and untreated cells. 2.5 NO secretion by microglia Nitric oxide (NO) is a cell signaling molecule required for many cell functions, including immune cell activation. NO can be produced both endogenously and exogenously. Nitrate is acquired through the diet and converted to nitrite by non-enzymatic processes, and then converted to NO by symbiotic gut bacteria (Ma, Hu, 22 Feng, & Wang, 2018). NO is also produced locally in the brain by microglia and other brain cell types. While NO secretion by microglia is considered a normal and healthy physiological response, chronic secretion can lead to the creation of reactive nitrogen species (RNS) and cytotoxicity (Ding, Nathan, & Stuehr, 1988; Vincent et al., 1998). Once activated, microglia secrete large amounts of NO, which has been used as a biomarker for adverse microglial activation (Miranda, Espey, & Wink, 2001; Vincent, Tilders, & Van Dam, 1998). NO is an unstable molecule and can be difficult to detect in extracellular space once secreted by microglia. NO is quickly transformed into nitrite, which can then be quantified by the Griess assay and used to estimate NO concentration in supernatant (Miranda et al., 2001). Nitrite in blood has a half life of 110 s; therefore, it can quickly be quantified by the Griess assay (Kelm, 1999). Griess reagents react with nitrite in the cell supernatant to form a pink azo product, which can then be spectrophotometrically measured (Miranda et al., 2001). 2.5.1 Seeding, treating and stimulating murine BV-2 microglia cells BV-2 murine microglia were used as a model to detect NO secretion by activated microglia. BV-2 cells were detached from T-75 flasks using 0.25 % trypsin-EDTA solution. Once unadhered, cells were resuspended in F10, counted using a hemocytometer, and centrifuged at 400 g for seven min at room temperature. Supernatant was removed, and cells were resuspended in F5 to a final concentration of 0.2 million cells/ml. BV-2 cell suspensions were seeded into a 24-well sterile plate at 0.5 ml per well. The plate was placed into an incubator for 24 h to allow cell adherence and 23 repair. Supernatant from the cells was removed and media was replaced with 0.5 ml of fresh F5. Following 30 min incubation, cells were treated by adding 2.5 µl of one of the following in duplicate for a final concentration of: 1) D-Serine: 0 µM (just solvent; PBS) and 0.1-100 μM, 2) TMAO: 0 μM (just solvent; PBS) and 0.1-100 μM, 3) IL-2: 0 ng/ml (just solvent; four mM acetic acid) and 1- 100 ng/ml, 4) Formate 0 μM (just solvent; diH2O) and 15-500 μM, 5) Valerate 0 μM (just solvent; diH2O) and 15-500 μM in diH2O After 15 min or 24 h incubation, cells in one set of the duplicate wells were stimulated with 20 ng/ml LPS, while cells in the other set of duplicate wells were left unstimulated. Cells were then incubated for 24 h. 2.5.2 Griess Assay To conduct the Griess assay, 50 µl of supernatant from each well on the 24-well plate were transferred to a 96-well plate. The remaining volume of the samples in each well of the 24-well plate was used to conduct the cell viability and cell death assays as described in sections 2.4.3 and 2.4.4 respectively. 50 µl of sodium nitrite in F5 (0-50 µM) were also transferred to the 96-well plate to create a concentration gradient. Six wells were additionally filled with 50 µl F5 without sodium nitrite (0 μM) to determine the lower limit of detection (LOD) of the Griess assay. 50 µl of reagent, created by mixing 2% sulfanilamide and 5% phosphoric acid/0.2% N-1-naphthylethylenediamine in H2O at a 1:1 ratio, were added to every well to react with nitrite. The plate was then 24 immediately placed into the FLUOstar Omega plate reader and OD was measured at 550 nm. To calculate the concentration of nitrite in each well, a calibration curve was created using the OD values obtained from the sodium nitrite standard curve (0-50 µM). OD values were plotted, and the linear trend was determined. The concentration of nitrite in each well was determined using the following equation: [nitrite]=OD-bm Where b represents the y-intercept and m the slope of the trend line. To calculate the LOD of the Griess assay, the mean OD (ODmean) of the wells containing 0 μM sodium nitrite in F5 were used in the following equation: LOD= [ODmean+(2×STDEV ODmean)]-bm Where STDEV = standard deviation; b = y-intercept; m = slope 2.6 Secretion of TNF-α and MCP-1 by microglia ELISAs were utilized to quantify the secretion of TNF-α and MCP-1 by immune-simulated microglia-like cells. ELISAs quantify the respective antigens using a double-layered enzyme-linked antibody approach. Hydrolysis of substrate that is added to the bound antigen and enzyme-linked antibody complex results in appearance of coloured product that can be quantified colourimetrically. The rate of substrate hydrolysis by the antibody-bound enzyme is proportional to the amount of antigen present in the sample (Sakamoto et al., 2018). 25 2.6.1 Enzyme-linked immunosorbent assay (ELISA) Human THP-1 microglia-like cells were used to model the secretion of TNF-α and MCP-1 by activated microglia. Cell-free supernatant was collected from THP-1 cells treated as described in section 2.4.1. Supernatant was then tested using ELISA kits from Peprotech and cytokine levels were quantified using the manufacturer’s recommendations. On day one, 96-well plates were coated with 100 µl primary antibody diluted in PBS (1 µg/ml for TNF-α and 0.2 µg/ml for MCP-1) into each well, and then wrapped in parafilm and placed in a 4° C fridge overnight. On day two, individual wells were washed four times with 200 µl PBS-Tween (0.05% Tween-20 in PBS). Plates were inverted and tapped gently to remove excess liquid, and then each well was filled with 200 µl block buffer (1 % BSA in PBS). Plates were then wrapped in parafilm and allowed to sit at room temperature for one h. Individual wells were washed four times with 200 µl PBS-Tween and samples were transferred to their respective wells. Standard curves dissolved in F5 were also added to the plate (0.0625-4 ng/ml for TNF-α and 0.0313-2 ng/ml for MCP-1) in duplicate, including six additional wells containing only F5 (0 ng/ml) to calculate the LOD of the ELISAs. Plates were wrapped in parafilm and placed in a 4° C fridge overnight. On day three, individual wells were washed four times with 200 µl PBS-Tween. Plates were inverted and tapped gently to remove excess liquid, and then wells were filled with 100 µl secondary antibody (0.15 µg/ml for TNF-α and 0.25 µg/ml for MCP-1) in diluent (0.05% Tween-20, 0.1% BSA in PBS). Plates were wrapped in parafilm and 26 left to sit at room temperature for two h. Individual wells were washed four times with 200 µl PBS-Tween, and then filled with 100 µl streptavidin-horseradish peroxidase (0.05 µg/ml) in diluent for 30 min at room temperature. Individual wells were washed four times with 200 µl PBS-Tween. Plates were inverted and tapped gently to remove excess liquid, then 100 µl of TMB liquid substrate was added to each well and left to develop for 20 min. Using the FLUOstar omega microplate reader, OD was determined at 450 nm with wavelength correction set at 620 nm. To calculate the concentration of TNF-α or MCP-1 in each well, a calibration curve was created using the standard curve. OD values were plotted, and the linear trend was determined. The concentration of the respective cytokine in each well was determined using the following equation: [Cytokine]=OD-bm Where b represents the intercept and m the slope of the trend line. To calculate the LOD of the ELISA, the mean OD (ODmean) of the wells containing 0 μM cytokine in F5 were used in the following equation: LOD= [ODmean+(2×STDEV ODmean)]-bm Where STDEV = standard deviation; b = y-intercept; m = slope 27 2.7 ROS secretion by Human HL-60 cells Human HL-60 cells were used as a model to detect the secretion of ROS, including superoxide anion, from activated microglia. HL-60 cells, when differentiated, express NADPH oxidase enzyme subunits, which are required to generate a respiratory burst (Levy et al., 1990). Generation of a respiratory burst is a microglial immune response in which large quantities of ROS are secreted following the assembly of NADPH oxidase enzyme subunits (Wilkinson & Landreth, 2006). In the respiratory burst assay, cells are stimulated using the bacterial peptide FMLP to produce ROS. Secreted ROS reacts with luminol, resulting in photon emittance which is then quantified as chemiluminescence (CHL) (Dahlgren & Karlsson, 1999). 2.7.1 Seeding and treatment of human HL-60 cells HL-60 cells were collected from T-75 flasks, counted using a hemocytometer, and centrifuged at 400 g for seven min at room temperature. Supernatant was removed, and cells were resuspended in F10 to a final concentration of 0.2 million cells/ml. Cell suspensions were then added to 10 cm sterile tissue culture plates. To differentiate HL-60 cells, DMSO was slowly added dropwise to cell culture to reach a final concentration of 1.3% v/v. Following a six-day incubation, cells were counted using a hemocytometer and centrifuged at 400 g for seven min at room temperature. Supernatant was removed and cells were resuspended in F10 to a final concentration of one million cells/ml. Cell suspensions were seeded into a 24-well sterile plate at a volume of one ml per well. 28 Following 30 min incubation, cells were treated by adding five µl one of the following in duplicate for a final concentration of: 1) D-Serine: 0 µM (just solvent; PBS) and 1-100 μM D-serine, 2) TMAO: 0 μM (just solvent; PBS) and 1-100 μM TMAO, 3) IL-2: 0 ng/ml (just solvent; four mM acetic acid) and 1- 100 ng/ml, 4) Formate 0 μM (just solvent; diH2O) and 15-1000 μM, 5) Valerate 0 μM (just solvent; diH2O) and 15-1000 μM Following 15 min incubation, cells in one of the duplicate wells were exposed to 0.5 µg/ml LPS, while cells in the other set of duplicate wells were left untreated for 24 h. The 24 h incubation of differentiated HL-60 cells with LPS will be called “priming” throughout this thesis since it leads to significantly higher response of cells to subsequent stimulation with FMLP compared to unprimed cells. Individual wells were thoroughly mixed and 500 µl of each sample was transferred to a microcentrifuge tube and counted using a hemocytometer. The remaining volume of samples in the 24-well plate was used to conduct the cell viability and cell death assays as described in sections 2.4.3 and 2.4.4, respectively. The 500 µl samples assigned for the respiratory burst assay were centrifuged at 12,000 g for 10 min. Supernatant was removed and cells were resuspended in phenol red-free DMEM/F12 supplemented with 2% CBS, penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (250 ng/ml) (F2 ) to a final concentration of one million cells/ml. 80 µl of samples were then transferred to a 96-well plate and incubated for 30 min prior to the respiratory burst assay. 29 2.7.2 Respiratory burst assay Luminol solution (10 mg/ml luminol sodium salt in PBS) and FMLP solution (20 mM FMLP in PBS) were placed in a 37° C incubator for five min prior to the assay. Luminol and FMLP solutions were then loaded into the first and second injector of the FLUOstar Omega plate reader, respectively. The 96-well plate containing the DMSO-differentiated HL-60 cells, that had also been exposed to various metabolites and stimuli, was placed into the plate reader and CHL was measured at 21 s cycles for a 60-cycle period. 10 µl luminol and five µl FMLP solutions were added during cycle five and 15, respectively. Mars Analysis Software (BMG Labtech) was used to analyze the plotted measurements over time. Data were expressed as CHL intensity using the following equation: CHL = CHLcurve2 - CHLbaseline Where CHLcurve2 represents the area under the second curve elicited by the application of FMLP, and CHLbaseline represents the range between curve one (elicited by the application of luminol), and curve two. 2.8 Phagocytosis by microglia The phagocytosis of unopsonized materials by microglia-like cells was quantified using fluorescent latex beads. Immune cells, including microglia, are capable of engulfing both opsonized and unopsonized materials (Galloway, Phillips, Owen, & Moore, 2019). Phagocytosis of unopsonized latex beads is achieved through the activation of class A scavenger receptors found on immune cells (Sulahian, Imrich, DeLoid, Winkler, & Kobzik, 2008). While increasing the phagocytic activity of microglia 30 may enhance their capacity to clear neurotoxic proteins and cellular debris, inhibition of phagocytosis may attenuate the adverse inflammatory effects that accompany microglial activation (Jung & Chung, 2018). 2.8.1 Seeding, treating, and stimulating THP-1 microglia-like cells THP-1 cells were used to model the phagocytic activity of microglia. Cells were collected from T-75 flasks and counted using a hemocytometer and centrifuged at 400 g for seven min at room temperature. Supernatant was removed, and cells were resuspended in F5 to a final concentration of 0.1 million cells/ml. THP-1 cell suspensions were seeded into a poly-D-lysine coated four-chambered sterile plate at 0.5 ml per well. Following 30 min incubation, cells were treated by adding 2.5 µl of one of the following in duplicate for a final concentration of: 1) D-Serine: 0 µM (just solvent; PBS) and 100 μM D-serine, 2) TMAO: 0 μM (just solvent; PBS) and 100 μM TMAO, 3) IL-2: 0 ng/ml (just solvent; 4 mM acetic acid) and 100 ng/ml, 4) Formate 0 µM (just solvent; diH2O) and 1000 μM, 5) Valerate 0 μM (just solvent; diH2O) and 1000 μM Following 15 min incubation, cells in one of the duplicate wells were stimulated with 200 ng/ml LPS plus 150 U/ml IFN-ɣ, while cells in the other duplicate wells were left unstimulated. Cells were then incubated for 24 h. 31 2.8.2 Phagocytosis assay Fluorescent latex beads were added to wells in a 10:1 bead:cell ratio, and the plate was incubated for one h. 100 µl of 0.4 % trypan blue was added to all wells. Supernatant, trypan blue, and beads were removed from all wells, which were then washed two times with one ml PBS. 400 µl 70% ethanol was added to all wells for five min, and wells were then washed two times with one ml PBS. 300 µl of one µg/ml Texas red membrane stain diluted in pbs was added to all wells for five min, as per manufacturer instructions. Wells were then washed once with one ml PBS then filled with 0.5 ml PBS. Fluorescence intensity of the cells was visualized using a Zeiss AxioObserver.Z1 microscope and imaged using Zen image acquisition software (version 2.0, Carl Zeiss). For each treatment, 30-50 cells were imaged and analyzed blindly. Only viable cells, identified by trypan blue exclusion, were examined. Images were analyzed using ImageJ (NIH) and fluorescence intensity of cells was determined by subtracting background fluorescence from the fluorescence density of the cell. 2.9 Statistical analyses Statistical analyses were conducted using GraphPad Prism software (version 7.0, GraphPad Software Inc., La Jolla, CA, USA). One-way analysis of variance (ANOVA) was conducted on all data, except for the phagocytosis assay, to determine differences across all treatment groups. If the one-way ANOVA showed significance, Fisher’s Least Significant Difference (LSD) post-hoc test was run to determine the significant 32 differences between individual treatment groups. Data are presented as means ± SEM and significance was determined if P < 0.05. Data gathered from the phagocytosis assay were analyzed using the Student’s t test. Analyses of the phagocytosis data were conducted using the raw values obtained from the assay and presented as fold-change against the unstimulated well containing cells treated with solvent only. Chapter 3: Results 3.1 Cytotoxicity of immune-stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells Stimulation of human THP-1 microglia-like cells with LPS plus IFN-ɣ was used to induce the secretion of cytotoxic molecules into their supernatant. Supernatant was then transferred, as described in section 2.4, to cultured SH-SY5Y neuronal cells to induce cell death. We explored whether the addition of D-serine, TMAO, formate, valerate or IL-2 to THP-1 cells before stimulation would modulate their cytotoxic effects towards SH-SY5Y cells. 3.1.1 D-Serine, TMAO and IL-2 do not affect the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells Figures 2-4 show data obtained in an experiment where D-serine (0.01-100 µM), TMAO (0.01-100 µM) or IL-2 (1-100 ng/ml) were added to THP-1 cells 15 min or 24 h before cell stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ. Following a 48 h incubation period, cell-free supernatant was transferred to cultured SH-SY5Y cells. 33 Viability of THP-1 cells was determined using the MTT assay. While LPS plus IFN-ɣ stimulation caused THP-1 cell death, D-serine and TMAO had no further significant effect on THP-1 cell viability (Fig. 2A,B; 3A,B). IL-2 increased the viability of THP-1 cells in a concentration-dependent manner when added 24 h before LPS- plus IFN-ɣ stimulation, but not 15 min before stimulation (Fig. 4A,B). D-Serine, TMAO and IL-2 did not affect the viability of THP-1 cells in the absence of LPS plus IFN-ɣ according to the MTT assay. Following a 72 h incubation period with supernatants from THP-1 cells, viability of SH-SY5Y cells was tested using the MTT assay. D-Serine, TMAO or IL-2, when added 15 min or 24 h before cell stimulation, had no significant effect on the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells (Fig. 2C,D; 3C,D; 4C,D). D-Serine, TMAO and IL-2, when added to unstimulated THP-1 cells, followed by supernatant transfer, did not affect the viability of SH-SY5Y cells (data not shown). Data were normalized to values obtained from untreated and unstimulated cells and presented as the means from three or five independent experiments completed on different cell populations and on different days. 34 05 01 0 01 5 0%THP-1 Cell ViabilityN = 3P = 0 . 2 1F = 3 . 1D - s e r i n e (  M )2 0 0 n g / m L L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +A - 1 5 m i n i n c u b a t i o n05 01 0 01 5 0%SH-SY5Y Cell ViabilityN = 3P = 0 . 3 0F = 1 . 9D - s e r i n e (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +C - 1 5 m i n i n c u b a t i o n05 01 0 01 5 0% SH-SY5Y Cell ViabilityN = 5P = 0 . 2 7F = 1 . 6D - s e r i n e (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +D - 2 4 h i n c u b a t i o n05 01 0 01 5 0% THP-1 Cell ViabilityN = 5P = 0 . 0 9F = 3 . 7D - s e r i n e (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +B - 2 4 h i n c u b a t i o n Figure 2. D-Serine did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells. D-Serine (0.01 – 100 µM) or its solvent (0 µM) were added to THP-1 cells 15 min (A,C), or 24 h (B,D) before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, cell-free supernatant was transferred to SH-SY5Y cells and THP-1 viability was measured by the MTT assay (A,B). Following a 72 h incubation period, viability of SH-SY5Y cells was determined using the MTT assay (C,D). Data (means ± SEM) from three or five independent experiments are presented. The viability of unstimulated THP-1 cells (A,C) and the viability of SH-SY5Y cells exposed to supernatants from unstimulated THP-1 cells (B,D) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 35 02 04 06 08 01 0 0%THP-1 Cell ViabilityN = 3P = 0 . 0 9F = 4 . 7T M A O (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +A - 1 5 m i n i n c u b a t i o n02 04 06 08 01 0 0% SH-SY5Y Cell ViabilityN = 3P = 0 . 1 5F = 5 . 1T M A O (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +C - 1 5 m i n i n c u b a t i o n05 01 0 0% THP-1 Cell ViabilityN = 5P = 0 . 0 9F = 3 . 9T M A O (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +B - 2 4 h i n c u b a t i o n02 04 06 08 01 0 0% SH-SY5Y Cell ViabilityN = 5P = 0 . 5 7F = 0 . 5T M A O (  M )2 0 0 n g / m l L P S1 5 0 U / m l I F N - 0 0 . 0 1 0 . 1 1 1 0 1 0 0+ + + + + ++ + + + + +D - 2 4 h i n c u b a t i o n Figure 3. TMAO did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells. TMAO (0.01 – 100 µM) or its solvent (0 µM) were added to THP-1 cells 15 min (A,C), or 24 h (B,D) before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, cell-free supernatant was transferred to SH-SY5Y cells, and THP-1 viability was measured by the MTT assay (A,B). Following a 72 h incubation period, viability of SH-SY5Y cells was determined using the MTT assay (C,D). Data (means ± SEM) from three or five independent experiments are presented. The viability of unstimulated THP-1 cells (A,C) and the viability of SH-SY5Y cells exposed to supernatants from unstimulated THP-1 cells (B,D) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 36 05 01 0 0% THP-1 Cell ViabilityN = 4P = 0 . 3 0F = 1 . 6I L - 2 ( n g / m l )2 0 0 n g / m l L P S1 5 0 U / m l I F N -  0 1 1 0 1 0 0 + + + + + + + +A - 1 5 m i n i n c u b a t i o n05 01 0 0% SH-SY5Y Cell ViabilityN = 4P = 0 . 3 4F = 1 . 3I L - 2 ( n g / m l )2 0 0 n g / m l L P S1 5 0 U / m l I F N -  0 1 1 0 1 0 0 + + + + + + + +C - 1 5 m i n i n c u b a t i o n05 01 0 0% THP-1 Cell ViabilityN = 5P < 0 . 0 1F = 4 5 . 3I L - 2 ( n g / m l )2 0 0 n g / m l L P S1 5 0 U / m l I F N -  0 1 1 0 1 0 0 + + + + + + + +* ** *B - 2 4 h i n c u b a t i o n05 01 0 0% SH-SY5Y Cell ViabilityN = 5P = 0 . 1 0F = 3 . 5I L - 2 ( n g / m l )2 0 0 n g / m l L P S1 5 0 U / m l I F N -  0 1 1 0 1 0 0 + + + + + + + +D - 2 4 h i n c u b a t i o n Figure 4. IL-2 did not affect the cytotoxicity of stimulated THP-1 microglia-like cells towards SH-SY5Y neuronal cells. IL-2 (1 – 100 ng/ml) or its solvent (0 ng/ml) were added to THP-1 cells (A,C) 15 min, or (B,D) 24 h before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, cell-free supernatant was transferred to SH-SY5Y cells, and THP-1 viability was measured by the MTT assay (A,B). Following a 72 h incubation period, viability of SH-SY5Y cells was determined using the MTT (C,D) assay. Data (means ± SEM) from three or five independent experiments are presented. The viability of unstimulated THP-1 cells (A,C) and the viability of SH-SY5Y cells exposed to supernatants from unstimulated THP-1 cells (B,D) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. ** P<0.01 according to Fisher’s LSD post-hoc test. 37 3.1.2 Formate and valerate reduce the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells Previous studies were conducted to determine if the SCFAs acetate, butyrate, propionate, formate and valerate (alone or in a mixture) could reduce the cytotoxicity of LPS- plus IFN-ɣ - stimulated THP-1 cells towards SH-SY5Y cells (Wenzel et al., 2020). Figure 5 shows data obtained from this study where SCFAs were added to THP-1 cells 15 min before cell stimulation with 20 ng/ml LPS plus 100 U/ml IFN-ɣ. Following a 48 h incubation period, cell-free supernatant was transferred to SH-SY5Y cells. Viability of THP-1 cells was determined using the MTT assay. Stimulation with LPS plus IFN-ɣ caused THP-1 cell death; however, treatment with 15 µM formate or valerate increased their viability compared to cells stimulated in the absence of SCFAs (Fig. 5A). The SCFAs did not affect the viability of THP-1 cells in the absence of LPS plus IFN-ɣ (data not shown). Following a 72 h incubation period with supernatants from stimulated THP-1 cells, viability of SH-SY5Y cells was determined using the MTT assay. The addition of the SCFAs as a cocktail (see Fig. 5 for concentrations used), as well as the addition of 15 µM formate or valerate on their own, significantly reduced the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells (Fig. 5B). The SCFAs, when added to unstimulated THP-1 cells, followed by supernatant transfer, did not affect the viability of SH-SY5Y cells (data not shown). Data were normalized to values obtained from untreated and unstimulated cells and presented as the mean of six independent experiments completed on different cell populations and on different days. 38 02 04 06 08 01 0 0% THP-1 Cell ViabilityN = 6P < 0 .0 1F = 4 .800000++00001 5++01 1 7000++001 1 700++2 3 50000++0001 50++2 3 51 1 71 1 71 51 5++A c e ta te (µ M )B u ty ra te (µ M )P ro p io n a te (µ M )F o rm a te (µ M )V a le ra te (µ M )— — — — — — — — — — — — — — — — — — — — — — —ΙF N -γ (1 0 0 U /m l)L P S (2 0 n g /m l)A* ** *02 04 06 08 01 0 0% SH-SY5Y Cell Viability** ** *N = 6P < 0 .0 5F = 3 .200000++00001 5++01 1 7000++001 1 700++2 3 50000++0001 50++2 3 51 1 71 1 71 51 5++A c e ta te (µ M )B u ty ra te (µ M )P ro p io n a te (µ M )F o rm a te (µ M )V a le ra te (µ M )— — — — — — — — — — — — — — — — — — — — — — —ΙF N -γ (1 0 0 U /m l)L P S (2 0 n g /m l)B Figure 5. Formate and valerate decreased the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells. The SCFAs acetate (235 µM), butyrate (117 µM), propionate (117 µM), formate (15 µM) and valerate (15 µM), or their solvent (0 µM), were added to THP-1 cells together or individually 15 min before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, cell-free supernatant was transferred to SH-SY5Y cells and THP-1 viability measured by the MTT assay (A). Following a 72 h incubation period, viability of SH-SY5Y cells was determined using the MTT assay (B). Data (means ± SEM) from six independent experiments are presented. The viability of unstimulated THP-1 cells (A) and the viability of SH-SY5Y cells exposed to supernatants from unstimulated THP-1 cells (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. *P<0.05; ** P<0.01 according to Fisher’s LSD post-hoc test. 3.2 Secretion of inflammatory mediators by immune-stimulated microglia-like cells Once activated, microglia secrete not only cytotoxins, but also a range of inflammatory mediators, such as NO, TNF-α, MCP-1 and ROS. We used the Griess assay, ELISA and respiratory burst assay to determine whether D-serine, TMAO, formate, valerate or IL-2 modulate the secretory profile of immune-stimulated microglia-like cells. 39 3.2.1 D-Serine, TMAO, valerate and IL-2 do not affect the concentration of nitrite in the supernatant of immune-stimulated BV-2 murine microglia Figures 6-9 show data obtained in an experiment where D-serine (0.01-100 µM), TMAO (0.01-100 µM), valerate (15-500 µM), or IL-2 (1-100 ng/ml) were added to BV-2 murine microglia 15 min or 24 h before cell stimulation with 20 ng/ml LPS. Following a 24 h incubation period, nitrite concentration in supernatant was quantified using the Griess assay described in section 2.5. Viability of BV-2 cells was determined using the MTT assay. D-Serine, TMAO, valerate and IL-2 did not significantly affect the concentration of nitrite in the supernatant of LPS-stimulated BV-2 cells when added either 15 min or 24 h before cell stimulation (Fig. 6A,B; 7A,B; 8A,B; 9A,B). The concentration of nitrite in the supernatant of untreated, unstimulated cells was below the limit of detection of the Griess assay. Additionally, the nitrite concentration in the supernatants of unstimulated cells treated with D-serine, TMAO, valerate or IL-2 at all concentrations studied was below the limit of detection. While the addition of LPS, in some cases, caused cell death to BV-2 cells, D-serine, TMAO or IL-2 did not further significantly affect the viability of cells (Fig. 6C,D; 7C,D; 8C,D). Valerate did not significantly affect the viability of LPS-stimulated BV-2 cells; however, when cells were pre-incubated with valerate 24 h before the addition of LPS, there was a concentration-dependent trend towards increased cell death (Fig. 8D). D-Serine, TMAO, valerate and IL-2 did not affect the viability of unstimulated BV-2 cells (data not shown). Data obtained from the MTT assay were normalized to values obtained from untreated and unstimulated cells. Data are 40 presented as the means from three or four independent experiments completed on different cell populations and on different days. 05 01 0 01 5 0% BV-2 Cell ViabilityN = 4P = 0 .9 5F = 0 .0 3D -s e rin e (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +D - 2 4 h in c u b a tio n01 02 03 04 05 0Nitrite (M)N = 4P = 0 .2 2F = 1 .9D -s e rin e (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +B - 2 4 h in c u b a tio n01 02 03 04 05 0Nitrite (M)N = 4P = 0 .1 3F = 2 .9D -s e rin e (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +A - 1 5 m in in c u b a tio n05 01 0 01 5 0%BV-2 Cell ViabilityN = 4P = 0 .3 4F = 1 .3D -s e rin e (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +C - 1 5 m in in c u b a tio n Figure 6. D-Serine did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells. D-Serine (0.01 – 100 µM) or its solvent (0 µM) were added to BV-2 cells 15 min (A,C) or 24 h (B,D) before LPS stimulation. Following a 24 h incubation period, concentration of nitrite in the cell-free supernatant was measured by the Griess assay (A,B), and the viability of BV-2 cells was measured by the MTT assay (C,D). Data (means ± SEM) from four independent experiments are presented. The limit of detection (A,B) and viability of unstimulated (no LPS) and untreated cells (C,D) are shown as dashed lines. Nitrite levels in supernatant from unstimulated cells were below the limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 41 05 01 0 01 5 0% BV-2 Cell ViabilityN = 3P = 0 .1 5F = 4 .2T M A O (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +D - 2 4 h in c u b a tio n01 02 03 04 0Nitrite (M)N = 3P = 0 .2 1F = 0 .3T M A O (M ) L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +B - 2 4 h in c u b a tio n01 02 03 04 0Nitrite (M)N = 3P = 0 .3 3F = 0 .9T M A O (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +A - 1 5 m in in c u b a tio n05 01 0 01 5 0% BV-2 Cell ViabilityN = 3P = 0 .1 7F = 3 .2T M A O (M )L P S (2 0 n g /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + +C - 1 5 m in in c u b a tio n Figure 7. TMAO did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells. TMAO (0.01 – 100 µM) or its solvent (0 µM) were added to BV-2 cells 15 min (A,C) or 24 h (B,D) before LPS stimulation. Following a 24 h incubation period, concentration of nitrite in the cell-free supernatant was measured by the Griess assay (A,B) and the viability of BV-2 cells was measured by the MTT assay (C,D). Data (means ± SEM) from four independent experiments are presented. The limit of detection (A,B) and viability of unstimulated (no LPS) and untreated cells (C,D) are shown as dashed lines. Nitrite levels in supernatant from unstimulated cells were below the limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 42 01 02 03 04 0Nitrite (M)N = 4P = 0 .1 3F = 3 .4V a le ra te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +B - 2 4 h in c u b a tio n05 01 0 01 5 0% BV-2 Cell ViabilityN = 4P = 0 .1 8F = 3 .0V a le ra te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +D - 2 4 h in c u b a tio n01 02 03 04 0Nitrite (M)N = 4P = 0 .5 2F = 0 .7V a le ra te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +A - 1 5 m in in c u b a tio n05 01 0 01 5 0% BV-2 Cell ViabilityV a le ra te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +N = 4P = 0 .0 9F = 5 .8C - 1 5 m in in c u b a tio n Figure 8. Valerate did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells. Valerate (15 and 500 µM) or its solvent (0 µM) were added to BV-2 cells 15 min (A,C), or 24 h (B,D) before LPS stimulation. Following a 24 h incubation period, concentration of nitrite in the cell-free supernatant was measured by the Griess assay (A,B) and the viability of BV-2 cells was measured by the MTT assay (C,D). Data (means ± SEM) from four independent experiments are presented. The limit of detection (A,B) and viability of unstimulated (no LPS) and untreated cells (C,D) are shown as dashed lines. Nitrite levels in supernatant from unstimulated cells were below the limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 43 01 02 03 04 0Nitrite (M)N = 4P = 0 .7 4F = 0 .4IL -2 (n g /m l)L P S (2 0 n g /m l)0 1 1 0 1 0 0 + + + +B - 2 4 h in c u b a tio n05 01 0 01 5 0% BV-2 Cell ViabilityN = 4P = 0 .5 5F = 0 .7IL -2 (n g /m l)L P S (2 0 n g /m l) 0 1 1 0 1 0 0 + + + +D - 2 4 h in c u b a tio n01 02 03 04 0Nitrite (M)N = 3P = 0 .6 6F = 0 .3IL -2 (n g /m l)L P S (2 0 n g /m l) 0 1 1 0 1 0 0 + + + +A - 1 5 m in in c u b a tio n05 01 0 01 5 0% BV-2 Cell ViabilityN = 3P = 0 .0 9F = 7 .0IL -2 (n g /m l)L P S (2 0 n g /m l) 0 1 1 0 1 0 0 + + + +C - 1 5 m in in c u b a tio n Figure 9. IL-2 did not affect the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells. IL-2 (1 – 100 ng/ml) or its solvent (0 ng/ml) were added to BV-2 cells 15 min (A,C), or 24 h (B,D) before LPS stimulation. Following a 24 h incubation period, concentration of nitrite in the cell-free supernatant was measured by the Griess assay (A, B) and the viability of BV-2 cells was measured by the MTT assay (C,D). Data (means ± SEM) from four independent experiments are presented. The limit of detection (A,B) and viability of unstimulated (no LPS) and untreated cells (C,D) are shown as dashed lines. Nitrite levels in supernatant from unstimulated cells were below the limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 44 3.2.2 Formate may affect the concentration of nitrite in the supernatant of immune-stimulated BV-2 murine microglia Figure 10 shows data obtained in an experiment where formate (0, 15 and 500 µM) was added to BV-2 murine microglia cells 15 min or 24 h before cell stimulation with 20 ng/ml of LPS. Nitrite concentration in the supernatant and viability of LPS-stimulated BV-2 cells were quantified as described in section 3.2.1. Formate, when added to BV-2 cells 15 min, but not 24 h, before LPS stimulation, decreased the concentration of nitrite in the supernatant of BV-2 cells, shown by the randomized block design one-way ANOVA. It is important to note that Fisher’s LSD post-hoc test did not identify significant differences between any of the experimental conditions. Formate did not significantly affect the viability of either unstimulated (data not shown) or LPS-stimulated BV-2 cells (Fig. 10C,D). 45 01 02 03 04 0Nitrite (M)F o rm a te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +N = 4P = 0 .5 0F = 0 .7B - 2 4 h in c u b a tio n02 04 06 08 01 0 01 2 0% BV-2 Cell ViabilityN = 4P = 0 .6 2F = 0 .3F o rm a te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +D - 2 4 h in c u b a tio n02 04 06 08 01 0 01 2 0% BV-2 Cell ViabilityC - 1 5 m in in c u b a tio nN = 4P = 0 .1 1F = 4 .2F o rm a te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +01 02 03 04 0Nitrite (M)N = 4P = 0 .0 4 5F = 9 .0F o rm a te (M )L P S (2 0 n g /m l)0+1 5 +5 0 0 +A - 1 5 m in in c u b a tio n Figure 10. Formate altered the concentration of nitrite in the supernatant of stimulated murine BV-2 microglia cells. Formate (15 and 500 µM) or its solvent (0 µM) were added to BV-2 cells 15 min (A,C), or 24 h (B,D) before LPS stimulation. Following a 24 h incubation period, concentration of nitrite in the cell-free supernatant was measured by the Griess assay (A,B) and the viability of BV-2 cells was measured by the MTT assay (C,D) . Data (means ± SEM) from four independent experiments are presented. The limit of detection (A,B) and viability of unstimulated (no LPS) and untreated cells (C,D) are shown as dashed lines. Nitrite levels in supernatant from unstimulated cells were below the limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 46 3.2.3 D-Serine, TMAO and IL-2 do not affect the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 cells Figures 11-13 show data obtained in an experiment where D-serine (0.01-100 µM), TMAO (0.01-100 µM), and IL-2 (1-100 ng/ml) were added to THP-1 cells 15 min or 24 h before stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ. Following a 48 h incubation period, TNF-α and MCP-1 concentrations in the cell-free supernatant were quantified using ELISAs as described in section 2.6. D-Serine, TMAO, and IL-2, when added 15 min or 24 h before cell stimulation, did not affect the secretion of TNF-α (Fig. 11A,B; 12A,B; 13A,B) or MCP-1 (Fig. 11CD; 12C,D; 13C,D) by THP-1 cells. TNF-α and MCP-1 secretion levels of unstimulated cells treated with D-serine, TMAO, IL-2, or just their solvents, were below the limit of detection for the corresponding ELISAs. Since THP-1 cell supernatants were harvested during the supernatant transfer experiments described above, viability of THP-1 cells after the 48 h incubation period corresponds to data shown in Figures 2-4 (panels A,B). Data are presented as the mean of three to five independent experiments completed on different cell populations and on different days. 47 01234TNF- (ng/ml)N = 3P = 0 .4 7F = 0 .8D -s e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +A - 1 5 m in in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 5P = 0 .3 6F = 1 .1D -s e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +C - 1 5 m in in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 4P = 0 .1F = 3 .5D -s e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +D - 2 4 h in c u b a tio n01234TNF- (ng/ml)N = 4P = 0 .7F = 0 .3D -s e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 0 .0 1 0 .1 1 1 0 1 0 0 + + + + + + + + + + + +B - 2 4 h in c u b a tio n Figure 11. D-Serine did not affect the secretion of TNF-α or MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells. D-Serine (0.01 – 100 µM) or its solvent (0 µM) were added to THP-1 cells 15 min (A,C), or 24 h (B,D) before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, TNF-α (A,B) and MCP-1 (C,D) concentrations in cell-free supernatant were determined using ELISAs. Data (means ± SEM) from three to five independent experiments are presented. The ELISA limits of detection are shown as dashed lines. Cytokine levels in supernatants of unstimulated cells treated with D-serine, or just its solvent, were below the ELISA limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 48 01234TNF- (ng/ml)N = 3P = 0 .5 6F = 0 .6T M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +A - 1 5 m in in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 4P = 0 .8 2F = 0 .2T M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +C - 1 5 m in in c u b a tio n01234TNF- (ng/ml)T M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0 0 .0 1 0 .1 1 1 0 1 0 0+ + + + + ++ + + + + +N = 4P = 0 .3 3F = 1 1 .9B - 2 4 h in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 4P = 0 .5F = 0 .6T M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 0 .0 1 0 .1 1 1 0 1 0 0 + + + + + + + + + + + +D - 2 4 h in c u b a tio n Figure 12. TMAO did not affect the secretion of TNF-α or MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells. TMAO (0.01 – 100 µM) or its solvent (0 µM) were added to THP-1 cells 15 min (A,C) or 24 h (B,D) before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, TNF-α (A,B) and MCP-1 (C,D) concentrations in cell-free supernatant were determined using ELISAs. Data (means ± SEM) from three or four independent experiments are presented. The ELISA limits of detection are shown as dashed lines. Cytokine levels in supernatants of unstimulated cells treated with TMAO, or just its solvent, were below the ELISA limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 49 01234TNF- (ng/ml)N = 3P = 0 .1 1F = 4 .5IL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 1 1 0 1 0 0 + + + + + + + +A - 1 5 m in in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 4P = 0 .6 9F = 0 .3IL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 1 1 0 1 0 0 + + + + + + + +C - 1 5 m in in c u b a tio n01234TNF- (ng/ml)N = 4P = 0 .4 6F = 0 .9IL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 1 1 0 1 0 0 + + + + + + + +B - 2 4 h in c u b a tio n0 .00 .51 .01 .5MCP-1 (ng/ml)N = 4P = 0 .0 9F = 4 .4IL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l) 0 1 1 0 1 0 0 + + + + + + + +D - 2 4 h in c u b a tio n Figure 13. IL-2 did not affect the secretion of TNF-α or MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells. IL-2 (1 – 100 ng/ml) or its solvent (0 ng/ml) were added to THP-1 cells 15 min (A,C) or 24 h (B,D) before LPS plus IFN-ɣ stimulation. Following a 48 h incubation period, TNF-α (A,B) and MCP-1 (C,D) concentrations in cell-free supernatant were determined using ELISAs. Data (means ± SEM) from three or four independent experiments are presented. The ELISA limits of detection are shown as dashed lines. Cytokine levels in supernatants of unstimulated cells treated with IL-2, or just its solvent, were below the ELISA limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 50 3.2.4 Formate and valerate inhibit the secretion of TNF-α and MCP-1 by immune-stimulated THP-1 cells Figures 14 and 15 show data obtained in an experiment where formate (15 and 500 µM) and valerate (15 and 500 µM) were added to THP-1 cells 15 min before stimulation with 20 ng/ml LPS plus 100 U/ml IFN-ɣ. Following a 48 h incubation period, TNF-α and MCP-1 concentrations in the cell-free supernatant were quantified using ELISAs as described in section 2.6. Formate and valerate significantly inhibited the secretion of TNF-α (Fig. 14A; 15A) and MCP-1 (Fig. 14B; 15B) by stimulated THP-1 cells. TNF-α and MCP-1 secretion levels of unstimulated cells, untreated or treated with formate or valerate, were below the ELISA limit of detection. Data are presented as the means from three or six independent experiments completed on different cell populations and on different days. Viability of cells after the 48 h incubation period was determined during the supernatant transfer assay. Figure 5A shows that both formate and valerate at 15 µM increased viability of stimulated THP-1 cells. The MTT assay also demonstrated that neither of these SCFAs at 500 µM effected viability of stimulated THP-1 cells (data not shown). 51 012345TNF- (ng/ml)0++1 5++5 0 0 + +F o rm a te (M )L P S (2 0 n g /m l)IF N - (1 0 0 U /m l)N = 3P < 0 .0 5F = 3 5 .0**A0 .00 .51 .01 .52 .0MCP-1 (ng/ml)0++1 5++5 0 0 + +F o rm a te (M )L P S (2 0 n g /m l)IF N - (1 0 0 U /m l)N = 6P < 0 .0 5F = 1 1 .3**B Figure 14. Formate inhibited the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells. Formate (15 and 500 µM) or its solvent (0 µM) were added to THP-1 cells 15 min before LPS plus IFN-ɣ stimulation. Following a 48 h incubation, TNF-α (A) and MCP-1 (B) concentrations in cell-free supernatant were determined using ELISAs. Data (means ± SEM) from three or six independent experiments are presented. The ELISA limits of detection are shown as dashed lines. Cytokine levels in supernatants of unstimulated cells, incubated in the presence or absence of formate, were below the ELISA limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. * P<0.05 according to Fisher’s LSD post-hoc test. 52 012345TNF- (ng/ml)0++1 5++5 0 0 + +V a le ra te (M )L P S (2 0 n g /m l)IF N - (1 0 0 U /m l)N = 3P < 0 .0 1F = 1 0 0 .5****C0 .00 .51 .01 .52 .0MCP-1 (ng/ml)0++1 5++5 0 0 + +V a le ra te (M )L P S (2 0 n g /m l)IF N - (1 0 0 U /m l)N = 6P < 0 .0 1F = 1 8 .1****D Figure 15. Valerate inhibited the secretion of TNF-α and MCP-1 by LPS plus IFN-ɣ-stimulated THP-1 microglia-like cells. Valerate (15 and 500 µM) or its solvent (0 µM) were added to THP-1 cells 15 min before LPS plus IFN-ɣ stimulation. Following a 48 h incubation, TNF-α (A) and MCP-1 (B) concentrations in cell-free supernatant were determined using ELISAs. Data (means ± SEM) from three or six independent experiments are presented. The ELISA limits of detection are shown as dashed lines. Cytokine levels in supernatants of unstimulated cells, incubated in the presence or absence of valerate, were below the ELISA limit of detection. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. ** P<0.01 according to Fisher’s LSD post-hoc test. 3.2.5 TMAO and valerate do not affect ROS secretion by immune-stimulated HL-60 cells Figures 16 and 17 show data obtained in an experiment where TMAO (1-100 µM) or valerate (15-1000 µM) were added to differentiated HL-60 cells 15 min before the addition of 0.5 µg/ml LPS. Following a 24 h priming period, cells were stimulated with 1.2 µM FMLP to induce the respiratory burst. ROS secretion and cell viability were quantified as described in section 2.7. TMAO and valerate did not significantly affect the secretion of ROS by LPS–primed and FMLP-stimulated HL-60 cells (Fig. 16A; 17A). TMAO and valerate did not 53 affect the viability of LPS-primed, unstimulated HL-60 cells (Fig 16B; 17B). ROS secretion and viability of unprimed cells were also not affected by TMAO or valerate (data not shown). 05 0 0 01 0 0 0 01 5 0 0 02 0 0 0 0CHLN = 4P = 0 .1 6F = 2 .8 0 1 1 0 1 0 0 + + + + + + + +T M A O (M )L P S (0 .5 g /m l)F M L P (1 .2 M )A05 01 0 01 5 02 0 02 5 0% HL-60 Cell ViabilityN = 4P = 0 .3F = 1 .5 0 1 1 0 1 0 0 + + + + - - - -T M A O (M )L P S (0 .5 g /m l)F M L P (1 .2 M )B Figure 16. TMAO did not affect the secretion of ROS by LPS-primed and FMLP- stimulated HL-60 microglia-like cells. TMAO (1 – 100 µM) or its solvent (0 µM) were added to HL-60 cells 15 min before priming with 0.5 µg/ml LPS. Following a 24 h incubation period, cells were stimulated with 1.2 µM FMLP to elicit the respiratory burst. ROS secretion was quantified by the intensity of chemiluminescence (CHL, A) and the viability of HL-60 cells was measured by the MTT assay (B). Data (means ± SEM) from four independent experiments are presented. ROS secretion from FMLP-stimulated HL-60 cells in the absence of TMAO and LPS priming (A), as well as the viability of HL-60 cells treated with vehicle solutions only (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 54 02 0 0 0 04 0 0 0 06 0 0 0 08 0 0 0 0CHLN = 4P = 0 .3 0F = 1 .6V a le ra te (M )L P S (0 .5 g /m l)F M L P (1 .2 M ) 0 1 5 5 0 0 1 0 0 0 + + + + + + + +A05 01 0 01 5 02 0 0% HL-60 Cell ViabilityN = 4P = 0 .3 2F = 1 .4 0 1 5 5 0 0 1 0 0 0 + + + + - - - -V a le ra te (M )L P S (0 .5 g /m l)F M L P (1 .2 M )B Figure 17. Valerate did not affect the secretion of ROS by LPS-primed and FMLP- stimulated HL-60 microglia-like cells. Valerate (15 – 1000 µM) or its solvent (0 µM) were added to HL-60 cells 15 min before priming with 0.5 µg/ml LPS. Following a 24 h incubation period, cells were stimulated with 1.2 µM FMLP to elicit a respiratory burst. ROS secretion was quantified by the intensity of chemiluminescence (CHL, A) and the viability of HL-60 cells was measured by the MTT assay (B). Data (means ± SEM) from four independent experiments are presented. ROS secretion from FMLP-stimulated HL-60 cells in the absence of valerate and LPS priming (A), as well as the viability of HL-60 cells treated with vehicle solutions only (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. 3.2.6 D-Serine, formate and IL-2 inhibit the secretion of ROS by immune-stimulated HL-60 cells Figures 18-20 show data obtained in an experiment where D-serine (1-100 µM), formate (15-1000 µM) or IL-2 (1-100 ng/ml) were added to differentiated HL-60 cells 15 min before the addition of 0.5 µg/ml LPS. Following a 24 h priming period, cells were stimulated with 1.2 µM FMLP to induce a respiratory burst. ROS secretion and HL-60 cell viability were quantified as described in section 2.7. D-Serine, formate and IL-2 significantly inhibited the secretion of ROS by LPS–primed and FMLP-stimulated HL-60 cells at the highest concentrations tested (Fig 18A; 55 19A; 20A). D-Serine, formate and IL-2 at any of the concentrations used did not affect the viability of LPS-primed, unstimulated HL-60 cells (Fig 18B; 19B; 20B). ROS secretion and viability of unprimed cells were also not affected by D-serine, formate or IL-2 (data not shown). 01 0 0 0 02 0 0 0 03 0 0 0 0CHLN = 9P < 0 .0 5F = 4 .5 0 1 1 0 1 0 0 + + + + + + + +D -s e rin e (M )L P S (0 .5 g /m l)F M L P (1 .2 M )*A05 01 0 01 5 0% HL-60 Cell ViabilityN = 9P = 0 .3 6F = 1 .1 0 1 1 0 1 0 0 + + + + - - - -D -s e rin e (M )L P S (0 .5 g /m l)F M L P (1 .2 M )B Figure 18. D-Serine inhibited the secretion of ROS by LPS-primed and FMLP-stimulated HL-60 microglia-like cells. D-Serine (1 – 100 µM) or its solvent (0 µM) were added to HL-60 cells 15 min before priming with 0.5 µg/ml LPS. Following a 24 h incubation period, cells were stimulated with 1.2 µM FMLP to elicit a respiratory burst. ROS secretion was quantified by the intensity of chemiluminescence (CHL, A) and the viability of HL-60 cells was measured by the MTT assay (B). Data (means ± SEM) from nine independent experiments are presented. ROS secretion from FMLP-stimulated HL-60 cells in the absence of D-serine and LPS priming (A), as well as the viability of HL-60 cells treated with vehicle solutions only (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. * P<0.05 according to Fisher’s LSD post-hoc test. 56 01 0 0 0 02 0 0 0 03 0 0 0 04 0 0 0 0CHLN = 4P < 0 .0 1F = 2 1 .8 0 1 5 5 0 0 1 0 0 0 + + + + + + + +F o rm a te (M )L P S (0 .5 g /m l)F M L P (1 .2 M )* *A05 01 0 01 5 02 0 02 5 0% HL-60 Cell ViabilityN = 4P = 0 .0 7F = 5 .6 0 1 5 5 0 0 1 0 0 0 + + + + - - - -F o rm a te (M )L P S (0 .5 g /m l)F M L P (1 .2 M )B Figure 19. Formate inhibited the secretion of ROS by LPS-primed and FMLP- stimulated HL-60 microglia-like cells. Formate (15 – 1000 µM) or its solvent (0 µM) were added to HL-60 cells 15 min before priming with 0.5 µg/ml LPS. Following a 24 h incubation period, cells were stimulated with 1.2 µM FMLP to elicit a respiratory burst. ROS secretion was quantified by the intensity of chemiluminescence (CHL, A). Formate did not affect the viability of LPS-primed HL-60 cells according to the MTT assay (B). Data (means ± SEM) from four independent experiments are presented. ROS secretion from FMLP-stimulated HL-60 cells in the absence of formate and LPS priming (A), as well as the viability of HL-60 cells treated with vehicle solutions only (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. ** P<0.01 according to Fisher’s LSD post-hoc test. 57 05 0 0 01 0 0 0 01 5 0 0 02 0 0 0 02 5 0 0 0CHL 0 1 1 0 1 0 0 + + + + + + + +IL -2 (n g /m l)L P S (0 .5 g /m l)F M L P (1 .2 M )N = 8P < 0 .0 5F = 4 .2*A05 01 0 01 5 02 0 02 5 0% HL-60 Cell ViabilityN = 7P = 0 .2 7F = 1 .5 0 1 1 0 1 0 0 + + + + - - - -IL -2 (n g /m l)L P S (0 .5 g /m l)F M L P (1 .2 M )B Figure 20. IL-2 inhibited the secretion of ROS by LPS-primed and FMLP- stimulated HL-60 microglia-like cells. IL-2 (1 – 100 ng/ml) or its solvent (0 ng/ml) were added to HL-60 cells 15 min before priming with 0.5 µg/ml LPS. Following a 24 h incubation period, cells were stimulated with 1.2 µM FMLP to elicit a respiratory burst. ROS secretion was quantified by the intensity of chemiluminescence (CHL, A). IL-2 did not affect the viability of LPS-primed HL-60 cells according to the MTT assay (B). Data (means ± SEM) from four independent experiments are presented. ROS secretion from FMLP-stimulated HL-60 cells in the absence of IL-2 and LPS priming (A), as well as the viability of HL-60 cells treated with vehicle solutions only (B) are shown as dashed lines. P and F values shown on the figure were calculated by the randomized block design one-way ANOVA. * P<0.05 according to Fisher’s LSD post-hoc test. 3.3 Phagocytic activity of immune-stimulated THP-1 microglia-like cells LPS plus IFN-ɣ were added to THP-1 microglia-like cells to induce phagocytosis, a characteristic of reactive microglia. Fluorescent latex beads were then added to cell culture and phagocytosis by THP-1 cells was quantified as described in section 2.8. I explored whether D-serine, TMAO, formate, valerate or IL-2 would modify the phagocytic activity of both stimulated and unstimulated THP-1 cells. 58 3.3.1 TMAO and IL-2 do not affect the phagocytic activity of THP-1 cells Figures 21 and 22 show data obtained after TMAO (100 µM) or IL-2 (100 ng/ml) were added to unstimulated THP-1 cells, or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ. Following a 24 h incubation period, fluorescent latex beads were added to cells for one h. Phagocytosis was then quantified using fluorescent microscopy. Only viable cells, identified by trypan blue exclusion, were assessed for their phagocytic activity. TMAO and IL-2 had no significant effect on the phagocytic activity of unstimulated THP-1 cells (Fig. 21-22A) or THP-1 cells stimulated with LPS plus IFN-ɣ (Fig. 21-22B). 59 0 .00 .51 .01 .5Fold Change Bead FluorescenceN = 1 1 9T M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0--1 0 0--AP = 0 .2 00 .00 .51 .01 .5Fold Change Bead FluorescenceT M A O (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0++1 0 0++BN = 1 1 9P = 0 .9 1 Figure 21. TMAO did not affect the phagocytic activity of THP-1 microglia-like cells. TMAO (100 µM) or its solvent (0 µM) were added to unstimulated THP-1 cells (A) or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ (B). Following a 24 h incubation period, fluorescent beads were added to cells in a 10:1 (bead:cell) ratio. Following a one h incubation period, phagocytosis was quantified using fluorescent microscopy. Data (means ± SEM) from 119 cells (30-50 cells in each of the three independent experiments) are presented and expressed as a fold change compared to cells treated with the vehicle solutions only. P value was determined using the Student’s t test. 60 0 .00 .51 .01 .52 .0Fold Change Bead FluorescenceN = 1 2 0IL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0--1 0 0--AP = 0 .4 10 .00 .51 .01 .52 .0Fold Change Bead FluorescenceN = 1 2 0BIL -2 (n g /m l)L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0++1 0 0++P = 0 .1 4 Figure 22. IL-2 did not affect the phagocytic activity of THP-1 microglia-like cells. IL-2 (100 ng/ml) or its solvent (0 ng/ml) were added to unstimulated THP-1 cells (A) or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ (B). Following a 24 h incubation period, fluorescent beads were added to cells in a 10:1 (bead:cell) ratio. Following a one h incubation period, phagocytosis was quantified using fluorescent microscopy. Data (means ± SEM) from 120 cells (30-50 from three independent experiments) are presented and expressed as a fold change compared to cells treated with the vehicle solutions only. P value was determined using the Student’s t test. 3.3.2 D-Serine, formate and valerate modulate the phagocytic activity of THP-1 cells Figures 23-25 show data obtained in an experiment where D-serine (100 µM), formate (1000 µM) or valerate (1000 µM) were added to unstimulated THP-1 cells, or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ. Following a 24 h incubation period, fluorescent latex beads were added to cells 61 for one h. Phagocytosis was then quantified using fluorescent microscopy. Only viable cells, identified by trypan blue exclusion, were assessed for their phagocytic activity. D-serine, formate and valerate significantly inhibited the phagocytosis of LPS plus IFN-ɣ-stimulated THP-1 cells (Fig. 23B; 24B; 25B). Furthermore, D-serine enhanced (Fig. 23A) and valerate inhibited (Fig. 25A) the phagocytic activity of unstimulated THP-1 cells. Formate did not significantly affect the phagocytic activity of unstimulated THP-1 cells (Fig. 24A). 0 .00 .51 .01 .52 .0Fold Change Bead FluorescenceD -S e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0--1 0 0--N = 1 2 1*A0 .00 .51 .01 .52 .0Fold Change Bead FluorescenceD -S e rin e (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0++1 0 0++**N = 1 2 1B Figure 23. D-Serine modulated the phagocytic activity of THP-1 microglia-like cells. D-serine (100 µM) or its solvent (0 µM) were added to unstimulated THP-1 cells (A) or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ (B). Following a 24 h incubation period, fluorescent beads were added to cells in a 10:1 (bead:cell) ratio. Following a one h incubation period, phagocytosis was quantified using fluorescent microscopy. Data (means ± SEM) from 121 cells (30-50 from three independent experiments) are presented and expressed as a fold change compared to cells treated with the vehicle solutions only. *P<0.05; ** P<0.01 according to the Student’s t test. 62 0 .00 .51 .01 .52 .0Fold Change Bead FluorescenceF o rm a te (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0--1 0 0 0--N = 1 2 5AP = 0 .8 20 .00 .51 .01 .52 .0Fold Change Bead FluorescenceF o rm a te (M )L P S (2 0 0 n g /m l)IF N - (1 5 0 U /m l)0++1 0 0 0++N = 1 2 5B** Figure 24. Formate inhibited the phagocytic activity of stimulated THP-1 microglia-like cells. Formate (1000 µM) or its solvent (0 µM) were added to unstimulated THP-1 cells (A) or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ (B). Following a 24 h incubation period, fluorescent beads were added to cells in a 10:1 (bead:cell) ratio. Following a one h incubation period, phagocytosis was quantified using fluorescent microscopy. Data (means ± SEM) from 125 cells (30-50 from three independent experiments) are presented and expressed as a fold change compared to cells treated with the vehicle solutions only. ** P<0.01 according to the Student’s t test. 63 0 .00 .51 .01 .5Fold Change Bead FluorescenceV a le ra te (M )L P S (2 0 n g /m l)IF N - (1 5 0 U /m l)0--1 0 0 0--N = 1 2 2A* *0 .00 .51 .01 .52 .0Fold Change Bead FluorescenceN = 1 2 2V a le ra te (M )L P S (2 0 n g /m l)IF N - (1 5 0 U /m l)0++1 0 0 0++B** Figure 25. Valerate inhibited the phagocytic activity of THP-1 microglia-like cells. Valerate (1000 µM) or its solvent (0 µM) were added to unstimulated THP-1 cells (A) or added to THP-1 cells 15 min before their stimulation with 200 ng/ml LPS plus 150 U/ml IFN-ɣ (B). Following a 24 h incubation period, fluorescent beads were added to cells in a 10:1 (bead:cell) ratio. Following a one h incubation period, phagocytosis was quantified using fluorescent microscopy. Data (means ± SEM) from 122 cells (30-50 from three independent experiments) are presented and expressed as fold change compared to cells treated with the vehicle solutions only. ** P<0.01 according to the Student’s t test. 64 Chapter 4: Discussion 4.1 Microglia-modulating effects of D-serine D-Serine was hypothesized to alter specific microglial functions as previous studies showed that the activation of NMDA receptors found on murine microglia led to secretion of inflammatory molecules (Kaindl et al., 2012). Whether D-serine acts on microglial NMDA receptors to exacerbate or attenuate this inflammatory response is unknown. On neurons, D-serine preferentially binds the synaptic GluN2A subunit of NMDA receptors and is associated with neuroprotection, while glycine preferentially binds GluN2B located on extrasynaptic NMDA receptors and is associated with neurotoxicity (MacKay et al., 2019). While the effects of D-serine on neurons have been well established, it may function differently on other cell types. A study using rat chondrocytes showed that D-serine acts as an antagonist at the glycine site on NMDA receptors and its application had negative effects on cartilage growth (Montesinos Guevara & Mani, 2016). This study suggested that the effects of D-serine may be cell type specific and could work differently on microglia compared to neurons. To my knowledge, no other studies have investigated the effects of D-serine in modulating immune cell activity, both in the CNS and periphery. Furthermore, the structure of the microglial NMDA receptor, its subunits, and interaction with glycine or D-serine is not well understood and requires further study (Van Horn et al., 2013). I tested D-serine for its ability to modulate microglia-mediated neurotoxicity, the secretory profile of stimulated microglia, and the phagocytic activity of microglia. 65 D-Serine did not modulate the cytotoxicity of stimulated THP-1 cells towards SH-SY5Y cells, nor did it alter the secretion of TNF-α and MCP-1 from stimulated THP-1 cells or NO from stimulated BV-2 cells. Interestingly, D-serine increased the phagocytic activity of unstimulated THP-1 cells and inhibited the phagocytic activity of stimulated THP-1 cells. A molecule which can modify the phagocytic activity of microglia without affecting the associated secretion of inflammatory mediators may be beneficial in clearing neurotoxic proteins that accumulate in the inflamed neurodegenerative brain (Leitner et al., 2019). A study using BV-2 murine microglia demonstrated that cell stimulation, using the toll like receptor (TLR) agonist LPS, was inhibited with propofol, which has previously been shown to inhibit NMDA receptor-mediated effects (Orser, Bertlik, Wang, & MacDonald, 1995; Q. Wu et al., 2018). Therefore, the effect of D-serine alone on microglia may be agonistic at the NMDA receptor; however, when co-administered with LPS, a TLR agonist, converging signaling pathways may become desensitized resulting in phagocytosis inhibition (Morris & Golan, 2011). While D-serine on its own did not induce ROS secretion by HL-60 cells, it inhibited ROS secretion when the cells were primed with LPS, further suggesting a possible interaction of signaling pathways involving LPS and D-serine. D-Serine may also decrease the release of ROS by activated immune cells through the increased production of antioxidant molecules. L-Serine is a precursor for the amino acids L-cysteine and L-glycine, which are key factors in the production of the antioxidant glutathione (GSH)(Lu, 2013). GSH has been shown to decrease ROS levels and may mediate the indirect ROS-inhibiting ability of D-serine. During states of 66 inflammation, the human CNS expresses high concentrations of microglial serine racemase (SRR), thereby increasing the ability to convert D-serine to L-serine, and vice versa (S.-Z. Wu et al., 2004). It is important to note that the cell lines used in my study, including HL-60 and THP-1, express SRR RNA (“SRR transcriptomics data - The Human Protein Atlas,” n.d.). Furthermore, the metabolism of L-serine and D-serine by SRR leads to the co-production of ammonia and pyruvate (Van Horn et al., 2013). While the production of ammonia is a source of oxidative stress, pyruvate is a ROS-scavenging molecule which may offset ROS production and secretion (X. Wang et al., 2007). 4.2 Microglia-modulating effects of TMAO TMAO was hypothesized to alter specific microglial functions as a previous study showed that mice that were fed 1.5 % TMAO in their drinking water had cognitive decline, increased oxidative stress and neuronal senescence in their brain hippocampal region compared to control mice. While the effects of TMAO on neurons were investigated, the effects of TMAO on microglial activity were not (D. Li et al., 2018). No studies, to my knowledge, explore the effects of TMAO on microglial functions. To address this knowledge gap, I investigated whether the negative effects of TMAO elicited on neurons could also be seen with microglia. I tested TMAO for its ability to modulate microglia-mediated neurotoxicity, the secretory profile of stimulated microglia, and the phagocytic activity of microglia. I found that TMAO did not modulate any of the microglial functions tested. 67 These results were unexpected as previous studies showed that TMAO may cause systemic inflammation through the modulation of peripheral immune cell activity. A study investigating the role of TMAO in endothelial dysfunction found that TMAO increased THP-1 cell adhesion to endothelial cells; however, these effects were believed to be through the upregulation of vascular cell adhesion molecule-1 expression on the endothelial cells themselves (G. Ma et al., 2017). Another study, using mice fed a diet supplemented with TMAO, showed increased protein expression of scavenger receptor (SR)-A1 and cluster of differentiation (CD) 36 on peritoneal macrophages (Z. Wang et al., 2011). SR-A1 and CD36 are scavenger receptors found on macrophages and microglia that are involved in regulating phagocytosis activity and the production of ROS; therefore, it was unexpected that TMAO had no effect on these tested parameters (Kelley, Ozment, Li, Schweitzer, & Williams, 2014; K. Wilkinson & El Khoury, 2012; Woo, Yang, Beltran, & Cho, 2016). As previous studies have shown that TMAO regulates neuronal activity, TMAO may act through mechanisms that do not affect microglial functions or act through mechanisms that were not investigated in this thesis. TMAO has widespread protein stabilizing functions, which may explain its involvement in both Aβ aggregation and tau tubulin assembly (Cho, Reddy, Straub, & Thirumalai, 2011; Smith et al., 2000; Tseng & Graves, 1998). A thermodynamic study, investigating the protein-stabilizing abilities of TMAO, revealed that TMAO enhanced solvent structure by increasing the number of hydrogen bonds in proximity to proteins. These interactions, between TMAO, solvent, and protein, promoted the stability of proteins by resisting the denaturing effects of stressors, such as urea or other osmolytes (Zou et al., 2002). Whether or not the 68 microglial stimulants LPS and IFN-ɣ directly participate in the modulation of osmotic stress and protein denaturation is unknown. Hyperosmotic stress, which can be an inflammatory stimulus, is often caused by diseases, such as asthma and diabetes mellitus (Brocker, Thompson, & Vasiliou, 2012). Therefore, further investigation is needed to ascertain how TMAO affects microglia in hyperosmotic environments. 4.3 Microglia-modulating effects of formate and valerate Formate and valerate were hypothesized to modulate select microglial functions since previous studies showed that SCFAs, such as butyrate, acetate and propionate, affected peripheral immune cell functions. Most SCFA peripheral studies focus on the effects of butyrate, acetate or propionate, and fail to consider other SCFAs, such as formate and valerate, that are also produced by gut microbiota. Furthermore, these studies explore the effects of SCFAs applied at high concentrations and neglect to appropriately address their synergistic effects at physiologically relevant concentrations (Huuskonen, Suuronen, Nuutinen, Kyrylenko, & Salminen, 2004; Ji et al., 2016; Nastasi et al., 2015; J. Tan et al., 2014). Few studies have investigated the CNS effects of SCFAs, specifically on microglia; therefore, we explored the microglia-modulating effects of butyrate, acetate, propionate, formate, and valerate. The selected SCFAs were tested together in a physiologically relevant ratio, or independently at concentrations similar to those detected previously in human serum (Ktsoyan et al., 2016; Pouteau, Meirim, Métairon, & Fay, 2001; Zhao, Liu, Nyman, Jan˚, & Jönsson, 2007). We found that formate and valerate on their own or mixed with the other three SCFAs decreased THP-1 cell-mediated cytotoxicity towards SH-SY5Y cells and 69 inhibited the secretion of TNF-α and MCP-1 by immune-stimulated THP-1 cells (Wenzel et al., 2020). These data led me to further explore the microglia-modulating effects of formate and valerate. It was determined that formate and valerate on their own inhibited the phagocytic activity of THP-1 cells and formate, but not valerate, inhibited the secretion of ROS by immune-stimulated HL-60 cells. Formate and valerate had no effect on the secretion of NO by BV-2 cells. The immunomodulatory effect of SCFAs on murine microglia has been previously studied. Propionate, butyrate and valerate inhibited the secretion of IL-8 and TNF-α, and increased the secretion of IL-6, by LPS-stimulated N9 murine microglia. Furthermore, propionate and butyrate increased the secretion of NO while valerate had no effect (Huuskonen et al., 2004). While we did not study the effects of SCFAs on cytokine secretion by murine cell lines, we similarly observed that valerate had no effect on the secretion of NO by immune-stimulated murine BV-2 microglia. However, it is important to note that valerate caused a trend towards decreased BV-2, but not THP-1, cell viability which suggested that valerate may have toxic effects on murine cell lines. We determined that formate and valerate inhibited the secretion of TNF-α and MCP-1 by immune-stimulated human monocytic THP-1 cells. A study, using peripheral blood mononuclear cells, reported similar immunomodulatory effects of SCFAs, showing that acetate, propionate and butyrate, but not formate, inhibited the secretion of TNF-α. While the study did not investigate the effects of valerate, it did show that the SCFAs, including formate, inhibited the secretion of MCP-1 (Cox et al., 2009). Another study also showed that high concentrations of SCFAs, including butyrate, acetate and propionate, inhibited the secretion of ROS and the phagocytic activity of bovine 70 polymorphonucleocytes (Mills, Montgomery, & Morck, 2006). We similarly demonstrated that formate and valerate inhibited the phagocytic activity of THP-1 monocytic cells. We also determined that formate, but not valerate, inhibited the secretion of ROS from HL-60 myelomonocytic cells. SCFAs work through FFAR2 and 3, and their affinity and activation efficacies at these receptors may depend on the carbon chain length of the individual SCFAs (M. Li et al., 2018). FFAR2 is preferentially activated by SCFAs with a two- to three-carbon chain length, such as acetate and propionate, while FFAR3 is preferentially activated by three- to five-carbon SCFAs, such as propionate, butyrate and valerate. While formate, a one-carbon SCFA, can activate both receptors, it interacts with FFAR2 more potently (Brown et al., 2003; Le Poul et al., 2003). A study using a cell electrophysiology assay revealed that propionate activated FFAR2 and 3 with maximum potency compared to several other SCFA, including formate and valerate (Brown et al., 2003). These results contradicted my findings, which identified formate and valerate, even at low concentrations, to be the SCFAs that most significantly inhibited microglia-mediated neurotoxicity. FFAR2 and 3 are differentially expressed on different cell types and serve independent functions. FFAR2 is expressed in higher levels on immune cells, including neutrophils and monocytes, and is most likely the receptor responsible for the immune modulating effects of SCFAs (Kim, Kim, Park, & Kwak, 2014). Activation of FFAR2 has been shown to decrease cyclic AMP levels and inhibit nuclear factor-кB, leading to anti-inflammatory activity (Brown et al., 2003; Gao et al., 2004; Lee et al., 2013). As both formate and valerate can activate FFAR2, even with low potencies, this is most likely 71 how they are modulating immune cell functions like ROS secretion, phagocytosis and cytokine secretion (Ballinger, Welliver, Straight, Peters-Golden, & Swanson, 2010; A. J. Brown et al., 2003; Le Poul et al., 2003; Morgan & Liu, 2011). 4.4 Microglia-modulating effects of IL-2 IL-2 was hypothesized to alter specific microglial functions as previous studies showed that mice with intestinal inflammation had upregulated brain levels of IL-2 (unpublished data, collaborative study with Dr. Gibson’s lab at UBC Okanagan). Whether IL-2 is able to pass into the brain through the BBB is still under investigation; therefore, local production in the brain induced by peripheral stimulation in the gut was hypothesized (Hanisch & Quirion, 1995). IL-2 is known to modulate peripheral immune cell functions; therefore, we anticipated that IL-2 would also modulate various microglial functions (Waters, Perry, Han, Bielekova, & Gedeon, 2018). No studies, to my knowledge, have tested the direct effects of IL-2 on microglial functions. Therefore, I studied IL-2 for its ability to modulate microglia-mediated neurotoxicity, the secretory profile of stimulated microglia, and the phagocytic activity of microglia. IL-2 did not affect THP-1 cell-mediated cytotoxicity towards SH-SY5Y cells. IL-2 did, however, increase the viability signal of LPS-treated THP-1 cells. As IL-2 is a T-cell expansion molecule, IL-2 most likely caused THP-1 cell proliferation rather than exhibiting protective effects (Ross & Cantrell, 2018). This was supported by the PI assay, which detected no changes in cell death between control and treatment groups. 72 While IL-2 may have caused THP-1 cell proliferation, it had no further effect on the secretion of TNF-α or MCP-1 by THP-1 cells or NO secretion by BV-2 murine microglia. These results were unexpected as previous studies showed that IL-2 had a stimulatory effect on human monocytes, resulting in the secretion of inflammatory mediators, such as TNF-a, IL-1β, IL-6 and IL-8 (Bosco et al., 2000). Interestingly, IL-2 inhibited the secretion of ROS by immune-stimulated HL-60 cells but not the phagocytic activity of immune-stimulated THP-1 cells. In combination with previous studies, these data suggest that IL-2 may have both a stimulatory and regulatory role in the immune system. IL-2 receptor expression on immune cells in the periphery and CNS has been shown to be dependent on immune activation by a stimulus, such as LPS; therefore, the presence of both LPS and IL-2 in high concentrations may result in signal inhibition as a fail-safe to prevent overactivation (Hanisch & Quirion, 1995; Sawada et al., 1995; Sundqvist, 2018). 73 Chapter 5: Summary and conclusions Table 4: Summary of results D-Serine Formate Valerate TMAO IL-2 Microglia-mediated neurotoxicity X ✓ ✓ X X NO secretion X ✓ X X X Cytokine secretion X ✓ ✓ X X ROS Production ✓ ✓ X X ✓ Phagocytosis ✓ ✓ ✓ X X X = No effect was observed, ✓ = Effect was observed 5.1 Hypotheses addressed D-Serine, formate, valerate and IL-2 modulated select microglial functions, while TMAO did not (Table 4). Formate and valerate, at a concentration of 15 μM, inhibited the cytotoxicity of immune-stimulated THP-1 microglia-like cells towards neurons. Formate and valerate also inhibited the secretion of TNF-α and MCP-1 by immune-stimulated microglia-like cells. D-Serine, TMAO and IL-2 had no effect on these tested parameters. While the one-way ANOVA showed that formate modulated the secretion of NO by BV-2 murine microglia, post-hoc analysis failed to determine which concentration tested was effective. D-Serine, valerate, TMAO and IL-2 had no effect on 74 the secretion of NO by immune-stimulated BV-2 murine microglia. D-Serine, formate and IL-2 inhibited the production of ROS by immune stimulated HL-60 microglia-like cells at the highest tested concentration, while valerate and TMAO had no effect. D-Serine, at a concentration of 100 μM, increased the phagocytic activity of unstimulated THP-1 cells, and inhibited the phagocytic activity of immune-stimulated THP-1 cells. Formate and valerate, at a concentration of 1 mM, inhibited the phagocytic activity of THP-1 cells. Valerate, but not formate, also inhibited the phagocytic activity of unstimulated THP-1 cells. TMAO and IL-2 had no effect on phagocytosis. 5.2 Future directions D-Serine modulated select microglia-like cell functions. Understanding how D-serine interacts with its receptor on microglia will be imperative for determining its potential in modulating neuroinflammation. Studies should be continued using NMDA receptor antagonists specific for the D-serine subunit. By antagonizing the receptor, one would be able to determine the specificity of D-serine for the NMDA receptor and begin to understand its mechanism of action. TMAO did not modulate any of the studied microglia-like cell functions. As TMAO is a protein stabilizing molecule and has been shown to modulate neuron viability, studies investigating how the molecule interacts with microglia in stressed environments may offer insight into its role in the CNS. During neurodegeneration, brain cells undergo drastic metabolic changes, resulting in brain pH fluctuations (Magnotta et al., 2012; Obara, Szeliga, & Albrecht, 2008). As TMAO can protect proteins from such stressors, 75 repeating the previously described experiments in pH altered media may illuminate how TMAO operates. Formate and valerate modulated several microglia-like cell functions. We saw that formate and valerate, either independently or mixed with other SCFAs, modulated the cytotoxicity of THP-1 cells toward SH-SY5Y cells. Studies should be continued to investigate whether formate and valerate, in combination with the other SCFAs, can modulate the secretion of ROS by HL-60 cells and the phagocytosis activity of THP-1 cells. Furthermore, studying the modulatory role of formate and valerate on phagocytosis, using a larger concentration range, will be imperative to know the potency of the metabolites. IL-2 modulated ROS secretion by HL-60 cells, however, had no effects on the other tested parameters. Verifying that IL-2 receptor expression on microglia is dependent on immune stimuli would help clarify the role of IL-2 in neuroinflammation. The microglia-modulating effects elicited by D-serine, fomate, valerate and IL-2 were seen using several different cell line models of microglia; therefore, repeating the experiments using primary human or murine microglia would confirm that these molecules can modulate microglial functions. 5.3 Study limitations All studies conducted were accomplished using cancerous or immortalized cell lines that were transfected with viral genes to ensure their continuous proliferation (Birnie, 1988; Bocchini et al., 1992; Påhlman et al., 1990; Tsuchiya et al., 1980). While 76 these cell lines offer important insight into immune and neuronal cell functions, they express different genotypes and phenotypes than their primary cell counterpart, which may result in different study outcomes (Horvath, Nutile-McMenemy, Alkaitis, & DeLeo, 2008; Pan, Kumar, Bohl, Klingmueller, & Mann, 2009). Furthermore, all immune cells used in the studies, except BV-2 cells, originate from the periphery and were not microglia that originate from the CNS. Immortalized human microglia are limited in their availability; therefore, we extended our studies to include BV-2 murine microglia to help address these limitations. While murine microglia cell lines offer important insight into some human microglial functions, their use has become controversial as they express different genes and often respond differently than human cells (Galatro et al., 2017). We used BV-2 murine microglia for the detection of NO in their supernatant. Quantifying NO in supernatant is an effective biomarker of inflammatory activity in murine cells; however, whether the overproduction of NO by microglia is relevant in human neuroinflammation has yet to be confirmed (Bal-Price & Brown, 2001). In the microglia-mediated cytotoxicity assay, we transferred the supernatant of treated THP-1 cells to a monoculture of SH-SY5Y neurons. While this assay allows us to limit variables and observe the unidirectional effects of microglia towards neurons, it may be an oversimplification of the interactions between brain immune cells and neurons. In the human brain, microglia and neurons are in close proximity of one another and require interaction for their proper functioning (Miki et al., 2012; Regier et al., 2016). Studies have shown that cells cultured in isolation express different cell-surface receptor genes than when cocultured with other cell types (Regier et al., 2016) 77 Therefore, any observations made during the microglia-mediated cytotoxicity assay, may not be a correct representation of microglia and neuron interactions in vivo. This research offers important preliminary data into the signaling mechanisms between gut bacteria and brain immune cells; however, to overcome these study limitations, future studies will need to include the use of primary microglia and animal models to confirm the pathophysiological relevance of the results of my research. Several statistical analyses that were performed identified insignificant results; yet, treatment groups showed up to a 50% effect compared to the untreated control group (for examples, see Figs. 2,3,8, and 9). Inconsistencies between statistical analysis and observed effects suggest the possibility of type II errors. To eliminate the possibility of a false negative result, future studies should include larger sample sizes to increase the power of analysis (Guo, Logan, Glueck, & Muller, 2013). 5.4 Research Significance We determined that the gut bacterial metabolites D-serine, formate, valerate and the related endogenous signaling molecule IL-2 modulate select microglia-like cell functions. Microglia are the resident immune cell of the CNS and key players in the neuroinflammatory mechanisms that underly neurodegenerative disorders, like AD, PD and MS. There are currently no effective treatments for these diseases; therefore, identifying new therapeutic targets for preventing or ameliorating their onset is crucial. As recent studies have highlighted a possible involvement of gut bacteria in the onset of neurodegenerative diseases, we set out to determine how gut bacteria are able to 78 communicate with the CNS and modulate neuroimmune functions. We determined that (1) D-serine modulates the secretion of ROS and the phagocytic activity of microglia-like cells, (2) formate and valerate decrease the cytotoxicity of microglia-like cells towards neuronal cells, inhibit the secretion of TNF-α and MCP-1 by microglia-like cells, and inhibit the phagocytic activity of microglia-like cells, (3) formate, but not valerate, inhibits the secretion of ROS by microglia-like cells, and (4) IL-2 inhibits the secretion of ROS by microglia-like cells. These data provide insight into how gut bacteria could modulate neuroinflammatory processes and may offer a new therapeutic target for neurodegenerative diseases. 79 Literature Cited Al-Qazzaz, N. K., Ali, S. H., Ahmad, S. A., Islam, S., & Mohamad, K. (2014). Cognitive impairment and memory dysfunction after a stroke diagnosis: A post-stroke memory assessment. Neuropsychiatric Disease and Treatment, 10, 1677–1691. https://doi.org/10.2147/NDT.S67184 Alves, S., Churlaud, G., Audrain, M., Michaelsen-Preusse, K., Fol, R., Souchet, B., … Cartier, N. (2017). Interleukin-2 improves amyloid pathology, synaptic failure and memory in Alzheimer’s disease mice. Brain : A Journal of Neurology, 140(3), 826–842. https://doi.org/10.1093/brain/aww330 Bachmann, C., Colombo, J. P., & Berüter, J. (1979). Short chain fatty acids in plasma and brain: Quantitative determination by gas chromatography. Clinica Chimica Acta, 92(2), 153–159. https://doi.org/10.1016/0009-8981(79)90109-8 Bal-Price, A., & Brown, G. C. (2001). Inflammatory neurodegeneration mediated by nitric oxide from activated glia-inhibiting neuronal respiration, causing glutamate release and excitotoxicity. Journal of Neuroscience, 21(17), 6480–6491. https://doi.org/10.1523/jneurosci.21-17-06480.2001 Ballinger, M. N., Welliver, T., Straight, S., Peters-Golden, M., & Swanson, J. A. (2010). Transient increase in cyclic AMP localized to macrophage phagosomes. PLoS ONE, 5(11), e13962. https://doi.org/10.1371/journal.pone.0013962 Banati, R. B., Gehrmann, J., Schubert, P., & Kreutzberg, G. W. (1993). Cytotoxicity of microglia. Glia, 7(1), 111–118. https://doi.org/10.1002/glia.440070117 Benakis, C., Garcia-Bonilla, L., Iadecola, C., & Anrather, J. (2014). The role of microglia and myeloid immune cells in acute cerebral ischemia. Frontiers in Cellular Neuroscience, 8, 461. https://doi.org/10.3389/fncel.2014.00461 Birnie, G. D. (1988). The HL60 cell line: A model system for studying human myeloid cell differentiation. British Journal of Cancer, 58(SUPPL. 9), 41–45. Blum-Degena, D., Müller, T., Kuhn, W., Gerlach, M., Przuntek, H., & Riederer, P. (1995). Interleukin-1β and interleukin-6 are elevated in the cerebrospinal fluid of Alzheimer’s and de novo Parkinson’s disease patients. Neuroscience Letters, 202(1–2), 17–20. https://doi.org/10.1016/0304-3940(95)12192-7 Bocchini, V., Mazzolla, R., Barluzzi, R., Blasi, E., Sick, P., & Kettenmann, H. (1992). An immortalized cell line expresses properties of activated microglial cells. Journal of Neuroscience Research, 31(4), 616–621. https://doi.org/10.1002/jnr.490310405 Bosco, M. C., Curiel, R. E., Zea, A. H., Malabarba, M. G., Ortaldo, J. R., & Espinoza-Delgado, I. (2000). IL-2 signaling in human monocytes involves the phosphorylation and activation of p59 hck 1. The Journal of Immunology, 164(9), 4575–4585. https://doi.org/10.4049/jimmunol.164.9.4575 Brocker, C., Thompson, D. C., & Vasiliou, V. (2012). The role of hyperosmotic stress in 80 inflammation and disease. Biomolecular Concepts, 3(4), 345–364. https://doi.org/https://doi.org/10.1515/bmc-2012-0001 Brown, A. J., Goldsworthy, S. M., Barnes, A. A., Eilert, M. M., Tcheang, L., Daniels, D., … Dowell, S. J. (2003). The orphan G protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. Journal of Biological Chemistry, 278(13), 11312–11319. https://doi.org/10.1074/jbc.M211609200 Brown, G. C., & Neher, J. J. (2014). Microglial phagocytosis of live neurons. Nature Reviews Neuroscience, 15(4), 209–216. https://doi.org/10.1038/nrn3710 Bryan, N. S., & Grisham, M. B. (2007). Methods to detect nitric oxide and its metabolites in biological samples. Free Radical Biology and Medicine, 43(5), 645–657. https://doi.org/https://doi.org/10.1016/j.freeradbiomed.2007.04.026 Calabrese, V., Mancuso, C., Calvani, M., Rizzarelli, E., Butterfield, D. A., & Giuffrida Stella, A. M. (2007). Nitric oxide in the central nervous system: neuroprotection versus neurotoxicity. Nature Reviews Neuroscience, 8(10), 766–775. https://doi.org/https://doi.org/10.1038/nrn2214 Cashman, J. R., & Zhang, J. (2006). Human flavin-containing monooxygenases. Annual Review of Pharmacology and Toxicology, 46(1), 65–100. https://doi.org/10.1146/annurev.pharmtox.46.120604.141043 Chen, X.-M., Chen, H.-S., Xu, M.-J., & Shen, J.-G. (2012). Targeting reactive nitrogen species: a promising therapeutic strategy for cerebral ischemia-reperfusion injury. Acta Pharmacologica Sinica, 34, 67–77. https://doi.org/10.1038/aps.2012.82 Cho, S. S., Reddy, G., Straub, J. E., & Thirumalai, D. (2011). Entropic stabilization of proteins by TMAO. Journal of Physical Chemistry B, 115(45), 13401–13407. https://doi.org/10.1021/jp207289b Cox, M. A., Jackson, J., Stanton, M., Rojas-Triana, A., Bober, L., Laverty, M., … Jenh, C.-H. (2009). Short-chain fatty acids act as antiinflammatory mediators by regulating prostaglandin E(2) and cytokines. World Journal of Gastroenterology, 15(44), 5549–5557. https://doi.org/10.3748/wjg.15.5549 Cryan, J. F., O’Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., … Dinan, T. G. (2019). The microbiota-gut-brain axis. Physiological Reviews, 99(4), 1877–2013. https://doi.org/10.1152/physrev.00018.2018 Cui, J., Yu, S., Li, Y., Li, P., & Liu, F. (2018). Direct binding of toll-like receptor 4 to ionotropic glutamate receptor N-methyl-D-aspartate subunit 1 induced by lipopolysaccharide in microglial cells N9 and EOC 20. International Journal of Molecular Medicine, 41(3), 1323–1330. https://doi.org/10.3892/ijmm.2017.3331 Cummings, J. H., Pomare, E. W., Branch, H. W. J., Naylor, C. P. E., & MacFarlane, G. T. (1987). Short chain fatty acids in human large intestine, portal, hepatic and venous blood. Gut, 28(10), 1221–1227. https://doi.org/10.1136/gut.28.10.1221 Dahlgren, C., & Karlsson, A. (1999). Respiratory burst in human neutrophils. Journal of 81 Immunological Methods, 232(1), 3–14. https://doi.org/https://doi.org/10.1016/S0022-1759(99)00146-5 Dalile, B., Van Oudenhove, L., Vervliet, B., & Verbeke, K. (2019). The role of short-chain fatty acids in microbiota–gut–brain communication. Nature Reviews Gastroenterology and Hepatology, 16(8), 461–478. https://doi.org/10.1038/s41575-019-0157-3 Del, D., Id, R., Zimetti, F., Caffarra, P., Tassotti, M., Bernini, F., … Zanotti, I. (2017). The gut microbial metabolite trimethylamine- N -oxide is present in human cerebrospinal fluid. Nutrients, 9(10), 1056. https://doi.org/10.3390/nu9101053 Ding, A. H., Nathan, C. F., & Stuehr, D. J. (1988). Release of reactive nitrogen intermediates and reactive oxygen intermediates from mouse peritoneal macrophages. Comparison of activating cytokines and evidence for independent production. The Journal of Immunology, 141(7), 2407 LP – 2412. Retrieved from http://www.jimmunol.org/content/141/7/2407.abstract Dugger, B. N., & Dickson, D. W. (2017). Pathology of neurodegenerative diseases. Cold Spring Harbor Perspectives in Biology, 9(7), a028035. https://doi.org/10.1101/cshperspect.a028035 Ferrari, M., Fornasiero, M. C., & Isetta, A. M. (1990). MTT colorimetric assay for testing macrophage cytotoxic activity in vitro. Journal of Immunological Methods, 131(2), 165–172. https://doi.org/https://doi.org/10.1016/0022-1759(90)90187-Z Fox, E. J. (2004). Immunopathology of multiple sclerosis. Neurology, 63(12 suppl 6), S3–S7. https://doi.org/10.1212/WNL.63.12_suppl_6.S3 Galatro, T. F., Holtman, I. R., Lerario, A. M., Vainchtein, I. D., Brouwer, N., Sola, P. R., … Eggen, B. J. L. (2017). Transcriptomic analysis of purified human cortical microglia reveals age-associated changes. Nature Neuroscience, 20(8), 1162–1171. https://doi.org/10.1038/nn.4597 Galloway, D. A., Phillips, A. E. M., Owen, D. R. J., & Moore, C. S. (2019). Phagocytosis in the Brain: Homeostasis and Disease . Frontiers in Immunology . Retrieved from https://www.frontiersin.org/article/10.3389/fimmu.2019.00790 Gao, H., Sun, Y., Wu, Y., Luan, B., Wang, Y., Qu, B., & Pei, G. (2004). Identification of β-arrestin2 as a G protein-coupled receptor-stimulated regulator of NF-кB pathways. Molecular Cell, 14(3), 303–317. https://doi.org/10.1016/S1097-2765(04)00216-3 Gerlier, D., & Thomasset, N. (1986). Use of MTT colorimetric assay to measure cell activation. Journal of Immunological Methods, 94(1), 57–63. https://doi.org/https://doi.org/10.1016/0022-1759(86)90215-2 Guo, Y., Logan, H. L., Glueck, D. H., & Muller, K. E. (2013). Selecting a sample size for studies with repeated measures. BMC Medical Research Methodology, 13(1), 100. https://doi.org/10.1186/1471-2288-13-100 Hanisch, U.-K., & Kettenmann, H. (2007). Microglia: Active sensor and versatile effector 82 cells in the normal and pathologic brain. Nature Neuroscience, 10(11), 1387–1394. https://doi.org/10.1038/nn1997 Hanisch, U.-K., & Quirion, R. (1995). Interleukin-2 as a neuroregulatory cytokine. NeuroImmune Biology, 21(3), 246–284. https://doi.org/10.1016/S1567-7443(07)10008-9 Hashimoto, K., Fukushima, T., Shimizu, E., Okada, S. I., Komatsu, N., Okamura, N., … Iyo, M. (2004). Possible role of D-serine in the pathophysiology of Alzheimer’s disease. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 28(2), 385–388. https://doi.org/10.1016/j.pnpbp.2003.11.009 Henn, A., Lund, S., Hedtjärn, M., Schrattenholz, A., Pörzgen, P., & Leist, M. (2009). The suitability of BV2 cells as alternative model system for primary microglia cultures or for animal experiments examining brain inflammation. Altex. https://doi.org/10.14573/altex.2009.2.83 Horvath, R. J., Nutile-McMenemy, N., Alkaitis, M. S., & DeLeo, J. A. (2008). Differential migration, LPS-induced cytokine, chemokine, and NO expression in immortalized BV-2 and HAPI cell lines and primary microglial cultures. Journal of Neurochemistry, 107(2), 557–569. https://doi.org/10.1111/j.1471-4159.2008.05633.x Huuskonen, J., Suuronen, T., Nuutinen, T., Kyrylenko, S., & Salminen, A. (2004). Regulation of microglial inflammatory response by sodium butyrate and short-chain fatty acids. British Journal of Pharmacology, 141(5), 874–880. https://doi.org/10.1038/sj.bjp.0705682 Ignarro, L. J., Cirino, G., Casini, A., & Napoli, C. (1999). Nitric oxide as a signaling molecule in the vascular system: An overview. Journal of Cardiovascular Pharmacology, 34(6), 879–886. https://doi.org/10.1097/00005344-199912000-00016 Jessen, K. R. (2004). Glial cells. International Journal of Biochemistry and Cell Biology, 36(10), 1861–1867. https://doi.org/10.1016/j.biocel.2004.02.023 Ji, J., Shu, D., Zheng, M., Wang, J., Luo, C., Wang, Y., … Qu, H. (2016). Microbial metabolite butyrate facilitates M2 macrophage polarization and function. Scientific Reports, 6, 1–10. https://doi.org/10.1038/srep24838 Jung, Y. J., & Chung, W. S. (2018). Phagocytic roles of glial cells in healthy and diseased brains. Biomolecules and Therapeutics, 26(4), 350–357. https://doi.org/10.4062/biomolther.2017.133 Kaindl, A. M., Degos, V., Gouadon, E., Chhor, V., Ali, C., Vivien, D., … Mantz, J. (2012). Activation of Microglial N-Methyl-D- Aspartate Receptors Triggers Inflammation and Neuronal Cell Death in the Developing and Mature Brain. https://doi.org/10.1002/ana.23626 Kawase, T., Nagasawa, M., Ikeda, H., Yasuo, S., Koga, Y., & Furuse, M. (2017). Gut microbiota of mice putatively modifies amino acid metabolism in the host brain. 83 British Journal of Nutrition, 117(6), 775–783. https://doi.org/10.1017/S0007114517000678 Kelley, J. L., Ozment, T. R., Li, C., Schweitzer, J. B., & Williams, D. L. (2014). Scavenger receptor-A (CD204): A two-edged sword in health and disease. Critical Reviews in Immunology, 34(3), 241–261. https://doi.org/10.1615/CritRevImmunol.2014010267 Kelm, M. (1999). Nitric oxide metabolism and breakdown. Biochimica et Biophysica Acta (BBA) - Bioenergetics, 1411(2), 273–289. https://doi.org/https://doi.org/10.1016/S0005-2728(99)00020-1 Kim, S., Kim, J. H., Park, B. O., & Kwak, Y. S. (2014). Perspectives on the therapeutic potential of short-chain fatty acid receptors. BMB Reports, 47(3), 173–178. https://doi.org/10.5483/BMBRep.2014.47.3.272 King, E., O’Brien, J. T., Donaghy, P., Morris, C., Barnett, N., Olsen, K., … Thomas, A. J. (2018). Peripheral inflammation in prodromal Alzheimer’s and Lewy body dementias. Journal of Neurology, Neurosurgery and Psychiatry, 89(4), 339–345. https://doi.org/10.1136/jnnp-2017-317134 Klegeris, A., Bissonnette, C. J., & McGeer, P. L. (2005). Modulation of human microglia and THP-1 cell toxicity by cytokines endogenous to the nervous system. Neurobiology of Aging, 26(5), 673–682. https://doi.org/10.1016/j.neurobiolaging.2004.06.012 Kobayashi, Y., Sugahara, H., Shimada, K., Mitsuyama, E., Kuhara, T., Yasuoka, A., … Xiao, J. Z. (2017). Therapeutic potential of Bifidobacterium breve strain A1 for preventing cognitive impairment in Alzheimer’s disease. Scientific Reports, 7(1), 1–10. https://doi.org/10.1038/s41598-017-13368-2 Kraft, A. D., & Harry, G. J. (2011). Features of Microglia and Neuroinflammation Relevant to Environmental Exposure and Neurotoxicity. Int. J. Environ. Res. Public Health, 8, 2980–3018. https://doi.org/10.3390/ijerph8072980 Ktsoyan, Z. A., Mkrtchyan, M. S., Zakharyan, M. K., Mnatsakanyan, A. A., Arakelova, K. A., Gevorgyan, Z. U., … Aminov, R. I. (2016). Systemic concentrations of short chain fatty acids are elevated in salmonellosis and exacerbation of familial mediterranean fever. Frontiers in Microbiology, 7, 776. https://doi.org/10.3389/fmicb.2016.00776 Kurynina, A. V., Erokhina, M. V., Makarevich, O. A., Sysoeva, V. Y., Lepekha, L. N., Kuznetsov, S. A., & Onishchenko, G. E. (2018). Plasticity of human THP–1 cell phagocytic activity during macrophagic differentiation. Biochemistry (Moscow), 83(3), 200–214. https://doi.org/10.1134/S0006297918030021 Le Poul, E., Loison, C., Struyf, S., Springael, J. Y., Lannoy, V., Decobecq, M. E., … Detheux, M. (2003). Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. Journal of Biological Chemistry, 278(28), 25481–25489. https://doi.org/10.1074/jbc.M301403200 84 Lee, S. U., In, H. J., Kwon, M. S., Park, B., Jo, M., Kim, M.-O., … Kim, S. (2013). β-Arrestin 2 mediates G protein-coupled receptor 43 signals to nuclear factor-κB. Biological and Pharmaceutical Bulletin, 36(11), 1754–1759. https://doi.org/10.1248/bpb.b13-00312 Leitner, G. R., Wenzel, T. J., Marshall, N., Gates, E. J., & Klegeris, A. (2019). Targeting toll-like receptor 4 to modulate neuroinflammation in central nervous system disorders. Expert Opinion on Therapeutic Targets, 23(10), 865–882. https://doi.org/10.1080/14728222.2019.1676416 Levy, R., Rotrosen, D., Nagauker, O., Leto, T. L., & Malech, H. L. (1990). Induction of the respiratory burst in HL-60 cells. Correlation of function and protein expression. Journal of immunology (Vol. 145). Li, D., Ke, Y., Zhan, R., Liu, C., Zhao, M., Zeng, A., … Hong, H. (2018). Trimethylamine-N-oxide promotes brain aging and cognitive impairment in mice. Aging Cell, 17(4), 1–13. https://doi.org/10.1111/acel.12768 Li, M., van Esch, B. C. A. M., Wagenaar, G. T. M., Garssen, J., Folkerts, G., & Henricks, P. A. J. (2018). Pro- and anti-inflammatory effects of short chain fatty acids on immune and endothelial cells. European Journal of Pharmacology, 831, 52–59. https://doi.org/10.1016/j.ejphar.2018.05.003 Lin, C.-H., Chiu, C.-C., Huang, C.-H., Yang, H.-T., & Lane, H.-Y. (2019). pLG72 levels increase in early phase of Alzheimer’s disease but decrease in late phase. Scientific Reports, 9(1), 1–9. https://doi.org/10.1038/s41598-019-49522-1 Liu, Y., Peterson, D. A., Kimura, H., & Schubert, D. (1997). Mechanism of Cellular 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) Reduction. Journal of Neurochemistry, 69(2), 581–593. https://doi.org/10.1046/j.1471-4159.1997.69020581.x Lu, S. C. (2013). Glutathione synthesis. Biochimica et Biophysica Acta - General Subjects. https://doi.org/10.1016/j.bbagen.2012.09.008 Ma, G., Pan, B., Chen, Y., Guo, C., Zhao, M., Zheng, L., & Chen, B. (2017). Trimethylamine N-oxide in atherogenesis: impairing endothelial self-repair capacity and enhancing monocyte adhesion. Bioscience Reports, 37(2). https://doi.org/10.1042/BSR20160244 Ma, L., Hu, L., Feng, X., & Wang, S. (2018). Nitrate and nitrite in health and disease. Aging and Disease, 9(5), 938–945. https://doi.org/10.14336/AD.2017.1207 MacKay, M. A. B., Kravtsenyuk, M., Thomas, R., Mitchell, N. D., Dursun, S. M., & Baker, G. B. (2019). D-serine: Potential therapeutic agent and/or biomarker in schizophrenia and depression? Frontiers in Psychiatry, 10(FEB), 18–23. https://doi.org/10.3389/fpsyt.2019.00025 Madeira, C., Lourenco, M., Vargas-Lopes, C., Suemoto, C., Brandão, C., Reis, T., … Panizzutti, R. (2015). D-serine levels in Alzheimer’s disease: Implications for novel biomarker development. Translational Psychiatry, 5(5), e561. 85 https://doi.org/10.1038/tp.2015.52 Magnotta, V. A., Heo, H. Y., Dlouhy, B. J., Dahdaleh, N. S., Follmer, R. L., Thedens, D. R., … Wemmie, J. A. (2012). Detecting activity-evoked pH changes in human brain. Proceedings of the National Academy of Sciences of the United States of America, 109(21), 8270–8273. https://doi.org/10.1073/pnas.1205902109 Miki, Y., Ono, K., Hata, S., Suzuki, T., Kumamoto, H., & Sasano, H. (2012). The advantages of co-culture over mono cell culture in simulating in vivo environment. The Journal of Steroid Biochemistry and Molecular Biology, 131(3–5), 68–75. https://doi.org/10.1016/j.jsbmb.2011.12.004 Miller, R. F. (2004). D-serine as a glial modulator of nerve cells. Glia, 47(3), 275–283. https://doi.org/10.1002/glia.20073 Millet, L. J., & Gillette, M. U. (2012). Over a century of neuron culture: From the hanging drop to microfluidic devices. Yale Journal of Biology and Medicine, 85(4), 501–521. Mills, S. W., Montgomery, S. H., & Morck, D. W. (2006). Evaluation of the effects of short-chain fatty acids and extracellular pH on bovine neutrophil function in vitro. American Journal of Veterinary Research, 67(11), 1901–1907. https://doi.org/10.2460/ajvr.67.11.1901 Miranda, K. M., Espey, M. G., & Wink, D. A. (2001). A rapid, simple spectrophotometric method for simultaneous detection of nitrate and nitrite. Nitric Oxide - Biology and Chemistry, 5(1), 62–71. https://doi.org/10.1006/niox.2000.0319 Montesinos Guevara, C., & Mani, A. R. (2016). The role of D-serine in peripheral tissues. European Journal of Pharmacology, 780, 216–223. https://doi.org/10.1016/j.ejphar.2016.03.054 Morgan, M. J., & Liu, Z. (2011). Crosstalk of reactive oxygen species and NF-κB signaling. Cell Research, 21(1), 103–115. https://doi.org/10.1038/cr.2010.178 Morris, Z. S., & Golan, D. E. (2011). Principles of pharmacology: The pathophysiologic basis of drug therapy. In D. E. Golan, A. H. Tashjian, Jr., E. J. Armstrong, & A. W. Armstrong (Eds.) (3rd ed., pp. 2–16). Philadelphia, PA: Lippincott Williams & Wilkens. Mowry, E. M., & Glenn, J. D. (2018). The dynamics of the gut microbiome in multiple sclerosis in relation to disease. Neurologic Clinics, 36(1), 185–196. https://doi.org/10.1016/j.ncl.2017.08.008 Nastasi, C., Candela, M., Bonefeld, C. M., Geisler, C., Hansen, M., Krejsgaard, T., … Woetmann, A. (2015). The effect of short-chain fatty acids on human monocyte-derived dendritic cells. Scientific Reports, 5(1), 16148. https://doi.org/10.1038/srep16148 Obara, M., Szeliga, M., & Albrecht, J. (2008). Regulation of pH in the mammalian central nervous system under normal and pathological coditions: Facts and hypotheses. Neurochemistry International, 52(6), 905–919. https://doi.org/10.1016/j.neuint.2007.10.015 86 Orser, B. A., Bertlik, M., Wang, L.-Y., & MacDonald, J. F. (1995). Inhibition by propofol (2,6 di-isopropylphenol) of the N-methyl-D-aspartate subtype of glutamate receptor in cultured hippocampal neurones. British Journal of Pharmacology, 116(2), 1761–1768. https://doi.org/10.1111/j.1476-5381.1995.tb16660.x Påhlman, S., Mamaeva, S., Meyerson, G., Mattsson, M. E., Bjelfman, C., Ortoft, E., & Hammerling, U. (1990). Human neuroblastoma cells in culture: a model for neuronal cell differentiation and function. Acta Physiologica Scandinavica. Supplementum, 592, 25–37. Pan, C., Kumar, C., Bohl, S., Klingmueller, U., & Mann, M. (2009). Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions. Molecular and Cellular Proteomics, 8(3), 443–450. https://doi.org/10.1074/mcp.M800258-MCP200 Pekny, M., & Pekna, M. (2014). Astrocyte Reactivity and Reactive Astrogliosis: Costs and Benefits. Physiological Reviews, 94(4), 1077–1098. https://doi.org/10.1152/physrev.00041.2013 Pekny, M., & Pekna, M. (2016). Reactive gliosis in the pathogenesis of CNS diseases. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, 1862(3), 483–491. https://doi.org/https://doi.org/10.1016/j.bbadis.2015.11.014 Pouteau, E., Meirim, I., Métairon, S., & Fay, L.-B. (2001). Acetate, propionate and butyrate in plasma: determination of the concentration and isotopic enrichment by gas chromatography/mass spectrometry with positive chemical ionization. Journal of Mass Spectrometry, 36(7), 798–805. https://doi.org/10.1002/jms.181 Regier, M. C., Maccoux, L. J., Weinberger, E. M., Regehr, K. J., Berry, S. M., Beebe, D. J., & Alarid, E. T. (2016). Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments. Biomedical Microdevices, 18(4), 70. https://doi.org/10.1007/s10544-016-0083-x Ross, S. H., & Cantrell, D. A. (2018). Signaling and function of interleukin-2 in T lymphocytes. Annual Review of Immunology, 36(1), 411–433. https://doi.org/10.1146/annurev-immunol-042617-053352 Saab, A. S., & Nave, K. A. (2017). Myelin dynamics: protecting and shaping neuronal functions. Current Opinion in Neurobiology, 47, 104–112. https://doi.org/10.1016/j.conb.2017.09.013 Sakamoto, S., Putalun, W., Vimolmangkang, S., Phoolcharoen, W., Shoyama, Y., Tanaka, H., & Morimoto, S. (2018). Enzyme-linked immunosorbent assay for the quantitative/qualitative analysis of plant secondary metabolites. Journal of Natural Medicines, 72(1), 32–42. https://doi.org/10.1007/s11418-017-1144-z Sampson, T. R., Debelius, J. W., Thron, T., Janssen, S., Shastri, G. G., Ilhan, Z. E., … Mazmanian, S. K. (2016). Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease. Cell, 167(6), 1469-1480.e12. https://doi.org/10.1016/j.cell.2016.11.018 87 Sankowski, B., Księżarczyk, K., Raćkowska, E., Szlufik, S., Koziorowski, D., & Giebułtowicz, J. (2020). Higher cerebrospinal fluid to plasma ratio of p-cresol sulfate and indoxyl sulfate in patients with Parkinson’s disease. Clinica Chimica Acta, 501, 165–173. https://doi.org/10.1016/j.cca.2019.10.038 Sawada, M., Suzumura, A., & Marunouchi, T. (1995). Induction of functional interleukin‐2 receptor in mouse microglia. Journal of Neurochemistry, 64(5), 1973–1979. https://doi.org/10.1046/j.1471-4159.1995.64051973.x Schell, M. J. (2004). The N-methyl D-aspartate receptor glycine site and D-serine metabolism: An evolutionary perspective. Philosophical Transactions of the Royal Society B: Biological Sciences, 359(1446), 943–964. https://doi.org/10.1098/rstb.2003.1399 Sharif, O., Bolshakov, V. N., Raines, S., Newham, P., & Perkins, N. D. (2007). Transcriptional profiling of the LPS induced NF-κB response in macrophages. BMC Immunology, 8(1). https://doi.org/10.1186/1471-2172-8-1 Singh, G. B., Zhang, Y., Boini, K. M., & Koka, S. (2019). High mobility group box 1 mediates TMAO-induced endothelial dysfunction. International Journal of Molecular Sciences, 20(14), 3570. https://doi.org/10.3390/ijms20143570 Smith, M. J., Crowther, R. A., & Goedert, M. (2000). The natural osmolyte trimethylamine N-oxide (TMAO) restores the ability of mutant tau to promote microtubule assembly. FEBS Letters, 484(3), 265–270. https://doi.org/10.1016/S0014-5793(00)02169-4 Sousa, A. M. M., Meyer, K. A., Santpere, G., Gulden, F. O., & Sestan, N. (2017). Evolution of the human nervous system function, structure, and development. Cell, 170(2), 226–247. https://doi.org/10.1016/j.cell.2017.06.036. Spielman, L. J., Little, J. P., & Klegeris, A. (2014). Inflammation and insulin/IGF-1 resistance as the possible link between obesity and neurodegeneration. Journal of Neuroimmunology, 273(1), 8–21. https://doi.org/10.1016/j.jneuroim.2014.06.004 SRR transcriptomics data - The Human Protein Atlas. (n.d.). Retrieved April 22, 2020, from https://www.proteinatlas.org/ENSG00000167720-SRR/summary/rna Stephenson, J., Nutma, E., van der Valk, P., & Amor, S. (2018). Inflammation in CNS neurodegenerative diseases. Immunology, 154(2), 204–219. https://doi.org/10.1111/imm.12922 Streit, W. J., Walter, S. A., & Pennell, N. A. (1999). Reactive microgliosis. Progress in Neurobiology, 57(6), 563–581. https://doi.org/https://doi.org/10.1016/S0301-0082(98)00069-0 Sulahian, T. H., Imrich, A., DeLoid, G., Winkler, A. R., & Kobzik, L. (2008). Signaling pathways required for macrophage scavenger receptor-mediated phagocytosis: Analysis by scanning cytometry. Respiratory Research, 9, 1–15. https://doi.org/10.1186/1465-9921-9-59 88 Sun, M. F., & Shen, Y. Q. (2018). Dysbiosis of gut microbiota and microbial metabolites in Parkinson’s Disease. Ageing Research Reviews, 45(February), 53–61. https://doi.org/10.1016/j.arr.2018.04.004 Sundqvist, K. G. (2018, May 3). T cell co-stimulation: Inhibition of immunosuppression? Frontiers in Immunology. Frontiers Media S.A. https://doi.org/10.3389/fimmu.2018.00974 Tan, A. H., Mahadeva, S., Thalha, A. M., Gibson, P. R., Kiew, C. K., Yeat, C. M., … Lim, S. Y. (2014). Small intestinal bacterial overgrowth in Parkinson’s disease. Parkinsonism and Related Disorders, 20(5), 535–540. https://doi.org/10.1016/j.parkreldis.2014.02.019 Tan, J., McKenzie, C., Potamitis, M., Thorburn, A. N., Mackay, C. R., & Macia, L. (2014). The role of short-chain fatty acids in health and disease. In Advances in Immunology (Vol. 121, pp. 91–119). Academic Press Inc. https://doi.org/10.1016/B978-0-12-800100-4.00003-9 Thomas, D. C. (2017). The phagocyte respiratory burst: Historical perspectives and recent advances. Immunology Letters, 192, 88–96. https://doi.org/https://doi.org/10.1016/j.imlet.2017.08.016 Topping, D. L., & Clifton, P. M. (2001). Short-chain fatty acids and human colonic function: Roles of resistant starch and nonstarch polysaccharides. Physiological Reviews, 81(3), 1031–1064. https://doi.org/10.1152/physrev.2001.81.3.1031 Tseng, H. C., & Graves, D. J. (1998). Natural methylamine osmolytes, trimethylamine N-oxide and betaine, increase tau-induced polymerization of microtubules. Biochemical and Biophysical Research Communications, 250(3), 726–730. https://doi.org/10.1006/bbrc.1998.9382 Tsuchiya, S., Yamabe, M., Yamaguchi, Y., Kobayashi, Y., Konno, T., & Tada, K. (1980). Establishment and characterization of a human acute monocytic leukemia cell line (THP‐1). International Journal of Cancer, 26(2), 171–176. https://doi.org/10.1002/ijc.2910260208 Ufnal, M., Zadlo, A., & Ostaszewski, R. (2015). TMAO: A small molecule of great expectations. Nutrition, 31(11–12), 1317–1323. https://doi.org/10.1016/j.nut.2015.05.006 Uhlen, M., Fagerberg, L., Hallstrom, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., … Ponten, F. (2015). Tissue-based map of the human proteome. Science, 347(6220), 1260419. https://doi.org/10.1126/science.1260419 Van Horn, M., Sild, M., & Ruthazer, E. (2013). D-serine as a gliotransmitter and its roles in brain development and disease. Frontiers in Cellular Neuroscience. https://doi.org/10.3389/fncel.2013.00039 Vernetti, L., Gough, A., Baetz, N., Blutt, S., Broughman, J. R., Brown, J. A., … Taylor, D. L. (2017). Functional coupling of human microphysiology systems: Intestine, liver, kidney proximal tubule, blood-brain barrier and skeletal muscle. Scientific 89 Reports, 7(1), 42296. https://doi.org/10.1038/srep42296 Vincent, V. A. M., Tilders, F. J. H., & Van Dam, A. M. (1998). Production, regulation and role of nitric oxide in glial cells. Mediators of Inflammation. https://doi.org/10.1080/09629359890929 Vincent, V. A., Tilders, F. J., & Van Dam, A. M. (1998). Production, regulation and role of nitric oxide in glial cells. Mediators of Inflammation, 7(4), 239–255. https://doi.org/10.1080/09629359890929 Vogt, N. M., Kerby, R. L., Dill-McFarland, K. A., Harding, S. J., Merluzzi, A. P., Johnson, S. C., … Rey, F. E. (2017). Gut microbiome alterations in Alzheimer’s disease. Scientific Reports, 7(1), 1–11. https://doi.org/10.1038/s41598-017-13601-y Vogt, N. M., Romano, K. A., Darst, B. F., Engelman, C. D., Johnson, S. C., Carlsson, C. M., … Rey, F. E. (2018). The gut microbiota-derived metabolite trimethylamine N-oxide is elevated in Alzheimer’s disease. Alzheimer’s Research and Therapy, 10(1), 1–8. https://doi.org/10.1186/s13195-018-0451-2 Wakida, N. M., Cruz, G. M. S., Ro, C. C., Moncada, E. G., Khatibzadeh, N., Flanagan, L. A., & Berns, M. W. (2018). Phagocytic response of astrocytes to damaged neighboring cells. PLOS ONE, 13(4), e0196153. Retrieved from https://doi.org/10.1371/journal.pone.0196153 Walker, K. R., & Tesco, G. (2013). Molecular mechanisms of cognitive dysfunction following traumatic brain injury. Frontiers in Aging Neuroscience, 5, 29. https://doi.org/10.3389/fnagi.2013.00029 Wang, X., Perez, E., Liu, R., Yan, L.-J., Mallet, R. T., & Yang, S.-H. (2007). Pyruvate protects mitochondria from oxidative stress in human neuroblastoma SK-N-SH cells. Brain Research, 1132, 1–9. https://doi.org/10.1016/j.brainres.2006.11.032 Wang, Z., Klipfell, E., Bennett, B. J., Koeth, R., Levison, B. S., DuGar, B., … Hazen, S. L. (2011). Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature, 472(7341), 57–63. https://doi.org/10.1038/nature09922 Waters, R. S., Perry, J. S. A., Han, S., Bielekova, B., & Gedeon, T. (2018). The effects of interleukin-2 on immune response regulation. Mathematical Medicine and Biology : A Journal of the IMA, 35(1), 79. https://doi.org/10.1093/IMAMMB/DQW021 Wenzel, T. J., Gates, E. J., Ranger, A. L., & Klegeris, A. (2020). Short-chain fatty acids (SCFAs) alone or in combination regulate select immune functions of microglia-like cells. Molecular and Cellular Neuroscience, 105, 103493. https://doi.org/10.1016/j.mcn.2020.103493 Wilkinson, B. L., & Landreth, G. E. (2006). The microglial NADPH oxidase complex as a source of oxidative stress in Alzheimer’s disease. Journal of Neuroinflammation, 3(1), 30. https://doi.org/10.1186/1742-2094-3-30 Wilkinson, K., & El Khoury, J. (2012). Microglial scavenger receptors and their roles in the pathogenesis of Alzheimer’s disease. International Journal of Alzheimer’s Disease, 2012, 489456. https://doi.org/10.1155/2012/489456 90 Woo, M.-S., Yang, J., Beltran, C., & Cho, S. (2016). Cell surface CD36 protein in Mmonocyte/macrophage contributes to phagocytosis during the resolution phase of ischemic stroke in mice. The Journal of Biological Chemistry, 291(45), 23654–23661. https://doi.org/10.1074/jbc.M116.750018 Wu, Q., Zhao, Y., Chen, X., Zhu, M., & Miao, C. (2018). Propofol attenuates BV2 microglia inflammation via NMDA receptor inhibition. Canadian Journal of Physiology and Pharmacology, 96(3), 241–248. https://doi.org/10.1139/cjpp-2017-0243 Wu, S.-Z., Bodles, A. M., Porter, M. M., Griffin, W. S. T., Basile, A. S., & Barger, S. W. (2004). Induction of serine racemase expression and D-serine release from microglia by amyloid β-peptide. Journal of Neuroinflammation, 1(1), 2. https://doi.org/10.1186/1742-2094-1-2 Wyss-Coray, T., & Rogers, J. (2012). Inflammation in Alzheimer disease-a brief review of the basic science and clinical literature. Cold Spring Harbor Perspectives in Medicine, 2(1), a006346. https://doi.org/10.1101/cshperspect.a006346 Zhao, G., Liu, J.-F., Nyman, M., Jan˚, J., & Jönsson, J. (2007). Determination of short-chain fatty acids in serum by hollow fiber supported liquid membrane extraction coupled with gas chromatography. Journal of Chromatography B, 846(1–2), 202–208. https://doi.org/10.1016/j.jchromb.2006.09.027 Zou, Q., Bennion, B. J., Daggett, V., & Murphy, K. P. (2002). The molecular mechanism of stabilization of proteins by TMAO and its ability to counteract the effects of urea. Journal of the American Chemical Society, 124(7), 1192–1202. https://doi.org/10.1021/ja004206b
Thesis/Dissertation
eng
Biochemistry and Molecular Biology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Signaling between gut microbiota and brain immune cells
Text