Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Involvement of regulatory non-coding RNA in motility, biofilm formation, and adaptive antibiotic resistance… Taylor, Patrick Kyle 2014

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2014_september_taylor_patrick.pdf [ 1.08MB ]
Metadata
JSON: 24-1.0167460.json
JSON-LD: 24-1.0167460-ld.json
RDF/XML (Pretty): 24-1.0167460-rdf.xml
RDF/JSON: 24-1.0167460-rdf.json
Turtle: 24-1.0167460-turtle.txt
N-Triples: 24-1.0167460-rdf-ntriples.txt
Original Record: 24-1.0167460-source.json
Full Text
24-1.0167460-fulltext.txt
Citation
24-1.0167460.ris

Full Text

INVOLVEMENT OF REGULATORY NON-CODING RNA IN MOTILITY, BIOFILM FORMATION AND ADAPTIVE RESISTANCE IN PSEUDOMONAS AERUGINOSA by Patrick Kyle Taylor B.Sc, The University of British Columbia, 2009 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Microbiology and Immunology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May, 2014 © Patrick Kyle Taylor, 2014 ii  Abstract Small, non-coding RNA (sRNA) transcripts are emerging as a major mechanism for regulating translational expression in bacteria. Since the discovery of 6S RNA acting to regulate translation of RNA polymerases in Escherichia coli, our understanding of sRNA regulation of translation has expanded, and sRNAs are now known to have a broad range of functions in bacteria ranging from metabolic regulation to virulence determination. The Gram-negative bacterium Pseudomonas aeruginosa is commonly found in natural microbiomes, and is also an opportunistic pathogen as it causes disease in immunocompromised individuals. P. aeruginosa displays a high level of resistance to numerous clinically relevant antibiotics, and is capable of developing biofilms on multiple surfaces in hospital environments. P. aeruginosa is also capable of swarming which is a complex motility involving rhamnolipid surface whetting agents, flagella and type IV pili. This work investigated the involvement of 32 sRNA species in adaptive resistance to antibiotics, swarming motility, and biofilm formation in P. aeruginosa. Unique expression profiles under conditions of swarming and biofilm formation for 27 previously uncharacterized sRNAs were found. It was also found that the sRNAs prrF1, prrF2 and phrS are involved in swarming motility and/or biofilm formation. Compared to free-swimming, planktonic growth expression of the prrF gene loci was up-regulated 163- and 13-fold under swarming and biofilm conditions, respectively, and mutants lacking the entire locus demonstrated modest decreases in swarming while prrF1 mutants demonstrated increased biofilm formation. A transposon insertion mutant in phrS in P. aeruginosa PA14 wildtype displayed a deficiency in swarming motility and biofilm formation. phrS was also found to be involved in the development of adaptive resistance to polymyxin B by impacting on the translation of a lipid A modification operon. Together this work demonstrates that sRNA regulation plays a critical role in swarming motility, biofilm formation and the development of adaptive resistance in P. aeruginosa.  iii  Preface Data from Chapter 2 is being included in a manuscript by our collaborators in Fiona Brinkman’s Laboratory at Simon Fraser University for publication. I was responsible for producing and analyzing all the RT-qPCR data in Chapter 2.  Parts of Chapter 3 are being including in a manuscript in preparation in Robert E.W. Hancock’s laboratory. I was responsible for carrying out all experiments and analysis of data in Chapter 3  Chapter 4 is being prepared as a manuscript for publication. Instruction in producing the complemented phrS strain was provided by Manjeet Bains but the work was done by me.  Biofilm flow-cell assays and confocal microscopy imaging was done by César de la Fuente-Núñez and Fany Reffuveille. All other studies were done by me.   iv  Table of Contents Abstract ........................................................................................................................................... ii Preface............................................................................................................................................ iii Table of Contents ........................................................................................................................... iv List of Tables ................................................................................................................................ vii List of Figures .............................................................................................................................. viii List of Abbreviations ..................................................................................................................... ix Acknowledgements ......................................................................................................................... x 1 Introduction ............................................................................................................................. 1 1.1 Pseudomonas aeruginosa ................................................................................................. 1 1.2 Swarming Motility ........................................................................................................... 1 1.3 Biofilms ............................................................................................................................ 2 1.4 Antibiotic Resistance in Biofilms .................................................................................... 4 1.5 Non-coding RNA ............................................................................................................. 5 1.6 Goals of This Study .......................................................................................................... 7 2 Confirmation and Differential Regulation of Novel sRNA Species in Pseudomonas aeruginosa Under Conditions of Biofilm Formation and Swarming Motility ............................... 9 2.1 Introduction ...................................................................................................................... 9 2.2 Materials and Methods ................................................................................................... 10 2.2.1 Bacterial Strains and Growth Conditions ............................................................... 10 2.2.2 RNA Isolation and cDNA Synthesis....................................................................... 11 2.2.3 Primer Design and Semi-Quantitative PCR ............................................................ 11 2.3 Results ............................................................................................................................ 14 2.4 Discussion ...................................................................................................................... 17 3 The Role of the prrF Locus in Pseudomonas aeruginosa .................................................... 19 3.1 Introduction .................................................................................................................... 19 v  3.2 Materials and Methods ................................................................................................... 20 3.2.1 Bacterial Strains and Growth Conditions ............................................................... 20 3.2.2 Primer Design and Semi-Quantitative PCR ............................................................ 21 3.2.3 Pyocyanin and Pyoverdin Secretion ....................................................................... 22 3.3 Results ............................................................................................................................ 22 3.3.1 Deletion Mutants of the prrF Locus had a Distinct Pyoverdin and Pyocyanin Secretion Phenotype from PAO1 Wildtype. ......................................................................... 22 3.3.2 Deletion Mutants in prrF Showed Unique Swarming Phenotypes in PAO1. ........ 24 3.4 Discussion ...................................................................................................................... 27 4 Role of the phrS sRNA in Pseudomonas aeruginosa ........................................................... 30 4.1 Introduction .................................................................................................................... 30 4.2 Materials and Methods ................................................................................................... 31 4.2.1 Bacterial Strains and Growth Conditions ............................................................... 31 4.2.2 Biofilm Development.............................................................................................. 32 4.2.3 Swarming Motility .................................................................................................. 32 4.2.4 Transformation of Pseudomonas aeruginosa ......................................................... 32 4.2.5 Semi-Quantitative Analysis of phrS Effects on Two-Component Systems and the Lipid A Modification Operon in Pseudomonas aeruginosa ................................................. 33 4.3 Results ............................................................................................................................ 33 4.3.1 The sRNA phrS had a Polymyxin B Resistance Phenotype Distinct from Its Known Transcriptional Regulator and a Known Downstream Effector Gene .................................. 33 4.3.2 The sRNA phrS Displayed Reduced Swarming Motility and Increased Biofilm Formation Compared to PA14 Wildtype .............................................................................. 37 4.4 Discussion ...................................................................................................................... 40 5 Concluding Remarks ............................................................................................................. 43 5.1 Introduction .................................................................................................................... 43 vi  5.2 Expression of Novel sRNA Species ............................................................................... 43 5.3 The prrF Locus sRNAs .................................................................................................. 44 5.4 The phrS sRNA .............................................................................................................. 45 5.5 Future Research Directions ............................................................................................ 45 References ..................................................................................................................................... 48    vii  List of Tables Table 2.1 Primers used in this study (F: forward; R: reverse). .................................................... 12 Table 2.2 Small RNA species detected by RT-qPCR to have differential expression in biofilms and during swarming motility. ...................................................................................................... 15 Table.3.1 PAO1 strains and plasmids used .................................................................................. 21 Table 3.2 Primers used in this study ............................................................................................ 21 Table 3.3 Fold change in prrF locus expression during swarming motility and biofilm formation........................................................................................................................................................ 25 Table 4.1 Strains and plasmids used ............................................................................................ 31 Table 4.2 Primers used in this study ............................................................................................ 33 Table 4.3 MICs of the phrS mutant compared to WT, and mutants in an upstream regulator anr and a downstream target pqsR under conditions of differing oxygen availability. ...................... 34 Table 4.4 Lack of change in arnBCADTEF operon gene expression in a phrS mutant relative to that in PA14 WT. Also shown is the increased expression of the arn operon in a cprR mutant used as a positive control (reference) for transcriptional regulation of the arn operon. ............... 36 Table 4.5 Genes containing complementarity with phrS. ............................................................ 41    viii  List of Figures Figure 3.1. Pyoverdin secretion by prrF locus mutant strains. .................................................... 23 Figure 3.2 Pyocyanin secretion of prrF locus mutant strains compared to PAO1 WT. .............. 24 Figure 3.3 Swarming phenotype of prrF locus mutants compared to PAO1 WT (H103). ......... 26 Figure 3.4 Crystal violet staining of prrF mutant strains. ........................................................... 27 Figure 4.1 Increased resistance of the phrS mutant, cf. the WT, to polymyxin B (2 µg/ml). ...... 35 Figure 4.2 Luminescence of lux reporter linked to the promoter and 5' untranslated region of the arn operon upstream of a promoterless luxCDABE cassette. ....................................................... 37 Figure 4.3 Lack of impact of a phrS mutant on twitching (A) and swimming (B) motility ........ 38 Figure 4.4 Inhibition of swarming motility by the phrS mutant .................................................. 38 Figure 4.5 Flow-cell analysis of the impact of the phrS mutant .................................................. 39    ix  List of Abbreviations 5’ UTR – 5’ untranslated region AMP – ampicillin BM2 – basal medium 2 bp – base pairs CAA – casamino acid medium CAZ – ceftazidime CF – Cystic Fibrosis CRISPRs – clustered regularly interspaced short palindromic repeats EPS – exopolysaccharide GEN – gentamicin IND – indolicidin IR – intergenic region KAN – kanamycin LB – Luria broth LPS – lipopolysaccharide nt – nucleotides OD – optical density PIP – piperacillin PXB – polymyxin B QS – quorum sensing RBS – ribosomal binding site RT-qPCR – real-time, semi-quantitative polymerase chain reaction sRNA – small RNA T3SS – type III secretion system T6SS – type VI secretion system TCS – two component regulatory system TET – tetracycline TOB – tobramycin UTR – Untranslated region WT – Wildtype    x  Acknowledgements I would like to thank my supervisor, Dr. Bob Hancock, for providing me the opportunity to begin a career in science. Under his mentorship I have developed the strong foundation of skills required to pursue a scientific career. Drs. Steven Hallam and Michael Murphy, while acting as members of my committee, have given me both encouragement and insightful thought, for which I am greatly appreciative. I would also like to thank my colleagues in the Hancock lab for their assistance while at work and their friendship both in and outside of the lab. I would like thank my fiancée Steph Halmhofer for her never ending support. She has taken the good times and the bad with me while I ventured through graduate studies. Finally, I could not have done this without the support of family, most notably my grandfather, Laird McCallum. He is no longer here to see me pursue a career in science but he was a constant supporter of my efforts to do so and his wisdom and out-look on life that I have taken to heart, will continue to motivate me for the rest of my scientific career.  1  1 Introduction 1.1 Pseudomonas aeruginosa Pseudomonas aeruginosa is a Gram-negative bacterium commonly found in aqueous environments, but it also is an opportunistic pathogen of humans, causing diverse and severe infections in ranging from acute burn and lung infections, to chronic colonization of the lungs of individuals afflicted with the genetic disease Cystic Fibrosis (CF) (Lyczak et al, 2000). P. aeruginosa is capable of colonizing diverse environments in part due to its ability to utilize aerobic and anaerobic metabolic pathways, its mechanisms of intrinsic, acquired, and adaptive antimicrobial resistance, and its expression of a multitude of virulence factors. P. aeruginosa has a large genome of more than 6.2 Mbp encoding >5500 genes (Stover et al, 2000). This is ~30% larger than other phylogenetically closely related pathogenic Proteobacteria, such as Escherichia coli and Salmonella enterica (Blattner et al, 1997; Holt, et al 2008; McClelland et al, 2001). Nearly a tenth of the P. aeruginosa genome contains genes encoding regulatory proteins (Stover et al, 2000). In addition, the P. aeruginosa genome has numerous large intergenic regions without annotated genes that have classically been considered to include ‘junk’ DNA. However, recent research revealed many genes within intergenic regions that encode regulatory RNAs (Dötsch et al, 2012; Gómez-Lozano et al, 2012; Wurtzel et al, 2012). 1.2 Swarming Motility P. aeruginosa is capable of swarming, a highly organized form of surface motility requiring flagella, type IV pili, and rhamnolipid surfactants. Under conditions of intermediate viscosity (0.4-0.6% agar) and a weak nitrogen source (amino acids), P. aeruginosa will swarm outwards from a central inoculation point, aligning longitudinally and moving in a concerted fashion, to form either a dendritic (PA14 strains) or starburst (PAO1 strains) pattern (Déziel et al, 2003; Köhler et al, 2000; Overhage et al, 2007). Swarming involves the dysregulation of 417 genes including the overexpression of a large number of virulence-related genes, including genes encoding the type III secretion system and its effectors, extracellular proteases, and iron transport systems (Overhage et al, 2008). In addition, swarming is dependent on the function of more than 230 genes that when mutated alter swarming (Leung et al, 2009). Thus, swarming is a highly complex social behaviour. The level of viscosity and amino acids as a nitrogen source, both of 2  which are required for swarming, resembles the conditions of mucosal surfaces (i.e., list an example). Therefore, swarming acts as an analog for the virulent state of P. aeruginosa when it is establishing infections in human hosts. 1.3 Biofilms Biofilms are structured multicellular consortia of bacteria embedded in a protective self-produced extracellular matrix (Friedman et al, 2004). P. aeruginosa readily forms biofilms on abiotic and biotic surfaces, including medical devices such as heart valves (causing endocarditis), prosthetic joint, catheters and stents, as well as patients with chronic infections such as individuals afflicted with the genetic disease of Cystic Fibrosis (Lindsay et al, 2006). The biofilm mode of growth is a major problem in hospital settings due to the exceptional (adaptive) resistance mechanisms of biofilms to antibiotics, antiseptics, disinfectants, and the immune system. Biofilms are up to one thousand-fold more resistant to antibiotics than their planktonic counterparts (Hoyle et al, 1991). Many characteristics of biofilms have been proposed to contribute to adaptive antibiotic resistance in biofilms and are discussed below. P. aeruginosa is a model organism for understanding biofilm development and provides a template for understanding how antibiotic resistance arises during biofilm growth. Biofilm development on solid substrates occurs in 5 major stages that complete the cycle from colonization of surfaces to dispersal. First, in a process mediated by flagella and/or type IV pili, free-swimming (planktonic) bacteria adhere to a solid surface (e.g. on a glass, plastic, metal, or tissue substratum) (O’Toole et al, 1998; Toutain et al, 2007). The second stage consists of several rounds of cell division and growth that lead to the formation of aggregates, also known as microcolonies (Sriramulu et al, 2005). Third, as the biofilm grows and matures, independent microcolonies grow together to form a mat, which is typically visible to the naked eye. Fourth, biofilms subsequently develop colonial structures at the microscopic level, which possess subpopulations of cells with separate physiologies. Bacterial biofilms are permeated by water channels allowing for flow of nutrients through the biofilm. Finally, the subsequent dispersal of single cells or small microcolonies from the biofilm enables the bacteria to move to a new location to initiate and propagate new biofilm colonies. A defining feature of a biofilm is the extracellular polymeric substance (EPS) matrix that provides a structural lattice interconnecting biofilm cells. EPS can be comprised of bacterial secreted components, including polysaccharides, extracellular DNA (eDNA), proteins, lipids, 3  and biosurfactants (Allesen-Holm et al, 2006; Barken et al, 2008; Klausen et al, 2003). The Pel and Psl polysaccharides are major contributors in P. aeruginosa biofilm formation (Jackson et al, 2004; Vasseur et al, 2005). Pel polysaccharide is a glucose-rich polymer while the Psl polysaccharide is a mannose-rich polymer. Both polysaccharides contribute to microcolony formation, during the initial stages of biofilm formation, subpopulation interactions, macrocolony formation in the later stages of biofilm formation, and eDNA release and distribution within the biofilm (Ma et al, 2009).  Extracellular DNA in a P. aeruginosa biofilm is generated by lysis of a subpopulation of the bacteria via a mechanism dependent on quorum sensing (QS), as well as flagella and type IV pili (Allesen-Holm et al, 20069). Microscopic investigations of flow chamber-grown P. aeruginosa biofilms stained with different DNA stains indicate that eDNA is located primarily in the stalks of mushroom-shaped multicellular structures (Allesen-Holm et al, 2006). DNAse-treatment dissolves mature biofilms formed by P. aeruginosa suggesting that eDNA is involved in cell-cell interconnection in young biofilms, with possible roles in initial attachment of bacterial cells (Whitchurch et al, 2002). The secretion of eDNA during early stages of growth might also be important for the survival of biofilms since it contributes to P. aeruginosa competition with other microbes and the development of adaptive resistance (Mulcahy et al, 2008).  The temporal and spatial development of biofilms is to some extent regulated by QS, a cell-cell communication mechanism that plays an important role in certain aspects of bacterial life, at high population densities, including virulence as well as biofilm formation (Davis et al, 1998; De Kievit et al, 2001). Prominent small molecules involved in QS of P. aeruginosa (and other bacteria) are acyl homoserine lactones. These molecules are freely diffusible into the environment and are very important for biofilm regulation, but are not the only quorum sensing molecules utilized by P. aeruginosa. In P. aeruginosa, QS for biofilm development involves 3 intertwined QS systems, the homoserine lactone-based LasRI and RhlRI systems and the Pseudomonas quinolone signal (PQS). When an appropriate bacterial density is reached, these molecules reach a threshold concentration in the cellular environment and are taken up by all cells in the vicinity, bind to their corresponding transcriptional regulators in the cell and result in coordinated multi-locus gene expression in the entire bacterial population. 4  1.4 Antibiotic Resistance in Biofilms P. aeruginosa cells in a biofilm state of growth are significantly more resistant to antimicrobial agents than are planktonic cells (Hoyle et al, 1991). This has been ascribed to a range of different factors including a complex array of adaptive gene expression changes, some of which influence antibiotic susceptibility, the low metabolic state of organisms deep within the biofilm, poor antibiotic penetration into the biofilm, and the higher concentration of extracellular antibiotic degrading enzymes. Of these the most intriguing involves adaptive changes in gene expression that accompany the switch to the biofilm mode of growth, which includes a range of genes that could be involved in determining biofilm resistance since they modulate resistance to one or more antibiotics. The Pseudomonas efflux pumps MexAB-OprM, MexCD-OprJ, MexEF-OprN, and MexXY-OprM expel multiple families of antimicrobial compounds, and have been proposed as a major cause of adaptive resistance during the biofilm mode of growth (Poole, 2001). Alterations to the permeability of the outer membrane via the PhoPQ and PmrAB pathways can be induced by divalent cation deficiency due to the high concentrations of extracellular polyanionic DNA in biofilms, resulting in tolerance to polymyxins and other cationic antimicrobial peptides (Mulcahy et al, 2008). The increasing accumulation of acquired mutations giving rise to antimicrobial resistance has been observed in the laboratory (Amini et al, 2011; Macia et al, 2011) and during the development of heterogeneous populations of P. aeruginosa in chronic lung infections (Wang et al, 2010; Xu et al, 1998), with the latter phenomenon being exacerbated by the development of mutants in mutator genes (Macia et al, 2011). Although it is often discussed, the effects of antimicrobial agents cannot be explained solely by an inability of compounds to penetrate the biofilm (Anderl et al, 2000), although the extracellular matrix possesses some ability to counter the effects of antimicrobials. For example the extracellular DNA present in the matrix has an overall anionic charge and has been shown to reduce the efficacy of positively charged antimicrobial agents including polymyxins and aminoglycosides (Kumon et al, 1994). Many antimicrobial agents penetrate reasonably well into biofilms, although certain nutrients such as oxygen might be limiting in the interior part of biofilms and create an anaerobic or microaerophilic environment (Borriello et al, 2004; Xu et al, 1998). The anaerobic environment within biofilms would impact directly on aminoglycoside antibiotic activity (Kindrachuk et al, 2011) due to decreased energy-dependent uptake (Hancock, 5  1981), as well as triggering changes in gene expression. Due to these and other changes brought about by the dense aggregation of bacteria within biofilms, such as limiting nutrient availability, bacteria deep within biofilms likely have reduced metabolic activity and lower rates of cell division than those closer to the surface of biofilms. Such cells in biofilms that survive antibiotic treatment due to non-mutational mechanisms have been termed persister cells. Persisters are proposed to be dormant cells that can survive antimicrobial treatments that kill the majority of their genetically identical siblings and thus represent a distinct category of adaptive resistance. Persister cells are considered to have entered an extremely slow-growing or non-growing physiological state (although the basis for this is unknown), which makes them insensitive or tolerant to the action of antimicrobial drugs. 1.5 Non-coding RNA Not all transcripts are utilized for protein translation. The roles of other so-called non-coding (i.e. non-translated) RNAs are varied, with diverse functions and unique mechanisms within the cell. The tRNAs and rRNAs have well characterized roles essential to mediating translation. There are also CRISPRs (clustered regularly interspaced short palindromic repeats) that have defensive roles in eliminating foreign gene expression through complementary binding to direct a cleavage enzyme, thus mitigating the effects of invasive phages and plasmids. A third major group of non-coding RNAs play a significant role in regulating translation within the cell and use evolutionarily distinct mechanisms. Our view of bacteria as a simple form of life on the planet is rapidly evolving as the complex life cycles and mechanisms of cellular signalling are being further elucidated. One of the most rapidly growing areas of research is the how non-coding RNAs are involved in regulating expression changes within a bacterial cell and add redundancy and integration to expression changes. At one level bacterial cells respond to environmental stimuli by altering a gene expression. Activation of gene expression creates mRNA transcripts, which then are translated into proteins that carry out various functions by mediating enzymatic reactions, thereby impacting on cell structure, or further regulating gene expression. Non-coding RNAs have come forward as a major mechanism that bacteria utilize for transcriptional and post-transcriptional regulation (Delihas et al, 2001). Various mnemonics have been used previously to describe non-coding, regulatory RNA species in bacteria such as non-coding RNA (ncRNA), non-protein coding RNA (npcRNA), small non-messenger RNA (snmRNA), untranslated RNA (utRNA), 6  and small RNA (sRNA). These mnemonics are largely synonymous with one another in bacterial species and, for simplicity; sRNA will hereafter be used to refer to non-coding, regulatory RNAs. This work specifically focused on a sub-type of sRNAs that act to regulate levels of translation of target mRNAs and thereby are an additional mechanism of regulation within the cell as well as a mechanism of signal integration between networks (Brencic et al, 2009; Sonnleitner et al, 2008; Sonnleitner et al, 2011; Wilderman et al, 2004; Olgesby et al, 2010). Of sRNAs that act within the cell to regulate translational levels there are two-major classifications according to their respective mechanisms of action, cis- and trans-encoded sRNAs. Cis-sRNAs are encoded on the opposing genomic strand to their target genes and have a high-degree of sequence complementarity, thereby silencing translation of complementary mRNA targets and even promoting mRNA degradation (Sonnleitner et al, 2011; Storz et al, 2011). Trans-encoded sRNAs have a larger array of confirmed mechanisms of action than cis-encoded sRNAs, and are the focus of this work. The gene architecture of trans-RNAs is unique from that of cis-RNAs (Biesel et al, 2010; Sonnleitner et al, 2011; Storz et al, 2011). Trans-encoded RNAs often do not have identifiable promoter regions and do not commonly have any identifiable ribosome binding site (RBS), which has made the identification of sRNA genes difficult and elusive until the recent development of second generation sequencing methods as explained below (Sonnleitner et al, 2008; Gómez-Lozano et al, 2012; Wurtzel et al, 2012). Trans-RNAs largely rely upon RNA binding proteins to directly or indirectly carry out regulatory functions. One well-characterized system involves the interactions of sRNAs RsmY and RsmZ with a small protein RsmA. In this system RsmA is an RNA binding protein with high affinity for target mRNA transcripts. RsmY and RsmZ sRNAs have higher affinity for RsmA than any target mRNA transcript (González et al, 2008; Brencic et al, 2009). When RsmY and RsmZ are expressed, RsmA is sequestered and target mRNA transcripts of RsmA are then released, the RBS is exposed, and translation can occur. Another major mechanism of trans-encoded sRNAs involves an RNA binding chaperone protein, Hfq (Sonnleitner et al, 2008). Hfq is highly conserved in bacteria and has been known for a long time to contribute to RNA stability. Trans-sRNAs share very little complementarity with their target transcripts. Often there is only a 7-nucleotide “seeder” region of sequence complementarity with the 5’ untranslated region (UTR) of the target mRNA transcript around the 7  RBS (Biesel et al, 2010). This low level of sequence complementarity allows trans-encoded sRNAs significant flexibility in interacting with multiple different target mRNAs. In addition to interacting with the RBS of some target mRNAs to negatively regulate translation, some trans-encoded sRNAs act at regions of the 5’UTR of mRNAs to alter secondary structure and expose the RBS to allow translation to occur, thereby having a positive effect on regulation. Because trans-encoded sRNAs are often of considerable length, in the range of 50-400 nucleotides, a single sRNA can possess a large number of “seeder” regions that access a large array of different target transcripts, acting as a positive regulator for specific targets and as a negative regulator for others, consistent with the results obtained in this investigation. Because of this, sRNAs are emerging a central mechanism by which bacteria regulate intracellular signalling pathways and rapidly provide exceptionally precise responses to environmental stimuli. Until recently, determination of novel sRNA genes and subsequent study of functional roles was highly limited and biased towards sRNAs that had protein interaction partners or had a high degree of complementarity to target mRNAs. A method of protein precipitation and northern blotting termed RNomics was previously used to elucidate sRNAs in P. aeruginosa (Sonnleitner et al, 2008). More recent studies of sRNAs have made use of second generation RNA-Sequencing (RNA-Seq) methods for high-throughput analysis. RNA-Seq utilizes transcripts expressed from the genome (the transcriptome) as templates for sequencing by synthesis. RNA-Seq has thus provided a high-throughput method of identifying novel sRNA genes. Several studies utilizing RNA-Seq for the study of sRNAs have found that the P. aeruginosa genome encodes at least 170 sRNAs in intergenic regions (IR) (Dötsch et al, 2012; Gómez-Lozano et al, 2012; Wurtzel et al, 2012). 1.6 Goals of This Study Adaptive responses to stress in the environment, swarming motility, and biofilm formation are all complex behaviours in bacteria, and molecular and regulatory mechanisms are known to coordinate these activities. The participation of sRNA species in the regulation and coordination of these complex behaviours is poorly understood. Indeed, many studies have focused on quantifying the number of sRNAs encoded in the genome, but relatively few studies have investigated how these species impact on cells. Thus, very few sRNA species have been characterized to have roles such as in swarming motility and/or biofilm formation, and no studies have investigated the roles that sRNAs might play in adaptive resistance. Here I hypothesized 8  that trans-encoded sRNAs have a significant influence in regulating complex adaptive behaviours. I thus aimed to to demonstrate that certain sRNAs have a central role in regulating swarming motility, biofilm resistance, and adaptive resistance to antimicrobial agents. To achieve this aim a genetic approach was taken to determine expression profiles of sRNAs and the phenotypic effects of sRNA mutants under conditions of swarming and biofilm formation. In chapter 2, I examined the dysregulation of 32 sRNAs under conditions of swarming as well as biofilm formation. In chapter 3, deletion mutants of prrF locus sRNAs were used to investigate the effects of these sRNAs on swarming motility and biofilm formation. In chapter 4, a transposon insertion in phrS was used to investigate the effects of phrS on swarming motility, biofilm formation, and adaptive resistance to antimicrobial agents. The purpose of this work was thus to further our understanding of how sRNAs are involved in complex behaviours, such as swarming motility, biofilm formation, and adaptive resistance.   9  2 Confirmation and Differential Regulation of Novel sRNA Species in Pseudomonas aeruginosa Under Conditions of Biofilm Formation and Swarming Motility 2.1 Introduction A variety of studies have previously been undertaken to identify novel sRNAs and determine their functional roles within P. aeruginosa. The earliest studies investigating sRNAs in P. aeruginosa utilized pull-down co-precipitation techniques and sequencing of the single-stranded RNAs that associated with RNA-binding proteins in the cell (Brencic et al, 2009; Sonnleitner et al, 2008; Sonnleitner et al, 2009; Sonnleitner et al, 2011). The methods used in these studies built an initial understanding of the functional roles of sRNAs in P. aeruginosa, but required time intensive methods that were not exhaustive and were biased towards sRNAs that interacted strongly with RNA-binding proteins. More recent studies have sought to be more exhaustive in determining the identity and number of sRNAs encoded in the P. aeruginosa genome with minimal bias through the use of the second-generation sequencing technology, i.e., RNA-Seq. The number of identified sRNA genes encoded in the P. aeruginosa genome has increased from an initial 40 to approximately 170 within a matter of years through increasingly intensive RNA-Seq analysis (Gómez-Lozano et al, 2012; González et al; 2008; Wurtzel et al, 2012). The variability between studies in the number of sRNA genes in the P. aeruginosa genome is based on the limitations of computational methods of analysis of whether an sRNA is indeed transcribed (given difficulties in identifying their promoters), and whether any sRNA is untranslated or instead is an mRNA expressing a small protein. An example of this can be seen in two recent studies using RNA-Seq analysis wherein Gómez-Lozano et al reported 513 novel sRNA transcripts expressed in P. aeruginosa, while another study by Wurtzel et al reported only 165 novel sRNA transcripts. Unfortunately, these studies performed very little follow up to confirm that the reported sRNAs are actually transcribed within cells. In this work, it was hypothesized that sRNA transcripts would have unique expression profiles under different growth conditions of P. aeruginosa cultures, and that novel sRNAs could be confirmed as genuine transcripts by studying the changes in expression under different growth conditions. Recent studies have investigated the expression profiles of sRNAs in P. aeruginosa but only using sRNAs that were well characterized in the literature (Dötsch et al, 2012). Collaborator Fiona Brinkman’s group at Simon Fraser University undertook a study to analyze the P. aeruginosa transcriptome in a PAO1 strain. At the time, Erin Gill of the Brinkman group 10  utilized a conservative manual curation of RNA-Seq data to initially identify 31 sRNA transcripts in P. aeruginosa, in addition to the 39 well-characterized sRNAs. The general method of RNA-Seq sequences short stretches (50 or 75 bp) derived as cDNAs from RNAs transcribed from the genome, to generate sequence-reads which are then mapped back onto the genome to determine the sequence of genome-wide transcripts at single-nucleotide resolution (Croucher et al, 2010). Determination of the threshold that represents genuine transcript expression from the genome vs. noise in the data was calculated and genes with read counts below this level were eliminated.  Automated curation methods utilize software to quantitatively determine any reads that surpass the cut-off within a single dataset and were not previously described as genes based on a lack of an identifiable promoter. Manual curation involves looking manually for features consistent with non-coding RNAs especially the lack of a recognizable ribosomal binding site in sequences identified by RNA-Seq. For this work transcripts were considered to be putative sRNAs were determined on the basis of being between 50-500 nt in length and lacking a ribosomal binding site and often an identifiable promoter. There have been no characterized sRNAs in prokaryotes that fall outside these definitions. Here we tested the expression of these sRNAs under swarming and biofilm formation conditions P. aeruginosa strain PAO1. Multicellular biofilms and cultures moving in a coordinated fashion in swarming motility require rapid and tightly controlled responses. The regulatory actions of sRNAs would provide one possible mechanism to enable cells to rapidly respond under conditions of biofilm formation and swarming motility. Here I confirmed the expression of 28 of the sRNAs found by RNA-Seq methods and demonstrated that, for most of these, sRNA expression varied under conditions of swarming and biofilm formation in P. aeruginosa. 2.2 Materials and Methods 2.2.1 BACTERIAL STRAINS AND GROWTH CONDITIONS Control growth conditions used as a basis of comparison with biofilm and swarming motility used P. aeruginosa strain PAO1 from the UBC mini-Tn5-lux library grown overnight in Luria broth (LB) liquid media at 37 ºC. Cultures were sub-cultured 1/100 into Basal Medium 2 (BM2, 7 mM (NH4)2SO4, 40 mM K2HPO4, 22 mM KH2PO4, 0.5 mM MgSO4, 10 µM FeSO4, and 22 mM glucose at pH 7), and grown to the mid-logarithmic growth phase at 37 ºC with shaking. Biofilms were grown by sub-culturing overnight cultures into fresh BM2-glucose liquid medium 11  and grown at room temperature, ~23oC, for 48 hrs without shaking. Cells growing as biofilms at the air-liquid interface were collected into fresh BM2 medium without glucose and biofilms were physically disrupted. Swarming was performed by inoculating 1 µl of mid-logarithmic phase culture grown in BM2-glucose onto swarming agar plates. Swarming agar plates consisted of 0.5% agar with BM2-glucose, except that 0.5 % casamino acids were used as a complex nitrogen source in place of (NH4)2SO4. Swarming cultures were grown for 18 hrs and only colony growth at the ends of swarm “tendrils” were used for analysis. 2.2.2 RNA ISOLATION AND CDNA SYNTHESIS Whole cell RNA was isolated from P. aeruginosa strain PAO1 using Qiagen QIAprep® Spin Miniprep Kit (27106) according to the manufacturer’s instructions. Isolated RNA preparations were treated with Ambion® Turbo DNA-freeTM (AM1907) by adding one tenth volume of 10X Turbo DNaseTM buffer, 0.5 µl Turbo DNaseTM, and 1 µl Ambion® SUPERaseTM inhibitor (AM2694) to isolated RNA and incubating for 1 hour. Another 0.5 µl of Turbo DNaseTM was then added and the mixture incubated for a further hour at 37ºC. Inactivation reagent was added to one tenth the volume of the reaction mixture, and incubated for 20 min at 37ºC before centrifuging the mixture at 10 000 x g in a microfuge. Treated RNA was extracted in the supernatant and checked for purity by spectrophotometric OD260/280 ratios as well as by PCR using primers for the house-keeping gene, rpsL. RNA was stored at -80ºC. Synthesis of cDNA for use in real-time semi-quantitative PCR (RT-qPCR) was performed by using 1 µg RNA added to a final volume of 15 µl reaction mixture containing final concentrations of 50 mM Tris-HCl, 75 mM KCl, 3 mM MgCl2, 10 µM dithiothreitol (DTT), 500 µM triphosphate deoxyribonucleotides, with 0.75 µl InvitrogenTM SuperScriptTM II reverse transcriptase (18064-022), and 0.375 µl Ambion® SUPERaseTM inhibitor placed in a thermocycler programmed to run 1 hr at 37ºC, 3 hrs at 42ºC, and 10 min at 72ºC. Yield was calculated by spectrophotometric A260/230 ratios and cDNA was stored at -20ºC.  2.2.3 PRIMER DESIGN AND SEMI-QUANTITATIVE PCR For detection of novel sRNAs previously characterized by Gill et al, primers for RT-qPCR were designed with the NCBI primer-BLAST server using default parameters and ordered from Invitrogen (Table 2.1).   12  Table 2.1 Primers used in this study (F: forward; R: reverse). Primer target  Direction Sequence PA0123.1 F CGTCGGGTTTCGGAAAAA R CCTGATTAGTTCTTTGGCTGACTCA PA0290.1 F CGCCAGAAAGGAAGCTGTAATAG R CTCCCGGCTGACGGG PA0296.1 F GGCCGTTTTCAGGGCAT R CCTTCGACGCGAGGTTTTT PA0314.1 F CGGGCTTCGCAGTGGA R TGCCTTCCGAATCAGGGA rsmY F CAGGAAGCGCCAAAGACAAT R TCCGTGCTACGCCACCA PA0667.1 F CGCTGCAACACCGCTG R AGAAAGCGCCGCCGTATTA PA0730.1 F AAATAGAGAGCGTCCGAAATCCT R TTCCTGCCCGGCCAAT PA0805.1 F TGGTATTGCGGGACGCC R ACTCTTCTGAAGCAATCCCCTG PA0958.1 F TCTTGTTGAGGTCGCTTCTCAA R CGGAACATGACATTTTTATTACAAGG PA1091.1 F AAAGCTCCGCCGGGAA R GCTCAGGTGCCCCAAGAAT PA1156.1 F GACTGTGAGTGCCTCCCTGG R AGGTATTGTGTTCGACGGCAA PA2461.1 F TGAACCACGTGAAGCGGATA R AGGGAGGCTCCGCGAG PA2461.2 F ACAGAACTTCAAAAGCCAGACTTTC R GGGCGGCTAGAGTCTACGC PA2461.3 F CCCCTTCGTCCTCGTGC R CCTAGCCAGATTCGACTAACATTCA PA2633.1 F CCTCGGCCTCCACCGT R TTCCAGTCGCAATCTCGTCA PA2952.1 F CAATACGGCAAAAGGGTGGT R TGAATTCTTTGGAAGCCTGATAGA PA3159.1 F CCGAGCTTCGAATACGGCT R TGTGCGAGAAGATGCCAAGT PA3299.1 F ACCGCTCATGGCGGC R GCGCCTAATAGCCCTGGG PA3514.1 F CGCGGAGAATTACCGAGGA R ACCGCGTGAAAACCGCT PA3580.1 F AAACCGGAGGGTCGTTTTT 13  Primer target  Direction Sequence R TTCACAAAGGAATGCTGTCAA PA4055.1 F GGATCTTGCGGGCGC R TCCGGATAAAGAGAGAACGGG PA4539.1 F TTCTCCGCCTTGAAACCG R GCAGGGAAAAGAAGCCGATA PA4639.1 F ATTAGCGCTTGAAACAGCCC R AGGCTCTGGTCATGAGGTATCC PA4656.1 F CGTTTTCGACTCAGCCAAGG R GCTGGCGCCGTTCACTAA PA4726.3 F CGCCCGAGAGGTCCTGATA R GCGTTGCTCAAACAGGACG PA5078.1 F AAAAGAATGCCTGTTTCCAGTCA R TGCCCCCTGGTCTTCCA PA5304.1 F TAGGAAGAGGCAGGCAGAAA R CCCCTAATTGTCCGGTTTTT PA5304.1 F ACCCGCTGCATCCCG R TTCTGATATAAAGCTGCGCTCTTTT Samples of cDNA were diluted 1/100 for RT-qPCR on an Applied Biosystems® 7300 Real Time PCR System programmed for a dissociation stage of 95ºC for 15 s and an elongation stage of 60ºC for 30 s repeated for 40 cycles. Expression changes were analysed using the comparative Ct method as per the following equations: ∆Cttest=Cttest-Cthousekeeping gene, rpsL); ∆Ctcontrol=Ctcontrol-CtrpsL; ∆∆Ct=∆Cttest-∆Ctcontrol; FC=2-∆∆Ct, where Ct indicates the cycle number threshold at which PCR amplification was exponential for all detectable samples, ΔCttest was for cells grown under the conditions of biofilm or swarming, while ΔCtcontrol was determined for planktonic mid-logarithmic phase growth of P. aeruginosa PAO1 in rich media, and FC represented positive fold changes in expression of ΔCttest compared to ΔCtcontrol. Negative fold changes or down-regulation was represented on a linear scale by taking the negative inverse of FC.   14  2.3 Results  Previous studies have utilized predominately computational methods to automate searches for sRNAs within the genome of P. aeruginosa (Gómez-Lozano et al, 2012). Unfortunately, these searches are only as good as the underlying assumptions guiding them, and as sRNAs have limited sequence features to enable recognition, it is difficult to definitively assign function. Here a conservative approach for confirmation of novel sRNAs by RT-qPCR was taken by studying differential expression of novel sRNAs found by manual analysis of RNA-Seq sequencing data from P. aeruginosa strain PAO1. Despite the high stringency cutoffs used by Dr. Gill, four of the sRNAs studied here, PA0296.1, PA0667.1, PA2952.1, and PA3299.1 were not previously identified by Gomez-Lozano et al (2012), despite their low stringency analysis. Conversely Wurtzel et al (2012) who used intermediate stringency did not observe 15 of these sRNAs (although 2 of these have no homologs in strain PA14 in which they performed their studies).  Here I examined the expression of a list of 31 sRNAs identified by manual curation of RNA-Seq data by Erin Gill. Four sRNAs found by the Brinkman group’s analysis of RNA-Seq data could not be amplified by RT-qPCR. RsmY acted as positive control since its expression profile has been previously characterized under biofilm conditions in P. aeruginosa strain PA14 (Dötsch et al, 2012), and the observed 4-fold upregulation agreed with the literature data (Table 2.2).   15  Table 2.2 Small RNA species detected by RT-qPCR to have differential expression in biofilms and during swarming motility. Name Complementarity Identity Gomez-Lozano et al, 2012 Identity Wurtzel et al, 2012 Fold change in biofilms Fold change in swarming motility PA0123.1 None pant15 Not identified 1.0±0.1 10.6±4.4 PA0290.1 pilW, plcH pant37 PA14sr_012 -8.5±-2.2 1.1±2.1 PA0296.1 rne Not identified P1 -2.5±-0.8 1.0±1.2 PA0314.1 None pant42 Not identified -4.5±-5.6 1.0±1.3 rsmY None rsmY rsmY 4.1±2.3 10.6±7.8 PA0667.1 PA3505, PA2897, PA0690 Not identified Not identified -3.4±-1.9 1.0±1.4 PA0730.1 None pant80 PA14sr_122 -3.0±-1.4 44.0±2.5 PA0805.1 None pant89 PA14sr_119/PA14sr_120 -4.8±-3.8 -5.0±-3.1 PA0958.1 None pant103 PA14sr_112 -6.1±-1.7 2.4±1.5 PA1091.1 PA0588 pant119 Not identified 2.8±0.7 4.5±3.2 PA1156.1 PA1123, phuR pant125 PA14sr_105 1.1±0.1 1.3±0.1 PA2461.1 PA2460, PA2458 pant225 PA14sr_076 -8.0±-1.2 -3.4±-1.0 PA2461.2 PA2460, PA2458 pant226 PA14sr_077 -5.4±-1.6 1.3±0.1 PA2461.3 PA5134 pant233 Not identified -2.0±-0.1 3.4±1.0 PA2633.1 PA3672, recJ, nrdG, PA3522, PA3949, PA5325 pant235 PA14sr_067 4.9±0.8 7.6±5.5 PA2952.1 PA4629 Not identified PA14sr_061 -2.0±-0.1 2.3±1.7 PA3159.1 None pant292 no ortholog in PA14 -1.8±-0.5 2.7±1.1 PA3299.1 PA0690, cyoB Not identified Not identified 2.0±4.5 1.3±2.3 PA3514.1 tagF1 pant326 no ortholog in PA14 10.2±4.7 1.0±0.4 PA3580.1 None pant337 no reads -4.0±-0.2 1.2±1.7 PA4055.1 PA2728, mfd, chpA, PA3641 pant373 Not identified -2.9±-1.4 -2.1±-2.9 PA4539.1 wzz pant415 Not identified 1.5±2.5 10.4±3.3 PA4639.1 PA5156, PA2502, PA4510, aruI, PA0475, PA0558, PA1025 pant428 PA14sr_139 4.7±5.2 n/a PA4656.1 PA2038, PA3517, PA2152, pslE, PA2472, PA2750 pant430 Not identified -3.6±1.9 3.5±1.1 PA4726.3 ispA, hepA, PA2018, PA3461 pant439 PA14sr_141 -5.3±-3.4 1.0±3.4 PA5078.1 PA0312, kds pant465 Not identified -5.7±-4.6 2.9±1.5 PA5304.1 None pant487 Not identified -3.5±-3.4 4.8±0.5 PA5316.2 PA1302, PA2933, gcp, PA0241, PA0364, pilJ, hsiC2, PA2325, PA3037, rnhB, pchF, recD, algP pant488 PA14sr_154 -6.8±-3.8 -1.5±-3.2 16   In total, 27 of the 28 sRNAs tested by RT-qPCR were modestly to considerably dysregulated under biofilm growth and/or swarming motility conditions. There were 25 sRNAs dysregulated in biofilms and 15 sRNAs were significantly dysregulated under swarming conditions (Table 2.2). Various patterns of regulation were observed including inverse relationships between sRNA expression under swarming and biofilm conditions and coordinate sRNA expression profiles consistent with other studies demonstrating regulators that coordinately or oppositely regulate swarming and biofilm formation (Overhage et al, 2008; Yeung et al, 2009). In this work the sRNA RsmY was used as a positive control as it is among the best-studied sRNA species in P. aeruginosa and its expression has previously been studied under biofilm conditions. In comparison to planktonic PA14, RsmY expression was upregulated 4.5-fold, on average, during biofilm growth (Dötsch et al, 2012). In this regard, I observed that RsmY was upregulated by 4-fold in PAO1 biofilms compared to planktonic growth, which is consistent with published results. Neither RsmY, nor any other sRNA, has been previously investigated in the context of swarming motility. It was found here that RsmY is also highly upregulated under swarming conditions with a 10-fold increase in expression compared to planktonic cultures of PAO1.   Under biofilm formation and swarming conditions, significant differences in expression were observed for all but one, PA1156.1, of the novel sRNA genes tested. Four of the sRNAs found in the initial RNA-Seq analysis by the Brinkman group failed to be amplified by PCR, suggesting that either these were incorrectly identified and are not expressed as transcripts, they had expression profiles too small to be detected under the growth conditions used, or that the selected primers were ineffective in amplifying the transcripts. The regions, which could not be amplified through PCR, mapped to the coordinates of 68836-69271, 99801-100048, 707395-707685, and 830970-831031. There was no consistent pattern of length or sequence homologies that helped to explain why other sRNA genes could readily be amplified while these four could not. One sRNA species, PA4639.1, was unable to be amplified in any of 3 biological repeats under conditions of swarming motility, but was readily detectable and was significantly upregulated in biofilms. There were nine sRNA genes (PA0290.1, PA0296.1, PA0314.1, PA0667.1, PA2461.2, PA3299.1, PA3514.1, PA3580.1, and PA4726.3) that were dysregulated only under biofilm conditions, while only PA0123.1 was dysregulated uniquely under swarming motility conditions. Seven sRNAs (PA0730.1, PA0958.1, PA2461.3, PA2952.1, PA3159.1, PA4656.1, and 17  PA5078.1) were reciprocally regulated, being upregulated under swarming conditions, and 8 (rsmY, PA0805.1, PA1091.1, PA2461.1, PA2633.1, PA4055.1, PA4539.1, and PA5316.2) were coordinately regulated. These data are thus consistent with sRNAs being involved in the fine control of complex adaptations. 2.4 Discussion This work demonstrated that nearly all of the tested sRNAs were expressed under normal lab growth conditions. In comparison to planktonic PAO1 cultures in log phase growth, most sRNAs demonstrated significantly altered expression profiles during biofilm formation, swarming motility, or both. This implies that sRNAs are intimately involved in the fine regulation of complex adaptations. However, it is entirely possible that no novel targets would be found by proteomic analysis due to the moderate effects that an sRNA may have on its targets as well as the limit of resolution of proteomics for poorly expressed targets. In addition, determination of direct RNA-binding interactions of mRNA targets by sRNAs could be performed by electro-mobility shift assays after incubating RNA in vitro for novel interactions but require knowledge of the target RNA. To fully study mechanisms of action and interaction partners of sRNAs interdisciplinary approaches will be required.  Knockout and overexpression of the sRNA combined with proteomic and transcriptomic investigations will aid in enhancing our understanding of the impact, mechanisms of action and regulomes of sRNAs. Other studies have recently been undertaken to identify the sRNAs expressed in P. aeruginosa, usually by RNA-Seq combined with bioinformatic analysis (Dötsch et al 2012; Gómez-Lozano et al, 2012; González et al, 2008; Wurtzel et al, 2012). The advantages of using RNA-Seq have allowed for high-throughput data generation under different bacterial growth conditions. However, the quality of these analyses depend on the depth of sequencing and minimal read count used to determine if a sequence is actually expressed, the accuracy of algorithms used to determine if the expressed sequence is actually translated, and particularly the growth conditions utilized since not all sRNAs would be expected to be transcribed under each growth condition utilized. The expression of putative sRNAs has been rarely confirmed using PCR. Finding the target genes of sRNAs is not simple since only a small portion of any given sRNA is actually involved in binding to targets, and even then chaperone proteins often enhance binding affinity and/or presentation to target mRNAs. Complementarity of the sRNAs to genes in the PAO1 genome was used to determine potential target mRNAs upon which the novel 18  sRNAs might act. It was considered that any observed similarity in the functional roles of genes that contained sequence homologies to a given sRNA might inform as to the functions of these sRNAs. In addition, complementarity to other genes within the genome was used to determine whether there were any specific sequences that might emerge as conserved target interaction regions.  Because relatively short stretches of nucleotides are used as interaction regions with target sequences, complementarity was decided by any stretch of homology larger than 7 nt that had an E-value of less than 1 when using BLAST. Discontiguous MegaBLAST was used to allow for more divergent short stretches of homology, and it was initially considered that an indecipherable number of return hits would be found using such broad search strategies. However, most sRNAs returned only small numbers of potential hits and only sRNAs PA2633.1, PA4639.1, PA4656.1, and PA5316.2 had more than 4 hits within in the genome. Overall the majority of novel sRNAs (19 of 27) had some complementarity in the genome. Of the 61 genes found that revealed some complementarity with an sRNA, only 23 had known functions with the remaining genes all coding for hypothetical proteins. For any single sRNA there was no common function for the genes such as all being part of the same metabolic or signalling pathway, or involved in particular biological functions such as motility. Taken together, these findings indicate that using sequence complementarity alone is insufficient to enable accurate elucidation of the targets of sRNAs. Indeed it seems likely that advanced proteomic methods or pulldowns with different combinations of sRNAs and chaperone proteins is needed to elucidate targets. However, it is clear from this work that sRNAs are themselves regulated and possess distinct expression patterns between different modes of growth such as swarming motility and biofilms. This is consistent with the suggestion that sRNAs might themselves have specific regulatory roles.  19  3 The Role of the prrF Locus in Pseudomonas aeruginosa 3.1 Introduction Iron is an essential nutrient for bacteria. However, the availability of biologically useful ferrous (Fe2+) sources is highly limited in the environment. Because of this, bacteria have tightly regulated mechanisms for iron uptake and metabolism in the cell and have sophisticated uptake systems for the acquisition of iron, e.g. using siderophores. Pyoverdin is one of the major iron siderophores of Pseudomonas aeruginosa. Iron homeostasis within the cell and siderophore biosynthesis is largely controlled by the transcriptional regulator Fur (Ferric uptake regulator). Recent work has found that Fur also exerts a regulatory effect by controlling the expression of sRNA species (Davis et al, 2005; Massé et al, 2005; Mey et al, 2002; Wilderman et al, 2004). Fur is in an active repressor conformation when complexed with divalent Fe2+ ions under conditions of excess iron within the cell. In the active state, Fur binds target promoters and represses the transcription of iron acquisition genes. When iron becomes limiting within the cell, Fe2+ ions will dissociate from Fur rendering it inactive (Leoni et al, 1996; Prince, 1991; Vasil et al, 1999). While the mechanism of Fur regulation has been well characterized, it has also been observed that Fur can both positively and negatively regulate certain target genes (Ochsner et al, 2002). This dual activity of Fur was resolved by characterization of sRNA species regulated by Fur (Davis et al, 2005; Massé et al, 2005; Mey et al, 2002; Wilderman et al, 2004).  In P. aeruginosa, Fur has been confirmed to regulate two tandem sRNA genes, prrF1 and prrF2 [Pseudomonas regulatory RNA involving iron (Fe)] (Wilderman et al, 2004). Evidence suggests that within the prrF locus there is potentially a third sRNA, prrH containing both individual sRNAs, which is also regulated by Fur (Oglesby-Sherrouse, 2010). The prrF1 and prrF2 sRNAs are nearly identical in sequence and regulation. These sRNAs are considered to be largely redundant with regard to functional roles within the cell and proposed to act as repressors of translation of their target transcripts. The prrF sRNAs have previously been found to be involved in the production of Pseudomonas Quinolone Signal (PQS) for quorum sensing under iron-limiting conditions, providing a link between pathways for regulation of iron homeostasis and quorum sensing in P. aeruginosa (Oglesby et al, 2008). In Escherichia coli and Vibrio cholerae there is an sRNA, ryhB, that is regulated by Fur similar to the prrF sRNAs in P. aeruginosa, and is utilized to regulate iron homeostasis (Davis et al, 2005; Massé et al, 2005; Mey et al, 2002). The sRNA ryhB also has a role in regulating 20  virulence (Davis et al, 2005). Because RyhB has this role beyond strict maintenance of iron homeostasis,  I hypothesized that prrF1 and prrF2 might also be involved in regulating translational expression of targets for complex biological phenomena such as coordinated motility in swarm colonies and biofilm formation in P. aeruginosa.  3.2 Materials and Methods 3.2.1 BACTERIAL STRAINS AND GROWTH CONDITIONS For all experimental conditions, the P. aeruginosa strains indicated in Table 3.1 were grown overnight in LB liquid media at 37 ºC then sub-cultured by 1/100 dilution into BM2 glucose medium and grown to logarithmic growth phase. For sRNA gene expression changes under biofilm conditions, P. aeruginosa strains were inoculated in BM2-glucose medium and were incubated at 23oC for 48 hrs. For crystal violet staining of simple biofilms, bacteria were inoculated into BM2-glucose medium in 96-well microtitre plates and incubated at 37ºC without shaking for 24 hrs. Anaerobic biofilm growth conditions were set up similarly to aerobic conditions but within a sealed chamber that had atmospheric oxygen chemically removed using a BD BBLTM GasPakTM anaerobic system. Crystal violet staining was done by washing plates with de-ionized water and incubated with 0.1% [w/v] crystal violet for 20 minutes to stain adhered biofilm growth before rinsing again and solubilizing with 70% ethanol. The absorbance at 595 nm was recorded on a PowerwaveTM X340 Bio-tek Instruments®, Inc. for biofilm development. Agar plates for swarming motility studies consisted of BM2-glucose agar (0.5% [w/v]) lacking NH2SO4 and supplemented with 0.1% [w/v] casamino acids as a weak nitrogen source. Iron depleted swarming plates contained a final concentration of 150 µM of the iron chelator 2,2-dipyridyl in place of adding FeSO4. Swarming cultures were grown for 18 hrs and only colony growth at the ends of swarm “tendrils” were used for transcriptional analyses. Pyocyanin secretion studies were done in LB liquid media and Pyoverdin secretion studies were performed in casamino acid medium (CAA, 0.5 % casamino acids, 7 mM K2HPO4, and 0.1 mM MgSO4 at pH 7.2) (Mirleau, 2000; Baysse, 2002).   21  Table.3.1 PAO1 strains and plasmids used Strain or plasmid Genotype or characteristics Reference P. aeruginosa   WT Wild-type P. aeruginosa PAO1 strain H103 Stover et al, 2000 ΔprrF1 PAO1 deletion mutant of prrF1; GENR Wilderman et al, 2004 ΔprrF2 PAO1 deletion mutant of prrF2; GENR Wilderman et al, 2004 ΔprrF1-F2 (ΔprrH) PAO1 deletion mutant of entire prrF locus; GENR Wilderman et al, 2004; Olgesby-Sherrouse et al, 2010 prrF1+ ΔprrF1 pVLT31::prrF1; GENR, TETR; a complemented isolate Wilderman et al, 2004  prrF2+ ΔprrF2 pVLT31::prrF2; GENR, TETR; a complemented isolate Wilderman et al, 2004 prrF1-F2+/prrH+ ΔprrF1-F2 pVLT31::prrF1-F2; GENR, TETR; a complemented isolate Wilderman et al, 2004; Olgesby-Sherrouse et al, 2010 Plasmid   pVLT31 Parent pMMB207 with TETR de Lorenzo et al, 1993 3.2.2 PRIMER DESIGN AND SEMI-QUANTITATIVE PCR Primers for the detection of prrF gene loci expression (Table 3.2) were designed using the NCBI primer-BLAST server at default settings. For the detection of the PrrH sRNA the forward primer of PrrF1 was used with the reverse primer of PrrF2. Whole cell RNA was isolated using a Qiagen QIAprep® Spin Miniprep Kit (27106) and used to produce cDNA for use in RT-qPCR. RT-qPCR was performed on an Applied BioSystems® 7300 Real Time PCR System under conditions of biofilm growth and swarming motility. Table 3.2 Primers used in this study (Forward: F; Reverse: R) Primer name/ target gene Primer direction Sequence prrF1 F TCGCGAGATCAGCCGG R GCCTGATGAGGAGATAATCTGAAGA prrF2 F ACTGGTCGCGAGGCCA R GCCTGATGAGGAGATAATCTGAAGA 22  3.2.3 PYOCYANIN AND PYOVERDIN SECRETION For the measurement of pyocyanin secretion, overnight growth cultures were centrifuged and supernatant was collected in new sterile microfuge tubes. One volume of CHCl3 was added to the supernatant and vigorously shaken to extract pyocyanin from the aqueous layer. Transferring the CHCl3 phase to 0.2 N HCl and again shaking vigorously was performed to remove pyocyanin from the hydrophobic layer. The absorbance of pyocyanin in 0.2 N HCl was measured at 520 nm (Whooley, 1982; Mavordi, 2001). For the measurement of pyoverdin secretion, overnight cultures were centrifuged and pellets were discarded and supernatant was diluted 1/200 in 10 mM Tris-HCl. Dilutions were excited at 405 nm for fluorescence emission detection of pyoverdin at 460 nm on a Perkin Elmer® Fluorescence Spectrometer LS 50B (Mirleau, 2000; Baysse, 2002). 3.3 Results 3.3.1 DELETION MUTANTS OF THE PRRF LOCUS HAD A DISTINCT PYOVERDIN AND PYOCYANIN SECRETION PHENOTYPE FROM PAO1 WILDTYPE. The prrF1 and prrF2 sRNAs have previously been characterized as being regulated by Fur in P. aeruginosa (Wilderman et al, 2004; Oglesby-Sherrouse, 2010). However, it has not been investigated whether regulation by the prrF sRNAs has any observable effect on the secretion of siderophores for iron acquisition. Pyoverdin is a major iron siderophore in P. aeruginosa and is readily detectable due to its ability to fluoresce when excited with ultraviolet light. Pyoverdin reproducibly emits between wavelengths of 420–540 nm when excited with ultraviolet radiation, with peak emission occurring at 460 nm. Relative differences between PAO1 strains were calculated, wherein emission intensity is positively correlated with the concentration of pyoverdin present. For analysis of pyoverdin secretion, cultures were incubated in BM2 minimal medium without added any added ferric iron in the form of FeSO4 and therefore, only trace amounts iron were possibly available, to maximize pyoverdin secretions. The data show that deletion of the entire prrF gene locus in the PAO1 strain ΔprrF1-2 consistently upregulated pyoverdin secretion compared to PAO1 wildtype (Figure 3.1). 23   Figure 3.1. Pyoverdin secretion by prrF locus mutant strains. The excitation spectra and relative intensity of pyoverdin fluorescence after excitation at 400 nm are shown. PAO1 is the wild type parent strain of the prrF deletion mutants. Strains ΔprrF1 and ΔprrF2 are deletion strains of PrrF1 and PrrF2, respectively. The ΔprrF1-2 strain is a deletion of the entire prrF locus and ΔprrF1-2 pVLT31::prrF1-2 is a complementation strain restoring prrF1-2 expression on a plasmid construct. Re-introducing PrrF expression on a plasmid construct with native promoters in the complemented strain ΔprrF1-2 pVLT31::prrF1-2 restored pyoverdin secretion to wild type levels. In deletion strains lacking the individual sRNAs prrF1 or prrF2 alone, there was no observable difference in pyoverdin secretion compared to the PAO1 parent strain (Figure 3.1). In addition, secretion of the phenazine pyocyanin was also tested for unique phenotypes in prrF sRNA deletion strains. Pyocyanin creates a blue tint in the supernatants of P. aeruginosa cultures. Pyocyanin secretion was not significantly reduced in the ΔprrF1-2 mutant strain of PAO1 as determined by one-way ANOVA, however, the difference was nearly significant when using a Bonferronni multiple comparison analysis with a p-value equal to 0.09 (Figure 3.2). 400 450 500 5500200400600800PAO1prrF1-2prrF1-2+wavelength (nm)Relative Fluorescence EmissionprrF2prrF124   Figure 3.2 Pyocyanin secretion of prrF locus mutant strains compared to PAO1 WT. Analysis by one-way ANOVA found no significant difference between any of the strains where p < 0.05.  Restoring prrF sRNA expression in the complemented strain (ΔprrF1-2 pVLT31::prrF1-2) restored wildtype levels of pyocyanin secretion. Deletion of the individual sRNAs in mutant strains ΔprrF1 and ΔprrF2, respectively, had no significant effect on pyocyanin secretion relative to PAO1 wildtype. 3.3.2 DELETION MUTANTS IN PRRF SHOWED UNIQUE SWARMING PHENOTYPES IN PAO1. To further study the biological roles of the prrF sRNAs distinct from iron metabolism, the prrF deletion strains were investigated for unique phenotypes in swarming motility and biofilm formation. Previous studies utilizing RNA-Seq demonstrated that the prrF genes are significantly increased under conditions of biofilm growth when compared to planktonic, free-swimming growth (Dötsch et al, 2012). Here semi-quantitative PCR (qPCR) was used to determine the expression profiles of prrF sRNAs during swarming motility and biofilm formation. In this regard, prrF1 and prrF2 were highly upregulated in swarming colonies and during biofilm formation. Relative to planktonic PAO1 cultures, biofilm cultures upregulated prrF1 and prrF2 12- and 20-fold, respectively. Expression of the putative third sRNA, prrH, which consists of both prrF1 and prrF2 in a single transcript, also showed a 13-fold increase under biofilm conditions. (Table 3.3). PAO1 prrF1 prrF2 prrF1-2 prrF1-2+0255075100125% Wildtypens25  Table 3.3 Fold change in prrF locus expression during swarming motility and biofilm formation.*  Name  Genomic Coordinates Size (bp) Complementarity Fold increase in biofilms Fold increase in swarming motility prrF1 5283960 - 5284110 151 prrF2 12.1±2.1 217±116 prrF2 5284172 - 5284319 148 prrF1 20.1±4.2 141±66.6 prrF1-2 (prrH) 5283960 - 5284319 360 prrF1, prrF2 12.5±1.7 163±54.0 * Fold change reported is the mean value for 3 biological replicates. Under swarming motility conditions, the prrF locus was even more highly up-regulated than it was under biofilm cultures. The prrF1 and prrF2 sRNAs showed an up-regulation of 217-fold and 141-fold, respectively. Moreover, compared to free-swimming cultures, prrH was up-regulated 163-fold in swarming colonies. It was then further studied whether prrF sRNA deletion mutants had observable phenotypes in swarming motility and biofilm formation. To test swarming, prrF deletion mutants were inoculated on swarm plates and compared with wildtype PAO1. The swarming colonies in the complete prrF locus deletion strain (ΔprrF1-2) were noticeably (46%) reduced in size, whereas deletions of only prrF1 and prrF2 (ΔprrF1 and ΔprrF2, respectively) maintained wildtype swarming levels. The complemented strain expressing prrF sRNAs from a plasmid constructed in a complete prrF deletion background was unable to restore wildtype levels of swarming (Figure 3.3), which was possibly due to gene dosage effects. Swarming was performed under iron rich (Figure 3.3A) as well as iron depleted conditions, the latter of which was accomplished by the inclusion of 2,2-dipyridyl (Figure 3.3B). Limited iron reduced the swarming ability of all PAO1 strains, but that the relative differences between PAO1 WT and mutant strains were maintained regardless of iron availability.  26   Figure 3.3 Swarming phenotype of prrF locus mutants compared to PAO1 WT (H103). (A) Swarming on regular swarming minimal medium with glucose as a carbon source and 10 µM FeSO4. (B) Swarming under iron depleted conditions created by including 150 µM 2,2 dipyridyl.   A. B. ΔprrF2 PAO1 ΔprrF1 ΔprrF1-2 ΔprrF1-2 pVLT31::prrF1-2 27   To investigate biofilm formation in the prrF sRNA mutants, crystal violet staining was used to assess plastic-adherent biofilms. In contrast to the results observed for swarming, the deletion strains in prrF2 (ΔprrF2) and the whole prrF gene locus (ΔprrF1-2) were not significantly different from PAO1 wildtype under iron replete or iron depleted conditions. However, the prrF1 deletion strain, ΔprrF1, formed biofilms on surfaces ~250% better than PAO1 under conditions of excess iron ,and nearly 150% greater under iron depleted growth condtions (p<0.0001) (Figure 3.4).  Figure 3.4 Crystal violet staining of prrF mutant strains. Iron replete conditions consisted of 10 µM FeSO4 and iron depleted conditions included the addition of the iron chelator 150 µM 2, 2 dipyridyl. Statistical analysis was performed by the unpaired Student's t test where significance is indicated by p<0.0001 (****). 3.4 Discussion The prrF locus sRNAs were previously characterized as translational regulators of enzymes involved in iron utilization and act as a mechanism to enhance effective use of iron under conditions of limited availability. The aim of this work was to investigate novel phenotypes in deletion mutants of the prrF sRNAs that might give insight into broader functions regulated by the prrF sRNAs. Here I found that the deletion of the prrF locus in PAO1 affects the secretion of both the iron siderophore pyoverdin, and the phenazine pyocyanin, as well as affects the complex 28  social behaviour of P. aeruginosa, namely swarming motility. The molecular structure of pyoverdine includes several aromatic rings and readily fluoresces in the range of 400-500nm when excited with 405 nm ultraviolet light. Using this as an indicator of levels of pyoverdin synthesized and secreted demonstrated that the deletion mutant of the entire prrF locus in the ΔprrF1-2 strain was heightened compared to PAO1 WT (Figure 3.1). Complementation of the prrF locus in the ΔprrF1-2 pVLT31::prrF1-2 strain restored WT levels of pyoverdin synthesis. Previous work showed that prrF1 and prrF2 are redundant in their roles within the cell, and pyoverdin secretion in the ΔprrF1 and ΔprrF2 strains support this conclusion as both have the same level of secretion as PAO1 WT (Figure 3.1).  I also investigated whether the prrF sRNAs regulate levels of another large secreted molecule, namely the phenazine compound pyocyanin. P. aeruginosa secretes many different pigmented compounds of which pyocyanin is one of the most predominant. Pyocyanin gives P. aeruginosa colonies their characteristic blue hue. Interestingly, compared to PAO1 WT, pyocyanin secretion in ΔprrF1-2, in which the prrF locus is completely deleted, was significantly reduced, whereas complementation of the full deletion of prrF1-2 partially restored wildtype levels of secretion (Figure 3.2). Redundant roles of prrF1 and prrF2 was revealed by the fact that deletion strains of only a single prrF sRNA gene had no significant effect on pyocyanin secretion compared to wildtype. These data demonstrated that the prrF sRNAs had functional roles other than regulation of iron usage within the cell.  Previous work in V. cholerae has indicated that RyhB, a functional homolog of the prrF sRNAs, has a regulatory role in biofilm formation (Mey et al, 2005). Here, analysis by crystal violet staining was used to study any effects the prrF sRNAs had on biofilm formation. I demonstrated that the deletion mutant of prrF1, under conditions of both excess iron and trace iron, led to biofilm formation of more than twice that of PAO1 WT. The effect of deleting a single prrF gene was unique to this assay system since in all other assays here, e.g. swarming, no significant differences were observed when either one of the single prrF sRNAs were deleted (Figure 3.3 and Figure 3.4). Both the prrF2 deletion strain and deletion of the whole of prrF locus (ΔprrF1-2) maintained the same level of biofilm formation as the PAO1 WT parent strain (Figure 3.4). These results are counter-intuitive when taking into consideration previous results in the literature, and those described here, which demonstrate that prrF1 and prrF2 possess nearly identical nucleotide sequences, promoters (Wilderman, 2004; Oglesby-Sherrouse, 2010) 29  and functions, as shown above. Crystal violet staining is used as an indicator of levels of biofilm formation due to the fact that it measures the level of cell adhesion to solid surfaces, which is a requirement for mature biofilms to develop. However, qPCR data showed prrF1 to be expressed at levels nearly half that of prrF2 from biofilm colonies (Table 3.3). Overall this data suggests that prrF1 has a negative regulatory role on biofilm formation although similar removal of prrF1 expression in the ΔprrF1-2 showed no significant difference compared to PAO1 WT; this might indicate that the full regulatory effects of the prrF sRNAs require an interplay of both sRNA transcripts, with specific roles for each. Under swarming conditions, prrF1 was somewhat more highly upregulated (217±116-fold change in expression) than prrF2 and prrF1-2 (141±66- and 163±54.0-fold change, respectively), The prrF1 and prrF2 sRNAs appear to have largely redundant roles in swarming since deleting either prrF1 or prrF2 alone had no effect on the ability to swarm. A reduced swarming phenotype was observed in both excess iron and iron depleted conditions when the complete prrF1-2 region is deleted in the ΔprrF1-2 strain (Figure 3.3). Complementation of the prrF1-2 deletion was however unsuccessful in restoring swarming, which I ascribed to gene dosage effects. Overall swarming appeared to be reduced under iron depleted conditions (Figure 3.3B). The ability and morphology of swarming was variable in single deletion mutants of prrF1 or prrF2, but deletion of the whole prrF1-2 region consistently resulted in a significantly reduced ability to swarm. Due to the fact that swarming phenotypes appear to be independent of the availability of iron, this suggests that prrF sRNAs have regulatory roles than are not limited to the regulation of iron usage by the cell. The targets that the prrF sRNAs act upon are still not well understood. Previous studies have only investigated dysregulation of gene expression in prrF locus deletion mutants, which cannot indicate direct targets of sRNAs. Only general conclusions on downstream effects can be made when analyzing gene expression profiles in sRNA mutants. Searching for targets of the prrF sRNAs by sequence homology yielded no results as sequences from the prrF locus only had homology to themselves (Table 3.3). In conclusion, the prrF sRNAs likely have greater regulatory roles than previously concluded with regards to dysregulation of pyocyanin production, being highly upregulated during biofilm development and in swarming colonies, and participating to some extent in both complex processes. In addition, this work indicates that the prrF sRNAs might not be entirely redundant although they appear to usually work in concert to effectively regulate targets. 30  4 Role of the phrS sRNA in Pseudomonas aeruginosa 4.1 Introduction In a clinical setting P. aeruginosa is able to develop resistance when exposed to low-levels of antibiotics and this is termed adaptive resistance. The phenomenon of adaptive resistance results from changes in gene expression rather than heritable changes. One of the best-studied mechanisms of adaptive resistance in P. aeruginosa is by reduction of the permeability of the outer membrane to polycationic antimicrobials through modification of the lipid A portion of lipopolysaccharide (LPS) molecules that make up the outer leaflet (Briedenstein et al, 2011; Moskowitz et al, 2004). Lipid A can be altered by capping the negatively charged phosphate molecules with positively-charged arabinosamine, thus reducing the ability of cationic antimicrobial agents such as polymyxin B to destabilize the integrity of the outer membrane, which leads to uptake across the outer membrane and cell death. The arn operon of P. aeruginosa encodes enzymes responsible for the arabinosaminylation of the lipid A portion of lipopolysaccharide (LPS) and multiple transcriptional regulators, which are to some extent redundant, that have been shown to regulate the arn operon. The role of sRNAs in regulating expression of arn operon proteins has not been proposed. One sRNA, phrS was previously characterized to post-transcriptionally regulate the production of a transcriptional regulator, PqsR (MvfR), which is a key regulator for the synthesis of the Pseudomonas Quinolone Signal (PQS) that is involved in one type of P. aeruginosa quorum sensing. Sonnleitner et al (2011) found that phrS was positively regulated by the transcriptional regulator Anr. Moreover, phrS positively regulates translational levels of PqsR by interacting with the 5’UTR of the pqsR mRNA transcript, alleviating secondary structures blocking access of the ribosome to the RBS. Previous deep-sequencing of P. aeruginosa using RNA-Seq found that phrS is significantly differentially expressed under conditions of biofilm formation compared to planktonic growth. Here, other functions of phrS were considered including roles in antibiotic susceptibility, biofilm formation and swarming motility.   31  4.2 Materials and Methods 4.2.1 BACTERIAL STRAINS AND GROWTH CONDITIONS Wildtype PA14, as well as phrS, anr, and pqsR mutant strains of P. aeruginosa were obtained from the Harvard Transposon mutant library (Table 4.1). Table 4.1 Strains and plasmids used Strain or plasmid Genotype or characteristics Reference P. aeruginosa   WT Wild-type P. aeruginosa PA14 Liberati et al, 2006 anr PA14 anr::MrT7; GENR Liberati et al, 2006 pqsR/MvfR PA14 pqsR::MrT7; GENR Liberati et al, 2006 phrS PA14 phrS::MrT7; GENR Liberati et al, 2006 phrS+ phrS/pUCP18::phrS; GENR, AMPR this study E. coli TOP10 DH5α parent; F- mcrA Δ(mrr-hsdRMS-mcrBC) Φ80lacZ_M15 ΔlacX74 recA1 araΔ139 Δ(ara-leu)7697 galU galK rpsL (STRR) endA1 nupG Invitrogen Plasmids   pCR-BLUNT II-TOPO PCR cloning vector; KANR Invitrogen pUCP18 E. coli derived plasmid containing AMPR marker Schweizer, 1991 pUCPlux::PA3552 pUCP23 containing intergenic region between PA3551 and PA3552 immediately upstream of luxCDABE McPhee et al, 2003 Assessment of the minimal inhibitory concentrations (MICs) of antibiotics was performed in 96-well microtitre plates in LB media using 2-fold dilutions of antibiotics (Wiegand et al, 2008). MIC measurements under aerobic conditions involved shaking at 250 rpm to encourage aeration of cultures. Microaerobic conditions were created by supplementing LB media with 15 mM KNO3 and sealing the plates with parafilm before incubation. Anaerobic MIC conditions utilized LB media supplemented with 15 mM KNO3, and microtitre plates were placed in an air-tight chamber and atmospheric oxygen was removed by a BD BBLTM GasPakTM aneraobic system.  Kill curves for PA14 strains were performed by growing strains overnight in LB medium, subculturing them into BM2-glucose medium and growing them to the mid logarithmic phase of growth. Log phase cultures were washed once with BM2 buffer salts, and were diluted 10-fold 32  into BM2 buffer salts. Cultures were sampled and plated on LB agar plates at 0 min to obtain a total colony count. They were then challenged with 2 µg/ml polymyxin B and incubated at room temperature. Cultures were sampled and plated for colony forming unit counts at time intervals of 5, 10, and 20 min. 4.2.2 BIOFILM DEVELOPMENT Biofilm flow-cell analysis of PA14 strains was performed by inoculating overnight cultures into flow-cells and letting cultures grow undisturbed for 3 hours before activating pumps and initiating flow. Biofilms were then grown for 3 days before flow-cell cultures were stained with syto9 (live cell stain) and propidium iodide (damaged and dying cells) to be analyzed by scanning-LASER confocal microscopy. 4.2.3 SWARMING MOTILITY For swarming growth analysis, overnight cultures of PA14 strains were sub-cultured 1/100 into fresh BM2-glucose media and grown to the mid logarithmic phase of growth. Swarming agar plates were made with BM2-glucose media supplemented with 0.5% casamino acids as a nitrogen source with 0.5% agar. They were inoculated with 1 µl log phase cultures and incubated at 37ºC for 18 hrs. 4.2.4 TRANSFORMATION OF PSEUDOMONAS AERUGINOSA Complementation of phrS was performed by ligating the PCR-amplifying phrS and its native promoter (using the following primers: forward, 5’CTTGATGGCGAACTTGAGCG and reverse, 5’TTTGAACCTGACCTTCCGCC), which was then ligated into the pCR-BLUNT II-TOPO vector. The resultant clone was transfected by the heat-shock technique into competent E. coli TOP10 (Table 4.1). The phrS construct was removed from the TOPO vector by endonuclease digestion with enzymes XbaI and KpnI. The phrS construct was then ligated into the similarly-cut pUCP18 P. aeruginosa expression plasmid, using T4 DNA ligase (New England Biolabs Cat. # M0202L) for 18 hrs at 37oC. Successful insertion of the phrS construct was detected by endonuclease digestion with PstI. For electroporation of the pUCP18::phrS and pUCPlux::PA3552 vectors into P. aeruginosa, cells were washed and suspended in 100 µl of sterile 10% glycerol, 6 µl of purified plasmid added, and cells were pulsed at 200 Ω, 25 µFD and 2.5 V using a BioRad MicroPulserTM electroporator (165-2100). Cultures were allowed to re-cover for 1 hour in LB media with shaking at 37oC before being plated on selective ampicillin plates. 33  4.2.5 SEMI-QUANTITATIVE ANALYSIS OF PHRS EFFECTS ON TWO-COMPONENT SYSTEMS AND THE LIPID A MODIFICATION OPERON IN PSEUDOMONAS AERUGINOSA  To study the effects of phrS on the Lipid A arabinosaminylation operon of P. aeruginosa PA14, strains were transformed with the pUClux::PA3552 expression vector, which contains the luxCDABE luciferase operon fused to the arnBCADTEF promoter and 5’ untranslated region (5’UTR) of the arn mRNA. Detection of luminescence under the regulation of the arn promoter and 5’UTR and assessing growth of cultures by absorbance at 620 nm (A620) was performed on a TECAN SPECTRAFluor Plus with or without induction with 2 µg/ml indolicidin. RT-qPCR, using the appropriate primers described in Table 4.2 was performed on an Applied BioSystems® 7300 Real Time PCR System in cells induced or not with indolicidin. Table 4.2 Primers used in this study (Forward: F; Reverse: R) Primer target Direction Sequence RT-qPCR   phrS F GTGCTCTGTGTATCCGGGAG  R GTAGGCCTCATGGTCGCTTT cprR F GCATATCCACGTACTCGTCGTC  R GTGATCGCAGACCACCCC Cloning   phrS F CTTGATGGCGAACTTGAGCG  R TTTGAACCTGACCTTCCGCC 4.3 Results 4.3.1 THE SRNA PHRS HAD A POLYMYXIN B RESISTANCE PHENOTYPE DISTINCT FROM ITS KNOWN TRANSCRIPTIONAL REGULATOR AND A KNOWN DOWNSTREAM EFFECTOR GENE Antimicrobial compounds commonly used in the clinic to treat P. aeruginosa infections were selected to determine if a phrS mutant strain had any unique antibiotic resistance phenotypes. Since previous studies demonstrated that Anr is a transcriptional regulator of phrS expression and is itself up-regulated in decreasing levels of available oxygen, mutants in this gene were also tested in addition to utilizing microaerobic and anaerobic conditions (which activate Anr) in addition to aerobic growth. In addition a mutant in the gene for PqsR, which has been shown to be downstream of phrS, was tested. Under aerobic conditions, the phrS mutant demonstrated a 4-fold increase in resistance to polymyxin B compared to its parent PA14 WT, anr mutant, and pqsR mutant strains (modal MICs of 5 biological repeats; Table 4.3). All other changes were less 34  than 2-fold (which is considered by convention within the margin of error for the MIC assay), and none of the observed changes were specific to the phrS mutant.  Table 4.3 MICs of the phrS mutant compared to WT, and mutants in an upstream regulator anr and a downstream target pqsR under conditions of differing oxygen availability.  Strain and growth condition MICs (μg/mL) Ceftazidime Ciprofloxacin Piperacillin Polymyxin B Tobramycin Aerobic PA14 WT 1 0.2 8 0.25 0.5 phrS 1 0.2 4 1 0.5 anr 1 0.1 4 0.25 0.5 pqsR 2 0.1 4 0.25 0.5 Microaerobic PA14 WT 8 0.8 8 0.5 2 phrS 4 0.4 8 1 2 anr 4 0.2 8 1 2 pqsR 4 0.8 4 1 2 Anaerobic PA14 8 0.2 >64 0.5 16 phrS 8 0.2 >64 1 32 anr 4 0.1 >64 0.5 32 pqsR 4 0.1 >64 0.5 8 With decreasing levels of available oxygen, decreased antibiotic susceptibility was generally observed for all strains and antibiotics used. The only phrS specific phenotype observed was a 2-fold increase in resistance to polymyxin under anaerobic, which is not considered significant as mentioned above (Table 4.3). Under microaerobic conditions, all 3 mutant strains showed the same 2-fold resistance. Other than a 4-fold increase in susceptibility to ciprofloxacin in the anr mutant under microaerobic conditions, no other significant changes in susceptibility were observed. Kill curves with polymyxin B were used to confirm the greater resistance of the phrS mutant to killing by polymyxin B. The effects of polymyxin B in cell killing is rapid and can be measured by plating cultures and counting viable cells. The PA14 wildtype and phrS mutant were incubated with a bactericidal concentration of 2 µg/ml polymyxin B over a time course of up to 20 min. Figure 4.1 shows that the WT PA14 demonstrated a rapid decrease in viable cells by ~100-fold within 5 minutes, while the phrS mutant showed only a mild (~2-fold) decrease at this time. This difference in killing was maintained over the entire 20 minute time course. 35  Complementation with the phrS gene behind its own promoter (phrS+) restored antibiotic susceptibility.   Figure 4.1 Increased resistance of the phrS mutant, cf. the WT, to polymyxin B (2 µg/ml). Results shown are representative of 3 biological repeats. Complementation with phrS under the regulation of its native promoter in the phrS+ strain restored strain PA14 WT susceptibility. The phrS VC is an empty vector control strain in a phrS mutant background. Together Table 4.3 and Figure 4.1 demonstrate that the phrS transposon mutant has a greater resistance to polymyxin B. P. aeruginosa has been previously shown to undergo adaptive resistance to cationic antimicrobial compounds, like polymyxin B, through alterations of the lipid A portion of lipopolysaccharides (LPS) in the outer membrane. The arnBCADTEF operon mediates the addition of arabinosamine to LPS. To determine whether phrS regulated this operon transcriptionally or post-transcriptionally, a combination of semi-quantitative RT-qPCR and assessment of luminescence to assess effects on protein expression was utilized. Analysis by RT-qPCR demonstrated that arn expression was not significantly different between the phrS mutant and PA14 wildtype indicating that the phrS sRNA species did not act through upstream regulators of the arn operon (Table 4.4).   36  Table 4.4 Lack of change in peptide-induced arnBCADTEF operon gene expression in a phrS mutant relative to that in PA14 WT. Also shown is the decreased induced expression of the arn operon in a cprR mutant used as a positive control (Fernández et al, 2012) for transcriptional regulation of the arn operon. Strain  Relative fold change in arnB gene expression (cf. WT) after treatment with 4 μg/ml indolicidin phrS 1.0±0.2 cprR -4.7±-1.6 To assess the impact on translation, wildtype and phrS mutant strains were transformed with a pUCP23 plasmid containing a transcriptional fusion construct of the 5' untranslated region (UTR) and promoter region of the arnBCADTEF operon fused to the open reading frame of the luxCDABE operon which codes for the expression of the luminescent protein luciferase. This lux fusion construct enabled levels of luminescence through luciferase expression by arnBCADTEF regulatory pathways. While this construct assessed effects on regulation, transcription, and translation of the arnBCADTEF operon in the face of the data in Table 4.4, any effects would reflect the interaction of phrS with the upstream region of the arn operon mRNA, impacting on translation of the fused lux genes. The phrS mutant and WT were transformed with a plasmid construct containing the promoter and 5' UTR of the arn operon upstream of a promoterless luxCDABE cassette. When the arn operon inducer, cationic antimicrobial compound indolicidin, was applied, as well as when unchallenged, the phrS mutant increased both basal and inducer-enhanced expression by about 2-fold when compared to that for the wildtype strain PA14 (Figure 4.2).   37   Figure 4.2 Effect of the phrS mutant on expression of a luxCDABE cassette assessed as relative luminescence of a lux reporter linked to the promoter and 5' untranslated region of the arn operon upstream. Unpaired Student’s t-tests were performed for statistical analysis and significance was found to confidence interval of p<0.01 (**). Taken together with the qPCR data showing that the lack of phrS had no effect on gene expression, these luminescence data showed that phrS likely acts directly on the arnBCADTEF operon mRNA to negatively impact translation.  4.3.2 THE SRNA PHRS DISPLAYED REDUCED SWARMING MOTILITY AND INCREASED BIOFILM FORMATION COMPARED TO PA14 WILDTYPE Since phrS has dual roles in PQS synthesis and polymyxin susceptibility, I examined whether it might have additional roles in social behaviours such as swarming motility and biofilm formation. The phrS mutant demonstrated similar twitching and swimming motility when compared to WT (Figure 4.3), indicating that it had functional pili and flagella, respectively. In contrast, phrS showed a strongly diminished ability to swarm compared to WT. Wildtype swarming was partly restored in the phrS mutant when transfected with a plasmid encoding the phrS gene and its native promoter (Figure 4.4A).   PA14 phrSNo treatmentSubinhibitory indolicidinRLU/OD620(x103)0510152025****38   Figure 4.3 Lack of impact of a phrS mutant on twitching (A) and swimming (B) motility. A complemented strain (phrS+), an empty vector control strain (phrS VC), and the wildtype PA14 parent strain (WT) were also tested. No significance (ns) was found when performing one-way ANOVA with a confidence interval of p < 0.05.  Figure 4.4 Inhibition of swarming motility by the phrS mutant. (A) Swarming motility was partially restored by complementation with phrS expressed on a pUCP18 vector (phrS+). (B) The swarming motility of the pqsR mutant was highly reduced compared to wildtype PA14 and phrS while the anr mutant was moderately reduced in its ability to swarm. 39  The swarming motility of a transposon insertion mutant in pqsR found it to be highly reduced in its ability to swarm, while an anr mutant displayed only a moderate reduction in its ability to swarm (Figure 4.4B). Previous work on the phrS sRNA demonstrated that it is regulated by Anr and that the phrS sRNA regulates the translational levels of the PqsR transcriptional regulator in a positive manner (Sonnleitner et al, 2011). To assess biofilm formation, flow cell methods were used combined with Syto-9 staining and confocal microscopy (Figure 4.5).  Figure 4.5 Flow-cell analysis of the impact of the phrS mutant and its complemented strain (phrS+) on biofilm formation. Other strains tested were a phrS vector control (phrS VC), anr and pqsR transposon insertion mutants, and PA14 parent strain (WT). After 3 days, bacteria were stained green with the all bacteria stain Syto-9, and red with the damaged cell wall/dead-bacteria stain propidium iodide prior to confocal imaging. Each panel shows reconstructions from the top in the large panel and sides in the right and bottom panels (xy, yz and xz dimensions). 40  The phrS mutant demonstrated significantly reduced micro-colony formation compared to the PA14 wildtype and near-normal biofilm formation was restored by complementation. This indicated that the phrS mutant had a tremendously reduced ability to form biofilms. Under conditions of biofilm formation the pqsR mutant displayed a reduced ability to form biofilms in a flow-cell apparatus. The anr mutant displayed no reduction in ability to form biofilms (Figure 4.5) The reduced swarming motility and biofilm formation observed in the phrS mutant is therefore likely due to the loss of the positive regulatory effect the phrS sRNA has on translation of pqsR and the phenotypes observed are due to dysregulation from PqsR dependent pathways. 4.4 Discussion Analysis of swarming motility and biofilm formation indicated that, relative to the PA14 parent strain, the phrS mutant was highly reduced in its ability to swarm, and was deficient in its ability to form biofilms. A transposon mutant in anr, a transcriptional regulator of phrS, had no observable defect in swarming motility and biofilm formation compared to wildtype. It was also observed that a transposon insertion mutant in pqsR, of which phrS was previously found to have a positive regulatory effect on its translation (Sonnleitner et al, 2011), had a reduced swarming, as well as biofilm phenotype similar to the phrS mutant (Figure 4.4 and Figure 4.5). It is likely that the effects on swarming motility and biofilm formation observed are in part due to dysregulation of PqsR dependent regulatory pathways for the synthesis of the cellular communication molecule PQS. However, because clear observable differences in the phenotypes of the pqsR and phrS mutants exist it is also likely that phrS exerts its regulatory effects on a large number of mRNA targets. This indicates that phrS has important roles in promoting complex social behaviours. Predictions of mRNA targets of phrS, determined by sequence complementarity, indicated that the proteases clpV1, PA2371, and clpB are potential targets of phrS (Table 4.5).   41  Table 4.5 Genes containing complementarity with phrS. PA gene number Gene Name Description PA0090 clpV1 ATP-binding subunits of Clp protease and DnaK/DnaJ chaperones PA0459   Probable ClpA/B protease ATP binding subunit PA1555.1 ccoQ2  Cytochrome c oxidase, cbb3-type, CcoQ subunit PA1784   Hypothetical, unclassified, unknown PA2333   probable sulfatase PA2371   Probable ClpA/B-type protease PA2492 mexT  transcriptional regulator MexT PA2525 opmB Membrane proteins, transport of small molecules, antibiotic resistance PA2544   Hypothetical, unclassified, unknown PA2830 hptX heat shock protein HtpX PA3100 xcpU General secretion pathway outer membrane protein H precursor PA3871 nifM  probable peptidyl-prolyl cis-trans isomerase, PpiC-type PA4282 sbcC probable exonuclease PA4542 clpB ATP-binding subunits of Clp protease and DnaK/DnaJ chaperones PA4560 ileS isoleucyl-tRNA synthetase PA5176   Hypothetical, unclassified, unknown PA5378   Hypothetical, unclassified, unknown Previous research demonstrated that ClpP and ClpS proteases affect swarming motility, biofilm formation and antibiotic resistance (Fernández et al, 2012). It is possible that phrS might be involved in the regulation of ClpP and ClpS proteases. The work here showed that phrS is involved in the translation of the arn operon of P. aeruginosa (Table 4.4 and Figure 4.2). Taken together, the qPCR (Table 4.4) and luciferase expression experiments demonstrated that phrS was exerting a direct negative regulatory role on translational expression of the arnBCADTEF operon. Given the lack of impact on transcription of this operon, measuring luciferase expression through detection of luminescence under the control of the arn 5' UTR revealed that phrS exerted a repressive role on expression, as revealed by stimulation in the mutant (Figure 4.2). Consistent with this, in the phrS mutant luciferase 42  expression was significantly increased, cf. WT, both in the absence of the inducer indolicidin as well as in its presence, despite clear differences in overall expression in WT, as expected due to increased transcription in the presence of inducer (Figure 4.2). From this evidence it can be concluded that phrS has a role in regulating the protein expression of the arn operon, by acting directly on the 5’ UTR region of the arn operon transcript. Since the phrS mutant caused no change in the expression of the transcriptional regulators previously characterized to be involved in controlling adaptive polymyxin resistance, this further supports that phrS is a novel and independent pathway regulating lipid A modifications involved in the development of adaptive resistance, and in fact suppresses this phenotype. Sonnleitner et al (2011) previously demonstrated that phrS has a positive regulatory effect on the translation of pqsR transcripts by altering mRNA folding upon phrS interactions exposing the RBS of pqsR. In addition the work in this thesis demonstrated that phrS is also able to negatively impact on the translation of the arn operon. The activity of sRNA species in the literature currently attributes either positive or negative regulatory roles to a specific sRNA. In theory sRNAs can have multiple interaction sites and exert both positive and negative regulatory effects depending on target mRNAs. The work here is the first to provide evidence suggesting this.   43  5 Concluding Remarks 5.1 Introduction Our current understanding of the regulation of translation by sRNAs in bacteria is at present modest, in part due to the difficulties that exist in studying the functions of non-coding RNAs. The use of RNA-Seq has been instrumental in revealing that the number of transcribed sRNAs encoded in genomes is much higher than initially thought. This is consistent with the suggestion that they might represent an important mechanism by which bacteria modulate and integrate intracellular signalling. Future work will require a detailed understanding of the breadth of targets that each single sRNA can act on within the cell, while developing a better understanding of the mechanisms by which sRNAs regulate targets. The use of high-throughput proteomics approaches and more accurate bioinformatic analyses is required to continue promoting an understanding of these elements. However, proteomic studies on such a large scale are still quite costly. Also, current bioinformatic studies to determine targets and the extent of involvement of sRNAs in signalling networks are not very accurate, and inevitably better strategies will rely on developing more information regarding the mechanisms and targets of sRNA. The current research studying sRNAs in P. aeruginosa aimed to provide greater knowledge of the biological roles of sRNAs in this bacterium. Here it is demonstrated that sRNAs such as prrF1, prrF2, and phrS have important roles in complex biological behaviours such as swarming motility and biofilm formation of P. aeruginosa, in addition to showing that phrS has a role in adaptive resistance to polymyxin B. This work thus demonstrates that sRNAs have diverse roles within the cell that are far reaching. Unfortunately, it still remains difficult to predict the targets of sRNAs based just on complementary sequence analyses.  5.2 Expression of Novel sRNA Species In the literature, confirmation of novel sRNA species is not as frequent as primary studies, meaning that it is difficult to conclude with certainty whether the identified sRNAs are truly expressed transcripts or artefacts of the data analysis procedure. Two studies have been published suggesting that the number of sRNA genes in P. aeruginosa lies between 165 and 513 (González et al, 2012; Wurtzel et al, 2012). None of these studies can claim to be sufficiently accurate to identify the actual number of sRNAs in the P. aeruginosa genome. The deeper that one sequences the more transcripts one will find, but deciding the cut-off between noise and actual transcripts can be difficult. Furthermore, numerous assumptions are made with regards to 44  gene architecture, length, potential for translation, and levels of expression that might influence the determination of the possibility of an sRNA gene. All sRNAs likely have specific conditions under which they are more abundantly expressed (see e.g. Table 2.2), and multiple different growth conditions would have to be considered to enable exhaustive discovery of novel sRNA genes and gain an appreciation for possible biological roles. Here we were able to demonstrate that the study of sRNA expression under different growth conditions of biofilm formation and swarming motility resulted in unique expression profiles for 26 of the 31 novel sRNAs identified by our collaborators Dr. Gill and Dr. Brinkman from SFU, and this provided insights into the prospective biological roles these sRNAs might have in the cell.  5.3 The prrF Locus sRNAs  The prrF locus is noteworthy for encoding sRNAs that are regulated by Fur. Also the two sRNA genes, prrF1 and prrF2 are to be redundant in their roles (Wilderman et al, 2004), while there is potentially a third transcript of prrH consisting of the entirety of the prrF1-2 sequences with potentially unique roles (Olgesby-Sherrouse et al, 2010). Previous work has shown that regulation of the prrF sRNAs is dependent on the availability of iron (Wilderman et al, 2004) and is likely involved in iron homeostasis within the cell. Consistent with this possibility, I showed that prrF negatively regulated the production of the iron chelator pyoverdin. In addition to this role, the work described here showed that the prrF sRNAs are also redundantly involved in regulating pyocyanin production and swarming motility, since deletion of the entire locus, but not the individual sRNA genes resulted in reduced pyocyanin production and swarming. The availability of iron under swarming conditions had no visible effect on the relative extent of swarming in the PAO1 wildtype and any prrF mutants, indicating that the swarming phenotype was independent of any role in iron utilization.  In addition, the prrF sRNAs were found to be highly up-regulated under conditions of biofilm formation and swarming motility which seems unlikely to be mediated by Fur regulation. Iron availability can have an effect on biofilm formation (Banin et al, 2005), but the availability of iron, as shown here, did not appear to have an effect on swarming in P. aeruginosa. Whether the effects on regulation by prrF sRNAs are direct or indirect, this thesis demonstrated that the prrF sRNAs are substantially dysregulated during the complex social behaviours of biofilm formation and swarming motility in P. aeruginosa, and in particular play a role in the latter. 45  5.4 The phrS sRNA The sRNA phrS affects complex social behaviours of P. aerugnisa, including biofilm formation and swarming motility; indeed they appear to be required for such social behaviours. It is still not understood to what extent, and which signalling pathways or essential events are regulated by phrS for these effects to be manifested. It seems possible that the effects of phrS on biofilm formation might be mediated by an effect on matrix polysaccharide synthesis as well as the known influence of downstream target pqsR on biofilm formation (Guo et al, 2013). The effects on swarming might be due to the influence of pqsR on swarming motility as well as its possible regulation of the ClpP intracellular protease, which is known to be essential for swarming and important in biofilm formation (Fernández et al 2012). Here it was confirmed that phrS regulates also pathways outside of the PQS quorum sensing pathway, since phrS had a role in regulating protein expression of the arnBCADTEF operon that mediates lipid A modifications leading to adaptive resistance upon exposure to polymyxin. This work has thus shown that a single sRNA species, phrS, has diverse and far-reaching roles in both complex growth states and responses to antibiotic stress, in addition to its known effect on PQS synthesis. 5.5 Future Research Directions The expression profiles of novel sRNAs during biofilm formation and swarming motility, compared to planktonic growth used for the majority of previous studies, showed substantial changes in expression under the different growth conditions. To further study the roles of these novel sRNAs, mutational and gene overexpression analysis of the sRNA genes would provide an easy way to observe mutant phenotypes and further attribute biological functions to the given sRNAs. Determination of targets could also be performed by proteomic analysis under the different growth conditions, utilizing mutant and overexpressing strains to narrow down the pathways that given sRNAs might be regulating. Novel sRNA transcripts are continually being reported based on second-generation RNA-Seq methods. However, confirmation of these sRNAs as real transcripts rather than artefacts of deep sequencing or limited informatic methods is somewhat lacking in the literature. In part, this is due to a lack of understanding of the architecture of sRNAs. The range of gene architectures that exist for sRNAs is currently being studied by others; they appear to able to lack obvious promoters, may possess a prospective RBS despite not coding for functional proteins, and may or may not have terminator regions characteristic of protein coding genes. Attempts to refine the bioinformatics underlying searches 46  for sRNAs are already being undertaken (e.g. Gómez-Lozano et al, 2012), but automatic assignment has not yet been proven to be accurate as the current study found sRNAs, not included in the Gómez-Lozano study, which were confirmed to be expressed by PCR. Confirmation of active, novel sRNAs requires quantitative PCR to determine protein expression using high-throughput proteomic analyses under varied biological growth conditions to elucidate specific effects on translation and gain insight into the functional roles of sRNAs. Unfortunately, high-throughput proteomic studies require considerable investment to achieve a genome level understanding of how single sRNA species regulate the protein expression of their targets. However, there is great potential in future studies utilizing high-throughput proteomic methods. Methods enabling the study of thousands of proteins at once are rapidly progressing to enable investigators to handle the requisite workflow and data analysis through use of improved digestion methods and computational analyses (Covert et al, 2004; Vaezzadeh et al, 2010). The greatest potential of high-throughput proteomics for studying the regulomes of sRNAs would be achieved by utilitizing proteomic analysis in conjunction with genetic and mutational studies of sRNAs. Comparison of the most highly expressed 1000 to 2000 proteins in sRNA deletion mutants cf. wildtype  would provide a powerful, unbiased method for observing the regulome for any sRNA species. This would be highly beneficial to advance our understanding of how far reaching is the regulation of translation by sRNAs. One shortfall of proteomic analysis would be that nothing would be determined about direct interactions of sRNAs with targets, however this would enable gel shift studies with targeted mRNAs. Gaining an understanding of direct mRNA targets in sRNA interactions will help in understanding the mechanisms of sRNAs and determine sequence motifs used by sRNAs to specify targets. This would also help to improve the ability to predict sRNA targets. In the case of regulation by phrS, a investigation of both gene expression and post-transcriptional regulation of the putative target arnBCADTEF found that phrS is likely directly interacting with the 5’ UTR of the arnBCADTEF transcript and negatively regulating its expression. It is interesting to consider that while phrS appears to have an effect on the translation of the arn operon transcript, it cannot be ruled out that there might in fact be another factor, regulated by phrS, which is actually the direct interaction partner that regulates the arn operon. Similarly although phrS works through the chaperone RNA-binding protein Hfq in pqrS regulation (Sonnleitner et al, 2011), it is not clear that this is true for the other events, shown 47  here, that are regulated by phrS. This highlights the need for highly detailed analysis of even a single sRNA species to understand its role and direct targets. To confirm whether phrS directly interacts with the arn operon, interaction assays with purified transcripts would be required.  The use of proteomic analysis with phrS mutants would provide the best understanding as to the targets that are affected during swarming motility and biofilm development. While this would not inform regarding direct interaction partners, proteomic analysis to determine dysregulated protein expression in phrS mutants compared to wildtype and would narrow down potential targets. Bioinformatic analysis would then be helpful in determining signalling networks that exist within the pool of potential targets of phrS. It is anticipated that there would be a sufficiently small enough number of potential targets that direct interaction studies through pull-down or gel band shift assays could be performed to confirm which are direct interaction partners of phrS. Likewise, this same progression of analysis could be utilized to better understand the targets of the prrF sRNAs as well as any novel sRNA species found by RNA-Seq, allowing us to better refine our understanding of sRNA interactions with targets, the mechanisms of action of sRNAs, and iteratively enhancing future bioinformatic analysis for unexplored sRNA species.   48  References Allesen-Holm, M., Barken, K.B., Yang, L., Klausen, M., Webb, J.S., Kjelleberg, S., Molin, S., Givskov, M., and T. Tolker-Nielsen. 2006. A characterization of DNA release in Pseudomonas aeruginosa cultures and biofilms. Mol. Microbiol. 59:1114-28. Amini, S., Hottes, A.K., Smith, L.E., and S. Tavazoie. 2011. Fitness landscape of antibiotic tolerance in Pseudomonas aeruginosa biofilms. PLoS Pathog. 7:e1002298. Anderl, J.N., Franklin, M.J. and P.S. Stewart. 2000. Role of antibiotic penetration limitation in klebsiella pneumoniae biofilm resistance to ampicillin and ciprofloxacin. Antimicrob. Agents Chemother. 44:1818-24. Banin, E., Vasil, M.L., and P. Greenberg. 2005. Iron and Pseudomonas aeruginosa biofilm formation. Proc. Natl. Acad. Sci. USA 102:11076-81. Barken, K.B., Pamp, S.J., Yang L., Gjermansen, M., Bertrand, J.J., Klausen, M., Givskov, M., Whitchurch, C.B., Engel, J.N., and T. Tolker-Nielsen. 2008. Roles of type IV pili, flagellum-mediated motility and extracellular DNA in the formation of mature multicellular structures in Pseudomonas aeruginosa biofilms. Environ. Microbiol. 10:2331-43. Baysse, C., Budzikiewicz, H., Fernandez, D.U., and P. Cornelis. 2002. Impaired maturation of the siderophore pyoverdin chromophere in Pseudomonas fluorescens ATCC 17400 deficient for the cytochrome c biogenesis protein CcmC. FEMS Microbiol. Lett. 523:23-28. Beisel, C.L. and G. Storz. Base pairing small RNAs and their roles in global regulatory networks. FEMS Microbiol. Rev. 34:866-82. Blattner, F.R., Plunkett III, G., Bloch, C.A., Perna, N.T., Burland, V., Riley, M., Collado-Vides, J., Glasner, J.D., Rode, C.K., Mayhew, G.F., Gregor, J., Davis, N.W., Kirkpatrick, H.A., Goeden, M.A., Rose, D.J., Mau, B., and Y. Shao. 1997. The complete genome sequence of Escherichia coli K-12. Science 277:1453-62. Borriello, G., Werner, E., Roe, F., Kim, A.M., Ehrlich, G.D. and P.S. Stewart. 2004. Oxygen limitation contributes to antibiotic tolerance of Pseudomonas aeruginosa in biofilms. Antimicrob. Agents Chemother. 48:2659-64. Briedenstein, E.B.M., de la Fuente-Núñez, C., and R.E.W. Hancock. 2011. Pseudomonas aeruginosa: All roads lead to resistance. Trends Microbiol. 19:419-26. Brencic, A., McFarland, K.A., McManus, H.R., Castang, S., Mogno, I., Dove, S.L., and S. Lory. 2009. The GacS/GacA signal transduction system of Pseudomonas aeruginosa acts 49  exclusively through its control over the transcription of the RsmY and RsmZ regulatory small RNAs. Mol. Microbiol. 73:434-45. Covert, M.W., Knight, E.M., Reed, J.L., Herrgard, M.J., and B.O. Palsson. 2004. Integrating high-throughput and computational data elucidates bacterial networks. Nature 429:92-6. Croucher, N.J., and N.R. Thomson. 2010. Studying bacterial transcriptomes using RNA-seq. Curr. Opin. Microbiol. 13:619-24. Davies, D.G., Parsek, M.R., Pearson, J.P., Iglewski, B.H., Costerton, J.W. and E.P. Greenberg. 1998. The involvement of cell-to-cell signals in the development of a bacterial biofilm. Science. 280:295-8.  Davis, B.M., Quinones, M., Pratt, J., Ding, Y., and M.K. Waldor. 2005. Characterization of the Small Untranslated RNA RyhB and its regulon in Virbio cholerae. J Bacteriol. 187:4005-14. De Kievit, T.R., Gillis, R., Marx, S., Brown, C. and B.H. Iglewski. 2001. Quorum-sensing genes in Pseudomonas aeruginosa biofilms: Their role and expression patterns. Appl. Environ. Microbiol. 67:1865-73. de Lorenzo, V., Eltis, L., Kessler, B., and K.N. Timmis. 1993. Analysis of Pseudomonas gene products using lacIq/Ptrp-lac plasmids and transposons that confer conditional phenotypes. Gene 123:17-24. Delihas, N. and S. Frost. 2001. MicF: an antisense RNA gene involved in response of Escherichia coli to global stress factors. J. Mol. Biol. 313:1-12. Déziel, E., Lépine, F., Milot S., and R. Villemur. 2003. rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxylakanoyloxy)alkonoic acids (HAAs), the precursors of rhamnolipids. Microbiology 49 :2005-13. Dötsch, A., Eckweiler, D., Schniederjans, M., Zimmermann, A., Jensen, V., Scharfe, M., Geffers, R., and S. Häussler. 2012. The Pseudomonas aeruginosa transcriptome in planktonic cultures and static biofilms using RNA Sequencing. PLoS ONE. 7:e31092. Fernández, L., Breidenstein, E.B.M., Song, D., and R.E.W. Hancock. 2012. Role of intracellular proteases in the antibiotic resistance, motility, and biofilm formation of Pseudmonas aeruginosa. Antimicrob. Agents Chemother. 56:1128-32. 50  Fernández, L., Jenssen H., Bains M., Wiegand, I., Gooderham, W.J., and R.E.W. Hancock. 2012. The two-component system CprRS senses cationic peptides and triggers adaptive resistance in Pseudomonas aeruginosa independently of ParRS. Antimicrob. Agents Chemother. 56:6212-22. Friedman, L. and R. Kolter. 2004. Genes involved in matrix formation in Pseudomonas aeruginosa PA14 biofilms. Mol. Microbiol. 51:675-90. Gómez-Lozano, M., Marvig, R.L., Molin, S., and K.S. Long. 2012. Genome-wide identification of novel small RNAs in Pseudomonas aeruginosa. Environ. Microbiol. 14:2006-16. González, N., Heeb, S., Valverde, C., Kay, E., Reimann, C., Junier, T., and D. Haas. 2008. Genome-wide search reveals a novel GacA-regulated small RNA in Pseudomonas species. BMC Genomics 9:167-81. Guo, Q., Kong, W., Jin, S., Chen, L., Xu, Y. and K. Duan. 2013. PqsR-dependent and PqsR-independent regulation of motility and biofilm formation by PQS in Pseudomonas aeruginosa PAO1. J. Basic Microbiol. (Epub ahead of print). Hancock, R.E.W. 1981. Aminoglycoside uptake and mode of action-with special reference to streptomycin and gentamicin. II. effects of aminoglycosides on cells. J. Antimicrob. Chemother. 8:429-45. Holt, K.E., Parkhill, J., Mazzoni, C.J., Roumagnac, P., Weill, F.-X., Goodhead, I., Rance, R., Baker, S., Maskell, D.J., Wain, J., Dolecek, C., Achtman, M., and G. Dougan. High-throughput sequencing provides insights into genome variation and evolution in Salmonella Typhi. Nat. Genet. 40:987-93. Hoyle, B.D. and J.W. Costerton. 1991. Bacterial resistance to antibiotics: The role of biofilms. Prog. Drug Res. 37:91-105. Jackson, K.D., Starkey, M., Kremer, S., Parsek, M.R. and D.J. Wozniak. 2004. Identification of psl, a locus encoding a potential exopolysaccharide that is essential for Pseudomonas aeruginosa PAO1 biofilm formation. J. Bacteriol. 186:4466-75. Kindrachuk, K.N., Fernandez, L., Bains, M. and R.E.W. Hancock. 2011. Involvement of an ATP-dependent protease, PA0779/AsrA, in inducing heat shock in response to tobramycin in Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 55:1874-82. 51  Klausen, M., Heydorn, A., Ragas, P., Lambertsen, L., Aaes-Jorgensen, A., Molin, S. and T. Tolker-Nielsen. 2003. Biofilm formation by Pseudomonas aeruginosa wild type, flagella and type IV pili mutants. Mol. Microbiol. 48:1511-24. Köhler, T., Curty, L.K., Barja, F., van Deiden, C., and J.-C. Pechére. 2000. Swarming of Pseudomonas aeruginosa is dependent on cell-to-cell signaling and requires flagella and pili. J. Bacteriol. 182:5990-6. Kumon, H., Tomochika, K., Matunaga, T., Ogawa, M. and H. Ohmori. 1994. A sandwich cup method for the penetration assay of antimicrobial agents through Pseudomonas exopolysaccharides. Microbiol. Immunol. 38:615-9.  Leoni, L., Ciervo, A., Orsi, N., and P. Visca. 1996. Iron-regulated transcription of the pvdA gene in Pseudomonas aeruginosa: Effect of Fur and PvdS on promoter activity. J. Bacteriol. 178:2299-313. Liberati, N.T., Urbach, J.M., Miyata, S., Lee, D.G., Drenkard, E., Wu, G., Villanueva, J., Wei, T., and F.M. Ausubel. 2006. An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants. Proc. Natl. Acad. Sci. USA 103:2833-8. Lindsay, D. and A. von Holy. 2006. Bacterial biofilms within the clinical setting: What healthcare professionals should know. J. Hosp. Infect. 64:313-25. Lyczak, J.B., Cannon, C.L., and G.B. Pier. 2000. Establishment of Pseudomonas aeruginosa infection: lessons from a versatile opportunist. Microb. Infect. 2:1051-60. Ma, L., M., Conover, H. Lu, Parsek, M.R., Bayles, K. and D.J. Wozniak. 2009. Assembly and development of the Pseudomonas aeruginosa biofilm matrix. PLoS Pathog. 5:e1000354. Macia, M.D., Perez, J.L., Molin, S. and A. Oliver. 2011. Dynamics of mutator and antibiotic-resistant populations in a pharmacokinetic/pharmacodynamic model of Pseudomonas aeruginosa biofilm treatment. Antimicrob. Agents Chemother. 55:5230-7.  Marvrodi, D.V., Bonsall, R.F., Delaney, S.M., Soule, M.J., Phillips, G., and L.S. Thomashow. 2001. Functional analysis of genes for biosynthesis of pyocyanin and phenazine-1-carboxamide from Pseudomonas aeruginosa PAO1. J. Bacteriol. 183:6454-64. Massé, E. and S. Gottesman. 2002. A small RNA regulates the expression of genes involved in iron metabolism in Escherichia coli. Proc. Natl. Acad. Sci. U.S.A. 99:4620-5. McClelland, M., Sanderson, K.E., Spieth, J., Clifton, S.W., Latreille, P., Courtney, L., Porwollik, S., Ali, J., Dante, M., Du, F., Hou, S., Layman, D., Leonard, S., Nguyen, C., 52  Scott, K., Holmes, A., Grewal, N., Mulvaney, E., Ryan, E., Sun, H., Florea, L., Miller, W., Stoneking, T., Nhan, M., Waterson, R., and R.K. Wilson. 2001. Complete genome sequence of Salmonella enterica serovar Typhimurium LT2. Nature 413:852-6. McPhee, J.B., Lewenza, S., and R.E.W. Hancock. 2003. Cationic antimicrobial peptides activate a two-component regulatory system, PmrA-PmrB, that regulates resistance to polymyxin B and cationic antimicrobial peptides in Pseudomonas aeruginosa. Mol. Microbiol. 50:205-17. Mey, A.R., Craig, S.A., and S.M. Payne. 2005. Characterization of Vibrio cholerae RyhB: The RyhB regulon and role of ryhB in biofilm formation. Infect. Immun. 73:5706-19. Mirleau, P., Delorme, S., Philippot, L., Meyer, J-M., Mazurier, S., and P. Lemanceau. 2000. Fitness in soil and rhizosphere of Pseudomonas fluorescens C7R12 compared with a C7R12 mutant affected in pyoverdin synthesis and uptake. FEMS Microbiol. Ecol. 34:35-44. Moskowitz, S.M., Ernst, R.K., and S.I. Miller. 2004. PmrAB, a two-component regulatory system of Pseudomonas aeruginosa that modulates resistance to cationic antimicrobial peptides and addition of aminoarabinose to lipid A. J. Bacteriol. 186:575-9. Mulcahy, H., Charron-Mazenod, L. and S. Lewenza. 2008. Extracellular DNA chelates cations and induces antibiotic resistance in Pseudomonas aeruginosa biofilms. PLoS Pathog. 4:e1000213. O'Toole, G.A. and R. Kolter. 1998. Flagellar and twitching motility are necessary for Pseudomonas aeruginosa biofilm development. Mol. Microbiol. 30:295-304.  Ochsner, U.A., Wilderman, P.J., Vasil, A.I., and M.L. Vasil. 2002. GeneChip® expression analysis of the iron starvation response in Pseudomonas aeruginosa: Identification of novel pyoverdin biosynthesis genes. Mol. Microbiol. 45:1277-87. Oglesby, A., Farrow III, J.M., Lee, J.-H., Tomaras, A.P., Greenberg, E.P., Pesci, E.C., and M.L. Vasil. 2008. The influence of iron on Pseudomonas aeruginosa physiology: A regulatory link between iron and quorum sensing. J. Biol. Chem. 283:15558-67. Oglesby-Sherrouse, A.G., and M.L. Vasil. 2010. Characterization of a Heme-regulated non-coding RNA encoded by the prrF locus of Pseudomonas aeruginosa. PLoS ONE. 5:e9930. Overhage, J., Lewenza, S., Marr, A.K., and R.E.W. Hancock. 2007. Identification of genes involved in swarming motility using a Pseudomonas aeruginosa PAO1 mini-Tn5-lux mutant library. J. Bacteriol. 189:2164-2169. 53  Overhage, J., Bains, M., Brazas, M.D., and R.E.W. Hancock. 2008. Swarming of Pseudomonas aeruginosa is a complex adaptation leading to increased production of virulence factors and antibiotic resistance. J. Bacteriol. 190:2671-9. Poole, K. 2001. Multidrug efflux pumps and antimicrobial resistance in Pseudomonas aeruginosa and related organisms. J. Mol. Microbiol. Biotechnol. 3:255-64. Prince, R.W., Storey, D.G., Vasil, A.I., and M.L. Vasil. 1991. Regulation of toxA and regA by the Escherichia coli fur gene and identification of a Fur homologue in Pseudomonas aeruginosa PA103 and PAO1. Mol. Microbiol. 5:2823-31. Schweizer, H.P. 1991. Improved broad-host-range lac-based plasmid vectors for the isolation and characterization of protein fusions in Pseudomonas aeruginosa. Gene 103:87-92. Sonnleitner, E., Sorger-Domenigg, T., Madej, M.J., Findeiss, S., Hackermüller, J., Hüttenhofer, A., Stadler, P.F., Bläsi, U., and I. Moll. 2008. Detection of small RNAs in Pseudomonas aeruginosa by RNomics and structure-based bioinformatic tools. Microbiology 154:3175-87. Sonnleitner, E., Abdou, L, and D. Haas. 2009. Small RNA as global regulator of carbon catabolite repression in Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. U.S.A. 106:21866-71. Sonnleitner, E. and D. Haas. 2011. Small RNAs as regulators of primary and secondary metabolism in Pseudomonas aeruginosa. Appl. Microbiol. Biotechnol. 91:63-79. Sonnleitner, E., González, N., Sorger-Domenigg, T., Heeb, S., Richter, A.S., Backofen, R., Williams, P., Hüttenhofer, A., Haas, D., and U. Bläsi. 2011. The small RNA PhrS stimulates synthesis of the Pseudomonas aeruginosa quinolone signal. Mol. Microbiol. 80:868-85. Sriramulu, D.D., H. Lunsdorf, J.S. Lam, and U. Romling. 2005. Microcolony formation: A novel biofilm model of Pseudomonas aeruginosa for the cystic fibrosis lung. J. Med. Microbiol. 54:667-76. Stover, C.K., Pham, X.Q., Erwin, A.L., Mizoguchi, S.D., Warrener, P., Hickey, M.J., Brinkman, F.S.L., Hufnagle, W.O., Kowalik, D.J., Lagrou, M., Garber, R.L., Goltry, L., Tolentino, E., Westbrock-Wadman, S., Yuan, Y., Brody, L.L., Coulter, S.N., Folger, F.R., Kas, A., Larbig, K., Lim, R., Smith, K., Spencer, D., Wong, G.K., Wu, Z.P., Reizer, 54  J., Saier, M.H., Hancock, R.E.W., Lory, S., and M.V. Olson. 2000. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature. 406:959-64. Storz, G., Vogel, J., and K.M. Wasserman. 2011. Regulation of Small RNAs in Bacteria: Expanding Frontiers. Mol. Cell 43:880-91. Toutain, C.M., N.C. Caizza, M.E. Zegans and G.A. O'Toole. 2007. Roles for flagellar stators in biofilm formation by Pseudomonas aeruginosa. Res. Microbiol. 158:471-7. Vaezzadeh, A.R., Deshusses, J.M.P., Wariel, P, François, Zimmermann-Ivol, C.G., Lescuyer, P, Schrenzel, J., and D.F. Hochstrasser. 2010. Accelerated digestion for high-throughput proteomic analysis of whole bacterial proteomes. J. Microbiol. Methods 80:56-62. Vasil, M.L. and U.A. Ochsner. 1999. The response of Pseudomonas aeruginosa to iron: Genetics, biochemistry and virulence. Mol. Microbiol. 34:399-13. Vasseur, P., Vallet-Gely, I., Soscia, C., Genin, S. and A. Filloux. 2005. The pel genes of the Pseudomonas aeruginosa PAK strain are involved at early and late stages of biofilm formation. Microbiology. 151:985-97. Wang, J., Zhou, J.Y., Qu, T.T., Shen, P., Wei, Z.Q., Yu, Y.S. and L.J. Li. 2010. Molecular epidemiology and mechanisms of carbapenem resistance in Pseudomonas aeruginosa isolates from chinese hospitals. Int. J. Antimicrob. Agents 35:486-91. Wiegand, I., Hilpert, K., and R.E.W. Hancock. 2008. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nature Protocols 3:163-175. Wilderman, P.J., Sowa, N.A., FitzGerald D.J., FitzGerald, P.C., Gottesman, S., Ochsner, U.A., and M.L. Vasil. 2004. Identification of tandem duplicate regulatory small RNAs in Pseudomonas aeruginosa involved in iron homeostasis. Proc. Natl. Acad. Sci. U.S.A. 101:9792-7. Whitchurch, C.B., Tolker-Nielsen, T., Ragas, P.C. and J.S. Mattick. Extracellular DNA required for bacterial biofilm formation. Science. 2002; 29:1487.  Whooley, M.A. and A.J. McLoughlin. 1982. The regulation of pyocyanin production in Pseudomonas aeruginosa. European J Appl Microbiol Biotechnol. 15:161-6. Wurtzel, O., Yoder-Himes, D.R., Han, K., Dandekar, A.A., Edelheit, E., Greenberg, P., Sorek, R., and S. Lory. 2012. The single-nucleotide resolution transcriptome of Pseudomonas aeruginosa grown in body temperature. PLoS Pathog. 8:e1002945. 55  Yeung, A.T.Y., Torfs, E.C.W., Jamshidi, F., Bains, M., Wiegand, I., Hancock, R.E.W., and J. Overhage. 2009. Swarming of Pseudomonas aeruginosa is controlled by a broad spectrum of transcriptional regulators, including MetR. J. Bacteriol. 191:5592-602. Xu, K.D., Stewart, P.S., Xia, F., Huang, C.T. and G.A. McFeters. 1998. Spatial physiological heterogeneity in Pseudomonas aeruginosa biofilm is determined by oxygen availability. Appl. Environ. Microbiol. 64:4035-9. 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.24.1-0167460/manifest

Comment

Related Items