Multifaceted RNA-Mediated Regulatory Mechanisms in Streptococcus Pyogenes

Multifaceted RNA-mediated regulatory mechanisms in Streptococcus pyogenes

Anaïs Le Rhun

Department of Molecular Biology Umeå Center for Microbial Research (UCMR) Laboratory for Molecular Infection Medicine Sweden (MIMS) Umeå University Umeå 2015

Responsible publisher under swedish law: the Dean of the Medical Faculty This work is protected by the Swedish Copyright Legislation (Act 1960:729) ISBN: 978-91-7601-304-5 ISSN: 0346-6612 New series: 1732 Cover picture: Anaïs Le Rhun, Thibaud Renault, Ines Fonfara; Streptococcus pyogenes and phage DT1 microscopy: Manfred Rohde (HZI, Braunschweig) Electronic version available at http://umu.diva-portal.org/ Printed by: Print & Media (Umeå University) Umeå, Sweden 2015

To my parents, family and friends, To everyone who encouraged me,

“I have a perfect cure for a sore throat: cut it.”

Alfred Hitchcock

Table of Contents

Table of Contents i Table of Illustrations iii Abstract iv Abbreviations v Aims of the thesis vi List of publications vii Introduction 1 I. Regulatory RNAs in bacteria 1 I.1. The non-coding RNA world 1 I.2. Regulation by non-coding RNAs 2 I.2.1. cis-encoded antisense RNAs 2 I.2.2. Riboswitches 4 I.2.3. trans-encoded sRNAs 5 I.2.4. CRISPR 7 I.3. sRNA-binding proteins 9 I.3.1. The chaperone Hfq 9 I.3.2. RNases 10 I.4. How to find non-coding RNAs in bacteria? 11 I.4.1. In silico predictions 11 I.4.2. In vivo determination 12 I.5. How to find targets of trans-acting sRNAs? 13 I.5.1. In silico target predictions 13 I.5.2. In vivo approaches 14 II. Streptococcus pyogenes, the flesh-eating bacteria 15 II.1. Taxonomy 15 II.2. Pathogenesis 17 II.2.1. S. pyogenes pathologies 17 II.2.2. Epidemiology 17 II.3. Virulence factors 18 II.4. Regulation of virulence factor expression 20 II.4.1. Stand-alone response regulators 21 II.4.2. Two-component systems 21 II.4.3. sRNAs 23 II.4.4. RNases 25 II.5. Transcriptomics studies 27 III. sRNAs involved in bacterial immunity – CRISPR-Cas systems 28 III.1. The CRISPR-Cas immune system 28 III.2.1. RNA maturation, DNA interference and adaptation 33 III.2.2. tracrRNA 36

Table of Contents

III.2.3. Cas9 36 III.3. CRISPR-Cas and regulation of virulence 39 Results and Discussion 41 I. Paper I – Novel sRNAs in Streptococcus pyogenes 41 I.1. sRNA sequencing of S. pyogenes reveals novel putative sRNAs 41 I.2. sRNAs regulated by RNases 42 I.3. Conclusion 43 II. Paper II – tracrRNA and Cas9 families 44 II.1. Bioinformatic analyses of type II CRISPR-Cas systems 44 II.2. sRNA sequencing 45 II.3. Conclusion 45 III. Paper III – dual-RNA and Cas9 orthologous systems 46 III.1. Origin of type II CRISPR-Cas systems 46 III.2. The conserved RuvC and HNH motifs of Cas9 47 III.3. Cas9 exchangeability in tracrRNA:pre-crRNA maturation by RNase III 47 III.4. Cas9 exchangeability in dual-RNA:Cas9 DNA interference 48 III.5. Conclusion 48 Summary of the main findings of this thesis 50 I. Small RNAs in S. pyogenes (paper I) 50 II. type II CRISPR-Cas systems (papers II and III) 50 Acknowledgements 51 References 53 Appendix: Papers I-III 75

Table of Illustrations

Figure 1. sRNA mechanisms of action...... 9

Figure 2. Electron microscopy of S. pyogenes M1 GAS...... 16

Figure 3. Virulence factors expressed by S. pyogenes at different stages during infection...... 20

Figure 4. Direct targets of FasX sRNA in S. pyogenes M1 GAS...... 25

Figure 5. The three stages of CRISPR-Cas immunity...... 31

Figure 6. Type II CRISPR-Cas maturation and DNA interference mechanisms...... 35

iii

Abstract

Bacterial pathogens rely on precise regulation of gene expression to coordinate host infection processes and resist invasion by mobile genetic elements. An interconnected network of protein and RNA regulators dynamically controls the expression of virulence factors using a variety of mechanisms. In this thesis, the role of selected regulators, belonging to the class of small RNAs (sRNAs), is investigated. Streptococcus pyogenes is a pathogen responsible for a wide range of human diseases. Genome-wide screenings have indicated that S. pyogenes encodes numerous sRNAs, yet only a limited number have been characterized. A major goal of this study was to identify and characterize novel sRNAs and antisense RNAs (asRNAs) using RNA sequencing analysis. We validated 30 novel sRNAs and asRNAs, and identified 9 sRNAs directly cleaved by the ribonucleases RNase III and/or RNase Y. Previous work from the laboratory has highlighted the role of sRNAs from the type II Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated proteins (CRISPR-Cas) systems in S. pyogenes. CRISPR-Cas systems provide adaptive immunity to prokaryotes against infection by mobile genetic elements. Two sRNAs, forming a complementary duplex (dual-RNA), are effectors of this system: the mature CRISPR RNAs (crRNAs) and the trans-activating crRNA (tracrRNA). The dual-RNA guides the Cas9 endonuclease to cleave both strands of the invading DNA in a sequence-specific manner. This RNA-programmable CRISPR-Cas9 system is now utilized for genome editing and engineering in a wide range of cells and organisms. To expand the potentialities of this tool, we both, searched for Cas9 orthologs and predicted numerous tracrRNA orthologs. We defined tracrRNA as a new family of sRNAs sharing the ability to base-pair to cognate crRNAs, without conservation of structure, sequence or location. We show that Cas9 and the dual tracrRNA:crRNAs are only interchangeable between closely related type II CRISPR-Cas systems. In summary, this thesis presents new insights into RNA-mediated regulatory mechanisms in S. pyogenes. We identified and described the expression of novel sRNAs, highlighting potential antisense RNAs. Focusing on the dual-RNA programmable type II CRISPR-Cas system, we provided evidence for co-evolution of the Cas9 enzyme with tracrRNA:crRNA, a basis for Cas9 multiplexing in genome editing.

Abbreviations

asRNA antisense RNA BLP bacterial lipoprotein BS binding site Cas CRISPR-associated CASCADE CRISPR-associated complex for antiviral defense CDS coding sequence cia competence induction and altered cefotaxime susceptibility cov control of virulence genes CRISPR Clustered Regularly Interspaced Short Palindromic Repeats crRNA CRISPR RNA dCas9 dead Cas9 DSB double-strand breaks dual-RNA tracrRNA:crRNA duplex ECM extracellular matrix HDR homology directed repair HGT horizontal gene transfer IGR intergenic region KO knock-out nCas9 nickase Cas9 ncRNA non-coding RNA NHEJ non-homologous end-joining nts nucleotides PAM protospacer adjacent motif pre-crRNA precursor CRISPR RNA rgRNA RNA-targeting guide RNA RNase ribonuclease rRNA ribosomal RNA sag streptolysin associated genes SAM S-adenosyl-L-methionine SD Shine Dalgarno sgRNA single guide RNA SpCas9 S. pyogenes Cas9 sRNA small RNA SRP signal recognition particle TA toxin-antitoxin TALEN transcription activation-like effector nuclease TCS two-component system tmRNA transfer-message RNA tracrRNA trans-activating crRNA UTR untranslated region ZFN zinc-finger nucleases

Aims of the thesis

Bacteria have evolved elaborate strategies to rapidly adapt to changing environments (e.g. attacks from the host immune system or bacteriophage). To understand the mechanisms responsible for this adaptation, we aimed to characterize bacterial regulation of gene expression. In addition to contributing to the fundamental understanding of bacterial physiology, these studies can lead to the identification of putative targets for novel antibiotics that might improve prevention and treatment of bacterial infections. The first goal of this study was to identify and characterize novel sRNAs in S. pyogenes. Bacterial sRNAs regulate fundamental adaptive pathogenicity-associated processes affecting translation (base-pairing with target mRNAs) or acting at a post-translational level (protein sequestration). Only a limited number of sRNAs were described in this human pathogen (Le Rhun and Charpentier, 2012) and numerous questions were still to be addressed, such as the number, the location, and the level of expression of sRNAs. We further aimed to characterize their level of regulation by growth phase and/or RNases (I. Paper I – Novel sRNAs in Streptococcus pyogenes page 41). One of the most expressed sRNAs in S. pyogenes, tracrRNA (trans- activating crRNA) – already identified in a previous sRNA screening (Deltcheva et al., 2011) – was found to be essential for both the steps of type II precursor CRISPR RNA (pre-crRNA) maturation and DNA interference (Deltcheva et al., 2011; Jinek et al., 2012). The second goal of this study was to provide an in-depth characterization of tracrRNA. To this end, we studied the conservation of CRISPR-Cas type II loci organization, and tracrRNA expression and processing in various bacterial species (II. Paper II – tracrRNA and Cas9 families page 44). Further questions about the evolution of the type II CRISPR-Cas system and of the exchangeability of tracrRNA and Cas9 among distinct type II systems were raised, leading us to test the activity of orthologous type II systems against invading DNA, and determine whether orthologous tracrRNA and Cas9 are interchangeable (III. Paper III – dual-RNA and Cas9 orthologous systems page 46).

vi List of publications

List of publications

I. Le Rhun A., Beer, Y.Y., Reimegård J., Chylinski K. and Charpentier E. (2015). RNA sequencing uncovers antisense RNAs and novel small RNAs in Streptococcus pyogenes. Accepted for publication in RNA biology.

II. Chylinski K., Le Rhun A. and Charpentier, E. (2013). The tracrRNA and Cas9 families of type II CRISPR-Cas immunity systems. RNA Biology. 10:5, 726–737.

III. Fonfara I.*, Le Rhun A.*, Chylinski K., Makarova K.S., Lécrivain A.-L., Bzdrenga J., Koonin E.V. and Charpentier E. (2014). Phylogeny of Cas9 determines functional exchangeability of dual- RNA and Cas9 among orthologous type II CRISPR-Cas systems. Nucleic Acids Research. 42:4, 2577–2590. *Contributed equally

vii

Introduction

I. Regulatory RNAs in bacteria

I.1. The non-coding RNA world

Main actors of the central dogma of molecular biology, RNA molecules comprise biotypes involved in protein synthesis, including ribosomal RNAs (rRNAs), transfer RNAs (tRNAs) and messenger RNAs (mRNAs). Over the past 30 years, increasing evidence has indicated a new role for RNA species that are not translated into proteins: the non-coding RNAs (ncRNAs). These regulatory RNAs, also referred to as small RNAs (sRNAs), have important biological functions in all kingdoms of life. This chapter will only discuss sRNAs encoded in bacteria. In the 1960s and 70s, highly expressed sRNAs – 4.5S RNA, 6S RNA, 10Sa RNA (tmRNA), 10Sb (RNase P RNA) – were first observed in Escherichia coli, but their functions remained elusive (Griffin, 1971; Hindley, 1967; Lee et al., 1978). The first regulatory mechanisms were discovered later, when plasmid-encoded antisense RNAs (asRNAs) were shown to inhibit plasmid replication, thus controlling copy number and plasmid incompatibility (Stougaard et al., 1981; Tomizawa and Itoh, 1981). In the early 1980s, two Nobel laureates, Altman and Cech, described RNA molecules with catalytic properties, the RNA component of the RNase P involved in the maturation of tRNAs (Stark et al., 1978) and the self-splicing pre-rRNA (Cech et al., 1981), respectively. These RNAs acting like enzymes were afterwards named ribozymes (ribonucleic enzymes). Since the discovery of the first sRNAs, the field of sRNA detection and characterization has expanded quickly. Although originally regulatory functions were only assigned to proteins, it is now clear that sRNAs play important regulatory roles and possess unique characteristics, with a reduced metabolic cost compared to proteins (Beisel and Storz, 2010). These small transcripts can rapidly and reversibly modulate bacterial adaptation by controlling target gene expression in response to environmental changes. sRNAs are often expressed under specific physiological conditions (e.g. stress response) and, in some cases, are degraded while performing their function (shutdown mechanisms are therefore not necessary for those sRNAs) (Beisel and Storz, 2010; Gottesman, 2004). sRNAs are versatile; a single sRNA can regulate multiple targets, and distinct

1 Introduction sRNAs can regulate the same target (Gottesman, 2004). Their length ranges from 50 to 600 nt and their structure – often composed of stem loops – is generally stable (Gottesman, 2005; Vogel and Wagner, 2007). sRNAs can affect gene expression at several levels such as replication, transcription, post-transcription, translation, and post- translation but also translocation and degradation of proteins (Gottesman, 2004). They are involved in a plethora of cellular processes including quality control, enzymatic processes, stress response, ion homeostasis, virulence control, metabolism (carbon, sugar, amino acid, iron), biofilm formation and quorum sensing (Michaux et al., 2014; Repoila and Darfeuille, 2009). In the following section, various sRNA regulatory mechanisms will be presented.

I.2. Regulation by non-coding RNAs

RNA regulators use various mechanisms, acting both in cis or in trans1 and new modes of action are constantly discovered. Nonetheless, all sRNAs share common characteristics (Gottesman, 2004) : (1) They are synthesized or activated under specific conditions; (2) Their sequence and/or structure are important for specific target recognition; (3) Their action is generally time limited (rapid turnover).

I.2.1. cis-encoded antisense RNAs

The first asRNA regulated systems were discovered in mobile genetic elements where they control plasmid replication, transposon mobility, and bacteriophage lysis/lysogeny switches. These processes are explained in detail in (Wagner et al., 2002; Wagner and Simons, 1994; Weaver, 2007). cis-encoded asRNAs and their targets are transcribed in an overlapping manner from opposite DNA strands, therefore they are fully complementary. However, asRNAs act in trans as they regulate a different RNA molecule, in contrast to cis-acting elements that regulate their own RNA molecule (e.g. section I.2.2. Riboswitches page 4). asRNAs can be classified in three categories depending on their location; antisense to 5’ or 3’ untranslated regions (UTRs) or to coding sequences (CDSs). Their sizes range

1 In this report, RNA encoded from the same gene locus (same strand or opposite strand) are considered as cis regulatory elements, and RNA encoded from different locus are named trans regulatory elements.

2 Introduction

from 100 to 300 nt for small asRNAs, and between 700 and 3500 nt for long asRNAs (Georg and Hess, 2011). Some long mRNAs overlap with the UTR regions of adjacent genes and act as asRNAs (Georg and Hess, 2011). Genome-wide overlapping transcription has been reported in both Gram-negative and Gram-positive bacteria, however the abundance of these RNAs is still controversial (probably due to methodological bias from the different methods used). The transcription of long asRNAs can affect gene expression through various mechanisms, the most common effect being the inhibition of target production. For example, the double- stranded (ds) duplexes asRNA:target RNA can be recognized and processed by ribonuclease III (RNase III), resulting in the production of short RNA fragments (Lasa et al., 2011; Lybecker et al., 2014). asRNAs can also stabilize their targets by forming RNA duplexes that protect targets from degradation (e.g. inhibition of RNase E dependent decay) (Brantl, 2012; Georg and Hess, 2011). The stabilization of the target can also derive from RNA processing, as exemplified in E. coli. GadY sRNA base-pairs within the internal UTR of the bicistronic gadX-gadW mRNA and the duplex is cleaved by RNase III. The processed gadX (transcriptional activator of the acid response system) and gadW mRNAs gain an enhanced stability and thus, the expression of regulated acid resistance genes is increased (Opdyke et al., 2004) (Figure 1 A.1 page 9). In addition, asRNA mechanisms can be found in type I Toxin– Antitoxin systems (TA systems) (Brantl and Jahn, 2015; Fozo et al., 2008; Gerdes and Wagner, 2007). In most of the type I TA systems, the genes encoding the stable toxin and the labile RNA antitoxin are located on opposite strands. The RNA antitoxin can be complementary to the 5′ or 3' end of the toxin gene. Thus the inhibition of toxin expression by antitoxins relies on base-pairing of the two RNAs, which blocks translation initiation or leads to mRNA degradation (Brantl and Jahn, 2015; Fozo et al., 2008; Gerdes and Wagner, 2007). For example, in Bacillus subtilis, the 3' UTR of the RNA antitoxin RatA and the mRNA toxin txpA overlap by approximately 75 nt, allowing the formation of a sRNA:mRNA duplex rapidly degraded by RNase III. Thus, cell lysis by the TxpA protein is inhibited (Durand et al., 2012; Silvaggi et al., 2005) (Figure 1 A.2 page 9).

Remarkably, some asRNAs, similarly to trans-encoded sRNAs can also interact with an imperfectly complementary region of their target (I.2.3. trans-encoded sRNAs page 5). The SprA1AS RNA is transcribed antisense to the 3' UTR of the sprA1 gene, encoding the

3 Introduction cytolytic peptide PepA1 whose function is to alter membrane integrity and induce cell death. Despite 35 nt of full complementarity between SprA1AS and sprA1 3' UTR, SprA1AS acts in trans by binding to the translation initiation region (TIR) of sprA1 mRNA, preventing its translation and toxic effect for the bacteria (Sayed et al., 2012).

I.2.2. Riboswitches

Riboswitches are structured 5’ UTRs present in certain mRNAs. Upon speciﬁc ligand binding, riboswitches can cause the modification of transcription or translation of the downstream mRNA. A riboswitch structure typically consists of an aptamer domain, which binds the ligand, and an expression platform, which regulates the binding/release of either the RNA polymerase or the ribosome and, consequently, the expression of the downstream gene is switched on and off (Breaker, 2012, 2011; Mellin and Cossart, 2015; Winkler, 2005; Winkler and Breaker, 2005). Ligand binding to the aptamer domain results in conformational changes within the riboswitch that can influence protein expression at two levels: 1/ formation of anti-terminator/terminator hairpins affecting transcription or, 2/ modification of the ribosome binding site (RBS) availability regulating translation (Figure 1 B. page 9). Several mechanisms have been described, affecting only transcription, translation, or both. Transcription attenuation is the most common riboswitch mechanism among Gram positive bacteria, in contrast to Gram negative bacteria, which use translational attenuation (Barrick and Breaker, 2007; Nudler and Mironov, 2004). Often, riboswitch-controlled proteins are involved in the biosynthesis or transport of the riboswitch ligand (e.g. metal ions, vitamin cofactors, amino-acids, nucleobases, and sugars) (Coppins et al., 2007; Serganov and Nudler, 2013). For example, the S-adenosyl- L-methionine (SAM-I) riboswitch of B. subtilis is located in the 5' UTR of genes involved in methionine or cysteine biosynthesis. When SAM levels are low, an anti-terminator hairpin is formed and the downstream genes are transcribed. In contrast, high levels of SAM lead to the formation of a terminator stopping the transcription (Epshtein et al., 2003; McDaniel et al., 2003) (Figure 1 B. page 9).

Remarkably, 5' UTR riboswitches can also function in trans, as demonstrated by the SreA SAM riboswitch, which regulates the expression of the virulence regulator PrfA in L. monocytogenes (Loh

4 Introduction

et al., 2009). SreA binds to the 5' UTR of prfA mRNA resulting in decreased expression level of PrfA (Loh et al., 2009).

A particular class of riboswitches, called thermosensors can sense temperature changes. They allow bacteria to adapt to temperature variation between environmental and infection conditions, and to express the appropriate genes accordingly (Hurme and Rhen, 1998). Examples of RNA thermosensors are the repression of the heat shock gene expression (ROSE) and the fourU elements (Narberhaus, 2002; Waldminghaus et al., 2007). In both examples, hairpin structures sequester the RBS – also named Shine Dalgarno (SD) sequence in bacteria – at low temperatures but are destabilized when temperatures increase, leading to translation activation (Kortmann and Narberhaus, 2012). Thermosensors can also regulate virulence gene expression as demonstrated by the 5’ UTR of the prfA mRNA in Listeria monocytogenes (Johansson et al., 2002). At temperatures below 30°C, the RBS is inaccessible to the ribosome. During infection (higher temperatures), the RNA conformation changes, allowing translation of the PrfA transcriptional regulator, and therefore of the virulence factors under its control (Johansson et al., 2002) (Figure 1 page 9).

Due to their ability to bind to a ligand and control bacterial growth, riboswitches are potential drug targets (Blount and Breaker, 2006). Synthetic riboswitches have also been developed to conditionally control gene expression (Groher and Suess, 2014).

I.2.3. trans-encoded sRNAs

The majority of sRNAs that have been studied so far act through base-pairing with target mRNAs that are not encoded in the same region of the genome, affecting positively or negatively their stability and/or translation. In contrast to the cis-encoded asRNAs, trans-encoded sRNAs only share short regions of incomplete complementarity with their target mRNAs including both canonical and non-canonical base-pairings (Bobrovskyy and Vanderpool, 2013). These interactions with 5' UTR, 3' UTR or the CDS of target RNAs, are highly dependent on the secondary structure of the sRNAs and often on the Hfq chaperone protein (Gottesman, 2004; Vogel and Luisi, 2011). As mentioned earlier, this partial complementarity allows one sRNA to act on multiple target mRNAs, but also several sRNAs to recognize the same target.

5 Introduction

trans-acting sRNAs do not only originate from intergenic regions (IGRs); they can also be part of mRNA UTRs. 3' UTR sRNAs can either originate from processing of the mRNA or can be transcribed from their own promoter (internal to the CDS) (Miyakoshi et al., 2015). Most trans-acting sRNAs silence gene expression. They base- pair within the 5’ UTR of the target mRNA, at the RBS and/or near the start codon. This prevents the ribosome attachment and thereby inhibits translation of the target gene. Nevertheless, some sRNAs activate gene expression. For example, the formation of a 5’ UTR structure inhibiting translational initiation can be prevented by the base pairing of a sRNA, allowing the ribosome to access the RBS and the translation to start (Papenfort and Vanderpool, 2015) (Figure 1 C.1. page 9). Translational activation may also be the result of direct stabilization of the mRNA target by interference with mRNA decay. For example, the 5′ UTR of the mRNA irvA can target the CDS of the glucan-binding proteins C (gbpC) mRNA in Streptococcus mutans, protecting its degradation by RNase J2 (Liu et al., 2015). This activation of GbpC production is important for S. mutans cariogenicity (Matsumura et al., 2003) (Figure 1 C.2 page 9). One example of trans-acting sRNA targeting mRNAs is the RNAIII from Staphylococcus aureus. RNAIII is the main effector of the accessory gene regulator (Agr) quorum sensing (QS) system, which regulates virulence-associated genes in response to cell density (Novick and Geisinger, 2008). RNAIII encodes the δ-hemolysin (responsible for cell lysis) but also acts as a sRNA, positively regulating the translation of α-hemolysin (Hla) (Novick et al., 1993) and extracellular adherence protein (Eap) (Liu et al., 2011), while downregulating the expression of various virulence genes (e.g. Staphylococcal protein A immune evasion molecule: SpA, transcriptional repressor of toxins: Rot, and Staphylocoagulase) (Boisset et al., 2007; Chevalier et al., 2010; Huntzinger et al., 2005).

Other sRNAs bind to proteins and antagonize their functions. For example, type III TA systems encode RNA pseudoknots antitoxins that bind the toxin proteins. Other protein-binding sRNAs (e.g. CsrB, CsrC and 6S RNA) neutralize the function of their target protein by mimicking the structure of the nucleic acids targeted by the protein. E. coli sRNAs CsrB and CsrC (carbon storage regulator B and C) contain repeated sequences recognized by CsrA, a global regulator of protein metabolic pathways, biofilm formation, motility, virulence, quorum sensing, and stress response (Romeo et al., 2013). Binding to

6 Introduction

CsrB and CsrC sRNAs titrate CsrA away from its mRNA targets (Liu et al., 1997; Weilbacher et al., 2003) (Figure 1 D. page 9). The 6S RNA balances temporal gene expression by controlling the transition between exponential and stationary phase of growth. The 6S RNA structure mimics an open promoter and sequesters the σ70 subunit of the RNA polymerase, which recognizes promoters of genes expressed during the exponential phase of growth (Steuten et al., 2014; Wassarman and Storz, 2000). 6S RNA accumulates in the stationary phase and causes a switch of RNA polymerase subunit from σ70 to σS (recognizes promoters of genes expressed during the stationary phase of growth) leading to the transcription of different genes (Wassarman, 2007). Remarkably, the 6S RNA itself serves as a template for the RNA polymerase and is transcribed into two small product RNAs (pRNAs) of 14–20 nt. Transcription of the pRNAs destabilizes the 6S RNA/σ70 complex, releasing the σ70 subunit (Wassarman and Saecker, 2006). Other protein binding sRNAs display an intrinsic catalytic activity such as the RNA component of RNase P (Kazantsev and Pace, 2006) or play a role in a ribonucleoprotein complex for instance the 4.5S RNA from the signal recognition particle (SRP, protein secretion) (Poritz et al., 1990) and the transfer-message RNA (tmRNA) during trans-translation (protein synthesis quality control) (Moore and Sauer, 2007).

Recently published summaries of sRNA mechanisms of action can be found in (Brantl, 2012; Caldelari et al., 2013; Brantl and Brückner, 2014).

I.2.4. CRISPR

The clustered regularly interspaced short palindromic repeats RNAs (CRISPR RNAs), are part of a bacterial adaptive immune system, which recognizes foreign nucleic acids and leads to their degradation. This topic will be discussed in chapter III. sRNAs involved in bacterial immunity – CRISPR-Cas systems page 28.

7 Introduction

8 Introduction

Figure 1. sRNA mechanisms of action. A.1. GadY asRNA (green) is encoded antisense to the gadX-gadW operon. GadY forms a duplex with the 3' UTR of gadX, which is recognized and cleaved by RNase III. This cleavage leads to the formation of stabilized single gadX and gadW mRNAs, subsequently translated into GadX and GadW, which regulate the expression of acid resistance genes. A.2. RatA antitoxin and txpA toxin are encoded within the same locus, but from opposite DNA strands (antisense). Thus, the 3' end of RatA (green) is fully complementary to the 3' end of txpA mRNA (orange). RNase III (purple) cleaves the RNA duplex, leading to the degradation of both RNAs, preventing txpA mRNA translation and therefore cell lysis. B. Two mechanisms of action of riboswitches are represented: anti-terminator vs terminator hairpins that regulate transcription and availability vs sequestration of the ribosome binding site (RBS) that regulate translation. Top: In presence of S-adenosyl-l-methionine (SAM, red), the anti-terminator loop is replaced by a terminator hairpin and the downstream genes involved in methionine or cysteine biosynthesis are no longer transcribed. Bottom: when temperature reaches 37°C during infection, L. monocytogenes PrfA global regulator is produced and can activate expression of virulence genes that are under its control. At temperatures below 30°C, the RBS (orange) of prfA mRNA is sequestered and prfA mRNA is not translated. C. trans-acting sRNAs can target mRNAs. C.1. Top: thermosensor: sRNA:mRNA duplex formation interferes with translation. Upon binding of the sRNA to the mRNA, the RBS (orange) is sequestrated and translation is repressed. Bottom: Upon binding of the sRNA to the mRNA, the RBS is released and translation is possible. C.2 sRNA:mRNA duplex formation interferes with RNA decay. The 5' UTR of the irvA RNA (green) base-pairs with the coding sequence (CDS) or the gbpC mRNA (orange), protecting gvpC mRNA from degradation by RNase J2. D. CsrB sRNA (green) contains repeated sequences recognized by the CsrA protein (purple), and can titrate it away from its mRNA targets involved in regulation of E. coli virulence. Unstable mRNAs are depicted in grey.

I.3. sRNA-binding proteins

Among proteins able to bind RNA, chaperones and RNases play a critical function in sRNAs regulation.

I.3.1. The chaperone Hfq

A major player involved in regulation by sRNAs is the thermostable chaperone Hfq (Brennan and Link, 2007; De Lay et al., 2013; Storz et al., 2004). Hfq is conserved in a wide range of bacteria and plays a role in virulence regulation. In a number of species, Hfq associates with many RNAs and facilitates and/or stabilizes sRNA:target mRNA duplex formation (Brennan and Link, 2007; Chao and Vogel, 2010; Valentin-Hansen et al., 2004). The importance of Hfq in Gram- positive bacteria is still controversial (Rochat et al., 2015). The absence of Hfq in Lactobacillales (including Streptococcus pyogenes) suggests that, in these bacteria, sRNAs interact in a

9 Introduction protein-independent manner or that another protein is acting as a protein chaperone replacing Hfq (Chao and Vogel, 2010).

I.3.2. RNases

Although mostly described as stable molecules, sRNAs have diverse half-lives (Vogel et al., 2003). Ribonucleases (RNases) are involved both in sRNA maturation/turnover2 and sRNA-mediated regulation, indeed they control the turnover rate of the sRNA alone but also of the sRNA:target mRNA duplexes (Viegas and Arraiano, 2008). These enzymes can either cleave within RNA molecules (endoribonucleases) or degrade transcripts from their 5' or 3' end (exoribonucleases). RNases are also characterized by their ability to cleave single stranded (ss) or double stranded (ds) RNA. All bacterial species contain their own pool of RNases, which possess specific activities (e.g. 5’ to 3’ exoribonucleases are not present in all bacteria) and present specific functions (e.g. rRNA and tRNA processing, mRNA decay). sRNAs can modulate mRNA stability by promoting or inhibiting their degradation by RNases. For example, the formation of a sRNA:mRNA duplex can generate a target site for the ds-specific RNase III, which cleaves both transcripts once they interact, resulting in their degradation. In contrast, sRNAs binding to their target mRNAs can protect single stranded mRNAs regions from the ss- specific RNase E (Saramago et al., 2014). Other RNases implicated in sRNA regulation are PNPase (3′ to 5′ exoribonuclease activity), RNase J1/J2 (5′ to 3′ exoribonuclease activity) and RNase Y (endoribonuclease) (Durand et al., 2012). Although several studies show the role of certain RNases on specific RNAs, the global control of sRNAs by RNases should be examined in more detail.

Additional information about two major RNases, RNase III and RNase Y, analyzed in I. Paper I – Novel sRNAs in Streptococcus pyogenes page 41, are given below, additional information about their role in S. pyogenes will be discussed in chapter II. Streptococcus pyogenes, the flesh-eating bacteria page 15. RNase III was reported to affect the abundance of only ~10% of mRNAs (both directly and indirectly) in B. subtilis and E. coli

2 In this report, RNA maturation/processing refers to a cleavage leading to functional transcripts, while RNA degradation/decay/turnover refers to a cleavage resulting in RNA deterioration.

10 Introduction

(Durand et al., 2015). This ds-specific RNase can act on either a stem loop formed by one RNA molecule or RNA duplexes. RNase III is highly conserved in bacteria and is also present in eukaryotes (i.e. Dicer and Drosha) (Court et al., 2013). In addition to its role in sRNA:mRNA duplex and long asRNA processing described in the previous chapter (Lasa et al., 2011; Lioliou et al., 2012; Lybecker et al., 2014), RNase III is involved in various bacterial processes including rRNA and tRNA maturation (Bonnin and Bouloc, 2015). In some B. subtilis strains, RNase III is essential to the bacteria as it leads to inhibition of toxins expression in type I TA systems by degrading the toxin/antitoxin duplexes (Durand et al., 2012). The RNase Y endonuclease cleaves single-stranded AU rich sequences and has similarities with RNase E of Gram negative bacteria (Bonnin and Bouloc, 2015; Shahbabian et al., 2009). It has been suggested that RNase Y is important in global mRNA turnover, as demonstrated by the doubling of the average RNA half-life in the RNase Y deletion strain of B. subtilis (Shahbabian et al., 2009). RNase Y deletion entails pleiotropic effects for the cell and also leads to the overexpression of ~10 to ~20% of the mRNAs in B. subtilis and 4% in S. aureus (Durand et al., 2015; Shahbabian et al., 2009). In B. subtilis, RNase Y initiates the decay of the terminated transcript from the SAM-dependent riboswitch (Shahbabian et al., 2009). Additionally, in S. aureus RNase Y regulates both RsaA and Sau63 sRNAs, however the mechanism of action remains unknown (Marincola et al., 2012).

I.4. How to find non-coding RNAs in bacteria?

Since the discovery of the first sRNAs, the sRNA-hunting ﬁeld has evolved rapidly. In most bacteria, a combination of both in silico and in vivo approaches has been used to identify new sRNA species. However, with the expansion of RNA sequencing, in silico programs are less and less used. Regardless of the technique applied to detect novel sRNAs, it is essential to validate their expression experimentally by RT-PCR, or preferably, by Northern blotting, which provides additional information about the expression and processing pattern of sRNAs under the tested conditions.

I.4.1. In silico predictions

Several computational programs have been developed to screen for non-coding RNAs in bacteria. Most of these algorithms share common parameters and rely only on DNA sequence features:

11 Introduction sRNAs are located in IGR, have promoters and Rho-independent terminators. In silico prediction programs have been widely reviewed in (Backofen et al., 2014; Li et al., 2012; Pichon and Felden, 2008). Other computer-based methods are based on the search of orthologs of known sRNAs (using Blast3 (Altschul et al., 1990) and the Rfam database4 (Nawrocki et al., 2015)) or of regulator binding sites (BS) in IGRs using, for example, the RegPrecise database5. Computational pipelines have also been developed for cis-regulatory RNA motifs (Yao et al., 2007) and type I and III TA systems mining (Fozo et al., 2010). However, using in silico predictions do not allow the identification of functional sRNAs that are part of longer mRNAs (located in the 5' or 3' UTR) and/or are not flanked by their own promoters or terminators.

I.4.2. In vivo determination

In vivo radioactive (32P) labelling of total RNAs enabled the visualization of the first stable sRNAs in E. coli (Gottesman, 2004). The sRNAs were extracted from the gels and cloned for further investigations. Initially, sRNAs were casually discovered while analyzing the function of known genetic systems. This identification by functional genetic screenings is time consuming and complicated, since some sRNAs act only under specific conditions. Nonetheless, this approach is rewarding as the sRNA is directly associated to a phenotype. Several genome-wide techniques have also been developed. In the method of shotgun cloning of sRNAs, all sRNAs are reverse- transcribed into cDNAs and cloned before being sequenced. Thus, both primary and processed forms of the sRNAs can be detected (Vogel et al., 2003). Microarrays (covering IGRs) can also be used, but nowadays RNA sequencing has become the preferential method for sRNA discovery. RNA sequencing determines at once the sRNAs expression levels, the strand from which the sRNAs are expressed, and allows the annotation of sRNAs specific 5' and 3' ends (of both primary and processed transcripts). This method can be employed using various growth conditions (e.g. temperature, pH, stresses) and also during host infection (dual-RNA sequencing (Westermann et al., 2012)).

3 http://blast.ncbi.nlm.nih.gov/Blast.cgi 4 http://rfam.xfam.org 5 http://regprecise.lbl.gov/RegPrecise

12 Introduction

Other sRNAs identification methods take advantage of RNA binding protein properties. For example, immunoprecipitation with Hfq (to identify Hfq-binding sRNAs) (Zhang et al., 2003) or with the J2 antibody (to identify asRNAs longer than 40 nt) (Lybecker et al., 2014) followed by microarray or RNA sequencing analyses were successfully applied. In vivo methods to detect novel sRNAs are detailed in (Altuvia, 2007; Sharma and Vogel, 2009; Vogel et al., 2005; Vogel and Sharma, 2005).

I.5. How to find targets of trans-acting sRNAs?

Characterizing the role of a specific sRNA and determining its molecular mechanism of action is challenging. Although several bioinformatic or experimental approaches are frequently combined to maximize the likelihood of finding sRNAs, luck remains an important factor for the success of such screenings (e.g. using conditions under which the sRNA target is expressed). This explains why, while a large number of putative regulatory RNAs have been identified, only a few have been characterized in detail.

I.5.1. In silico target predictions

Different programs are available to predict sRNA:mRNA interactions (Table 1 page 14). They normally search for common features of sRNA:mRNA duplexes, including a 6-8 nt seed region sequence (Künne et al., 2014), sRNA and mRNA secondary structures, thermodynamics of the duplex formation, RBS accessibility. Some algorithms are based on the assumption that the binding site of the sRNA should be located in the region of the RBS/start codon of the mRNA target, thus only identifying mRNA targets negatively regulated by sRNAs (the most common mechanism of action of trans-acting sRNAs, see I.2. Regulation by non-coding RNAs page 2). As previously described, trans-encoded sRNAs present only short and imperfect complementarities with their target mRNAs, which complicates computational predictions. Therefore, bioinformatic tools often produce a high number of false positive hits. Programs used for finding putative sRNA targets, predicting sRNA:mRNA interactions and RNA structures are summarized in Table 1 page 14; more details can be found in the following reviews: (Backofen et al., 2014; Backofen and Hess, 2010; Li et al., 2012; Pain et al., 2015; Pichon and Felden, 2008; Steger, 2005).

13 Introduction sRNA target predictions

CopraRNA http://rna.informatik.uni-freiburg.de/CopraRNA/Input.jsp (Wright et al., 2013) IntaRNA http://rna.informatik.uni-freiburg.de/IntaRNA/Input.jsp (Busch et al., 2008) RNApredator http://rna.tbi.univie.ac.at/RNApredator2/target_search.cgi (Eggenhofer et al., 2011) sRNATarget http://ccb.bmi.ac.cn/srnatarget/ (Cao et al., 2009; Zhao et al., 2008) sTarpicker http://ccb.bmi.ac.cn/starpicker/prediction.php (Ying et al., 2011) TargetRNA http://cs.wellesley.edu/~btjaden/TargetRNA2/ (Tjaden et al., 2006) RNA-RNA interaction predictions

RNAcofold http://rna.tbi.univie.ac.at/cgi-bin/RNAcofold.cgi (Lorenz et al., 2011) (Krüger and Rehmsmeier, 2006; http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/ RNAhybrid Rehmsmeier et al., 2004) Pairfold http://www.rnasoft.ca/cgi-bin/RNAsoft/PairFold/pairfold.pl (Andronescu et al., 2005) RNAduplex http://www.tbi.univie.ac.at/RNA/RNAduplex.html (Lorenz et al., 2011) RNAplex http://www.bioinf.uni-leipzig.de/Software/RNAplex/ (Tafer and Hofacker, 2008) RNAup https://www.tbi.univie.ac.at/~ulim/RNAup/ (Lorenz et al., 2011) RNA structure predictions mfold http://mfold.rna.albany.edu/?q=mfold (Zuker, 2003) RNAfold http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi (Gruber et al., 2008) Alifold http://rna.tbi.univie.ac.at/cgi-bin/RNAalifold.cgi (Hofacker, 2003)

Table 1. Main computational RNA target, interaction and structure prediction tools

I.5.2. In vivo approaches

Until now, in vivo approaches used for discovery/study of sRNA targets only permit the identification of targets for one sRNA at a time. A common approach is to determine the phenotype of either over-expression (pulse expression) or deletion of the sRNA of interest in various conditions. High throughput approaches can then be performed (transcriptomics, proteomics and metabolomics), and selected phenotypic assays can give a hint about the pathway in which the sRNA is involved (Gerhart et al., 2005; Hofacker, 2003). Immunoprecipitation experiments are used to detect putative RNA or protein targets of a sRNA. Additional methods for deciphering the sRNA mechanism of action are available once the target is identified, or narrowed down to a few candidates. Transcriptional/translational fusions to a reporter gene are useful to define at which level the regulation occurs (e.g. transcriptional, post transcriptional) and the exact region where the sRNA acts. Also, the kinetics of both RNA:protein and RNA:RNA

14 Introduction

complexes can be assessed using electrophoretic mobility shift assays (EMSA). Regarding the characterization of sRNAs, their exact 5’ and 3’ ends can be defined using Rapid Amplification of cDNA Ends (RACE) or primer extension methods. The structure of sRNAs alone or with their mRNA targets can be determined by cleaving radioactively labeled in vitro transcribed RNAs with for example RNase T1 (cleaves ssRNA at G residues), lead(II) acetate (cleaves ss regions, loops and bulges), hydroxyl radicals (alkaline hydrolysis results in a ladder with cleavages at each single nucleotide positions) and analyzing the digestion profiles following migration on a polyacrylamide gel. The method of in-line probing has been established to identify riboswitch ligands. It is based on the natural tendency of RNA to cleave itself, depending on its structure, and varies in response to the presence/absence of the ligand (Regulski and Breaker, 2008).

II. Streptococcus pyogenes, the flesh-eating bacteria

II.1. Taxonomy

Bacteria > Firmicutes > Bacilli > Lactobacillales > Streptococcaceae

The Streptococcus genus comprises over 90 species of both commensal and/or pathogenic bacteria, which have a broad range of hosts, including humans6. The most clinically prominent streptococcal human pathogens include Streptococcus pyogenes, Streptococcus pneumoniae, Streptococcus agalactiae, Streptococcus mitis and Streptococcus mutans. Historically, the first record of an S. pyogenes infection is attributed to Hippocrates (5th-4th century B.C.) who described a scarlet fever epidemic (Quinn, 1991). Later studies by Billroth in 1874 and Pasteur in 1879 described S. pyogenes cocci from wound infections and from the blood of a patient with puerperal sepsis, respectively. Fehleisen published the first isolation of S. pyogenes in 1883, which preceded the naming of these bacteria S. pyogenes in 1884 by Rosenbach (Evans, 1936). Streptococcal species can be classified by the type of hemolysis they exhibit when cultured on blood agar. These classes of hemolysis comprise β-hemolysis (complete lysis resulting in a cleared area around colonies, e.g S. pyogenes); α-hemolysis (incomplete, “green” lysis, e.g. S. pneumoniae) and γ-hemolysis (no hemolysis). The work

6 http://www.ncbi.nlm.nih.gov/Taxonomy/

15 Introduction of Lancefield further classified beta-hemolytic bacteria via serotyping based on their cell wall antigenic characteristics (Lancefield, 1928, 1933). S. pyogenes is also called group A Streptococcus (GAS) as it exposes a group A carbohydrate containing a rhamnose linked to an N-acetylglucosamine molecule on its surface (Mccarty, 1956). Further classification of GAS serotype is conducted using the emm gene, encoding the surface M protein (sequencing of the emm gene led to the identification of over 220 emm-types) (Beall et al., 1996; Sanderson-Smith et al., 2014).

General characteristics

S. pyogenes is a Gram-positive, aero-tolerant anaerobe, catalase negative, homofermentative, non-motile and non-spore forming coccus (1 μm) with a hyaluronic acid capsule and pili. It occurs in pairs or chains (Figure 2 page 16). This pathogen belongs to the Risk Group 2 (moderate individual risk and a low community risk)7.

Figure 2. Electron microscopy of S. pyogenes M1 GAS. Microscopy picture from Manfred Rohde, HZI, Braunschweig.

7 Biosafety in Microbiological and Biomedical Laboratories

16 Introduction

II.2. Pathogenesis

II.2.1. S. pyogenes pathologies

S. pyogenes is a strict human pathogen that can colonize asymptomatically, but is also a common cause of clinical diseases. S. pyogenes is an agent of mild cutaneous and mucosal epithelial infections, including pharyngitis and impetigo. S. pyogenes transmission usually results from direct contact (through respiratory droplets via coughing or sneezing, contact with an infected wound) or from contaminated food. The incubation period is 1 to 3 days (Prevention of Invasive Group A Streptococcal Infections Workshop Participants, 2002). It is in addition responsible for severe infections such as necrotizing fasciitis (also called "flesh-eating disease"), meningitis, endocarditis, scarlet fever, puerperal fever and the streptococcal toxic shock syndrome. Autoimmune post-streptococcal sequelae can be triggered in 1 to 3% of the cases after untreated infection (e.g. rheumatic heart disease and glomerulonephritis). These sequelae are caused by immunological reactions to S. pyogenes antigens, even after the elimination of the pathogen (Martin and Green, 2006; Tart et al., 2007; Walker et al., 2014; WHO, 2005). The diagnosis of S. pyogenes infection may be guided by clinical signs, but the presence of the bacterium needs to be validated by microbial culture and serological method to identify specific antigens (Patterson, 1996). The reference treatment of streptococcal infections is penicillin (Stevens, 2001); cephalosporins, macrolides, and clindamycin are also prescribed (e.g. in case of penicillin allergy), but resistance to these antibiotics becomes an increasing concern (Walker et al., 2014). Despite on-going research and development, a vaccine to prevent S. pyogenes infections has not yet been licensed (Dale et al., 2013).

II.2.2. Epidemiology

Previous global studies estimate that S. pyogenes is responsible for more than 18 million cases of severe diseases per year, resulting in at least 500 000 deaths. S. pyogenes also causes a significant burden of non-invasive diseases, with more than 600 million cases of pharyngitis per year (Carapetis et al., 2005). It is the most common bacterial cause of “sore throat”, representing a high economic burden for the health care system (in view of doctor visits, treatment cost, loss of working days) (Pfoh et al., 2008).

17 Introduction

S. pyogenes infections have been associated with high morbidity and mortality until the middle of the 20th century, then the incidence and severity of the infections declined; probably due to decrease in the virulence and improvement of the socioeconomic conditions. However, since the late 1980s, there has been a resurgence in the incidence of severe invasive infections (Katz and Morens, 1992; Stevens, 1992). These infections associated with high morbidity and mortality are often linked to the emergence of new emm genotypes and/or transfer of new virulence factors between strains (mediated by mobile genetic elements) (Turner et al., 2015). For example, the M1 serotype has been frequently associated with severe invasive diseases (Cole et al., 2011).

II.3. Virulence factors

To cause the above-mentioned diseases, S. pyogenes must not only disseminate from the initial site of infection and survive in the blood, but it also has to fight the human host response. To accomplish this, S. pyogenes has evolved complex regulatory mechanisms and produces a wide range of virulence factors, in charge of (1) adherence, (2) dissemination, (3) defense against host immune responses, (4) production of toxins and other systemic effects (Cole et al., 2011; Tart et al., 2007) (Figure 3 page 20).

(1) Adherence

S. pyogenes adhesion to human cells depends on the presence of cell surface adhesins such as the lipoteichoic acid, fibronectin-binding proteins, laminin-binding proteins, the M protein and the Cpa protein (collagen binding protein present in the pili) (Bisno et al., 2003; Nobbs et al., 2009; Walker et al., 2014). The cell wall associated M protein is a major virulence factor of S. pyogenes, which can bind directly to the extracellular matrix components (e.g. fibrinogen). S. pyogenes also harbors long filamentous structures, pili, which can adhere to host cells and form biofilms by binding to collagen (Mora et al., 2005).

(2) Dissemination

To disseminate, S. pyogenes needs to escape the local thrombosis (blood clot), a result of the activation of the coagulatory cascade at the site of infection. Streptokinase, a secreted factor, activates the host plasminogen into plasmin, a serine protease, which in turn digests the

18 Introduction

major constituent of blood clots leading to the dissolution of local thrombosis. S. pyogenes also produces a streptodornase (Sda1) which hydrolyzes DNA from neutrophil extracellular traps (NETs) and a hyaluronidase, which hydrolyzes hyaluronic acid breaking down the connective tissues of the host (Bisno et al., 2003; Johansson et al., 2010; Shannon et al., 2013).

(3) Defense against host immune responses

S. pyogenes possesses an arsenal of countermeasures against attacks from the host. Resistance of phagocytosis can be mediated by the hyaluronic acid capsule (hasA, hasB, hasC genes) and the Immunoglobulin G cleaving enzyme (IdeS) (Bisno et al., 2003; von Pawel-Rammingen et al., 2002; Wessels, 1997). The host complement system is inhibited by the C5a peptidase (scpA, which inactivates the chemoattractant C5a) (Cleary et al., 1992) and the streptococcal inhibitor of complement (Sic). Sic blocks the innate immunity response by interfering with antibacterial activity of the contact and complement systems (Akesson et al., 1996). SpyCep, a cell envelope serine protease degrades interleukin 8, preventing the recruitment of the host neutrophil to the infection site (Edwards et al., 2005).

(4) Production of toxins and other systemic effects

Streptolysin O (SLO) and streptolysin S (SLS produced by the sag operon) are cytolytic toxins secreted by S. pyogenes. They form pores in the host cells and lead to irreversible osmotic changes. SLS is responsible for the characteristic zone of beta-hemolysis surrounding S. pyogenes colonies grown on blood-agar plates (Molloy et al., 2011). The secreted streptococcal exotoxin B (SpeB) degrades a wide range of proteins from the host including extracellular matrix (ECM) components, immunoglobulins, complement 3 and antimicrobial peptides and activates interleukin-1 and releases kinins and histamine. Additionally, SpeB also degrades many S. pyogenes factors such as M protein, C5a peptidase and Ska (Berge and Björck, 1995; Carroll and Musser, 2011; Chiang-Ni and Wu, 2008; Kapur et al., 1993).

This section deliberately describes only the strategies deployed by S. pyogenes during infection. For details regarding the host responding mechanisms, please refer to (Tsatsaronis et al., 2014).

19 Introduction

Figure 3. Virulence factors expressed by S. pyogenes at different stages during infection. The circles represent S. pyogenes at different stages during infection. Adherence (blue): M protein, fibronectin binding protein, and pili mediate S. pyogenes binding to the host extracellular matrix (ECM). Dissemination (green): The secreted streptokinase converts plasminogen into plasmin which helps bacterial colonization of host tissues. The secreted streptodornase (DNase) degrades neutrophil extracellular traps (NETs) and the hyaluronidase hydrolyses hyaluronic acid to break down the connective tissues of the host. Defense against host immune response (orange): The streptococcal inhibitor of complement (Sic) and the C5a peptidase inhibit the host complement system. The SpyCEP degrades chemokines, the immunoglobulin G cleaving enzyme (IdeS) degrades immunoglobulins and the capsule prevents phagocytosis of S. pyogenes. Toxin production (purple): Streptolysin O and S mediate cell lysis. SpeB degrades the host ECM, cytokines, chemokines, complement components, immunoglobulins and in addition can regulate other streptococcal proteins by degrading them or releasing them from the bacterial surface.

II.4. Regulation of virulence factor expression

As described in the preceding paragraph, S. pyogenes can colonize, rapidly multiply and spread in the host while evading phagocytosis, and confound the immune system. The ability of these bacteria to cause many types of diseases in various environments (e.g. pharyngeal and cutaneous epithelial, soft tissue, blood) is illustrative of how efficiently they can reprogram virulence factors expression. S. pyogenes’ network of interconnected regulators is responsible for this tight coordination of virulence factors expression in response to environmental cues. For example, stand-alone response regulators

20 Introduction

(RR) and two-component systems (TCS) sense external signals and directly bind to virulence genes promoters; sRNAs and RNases and other regulators such as proteases are also involved in this regulation. Numerous regulatory systems are present in the S. pyogenes genome; as such only a few selected ones will be described here.

II.4.1. Stand-alone response regulators

One of the best characterized stand-alone virulence regulators is the multiple gene activator (Mga), which influences the expression of more than 10% of S. pyogenes genes. It is present in all S. pyogenes strains and controls S. pyogenes adherence, internalization and host immune evasion. It regulates directly the expression of surface- associated and secreted factors involved in early stages of S. pyogenes infection such as M protein, C5a peptidase, Sic and ECM binding proteins. It also controls the expression of several virulence genes indirectly, such as the capsule operon and SpeB. The regulation of Mga depends on an autoregulation mechanism and other transcriptional regulators (Hondorp and McIver, 2007; Patenge et al., 2013; Ribardo and McIver, 2006). The RofA-like protein (RALP) transcriptional regulator family is composed of four members including RofA (RALP-1), Nra (RALP-2) and RivR (RALP-4) (Granok et al., 2000; Kreikemeyer et al., 2003). RofA and Nra control the interactions with the host cell by regulating the expression of a set of genes like MSCRAMMs (microbial surface components that recognize adhesive matrix molecules such as fibronectin-binding protein and collagen-binding protein (Cpa)), extracellular enzymes (e.g. SLS and SpeB), and the regulator Mga (Nobbs et al., 2009). RivR is a negative regulator of capsule proteins and of the protein G-related α(2)-macroglobulin-binding protein (Roberts and Scott, 2007; Treviño et al., 2013). Rgg-like transcription regulator Proteinase B (RopB) influences the expression of extracellular proteins for instance SpeB, SLS, SLO, through modulation of existing regulatory networks (Mga and various TCS) (Chaussee et al., 2002).

II.4.2. Two-component systems

Signal transduction of extracellular signals leading to intracellular responses via TCSs is a common mechanism in bacteria. Upon interaction with a specific signaling substance, the transmembrane protein sensor (histidine kinase) forms a dimer, which is activated by autophosphorylation of conserved histidine residues located in their

21 Introduction cytoplasmic transducer domain. The phosphoryl group is then transferred to an aspartate residue of the cytoplasmic response regulator (transcription factor), which controls target gene transcription (Kreikemeyer et al., 2003). At least 13 TCSs are present in S. pyogenes, but only few have been functionally characterized (Sitkiewicz and Musser, 2006). The Ihk/Irr (isp-adjacent histidine kinase/response regulator) TCS plays an essential role in escaping neutrophil mediated killing (Voyich et al., 2003). It also down-regulates the expression of genes involved in cell wall metabolism, transcription, oxidative stress and virulence (Musser and DeLeo, 2005). The FasBCAX (fibronectin/fibrinogen binding/haemolytic activity/streptokinase regulator) operon downregulates the expression of adhesins and induces the expression of secreted virulence factors, for instance streptokinase or streptolysin S (SLS). It is involved in the destruction of tissue from the host and general bacterial aggressiveness (Klenk et al., 2005). FasB and FasC are two sensor histidine kinases, FasA is the response regulator and the sRNA FasX is the main effector of the system (mechanism of action detailed in chapter II.4.3. sRNAs page 23) (Kreikemeyer et al., 2001). CovRS (control of virulence genes), influences about 15% of the GAS genome (Graham et al., 2002). CovS is a sensor kinase that can either phosphorylate or dephosphorylate CovR to repress or derepress different CovR targets. When the Mg2+ concentration is high (inside host cells or outside the human body), the CovRS system represses the expression of virulence factors, while at low Mg2+ concentrations it switches to an activating role (Gryllos et al., 2003). It controls the expression of the capsule, streptokinase, SLS, speB, IdeS, and RivR, and influences the expression of other RRs and TCSs (Federle et al., 1999; Heath et al., 1999; Gusa and Scott, 2005; Roberts and Scott, 2007). CiaRH (Competence induction and altered cefotaxime susceptibility) TCS regulates genes involved in various functions such as competence, antibiotic resistance (beta lactams), stress responses, maintenance of cell-wall integrity, autolysis, polysaccharide metabolism and transport, and virulence (Mascher et al., 2003). CiaH is the sensor and CiaR the response regulator, which recognizes a TTTAAG-5N-TTTAAG sequence conserved among all streptococci (Marx et al., 2010). In addition to targeting mRNA, CiaR has been shown to bind the promoters of cia-dependent small RNAs (csRNAs) (Halfmann et al., 2007; Marx et al., 2010). In GAS, the function of the CiaRH homologue is unclear (Riani et al., 2007).

22 Introduction

II.4.3. sRNAs

Knowledge about sRNA mechanisms of action is very limited in S. pyogenes. Although multiple putative regulatory RNAs have been identified using various screening methods, few S. pyogenes-specific sRNAs have been studied in detail. Here are presented briefly the methods used for identification of sRNAs in S. pyogenes and a short description of FasX, Pel and RivX sRNAs (CRISPR RNA and tracrRNA are described in chapter III. sRNAs involved in bacterial immunity – CRISPR-Cas systems page 28). For an extensive review on this subject, please refer to (Le Rhun and Charpentier, 2012). Novel regulatory RNAs in S. pyogenes were initially identified using computational methods such as 1/ sRNApredict (62 putative sRNAs in M1 GAS) (Livny et al., 2006), 2/ SIPHT (sRNA identification protocol using high‐throughput technologies) (29 putative sRNAs in M1 GAS) (Livny et al., 2008), 3/ sRNA scanner (169 putative sRNAs in strain D471) (Sridhar et al., 2010), 4/ MOSES (Raasch et al., 2010) (20 putative sRNAs in M1 GAS) and 5/ a combination of three algorithms: sRNAPredict, eQRNA and RNAz (45 putative sRNAs in MGAS315) (Tesorero et al., 2013). These screens were soon followed by experimental analyses, two intergenic tiling arrays studies (40 putative sRNAs in MGAS2221) (Perez et al., 2009) and (55 putative sRNAs in GAS M49) (Patenge et al., 2012), and two RNA sequencing studies (140 putative sRNAs) (Deltcheva et al., 2011) and (400 putative sRNAs in MGAS2221) (McClure et al., 2013). Few sRNAs have been validated by Northern blot or RT-PCR analyses in these studies, and only one new mechanism of action was described, the trans-acting mechanism of tracrRNA (chapter III. sRNAs involved in bacterial immunity – CRISPR-Cas systems page 28).

One of the best understood regulatory RNAs in S. pyogenes is FasX. It has been identified during the characterization of the FasBCA TCS system, connecting TCS and sRNAs (Kreikemeyer et al., 2001). FasX, the main effector of the system, is required for the FasBCA to be active (Kreikemeyer et al., 2001). FasX is a trans-acting sRNA, which binds to its target mRNAs using different mechanisms (Figure 3 page 20). FasX can base-pair to the 5’ end of the streptokinase (ska) mRNA and enhance its stability as the dsRNA formed by the FasX:ska mRNA duplex can no longer be degraded by RNases (Ramirez-Peña et al., 2010). In addition, FasX base-pairs to the 5' end of the mRNA of the pilus synthesis operon, inhibiting the translation of the first gene of this operon (cpa), reducing mRNA stability and thus

23 Introduction decreasing adherence to host epithelial cells (Liu et al., 2012). It was shown that FasX regulates both the expression of streptokinase and pili targets in a serotype dependent manner (Danger et al., 2015a). A recent study demonstrated that the translation of prtF1/2 mRNA (encoding fibronectin-binding proteins PrtF1 and PrtF2) is inhibited by the binding of FasX to their 5’UTRs (Danger et al., 2015b). Reduction of S. pyogenes adherence, and activation of the streptokinase virulence gene by FasX could be crucial in the transition between bacterial colonization and dissemination stages (Patenge et al., 2013; Danger et al., 2015b). Pel (pleiotropic effect locus) RNA is part of the sag operon (Streptolysin associated genes: sagABCDEFGHI), where SLS (encoded by sagA) is responsible for S. pyogenes hemolytic activity and SagB to SagI are required for the proper processing and export of SLS (Datta et al., 2005). Pel RNA is a bifunctional RNA as it codes for the hemolysin SLS, and regulates in addition the expression of other virulence factors in a serotype dependent manner (Li et al., 1999; Biswas et al., 2001; Mangold et al., 2004). In a M1 serotype, Pel RNA regulates expression of the M protein SpeB and Sic (Mangold et al., 2004). However, the mechanisms by which Pel RNA regulates the expression of virulence factors are unknown so far. RivX is a sRNA that originates from the processed 3’ UTR of the rivR mRNA transcript (Roberts and Scott, 2007). Both rivR and RivX control independently the expression of virulence genes from the Mga regulon such as M protein, the C5a peptidase, SpeB or Mga. RivRX is directly repressed by CovR, but RivX molecular mechanisms of regulation are not known (Roberts and Scott, 2007).

24 Introduction

Figure 4. Direct targets of FasX sRNA in S. pyogenes M1 GAS. Left panel: FasX sRNA (green) activates streptokinase (Ska, orange) production by binding to the 5' untranslated region (UTR) of the ska mRNA preventing its degradation by RNases (possibly RNases J1 and/or J2, blue). The secreted streptokinase converts plasminogen into plasmin, leading to the dissolution of blood clots and degradation of the host tissue barrier. Right panel: FasX inhibits production of pili (collagen binding protein, cpa, purple) by binding to the 5' UTR of the pilus operon mRNA, preventing the ribosome (grey) to bind to the ribosome binding site (RBS) and translate the first coding sequence (cds) of this operon (cpa). FasX also destabilizes the pilus operon mRNA. A decrease in Cpa production diminishes S. pyogenes adherence to epithelial cells. Both mechanisms employed by FasX facilitate the transition from colonization stage to bacterial dissemination.

II.4.4. RNases

S. pyogenes expresses a specific set of endoribonucleases (including RNase III, RNase Y and RNase J2) and exoribonucleases (including RNases J1, PNPase, RNase R and YhaM). As demonstrated by the important role of mRNA decay in growth phase dependent gene regulation in S. pyogenes, the control of mRNA stability is a crucial factor for virulence gene regulation (Barnett et al., 2007; Bugrysheva and Scott, 2010).

25 Introduction

S. pyogenes transcripts are classified in two categories depending on their rate of decay during the exponential phase and on their stability during the stationary phase of growth. The decay of Class I and Class II transcripts results from different pathways (Barnett et al., 2007; Bugrysheva and Scott, 2010). Class I mRNAs correspond to transcripts that are mostly absent during the stationary phase (e.g. the has mRNA from capsule operon). Class II mRNAs are the few transcripts that are present in higher quantity during the stationary phase compared to the exponential phase of growth (e.g. sagA and sda1 mRNA). These RNAs were shown to have long half- lives during stationary phase (≥100 min) (Bugrysheva and Scott, 2010). Class I mRNA 5′ ends are substrates for RNase J1 and/or RNase J2 endonucleolytic and exonucleolytic cleavages and their decay is rapid during the exponential and stationary phases of growth. Class II mRNAs are less sensitive to the J1 and/or J2 RNases, and their degradation only begins after depletion of Class I mRNAs by RNase J1 and/or J2 endonucleolytic cleavage. Class II mRNAs are then further degraded by exoribonucleases (e.g. 3′ to 5′ PNPase) (Bugrysheva and Scott, 2010; Bugrysheva and Scott, 2010).

The roles of S. pyogenes RNase III and RNase Y in sRNA regulation are described in I. Paper I – Novel sRNAs in Streptococcus pyogenes page 41, presented in this thesis, Only one study reports the role of RNase III in S. pyogenes, describing its involvement in the maturation of CRISPR RNAs from the type II CRISPR-Cas system (discussed later in chapter III. sRNAs involved in bacterial immunity – CRISPR-Cas systems page 28). However, several reports discuss the implication of RNase Y (previously known as CvfA) in S. pyogenes virulence (Chen et al., 2013; Kang et al., 2010). A first microarray analysis demonstrated that RNase Y influences virulence gene expression depending on growth phase and nutrition (carbon and nitrogen sources) in S. pyogenes strain HSC5. The role of RNase Y was shown to be more important during stationary phase of growth in a medium poor in carbohydrates, where 30% of the transcriptome was altered by the deletion of RNase Y (including SpeB, streptokinase, SLO, M protein) (Kang et al., 2010). Later it was demonstrated that RNase Y also affects the thermoregulation of the capsule in an indirect manner, probably by regulating a capsule regulator (Kang et al., 2012). A recent study using microarray and Northern blot analyses investigated S. pyogenes mRNA half-lives in the strain NZ131 (Chen

26 Introduction

et al., 2013). S. pyogenes has a high mRNA turnover rate (85% of mRNA half-lives < 2 min), and the deletion of RNase Y causes a 2-fold increase of the half-lives without significantly changing the level of mRNAs. In the same study it was shown that RNase Y also regulates mRNA processing of virulence associated genes, and rapid degradation of highly structured read-through transcripts in S. pyogenes (Chen et al., 2013). RNase Y might be processing speB and ropB mRNA overlapping 5' UTRs, leading to stabilization of both transcripts (Chen et al., 2013, 2012; Neely et al., 2003). RNase Y is also responsible for the rapid degradation of the read through transcripts of the RNA component of RNase P. Only one sRNA, the FasX regulatory RNA, was found to be destabilized in the absence of RNase Y (Chen et al., 2013).

II.5. Transcriptomics studies

Numerous transcriptomic studies have been performed in S. pyogenes, showing characteristic changes in transcript expression. The expression of virulence genes in S. pyogenes depends on growth phase, temperature, pH, salt concentration and media (Smoot et al., 2001; Barnett et al., 2007; Chaussee et al., 2008; Fiedler et al., 2010). It was found that while virulence gene transcripts are predominant in the transition from exponential to stationary growth phase, transcripts involved in stress response and regulation of metabolism are mostly present in the stationary phase (Beyer-Sehlmeyer et al., 2005). S. pyogenes transcriptional studies in human saliva led to the identification of a new TCS, SptR/S, essential for persistence of S. pyogenes (Shelburne et al., 2005). In blood, the expression of genes involved in enhanced survival and pathogenesis is massively induced (Graham et al., 2005). Studies of various S. pyogenes isolates show two distinct transcriptome profiles with 10% of genes differentially expressed: the pharyngeal transcriptome profile (PTP) and the invasive transcriptome profile (ITP) (Sumby et al., 2006). This variation in gene expression was shown to be due to a 7-bp frameshift mutation in the CovS histidine kinase, with all PTP isolates having a wild-type CovS gene, and the ITP isolates having a mutation in the CovRS TCS. Further studies performed in various infection models are summarized in (Fiedler et al., 2010).

27 Introduction

Strain used in this study

The reference S. pyogenes strain used in the laboratory, M1 GAS (SF370, ATCC 700294, RefSeq: NC_002737), was isolated in 1985 from a wound infection (Ferretti et al., 2001). Its genome (1.85 Mb) contains 1,752 predicted genes, however, for around one-third of these genes no function has been ascertained yet (Ferretti et al., 2001). Exogenous genetic elements occupy about 10% of the genome, and include prophages and integrated conjugative elements that encode virulence factors and antibiotic resistance genes (Bessen, 2009).

III. sRNAs involved in bacterial immunity – CRISPR-Cas systems

Phages and other mobile genetic elements can be beneficial, by integrating in the bacterial chromosome (prophage) and conferring the bacteria new traits such as virulence or resistance genes via horizontal gene transfer (HGT). Nevertheless, bacteriophages also represent a threat as they can kill the bacteria and produce new viral particles (lytic cycle). Thus, to prevent infection, bacteria evolved innate and adaptive immune systems. Innate immune systems consist of prevention of phage adsorption, blocking of phage entry (superinfection exclusion (Sie) systems) and replication of phage DNA (Bacteriophage Exclusion (BREX) systems), restriction- modification and abortive infection (Abi) systems (Hyman and Abedon, 2010; Labrie et al., 2010; Goldfarb et al., 2015). To date, the only known prokaryotic adaptive immune system is the clustered regularly interspaced short palindromic repeats-CRISPR associated proteins (CRISPR-Cas) system. This system enables bacteria to recall previous infections and be resistant during a reinfection by the same threat.

III.1. The CRISPR-Cas immune system

The prokaryotic adaptive immune system CRISPR-Cas uses small CRISPR RNAs (crRNA) to specifically guide the targeting of invading nucleic acids for their destruction (Wiedenheft et al., 2012; Koonin and Makarova, 2013). These systems, which allow prokaryotes to resist bacteriophage infections but also prevent plasmid transformation and conjugation (Marraffini and Sontheimer, 2008; Sorek et al., 2008; Marraffini and Sontheimer, 2010), can be found in 40 % of the bacteria and 90% of the archaea (Grissa et al., 2007).

28 Introduction

CRISPR-Cas systems are often compared to the RNA interference pathways in eukaryotes, as both depend on sRNAs which recognize and silence foreign nucleic acids in a sequence specific manner.

At first, highly homologous sequences of 29 nucleotides, arranged as direct repeats separated by unique 32 nt long spacers, were found in E. coli (Ishino et al., 1987). It was later observed that these repeated motifs are common among bacteria and archaea (Mojica et al., 2000). In 2002, these systems were named CRISPR and associated cas genes were found in the vicinity of the array (Jansen et al., 2002). It was only in 2005 that the sequence homology between CRISPR spacers and plasmid or phage sequences was discovered, implying a possible role in defense against mobile genetic elements (Bolotin et al., 2005; Makarova et al., 2006; Mojica et al., 2005). This was confirmed experimentally by phage challenge of Streptococcus thermophilus, which led to the integration of new phage-derived spacers in the bacterial CRISPR array, rendering the new strains resistant to re-infection by the same phage (Barrangou et al., 2007).

The CRISPR-Cas locus is typically composed of a cas operon encoding the Cas proteins and a CRISPR array encoding the guide crRNAs. The precursor CRISPR RNA (pre-crRNA) comprises an A/U rich leader sequence followed by repeated sequences (24 to 47 nt) interspaced by spacer sequences (26 to 72 nt). Spacers are unique, highly variable and are often complementary to sequences of phages or plasmids. The matching sequences on the invader are called “protospacers” (Brouns et al., 2008; Marraffini and Sontheimer, 2008; Sorek et al., 2008).

Based on evolution and functionality, CRISPR-Cas systems can be classified into five major types (I to IV) that can be further subdivided (Chylinski et al., 2014; Makarova et al., 2015, 2011a, 2011b, 2011c). The Cas protein composition and location varies between the types but they share a common organization and mechanism of action.

CRISPR-Cas systems act in three steps (Figure 5 page 31): (1) Acquisition/Adaptation, (2) Expression/Maturation and (3) Interference, which are briefly described in the following text and summarized in detail in (Sorek et al., 2008; Koonin and Makarova, 2009; Bhaya et al., 2011; Terns and Terns, 2011; Wiedenheft et al.,

29 Introduction

2012; van der Oost et al., 2014; Charpentier et al., 2015; Plagens et al., 2015).

(1) Acquisition / Adaptation

During intrusion of foreign nucleic acids, bacteria can integrate one or more new spacer sequences in their CRISPR array. This genetic memory renders the bacteria immune against a reoccurring invasion with the same phages or plasmids. Cas1 and Cas2, the only Cas proteins conserved among all CRISPR-Cas types, form a complex essential for acquisition (Datsenko et al., 2012; Heler et al., 2014; Nuñez et al., 2014; Yosef et al., 2012).

(2) Expression and Maturation

The CRISPR array encodes the long pre-crRNA transcript, which contains a series of repeat-spacer units. After transcription, the pre- crRNA is matured into active crRNA species, which are composed of a unique spacer sequence flanked by parts of the repeat. This maturation step involves one or more Cas proteins and in some cases host ribonucleases (Brouns et al., 2008; Carte et al., 2008; Deltcheva et al., 2011).

(3) Interference

The mature crRNA directs the executing Cas protein(s) (interference complex or single Cas protein) to the protospacer. After binding to the target, the foreign nucleic acids (DNA or RNA) are cleaved and further degraded (Brouns et al., 2008; Garneau et al., 2010; Hale et al., 2009; Jinek et al., 2012; Samai et al., 2015; Staals et al., 2014; Tamulaitis et al., 2014; Westra et al., 2012).

30 Introduction

Figure 5. The three stages of CRISPR-Cas immunity. Acquisition/Adaptation. Cas proteins (purple) integrate a portion of the invading DNA (orange) into the CRISPR array (leader: grey box; repeats: black boxes; spacers: colored boxes), forming a new spacer (orange box) and duplicating the leader proximal repeat. This new spacer will enable the bacterium to recognize the same threat upon reinfection. Expression and Maturation. The CRISPR array is transcribed into a precursor CRISPR RNA (pre-crRNA). pre-crRNA is recognized by the Cas proteins and processed into mature CRISPR RNAs (crRNAs), containing only one spacer. Interference. The protospacer sequence (blue) of the invading DNA is targeted by the complementary crRNAs (blue) in complex with Cas protein(s). The invading nucleic acid is cleaved (scissors) and further degraded. A protospacer adjacent motif (PAM, represented in red) – short sequence flanking the protospacer – is necessary for the steps of acquisition and interference of type I and II CRISPR– Cas systems. The purple rectangles represent either a complex of several Cas proteins (for type I and III) or Cas9 alone (for type II).

31 Introduction

To avoid self-targeting by the CRISPR-Cas system (meaning cleavage of the bacterial chromosomal DNA), bacteria have evolved several strategies. In type I and II systems, a protospacer adjacent motif (PAM) – a short DNA sequence located in the vicinity of the protospacer – (Deveau et al., 2008; Mojica et al., 2009) is necessary for both acquisition and interference steps (Sapranauskas et al., 2011; Swarts et al., 2012; Datsenko et al., 2012). This sequence is not present next to the spacer in the chromosomal CRISPR array, which is therefore not recognized by the system (Shah et al., 2013; Westra et al., 2013). In type III, the self versus non-self discrimination depends on mismatches between the crRNA flanking repeat and the target nucleic acid. If there is an extended base-pairing with the repeats of the CRISPR array, autoimmunity is prevented (Marraffini and Sontheimer, 2010).

To escape the CRISPR response, bacteriophages can mutate randomly protospacer or PAM sequences and have also evolved so-called anti- CRISPR systems. Some phages harbor anti-CRISPR genes encoding proteins that interfere with the DNA-binding or cleaving activities of the CRISPR-Cas type I systems (Bondy-Denomy et al., 2013; Pawluk et al., 2014; Rath et al., 2015; Bondy-Denomy et al., 2015).

Briefly, in type I and III CRISPR-Cas systems, pre-crRNA is typically processed by an endoribonuclease from the Cas6 family associated with a complex composed of other Cas proteins, named respectively Cascade (CRISPR-associated complex for antiviral defense for type I), Csm (CRISPR-Cas subtype Mtube for type III-A) or Cmr (Cas module receptor activity-modifying proteins, RAMP for type III-B) (Brouns et al., 2008; Carte et al., 2008). During the interference step, type I Cascade recruits the Cas3 helicase/nuclease to cleave the DNA of the invader. In the type III system, the identified catalytic subunits Csm3 and Cmr4 from the Csm and Cmr complex mediates the DNA/RNA interference (Hale et al., 2009; Staals et al., 2014; Tamulaitis et al., 2014; Plagens et al., 2015).

III.2. Type II CRISPR-Cas systems

The main focus of this section will be on the recent discoveries of the type II systems, particularly the type II-A system characterized in S. pyogenes SF370. While some CRISPR-Cas systems (e.g. type I and III) employ complexes of multiple Cas proteins in complex with crRNAs during RNA maturation and DNA interference stages; type

32 Introduction

II systems are minimal, with only one Cas protein in complex with an RNA duplex handling these two steps (Deltcheva et al., 2011; Jinek et al., 2012). Type II systems harbor only three to four Cas proteins. They contain the Cas9 signature protein and the universal Cas1/Cas2 proteins (spacer acquisition) (Heler et al., 2015; Nuñez et al., 2014; Wei et al., 2015a). While type II-C only contains the three mentioned proteins (Cas9, Cas1 and Cas2), subtype specific proteins are present in type II-A (Csn2) and type II-B (Cas4). Both Csn2 and Cas4 are involved in adaptation to new phages/plasmids (Barrangou et al., 2007; Chylinski et al., 2014; Heler et al., 2015; Li et al., 2014; Wei et al., 2015a).

S. pyogenes SF370 harbors two CRISPR-Cas systems, a type II-A and a type I-C (Jansen et al., 2002). The cas operon of the type II-A is composed cas9, cas1, cas2 and csn2 and six CRISPR spacers that target prophage genes: an endopeptidase, the speM superantigen, a methyltransferase, a hyaluronidase, a phage hypothetical protein and an unknown target, respectively (Deltcheva et al., 2011; Mojica et al., 2005). The first five spacers are targeting a prophage present in other S. pyogenes strains that do not harbor CRISPR systems (SSI-1, MGS8232 and MGAS315). In the case where a prophage target is present in the genome, either the protospacer gene is absent/mutated, or the spacer sequence is degenerated (Mojica et al., 2005). For example, SPy_0700, the gene targeted by spacer 1 is present in the SF370 genome but has a mutated PAM sequence. It was suggested that the limited spacer content of S. pyogenes (compared to other streptococcal strains) could explain strain-specific pathogenesis; because CRISPR phage resistance is minimal, thus, phage insertion leads to acquisition of new virulence factors and antibiotic resistance genes (Beres and Musser, 2007; Nozawa et al., 2011). This is supported by the fact that the number of CRISPR spacers and prophages is inversely correlated, hence S. pyogenes virulence factor acquisition is limited by the presence of CRISPR systems (Deltcheva et al., 2011; Nozawa et al., 2011). Moreover, some strains lost their CRISPR system; a possible selective pressure to allow HGT (Nozawa et al., 2011).

III.2.1. RNA maturation, DNA interference and adaptation

A bioinformatic screening, later confirmed by deep RNA sequencing of S. pyogenes led to the identification of an abundant small RNA found in the vicinity of the CRISPR array (type II-A), the trans- activating crRNA (tracrRNA) (Deltcheva et al., 2011). Following

33 Introduction this discovery, the maturation and interference pathways for S. pyogenes type II CRISPR-Cas systems were rapidly unraveled (Deltcheva et al., 2011; Jinek et al., 2012). In type I, the pre-crRNA repeats form small hairpin structures that are recognized and cleaved by Cas6 family proteins (Brouns et al., 2008; Carte et al., 2008; Charpentier et al., 2015). Similar hairpins are absent in type II repeats, however 25 nt of tracrRNA are complementary to the repeats of the type II CRISPR array and entail formation of RNA duplexes between tracrRNA anti-repeats and pre- crRNA repeats, which are recognized by Cas9. This Cas9 bound tracrRNA:pre-crRNA duplexes are processed by the host RNase III within the repeat:anti-repeat (Deltcheva et al., 2011) (Figure 6 page 35). The first maturation of pre-crRNA leads to the formation of intermediate 66 nt forms of crRNAs (1/3 repeat - spacer - 2/3 repeat) and a 75 nt processed form of tracrRNA (Deltcheva et al., 2011). An uncharacterized second maturation event produces mature crRNA forms (Deltcheva et al., 2011). The mature crRNAs remain bound to tracrRNA and Cas9, forming active complexes for DNA targeting (Figure 6 page 35). In vivo analyses have shown that Cas9 is the only Cas protein essential for the DNA interference stage (Makarova et al., 2006; Barrangou et al., 2007; Garneau et al., 2010) and it was demonstrated that the mature tracrRNA:crRNA-Cas9 complex is responsible for the cleavage of invading DNA (Jinek et al., 2012). Briefly, RNA activated SpCas9 (Cas9 from S. pyogenes) first recognizes the NGG PAM from the target DNA (Mojica et al., 2009; Anders et al., 2014; Jiang et al., 2015). Then, the spacer sequence of crRNA base-pairs with the complementary protospacer present in the close vicinity of the PAM (located on the non-complementary strand) (Jinek et al., 2012). Cas9 is responsible for the cleavage of both DNA strands and produces a blunt dsDNA break (DBS) (Jinek et al., 2012) (see section III.2.3. Cas9 page 36 for details about the mechanism) (Figure 6 page 35). The same mechanism was later reported for S. thermophilus type II-A CRISPR-Cas locus (Gasiunas et al., 2012; Karvelis et al., 2013). Recently, it was shown that both tracrRNA and Cas9 are also required during the spacer acquisition stage. The tracrRNA-Cas9 complex provides PAM-specificity as it recognizes the PAMs in the invading DNA and thus helps in the selection of functional spacers (Heler et al., 2015). In the type II-A system, the proteins responsible for spacer acquisition, Cas1, Cas2 and Csn2, seem to interact with Cas9 to integrate new spacer sequences (Heler et al., 2015; Wei et al., 2015b).

34 Introduction

Figure 6. Type II CRISPR-Cas maturation and DNA interference mechanisms. Representation of the type II CRISPR-Cas locus of S. pyogenes strain SF370 with the trans-activating crRNA (tracrRNA) in green, the cas (CRISPR associated) genes in purple, the CRISPR array in grey (leader), black (repeats) and colored (spacers) boxes, and the flanking genes in grey. pre-crRNA maturation: tracrRNA anti- repeats base-pair with precursor-CRISPR RNA (pre-crRNA) repeats. Ribonuclease III (RNase III, black triangles) cleaves the repeat:anti-repeat duplexes in the presence of Cas9 (purple). A second uncharacterized maturation event (grey triangle) occurs in the crRNA spacer (blue). The mature crRNAs produced after processing remain bound with tracrRNA and Cas9. DNA interference: The mature tracrRNA:crRNA duplex guides Cas9 to the target DNA. Following Cas9 recognition of the protospacer adjacent motif (NGG PAM in red), crRNA and the DNA protospacer (blue) base-pair, forming an R-loop. The complementary strand (binding to crRNA spacer) and the non-complementary strand are then cleaved by the Cas9 HNH and RuvC motifs (scissors), creating a double strand break (DSB) three base pairs upstream of the PAM.

35 Introduction

III.2.2. tracrRNA

As described above, tracrRNA is a trans-acting sRNA which targets crRNA repeats and controls all stages of the CRISPR-Cas immune pathway, as it is required for spacer adaptation, RNA maturation and DNA interference. One critical event is the base-pairing between tracrRNA and crRNA forming the dual-RNA. This is demonstrated by the co-evolution of tracrRNA anti-repeat and CRISPR repeat sequences, as the base-pairing is preserved by compensatory substitutions, in spite of the sequence divergence among species (Deltcheva et al., 2011). Thus, tracrRNA is defined by its function and not its sequence or structure, and orthologous tracrRNAs cannot be found simply by homology searches (e.g. using BLAST). To find novel tracrRNAs orthologues it is necessary to first look for the CRISPR array repeat sequences and then search for putative anti-repeat sequences in the vicinity of the array (II. Paper II – tracrRNA and Cas9 families page 44). tracrRNA of S. pyogenes is present in four forms, as seen by Northern blot analysis: two primary forms of 171 and 89 nt, a processed form of ~75 nt (resulting from pre-crRNA maturation) and an uncharacterized form of ~65 nt. Both tracrRNA and crRNAs were shown to be expressed and processed also in other bacterial species (e.g. Neisseria meningitidis and Listeria innocua) (Deltcheva et al., 2011). Note that the size and number of the different forms of tracrRNA vary among CRISPR types, for example only three forms of tracrRNA are visible in L. innocua, S. mutans, and S. thermophilus, and only two main forms are visible in N. meningitidis (Deltcheva et al., 2011). Although additional roles of tracrRNA were described in other bacteria (Chapter III.3. CRISPR-Cas and regulation of virulence page 39), it is not known whether it possesses other functions in S. pyogenes.

III.2.3. Cas9

Since the first publication describing DNA interference by Cas9 (Jinek et al., 2012), the molecular details of RNA binding and DNA cleavage have been elucidated, and four crystal structures of SpCas9 are publicly available (Anders et al., 2014; Jiang et al., 2015; Jinek et al., 2014; Nishimasu et al., 2014; Charpentier, 2015). In these structures, the tracrRNA:crRNA duplex was replaced by a single- guide RNA (sgRNA), a synthetic fusion between both RNA sequences, that was shown to be functional for DNA targeting in vitro and in vivo

36 Introduction

(Jinek et al., 2012; Nishimasu et al., 2014). The different structures – Cas9 apoenzyme, Cas9 in complex with single guide RNA and target DNA, and Cas9 bound to single-guide RNA – reveal that Cas9 undergoes major conformational changes both upon dual- RNA binding and target DNA recognition (Anders et al., 2014; Nishimasu et al., 2014; Jiang et al., 2015). Cas9 contains two flexible lobes, the recognition (REC) and the nuclease (NUC) lobes; harboring a positively charged groove at their interface which can accommodate the negatively charged sgRNA:target DNA duplex (20 bp) (Nishimasu et al., 2014). The Cas9 specific REC lobe is not conserved in the different type II subtypes and varies both in sequence and length. The HNH and the RuvC-like domains of the NUC lobe are responsible for the dsDNA cleavage (Jinek et al., 2012; Sapranauskas et al., 2011). The NUC lobe also contains a Cas9 specific C-terminal region involved in PAM recognition (PI domain) (Nishimasu et al., 2014). An arginine rich motif which forms a “bridge helix” that is critical for the binding of the sgRNA and the target DNA connects both lobes (Nishimasu et al., 2014). In detail, the mechanism of SpCas9 activity begins first with the recognition of the RNA-duplex; this yields conformational changes of Cas9 which is then in an active state for DNA recognition (Jiang et al., 2015). Thereby, the structure of tracrRNA anti-repeat and crRNA repeat duplex, and the specific secondary structure of the tracrRNA 3’ end are crucial features. Although a short sgRNA (with a short tracrRNA tail) can activate Cas9 cleavage in vitro (Jinek et al., 2012), longer sgRNAs improve in vivo Cas9 cleavage (Hsu et al., 2013; Nishimasu et al., 2014). Thus, while stem loop 1 is necessary to form a functional sgRNA-Cas9 complex, stem loops 2 and 3 are important for the complex stability (Nishimasu et al., 2014). Upon sgRNA binding, the PI domain of the sgRNA-Cas9 complex recognizes the PAM’s “GG” sequence (located on the non-complementary strand of the dsDNA target) in a sequence specific manner (Anders et al., 2014). Two conserved arginine residues from the PI domain, R1333 and R1335, are interacting with the PAM (Anders et al., 2014). This triggers the DNA strand separation allowing the sgRNA-Cas9 complex to search for complementary nucleotides directly upstream of the PAM. Base-pairing between the sgRNA and the target DNA entails formation of a stable R-loop (Jinek et al., 2012; Sternberg et al., 2014; Anders et al., 2014; Szczelkun et al., 2014; Jiang et al., 2015). R-loop formation progresses from the PAM proximal to the PAM distal end of the protospacer. The RuvC domain (assembled from the three split RuvC motifs) cleaves the non-complementary

37 Introduction strand of the invading DNA, while the HNH domain cleaves the complementary strand, resulting in a blunt cut, 3 nt upstream of the PAM sequence (Jinek et al., 2014; Sapranauskas et al., 2011).

Harnessing Cas9 activity for genome editing purposes

In 1997, although the role of CRISPR-Cas was not yet understood, it was proposed that this repeat-spacer system could be used for strain typing, by comparing spacer composition (Kamerbeek et al., 1997). After the experimental demonstration that the type II-A CRISPR-Cas system of S. thermophilus acts as an adaptive immune system against phages (Barrangou et al., 2007), it was suggested that artificially modeling this system could be utilized in the dairy industry, where avoiding phage infection is a constant challenge (Barrangou and Horvath, 2012; Pennisi, 2013). Then, the interest of the scientific community in this system started to grow rapidly when applications for Cas6 (specific RNA cleavage) (Hochstrasser and Doudna, 2015) and especially Cas9 were proposed (Jinek et al., 2012). Indeed, it was suggested that sgRNA programmed SpCas9 could cleave any dsDNA sequence of interest followed by a NGG PAM (Jinek et al., 2012). As of today, Cas9 is widely used as a dual-RNA programmable nuclease with a broad range of applications, including genome editing and gene silencing, in numerous organisms (Cong et al., 2013; Jinek et al., 2013; Mali et al., 2013b; Doudna and Charpentier, 2014). Cas9 generates sequence specific DSB that can be repaired either by the non-homologous end-joining (NHEJ) or the homology- directed repair (HDR) systems. NHEJ repair will result in mutation, by insertions or deletion (INDELS) at the site of the DSBs, and with the HDR system, the targeted sequence can be replaced by a sequence of interest (Ran et al., 2013). Combining several sgRNAs allows the cleavage of multiple target sequences at the same time, so called multiplexing (Sakuma et al., 2014). Both nuclease domains can be inactivated separately or together to utilize Cas9 as a DNA nicking enzyme (nickase Cas9: nCas9) or as a DNA binding protein (dead Cas9: dCas9), respectively (Jinek et al., 2012; Doudna and Charpentier, 2014). Using nCas9 in combination with paired sgRNAs targeting each DNA strand improves specificity in eukaryotic cells and facilitates homology- directed repair (Mali et al., 2013a; Ran et al., 2013). The DNA binding dCas9 tool enables silencing of the transcription of the sequence of interest. This technique, named CRISPRi (CRISPR interference), allows the creation of knock-down strains (Perez-Pinera et al., 2013; Qi et al., 2013). In addition, dCas9 fused with transcriptional

38 Introduction

activators or repressors constitutes a new way to control the transcription of the targeted sequences (Gilbert et al., 2013). The possibilities offered by this tool are constantly increasing, with nearly 1000 publications about Cas9 since 2012. Indeed, many studies aim to increase Cas9 specificity and efficiency by decreasing off-site targeting (cleavage by Cas9 when presence of mismatches between guide RNA and targeted sequence), broaden the choice of PAMs by searching for orthologous Cas9, and make delivery in cell easier (smaller Cas9 variants) (Doudna and Charpentier, 2014).

III.3. CRISPR-Cas and regulation of virulence

In addition to their role in adaptive immunity, a variety of additional roles have been reported for the components of various CRISPR-Cas systems in diverse cellular processes, including bacterial virulence regulation (Sampson and Weiss, 2013; Louwen et al., 2014; Westra et al., 2014; Barrangou, 2015). Cas proteins from E. coli (type I-E) and Myxococcus xanthus (type I and III) were proposed to mediate DNA repair (Babu et al., 2011) and regulate sporulation and fruiting-body formation, respectively (Boysen et al., 2002; Wallace et al., 2014). In the type I system of Pseudomonas aeruginosa the interaction between a spacer and a partially complementary prophage inhibits biofilm formation and swarming (Cady and O’Toole, 2011) (Heussler et al., 2015). In L. monocytogenes, an orphan CRISPR array that contains 5 repeats, codes for RliB sRNA. RliB base-pairs with and stabilizes the feoAB mRNA, which encodes an iron transporter (Mandin et al., 2007).

In a number of bacteria, the Cas proteins of type II CRISPR-Cas systems have been reported to participate in virulence regulation. For example, Cas2 from the type II-B CRISPR-Cas system of Legionella pneumophila is important for intracellular survival within amoebae, independently from the rest of the system (Gunderson and Cianciotto, 2013). Although the molecular mechanism is unknown, it was postulated that Cas2 RNase activity could regulate mRNAs of virulence genes (Beloglazova et al., 2008; Gunderson and Cianciotto, 2013). Additionally, in Campylobacter jejuni and Neisseria meningitidis, Cas9 is critical for interactions with host cells (Louwen et al., 2013; Louwen and van Baarlen, 2013; Sampson et al., 2013). The best-described example was discovered in the intracellular pathogen Francisella novicida, where the mRNA of an endogenous BLP (membrane bacterial lipoprotein) important for F. novicida

39 Introduction virulence (Sampson et al., 2013) is destabilized in presence of Cas9. Upon cell invasion, BLP is recognized by the Toll-like receptor 2 of the host immune system, which results in a pro-inflammatory response leading to clearance of the infection. Thus, downregulation of the BLP in presence of Cas9 allows the bacteria to escape this host response (Sampson et al., 2014). In this type II-B system, an additional sRNA, the small CRISPR-Cas associated RNA (scaRNA) – a degenerated CRISPR repeat-spacer sequence – is encoded in the vicinity of the CRISPR array (Sampson et al., 2013; Sampson and Weiss, 2013; Chylinski et al., 2014). Cas9, tracrRNA and scaRNA are the only CRISPR components necessary for the repression of the lipoprotein. Although the exact function of the scaRNA remains unknown, it was proposed to form a “degenerated repeat: anti-repeat” duplex with tracrRNA, reminiscent of the tracrRNA:crRNA duplex which could be recognized by Cas9 (Weiss and Sampson, 2014). The unpaired tracrRNA tail could then base-pair with the start codon/RBS region of the BLP transcript, guiding Cas9 to the BLP transcript and promoting its rapid degradation. The HNH and RuvC nuclease domains of Cas9 are not required for BLP repression by Cas9, however, a mutation in the RNA-binding arginine rich motif completely abrogates the regulatory effect (Sampson et al., 2013). It is still unknown how the stability of the BLP transcript is affected. It was suggested that unknown endonuclease motifs of Cas9 could act on the target RNA. Alternatively, Cas9 could help to recruit host RNase E which would degrade the mRNA target (Sampson et al., 2013; Weiss and Sampson, 2014). Following the characterization of RNA-targeting by F. novicida Cas9, this system was re-programmed with an RNA-targeting guide RNA (rgRNA) to cleave the viral hepatitis C ssRNA in eukaryotic cells (Price et al., 2015). It is now evident that components of the CRISPR-Cas system can also be recruited for alternative functions, unrelated to immunity. Given the number and the variability of CRISPR-Cas systems, it is likely that more examples of CRISPR regulatory functions remain to be discovered (Bikard and Marraffini, 2013). Upcoming challenges will be to discover and investigate novel mechanisms where components of CRISPR-Cas systems are involved in the regulation of bacterial gene expression. As Cas proteins have proven to be great biotechnology tools, these novel functions could also be used for synthetic gene regulation.

40 Results and Discussion

Results and Discussion

This chapter summarizes the results presented in the papers included in this thesis, with an emphasis on my contribution to these projects.

I. Paper I – Novel sRNAs in Streptococcus pyogenes

Le Rhun A., Beer Y.Y., Reimegård J., Chylinski K. and Charpentier E. (2015). RNA sequencing uncovers antisense RNAs and novel small RNAs in Streptococcus pyogenes. Accepted in RNA biology.

S. pyogenes is an important human pathogen responsible for a wide range of diseases. Numerous regulatory pathways controlling metabolism and virulence in this pathogen are yet to be deciphered. In this study, we aimed to identify and study novel sRNA regulators using sRNA sequencing in S. pyogenes SF370. To gain insights about the regulation of newly identified sRNAs, we also characterized the expression and maturation pattern of selected candidates at different times of growth in the presence or absence of rnc (encoding RNase III) and/or rny (encoding RNase Y), two endoribonucleases shown to be involved in the processing of sRNAs in other bacterial species (Shahbabian et al., 2009; Deltcheva et al., 2011; Marincola et al., 2012).

I.1. sRNA sequencing of S. pyogenes reveals novel putative sRNAs

We prepared cDNA libraries (ScriptMiner Small RNA-Seq kit Epicenter, using TAP) from RNA samples from S. pyogenes SF370 axenic cultures (mid-logarithmic phase of growth). The libraries were sequenced using an Illumina HiSeq2000 sequencing instrument (100 bp single end sequencing). The mapped reads were visualized using Integrative Genomics Viewer (IGV). Both a bioinformatic screening and a visual inspection of the genome with IGV were employed to identify novel putative sRNAs. Bioinformatic screening using parameters based on the 5’ start positions of the small transcripts led to the identification of 137 putative sRNAs in IGRs, 269 in UTRs, and 22 antisense to CDSs. By visual inspection of the mapped reads, 197 transcripts were annotated as putative regulatory RNAs (58 in IGRs, 97 in UTRs and 28 antisense to another transcript). Among the identified sRNAs, 92 are novel. The validity of our screening was supported by the fact that 141

41 Results and Discussion sRNAs were retrieved in both screens, including the already described FasX RNA, Pel RNA and tracrRNA. In total, 35 sRNAs were attributed a predicted function using the Rfam database, including functional sRNAs such as 6S RNA, 4.5S RNA, tmRNA, ribosomal proteins leaders, T-boxes and riboswitches. Experimental validation of the expression of 30 selected sRNAs and asRNAs was performed by Northern blot analysis at different phases of growth. We noticed that several sRNAs are expressed in a growth dependent manner. We also observed that some sRNA transcripts could be processed forms of longer RNAs (not detected by sRNA sequencing). In some cases, the size of the sRNA in the sRNA sequencing data and in the Northern blot analysis are different (transcript longer by Northern blot), which could be an artefact of the single-end sequencing data. We hypothesize that these longer sRNAs could originate from longer transcripts which are not visible in our sequencing results. Four sRNAs and four asRNAs harboring both a promoter and terminator were selected as examples, and the detailed locus, structure and conservation of those RNAs were described. Defined sizes by Northern blot, comparable to the ones predicted between the promoter and terminator, strongly support that these RNAs constitute products of specific transcription.

I.2. sRNAs regulated by RNases

The fact that some sRNAs have several transcript forms of different size in the Northern blot analysis suggested that RNases could be involved in their processing (alone or in duplex with their target mRNA). To test the possible role of S. pyogenes RNases in sRNA processing/degradation, we compared the expression profile of the 30 candidates in WT, ∆rnc, and ∆rny strains. We demonstrated that two putative regulatory elements, Lacto- rpoB and 23S-methyl are regulated by RNase III. These elements are located respectively in the 5’ UTR of the gene encoding the RpoB RNA polymerase subunit and the 23S rRNA methyltransferase. Both sRNA species exhibit two transcript forms by Northern blotting analysis with the smaller one being absent in the ∆rnc strain. The transcript ends visualized on IGV form a 2 nt 3'-overhang, characteristic of RNase III cleavage, in the double-stranded region of the stem loop (predicted by RNAfold). The sizes of the RNAs after processing are consistent with the ones retrieved by Northern blot analysis. We also observed that the expression of several novel sRNAs and asRNAs are affected by RNase III and/or RNase Y deletion. For

42 Results and Discussion

example, Spy_sRNA1222613 from the 3’ UTR of hlpA virulence factor (histone-like DNA-binding protein) (Stinson et al., 1998), was regulated by both RNases III and Y. Analysis of this sRNA by Northern blot showed one long form and two smaller transcripts. In the WT strain, the smallest transcript (~30 nt) was present only during the early logarithmic growth phase and the second transcript (~48 nt) was present only during the early stationary growth phase. None of the small transcripts were present during the mid- logarithmic phase of growth. The smallest transcript (~30 nt) was absent in the ∆rnc strain, suggesting that this form was dependent of 3’ UTR hlpA mRNA RNase III processing. The ~48 nt form was absent in the ∆rny strain, suggesting that the 3’ UTR hlpA mRNA was also processed by RNase Y. Hence, the 3’ UTR hlpA mRNA virulence factor is tightly regulated in a growth phase and RNases dependent manner. In addition to its histone role, HlpA was shown to be able to bind heparan sulfate-proteoglycans from the host ECM, and to induce immune complex formation. It is still to be determined if the two small transcripts are processed during interaction with a target or if they originate from hlpA growth dependent autoregulation. asRNA Spy_sRNA477741 is encoded antisense to the 3’ UTR of SPy_0593 hypothetical protein. Spy_sRNA477741 presented two long transcripts by Northern blotting analysis in the WT. Both transcripts were absent in the ∆rnc strain, and only the smaller transcript was absent in the ∆rny strain. These data suggest that each of the two transcripts originated from a cut by RNase Y and RNase III, respectively.

I.3. Conclusion sRNA sequencing analysis revealed 92 new putative sRNAs, located in IGRs, UTRs and for the first time described sRNAs antisense to transcripts in S. pyogenes. 30 sRNAs were validated by Northern blot analysis, presenting various patterns of expression and growth phase regulation. Additional studies in RNases III and Y deletion mutant strains established that 9 sRNAs were affected by one or both RNases. We added a large number of novel putative sRNAs to the previously existing collection. Our observations that these sRNAs are tightly regulated, either by growth phase and/or RNases, may predict a regulatory function in S. pyogenes. This study should incentivize identification of sRNA targets and elucidation of specific mechanisms of action in this pathogen.

43 Results and Discussion

II. Paper II – tracrRNA and Cas9 families

Chylinski K., Le Rhun A. and Charpentier E. (2013). The tracrRNA and Cas9 families of type II CRISPR-Cas immunity systems. RNA Biology. 10:5, 726–737.

In this study, we used bioinformatics and RNA sequencing approaches to characterize the type II CRISPR-Cas system. This type is defined by the presence of Cas9 and tracrRNA. By searching all available genomes on NCBI for the occurrence of Cas9, we were able to collect a list of type II systems in which tracrRNA gene location was predicted using bioinformatics. Subsequent experimental analyses by RNA sequencing, performed mainly by myself (see figures and table underlined in the text), allowed us to determine the characteristics of orthologous tracrRNAs and crRNAs from selected species.

II.1. Bioinformatic analyses of type II CRISPR-Cas systems

We first used BLAST to identify homologous Cas9 sequences, and retrieved 235 sequences from 203 bacterial species with high diversities in amino acid composition and protein size. We constructed a Cas9 phylogenetic tree based on multiple sequence alignment of 75 representative sequences and investigated the architecture of CRISPR loci associated with chosen Cas9 orthologs. Phylogenetic analyses showed that the Cas9 subclustering correlates with the diverse cas operon architecture, the CRISPR repeat length, and the predicted position of tracrRNA. Moreover, in addition to the previously described subtypes II-A (characterized by the presence of csn2) and II-B (encoding long and divergent cas9 variants and the cas4 gene), we identified a new monophyletic subgroup, the subtype II-C; characterized by a minimal three-cas gene operon (cas9, cas1 and cas2). To assess the presence of tracrRNA ortholog sequences in the 75 representative loci, we looked for anti-CRISPR repeat sequences within the CRISPR-Cas loci and selected the ones located in the intergenic regions. In total, we could predict putative tracrRNA orthologs in 56 out of the 75 loci. These RNAs were found in four typical locations: upstream of the cas9 gene, in the region between cas9 and cas1, and upstream or downstream of the CRISPR array. For some loci we could not detect a tracrRNA ortholog, thus, their functionality remains to be determined.

44 Results and Discussion

The comparative analysis of orthologous tracrRNA sequences and predicted structures revealed a family of highly diverse sRNAs with no significant similarities.

II.2. sRNA sequencing

We used small RNA sequencing to validate the expression and co- processing of the in silico predicted pre-crRNAs and tracrRNAs. As representatives of the different type II CRISPR-Cas subtypes, we selected the type II-A systems from S. mutans and Listeria innocua, the type II-B system from Francisella novicida and the type II-C systems from Neisseria meningitidis and Campylobacter jejuni. The libraries were prepared with ScriptMiner Small RNA-Seq Library Preparation Kit (Epicenter) from TAP treated total RNA (deprived from rRNAs) extracted during mid-logarithmic phase of growth and sequenced using HiSeq2000 sequencing instrument (Illumina). The 5' and 3' ends of the primary and processed transcripts of tracrRNAs and crRNAs were determined by selecting the most highly represented ends of the sequenced reads (Table 1, Supplementary Figure 2 and Supplementary Table 3). The 5’ ends of the processed tracrRNAs and crRNAs were found within the repeat:anti-repeat complementarity regions and the processed tracrRNA:crRNA duplexes were forming 2 nt 3’-overhangs typical for RNase III- mediated dsRNA cleavage. Thus, we confirmed the previous finding of RNase III being the endoribonuclease involved in type II CRISPR RNA maturation (Figure 3 and Supplementary Table 3).

II.3. Conclusion tracrRNAs are characterized by their ability to base-pair with pre- crRNA repeats from type II CRISPR-Cas systems, a feature required both in pre-crRNA maturation and specific DNA interference by dual- RNA:Cas9 (Deltcheva et al., 2011; Jinek et al., 2012). This study shows that tracrRNAs comprise a family of unusual sRNAs defined by a common function, but with no obvious conservation of structure, sequence or position of the tracrRNA-encoding gene within the CRISPR locus. In this study we identified a large panel of diverse tracrRNA and Cas9 sequences, including five experimentally validated tracrRNA sequences, forming a vast collection of Cas9 orthologs with their corresponding dual-RNAs for genome editing purposes. Our data show as well that although tracrRNA orthologs are not generally conserved; in closely related loci defined by Cas9

45 Results and Discussion conservation there are sequence similarities of tracrRNA orthologs, which raises the question of co-evolution between Cas9 proteins and tracrRNAs.

III. Paper III – dual-RNA and Cas9 orthologous systems

Fonfara I.*, Le Rhun A.*, Chylinski K., Makarova K.S., Lécrivain A.- L., Bzdrenga J., Koonin E.V. and Charpentier E. (2014). Phylogeny of Cas9 determines functional exchangeability of dual-RNA and Cas9 among orthologous type II CRISPR-Cas systems. Nucleic Acids Research. 42:4, 2577–2590. *Contributed equally

To follow up on the questions from the previous study (II. Paper II – tracrRNA and Cas9 families page 44), we used bioinformatic predictions followed by in vivo and in vitro approaches to characterize the evolution of the type II CRISPR-Cas system, in particular the interchangeability of Cas9 and dual-RNAs from various systems. I contributed mainly to the in vivo analyses presented in the paper (see figures and table underlined in the text).

III.1. Origin of type II CRISPR-Cas systems

We updated our previous screening of Cas9 orthologous sequences and identiﬁed 653 Cas9 orthologs in bacterial species from 12 phyla isolated from diverse environments. We constructed a phylogenetic tree based on 83 representative sequences. As described before, we observed a high diversity in Cas9 length and amino acid sequence. We found a poor correlation between Cas9 phylogeny and taxonomy of Cas9 harboring bacterial species but we identiﬁed similar Cas9 orthologs in evolutionary distant bacteria isolated from similar habitats. This strongly supports the hypothesis that transfer of the type II CRISPR-Cas systems among bacteria is both vertical and horizontal. By trans-complementation of S. pyogenes RNase III-deficient strains followed by Northern blot analysis, we showed that diverse RNases III from various bacterial species can process S. pyogenes tracrRNA:pre-crRNA duplex. This suggests that after horizontal transfer, crRNAs from type II CRISPR-Cas systems could be maturated and functional (Figure 2, Supplementary Figure S5).

46 Results and Discussion

III.2. The conserved RuvC and HNH motifs of Cas9

Although Cas9 proteins are very diverse and variable, specific endonuclease motifs are present in all orthologs and are well conserved. In order to further characterize the involvement of the two catalytic domains of Cas9 (i.e. HNH and split RuvC) in tracrRNA:pre- crRNA processing and DNA interference, we mutated selected putative catalytic residues substituting them with alanine (RuvC: D10A, E762A, HH983AA, D986A and HNH: H840A, N854A, N863A). The presence of processed tracrRNA and mature crRNAs in S. pyogenes Cas9 deletion mutant trans-complemented with the aforementioned Cas9 point mutants established that these catalytic motifs are not involved in the binding of Cas9 to the dual-RNA (Figure 3B and Supplementary Figure S7). We also performed phage infection-mimicking experiments, using transformation assays with plasmids containing a protospacer targeted by one of S. pyogenes SF370 crRNAs accompanied by S. pyogenes Cas9 PAM, to investigate the role of those residues in DNA interference. The plasmids were targeted by Cas9 wild-type and Cas9 N854A, but not by the other Cas9 point mutants, showing their importance in DNA interference (Figure 3C). In vitro DNA cleavage assays confirmed these data since Cas9 point mutants with a single nuclease domain inactivated cleave only one strand of the plasmid DNA (in contrary to Cas9 wild-type and Cas9 N854A double stranded DNA break). We showed that in addition to the previously described N-terminal RuvC and HNH motifs (Jinek et al., 2012), catalytic residues from the central RuvC motifs are also involved in DNA interference.

III.3. Cas9 exchangeability in tracrRNA:pre-crRNA maturation by RNase III

To test our hypothesis of Cas9 and dual-RNA co-evolution we selected CRISPR-Cas systems from all three major type II subtypes. For type II-A, we selected S. pyogenes, S. mutans and S. thermophilus (locus 1 and 2); for type II-B, Francisella novicida; and for type II-C, Neisseria meningitidis, Pasteurella multocida and Campylobacter jejuni. The presence of processed tracrRNA and mature crRNAs in S. pyogenes Cas9 deletion mutant complemented with the Cas9 from S. mutans and S. thermophilus (locus 1) showed that these proteins are able to assist tracrRNA:pre-crRNA processing by RNase III. Cas9

47 Results and Discussion proteins from the other orthologous systems could not restore the dual-RNA processing phenotype in S. pyogenes. Thus, only proteins from closely related systems (II-A) can substitute for endogenous Cas9 in dual-RNA stabilization and RNase III maturation (Figure 4B, Supplementary Figure S8).

III.4. Cas9 exchangeability in dual-RNA:Cas9 DNA interference

Cas9 requires a specific PAM sequence for DNA cleavage activity. In order to identify PAMs for the selected representative Cas9 orthologs, we aligned the sequences downstream of the targeted protospacers (crRNA-targeted sequences) and looked for conserved motifs. For all investigated CRISPR loci, we identified putative PAMs and validated their functionality in DNA interference using the corresponding dual- RNA:Cas9. Having identified the Cas9 specific PAM sequences, we were able to study the exchangeability between Cas9 and tracrRNA:crRNA from various orthologs in DNA interference by in vitro plasmid cleavage assays using the specific corresponding PAM for each Cas9 ortholog. Only the combinations of Cas9 and dual-RNA from closely related type II systems confer DNA cleavage. We showed that phylogenetic clustering of Cas9 defines dual-RNA:Cas9 exchangeability, providing an experimental support of dual-RNA/Cas9 co-evolution.

III.5. Conclusion

In this paper, we studied eight Cas9 protein representatives of the different type II subtypes. We found functional PAMs and assessed Cas9 specificity toward dual-RNA using in vitro and in vivo experiments.

The Cas9 phylogeny differs from their bacterial host taxonomy, but can correlate with their habitat; this supports the hypothesis of the horizontal transfer of the type II CRISPR-Cas systems. Moreover, the lack of host RNase III specificity for dual-RNA processing supports the feasibility of this horizontal transfer and shows that dual-RNA diversity is not connected with adaptation to the host enzymatic machinery. Our data further describe the type II CRISPR RNA processing mechanism, showing that dual-RNA processing and/or stability do not involve Cas9 enzymatic activity. We further demonstrated a dual-RNA/Cas9 co-evolution by showing the possible interchangeability of RNA and protein components of close type II

48 Results and Discussion

systems. Identification of exchangeable and orthogonal systems could serve as basis for multiplexing gene targeting experiments with various dual-RNA/Cas9 combinations used simultaneously, e.g. for DNA binding and cleavage. Indeed, two distinct type II CRISPR-Cas systems could function independently in the same cell, each one with a specific dual-RNA/Cas9 complex and a Cas9 specific PAM. This work contributes to enhance the specificity and adaptability of Cas9 nuclease for various genetic applications. This was shown recently by others, which labelled diverse genomic loci using dCas9-fluorescent orthologs that cannot cross-talk (Ma et al., 2015). In addition, we described that similar dual-RNAs from closely related systems display similar secondary structures and suggested that this is the basis of Cas9 speciﬁc recognition of the repeat:anti- repeat duplexes, also observed in (Nishimasu et al., 2014).

49 Summary of the main findings of this thesis

Summary of the main findings of this thesis

I. Small RNAs in S. pyogenes (paper I)

• 92 novel putative sRNAs and asRNAs were identified and the expression of 30 selected sRNAs was validated experimentally by Northern blot analysis

• 2 regulatory elements, 6 sRNAs and 2 asRNAs are regulated by RNase III or/and RNase Y

II. type II CRISPR-Cas systems (papers II and III)

• tracrRNAs and crRNAs from diverse representative orthologs of the type II CRISPR-Cas system are expressed and their maturation is done by RNase III in the repeat:anti-repeat duplexes

• tracrRNA is part of an unusual family gathering sRNAs with the same function, with no conservation of structure, sequence or location

• tracrRNA:crRNA duplex structure is conserved in closely related systems and co-evolved with the Cas9 protein

• Cas9 proteins and dual-RNAs are exchangeable only between closely related subtypes of CRISPR-Cas type II systems. Hence, orthogonal Cas9 enzymes can be combined to increased versatility and possibly specificity of the RNA- programmable Cas9 tool

50 Acknowledgements

Acknowledgements

I am grateful to my thesis committee: Anna Arnqvist, Jörgen Johansson, Franz Narberhaus and Gerhart Wagner, for accepting to attend my thesis defense8.

I would like to thank the people who made this thesis possible. My first contacts with the world of research, Brice Felden and Marc Hallier, who encouraged me during my pharmacy and master studies, and shared their passion for "les petits ARN bactériens". My thesis supervisor, Emmanuelle Charpentier, who gave me the chance to work with interesting and challenging sRNAs projects. Thank you for the opportunity to attend great conferences and courses, and for the unexpected surprise of making me move over Europe! Small digression: I am still waiting for your famous chocolate cake I heard so much about: Is it a story only told to impress new PhD students? My co-supervisor, Sun Nyunt Wai, the members of my Ph.D. committee, Tracy Nissan and Ulrich v. Pawel-Rammingen, the JC groups, BEH, SNW, JJ, for your comments on my work over the years. Maria and Eva-Maria, Anne, Helga and Jennifer, for your help with the Swedish and German administrations. Johan, Estelle and Michael, at SciLifeLab, for the helpful collaboration and for teaching me bioinformatics. All my colleagues at the MIMS and HZI for the nice work environment.

Many thanks to all the present and past members of the Charpentier’s groups of Vienna, Umeå, Braunschweig and Berlin, especially: MFPL: Karine, Eli, Fanny and Silvia, for your help when I was starting in the lab. Chris, my first long-distance colleague! It was really a good experience working together, I learned a lot from you. MIMS: Martine, Emmanuel and Hinnerk, for the good time we had in the lab. Sophie, among so many things... our amazing Easter trip to Abisko. Khan, for bringing the best princess cakes ;) Geetanjali, for your chocolate lemon cheese cake (obviously), the dress days, the movie nights, your wonderful paintings and the lab song that will stay in our mind forever. Anne-Laure, for making me discover a new level of complexity with our intricate email

8 December in Umeå "Daily low temperatures range from -11°C to -6°C, falling below -20°C or exceeding 1°C only one day in ten."

51 Acknowledgements conversations and our intense Uppsala work trips. Uli, for your enthusiasm during project discussions. I have one question for you guys... How is it possible that the number of raclette parties doubled after I left Umeå?! HZI: Sonja, for the mattress shopping on my first day in Braunschweig! Majda, for the cute guinea pigs pictures and for our shared passion for chocolate! Andrés, for your inexhaustible good mood and for our juggling workouts. Lina, pour nos conversations en Français :) Hagen and Frank, for the best morning greetings. James for all these English words I never heard before. Caro, Lisa, Sarah and Katja for the small talks. Yan Yan, for your dynamic nature and Annette, for your enthusiasm, it was a great pleasure working with both of you. Cristina, for listening to all my server issues and helping me with bioinformatics. MPIIB: Dominik, for setting up the lab! We will be there soon. The best students: Svitlana, Aman, Frieda, Hélène and Laura for your very hard work and the fun we had :) I have been so lucky to work with you. The wonderful people who moved with me... TWICE! Shi Pey for keeping the lab song alive even after the moving, for the chocolate macarons overdose, for our French conversations about coffee, and coffee, and coffee... Ines for the knitting, the flammkuchen, the amazing handbrot, for always having the best advices: from “How to make the best EMSAs?” to “What to cook tonight?”. Thank you all for your support during these years and all the moments we shared, which made my work so fun, of course thanks for all your wise comments about my thesis.

A huge tack to Telli and Linn! I miss Swedish folkmusik, the Polska dans, the knitting afternoons and calm winter evenings with soups... so relaxing! Merci Cendrella, for the best profiteroles ever.

Merci Maman, Papa, Fabienne, Patrick, Jeanne, Pierrot, Zoé, Maële, Emilie, Anaïs, Marc, pour m'avoir toujours soutenue. Vous êtes tous venus me rendre visite, que de bons souvenirs :) Promis, il fait toujours beau à Umeå, ou alors il neige, mais pas de pluie... enfin presque ! Sans oublier bien sûr... Thibaud. Tu m'as appris tellement de choses et tu m'as beaucoup aidé, même si je n'ai pas toujours été la plus patiente ! Merci de m'avoir tant encouragée et d'être là pour moi.

52 References

References

Akesson, P., Sjöholm, A.G., Björck, L., 1996. Protein SIC, a novel extracellular protein of Streptococcus pyogenes interfering with complement function. J. Biol. Chem. 271, 1081–1088.

Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local alignment search tool. J. Mol. Biol. 215, 403–410.

Altuvia, S., 2007. Identification of bacterial small non-coding RNAs: experimental approaches. Curr. Opin. Microbiol. 10, 257–261.

Anders, C., Niewoehner, O., Duerst, A., Jinek, M., 2014. Structural basis of PAM-dependent target DNA recognition by the Cas9 endonuclease. Nature 513, 569–573.

Andronescu, M., Zhang, Z.C., Condon, A., 2005. Secondary structure prediction of interacting RNA molecules. J. Mol. Biol. 345, 987–1001.

Babu, M., Beloglazova, N., Flick, R., Graham, C., Skarina, T., Nocek, B., Gagarinova, A., Pogoutse, O., Brown, G., Binkowski, A., Phanse, S., Joachimiak, A., Koonin, E.V., Savchenko, A., Emili, A., Greenblatt, J., Edwards, A.M., Yakunin, A.F., 2011. A dual function of the CRISPR–Cas system in bacterial antivirus immunity and DNA repair. Mol. Microbiol. 79, 484–502.

Backofen, R., Amman, F., Costa, F., Findeiß, S., Richter, A.S., Stadler, P.F., 2014. Bioinformatics of prokaryotic RNAs. RNA Biol. 11, 31–44.

Backofen, R., Hess, W.R., 2010. Computational prediction of sRNAs and their targets in bacteria. RNA Biol. 7, 33–42.

Barnett, T.C., Bugrysheva, J.V., Scott, J.R., 2007. Role of mRNA stability in growth phase regulation of gene expression in the group A Streptococcus. J. Bacteriol. 189, 1866– 1873.

Barrangou, R., 2015. The roles of CRISPR-Cas systems in adaptive immunity and beyond. Curr. Opin. Immunol. 32, 36–41.

Barrangou, R., Fremaux, C., Deveau, H., Richards, M., Boyaval, P., Moineau, S., Romero, D.A., Horvath, P., 2007. CRISPR provides acquired resistance against viruses in prokaryotes. Science 315, 1709–1712.

Barrangou, R., Horvath, P., 2012. CRISPR: new horizons in phage resistance and strain identification. Annu. Rev. Food Sci. Technol. 3, 143–162.

Barrick, J.E., Breaker, R.R., 2007. The distributions, mechanisms, and structures of metabolite- binding riboswitches. Genome Biol. 8, R239.

Beall, B., Facklam, R., Thompson, T., 1996. Sequencing emm-specific PCR products for routine and accurate typing of group A streptococci. J. Clin. Microbiol. 34, 953–958.

Beisel, C.L., Storz, G., 2010. Base pairing small RNAs and their roles in global regulatory networks. FEMS Microbiol. Rev. 34, 866–882.

53 References

Beloglazova, N., Brown, G., Zimmerman, M.D., Proudfoot, M., Makarova, K.S., Kudritska, M., Kochinyan, S., Wang, S., Chruszcz, M., Minor, W., Koonin, E.V., Edwards, A.M., Savchenko, A., Yakunin, A.F., 2008. A novel family of sequence-specific endoribonucleases associated with the clustered regularly interspaced short palindromic repeats. J. Biol. Chem. 283, 20361–20371.

Beres, S.B., Musser, J.M., 2007. Contribution of Exogenous Genetic Elements to the Group A Streptococcus Metagenome. PLoS ONE 2, e800.

Berge, A., Björck, L., 1995. Streptococcal cysteine proteinase releases biologically active fragments of streptococcal surface proteins. J. Biol. Chem. 270, 9862–9867.

Bessen, D.E., 2009. Population biology of the human restricted pathogen, Streptococcus pyogenes. Infect. Genet. Evol. J. Mol. Epidemiol. Evol. Genet. Infect. Dis. 9, 581–593.

Beyer-Sehlmeyer, G., Kreikemeyer, B., Hörster, A., Podbielski, A., 2005. Analysis of the growth phase-associated transcriptome of Streptococcus pyogenes. Int. J. Med. Microbiol. 295, 161–177.

Bhaya, D., Davison, M., Barrangou, R., 2011. CRISPR-Cas systems in bacteria and archaea: versatile small RNAs for adaptive defense and regulation. Annu. Rev. Genet. 45, 273– 297.

Bikard, D., Marraffini, L.A., 2013. Control of gene expression by CRISPR-Cas systems. F1000prime Rep. 5, 47.

Bisno, A.L., Brito, M.O., Collins, C.M., 2003. Molecular basis of group A streptococcal virulence. Lancet Infect. Dis. 3, 191–200.

Biswas, I., Germon, P., McDade, K., Scott, J.R., 2001. Generation and surface localization of intact M protein in Streptococcus pyogenes are dependent on sagA. Infect. Immun. 69, 7029–7038.

Blount, K.F., Breaker, R.R., 2006. Riboswitches as antibacterial drug targets. Nat. Biotechnol. 24, 1558–1564.

Bobrovskyy, M., Vanderpool, C.K., 2013. Regulation of bacterial metabolism by small RNAs using diverse mechanisms. Annu. Rev. Genet. 47, 209–232.

Boisset, S., Geissmann, T., Huntzinger, E., Fechter, P., Bendridi, N., Possedko, M., Chevalier, C., Helfer, A.C., Benito, Y., Jacquier, A., Gaspin, C., Vandenesch, F., Romby, P., 2007. Staphylococcus aureus RNAIII coordinately represses the synthesis of virulence factors and the transcription regulator Rot by an antisense mechanism. Genes Dev. 21, 1353–1366.

Bolotin, A., Quinquis, B., Sorokin, A., Ehrlich, S.D., 2005. Clustered regularly interspaced short palindrome repeats (CRISPRs) have spacers of extrachromosomal origin. Microbiol. Read. Engl. 151, 2551–2561.

Bondy-Denomy, J., Garcia, B., Strum, S., Du, M., Rollins, M.F., Hidalgo-Reyes, Y., Wiedenheft, B., Maxwell, K.L., Davidson, A.R., 2015. Multiple mechanisms for CRISPR-Cas inhibition by anti-CRISPR proteins. Nature 526, 136–139.

54 References

Bondy-Denomy, J., Pawluk, A., Maxwell, K.L., Davidson, A.R., 2013. Bacteriophage genes that inactivate the CRISPR/Cas bacterial immune system. Nature 493, 429–432.

Bonnin, R.A., Bouloc, P., 2015. RNA degradation in Staphylococcus aureus: diversity of ribonucleases and their impact. Int. J. Genomics 2015, 395753.

Boysen, A., Ellehauge, E., Julien, B., Søgaard-Andersen, L., 2002. The DevT protein stimulates synthesis of FruA, a signal transduction protein required for fruiting body morphogenesis in Myxococcus xanthus. J. Bacteriol. 184, 1540–1546.

Brantl, S., 2012. Acting antisense: plasmid- and chromosome-encoded sRNAs from Gram- positive bacteria. Future Microbiol. 7, 853–871.

Brantl, S., Brückner, R., 2014. Small regulatory RNAs from low-GC Gram-positive bacteria. RNA Biol. 11, 443–456.

Brantl, S., Jahn, N., 2015. sRNAs in bacterial type I and type III toxin-antitoxin systems. FEMS Microbiol. Rev. 39, 413–427.

Breaker, R.R., 2012. Riboswitches and the RNA world. Cold Spring Harb. Perspect. Biol. 4, a003566.

Breaker, R.R., 2011. Prospects for riboswitch discovery and analysis. Mol. Cell 43, 867–879.

Brennan, R.G., Link, T.M., 2007. Hfq structure, function and ligand binding. Curr. Opin. Microbiol. 10, 125–133.

Brouns, S.J.J., Jore, M.M., Lundgren, M., Westra, E.R., Slijkhuis, R.J.H., Snijders, A.P.L., Dickman, M.J., Makarova, K.S., Koonin, E.V., Oost, J. van der, 2008. Small CRISPR RNAs guide antiviral defense in prokaryotes. Science 321, 960–964.

Bugrysheva, J.V., Scott, J.R., 2010. The ribonucleases J1 and J2 are essential for growth and have independent roles in mRNA decay in Streptococcus pyogenes. Mol Microbiol 75, 731–43.

Bugrysheva, J.V., Scott, J.R., 2010. Regulation of virulence gene expression in Streptococcus pyogenes: determinants of differential mRNA decay. RNA Biol. 7, 569–572.

Busch, A., Richter, A.S., Backofen, R., 2008. IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions. Bioinforma. Oxf. Engl. 24, 2849–2856.

Cady, K.C., O’Toole, G.A., 2011. Non-identity-mediated CRISPR-bacteriophage interaction mediated via the Csy and Cas3 proteins. J. Bacteriol. 193, 3433–3445.

Caldelari, I., Chao, Y., Romby, P., Vogel, J., 2013. RNA-mediated regulation in pathogenic bacteria. Cold Spring Harb. Perspect. Med. 3, a010298.

Cao, Y., Zhao, Y., Cha, L., Ying, X., Wang, L., Shao, N., Li, W., 2009. sRNATarget: a web server for prediction of bacterial sRNA targets. Bioinformation 3, 364–366.

Carapetis, J.R., Steer, A.C., Mulholland, E.K., Weber, M., 2005. The global burden of group A streptococcal diseases. Lancet Infect. Dis. 5, 685–694.

55 References

Carroll, R.K., Musser, J.M., 2011. From transcription to activation: how group A Streptococcus, the flesh-eating pathogen, regulates SpeB cysteine protease production. Mol. Microbiol. 81, 588–601.

Carte, J., Wang, R., Li, H., Terns, R.M., Terns, M.P., 2008. Cas6 is an endoribonuclease that generates guide RNAs for invader defense in prokaryotes. Genes Dev. 22, 3489–3496.

Cech, T.R., Zaug, A.J., Grabowski, P.J., 1981. In vitro splicing of the ribosomal RNA precursor of Tetrahymena: involvement of a guanosine nucleotide in the excision of the intervening sequence. Cell 27, 487–496.

Chao, Y., Vogel, J., 2010. The role of Hfq in bacterial pathogens. Curr. Opin. Microbiol. 13, 24– 33.

Charpentier, E., 2015. CRISPR-Cas9: how research on a bacterial RNA-guided mechanism opened new perspectives in biotechnology and biomedicine. EMBO Mol. Med. 7, 363– 365.

Charpentier, E., Richter, H., van der Oost, J., White, M.F., 2015. Biogenesis pathways of RNA guides in archaeal and bacterial CRISPR-Cas adaptive immunity. FEMS Microbiol. Rev. 39, 428–441.

Chaussee, M.A., Dmitriev, A.V., Callegari, E.A., Chaussee, M.S., 2008. Growth phase-associated changes in the transcriptome and proteome of Streptococcus pyogenes. Arch. Microbiol. 189, 27–41.

Chaussee, M.S., Sylva, G.L., Sturdevant, D.E., Smoot, L.M., Graham, M.R., Watson, R.O., Musser, J.M., 2002. Rgg influences the expression of multiple regulatory loci to coregulate virulence factor expression in Streptococcus pyogenes. Infect. Immun. 70, 762–770.

Chen, Z., Itzek, A., Malke, H., Ferretti, J.J., Kreth, J., 2013. Multiple roles of RNase Y in Streptococcus pyogenes mRNA processing and degradation. J Bacteriol 195, 2585– 94.

Chen, Z., Itzek, A., Malke, H., Ferretti, J.J., Kreth, J., 2012. Dynamics of speB mRNA transcripts in Streptococcus pyogenes. J Bacteriol 194, 1417–26.

Chevalier, C., Boisset, S., Romilly, C., Masquida, B., Fechter, P., Geissmann, T., Vandenesch, F., Romby, P., 2010. Staphylococcus aureus RNAIII binds to two distant regions of coa mRNA to arrest translation and promote mRNA degradation. PLoS Pathog. 6, e1000809.

Chiang-Ni, C., Wu, J.-J., 2008. Effects of streptococcal pyrogenic exotoxin B on pathogenesis of Streptococcus pyogenes. J. Formos. Med. Assoc. Taiwan Yi Zhi 107, 677–685.

Chylinski, K., Makarova, K.S., Charpentier, E., Koonin, E.V., 2014. Classification and evolution of type II CRISPR-Cas systems. Nucleic Acids Res. 42, 6091–105.

Cleary, P.P., Prahbu, U., Dale, J.B., Wexler, D.E., Handley, J., 1992. Streptococcal C5a peptidase is a highly specific endopeptidase. Infect. Immun. 60, 5219–5223.

56 References

Cole, J.N., Barnett, T.C., Nizet, V., Walker, M.J., 2011. Molecular insight into invasive group A streptococcal disease. Nat. Rev. Microbiol. 9, 724–736.

Cong, L., Ran, F.A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P.D., Wu, X., Jiang, W., Marraffini, L.A., Zhang, F., 2013. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823.

Coppins, R.L., Hall, K.B., Groisman, E.A., 2007. The intricate world of riboswitches. Curr. Opin. Microbiol. 10, 176–181.

Court, D.L., Gan, J., Liang, Y.-H., Shaw, G.X., Tropea, J.E., Costantino, N., Waugh, D.S., Ji, X., 2013. RNase III: genetics and function; structure and mechanism. Annu. Rev. Genet. 47, 405–431.

Dale, J.B., Fischetti, V.A., Carapetis, J.R., Steer, A.C., Sow, S., Kumar, R., Mayosi, B.M., Rubin, F.A., Mulholland, K., Hombach, J.M., Schödel, F., Henao-Restrepo, A.M., 2013. Group A streptococcal vaccines: paving a path for accelerated development. Vaccine 31 Suppl 2, B216–222.

Danger, J.L., Cao, T.N., Cao, T.H., Sarkar, P., Treviño, J., Pflughoeft, K.J., Sumby, P., 2015a. The small regulatory RNA FasX enhances group A Streptococcus virulence and inhibits pilus expression via serotype-specific targets. Mol. Microbiol. 96, 249–262.

Danger, J.L., Makthal, N., Kumaraswami, M., Sumby, P., 2015b. The small regulatory RNA FasX negatively regulates the expression of two fibronectin-binding proteins in the group A Streptococcus. J. Bacteriol. advance online publication.

Datsenko, K.A., Pougach, K., Tikhonov, A., Wanner, B.L., Severinov, K., Semenova, E., 2012. Molecular memory of prior infections activates the CRISPR/Cas adaptive bacterial immunity system. Nat. Commun. 3, 945.

Datta, V., Myskowski, S.M., Kwinn, L.A., Chiem, D.N., Varki, N., Kansal, R.G., Kotb, M., Nizet, V., 2005. Mutational analysis of the group A streptococcal operon encoding streptolysin S and its virulence role in invasive infection. Mol. Microbiol. 56, 681–695.

De Lay, N., Schu, D.J., Gottesman, S., 2013. Bacterial small RNA-based negative regulation: Hfq and its accomplices. J. Biol. Chem. 288, 7996–8003.

Deltcheva, E., Chylinski, K., Sharma, C.M., Gonzales, K., Chao, Y., Pirzada, Z.A., Eckert, M.R., Vogel, J., Charpentier, E., 2011. CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III. Nature 471, 602–607.

Deveau, H., Barrangou, R., Garneau, J.E., Labonté, J., Fremaux, C., Boyaval, P., Romero, D.A., Horvath, P., Moineau, S., 2008. Phage response to CRISPR-encoded resistance in Streptococcus thermophilus. J. Bacteriol. 190, 1390–1400.

Doudna, J.A., Charpentier, E., 2014. The new frontier of genome engineering with CRISPR- Cas9. Science 346, 1258096.

Durand, S., Gilet, L., Condon, C., 2012. The essential function of B. subtilis RNase III is to silence foreign toxin genes. PLoS Genet. 8, e1003181.

57 References

Durand, S., Tomasini, A., Braun, F., Condon, C., Romby, P., 2015. sRNA and mRNA turnover in Gram-positive bacteria. FEMS Microbiol. Rev. 39, 316–330.

Edwards, R.J., Taylor, G.W., Ferguson, M., Murray, S., Rendell, N., Wrigley, A., Bai, Z., Boyle, J., Finney, S.J., Jones, A., Russell, H.H., Turner, C., Cohen, J., Faulkner, L., Sriskandan, S., 2005. Specific C-terminal cleavage and inactivation of interleukin-8 by invasive disease isolates of Streptococcus pyogenes. J. Infect. Dis. 192, 783–790.

Eggenhofer, F., Tafer, H., Stadler, P.F., Hofacker, I.L., 2011. RNApredator: fast accessibility- based prediction of sRNA targets. Nucleic Acids Res. 39, W149–154.

Epshtein, V., Mironov, A.S., Nudler, E., 2003. The riboswitch-mediated control of sulfur metabolism in bacteria. Proc. Natl. Acad. Sci. U. S. A. 100, 5052–5056.

Evans, A.C., 1936. Studies on hemolytic streptococci. J. Bacteriol. 31, 611–624.

Federle, M.J., McIver, K.S., Scott, J.R., 1999. A response regulator that represses transcription of several virulence operons in the group A Streptococcus. J. Bacteriol. 181, 3649– 3657.

Ferretti, J.J., McShan, W.M., Ajdic, D., Savic, D.J., Savic, G., Lyon, K., Primeaux, C., Sezate, S., Suvorov, A.N., Kenton, S., Lai, H.S., Lin, S.P., Qian, Y., Jia, H.G., Najar, F.Z., Ren, Q., Zhu, H., Song, L., White, J., Yuan, X., Clifton, S.W., Roe, B.A., McLaughlin, R., 2001. Complete genome sequence of an M1 strain of Streptococcus pyogenes. Proc. Natl. Acad. Sci. U. S. A. 98, 4658–4663.

Fiedler, T., Sugareva, V., Patenge, N., Kreikemeyer, B., 2010. Insights into Streptococcus pyogenes pathogenesis from transcriptome studies. Future Microbiol. 5, 1675–1694.

Fozo, E.M., Hemm, M.R., Storz, G., 2008. Small toxic proteins and the antisense RNAs that repress them. Microbiol. Mol. Biol. Rev. 72, 579–589.

Fozo, E.M., Makarova, K.S., Shabalina, S.A., Yutin, N., Koonin, E.V., Storz, G., 2010. Abundance of type I toxin-antitoxin systems in bacteria: searches for new candidates and discovery of novel families. Nucleic Acids Res. 38, 3743–3759.

Garneau, J.E., Dupuis, M.-È., Villion, M., Romero, D.A., Barrangou, R., Boyaval, P., Fremaux, C., Horvath, P., Magadán, A.H., Moineau, S., 2010. The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA. Nature 468, 67–71.

Gasiunas, G., Barrangou, R., Horvath, P., Siksnys, V., 2012. Cas9-crRNA ribonucleoprotein complex mediates specific DNA cleavage for adaptive immunity in bacteria. Proc. Natl. Acad. Sci. U. S. A. 109, E2579–2586.

Georg, J., Hess, W.R., 2011. cis-antisense RNA, another level of gene regulation in bacteria. Microbiol. Mol. Biol. Rev. 75, 286–300.

Gerdes, K., Wagner, E.G.H., 2007. RNA antitoxins. Curr. Opin. Microbiol. 10, 117–124.

Gerhart, E., Wagner, H., Vogel, J., 2005. Approaches to identify novel non-messenger RNAs in bacteria and to investigate their biological functions: functional analysis of identified non-mRNAs, in: Hartmann, R.K., Bindereif, A., Schön, A., Westhof, E. (Eds.), Handbook of RNA Biochemistry. Wiley, pp. 614–642.

58 References

Gilbert, L.A., Larson, M.H., Morsut, L., Liu, Z., Brar, G.A., Torres, S.E., Stern-Ginossar, N., Brandman, O., Whitehead, E.H., Doudna, J.A., Lim, W.A., Weissman, J.S., Qi, L.S., 2013. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 154, 442–451.

Goldfarb, T., Sberro, H., Weinstock, E., Cohen, O., Doron, S., Charpak-Amikam, Y., Afik, S., Ofir, G., Sorek, R., 2015. BREX is a novel phage resistance system widespread in microbial genomes. EMBO J. 34, 169–183.

Gottesman, S., 2005. Micros for microbes: non-coding regulatory RNAs in bacteria. Trends Genet. 21, 399–404.

Gottesman, S., 2004. The small RNA regulators of Escherichia coli: roles and mechanisms. Annu. Rev. Microbiol. 58, 303–328.

Graham, M.R., Smoot, L.M., Migliaccio, C.A.L., Virtaneva, K., Sturdevant, D.E., Porcella, S.F., Federle, M.J., Adams, G.J., Scott, J.R., Musser, J.M., 2002. Virulence control in group A Streptococcus by a two-component gene regulatory system: global expression profiling and in vivo infection modeling. Proc. Natl. Acad. Sci. U. S. A. 99, 13855– 13860.

Graham, M.R., Virtaneva, K., Porcella, S.F., Barry, W.T., Gowen, B.B., Johnson, C.R., Wright, F.A., Musser, J.M., 2005. Group A Streptococcus transcriptome dynamics during growth in human blood reveals bacterial adaptive and survival strategies. Am. J. Pathol. 166, 455–465.

Granok, A.B., Parsonage, D., Ross, R.P., Caparon, M.G., 2000. The RofA binding site in Streptococcus pyogenes is utilized in multiple transcriptional pathways. J. Bacteriol. 182, 1529–1540.

Griffin, B.E., 1971. Separation of 32P-labelled ribonucleic acid components. The use of polyethylenimine-cellulose (TLC) as a second dimension in separating oligoribonucleotides of “4.5 S” and 5 S from E. coli. FEBS Lett. 15, 165–168.

Grissa, I., Vergnaud, G., Pourcel, C., 2007. The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformatics 8, 172.

Groher, F., Suess, B., 2014. Synthetic riboswitches - A tool comes of age. Biochim. Biophys. Acta 1839, 964–973.

Gruber, A.R., Lorenz, R., Bernhart, S.H., Neuböck, R., Hofacker, I.L., 2008. The Vienna RNA websuite. Nucleic Acids Res. 36, W70–74.

Gryllos, I., Levin, J.C., Wessels, M.R., 2003. The CsrR/CsrS two-component system of group A Streptococcus responds to environmental Mg2+. Proc. Natl. Acad. Sci. U. S. A. 100, 4227–4232.

Gunderson, F.F., Cianciotto, N.P., 2013. The CRISPR-associated gene cas2 of Legionella pneumophila is required for intracellular infection of amoebae. mBio 4, e00074– 00013.

59 References

Gusa, A.A., Scott, J.R., 2005. The CovR response regulator of group A Streptococcus (GAS) acts directly to repress its own promoter. Mol. Microbiol. 56, 1195–1207.

Hale, C.R., Zhao, P., Olson, S., Duff, M.O., Graveley, B.R., Wells, L., Terns, R.M., Terns, M.P., 2009. RNA-guided RNA cleavage by a CRISPR RNA-Cas protein complex. Cell 139, 945–956.

Halfmann, A., Kovács, M., Hakenbeck, R., Brückner, R., 2007. Identification of the genes directly controlled by the response regulator CiaR in Streptococcus pneumoniae: five out of 15 promoters drive expression of small non-coding RNAs. Mol. Microbiol. 66, 110–126.

Heath, A., DiRita, V.J., Barg, N.L., Engleberg, N.C., 1999. A two-component regulatory system, CsrR-CsrS, represses expression of three Streptococcus pyogenes virulence factors, hyaluronic acid capsule, streptolysin S, and pyrogenic exotoxin B. Infect. Immun. 67, 5298–5305.

Heler, R., Marraffini, L.A., Bikard, D., 2014. Adapting to new threats: the generation of memory by CRISPR-Cas immune systems. Mol. Microbiol. 93, 1–9.

Heler, R., Samai, P., Modell, J.W., Weiner, C., Goldberg, G.W., Bikard, D., Marraffini, L.A., 2015. Cas9 specifies functional viral targets during CRISPR-Cas adaptation. Nature advance online publication.

Heussler, G.E., Cady, K.C., Koeppen, K., Bhuju, S., Stanton, B.A., O’Toole, G.A., 2015. Clustered Regularly Interspaced Short Palindromic Repeat-dependent, biofilm-specific death of Pseudomonas aeruginosa mediated by increased expression of phage-related genes. mBio 6, e00129–00115.

Hindley, J., 1967. Fractionation of 32P-labelled ribonucleic acids on polyacrylamide gels and their characterization by fingerprinting. J. Mol. Biol. 30, 125–136.

Hochstrasser, M.L., Doudna, J.A., 2015. Cutting it close: CRISPR-associated endoribonuclease structure and function. Trends Biochem. Sci. 40, 58–66.

Hofacker, I.L., 2003. Vienna RNA secondary structure server. Nucleic Acids Res. 31, 3429– 3431.

Hondorp, E.R., McIver, K.S., 2007. The Mga virulence regulon: infection where the grass is greener. Mol. Microbiol. 66, 1056–1065.

Hsu, P.D., Scott, D.A., Weinstein, J.A., Ran, F.A., Konermann, S., Agarwala, V., Li, Y., Fine, E.J., Wu, X., Shalem, O., Cradick, T.J., Marraffini, L.A., Bao, G., Zhang, F., 2013. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827-832.

Huntzinger, E., Boisset, S., Saveanu, C., Benito, Y., Geissmann, T., Namane, A., Lina, G., Etienne, J., Ehresmann, B., Ehresmann, C., Jacquier, A., Vandenesch, F., Romby, P., 2005. Staphylococcus aureus RNAIII and the endoribonuclease III coordinately regulate spa gene expression. EMBO J. 24, 824–835.

Hurme, R., Rhen, M., 1998. Temperature sensing in bacterial gene regulation - what it all boils down to. Mol. Microbiol. 30, 1–6.

60 References

Hyman, P., Abedon, S.T., 2010. Bacteriophage host range and bacterial resistance. Adv. Appl. Microbiol. 70, 217–248.

Ishino, Y., Shinagawa, H., Makino, K., Amemura, M., Nakata, A., 1987. Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. J. Bacteriol. 169, 5429–5433.

Jansen, R., Embden, J.D.A. van, Gaastra, W., Schouls, L.M., 2002. Identification of genes that are associated with DNA repeats in prokaryotes. Mol. Microbiol. 43, 1565–1575.

Jiang, F., Zhou, K., Ma, L., Gressel, S., Doudna, J.A., 2015. Structural Biology. A Cas9-guide RNA complex preorganized for target DNA recognition. Science 348, 1477–1481.

Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J.A., Charpentier, E., 2012. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821.

Jinek, M., East, A., Cheng, A., Lin, S., Ma, E., Doudna, J., 2013. RNA-programmed genome editing in human cells. eLife 2, e00471.

Jinek, M., Jiang, F., Taylor, D.W., Sternberg, S.H., Kaya, E., Ma, E., Anders, C., Hauer, M., Zhou, K., Lin, S., Kaplan, M., Iavarone, A.T., Charpentier, E., Nogales, E., Doudna, J.A., 2014. Structures of Cas9 endonucleases reveal RNA-mediated conformational activation. Science 343, 1247997.

Johansson, J., Mandin, P., Renzoni, A., Chiaruttini, C., Springer, M., Cossart, P., 2002. An RNA thermosensor controls expression of virulence genes in Listeria monocytogenes. Cell 110, 551–561.

Johansson, L., Thulin, P., Low, D.E., Norrby-Teglund, A., 2010. Getting under the skin: the immunopathogenesis of Streptococcus pyogenes deep tissue infections. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 51, 58–65.

Kamerbeek, J., Schouls, L., Kolk, A., van Agterveld, M., van Soolingen, D., Kuijper, S., Bunschoten, A., Molhuizen, H., Shaw, R., Goyal, M., van Embden, J., 1997. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J. Clin. Microbiol. 35, 907–914.

Kang, S.O., Caparon, M.G., Cho, K.H., 2010. Virulence gene regulation by CvfA, a putative RNase: the CvfA-enolase complex in Streptococcus pyogenes links nutritional stress, growth-phase control, and virulence gene expression. Infect. Immun. 78, 2754–67.

Kang, S.O., Wright, J.O., Tesorero, R.A., Lee, H., Beall, B., Cho, K.H., 2012. Thermoregulation of capsule production by Streptococcus pyogenes. PloS One 7, e37367.

Kapur, V., Topouzis, S., Majesky, M.W., Li, L.L., Hamrick, M.R., Hamill, R.J., Patti, J.M., Musser, J.M., 1993. A conserved Streptococcus pyogenes extracellular cysteine protease cleaves human fibronectin and degrades vitronectin. Microb. Pathog. 15, 327–346.

Karvelis, T., Gasiunas, G., Miksys, A., Barrangou, R., Horvath, P., Siksnys, V., 2013. crRNA and tracrRNA guide Cas9-mediated DNA interference in Streptococcus thermophilus. RNA Biol. 10, 841–51.

61 References

Katz, A.R., Morens, D.M., 1992. Severe streptococcal infections in historical perspective. Clin. Infect. Dis. 14, 298–307.

Kazantsev, A.V., Pace, N.R., 2006. Bacterial RNase P: a new view of an ancient enzyme. Nat. Rev. Microbiol. 4, 729–740.

Klenk, M., Koczan, D., Guthke, R., Nakata, M., Thiesen, H.-J., Podbielski, A., Kreikemeyer, B., 2005. Global epithelial cell transcriptional responses reveal Streptococcus pyogenes Fas regulator activity association with bacterial aggressiveness. Cell. Microbiol. 7, 1237–1250.

Koonin, E.V., Makarova, K.S., 2013. CRISPR-Cas: evolution of an RNA-based adaptive immunity system in prokaryotes. RNA Biol. 10, 679–686.

Koonin, E.V., Makarova, K.S., 2009. CRISPR-Cas: an adaptive immunity system in prokaryotes. F1000 Biol. Rep. 1, 95.

Kortmann, J., Narberhaus, F., 2012. Bacterial RNA thermometers: molecular zippers and switches. Nat. Rev. Microbiol. 10, 255–265.

Kreikemeyer, B., Boyle, M.D., Buttaro, B.A., Heinemann, M., Podbielski, A., 2001. Group A streptococcal growth phase-associated virulence factor regulation by a novel operon (Fas) with homologies to two-component-type regulators requires a small RNA molecule. Mol. Microbiol. 39, 392–406.

Kreikemeyer, B., McIver, K.S., Podbielski, A., 2003. Virulence factor regulation and regulatory networks in Streptococcus pyogenes and their impact on pathogen–host interactions. Trends Microbiol. 11, 224–232.

Krüger, J., Rehmsmeier, M., 2006. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 34, W451–454.

Künne, T., Swarts, D.C., Brouns, S.J.J., 2014. Planting the seed: target recognition of short guide RNAs. Trends Microbiol. 22, 74–83.

Labrie, S.J., Samson, J.E., Moineau, S., 2010. Bacteriophage resistance mechanisms. Nat. Rev. Microbiol. 8, 317–327.

Lancefield, R.C., 1933. A serological differentiation of human and other groups of hemolytic streptococci. J. Exp. Med. 57, 571–595.

Lancefield, R.C., 1928. The antigenic complex of Streptococcus haemolyticus. J. Exp. Med. 47, 857–875.

Lasa, I., Toledo-Arana, A., Dobin, A., Villanueva, M., de los Mozos, I.R., Vergara-Irigaray, M., Segura, V., Fagegaltier, D., Penadés, J.R., Valle, J., Solano, C., Gingeras, T.R., 2011. Genome-wide antisense transcription drives mRNA processing in bacteria. Proc. Natl. Acad. Sci. U. S. A. 108, 20172–20177.

Lee, S.Y., Bailey, S.C., Apirion, D., 1978. Small stable RNAs from Escherichia coli: Evidence for the existence of new molecules and for a new ribonucleoprotein particle containing 6S RNA. J. Bacteriol. 133, 1015–1023.

Le Rhun, A., Charpentier, E., 2012. Small RNAs in streptococci. RNA Biol. 9, 414–26.

62 References

Li, M., Wang, R., Zhao, D., Xiang, H., 2014. Adaptation of the Haloarcula hispanica CRISPR- Cas system to a purified virus strictly requires a priming process. Nucleic Acids Res. 42, 2483–2492.

Lioliou, E., Sharma, C.M., Caldelari, I., Helfer, A.C., Fechter, P., Vandenesch, F., Vogel, J., Romby, P., 2012. Global regulatory functions of the Staphylococcus aureus endoribonuclease III in gene expression. PLoS Genet 8, e1002782.

Liu, M., Gui, G., Wei, B., Preston, J.F., Oakford, L., Yüksel, U., Giedroc, D.P., Romeo, T., 1997. The RNA molecule CsrB binds to the global regulatory protein CsrA and antagonizes its activity in Escherichia coli. J. Biol. Chem. 272, 17502–17510.

Liu, N., Niu, G., Xie, Z., Chen, Z., Itzek, A., Kreth, J., Gillaspy, A., Zeng, L., Burne, R., Qi, F., Merritt, J., 2015. The Streptococcus mutans irvA gene encodes a trans-acting riboregulatory mRNA. Mol. Cell 57, 179–190.

Liu, Y., Mu, C., Ying, X., Li, W., Wu, N., Dong, J., Gao, Y., Shao, N., Fan, M., Yang, G., 2011. RNAIII activates map expression by forming an RNA-RNA complex in Staphylococcus aureus. FEBS Lett. 585, 899–905.

Liu, Z., Treviño, J., Ramirez-Peña, E., Sumby, P., 2012. The small regulatory RNA FasX controls pilus expression and adherence in the human bacterial pathogen group A Streptococcus. Mol. Microbiol. 86, 140–154.

Livny, J., Brencic, A., Lory, S., Waldor, M.K., 2006. Identification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNAPredict2. Nucleic Acids Res. 34, 3484–3493.

Livny, J., Teonadi, H., Livny, M., Waldor, M.K., 2008. High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs. PLoS ONE 3, e3197.

Li, W., Ying, X., Lu, Q., Chen, L., 2012. Predicting sRNAs and their targets in bacteria. Genomics Proteomics Bioinformatics 10, 276–284.

Li, Z., Sledjeski, D.D., Kreikemeyer, B., Podbielski, A., Boyle, M.D., 1999. Identification of pel, a Streptococcus pyogenes locus that affects both surface and secreted proteins. J. Bacteriol. 181, 6019–6027.

Loh, E., Dussurget, O., Gripenland, J., Vaitkevicius, K., Tiensuu, T., Mandin, P., Repoila, F., Buchrieser, C., Cossart, P., Johansson, J., 2009. A trans-acting riboswitch controls expression of the virulence regulator PrfA in Listeria monocytogenes. Cell 139, 770– 779.

Lorenz, R., Bernhart, S.H., Höner Zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P.F., Hofacker, I.L., 2011. ViennaRNA Package 2.0. Algorithms Mol. Biol. AMB 6, 26.

Louwen, R., Horst-Kreft, D., de Boer, A.G., van der Graaf, L., de Knegt, G., Hamersma, M., Heikema, A.P., Timms, A.R., Jacobs, B.C., Wagenaar, J.A., Endtz, H.P., van der Oost, J., Wells, J.M., Nieuwenhuis, E.E.S., van Vliet, A.H.M., Willemsen, P.T.J., van Baarlen, P., van Belkum, A., 2013. A novel link between Campylobacter jejuni bacteriophage defence, virulence and Guillain-Barré syndrome. Eur. J. Clin. Microbiol. Infect. Dis. 32, 207–226.

63 References

Louwen, R., Staals, R.H.J., Endtz, H.P., Baarlen, P. van, Oost, J. van der, 2014. The role of CRISPR-Cas systems in virulence of pathogenic bacteria. Microbiol. Mol. Biol. Rev. 78, 74–88.

Louwen, R., van Baarlen, P., 2013. Are bacteriophage defence and virulence two sides of the same coin in Campylobacter jejuni? Biochem. Soc. Trans. 41, 1475–1481.

Lybecker, M., Zimmermann, B., Bilusic, I., Tukhtubaeva, N., Schroeder, R., 2014. The double- stranded transcriptome of Escherichia coli. Proc. Natl. Acad. Sci. 111, 3134–3139.

Ma, H., Naseri, A., Reyes-Gutierrez, P., Wolfe, S.A., Zhang, S., Pederson, T., 2015. Multicolor CRISPR labeling of chromosomal loci in human cells. Proc. Natl. Acad. Sci. 112, 3002–3007.

Makarova, K.S., Aravind, L., Wolf, Y.I., Koonin, E.V., 2011a. Unification of Cas protein families and a simple scenario for the origin and evolution of CRISPR-Cas systems. Biol. Direct 6.

Makarova, K.S., Grishin, N.V., Shabalina, S.A., Wolf, Y.I., Koonin, E.V., 2006. A putative RNA- interference-based immune system in prokaryotes: computational analysis of the predicted enzymatic machinery, functional analogies with eukaryotic RNAi, and hypothetical mechanisms of action. Biol. Direct 1.

Makarova, K.S., Haft, D.H., Barrangou, R., Brouns, S.J.J., Charpentier, E., Horvath, P., Moineau, S., Mojica, F.J.M., Wolf, Y.I., Yakunin, A.F., van der Oost, J., Koonin, E.V., 2011b. Evolution and classification of the CRISPR-Cas systems. Nat. Rev. Microbiol. 9, 467–477.

Makarova, K.S., Wolf, Y.I., Alkhnbashi, O.S., Costa, F., Shah, S.A., Saunders, S.J., Barrangou, R., Brouns, S.J.J., Charpentier, E., Haft, D.H., Horvath, P., Moineau, S., Mojica, F.J.M., Terns, R.M., Terns, M.P., White, M.F., Yakunin, A.F., Garrett, R.A., van der Oost, J., Backofen, R., Koonin, E.V., 2015. An updated evolutionary classification of CRISPR- Cas systems. Nat. Rev. Microbiol. advance online publication.

Makarova, K.S., Wolf, Y.I., Snir, S., Koonin, E.V., 2011c. Defense islands in bacterial and archaeal genomes and prediction of novel defense systems. J. Bacteriol. 193, 6039– 6056.

Mali, P., Aach, J., Stranges, P.B., Esvelt, K.M., Moosburner, M., Kosuri, S., Yang, L., Church, G.M., 2013a. Cas9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat. Biotechnol. 31, 833–838.

Mali, P., Yang, L., Esvelt, K.M., Aach, J., Guell, M., DiCarlo, J.E., Norville, J.E., Church, G.M., 2013b. RNA-guided human genome engineering via Cas9. Science 339, 823–826.

Mandin, P., Repoila, F., Vergassola, M., Geissmann, T., Cossart, P., 2007. Identification of new noncoding RNAs in Listeria monocytogenes and prediction of mRNA targets. Nucleic Acids Res. 35, 962–974.

Mangold, M., Siller, M., Roppenser, B., Vlaminckx, B.J.M., Penfound, T.A., Klein, R., Novak, R., Novick, R.P., Charpentier, E., 2004. Synthesis of group A streptococcal virulence factors is controlled by a regulatory RNA molecule. Mol. Microbiol. 53, 1515–1527.

64 References

Marincola, G., Schäfer, T., Behler, J., Bernhardt, J., Ohlsen, K., Goerke, C., Wolz, C., 2012. RNase Y of Staphylococcus aureus and its role in the activation of virulence genes. Mol. Microbiol. 85, 817–832.

Marraffini, L.A., Sontheimer, E.J., 2010. Self versus non-self discrimination during CRISPR RNA-directed immunity. Nature 463, 568–571.

Marraffini, L.A., Sontheimer, E.J., 2008. CRISPR interference limits horizontal gene transfer in staphylococci by targeting DNA. Science 322, 1843–1845.

Martin, J.M., Green, M., 2006. Group A Streptococcus. Semin. Pediatr. Infect. Dis. 17, 140–148.

Marx, P., Nuhn, M., Kovács, M., Hakenbeck, R., Brückner, R., 2010. Identification of genes for small non-coding RNAs that belong to the regulon of the two-component regulatory system CiaRH in Streptococcus. BMC Genomics 11, 661.

Mascher, T., Zähner, D., Merai, M., Balmelle, N., de Saizieu, A.B., Hakenbeck, R., 2003. The Streptococcus pneumoniae cia regulon: CiaR target sites and transcription profile analysis. J. Bacteriol. 185, 60–70.

Matsumura, M., Izumi, T., Matsumoto, M., Tsuji, M., Fujiwara, T., Ooshima, T., 2003. The role of glucan-binding proteins in the cariogenicity of Streptococcus mutans. Microbiol. Immunol. 47, 213–215.

Mccarty, M., 1956. Variation in the group-specific carbohydrate of group A streptococci. II. Studies on the chemical basis for serological specificity of the carbohydrates. J. Exp. Med. 104, 629–643.

McClure, R., Balasubramanian, D., Sun, Y., Bobrovskyy, M., Sumby, P., Genco, C.A., Vanderpool, C.K., Tjaden, B., 2013. Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res. 41, e140.

McDaniel, B.A.M., Grundy, F.J., Artsimovitch, I., Henkin, T.M., 2003. Transcription termination control of the S box system: direct measurement of S- adenosylmethionine by the leader RNA. Proc. Natl. Acad. Sci. U. S. A. 100, 3083– 3088.

Mellin, J.R., Cossart, P., 2015. Unexpected versatility in bacterial riboswitches. Trends Genet. 31, 150-6.

Michaux, C., Verneuil, N., Hartke, A., Giard, J.-C., 2014. Physiological roles of small RNA molecules. Microbiology 160, 1007-19.

Miyakoshi, M., Chao, Y., Vogel, J., 2015. Regulatory small RNAs from the 3’ regions of bacterial mRNAs. Curr. Opin. Microbiol. 24C, 132–139.

Mojica, F.J., Díez-Villaseñor, C., Soria, E., Juez, G., 2000. Biological significance of a family of regularly spaced repeats in the genomes of Archaea, Bacteria and mitochondria. Mol. Microbiol. 36, 244–246.

Mojica, F.J.M., Díez-Villaseñor, C., García-Martínez, J., Almendros, C., 2009. Short motif sequences determine the targets of the prokaryotic CRISPR defence system. Microbiol. Read. Engl. 155, 733–740.

65 References

Mojica, F.J.M., Díez-Villaseñor, C., García-Martínez, J., Soria, E., 2005. Intervening sequences of regularly spaced prokaryotic repeats derive from foreign genetic elements. J. Mol. Evol. 60, 174–182.

Molloy, E.M., Cotter, P.D., Hill, C., Mitchell, D.A., Ross, R.P., 2011. Streptolysin S-like virulence factors: the continuing sagA. Nat. Rev. Microbiol. 9, 670–681.

Moore, S.D., Sauer, R.T., 2007. The tmRNA system for translational surveillance and ribosome rescue. Annu. Rev. Biochem. 76, 101–124.

Mora, M., Bensi, G., Capo, S., Falugi, F., Zingaretti, C., Manetti, A.G.O., Maggi, T., Taddei, A.R., Grandi, G., Telford, J.L., 2005. Group A Streptococcus produce pilus-like structures containing protective antigens and Lancefield T antigens. Proc. Natl. Acad. Sci. U. S. A. 102, 15641–15646.

Musser, J.M., DeLeo, F.R., 2005. Toward a genome-wide systems biology analysis of host- pathogen interactions in group A Streptococcus. Am. J. Pathol. 167, 1461–1472.

Narberhaus, F., 2002. mRNA-mediated detection of environmental conditions. Arch. Microbiol. 178, 404–410.

Nawrocki, E.P., Burge, S.W., Bateman, A., Daub, J., Eberhardt, R.Y., Eddy, S.R., Floden, E.W., Gardner, P.P., Jones, T.A., Tate, J., Finn, R.D., 2015. Rfam 12.0: updates to the RNA families database. Nucleic Acids Res. 43, D130–137.

Neely, M.N., Lyon, W.R., Runft, D.L., Caparon, M., 2003. Role of RopB in growth phase expression of the SpeB cysteine protease of Streptococcus pyogenes. J. Bacteriol. 185, 5166–5174.

Nishimasu, H., Ran, F.A., Hsu, P.D., Konermann, S., Shehata, S.I., Dohmae, N., Ishitani, R., Zhang, F., Nureki, O., 2014. Crystal structure of Cas9 in complex with guide RNA and target DNA. Cell 156, 935–949.

Nobbs, A.H., Lamont, R.J., Jenkinson, H.F., 2009. Streptococcus adherence and colonization. Microbiol. Mol. Biol. Rev. 73, 407–450.

Novick, R.P., Geisinger, E., 2008. Quorum sensing in staphylococci. Annu. Rev. Genet. 42, 541– 564.

Novick, R.P., Ross, H.F., Projan, S.J., Kornblum, J., Kreiswirth, B., Moghazeh, S., 1993. Synthesis of staphylococcal virulence factors is controlled by a regulatory RNA molecule. EMBO J. 12, 3967–3975.

Nozawa, T., Furukawa, N., Aikawa, C., Watanabe, T., Haobam, B., Kurokawa, K., Maruyama, F., Nakagawa, I., 2011. CRISPR inhibition of prophage acquisition in Streptococcus pyogenes. PloS One 6, e19543.

Nudler, E., Mironov, A.S., 2004. The riboswitch control of bacterial metabolism. Trends Biochem. Sci. 29, 11–17.

Nuñez, J.K., Kranzusch, P.J., Noeske, J., Wright, A.V., Davies, C.W., Doudna, J.A., 2014. Cas1- Cas2 complex formation mediates spacer acquisition during CRISPR-Cas adaptive immunity. Nat. Struct. Mol. Biol. 21, 528–534.

66 References

Opdyke, J.A., Kang, J.-G., Storz, G., 2004. GadY, a small-RNA regulator of acid response genes in Escherichia coli. J. Bacteriol. 186, 6698–6705.

Pain, A., Ott, A., Amine, H., Rochat, T., Bouloc, P., Gautheret, D., 2015. An assessment of bacterial small RNA target prediction programs. RNA Biol. 15, 509–13.

Papenfort, K., Vanderpool, C.K., 2015. Target activation by regulatory RNAs in bacteria. FEMS Microbiol. Rev. 39, 362–378.

Patenge, N., Billion, A., Raasch, P., Normann, J., Wisniewska-Kucper, A., Retey, J., Boisguérin, V., Hartsch, T., Hain, T., Kreikemeyer, B., 2012. Identification of novel growth phase- and media-dependent small non-coding RNAs in Streptococcus pyogenes M49 using intergenic tiling arrays. BMC Genomics 13, 550.

Patenge, N., Fiedler, T., Kreikemeyer, B., 2013. Common regulators of virulence in streptococci. Curr. Top. Microbiol. Immunol. 368, 111–153.

Patterson, M.J., 1996. Streptococcus, in: Baron, S. (Ed.), Medical Microbiology. University of Texas Medical Branch at Galveston, Galveston (TX).

Pawluk, A., Bondy-Denomy, J., Cheung, V.H.W., Maxwell, K.L., Davidson, A.R., 2014. A new group of phage anti-CRISPR genes inhibits the type I-E CRISPR-Cas system of Pseudomonas aeruginosa. mBio 5, e00896.

Pennisi, E., 2013. The CRISPR craze. Science 341, 833–836.

Perez, N., Treviño, J., Liu, Z., Ho, S.C.M., Babitzke, P., Sumby, P., 2009. A genome-wide analysis of small regulatory RNAs in the human pathogen group A Streptococcus. PLoS ONE 4, e7668.

Perez-Pinera, P., Kocak, D.D., Vockley, C.M., Adler, A.F., Kabadi, A.M., Polstein, L.R., Thakore, P.I., Glass, K.A., Ousterout, D.G., Leong, K.W., Guilak, F., Crawford, G.E., Reddy, T.E., Gersbach, C.A., 2013. RNA-guided gene activation by CRISPR-Cas9-based transcription factors. Nat. Methods 10, 973–976.

Pfoh, E., Wessels, M.R., Goldmann, D., Lee, G.M., 2008. Burden and economic cost of group A streptococcal pharyngitis. Pediatrics 121, 229–234.

Pichon, C., Felden, B., 2008. Small RNA gene identification and mRNA target predictions in bacteria. Bioinforma. Oxf. Engl. 24, 2807–2813.

Plagens, A., Richter, H., Charpentier, E., Randau, L., 2015. DNA and RNA interference mechanisms by CRISPR-Cas surveillance complexes. FEMS Microbiol. Rev. 39, 442– 463.

Poritz, M.A., Bernstein, H.D., Strub, K., Zopf, D., Wilhelm, H., Walter, P., 1990. An E. coli ribonucleoprotein containing 4.5S RNA resembles mammalian signal recognition particle. Science 250, 1111–1117.

Prevention of Invasive Group A Streptococcal Infections Workshop Participants, 2002. Prevention of invasive group A streptococcal disease among household contacts of case patients and among postpartum and postsurgical patients: recommendations

67 References

from the Centers for Disease Control and Prevention. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 35, 950–959.

Price, I.R., Gaballa, A., Ding, F., Helmann, J.D., Ke, A., 2015. Mn2+-sensing mechanisms of yybP-ykoY orphan riboswitches. Mol. Cell 57, 1110–1123.

Qi, L.S., Larson, M.H., Gilbert, L.A., Doudna, J.A., Weissman, J.S., Arkin, A.P., Lim, W.A., 2013. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183.

Quinn, R.W., 1991. Did scarlet fever and rheumatic fever exist in Hippocrates’ time? Rev. Infect. Dis. 13, 1243–1244.

Raasch, P., Schmitz, U., Patenge, N., Vera, J., Kreikemeyer, B., Wolkenhauer, O., 2010. Non- coding RNA detection methods combined to improve usability, reproducibility and precision. BMC Bioinformatics 11, 491.

Ramirez-Peña, E., Treviño, J., Liu, Z., Perez, N., Sumby, P., 2010. The group A Streptococcus small regulatory RNA FasX enhances streptokinase activity by increasing the stability of the ska mRNA transcript. Mol. Microbiol. 78, 1332–1347.

Ran, F.A., Hsu, P.D., Lin, C.-Y., Gootenberg, J.S., Konermann, S., Trevino, A.E., Scott, D.A., Inoue, A., Matoba, S., Zhang, Y., Zhang, F., 2013. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154, 1380–1389.

Rath, D., Amlinger, L., Rath, A., Lundgren, M., 2015. The CRISPR-Cas immune system: Biology, mechanisms and applications. Biochimie 117, 119–128.

Regulski, E.E., Breaker, R.R., 2008. In-line probing analysis of riboswitches. Methods Mol. Biol. Clifton NJ 419, 53–67.

Rehmsmeier, M., Steffen, P., Hochsmann, M., Giegerich, R., 2004. Fast and effective prediction of microRNA/target duplexes. RNA N. Y. N 10, 1507–1517.

Repoila, F., Darfeuille, F., 2009. Small regulatory non-coding RNAs in bacteria: physiology and mechanistic aspects. Biol. Cell Auspices Eur. Cell Biol. Organ. 101, 117–131.

Riani, C., Standar, K., Srimuang, S., Lembke, C., Kreikemeyer, B., Podbielski, A., 2007. Transcriptome analyses extend understanding of Streptococcus pyogenes regulatory mechanisms and behavior toward immunomodulatory substances. Int. J. Med. Microbiol. 297, 513–523.

Ribardo, D.A., McIver, K.S., 2006. Defining the Mga regulon: Comparative transcriptome analysis reveals both direct and indirect regulation by Mga in the group A Streptococcus. Mol. Microbiol. 62, 491–508.

Roberts, S.A., Scott, J.R., 2007. RivR and the small RNA RivX: the missing links between the CovR regulatory cascade and the Mga regulon. Mol. Microbiol. 66, 1506–1522.

Rochat, T., Delumeau, O., Figueroa-Bossi, N., Noirot, P., Bossi, L., Dervyn, E., Bouloc, P., 2015. Tracking the elusive function of Bacillus subtilis Hfq. PloS One 10, e0124977.

Romeo, T., Vakulskas, C.A., Babitzke, P., 2013. Post-transcriptional regulation on a global scale: form and function of Csr/Rsm systems. Environ. Microbiol. 15, 313–324.

68 References

Sakuma, T., Nishikawa, A., Kume, S., Chayama, K., Yamamoto, T., 2014. Multiplex genome engineering in human cells using all-in-one CRISPR/Cas9 vector system. Sci. Rep. 4, 5400.

Samai, P., Pyenson, N., Jiang, W., Goldberg, G.W., Hatoum-Aslan, A., Marraffini, L.A., 2015. Co-transcriptional DNA and RNA Cleavage during Type III CRISPR-Cas Immunity. Cell 161, 1164–1174.

Sampson, T.R., Napier, B.A., Schroeder, M.R., Louwen, R., Zhao, J., Chin, C.-Y., Ratner, H.K., Llewellyn, A.C., Jones, C.L., Laroui, H., Merlin, D., Zhou, P., Endtz, H.P., Weiss, D.S., 2014. A CRISPR-Cas system enhances envelope integrity mediating antibiotic resistance and inflammasome evasion. Proc. Natl. Acad. Sci. U. S. A. 111, 11163–8.

Sampson, T.R., Saroj, S.D., Llewellyn, A.C., Tzeng, Y.-L., Weiss, D.S., 2013. A CRISPR/Cas system mediates bacterial innate immune evasion and virulence. Nature 497, 254– 257.

Sampson, T.R., Weiss, D.S., 2013. Alternative roles for CRISPR/Cas systems in bacterial pathogenesis. PLoS Pathog. 9, e1003621.

Sanderson-Smith, M., De Oliveira, D.M.P., Guglielmini, J., McMillan, D.J., Vu, T., Holien, J.K., Henningham, A., Steer, A.C., Bessen, D.E., Dale, J.B., Curtis, N., Beall, B.W., Walker, M.J., Parker, M.W., Carapetis, J.R., Van Melderen, L., Sriprakash, K.S., Smeesters, P.R., The M Protein Study Group, 2014. A systematic and functional classification of Streptococcus pyogenes that serves as a new tool for molecular typing and vaccine development. J. Infect. Dis. 210, 1325–38.

Sapranauskas, R., Gasiunas, G., Fremaux, C., Barrangou, R., Horvath, P., Siksnys, V., 2011. The Streptococcus thermophilus CRISPR/Cas system provides immunity in Escherichia coli. Nucleic Acids Res. 39, 9275–9282.

Saramago, M., Bárria, C., dos Santos, R.F., Silva, I.J., Pobre, V., Domingues, S., Andrade, J.M., Viegas, S.C., Arraiano, C.M., 2014. The role of RNases in the regulation of small RNAs. Curr. Opin. Microbiol., Cell regulation 18, 105–115.

Sayed, N., Jousselin, A., Felden, B., 2012. A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide. Nat. Struct. Mol. Biol. 19, 105–112.

Serganov, A., Nudler, E., 2013. A decade of riboswitches. Cell 152, 17–24.

Shahbabian, K., Jamalli, A., Zig, L., Putzer, H., 2009. RNase Y, a novel endoribonuclease, initiates riboswitch turnover in Bacillus subtilis. EMBO J. 28, 3523–3533.

Shah, S.A., Erdmann, S., Mojica, F.J.M., Garrett, R.A., 2013. Protospacer recognition motifs: mixed identities and functional diversity. RNA Biol. 10, 891–899.

Shannon, O., Herwald, H., Oehmcke, S., 2013. Modulation of the coagulation system during severe streptococcal disease. Curr. Top. Microbiol. Immunol. 368, 189–205.

Sharma, C.M., Vogel, J., 2009. Experimental approaches for the discovery and characterization of regulatory small RNA. Curr. Opin. Microbiol. 12, 536–546.

69 References

Shelburne, S.A., Sumby, P., Sitkiewicz, I., Granville, C., DeLeo, F.R., Musser, J.M., 2005. Central role of a bacterial two-component gene regulatory system of previously unknown function in pathogen persistence in human saliva. Proc. Natl. Acad. Sci. U. S. A. 102, 16037–16042.

Silvaggi, J.M., Perkins, J.B., Losick, R., 2005. Small untranslated RNA antitoxin in Bacillus subtilis. J. Bacteriol. 187, 6641–6650.

Sitkiewicz, I., Musser, J.M., 2006. Expression microarray and mouse virulence analysis of four conserved two-component gene regulatory systems in group A Streptococcus. Infect. Immun. 74, 1339–1351.

Smoot, L.M., Smoot, J.C., Graham, M.R., Somerville, G.A., Sturdevant, D.E., Migliaccio, C.A., Sylva, G.L., Musser, J.M., 2001. Global differential gene expression in response to growth temperature alteration in group A Streptococcus. Proc. Natl. Acad. Sci. U. S. A. 98, 10416–10421.

Sorek, R., Kunin, V., Hugenholtz, P., 2008. CRISPR -a widespread system that provides acquired resistance against phages in bacteria and archaea. Nat. Rev. Microbiol. 6, 181–186.

Sridhar, J., Narmada, S.R., Sabarinathan, R., Ou, H.-Y., Deng, Z., Sekar, K., Rafi, Z.A., Rajakumar, K., 2010. sRNAscanner: a computational tool for intergenic small RNA detection in bacterial genomes. PLoS ONE 5, e11970.

Staals, R.H.J., Zhu, Y., Taylor, D.W., Kornfeld, J.E., Sharma, K., Barendregt, A., Koehorst, J.J., Vlot, M., Neupane, N., Varossieau, K., Sakamoto, K., Suzuki, T., Dohmae, N., Yokoyama, S., Schaap, P.J., Urlaub, H., Heck, A.J.R., Nogales, E., Doudna, J.A., Shinkai, A., van der Oost, J., 2014. RNA targeting by the type III-A CRISPR-Cas Csm complex of Thermus thermophilus. Mol. Cell 56, 518–530.

Stark, B.C., Kole, R., Bowman, E.J., Altman, S., 1978. Ribonuclease P: an enzyme with an essential RNA component. Proc. Natl. Acad. Sci. U. S. A. 75, 3717–3721.

Steger, G., 2005. Secondary Structure Prediction, in: Hartmann, R.K., Bindereif, A., Schön, A., Westhof, E. (Eds.), Handbook of RNA Biochemistry. Wiley, pp. 513–535.

Sternberg, S.H., Redding, S., Jinek, M., Greene, E.C., Doudna, J.A., 2014. DNA interrogation by the CRISPR RNA-guided endonuclease Cas9. Nature 507, 62–67.

Steuten, B., Hoch, P.G., Damm, K., Schneider, S., Köhler, K., Wagner, R., Hartmann, R.K., 2014. Regulation of transcription by 6S RNAs: insights from the Escherichia coli and Bacillus subtilis model systems. RNA Biol. 11, 508–521.

Stevens, D.L., 2001. Invasive streptococcal infections. J. Infect. Chemother. Off. J. Jpn. Soc. Chemother. 7, 69–80.

Stevens, D.L., 1992. Invasive group A Streptococcus infections. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 14, 2–11.

Stinson, M.W., McLaughlin, R., Choi, S.H., Juarez, Z.E., Barnard, J., 1998. Streptococcal histone-like protein: primary structure of HlpA and protein binding to lipoteichoic acid and epithelial cells. Infect. Immun. 66, 259–265.

70 References

Storz, G., Opdyke, J.A., Zhang, A., 2004. Controlling mRNA stability and translation with small, noncoding RNAs. Curr. Opin. Microbiol. 7, 140–144.

Stougaard, P., Molin, S., Nordström, K., 1981. RNAs involved in copy-number control and incompatibility of plasmid R1. Proc. Natl. Acad. Sci. U. S. A. 78, 6008–6012.

Sumby, P., Whitney, A.R., Graviss, E.A., DeLeo, F.R., Musser, J.M., 2006. Genome-wide analysis of group A streptococci reveals a mutation that modulates global phenotype and disease specificity. PLoS Pathog. 2, e5.

Swarts, D.C., Mosterd, C., van Passel, M.W.J., Brouns, S.J.J., 2012. CRISPR interference directs strand specific spacer acquisition. PloS One 7, e35888.

Szczelkun, M.D., Tikhomirova, M.S., Sinkunas, T., Gasiunas, G., Karvelis, T., Pschera, P., Siksnys, V., Seidel, R., 2014. Direct observation of R-loop formation by single RNA- guided Cas9 and Cascade effector complexes. Proc. Natl. Acad. Sci. 111, 9798–9803.

Tafer, H., Hofacker, I.L., 2008. RNAplex: a fast tool for RNA-RNA interaction search. Bioinforma. Oxf. Engl. 24, 2657–2663.

Tamulaitis, G., Kazlauskiene, M., Manakova, E., Venclovas, Č., Nwokeoji, A.O., Dickman, M.J., Horvath, P., Siksnys, V., 2014. Programmable RNA shredding by the type III-A CRISPR-Cas system of Streptococcus thermophilus. Mol. Cell 56, 506–517.

Tart, A.H., Walker, M.J., Musser, J.M., 2007. New understanding of the group A Streptococcus pathogenesis cycle. Trends Microbiol. 15, 318–325.

Terns, M.P., Terns, R.M., 2011. CRISPR-based adaptive immune systems. Curr. Opin. Microbiol. 14, 321–327.

Tesorero, R.A., Yu, N., Wright, J.O., Svencionis, J.P., Cheng, Q., Kim, J.-H., Cho, K.H., 2013. Novel Regulatory Small RNAs in Streptococcus pyogenes. PLoS ONE 8, e64021.

Tjaden, B., Goodwin, S.S., Opdyke, J.A., Guillier, M., Fu, D.X., Gottesman, S., Storz, G., 2006. Target prediction for small, noncoding RNAs in bacteria. Nucleic Acids Res. 34, 2791– 2802.

Tomizawa, J., Itoh, T., 1981. Plasmid ColE1 incompatibility determined by interaction of RNA I with primer transcript. Proc. Natl. Acad. Sci. U. S. A. 78, 6096–6100.

Treviño, J., Liu, Z., Cao, T.N., Ramirez-Peña, E., Sumby, P., 2013. RivR is a negative regulator of virulence factor expression in group A Streptococcus. Infect. Immun. 81, 364–372.

Tsatsaronis, J.A., Walker, M.J., Sanderson-Smith, M.L., 2014. Host responses to Group A Streptococcus: Cell death and inflammation. PLoS Pathog. 10, e1004266.

Turner, C.E., Abbott, J., Lamagni, T., Holden, M.T.G., David, S., Jones, M.D., Game, L., Efstratiou, A., Sriskandan, S., 2015. Emergence of a new highly successful acapsular group A Streptococcus clade of genotype emm89 in the united kingdom. mBio 6, e00622.

Valentin-Hansen, P., Eriksen, M., Udesen, C., 2004. The bacterial Sm-like protein Hfq: a key player in RNA transactions. Mol. Microbiol. 51, 1525–1533.

71 References

van der Oost, J., Westra, E.R., Jackson, R.N., Wiedenheft, B., 2014. Unravelling the structural and mechanistic basis of CRISPR-Cas systems. Nat. Rev. Microbiol. 12, 479–492.

Viegas, S.C., Arraiano, C.M., 2008. Regulating the regulators: How ribonucleases dictate the rules in the control of small non-coding RNAs. RNA Biol. 5, 230–243.

Vogel, J., Bartels, V., Tang, T.H., Churakov, G., Slagter-Jäger, J.G., Hüttenhofer, A., Wagner, E.G.H., 2003. RNomics in Escherichia coli detects new sRNA species and indicates parallel transcriptional output in bacteria. Nucleic Acids Res. 31, 6435–6443.

Vogel, J., Gerhart, E., Wagner, H., 2005. Approaches to identify novel non-messenger RNAs in bacteria and to investigate their biological functions: RNA mining, in: Hartmann, R.K., Bindereif, A., Schön, A., Westhof, E. (Eds.), Handbook of RNA Biochemistry. Wiley, pp. 595–613.

Vogel, J., Luisi, B.F., 2011. Hfq and its constellation of RNA. Nat. Rev. Microbiol. 9, 578–589.

Vogel, J., Sharma, C.M., 2005. How to find small non-coding RNAs in bacteria. Biol. Chem. 386, 1219–1238.

Vogel, J., Wagner, E.G.H., 2007. Target identification of small noncoding RNAs in bacteria. Curr. Opin. Microbiol. 10, 262–270. von Pawel-Rammingen, U., Johansson, B.P., Björck, L., 2002. IdeS, a novel streptococcal cysteine proteinase with unique specificity for immunoglobulin G. EMBO J. 21, 1607– 1615.

Voyich, J.M., Sturdevant, D.E., Braughton, K.R., Kobayashi, S.D., Lei, B., Virtaneva, K., Dorward, D.W., Musser, J.M., DeLeo, F.R., 2003. Genome-wide protective response used by group A Streptococcus to evade destruction by human polymorphonuclear leukocytes. Proc. Natl. Acad. Sci. U. S. A. 100, 1996–2001.

Wagner, E.G.H., Altuvia, S., Romby, P., 2002. Antisense RNAs in bacteria and their genetic elements. Adv. Genet. 46, 361–398.

Wagner, E.G., Simons, R.W., 1994. Antisense RNA control in bacteria, phages, and plasmids. Annu. Rev. Microbiol. 48, 713–742.

Waldminghaus, T., Heidrich, N., Brantl, S., Narberhaus, F., 2007. FourU: a novel type of RNA thermometer in Salmonella. Mol. Microbiol. 65, 413–424.

Walker, M.J., Barnett, T.C., McArthur, J.D., Cole, J.N., Gillen, C.M., Henningham, A., Sriprakash, K.S., Sanderson-Smith, M.L., Nizet, V., 2014. Disease manifestations and pathogenic mechanisms of Group A Streptococcus. Clin. Microbiol. Rev. 27, 264–301.

Wallace, R.A., Black, W.P., Yang, X., Yang, Z., 2014. A CRISPR with roles in Myxococcus xanthus development and exopolysaccharide production. J. Bacteriol. 196, 4036– 4043.

Wassarman, K.M., 2007. 6S RNA: a regulator of transcription. Mol. Microbiol. 65, 1425–1431.

Wassarman, K.M., Saecker, R.M., 2006. Synthesis-mediated release of a small RNA inhibitor of RNA polymerase. Science 314, 1601–1603.

72 References

Wassarman, K.M., Storz, G., 2000. 6S RNA regulates E. coli RNA polymerase activity. Cell 101, 613–623.

Weaver, K.E., 2007. Emerging plasmid-encoded antisense RNA regulated systems. Curr. Opin. Microbiol. 10, 110–116.

Weilbacher, T., Suzuki, K., Dubey, A.K., Wang, X., Gudapaty, S., Morozov, I., Baker, C.S., Georgellis, D., Babitzke, P., Romeo, T., 2003. A novel sRNA component of the carbon storage regulatory system of Escherichia coli. Mol. Microbiol. 48, 657–670.

Weiss, D., Sampson, T., 2014. CRISPR-Cas systems: new players in gene regulation and bacterial physiology. Front. Cell. Infect. Microbiol. 4, 37.

Wei, Y., Chesne, M.T., Terns, R.M., Terns, M.P., 2015a. Sequences spanning the leader-repeat junction mediate CRISPR adaptation to phage in Streptococcus thermophilus. Nucleic Acids Res. 43, 1749–1758.

Wei, Y., Terns, R.M., Terns, M.P., 2015b. Cas9 function and host genome sampling in Type II-A CRISPR–Cas adaptation. Genes Dev. 29, 356–361.

Wessels, M.R., 1997. Biology of streptococcal capsular polysaccharides. Soc. Appl. Bacteriol. Symp. Ser. 26, 20S–31S.

Westermann, A.J., Gorski, S.A., Vogel, J., 2012. Dual RNA-seq of pathogen and host. Nat. Rev. Microbiol. 10, 618–630.

Westra, E.R., Buckling, A., Fineran, P.C., 2014. CRISPR-Cas systems: beyond adaptive immunity. Nat. Rev. Microbiol. 12, 317–26.

Westra, E.R., Semenova, E., Datsenko, K.A., Jackson, R.N., Wiedenheft, B., Severinov, K., Brouns, S.J.J., 2013. Type I-E CRISPR-cas systems discriminate target from non- target DNA through base pairing-independent PAM recognition. PLoS Genet. 9, e1003742.

Westra, E.R., van Erp, P.B.G., Künne, T., Wong, S.P., Staals, R.H.J., Seegers, C.L.C., Bollen, S., Jore, M.M., Semenova, E., Severinov, K., de Vos, W.M., Dame, R.T., de Vries, R., Brouns, S.J.J., van der Oost, J., 2012. CRISPR immunity relies on the consecutive binding and degradation of negatively supercoiled invader DNA by Cascade and Cas3. Mol. Cell 46, 595–605.

WHO, 2005. The current evidence for the burden of group A streptococcal diseases. WHO. URL http://www.who.int/maternal_child_adolescent/documents/fch_cah_05_07/en/ (10.5.15).

Wiedenheft, B., Sternberg, S.H., Doudna, J.A., 2012. RNA-guided genetic silencing systems in bacteria and archaea. Nature 482, 331–338.

Winkler, W.C., 2005. Riboswitches and the role of noncoding RNAs in bacterial metabolic control. Curr. Opin. Chem. Biol. 9, 594–602.

Winkler, W.C., Breaker, R.R., 2005. Regulation of bacterial gene expression by riboswitches. Annu. Rev. Microbiol. 59, 487–517.

73 References

Wright, P.R., Richter, A.S., Papenfort, K., Mann, M., Vogel, J., Hess, W.R., Backofen, R., Georg, J., 2013. Comparative genomics boosts target prediction for bacterial small RNAs. Proc. Natl. Acad. Sci. U. S. A. 110, E3487–3496.

Yao, Z., Barrick, J., Weinberg, Z., Neph, S., Breaker, R., Tompa, M., Ruzzo, W.L., 2007. A computational pipeline for high- throughput discovery of cis-regulatory noncoding RNA in prokaryotes. PLoS Comput. Biol. 3, e126.

Ying, X., Cao, Y., Wu, J., Liu, Q., Cha, L., Li, W., 2011. sTarPicker: a method for efficient prediction of bacterial sRNA targets based on a two-step model for hybridization. PloS One 6, e22705.

Yosef, I., Goren, M.G., Qimron, U., 2012. Proteins and DNA elements essential for the CRISPR adaptation process in Escherichia coli. Nucleic Acids Res. 40, 5569–5576.

Zhang, A., Wassarman, K.M., Rosenow, C., Tjaden, B.C., Storz, G., Gottesman, S., 2003. Global analysis of small RNA and mRNA targets of Hfq. Mol. Microbiol. 50, 1111–1124.

Zhao, Y., Li, H., Hou, Y., Cha, L., Cao, Y., Wang, L., Ying, X., Li, W., 2008. Construction of two mathematical models for prediction of bacterial sRNA targets. Biochem. Biophys. Res. Commun. 372, 346–350.

Zuker, M., 2003. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31, 3406–3415.

74 Appendix: Papers I-III

Appendix: Papers I-III