Literature DB >> 25859258

Cis-encoded non-coding antisense RNAs in streptococci and other low GC Gram (+) bacterial pathogens.

Kyu Hong Cho1, Jeong-Ho Kim2.   

Abstract

Due to recent advances of bioinformatics and high throughput sequencing technology, discovery of regulatory non-coding RNAs in bacteria has been increased to a great extent. Based on this bandwagon, many studies searching for trans-acting small non-coding RNAs in streptococci have been performed intensively, especially in the important human pathogen, group A and B streptococci. However, studies for cis-encoded non-coding antisense RNAs in streptococci have been scarce. A recent study shows antisense RNAs are involved in virulence gene regulation in group B streptococcus, S. agalactiae. This suggests antisense RNAs could have important roles in the pathogenesis of streptococcal pathogens. In this review, we describe recent discoveries of chromosomal cis-encoded antisense RNAs in streptococcal pathogens and other low GC Gram (+) bacteria to provide a guide for future studies.

Entities:  

Keywords:  Gram (+) pathogens; antisense RNAs; non-coding RNAs; regulatory RNAs; streptococci

Year:  2015        PMID: 25859258      PMCID: PMC4374534          DOI: 10.3389/fgene.2015.00110

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


Introduction

Non-coding regulatory RNAs exist in all three kingdoms and confer another layer of regulation mechanism for gene expression. Generally, the regulation by non-coding RNAs occurs at a post-transcriptional level, so their regulation would be fast and effective. Bacteria produce three general groups of non-coding regulatory RNAs: (i) cis-acting 5′ element non-coding RNAs, (ii) trans-acting small non-coding RNAs, and (iii) cis-encoded antisense RNAs. A cis-acting 5′ non-coding RNA is usually attached to the 5′ side of an mRNA whose expression is regulated by the non-coding RNA. A structural change of the non-coding RNA occurs by binding to small metabolites (riboswitches), or by change of temperature (thermoregulators) or pH (pH sensors). The structural change influences transcription or translation of the downstream gene or genes in an operon. Trans-acting small non-coding RNAs are usually encoded in intergenic regions on the chromosome and control translation or degradation of their target mRNAs. Generally, each trans-acting non-coding RNA has multiple target mRNAs and binds near the ribosomal binding site of the target mRNAs. A cis-acting antisense RNA (antisense RNA) is expressed as a complementary sequence of an mRNA that becomes the sole target RNA. Previously, these non-coding RNAs had been discovered by computational predictions coupled with expression studies, microarrays, sequencing of small sized cDNA libraries, and high throughput sequencing approaches. Due to recent technological advances of tiling microarray, RNA deep sequencing, and bioinformatics, the search for non-coding regulatory RNAs on a genome-wide scale has been actively performed. As a result, the functions and regulatory mechanisms of discovered non-coding regulatory RNAs are widely studied. However, because of technical difficulties to distinguish the source of expressed RNAs between the two DNA strands, the search for antisense RNAs using high throughput methods has been retarded, compared to the search for trans-acting small RNAs. This makes antisense RNAs the least studied non-coding RNAs in streptococci to date. Currently no systematic search for antisense RNAs has been done in S. pyogenes, and only one search has been performed in S. agalactiae. Considerable antisense transcription has been discovered in both eukaryotes and prokaryotes. The number of cis-encoded antisense RNAs in bacteria was once considered much smaller than that of eukaryotes due to the compact organization of protein-coding genes in the chromosome. However, recent studies indicate bacteria also produce a number of cis-encoded antisense RNAs. Bacterial cis-encoded antisense RNAs were discovered several decades ago, and most antisense RNAs were expressed from mobile genetic elements such as plasmids, phages, and transposons (Brantl, 2007). Since antisense RNAs expressed from bacterial chromosomes had not been discovered, it was thought that antisense RNAs were not generally used to control chromosomal gene expression in bacteria. However, during recent decades, many RNAs antisense to chromosomal genes have been discovered in bacteria. The other kingdom of prokaryotic microorganisms, archaea, also express cis-encoded antisense transcripts. An archaeal organism, Sulfolobus solfataricus P2, expresses about 310 non-coding RNAs and among these non-coding RNAs, almost 60% (185 non-coding RNAs) are cis-encoded antisense RNAs (Wurtzel et al., 2010). Although many antisense RNAs have been discovered in prokaryotes recently, their functions and regulation mechanisms are largely not studied. Most cis-encoded antisense RNAs are complementary to a small portion of an open reading frame (ORF) and often the complementary portion includes the ribosome-binding site (Figure 1A). These small antisense RNAs are widely expressed on the chromosomes, plasmids, and transposons. However, some antisense RNAs are longer than typical ones and even reach several kilobases. Long antisense RNAs can be complementary to an entire gene or genes (Figure 1B). Among long antisense RNAs, some contains the sequence of a neighboring ORF or ORFs on their 5′ or 3′ side (Figure 1C). These type of antisense RNAs, which were named excludons (Sesto et al., 2013), have been discovered only on the chromosomes of several bacteria such as Listeria monocytogenes (Toledo-Arana et al., 2009), Bacillus subtilis (Rasmussen et al., 2009), a cyanobacterium Synechocystis sp. (Stazic et al., 2011), and Staphylococcus aureus (Beaume et al., 2010). However, as more bacteria are searched for antisense RNAs, more excludons are expected to be discovered.
Figure 1

Examples of antisense RNA types illustrated with a three-gene operon. The solid lines depict double stranded DNA with genes (arrows). Each dotted line represents expressed RNA matching with the sequence of each DNA strand. The top dotted lines are mRNAs and the bottom dotted lines are cis-encoded antisense RNAs. (A) Small antisense RNAs complementary to the sequence of ribosome-binding site (RBS), in the middle of a gene, or of an intergenic region. (B) Long antisense RNAs complementary to an entire gene or an operon. (C) Excludons containing genes at its 5′ or 3′ side.

Examples of antisense RNA types illustrated with a three-gene operon. The solid lines depict double stranded DNA with genes (arrows). Each dotted line represents expressed RNA matching with the sequence of each DNA strand. The top dotted lines are mRNAs and the bottom dotted lines are cis-encoded antisense RNAs. (A) Small antisense RNAs complementary to the sequence of ribosome-binding site (RBS), in the middle of a gene, or of an intergenic region. (B) Long antisense RNAs complementary to an entire gene or an operon. (C) Excludons containing genes at its 5′ or 3′ side.

Cis-encoded antisense RNAs in streptococci and other low GC gram (+) bacteria

S. agalactiae (Group B Streptococcus, GBS), which is an opportunistic pathogen and causative agent of bacterial sepsis, pneumonia, and meningitis in newborns, employs antisense RNAs to control virulence factors (Pichon et al., 2012). In the study of Pichon et al. they used an in silico method to find small non-coding RNAs and predicted the existence of 63 antisense RNAs (Table 1). They validated the existence of these antisense RNAs by verifying three of them through northern blotting (Table 2). The three RNAs, which have the sizes of 123 bps, 239 bps, and 243 bps, are fully or partially antisense to coding sequences (CDSs) involved in the pathogenicity of S. agalactiae. When they overexpressed two of these antisense RNAs using a multi-copy plasmid, one reduced the expression of the adjacent target gene but the other increased the expression of its target gene. This shows that antisense RNAs can carry out both negative and positive regulation.
Table 1

High throughput searches for chromosomal .

BacteriumTotal number of antisense RNAs discovered or predictedSearch method [references]
Bacillus subtilis143High density tiling microarray covering both strands (Rasmussen et al., 2009) Differential RNA-seq (Irnov et al., 2010)
Listeria monocytogenes10Tiling microarray covering both strands (Toledo-Arana et al., 2009)
Staphylococcus aureus113Sequencing cDNA libraries and northern blotting (Abu-Qatouseh et al., 2010) Illuminar RNA-seq with orientation protocol (Beaume et al., 2010)
Streptococcus agalactiae63In silico prediction (Pichon et al., 2012)
Table 2

Chromosomal .

BacteriumName of antisense RNAGene (protein) antisense toSize (bases)Discovered method*Validation methodReferences
Bacillus subtilisncr2706ywqA47RNA-seqIrnov et al., 2010
ncr1430bglP70
ncr1687wprA24
ncr1265yutK218
ncr2153comER101
ncr1186nadB17
ncr1006yoeA219
ncr1799mutS25
ncr2058yqzJ110
ncr2160sda259
ncr1351mbl227
ncr1565yddR61
ncr2885yyaQ106
ncr1546mtlD50
ncr507yfhD30
ncr2410ytoA249
Bacillus subtilisshd1yaaC681Tiling microarrayRasmussen et al., 2009
shd2dck681
shd3yabD yabE813
shd4yabE1121
shd5coaX hslO yacD2816
shd6lysS681
shd7ybaC1187
shd8ybbB461
shd9ybfG ybfH3233
shd10nagBB1077
shd11ycbR263
shd12yceJ1319
shd13nasE nasD813
shd14yckC yckD bglC2675
shd15tlpC1759
shd16hxlB hxlA1452
shd17hxlR417
shd18ycxD461
shd19yczM yczN439
shd20kipR lipC836
shd21ydbM791
shd22ydbO527
shd23ndoA rsbRA1099
shd24ydcO241
shd25vmlR637
shd26ydiF285
shd27ydzW ydzW ydzW ydzW527
shd28ydjE373
shd29yebD yebE yebG1077
shd30yerA351
shd31yeeD yezA791
shd32yeeK263
shd33lplD yetF1583
shd34yfmG461
shd35yfhK yfhL yfhM1583
shd36ygaB417
shd37ygaJ636
shd38ygaK967
shd39nhaC197
shd40yhfA1495
shd41yisI483
shd42yisL593
shd43yisQ769
shd44yitZ703
shd45yjzC329
shd46yjaZ857
shd47yjbB1209
shd48yjbE835
shd49yjcK yjcL1915
shd50ykuT923
shd51ylaK307
shd52ctaA681
shd53yloB659
shd54ymfJ373
shd55yncF593
shd56yneE615
shd57cotM sspP sspO879
shd58yogA615
shd59yoaE yoaF1252
shd60yoqZ yoqY637
shd61yonT417
shd62blyA bhlA bhlB1517
shd63yokD549
shd64dinF1187
shd65yppC373
shd66ponA351
shd67birA197
shd68yqxK483
shd69yqjF901
shd70yqjD373
shd71yqjB yqjA1504
shd72yqiG696
shd73yqhR725
shd74yqzG241
shd75yqhB637
shd76yqgE1451
shd77sigA967
shd78dgkA241
shd79comEC527
shd80yqdB219
shd81ncr58/bsrH549
shd82yrrI483
shd83leuA ilvC1693
shd84ytoI725
shd85ytrP637
shd86ytoP461
shd87ytlD769
shd88ythA ythB ytzL1715
shd89yugH1055
shd90yufK659
shd91mrpE mrpF mrpG901
shd92yueB1847
shd93yukB769
shd94yutK681
shd95yuzB593
shd96yutH527
shd97yurQ yurR1033
shd98yuzK yurZ metN1099
shd99yusW615
shd100cssS769
shd101nhaK571
shd102opuBD opuBC opuBB1957
shd103yvaV373
shd104sdpI sdpR842
shd105araE879
shd106yvfU285
shd107cwlO395
shd108yvjA prfB1209
shd109comFC comFB comFA yviA3516
shd110tuaH373
shd111tuaA329
shd112ggaA1319
shd113spo0F593
shd114narK461
shd115ywfM ywfL cysL2903
shd116pta505
shd117bacF593
shd118yxlH681
shd119cimH yxkI yxzE2661
shd120yxkA725
shd121yxjA637
shd122yxxF1055
shd123yxeA yxdM yxdL2309
shd124yybT yybS1429
shd125yybI615
shd126yyaM461
shd127jag549
Listeria monocytogenesSRPPartially antisense to lmo2711332Tiling microarrayToledo-Arana et al., 2009
rli23lmo0172 (Transposase)97
rli25lmo0330 (Transposase)102
rli29Antisense to the 5′UTR of lmo0471193
rli30lmo0506115
rli35lmo0828 (Transposase)102
rli45Antisense to rli46 (small non-coding RNA)77
rli46Antisense to rli45294
Anti2095-8 RNA1 RNA2lmo2095 lmo2095-8255 2149
Anti2325-7 RNA1 RNA2lmo2325 lmo2325-7264 995
Anti2394-5 RNA1 RNA2lmo2394 lmo2394-5216 693
Staphylococcus aureusSau-13SA2421110; 140; 210cDNA library SequencingNorthern blotAbu-Qatouseh et al., 2010
Sau-31SA2021210
Sau-50hu (DNA-binding prtein II)210
Sau-53argC200
Sau-59SA0931130
Sau-66SA0671210
Staphylococcus aureusTeg5asSA0024330RNA-seqBeaume et al., 2010
Teg6asSA0025405
Teg7asSA0027 and SA002636
Teg8asSAS002 and SA002884
Teg10asSA004442
Teg14asSA0062143
Teg15asSA0097 and SA009872
Teg16asSA0101 and SA010081
Teg17ascapM108
Teg18asSA0306864
Teg19asSA0412 and SA04132475
Teg20asSA06201008
Teg21asSA182563
Teg22asSA183063
Teg23asnrgA36
Teg25asSA2200117
Teg26asSA221863
Teg27asSA222490
Teg28asSA244036
Teg36asssaA448
Teg37asSA0970108
Teg38asSA035150
Teg10asplSAP03136
Teg39asSA0031210
Teg40asSA0751299
Teg41asSAS024141
Streptococcus agalactiaeSQ18gbs0031 (Surface exposed protein123In Silico predictionNorthern blotPichon et al., 2012
SQ407lmb (Laminin binding protein)239
SQ485gbs1558/1559 (putative ABC transporter)242
Streptococcus mutanssrSmFst-Sm (Fst-like toxin)70PSI-BLAST and TBLASTNorthern blotKoyanagi and Levesque, 2013

Putative antisense RNAs predicted by in silico or cDNA library sequencing without any validation are not listed in this table.

High throughput searches for chromosomal . Chromosomal . Putative antisense RNAs predicted by in silico or cDNA library sequencing without any validation are not listed in this table. On the other hand, the discovery of antisense RNAs in another important streptococcal pathogen Streptococcus pyogenes (Group A Streptococcus, GAS) has not been reported. Many studies have been done to search for trans-acting small non-coding RNAs, but no systematic study has been done so far to search for antisense RNAs. Thus, it is not known if antisense RNAs in this pathogen have an important role in controlling gene expression and/or virulence. An RNA-based toxin-antitoxin system was discovered on the chromosome of Streptococcus mutans, an oral streptococcal pathogen (Table 2) (Koyanagi and Levesque, 2013). This is an unusual case because most toxin-antitoxin systems in bacteria are encoded in plasmids. The S. mutans antitoxin is an antisense RNA (srSm) converging toward the end of the gene of Fst-like toxin (Fst-Sm), so the expression of the antitoxin antisense RNA inhibits the production of Fst-like toxin. High throughput searches for non-coding regulatory RNAs in Bacillus subtilis have been performed to gain more knowledge on the regulation of gene expression by non-coding RNAs in this low GC Gram (+) model organism (Rasmussen et al., 2009; Irnov et al., 2010). In these searches, Rasmussen et al. discovered 127 antisense RNAs through a high density tiling array (Rasmussen et al., 2009), and then Irnov et al. discovered 16 novel antisense RNAs using a differential RNA-seq analysis (Table 1) (Irnov et al., 2010). The results from these studies reveal that target genes of antisense RNAs are involved in stress response, sporulation, and expression of SigA, the principal sigma factor during vegetative growth (Table 2). Therefore, antisense RNAs in B. subtilis appear to influence a variety of important regulations to adapt diverse environmental conditions. Staphylococcus aureus is a remarkable opportunistic pathogen causing a broad spectrum of diseases like S. pyogenes, which range from superficial skin diseases to fatal systemic infections including sepsis, pneumonia, and bone infections. Since the emergence and spread of drug-resistant and community-acquired strains, S. aureus infections have drawn great attention. The most intensively studied non-coding RNA in S. aureus is RNAIII that is a regulatory RNA controlling many virulence factors as the effector of the agr quorum sensing system. Even though RNAIII controls translation and degradation of target mRNAs with an antisense mechanism, its action is trans, not cis, thus RNAIII is not discussed here because of the narrow scope of this review (for a review on RNAIII, see Novick and Geisinger, 2008). Previously, several studies have been performed to discover non-coding regulatory RNAs in S. aureus through computational methods, sequencing of small sized cDNAs, and high throughput strand-specific RNA sequencing technology (Table 1) (Pichon and Felden, 2005; Geissmann et al., 2009; Abu-Qatouseh et al., 2010; Beaume et al., 2010; Bohn et al., 2010). From these studies, about 100 cis-encoded antisense RNAs have been discovered, some of which were experimentally detected by northern blotting, Rapid Amplification of cDNA Ends (RACE) mapping, or reverse transcriptase quantitative PCR (RT-qPCR) (Table 2). Many of these antisense RNAs are expressed from pathogenicity islands and mobile elements such as plasmids and transposons. Interestingly, existence of some antisense RNAs was unique in a strain, suggesting that gene regulation by cis-encoded antisense RNA could be strain specific. Long antisense RNAs are also present in S. aureus. The antisense RNA complementary to the gene encoding a secretory antigen (SA0620) is bigger than 1 kb (Beaume et al., 2010). In the study by Beaume et al., 10 cis-encoded antisense RNAs out of total discovered 35 were expressed in pathogenicity islands or in the chromosome mec cassette, which is a mobile genetic element conferring methicillin resistance (Beaume et al., 2010). This indicates that antisense RNAs could play a key role in S. aureus infections. These antisense RNAs are particularly abundant in genes involved in cell wall and cell envelope biogenesis and in replication, recombination, and repair. Interestingly, two of these antisense RNAs are complementary to the small non-coding RNAs, SprA1, and AprG. These two antisense RNA-small non-coding RNA pairs are predicted to form type I toxin-antitoxin modules. The study of S. aureus small colony variants identified 78 antisense RNA candidates (Abu-Qatouseh et al., 2010). Some antisense RNAs in S. aureus are involved in the differential expression of genes in the same operon. An example is antisense RNAs complementary to a part of each capF and capM transcript of the same capsular polysaccharide synthesis operon (cap operon) (Abu-Qatouseh et al., 2010; Beaume et al., 2010). Even though they are expressed as one mRNA, the two genes are differentially translated by the antisense RNAs. Listeria monocytogenes is a Gram (+) pathogenic bacterium causing food-borne infection, listeriosis, which can lead to meningitis in newborns. This pathogen has a well-defined virulence mechanism to inhibit phagolysosome formation and proliferate inside host cells, so has been extensively used as a model organism for the study of pathogen-host interaction (Hamon et al., 2006). Previously, the Cossart group examined the transcription profile of this pathogen using tiling microarrays that covered both strands of the chromosome, and discovered many non-coding RNAs including 10 cis-encoded antisense RNAs (Table 1). Three of them were already classified as small RNAs and seven were newly discovered (Toledo-Arana et al., 2009). Most cis-encoded antisense RNAs cover a small portion of an open reading frame (ORF), but three antisense RNAs are large enough to cover more than one ORF. Interestingly, all of these long antisense RNAs are expressed with a shorter antisense RNA. Both shorter and longer antisense RNAs are expressed at the same start site but they have different termination sites. The importance of these two different size antisense transcripts has not been determined yet.

Regulation mechanisms by Cis-encoded antisense RNAs

Antisense RNAs can control gene expression by binding to their cognate sense RNAs. The binding occurs at the 5′ end, 3′ end, or in the middle of mRNAs depending on the location they are expressed (Figure 1A). Also, long antisense RNAs can overlap an entire mRNA encoding a protein or proteins (Figure 1B). The different binding locations confer different control mechanisms. Based on their binding locations on sense RNAs, antisense RNAs may act in three ways: (i) transcription terminators in the mechanism of transcription attenuation or transcription interference, (ii) potential inhibitors of translation initiation, or (iii) modulators of mRNA degradation. Antisense RNAs influence gene expression at the transcriptional or post-transcriptional level. Transcription interference and transcription attenuation occur at the transcriptional levels, and translation inhibition and mRNA degradation occur at post-transcriptional levels. The degree of control by antisense RNAs can be achieved by their differential expression level at different conditions. The expression ratio between a sense RNA and the antisense RNA will influence the expression of the sense gene. In transcription interference, two promoters of an antisense RNA and its target sense RNA present very close in cis-position and their transcriptions occur in the convergent direction, and then the transcription rate from one promoter becomes suppressed by the other promoter (Callen et al., 2004). In this case, the transcription of the weaker promoter seems suppressed more. Another regulation mechanism at the transcriptional level by antisense RNAs is transcription attenuation. In transcription attenuation, an antisense RNA binds to the region in front of the Shine-Dalgano sequence of the target mRNA, and this binding induces the formation of transcription terminator structure. Hence, when the antisense RNA binds near or at the 5′ end of the cognate sense RNA, the transcription of the sense RNA is terminated (Brantl, 2002; Stork et al., 2007). In this regulation, if an antisense RNA binds an intergenic region in a polycistronic mRNA, then it can create differential gene expression between the genes located upstream and downstream of the intergenic region, and the upstream gene is more expressed than the downstream gene (Stork et al., 2007). A common post-transcriptional level regulation by antisense RNAs is modulating translation resulting in translation inhibition or activation. In translation inhibition, antisense RNAs bind directly to the Shine-Dalgano sequence (SD sequence) of mRNAs, and inhibit ribosome-binding (Greenfield et al., 2001; Hernandez et al., 2006; Kawano et al., 2007). This inhibition of translation might increase or decrease the degradation of mRNAs by ribonuclease. In translation activation, an antisense RNA bind near the SD sequence whose access by ribosomes are blocked by a preformed stem and loop structure, then the binding of the antisense RNA frees the SD sequence (Asano et al., 1998). As mentioned, mRNA degradation can be influenced by a bound antisense RNA. The pairs of antisense RNA–target mRNA can be substrates of RNase III, which is a double strand specific endoribonuclease. RNase III is conserved in all the three kingdoms. A previous study of S. aureus showed that the deletion of RNase III increased the amount of antisense transcripts, indicating that target mRNAs bound by antisense RNAs are degraded by RNase III in vivo (Lasa et al., 2011). Deep sequencing analysis in the same study showed that RNase III generates 22 nt long RNA fragments with 2 nucleotide 3′ overhang from the pairs of sense-antisense transcripts. Surprisingly, 75% of mRNAs are processed by RNase III, implying that antisense regulation occurs more extensively than previously thought. Studies on other bacteria also indicate that antisense transcription occurs extensively throughout the chromosome (For a review, see Georg and Hess, 2011). Another RNase shown to be involved in degradation of sense-antisense RNA pairs is RNase E, an endoribonuclease degrading 5′ monophosphorylated mRNAs. RNase E degrades mgtC mRNA in Salmonella enterica with an unknown mechanism when the sense RNA is bound by the antisense RNA, AmgR (Lee and Groisman, 2010). RNase E is a member of the RNA degradosome in Gram (−) bacteria, a multicomponent complex that also includes an RNA helicase, RhlB, a glycolytic enzyme, enolase, and the exoribonuclease polynucleotide phosphorylase (PNPase) (Carpousis, 2007). The main function of the RNA degradosome is known to control mRNA turnover. Most Gram (+) bacteria including streptococci, bacilli, and staphylococci do not possess an RNase E homolog. However, these bacteria possess the RNA degradosome. The Gram (+) RNA degradosome contains similar kinds of components but more members, compared to the Gram (−) counterpart: four ribonuclases, RNase Y, RNase J1, J2, and PNPase; an RNA helicase, CshA; two glycolytic enzymes, phosphofructokinase (PfkA) and enolase (Lehnik-Habrink et al., 2012). RNase E is a membrane bound protein providing the major structural scaffold interacting with other components in the Gram (−) degradosome. The structure of Gram (+) RNA degradosome has not been resolved, but protein interaction studies revealed that the endoribonuclease RNase Y, a membrane anchored protein, interacts with most other components in the degradosome, so RNase Y might be the functional homolog of RNase E (Kang et al., 2010). No study has been done yet if RNase Y is also involved in the degradation of some sense-antisense RNA pairs in Gram (+) bacteria. In Gram (−) bacteria, most small non-coding regulatory RNAs work with the RNA chaperone protein Hfq. Generally, the presence of the Hfq protein increases the stability of small non-coding RNAs and facilitates the interaction to their target mRNAs (Gottesman and Storz, 2011). However, the role of Hfq does not seem critical in Gram (+) bacteria. The role of Hfq is dispensable in S. aureus (Bohn et al., 2007). There have not been many studies of Hfq in terms of cis-encoded antisense RNAs so far, but previous studies show that some antisense RNAs interact with Hfq (Sittka et al., 2008; Lorenz et al., 2010), and Hfq is required for the function of a cis-encoded antisense RNA (Ross et al., 2010). Streptococci and lactobacilli do not possess any Hfq homologs, and it has not been studied if some other protein or proteins replace the role of Hfq in trans-acting small RNA- or cis-acting antisense RNA-mediated regulation. It has been suggested that the role of Hfq might be dispensable in low GC Gram (+) bacteria because non-coding RNAs in these bacteria are longer than higher GC Gram (−) bacteria to compensate for the low GC content of the pairings (Jousselin et al., 2009). One advantage of regulation by antisense RNAs is to confer an additional layer of gene regulation like other non-coding regulatory RNAs. In concert with protein regulators, antisense RNAs can provide more precise regulation or regulation responding to different signals. Compared to trans-acting small non-coding RNAs, the regulation by antisense RNAs are generally more specific. Usually trans-acting non-coding small RNAs have multiple target mRNAs with imperfect base-pairs, but antisense RNAs usually have just one target mRNA with the complete complementary sequence. Even though we cannot completely rule out the possibility that some antisense RNAs have several targets with partial base matches by acting in trans, multiple targets of an antisense RNA have not been discovered yet. Another advantage of regulation by cis-encoded antisense RNAs is regulation speed. Like other non-coding regulatory RNAs, most antisense RNAs act at the post-transcriptional level, so the result of the action by antisense RNAs would be faster than protein transcriptional regulators.

Perspectives

Compared to small non-coding trans-acting RNAs, bacterial cis-encoded antisense RNAs had not been studied in the genome-wide scale because of technical difficulties. However, due to the recent development of strand specific RNA sequencing and tiling microarrays covering both strands, cis-encoded antisense RNAs have been subjected under the genome-wide search in many bacteria. Already hundreds of bacterial antisense RNAs have been discovered and changed the concept of regulation by antisense RNAs. So far few streptococcal antisense RNAs have been discovered, but further genome-wide search would definitely find a number of antisense RNAs in this group of bacteria and promote studies to investigate the function and molecular mechanism of regulation by antisense RNAs.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  35 in total

1.  Antisense RNA regulation of the par post-segregational killing system: structural analysis and mechanism of binding of the antisense RNA, RNAII and its target, RNAI.

Authors:  T J Greenfield; T Franch; K Gerdes; K E Weaver
Journal:  Mol Microbiol       Date:  2001-10       Impact factor: 3.501

2.  Transcriptional interference between convergent promoters caused by elongation over the promoter.

Authors:  Benjamin P Callen; Keith E Shearwin; J Barry Egan
Journal:  Mol Cell       Date:  2004-06-04       Impact factor: 17.970

3.  Tn10/IS10 transposition is downregulated at the level of transposase expression by the RNA-binding protein Hfq.

Authors:  Joseph A Ross; Simon J Wardle; David B Haniford
Journal:  Mol Microbiol       Date:  2010-09-22       Impact factor: 3.501

Review 4.  Bacterial small RNA regulators: versatile roles and rapidly evolving variations.

Authors:  Susan Gottesman; Gisela Storz
Journal:  Cold Spring Harb Perspect Biol       Date:  2011-12-01       Impact factor: 10.005

Review 5.  The RNA degradosome of Escherichia coli: an mRNA-degrading machine assembled on RNase E.

Authors:  Agamemnon J Carpousis
Journal:  Annu Rev Microbiol       Date:  2007       Impact factor: 15.500

6.  Structural basis for binding of the plasmid ColIb-P9 antisense Inc RNA to its target RNA with the 5'-rUUGGCG-3' motif in the loop sequence.

Authors:  K Asano; T Niimi; S Yokoyama; K Mizobuchi
Journal:  J Biol Chem       Date:  1998-05-08       Impact factor: 5.157

7.  The Listeria transcriptional landscape from saprophytism to virulence.

Authors:  Alejandro Toledo-Arana; Olivier Dussurget; Georgios Nikitas; Nina Sesto; Hélène Guet-Revillet; Damien Balestrino; Edmund Loh; Jonas Gripenland; Teresa Tiensuu; Karolis Vaitkevicius; Mathieu Barthelemy; Massimo Vergassola; Marie-Anne Nahori; Guillaume Soubigou; Béatrice Régnault; Jean-Yves Coppée; Marc Lecuit; Jörgen Johansson; Pascale Cossart
Journal:  Nature       Date:  2009-05-17       Impact factor: 49.962

8.  Identification of regulatory RNAs in Bacillus subtilis.

Authors:  Irnov Irnov; Cynthia M Sharma; Jörg Vogel; Wade C Winkler
Journal:  Nucleic Acids Res       Date:  2010-06-04       Impact factor: 16.971

9.  The transcriptionally active regions in the genome of Bacillus subtilis.

Authors:  Simon Rasmussen; Henrik Bjørn Nielsen; Hanne Jarmer
Journal:  Mol Microbiol       Date:  2009-08-04       Impact factor: 3.501

10.  Characterization of a Streptococcus mutans intergenic region containing a small toxic peptide and its cis-encoded antisense small RNA antitoxin.

Authors:  Stephanie Koyanagi; Céline M Lévesque
Journal:  PLoS One       Date:  2013-01-11       Impact factor: 3.240

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  8 in total

Review 1.  The Mechanisms of Virulence Regulation by Small Noncoding RNAs in Low GC Gram-Positive Pathogens.

Authors:  Stephanie Pitman; Kyu Hong Cho
Journal:  Int J Mol Sci       Date:  2015-12-14       Impact factor: 5.923

2.  A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae.

Authors:  Ciro C Rossi; Janine T Bossé; Yanwen Li; Adam A Witney; Kate A Gould; Paul R Langford; Denise M S Bazzolli
Journal:  RNA       Date:  2016-07-11       Impact factor: 4.942

3.  Identification of streptococcal small RNAs that are putative targets of RNase III through bioinformatics analysis of RNA sequencing data.

Authors:  Ethan C Rath; Stephanie Pitman; Kyu Hong Cho; Yongsheng Bai
Journal:  BMC Bioinformatics       Date:  2017-12-28       Impact factor: 3.169

Review 4.  Natural antisense RNAs as mRNA regulatory elements in bacteria: a review on function and applications.

Authors:  Fatemeh Saberi; Mehdi Kamali; Ali Najafi; Alavieh Yazdanparast; Mehrdad Moosazadeh Moghaddam
Journal:  Cell Mol Biol Lett       Date:  2016-07-28       Impact factor: 5.787

5.  Integrated transcriptome and proteome analyses identify novel regulatory network of nucleus pulposus cells in intervertebral disc degeneration.

Authors:  Chen Xu; Shengchang Luo; Leixin Wei; Huiqiao Wu; Wei Gu; Wenchao Zhou; Baifeng Sun; Bo Hu; Hongyu Zhou; Yang Liu; Huajiang Chen; Xiaojian Ye; Wen Yuan
Journal:  BMC Med Genomics       Date:  2021-02-03       Impact factor: 3.063

6.  Modulation of sol mRNA expression by the long non-coding RNA Assolrna in Clostridium saccharoperbutylacetonicum affects solvent formation.

Authors:  Saskia Tabea Baur; Anja Poehlein; Niklas Jan Renz; Stefanie Karolina Hollitzer; José David Montoya Solano; Bettina Schiel-Bengelsdorf; Rolf Daniel; Peter Dürre
Journal:  Front Genet       Date:  2022-08-11       Impact factor: 4.772

7.  RNA sequencing uncovers antisense RNAs and novel small RNAs in Streptococcus pyogenes.

Authors:  Anaïs Le Rhun; Yan Yan Beer; Johan Reimegård; Krzysztof Chylinski; Emmanuelle Charpentier
Journal:  RNA Biol       Date:  2016       Impact factor: 4.652

Review 8.  Regulatory RNAs in the Less Studied Streptococcal Species: From Nomenclature to Identification.

Authors:  Mohamed A Zorgani; Roland Quentin; Marie-Frédérique Lartigue
Journal:  Front Microbiol       Date:  2016-07-26       Impact factor: 5.640

  8 in total

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