BACKGROUND
the importance of small rnas  in bacterial gene expression regulation is now broadly appreciated  <cit> .
srnas play essential regulatory roles in diverse processes including metabolic reactions, stress response, biofilm formation and pathogenesis  <cit> .
they act as either activators or repressors of proteins and mrnas.
the length of most of the bacterial srnas ranges between  <dig> and  <dig> but can reach up to  <dig> nucleotides  <cit> .
the best studied bacterial regulatory srnas are those that act through base-pairing interactions with target rnas, usually modulating gene expression post-transcriptionally by controlling the translation and stability of mrnas.
the majority of these are trans-acting srnas found within intergenic regions .
trans-acting srnas typically regulate mrnas encoded at different genomic locations on the chromosome in response to changes in environmental conditions  <cit> .
furthermore, trans-encoded srnas tend to have limited complementarity with their target rnas and require the rna chaperone hfq to facilitate their pairing with mrna targets  <cit> .
in contrast, cis-encoded antisense rnas , also referred to as naturally occurring rnas, are expressed on reverse strands opposite to annotated genes and have extensive complementarity with their target mrnas  <cit> .
antisense rnas are thought to play physiological roles such as repression of genes encoding potentially toxic proteins  <cit> .
additional roles of asrnas include blocking the translation of mrna transcripts encoded on the opposite strand and directing their rnase iii-mediated cleavage  <cit> .
other important classes of srnas include 1) riboswitches , which form part of the mrna they regulate and usually present in the 5′ utr regions; 2) srnas which interact with proteins and modify their activities by mimicking their rna or dna targets, and 3) srnas with intrinsic regulatory activities  <cit> .
the advent of rna-seq for the resolution of messenger and structural rnas has facilitated the analysis of vast numbers of srnas with increased sensitivity  <cit> .
an additional benefit of rna-seq approaches is that information about the direction of transcription can be resolved using directional rna-seq .
this information is important for the detection of non-coding  rnas as well as 5′ and 3′ untranslated regions , antisense transcripts and determination of overlapping features within the genome  <cit> .
combining deep sequencing with computational  prediction methods is emerging as an important approach for srna detection in bacterial genome sequences  <cit> .
pectobacterium atrosepticum is an important plant pathogen belonging to the bacterial family enterobacteriaceae  <cit> .
this pathogen causes major yield losses globally through blackleg disease on potato plants in the field and potato tuber soft rot diseases during post-harvest storage.
most of the information on pectobacteria concerns their interaction with plant hosts, and little is known about how these bacteria spend much of their life outside of the host  <cit> .
however, it is known that p. atrosepticum is able to utilize various adaptive programs that enable bacteria to survive under adverse conditions  <cit> .
in a previous study, we showed that realization of these programs under nutrient-deficient conditions  is coupled with an increased transcript abundance of stress responsive genes in p. atrosepticum, and bacterial cells undergo morphological and ultrastructural changes  <cit> .
in the current study we have evaluated the possible participation of srnas in bacterial starvation-induced stress response.
few experimental studies on srnas have been carried out in p. atrosepticum.
a well-known regulatory srna in p. atrosepticum is rsmb.
this srna binds the rsma protein, which is a homologue of escherichia coli crsa, a carbon storage regulator, and modulates its activity.
in p. atrosepticum the rsma/rsmb system regulates the production of virulence factors .
moreover, a regulatory rna antisense to the expi gene transcript, which encodes the synthase of mediators of quorum sensing , was found recently in p. atrosepticum  <cit> .
in the present study, identification of srnas in the complete genome of p. atrosepticum scri <dig> was undertaken using in silico prediction and experimental validation via strand-specific rna-sequencing.
both true  and potentially novel srna candidates expressed under starvation conditions were identified.
differential expression analysis indicated that many of these srnas increase in abundance during exposure of bacteria to starvation compared to rich medium conditions, suggesting an important role of srnas in the survival of p. atrosepticum cells during nutrient deficiency induced stress.
RESULTS
strand-specific rna-seq detection of p. atrosepticum srnas under starvation-conditions
for experimental detection of srnas in p. atrosepticum scri <dig>  we used a combination of in silico and directional whole-transcriptome cdna sequencing  .
the experimental approach for determination of srna in p. atrosepticum is outlined in fig.
1a.
a total of  <dig>  and  <dig>  million paired-end  reads were obtained from nutrient rich and starvation conditions, respectively.
by using samtools  <cit> , pe reads mapped to each strand were extracted.
thus, enabling visualization of the sequence  read alignments on the genome in a strand-specific manner.
visual inspections enabled the identification of candidate srna transcripts by manually analysing the position of pe reads with respect to annotated protein-coding regions .
this can be a particularly powerful approach to identify srnas and resolve their genomic positions because reads that map to intergenic regions may represent previously unannotated transcriptionally active non-coding srnas  <cit> .
only srna candidates with a length between  <dig> to  <dig> nucleotides were considered to be true positive srnas candidates.
this technique enabled identification of a total of  <dig> srna candidates expressed under starvation condition .
these candidate srnas were classified into four distinct srna groups based on their position in relation to adjacent cdss: igr/ trans-encoded srnas, asrna, 5′ utr , and 3′ utr srnas .
an in silico approach  was employed to determine the putative transcriptional start sites  of the identified  <dig> srnas and to resolve their 5′ ends.
only predicted tss with transcription factor binding sites were considered as bona fide promoters.
thus, using this filter, tss were identified upstream of  <dig> srna genes .fig.
<dig> scheme for srna identification.
a determination of srna using strand-specific rna seq of p. atrosepticum cultured under starvation conditions.
b comparison of srnas identified by strand-specific rna-seq with srna candidates predicted for p. atrosepticum in rfam database and srnas predicted computationally in this study.
c computational  srna prediction
fig.
<dig> classification of srnas identified using ssrna-seq into five classes: these include; igr/ trans-encoded srnas, asrna, 5′utr , 3′ utr and sense srnas , based on their proximity and location with regards to cds regions
identification of 3′ utr encoded srnas
we identified  <dig> srnas encoded within the 3′ utr regions of mrna  .
it is now appreciated that srnas not only originate from intergenic regions as independent transcripts but are also transcribed from 3′ regions of coding mrna  <cit> .
these 3′ utr srnas are generated either by means of mrna transcript processing or as primary transcripts from an internal promoter within the mrna coding sequence as in the case of dapz srna  <cit> .
thus, based on how they are produced, 3′ utr encoded srnas can be divided into  <dig> groups, that are: 1) srnas transcribed from an independent promoter located inside the overlapping mrna gene or 3′ utr region ; and 2) srnas which are originated from the processing of the parent mrna   <cit> .
hence we used our ssrna-seq data to determine whether the identified 3′ utr embedded srnas are transcribed independently from the parent mrna.
ten 3′ utr srnas were considered to be independently transcribed based on comparisons of srna and parent mrna rpkm  values and the presence or absence of an internal promoter .
to determine the putative 5′ ends and fundamental types of the detected 3′ utr srnas based on their biogenesis, we extracted each srna sequence plus 200 nt upstream of the start position of each srna and performed promoter predictions using bprom program .
this approach led to the identification of  <dig> distinct putative promoter sites  embedded within the coding or 3′ utr regions of the parent mrna upstream of each 3′ utr srna gene .
in addition, transcription factor binding sites were also detected within the predicted promoter regions.
taken together, the presence of putative internal promoter sites upstream of srnas tss and the predicted transcriptional factor binding sites for each promoter, strongly suggests that fourteen 3′ utr srnas are type  <dig>  nine of which were also differentially expressed compared to their parent mrnas based on rpkm values, further indicating evidence of independent expression.
the remaining srna reg_seq <dig> could be a product of mrna processing, thus type  <dig> since no internal promoters supported by transcription binding sites were predicted for this srna.
overall, since the srna 5′ ends and subsequent tsss were predicted computationally, we were not able to determine whether these srnas possessed the characteristic 5′-triphosphate  cap common to type  <dig> srnas in this present study.table  <dig> 3′ utr encoded srnas
rbsb
pola
eca0044
expi
alda
eca0332
eca0449
mdh
eca2516
rpil
glna
slma
eca2950
glpc
eca <dig>
the  <dig> srnas identified using strand-specific rna-seq approach were checked against known p. atrosepticum scri <dig> non-coding rna descriptions on the rfam database  <cit> .
for this analysis, all descriptions for trnas, rrnas and crispr rnas were excluded.
this also served to assess the efficiency of the strand-specific rna-seq method in detecting srna transcripts.
in total  <dig>  %  of the known p. atrosepticum srnas in the rfam database were identified using ssrna-seq of cells cultured under starvation conditions .
computational prediction of srna in the pectobacterium atrosepticum genome
even though ssrna-seq is a powerful tool for identification of srnas, it might be subject to some limitations.
for example, since the formation of particular srnas is highly dependent on culture conditions, it is not possible to unravel the whole pool of srnas that is encoded in the genome of the target microorganism within the frameworks of a given experiment.
consequently, a combination of experimental and computational identification of srna is often seen as a more comprehensive approach towards identification of srnas  <cit> .
hence, in addition to ssrna-seq, an in silico srna analysis was performed according to computational methods implemented previously  <cit> , with some modifications .
an initial step towards in silico srna candidate disclosure consisted of identification of predicted rho-independent terminators  in the p. atrosepticum scri <dig> genome.
since about 72 % of known srnas located within igrs possess a rit, computational methods based on prediction of rit signature sequences have emerged as valuable algorithms for the detection of srna molecules  <cit> .
in intergenic and antisense to annotated open reading frames  in the p. atrosepticum scri <dig> genome we detected a total of  <dig> putative terminators  with the ‘greatest Δg’ i.e.
the most negative Δg  value.
from the  <dig> putative srna identified,  <dig> were filtered out and excluded from further analysis due to the fact that their rits were located less than  <dig> nucleotides downstream from stop codons of preceding annotated orfs within the same strand.
this resulted in identification of  <dig> srna candidates of 226–248 nt in length .
to be more confident about the accuracy of the rho-independent terminator based prediction strategy used, a second prediction tool   <cit>  was employed.
herewith, the filtered set of srna candidate signatures was compared against srna predictions for p. atrosepticum scri <dig> from the sipht web interface by means of blast local pairwise alignments using the genomic similarity search tool yass  <cit> , with standard parameters.
each comparison was made on both regular and complementary strands separately.
as a result, a total of  <dig> and  <dig> matches  were identified, partially or fully overlapping, for the forward and complementary strands, respectively.
this additional filtering step combining comparative genomics with rit based predictions yielded  <dig> srna candidates in p. atrosepticum scri <dig> .
similarly to srna detected using ssrna-seq, predicted srnas were further classified into five distinct srna groups based on their position in relation to adjacent cdss .
comparison of rna-seq results with computational srna predictions
the  <dig> candidate srnas identified computationally were compared to the  <dig> srna transcripts identified using ssrna-seq.
only  <dig> of the in silico predicted srna candidates were also identified by rna sequencing .
such an incomplete overlap between computational srna predictions and deep sequencing detection has been noted in previous studies  <cit> .
it is possible that the discrepancy observed here could be largely because experimental detection of srnas was restricted to srnas expressed under one condition, viz starvation.
hence, it may well be that increasing the number of conditions in which rna is harvested could lead to bridging the gap between in silico predicted and ssrnaseq identified srnas.
lastly, the disparity could be due to the presence of false positive in silico predictions as well as the elimination of srnas associated with rits in close proximity to cds regions when using rit identification based in silico predictions.
nonetheless, the lengths of the majority of the in silico predicted srna transcripts were comparable to the sizes deduced from the strand-specific rna-seq srna detections for the confirmed srna candidates.table  <dig>
in silico predicted srna candidates confirmed by strand-specific rna-seq
functional annotation of rna-seq detected srnas
to describe and assign biological functions to the  <dig> srnas detected by strand-specific rna-seq , we used the rfam database   <cit>  and the rnaspace platform  <cit> .
the rnaspace platform comprises a suite of ncrna prediction tools.
similarity searches on the rnaspace platform were restricted to comparative analysis and homology searches using blast/ yass  against the rfam  <dig>  seed database and three rna motif search tools, darn, erpin and infernal.
in total,  <dig> srnas representing true , previously described srna sequences were assigned into  <dig> functional classes , and these included:  <dig> ribozyme,  <dig> riboswitches ,  <dig> rna elements ,  <dig> srnas ,  <dig> asrna and  <dig> tmrna .
amongst these, we characterized  <dig> srna sequences which were previously uncharacterized within the p. atrosepticum genome by means of blast  and secondary structure predictions using the rnafold webserver  <cit> .
no functional classes were assigned to the remaining  <dig> srnas computationally, suggesting that they could be potentially novel srna candidates in p. atrosepticum.table  <dig> functional annotation of the  <dig> true  srnas identified by strand-specific rna-seq
staxi
crcb
csrb
rye
stnc240
styr-44
t44
frns
isrh
omra
rpra
ryhb
ryeb
sgrs
spot 42
hpnc0260
most of the detected riboswitches in this study corresponded to thiamine pyrophosphate   riboswitches .
bacterial riboswitches are embedded within the leader sequences  of numerous metabolic genes and act by repressing or activating their cognate genes at the translational level in gram-negative bacteria  <cit> .
most thiamin-regulated genes encode transporters in different bacterial organisms  <cit> .
for example, tpp riboswitches identified are present upstream of genes involved in potassium transport , amino acid biosynthesis , and genes related to the biosynthesis of secondary metabolites .
generally, tpp riboswitches are found upstream  of many genes key in metabolic processes which use tpp as a cofactor  <cit> .
in this study, we also detected other riboswitches other than tpp-type riboswitches, that include flavin mononucleotide , glycine, lysine, yybp-ykoy and moco rna motif riboswitches.
some of the detected rna elements  were located upstream of operons or genes involved in biosynthesis of amino acids including leucine, histidine and tryptophan biosynthesis; and polysaccharide synthesis .
it therefore seems plausible that most of the detected cis-regulatory elements are engaged in regulating processes involving substrate transport and biosynthesis in p. atrosepticum.
conservation analysis of predicted srnas
the vast majority of known srnas are typically highly conserved across genera  <cit> .
we therefore analysed the conservation of identified srnas in p. atrosepticum scri <dig> in five soft rot enterobacteriaceae species whose complete genome sequences are available on genbank.
the  <dig> true/ known srna sequences with assigned functional classes were used for the conservation analysis.
blastn analysis  using the yass tool against p. carotovorum subsp.
carotovorum pc <dig>  p. wasabiae wpp <dig>  pectobacterium spp.
scc <dig>  dickeya dadantii ech <dig> and d. zeae ech <dig> complete genome sequences revealed that most srnas are conserved within the soft rot bacterial species with  <dig> srnas  being present in all five sre species .
the high conservation of srnas within the sre species emphasizes their regulatory importance in these bacteria.
six igr srnas were conserved only in the pectobacterium genus and belonged to two rna families; namely styr- <dig>  and crcb rna motif  sensing fluoride ions and regulating the crcb gene  which possibly encodes a protein that functions by removing excess fluoride ions from the cell.fig.
<dig> summary of srnas conserved in soft rot enterobacterieace
to be more confident with the  <dig> potentially novel srna candidates detected by ssrna-seq, we filtered and screened them by checking their conservation within the five representative sre strains using sequence similarity analysis.
nine of these candidate srnas had high sequence conservation  within sre strains and only single hits from the blast analysis and therefore were considered as novel srnas .
to validate the expression and lengths of the nine novel srnas, reverse transcription pcr  was performed on cdna of bacteria cells cultured under starvation conditions .
for each of the cdna samples, a single amplicon that corresponded to the srna transcript size identified by ssrna-seq was observed.
as an additional validation step, the nucleotide bases of observed amplicons were confirmed by sequencing and alignment to respective srna sequences .table  <dig> novel srna candidates obtained using conservation analysis
fig.
<dig> validation of novel srna expression by rt-pcr: agarose gel electrophoresis of the pcr amplicon fragments of the  <dig> novel srnas.
lane  <dig>  rev_ <dig>  lane  <dig>  rev_ <dig>  lane  <dig>  fwd_ <dig>  lane  <dig>  rev_ <dig>  lane  <dig>  fwd_ <dig>  lane  <dig>  fwd_ <dig>  lane  <dig>  fwd_ <dig>  lane  <dig>  rev_ <dig>  lane  <dig>  rev_ <dig>  lane  <dig>  no reverse transcriptase control, lane  <dig>  100 bp dna ladder
differential expression of srnas under nutrient-rich and starvation conditions
application of strand-specific rna-seq to study the transcriptome of p. atrosepticum uncovered an abundance of srnas including antisense transcripts, intergenic srnas and cis-encoded regulatory elements.
the number of rna-seq reads mapping to individual srna sequences provides a realistic assessment of relative transcript abundance  <cit> , thus enabling quantification of differential expression of the srna transcripts in p. atrosepticum cells existing under nutrient-rich and nutrient-deficient  conditions.
the differential expression of srnas when growth conditions are changed could suggest potential functions and clarify conditions that induce or repress formation of specific srnas  <cit> .
hence, in order to understand the expression profiles of srnas in response to carbon and phosphorus starvation, we compared expression patterns of p. atrosepticum cells under nutrient-rich and nutrient-deficient  conditions.
based on the combined statistics of edger package  <cit>  , and gfold algorithm   <cit> , which uses a posterior distribution of log fold change for determining expression changes in experiments with single biological replication, thus, overcoming the shortcomings of relying on statistics based on p-value when biological replication is lacking  <cit> .
subsequently, only srnas with significant differential expression from edger and gfold analyses were considered.
thus, a total of  <dig> srna candidates were differentially expressed .
of these,  <dig> srnas were up-regulated under nutrient-deficient conditions  suggesting that they are likely involved in regulatory mechanisms of stress response or adaptation in p. atrosepticum.
to validate expression profiles identified by ssrna-seq, we performed reverse transcription quantitative pcr  using three biological replicates, on eight selected srnas that were differentially expressed under nutrient-rich and starvation conditions.
the rt-qpcr results confirmed expression patterns of these eight srna transcripts and validated our rna-seq data .
selected examples are discussed below.fig.
<dig> rt-qpcr validation of rna-seq expression analysis.
relative expression changes of srnas were determined using the 2-ΔΔct method by comparing expression in starvation conditions to nutrient-rich.
error bars indicate the standard error of three independent biological replicates.
asterisks represent significant difference at p <  <dig>
we noticed that rpra was up-regulated  in p. atrosepticum under carbon-starvation conditions .
the srna rpra acts by increasing  the translation of rpos gene transcript  <cit> .
rpos is a sigma factor that controls the expression of stress responsive genes in bacteria during adverse conditions and stationary phase.
we observed that the expression of rpos gene in p. atrosepticum was higher during starvation than under nutrient-rich conditions .
this observation is consistent with previous data demonstrating that rpos is a principal regulator of the general stress response in bacteria allowing cells to survive environmental challenges as well as prepare for subsequent stresses  <cit> .
this is also consistent with our previous observations, demonstrating that rpos gene expression increases significantly in p. atrosepticum under stress conditions  <cit> .
generally, the regulation of rpos gene expression is known to be modulated at the translational level by at least four srna, namely, arcz, dsra, rpra, and oxys in response to temperature, osmotic shock, oxidative stress and nutrient deprivation in e. coli  <cit> .
hence, increased rpra expression observed in our study in p. atrosepticum under nutrient starvation conditions is likely to promote the enhanced translation of rpos mrna during adaptation of bacteria to starvation conditions.
ryhb <dig>  a  <dig> nucleotide paralogue of ryhb srna, was up-regulated by a 15-fold magnitude in p. atrosepticum under nutrient-starvation conditions .
generally, ryhb, regulates iron metabolism, including its acquisition and assimilation.
ryhb acts by down-regulating expression of genes encoding iron-storage and iron-using proteins when iron is in limited supply.
the main target genes for ryhb include the sdhcdab operon encoding succinate dehydrogenase and sodb which encodes the iron-dependent superoxide dismutase  <cit> .
ryhb expression level is usually inversely correlated with expression levels of the mrna for the sdhcdab operon  <cit> .
this is consistent with our observations for p. atrosepticum: the transcription of the sdhcdab operon was reduced under starvation conditions compared to the growth-promoting ones .fig.
<dig> the expression of the sdhcdab operon is relatively lower under starvation compared to growth promoting conditions.
reads mapped from the nutrient-rich condition are represented by the red line.
the blue line represents mapped reads from the starvation conditions.
annotated features are labelled below the plot in blue blocks.
the y-axis shows the read coverage per coding region
starvation conditions also induced the expression of glmz  and glmy  srnas in p. atrosepticum .
in enteric bacteria, these two srnas regulate amino sugar metabolism by activating the expression of glmus operon which encodes the glucosamine-6-phosphate synthase, an essential enzyme in amino sugar metabolism  <cit> .
the regulation by these two srnas modulates the transitions between carbon storage and carbon metabolism  <cit> .
the level of glmy is increased in the absence of glucosamine-6-phosphate leading to stabilization of glmz.
the latter, in turn, activates glms gene expression in an anti-antisense mechanism  <cit> .
glms enables cells to utilize the intermediates of glycolytic pathway including the fructose-6-phosphate for production of amino sugars.
the glucosamine-6-phosphate is an essential precursor for biosynthesis of essential components of the cell envelope such as peptidoglycan and lipopolysaccharide in gram-negative bacteria.
thus, induction of glmy and glmz expression in p. atrosepticum under starvation conditions likely indicates the important role of the amino sugar metabolism in adaptive response on this bacterium.
in summary, we have shown that several srnas are induced under nutrient-deficient compared to nutrient-rich conditions.
we have also shown that induction of these srna leads to induction of various genes that potentially play a role in the survival of p. atrosepticum.
in other members of the enterobacteriaceae family including e. coli and salmonella, srnas have also been shown to play an important role in adaptation to nutrient limited condition  <cit> .
in these bacteria, srnas provide a signal that triggers production of extracellular polysaccharides  which in turn are involved in biofilm formation  <cit> .
although p. atrosepticum does not readily form biofilms in vitro, the overexpression of a diguanylate cyclase , induced formation of biofilms suggesting that biofilm formation in this pathogen is cryptic and can be activated under optimum conditions  <cit> .
part of the pathogenesis of p. atrosepticum is in xylem tissue .
the xylem is typified by limited nutrients and as such a harsh environment that requires well defined methods of survival.
hence, it is not surprising that many xylem dwelling phytopathogens such as xanthomonas, clavibacter, ralstonia and xylella form biofilms in xylem tissues of their respective hosts.
thus, it is possible that srna are extensively involved in the adaptation of p. atrosepticum and survival in stem vasculature.
identification of this suite of srna will allow us to study the role that these play in survival of this phytopathogen during stem colonisation.
CONCLUSIONS
in conclusion, in this study we have used a combination of strand-specific rna-sequencing and in silico approaches to detect and analyse srnas in p. atrosepticum scri <dig>  we demonstrated the efficiency of ssrna-seq in detecting srnas and determining the srna expression levels in response to specific bacterial growth conditions.
a total of  <dig> srnas and srna candidates were experimentally detected in this study.
we successfully determined srnas  that may play key roles in regulating stress responses.
most of the identified srnas in p. atrosepticum are conserved within the soft rot enterobacteria  species suggesting their importance in physiological responses for the sre species.
to our knowledge, this study constitutes the first genome/ transcriptome-wide analysis aimed at the discovery of srnas responsive to nutrient-deficiency  in bacteria.
a significant fraction of the unravelled srnas appeared to be starvation responsive indicative of their importance in adaptation of bacteria to stress conditions.
determining the biological roles of these srnas will broaden our understanding of the diverse regulatory mechanisms they provide in modulating gene expression in p. atrosepticum and other sre species during adaptation to changing environments.

 the importance of small rnas in bacterial gene expression regulation is now broadly appreciated. srnas play essential regulatory roles in diverse processes including metabolic reactions, stress response, biofilm formation and pathogenesis. they act as either activators or repressors of proteins and mrnas. the length of most of the bacterial srnas ranges between and but can reach up to nucleotides. the best studied bacterial regulatory srnas are those that act through base-pairing interactions with target rnas, usually modulating gene expression post-transcriptionally by controlling the translation and stability of mrnas. the majority of these are trans-acting srnas found within intergenic regions. trans-acting srnas typically regulate mrnas encoded at different genomic locations on the chromosome in response to changes in environmental conditions. furthermore, trans-encoded srnas tend to have limited complementarity with their target rnas and require the rna chaperone hfq to facilitate their pairing with mrna targets. in contrast, cis-encoded antisense rnas, also referred to as naturally occurring rnas, are expressed on reverse strands opposite to annotated genes and have extensive complementarity with their target mrnas. antisense rnas are thought to play physiological roles such as repression of genes encoding potentially toxic proteins. additional roles of asrnas include blocking the translation of mrna transcripts encoded on the opposite strand and directing their rnase iii-mediated cleavage. other important classes of srnas include 1) riboswitches, which form part of the mrna they regulate and usually present in the 5′ utr regions; 2) srnas which interact with proteins and modify their activities by mimicking their rna or dna targets, and 3) srnas with intrinsic regulatory activities. the advent of rna-seq for the resolution of messenger and structural rnas has facilitated the analysis of vast numbers of srnas with increased sensitivity. an additional benefit of rna-seq approaches is that information about the direction of transcription can be resolved using directional rna-seq. this information is important for the detection of non-coding rnas as well as 5′ and 3′ untranslated regions, antisense transcripts and determination of overlapping features within the genome. combining deep sequencing with computational prediction methods is emerging as an important approach for srna detection in bacterial genome sequences. pectobacterium atrosepticum is an important plant pathogen belonging to the bacterial family enterobacteriaceae. this pathogen causes major yield losses globally through blackleg disease on potato plants in the field and potato tuber soft rot diseases during post-harvest storage. most of the information on pectobacteria concerns their interaction with plant hosts, and little is known about how these bacteria spend much of their life outside of the host. however, it is known that p. atrosepticum is able to utilize various adaptive programs that enable bacteria to survive under adverse conditions. in a previous study, we showed that realization of these programs under nutrient-deficient conditions is coupled with an increased transcript abundance of stress responsive genes in p. atrosepticum, and bacterial cells undergo morphological and ultrastructural changes. in the current study we have evaluated the possible participation of srnas in bacterial starvation-induced stress response. few experimental studies on srnas have been carried out in p. atrosepticum. a well-known regulatory srna in p. atrosepticum is rsmb. this srna binds the rsma protein, which is a homologue of escherichia coli crsa, a carbon storage regulator, and modulates its activity. in p. atrosepticum the rsma/rsmb system regulates the production of virulence factors. moreover, a regulatory rna antisense to the expi gene transcript, which encodes the synthase of mediators of quorum sensing, was found recently in p. atrosepticum. in the present study, identification of srnas in the complete genome of p. atrosepticum scri was undertaken using in silico prediction and experimental validation via strand-specific rna-sequencing. both true and potentially novel srna candidates expressed under starvation conditions were identified. differential expression analysis indicated that many of these srnas increase in abundance during exposure of bacteria to starvation compared to rich medium conditions, suggesting an important role of srnas in the survival of p. atrosepticum cells during nutrient deficiency induced stress.  strand-specific rna-seq detection of p. atrosepticum srnas under starvation-conditions for experimental detection of srnas in p. atrosepticum scri we used a combination of in silico and directional whole-transcriptome cdna sequencing. the experimental approach for determination of srna in p. atrosepticum is outlined in fig. 1a. a total of and million paired-end reads were obtained from nutrient rich and starvation conditions, respectively. by using samtools, pe reads mapped to each strand were extracted. thus, enabling visualization of the sequence read alignments on the genome in a strand-specific manner. visual inspections enabled the identification of candidate srna transcripts by manually analysing the position of pe reads with respect to annotated protein-coding regions. this can be a particularly powerful approach to identify srnas and resolve their genomic positions because reads that map to intergenic regions may represent previously unannotated transcriptionally active non-coding srnas. only srna candidates with a length between to nucleotides were considered to be true positive srnas candidates. this technique enabled identification of a total of srna candidates expressed under starvation condition. these candidate srnas were classified into four distinct srna groups based on their position in relation to adjacent cdss: igr/ trans-encoded srnas, asrna, 5′ utr, and 3′ utr srnas. an in silico approach was employed to determine the putative transcriptional start sites of the identified srnas and to resolve their 5′ ends. only predicted tss with transcription factor binding sites were considered as bona fide promoters. thus, using this filter, tss were identified upstream of srna genes.fig. scheme for srna identification. a determination of srna using strand-specific rna seq of p. atrosepticum cultured under starvation conditions. b comparison of srnas identified by strand-specific rna-seq with srna candidates predicted for p. atrosepticum in rfam database and srnas predicted computationally in this study. c computational srna prediction fig. classification of srnas identified using ssrna-seq into five classes: these include; igr/ trans-encoded srnas, asrna, 5′utr, 3′ utr and sense srnas, based on their proximity and location with regards to cds regions identification of 3′ utr encoded srnas we identified srnas encoded within the 3′ utr regions of mrna. it is now appreciated that srnas not only originate from intergenic regions as independent transcripts but are also transcribed from 3′ regions of coding mrna. these 3′ utr srnas are generated either by means of mrna transcript processing or as primary transcripts from an internal promoter within the mrna coding sequence as in the case of dapz srna. thus, based on how they are produced, 3′ utr encoded srnas can be divided into groups, that are: 1) srnas transcribed from an independent promoter located inside the overlapping mrna gene or 3′ utr region; and 2) srnas which are originated from the processing of the parent mrna. hence we used our ssrna-seq data to determine whether the identified 3′ utr embedded srnas are transcribed independently from the parent mrna. ten 3′ utr srnas were considered to be independently transcribed based on comparisons of srna and parent mrna rpkm values and the presence or absence of an internal promoter. to determine the putative 5′ ends and fundamental types of the detected 3′ utr srnas based on their biogenesis, we extracted each srna sequence plus 200 nt upstream of the start position of each srna and performed promoter predictions using bprom program. this approach led to the identification of distinct putative promoter sites embedded within the coding or 3′ utr regions of the parent mrna upstream of each 3′ utr srna gene. in addition, transcription factor binding sites were also detected within the predicted promoter regions. taken together, the presence of putative internal promoter sites upstream of srnas tss and the predicted transcriptional factor binding sites for each promoter, strongly suggests that fourteen 3′ utr srnas are type nine of which were also differentially expressed compared to their parent mrnas based on rpkm values, further indicating evidence of independent expression. the remaining srna reg_seq could be a product of mrna processing, thus type since no internal promoters supported by transcription binding sites were predicted for this srna. overall, since the srna 5′ ends and subsequent tsss were predicted computationally, we were not able to determine whether these srnas possessed the characteristic 5′-triphosphate cap common to type srnas in this present study.table 3′ utr encoded srnas rbsb pola eca0044 expi alda eca0332 eca0449 mdh eca2516 rpil glna slma eca2950 glpc eca the srnas identified using strand-specific rna-seq approach were checked against known p. atrosepticum scri non-coding rna descriptions on the rfam database. for this analysis, all descriptions for trnas, rrnas and crispr rnas were excluded. this also served to assess the efficiency of the strand-specific rna-seq method in detecting srna transcripts. in total  % of the known p. atrosepticum srnas in the rfam database were identified using ssrna-seq of cells cultured under starvation conditions. computational prediction of srna in the pectobacterium atrosepticum genome even though ssrna-seq is a powerful tool for identification of srnas, it might be subject to some limitations. for example, since the formation of particular srnas is highly dependent on culture conditions, it is not possible to unravel the whole pool of srnas that is encoded in the genome of the target microorganism within the frameworks of a given experiment. consequently, a combination of experimental and computational identification of srna is often seen as a more comprehensive approach towards identification of srnas. hence, in addition to ssrna-seq, an in silico srna analysis was performed according to computational methods implemented previously, with some modifications. an initial step towards in silico srna candidate disclosure consisted of identification of predicted rho-independent terminators in the p. atrosepticum scri genome. since about 72 % of known srnas located within igrs possess a rit, computational methods based on prediction of rit signature sequences have emerged as valuable algorithms for the detection of srna molecules. in intergenic and antisense to annotated open reading frames in the p. atrosepticum scri genome we detected a total of putative terminators with the ‘greatest Δg’ i.e. the most negative Δg value. from the putative srna identified, were filtered out and excluded from further analysis due to the fact that their rits were located less than nucleotides downstream from stop codons of preceding annotated orfs within the same strand. this resulted in identification of srna candidates of 226–248 nt in length. to be more confident about the accuracy of the rho-independent terminator based prediction strategy used, a second prediction tool was employed. herewith, the filtered set of srna candidate signatures was compared against srna predictions for p. atrosepticum scri from the sipht web interface by means of blast local pairwise alignments using the genomic similarity search tool yass, with standard parameters. each comparison was made on both regular and complementary strands separately. as a result, a total of and matches were identified, partially or fully overlapping, for the forward and complementary strands, respectively. this additional filtering step combining comparative genomics with rit based predictions yielded srna candidates in p. atrosepticum scri. similarly to srna detected using ssrna-seq, predicted srnas were further classified into five distinct srna groups based on their position in relation to adjacent cdss. comparison of rna-seq results with computational srna predictions the candidate srnas identified computationally were compared to the srna transcripts identified using ssrna-seq. only of the in silico predicted srna candidates were also identified by rna sequencing. such an incomplete overlap between computational srna predictions and deep sequencing detection has been noted in previous studies. it is possible that the discrepancy observed here could be largely because experimental detection of srnas was restricted to srnas expressed under one condition, viz starvation. hence, it may well be that increasing the number of conditions in which rna is harvested could lead to bridging the gap between in silico predicted and ssrnaseq identified srnas. lastly, the disparity could be due to the presence of false positive in silico predictions as well as the elimination of srnas associated with rits in close proximity to cds regions when using rit identification based in silico predictions. nonetheless, the lengths of the majority of the in silico predicted srna transcripts were comparable to the sizes deduced from the strand-specific rna-seq srna detections for the confirmed srna candidates.table in silico predicted srna candidates confirmed by strand-specific rna-seq functional annotation of rna-seq detected srnas to describe and assign biological functions to the srnas detected by strand-specific rna-seq, we used the rfam database and the rnaspace platform. the rnaspace platform comprises a suite of ncrna prediction tools. similarity searches on the rnaspace platform were restricted to comparative analysis and homology searches using blast/ yass against the rfam seed database and three rna motif search tools, darn, erpin and infernal. in total, srnas representing true, previously described srna sequences were assigned into functional classes, and these included: ribozyme, riboswitches, rna elements, srnas, asrna and tmrna. amongst these, we characterized srna sequences which were previously uncharacterized within the p. atrosepticum genome by means of blast and secondary structure predictions using the rnafold webserver. no functional classes were assigned to the remaining srnas computationally, suggesting that they could be potentially novel srna candidates in p. atrosepticum.table functional annotation of the true srnas identified by strand-specific rna-seq staxi crcb csrb rye stnc240 styr-44 t44 frns isrh omra rpra ryhb ryeb sgrs spot 42 hpnc0260 most of the detected riboswitches in this study corresponded to thiamine pyrophosphate riboswitches. bacterial riboswitches are embedded within the leader sequences of numerous metabolic genes and act by repressing or activating their cognate genes at the translational level in gram-negative bacteria. most thiamin-regulated genes encode transporters in different bacterial organisms. for example, tpp riboswitches identified are present upstream of genes involved in potassium transport, amino acid biosynthesis, and genes related to the biosynthesis of secondary metabolites. generally, tpp riboswitches are found upstream of many genes key in metabolic processes which use tpp as a cofactor. in this study, we also detected other riboswitches other than tpp-type riboswitches, that include flavin mononucleotide, glycine, lysine, yybp-ykoy and moco rna motif riboswitches. some of the detected rna elements were located upstream of operons or genes involved in biosynthesis of amino acids including leucine, histidine and tryptophan biosynthesis; and polysaccharide synthesis. it therefore seems plausible that most of the detected cis-regulatory elements are engaged in regulating processes involving substrate transport and biosynthesis in p. atrosepticum. conservation analysis of predicted srnas the vast majority of known srnas are typically highly conserved across genera. we therefore analysed the conservation of identified srnas in p. atrosepticum scri in five soft rot enterobacteriaceae species whose complete genome sequences are available on genbank. the true/ known srna sequences with assigned functional classes were used for the conservation analysis. blastn analysis using the yass tool against p. carotovorum subsp. carotovorum pc p. wasabiae wpp pectobacterium spp. scc dickeya dadantii ech and d. zeae ech complete genome sequences revealed that most srnas are conserved within the soft rot bacterial species with srnas being present in all five sre species. the high conservation of srnas within the sre species emphasizes their regulatory importance in these bacteria. six igr srnas were conserved only in the pectobacterium genus and belonged to two rna families; namely styr- and crcb rna motif sensing fluoride ions and regulating the crcb gene which possibly encodes a protein that functions by removing excess fluoride ions from the cell.fig. summary of srnas conserved in soft rot enterobacterieace to be more confident with the potentially novel srna candidates detected by ssrna-seq, we filtered and screened them by checking their conservation within the five representative sre strains using sequence similarity analysis. nine of these candidate srnas had high sequence conservation within sre strains and only single hits from the blast analysis and therefore were considered as novel srnas. to validate the expression and lengths of the nine novel srnas, reverse transcription pcr was performed on cdna of bacteria cells cultured under starvation conditions. for each of the cdna samples, a single amplicon that corresponded to the srna transcript size identified by ssrna-seq was observed. as an additional validation step, the nucleotide bases of observed amplicons were confirmed by sequencing and alignment to respective srna sequences.table novel srna candidates obtained using conservation analysis fig. validation of novel srna expression by rt-pcr: agarose gel electrophoresis of the pcr amplicon fragments of the novel srnas. lane rev_ lane rev_ lane fwd_ lane rev_ lane fwd_ lane fwd_ lane fwd_ lane rev_ lane rev_ lane no reverse transcriptase control, lane 100 bp dna ladder differential expression of srnas under nutrient-rich and starvation conditions application of strand-specific rna-seq to study the transcriptome of p. atrosepticum uncovered an abundance of srnas including antisense transcripts, intergenic srnas and cis-encoded regulatory elements. the number of rna-seq reads mapping to individual srna sequences provides a realistic assessment of relative transcript abundance, thus enabling quantification of differential expression of the srna transcripts in p. atrosepticum cells existing under nutrient-rich and nutrient-deficient conditions. the differential expression of srnas when growth conditions are changed could suggest potential functions and clarify conditions that induce or repress formation of specific srnas. hence, in order to understand the expression profiles of srnas in response to carbon and phosphorus starvation, we compared expression patterns of p. atrosepticum cells under nutrient-rich and nutrient-deficient conditions. based on the combined statistics of edger package, and gfold algorithm, which uses a posterior distribution of log fold change for determining expression changes in experiments with single biological replication, thus, overcoming the shortcomings of relying on statistics based on p-value when biological replication is lacking. subsequently, only srnas with significant differential expression from edger and gfold analyses were considered. thus, a total of srna candidates were differentially expressed. of these, srnas were up-regulated under nutrient-deficient conditions suggesting that they are likely involved in regulatory mechanisms of stress response or adaptation in p. atrosepticum. to validate expression profiles identified by ssrna-seq, we performed reverse transcription quantitative pcr using three biological replicates, on eight selected srnas that were differentially expressed under nutrient-rich and starvation conditions. the rt-qpcr results confirmed expression patterns of these eight srna transcripts and validated our rna-seq data. selected examples are discussed below.fig. rt-qpcr validation of rna-seq expression analysis. relative expression changes of srnas were determined using the 2-ΔΔct method by comparing expression in starvation conditions to nutrient-rich. error bars indicate the standard error of three independent biological replicates. asterisks represent significant difference at p <  we noticed that rpra was up-regulated in p. atrosepticum under carbon-starvation conditions. the srna rpra acts by increasing the translation of rpos gene transcript. rpos is a sigma factor that controls the expression of stress responsive genes in bacteria during adverse conditions and stationary phase. we observed that the expression of rpos gene in p. atrosepticum was higher during starvation than under nutrient-rich conditions. this observation is consistent with previous data demonstrating that rpos is a principal regulator of the general stress response in bacteria allowing cells to survive environmental challenges as well as prepare for subsequent stresses. this is also consistent with our previous observations, demonstrating that rpos gene expression increases significantly in p. atrosepticum under stress conditions. generally, the regulation of rpos gene expression is known to be modulated at the translational level by at least four srna, namely, arcz, dsra, rpra, and oxys in response to temperature, osmotic shock, oxidative stress and nutrient deprivation in e. coli. hence, increased rpra expression observed in our study in p. atrosepticum under nutrient starvation conditions is likely to promote the enhanced translation of rpos mrna during adaptation of bacteria to starvation conditions. ryhb a nucleotide paralogue of ryhb srna, was up-regulated by a 15-fold magnitude in p. atrosepticum under nutrient-starvation conditions. generally, ryhb, regulates iron metabolism, including its acquisition and assimilation. ryhb acts by down-regulating expression of genes encoding iron-storage and iron-using proteins when iron is in limited supply. the main target genes for ryhb include the sdhcdab operon encoding succinate dehydrogenase and sodb which encodes the iron-dependent superoxide dismutase. ryhb expression level is usually inversely correlated with expression levels of the mrna for the sdhcdab operon. this is consistent with our observations for p. atrosepticum: the transcription of the sdhcdab operon was reduced under starvation conditions compared to the growth-promoting ones.fig. the expression of the sdhcdab operon is relatively lower under starvation compared to growth promoting conditions. reads mapped from the nutrient-rich condition are represented by the red line. the blue line represents mapped reads from the starvation conditions. annotated features are labelled below the plot in blue blocks. the y-axis shows the read coverage per coding region starvation conditions also induced the expression of glmz and glmy srnas in p. atrosepticum. in enteric bacteria, these two srnas regulate amino sugar metabolism by activating the expression of glmus operon which encodes the glucosamine-6-phosphate synthase, an essential enzyme in amino sugar metabolism. the regulation by these two srnas modulates the transitions between carbon storage and carbon metabolism. the level of glmy is increased in the absence of glucosamine-6-phosphate leading to stabilization of glmz. the latter, in turn, activates glms gene expression in an anti-antisense mechanism. glms enables cells to utilize the intermediates of glycolytic pathway including the fructose-6-phosphate for production of amino sugars. the glucosamine-6-phosphate is an essential precursor for biosynthesis of essential components of the cell envelope such as peptidoglycan and lipopolysaccharide in gram-negative bacteria. thus, induction of glmy and glmz expression in p. atrosepticum under starvation conditions likely indicates the important role of the amino sugar metabolism in adaptive response on this bacterium. in summary, we have shown that several srnas are induced under nutrient-deficient compared to nutrient-rich conditions. we have also shown that induction of these srna leads to induction of various genes that potentially play a role in the survival of p. atrosepticum. in other members of the enterobacteriaceae family including e. coli and salmonella, srnas have also been shown to play an important role in adaptation to nutrient limited condition. in these bacteria, srnas provide a signal that triggers production of extracellular polysaccharides which in turn are involved in biofilm formation. although p. atrosepticum does not readily form biofilms in vitro, the overexpression of a diguanylate cyclase, induced formation of biofilms suggesting that biofilm formation in this pathogen is cryptic and can be activated under optimum conditions. part of the pathogenesis of p. atrosepticum is in xylem tissue. the xylem is typified by limited nutrients and as such a harsh environment that requires well defined methods of survival. hence, it is not surprising that many xylem dwelling phytopathogens such as xanthomonas, clavibacter, ralstonia and xylella form biofilms in xylem tissues of their respective hosts. thus, it is possible that srna are extensively involved in the adaptation of p. atrosepticum and survival in stem vasculature. identification of this suite of srna will allow us to study the role that these play in survival of this phytopathogen during stem colonisation.  in conclusion, in this study we have used a combination of strand-specific rna-sequencing and in silico approaches to detect and analyse srnas in p. atrosepticum scri we demonstrated the efficiency of ssrna-seq in detecting srnas and determining the srna expression levels in response to specific bacterial growth conditions. a total of srnas and srna candidates were experimentally detected in this study. we successfully determined srnas that may play key roles in regulating stress responses. most of the identified srnas in p. atrosepticum are conserved within the soft rot enterobacteria species suggesting their importance in physiological responses for the sre species. to our knowledge, this study constitutes the first genome/ transcriptome-wide analysis aimed at the discovery of srnas responsive to nutrient-deficiency in bacteria. a significant fraction of the unravelled srnas appeared to be starvation responsive indicative of their importance in adaptation of bacteria to stress conditions. determining the biological roles of these srnas will broaden our understanding of the diverse regulatory mechanisms they provide in modulating gene expression in p. atrosepticum and other sre species during adaptation to changing environments. 
in the study reported herein, by using strand-specific rna-seq analysis and in silico srna predictions, we describe the srna pool of pectobacterium atrosepticum and reveal numerous srna candidates, including those that are induced during starvation-activated stress responses. conservation analysis using blast showed that most of the identified srnas are conserved within the sre. subsequently, we identified novel srnas within the p. atrosepticum genome. since many of the identified srnas are starvation-induced, the results of our study suggests that srnas play key roles in bacterial adaptive response. consequently, strand-specific rna-seq enabled detection of srnas and srna candidates under starvation conditions; of these srnas were predicted for this bacterium in silico. small rnasstrand-specific rna-seqpectobacterium atrosepticumin silico predictiontranscriptomeriboswitches5′ utr3′ utrissue-copyright-statement© the author 2016 small rnas have emerged as important regulatory molecules and have been studied in several bacteria. the expression of srnas in p. atrosepticum was compared under growth-promoting and starvation conditions: srnas were differentially expressed with srnas up-regulated under nutrient-deficient conditions.
 small rnas have emerged as important regulatory molecules and have been studied in several bacteria. however, to date, there have been no whole-transcriptome studies on srnas in any of the soft rot enterobacteriaceae group of pathogens. although the main ecological niches for these pathogens are plants, a significant part of their life cycle is undertaken outside their host within adverse soil environment. however, the mechanisms of sre adaptation to this harsh nutrient-deficient environment are poorly understood.  in the study reported herein, by using strand-specific rna-seq analysis and in silico srna predictions, we describe the srna pool of pectobacterium atrosepticum and reveal numerous srna candidates, including those that are induced during starvation-activated stress responses. consequently, strand-specific rna-seq enabled detection of srnas and srna candidates under starvation conditions; of these srnas were predicted for this bacterium in silico. functional annotations were computationally assigned to srnas. the expression of srnas in p. atrosepticum was compared under growth-promoting and starvation conditions: srnas were differentially expressed with srnas up-regulated under nutrient-deficient conditions. conservation analysis using blast showed that most of the identified srnas are conserved within the sre. subsequently, we identified novel srnas within the p. atrosepticum genome.  since many of the identified srnas are starvation-induced, the results of our study suggests that srnas play key roles in bacterial adaptive response. finally, this work provides a basis for future experimental characterization and validation of srnas in plant pathogens. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords small rnasstrand-specific rna-seqpectobacterium atrosepticumin silico predictiontranscriptomeriboswitches5′ utr3′ utrissue-copyright-statement© the author 2016 