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PLoS One. 2012; 7(4): e34769.
Published online Apr 18, 2012. doi:  10.1371/journal.pone.0034769
PMCID: PMC3329508

Complete Genome and Transcriptomes of Streptococcus parasanguinis FW213: Phylogenic Relations and Potential Virulence Mechanisms

Indranil Biswas, Editor

Abstract

Streptococcus parasanguinis, a primary colonizer of the tooth surface, is also an opportunistic pathogen for subacute endocarditis. The complete genome of strain FW213 was determined using the traditional shotgun sequencing approach and further refined by the transcriptomes of cells in early exponential and early stationary growth phases in this study. The transcriptomes also discovered 10 transcripts encoding known hypothetical proteins, one pseudogene, five transcripts matched to the Rfam and additional 87 putative small RNAs within the intergenic regions defined by the GLIMMER analysis. The genome contains five acquired genomic islands (GIs) encoding proteins which potentially contribute to the overall pathogenic capacity and fitness of this microbe. The differential expression of the GIs and various open reading frames outside the GIs at the two growth phases suggested that FW213 possess a range of mechanisms to avoid host immune clearance, to colonize host tissues, to survive within oral biofilms and to overcome various environmental insults. Furthermore, the comparative genome analysis of five S. parasanguinis strains indicates that albeit S. parasanguinis strains are highly conserved, variations in the genome content exist. These variations may reflect differences in pathogenic potential between the strains.

Introduction

Streptococcus parasanguinis is a member of the viridans streptococci that constitute the major population of the oral microbial ecosystem in human. In its primary niche, the oral cavity, S. parasanguinis is one of the early colonizers of the tooth surface. The successful adherence of S. parasanguinis can serve as a substratum for the adherence of additional oral bacteria and subsequently develop into a mature biofilm called dental plaque [1], [2]. During oral trauma or surgery, oral streptococci may gain access to the bloodstream and cause transient bacteremia. Furthermore, S. parasanguinis and other viridans streptococci are the common causes of native and prosthetic heart valve endocarditis [3], [4]. Thus, the ability to evade host immune clearance is critical for the pathogenesis of S. parasanguinis.

Studies on the pathogenic factors of S. parasanguinis, in spite of its significance in the oral ecosystem and systemic infection, have been limited to two genetic loci, the fap1 gene cluster [5][8] and the fimCBA-tpx operon [9], [10] in the past. The fap1 gene cluster encodes all proteins that participate in the biogenesis of the long fimbriae which are essential for the adherence of S. parasanguinis FW213 to the hydroxyapatite discs and optimal biofilm formation [11][13]. FimA, a 36-kDa lipoprotein of the FimCBA Mn2+/Zn2+ ATP-binding cassette (ABC) transporter, is involved in the metal transport [14] and the development of infective endocarditis [15], [16]. Although the cellular location of the FimA determined by anti-FimA serum is at the tips of the long fimbriae of FW213 [9], the precise role of FimA in the adherence to host cells is yet to be defined.

The genomes of several viridans streptococci have been completed [17][21] since the completion of the Streptococcus mutans genome in 2002 [22]. The complete genome sequences not only allow for detailed analysis of the phylogenic relationship between species but also provide insights into the biology and pathogenic capacity of the streptococci. However, the validation of the genome annotation generally requires extensive analysis. The recent advances in high-throughput RNA sequencing (RNA-seq) have provided a powerful tool for genomic studies at the overall transcription level [23]. RNA-seq has been successfully used to analyze the transcriptomes in several bacteria [24][28], and the unexpected complexity of the gene structure and functional plasticity of RNA elements have been reported [24]. Additionally, RNA-seq analysis is effective in defining the operon structure, refining gene annotation, and discovering new genes and noncoding RNAs [24], [25], [27]. The newly developed Applied Biosystems SOLiD platform allows the cost-effective direct sequencing of the whole transcriptome, and the sequencing coverage of each transcript permits a quantitative comparison of the relative expression levels of interested genes [24]. Here we report the complete genome sequence, which has been refined based on the transcriptomes, of the human isolate S. parasanguinis strain FW213. Furthermore, we compare the transcriptomes of cells grown in early exponential and early stationary growth stages at single-nucleotide (nt) resolution by using the SOLiD RNA-seq method. The pH and nutrient availability differ drastically between these two growth phases, thus the results of this study also provide an overview on the physiological activity of these two stages. We propose these differences play an essential role in the survival of S. parasanguinis in its natural and alternative niches.

Results and Discussion

The general features of the S. parasanguinis FW213 genome and its basic transcriptomic structure

The basic features of the FW213 genome are listed in Fig. 1 and Table 1. This organism also possesses a cryptic plasmid, pFW213. A detailed analysis of pFW213 has been reported previously [29], and will not be discussed in this manuscript. This genome contains 84 hypothetical genes without any matches in the non-redundant protein database; 38 of them are less than 300 bp and are expressed in both the early exponential- and early stationary-phase cultures. As none of these open reading frames (ORFs) matches to the Rfam database [30], these ORFs may encode mini-proteins for various biological processes and regulation in bacteria [31]. 16 transcripts with an average sequence coverage score and a length greater than 100 bp dispersed in the GLIMMER analysis-defined intergenic regions were detected from RNA-seq analysis (Table 1). 10 of these transcripts encode proteins matched to known hypothetical proteins, one is a pseudogene, and the other 5 matched to Rfam database. Additionally, 87 possible small RNA were extracted from intergenic regions by using the integrative computational tool sRNAPredict2 [32] and further confirmed by the transcriptome analysis. Thus the transcriptome not only refines the annotation but also suggests that S. parasanguinis utilizes small RNAs to modulate gene expression.

Figure 1
Circular presentation of the S. parasanguinis FW213 chromosome.
Table 1
General features of S. parasanguinis FW213 genome.

Global transcriptomic analyses using RNA-seq confirmed that 1981 and 2007 of 2,020 ORFs were expressed in cultures at OD600 = 0.3 and OD600 = 0.8, respectively (Fig. 2A and Table S1). The expression levels of 30 randomly selected ORFs were confirmed by RT-PCR (Table S2 and Fig. S1). Among these expressed ORFs, 227 and 395 genes were up-regulated with more than a 2-fold change in RPKM values (p<0.05) in cells grown at OD600 = 0.3 and at OD600 = 0.8, respectively. As expected, most of the genes that were up-regulated in the active growth phase (OD600 = 0.3) belong to categories J (translation, ribosomal structure and biogenesis) or L (replication, recombination and repair) of the Cluster of Orthologous Groups (COG), whereas genes in categories G, E, and F that encode proteins for carbohydrate, amino acid (aa) and nt uptake and metabolism were up-regulated when approaching nutrient starvation (Fig. 2B). Similar results have been interpreted from E. coli transcriptomic analyses [33], [34]. Of note, 28 ORFs without a predicted function (category S) are up-regulated in the early exponential growth phase. The functions of these ORFs remain to be determined.

Figure 2
The global transcriptomes of S. parasanguinis at OD 600 = 0.3 and OD 600 = 0.8.

Attempts were made to determine the transcription initiation of an ORF based on the transcriptome. As an example, the transcription initiation site of Spaf_0344 was mapped to an A located at 22-base 5′ to the translation start site by primer extension analysis (Fig. 3). This result is in agreement with the transcriptomics analysis. A similar result was also observed with the fimCBA operon (data not shown). However, the initiation site for pepO predicted by the transcriptome was closer to the ATG start codon than the previous determination by primer extension analysis [14]. Previous analysis indicates that pepO transcribes from 3 sites, located at 267-, 155-, and 123-base 5′ to the translation start site, respectively. It is likely that the short half-life of the 5′ long untranslated region leads to the discrepancy between these two results. Similarly, we failed to map the end of the transcripts with confidence, presumably due to a high frequency of degradation. Based on the contiguous sequence coverage obtained from RNA-seq analysis, the operon boundaries were also determined through sharp sequence coverage changes (Fig. 4), and further confirmed by RT-PCR. The overall results suggest that there are a total of 427 polycistronic operons and 271 monocistronic genes in FW213. Moreover, different operon organizations within the same region were detected in cells in different growth phases. For instance, Spaf_0314, Spaf_0379, Spaf_0702, Spaf_1731, and Spaf_1764 were part of a polycistronic message in cells grown at OD600 = 0.8, while at the stage of OD600 = 0.3 these genes were not cotranscribed with the 3′ flanking ORF, suggesting the presence of differential expression and/or termination within an operon in response to growth phases. The presence of alternative transcripts has also been reported in Halobacterium salinarum and Mycoplasma pneumoniae [28], [35]. Taken together, these findings indicate that transcription regulation in prokaryotes is more complicated than previously thought.

Figure 3
Determination of the transcription initiation site of Spaf_0344.
Figure 4
Identification of operons based on the expression profiles.

The comparative genomic analysis of S. parasanguinis FW213 with other streptococci

Comparative genomic analysis with S. mutans UA159 (AE014133) [17], Streptococcus pneumoniae CGSP14 (CP001033) [19], Streptococcus sanguinis SK36 (CP000387) [21], Streptococcus thermophilus CNRZ1066 (CP000024) [18], Streptococcus gordonii CH1 (CP000725) [20], Streptococcus pyogenes M1 GAS (AE004092), and Streptococcus suis 05ZYH33 (CP000407) revealed that S. parasanguinis is most closely related to S. sanguinis, although large-scale rearrangements are observed between these two genomes (Fig. S2). Analysis of the orthologous genes also indicated that S. parasanguinis is more closely related to S. gordonii and S. sanguinis than to the other 5 species, consistent with the result of 16S rRNA-based phylogenetic analysis [36]. Furthermore, the genes of S. parasanguinis that are without an ortholog in S. gordonii or S. sanguinis are clustered in 3 acquired-DNA segments (Fwisland_1, Fwisland_2, and Fwisland_4). Interestingly, the 4 acquired-DNA segments (FWisland_1 to FWisland_4) reside in the same replichore (Fig. 1), which could result in lopsided genome architecture across the replication axis. The uneven distribution of the FW213 genome could lead to chromosomal inversion and translocation for stabilizing genome architecture as seen in S. pyogenes strain M3 [37].

The comparative analysis of the FW213 genome with the complete genome of S. parasanguinis ATCC15912 (CP002843), and the drafts of ATCC903 (AEVE00000000), F0405 (AEKM00000000) and SK236 (PRJNA67179) identified a total of 1,498 ORFs that are shared by all 5strains (Fig. 5). In addition to these 1,498 ORFs, FW213 shares 260, 129, 127 and 88 ORFs with strains ATCC15912, ATCC903, F0405 and SK236, respectively, suggesting that FW213 is more closely related to ATCC15912 than to the other strains. Interestingly, a cluster of genes within the proposed FW213 FWisland_1 (see below) is absent in the other 4 genomes. A close examination of the genomes of FW213 and ATCC15912 confirms the rearrangement and variation between these two strains (Fig. 6). Most significantly, both the relative location of fap1 within FWisland_3 and the deduced aa sequence of Fap1 are different between FW213 and ATCC15912, albeit both proteins contain a serine-rich motif and are of compatible sizes, suggesting that variations in the genomes, perhaps also in the pathogenic capacity, exists between S. parasanguinis strains.

Figure 5
The whole genome comparison between S. parasanguinis strains.
Figure 6
ACT visualization of the whole genome comparison based on BLAST between strains FW213 and ATCC15912.

Competence for horizontal gene transfer (HGT)

In contrast to S. sanguinis SK36, in which only 2 functional insertion sequence (IS) elements are found, there are 6 copies of IS111A, 4 copies of IS200 family transposases and 19 other transposases in the S. parasanguinis FW213 genome. Although some of them appear to be remnants without an active function, these sequences could provide sites for homologous recombination in acquisition of novel genes from related organisms via HGT, which is especially significant in a close contact population, such as the oral biofilm. This genome contains10 genes encoding apparent remnants of phage-related proteins, but is without any intact prophages, demonstrating that HGT via phage infection plays a role in the genome evolution. Interestingly, S. parasanguinis is not naturally competent for transformation, but 18 competence-specific genes that are found in naturally competent streptococcal species are present in the genome (Table S2). A close examination revealed that comC, encoding the competence-stimulating peptide (CSP), and comAB, encoding proteins for the secretion and processing of ComC, are absent in this genome. Furthermore, most of these competence-related genes are expressed at relatively low levels, which is consistent with the phenotype.

Genomic islands (GIs)

Based on the GC content, 4 possible GIs termed Fwisland_1 to 4 are identified in the FW213 genome (Fig. 1, Table 2). An additional Fwisland_5 is mined through annotation. Sequence and annotation analyses of these islands revealed that these GIs contain known or putative virulence genes and mobility genes (Tables S3, S4, S5, S6, S7). The expression and potential impact of these islands in the physiology and pathogenesis of S. parasanguinis are discussed below.

Table 2
Properties of the genomic islands in S. parasanguinis FW213.

i. FWisland_1: the salivaricin B and nisin secretion GI

Fwisland_1 contains mosaic mobile elements resembling the conjugative transposon Tn5253 [38], which is a composite of Tn5251 and Tn5252, with former inserted in the latter (Table S4). Although some of the main components such as ermAM and tetM of Tn5253 are absent in FW213, some lantibiotic related genes are included. The first transposon (Spaf_1090 to Spaf_1100 and Spaf_1119 to Spaf_1138) harbors the partial lantibiotic nisin biosynthesis operon [39], indicating that this region has undergone deletion during evolution and S. parasanguinis may not produce nisin. The second transposon (Spaf_1101 to Spaf_1118), harbors two operons of the sboB locus for the lantibiotic salivaricin B (SboB) production [40]. The first operon (sboKR) encodes a putative two component system, and the second operon comprises genes encoding the SboB pre-peptide (encoded by sboA) and the immunity proteins (encoded by sboFEG). Genes encoding the Tn5252 relaxase and a putative conjugative transposase are also located within this region. On the other hand, genes encoding proteins for transportation (sboT) and modification (sboM) of SboB are absent in S. parasanguinis. It remains possible that S. parasanguinis FW213 modifies and exports SboB by an unknown system other than SboM and SboT. Interestingly, the sboFEG, together encoding the subtilin immunity exporter, and the TraG/TraD family protein are also found in this island, which may provide an alternative secretion mechanism for SboB in S. parasanguinis. As shown in Fig. 7A, all sbo genes were expressed in both growth conditions although the overall coverage of FWisland_1 was generally low, especially in early exponential growth. It has been predicted that the production of bacteria inhibitory substances may provide advantages within a complex ecosystem, such as dental plaque. Thus an up-regulation of this island in the early exponential growth phase may reflect the physiological needs of S. parasanguinis in the oral cavity.

Figure 7
Schematic representation of the putative GIs and their expression in S. parasanguinis FW213.

ii. FWisland_2: the putative bacterocin production GI

This island includes genes encoding proteins for a putative lactococcin production (Table S5). All genes within the island are expressed at both stages of growth (Fig. 7B). Interestingly, the expression of genes encoding the lactococcin 972 type bacteriocin (Spaf_1859) and an ATP-binding cassette (ABC) transporter (Spaf_1860 and Spaf_1861) are up-regulated 3- and 6-fold, respectively, in cells at OD600 = 0.8. A similar expression pattern has been observed in the lclAB operon of Lactococcus lactis PILA972, which encodes the lactococcin 972 and immunity protein [41]. It is tempting to suggest that FW213 also produces a lactococcin-related bacteriocin, and the production is modulated by the growth phase.

iii. FWisland_3: the fimbriae encoding and maturation GI

Genes encoding the structure subunit of the long fimbriae, fap1, and all enzymes required for the maturation and presentation of the fimbriae are clustered within a 23.9-kp region, designated FWisland_3 (Table S6). Extensive analysis on this island has been previously reported [7], [8]. Homologues of fap1 and organization of the flanking ORFs are also observed in other oral streptococci such as S. gordonii CH1 [20] and S. sanguinis SK36 [21], indicating that the biogenesis and glycosylation of the Fap1-like proteins are highly conserved throughout evolution. All genes of this island were expressed at both growth stages (Fig. 7C), and were up-regulated at OD600 = 0.8, confirming the impact of the long fimbriae in the biofilm lifestyle [13]. It is also noticed that the expression of fap1, encoding the subunit of the long fimbriae, is at relative high levels at both stages, with a 2.8-fold increase at early stationary stage. The up-regulation of FWisland_3 expression and conceivably higher fimbriae presentation shall enhance the biofilm formation of S. parasanguinis in the late exponential growth phase, when the biofilm lifestyle may provide better advantages for survival.

iv. FWisland_4: the extracellular polysaccharides (EPS) and capsule polysaccharide (CPS) production GI

EPS production plays an essential role in the adherence and initiation of bacterial endocarditis [42], [43]. The EPS production is also associated with endocardial vegetation mediated by many viridans streptococci [44]. FWisland_4 (Table S7) encodes proteins that share strong homology with the protein products of S. pneumoniae Type 19F cpsA-K genes [45], while only cpsA, cpsB, cpsC, cpsD, cpsE and cpsG are present in S. sanguinis and S. gordonii. This GI also encodes glycosyltransferases (Spaf_2008 and Spaf_2009) and a putative phosphotransferase (Spaf_2004). Homologs of the cps19fL, cps19fO, cps19fN, and cps19fM which are involved in the biosynthesis of dTDP-L-rhamnose in S. pneumoniae capsule production are found elsewhere in the FW213 genome (Spaf_1350 to 1352 and Spaf_0821). Together, it is suggested that the products of FWisland_4 participate in the biogenesis and export of EPS and that the repeat unit of polysaccharide structure is similar to that of S. pneumoniae type 19F capsular polysaccharide. All genes in this island are expressed at moderate levels at both growth conditions (Fig. 7D), and all EPS production-related genes were up-regulated on average 4-fold in early stationary versus early exponential phase of growth. The polysaccharide capsule constitutes the outermost layer of the cell, and its role in adherence, biofilm formation, and resistant to host phagocytic activity is well documented [46]. The expression of this island may provide basic protection against host immune clearance, and an up-regulation in the late exponential growth phase may further promote the biofilm formation of S. parasanguinis.

v. FWisland_5: the adc operon

FWisland_5 contains ORFs homologous to known transcriptional regulators, a phosphoglycerate mutase and the adc operon consisting of a adcR, adcC, adcB, and adcA (Table S8). Gene adcR encodes a putative transcriptional repressor for Zn2+/Mn2+-responsive expression, and adcCBA together encode a putative Zn2+/Mn2+-specific ABC transporter. Furthermore, the histidine-rich metal-binding domain was found in AdcR and AdcA of S. parasanguinis FW213. Thus, the adcRCBA operon may play an important role in Zn2+ and/or Mn2+ uptake in S. parasanguinis FW213. It is also noticed that the expression of the adc operon was up-regulated 3-fold in cells grown at OD600 = 0.8 (Fig. 7E), similar to the regulation by AdcR in S. gordonii [47]. It was proposed that, in addition to maintaining the intracellular metal homeostasis, AdcR may act as a signal to modulate biofilm formation [48]. As S. gordonii and S. parasanguinis occupy the same habitat in the oral cavity and both cause subacute endocarditis, it is likely that the Adc system plays a similar role in S. parasanguinis.

Genes encoding proteins that modulate oxidative stress responses, the pathogenicity for endocarditis, host cell lysis, cell wall integrity and osmotic stress responses are induced in the early exponential growth phase

To reach the heart valve successfully and establish infection, S. parasanguinis has to evade innate host defenses. An examination of the FW213 genome reveals genes encoding superoxide dismutase (Spaf_0708), thioredoxin (Spaf_0302, Spaf_0423, Spaf_1008 and Spaf_1295), thioredoxin reductase (Spaf_0208 and Spaf_0772), and glutathione peroxidase (Spaf_1379). With the exception of Spaf_0208 and Spaf_0423, all genes were up-regulated in cells at OD600 = 0.3 (Table 3). Furthermore, two putative Spx proteins (Spaf_2030 and Spaf_2069), an activator for RNA polymerase under thiol-specific oxidative stress condition [49], were also up-regulated at this stage of growth. Thus, it is possible that the expression of the above genes and the regulation by Spx play a role in early exponential phase of growth.

Table 3
Potential virulence factors for the early exponential growth phase in S. parasanguinis FW213.

A greater than 3-fold increase in the expression of fimCBA was detected in cells grown at OD600 = 0.3 compared to cells of OD600 = 0.8 (Table 3). The binding of FW213 to fibrin monolayers via FimA is essential for the development of endocarditis by S. parasanguinis [15], and the up-regulation of the fim operon at this stage could enhance the colonization of S. parasanguinis to the damaged heart valves. It is interesting to note, the expression pattern of the fim operon is opposite that of the adc operon. Since both the Fim and the Adc systems recognize low and high concentrations of extracellular manganese, respectively, the coordinated regulation of these two systems would ensure an adequate acquisition of essential metal ions for all cell activities.

The annotation also led to the discovery of 3 putative hemolysins (Table 3), two of which (Spaf_1208 and Spaf_1675) are up-regulated in early exponential growth. As the expression of these two proteins is the highest among the three, Spaf_1208 and Spaf_1675 may be associated with the development of bacteremia.

Spaf_0018, Spaf_1442, and Spaf_2091, encoding enzymes catalyze cell-wall digestion, are up-regulated in the early exponential growth phase (Table 3). Spaf_0018 contains a C-terminal DivIC domain required for septum formation and a N-terminal CHAP domain that corresponds to amidase function. Studies on the homologues in S. pneumoniae [50] and S. mutans [51] indicate that this protein participates in cell-wall biosynthesis and cell division. As this ORF is essential for survival in most bacterial species, functional studies were limited. On the other hand, Spaf_1442 is a putative glycosyl hydrolase for cell wall structure, and studies on the homologues reveal that this ORF mediates both cell-wall metabolism and essential cell activity such as biofilm formation. As demonstrated in Staphylococcus epidermidis [52], Lactococcus lactis [53] and S. mutans [54], the peptidoglycan hydrolase activity is essential for optimal biofilm formation. Thus, the up-regulation of Spaf_1442 in the early exponential growth phase may enhance the initial attachment of S. parasanguinis to the tooth surface as well as host tissue. Spaf_2091 is a homolog of IsaA of Staph. aureus [55], a suggested soluble lytic transglycosylase. IsaA modulates the overall virulence of Staph. aureus by altering the peptidoglycan structure [56]. Spaf_2091 is highly expressed at the early exponential growth phase (Table 3), and thus it is possible that this protein plays a similar role in the early stage of endocarditis infection.

Interestingly, genes encoding the putative conductance mechanosensitive (MS) channels (Spaf_0774 and Spaf_1806) express at relative high levels in the early exponential growth phase, and a 3-fold reduction was detected when cells reached stationary phase. This expression pattern is opposite to the MscS and MscL pattern found in E. coli [57], where an up-regulation in the stationary phase is detected. As MS channels are required for the survival of osmotic stress, it is peculiar that S. parasanguinis expresses these genes at high levels in the early growth phase. Additionally, a relatively high level of expression was seen in genes encoding the trehalose-specific EIIAB (Spaf_1559) and the trehalose-6 phosphate hydrolase (Spaf_1558) in the early growth phase. Trehalose is a compatible solute that accumulates intracellularly upon osmotic stress [58] and the expression of trehalose PTS in S. mutans only occurs in the presence of the substrate [59]. Taken together, systems that are commonly known to participate in osmotic stress may have a very different role in the physiology of S. parasanguinis.

ORFs participate in the acid tolerance response (ATR), alcohol metabolism, extracellular matrix (ECM) binding, and peptide digestion are up-regulated in the early stationary growth phase

ATR is one of the hallmarks for survival in the oral streptococci. A number of mechanisms contributing to the aciduric response have been identified in S. mutans [60], [61]. Genes encoding a functional F-ATPase (H+-translocating ATPase), the primary factor for maintaining cytoplasmic pH homeostasis in oral streptococci [60], are arranged as an operon in the FW213 genome (Spaf_0740 to Spaf_0747). The expression of this operon is moderately up-regulated in cells grown at OD600 = 0.8. The pH value of S. parasanguinis cultures at OD600 = 0.3 is around 6.8, whereas cultures at OD600 = 0.8 is at 5.5–5.6, thus the up-regulation of the atp operon at OD600 = 0.8 confirms the role of ATPase in pH homeostasis (Table 4). Furthermore, the arc operon encoding the arginine deiminase system (ADS) that provides competitive fitness for survival at sub-lethal acidic pH by concomitant production of NH3 and ATP in Streptococcus rattus and S. gordonii [62], [63] is located in the FW213 genome (Spaf_0712 to Spaf_0718). The expression of ADS in S. gordonii is regulated by multiple environmental factors, and the expression is enhanced in the stationary growth phase [64]. Similarly, the expression of the arc operon in FW213 was up regulated in cells grown at OD600 = 0.8, suggesting that the ADS also participates in the ATR of S. parasanguinis.

Table 4
Potential virulence factors that are up-regulated in the early stationary phase in S. parasanguinis FW213.

A total of 7 alcohol dehydrogenase (ADH) homologues are identified in the FW213 genome and 5 of them are up-regulated at the early stationary phase (Table 4) whereas the other two (Spaf_0456 and Spaf_1747) are not regulated by growth phases. It is peculiar as only 3 and 4 ADHs are found in the S. gordonii CH1 and S. sanguinis SK36 genomes, respectively. It has been suggested by Kurkivuori and colleagues that the conversion of ethanol to carcinogenic acetaldehyde by bacterial ADH in the oral cavity may promote the development of oral cancer [65]. Thus, the multiple ADHs and relatively abundant expression, especially at early stationary phase, may contribute to not only energy generation but also the development of other oral diseases.

S. parasanguinis FW213 possesses 3 collagen-binding protein (CBP) homologues (Spaf_0420, Spaf_1570 and Spaf_1943), one fibronectin-binding protein homologue (Spaf_1409), and a collagen-binding domain containing surface protein (Spaf_1943). The expression of all 3 CBP homologues and Spaf_1943 were up-regulated at OD600 = 0.8 by more than 2-fold, whereas an 1.8-fold increase in expression was observed with Spaf_1409 at the same growth stage, indicating that FW213 possess a strong affinity for ECM molecules. The function of Spaf_1943 in bacterial autoaggregation and biofilm formation has been demonstrated recently [66], further supporting the pathogenic role of this ORF in both the oral cavity as well as on heart valves.

3 serine protease (Spaf_0194, Spaf_1710 and Spaf_1711) of the Subtilisin family are identified in FW213. Although only low levels of expression were observed with all 3 ORFs, significant induction was detected in the early stationary phase (Table 4). Previous studies indicate that the production of Challisin by S. gordonii, a homologue of Subtilisin, can interfere with the colonization of S. mutans in a two-species biofilm system by inactivation of S. mutans CSP [67]. Thus, the optimal expression of these serine proteases by FW213 in the later stage of growth may provide competitive advantages for the bacteria within the complex oral ecosystem.

Other potential virulence factors

The genome also revealed potential virulence traits including drug and metal resistance (Table 5). A copy of aph (Spaf_0881) and of aadK (Spaf_0970) encoding the aminoglycoside phosphotransferase and aminoglycoside adenylyltransferase, respectively, are found in the FW213 genome; the expression of these genes may count for the relative high minimal inhibitory concentrations (MICs) for aminoglycosides in S. parasanguinis FW213. ORFs potentially encoding resistance for β-lactam (Spaf_0010) and bacitracin (Spaf_0519) are also found in the genome. Furthermore, outside the GIs described above, the FW213 genome contains 3 genes encoding putative cation-driven multidrug efflux systems and 14 genes encoding putative ABC-type multidrug transporters; all of which are expressed at moderate to high levels (data not shown), indicating that this microbe possess a strong defense system.

Table 5
Additional virulence factors.

A cadDX cassette (Spaf_0449 and Spaf_0450) that confers resistance to cadmium and zinc in S. salivarius 57.I [68] is also present in the FW213 genome, suggesting that FW213 possesses relatively high MICs for these two metals. Furthermore, both ORFs Spaf_0788 and Spaf_1749 share significant homologies with the cation efflux proteins for cobalt-zinc-cadmium resistance, and both are highly activated in the late exponential growth phase (Table 5). Together, it is predicted that FW213 is relatively resistant to heavy metal killing.

The study by Vriesema and colleagues suggests that the expression of msrA [69], encoding methionine sulfoxide reductase, modulates the virulence potential of S. gordonii CH1 in the development of endocarditis by enhancing the growth and oxidative stress capacity. The msrA homologues (Spaf_1798) in FW213 expressed well at both growth conditions (Table 5). Whether this ORF also plays a similar role in the disease development requires further analysis. On the other hand, the expression of Spaf_1788, encoding pyruvate oxidase for H2O2 production under aerobic growth [70], was highly activated at the early stationary phase. It has been demonstrated that S. sanguinis and S. gordonii compete effectively against S. mutans by H2O2 production [70]. Thus, this locus is likely to provide a similar advantage for FW213 within oral biofilm.

Conclusions

The genome and expression analysis of S. parasanguinis FW213 provide basic information on the physiology and potential pathogenic capacity of this bacterium. The comparative genomics and phylogenetic analysis indicate that this genome is shaped by chromosomal inversion, recombination and HGT events. All putative virulence genes, both within the GIs and elsewhere on the chromosome equip this microbe to maintain an ecological niche in dental plaque, escape from host defense and establish infection in heart valves. Ultimately, the availability of the complete FW213 genome sequence will facilitate further studies of this pathogen and the development of diagnostics and vaccines.

Materials and Methods

Strain and growth conditions

S. parasanguinis FW213, an isolate of human dental plaque [71], was chosen for this study for reasons listed below. First, FW213 is a frequent isolate of the dental plaque. Second, the infectivity of FW213 in subacute endocarditis has been well established in an animal model [15]. Third, the Fap1 of FW213 is a model system for studying Gram-positive bacterial protein glycosylation and the role of glycosylation in bacterial pathogenesis. Finally, FW213 possesses a cryptic plasmid that is not reported in other S. parasanguinis strains. To prepare total cellular DNA or RNA from S. parasanguinis FW213, bacteria were grown in Todd-Hewitt (Difco) broth at 37°C, in a 10% CO2 atmosphere. Total cellular DNA was isolated from the mid-exponential (OD600 = 0.6) phase culture as described previously [72]. Total cellular RNA was isolated from the early exponential (OD600 = 0.3) and early stationary (OD600 = 0.8) growth phases as described previously [73].

Genome sequencing and annotation

Genome sequencing was performed using the whole genome shotgun strategy [74]. Briefly, total cellular DNA was mechanically sheared and end-repaired by using T4 DNA polymerase (NEB). 4 libraries containing sheared DNA fragments of various lengths (1.5 to 2 kb, 2 to 3 kb, 4 to 5 kb, and 6 kb) were constructed in pUC18. The nt sequences of the library inserts were determined by using the ET terminator chemistry on an ABI 3700 sequencer (Applied Biosystems) and a MegaBACE 1000 sequencer (Amersham Bioscience). Sequences were assembled and edited using PHRED, PHRAP and CONSED (http://www.phrap.org/phredphrapconsed.html). Gaps were closed by primer walking, long-distance PCR and optimized multiplex PCR [75]. Sequences of the reads in low quality regions were resequenced to ensure the accuracy. We acquired usable shotgun-sequencing traces with an average length of 529 bp, resulting in an 8.84-fold sequence coverage. The complete genome sequence of S. parasanguinis FW213 has been deposited in the GenBank database with the accession number CP003122.

The start point of the FW213 genome base numbering is set at the replication origin (oriC) which is identified by the GC-skew analysis and Ori-Finder software [76]. ORFs were predicted initially with GLIMMER 2.0 [77] at the default settings with a cutoff at 90 nt. Predicted ORFs were validated with translational start codon assignment based on protein homology and ribosomal binding motifs [78]. The deduced aa sequence of each ORF was then BLASTP searched against the nonredundant database of GenBank and the “true proteins” (80% overlapping, E_value<1e−10) were extracted. The remaining ORFs and intergenic sequences were BLASTX searched against the nonredundant database and “true ORFs” (the same criteria as above) were identified. The problematic cases such as overlapping proteins were resolved according to the principle described previously [79], [80]. The function of each protein is predicted by searching against the KEGG pathway database [81], the COG database [82] and the InterPro protein family database [83], [84]. Transfer RNAs were predicted with tRNAscan-SE [85], and ribosomal RNAs (rRNAs) were identified based on the similarity to the corresponding genes of other streptococcal genomes. The final annotation was manually inspected by integrating comprehensively the genome annotation and transcriptomic results to further refine the structure of the predicted genes and annotation.

Comparative genomic analysis

Whole genome sequences alignments of the streptococcal strains were constructed by using the MUMmer package [86]. The orthologs were identified by Inparanoid and MultiParanoid [87]. The ClustalX software [88] was used to align the concatenated sequences from all orthologs. The Artemis Comparison Tool (ACT) [89] was used to view the overall comparison of S. parasanguinis FW213 and ATCC15912 genomes.

SOLiD RNA-seq library construction, sequencing and mapping

The isolated RNA was treated with DNase I and further purified by using RNeasy Kits (Qiagen) to remove residual chromosome. The rRNA was depleted from the sample based on the standard protocols from RiboMius™ Transcriptome Isolation Kits (Invitrogen). The library construction and sequencing were performed followed the standard protocols from SOLiD™ Small RNA Expression Kit (ABI). Only reads with a quality value greater than 8 were selected and used in the mapping. The selected reads were mapped to the S. parasanguinis FW213 genome by using the SOLiD™ System Analysis Pipeline Tool (Corona Lite) allowing mismatches up to 5 bases. The first 45 bases of the unmapped reads were then again used in the second-run mapping. This process was repeated one more time with the first 40 bases of the unmapped reads. rRNA reads were filtered prior to the mapping.

Gene expression analysis

The expression level of a given gene was evaluated by read counts normalized with the total mapped reads and gene length with the RPKM method [90]. The differential expressions of genes between two libraries were analyzed based on the IDEG6 modeling methods [91] and further confirmed by reverse transcription (RT)-PCR. The differentially expressed genes were sorted into 18 cellular functional groups according to the COG database [82]. To determine the transcription initiation site of Spaf_0344, 50 µg of total RNA was hybridized with the IRD-800 labeled primer scaRAS9650 (5′-CATGCGACTGGCGATTTCCTTATTACT) at 42°C for 90 min, followed by RT. The extended products were analyzed alongside a DNA sequencing reaction using the same primer on a 9% gel, and signals were detected on a LI-COR DNA sequencer (model 4000L).

Operon identification and confirmation

The genome wide strand-specific sequencing coverage was generated with perl scripts based on the results of unique mapping reads. The operon boundaries are defined based on sharp sequencing coverage transitions (greater than a 2-fold difference) between two neighboring genes that are greater than 100 bp apart and are in the same transcription orientation. The adjacent genes located on the complementary strands were considered as members of two operons. The predicted operon boundaries are confirmed by RT-PCR. Specifically, within an operon, the contiguous transcript between two genes with an intergenic region greater than 100 bp was further confirmed by end-point RT-PCR. That two genes with an intergenic region that are less (and equal to) 100 bp and yet were assigned in two separate operons was also checked by RT-PCR.

Supporting Information

Figure S1

Comparison of RT-PCR and transcriptome results. The best-fit line is shown. The two data sets showed a correlation coefficient (R) of 0.86.

(TIF)

Figure S2

The whole genome alignments of S. parasanguinis FW213 (X-axis) with the genomes of 7 streptococcal species (Y-axis), respectively. Mummer-based genomic display of S. parasanguinis FW213 genome pairing with the genome of (A) S. sanguinis SK36, (B) S. gordonii CH1, (C) S. pneumoniae CGSP14, (D) S. mutans UA159, (E) S. pyogenes M1 GAS, (F) S. suis 05ZYH33, and (G) S. thermophilus CNRZ1066. The forward matches are displayed in red, and the reverse matches are in cobalt blue.

(TIF)

Table S1

The RPKM values of all genes in cultures at OD600 = 0.3 and OD600 = 0.8.

(XLS)

Table S2

Confirmation of expression analysis of RNA-seq by RT-PCR.

(DOC)

Table S3

The competence-related genes and their expression in S. parasanguinis FW213.

(DOC)

Table S4

The features and expression of FWisland_1.

(DOC)

Table S5

The features and expression of FWisland_2.

(DOC)

Table S6

The features and expression of FWisland_3.

(DOC)

Table S7

The features and expression of FWisland_4.

(DOC)

Table S8

The features and expression of FWisland_5.

(DOC)

Acknowledgments

We thank P. Fives-Taylor for review of this manuscript, and S. Liang for excellent technical assistance.

Footnotes

Competing Interests: The authors have declared that no competing interests exist.

Funding: This study was supported by the Chang Gung Memorial Hospital grants CMRPG371602 and CMPRD1A0451. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1. Gibbons RJ, Houte JV. Bacterial adherence in oral microbial ecology. Annu Rev Microbiol. 1975;29:19–44. [PubMed]
2. Kolenbrander PE. Oral microbial communities: biofilms, interactions, and genetic systems. Annu Rev Microbiol. 2000;54:413–437. [PubMed]
3. Lutwick LI, Vaghjimal A, Connolly MW. Postcardiac surgery infections. Crit Care Clin. 1998;14:221–250. [PubMed]
4. van der Meer JT, van Vianen W, Hu E, van Leeuwen WB, Valkenburg HA, et al. Distribution, antibiotic susceptibility and tolerance of bacterial isolates in culture-positive cases of endocarditis in The Netherlands. Eur J Clin Microbiol Infect Dis. 1991;10:728–734. [PubMed]
5. Wu H, Fives-Taylor PM. Identification of dipeptide repeats and a cell wall sorting signal in the fimbriae-associated adhesin, Fap1, of Streptococcus parasanguis. Mol Microbiol. 1999;34:1070–1081. [PubMed]
6. Wu H, Mintz KP, Ladha M, Fives-Taylor PM. Isolation and characterization of Fap1, a fimbriae-associated adhesin of Streptococcus parasanguis FW213. Mol Microbiol. 1998;28:487–500. [PubMed]
7. Wu H, Bu S, Newell P, Chen Q, Fives-Taylor P. Two gene determinants are differentially involved in the biogenesis of Fap1 precursors in Streptococcus parasanguis. J Bacteriol. 2007;189:1390–1398. [PMC free article] [PubMed]
8. Wu H, Zeng M, Fives-Taylor P. The glycan moieties and the N-terminal polypeptide backbone of a fimbria-associated adhesin, Fap1, play distinct roles in the biofilm development of Streptococcus parasanguinis. Infect Immun. 2007;75:2181–2188. [PMC free article] [PubMed]
9. Fenno JC, Shaikh A, Spatafora G, Fives-Taylor P. The fimA locus of Streptococcus parasanguis encodes an ATP-binding membrane transport system. Mol Microbiol. 1995;15:849–863. [PubMed]
10. Spatafora G, Van Hoeven N, Wagner K, Fives-Taylor P. Evidence that ORF3 at the Streptococcus parasanguis fimA locus encodes a thiol-specific antioxidant. Microbiology. 2002;148:755–762. [PubMed]
11. Fachon-Kalweit S, Elder BL, Fives-Taylor P. Antibodies that bind to fimbriae block adhesion of Streptococcus sanguis to saliva-coated hydroxyapatite. Infect Immun. 1985;48:617–624. [PMC free article] [PubMed]
12. Fives-Taylor PM, Thompson DW. Surface properties of Streptococcus sanguis FW213 mutants nonadherent to saliva-coated hydroxyapatite. Infect Immun. 1985;47:752–759. [PMC free article] [PubMed]
13. Froeliger EH, Fives-Taylor P. Streptococcus parasanguis fimbria-associated adhesin fap1 is required for biofilm formation. Infect Immun. 2001;69:2512–2519. [PMC free article] [PubMed]
14. Oetjen J, Fives-Taylor P, Froeliger EH. The divergently transcribed Streptococcus parasanguis virulence-associated fimA operon encoding an Mn(2+)-responsive metal transporter and pepO encoding a zinc metallopeptidase are not coordinately regulated. Infect Immun. 2002;70:5706–5714. [PMC free article] [PubMed]
15. Burnette-Curley D, Wells V, Viscount H, Munro CL, Fenno JC, et al. FimA, a major virulence factor associated with Streptococcus parasanguis endocarditis. Infect Immun. 1995;63:4669–4674. [PMC free article] [PubMed]
16. Viscount HB, Munro CL, Burnette-Curley D, Peterson DL, Macrina FL. Immunization with FimA protects against Streptococcus parasanguis endocarditis in rats. Infect Immun. 1997;65:994–1002. [PMC free article] [PubMed]
17. Bolotin A, Quinquis B, Renault P, Sorokin A, Ehrlich SD, et al. Complete sequence and comparative genome analysis of the dairy bacterium Streptococcus thermophilus. Nat Biotechnol. 2004;22:1554–1558. [PubMed]
18. Ding F, Tang P, Hsu MH, Cui P, Hu S, et al. Genome evolution driven by host adaptations results in a more virulent and antimicrobial-resistant Streptococcus pneumoniae serotype 14. BMC Genomics. 2009;10:158. [PMC free article] [PubMed]
19. Vickerman MM, Iobst S, Jesionowski AM, Gill SR. Genome-wide transcriptional changes in Streptococcus gordonii in response to competence signaling peptide. J Bacteriol. 2007;189:7799–7807. [PMC free article] [PubMed]
20. Xu P, Alves JM, Kitten T, Brown A, Chen Z, et al. Genome of the opportunistic pathogen Streptococcus sanguinis. J Bacteriol. 2007;189:3166–3175. [PMC free article] [PubMed]
21. Geng J, Huang SC, Li S, Hu S, Chen YY. Complete genome sequence of the ureolytic Streptococcus salivarius strain 57.I. J Bacteriol. 2011;193:5596–5597. [PMC free article] [PubMed]
22. Ajdic D, McShan WM, McLaughlin RE, Savic G, Chang J, et al. Genome sequence of Streptococcus mutans UA159, a cariogenic dental pathogen. Proc Natl Acad Sci U S A. 2002;99:14434–14439. [PMC free article] [PubMed]
23. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63. [PMC free article] [PubMed]
24. Passalacqua KD, Varadarajan A, Ondov BD, Okou DT, Zwick ME, et al. Structure and complexity of a bacterial transcriptome. J Bacteriol. 2009;191:3203–3211. [PMC free article] [PubMed]
25. Yoder-Himes DR, Chain PS, Zhu Y, Wurtzel O, Rubin EM, et al. Mapping the Burkholderia cenocepacia niche response via high-throughput sequencing. Proc Natl Acad Sci U S A. 2009;106:3976–3981. [PMC free article] [PubMed]
26. Wurtzel O, Sapra R, Chen F, Zhu Y, Simmons BA, et al. A single-base resolution map of an archaeal transcriptome. Genome Res. 2010;20:133–141. [PMC free article] [PubMed]
27. Perkins TT, Kingsley RA, Fookes MC, Gardner PP, James KD, et al. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet. 2009;5:e1000569. [PMC free article] [PubMed]
28. Guell M, van Noort V, Yus E, Chen WH, Leigh-Bell J, et al. Transcriptome complexity in a genome-reduced bacterium. Science. 2009;326:1268–1271. [PubMed]
29. Chen YY, Shieh HR, Lin CT, Liang SY. Properties and construction of plasmid pFW213, a shuttle vector with the oral Streptococcus origin of replication. Appl Environ Microbiol. 2011;77:3967–3974. [PMC free article] [PubMed]
30. Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, et al. Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 2005;33:D121–124. [PMC free article] [PubMed]
31. Wang F, Xiao J, Pan L, Yang M, Zhang G, et al. A systematic survey of mini-proteins in bacteria and archaea. PLoS One. 2008;3:e4027. [PMC free article] [PubMed]
32. Livny J, Fogel MA, Davis BM, Waldor MK. sRNAPredict: an integrative computational approach to identify sRNAs in bacterial genomes. Nucleic Acids Res. 2005;33:4096–4105. [PMC free article] [PubMed]
33. Selinger DW, Cheung KJ, Mei R, Johansson EM, Richmond CS, et al. RNA expression analysis using a 30 base pair resolution Escherichia coli genome array. Nat Biotechnol. 2000;18:1262–1268. [PubMed]
34. Yoon SH, Han MJ, Lee SY, Jeong KJ, Yoo JS. Combined transcriptome and proteome analysis of Escherichia coli during high cell density culture. Biotechnol Bioeng. 2003;81:753–767. [PubMed]
35. Koide T, Reiss DJ, Bare JC, Pang WL, Facciotti MT, et al. Prevalence of transcription promoters within archaeal operons and coding sequences. Mol Syst Biol. 2009;5:285. [PMC free article] [PubMed]
36. Kawamura Y, Hou XG, Sultana F, Miura H, Ezaki T. Determination of 16S rRNA sequences of Streptococcus mitis and Streptococcus gordonii and phylogenetic relationships among members of the genus Streptococcus. Int J Syst Bacteriol. 1995;45:406–408. [PubMed]
37. Nakagawa I, Kurokawa K, Yamashita A, Nakata M, Tomiyasu Y, et al. Genome sequence of an M3 strain of Streptococcus pyogenes reveals a large-scale genomic rearrangement in invasive strains and new insights into phage evolution. Genome Res. 2003;13:1042–1055. [PMC free article] [PubMed]
38. Ayoubi P, Kilic AO, Vijayakumar MN. Tn5253, the pneumococcal omega (cat tet) BM6001 element, is a composite structure of two conjugative transposons, Tn5251 and Tn5252. J Bacteriol. 1991;173:1617–1622. [PMC free article] [PubMed]
39. Kuipers OP, Beerthuyzen MM, de Ruyter PG, Luesink EJ, de Vos WM. Autoregulation of nisin biosynthesis in Lactococcus lactis by signal transduction. J Biol Chem. 1995;270:27299–27304. [PubMed]
40. Hyink O, Wescombe PA, Upton M, Ragland N, Burton JP, et al. Salivaricin A2 and the novel lantibiotic salivaricin B are encoded at adjacent loci on a 190-kilobase transmissible megaplasmid in the oral probiotic strain Streptococcus salivarius K12. Appl Environ Microbiol. 2007;73:1107–1113. [PMC free article] [PubMed]
41. Martinez B, Fernandez M, Suarez JE, Rodriguez A. Synthesis of lactococcin 972, a bacteriocin produced by Lactococcus lactis IPLA 972, depends on the expression of a plasmid-encoded bicistronic operon. Microbiology. 1999;145(Pt 11):3155–3161. [PubMed]
42. Ramirez-Ronda CH. Adherence of glucan-positive and glucan-negative streptococcal strains to normal and damaged heart valves. J Clin Invest. 1978;62:805–814. [PMC free article] [PubMed]
43. Ramirez-Ronda CH. Effects of molecular weight of dextran on the adherence of Streptococcus sanguis to damaged heart valves. Infect Immun. 1980;29:1–7. [PMC free article] [PubMed]
44. Mills J, Pulliam L, Dall L, Marzouk J, Wilson W, et al. Exopolysaccharide production by viridans streptococci in experimental endocarditis. Infect Immun. 1984;43:359–367. [PMC free article] [PubMed]
45. Morona JK, Morona R, Paton JC. Characterization of the locus encoding the Streptococcus pneumoniae type 19F capsular polysaccharide biosynthetic pathway. Mol Microbiol. 1997;23:751–763. [PubMed]
46. Roberts IS. The biochemistry and genetics of capsular polysaccharide production in bacteria. Annu Rev Microbiol. 1996;50:285–315. [PubMed]
47. Loo CY, Mitrakul K, Voss IB, Hughes CV, Ganeshkumar N. Involvement of the adc operon and manganese homeostasis in Streptococcus gordonii biofilm formation. J Bacteriol. 2003;185:2887–2900. [PMC free article] [PubMed]
48. Aanensen DM, Mavroidi A, Bentley SD, Reeves PR, Spratt BG. Predicted functions and linkage specificities of the products of the Streptococcus pneumoniae capsular biosynthetic loci. J Bacteriol. 2007;189:7856–7876. [PMC free article] [PubMed]
49. Nakano S, Kuster-Schock E, Grossman AD, Zuber P. Spx-dependent global transcriptional control is induced by thiol-specific oxidative stress in Bacillus subtilis. Proc Natl Acad Sci U S A. 2003;100:13603–13608. [PMC free article] [PubMed]
50. Giefing-Kroll C, Jelencsics KE, Reipert S, Nagy E. Absence of pneumococcal PcsB is associated with overexpression of LysM domain-containing proteins. Microbiology. 2011;157:1897–1909. [PubMed]
51. Mattos-Graner RO, Porter KA, Smith DJ, Hosogi Y, Duncan MJ. Functional analysis of glucan binding protein B from Streptococcus mutans. J Bacteriol. 2006;188:3813–3825. [PMC free article] [PubMed]
52. Heilmann C, Hussain M, Peters G, Gotz F. Evidence for autolysin-mediated primary attachment of Staphylococcus epidermidis to a polystyrene surface. Mol Microbiol. 1997;24:1013–1024. [PubMed]
53. Mercier C, Durrieu C, Briandet R, Domakova E, Tremblay J, et al. Positive role of peptidoglycan breaks in lactococcal biofilm formation. Mol Microbiol. 2002;46:235–243. [PubMed]
54. Ahn SJ, Burne RA. The atlA operon of Streptococcus mutans: role in autolysin maturation and cell surface biogenesis. J Bacteriol. 2006;188:6877–6888. [PMC free article] [PubMed]
55. Sakata N, Terakubo S, Mukai T. Subcellular location of the soluble lytic transglycosylase homologue in Staphylococcus aureus. Curr Microbiol. 2005;50:47–51. [PubMed]
56. Stapleton MR, Horsburgh MJ, Hayhurst EJ, Wright L, Jonsson IM, et al. Characterization of IsaA and SceD, two putative lytic transglycosylases of Staphylococcus aureus. J Bacteriol. 2007;189:7316–7325. [PMC free article] [PubMed]
57. Stokes NR, Murray HD, Subramaniam C, Gourse RL, Louis P, et al. A role for mechanosensitive channels in survival of stationary phase: regulation of channel expression by RpoS. Proc Natl Acad Sci U S A. 2003;100:15959–15964. [PMC free article] [PubMed]
58. Giaever HM, Styrvold OB, Kaasen I, Strom AR. Biochemical and genetic characterization of osmoregulatory trehalose synthesis in Escherichia coli. J Bacteriol. 1988;170:2841–2849. [PMC free article] [PubMed]
59. Ajdic D, Pham VT. Global transcriptional analysis of Streptococcus mutans sugar transporters using microarrays. J Bacteriol. 2007;189:5049–5059. [PMC free article] [PubMed]
60. Lemos JA, Abranches J, Burne RA. Responses of cariogenic streptococci to environmental stresses. Curr Issues Mol Biol. 2005;7:95–107. [PubMed]
61. Lemos JA, Burne RA. A model of efficiency: stress tolerance by Streptococcus mutans. Microbiology. 2008;154:3247–3255. [PMC free article] [PubMed]
62. Burne RA, Marquis RE. Alkali production by oral bacteria and protection against dental caries. FEMS Microbiol Lett. 2000;193:1–6. [PubMed]
63. Casiano-Colon A, Marquis RE. Role of the arginine deiminase system in protecting oral bacteria and an enzymatic basis for acid tolerance. Appl Environ Microbiol. 1988;54:1318–1324. [PMC free article] [PubMed]
64. Liu Y, Dong Y, Chen YY, Burne RA. Environmental and growth phase regulation of the Streptococcus gordonii arginine deiminase genes. Appl Environ Microbiol. 2008;74:5023–5030. [PMC free article] [PubMed]
65. Kurkivuori J, Salaspuro V, Kaihovaara P, Kari K, Rautemaa R, et al. Acetaldehyde production from ethanol by oral streptococci. Oral Oncol. 2007;43:181–186. [PubMed]
66. Liang X, Chen YY, Ruiz T, Wu H. New cell surface protein involved in biofilm formation by Streptococcus parasanguinis. Infect Immun. 2011;79:3239–3248. [PMC free article] [PubMed]
67. Wang BY, Deutch A, Hong J, Kuramitsu HK. Proteases of an early colonizer can hinder Streptococcus mutans colonization in vitro. J Dent Res. 2011;90:501–505. [PMC free article] [PubMed]
68. Chen YY, Feng CW, Chiu CF, Burne RA. cadDX operon of Streptococcus salivarius 57.I. Appl Environ Microbiol. 2008;74:1642–1645. [PMC free article] [PubMed]
69. Vriesema AJ, Dankert J, Zaat SA. A shift from oral to blood pH is a stimulus for adaptive gene expression of Streptococcus gordonii CH1 and induces protection against oxidative stress and enhanced bacterial growth by expression of msrA. Infect Immun. 2000;68:1061–1068. [PMC free article] [PubMed]
70. Kreth J, Zhang Y, Herzberg MC. Streptococcal antagonism in oral biofilms: Streptococcus sanguinis and Streptococcus gordonii interference with Streptococcus mutans. J Bacteriol. 2008;190:4632–4640. [PMC free article] [PubMed]
71. Cole RM, Calandra GB, Huff E, Nugent KM. Attributes of potential utility in differentiating among “group H” streptococci or Streptococcus sanguis. J Dent Res. 1976;55:A142–153. [PubMed]
72. Chen YY, Clancy KA, Burne RA. Streptococcus salivarius urease: genetic and biochemical characterization and expression in a dental plaque streptococcus. Infect Immun. 1996;64:585–592. [PMC free article] [PubMed]
73. Chen YY, Weaver CA, Mendelsohn DR, Burne RA. Transcriptional regulation of the Streptococcus salivarius 57.I urease operon. J Bacteriol. 1998;180:5769–5775. [PMC free article] [PubMed]
74. Frangeul L, Nelson KE, Buchrieser C, Danchin A, Glaser P, et al. Cloning and assembly strategies in microbial genome projects. Microbiology. 1999;145(Pt 10):2625–2634. [PubMed]
75. Tettelin H, Radune D, Kasif S, Khouri H, Salzberg SL. Optimized multiplex PCR: efficiently closing a whole-genome shotgun sequencing project. Genomics. 1999;62:500–507. [PubMed]
76. Gao F, Zhang CT. Ori-Finder: a web-based system for finding oriCs in unannotated bacterial genomes. BMC Bioinformatics. 2008;9:79. [PMC free article] [PubMed]
77. Delcher AL, Harmon D, Kasif S, White O, Salzberg SL. Improved microbial gene identification with GLIMMER. Nucleic Acids Res. 1999;27:4636–4641. [PMC free article] [PubMed]
78. Suzek BE, Ermolaeva MD, Schreiber M, Salzberg SL. A probabilistic method for identifying start codons in bacterial genomes. Bioinformatics. 2001;17:1123–1130. [PubMed]
79. Bao Q, Tian Y, Li W, Xu Z, Xuan Z, et al. A complete sequence of the T. tengcongensis genome. Genome Res. 2002;12:689–700. [PMC free article] [PubMed]
80. Luo Y, Xu X, Ding Z, Liu Z, Zhang B, et al. Complete genome of Phenylobacterium zucineum-a novel facultative intracellular bacterium isolated from human erythroleukemia cell line K562. BMC Genomics. 2008;9:386. [PMC free article] [PubMed]
81. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, et al. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 2006;34:D354–357. [PMC free article] [PubMed]
82. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28:33–36. [PMC free article] [PubMed]
83. Mulder NJ, Apweiler R. The InterPro database and tools for protein domain analysis. Curr Protoc Bioinformatics Chapter. 2008;2:Unit 2 7. [PubMed]
84. Mulder NJ, Apweiler R, Attwood TK, Bairoch A, Barrell D, et al. The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Res. 2003;31:315–318. [PMC free article] [PubMed]
85. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25:955–964. [PMC free article] [PubMed]
86. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, et al. Versatile and open software for comparing large genomes. Genome Biol. 2004;5:R12. [PMC free article] [PubMed]
87. Alexeyenko A, Tamas I, Liu G, Sonnhammer EL. Automatic clustering of orthologs and inparalogs shared by multiple proteomes. Bioinformatics. 2006;22:e9–15. [PubMed]
88. Thompson JD, Gibson TJ, Higgins DG. Multiple sequence alignment using ClustalW and ClustalX. Curr Protoc Bioinformatics Chapter. 2002;2:Unit 2 3. [PubMed]
89. Carver TJ, Rutherford KM, Berriman M, Rajandream MA, Barrell BG, et al. ACT: the Artemis Comparison Tool. Bioinformatics. 2005;21:3422–3423. [PubMed]
90. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5:621–628. [PubMed]
91. Romualdi C, Bortoluzzi S, D'Alessi F, Danieli GA. IDEG6: a web tool for detection of differentially expressed genes in multiple tag sampling experiments. Physiol Genomics. 2003;12:159–162. [PubMed]

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