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Independent evolution of competence regulatory cascades in streptococci?

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modules had a higher tendency to be co-expressed, to co- localize, and to be evolutionarily conserved across species in an all-or-none fashion. These findings are not funda- mentally new [13,14] but they do emphasize the challenges ahead. Beyond reporting correlations over genome-wide datasets, more detailed information can be gained at multi- ple organizational levels; for example, by comparing each module with another to derive the properties of individual modules. Concluding remarks and future perspectives Interactions within cells, whether physical or functional, are instrumental in understanding the cellular machinery. These recent studies [2,3] provide an advance in delineat- ing the organization of the proteome. More analysis must be done to derive a consensual and benchmarked set of complexes out of these datasets and to evaluate the biolo- gical function of modules. The next stage will be the dynamic analysis of protein complexes on a large scale. TAP–MS can capture the dynamics of interactions, for example, as demonstrated in the comparative study of the human tumour necrosis factor pathway in stimulated and resting cells [15]. Similar to the way cells integrate input signals, create connectivity to process signals and output the results, the next challenge is to integrate these different networks and their dynamics into a more com- prehensive picture of cellular machines and their function. This will accelerate the determination of systems proper- ties for specific machines and even, eventually, for whole cells. References 1 Alberts, B. (1998) The cell as a collection of protein machines: preparing the next generation of molecular biologists. Cell 92, 291–294 2 Gavin, A.C. et al. (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature 440, 631–636 3 Krogan, N.J. et al. (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature 440, 637–643 4 Gavin, A.C. et al. (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415, 141–147 5 Krause, R. et al. (2004) Shared components of protein complexes – versatile building blocks or biochemical artefacts? Bioessays 26, 1333–1343 6 Hartwell, L.H. et al. (1999) From molecular to modular cell biology. Nature 402 (6761 Suppl.), C47–C52 7 Alon, U. (2003) Biological networks: the tinkerer as an engineer. Science 301, 1866–1867 8 Gagneur, J. et al. (2004) Modular decomposition of protein–protein interaction networks. Genome Biol. 5, R57 9 Lee, I. et al. (2004) A probabilistic functional network of yeast genes. Science 306, 1555–1558 10 von Mering, C. et al. (2005) STRING: known and predicted protein– protein associations, integrated and transferred across organisms. Nucleic Acids Res. 33 (Database issue), D433–D437 11 Ghaemmaghami, S. et al. (2003) Global analysis of protein expression in yeast. Nature 425, 737–741 12 Jensen, L.J. and Steinmetz, L.M. (2005) Re-analysis of data and its integration. FEBS Lett. 579, 1802–1807 13 Ge, H. et al. (2001) Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat. Genet. 29, 482–486 14 Wuchty, S. et al. (2003) Evolutionary conservation of motif constituents in the yeast protein interaction network. Nat. Genet. 35, 176–179 15 Bouwmeester, T. et al. (2004) A physical and functional map of the human TNF-a/NF-kB signal transduction pathway. Nat. Cell Biol. 6, 97–105 16 Ito, T. et al. (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. U. S. A. 98, 4569–4574 17 Uetz, P. et al. (2000) A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae. Nature 403, 623–627 18 Ho, Y. et al. (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415, 180–183 19 von Mering, C. et al. (2002) Comparative assessment of large-scale data sets of protein–protein interactions. Nature 417, 399–403 0922-1425/$ – see front matter # 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.tim.2006.06.002 Genome Analysis Independent evolution of competence regulatory cascades in streptococci? Bernard Martin, Yves Quentin, Gwennaele Fichant and Jean-Pierre Claverys Laboratoire de Microbiologie et Ge ´ne ´ tique Mole ´ culaires, UMR 5100 CNRS-Universite ´ Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex 9, France Natural genetic transformation is a mechanism of horizontal gene transfer that is widely distributed in bacteria and requires assembly of a DNA uptake machin- ery. Transformable bacteria use fundamentally the same machine, which in most species is assembled only in cells that are developing competence. Competence reg- ulation usually differs between unrelated species. Here, we examine whether related streptococci use the same competence regulatory cascade. Phylogenetic analyses of streptococcal genome sequences reveal the existence of two paralogous two-component regulatory systems, either of which might control competence. This sug- gests the distribution of streptococci into two groups that use competence regulatory cascades that have at least partly evolved independently. Comparison of data obtained with two transformable streptococci, Streptococcus pneumoniae and Streptococcus mutans, provides support to this suggestion. Genetic transformation and competence Natural genetic transformation is a mechanism of hori- zontal gene transfer that is widely distributed among Update TRENDS in Microbiology Vol.14 No.8 339 Corresponding author: Claverys, J.P. ([email protected]) Available online 3 July 2006 www.sciencedirect.com
Transcript

Update TRENDS in Microbiology Vol.14 No.8 339

modules had a higher tendency to be co-expressed, to co-localize, and to be evolutionarily conserved across speciesin an all-or-none fashion. These findings are not funda-mentally new [13,14] but they do emphasize the challengesahead. Beyond reporting correlations over genome-widedatasets, more detailed information can be gained atmulti-ple organizational levels; for example, by comparing eachmodule with another to derive the properties of individualmodules.

Concluding remarks and future perspectivesInteractions within cells, whether physical or functional,are instrumental in understanding the cellular machinery.These recent studies [2,3] provide an advance in delineat-ing the organization of the proteome. More analysis mustbe done to derive a consensual and benchmarked set ofcomplexes out of these datasets and to evaluate the biolo-gical function of modules. The next stage will be thedynamic analysis of protein complexes on a large scale.TAP–MS can capture the dynamics of interactions, forexample, as demonstrated in the comparative study ofthe human tumour necrosis factor pathway in stimulatedand resting cells [15]. Similar to the way cells integrateinput signals, create connectivity to process signals andoutput the results, the next challenge is to integrate thesedifferent networks and their dynamics into a more com-prehensive picture of cellular machines and their function.This will accelerate the determination of systems proper-ties for specific machines and even, eventually, for wholecells.

References1 Alberts, B. (1998) The cell as a collection of protein machines: preparing

the next generation of molecular biologists. Cell 92, 291–294

Corresponding author: Claverys, J.P. ([email protected])Available online 3 July 2006

www.sciencedirect.com

2 Gavin, A.C. et al. (2006) Proteome survey reveals modularity of the yeastcell machinery. Nature 440, 631–636

3 Krogan, N.J. et al. (2006) Global landscape of protein complexes in theyeast Saccharomyces cerevisiae. Nature 440, 637–643

4 Gavin, A.C. et al. (2002) Functional organization of the yeast proteomeby systematic analysis of protein complexes. Nature 415, 141–147

5 Krause, R. et al. (2004) Shared components of protein complexes –versatile building blocks or biochemical artefacts? Bioessays 26,1333–1343

6 Hartwell, L.H. et al. (1999) From molecular to modular cell biology.Nature 402 (6761 Suppl.), C47–C52

7 Alon, U. (2003) Biological networks: the tinkerer as an engineer. Science301, 1866–1867

8 Gagneur, J. et al. (2004) Modular decomposition of protein–proteininteraction networks. Genome Biol. 5, R57

9 Lee, I. et al. (2004) A probabilistic functional network of yeast genes.Science 306, 1555–1558

10 von Mering, C. et al. (2005) STRING: known and predicted protein–protein associations, integrated and transferred across organisms.Nucleic Acids Res. 33 (Database issue), D433–D437

11 Ghaemmaghami, S. et al. (2003) Global analysis of protein expressionin yeast. Nature 425, 737–741

12 Jensen, L.J. and Steinmetz, L.M. (2005) Re-analysis of data and itsintegration. FEBS Lett. 579, 1802–1807

13 Ge, H. et al. (2001) Correlation between transcriptome and interactomemapping data from Saccharomyces cerevisiae. Nat. Genet. 29, 482–486

14 Wuchty, S. et al. (2003) Evolutionary conservation ofmotif constituentsin the yeast protein interaction network. Nat. Genet. 35, 176–179

15 Bouwmeester, T. et al. (2004) A physical and functional map of thehuman TNF-a/NF-kB signal transduction pathway. Nat. Cell Biol. 6,97–105

16 Ito, T. et al. (2001) A comprehensive two-hybrid analysis to explore theyeast protein interactome. Proc. Natl. Acad. Sci. U. S. A. 98, 4569–4574

17 Uetz, P. et al. (2000) A comprehensive analysis of protein–proteininteractions in Saccharomyces cerevisiae. Nature 403, 623–627

18 Ho, Y. et al. (2002) Systematic identification of protein complexes inSaccharomyces cerevisiae by mass spectrometry. Nature 415, 180–183

19 vonMering, C. et al. (2002) Comparative assessment of large-scale datasets of protein–protein interactions. Nature 417, 399–403

0922-1425/$ – see front matter # 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.tim.2006.06.002

Genome Analysis

Independent evolution of competence regulatorycascades in streptococci?

Bernard Martin, Yves Quentin, Gwennaele Fichant and Jean-Pierre Claverys

Laboratoire de Microbiologie et Genetique Moleculaires, UMR 5100 CNRS-Universite Paul Sabatier,

118 route de Narbonne, 31062 Toulouse Cedex 9, France

Natural genetic transformation is a mechanism ofhorizontal gene transfer that is widely distributed inbacteria and requires assembly of a DNA uptake machin-ery. Transformable bacteria use fundamentally the samemachine, which in most species is assembled only incells that are developing competence. Competence reg-ulation usually differs between unrelated species. Here,we examine whether related streptococci use the samecompetence regulatory cascade. Phylogenetic analysesof streptococcal genome sequences reveal the existence

of two paralogous two-component regulatory systems,either of which might control competence. This sug-gests the distribution of streptococci into two groupsthat use competence regulatory cascades that have atleast partly evolved independently. Comparison ofdata obtained with two transformable streptococci,Streptococcus pneumoniae and Streptococcus mutans,provides support to this suggestion.

Genetic transformation and competenceNatural genetic transformation is a mechanism of hori-zontal gene transfer that is widely distributed among

340 Update TRENDS in Microbiology Vol.14 No.8

Figure 1. Genetic organization of the Blp and Com systems in Streptococcus

pneumoniae. Percentage of identical amino acids between S. pneumoniae Blp and

Com components are indicated between parentheses. Key to colours: pheromone

response genes include the RR (red) and HK genes (orange); pheromone export

genes include those that encode ABC proteins (dark blue) and accessory proteins

(light blue). Pheromone-encoding genes are in green. Percentage of identical amino

acids between Streptococcus mutans Com (or Csl) proteins and S. pneumoniae

Blp and Com components are indicated above and below the S. mutans genetic

organization diagram, respectively. Red flags indicate binding sites for the

corresponding RR (E, ComE; R, BlpR). S. mutans comC and cslB are separated

by �7.5 kb DNA that contains several ORFs encoding putative bacteriocins with

double-glycine leaders. bsmA, bsmH and blpI also encode candidate bacteriocins.

S. pneumoniae comC and comA are more than 45 kb apart (and separated by ori).

Corresponding annotations in the S. mutans genome (http://www.ncbi.nlm.nih. gov/

entrez/viewer.fcgi?val=AE014133) are as follows: cslB, smu.1900; cslA, smu.1897 and

smu.1898 (underlined); bsmH, smu.1896.

taxonomic groups (including Archaea); it has been foundto occur in �40 different species [1]. Transformationdepends on a DNA uptake machinery that includes pro-teins related to those involved in the assembly of type IVpili and in type II secretion systems [2,3]. In most trans-formable species, expression of this machinery is tightlyregulated and occurs only in cells that are in the process ofdeveloping competence. Comparison of two well-documen-ted transformation systems, those of the soil-dwellerBacillus subtilis [4] and the human pathogen Streptococ-cus pneumoniae [5], showed that the two species haveindependently evolved competence regulatory circuitsmost adapted to their own lifestyle [6,7]. Nevertheless,could data obtainedwith a given species be extrapolated torelated species, at least those sharing a similar niche?Examination of the situation with transformable strepto-cocci provides some clues.

The S. pneumoniae modelIn S. pneumoniae, competence is induced by a smallpeptide pheromone, the competence stimulating peptide(CSP). CSP is an unmodified 17-residue peptide [8],exported and matured by ComA–ComB, a dedicatedABC exporter, which removes a leader peptide after aGly–Gly motif (double-glycine leader) [9] in the 45-residuepre-CSP encoded by comC [10]. A dedicated two-component regulatory system (TCS), ComDE, detectsextracellular CSP and transmits a signal that leads totranscriptional activation of the competence regulon. Byanalogy with other TCSs, it is assumed that CSP bindingstimulates the polytopic, membrane-embedded histidinekinase (HK) ComD to autophosphorylate and transfer aphosphoryl group to its cognate response regulator (RR),ComE. ComE belongs to the AgrA/AlgR/LytR family of RRs[11]. Phosphorylated ComE directly activates expression ofthe so-called early com genes, which are preceded by adirect repeat to which ComE binds [12]. The early genesinclude comAB and comCDE (Figure 1), comW (see later)and comX [13], which encodes a competence-specific sigmafactor [14]. ComX recognizes a conserved –10 sX promoter,designated the combox or cin-box [5], which is present infront of the late com genes. The late com genes includethose that encode the machinery for DNA uptake andprocessing [5,7].

This regulatory cascade leads to the autocatalyticaccumulation of CSP once a critical threshold is attained,which probably accounts for the high degree of competencesynchrony in pneumococcal cultures. It also results in anextremely fast response to CSP. Upon CSP addition,transcription of the early and late genes reaches a max-imum after 5–7 minutes and 10–12 minutes, respectively[15–19]. Pneumococcal competence is also tightly con-trolled at the post-transcriptional level [7]. Thus, theearly gene product ComW is required to activate ComX(by a yet unknown mechanism) and to prevent ClpP-dependent proteolysis of the competence-specific sX [20].Such regulation presumably makes the expression of lategenes more strictly dependent on ComE signalling andcould prevent adventitious competence developmentresulting from read-through transcription of the comXgenes [21].

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Natural transformation and the presence of ComX instreptococciIn addition to S. pneumoniae, genetic transformationhas been reported in Streptococcus gordonii (formerlyStreptococcus sanguis Challis) and in the odontopathicbacterium Streptococcus mutans [1] and, more recently,in members of the viridans group of streptococci [22]. It is,therefore, not surprising that these species encode aComX-like s factor (Figure 2). Homologues of S. pneumo-niae proteins required for the uptake of DNA and itsprocessing into recombinants are also found in thesespecies [23,24]. It is more surprising to find that a ComXorthologue is encoded in all streptococcal genomessequenced so far (Figure 2) and in all other Lactobacillales(Lactococcus lactis, Lactobacillus plantarum, Enterococcusfaecalis and Enterococcus faecium; data not shown). Aminoacid identity ranges from 38% (Streptococcus thermophilus)to 46% (S.mutans) and up to 92% (Streptococcusmitis), andfrom29%(L. lactis) to27%(E. faecium).Canthisobservationbe taken as an indication that most streptococcal speciesare naturally transformable and fundamentally use thesame alternative sX factor for com gene expression?The presence of key competence-regulatory proteins,particularly homologues of the ComDE TCS that regulatesComXactivity bothdirectlyand indirectly inS.pneumoniae,could help to predict new transformable species [6].

S. pneumoniae ComDE homologues in streptococciS. pneumoniae itself contains a twin of the ComABCDEregulation system, BlpABCRH [5]. Among 13 TCSs iden-

Update TRENDS in Microbiology Vol.14 No.8 341

Figure 2. Phylogenetic relationships and distribution of ComD (BlpH) and ComE (BlpR) homologues in streptococci. The phylogenetic tree is based on 16S rRNA sequences

of streptococcus type strains retrieved from the Ribosomal Database Project II (http://rdp.cme.msu.edu/) [40]. The six phylogenetic groups defined previously [41] are

indicated with a colour code (vertical bars). Streptococcus pneumoniae and Streptococcus mutans are indicated by red horizontal arrows. Plus symbols (+) in the

‘Transformability’ column indicate species for which natural transformation has been documented. Filled and unfilled circles in the ‘Genome sequence’ column indicate

availability of finished and unfinished (not yet released) genome sequences. Filled diamonds indicate the presence and number of copies of comX gene(s) identified

through TBLASTN searches in the corresponding genome. The PCR column refers to the detection (+) or absence (�) of the comCDE chromosomal region in the study of

Havarstein and co-workers [22]. Filled squares indicate the presence of Com, Blp or Fas TCSs. Half-filled symbols indicate that the gene or protein is present only in some

isolates in the corresponding species. The half-filled square in parentheses indicates that the corresponding ORF contained a frameshift. Sequence alignments were carried

out using ClustalX [42] and edited with SEAVIEW [43]. The phylogenetic analyses were performed with PHYLO_WIN [43] and distances were estimated with the substitution

model of Tamura and Nei [44]. The tree is unrooted and was reconstructed using the neighbour-joining method on alignment positions without a gap [45]. For each sample,

500 bootstrap replicates were computed and only bootstrap values >50% are reported on branches.

tified in S. pneumoniae,only two RRs – BlpR and ComE –belong to the AgrA/AlgR/LytR family [25]. BlpR controls theBlp regulon [26,27], which is made of several bacteriocin-like peptides (hence the name Blp) with double-glycineleaders; however, the experimental demonstration thatthese peptides have antimicrobial activity is still lacking.A Blp-inducing peptide (BIP) is encoded by blpC and ispossibly exported and matured through BlpAB, a ComABparalogue. BIP is sensed by BlpH, a paralogue of the HK

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ComD. It is of note that the blpABCRH and comABCDEgene organizations differ, and that no BlpR binding site ispresent in front of the blpRH genes [26] (Figure 1).

Interestingly, a comparison of S. mutans ComDE pro-teins, which have been reported to control competence inthis species [28], with S. pneumoniae ComDE and BlpRHproteins revealed that they are more closely related to theBlpRH proteins (Figure 1). This observation suggestedthat S. mutans proteins are orthologues of S. pneumoniae

342 Update TRENDS in Microbiology Vol.14 No.8

BlpRH and that the two species could have recruiteddifferent TCSs to control competence. It prompted us toanalyze the distribution and phylogenetic relationships ofComDE homologues in species of the genus Streptococcus.Similarity searches using ComD, ComE, BlpR and BlpHproteins of S. pneumoniae as queries were performed onfinished and unfinished (not yet released) genomes ofstreptococci. To enlarge theStreptococcus species coverage,ComDE homologues were also identified by scanning thenon-redundant database. After discarding the sequenceredundancy caused by sequencing of different strains ofthe same species, a final set of 16 RR and 21 HK proteinshas been obtained from 14 streptococcal species (as ofFebruary 28, 2006). This set includes proteins that controlstreptokinase gene expression in group A and C strepto-cocci (the Fas system [29]). The phylogenetic trees showedthat streptococcal ComE homologues distribute into threedistinct clusters, referred to as Com, Blp and Fas(Figure 3), consistent with a previous analysis on the RRproteins of those systems [29]. In each cluster, the branchtopology is in agreement with the tree obtained on 16SrRNA (Figure 2). Heterogeneity in branch length in Blpclusters suggests a rapid evolution of proteins in thefamily. This evolution could be favoured by a gain-and-lossmechanism that can occur because these TCSs control

Figure 3. Phylogenetic trees of the RR (left) and the HK (right) proteins. For the HK pro

are identified by different colours: Com (dark blue), Blp (light blue) and Fas (mid-blu

orthologue (with the noticeable exception of Streptococcus suis, although the comDE l

location, distant from ori; data not shown). Streptococcus pneumoniae and Strepto

prototype Staphylococcus Agr family were used as an outgroup. Species are identified

aureus; Scon, S. constellatus; Sepi, Staphylococcus epidermidis; Sequ, S. equi; Sgor, S

Smil, S. milleri; Smit, S. mitis; Sora, S. oralis; Spne, S. pneumoniae; Spyo, S. pyogene

for the Com and Blp proteins of S. pneumoniae, each streptococcal protein in the Com

ComD–BlpH tree (right) identify cognate kinases. Numbers 20–22 in the right-hand tree

gene was not available; numbers 17b and 18b correspond to two homologous kinase

protein lists.) Trees were constructed as described for Figure 2 but distances were esti

and sequences of the Staphylococcus Agr system (highlighted in grey) were used as

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bacteriocin production and are, therefore, not as impor-tant as TCSs that control the competence regulon inS. pneumoniae or virulence in Staphylococcus aureus.Fas could represent an emerging cluster.

It is of note that HK–RR pairs defined experimentally(e.g. S. pneumoniae ComDE) and HK and RR proteinsencoded by genes in the same chromosomal neighbourhoodfollow parallel evolutionary trajectories, except for a fewtree rearrangements that involved branches with the low-est bootstrap supports (<53%). On both trees, the S. suishomologues are located between Com and Blp clusters.

Genes encoding ComDE orthologues were previouslydetected only in members of the mitis and anginosusphylogenetic groups [22]. However, because this studywas based on PCR reactions using the tRNA genes flankingcomDE in S. pneumoniae (see later), it could have missedorthologues with a different genetic organization in otherstreptococci. Nevertheless, analysis of genome sequencesaccumulated since then strongly suggests that ComDEorthologues are restricted to the mitis and anginosusgroups (Figure 2). This clustering is well supported by abootstrap of 100% (Figure 3). It was previously noticed thatthe S. pneumoniae comCDE operon exhibited a rather lowGC content for the species (�30%) and was flanked bytRNAs, two features commonly associated with pathogeni-

teins, the tree was computed using the histidine kinase domains. The three clusters

e). Only streptococci belonging to the mitis and anginosus groups harbour a Com

ocus present in one of the two sequenced isolates exhibits an atypical chromosomal

coccus mutans proteins are indicated by red horizontal arrows. Members of the

by a four-letter code: Saga, S. agalactiae; Sang, S. anginosus; Saur, Staphylococcus

. gordonii; Shae, Staphylococcus haemolyticus; Sinf, S. infantis; Sint, S. intermedius;

s; Ssap, Staphylococcus saprophyticus; Ssui, S. suis; Sthe, S. thermophilus. Except

E–BlpR tree (left) was given a number between 1 and 19. Identical numbers in the

correspond to ‘orphan’ kinases for which the sequence of the corresponding comE

s for each FasA RR. (See the online Supplementary Material for the corresponding

mated using the PAM (percent accepted mutation) model of amino acid substitution

an outgroup.

Update TRENDS in Microbiology Vol.14 No.8 343

city islands [30]. These characteristics could indicate thatthis piece of DNA was acquired by lateral gene transfer.The clustering we observe suggests a scenario in which thisacquisition has occurred at an early stage before differen-tiation into the mitis and anginosus groups. By contrast,because orthologues of BlpRH are found in all streptococciinvestigated so far (Figure 2) with the exception of someS. pyogenes strains [6], it is likely that this system waspresent in a common ancestor. With respect to S. mutans,our phylogenetic analysis confirms that this species has aBlpRH-type TCS but no ComDE orthologue.

Inferences on the regulation of competence instreptococciAnalysis of the available genome sequences of S. mitis andS. gordonii suggests that these species use competenceregulatory cascades that are highly related to that ofS. pneumoniae. Thus, their comCDE operon is similarlylocated close to ori, the putative origin of chromosomereplication. Both species also encode orthologues ofComAB (data not shown) and two copies of comX(Figure 2). In view of these similarities, it is most likelythat S. mitis and S. gordonii are highly similar toS. pneumoniae with respect to the regulation of compe-tence. However, a gene encoding a ComW-like protein wasdetected in S.mitis but not inS. gordonii (using TBLASTN;our observations), which suggests that S. gordonii mightuse a different mechanism to control ComX. Nevertheless,we propose that S. pneumoniae is the paradigm for natu-rally transformable streptococcal species belonging to themitis and anginosus groups. By contrast, S. pneumoniaeshould not be considered the paradigm for other strepto-coccal species because these lack a ComDE orthologue.Examination of the S. mutans competence regulatorycascade strongly supports this view.

S. mutans and S. pneumoniae competence regulatorycascades differIn addition to the observation that S. mutans ‘ComDE’ isorthologous to S. pneumoniae BlpRH (Figure 3), we foundthat the S. mutans CSP exporter, CslAB [31], is the ortho-logue of S. pneumoniae BlpAB (Figure 1; and data notshown). [Note that the two genes annotated as comAB(smu.0286–0287) in the genome sequence of S. mutans(AE014133) are not involved in CSP export and were,therefore, proposed to be renamed nlmTE [32].] Interest-ingly, whereas in ComA the three functional domains of theABC exporter (an ATP-hydrolysing domain, a membranedomain for peptide translocation, and a proteolytic, N-terminal domain) are fused [5], the proteolytic domainconstitutes an independent polypeptide in both BlpAand CslA [underlined open reading frames (ORFs) inFigure 1]. It was previously noticed that the genetic orga-nization of theS.mutans com–csl systemdiffered from thatof the comCDE genes in S. pneumoniae [28]. Whereas thecomCDE genetic organization has only been observed instreptococci belonging to the mitis and anginosus groups[22], the S. mutans com–csl gene arrangement is strikinglysimilar to that of the S. pneumoniae Blp system (Figure 1).This microsynteny constitutes an additional argument infavour of a common evolutionary origin of the S. mutans

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Com and S. pneumoniae Blp systems. Together, theseobservations clearly establish that different TCSs havebeen recruited to regulate competence in S. mutans andS. pneumoniae. It is also of note that, unlike the situationin S. pneumoniae, S. mutans comCDE is not located at ori.This could result in further differences in competenceregulation between the two species because it has beenproposed that this co-location provided the capacity forcoordinating competence and the initiation of replication[33].

Several experimental data also indicate that S.pneumoniae and S. mutans competence regulatory cas-cades differ. Thus, it is particularly striking that S.mutanscells do not become competent soon after CSP addition;instead, transformation exhibits a maximum in the expo-nential growth phase only after a �2 h delay [34]. Thisresult suggests that, in S. mutans, the expression of comXis not directly regulated by ‘ComE’. By contrast, expres-sion of S. mutans nlmAB, which encodes the two-peptidebacteriocin NlmAB (mutacin IV), is rapidly induced byCSP [34]. nlmAB expression is dependent on ‘ComE’ butnot on ComX. It relies on the presence of a direct repeatupstream of nlmAB, the sequence of which fits with theconsensus binding sequence proposed for RRs of the AlgR/AgrA/LytR family [11], and is likely to represent a bindingsite for ‘ComE’ [35]. This direct control of mutacin IVproduction by S. mutans ‘ComDE’ is reminiscent of theinvolvement of S. pneumoniae BlpRH in the control of aregulon that essentially encodes bacteriocin-like peptides[26,27], and is fully consistent with the direct phylogeneticrelationship that we propose. It strongly suggests that theprimary function of S. mutans ‘ComDE’ is in the regula-tion of bacteriocin production and not in the regulation ofcompetence.

No ‘ComE’ binding site could be detected in front of thecomX gene [35], which is fully consistent with the conclu-sion that comX expression is not directly regulated by‘ComE’. It is, therefore, not surprising that inactivationof ‘comE’ has a different impact on genetic transformationin this species. A ‘comE’ (and ‘comC’ or ‘comD’) mutant of S.mutans was reported to have a high residual level oftransformation [28], whereas S. pneumoniae comE (orcomABCD) mutants have no detectable transformation.

DNA sequence analysis also revealed additional sub-stantial differences between S. pneumoniae and S. mutanscompetence regulatory circuits. First, no ‘ComE’ bindingsite could be detected upstream of the ‘comDE’ genes [35].This situation is reminiscent of that of the blpRH genes ofS. pneumoniae, which are not induced in response to BIP[26]. Second, we did not detect a ‘ComE’ binding site infront of the genes encoding the CSP exporter, cslA–cslB.This implied that S. mutans lacks the autoinductionmechanism that results in higher rates of CSP synthesisand secretion, and amplifies the response to CSP inS. pneumoniae [5]. Using TBLASTN, we also failed todetect a gene in the S. mutans genome that wouldencode a protein homologous to S. pneumoniae ComW.Finally, it was recently established that inactivationof ciaH but not of ciaR (which encode a HK and itscognate RR, respectively) significantly reduced theexpression of comDE in S. mutans [36]. This is in contrast

344 Update TRENDS in Microbiology Vol.14 No.8

Figure 4. Independent evolution of competence regulatory cascades in streptococci. In Streptococcus pneumoniae (green text) but not in Streptococcus mutans (blue text),

CSP triggers direct activation of comCDE and comX expression by ComE (red arrows). Therefore, autocatalytic CSP accumulation occurs only in S. pneumoniae. This

difference between S. pneumoniae and S. mutans is attributed to the recruitment of paralogous TCSs (and paralogous pheromone exporters; see Figures 1 and Figure 2) to

regulate competence. To avoid misleading parallels between the two species, we suggest renaming the S. mutans system BlpCHR to the name of the S. pneumoniae

orthologue, as done here. The �2 h delay before induction of S. mutans transformation by BIP (CSP) [34] suggests that comX induction is indirect and/or that ComX

requires activation by some unknown mechanism (dotted red line and question mark).

to S. pneumoniae, in which inactivation of ciaR resulted incompetence upregulation [5].

We conclude that, despite the use of the same alternativesX factor for com gene expression, S. pneumoniae and S.mutans have evolved completely different regulatory cir-cuits to control the production, activity and stability of thisfactor (Figure 4). Although the nature of the connectionbetween ‘ComE’ and comX gene expression in S. mutansremains to be established, the case of S. mutans mightrepresent a current example of the idea that competenceregulation evolved by co-opting a bacteriocin regulator. Theuse of the same name (ComDE) to designate paralogousTCSs that differently affect competence development in thetwo species is, therefore, misleading because it conveys theidea that a common competence regulatory circuit operatesin both species, which is clearly not the case (Figure 4).

Concluding remarks and future perspectivesAs previously observed inS. pyogenes [37], all streptococcalgenomes sequenced so far contain not only a comX gene(Figure 2) but also genes that potentially encode DNAuptake and processing functions (data not shown). Thesegenes are preceded by bona fide cin-boxes and, in the caseof S. pyogenes, could be transcribed in vitro with thecore polymerase associated with sX [38]. What about theirtransformability and the control of comX? Altogether, theobservations discussed earlier suggest that S. pneumoniaecan be considered the paradigm for streptococci equippedwith a Com-type TCS (i.e. those belonging to the mitis andanginosus groups; Figure 2), whereas S. mutans could

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serve as a model for streptococci that can only rely onBlp-type TCSs for the regulation of competence (Figure 3).Therefore, we propose that whatever their niche (the oralcavity or the nasopharynx), species that harbour a Com-type TCS are likely to be readily transformable and willthen use orthologues of the S. pneumoniae ComDE TCS tocontrol comX transcription directly.

By contrast, all S. mutans-like species should follow theS. mutans paradigm. They will use orthologues of the S.pneumoniae BlpRH TCS (as does S. mutans) to controlcomX expression by an as yet uncharacterized indirectmechanism. Thus, any attempt at transforming such spe-cies should incorporate a long delay between the additionof synthetic candidate peptide pheromone to trigger com-petence and the transformation assay. In light of theseobservations, it would be interesting to reinvestigate com-petence induction in the S. pyogenes clinical isolate, whichencodes an S. pneumoniae BlpABCRH-like system [6] andwas previously reported to be capable of DNA transfer inmixed cultures (although the involvement of transforma-tion was not formally established) [39].

In most cases, species phylogenetic relatedness is,therefore, probably the best criterion to be used to predictnot only whether a species is naturally transformable butalso which part of a competence regulatory cascade it couldshare with a model transformable organism (Figure 4).

AcknowledgementsWe thank Mike Chandler for editing the manuscript. Our phylogeneticanalyses benefited from facilities at the NCBI, TIGR and Welcome TrustSanger Institute.

Update TRENDS in Microbiology Vol.14 No.8 345

Appendix A. Supplementary dataSupplementary data associated with this article canbe found, in the online version, at doi:10.1016/j.tim.2006.06.007.

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