Genomic Heterogeneity and Ecological Speciation within OneSubspecies of Bacillus subtilis

Sarah Kopac,a Zhang Wang,b Jane Wiedenbeck,a* Jessica Sherry,a* Martin Wu,b Frederick M. Cohana

Department of Biology, Wesleyan University, Middletown, Connecticut, USAa; Department of Biology, University of Virginia, Charlottesville, Virginia, USAb

Closely related bacterial genomes usually differ in gene content, suggesting that nearly every strain in nature may be ecologicallyunique. We have tested this hypothesis by sequencing the genomes of extremely close relatives within a recognized taxon andanalyzing the genomes for evidence of ecological distinctness. We compared the genomes of four Death Valley isolates plus thelaboratory strain W23, all previously classified as Bacillus subtilis subsp. spizizenii and hypothesized through multilocus analy-sis to be members of the same ecotype (an ecologically homogeneous population), named putative ecotype 15 (PE15). Thesestrains showed a history of positive selection on amino acid sequences in 38 genes. Each of the strains was under a different regi-men of positive selection, suggesting that each strain is ecologically unique and represents a distinct ecological speciation event.The rate of speciation appears to be much faster than can be resolved with multilocus sequencing. Each PE15 strain containedunique genes known to confer a function for bacteria. Remarkably, no unique gene conferred a metabolic system or subsystemfunction that was not already present in all the PE15 strains sampled. Thus, the origin of ecotypes within this clade shows noevidence of qualitative divergence in the set of resources utilized. Ecotype formation within this clade is consistent with the na-noniche model of bacterial speciation, in which ecotypes use the same set of resources but in different proportions, and geneticcohesion extends beyond a single ecotype to the set of ecotypes utilizing the same resources.

Microbial ecology is challenged to explain the extreme dispar-ity among bacteria in physiology, cell structure, and ecology

(1–4), as well as the huge numerical diversity of bacterial taxa,which run over 70 phyla (5, 6) and possibly billions of species(7–9). Ultimately, the origins of all bacterial groups, from theprofoundly disparate divisions to the most closely related taxa,trace back to the origin of species, whereby one lineage splits intotwo ecologically distinct lineages that are able to coexist. In thisstudy, we aimed to estimate the tempo of bacterial speciation andto characterize the processes of divergence that underlie the originof species.

How easy is bacterial speciation? Over the last several decades,evolutionary biology has seen the emergence of models of sympa-tric speciation (10, 11). One such model is ecological speciation(10), in which local populations living in different habitat types orutilizing different resources can successfully and indefinitely di-verge, despite interbreeding.

Ecological speciation is likely to occur frequently in the bacte-rial world (12–20), owing to several aspects of bacterial popula-tion dynamics. First, the low rate of genetic exchange in bacteria,even among the closest relatives, is not sufficient to hinder adap-tive divergence, so evolution of sexual isolation is not a necessarymilestone of bacterial speciation (14, 21–23). Second, genetic ex-change can occur between distantly related bacteria (22, 24, 25),allowing a single gene acquisition event to dramatically change theecological niche of the recipient population. Third, recombiningsegments are often quite short (26–29), so niche-transcending ad-aptations can be transferred without the cotransfer of niche-spec-ifying genes (22, 30, 31). Finally, the astronomical sizes of manybacterial populations make adaptive mutations and recombina-tions that are rare on a per-capita basis accessible on a per-popu-lation basis (32).

Empirical evidence for rapid speciation has emerged from ge-nome comparisons, in which close relatives within a named spe-cies have been shown to differ in the contents of their genomes

(19, 33–35). Because acquisition of novel genes can effect changein ecological niche (24, 35–37), Doolittle and Zhaxybayeva haveinferred that even the closest relatives may be ecologically distinct(19).

Nevertheless, this conclusion is not yet well supported. First,the species recognized by bacterial systematics are well known tohold an enormous level of diversity in physiology and ecology (15,20, 33, 35, 38–46), so finding that members of a species are alsodiverse in their genome content is not surprising. What is neededis to compare the genome contents of the closest relatives, not justmembers of the same species taxon. In addition, genome contentdifferences between the closest relatives must be shown to haveecological importance. Genome content differences among mem-bers of the same species are dominated by genes that are functionalfor phage or transposons and by the so-called “hypothetical”genes, with no known function for bacteria (33, 47). An ecologi-cally motivated genome comparison should do more than trackthe comings and goings of genetic elements that parasitize bacte-ria.

We have aimed to characterize the origins of ecological diver-sity in bacteria by comparing the genomes of close relatives that

Received 19 February 2014 Accepted 23 May 2014

Published ahead of print 6 June 2014

Editor: J. L. Schottel

Address correspondence to Frederick M. Cohan, fcohan@wesleyan.edu.

* Present address: Jane Wiedenbeck, Public Interest Network, Boston, MA; JessicaSherry, Department of Biochemistry, University of California, San Francisco, CA.

S.K. and Z.W. contributed equally to this article.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/AEM.00576-14.

Copyright © 2014, American Society for Microbiology. All Rights Reserved.

doi:10.1128/AEM.00576-14

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represent the most newly divergent “ecotypes.” We define ecotypehere as a phylogenetic group of close relatives that are ecologicallyvery similar, in that the members of an ecotype share genetic ad-aptations to a particular set of habitats, resources, and conditions(48). More specifically, different ecotypes are predicted to coexistindefinitely as a result of their ecological differences, while lin-eages within one ecotype are ecologically too homogeneous toallow indefinite coexistence (49, 50). This definition contrastswith earlier ecotype concepts (51), in that the present definition ofecotype implies no other species-like characteristics beyond eco-logical distinctness. Our goals are to discover empirically whichspecies-like properties follow from ecological distinctness and toquantify the rate at which ecotypes originate. We use the termsecotype and species interchangeably, to mean the most newly di-vergent, ecologically distinct populations, and we refer to the or-igin of bacterial ecotypes as “speciation.”

Models of bacterial speciation. de Queiroz has enumeratedspecies-like properties shared among zoological models of specia-tion, of which we consider three: (i) a species is cohesive, in thatdiversity within the species is recurrently constrained; (ii) differ-ent species are ecologically distinct; and (iii) different species areirreversibly separate (52); additionally, species may be discoveredas distinct sequence clusters (51, 53). Newly divergent species ofbacteria may hold all or some of these species properties, depend-ing on the model of bacterial speciation (Table 1). These modelsdiffer profoundly in the rate at which new ecological diversity isinvented, as well as the extent to which newly invented diversitypersists into the future.

In the stable-ecotype model, bacterial speciation is infrequentand ecologically distinct species coexist long enough to be distin-guished as multilocus sequence clusters (Fig. 1A; Table 1) (51).The long-term coexistence of different ecotypes may be fosteredby a qualitative ecological divergence, where each ecotype utilizessome unique resource not shared with others (22). In this model,an ecotype is subject to cohesion through many recurrent bouts ofdiversity-purging events, caused by periodic selection and/or ge-netic drift, during the long lifetime of the ecotype. Differentecotypes have the species property of being irreversibly separatebecause, owing to their ecological differences, neither periodicselection nor genetic drift can prevent further divergence amongnewly split ecotypes; moreover, ecological divergence between theecotypes is not prevented by recurrent genetic exchange (12, 21–23). In the stable-ecotype model, most ecotypes are discernible assequence clusters because longstanding ecotypes have had oppor-tunity to accumulate neutral sequence divergence at every locus,while diversity within ecotypes is recurrently purged (51).

In contrast, several models of bacterial speciation accommo-

date rapid ecological diversification. The speedy-speciation modelis much like the stable-ecotype model, except that the pace ofspeciation is faster, so closely related ecotypes are not distinguish-able as multilocus sequence clusters (Fig. 1B; Table 1) (51).

In the nanoniche model (Fig. 1C; Table 1), speciation occursrapidly, but the most newly divergent, “nanoniche” ecotypes areonly quantitatively different. Here each ecotype has no uniqueresources but utilizes the same set of resources in different pro-portions (22, 51). This pattern of ecological divergence is com-mon in animal and plant speciation (54) and may extend to bac-teria, as closely related bacterial ecotypes frequently overlap in thehabitats they occupy (15, 42, 55–58). Nanoniche ecotypes are pre-dicted to be ephemeral because each is vulnerable to a speciation-quashing periodic selection event emanating from anotherecotype (Fig. 1C) (59). The nanoniche ecotypes are not irrevers-ibly separate because cohesion can occur at the level of a set ofecotypes that utilize the same set of resources (Table 1).

Another possibility is that there is both rapid formation andextinction of ecotypes, as in the speciesless model (Fig. 1D) (50).Here each ecotype lives only briefly before going extinct, so thediversity within an ecotype is constrained by the short time of itsexistence rather than recurrent cohesive forces like periodic selec-tion. Related to the speciesless model is the opportunitrophmodel, in which various generalist lineages adapt convergently tosimilar types of ephemeral particles (60).

Finally, the recurrent niche invasion model allows for the pos-sibility that the ecological distinctness of ecotypes is encoded byplasmids or other transferable elements (22, 51, 61). Ecotypes inthis model are not irreversibly separate (Fig. 1E; Table 1).

Testing the models of speciation requires identification of theecotypes representing the most recent products of speciation, aswe have set out to do.

The model system. We have aimed to identify the models ofspeciation that apply to Bacillus subtilis relatives. We previouslyisolated Bacillus from various soil microhabitats within Radio Fa-cility Wash (RFW), a canyon on the floor of Death Valley (55), anddemarcated putative ecotypes using two sequence-based algo-rithms, ecotype simulation (ES) (13) and AdaptML (15). Themembership of each putative ecotype contains a group of ex-tremely close relatives that have been hypothesized to be ecologi-cally interchangeable with one another but ecologically distinctfrom other ecotypes (62).

Our previous sequence-based analyses were conducted on a1,776-bp concatenation of partial sequences of three genes, andthey identified 32 putative ecotypes among the 11 recognized spe-cies and subspecies within the B. subtilis-Bacillus licheniformisclade (55, 63). Each putative ecotype hypothesized by ES and

TABLE 1 Properties of bacterial species under different models of speciation

Model

Species-like property of ecotypesDistinguishable as sequenceclusters in multilocussequence analysis

Ecologicaldistinctness Cohesion

Irreversibleseparateness

Stable ecotype ✓ ✓ ✓ ✓

Speedy speciation ✓ ✓ ✓

Nanoniche ✓ ✓ (across ecotypes sharing thesame resources)

Speciesless ✓

Recurrent niche invasion ✓ ✓

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AdaptML analyses was confirmed to be ecologically distinct fromother ecotypes through differences in their associations with mi-crohabitats of different solar exposures and soil textures, as well asphysiological differences (13, 55, 64). Nevertheless, we have notyet confirmed whether the putative ecotypes are each homoge-neous in their ecological adaptations.

In this study, we have focused on discovering and characteriz-ing ecological heterogeneity within a single putative ecotype (PE)we previously identified as PE15 and classified within Bacillus sub-tilis subsp. spizizenii (55). We tested for ecological heterogeneitywithin PE15 by comparing the genomes of four PE15 isolates fromRFW, plus the genomes of reference strain W23 of B. subtilissubsp. spizizenii (65) and strain 168 of Bacillus subtilis subsp. sub-tilis (66). We demonstrated a high rate of invention of newecotypes within the putative ecotype PE15. By characterizing thegenetic basis of ecological differences among these ecotypes, weshow that the genome comparisons most strongly support the

nanoniche model, in which the most newly divergent ecotypesutilize only resources that are shared with their closest relativesand ecotypes are not irreversibly separate.

MATERIALS AND METHODS

Strains. We chose PE15 as the focus of this study because it was the bestsampled of all putative ecotypes from RFW and because the fully se-quenced laboratory strain W23 was previously shown to be a member ofPE15 (55). We selected four RFW isolates from PE15 to represent strainsmost likely to be ecologically distinct, based on their habitats of isolationand physiological properties (55). Two strains (RFWG1A3 andRFWG1A4) were isolated from the warmer and sunnier south-facingslope and appeared to be among the best adapted to high temperatures,based on heat adaptation index (HAI), a measure of the proportion ofwarm-adapting fatty acids versus cool-adapting fatty acids; two strains(RFWG4C10 and RFWG5B15) were isolated from the cooler and shadiernorth-facing slope and appeared to be among the best adapted to cooler

FIG 1 Models of bacterial speciation. Ecotypes are represented by different colors, periodic selection events are indicated by asterisks, and extinct lineages arerepresented by dashed lines. The letters at the top represent the resources that each group of organisms can utilize. In cases where ecotypes utilize the same set ofresources but in different proportions, the predominant resource of each ecotype is noted by a capital letter. (A) Stable-ecotype model. In this model, each ecotypeendures many periodic selection events during its long lifetime. The stable-ecotype model generally yields a one-to-one correspondence between ecotypes andsequence clusters. The ecotypes are able to coexist indefinitely because each has a resource not shared with the others (22). (Reprinted from reference 22[copyright 2011 Federation of European Microbiological Societies; published by Blackwell Publishing Ltd., all rights reserved].) (B) Speedy-speciation model.This model is much like the stable-ecotype model, except that speciation occurs so rapidly that most newly divergent ecotypes cannot be detected as sequenceclusters in multilocus analyses (51). (Adapted from reference 51 with permission of Elsevier.) (C) Nanoniche model. Three nanoniche ecotypes use the same setof resources but in different proportions (noted by Abc, aBc, and abC). Each nanoniche ecotype can coexist with the other two because they have partitioned theirresources, at least quantitatively. However, because the ecotypes share all their resources, each is vulnerable to a possible speciation-quashing mutation that mayarise in the other ecotypes. This could be a mutation that increases efficiency in utilization of all resources. These speciation-quashing mutations are indicated bya large asterisk; each of these extinguishes the other nanoniche ecotypes. Thus, in the nanoniche model, cohesion can cut across ecologically distinct populations,provided that they are only quantitatively different in their resource utilization (22). (Reprinted from reference 22 [copyright 2011 Federation of EuropeanMicrobiological Societies; published by Blackwell Publishing Ltd., all rights reserved].) (D) Speciesless model. Here the diversity within an ecotype is limited notby periodic selection but instead by the short time from the ecotype’s invention as a single mutant until its extinction. The origination and extinction of eachecotype i are indicated by si and ei, respectively. In the absence of periodic selection, each extant ecotype that has given rise to another ecotype is a paraphyleticgroup, and each recent ecotype that has not yet given rise to another ecotype is monophyletic (50). (Adapted from reference 50.) (E) Recurrent niche invasionmodel. Here a lineage may move, frequently and recurrently, from one ecotype to another, usually by acquisition and loss of niche-determining plasmids. Redlines indicate the times in which a lineage is in the plasmid-containing ecotype; blue lines indicate the times when the lineage is in the plasmid-absent ecotype.Periodic selection events within one ecotype extinguish only the lineages of the same ecotype. For example, in the most ancient periodic selection event shown,which is in the plasmid-absent (blue) ecotype, only the lineages missing the plasmid at the time of periodic selection are extinguished, while the plasmid-containing lineages (red) persist. Ecotypes determined by a plasmid are not likely to be discoverable as sequence clusters (22). (Reprinted from reference 22[copyright 2011 Federation of European Microbiological Societies; published by Blackwell Publishing Ltd., all rights reserved].)

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temperatures based on HAI (55). We abbreviate the strain names here asG1A3, G1A4, G4C10, and G5B15.

We also included the strains B. subtilis subsp. spizizenii W23 and B.subtilis subsp. subtilis 168, whose genomes were previously sequenced (65,66). Strain W23 was previously classified to the ecotype of interest (PE15),and strain 168 had been classified to PE10; both assignments were basedon analysis of three genes (13, 55).

Genome sequencing and annotation. Genomic DNA was extractedfrom liquid growth cultures, using the Gentra Puregene Yeast/Bact. kit,and was sequenced with a Roche 454 GS FLX pyrosequencer. Genomeswere assembled using MIRA (Mimicking Intelligent Read Assembly) (67,68) and Newbler (69). Contigs were ordered with Mauve (70) using thefully sequenced 168 (66) and W23 (65) genomes for reference. Gaps weremanually closed using Consed (71). The draft genomes were annotatedusing the RAST automated server (72), which uses the SEED framework(73). Genes that were not phage or transposon related or hypotheticalwere classified to one of the functional systems and subsystems of RAST.Some genes were annotated as part of more than one functional subsys-tem or system. For example, the gene for beta-phosphoglucomutase wasclassified to two subsystems within the carbohydrate system: maltose andmaltodextrin utilization and trehalose uptake and utilization.

Core genome phylogeny. We identified orthologous genes shared byall six strains using Mauve (70). These orthologs were aligned and concat-enated to establish a “core genome.” Applying Treefinder (74), we createda maximum likelihood core genome phylogeny for the five PE15 strains,rooted by strain 168.

Genome content comparisons. Regions unique to individual ge-nomes were discovered using the Novel Regions Finder of Panseq (75).Genes shared by each subset of strains were identified using Mauve (70).Unshared genes were categorized as hypothetical, phage or transposonrelated, or functional (i.e., for the bacterium), according to the RASTannotation.

Positive selection. Two tests in the PAML package (76, 77) were im-plemented to identify orthologous genes shared by all six strains that hada history of positive selection on amino acid sequence. We eliminatedfrom analyses any orthologs with stop codons in frame and those whosesequence length was not a multiple of three. We thus tested for positiveselection in 2,892 of the 3,121 genes shared among the six strains.

We first tested for positive selection occurring anywhere in the six-strain phylogeny for each gene by comparing a “nearly neutral” model(M1A) to a positive-selection model (M2A). We then identified genesunder positive selection in each internode of the phylogeny using BranchTest Two. All the genes hypothesized to be under positive selection werechecked for evidence of recombination on the basis of noncongruence ofphylogenies and RDP3 (78).

Growth in monoculture. We employed monoculture and competi-tion experiments to test whether the strains differ in utilization of maltose,maltodextrin, and inositol, as suggested from gene content comparisons.For monoculture growth, the four Death Valley isolates of PE15 weregrown separately in liquid LB medium, and at log phase they were diluted1:2,000 into minimal salts (79) (with no carbon source added) and vor-texed. The diluted culture was added to minimal salts supplemented with1% (final concentration) of glucose, maltose, maltodextrin, or inositol(with no additional carbon source) and incubated at 28°C, with shaking,in a sterile microtiter plate. Growth was monitored in a SpectraMaxM5 microplate reader as percent absorbance at 405 nm at 15-minintervals for 24 h.

For a given substrate, experiments were conducted in three replicateson different days. Within each day, there were two subreplicate growthcultures, stemming from the same LB culture; control growth tests onglucose were based on the same LB culture. The unit of replication in ouranalyses was the mean of the two subreplicates from a given LB culture.Experiments were also set up with minimal medium and no carbon sourceadded, as a control for the effects of possible residual LB.

Competition experiments. For competition experiments, two strains(G1A4 and G4C10) were grown overnight in brain heart infusion (Bacto).Approximately equal numbers of cells from the two strains’ overnightcultures (following previous estimates of cell densities), in a total volumeof 25 �l, were inoculated into 10 ml of minimal medium with glucose,maltose, or maltodextrin (plus citrate, which does not allow significantgrowth of either strain [data not shown]). Cultures were incubated at30°C with shaking (225 rpm) for 22 h. At 0, 4, 13, and 17 h, 1-ml aliquotswere sampled and then stored at �20°C. These time points were selectedto represent the time of inoculation, the beginning of exponential growth,the end of exponential growth, and stationary phase, respectively. Thewhole set of competition experiments was replicated twice, on differentdays.

The abundance of each strain was analyzed by quantitative PCR(qPCR). Bacterial genomic DNA was extracted by incubating 50 �l of theculture at 95°C for 20 min. Primers for each strain were designed from aunique, single-copy gene of its genome using Primer3 (80) (G1A4 geneidentifier [ID], fig�932005.3.peg.207, beta-phosphoglucomutase; G1A4forward, TGCCTCACAATCAGATCAGC; G1A4 reverse, AACACGTTTGGGGATTATGG; G4C10 gene ID, fig�932007.3.peg.1742, hypotheticalprotein; G4C10 forward, CCGCTTTCAAGGTATTGAGC; G4C10 re-verse, AGACCAAAGAAAAGGCATGG; gene IDs assigned by RAST an-notation [72]).

The qPCR was performed with Fast SYBR green master mix (AppliedBiosystems) in the 7500/7500 Fast real-time PCR system, with the holdingstage at 95°C for 20 s and the cycling stage at 95°C for 3 s and 60°C for 30s (40 cycles). Three replicates were conducted for each reaction. The re-producibility of the qPCR essay was evaluated by the standard deviation ofthe cycle numbers required for fluorescence to reach a set threshold, overthree replicates (�0.3). The average cycle number of the three replicateswas used to calculate the copy number. The primer specificity of qPCRessays was verified by a melt curve analysis. Standard curves for each strainwere obtained using its pure genomic DNA for absolute quantification.The consistency of amplification efficiency was validated by the R2 of thestandard curves (all are greater than 0.99).

Analysis of stationary-phase density. Absorbance values at 24 h(monoculture) or qPCR copy number values at 22 h (competition) werelog10 transformed. To account for G1A4’s superior performance in min-imal medium (as measured by growth in minimal medium with glucose),the values for maltose, maltodextrin, and inositol for each replicate ofeach strain were divided by the value for glucose. Strains were comparedfor performance in media with each carbon source (corrected and notcorrected by glucose) in one-way analyses of variance (ANOVAs).

RESULTSGenome sequencing and annotation. All four genomes were se-quenced using 454 pyrosequencing, yielding a total sequence pergenome of 59.22 to 109.92 Mb (see Table S1 in the supplementalmaterial). The genomes were assembled as 11 to 20 contigs, withthe N50 statistic ranging from 285 kbp to 848 kbp. The sizes ofgaps were estimated by comparison to the complete genome se-quence of B. subtilis subsp. spizizenii strain W23 (65). Gaps be-tween contigs were usually shorter than 50 bp, except for the re-petitive RNA genes (see Table S2 in the supplemental material).Thus, the genome assemblies all have an extremely high percentcoverage and are unlikely to have missed any protein-codinggenes. The genome sizes and GC contents of the four RFW strainsof the putative ecotype PE15 (Table 2) were similar to those of B.subtilis subsp. spizizenii strain W23 (65). The assemblies con-tained no separate circular contigs, indicating an absence of plas-mids.

Core genome phylogeny. The mean pairwise average nucleo-tide identity (ANI) value between the PE15 strains and the 168strain of PE10 was 92.9% (Table 3). Within PE15, all strain pairs

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showed an ANI value of �99.4%. The average number of sharedgenes between the PE15 strains and the PE10 strain was 3,566; allpairs within PE15 shared at least 3,869 genes (Table 3).

The core genome alignment confirmed earlier results (55)showing that strain W23 clusters within PE15 (Fig. 2). The PE15clade contains two sister subclades of two strains each, plus a morebasal strain.

Functional capabilities. The members of PE15 were extremelysimilar in their functional capabilities (Fig. 3; see also Table S3 inthe supplemental material). Comparisons across the putativeecotypes PE15 and PE10 showed much greater variation in genecontent across functional systems. For each of three system cate-gories (cell wall and capsule, protein metabolism, and carbohy-drates), each putative ecotype contained at least 24 genes not pres-ent in the other (see Tables S4 and S5 in the supplementalmaterial).

Unique chromosomal regions. Panseq identified 561 genes(in 116 regions) unique to strain 168 of PE10 compared to PE15,197 of which (35.1%) were hypothetical and 68 of which (12.1%)were phage related (Fig. 2A; see also Table S3 in the supplementalmaterial). Mauve identified 186 genes shared among the five PE15strains but not found in PE10, 91 of which (48.9%) were hypo-thetical and 1 of which (0.5%) was phage related (Fig. 2A).

The individual strains of PE15 had an average of 67 uniquegenes. The majority of these (mean, 62.6%) were hypothetical(Fig. 2A). Chromosomal regions unique to subclades (or individ-ual strains) within the PE15 phylogeny indicated the acquisition ofthat region by horizontal genetic transfer, as inferred by maxi-mum parsimony, since each unique gene was most closely relatedto a gene in another species (see Table S4 in the supplementalmaterial).

In a very few cases, the most parsimonious interpretation of

comparative genome content analyses indicated gene loss in aPE15 lineage (see Fig. S1 in the supplemental material). In total,only 30 genes were lost along all the lineages.

Surprisingly, no unique gene conferred a metabolic system orsubsystem function that was not already present in the PE15 coregenome. That is, each unique metabolic gene was either an addi-tional, paralogous copy of a gene already present in all the PE15genomes or an additional gene within one or more functionalsubsystems present in all the PE15 genomes (Table 4; see alsoTable S4 in the supplemental material). The only unique genesto confer a subsystem function not present in all PE15 strains

TABLE 2 Genome sequencing data

Straina

Genomesize (Mb)

Coveragedepth

No. ofgaps

GC content(%)

No. ofcodingsequences

168 4.21 NAb 0 43.5 4,114W23 4.03 NA 0 43.8 4,125G1A3 4.07 13X 19 43.8 4,222G1A4 4.00 19X 10 43.7 4,103G4C10 3.98 25X 13 43.8 4,103G5B15 4.01 19X 10 43.7 4,122a Strains 168 and W23 were sequenced previously (65, 66).b NA, not applicable.

TABLE 3 Average nucleotide identity and number of genes shareda

StrainPE10strain 168

PE15

W23 G1A3 G1A4 G4C10 G5B15

168 92.907 92.919 92.899 92.923 92.933W23 3,530 99.482 99.556 99.522 99.505G1A3 3,619 3,869 99.443 99.592 99.498G1A4 3,533 3,919 3,911 99.540 99.497G4C10 3,554 3,915 3,970 3,923 99.627G5B15 3,592 3,897 4,017 3,959 3,972a The average nucleotide identity (percent) is shown above the diagonal, and thenumber of genes shared is shown below the diagonal for strains of PE15 (within B.subtilis subsp. spizizenii) and PE10 (within B. subtilis subsp. subtilis).

FIG 2 Maximum likelihood core genome phylogeny of PE15 strains, rootedby strain 168 of PE10, with genome content comparisons (A) and positiveselection analyses (B). In each internode, the unique genes are classified asfollows: total genes/genes with known bacterial function/genes present incharacterized functional subsystems. Each node was supported by 100% of1,000 bootstrap replicates. In panel A, the left pie chart for each internodeindicates the proportion of unique genes that are hypothetical, are phage ortransposon related, or have a known bacterial function; the right pie chartindicates the proportion of unique genes in each of the RAST major functionalsystems. In the case of strain 168, the fraction of genes in five systems was toosmall to be visible, with each of the following at 1%: cell division and cell cycle,nitrogen metabolism, potassium metabolism, respiration, and membranetransport. In panel B, the pie charts indicate the functional classification ofgenes under positive selection for amino acid sequence.

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were members of the nonmetabolic restriction-modificationsubsystem.

In the case of the carbohydrate system, for example, G1A3 wasshown to have three unique genes involved in inositol utilization.All of these appear to be acquired from other Bacillus species taxaand are additional, paralogous copies of genes found in all thePE15 genomes sampled. Similarly, G1A4 has nine unique genesinvolved in maltose or maltodextrin utilization, which is a func-tion encoded by all the PE15 genomes: three genes were paralogsof genes shared by all PE15 strains, and six were additional genesinvolved in maltose or maltodextrin utilization, particularly up-take and metabolism of maltodextrin (Table 4).

Growth experiments. In monoculture, the four PE15 strainswere significantly heterogeneous in their stationary-phase densi-ties in minimal medium with maltose, maltodextrin, and inositol(F � 57.13, 143.04, and 4.73; P � 0.0001, P � 0.0001, and P �0.012, respectively; degrees of freedom [df] � 3, 8), as well as in thecontrol medium with glucose (F � 6.06; P � 0.0026; df � 3, 8)(Fig. 4A; see also Fig. S2 in the supplemental material). (Strains

did not grow and were not significantly different from one anotherin control medium with no carbon source added, as shown in Fig.S3 in the supplemental material.) Moreover, the strain expected tohold an advantage in maltose and maltodextrin (G1A4), owing toits nine unique genes, had a significantly higher stationary-phasedensity than each of the other strains with those resources (Tukeytest, P � 0.01). Because G1A4 also had the highest density in theglucose control (although not significantly), we tested whetherthis strain was benefited the greatest by maltose and maltodextrin,by comparing the ratio of densities in maltose and maltodextrin todensities in glucose [log (density in maltose or maltodextrin/den-sity in glucose)]. The four strains were marginally significantlyheterogeneous in their maltose and maltodextrin density ratios(P � 0.080 and 0.075, respectively). As predicted, strain G1A4 hadthe highest average ratio of densities for both maltose and malto-dextrin (Fig. 4B) and, indeed, had the greatest ratio in all threeindependent replicates, expected by chance with a probability of(1/4)3, i.e., 0.016 (for each resource).

In the case of growth in inositol, where G1A3 was expected to

FIG 3 Functional classification of gene content for strain G1A3 of PE15, by RAST functional systems (A) and subsystems (B) within the carbohydrate system.The number of genes in each system or subsystem is indicated in parentheses. The percentages of genes in each system category were very similar across the PE15strains (with an average standard deviation of 0.20% across all system categories) (see Table S3 in the supplemental material). Likewise, the PE15 genomes weresimilar in the number of genes at the subsystem level. For example, in the carbohydrate subsystem, the average standard deviation of gene content was 0.66%.

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be superior owing to its additional three genes, this strain did notreach the highest stationary phase either corrected or uncorrectedfor growth in glucose (Fig. 4; see also Fig. S4 in the supplementalmaterial).

Competition experiments. qPCR analysis of strains G1A4 andG4C10 grown in coculture on maltose and maltodextrin showedthat G1A4 grew to a higher density than G4C10 on both theseresources (maltose, t � 4.05, P � 0.028, 2 df, one-tailed test;maltodextrin, t � 12.0, P � 0.0034, 2 df, one-tailed test; [see Fig.S5 in the supplemental material]). When corrected for growth onglucose, G1A4 still showed superior growth on maltose (although

not significantly) and on maltodextrin (t � 3.21, P � 0.043, 2 df,one-tailed test).

Positive selection. Phylogeny-wide testing for positive selec-tion identified 14 genes under positive selection in one or morePE15 strains (see Table S6 in the supplemental material), and allbut one gene has a known function in B. subtilis subsp. subtilis 168(Fig. 2B).

Branch-specific testing indicated positive selection in 38 geneson six internodes within PE15; all these genes had a known bacte-rial function (Fig. 2B). The individual genomes had relatively fewgenes under positive selection—ranging from 0 to 2 genes per

TABLE 4 Classification of unique genes to functional subsystemsa

PE 15 strainFunctional subsystem(s) (no. of uniquegenes)

Product(s) of unique genes that areparalogs of genes present in all PE15strains

Product(s) of nonparalogous unique genesthat are members of subsystems present inall or some PE15 strains

G1A3 Branched-chain amino acid biosynthesis (1) 3-Isopropylmalate dehydrogenaseLeucine biosynthesis (1) 3-Isopropylmalate dehydrogenaseCBSS-262719.3.peg.410 (1) Replicative DNA helicaseDNA replication (1) Replicative DNA helicaseDNA repair, bacterial (1) DNA-cytosine methyltransferaseb

Glutamine, glutamate, aspartate, andasparagine biosynthesis; Iojap; threonineand homoserine biosynthesis (1)

Transcriptional regulator, GntR familydomain/aspartate aminotransferase

Inositol catabolism; inositol utilization (3) Major myo-inositol transporter IolT;inosose isomerase; myo-inositol2-dehydrogenase

Nitric oxide synthase (1) Putative cytochrome P450 hydroxylasePhosphate metabolism (1) Alkaline phosphatase-like protein

G1A4 Alpha-amylase locus in Streptococcus;bacterial chemotaxis; maltose andmaltodextrin utilization (1)

Maltose/maltodextrin ABC transporter,substrate binding periplasmic proteinMalE

DNA replication (1) DNA replication protein DnaCMaltose and maltodextrin utilization (7) Maltose/maltodextrin ABC transporter,

permease protein MalG; maltose/maltodextrin ABC transporter,permease protein MalF

Neopullulanaseb (2); maltosephosphorylaseb; maltodextroseutilization protein MalAb; maltoseoperon transcriptional repressor MalR,LacI familyb

Maltose and maltodextrin utilization;trehalose uptake and utilization (7)

Beta-phosphoglucomutaseb

Teichoic and lipoteichoic acid biosynthesis(1)

CDP-glycerol:poly(glycerophosphate)glycerophosphotransferase (2)

G4C10 At3g21300 (1) RNA methyltransferase, TrmA familyb

Biotin biosynthesis; biotin biosynthesisexperimental; biotin synthesis cluster;YhgI, YhgH (1)

Adenosylmethionine-8-amino-7-oxononanoate aminotransferase

Protein chaperones; proteolysis in bacteria,ATP dependent (1)

ClpB protein

ESAT-6 protein secretion system inFirmicutes; ESAT-6 protein secretionsystem in Firmicutes (1)

Putative toxin component near putativeESAT-related proteins, repetitive/repetitive hypothetical protein nearESAT cluster, SA0282 homolog (5)

G5B15 Restriction-modification system; type Irestriction-modification (3)

Type I restriction-modification system,specificity subunit Sc; type I restriction-modification system, DNA-methyltransferase subunit Mc; type Irestriction-modification system,restriction subunit Rc

a In some cases, a unique gene was a member of more than one subsystem, indicated with subsystems separated by semicolons. All unique genes either were paralogs of genespresent in all PE15 strains or were nonparalogous additional genes in functional subsystems already present in some or all sampled strains within PE15. In cases where a uniquegene with a given specific function was present in more than one copy, the number of copies is indicated in parentheses (e.g., 2 copies of neopullulanase in G1A4).b Present in all P15 strains.c Present in some P15 strains.

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genome— but each strain was under a unique regimen of positiveselection. Strain G1A4, which had acquired several genes codingfor maltose or maltodextrin utilization, also showed evidence forpositive selection in the maltose or maltodextrin utilization genecoding for glycogen phosphorylase (see Table S6 in the supple-mental material).

DISCUSSION

We have investigated the rate at which bacterial lineages split toform ecologically distinct populations and have aimed to identifythe species-like properties that follow the invention of newecotypes. Our approach was to compare the genomes of very closerelatives that had previously been hypothesized to belong to asingle ecotype, to identify any ecological heterogeneity within theputative ecotype, and to discover the genetic and physiologicalbases of ecological differences.

The previous ecotype simulation and AdaptML analyses of Ba-cillus isolates from Radio Facility Wash of Death Valley, based onthree genes, suggested the clade labeled PE15 to be one ecotypewhose members are ecologically interchangeable with one anotherbut ecologically distinct from other ecotypes (55). This putativeecotype was indeed confirmed to be ecologically distinct from its

close relatives by differences in its habitat associations and inphysiological differences (55). However, like previous studies (13,15, 42, 56–58, 81), our ecological confirmation of ecotypes did nottest for ecological interchangeability among the members of anecotype identified through analysis of sequence diversity.

Evidence of multiple ecotypes within PE15. The genomicanalysis of the five PE15 strains confirmed the earlier conclusion(55) that PE15 is a clade of close relatives. The core genome phy-logeny showed the five PE15 strains to be extremely closely related(Fig. 2), with all pairwise ANI values of �99.4% (Table 3).

The core genome of the PE15 members showed a phylogeneticstructure of two sister clades plus a more basal strain, with allnodes having highly significant support (Fig. 2). This structurewould not be expected under a model in which PE15 is a singleecotype whose diversity is recurrently purged by periodic selec-tion, as previously predicted (55). When periodic selection is thedominant force of cohesion, a star phylogeny is expected to result(with all strains equally related) (51). One explanation for thephylogenetic structure within PE15 would be that genetic drift isthe primary force of cohesion within the ecotype, but the enor-mous population sizes of taxa within the B. subtilis-B. licheniformisclade in nature make this explanation unlikely (13, 55). The mostplausible interpretation is that the phylogenetic structure reflectsthe origination of multiple ecotypes within PE15.

Further evidence of ecological heterogeneity within PE15emerges from tests of positive selection on amino acid sequencesof shared genes. Three of the five PE15 strains showed at least onegene under positive selection, and three of the nonterminal inter-nodes within the PE15 clade also showed positive selection, indi-cating a unique regimen of positive selection on each of the fivePE15 isolates (Fig. 2B). Finding a clade to be under a unique reg-imen of positive selection provides evidence that the clade is adistinct ecotype (23), and so we conclude that each of the five PE15strains sampled represents a separate ecotype. Our genome-basedanalyses have thus indicated five ecotypes within one clade (PE15)that our previous analyses, based on three genes, had demarcatedas a single ecotype (55).

It then became interesting to compare the rates of ecotype for-mation based on the present full-genome analysis versus the pre-vious three-gene analysis (55). Our first step was to estimate therate of ecotype formation within the full B. subtilis-B. licheniformisclade (excluding the outgroup strain from Bacillus halodurans),based on the three genes. A maximum likelihood analysis, usingTreeFinder (74), yielded a Newick tree from which we estimated atotal branch length of 0.872 substitution per site in the entire B.subtilis-B. licheniformis clade. The 31 putative ecotypes previouslyidentified (55) correspond to 30 ecotype formation events ema-nating from an ancestral ecotype. Thus, the resolution of the ear-lier three-gene analysis yields a rate of 34.4 (� 30/0.872) ecotypeformation events per nucleotide substitution per site (over thethree-gene concatenation).

We then estimated the rate of ecotype formation within PE15,based on the present analysis of genomes, where the tree of fivePE15 strains contains five ecotypes, or four ecotype formationevents. A maximum likelihood phylogenetic analysis of the fivePE15 strains, based on the three-gene concatenation, yielded atotal branch length of 0.000605 substitution per site. The origina-tion of four ecotypes within this clade yields 6,610 (� 4/0.000605)ecotype formation events per nucleotide substitution per site (inthe three-gene concatenation). The full-genome analysis thus in-

FIG 4 Stationary-phase densities in monoculture with maltose, maltodextrin,inositol, or glucose. (A) Stationary-phase density (K) as estimated by absor-bance; (B) stationary-phase density corrected by density in glucose.

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dicates a far higher rate of ecotype formation events than the orig-inal three-gene analysis, by a factor of 192.

The ecological uniqueness of every strain in our small samplestrongly suggests an enormous number of ecotypes among ex-tremely close relatives, at least within our focus group of B. subtilis.It appears that ecotypes are formed at too high a rate to be discov-ered by analyzing the sequences of just a few genes. We predict thata high-resolution analysis by either ecotype simulation orAdaptML that is based on the entire core genome would demar-cate multiple ecotypes within PE15.

Additional evidence for ecological heterogeneity within PE15comes from comparisons of gene content. The number of genesunique to a single strain ranged from 22 to 117, and various sub-clades within PE15 also had unique genes. As expected (33, 47),many of the most newly acquired unique genes reflected the com-ings and goings of phage and transposons (Fig. 2A). However,every strain and every clade within PE15 had acquired a set ofunique genes with known bacterial functions, some possibly withniche-specifying properties. In particular, genes in the carbohy-drate system category are among the most likely of the functional,unique genes to have an effect on the ecological niche. Additionalevidence for the ecological significance of the unique genes comesfrom the positive selection analyses on shared genes—the malt-ose-maltodextrin subsystem, which had some unique genes, alsoshowed positive selection in one gene shared by all strains.

The nature of ecological divergence among ecotypes withinPE15. It would be difficult to pinpoint a single ecological or phys-iological dimension along which the PE15 ecotypes have divergedfrom one another. This is because the 38 genes under positiveselection in the PE15 clade comprise a great variety of functionsdivided among multiple system categories (see Table S6 in thesupplemental material). Nevertheless, the horizontally acquiredgenes point to a role for carbohydrate metabolism (see Table S4in the supplemental material). Two possibilities for ecologicaldivergence based on carbohydrate metabolism involve geneacquisitions in the maltose-maltodextrin and inositol subsys-tems (Table 4).

Remarkably, in no case has a functional gene unique to a PE15genome conferred a novel metabolic subsystem function uponthat strain. This is well exemplified by the nine additional genes formaltose or maltodextrin usage in G1A4. Because all the PE15 ge-nomes studied already have the minimum set of genes for maltoseor maltodextrin usage, we may conclude that the additional genesdo not provide a novel resource; indeed, we found that all strainshad the ability to use maltose and maltodextrin as their sole car-bon source when cultured. The nine additional genes in the G1A4genome appear to allow for an expanded usage of maltose andmaltodextrin. For example, the operon of neopullulanase, maltosephosphorylase, and beta-phosphoglucomutase genes in G1A4confers two alternative pathways from maltodextrin to glucose(82). Growth tests confirmed that when maltose or maltodextrinwas the only carbon source, G1A4 grew significantly better inmonoculture than the other strains, and this advantage was cor-roborated in coculture with one other strain. We note that maltoseand maltodextrin are likely resources for soil heterotrophs such asBacillus, as these are breakdown products of starch, which can becontributed to soil from a great diversity of plant sources.

Unique genes in 14 functional subsystems were similarly foundto belong to subsystems present in all other strains (Table 4).Additional genes in the inositol catabolism-utilization pathway

did not give G1A3 a growth advantage in our experiments. There-fore, we conclude that recently acquired genes, even if functional,may not always be adaptive and so adaptations must be experi-mentally confirmed.

In only one case did unique genes confer a subsystem notshared by all members of PE15; this was the case of unique genes inthe restriction-modification subsystem, which confers protectionagainst phage but does not directly affect resource usage.

The limited differences among strains in genome content sug-gest that the ecological distinctness within PE15 is only quantita-tive in nature, with the various ecotypes appearing to share thesame metabolic functions. The sequence differences in sharedproteins, as well as the addition of unique genes in shared path-ways, may contribute to ecotypes utilizing the same chemical re-sources but in different microhabitats or in different proportionsin the same microhabitat.

Which model of ecological speciation? The nanoniche modelappears to best explain the origin of newly divergent ecotypeswithin PE15, given the available data, as no members of PE15show evidence of utilizing any unique resources. This kind ofquantitative divergence runs counter to the intuition built up fordecades by systematic microbiology, where ecological differencesbetween recognized taxa are usually scored as positive versus neg-ative ability to utilize a given resource (83, 84), and where HGTacquisition of new capabilities is thought to drive speciation (24,37). However, closely related populations have been shown to bequantitatively divergent in rates of utilization of shared substrates(85) and in expression of shared genes responsible for metabolismof environmental substrates (42). Moreover, the paradigm ofquantitative ecological divergence is likely the dominant mode ofspecialization in animals and plants (54).

The consequences of the nanoniche model are quite differentfrom those of the stable-ecotype model, in which ecotypes have allthe species-like qualities attributed to species, including ecologicaldistinctness, cohesiveness, irreversible separateness, and recogni-tion through multilocus sequence analysis. In the nanonichemodel, each ecotype is cohesive, in that there may be periodicselection events that sweep the diversity within one ecotype. How-ever, the unit of cohesion would extend beyond the individualnanoniche ecotypes to the set of all ecotypes using the same re-sources (Table 1; Fig. 1C). The possibility of such speciation-quashing adaptive mutations means that the individual nano-niche ecotypes are not irreversibly separate (22, 51, 59).

While the nanoniche model is consistent with the set ofgenomic data at hand, this interpretation must be tentative. Oneissue is that in a larger sample, some strains may have been foundto be qualitatively different in resource utilization (with some re-sources not shared); however, the available data suggest that na-noniche is at least the predominant mode of speciation. One ad-ditional issue is that some of the unique hypothetical genes inPE15 strains may later be shown to be niche specifying and toprovide unshared resources (86).

In that case, there are other possible rapid-speciation modelsthat may explain the high rate of speciation seen within PE15. Onepossibility is that this taxon is in a moment of adaptive radiation,in which ecologically distinct, cohesive (with recurrent periodicselection events), and irreversibly separate ecotypes (each withunique resources) are being invented at a high rate, as in thespeedy-speciation model (Table 1; Fig. 1B). Another possibility isthe speciesless model (Fig. 1D), in which a rapid speciation rate is

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matched by an equally high rate of extinction. This model requiresthat most ecological niches are ephemeral, such that the demise ofa habitat type brings about the extinction of a specialized ecotype,perhaps as seen in the pathogen Neisseria meningitidis (87) or inmarine heterotrophs adapting to an ephemeral particle of marinesnow (60). We have previously laid out a protocol for distinguish-ing the speedy-speciation and speciesless models, but this requiresa larger sample of fully sequenced genomes (50). Finally, one othermodel of rapid ecological change is the recurrent niche invasionmodel, in which a lineage moves in and out of different ecotypeswith the acquisition or loss of various niche-specifying plasmids(Fig. 1E). This model may be ruled out in the present case, as thegenomes showed no plasmids, and more generally the plasmids ofB. subtilis relatives are too small to code for host adaptations (88).

In summary, our focus clade has shown a recent historymarked by the rapid formation of new, ecologically distinct pop-ulations. This result is consistent with the hypothesis of Doolittleand Zhaxybayeva that nearly every strain among close relatives isecologically distinct (19). However, there is no evidence that thesenewly divergent ecotypes are sufficiently distinct to diverge indef-initely; it appears that their divergence may be constrained bycompetition with one another. The most newly divergent ecotypeshave the species-like properties of being ecologically distinct andcohesive, but they appear to lack the property of being irreversiblyseparate.

Divergence between putative ecotypes. The genomic compar-ison of the two putative ecotypes previously identified throughthree-gene analyses, PE15 and PE10, reveals substantial geneticand ecological divergence. First, the average nucleotide identity ofthese groups is much less than that within PE15, at 92.9%. Also,positive selection on amino acid sequences has accelerated thedivergence between PE15 and PE10 in 38 genes across 12 func-tional systems, much more than the case for divergence withinPE15. Finally, gene content comparisons show 186 and 561unique genes for PE15 and PE10, respectively, and many of theseconstitute functional subsystems not present at all in the otherecotype. That is, each putative ecotype appears to utilize resourcesnot available to the other, and they may thus be irreversibly sepa-rate. While the previous three-gene analyses missed the discoveryof ecological heterogeneity within PE15, it appears that the puta-tive ecotypes identified by previous analyses represent the mostclosely related of clades that are both ecologically distinct andirreversibly separate.

ACKNOWLEDGMENTS

This work was supported by funds from Connecticut Space Grant fellow-ships to S.K. and J.W., an NSF FIBR award (EF-0328698) to F.M.C., andresearch funds from Wesleyan University and the University of Virginia.

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