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.2008 Feb 19;105(7):2504-9.
doi: 10.1073/pnas.0712205105. Epub 2008 Feb 12.

Identifying the fundamental units of bacterial diversity: a paradigm shift to incorporate ecology into bacterial systematics

Affiliations

Identifying the fundamental units of bacterial diversity: a paradigm shift to incorporate ecology into bacterial systematics

Alexander Koeppel et al. Proc Natl Acad Sci U S A..

Abstract

The central questions of bacterial ecology and evolution require a method to consistently demarcate, from the vast and diverse set of bacterial cells within a natural community, the groups playing ecologically distinct roles (ecotypes). Because of a lack of theory-based guidelines, current methods in bacterial systematics fail to divide the bacterial domain of life into meaningful units of ecology and evolution. We introduce a sequence-based approach ("ecotype simulation") to model the evolutionary dynamics of bacterial populations and to identify ecotypes within a natural community, focusing here on two Bacillus clades surveyed from the "Evolution Canyons" of Israel. This approach has identified multiple ecotypes within traditional species, with each predicted to be an ecologically distinct lineage; many such ecotypes were confirmed to be ecologically distinct, with specialization to different canyon slopes with different solar exposures. Ecotype simulation provides a long-needed natural foundation for microbial ecology and systematics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Observed and modeled clade sequence diversity patterns. Sequences for a gene (or a concatenation of genes) were binned by complete linkage clustering (23) into clusters with different levels of minimum pairwise identity. ES analysis of each clade yielded two solutions, one with low drift and one with high drift. The high-drift solutions require population sizes that are unrealistically low for these taxa (SI), so the model curves are based on the low-drift solutions. For taxa with low population sizes and/or extremely high recombination rates, high-drift solutions (with little or no periodic selection) may be the most appropriate. The individual points for each model are means based on 1,000 replications of the low-drift solution. (A) Diversity among 116B. simplex isolates from Evolution Canyons I and II based on a concatenation ofgapA,rpoB, anduvrA, with recombinant organisms removed. (B) Diversity among 73 isolates within theB. licheniformis–B. subtilis clade, primarily from Evolution Canyon III, as based on a concatenation ofgapA,gyrA, andrpoB, with recombinant organisms removed.
Fig. 2.
Fig. 2.
The ecotype simulation algorithm. The algorithm simulates the evolutionary history of the ν organisms sampled from nature, under different quartets of values for the net rate of ecotype formation (EF), the rates of periodic selection (PS) and drift (D), and the number of ecotypes in the sample. In the coalescence approach taken (36), the algorithm considers only the lineages that are directly ancestral to the ν sampled organisms (represented by black circles). These focal lineages are represented by solid lines; the many contemporary lineages not sampled from each ecotype are indicated by light dashed lines (E1, E2, and E3); the lineages extinguished by past PS and D are represented by bold short-dashed lines and long-dashed lines, respectively, with each extinction represented by a square. The program begins with a “backward” simulation that stochastically produces a phylogenetic representation of the history of the community, establishing nodes of coalescence of lineages (due to PS, EF, or D; indicated by gray circles) and time between nodes (t1, t2, etc.); this phylogeny is then taken as a scaffold for the forward simulation. The purpose of the forward simulation is to produce mutational nucleotide substitutions throughout the history of the clade, according to the phylogenetic scaffold. To begin a simulation, a set of ν contemporary organisms (representing the ν organisms sampled from nature) are distributed randomly (according to the canonical lognormal distribution) amongn ecotypes (here, ν = 14 andn = 3). Working backward from the ν organisms in the present, the processes of EF, PS, and D occur stochastically in time according to their respective rates (Ω, σ, andd). For each such event, one or more lineages coalesce into a single ancestral lineage, as described inSI. Note that in the backward-looking view of the coalescence formulation, each PS appears as a coalescence event, in which all lineages after the PS coalesce into the survivor of the PS event. Likewise, each D event appears in this backward-looking view as the coalescence of a pair of lineages within an ecotype (e.g., two contemporary lineages coalesce into lineage D1 to reflect the increased representation of lineage D1 after the random loss by drift of lineage D2). Because Ω is the net rate of EF events, taking into account extinction, we include in the simulation only those EF events resulting in ecotypes that survive into our contemporary sample. The backward phase of the simulation ends when all of the branches have coalesced into a single node; this represents the most recent common ancestor of all of the sampled organisms. Then the forward simulation begins when a sequence (of the same length as the observed sequence data) is assigned to this most recent common ancestor. Nucleotide substitutions then occur stochastically, going forward in time, between each pair of nodes in the phylogeny derived from the backward simulation, according to the time between the events determining the nodes. This generates a matrix of pairwise sequence divergence between all ν contemporary organisms for a simulation replicate, from which a clade sequence diversity curve is calculated; the simulated clade sequence diversity curve is then compared against the observed clade sequence diversity curve (seeSI).
Fig. 3.
Fig. 3.
Phylogeny and ecotype demarcation of theB. simplex andB. subtilis–B. licheniformis clades. Phylogenies are based on parsimony, with 100-replicate bootstrapping, using MEGA (37). In isolates for which one gene had recombined (a group of related recombinants is indicated by “R” following the number of recombinants), the recombined gene was replaced in the input for MEGA by “unknown” nucleotides; so the phylogeny estimates the recombination-free tree. Ecotypes were demarcated conservatively as the most inclusive clades that were each consistent with being a single ecotype (SI). For nearly all putative ecotypes, the maximum likelihood solution ofn was equal to 1, although in some casesn = 2 with the lower confidence interval includingn = 1. Ecotype demarcations are indicated by brackets, for the concatenation and each individual gene. The ecotype demarcations were similar based on the concatenation and the individual genes, except that the more rapidly evolving genes (gyrA in the case ofB. subtilis–B. licheniformis andrpoB in the case of those genes analyzed inB. simplex) tended to split the ecotypes determined by analysis of the concatenation. For isolates that had recombined at one gene locus, ecotype placement was determined by ES of the two genes that had not recombined. For example, the three recombinants indicated within PE 5 of theB. subtilis–B. licheniformis clade (which had recombined atgapA) were found to be in the same ecotype as the members of PE 5 in analyses ofgyrA andrpoB. With two exceptions, demarcated ecotypes were supported as monophyletic groups in at least 50% of bootstrap replications; the exceptions were PE9 ofB. simplex and PE8 of theB. subtilis–B. licheniformis clade, which are asterisked to indicate that their phylogenetic status is tentative, pending additional sequence data. The median bootstrap support for putative ecotypes was 72% withinB. simplex and 99% within theB. subtilis–B. licheniformis clade. Whereas theB. simplex ecotypes do not generally have high bootstrap support, owing in part to their very close relatedness, their monophyly is supported by alternative phylogenetic approaches, including Bayesian and neighbor joining algorithms (data not shown). Microhabitat sources were the south-facing slope (open circles), the north-facing slope (filled circles), and the canyon bottom (indicated by V). For each ecotype represented by at least four isolates, the principal microhabitat source(s) is indicated. If one microhabitat provided at least 80% of the isolates, the principal microhabitat source is indicated; for ecotypes not so dominated by a single source, all microhabitat sources are indicated. The number of isolates from each source is indicated. (A) The phylogeny ofB. simplex rooted byB. subtilis,B. licheniformis,B. cereus, andB. halodurans. The nine putative ecotypes of this clade differ significantly in their associations with the two slopes. (B) The phylogeny of theB. subtilis–B. licheniformis clade rooted byB. halodurans. The 13 putative ecotypes differ significantly in their associations with the two slopes and the canyon bottom.
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