Charles C. Traverse

Tangled bank of experimentally evolved Burkholderia biofilms reflects selection during chronic infections

How diversity evolves and persists in biofilms is essential for understanding much of microbial life, including the uncertain dynamics of chronic infections. We developed a biofilm model enabling long-term selection for daily adherence to and dispersal from a plastic bead in a test tube. Focusing on a pathogen of the cystic fibrosis lung, Burkholderia cenocepacia, we sequenced clones and metagenomes to unravel the mutations and evolutionary forces responsible for adaptation and diversification of a single biofilm community during 1,050 generations of selection. The mutational patterns revealed recurrent evolution of biofilm specialists from generalist types and multiple adaptive alleles at relatively few loci. Fitness assays also demonstrated strong interference competition among contending mutants that preserved genetic diversity. Metagenomes from five other independently evolved biofilm lineages revealed extraordinary mutational parallelism that outlined common routes of adaptation, a subset of which was found, surprisingly, in a planktonic population. These mutations in turn were surprisingly well represented among mutations that evolved in cystic fibrosis isolates of both Burkholderia and Pseudomonas. These convergent pathways included altered metabolism of cyclic diguanosine monophosphate, polysaccharide production, tricarboxylic acid cycle enzymes, global transcription, and iron scavenging. Evolution in chronic infections therefore may be driven by mutations in relatively few pathways also favored during laboratory selection, creating hope that experimental evolution may illuminate the ecology and selective dynamics of chronic infections and improve treatment strategies.

Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq

BackgroundMutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.ResultsWe have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold).ConclusionsUsing breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles

Significance Organisms rely on accurate transcription for proper cellular function. Whereas errors incurred during replication are transmitted to subsequent generations, those that occur during transcription are transient and affect only a subset of the encoded proteins. Although transcription errors may increase survival in stressful conditions, the majority of these errors are harmful, and their rates must be minimized. By assessing the transcription errors genome-wide in Escherichia coli and in two bacterial endosymbionts, we discovered that all species had remarkably similar transcription error rates. This conservation is unexpected given that both endosymbiotic species lack orthologs of several E. coli RNA fidelity factors and that lifestyle differences among these species have led to vast differences in their mutation and substitution rates. Errors that occur during transcription have received much less attention than the mutations that occur in DNA because transcription errors are not heritable and usually result in a very limited number of altered proteins. However, transcription error rates are typically several orders of magnitude higher than the mutation rate. Also, individual transcripts can be translated multiple times, so a single error can have substantial effects on the pool of proteins. Transcription errors can also contribute to cellular noise, thereby influencing cell survival under stressful conditions, such as starvation or antibiotic stress. Implementing a method that captures transcription errors genome-wide, we measured the rates and spectra of transcription errors in Escherichia coli and in endosymbionts for which mutation and/or substitution rates are greatly elevated over those of E. coli. Under all tested conditions, across all species, and even for different categories of RNA sequences (mRNA and rRNAs), there were no significant differences in rates of transcription errors, which ranged from 2.3 × 10−5 per nucleotide in mRNA of the endosymbiont Buchnera aphidicola to 5.2 × 10−5 per nucleotide in rRNA of the endosymbiont Carsonella ruddii. The similarity of transcription error rates in these bacterial endosymbionts to that in E. coli (4.63 × 10−5 per nucleotide) is all the more surprising given that genomic erosion has resulted in the loss of transcription fidelity factors in both Buchnera and Carsonella.

Character displacement and the evolution of niche complementarity in a model biofilm community

Colonization of vacant environments may catalyze adaptive diversification and be followed by competition within the nascent community. How these interactions ultimately stabilize and affect productivity are central problems in evolutionary ecology. Diversity can emerge by character displacement, in which selection favors phenotypes that exploit an alternative resource and reduce competition, or by facilitation, in which organisms change the environment and enable different genotypes or species to become established. We previously developed a model of long‐term experimental evolution in which bacteria attach to a plastic bead, form a biofilm, and disperse to a new bead. Here, we focus on the evolution of coexisting mutants within a population of Burkholderia cenocepacia and how their interactions affected productivity. Adaptive mutants initially competed for space, but later competition declined, consistent with character displacement and the predicted effects of the evolved mutations. The community reached a stable equilibrium as each ecotype evolved to inhabit distinct, complementary regions of the biofilm. Interactions among ecotypes ultimately became facilitative and enhanced mixed productivity. Observing the succession of genotypes within niches illuminated changing selective forces within the community, including a fundamental role for genotypes producing small colony variants that underpin chronic infections caused by B. cenocepacia.

Detecting rare structural variation in evolving microbial populations from new sequence junctions using breseq.

New mutations leading to structural variation (SV) in genomes—in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements—can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide substitutions and indels (SN), so it is not yet routinely identified in studies that profile population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm using simulated Escherichia coli data and then applied it to 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously analyzed clonal isolates allowed us to evaluate the accuracy of our procedure. Overall, SV accounted for ~25% of the genetic diversity found in these samples. By profiling rare SV, we were able to identify many cases where alternative mutations in key genes transiently competed within a single population. We also found, unexpectedly, that mutations in two genes that rose to prominence at these early time points always went extinct in the long term. Because it is not limited by the base-calling error rate of the sequencing technology, our approach for identifying rare SV in whole-population samples may have a lower detection limit than similar predictions of SNs in these data sets. We anticipate that this functionality of breseq will be useful for providing a more complete picture of genome dynamics during evolution experiments with haploid microorganisms.

Impermanence of bacterial clones.

Bacteria reproduce asexually and pass on a single genome copied from the parent, a reproductive mode that assures the clonal descent of progeny; however, a truly clonal bacterial species is extremely rare. The signal of clonality can be interrupted by gene uptake and exchange, initiating homologous recombination that results in the unique sequence of one clone being incorporated into another. Because recombination occurs sporadically and on local scales, these events are often difficult to recognize, even when considering large samples of completely sequenced genomes. Moreover, several processes can produce the appearance of clonality in populations that undergo frequent recombination. The rates and consequences of recombination have been studied in Escherichia coli for over 40 y, and, during this time, there have been several shifting views of its clonal status, population structure, and rates of gene exchange. We reexamine the studies and retrace the evolution of the methods that have assessed the extent of DNA flux, largely focusing on its impact on the E. coli genome.

There and back again: consequences of biofilm specialization under selection for dispersal

Experimental evolution paired with modern sequencing can be a powerful approach to identify the mechanisms by which bacteria adapt to discrete environmental conditions found in nature or during infections. We used this approach to identify mechanisms enabling biofilm specialists of the opportunistic respiratory pathogen Burkholderia cenocepacia to regain planktonic fitness. Seven mutants producing wrinkly (W) small-colony variants by mutations in the wrinkly-spreader operon (wsp) cluster, but with varying duration of biofilm adaptation, served as ancestors of this experiment. Following planktonic growth, each W ancestor produced smooth (S) mutants with distinct fitness effects across planktonic, biofilm, and dispersal-phase environments. The causes of the S phenotype traced to mutations in three gene clusters: wsp, Bcen2424_1436, an uncharacterized two-component transcriptional regulator which appears to be critical for wsp signaling, and a cohort of genes involved in polysaccharide synthesis. The genetic pathway from W to S also associated with evolutionary history in the biofilm environment. W mutants isolated from long-term biofilm selection usually produced S types via secondary wsp mutations, whereas S types evolved from less adapted W ancestors by a wider scope of mutations. These different genetic pathways to suppress the W phenotype suggest that prolonged biofilm adaptation limits routes to subsequent planktonic adaptation, despite common initial mechanisms of biofilm adaptation. More generally, experimental evolution can be used as a nuanced screen for gain-of-function mutations in multiple conditions that illustrate tensions that bacteria may face in changing environments or hosts.

Local genic base composition impacts protein production and cellular fitness

The maintenance of a G + C content that is higher than the mutational input to a genome provides support for the view that selection serves to increase G + C contents in bacteria. Recent experimental evidence from Escherichia coli demonstrated that selection for increasing G + C content operates at the level of translation, but the precise mechanism by which this occurs is unknown. To determine the substrate of selection, we asked whether selection on G + C content acts across all sites within a gene or is confined to particular genic regions or nucleotide positions. We systematically altered the G + C contents of the GFP gene and assayed its effects on the fitness of strains harboring each variant. Fitness differences were attributable to the base compositional variation in the terminal portion of the gene, suggesting a connection to the folding of a specific protein feature. Variants containing sequence features that are thought to result in rapid translation, such as low G + C content and high levels of codon adaptation, displayed highly reduced growth rates. Taken together, our results show that purifying selection acting against A and T mutations most likely results from their tendency to increase the rate of translation, which can perturb the dynamics of protein folding.

A Genome-Wide Assay Specifies Only GreA as a Transcription Fidelity Factor in Escherichia coli

Although mutations are the basis for adaptation and heritable genetic change, transient errors occur during transcription at rates that are orders of magnitude higher than the mutation rate. High rates of transcription errors can be detrimental by causing the production of erroneous proteins that need to be degraded. Two transcription fidelity factors, GreA and GreB, have previously been reported to stimulate the removal of errors that occur during transcription, and a third fidelity factor, DksA, is thought to decrease the error rate through an unknown mechanism. Because the majority of transcription-error assays of these fidelity factors were performed in vitro and on individual genes, we measured the in vivo transcriptome-wide error rates in all possible combinations of mutants of the three fidelity factors. This method expands measurements of these fidelity factors to the full spectrum of errors across the entire genome. Our assay shows that GreB and DksA have no significant effect on transcription error rates, and that GreA only influences the transcription error rate by reducing G-to-A errors.