The influence of cellular physiology on the initiation of mutational pathways in Escherichia coli populations.
ABSTRACT: The factors affecting the direction of evolutionary pathways and the reproducibility of adaptive responses were investigated under closely related but non-identical conditions. Replicate chemostat cultures of Escherichia coli were compared when adapting to partial or severe glucose limitation. Four independent populations used a reproducible sequence of early mutational changes under both conditions, with rpoS mutations always occurring first before mgl. However, there were interesting differences in the timing of mutational sweeps: rpoS mutations appeared in a clock-like fashion under both partial and severe glucose limitation, while mgl sweeps arose under both conditions but at different times. Interestingly, malT and mlc mutations appeared only under severe limitation. Even though the ancestors were genotypically identical, the semi-differentiated properties of bacteria growing with mild or severe glucose limitation sent the populations in characteristic directions. Mutation supply and the fitness contribution of mutations were estimated and demonstrated to be potential influences in the choice of particular adaptation pathways under severe and mild glucose limitation. Predicting all the mutations fixed in adapting populations is beyond our current understanding of evolutionary processes, but the interplay between ancestor physiology and the initiation of adaptation pathways is demonstrated and definable in bacterial populations.
Project description:Changes in allele frequencies and the fixation of beneficial mutations are central to evolution. The precise relationship between mutational and phenotypic sweeps is poorly described however, especially when multiple alleles are involved. Here, we investigate these relationships in a bacterial population over 60 days in a glucose-limited chemostat in a large population. High coverage metagenomic analysis revealed a disconnection between smooth phenotypic sweeps and the complexity of genetic changes in the population. Phenotypic adaptation was due to convergent evolution and involved soft sweeps by 7-26 highly represented alleles of several genes in different combinations. Allele combinations spread from undetectably low baselines, indicating that minor subpopulations provide the basis of most innovations. A hard sweep was also observed, involving a single combination of rpoS, mglD, malE, sdhC, and malT mutations sweeping to greater than 95% of the population. Other mutant genes persisted but at lower abundance, including hfq, consistent with its demonstrated frequency-dependent fitness under glucose limitation. Other persistent, newly identified low-frequency mutations were in the aceF, galF, ribD and asm genes, in noncoding regulatory regions, three large indels and a tandem duplication; these were less affected by fluctuations involving more dominant mutations indicating separate evolutionary paths. Our results indicate a dynamic subpopulation structure with a minimum of 42 detectable mutations maintained over 60 days. We also conclude that the massive population-level mutation supply in combination with clonal interference leads to the soft sweeps observed, but not to the exclusion of an occasional hard sweep.
Project description:Microbial populations founded by a single clone and propagated under resource limitation can become polymorphic. We sought to elucidate genetic mechanisms whereby a polymorphism evolved in Escherichia coli under glucose limitation and persisted because of cross-feeding among multiple adaptive clones. Apart from a 29 kb deletion in the dominant clone, no large-scale genomic changes distinguished evolved clones from their common ancestor. Using transcriptional profiling on co-evolved clones cultured separately under glucose-limitation we identified 180 genes significantly altered in expression relative to the common ancestor grown under similar conditions. Ninety of these were similarly expressed in all clones, and many of the genes affected (e.g., mglBAC, mglD, and lamB) are in operons coordinately regulated by CRP and/or rpoS. While the remaining significant expression differences were clone-specific, 93% were exhibited by the majority clone, many of which are controlled by global regulators, CRP and CpxR. When transcriptional profiling was performed on adaptive clones cultured together, many expression differences that distinguished the majority clone cultured in isolation were absent, suggesting that CpxR may be activated by overflow metabolites removed by cross-feeding strains in co-culture. Relative to their common ancestor, shared expression differences among adaptive clones were partly attributable to early-arising shared mutations in the trans-acting global regulator, rpoS, and the cis-acting regulator, mglO. Gene expression differences that distinguished clones may in part be explained by mutations in trans-acting regulators malT and glpK, and in cis-acting sequences of acs. In the founder, a cis-regulatory mutation in acs (acetyl CoA synthetase) and a structural mutation in glpR (glycerol-3-phosphate repressor) likely favored evolution of specialists that thrive on overflow metabolites. Later-arising mutations that led to specialization emphasize the importance of compensatory rather than gain-of-function mutations in this system. Taken together, these findings underscore the importance of regulatory change, founder genotype, and the biotic environment in the adaptive evolution of microbes.
Project description:Understanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation, including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.
Project description:Emergence of antibiotic resistance, an evolutionary process of major importance for human health , often occurs under changing levels of antibiotics. Selective sweeps, in which resistant cells become dominant in the population, are a critical step in this process . While resistance emergence has been studied in laboratory experiments [3-8], the full progression of selective sweeps under fluctuating stress, from stochastic events in single cells to fixation in populations, has not been characterized. Here, we study fluctuating selection using Escherichia coli populations engineered with a stochastic switch controlling tetracycline resistance. Using microfluidics and live-cell imaging, we treat multiple E. coli populations with the same total amount of tetracycline but administered in different temporal patterns. We find that populations exposed to either short or long antibiotic pulses are likely to develop resistance through selective sweeps, whereas intermediate pulses allow higher growth rates but suppress selective sweeps. On the basis of single-cell measurements and a dynamic growth model, we identify the major determinants of population growth and show that both physiological memory and environmental durations can strongly modulate the emergence of resistance. Our detailed quantification in a model synthetic system provides key lessons on the interaction between single-cell physiology and selection that should inform the design of treatment regimens [9-12] and the analysis of phenotypically diverse populations adapting under fluctuating selection [13-17].
Project description:Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a "one-step" mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.
Project description:The alternative sigma factor RpoS controls a large regulon that allows E. coli to respond to a variety of stresses. Mutations in rpoS can increase rates of nutrient acquisition at the cost of a decrease in stress resistance. These kinds of mutations evolve rapidly under certain laboratory conditions where nutrient acquisition is especially challenging. The frequency of strains lacking RpoS in natural populations of E. coli is less clear. Such strains have been found at frequencies over 20% in some collections of wild isolates. However, laboratory handling can select for RpoS-null strains and may have affected some of these strain collections. Other studies have included an unknown diversity of strains or only used a phenotypic proxy as a measure of RpoS levels. We directly measured RpoS levels in a collection of E. coli that includes the full diversity of the species and that was handled in a manner to minimize the potential for laboratory evolution. We found that only 2% of strains produce no functional RpoS. Comparison of these strains in multiple labs shows that these rpoS mutations occurred in the laboratory. Earlier studies reporting much higher levels of RpoS polymorphism may reflect the storage history of the strains in laboratories rather than true frequency of such strains in natural populations.
Project description:Long-term survival under limited growth conditions presents bacterial populations with unique environmental challenges. The existence of Salmonella enterica serovar Typhimurium cultures undisturbed in sealed nutrient agar stab vials for 34 to 45 years offered a unique opportunity to examine genetic variability under natural conditions. We have initiated a study of genetic changes in these archival cultures. We chose to start with examination of the rpoS gene since, among gram-negative bacteria, many genes needed for survival are regulated by RpoS, the stationary-phase sigma factor. In each of 27 vials examined, cells had the rpoS start codon UUG instead of the expected AUG of Salmonella and Escherichia coli strains recorded in GenBank. Ten of the 27 had additional mutations in the rpoS gene compared with the X77752 wild-type strain currently recorded in GenBank. The rpoS mutations in the 10 strains included two deletions as well as point mutations that altered amino acid sequences substantially. Since these stored strains were derived from ancestral cells inoculated decades ago and remained undisturbed, it is assumed that the 10 rpoS mutations occurred during storage. Since the remaining 17 sequences were wild type (other than in the start codon), it is obvious that rpoS remained relatively stable during decades of sealed storage.
Project description:The genetic diversity of a species is shaped by its recent evolutionary history and can be used to infer demographic events or selective sweeps. Most inference methods are based on the null hypothesis that natural selection is a weak or infrequent evolutionary force. However, many species, particularly pathogens, are under continuous pressure to adapt in response to changing environments. A statistical framework for inference from diversity data of such populations is currently lacking. Towards this goal, we explore the properties of genealogies in a model of continual adaptation in asexual populations. We show that lineages trace back to a small pool of highly fit ancestors, in which almost simultaneous coalescence of more than two lineages frequently occurs. Whereas such multiple mergers are unlikely under the neutral coalescent, they create a unique genetic footprint in adapting populations. The site frequency spectrum of derived neutral alleles, for example, is nonmonotonic and has a peak at high frequencies, whereas Tajima's D becomes more and more negative with increasing sample size. Because multiple merger coalescents emerge in many models of rapid adaptation, we argue that they should be considered as a null model for adapting populations.
Project description:Beneficial mutations in diversifying glucose-limited Escherichia coli populations are mostly unidentified. The genome of an evolved isolate with multiple differences from that of the ancestor was fully assembled. Remarkably, a single mutation in hfq was responsible for the multiple benefits under glucose limitation through changes in at least five regulation targets.
Project description:Nutrient starvation is an important survival challenge for bacteria during industrial production of functional foods. Lactobacilli are increasingly being used as probiotics in functional foods. As next-generation sequencing technology has greatly advanced, we performed integrative proteomic and genomic analysis to investigate the response of Lactobacillus casei Zhang to a glucose-restricted environment. L. casei Zhang strains were permitted to evolve in glucose-limited or normal medium from a common ancestor over a 3-year period, and they were sampled after 1000, 2000, 3000, 4000, 5000, 6000, 7000, and 8000 generations and subjected to proteomic and genomic analyses. Genomic resequencing data revealed different point mutations and other mutational events in each generation of L. casei Zhang under glucose limitation stress. The proteins expressed differentially under glucose limitation were found to be significantly related to fructose and mannose metabolism, carbohydrate metabolic processes, lyase activity, and amino acid-transporting ATPase activity. The integrative proteomic and genomic analysis revealed that the mutations protected L. casei Zhang against glucose starvation by regulating other cellular carbohydrate, fatty acid, and amino acid catabolism; phosphoenolpyruvate system pathway activation; glycogen synthesis; ATP consumption; pyruvate metabolism; and general stress response protein expression. The results help reveal the mechanisms of adapting to glucose starvation and provide new strategies for enhancing the industrial utility of L. casei Zhang.