Adaptation by natural selection depends on the rates, effects, and interactions of many mutations, making it difficult to determine what proportion of mutations in an evolving lineage are beneficial. We analysed 264 complete genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The populations that retained the ancestral mutation rate support a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to mutation-accumulation lines evolved under a bottlenecking regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long-term populations, further supporting the inference that most mutations that reached high frequency were favoured by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.

*These authors contributed equally to this work.Adaptation depends on the rates, effects, and interactions of many mutations. We analyzed 264 genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The trajectories for genome evolution in populations that retained the ancestral mutation rate fit a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to lines evolved under a mutation--accumulation regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long--term populations, supporting the inference that most fixed mutations are favored by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Modern systems biology requires extensive, carefully curated measurements of cellular components in response to different environmental conditions. While high-throughput methods have made transcriptomics and proteomics datasets widely accessible and relatively economical to generate, systematic measurements of both mRNA and protein abundances under a wide range of different conditions are still relatively rare. Here we present a detailed, genome-wide transcriptomics and proteomics dataset of E. coli grown under 34 different conditions. Additionally, we provide measurements of doubling times and in-vivo metabolic fluxes through the central carbon metabolism. We manipulate concentrations of sodium and magnesium in the growth media, and we consider four different carbon sources glucose, gluconate, lactate, and glycerol. Moreover, samples are taken both in exponential and stationary phase, and we include two extensive time-courses, with multiple samples taken between 3 hours and 2 weeks. We find that exponential-phase samples systematically differ from stationary-phase samples, in particular at the level of mRNA. Regulatory responses to different carbon sources or salt stresses are more moderate, but we find numerous differentially expressed genes for growth on gluconate and under salt and magnesium stress. Our data set provides a rich resource for future computational modeling of E. coli gene regulation, transcription, and translation.

The genomes of most bacteria contain mobile DNA elements that can contribute to undesirable genetic instability in engineered cells. In particular, transposable insertion sequence (IS) elements can rapidly inactivate genes that are important for a designed function. We deleted all six copies of IS from the genome of the naturally transformable bacterium ADP1. The natural competence of ADP1 made it possible to rapidly repair deleterious point mutations that arose during strain construction. In the resulting ADP1-ISx strain, the rates of mutations inactivating a reporter gene were reduced by 7- to 21-fold. This reduction was higher than expected from the incidence of new IS insertions found during a 300-day mutation accumulation experiment with wild-type ADP1 that was used to estimate spontaneous mutation rates in the strain. The extra improvement appears to be due in part to eliminating large deletions caused by IS activity, as the point mutation rate was unchanged in ADP1-ISx. Deletion of an error-prone polymerase () and a DNA damage response regulator ( [the gene of]) from the ADP1-ISx genome did not further reduce mutation rates. Surprisingly, ADP1-ISx exhibited increased transformability. This improvement may be due to less autolysis and aggregation of the engineered cells than of the wild type. Thus, deleting IS elements from the ADP1 genome led to a greater than expected increase in evolutionary reliability and unexpectedly enhanced other key strain properties, as has been observed for other clean-genome bacterial strains. ADP1-ISx is an improved chassis for metabolic engineering and other applications. ADP1 has been proposed as a next-generation bacterial host for synthetic biology and genome engineering due to its ability to efficiently take up DNA from its environment during normal growth. We deleted transposable elements that are capable of copying themselves, inserting into other genes, and thereby inactivating them from the ADP1 genome. The resulting "clean-genome" ADP1-ISx strain exhibited larger reductions in the rates of inactivating mutations than expected from spontaneous mutation rates measured via whole-genome sequencing of lineages evolved under relaxed selection. Surprisingly, we also found that IS element activity reduces transformability and is a major cause of cell aggregation and death in wild-type ADP1 grown under normal laboratory conditions. More generally, our results demonstrate that domesticating a bacterial genome by removing mobile DNA elements that have accumulated during evolution in the wild can have unanticipated benefits.