scholarly journals Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli

2011 ◽  
Vol 1 (3) ◽  
pp. 183-186 ◽  
Author(s):  
Sébastien Wielgoss ◽  
Jeffrey E. Barrick ◽  
Olivier Tenaillon ◽  
Stéphane Cruveiller ◽  
Béatrice Chane-Woon-Ming ◽  
...  
Author(s):  
Rohan Maddamsetti

Abstract Although it is well known that abundant proteins evolve slowly across the tree of life, there is little consensus for why this is true. Here, I report that abundant proteins evolve slowly in the hypermutator populations of Lenski’s long-term evolution experiment with Escherichia coli (LTEE). Specifically, the density of all observed mutations per gene, as measured in metagenomic time series covering 60,000 generations of the LTEE, significantly anti-correlates with mRNA abundance, protein abundance, and degree of protein-protein interaction. The same pattern holds for nonsynonymous mutation density. However, synonymous mutation density, measured across the LTEE hypermutator populations, positively correlates with protein abundance. These results show that universal constraints on protein evolution are visible in data spanning three decades of experimental evolution. Therefore, it should be possible to design experiments to answer why abundant proteins evolve slowly.


2020 ◽  
Author(s):  
Rohan Maddamsetti ◽  
Nkrumah A. Grant

ABSTRACTAll organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good, et al. 2017), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB— loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.


2016 ◽  
Author(s):  
Rohan Maddamsetti ◽  
Philip J. Hatcher ◽  
Anna G. Green ◽  
Barry L. Williams ◽  
Debora S. Marks ◽  
...  

AbstractBacteria can evolve rapidly under positive selection owing to their vast numbers, allowing their genes to diversify by adapting to different environments. We asked whether the same genes that are fast evolving in the long-term evolution experiment with Escherichia coli (LTEE) have also diversified extensively in nature. We identified ~2000 core genes shared among 60 E. coli strains. During the LTEE, core genes accumulated significantly more nonsynonymous mutations than flexible (i.e., noncore) genes. Furthermore, core genes under positive selection in the LTEE are more conserved in nature than the average core gene. In some cases, adaptive mutations appear to fine-tune protein functions, rather than merely knocking them out. The LTEE conditions are novel for E. coli, at least in relation to the long sweep of its evolution in nature. The constancy and simplicity of the environment likely favor the complete loss of some unused functions and the fine-tuning of others.Competing Interests StatementWe, the authors, declare that we have no conflicts of interest.


2021 ◽  
Author(s):  
Rohan Maddamsetti

AbstractBacteria, Archaea, and Eukarya all share a common set of metabolic reactions. This implies that the function and topology of central metabolism has been evolving under purifying selection over deep time. Central metabolism may similarly evolve under purifying selection during longterm evolution experiments, although it is unclear how long such experiments would have to run (decades, centuries, millennia) before signs of purifying selection on metabolism appear. I hypothesized that central and superessential metabolic enzymes would show evidence of purifying selection in the long-term evolution experiment with Escherichia coli (LTEE), in which 12 initially identical bacterial populations have been evolving in the laboratory for more than 30 years and 60,000 bacterial generations. I also hypothesized that enzymes that specialize on single substrates would show stronger evidence of purifying selection in the LTEE than generalist enzymes that catalyze multiple reactions. I tested these hypotheses by analyzing metagenomic time series covering 60,000 generations of the LTEE. I find mixed support for these hypotheses: patterns of purifying selection on metabolic enzymes, at least after 60,000 generations of experimental evolution, are largely idiosyncratic and population-specific.Significance StatementPurifying selection conserves organismal function over evolutionary time. I looked for evidence of purifying selection on metabolic enzymes in an ongoing long-term evolution experiment with E. coli. While some populations show signs of purifying selection, the overall pattern is inconsistent. To explain this finding, I propose that each population’s metabolism is evolving in a molecular game of Jenga. In this conceptual model, loss-of-function mutations degrade costly, redundant, and inessential metabolic functions, after which purifying selection begins to dominate. The threshold at which purifying selection activates depends on the idiosyncratic trajectory of lost redundancies in each population.


2017 ◽  
Vol 9 (4) ◽  
pp. 1072-1083 ◽  
Author(s):  
Rohan Maddamsetti ◽  
Philip J. Hatcher ◽  
Anna G. Green ◽  
Barry L. Williams ◽  
Debora S. Marks ◽  
...  

2020 ◽  
Vol 12 (9) ◽  
pp. 1591-1603 ◽  
Author(s):  
Rohan Maddamsetti ◽  
Nkrumah A Grant

Abstract All organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good BH, McDonald MJ, Barrick JE, Lenski RE, Desai MM. 2017. The dynamics of molecular evolution over 60,000 generations. Nature 551(7678):45–50.), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB—loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.


mBio ◽  
2014 ◽  
Vol 5 (5) ◽  
Author(s):  
Colin Raeside ◽  
Joël Gaffé ◽  
Daniel E. Deatherage ◽  
Olivier Tenaillon ◽  
Adam M. Briska ◽  
...  

ABSTRACTLarge-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelveEscherichia colipopulations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement events were detected, including 82 deletions, 19 inversions, and 9 duplications, with lineages having between 5 and 20 events. In three populations, successive rearrangements impacted particular regions. In five populations, rearrangements affected over a third of the chromosome. Most rearrangements involved recombination between insertion sequence (IS) elements, illustrating their importance in mediating genome plasticity. Two lines of evidence suggest that at least some of these rearrangements conferred higher fitness. First, parallel changes were observed across the independent populations, with ~65% of the rearrangements affecting the same loci in at least two populations. For example, the ribose-utilization operon and themanB-cpsGregion were deleted in 12 and 10 populations, respectively, suggesting positive selection, and this inference was previously confirmed for the former case. Second, optical maps from clones sampled over time from one population showed that most rearrangements occurred early in the experiment, when fitness was increasing most rapidly. However, some rearrangements likely occur at high frequency and may have simply hitchhiked to fixation. In any case, large-scale rearrangements clearly influenced genomic evolution in these populations.IMPORTANCEBacterial chromosomes are dynamic structures shaped by long histories of evolution. Among genomic changes, large-scale DNA rearrangements can have important effects on the presence, order, and expression of genes. Whole-genome sequencing that relies on short DNA reads cannot identify all large-scale rearrangements. Therefore, deciphering changes in the overall organization of genomes requires alternative methods, such as optical mapping. We analyzed the longest-running microbial evolution experiment (more than 25 years of evolution in the laboratory) by optical mapping, genome sequencing, and PCR analyses. We found multiple large genome rearrangements in all 12 independently evolving populations. In most cases, it is unclear whether these changes were beneficial themselves or, alternatively, hitchhiked to fixation with other beneficial mutations. In any case, many genome rearrangements accumulated over decades of evolution, providing these populations with genetic plasticity reminiscent of that observed in some pathogenic bacteria.


Sign in / Sign up

Export Citation Format

Share Document