skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Universal Constraints on Protein Evolution in the Long-Term Evolution Experiment with Escherichia coli
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 anticorrelates 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.  more » « less
Award ID(s):
1951307
PAR ID:
10272493
Author(s) / Creator(s):
Editor(s):
Golding, Brian
Date Published:
Journal Name:
Genome Biology and Evolution
Volume:
13
Issue:
6
ISSN:
1759-6653
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; (, Genome Biology and Evolution)
    Zhang, George (Ed.)
    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. 
    more » « less
  2. (, Genome Biology and Evolution)
    Golding, Brian (Ed.)
    Abstract Most cellular functions are carried out by a dynamic network of interacting proteins. An open question is whether the network properties of protein interactomes represent phenotypes under natural selection. One proposal is that protein interactomes have evolved to be resilient, such that they tend to maintain connectivity when proteins are removed from the network. This hypothesis predicts that interactome resilience should be maintained by natural selection during long-term experimental evolution. I tested this prediction by modeling the evolution of protein–protein interaction (PPI) networks in Lenski’s long-term evolution experiment with Escherichia coli (LTEE). In this test, I removed proteins affected by nonsense, insertion, deletion, and transposon mutations in evolved LTEE strains, and measured the resilience of the resulting networks. I compared the rate of change of network resilience in each LTEE population to the rate of change of network resilience for corresponding randomized networks. The evolved PPI networks are significantly more resilient than networks in which random proteins have been deleted. Moreover, the evolved networks are generally more resilient than networks in which the random deletion of proteins was restricted to those disrupted in LTEE. These results suggest that evolution in the LTEE has favored PPI networks that are, on average, more resilient than expected from the genetic variation across the evolved strains. My findings therefore support the hypothesis that selection maintains protein interactome resilience over evolutionary time. 
    more » « less
  3. ; ; ; ; ; ; (, Applied and Environmental Microbiology)
    Villanueva, Laura (Ed.)
    ABSTRACT Experimental evolution provides a powerful tool for examining how Bdellovibrio evolves in response to unique selective pressures associated with its predatory lifestyle. We tested how Bdellovibrio sp. NC01 adapts to long-term coculture with Pseudomonas sp. NC02, which is less susceptible to predation compared to other Gram-negative bacteria. Analyzing six replicate Bdellovibrio populations across six time points spanning 40 passages and 2,880 h of coculture, we detected 30 to 40 new mutations in each population that exceeded a frequency of 5%. Nonsynonymous substitutions were the most abundant type of new mutation, followed by small indels and synonymous substitutions. After completing the final passage, we detected 20 high-frequency (>75%) mutations across all six evolved Bdellovibrio populations. Eighteen of these alter protein sequences, and most increased in frequency rapidly. Four genes acquired a high-frequency mutation in two or more evolved Bdellovibrio populations, reflecting parallel evolution and positive selection. The genes encode a sodium/phosphate cotransporter family protein (Bd2221), a metallophosphoesterase (Bd0054), a TonB family protein (Bd0396), and a hypothetical protein (Bd1601). Tested prey range and predation efficiency phenotypes did not differ significantly between evolved Bdellovibrio populations and the ancestor; however, all six evolved Bdellovibrio populations demonstrated enhanced starvation survival compared to the ancestor. These results suggest that, instead of evolving improved killing of Pseudomonas sp. NC02, Bdellovibrio evolved to better withstand nutrient limitation in the presence of this prey strain. The mutations identified here point to genes and functions that may be important for Bdellovibrio adaptation to the different selective pressures of long-term coculture with Pseudomonas . IMPORTANCE Bdellovibrio attack and kill Gram-negative bacteria, including drug-resistant pathogens of animals and plants. This lifestyle is unusual among bacteria, and it imposes unique selective pressures on Bdellovibrio . Determining how Bdellovibrio evolve in response to these pressures is valuable for understanding the mechanisms that govern predation. We applied experimental evolution to test how Bdellovibrio sp. NC01 evolved in response to long-term coculture with a single Pseudomonas strain, which NC01 can kill, but with low efficiency. Our experimental design imposed different selective pressures on the predatory bacteria and tracked the evolutionary trajectories of replicate Bdellovibrio populations. Using genome sequencing, we identified Bdellovibrio genes that acquired high-frequency mutations in two or more populations. Using phenotype assays, we determined that evolved Bdellovibrio populations did not improve their ability to kill Pseudomonas , but rather are better able to survive starvation. Overall, our results point to functions that may be important for Bdellovibrio adaptation. 
    more » « less
  4. ; ; ; (, PLOS Biology)
    McLysaght, Aoife (Ed.)
    The phenomenon of de novo gene birth—the emergence of genes from non-genic sequences—has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli long-term evolution experiment (LTEE) for changes indicative of “proto-genic” phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, with levels of transcription across low-expressed regions increasing in later generations of the experiment. Proto-genes formed downstream of new mutations result either from insertion element activity or chromosomal translocations that fused preexisting regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter, although such cases were rare compared to those caused by recruitment of preexisting promoters. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, can persist stably, and can serve as potential substrates for new gene formation. 
    more » « less
  5. ; ; ; ; ; (, Genome Biology and Evolution)
    dos Reis, Mario (Ed.)
    Highly abundant proteins tend to evolve slowly (a trend called E-R anticorrelation), and a number of hypotheses have been proposed to explain this phenomenon. The misfolding avoidance hypothesis attributes the E-R anticorrelation to the abundance-dependent toxic effects of protein misfolding. To avoid these toxic effects, protein sequences (particularly those of highly expressed proteins) would be under selection to fold properly. One prediction of the misfolding avoidance hypothesis is that highly abundant proteins should exhibit high thermostability (i.e., a highly negative free energy of folding, ΔG). Thus far, only a handful of analyses have tested for a relationship between protein abundance and thermostability, producing contradictory results. These analyses have been limited by 1) the scarcity of ΔG data, 2) the fact that these data have been obtained by different laboratories and under different experimental conditions, 3) the problems associated with using proteins’ melting energy (Tm) as a proxy for ΔG, and 4) the difficulty of controlling for potentially confounding variables. Here, we use computational methods to compare the free energy of folding of pairs of human–mouse orthologous proteins with different expression levels. Even though the effect size is limited, the most highly expressed ortholog is often the one with a more negative ΔG of folding, indicating that highly expressed proteins are often more thermostable. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email