Universal constraints on protein evolution in the long-term evolution experiment with Escherichia coli

Genome Biology and Evolution

2021

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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.

Section: Discussionmentioning

confidence: 96%

Selection Maintains Protein Interactome Resilience in the Long-Term Evolution Experiment with Escherichia coli

Genome Biology and Evolution

2021

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“…Protein interactome resilience could be maintained by direct selection, or as a byproduct of selection on phenotypes that correlate with interactome resilience. In previous work, I found evidence for purifying selection on essential genes in metagenomic time series covering 60,000 generations of the LTEE (Maddamsetti and Grant 2020b), as well as evidence of purifying selection on highly interacting genes (Maddamsetti 2020). Consistent with those findings, the LTEE genomes analyzed here show evidence of purifying selection on essential genes, which are also highly enriched for protein-protein interactions.…”

Section: Discussionmentioning

confidence: 96%

“…The fact that evolved PPI networks in the LTEE are more resilient than networks with random deletions implies purifying selection on highly interacting genes in the LTEE. Indeed, evidence for purifying selection on essential genes in the LTEE has been found (Maddamsetti and Grant 2020b) as has evidence of purifying selection on highly interacting genes (Maddamsetti 2020). That said, it is unclear whether purifying selection on essential genes maintains network resilience as a side-effect, or whether the maintenance of network resilience causes selection on essential genes, or both.…”

Section: Discussionmentioning

confidence: 99%

Selection maintains protein interactome resilience in the long-term evolution experiment withEscherichia coli

2021

Preprint

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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 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 populations. My findings therefore support the hypothesis that selection maintains protein interactome resilience over evolutionary time.Significance StatementUnderstanding how protein-protein interaction (PPI) networks evolve is a central goal of evolutionary systems biology. One property that has been hypothesized to be important for PPI network evolution is resilience, which means that networks tend to maintain connectivity even after many nodes (proteins in this case) have been removed. This hypothesis predicts that PPI network resilience should be maintained during long-term experimental evolution. Consistent with this prediction, I found that the PPI networks that evolved over 50,000 generations of Lenski’s long-term evolution experiment with E. coli are more resilient than expected by chance.

“…We used STIMS to find evidence of purifying selection on aerobic-specific and anaerobic-specific genes and essential genes (Maddamsetti and Grant 2020b) in the LTEE. In addition, we found evidence of purifying selection on genes encoding highly expressed and highly interacting proteins, using different methods (Maddamsetti 2020).…”

Section: Introductionmentioning

confidence: 89%

Idiosyncratic purifying selection on metabolic enzymes in the long-term evolution experiment withEscherichia coli

2021

Preprint

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Bacteria, 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.