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Species interactions differ in their genetic robustness.

ABSTRACT: Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica. The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.

SUBMITTER: Chubiz LM

PROVIDER: S-EPMC4396422 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Species interactions differ in their genetic robustness.

Chubiz Lon M LM Granger Brian R BR Segrè Daniel D Harcombe William R WR

Frontiers in microbiology 20150414

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E ...[more]

PMID: 25926820

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Project description:BackgroundExpression profiling has been proposed as a means for screening non-model organisms in their natural environments to identify genes potentially important in adaptive diversification. Tag profiling using high throughput sequencing is a relatively low cost means of expression profiling with deep coverage. However the extent to which very short cDNA sequences can be effectively used in screening for candidate genes is unclear. Here we investigate this question using an evolutionarily distant as well as a closely related transcriptome for referencing tags. We do this by comparing differentially expressed genes and processes between two closely related allopolyploid species of Pachycladon which have distinct altitudinal preferences in the New Zealand Southern Alps. We validate biological inferences against earlier microarray analyses.ResultsStatistical and gene annotation enrichment analyses of tag profiles identified more differentially expressed genes of potential adaptive significance than previous analyses of array-based expression profiles. These include genes involved in glucosinolate metabolism, flowering time, and response to cold, desiccation, fungi and oxidation. In addition, despite the short length of 20mer tags, we were able to infer patterns of homeologous gene expression for 700 genes in our reference library of 7,128 full-length Pachycladon ESTs. We also demonstrate that there is significant information loss when mapping tags to the non-conspecific reference transcriptome of A. thaliana as opposed to P. fastigiatum ESTs but also describe mapping strategies by which the larger collection of A. thaliana ESTs can be used as a reference.ConclusionWhen coupled with a reference transcriptome generated using RNA-seq, tag sequencing offers a promising approach for screening natural populations and identifying candidate genes of potential adaptive significance. We identify computational issues important for the successful application of tag profiling in a non-model allopolyploid plant species.

Project description:Genetic robustness (tolerance of mutation) may be a naturally selected property in some viruses, because it should enhance adaptability. Robustness should be especially beneficial to viruses like HIV-1 that exhibit high mutation rates and exist in immunologically hostile environments. Surprisingly, however, the HIV-1 capsid protein (CA) exhibits extreme fragility. To determine whether fragility is a general property of HIV-1 proteins, we created a large library of random, single-amino-acid mutants in HIV-1 integrase (IN), covering >40% of amino acid positions. Despite similar degrees of sequence variation in naturally occurring IN and CA sequences, we found that HIV-1 IN was significantly more robust than CA, with random nonsilent IN mutations only half as likely to cause lethal defects. Interestingly, IN and CA were similar in that a subset of mutations with high in vitro fitness were rare in natural populations. IN mutations of this type were more likely to occur in the buried interior of the modeled HIV-1 intasome, suggesting that even very subtle fitness effects suppress variation in natural HIV-1 populations. Lethal mutations, in particular those that perturbed particle production, proteolytic processing, and particle-associated IN levels, were strikingly localized at specific IN subunit interfaces. This observation strongly suggests that binding interactions between particular IN subunits regulate proteolysis during HIV-1 virion morphogenesis. Overall, use of the IN mutant library in conjunction with structural models demonstrates the overall robustness of IN and highlights particular regions of vulnerability that may be targeted in therapeutic interventions.The HIV-1 integrase (IN) protein is responsible for the integration of the viral genome into the host cell chromosome. To measure the capacity of IN to maintain function in the face of mutation, and to probe structure/function relationships, we created a library of random single-amino-acid IN mutations that could mimic the types of mutations that naturally occur during HIV-1 infection. Previously, we measured the robustness of HIV-1 capsid in this manner and determined that it is extremely intolerant of mutation. In contrast to CA, HIV-1 IN proved relatively robust, with far fewer mutations causing lethal defects. However, when we subsequently mapped the lethal mutations onto a model of the structure of the multisubunit IN-viral DNA complex, we found the lethal mutations that caused virus morphogenesis defects tended to be highly localized at subunit interfaces. This discovery of vulnerable regions of HIV-1 IN could inform development of novel therapeutics.

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Species interactions differ in their genetic robustness.

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Species interactions differ in their genetic robustness.

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