Collateral fitness effects of mutations
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA565236 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10107300_1.fastq.gz | Fastqsanger.gz | |||
| SRR10107300_2.fastq.gz | Fastqsanger.gz | |||
| SRR10107278_1.fastq.gz | Fastqsanger.gz | |||
| SRR10107278_2.fastq.gz | Fastqsanger.gz | |||
| SRR10107279_1.fastq.gz | Fastqsanger.gz |
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Project description:Variation in gene expression arises from cis- and trans-regulatory mutations, which contribute differentially to expression divergence. Here, we compare the impacts on gene expression and fitness for cis- and trans-regulatory mutations affecting expression of the TDH3 gene in Saccharomyces cerevisiae. We use the effects of cis-regulatory mutations to isolate effects of trans-regulatory mutations caused by impacts on TDH3 from pleiotropic impacts on other genes, providing a rare distribution of pleiotropic effects. These pleiotropic effects were often, but not always, deleterious. For cis- and trans-regulatory mutations with similar effects on TDH3, trans-regulatory mutations had more widespread effects on gene expression, with distinct impacts on expression of genes downstream of TDH3. These differences between cis-and trans-regulatory mutations help explain their different contributions to regulatory evolution.
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Project description:We found that several variants with 2-4 mutations on Higher Eukaryotes and Prokaryotes Nucleotide-binding (HEPN) domains showed undiminished on-target activity but markedly reduced collateral effects. Furthermore, transcriptome-wide off-target effects and cell growth arrest induced by wild-type Cas13d were found to be absent for a Cas13d variant. Thus, high-fidelity Cas13 variants with minimal collateral effects are now available for the targeted degradation of RNAs in basic research and therapeutic applications.
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Project description:The distribution of fitness effects of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutation's collateral fitness effects, which we define as effects that do not derive from changes in the protein's ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the Escherichia coli TEM-1 β-lactamase antibiotic resistance gene using growth competition experiments in the absence of antibiotic. At least 42% of missense mutations in TEM-1 were deleterious, indicating that for some proteins collateral fitness effects occur as frequently as effects on protein activity and abundance. Deleterious mutations caused improper posttranslational processing, incorrect disulfide-bond formation, protein aggregation, changes in gene expression, and pleiotropic effects on cell phenotype. Deleterious collateral fitness effects occurred more frequently in TEM-1 than deleterious effects on antibiotic resistance in environments with low concentrations of the antibiotic. The surprising prevalence of deleterious collateral fitness effects suggests they may play a role in constraining protein evolution, particularly for highly expressed proteins, for proteins under intermittent selection for their physiological function, and for proteins whose contribution to fitness is buffered against deleterious effects on protein activity and protein abundance.
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Project description:In adaptive evolution, an increase in fitness to an environment is frequently accompanied by changes in fitness to other environmental conditions, called cross-resistance and sensitivity. Although the networks between fitness changes affect the course of evolution substantially, the mechanisms underlying such fitness changes are yet to be fully elucidated. Herein, we performed high-throughput laboratory evolution of Escherichia coli under various stress conditions using an automated culture system, and quantified how the acquisition of resistance to one stressor alters the resistance to other stressors. We demonstrated that resistance changes could be quantitatively predicted based on changes in the transcriptome of the resistant strains. We also identified several genes and gene functions, for which mutations were commonly fixed in the strains resistant to the same stress, which could partially explain the observed cross-resistance and collateral sensitivity. The integration of transcriptome and genome data enabled us to clarify the bacterial stress resistance mechanisms.
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