Shibai, A. | bioRxiv Science

bioRxiv2022

Multi-dimensional antibiotic resistance time series reveals the phenotype-based fitness landscape for Escherichia coli

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes based on comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the fitness landscape for antibiotic resistance evolution by quantifying the phenotypic changes, that is, multi-dimensional time-series measurements of the drug resistance profile. Using the time-series data of drug resistance for multiple drugs, we inferred that the fitness landscape underlies the evolution dynamics of resistance. We showed that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

evolutionary biology↗

bioRxiv2022

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E-R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the two evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E-R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression level on molecular evolution, and to test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for microevolution in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo microevolution. Here, we show that the E-R anticorrelation is significant in both past and de novo microevolution in E. coli. Our data also confirmed ongoing purifying selection acting on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, their contributions to the constraints in recent evolution might be smaller than previously expected from past macroevolution.

evolutionary biology↗