Experimental Evolution Expands the Breadth of Adaptation to an Environmental Gradient Correlated With Genome Reduction

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth

A complex interplay of genetic and environmental factors influences bacterial growth. Understanding these interactions is crucial for insights into complex living systems. This study employs a data-driven approach to uncover the principles governing bacterial growth changes due to genetic and environmental variation. A pilot survey is conducted across 115 Escherichia coli strains and 135 synthetic media comprising 45 chemicals, generating 13,944 growth profiles. Machine learning analyzes this dataset to predict the chemicals' priorities for bacterial growth. The primary gene-chemical networks are structured hierarchically, with glucose playing a pivotal role. Offset in bacterial growth changes is frequently observed across 1,445,840 combinations of strains and media, with its magnitude correlating to individual alterations in strains or media. This counterbalance in the gene-chemical interplay is supposed to be a general feature beneficial for bacterial population growth.

Experimental evolution for the recovery of growth loss due to genome reduction

As the genome encodes the information crucial for cell growth, a sizeable genomic deficiency often causes a significant decrease in growth fitness. Whether and how the decreased growth fitness caused by genome reduction could be compensated by evolution was investigated here. Experimental evolution with an Escherichia coli strain carrying a reduced genome was conducted in multiple lineages for approximately 1000 generations. The growth rate, which largely declined due to genome reduction, was considerably recovered, associated with the improved carrying capacity. Genome mutations accumulated during evolution were significantly varied across the evolutionary lineages and were randomly localized on the reduced genome. Transcriptome reorganization showed a common evolutionary direction and conserved the chromosomal periodicity, regardless of highly diversified gene categories, regulons, and pathways enriched in the differentially expressed genes. Genome mutations and transcriptome reorganization caused by evolution, which were found to be dissimilar to those caused by genome reduction, must have followed divergent mechanisms in individual evolutionary lineages. Gene network reconstruction successfully identified three gene modules functionally differentiated, which were responsible for the evolutionary changes of the reduced genome in growth fitness, genome mutation, and gene expression, respectively. The diversity in evolutionary approaches improved the growth fitness associated with the homeostatic transcriptome architecture as if the evolutionary compensation for genome reduction was like all roads leading to Rome.

Efforts to Minimise the Bacterial Genome as a Free-Living Growing System

Exploring the minimal genetic requirements for cells to maintain free living is an exciting topic in biology. Multiple approaches are employed to address the question of the minimal genome. In addition to constructing the synthetic genome in the test tube, reducing the size of the wild-type genome is a practical approach for obtaining the essential genomic sequence for living cells. The well-studied Escherichia coli has been used as a model organism for genome reduction owing to its fast growth and easy manipulation. Extensive studies have reported how to reduce the bacterial genome and the collections of genomic disturbed strains acquired, which were sufficiently reviewed previously. However, the common issue of growth decrease caused by genetic disturbance remains largely unaddressed. This mini-review discusses the considerable efforts made to improve growth fitness, which was decreased due to genome reduction. The proposal and perspective are clarified for further accumulated genetic deletion to minimise the Escherichia coli genome in terms of genome reduction, experimental evolution, medium optimization, and machine learning.

Growth rate-associated transcriptome reorganization in response to genomic, environmental, and evolutionary interruptions

The genomic, environmental, and evolutionary interruptions caused the changes in bacterial growth, which were stringently associated with changes in gene expression. The growth and gene expression changes remained unclear in response to these interruptions that occurred combinative. As a pilot study, whether and how bacterial growth was affected by the individual and dual interruptions of genome reduction, environmental stress, and adaptive evolution were investigated. Growth assay showed that the presence of the environmental stressors, i.e., threonine and chloramphenicol, significantly decreased the growth rate of the wild-type Escherichia coli, whereas not that of the reduced genome. It indicated a canceling effect in bacterial growth due to the dual interruption of the genomic and environmental changes. Experimental evolution of the reduced genome released the canceling effect by improving growth fitness. Intriguingly, the transcriptome architecture maintained a homeostatic chromosomal periodicity regardless of the genomic, environmental, and evolutionary interruptions. Negative epistasis in transcriptome reorganization was commonly observed in response to the dual interruptions, which might contribute to the canceling effect. It was supported by the changes in the numbers of differentially expressed genes (DEGs) and the enriched regulons and functions. Gene network analysis newly constructed 11 gene modules, one out of which was correlated to the growth rate. Enrichment of DEGs in these modules successfully categorized them into three types, i.e., conserved, responsive, and epistatic. Taken together, homeostasis in transcriptome architecture was essential to being alive, and it might be attributed to the negative epistasis in transcriptome reorganization and the functional differentiation in gene modules. The present study directly connected bacterial growth fitness with transcriptome reorganization and provided a global view of how microorganisms responded to genomic, environmental, and evolutionary interruptions for survival from wild nature.

Global coordination of the mutation and growth rates across the genetic and nutritional variety in Escherichia coli

Fitness and mutability are the primary traits of living organisms for adaptation and evolution. However, their quantitative linkage remained largely deficient. Whether there is any general relationship between the two features and how genetic and environmental variables influence them remained unclear and were addressed here. The mutation and growth rates of an assortment of Escherichia coli strain collections, including the wild-type strains and the genetically disturbed strains of either reduced genomes or deletion of the genes involved in the DNA replication fidelity, were evaluated in various media. The contribution of media to the mutation and growth rates was differentiated depending on the types of genetic disturbance. Nevertheless, the negative correlation between the mutation and growth rates was observed across the genotypes and was common in all media. It indicated the comprehensive association of the correlated mutation and growth rates with the genetic and medium variation. Multiple linear regression and support vector machine successfully predicted the mutation and growth rates and the categories of genotypes and media, respectively. Taken together, the study provided a quantitative dataset linking the mutation and growth rates, genotype, and medium and presented a simple and successful example of predicting bacterial growth and mutability by data-driven approaches.

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity

Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth remains largely unknown. The present study focused on the contribution of environmental constituents to population dynamics via a high-throughput assay and data-driven analysis of a wild-type Escherichia coli strain. A large dataset constituting a total of 12,828 bacterial growth curves with 966 medium combinations, which were composed of 44 pure chemical compounds, was acquired. Machine learning analysis of the big data relating the growth parameters to the medium combinations revealed that the decision-making components for bacterial growth were distinct among various growth phases, e.g., glucose, sulfate, and serine for maximum growth, growth rate, and growth delay, respectively. Further analyses and simulations indicated that branched-chain amino acids functioned as global coordinators for population dynamics, as well as a survival strategy of risk diversification to prevent the bacterial population from undergoing extinction.

Contribution of the genomic and nutritional differentiation to the spatial distribution of bacterial colonies

Colony growth is a common phenomenon of structured populations dispersed in nature; nevertheless, studies on the spatial distribution of colonies are largely insufficient. Here, we performed a systematic survey to address the questions of whether and how the spatial distribution of colonies was influenced by the genome and environment. Six Escherichia coli strains carrying either the wild-type or reduced genomes and eight media of varied nutritional richness were used to evaluate the genomic and environmental impacts, respectively. The genome size and nutritional variation contributed to the mean size and total area but not the variation and shape of size distribution of the colonies formed within the identical space and of equivalent spatial density. The spatial analysis by means of the Voronoi diagram found that the Voronoi correlation remained nearly constant in common, in comparison to the Voronoi response decreasing in correlation to genome reduction and nutritional enrichment. Growth analysis at the single colony level revealed positive correlations of the relative growth rate to both the maximal colony size and the Voronoi area, regardless of the genomic and nutritional variety. This result indicated fast growth for the large space assigned and supported homeostasis in the Voronoi correlation. Taken together, the spatial distribution of colonies might benefit efficient clonal growth. Although the mechanisms remain unclear, the findings provide quantitative insights into the genomic and environmental contributions to the growth and distribution of spatially or geographically isolated populations.