Abstract

Several methods are available to probe cellular responses to external stresses at the whole genome level. RNAseq can be used to measure changes in expression of all genes following exposure to stress, but gives no information about the contribution of these genes to an organism’s ability to survive the stress. The relative contribution of each non-essential gene in the genome to the fitness of the organism under stress can be obtained using methods that use sequencing to estimate the frequencies of members of a dense transposon library grown under different conditions, for example by transposon-directed insertion sequencing (TraDIS). These two methods thus probe different aspects of the underlying biology of the organism. We were interested to determine the extent to which the data from these two methods converge on related genes and pathways. To do this, we looked at a combination of biologically meaningful stresses. The human gut contains different organic short-chain fatty acids (SCFAs) produced by fermentation of carbon compounds, and Escherichia coli is exposed to these in its passage through the gut. Their effect is likely to depend on both the ambient pH and the level of oxygen present. We, therefore, generated RNAseq and TraDIS data on a uropathogenic E. coli strain grown at either pH 7 or pH 5.5 in the presence or absence of three SCFAs (acetic, propionic and butyric), either aerobically or anaerobically. Our analysis identifies both known and novel pathways as being likely to be important under these conditions. There is no simple correlation between gene expression and fitness, but we found a significant overlap in KEGG pathways that are predicted to be enriched following analysis of the data from the two methods, and the majority of these showed a fitness signature that would be predicted from the gene expression data, assuming expression to be adaptive. Genes which are not in the E. coli core genome were found to be particularly likely to show a positive correlation between level of expression and contribution to fitness.

Highlights

  • The ability to predict the phenotype of an organism from knowledge of its genotype is one of the most desirable, and one of the hardest to achieve, targets in genetics

  • To grow cultures for transposon-directed insertion sequencing (TraDIS) analysis, 10 μL of the EO499 transposon mutant library was added to 50 mL M9supp pre-adjusted to the required pH (7 or 5.5) and containing, where necessary, the relevant short-chain fatty acids (SCFAs) at the appropriate concentration, giving a starting OD600 of 0.01

  • For TraDIS to be possible, bacteria generally have to go through multiple generations, in order for the selective effects of different mutations to be detectable; significant growth was required after imposition of the stress

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Summary

Introduction

The ability to predict the phenotype of an organism from knowledge of its genotype is one of the most desirable, and one of the hardest to achieve, targets in genetics. A complete deterministic model of the genome including the properties of every entity it encodes, and how they interact with each other and with every aspect of their environment would enable the prediction of the behaviour and properties of any organism in any environment from a knowledge of its genome alone Such models are far out of reach, and remarkable progress has been achieved in developing methods for inferring phenotypes from large-scale datasets [1,2,3,4,5], significant obstacles remain to the development of improved predictive models of organisms based on knowledge of their genome sequences. Much hope has been put in the application of ML/AI models that bypass to some extent the needs to understand the mechanisms in full and which may provide prediction and hypothesis at the same time

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