Mapping the Transcriptional and Fitness Landscapes of a Pathogenic E. coli Strain: The Effects of Organic Acid Stress under Aerobic and Anaerobic Conditions

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.

Visualizing the pH in Escherichia coli Colonies via the Sensor Protein mCherryEA Allows High-Throughput Screening of Mutant Libraries

“…Many bacterial regulatory mechanisms have been identified via phenotypic screening of strain libraries with respect to its growth patterns under different conditions. Screening of Escherichia coli and other microorganisms for growth versus nongrowth at low or high pH values revealed many of the processes and control mechanisms underlying pH homeostasis ( 19 – 24 ). To achieve pH homeostasis, E. coli possesses regulatory networks for acid and alkaline conditions, which trigger expression of distinct sets of genes ( 25 , 26 ).…”

Genome-wide identification of fitness-genes in aminoglycoside-resistant Escherichia coli during antibiotic stress

“…Fitness in bacteria has been quantified by measuring the (maximum) growth rate in monoculture, MIC testing and by competition assays 48 . The latter assay is regarded as closest to the meaning of fitness in the evolutionary sense 48 , and this also resembled the situation during the TraDIS procedure, where a pool of more than 200.000 mutants was cultivated together 49 . It may also be considered similar to natural conditions, where in many situations a vast variety of different microorganisms are present at the same time and compete for growth 50 .…”

Visualizing the pH inEscherichia colicoloniesviathe sensor protein mCherryEA allows high-throughput screening of mutant libraries

“…Many bacterial regulatory mechanisms have been identified via phenotypic screening of strain libraries with respect to its growth patterns under different conditions. Screening of E. coli and other microorganisms towards growth vs. non-growth at low or high pH-values revealed many of the processes and control mechanisms underlying pH-homeostasis (Reva et al , 2006; Mira et al , 2010; Guerrero-Castro et al , 2018; Palud et al , 2018; Bushell et al , 2021). To achieve pH homeostasis, E. coli possesses regulatory networks for acid and alkaline conditions, which trigger expression of distinct sets of genes (Maurer et al , 2005; Hayes et al , 2006).…”