Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

Abstract

Central metabolism is a topic that has been studied for decades, and yet, this process is still not fully understood in Escherichia coli, perhaps the most amenable and well-studied model organism in biology. To further our understanding, we used a high-throughput method to measure the growth kinetics of each of 3,796 E. coli single-gene deletion mutants in 30 different carbon sources. In total, there were 342 genes (9.01%) encompassing a breadth of biological functions that showed a growth phenotype on at least 1 carbon source, demonstrating that carbon metabolism is closely linked to a large number of processes in the cell. We identified 74 genes that showed low growth in 90% of conditions, defining a set of genes which are essential in nutrient-limited media, regardless of the carbon source. The data are compiled into a Web application, Carbon Phenotype Explorer (CarPE), to facilitate easy visualization of growth curves for each mutant strain in each carbon source. Our experimental data matched closely with the predictions from the EcoCyc metabolic model which uses flux balance analysis to predict growth phenotypes. From our comparisons to the model, we found that, unexpectedly, phosphoenolpyruvate carboxylase (ppc) was required for robust growth in most carbon sources other than most trichloroacetic acid (TCA) cycle intermediates. We also identified 51 poorly annotated genes that showed a low growth phenotype in at least 1 carbon source, which allowed us to form hypotheses about the functions of these genes. From this list, we further characterized the ydhC gene and demonstrated its role in adenosine efflux. IMPORTANCE While there has been much study of bacterial gene dispensability, there is a lack of comprehensive genome-scale examinations of the impact of gene deletion on growth in different carbon sources. In this context, a lot can be learned from such experiments in the model microbe Escherichia coli where much is already understood and there are existing tools for the investigation of carbon metabolism and physiology (1). Gene deletion studies have practical potential in the field of antibiotic drug discovery where there is emerging interest in bacterial central metabolism as a target for new antibiotics (2). Furthermore, some carbon utilization pathways have been shown to be critical for initiating and maintaining infection for certain pathogens and sites of infection (3–5). Here, with the use of high-throughput solid medium phenotyping methods, we have generated kinetic growth measurements for 3,796 genes under 30 different carbon source conditions. This data set provides a foundation for research that will improve our understanding of genes with unknown function, aid in predicting potential antibiotic targets, validate and advance metabolic models, and help to develop our understanding of E. coli metabolism.

A curated collection of Klebsiella metabolic models reveals variable substrate usage and gene essentiality

“…In addition to growth capabilities, our analyses revealed considerable variation in terms of predicted gene essentiality, as has been implicated for other bacterial species (Breton et al 2015;Poulsen et al 2019;Rousset et al 2021;Tong et al 2020). Specifically, our data indicate that i) deletion of a single core gene in a given strain may result in loss of growth on all, none or only a subset of growth substrates; and ii) the impact of such deletions may vary considerably between strains (Fig.…”

Exploring the Glucose Fluxotype of the E. coli y-ome Using High-Resolution Fluxomics

“…The fact that the metabolic effects are so wide-ranging suggests that the products of these genes affect central metabolic parameters, such as the redox status or that they are global regulators of metabolism, either directly or indirectly. The dispensability of the two y-genes during growth on various carbon sources has recently been documented [ 12 ]. The ΔydcS strain shows reduced growth on certain sugars (mainly mannose, glucosamine, fructose) and two organic acids (alpha-ketoglutarate and acetate).…”

“…The ΔybjP strain shows reduced growth on a few carbon sources, mainly including pyruvate, ribose, sorbitol and galacturonate. Deletion of these y-genes has no effect [ 12 ] or only a slight effect (this work) on growth with glucose as sole carbon source, in spite of significant metabolic changes in the two mutant strains. These observations emphasize that gene dispensability does not mean the gene lacks a metabolic function, but rather that the metabolism has successfully adapted to the absence of the gene product [ 4 ].…”

“…Alongside studies aimed at directly identifying gene product function, an alternative strategy for studying the role of y-genes consists of detailing the phenotypic consequences of a loss-of-function mutation or a gene deletion [ 7 , 8 ]. Together with the generation of mutant libraries, such as the Keio E. coli mutant collection [ 9 ], which facilitates genome-wide investigations, this approach has been used for large-scale investigations of gene essentiality [ 9 , 10 , 11 , 12 ] and of molecular [ 13 ], morphological [ 14 ] and fitness [ 15 ] phenotypes in bacteria. Metabolic phenotyping approaches have also been developed in which comparative metabolomics is applied to reveal gene functions in yeast [ 4 ].…”

sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution

“…The cellular growth curve arising from cell density variation over time is an important phenotype for cell physiology and systems biology studies ( 1 ). Improving the throughput of growth rate calculations from growth curves benefits from automated curve-fitting algorithms, but most existing software has been developed for data with high temporal resolution ( 2 – 8 ). Such data are usually generated by automated optical density measurements ( 5 ), which apply only to a limited set of organisms that can achieve high cell densities.…”