Antimicrobial peptides (AMPs) are key effectors of the innate immune system and promising therapeutic agents. Yet, knowledge on how to design AMPs with minimal cross-resistance to human host-defense peptides remains limited. Here, we systematically assess the resistance determinants of Escherichia coli against 15 different AMPs using chemical-genetics and compare to the cross-resistance spectra of laboratory-evolved AMP-resistant strains. Although generalizations about AMP resistance are common in the literature, we find that AMPs with different physicochemical properties and cellular targets vary considerably in their resistance determinants. As a consequence, cross-resistance is prevalent only between AMPs with similar modes of action. Finally, our screen reveals several genes that shape susceptibility to membrane- and intracellular-targeting AMPs in an antagonistic manner. We anticipate that chemical-genetic approaches could inform future efforts to minimize cross-resistance between therapeutic and human host AMPs.

No abstract

Folate derivatives are important cofactors for enzymes in several metabolic processes. Folate-related inhibition and resistance mechanisms in bacteria are potential targets for antimicrobial therapies and therefore a significant focus of current research. Here, we report that the activity of poly-γ-glutamyl tetrahydrofolate/dihydrofolate synthase (FolC) is regulated by glutamate/glutamine-sensing uridylyltransferase (GlnD), THF-dependent tRNA modification enzyme (MnmE), and UDP-glucose dehydrogenase (Ugd) as shown by direct protein-protein interactions. Using kinetics analyses, we observed that GlnD, Ugd, and MnmE activate FolC many-fold by decreasing the of FolC for its substrate l-glutamate. Moreover, FolC inhibited the GTPase activity of MnmE at low GTP concentrations. The growth phenotypes associated with these proteins are discussed. These results, obtained using direct enzyme assays, reveal unanticipated networks of allosteric regulatory interactions in the folate pathway in and indicate regulation of polyglutamylated tetrahydrofolate biosynthesis by the availability of nitrogen sources, signaled by the glutamine-sensing GlnD protein.

YhcB, an uncharacterized protein conserved across gamma-proteobacteria, is composed predominantly of a single Domain of Unknown Function (DUF 1043) with an N-terminal transmembrane α-helix. Here, we show that E. coli YhcB is a conditionally essential protein that interacts with the proteins of the cell divisome (e.g., FtsI, FtsQ) and elongasome (e.g., RodZ, RodA). We found 7 interactions of YhcB that are conserved in Yersinia pestis and/or Vibrio cholerae. Furthermore, we identified several point mutations that abolished interactions of YhcB with FtsI and RodZ. The yhcB knock-out strain does not grow at 45°C and is hypersensitive to cell-wall acting antibiotics even in stationary phase. The deletion of yhcB leads to filamentation, abnormal FtsZ ring formation, and aberrant septa development. The 2.8 Å crystal structure for the cytosolic domain from Haemophilus ducreyi YhcB shows a unique tetrameric α-helical coiled-coil structure that combines parallel and anti-parallel coiled-coil intersubunit interactions. This structure is likely to organize interprotein oligomeric interactions on the inner surface of the cytoplasmic membrane, possibly involved in regulation of cell division and/or envelope biogenesis/integrity in proteobacteria. In summary, YhcB is a conserved and conditionally essential protein that is predicted to play a role in cell division and consequently or in addition affects envelope biogenesis.ImportanceOnly 0.8 % of the protein annotations in the UniProt are based on experimental evidence and thus, functional characterization of unknown proteins remains a rate-limiting step in molecular biology. Herein, the functional properties of YhcB (DUF1043) were investigated using an integrated approach combining X-ray crystallography with genetics and molecular biology. YhcB is a conserved protein that appears to be needed for the transition from exponential to stationary growth and is involved in cell division and/or envelope biogenesis/integrity. This study will serve as a starting point for future studies on this protein family and on how cells transit from exponential to stationary survival.

Bacterial transcription factors (TFs) are widely studied in Escherichia coli. Yet it remains unclear how individual genes in the underlying pathways of TF machinery operate together during environmental challenge. Here, we address this by applying an unbiased, quantitative synthetic genetic interaction (GI) approach to measure pairwise GIs among all TF genes in E. coli under auxotrophic (rich medium) and prototrophic (minimal medium) static growth conditions. The resulting static and differential GI networks reveal condition-dependent GIs, widespread changes among TF genes in metabolism, and new roles for uncharacterized TFs (yjdC, yneJ, ydiP) as regulators of cell division, putrescine utilization pathway, and cold shock adaptation. Pan-bacterial conservation suggests TF genes with GIs are co-conserved in evolution. Together, our results illuminate the global organization of E. coli TFs, and remodeling of genetic backup systems for TFs under environmental change, which is essential for controlling the bacterial transcriptional regulatory circuits.

No abstract

Allantoin is a good source of ammonium for many organisms, and in Escherichia coli it is utilized under anaerobic conditions. We provide evidence that allantoinase (AllB) is allosterically activated by direct binding of the allantoin catabolic enzyme, glycerate 2-kinase (GlxK) in the presence of glyoxylate. Glyoxylate is known to be an effector of the AllR repressor which regulates the allantoin utilization operons in E. coli. AllB has low affinity for allantoin, but its activation by GlxK leads to increased affinity for its substrate. We also show that the predicted allantoin transporter YbbW (re-named AllW) has allantoin specificity and the protein–protein interaction with AllB. Our results show that the AllB-dependent allantoin degradative pathway is subject to previously unrecognized regulatory mechanisms involving direct protein–protein interactions.

Motivation A digenic genetic interaction (GI) is observed when mutations in two genes within the same organism yield a phenotype that is different from the expected, given each mutation’s individual effects. While multiplicative scoring is widely applied to define GIs, revealing underlying gene functions, it remains unclear if it is the most suitable choice for scoring GIs in Escherichia coli. Here, we assess many different definitions, including the multiplicative model, for mapping functional links between genes and pathways in E.coli. Results Using our published E.coli GI datasets, we show computationally that a machine learning Gaussian process (GP)-based definition better identifies functional associations among genes than a multiplicative model, which we have experimentally confirmed on a set of gene pairs. Overall, the GP definition improves the detection of GIs, biological reasoning of epistatic connectivity, as well as the quality of GI maps in E.coli, and, potentially, other microbes. Availability and implementation The source code and parameters used to generate the machine learning models in WEKA software were provided in the Supplementary information. Supplementary information Supplementary data are available at Bioinformatics online.