Biology subjects

Hobman, J. L.

Publications and source records attributed to Hobman, J. L..

4 recordsLinked to original sources

bioRxiv2022

Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics

Antibiotics enter the environment through waste streams, where they can exert selective pressure for antimicrobial resistance in bacteria. However, many antibiotics are excreted as partly metabolized forms, or can be subject to partial breakdown in wastewater treatment, soil, or through natural processes in the environment. If a metabolite is bioactive, even at sub-lethal levels, and also stable in the environment, then it could provide selection pressure for resistance. (5S)-penicilloic acid of piperacillin has previously been found complexed to the binding pocket of penicillin binding protein 3 (PBP3) of Pseudomonas aeruginosa. Here, we predicted the affinities of all potentially relevant antibiotic metabolites of ten different penicillins to that target protein, using molecular docking and molecular dynamics simulations. Docking predicts that, in addition to penicilloic acid, pseudopenicillin derivatives of these penicillins, as well as 6-aminopenicillanic acid (6APA), could also bind to this target. Molecular dynamics simulations further confirmed that (5R)-pseudopenicillin and 6APA bind the target protein, in addition to (5S)-penicilloic acid. Thus, it is possible that these metabolites are bioactive, and, if stable in the environment, could be contaminants selective for antibiotic resistance. This could have considerable significance for environmental surveillance for antibiotics as a means to reduce antimicrobial resistance, because targeted mass spectrometry could be required for relevant metabolites as well as the native antibiotics.

microbiology↗

bioRxiv2022

Laboratory strains of Escherichia coli K-12: not such perfect role models after all.

Escherichia coli K-12 was originally isolated 100 years ago and since then, it has become an invaluable model organism and a cornerstone of molecular biology research. However, despite its apparent pedigree, since its initial isolation, E. coli K-12 has been repeatedly cultured, passaged, and mutagenized, resulting in an organism that carries extensive genetic changes. To understand more about the evolution of this important model organism, we have sequenced the genomes of two ancestral K-12 strains, WG1 and EMG2, considered to be the progenitors of many key laboratory strains. Our analysis confirms that these strains still carry genetic elements such as bacteriophage lambda ({lambda}) and the F plasmid, but also indicates that they have undergone extensive lab-based evolution. Thus, scrutinizing the genomes of ancestral E. coli K-12 strains, leads us to question whether E. coli K-12 is a sufficiently robust model organism for 21st century microbiology. DATA SUMMARYAll supporting data are provided within the article or through supplementary data files. Supplementary Figs. S1 to S14 and Supplementary File S1 are available with the online version of this article. All genome sequence data has been deposited in NCBI GenBank under Bioproject ID PRJNA848777. The assembled and annotated genomes of WG1 and EMG2 have been deposited with the accession numbers, CP099590 and CP099591 (WG1) and CP099588 and CP099589 (EMG2). Impact StatementSince its isolation in 1922, Escherichia coli K-12, has become arguably the premier model organism for contemporary science. The adoption of E. coli K-12 by many microbiologists across the globe, means that it has a complex pedigree, and, although many E. coli K-12 strains have been sequenced, little is known about the early versions of K-12, which still carry the F plasmid and bacteriophage {lambda}. To understand more about the lab-based evolution that has shaped this important model organism, we have sequenced two ancestral K-12 strains, WG1 and EMG2, that are considered to be the progenitors of many of the laboratory strains used today.

genomics↗

bioRxiv2022

Antimicrobial resistance in dairy slurry tanks: a critical point for measurement and control

Waste from dairy production is one of the worlds largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs). However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with >99% reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for prevalence and control of AMR, and that measures to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

microbiology↗

bioRxiv2020

Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), Zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.

microbiology↗