Biology subjects

Manson, A.

Publications and source records attributed to Manson, A..

3 recordsLinked to original sources

bioRxiv2024

Rapid Emergence of Resistance to Broad-Spectrum Direct Antimicrobial Activity of Avibactam

Avibactam (AVI) is a diazabicyclooctane (DBO) {beta}-lactamase inhibitor used clinically in combination with ceftazidime. At concentrations higher than those typically achieved in vivo, it also has broad-spectrum direct antibacterial activity against Enterobacterales strains, including metallo-{beta}-lactamase-producing isolates, mediated by inhibition of penicillin-binding protein 2 (PBP2). This activity is mechanistically similar to that of more potent novel DBOs (zidebactam, nacubactam) in late clinical development. We found that resistance to AVI emerged readily, with a mutation frequency of 2x10-6 to 8x10-5. Whole genome sequencing of resistant isolates revealed a heterogeneous mutational target that permitted bacterial survival and replication despite PBP2 inhibition, in line with prior studies of PBP2-targeting drugs. While such mutations are believed to act by upregulating the bacterial stringent response, we found a similarly high mutation frequency in bacteria deficient in components of the stringent response, although we observed a different set of mutations in these strains. Although avibactam-resistant strains had increased lag time, suggesting a fitness cost that might render them less problematic in clinical infections, there was no statistically significant difference in growth rates between susceptible and resistant strains. The finding of rapid emergence of resistance to avibactam as the result of a large mutational target has important implications for novel DBOs with potent direct antibacterial activity, which are being developed with the goal of expanding cell wall-active treatment options for multidrug-resistant gram-negative infections but may be vulnerable to treatment-emergent resistance.

microbiology↗

bioRxiv2023

Role of ugt genes in detoxification and glycosylation of 1-hydroxy phenazine (1-HP) in Caenorhabditis elegans

Caenorhabditis elegans is an ideal model organism to study the xenobiotic detoxification pathways of various natural and synthetic toxins. One toxin shown to cause death in C. elegans is 1-hydroxyphenazine (1-HP), a molecule produced by the bacterium Pseudomonas aeruginosa. We previously showed that the median lethal dose (LD50) for 1-HP in C elegans is 179 M in PD1074 and between 150-200 M in N2 (C. elegans lab strain). We also showed that C. elegans detoxifies 1-HP by glycosylation by adding one, two, or three glucose molecules in N2 worms. This study tested whether UDP-glycosyltransferase (ugt) genes play a role in 1-HP detoxification. We show that ugt-23 and ugt-49 knockout mutants are more sensitive to 1-HP. Our data also show that ugt-23 knockout mutants produce reduced amounts of the trisaccharide sugars, while the ugt-49 knockout mutants produce reduced amounts of all 1-HP derivatives except for the glucopyranosyl product. We have also characterized the structure of the trisaccharide sugar phenazine structures made by C. elegans and show that one of the sugar modifications contains an N-acetylglucosamine (GlcNAc) in place of glucose. This implies broad specificity regarding UGT function and the role of genes other than ogt-1 in adding GlcNAc, at least in small-molecule detoxification.

biochemistry↗

bioRxiv2023

SAP: Synteny-aware gene function prediction for bacteria using protein embeddings

MotivationToday, we know the function of only a small fraction of the protein sequences predicted from genomic data. This problem is even more salient for bacteria, which represent some of the most phylogenetically and metabolically diverse taxa on Earth. This low rate of bacterial gene annotation is compounded by the fact that most function prediction algorithms have focused on eukaryotes, and conventional annotation approaches rely on the presence of similar sequences in existing databases. However, often there are no such sequences for novel bacterial proteins. Thus, we need improved gene function prediction methods tailored for prokaryotes. Recently, transformer-based language models - adopted from the natural language processing field - have been used to obtain new representations of proteins, to replace amino acid sequences. These representations, referred to as protein embeddings, have shown promise for improving annotation of eukaryotes, but there have been only limited applications on bacterial genomes. ResultsTo predict gene functions in bacteria, we developed SAP, a novel synteny-aware gene function prediction tool based on protein embeddings from state-of-the-art protein language models. SAP also leverages the unique operon structure of bacteria through conserved synteny. SAP outperformed both conventional sequence-based annotation methods and state-of-the-art methods on multiple bacterial species, including for distant homolog detection, where the sequence similarity to the proteins in the training set was as low as 40%. Using SAP to identify gene functions across diverse enterococci, of which some species are major clinical threats, we identified 11 previously unrecognized putative novel toxins, with potential significance to human and animal health. Availabilityhttps://github.com/AbeelLab/sap Contactt.abeel@tudelft.nl Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗