Biology subjects

Peleg, A. Y.

Publications and source records attributed to Peleg, A. Y..

13 recordsLinked to original sources

bioRxiv2026

Disruption of cAMP Signalling and RNA Regulation Confers Cefiderocol Resistance in Acinetobacter baumannii

Cefiderocol is a siderophore-conjugated cephalosporin used to treat severe multidrug-resistant Gram-negative infections. Its recent prioritisation for US national preparedness underscores its clinical importance, yet resistance can emerge despite apparent in vitro susceptibility. Here, we identify two regulatory routes to cefiderocol resistance in carbapenem-resistant Acinetobacter baumannii (CRAB): mutation of the cAMP-producing adenylate cyclase CavA and truncation of the glycine-rich RNA-binding domain of the post-transcriptional regulator Hfq. These variants occurred in contemporary clinical isolates, conferred resistance in a murine CRAB lung-infection model and imposed minimal fitness costs. In Escherichia coli, deletion of the CavA orthologue cyaA increased competitive fitness during sub-inhibitory cefiderocol exposure. Hfq-CLASH and integrated omics revealed Hfq-dependent regulation of Fur-associated iron homeostasis in A. baumannii. Under iron limitation, truncated-Hfq induced a defence-primed state that attenuated siderophore uptake and reduced cefiderocol activity. These findings identify bacterial regulatory state and iron availability as determinants of cefiderocol susceptibility, with implications for resistance surveillance and susceptibility testing.

microbiology↗

bioRxiv2025

AMR-GNN: A multi-representation graph neural network framework to enable genomic antimicrobial resistance prediction

Whole-genome sequencing (WGS) data are an invaluable resource for understanding antimicrobial resistance (AMR) mechanisms. However, WGS data are high-dimensional and the lack of standardized genomic representations is a key barrier to AMR prediction. To fully explore these high-resolution data, we propose AMR-GNN, a graph deep learning-based framework that integrates multiple genomic representations with graph neural networks (GNN) to enable AMR prediction from genomic sequence data. We tested AMR-GNN with Pseudomonas aeruginosa, a clinically relevant Gram-negative bacterial pathogen known for its complex AMR mechanisms. We demonstrate that AMR-GNN addresses several key problems in AMR prediction with data-driven machine learning (ML) approaches, including using multiple genomic representations to enhance performance, mitigate the influence of clonal relationships, and identify informative biomarkers to provide explainability and generate novel hypotheses. Follow-up validation on the largest publicly available dataset spanning both Gram-negative and Gram-positive pathogens highlights AMR-GNNs broad applicability in detecting AMR in diverse and clinically relevant pathogen-drug combinations.

genomics↗

bioRxiv2025

Mechanistic insights and clinical implications of cross-reactive anti-prophage antibodies and bacterial heteroresistance on phage therapeutic failure

Phage therapy is an exciting strategy against antimicrobial-resistant bacterial infections, but critical knowledge gaps regarding its clinical application persist. Studying a patient with a life-threatening, chronic bacterial infection who failed phage therapy, we uncovered important biological concepts with direct translational impact. Using longitudinal clinical samples, we found that patients can harbour pre-existing antibodies against active prophages induced from the genome of the causative pathogen. Notably, these antibodies can contribute to clinical failure by cross-reacting with and effectively neutralising therapeutic phage. We also uncovered bacterial heteroresistance, characterised by bacterial subpopulations from the initial infection with reduced phage susceptibility, as a further contributor to treatment failure. These findings highlight the intricate interplay between host immunology, bacterial genetic diversity and phage biology, bearing broad significance for clinical phage therapy. Future phage therapy patients, especially those with chronic infections, should be screened for antiphage immunity and bacterial heteroresistance prior to phage treatment.

microbiology↗

bioRxiv2024

Targeted sequencing of Enterobacterales bacteria using CRISPR-Cas9 enrichment and Oxford Nanopore Technologies

Sequencing DNA directly from patient samples enables faster pathogen characterisation compared to traditional culture-based approaches, but often yields insufficient sequence data for effective downstream analysis. CRISPR-Cas9 enrichment is designed to improve yield of low abundance sequences but has not been thoroughly explored with Oxford Nanopore Technologies (ONT) for use in clinical bacterial epidemiology. We designed CRISPR-Cas9 guide RNAs to enrich for the human pathogen Klebsiella pneumoniae, by targeting multi-locus sequence type (MLST) and transfer RNA (tRNA) genes, as well as common antimicrobial resistance (AMR) genes and the resistance-associated integron gene intI1. We validated enrichment performance in bacterial isolates before comparing enriched and unenriched sequencing of three human faecal samples spiked with K. pneumoniae at varying abundance. Enriched sequencing generated 56x and 11.3x the number of AMR and MLST reads respectively compared to unenriched sequencing and required approximately one third of the computational storage space. Targeting the intI1 gene often led to detection of 10-20 proximal resistance genes due to the long reads produced by ONT sequencing. We demonstrated that CRISPR-Cas9 enrichment combined with ONT sequencing enabled improved genomic characterisation outcomes over unenriched sequencing of patient samples. This method could be used to inform infection control strategies by identifying patients colonised with high-risk strains.

microbiology↗

bioRxiv2023

Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used in clinical microbiology laboratories for bacterial identification but its use for prediction of antimicrobial resistance (AMR) remains limited. Here, we used MALDI-TOF MS with artificial intelligence (AI) approaches to successfully predict AMR in Pseudomonas aeruginosa, a priority pathogen with complex AMR mechanisms. The highest performance was achieved for modern {beta}-lactam/{beta}-lactamase inhibitor drugs, namely ceftazidime/avibactam and ceftolozane/tazobactam, with area under the receiver operating characteristic curve (AUROC) of 0.86 and 0.87, respectively. As part of this work, we developed dynamic binning, a feature engineering technique that effectively reduces the high-dimensional feature set and has wide-ranging applicability to MALDI-TOF MS data. Compared to conventional methods, our approach yielded superior performance in 10 of 11 antimicrobials. Moreover, we showcase the efficacy of transfer learning in enhancing the performance for 7 of 11 antimicrobials. By assessing the contribution of features to the models prediction, we identified proteins that may contribute to AMR mechanisms. Our findings demonstrate the potential of combining AI with MALDI-TOF MS as a rapid AMR diagnostic tool for Pseudomonas aeruginosa.

microbiology↗

bioRxiv2023

genomicBERT and data-free deep-learning model evaluation

The genome, which serves as the inherent language directing the blueprint of life, offers significant analysis prospects by combining Natural Language Processing (NLP) and machine learning (ML). Integrating biological sequences with other digital healthcare information has potential to transform data-driven diagnostics. Large language models (LLMs) can be harnessed to decode the genomic language. This endeavor encounters three critical challenges: First, long biomolecular sequences require segmentation into smaller subunits, which is non-trivial since many biological "words" remain unknown. Second, the analysis of extended DNA sequences using LLMs demands a compute-intensive infrastructure. Third, ensuring reproducibility and reusability of modeling workflows remains an unresolved issue. To tackle these challenges, we introduce an empirical DNA tokenisation approach and a versatile, semantic-aware, genome language model --genomicBERT. The model is species-agnostic and operates seamlessly at the DNA or RNA levels. By introducing a reduced and specialized DNA vocabulary, our approach minimizes computational overhead and optimizes performance. Our benchmarking demonstrates that the genomicBERT matches or surpasses the performance of contemporary tools on the same datasets under different experimental conditions. To encourage collaboration and ease of access, we introduce genomicBERT as an integral component of the openly accessible conda package, genomeNLP. Validated across diverse case studies, genomicBERT lowers the barriers to decoding genomic language, relying solely on sequence data to extract meaningful insights. HighlightsO_LIThis novel model offers a compelling solution for DNA sequence analysis by significantly reducing model size and computational costs without compromising performance, setting a new standard for efficient model development. C_LIO_LIWe demonstrate that a powerful vocabulary and tokenization method helps to derive patterns from biological sequence data while accounting for hidden semantic rules. C_LIO_LIOur method is agnostic to species or biomolecule type as it is data-driven. Hence, it can be applied to DNA and RNA C_LIO_LIWe validate the important genomicBERT tokens by mapping back to the biologically significant motifs. C_LIO_LIWe present a publicly available genome language modeling toolkit called genomeNLP, specifically designed to combine computational linguistics and genomics, enabling researchers from biology backgrounds to analyze and interpret genomic sequences effectively. C_LI

bioinformatics↗

bioRxiv2023

Genomic dissection of endemic carbapenem resistance: metallo-beta-lactamase gene dissemination through clonal, plasmid and integron transfer pathways

Infections caused by metallo-beta-lactamase-producing organisms (MBLs) are a global health threat. Our understanding of transmission dynamics and how MBLs establish endemicity remains limited. We analysed two decades of blaIMP-4 evolution in a hospital using sequence data from 270 clinical and environmental isolates (including 169 completed genomes) and identified extreme gene promiscuity across 7 Gram-negative genera, 68 bacterial strains and 7 distinct plasmid types. An initial multi-species outbreak of conserved IncC plasmids (95 genomes across 37 strains) allowed endemicity to be established through the ability of blaIMP-4 to disseminate in successful strain-genetic setting pairs we termed propagators, in particular Serratia marcescens and Enterobacter hormaechei. From this reservoir, blaIMP-4 persisted through diversification of genetic settings that resulted from transfer of blaIMP-4 plasmids between bacterial hosts and of the integron carrying blaIMP-4 between plasmids. Our findings provide a framework for understanding endemicity and spread of MBLs and may have broader applicability to other carbapenemase-producing organisms.

microbiology↗

bioRxiv2023

Novel determinant of antibiotic resistance: a clinically selected Staphylococcus aureus clpP mutant survives daptomycin treatment by reducing binding of the antibiotic and adapting a rod-shaped morphology

Daptomycin is a last-resort antibiotic used for treatment of infections caused by Gram-positive antibiotic-resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA). Treatment failure is commonly linked to accumulation of point mutations, however, the contribution of single mutations to resistance and the mechanisms underlying resistance remain incompletely understood. Here we show that a single nucleotide polymorphism (SNP) selected during daptomycin therapy inactivates the highly conserved ClpP protease and is causing reduced susceptibility of MRSA to daptomycin, vancomycin, and {beta}-lactam antibiotics as well as decreased expression of virulence factors. Super-resolution microscopy demonstrated that the improved survival of the clpP mutant strain during daptomycin treatment was associated with reduced binding of daptomycin to the septal site and diminished membrane damage. In both the parental strain and the clpP strain, daptomycin inhibited the inward progression of septum synthesis eventually leading to lysis and death of the parental strain while surviving clpP cells were able to continue synthesis of the peripheral cell wall in the presence of 10 x MIC daptomycin resulting in a rod-shaped morphology. To our knowledge, this is the first demonstration that synthesis of the outer cell wall continues in the presence of daptomycin. Collectively, our data provide novel insight into the mechanisms behind bacterial killing and resistance to this important antibiotic. Also, the study emphasizes that treatment with last-line antibiotics is selective for mutations that, like the SNP in clpP, favor antibiotic resistance over virulence gene expression. IMPORTANCEThe bacterium Staphylococcus aureus is a leading cause of life-threatening infections and treatment is challenged by the worldwide dissemination of methicillin-resistant Staphylococcus aureus (MRSA) that are multi-drug resistant. Daptomycin, a cell membrane-targeting cationic lipopeptide, is one of the few antibiotics with activity against MRSA, however, the killing mechanism of daptomycin and the mechanisms leading to resistance are not fully understood. Here we show than an MRSA strain, isolated from the blood of a patient treated with daptomycin, has acquired a mutation that inactivates the ClpXP protease resulting in increased resistance to several antibiotics and diminished expression of virulence genes. Super resolution microscopy showed that the mutant avoids daptomycin-elicited killing by preventing the binding of the antibiotic to the septal site and by growing into a rod-shaped morphology. In summary, this study discloses new perspectives on the mechanism of killing and the mechanism of resistance to an antibiotic of last resort.

microbiology↗

bioRxiv2022

Characterisation of key genotypic and phenotypic traits of clinical cystic fibrosis Staphylococcus aureus isolates

IntroductionOne third of people with CF in the UK are co-infected by both Staphylococcus aureus and Pseudomonas aeruginosa. Chronic bacterial infection in CF contributes to the gradual destruction of lung tissue, and eventually respiratory failure in this group. Gap StatementThe contribution of S. aureus to cystic fibrosis (CF) lung decline in the presence or absence of P. aeruginosa is unclear. Defining the molecular and phenotypic characteristics of a range of S. aureus clinical isolates will help further understand its pathogenic capabilities. AimOur objective was to use molecular and phenotypic tools to characterise twenty-five clinical S. aureus isolates collected from mono- and coinfection with P. aeruginosa from people with CF at the Royal Victoria Infirmary, Newcastle upon Tyne. MethodologyGenomic DNA was extracted and sequenced. Multilocus sequence typing was used to construct phylogeny from the seven housekeeping genes. A pangenome was calculated using Roary. and cluster of Orthologous groups were assigned using eggNOG-mapper which were used to determine differences within core, accessory, and unique genomes. Characterisation of sequence type, clonal complex, agr and spa types was carried out using PubMLST, eBURST, AgrVATE and spaTyper, respectively. Antibiotic resistance was determined using Kirby Bauer disk diffusion tests. Phenotypic testing of haemolysis was carried out using ovine red blood cell agar plates and mucoid phenotypes visualised using Congo red agar. ResultsClinical strains clustered closely based on agr type, sequence type and clonal complex. COG analysis revealed statistically significant enrichment of COG families between core, accessory and unique pangenome groups. The unique genome was significantly enriched for replication, recombination and repair, and defence mechanisms. The presence of known virulence genes and toxins were high within this group, and unique genes were identified in 11 strains. Strains which were isolated from the same patient all surpassed average nucleotide identity thresholds, however, differed in phenotypic traits. Antimicrobial resistance to macrolides was significantly higher in the coinfection group. ConclusionThere is huge variation in genetic and phenotypic capabilities of S. aureus strains. Further studies on how these may differ in relation to other species in the CF lung may give insight into inter-species interactions. Data summaryThe assembled GenBank (gbk) files for all clinical isolates in this study have been deposited in ENA under the study accession PRJEB56184, accession numbers for each of the twenty-five clinical isolates have been provided in Table S1. The reference strains were collected from the NCBI BioSample database (www.ncbi.nlm.nih.gov/biosample): MRSA_252 (NC_002952.2), HO 5096 0412 (NC_017763.1), ST398 (NC_017333.1) and NCTC8325 (NC_007795.1).

microbiology↗

bioRxiv2020

BonA from Acinetobacter baumannii forms a divisome-localized decamer that supports outer envelope function

Acinetobacter baumannii is a high-risk pathogen due to the rapid global spread of multi-drug resistant lineages. Its phylogenetic divergence from other ESKAPE pathogens means that determinants of its antimicrobial resistance can be difficult to extrapolate from other widely studied bacteria. A recent study showed that A. baumannii upregulates production of an outer-membrane lipoprotein, which we designate BonA, in response to challenge with polymyxins. Here we show that BonA has limited sequence similarity and distinct structural features compared to lipoproteins from other bacterial species. Analyses through X-ray crystallography, small-angle X-ray scattering, electron microscopy, and multiangle light scattering demonstrate that BonA has a dual BON-domain architecture and forms a decamer via an unusual oligomerization mechanism. This analysis also indicates this decamer is transient, suggesting dynamic oligomerization plays a role in BonA function. Antisera recognizing BonA shows it is an outer membrane protein localized to the divisome. Loss of BonA modulates the density of the outer membrane, consistent with a change in its structure or link to the peptidoglycan, and prevents motility in a clinical strain (ATCC 17978). Consistent with these findings, the dimensions of the BonA decamer are sufficient to permeate the peptidoglycan layer, with the potential to form a membrane-spanning complex during cell division.

biochemistry↗

bioRxiv2020

Bacteriophages targeting Acinetobacter baumannii capsule induce antimicrobial resensitization

Carbapenem-resistant Acinetobacter baumannii is responsible for frequent, hard-to-treat and often fatal healthcare-associated infections. Phage therapy, the use of viruses that infect and kill bacteria, is an approach gaining significant clinical interest to combat antibiotic-resistant infections. However, a major limitation is that bacteria can develop resistance against phages. Here, we isolated phages with activity against a panel of A. baumannii strains and focused on clinical isolates AB900 and A9844 and their phages for detailed characterization. As expected, coincubation of the phages with their hosts in vitro resulted in the emergence of phage-resistant bacterial mutants. Genome sequence analysis revealed that phage-resistant mutants harbored loss-of-function mutations in genes from the K locus, responsible for the biosynthesis of the bacterial capsule. Using molecular biology techniques, phage adsorption assays, and quantitative evaluation of capsule production, we established that the bacterial capsule serves as the primary receptor for these phages. As a collateral phenotype of impaired capsule production, the phage-resistant strains could not form biofilms, became fully sensitized to the human complement system, showed increased susceptibility to beta-lactam antibiotics, and became vulnerable to additional phages. Finally, in a murine model of bacteremia, the phage-resistant A. baumannii demonstrated a diminished capacity to colonize blood and solid tissues. This study demonstrates that phages can be used not only for their lytic activity but, if combined with a posteriori knowledge of their receptors and the mechanism of bacterial resistance, for their potential synergy with other antimicrobial agents, thus providing even broader clinical options for phage therapy.

microbiology↗

bioRxiv2018

Comprehensive antibiotic-linked mutation assessment by Resistance Mutation Sequencing (RM-seq)

Acquired mutations are a major mechanism of bacterial antibiotic resistance generation and dissemination, and can arise during treatment of infections. Early detection of sub-populations of resistant bacteria harbouring defined resistance mutations could prevent inappropriate antibiotic prescription. Here we present RM-seq, a new amplicon-based DNA sequencing workflow based on single molecule barcoding coupled with deep-sequencing that enables the high-throughput characterisation and sensitive detection of resistance mutations from complex mixed populations of bacteria. We show that RM-seq reduces both background sequencing noise and PCR amplification bias and allows highly sensitive identification and accurate quantification of antibiotic resistant sub-populations, with relative allele frequencies as low as 10-4. We applied RM-seq to identify and quantify rifampicin resistance mutations in Staphylococcus aureus using pools of 10,000 in vitro selected clones and identified a large number of previously unknown resistance-associated mutations. Targeted mutagenesis and phenotypic resistance testing was used to validate the technique and demonstrate that RM-seq can be used to link subsets of mutations with clinical resistance breakpoints at high-throughput using large pools of in vitro selected resistant clones. Differential analysis of the abundance of resistance mutations after a selection bottleneck detected antimicrobial cross-resistance and collateral sensitivity-conferring mutations. Using a mouse infection model and human clinical samples, we also demonstrate that RM-seq can be effectively applied in vivo to track complex mixed populations of S. aureus and another major human pathogen, Mycobacterium tuberculosis during infections. RM-seq is a powerful new tool to both detect and functionally characterise mutational antibiotic resistance.

genomics↗

bioRxiv2017

Evolution of carbapenem resistance in Acinetobacter baumannii during a prolonged infection

Acinetobacter baumannii is a common causative agent of hospital-acquired infections and a leading cause of infection in burns patients. Carbapenem resistant A. baumannii is considered a major public health threat and has been identified by the World Health Organization as the top priority organism requiring new antimicrobials. The most common mechanism for carbapenem resistance in A. baumannii is via horizontal acquisition of carbapenemase genes. In this study, we sampled 20 A. baumannii isolates from a patient with extensive burns, and characterized the evolution of carbapenem resistance over a 45-day period via Illumina and Oxford Nanopore sequencing. All isolates were multi-drug resistant, carrying two genomic islands that harboured several antibiotic resistance genes. Most isolates were genetically identical and represent a single founder genotype. We identified three novel non-synonymous substitutions associated with meropenem resistance: F136L and G288S in AdeB (part of the AdeABC efflux pump) associated with an increase in meropenem MIC to [≥]8 g/mL; and A515V in FtsI (PBP3, a penicillin-binding protein) associated with a further increase in MIC to 32 g/mL. Structural modelling of AdeB and FtsI showed that these mutations affected their drug binding sites and revealed mechanisms for meropenem resistance. Notably, one of the adeB mutations arose prior to meropenem therapy but following ciprofloxacin therapy, suggesting exposure to one drug whose resistance is mediated by the efflux pump can induce collateral resistance to other drugs to which the bacteria has not yet been exposed.\n\nDATA SUMMARYO_LIAll raw genome sequences, including Illumina paired end short reads and Oxford Nanopore long reads, have been deposited in the SRA under project PRJNA396979. Individual accessions for each strain are provided in Table S1.\nC_LIO_LIThe annotated genome assembly for strain A2, the reference genome for the founder genotype, has been submitted to GenBank under accession CP024124 (chromosome) and CP024125 (plasmid).\nC_LIO_LIHybrid assemblies for strains A1, A3, A8, A13, A15, A17 and A20 are available in FigShare, doi: 10.4225/49/5987e14e9b530 (note they were not deposited in GenBank as they differ from A2 by only 1-4 SNPs as indicated).\nC_LI\n\nIMPACT STATEMENTSAcinetobacter baumannii is a highly drug resistant pathogen that is frequently found within intensive care units (ICUs) and especially impacts patients with severe burns. While several studies have examined the global population structure of A. baumannii, few have investigated within-host evolution of A. baumannii in direct response to antibiotic treatment in a single patient. Here, we analysed the genetic evolution of A. baumannii isolated from a patient with severe burns over the course of their stay in ICU. The A. baumannii population on this patient was highly drug resistant, carrying two distinct genomic islands encoding resistance to several antibiotics but not carbapenems. The bacterial population comprised four distinct subclades, two of which had evolved carbapenem resistance over the course of antibiotic treatment through novel mutations in genes associated with drug binding. One subclade was also transmitted to another patient on the ward. While carbapenem resistance is common in A. baumannii, this is generally attributed to horizontally transferred carbapenemase genes. These data provide evidence for carbapenem resistance arising in vivo via non-synonymous substitutions during a single infection episode, demonstrating carbapenem resistance can emerge in genetic isolation in response to exposure to carbapenems and other drugs.

genomics↗