npj antimicrobials and resistance最新文献

Antimicrobial resistance (AMR) databases enable the identification of AMR determinants from pathogen sequence data and the prediction of resistance profiles, enhancing AMR surveillance and informing a range of public health interventions. This review compares freely available and regularly updated AMR databases, explores their public health value and highlights key challenges to and opportunities for fully harnessing their potential.

Patients with advanced chronic liver disease who have underlying cirrhosis are highly susceptible to bacterial infections, which significantly increase the risk of complications and mortality, compounded by escalating antimicrobial resistance. The current gold standard for infection detection and antimicrobial resistance (AMR) profiling remains dependant on traditional microbiological methods. These conventional approaches are slow, labour-intensive, and often fail to deliver timely and accurate results, delaying critical antimicrobial treatment decisions. Clinical metagenomics (CMg) is emerging as a transformative molecular-based tool in infection diagnostics. By enabling the direct sequencing of pathogens from patient-derived samples, CMg offers rapid and comprehensive identification of pathogens and their resistance profiles. Incorporating this technology into the clinical management of patients with cirrhosis has potential to address diagnostic challenges, reduce reliance on broad-spectrum antibiotics and improve outcomes. To effectively incorporate CMg into infection diagnostics, it will be essential to embed of point-of-care sequencing, standardisation of AMR databases, and accessibility to bioinformatics workflows.

Biocides are used in large amounts in industrial, medical, and domestic settings. Benzalkonium chloride (BAC) is a commonly used biocide, for which previous research revealed that Escherichia coli can rapidly adapt to tolerate BAC-disinfection, with consequences for antibiotic susceptibility. However, the consequences of BAC tolerance for selection dynamics and resistance evolution to antibiotics remain unknown. Here, we investigated the effect of BAC tolerance in E. coli on its response upon challenge with different antibiotics. Competition assays showed that subinhibitory concentrations of ciprofloxacin-but not ampicillin, colistin and gentamicin-select for the BAC-tolerant strain over the BAC-sensitive ancestor at a minimal selective concentration of 0.0013-0.0022 µg∙mL^-1. In contrast, the BAC-sensitive ancestor was more likely to evolve resistance to ciprofloxacin, colistin and gentamicin than the BAC-tolerant strain when adapted to higher concentrations of antibiotics in a serial transfer laboratory evolution experiment. The observed difference in the evolvability of resistance to ciprofloxacin was partly explained by an epistatic interaction between the mutations conferring BAC tolerance and a knockout mutation in ompF encoding for the outer membrane porin F. Taken together, these findings suggest that BAC tolerance can be stabilized in environments containing low concentrations of ciprofloxacin, while it also constrains evolutionary pathways towards antibiotic resistance.

The gut microbiome regulates immunity, inflammation, and metabolism. Disruption by antibiotic and non-antibiotic drugs, termed microbiotoxicity, may impair efficacy of treatments, including cancer immunotherapy and vaccination, and contribute to antimicrobial resistance (AMR). This review explores microbiotoxicity's clinical impacts, highlighting non-antibiotic drug effects. Further research into drug-microbiome interactions in future may help inform prescribing practices and drug development as a way to improve health outcomes, reduce toxicity, and support AMR stewardship.

Rapid prediction of antimicrobial resistance (AMR) from genome sequences is essential for timely therapy, yet models based on curated marker panels or core-genome Single Nucleotide Polymorphisms (SNPs) often fail to generalize to novel bacterial lineages. We evaluate AMR prediction in Staphylococcus aureus using pan-genome features that encode homologous gene copy number (including absence) and compare them to SNP-based models across six antibiotics and 4255 isolates. Gradient-boosted decision tree ensembles (XGBoost) trained on gene copy number achieve macro-averaged F1-scores of 0.925-0.988, surpassing SNP-based models (0.838-0.935). Under lineage-held-out evaluation, which withholds entire clades to mimic previously unseen lineages, gene-content models retain markedly higher performance (F1 = 0.875 and 0.904 across two split schemes), whereas SNP-based models degrade substantially (F1 = 0.557 and 0.638). Feature ablation indicates that predictive signal is distributed across many homologous gene families rather than dominated by a few markers, a structure consistent with stronger cross-lineage generalization. Because gene-content features can be robustly obtained even from low-coverage sequencing, this approach extends genome-based AMR prediction to real-world clinical and epidemiological datasets. Together, these results show that copy-number-based pan-genome representations provide a robust alternative to SNP-only approaches, particularly when models must generalize to lineages not represented in training data.

Candida parapsilosis is an opportunistic yeast that was recently deemed a high- importance fungal pathogen by the World Health Organization. In fact, C. parapsilosis poses an escalating threat in healthcare settings due to its ability to adapt to diverse environments, propensity for human-to-human transmission, and capacity to develop antifungal resistance. Recent studies emphasize its rising clinical importance, particularly with the increasing resistance to antifungals and the emergence of clonal outbreaks, making it a serious threat to public health. This review provides an up-to-date synthesis of our current knowledge on this yeast, addressing its epidemiology, environmental adaptability, and the molecular mechanisms driving resistance to azoles and echinocandins. In particular, it provides a comprehensive overview of the resistome of C. parapsilosis, offering insights into the genetic determinants associated with antifungal resistance. We also identify key unresolved questions and emphasize the need for further research to mitigate its impact on healthcare systems.

Antibiotic resistance is surging, demanding approaches that detect resistance before genetic fixation, since MIC, sequencing, and culture assays detect resistance late. We present Metabolomics-Driven Intervention Antibiotic Design (MDAD), which stages resistance evolution from metabolic compensation to sub-lethal adaptation to genetic fixation. A brief pulse challenge with a targeted metabolomics panel yields a pre-genetic risk index, interpreted with time-kill assays to situate early survival behaviours and guide mechanism-aware treatment and surveillance.

Metallo-β-lactamases (MBLs), such as those encoded by bla_IMP-1, confer resistance to carbapenem antibiotics and represent a critical challenge in treating infections caused by multidrug-resistant Pseudomonas aeruginosa. Here, we report a programmable antimicrobial strategy that restores bacterial antibiotic susceptibility through phage capsid-mediated delivery of CRISPR-Cas13a. We engineered a non-replicative phage capsid, which we called antibacterial capsid (AB-Capsid), packaged with a phagemid encoding a codon-optimized Cas13a from Leptotrichia shahii (cas13aPA) and a guide RNA targeting bla_IMP-1. The resulting construct, AB-Capsid_cas13aPA_bla_IMP-1, specifically inhibited the growth of bla_IMP-1-expressing P. aeruginosa and significantly reduced the minimum inhibitory concentration (MIC) of imipenem. No bactericidal effect was observed in the absence of the target gene or with a non-targeting AB-Capsid. Furthermore, spacer-dependent and expression-level-dependent killing activity was confirmed using inducible bla_IMP-1 systems. These findings demonstrate that programmable AB-Capsids delivering Cas13a provide a gene-specific, non-replicative antimicrobial platform capable of reversing drug resistance and represent a versatile class of CRISPR-based antibiotic adjuvants.

Targeted protein degradation (TPD) is an innovative therapeutic approach that bypasses traditional drug inhibition methods. Proteolysis-targeting chimeras (PROTACs) are bifunctional molecules that harness degradation machinery to remove target proteins. This review examines the evolution of PROTACs and their application in targeting microorganisms that develop drug resistance, covering their development, advancements in linker design, E3 ligase selection, and delivery methods, including nanoparticles and exosomes.

Biosolids land application introduces antibiotic resistance genes (ARGs) and clinically relevant pathogens into agricultural soils, raising concerns about long-term environmental and public health impacts. Despite growing interest in biosolids reuse, there remains a critical need for replicated, longitudinal studies to assess how biosolids amendments shape soil microbiomes and resistomes during crop cultivation. In this replicated longitudinal greenhouse study, we used shotgun metagenomics to characterize the impact of biosolids amendment on the soil microbiome, resistome, virulence factors, and ESKAPE pathogens during carrot cultivation. Biosolids-amended soils exhibited increased richness of microbial genera (e.g., Rhodanobacter, Dyella, and Thermomonas), ARG subtypes (resistance to sulfonamide, tetracycline, fosmidomycin, and macrolides), and virulence factors compared to pristine controls. Notably, all six ESKAPE pathogens, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., were detected at elevated relative abundances (1.4- and 3.4-fold) in biosolids-amended soils and remained detectable throughout the 11-week cultivation period. Network analysis revealed statistically supported co-occurrences between microbial taxa and ARGs (with resistance to tetracyclines, beta-lactams, chloramphenicol, and multidrugs), suggesting possible host associations. These findings underscore the ecological and clinical relevance of biosolids amendment and highlight the need for integrated surveillance frameworks to mitigate antimicrobial resistance dissemination in agricultural environments.