The rise of antibiotic-resistant pathogens such as Staphylococcus aureus has created an urgent need for new antibiotics. Generative artificial intelligence (AI) has shown promise in drug discovery, but existing models often fail to propose compounds that are both effective and synthetically tractable. To address these challenges, we introduce SyntheMol-RL, a reinforcement learning-based generative model that can rapidly design synthetically accessible small-molecule drug candidates from a massive chemical space of 46 billion compounds. SyntheMol-RL improves upon our prior Monte Carlo tree search (MCTS)-based SyntheMol model by generalizing across chemically similar building blocks and enabling multi-parameter optimization. We applied SyntheMol-RL to generate candidate antibiotics against S. aureus by optimizing for both antibacterial activity and aqueous solubility, and we found that SyntheMol-RL generated molecules with improved predicted properties compared to both the previous MCTS version of SyntheMol as well as an AI-based virtual screening baseline. We synthesized 79 SyntheMol-RL compounds that were unique relative to the training dataset and found that 13 showed potent in vitro activity, of which seven passed our structural novelty filters that compared them to known antibiotics. Furthermore, one hit compound, synthecin, demonstrated efficacy in a murine wound infection model of methicillin-resistant S. aureus (MRSA). These results validate SyntheMol-RL's ability to generate synthetically accessible candidate antibiotics and position SyntheMol-RL as a powerful tool for drug design across therapeutic domains.

The rise of drug-resistant fungal pathogens, including Candida auris, highlights the urgent need for innovative antifungal therapies. We have developed a cost-effective platform combining microbial extract prefractionation with rapid mass spectrometry-bioinformatics-based dereplication to efficiently prioritize previously uncharacterized antifungal scaffolds. Screening C. auris and Candida albicans reveals coniotins, lipopeptaibiotics isolated from Coniochaeta hoffmannii, which are undetectable in crude extracts. Coniotins exhibits potent activity against critical priority fungal pathogens listed by the World Health Organization, including C. albicans, Cryptococcus neoformans, multidrug-resistant Candida auris, and Aspergillus fumigatus, with high selectivity and low resistance potential. Coniotin A targets beta-glucan, compromising fungal cell wall integrity, remodelling, and sensitizing C. auris to caspofungin. Identification of its hybrid polyketide synthase-nonribosomal peptide synthetase biosynthetic gene cluster facilitates discovering structurally diverse lipopeptaibiotics. Here, we show that natural product prefractionation enables the discovery of previously hidden bioactive scaffolds and introduces coniotins as candidates for combating multidrug-resistant fungal pathogens.

Fungal infections cause millions of deaths annually and are challenging to treat due to limited therapeutic options and rising resistance. Cryptococci are intrinsically resistant to the latest generation of antifungals, echinocandins, while Candida auris, a notorious global threat, is also increasingly resistant. We performed a natural product extract screen to rescue caspofungin fungicidal activity against Cryptococcus neoformans H99 and identified butyrolactol A, which restores echinocandin efficacy against resistant fungal pathogens, including multidrug-resistant C. auris. Mode of action studies revealed that butyrolactol A inhibits the phospholipid flippase Apt1-Cdc50, blocking phospholipid transport. Cryo-electron microscopy analysis of the Apt1•butyrolactol A complex revealed that the flippase is trapped in a dead-end state. Apt1 inhibition disrupts membrane asymmetry, vesicular trafficking, and cytoskeletal organization, thereby enhancing echinocandin uptake and potency. This study identifies lipid flippases as promising antifungal targets and demonstrates the potential of revisiting natural products to expand the antifungal arsenal and combat resistance.

Carbapenems are last-resort antibiotics for treating bacterial infections. The widespread acquisition of metallo-β-lactamases, such as VIM-2, contributes to the emergence of carbapenem-resistant pathogens, and currently, no metallo-β-lactamase inhibitors are available in the clinic. Here we show that bacteria expressing VIM-2 have impaired growth in zinc-deprived environments, including human serum and murine infection models. Using transcriptomic, genomic and chemical probes, we identified molecular pathways critical for VIM-2 expression under zinc limitation. In particular, disruption of envelope stress response pathways reduced the growth of VIM-2-expressing bacteria in vitro and in vivo. Furthermore, we showed that VIM-2 expression disrupts the integrity of the outer membrane, rendering VIM-2-expressing bacteria more susceptible to azithromycin. Using a systemic murine infection model, we showed azithromycin’s therapeutic potential against VIM-2-expressing pathogens. In all, our findings provide a framework to exploit the fitness trade-offs of resistance, potentially accelerating the discovery of additional treatments for infections caused by multidrug-resistant bacteria. Expression of VIM-2 leads to physiological trade-offs for bacterial pathogens that can be exploited to treat infections caused by multidrug-resistant bacteria.

The strong association of the human leukocyte antigen B∗27 alleles (HLA-B∗27) with spondyloarthritis and related rheumatic conditions has long fascinated researchers, yet the precise mechanisms underlying its pathogenicity remain elusive. Here, we review how interplay between the microbiome, the immune system, and the enigmatic HLA-B∗27 could trigger spondyloarthritis, with a focus on whether HLA-B∗27 presents an arthritogenic peptide. We propose mechanisms by which the unique biochemical characteristics of the HLA-B∗27 protein structure, particularly its peptide binding groove, could dictate its propensity to induce pathological T cell responses. We further provide new insights into how TRBV9+ CD8+ T cells are implicated in the disease process, as well as how the immunometabolism of T cells modulates tissue-specific inflammatory responses in spondyloarthritis. Finally, we present testable models and suggest approaches to this problem in future studies given recent advances in computational biology, chemical biology, structural biology, and small-molecule therapeutics.

Current clinical antibiotics are largely broad-spectrum agents that can alter the gut microbiome and promote colonization by Enterobacteriaceae, which are often drug resistant. This includes adherent-invasive Escherichia coli (AIEC), particularly in patients with inflammatory bowel disease, in which dysbiosis creates a niche for this pathogen to colonize. There is an urgent and unmet need for novel narrow-spectrum and microbiome-sparing antibiotics. Here we screened 10,747 bioactive small molecules for antibacterial activity against AIEC and discovered enterololin, an antibacterial compound with targeted activity against Enterobacteriaceae species. Enterololin could overcome intrinsic and acquired resistance mechanisms in clinical isolates when combined with a subinhibitory concentration of SPR741, a polymyxin B analogue used here to increase outer membrane permeability in Gram-negative bacteria. Molecular substructure- and deep learning-guided mechanism-of-action investigations revealed that enterololin perturbs lipoprotein trafficking through a mechanism involving the LolCDE complex, laboratory-evolved resistant mutants predominantly mapped to lolC and lolE, with an in vitro frequency of resistance of ~10-8 to 10-7. Enterololin showed low mammalian cytotoxicity (HEK293 half-maximal inhibitory concentration ~100 µg ml-1) and suppressed AIEC infection in mouse models when administered in combination with SPR741, while largely preserving the overall microbiome composition. This study highlights the utility of deep learning methods for predicting molecular interactions and identifies a promising Enterobacteriaceae-specific antibacterial candidate for further development.

Wastewater-based analysis has emerged as a pivotal method for monitoring SARS-CoV-2 (SC2). Leveraging high-throughput sequencing on wastewater samples facilitates a comprehensive, population-level assessment of circulating and emerging SC2 variants within a community. This study meticulously evaluates the detection performance, variant calling accuracy, and the time taken from sample collection to public data release for wastewater SC2 monitoring. Two different SC2 target enrichment panels were employed, Illumina MiSeq and Oxford Nanopore Technologies (ONT) GridION sequencing platforms for a robust analysis. Daily collection of routine raw grab and composite samples took place at a wastewater treatment plant (WWTP) site in Maryland, USA (MD) from mid-January 2022 to the end of June 2022. Total Nucleic Acid (TNA) was extracted from samples and target enrichment was executed using QIAseq DIRECT and NEBNext VarSkip Short amplicon kits, with subsequent sequencing on MiSeq or ONT GridION platforms, respectively. Obtained sequences was analyzed using custom CFSAN Wastewater Analysis Pipeline (C-WAP). Raw sequence data and detailed metadata were submitted to NCBI (BioProject PRJNA757291) as it became available. Wastewater data successfully detected the onset of new variants BA.2, BA.2.12, BA.4.6, and BA.5 to the observed population. Notably, Omicron sub-variants were identified approximately a week ahead of publicly available clinical data at the MD ZIP-code level. Variation in quality metrics paralleled the rise and fall of BA waves, underscoring the impact of viral load on sequencing quality. Regular updates of estimated variant proportions were made available on the FDA-CFSAN "Wastewater Surveillance for SARS-CoV-2 Variants" website. In contrast to the median 28-day turnaround, the lead time from sample collection to public release of raw sequence data via NCBI was remarkably swift, accomplished within a mere 57 h in this specific exercise. Processing, sequencing, and analysis methods empowered the swift and accurate detection of SC2 trends and circulating variants within a community, offering insights for public health decision-making.

Context: The genomic surveillance of foodborne pathogens in the United States has grown exponentially in the past decade, grounded in a powerful combination of novel sequencing technologies, bioinformatic approaches, data-sharing networks, and metadata harmonization efforts. This practice report examines recent advances in genomic epidemiology as applied to food safety programs and delineates State, Tribal, Local, and Territorial infrastructure necessary for continued life-saving improvements in public health. Program: National databases of foodborne pathogen genomes, along with data sharing and evaluation networks such as GenomeTrakr and PulseNet, have transformed how connections are made among isolates and how root causes of outbreaks are determined, allowing much more timely interventions to protect public health. Freely available bioinformatics tools such as GalaxyTrakr and the National Center for Biotechnology Information Pathogen Detection database have allowed laboratories with limited local computing resources to participate in surveillance efforts and contribute to traceback investigations. Implementation: In this report, we describe advances in genomic epidemiology that have occurred over the past decade and examine obstacles to fully implementing this technology within State, Tribal, Local, and Territorial public health systems. Evaluation: Despite a clear return on investment from governmental expenditures on genomic surveillance of foodborne pathogens, we identify significant obstacles to further sustained progress. These obstacles include workforce gaps, ineffective data sharing, and lack of constitutive and sustained funding. Discussion: Many public health laboratories face major obstacles to widespread and routine adoption of genomic surveillance technologies. While whole genome sequencing has become an integral part of routine public health microbiology, the seamless integration of these protocols into the existing practices, laboratory workflows, and information systems remains challenging. Centralized efforts to address these issues include (1) support through the Food and Drug Administration Laboratory Flexible Funding Model, (2) training and proficiency assessments, (3) open-source, standardized protocols for collecting high-quality genomic data, and (4) open access informatics software.

The postantibiotic effect (PAE) is the delay in bacterial regrowth following antibiotic removal. It has important implications for dosing regimens since drugs that have extended activity following their elimination can be dosed less frequently, widening the therapeutic window. While the PAE has been associated with target vulnerability and the rate of target turnover, little is known about the genetic components that modulate the PAE. Here, we developed a high-throughput assay to screen the Escherichia coli Keio collection of ∼4000 deletion strains, identifying genes that enhance the PAE for CHIR-090, an inhibitor of UDP-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC). This screen revealed approximately 400 gene knockouts that enhanced the PAE of CHIR-090. The list of PAE enhancers was enriched for genes involved in transmembrane transport and outer membrane synthesis. Notably, deletion of the rfaE gene, which is involved in lipopolysaccharide (LPS) biosynthesis, increased the PAE of the LpxC inhibitors CHIR-090 and LPC-058 by 2 and 3 h, respectively. Consistent with this phenotype, cotreatment of wild-type E. coli with an RfaE inhibitor increased the PAE of CHIR-090 or LPC-058 by 1 h. To probe the mechanism of this interaction, we measured the rate of LpxC turnover and found that knocking out rfaE extended the half-life of LpxC by 2-fold, suggesting that disrupting RfaE increases the stability of LpxC, increasing target vulnerability and enhancing the PAE of LpxC inhibitors.

The rise of drug-resistant fungal pathogens, including Candida auris, highlights the urgent need for novel antifungal therapies. We developed a cost-effective platform combining microbial extract prefractionation with rapid MS/MS-bioinformatics-based dereplication to efficiently prioritize new antifungal scaffolds. Screening C. auris and C. albicans revealed novel lipopeptaibiotics, coniotins, from Coniochaeta hoffmannii WAC11161, which were undetectable in crude extracts. Coniotins exhibited potent activity against critical fungal pathogens on the WHO Fungal Priority Pathogens List, including C. albicans, C. neoformans, multidrug-resistant C. auris, and Aspergillus fumigatus, with high selectivity and low resistance potential. Coniotin A targets β-glucan, compromising fungal cell wall integrity, remodelling, and sensitizing C. auris to caspofungin. Identification of a PKS-NRPS biosynthetic gene cluster further enables the discovery of related clusters encoding potential novel lipopeptaibiotics. This study demonstrates the power of natural product prefractionation in uncovering bioactive scaffolds and introduces coniotins as promising candidates for combating multidrug-resistant fungal pathogens.

Wall teichoic acid (WTA) is a polyol phosphate polymer that covalently decorates peptidoglycan of gram-positive bacteria, including Staphylococcus aureus . Central to WTA biosynthesis is flipping of lipid-linked precursors across the cell membrane by TarGH, a type V ABC transporter. Here, we present cryo-EM structures of S. aureus TarGH in the presence of targocil-II, a promising small-molecule lead with β-lactam antibiotic synergistic action. Targocil-II binds to the extracellular dimerisation interface of TarG, we suggest mimicking flipped but not yet released substrate. In absence of targocil-II and in complex with ATP analogue ATPγS, determined at 2.3 Å resolution, the ATPase active site is allosterically inhibited. This is due to a so far undescribed D-loop conformation, potentially minimizing spurious ATP hydrolysis in the absence of substrate. Targocil-II binding comparatively causes local and remote conformational changes through to the TarH active site, with the D-loop now optimal for ATP hydrolysis. These structures suggest an ability to modulate ATP hydrolysis in a WTA substrate dependent manner and a jammed ATPase cycle as the basis of the observed inhibition by targocil-II. The molecular insights provide an unprecedented basis for development of TarGH targeted therapeutics for treatment of multidrug-resistant S. aureus and other gram-positive bacterial infections.

ABSTRACT Surface waters function as ecological niches where Salmonella enterica can persist and disseminate to fresh produce production systems. We examined the genomic characteristics of S. enterica serotypes Agona (n = 86), Braenderup (n = 47), Muenchen (n = 53), and Panama (n = 69) isolates from surface waters in Chile, Mexico, and Brazil between 2019 and 2022. Mexican isolates consistently displayed a higher occurrence of genotypic antimicrobial resistance (AMR) than Chilean and Brazilian isolates. All S. Agona isolates exhibited the presence of fosA7.2, while qnrB19 emerged as the predominant AMR gene (ARG) among S. Braenderup isolates. S. Muenchen isolates from Chile displayed an absence of any ARGs, while those from Mexico and Brazil predominantly carried qnrB19. Among S. Panama isolates from Chile, aadA1, floR, sat2, and tet(B) were the most prevalent ARGs, whereas those from Mexico and Brazil harbored tet(A), and floR and tet(A) as the leading ARGs, respectively. ARG sharing among isolates and ARG co-occurrence within individual isolates were prevalent across countries and serotypes. All isolates containing integrons exhibited genotypic multidrug resistance. The principal coordinates analysis reveals distinct clustering patterns based on country, serotype, number of ARGs per isolate, and plasmid and integron presence/absence. The whole-genome phylogenetic analysis demonstrates clear clusters, each associated with their respective countries. However, a notable exception was observed with one S. Agona isolate from Brazil closely related to two isolates from Chile, differing by only 18 and 19 single-nucleotide polymorphisms, respectively.IMPORTANCEThis comprehensive study explored the intricate genomic landscapes of S. Agona, Braenderup, Muenchen, and Panama isolates from surface waters across Chile, Mexico, and Brazil. By filling important knowledge gaps related to the genomic characteristics of these serotypes, the research offers a nuanced understanding of these serotypes as potential reservoirs for multidrug resistance. Our findings emphasize the urgency of targeted interventions to mitigate the emergence and dissemination of multidrug-resistant Salmonella enterica. This work underscores the need for informed policies and collaborative efforts to address the risks posed by S. enterica in Latin American surface waters.

Salmonella enterica (S. enterica), a ubiquitous zoonotic foodborne pathogen, remains a worldwide public health hazard and economic burden. In recent years, outbreaks associated with the consumption of plant-based foods probably contaminated by irrigation water highlights the importance of water sources. This study investigated anthropogenic and environmental factors influencing S. enterica occurrence in natural watersheds impacted by agricultural and livestock industries in a 10-month longitudinal study in Paraiba, Brazil. Water samples were obtained from multiple sites within the three major river basins by modified Moore Swabs (MMS) and processed by conventional S. enterica isolation methodologies. Physicochemical parameters, climate, and human activities near the water sources were recorded. A logistic regression model was fitted using Generalized Linear Model (GLM) and further adjusted according to the selected variables using the Least Absolute Shrinkage and Selection Operator (LASSO) method. A non-statistical decision tree model was also fitted using the rpart package in R. Season, rainfall regime, water physicochemical features, and anthropogenic activities were significantly associated with S. enterica contamination. According to the regression tree analysis, rainfall within the sampling month was the strongest predictor of S. enterica recovery, potentially due to leaching from soil or runoff from adjacent human and animal activities. The complexity of multivariate conditions driving S. enterica contamination in surface waters highlights the need for region-specific investigations.

Antimalarial drug discovery largely relies on nutrient-rich media that may obscure physiologically relevant targets. In this issue of Cell Chemical Biology, Molina et al.1 validate the plasmodial surface anion channel as essential for Plasmodium falciparum survival under nutrient-restricted conditions, demonstrating how physiological media can expose druggable biology overlooked by standard screening approaches.

Fungal infections cause millions of deaths annually and are challenging to treat due to limited therapeutic options and rising resistance. Cryptococci are intrinsically resistant to the latest generation of antifungals, echinocandins, while Candida auris, a notorious global threat, is also increasingly resistant. We performed a natural product screen to rescue caspofungin fungicidal activity against Cryptococcus neoformans H99 and identified butyrolactol A, which restores echinocandin efficacy against resistant fungal pathogens, including multidrug-resistant C. auris. Mode-of-action studies reveal that butyrolactol A inhibits the phospholipid flippase Apt1-Cdc50, blocking phospholipid transport. Cryo-electron microscopy analysis of the Apt1-butyrolactol A complex reveals that the flippase is trapped in a dead-end state. Apt1 inhibition disrupts membrane asymmetry, vesicular trafficking, and cytoskeletal organization, thereby enhancing echinocandin uptake and potency. This study identifies lipid flippases as promising antifungal targets and demonstrates the potential of revisiting natural products to expand the antifungal arsenal and combat resistance.

Surface water ecosystems are intimately intertwined with anthropogenic activities and have significant public health implications as primary sources of irrigation water in agricultural production. Our extensive metagenomic analysis examined 404 surface water samples from four different geological regions in Chile and Brazil, spanning irrigation canals (n = 135), rivers (n = 121), creeks (n = 74), reservoirs (n = 66), and ponds (n = 8). Overall, 50.25 % of the surface water samples contained at least one of the pathogenic or contaminant bacterial genera (Salmonella: 29.21 %; Listeria: 6.19 %; Escherichia: 35.64 %). Furthermore, a total of 1,582 antimicrobial resistance (AMR) gene clusters encoding resistance to 25 antimicrobial classes were identified, with samples from Brazil exhibiting an elevated AMR burden. Samples from stagnant water sources were characterized by dominant Cyanobacteriota populations, resulting in significantly reduced biodiversity and more uniform community compositions. A significant association between taxonomic composition and the resistome was supported by a Procrustes analysis (p < 0.001). Notably, regional signatures were observed regarding the taxonomic and resistome profiles, as samples from the same region clustered together on both ordinates. Additionally, network analysis illuminated the intricate links between taxonomy and AMR at the contig level. Our deep sequencing efforts not only mapped the microbial landscape but also expanded the genomic catalog with newly characterized metagenome-assembled genomes (MAGs), boosting the classification of reads by 12.85 %. In conclusion, this study underscores the value of metagenomic approaches in surveillance of surface waters, enhancing our understanding of microbial and AMR dynamics with far-reaching public health and ecological ramifications.

Advances in gene editing, in particular CRISPR interference (CRISPRi), have enabled depletion of essential cellular machinery to study the downstream effects on bacterial physiology. Here, we describe the construction of an ordered E. coli CRISPRi collection, designed to knock down the expression of 356 essential genes with the induction of a catalytically inactive Cas9, harbored on the conjugative plasmid pFD152. This mobile CRISPRi library can be conjugated into other ordered genetic libraries to assess combined effects of essential gene knockdowns with non -essential gene deletions. As proof of concept, we probed cell envelope synthesis with two complementary crosses: (1) an Lpp deletion into every CRISPRi knockdown strain and (2) the lolA knockdown plasmid into the Keio collection. These experiments revealed a number of notable genetic interactions for the essential phenotype probed and, in particular, showed suppressing interactions for the loci in question.