mSystems

Understanding pathogen metabolism is critical for identifying key functions for drug targeting, establishing effective in vitro experimental systems, etc., particularly for metabolically unique organisms such as Leptospira. Pathogenic Leptospira are thought to infect humans from environmental sources; however, direct isolation from environmental samples remains technically challenging and is not yet well established. Here, we report that a ubiquitous environmental bacterium, Massilia sp., produces metabolites that promote the growth of Leptospira interrogans, encountered through an incidental contamination event, and identified in this study. Gas chromatography-tandem mass spectrometry (GC-MS/MS) analysis showed demonstrated that cultivating of Massilia sp. in R2A medium resulted in the accumulation of metabolites, including branched-chain amino acid (BCAA) intermediates, compared to fresh medium. By combining genome-scale metabolic modeling with experimental validation using cell-free culture supernatant supplementation assays, we demonstrate that BCAA intermediates, particularly 2-ketoisocaproic acid (4-methyl-2-oxopentanoate; 4MOP), a leucine biosynthetic intermediate produced by Massilia sp., enhance Leptospira growth. To investigate the metabolic role of 4MOP, we incorporated transcriptomic data into a genome-scale metabolic network model to generate condition-specific models. Resulted flux distributions indicated that Leptospira catabolized imported 4MOP to produce acetyl-CoA. Our results reveal a previously unrecognized metabolic interaction where metabolites produced by environmental bacteria support the growth of pathogenic Leptospira, offering mechanistic insight into its metabolic requirement. These findings have implications to understand the environmental persistence of Leptospira through its metabolic dependencies on coexisting microbes, and they also help develop better strategies for this pathogen. ImportancePathogenic Leptospira persist in environmental reservoirs, yet the mechanisms supporting their growth remain poorly defined. Here, we find that metabolites produced by common environmental bacteria, Massilia sp., can promote Leptospira growth, suggesting a previously unrecognized metabolic dependency on coexisting microbes. Importantly, this study indicates that combining genome-scale metabolic modeling with experimental validation provides a useful framework for identifying metabolic interactions that are otherwise difficult to resolve using conventional culture-based approaches. Current strategy may facilitate the systematic identification of growth-supporting metabolites and provide a basis for improving selective cultivation for uncultured or difficult to culture organisms. Determination of growth promoting metabolites advances our understanding of pathogen persistence in natural environments and offers a generalized framework to study metabolically dependent microorganisms.

Honeypot ants engage in a convergently-evolved phenotype called repletism, where specialized workers expand their crops and gasters to store vast amounts of food internally. They then store that food for months to support colonies during times of food scarcity. This fascinating phenotype is not well-understood and very little is known about the microbial interactions happening within the fructose-rich replete crop. Previous research using amplicon sequencing showed that Fructilactobacillus makes up nearly 100% of the crop microbiomes of Myrmecocystus mexicanus repletes. This striking result and successful isolation of those strains led to the present investigation into the phylogenetic diversity of these strains and any clues to the nature of the symbiotic relationship between them and the ant host. We find that the isolates from these repletes represented two evolutionary lineages, both most closely related to F. fructivorans. One of those lineages was also found to be phylogenetically and metabolically distinct from all other Fructilactobacillus reference genomes used in this study. This discovery in a genus of bacteria that are highly relevant for fermented human foods and will also lay the groundwork for future understanding of the convergent evolutionary mechanisms of repletism in ants. 3. Impact statementThese analyses add to the literature by identifying a new microbe within a genus that is relevant to food systems. In addition, the host phenotype is convergently evolved and likely microbe-mediated (or at least highly exposed). Understanding this system allows for the testing of ideas of coevolutionary hypotheses with natural replicates. We expect interest to come from food safety and probiotics researchers, evolutionary biologists that think about the impacts of microbes, microbial ecologists interested in novel systems, and those interested in bacteria that may display unique metabolic possibilities. This output allows for the clear future examination of this system with many clear hypotheses. Our analysis allows for the creation of a new and unique model system of host-microbe symbiosis. 4. Data summaryNew genomes assembled in this work can be found under BioProject ID PRJNA1449409. https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1449409. Reference bacterial genomes were obtained from NCBI at the following accession numbers: SAMN20557570, SAMN28081009, SAMN28081010, SAMN02597458, SAMN43111088, SAMN28081011, SAMN28535231, SAMN04505734, SAMN28081013, SAMN33452149, SAMN37926504, SAMN02849426, SAMN02470196, SAMN02369432, SAMN02797779, SAMN02797782, SAMN02797768, SAMN09762388, SAMN12785275, SAMEA117660288. The honeypot ant genome was obtained from SAMN37666067. Raw proteomics files will be uploaded to ProteomeXchange with a unique identifier upon manuscript acceptance.

Metaproteomics enables the functional characterization of microbiomes and host-microbe interactions by detecting and quantifying thousands of proteins. In data-dependent acquisition metaproteomics, protein quantification is commonly performed using either MS1-based area under the curve (AUC) or MS2-based peptide spectral counts (SpC). In AUC quantification, match between runs (MBR) is frequently employed to minimize data sparsity, yet its impact on metaproteomic data remains unclear. Understanding MBRs impact on metaproteomics data is especially important due to the high peak density in the MS1 mass spectra and the potential presence of not only proteins, but even entire organisms, in one sample and their absence in the other, which would complicate accurate feature mapping and transfer. While accurate quantification is essential for deriving meaningful biological inferences from metaproteomic analyses, systematic evaluations of AUC and SpC quantification in metaproteomics remain scarce. In this study, we used defined complex metaproteomic samples to perform a ground truth-based evaluation of AUC and SpC quantification and to determine the impact of MBR on AUC quantification. We found that MBR led to a substantial number of falsely identified proteins in complex samples. Protein identifications from an organism not present in the sample were wrongly transferred from other samples when MBR was used. We found that MBR-free AUC data had a wider dynamic range, higher quantitative accuracy, and more sensitive detection of abundance differences. Significance of the StudyAlthough metaproteomics is increasingly used to advance microbiome research, quantification strategies in metaproteomics are mostly selected based on convention rather than evidence, due to a lack of ground truth-based evaluation of quantification strategies in metaproteomics. Accurate protein quantification is key to deriving meaningful biological inferences from metaproteomic samples, yet it remains challenging due to their high complexity and uneven protein abundances. Here, we used defined metaproteomic samples to evaluate widely used quantification strategies in metaproteomics and to determine the effects of match between runs (MBR) on quantitative accuracy. Based on our findings, MBR adds falsely identified proteins to metaproteomic data. While MBR-free AUC offers a broader dynamic range and higher quantitative accuracy, SpC offers better proteome coverage. With this study, we provide an evidence-based framework for the informed selection of quantification strategies in metaproteomics, and highlight the strengths and limitations of these approaches with respect to proteome coverage, dynamic range, quantitative accuracy, and error propagation. Our findings also have important implications for the biological interpretation of data derived from these strategies and lay the groundwork for future studies validating quantitative approaches in data-independent acquisition workflows.

The female reproductive tract harbors complex microbial communities that may influence reproductive success. In previous work using 16S rRNA gene sequencing, we identified bacterial taxa in the vagina and uterus of beef cattle associated with pregnancy outcomes, but taxonomic resolution and functional inference was limited. Here we used shotgun metagenomic sequencing to characterize the taxonomic composition, functional potential, and antimicrobial resistome of vaginal and uterine microbiomes at the time of artificial insemination (AI) in cows that subsequently became pregnant or remained open. Vaginal (pregnant n = 54; open n = 7) and uterine (pregnant, n = 41; open, n = 9) samples were collected prior to AI. Microbial community structure did not differ between pregnancy outcome groups in either anatomical site (PERMANOVA; P > 0.05). However, cows that remained open showed significantly greater species-level richness and diversity in the vaginal microbiome (P < 0.05). No diversity differences were observed in the uterine microbiome. In contrast, significant differences were detected between anatomical sites, with distinct dominant taxa and functional profiles. Vaginal microbiomes were enriched in pathways related to genetic information processing, whereas uterine microbiomes exhibited greater representation of metabolic pathways. A total of 105 ARGs spanning 11 antimicrobial classes were identified, with tetracycline resistance genes [tet(Q), tet(W), and tet(M)] predominating, and blaTEM-116 more abundant in the uterine microbiome. Overall, while vaginal and uterine microbiomes were compositionally and functionally distinct, no robust pregnancy-associated taxonomic or functional signatures were detected, likely reflecting limited statistical power and challenges inherent to low-biomass metagenomic datasets. IMPORTANCEUnderstanding the role of the reproductive tract microbiome in fertility could improve reproductive efficiency in cattle. We used shotgun metagenomic sequencing to characterize the taxonomic composition, functional potential, and antimicrobial resistome of vaginal and uterine microbiomes at the time of artificial insemination in cows that subsequently became pregnant or remained open. Using paired samples from the same animals, we directly compared microbial communities between the upper and lower reproductive tract to identify shared and site-specific features. Although no distinct microbial signatures associated with pregnancy outcomes were detected, this may reflect limited statistical power and low microbial biomass inherent to these samples. Despite these challenges, our study provides high-resolution insights into the composition, functional potential, and resistome of bovine reproductive microbiomes and highlights important technical considerations for studying low-biomass microbial ecosystems.

Short-chain fatty acids (SCFAs) like butyrate and propionate are abundant microbiota-derived metabolites that influence bacterial physiology in host-associated niches such as the gastrointestinal tract. However, their effects on Staphylococcus aureus under varying nutritional conditions remain incompletely understood. Here we investigated how SCFAs interact with glucose or galactose to regulate anaerobic growth, biofilm formation, and global transcription in S. aureus. Both SCFAs inhibit growth in a dose-dependent manner. Biofilm formation was differentially affected, with butyrate promoting and propionate suppressing biofilm formation. Glucose and galactose alleviated SCFA-mediated growth inhibition, with glucose exerting the strongest effect. Notably, glucose enhanced butyrate-associated growth and biofilm formation beyond glucose alone, whereas galactose produced more modest effects. Enzymatic and genetic analyses indicated that SCFA-sugar biofilms contain proteins and extracellular DNA and involve VraSR-dependent regulation. Transcriptomic profiling revealed broad metabolic reprogramming, including induction of urease genes, amino acid biosynthesis, and stress response pathways. Synergistic effects between butyrate and glucose were partially dependent on anaplerotic metabolism via pyruvate carboxylase, linking the TCA cycle to SCFA adaptation. Together these findings demonstrate that the nutritional environment dictates whether SCFAs impair S. aureus growth or reprogram its physiology, promoting metabolic adaptation and biofilm formation under sugar-replete conditions.

Adaptive laboratory evolution is used to improve the phenotypes of microorganisms and to characterise the mechanisms underlying resistance against complex growth inhibition. Here we focused on lactic acid bacteria (LAB) as starter cultures for food fermentations. Production of LAB starter cultures is challenging due to growth inhibition by organic acids, mainly lactate, produced during fermentation. By utilising stressostat cultivation we generated Lactococcus lactis isolates with enhanced lactate resistance. Using a combination of (meta)genomics, proteomics and pH-controlled batch fermentations, we deciphered the lactate resistance mechanisms of these L. lactis isolates. Proteome responses of L. lactis, combined with similar growth inhibition at high salt, suggest that high lactate mainly causes osmotic stress. We identified RNA polymerase (RNAP) mutations in subunits {beta} (rpoB) and {beta} (rpoC) as key mutations, causing pleiotropic effects in the proteome. These proteome adaptations are linked to enhanced lactate resistance, particularly the resistance to hyperosmotic stress without glycine-betaine supplementation, likely by altering cross-linking of the peptidoglycan in the cell envelope via downregulation of MurE. The proteome changes indicate that lactate might (indirectly) cause oxidative stress. Combined, our study shows that RNAP mutations enhanced lactate resistance through pleotropic effects in the proteome that changed L. lactis responses against multiple stresses. HighlightsO_LILactate resistant variants were isolated from stressostat cultivations C_LIO_LIMetagenomics revealed evolutionary trajectory during stressostat cultivation C_LIO_LIRNAP mutations were identified as key drivers for improved lactate resistance C_LIO_LIRNAP mutations altered the proteome, enhancing the osmotic stress resistance C_LI

The supernatant of Bacillus toyonensis biovar thuringiensis Bto_UNVM-42 exhibits nematicidal activity, although its molecular basis remains unclear. While pesticidal proteins in Bacillus thuringiensis and related species are classically considered to be intracellular and associated with parasporal crystals, their potential presence in the extracellular fraction has been largely unexplored. Here, LC-MS/MS analysis of the secretome from LB-grown cultures revealed the extracellular presence of pesticidal protein homologs related to Cry32-, Cyt1-, and Mpp3-like protein families, together with degradative enzymes including collagenase, chitinase, proteases, and cytolysins. Signal peptide prediction supported classical secretion for several proteins, while others were consistent with non-classical secretion pathways. The consistent detection of these proteins in cell-free supernatants provides strong proteomic evidence for their extracellular localization. These findings challenge the prevailing crystal-centric paradigm of Bt-like pesticidal proteins and support an expanded model in which soluble extracellular components contribute to pathogenicity. This work highlights the value of secretome analysis for the characterization of Bt-like strains and provides new insights into the molecular basis of nematicidal activity in B. toyonensis. O_LIFirst report of Cry32-, Cyt-, and Mpp-like homologs in the Bto_UNVM-42 secretome. C_LIO_LIExtracellular detection challenges classical intracellular Bt-like toxin paradigm. C_LIO_LILC-MS/MS reveals toxin homologs in culture supernatant. C_LIO_LIEvidence supports secretion beyond crystal-associated proteins. C_LIO_LISecretome suggests expanded functional repertoire in Bt-related strains. C_LI

BackgroundGut microbiome disruption is often characterized by loss of obligate anaerobic bacteria, which may lead to altered production of microbial metabolites that can be detected peripherally. The application of widely used sequencing-based microbiome analyses to clinical settings is limited by cost, turnaround time, and challenges with patients with very low stool output. Since some products of strictly bacterial metabolism detectable in blood, peripheral metabolites may provide a potentially rapid and scalable indicator of gut microbiome composition and function. We performed a systematic review and meta-analysis of studies reporting circulating microbial metabolites and gut microbiome composition to evaluate whether peripheral microbial metabolites could identify gut microbiome perturbation. ResultsCandidate metabolites were identified systematically across an independent set of studies reporting metabolite-microbiome associations, enabling assessment of reproducibility across disease states and cohorts. We performed a meta-analysis of 19 human cohorts comprising 3242 participants with paired blood metabolite and stool microbiome data. Anaerobe depletion (obligate anaerobe relative abundance <0.70 by sequencing) was associated with decreased products of anaerobic microbial metabolism. Combinations of metabolites distinguished individuals with anaerobe-depleted microbiomes from those without. Circulating metabolite levels distinguished between cases and controls with similar performance as gut microbiome composition across a range of health/disease states, and changed markedly within patients experiencing gut anaerobe depletion after antibiotic exposure. ConclusionsCirculating microbial metabolites are potentially informative indicators of gut microbiome disruption and may serve as a rapid and method for patient stratification in clinical trials or acute care settings. ImportanceCirculating microbial metabolites represent a practical and scalable approach to detecting significant gut microbiome disruption, particularly loss of obligate anaerobes. Unlike stool-based sequencing, which can be logistically challenging and slow, blood-based metabolite profiling could be actionably integrated into existing clinical workflows. Our findings suggest metabolites capture compositional consequences of microbiome collapse, with performance comparable to direct microbiome profiling in distinguishing disease states. Enabling diagnostic enrichment and real-time monitoring of microbiome injury (e.g., during antibiotic use or critical illness) has potential implications for both clinical care and research, including selection of patients for investigation of microbiome-targeted therapies. With further validation, circulating metabolites could provide an accessible surrogate for gut microbiome composition in settings where sequencing is impractical.

Characterizing aroma and flavours generated during cheese production is of high relevance for the food industry. A deeper comprehension of flavour generation can be achieved by understanding the role of microbial population governing milk processing, and in particular their metabolic activity governed by gene expression. In this work we considered two independent experiments in which gene expression of the microbial population involved in cheese processing is sampled, together with final volatile products quantification. We estimated the final volatile compound profile from the measured metatranscriptomic expression by using machine learning with two different strategies for model training and validation, and we were able to associate specific biochemical pathways to the identified gene signatures.

Hydrocarbons are recalcitrant organic matter that are released into the environment via natural and anthropogenic activities. We hypothesized that abiotic and biotic factors, including salinity, temperature, seasonality, microbial interactions, and functional redundancy, influence the abundance and activity of potential hydrocarbon degraders in the Delaware and Chesapeake Bays. We identified key genes in hydrocarbon degradation pathways in metagenomes, metatranscriptomes, and metagenome assembled genomes (MAGs) from these estuaries. Aerobic aromatic and alkane degradation pathways predominated in both estuaries, with higher gene abundances observed in low-salinity spring and summer samples. Hydrocarbon degrading MAG abundance were significantly structured by salinity, temperature, nitrate, and silicate concentrations. Metatranscriptomic analyses revealed consistently higher expression of aerobic alkane and aromatic degradation genes in the Delaware compared to the Chesapeake Bay, with the highest occurring under low-salinity spring conditions in the former. Catechol degradation pathways exhibited high functional redundancy, whereas the naphthalene degradation pathway showed restricted distribution. Co-expression analysis revealed that Burkholderiales displayed condition dependent metabolic coupling while Pseudomonadales integrated hydrocarbon degradation with fermentation and central metabolism, demonstrating complementary strategies that support multi-scale ecosystem resilience. In conclusion, environmental gradients and taxon-specific metabolic strategies together govern hydrocarbon degradation potential in these estuaries, with implications for predicting ecosystem responses to hydrocarbon inputs under changing conditions. ImportanceCoastal estuaries are among the most contaminated aquatic environments on Earth, receiving continuous hydrocarbon inputs from industrial activity, urban runoff, and natural sources. Microorganisms are the primary agents of hydrocarbon breakdown in these systems yet predicting when and where this capacity is active and how resilient it is to environmental change remains a major challenge. Using paired genomic and transcriptomic data from microbial genomes across two major mid-Atlantic estuaries, we show that hydrocarbon degradation capacity is not uniformly distributed but is instead shaped by salinity, nutrients, and seasonality in pathway-specific ways. Critically, dominant degrader taxa employ fundamentally different metabolic strategies to sustain this function across fluctuating conditions, providing a form of community-level insurance against environmental disturbance. These findings advance our ability to predict microbial hydrocarbon degradation in coastal systems and inform nature-based approaches to bioremediation under increasing climate and anthropogenic pressures.

Listeria monocytogenes relies on a tightly controlled set of surface-associated and secreted proteins to mediate host interaction and infection. The correct localization and exposure of these proteins at the bacterial surface are critical for virulence, yet the role of cell wall components in organizing this process remains incompletely understood. In particular, wall teichoic acid (WTA) glycosylation has been implicated in anchoring and function of selected surface proteins, but its global impact on protein distribution across the bacterial cell envelope is unclear. Here, we performed a comprehensive proteomic analysis to investigate how WTA glycosylation influences protein distribution in L. monocytogenes. Using isogenic mutants lacking rhamnose ({Delta}rmlT) or GlcNAc ({Delta}lmo1079) WTA glycosylation, we compared the exoproteome, the surface-accessible proteome and the surface-exposed proteome. Loss of WTA glycosylation did not result in a global disruption of the surface proteome but instead induced a redistribution of proteins across extracellular and surface-associated fractions. This effect was dependent on protein anchoring mechanisms, with limited changes observed for LPXTG-anchored proteins, moderate effects on non-covalently associated proteins, and a marked enrichment of lipoproteins in the surface-exposed proteome, particularly in the {Delta}lmo1079 mutant. In parallel, virulence-associated proteins displayed altered accessibility and exposure, with a progressive shift towards increased surface localization and a combination of shared and mutant-specific responses. This global effect was supported by functional annotation, which revealed that the affected proteins were associated with similar biological processes across fractions, highlighting a broad rather than pathway-specific impact of WTA glycosylation loss Together, these findings indicate that WTA glycosylation plays a key role in organizing the bacterial surface by modulating protein retention, exposure and release. Rather than affecting specific proteins, WTA glycosylation broadly shapes the spatial distribution of proteins across the cell envelope, with potential consequences for host- pathogen interactions.

BackgroundBuilt environment microbiome studies have identified numerous factors that shape indoor microbiomes, yet the reproducibility of these findings across buildings, timepoints, and research groups remains unclear. Differences in sequencing protocols, sampling design, and environments pose major challenges for cross-study comparisons, particularly in low-biomass environments where technical variation can obscure biological signal. To address this gap, we constructed a simple ontology which groups samples into one of three categories: hand, hand-associated surfaces, and floor then applied it to four publicly available 16S rRNA gene datasets: a hospital, university dormitory, Air Force dormitory, and private residential houses. ResultsWe identified strong and reproducible separation between floors and surfaces with frequent human contact. We found that floors consistently harbored soil-associated taxa, including KD4-96, 67-14, Skermanella, and Sphingobacterium, whereas hands and hand-associated surfaces were enriched with skin-associated genera, such as Lawsonella and Cutibacterium. Within studies, these results were generally consistent across timepoints. Across studies, mixed-model PERMANOVA analysis revealed significant clustering by sample type, with modest effects of study, suggesting that biological signal outweighed differences in laboratory or sequencing methods. Leave-one-study-out random forest models achieved high AUCs for hand vs. floor comparisons (0.865 to 0.921), moderate AUCs for hand-associated vs. floor comparisons, and weaker performance for hand vs. hand-associated comparisons. Application of the batch-correction method DEBIAS-M did not improve effect sizes or classification performance, indicating that reproducible structure was already discernible without batch adjustment. ConclusionsDespite substantial temporal and environmental heterogeneity among studies, we found that the built environment microbiome has a reproducible bacterial signal. There was consistent enrichment of soil-derived taxa on floors and human-associated taxa on hands and hand-associated surfaces suggesting a stable microbiome despite differences in building type, occupancy, and methodology. These findings establish an important foundation for future studies, suggesting cross-study comparability, the accuracy of ecological inference, and the ability to support the development of predictive applications in indoor microbiome research.

ObjectivesAntimicrobial resistance (AMR) in Gram-negative pathogens is driven by complex and coordinated molecular mechanisms that remain incompletely characterized. This study integrated phenotypic, genomic, and quantitative proteomic analyses to characterize multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria circulating in an intensive care unit (ICU) in Northeastern Brazil. MethodsA total of 259 Gram-negative isolates collected between 2019 and 2021 underwent species identification, antimicrobial susceptibility testing, and targeted qPCR for resistance genes. Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa representing susceptible, MDR, and XDR phenotypes were selected for whole-genome sequencing and label-free quantitative proteomics. Differential protein abundance was assessed using Limma with |log2FC| > 1 and p < 0.05. ResultsK. pneumoniae (47%), A. baumannii (24%), and P. aeruginosa (21%) predominated. Carbapenem resistance reached 44%, 93%, and 61%, respectively, and MDR/XDR phenotypes occurred in >30% of isolates. Genomic analyses revealed dense resistomes with coexisting {beta}-lactamases (blaKPC, blaNDM, blaCTX-M, OXA) and widespread efflux systems. Proteomic profiling demonstrated phenotype-associated differences in outer membrane proteins, transport systems, regulatory proteins, and metabolic pathways. XDR isolates showed additional enrichment of envelope remodeling proteins, stress response mechanisms, and proteostasis-associated factors. ConclusionsMDR and XDR Gram-negative ICU pathogens exhibit coordinated resistance architecture characterized by accumulation of resistance genes and adaptive proteomic remodeling. Integrated multi-omics approaches provide mechanistic insight into antimicrobial resistance and support improved surveillance and therapeutic strategies. What is known?O_LIAntimicrobial resistance is a priority and a serious problem in global health, resulting in high rates of morbidity and mortality. C_LIO_LIKlebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa are on the World Health Organizations (WHO) priority list as major causes of morbidity and mortality worldwide. C_LIO_LIClassical characterization of susceptibility and resistance phenotypes does not capture the complexity of antimicrobial resistance and hampers effective control measures and actions to minimize the evolutionary dynamics of resistance in these bacteria. C_LI What is new?O_LIThe study characterizes the phenotypic pattern of antimicrobial susceptibility, the presence and sequencing of the resistome and virulome, and analyzes the label-free quantitative proteome of susceptible, MDR, and XDR phenotypes in strains of K. pneumoniae, A. baumannii, and P. aeruginosa circulating in hospital ICUs in Brazil. C_LIO_LIMDR and XDR gram-negative phenotypes are associated with a dense resistome, with widespread dissemination of beta-lactamase genes (bla_KPC, bla_NDM, bla_CTX-M, and OXA) and RND-type (MEXs) and acrAB-tolC efflux pumps, without changes in virulence genes. C_LIO_LIProteomic analysis demonstrated increased production of beta-lactamases, components of efflux pump systems, outer membrane protein synthesis, protection for oxidative stress mechanisms, proteins for iron acquisition, and systemic regulators. XDR strains additionally showed enhanced remodeling of the cell envelope, activation of proteostasis, and metabolic adaptation. C_LI

Microbial communities of geothermal habitats are central to understanding the evolution of life on Earth. Metagenomics has provided insight into the role of viruses in shaping microbial diversity of complex environments. However, identification of novel viruses is constrained by lack of marker genes and low nucleotide similarities between related viral taxa. While microbial and viral diversity have been explored in terrestrial hot springs and hydrothermal vent systems, other volcanic features remain underexplored. Fumaroles (steam vents) are geothermal features that heat groundwater with magma, releasing steam and volcanic gases such as CO2 and H2S. Comparatively physicochemically dynamic to hot springs, fumarole temperatures and gas emissions rapidly fluctuate with volcanic activity. Here, we describe viruses identified metagenomically from microbial mats hosted near basaltic fumaroles on the Big Island of Hawai`i. To our knowledge, this is the first systematic survey of fumarole viruses. Our utilization of a sensitive profile-based approach for identification reveals high viral diversity in fumaroles, resulting in estimation of two undescribed order-level clades of Caudoviricetes (tailed phages). Viral metabolic genes provide evidence of viral-mediated adaptation of microbes to fumarole conditions. We describe patterns of viral diversity that diverge from the Bank model of viral ecology, hinting at viral dispersal between biofilms and high viral richness and evenness. Lastly, we provide a description of the first terrestrial geothermal environment dominated by Microviridae, previously only described in viral communities of deep ocean hydrothermal vents. This study offers important findings for exploration of viral ecology in extreme environments.

Myrmecocystus honeypot ants rely on specialized workers, repletes, to store dissolved carbohydrates in their crops long term. The repletes store this liquid, which does not spoil in their crops, for many months at a time. When resources are scarce, repletes redistribute the stored nutrients to their colony members via trophallaxis. While we suspect that the gut microbiome of honeypot ants may aid in spoilage prevention, before we can investigate this, we must first characterize it. Here, we used 16S rRNA gene sequencing to determine the microbial community composition across six Myrmecocystus honeypot ant species, sampling multiple colonies, castes, and organs. We found that microbiome community composition was strongly shaped by species, with variation between colonies in M. arenarius, M. depilis, and M. mexicanus. Organ level differences were observed in the crop and midgut in M. mexicanus. Caste differences were observed in M. flaviceps and M. mexicanus. Replete crops of M. mexicanus and M. depilis were enriched in Fructilactobacillus, other lactic acid bacteria, and acetic acid bacteria, whereas halophiles were more prominent in the gut of species such as M. flaviceps and M. wheeleri. In this study we demonstrate that Myrmecocystus ants host species-specific gut microbiomes and identify an association between lactic acid bacteria, acetic acid bacteria, and halophiles within replete crops. While much work remains in understanding the roles of the microbes in the symbiosis with their host ants, the dominance of these particular taxonomic groups suggests an association with a high sugar environment and a potential microbial role in preventing spoilage of the crop contents.

Streptococcus gallolyticus subsp. gallolyticus (Sgg) is an opportunistic pathobiont associated with bacteremia, infective endocarditis, and colorectal cancer. However, the genomic diversity of this subspecies and the distribution of key virulence determinants, particularly the type VII secretion system (T7SS), remain poorly characterized. Here, we performed genomic analyses of 76 Sgg strains from diverse geographic and host origins. Core- and pan-genome analyses, multi locus sequence typing, and phylogenetic reconstruction revealed dominant sequence types (STs) that correlate with geographic origin or source of isolation. Furthermore, systematic characterization of the T7SS locus identified five new T7SS subtypes and demonstrated a strong association between T7SS subtype and ST. We further expanded the known repertoire of T7SS LXG domain-containing polymorphic toxins (LXG toxins) in Sgg substantially through genome-wide searches. Distinct distribution patterns were observed for the LXG toxins across the strains. Lastly, our data indicated that T7SS subtype was significantly associated with biofilm formation capacity of Sgg strains. Together, these findings advance our understanding of Sgg genomic diversity, reveal substantial lineage-associated variation in T7SS architecture and effector repertoires, and suggest a previously unrecognized connection between T7SS and biofilm formation in Sgg.

Wastewater sequencing is an increasingly valuable tool in tracking the spread of infectious disease agents across space and time in areas of dense human settlement. Among pathogens that can be readily detected by this approach is influenza A, which follows predictable patterns of prevalence through the winter months in North America. Here, we leverage routine surveillance of a municipal wastewater treatment plant in Northern California to describe an atypical, off-season spike in influenza A concentrations that rivals that of the winter respiratory virus season. Drawing upon metagenomic data generated through hybrid-capture sequencing, we assemble and subsequently characterize fragments of divergent influenza genomes that appear to derive predominantly from the avian H16 clade. These strains exhibit close evolutionary relationships to influenza isolated from migratory shorebirds, hinting at potential host species and mechanisms of geographic spread. Analysis of read abundances suggest that these avian strains dominate the pool of influenza circulating during the summer months, when typical human-infecting strains are essentially absent. Together, our results expand the value of wastewater sequencing to encompass sensitive tracking of outbreaks within animals in interface regions where human settlement abuts wildlands, increasing overall pandemic preparedness.

The worldwide rise in the prevalence of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli is a major public health concern. In Europe, ESBL carriage frequency increased then stabilized at about 6-8 %. Past antibiotic use and travel in countries with high ESBL frequency, notably South-East Asia, have repeatedly been identified as risk factors of ESBL carriage. Yet, the relative contributions of these mechanisms to the observed maintenance of a stable low frequency of ESBL in Europe remains unknown. Here, we used comprehensive data on the risk factors for carriage of ESBL-producing E. coli in the French community, alongside detailed microbiological characterization of both resistant and overall E. coli, to develop a biologically plausible mathematical model of ESBL resistance spread in France. The model also includes several mechanisms previously showed to favor coexistence such as population structure, variability in carriage duration and within-host dynamics. The level of resistance in the community implies resistant strains transmit 14% less than sensitive (95% credible interval 0.6-38%), and are cleared at a +23% larger rate (0.9-62%). ESBL resistance is predicted to be strongly associated with factors prolonging residence in the gut. Both the rate of antibiotic treatment and transmission strongly impact the frequency of ESBL in the community. In contrast, travel has little impact on ESBL frequency. Whether reducing treatment or transmission is best to reduce resistance depends on community-specific parameters. Our study opens perspectives for the quantitative study of resistance evolution and argues for future work to improve the characterization of the duration of carriage of commensal bacterial strains.

The human gut microbiome plays a critical role in host health, yet its functional organization in disease remains poorly understood. Most studies focus on taxonomic composition or pathway abundance, which fail to capture higher-order interactions governing system-level behavior. Here, we investigated microbiome functional organization in inflammatory bowel disease (IBD), including Crohns disease (CD), ulcerative colitis (UC), and healthy controls (HC), using a network-based framework across 60 metagenomic samples. Functional pathway profiles were used to construct correlation-based interaction networks, followed by analysis of network topology, functional redundancy, keystone pathway architecture, and system robustness. Disease-associated networks (CD and UC) exhibited reduced global connectivity, increased modular fragmentation, and centralization of keystone pathways, indicating a shift from distributed organization to more fragmented and fragile network structures compared to healthy controls. Notably, machine learning models demonstrated that network-derived features achieved higher classification performance (accuracy up to 0.824) compared to redundancy-based measures. These findings reveal that microbiome dysfunction in IBD is driven by large-scale reorganization of functional interaction networks rather than loss of functional capacity. This study highlights the importance of network-level analysis in understanding microbiome-associated disease and provides a systems-level framework for future research.

This study investigates the seasonal dynamics of the microbiome within the marine sponge Halichondria panicea from Baltic coastal waters, focusing on its symbiotic relationship with Candidatus Halichondribacter symbioticus. Over 16 months, we observed distinct summer and winter microbial communities, transitioning rapidly between these states during spring and fall. Marine sponges host complex microbiomes composed of diverse microbial taxa that play critical roles in host metabolism and nutrient cycling within marine ecosystems. While our understanding of sponge microbiomes has traditionally been based on static characterizations, the temporal dynamics of these associations across seasonal cycles remain poorly understood. In this study, we investigated temporal variation in bacterial symbionts of Halichondria panicea over 16 months in Baltic coastal waters using high-throughput amplicon sequencing of bacterial 16S rRNA gene sequences. The microbiota of H. panicea exhibited host-specific structure and a high degree of stability across seasons, despite fluctuations in environmental factors such as temperature, salinity, photoperiod intensity, and inorganic nutrient availability. In contrast, bacterial communities in surrounding seawater displayed large seasonal shifts which potentially mix with the sponge bacterial community, suggesting that different degrees of ecological pressures act on free-living and symbiotic marine bacteria. These findings establish an empirical baseline for identifying abnormal shifts in symbiont communities, which could be indicative of environmental stress or biological disturbance events.