The ISME Journal

Viral infection is a major yet poorly quantified driver of microbial interactions and biogeochemical fluxes in the ocean. In diatoms, which are key contributors to marine primary production, the extent to which viruses reprogram host cell metabolism and alter elemental cycling remains largely unresolved. Here, we investigated how infection by a lytic single-stranded RNA virus reshapes carbon (C) and nitrogen (N) fluxes in the ecologically relevant nanoplanktonic diatom Mediolabrus comicus. Using controlled infection experiments coupled with flow cytometry, electron microscopy, PAM fluorimetry, and stable isotope probing, we resolved infection-driven changes from the population to the cellular scale. Infection induced rapid optical shifts and cellular reorganization, including the formation of membrane-bound viral replication compartments. These changes coincided with early impairment of plastidial functions, as shown by disruption of photosystem II functionality and a concomitant decline in photosynthetic carbon fixation. In contrast, nitrogen uptake was maintained and strongly enhanced during late stages of infection, indicating sustained resource acquisition to support viral replication. This decoupling led to dynamic changes in cellular stoichiometry and, overall, to substantial reductions in population-level carbon and nitrogen assimilation due to growth inhibition. Together, these findings demonstrate that diatom RNA virus infection reshapes host carbon and nitrogen metabolism, with cascading effects on elemental cycling. Our results identify diatom RNA viruses as important drivers of marine biogeochemical processes, with implications for primary production and the fate of organic matter in the ocean.

Winogradsky columns are a classic model ecosystem for studying microbial biogeochemistry across steep gradients of oxygen and sulfide. They also remain widely used in microbiology education, introducing generations of students to microbial diversity. Yet, the genomic potential of their microbial communities remains uncharacterized. Here, we applied shotgun metagenomic sequencing to a Winogradsky column community at multiple depths, yielding 20 metagenome-assembled genomes (MAGs) representing diverse, largely uncultivated taxa. Genome-resolved analyses revealed metabolically diverse oxygenic and anoxygenic phototrophs that could potentially contribute to carbon and nitrogen fixation across all layers of the column. Most of these phototrophs also encoded one or more pathways for sulfur oxidation, which we speculated may support both energy conservation and/or sulfide detoxification by these populations. Complex carbon degradation capacity was also widespread across the MAGs, suggestive of the potential for the transformation of the column's amended organic matter (shredded coffee filters) into smaller depolymerization products and, through fermentation, organic acids. Together, these findings reveal how distinct microbial guilds might partition interconnected carbon, sulfur, and nitrogen transformations within redox-stratified systems.

Microbial communities are dynamic, adaptive ecosystems whose collective behavior emerges from metabolic interactions such as cross-feeding, competition, and cooperation, rather than taxonomic diversity or individual metabolic potential alone. This distinction is clinically significant in the postmenopausal urinary tract, where recurrent urinary tract infections (rUTIs) are associated with complex, persistent infection dynamics including multiple contributing bacterial species. The ability of resident microbial communities to prevent pathogen establishment, known as colonization resistance, is increasingly attributed to the metabolic interactions within the urobiome itself rather than any single resident species. However, current approaches, such as taxonomic profiling and classical differential abundance analysis, can only partially describe the presence or maintenance of such interactions. Consequently, the community-level metabolic architecture determining pathogen resistance remains incompletely understood. To address this gap, we developed PhenoRewire, a network-based framework that quantifies how metabolite co-variation is rewired between biological states using untargeted metabolomics data. We applied this framework to an induced pluripotent stem cell (iPSC) urothelial organoid-derived barrier co-cultured with synthetic urobiome communities as a model of urobiome-pathogen dynamics relevant to rUTIs in two approaches. In an infection model, clinically isolated uropathogens Escherichia coli and Enterococcus faecalis, were co-cultured with a three-member urobiome community consisting of Lactobacillus gasseri, Lactobacillus crispatus, and Gardnerella vaginalis. Here we show how E. coli drove the metabolic reorganization, while E. faecalis amplified it disproportionately. PhenoRewire disentangled the 6-fold metabolic network amplification mediated by E. faecalis as a metabolic facilitator, revealing an emergent urobiome-pathogen co-variation architecture (1,781 vs 227 edges) not recapitulated by either community alone. Moreover, in a six-member urobiome single-strain dropout experiment, we revealed that removal of the sole Actinomycete Winkia anitrata caused significant network collapse (Louvain modularity falls from 0.707 to 0.038), identifying it as the single non-redundant keystone of the community. More broadly, these results demonstrate how untargeted metabolomics co-variation network analysis can be applied to defined synthetic urobiomes in combination with a urothelial host model to elucidate community dynamics. This framework provides a template that can be extended beyond the urobiome to investigate any complex microbial community where ecological behavior remains an open question.

Organosulfur compounds are the predominant sulfur source in terrestrial environments, requiring bacteria to use enzymes for their assimilation. Most described organosulfur-assimilating enzymes require oxygen, and enzymes that function under anoxic conditions remain poorly understood. Recently, methylthio-alkane reductase (Mar), a nitrogenase-like enzyme that reduces the volatile organic sulfur compounds (VOSCs) methylthio ethanol (MT-EtOH), dimethyl sulfide (DMS), and ethyl methyl sulfide (EMS) under anoxic conditions, was identified in the purple nonsulfur bacterium Rhodospirillum rubrum. However, another purple nonsulfur bacterium, Rhodopseudomonas palustris, has three loci of nitrogen fixation-like (NFL) genes with high sequence similarity to Mar, suggesting additional Mar-like enzymes with distinct roles. Here, we tested whether these NFL genes are required for VOSC assimilation in R. palustris. RNA-seq analysis revealed that all three NFL loci are upregulated under sulfur limitation, supporting a role in sulfur assimilation. Only disruption of the NFL genes encoded by RPA2634-37, renamed marBHDK1, caused fitness defects with EMS, DMS, and dimethylsulfoniopropionate (DMSP) as sulfur sources, indicating a functional Mar enzyme. The NFL genes RPA2347-48 and RPA2353-54, renamed marKD2 and marHB2, were required for activity with MT-EtOH or ethanethiol but not DMS, EMS, or DMSP. No activity was observed for the third locus, RPA2363-64, renamed nflDK. Overall, two Mar homologs in R. palustris are capable of VOSC reduction, one specialized for simple VOSCs and the other preferring a substrate with an additional functional group.

Water availability is critical for plants and their microbial communities, including pathogens. The plant pathogen Phytophthora cinnamomi persists in soils with fluctuating moisture, yet cellular responses to water limitation remain poorly understood in Phytophthora and oomycetes more broadly. Although we recently characterized the proteomic response of P. cinnamomi to NaCl-induced osmotic and ionic stress, its response to PEG-mediated water limitation remains poorly understood, leaving a critical gap in our understanding of drought-relevant stress adaptation. Here, we quantified mycelial growth and profiled time-resolved proteome dynamics of P. cinnamomi during polyethylene glycol (PEG-3350)-treatment, simulating moderate water limiting conditions. Treatment with 5% PEG-3350 enhanced radial mycelial growth relative to controls, with no early growth inhibition observed. Label-free proteomics identified 1,097 protein groups, with 880 proteins shared between conditions and an asymmetric abundance profile dominated by decreasing protein abundance over time. Only a small subset of proteins increased, mainly enzymes involved in redox buffering (e.g., thioredoxin and glutaredoxin-like proteins) and mitochondrial/metabolic regulation (e.g., alternative oxidase) and mitochondrial/metabolic regulation. Hierarchical clustering revealed a potential three-phase temporal program: early translational and regulatory remodeling (1-6 HPT), sustained metabolic adjustment (6-12 HPT), and delayed engagement of redox and proteostasis functions (12-24 HPT). Network analysis demonstrated that redox-associated function was integrated throughout this adaptation, with individual clusters further specialized by cofactor preference (NADP- versus NAD-dependent enzymes) and distinct metabolic roles (malate dehydrogenase, CoA-ligase activity). This coordinated, multi-phase reorganization sustained mycelial growth despite moderate osmotic stress, indicating that P. cinnamomi employs active proteomic adaptation rather than passive stress tolerance. These findings reveal the cellular mechanisms underlying drought persistence in this invasive pathogen and suggest molecular targets for disease management under water-limited conditions.

Antibiotic-induced disruption of plant-associated microbiomes has the potential to alter host health beyond the directly exposed generation, yet whether the effects of dysbiosis are transmitted through the seed microbiome remains unknown. Here, we investigated the intergenerational impacts of streptomycin-induced dysbiosis in tomato (Solanum lycopersicum), demonstrated that seed microbiome transfer (SMT) restores progeny microbiome function and disease resistance, and characterized the underlying physiological and genetic mechanisms. Parental streptomycin exposure altered the composition of progeny rhizosphere bacterial communities, reduced expression of defense-associated genes, and increased susceptibility to Xanthomonas perforans. Suppression of immune gene expression was strongly associated with increased disease severity, indicating that parental dysbiosis impaired progeny plants ability to mount effective immune responses. Transfer of the seed microbiome from healthy plant donors partially restored rhizosphere community composition, reduced disease severity and recovered defense gene expression of three genes. Together, our findings demonstrated that antibiotic exposure microbiome disturbance generates intergenerational legacy effects that influence plant immunity and disease susceptibility and seed microbiome transfer can counteract this dysbiosis across generations.

Marine diatoms contribute to about 20% of global primary production. We present the first basin-scale, multiyear assessment of diatom communities in the North Pacific, combining taxonomically high-resolution RuBisCO large subunit gene (rbcL) metabarcoding with concurrent environmental measurements. Using a nine-year time series of daily samples resolved at the species level via ~500 bp rbcL fragments, we performed multivariate analyses across biogeographic provinces, identifying significant correlations between community structure and environmental drivers such as temperature and macronutrient availability. We report the prevalence of a previously overlooked centric diatom species in the North Pacific, Eunotogramma lunatum, which appears to be near-dominant even in subarctic high-nitrate, low-chlorophyll waters where pennate diatoms are typically favored. These results demonstrate the power of rbcL for large-scale ocean monitoring and provide a critical baseline for future studies of diatom population dynamics, climate change impacts, and ecosystem resilience in a key marine region.

Protists play important roles in food chains and symbioses in soil and aquatic environments, displaying an enormous morphological and functional diversity. While most commonly found protist species are well known to science, our global-scale environmental DNA survey across soil, water, and sediments reveals dozens of novel, phylum-level phylogenetic lineages that remain to be characterized for basic morphology and function. A vast majority of these undescribed taxa occur in marine water and sediments, but some are common in soil. Most of these novel taxa have distinct substrate and habitat preferences and biogeographic patterns. To accord these lineages scientific agency and enable unambiguous scientific communication, we propose formal names for 150 species to phylum-level taxa from 25 deep lineages based on eDNA and rRNA gene long-read sequence information.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

Maintaining a prescribed composition in engineered microbial consortia is difficult because small fitness differences can drive competitive exclusion. We study a two-strain consortium in continuous culture and develop a feedback architecture that regulates composition by selectively slowing the fast strain as a function of the population ratio. At the population level, we derive an idealized ratio-feedback law with a tunable positive coexistence equilibrium. We then propose a biomolecular realization using orthogonal quorum sensing, an sRNA-based ratiometric controller, and a ppGpp-mediated growth actuator. Exploiting the separation between slow population growth and faster intracellular controller dynamics, we use singular perturbation theory to show that, for sufficiently fast controller dynamics, the full implementation model inherits the coexistence equilibrium and its local stability properties from the reduced model. Numerical simulations validate the reduction and show how weaker timescale separation or loss of the assumed molecular regime degrades performance.

Myxococcus xanthus bacteria form aggregates when starved on solid surfaces and some cells differentiate into spores. Studies of mutants in monoculture have advanced knowledge of this multi-cellular developmental process, but our understanding of the genetic determinants is incomplete. To assess gene function genomewide, we generated a pool of barcoded transposon insertion mutants, subjected it to starvation, and separated developmental samples into non-aggregated cells, aggregated cells, and spores. We also subjected our pool to chemically-induced unicellular sporulation. Evaluation of changes in the abundance of mutants in samples allowed identification of 200 genes in which insertions reproducibly caused distinct patterns of depletion and/or accumulation over time. Many of these genes have well-established roles in development, validating our approach, while many others have not previously been associated with development. Genes involved in type IV pili (T4P)-dependent motility were more important than gliding motility genes for aggregation and sporulation in the mixed population. Although exopolysaccharide (EPS) synthesis genes are required for aggregation in monoculture, most were dispensable for aggregation in our pool, consistent with EPS sharing between cells, yet these genes were required cell-autonomously for efficient sporulation. Genes for positive regulators of EPS synthesis were important for aggregation as well as sporulation, suggesting functions beyond EPS production. Insertions in several novel genes impaired both starvation- and chemically-induced sporulation. Many genes increased the efficiency of starvation-induced sporulation. Some of these mutants, which we call "developmental winners", are novel cheaters. Our results demonstrate the power of using the newly-created mutant library to elucidate M. xanthus biology.

Bacterial genome-wide association studies (GWAS) offer a powerful approach to identify the genetic basis of a trait measured in a set of sequenced isolates. As the number of sequenced isolates has grown, the limiting factor for GWAS has become phenotyping enough isolates to achieve statistical power. To overcome the need for large-scale phenotyping, we developed Bayesian Adaptive Sequential Sampling GWAS (BASS-GWAS), which couples Bayesian adaptive experimental design with a sparse regression model to select maximally informative isolates for phenotypic testing. BASS-GWAS efficiently recovered causal loci for three antimicrobial resistance traits in Neisseria gonorrhoeae, requiring many fewer phenotyped isolates than random sampling. We applied BASS-GWAS to discover variants enabling gyrBD429N-dependent cross-resistance to the novel topoisomerase inhibitors zoliflodacin and gepotidacin. After phenotyping fewer than 30 isolates, we identified and then validated both parCD86N and a gyrA-parE-based pathway as enabling cross-resistance. BASS-GWAS provides a practical and statistically principled solution for efficient bacterial GWAS.

Enterococcus faecalis is an opportunistic pathogen and facultative anaerobe that primarily relies on fermentative metabolism to colonize a wide range of aerobic and anaerobic environments. In the presence of exogenous heme, E. faecalis can assemble a minimal electron transport chain consisting of membrane-associated primary dehydrogenases, demethylmenaquinone, and the terminal cytochrome bd oxidase (CydAB). This respiratory chain is thought to generate a proton motive force to drive ATP synthesis via the F-type ATP synthase, thereby improving energy conservation under aerobic conditions. However, a cytosolic NADH oxidase (Nox) also consumes NADH and oxygen, potentially competing with the electron transport chain for reducing equivalents and terminal electron acceptors; but the relative physiological contributions of these two oxygen-reducing pathways remain poorly understood. To define the roles of CydAB and Nox under normoxic and hypoxic conditions, we constructed {Delta}cydAB and {Delta}nox mutants. Real-time, in situ measurements revealed {Delta}cydAB had no significant effect on oxygen utilization while in the {Delta}nox it was significantly reduced; revealing Nox as the major consumer of oxygen. Semi-untargeted metabolomic analysis further revealed oxidase-specific alterations in central metabolism with the {Delta}nox causing pronounced shifts in the ATP and NADH ratios; highlighting Nox as a key determinant of intracellular redox and energy homeostasis. Finally, single-cell fluorescence microscopy showed that membrane potential, a component of proton motive force, was substantially diminished only in the absence of both CydAB and Nox, or the F-type ATP synthase. These findings indicate that the F-type ATP synthase is a major generator of proton motive force, even upon aerobic growth, and demonstrate a complementary role for the electron transport chain and Nox in the bioenergetics of E. faecalis.

Brettanomyces bruxellensis is a yeast species associated with diverse fermentation environments and characterized by extensive genetic diversity, including diploid, autotriploid, and allotriploid lineages resulting from independent hybridization events. These lineages are associated with distinct ecological niches and provide a framework for studying metabolic trait evolution in complex genomes. Nitrate assimilation is a relatively uncommon trait among yeasts and has been reported in B. bruxellensis, but its distribution and evolutionary history within the species remain poorly understood. Here, we combined phenotypic characterization of 151 strains with genomic analyses of 946 whole-genome sequences to investigate nitrate assimilation. Growth assays revealed that nitrate assimilation is widespread but unevenly distributed across genetic lineages, with some populations largely retaining the trait whereas others have frequently lost it. Genomic analyses identified extensive variation affecting the nitrate assimilation gene cluster composed of YNR1, YNI1, and YNT1. Nitrate assimilation was strongly associated with both gene copy number and predicted gene functionality, with nitrate-assimilating strains generally carrying more functional copies of the cluster. Leveraging the complex genomic architecture of the species, we independently analyzed primary and acquired genomes in allotriploid lineages and uncovered contrasting evolutionary trajectories following hybridization. While nitrate assimilation genes were generally maintained in primary genomes, acquired genomes showed a higher prevalence of gene loss and predicted loss-of-function variants, revealing asymmetric dynamics between subgenomes. Altogether, our results suggest that nitrate assimilation represents an ancestral trait that has been differentially maintained across B. bruxellensis lineages through a combination of copy number variation, gene degeneration, and genome-specific evolutionary dynamics. These findings provide new insights into how genome architecture and polyploid evolution shape the maintenance and loss of metabolic traits in an industrially relevant yeast species.

Genetic variation among microbial strains of the same species can profoundly influence their phenotypes, ecological functions, and impacts on human health. Traditionally, the relative abundance of a species has been used to identify associations between the microbiome and disease. However, this approach overlooks intra-species genetic variation and is susceptible to spurious correlations arising from the compositional nature of abundance data and microbial load. Fast, k-mer-based algorithms can now accurately estimate strain-level Average Nucleotide Identity (ANI) in metagenomes. Despite its value as an orthogonal metric for strain-level analysis, methods for conducting ANI-based association studies remain limited. To address this, we developed StrainSpy, a statistical algorithm that identifies associations between containment ANI and variables of interest across a wide range of study designs, including longitudinal and multi-cohort designs. Re-analysis of a study examining gut microbiota recovery in 12 healthy adults following antibiotic exposure revealed novel strain-level associations, including a reduction in strain-level diversity despite species persistence. Applying StrainSpy to a multi-cohort analysis of 3,414 colorectal cancer metagenomes identified novel strain-level associations with colorectal cancer. However, in a separate collection of microbiome-immunotherapy studies, no individual strain was consistently associated across cohorts. Importantly, across both datasets, StrainSpy informed containment ANI-based machine learning models achieved comparable accuracy to traditional abundance-based methods. StrainSpy is publicly available as an R package github.com/gtonkinhill/strainspy.

Drug resistance emerges repeatedly in outbreaks of Candida fungal pathogens, but little is known about its origins or persistence. Here, we investigated the evolutionary processes shaping echinocandin resistance in Candida auris, a globally emerging and predominantly clonal fungal pathogen. Genome-wide association across over 600 isolates identified mutations in the {beta}-1,3-glucan synthase gene FKS1 as the most significant driver of resistance to an echinocandin drug. Ancestral reconstruction of this population traced shared resistance mutations among small groups typically consisting of 2-3 closely related isolates, but clusters could include up to 16 isolates. Nearly all resistant clusters consisted of isolates collected in the same year and region, consistent with local transmission. To further examine population-level selection, we measured adaptive signatures in FKS1 and the highly diverged paralog FKS2 across 22,000 genomes. This revealed excess nonsynonymous polymorphisms in FKS1, primarily due to independent, recurrent mutations at resistance hotspots, consistent with parallel evolution and incomplete fixation of adaptive alleles. In FKS2, there is no evidence of hotspots and little support for diversifying selection. Together, these results indicate that resistance mutations emerge under strong genetic constraint, with adaptation restricted to only one FKS homolog and predominantly at mutational hotspots.

Prions, once mainly studied for their pathogenic roles, are now gaining recognition as adaptive elements in microbial physiology. Over one-third of wild yeast isolates harbor prion proteins, yet their impact on host-microbe interactions remains poorly characterized. Given the ecological dominance of yeasts in the Drosophila mycobiome, we leveraged the Drosophila melanogaster-Saccharomyces cerevisiae system to investigate how the mycobiome-derived prion, [MRPL10+], modulates host physiology. We show that flies exposed to [MRPL10+] yeast exhibit significantly enhanced cold tolerance and increased locomotor activity. This effect persists with heat-killed yeast and diluted culture, suggesting a stable, potent bioactive factor. Using the genetically diverse Drosophila Global Diversity Lines (GDL), we identified natural variation in responsiveness to [MRPL10+] yeast. Genome-wide association and functional RNAi screening revealed a gut-brain signaling axis involving genes critical for digestion, intercellular communication, transcription regulation, and neural transmission. Notably, serotonin and octopamine pathways were essential for [MRPL10+]-induced changes in cold tolerance and locomotion, implicating neuromodulatory circuits in prion-mediated microbial signaling. Our findings establish a mechanistic link between a fungal prion and host metabolic and neural adaptation. This work provides the first genetic dissection of a prion-mediated host-microbe interaction, laying the groundwork for investigating beneficial prions in complex microbial communities and highlighting a new dimension of the mycobiomes influence on animal physiology.

High pathogenicity avian influenza viruses (HPAIVs) emerge from H5 and H7 low-pathogenicity avian influenza virus progenitors through mutations that introduce a multibasic cleavage site in haemagglutinin. Although nucleotide insertions recurrently generate this motif, the molecular determinants of insertion and whether particular HA sequences are genetically predisposed to evolve toward HPAIV remain unknown. Combining experimental virology and thermodynamic modelling, we show that insertions arise through polymerase slippage controlled by local product-template duplex thermodynamics within the viral polymerase catalytic site. Predicted RNA secondary structures outside the polymerase are not required for high-frequency insertions and only modestly modulate insertion rates. We formalize this mechanism in HPAIVpredict, which predicts insertion profiles, recapitulates intermediates associated with documented HPAIV emergence events and identifies H5 and H7 sequence backgrounds predisposed to acquire functional multibasic cleavage sites.

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

Infections with bacteria which have evolved multi-drug resistance (MDR) cause millions of deaths worldwide. Large-scale efforts are gathering genotypic and phenotypic data on MDR bacteria, but methods for learning the structure, diversity, and predictors of evolutionary pathways to MDR have yet to take full advantage of these data. Here, we use evolutionary accumulation modelling (EvAM), an emerging class of machine learning methods with roots in cancer progression, to infer these evolutionary pathways across ESKAPEE pathogens (seven bacterial species that dominate health burdens), using a database of over 635k genotyped phenotypic observations from around the world. We identify global patterns in MDR evolutionary pathways, remarkably shared across multiple ESKAPEE species. Species-specific deviations from these stereotypical pathways are connected with geographical and demographic covariates, facilitating predictions of future MDR evolution. We verify these predictions with several hundred new phenotypes from ESKAPEE samples spanning decades of clinical infections in sub-Saharan Africa, demonstrating the capacity to forecast future MDR evolution from these inferred shared pathways.