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PubMed2025

The ecology and evolution of microbial immune systems: a look on the wild vibrio side.

Natural populations of vibrio beyond the well-studied pandemic strains of Vibrio cholerae, provide a powerful model for investigating the eco-evolutionary dynamics of microbial immune systems. Their genetic diversity, ecological versatility, ease of culturability and the availability of time-series data enable detailed studies of phage-host interactions in natural contexts. This review synthesizes recent advances in vibriophage research, highlighting key findings and emerging tools. High-throughput assays and genomic tools have offered new perspectives on phage specificity, host range and the evolutionary pressures shaping these interactions. Theoretical frameworks, such as arms race and fluctuating selection dynamics, are informed by empirical data from vibrio-phage systems, with time-series sampling providing crucial insights into their temporal and spatial dynamics. A major finding is the role of mobile genetic elements (MGEs) in encoding bacterial defence systems, which shape phage-host coevolution. Discoveries like the phage satellite PICMI illustrate how MGEs facilitate the transfer of antiviral systems, influencing ecological and evolutionary dynamics. The paradox of generalist vibriophages, rare despite their broad host ranges, is also explored. By integrating experimental approaches with field observations, vibriophage research advances microbial ecology and informs sustainable applications in aquaculture and phage therapy, reinforcing vibrios as a versatile model system.This article is part of the discussion meeting issue 'The ecology and evolution of bacterial immune systems'.

Bacteriophages↗
PubMed2025

Climate-driven co-evolution of antimicrobial resistance and virulence in Escherichia coli on dairy farms: unraveling adaptive genetic signatures with novel SSCP-PCR.

This study addresses a critical One Health challenge by investigating the epidemiological and genetic drivers of antimicrobial resistance (AMR) in E. coli from 290 clinical bovine samples. On Egyptian dairy farms, our findings revealed that while calf diarrhea peaked during the winter, a higher rate of multidrug resistance was consistently observed in isolates from the summer, directly linking seasonal pressures to AMR dissemination. Strikingly, a mastitis isolate was confirmed as the highly virulent E. coli O157:H7 serotype, harboring the Shiga toxin genes stx1 and stx2, underscoring a direct and significant public health risk. To dissect the molecular basis of these trends, we pioneered the use of a novel Single-Strand Conformation Polymorphism Polymerase Chain Reaction (SSCP-PCR) assay on 33 selected isolates. This high-throughput approach revealed prevalent mutations in resistance genes (blaTEM and gyrB) and the virulence gene (fimH). Crucially, sequencing confirmed that mutations in the highly conserved 16S rRNA gene significantly co-occurred with mutations in blaTEM, fimH, and lacI, providing compelling evidence for co-selected adaptive pathways and clonal expansion. Our research demonstrates that climate-driven environmental pressures fuel the co-evolution of AMR and virulence on farms, championing SSCP-PCR as a robust tool for tracking microbial evolution and advocating for integrated, molecularly-informed One Health strategies.

Escherichia coli↗
PubMed2026

Effector loss and gain drives host range at a fitness cost.

Epidemic preparedness depends on tracking microbial evolution that drives shifts in ecological behaviors such as disease emergence. However, the genetic constraints mediating microbial emergence for generalist and specialist behaviors remain poorly described. Here, we addressed this question by combining comparative and functional genomics with phylogeny-based evolutionary analyses of the cereal pathogen Xanthomonas translucens. We show that a generalist X. translucens subgroup arose from a specialist ancestor, and the loss of a single effector gene, xopAL1, contributed to the generalist host expansion by promoting host jump from barley to wheat. Deleting barley-specialist X. translucens xopAL1 recapitulated the host jump to wheat and demonstrates risk across each globally distributed genetic lineage. However, this niche expansion via XopAL1 loss incurs a significant fitness cost to colonize barley. Moreover, the specialist lineage gained an additional effector gene, xopAJ, which enhanced virulence on barley while restricting oat infection, thereby reinforcing niche specialization. We further conducted transcriptomic analysis of wheat and determined that XopAL1 triggers a defense response that involves the reduction of photosynthetic processes. Our work provides an experimentally validated evolutionary framework to understand mechanisms of intergenera host jump. Overall, we demonstrate that single events of gene loss and gain shape ecological behaviors by creating a dynamic trade-off between niche breadth and specialization.

Triticum↗
PubMed2026

Environmental Gradients as a Dominant Force in the Macroevolution of a Host-Associated Marine Bacterium.

Natural selection is imposed by both abiotic environmental filtering and biotic interactions, yet their relative roles in shaping the deep phylogeny of widespread, generalist host-associated bacteria remain unclear. Here, we integrate large-scale phylogenomics, environmental sequencing, functional genomics, and global metagenomic analysis to demonstrate that tidal zonation overrides host association as the dominant macroevolutionary force structuring the marine bacterial genus Ruegeria. Analysis of 533 genomes and 74 global coastal metagenomes reveals that the intertidal-subtidal boundary structures the deepest phylogenetic splits, driving the repeated evolution of distinct ecotypes through independent zonation transitions across global coastlines. These ecotypes possess divergent genomic toolkits: intertidal strains are enriched for genes coding for stress resistance and anaerobic metabolism, whereas subtidal strains specialize in high-affinity nutrient scavenging. Our findings establish that predictable physicochemical gradients act as filters that generate foundational diversity from which specialized host symbionts subsequently emerge, reframing how environmental gradients shape microbial evolution at the eco-evolutionary interface.

Journal Article↗
PubMed2026

ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.

UNLABELLED: Resolving bacterial strain diversity from shotgun metagenomic data is fundamental to understanding intra-host evolution, transmission dynamics, and phenotypic heterogeneity. However, current probabilistic approaches face a severe "identifiability limit" when disentangling highly similar genomes. Under high-noise conditions, sequencing errors, coverage overdispersion, and collinearity confound standard expectation-maximization algorithms, resulting in overfitting and spurious "ghost" strains. Here, we introduce zero-inflated latent allocation for strain reconstruction from metagenomes with adaptive sparsity regularization (ZILA-SRM) to overcome this barrier through three innovations. First, we integrate a zero-inflated Poisson mixture model to decouple "structural zeros" (true strain absence) from "sampling zeros" (stochastic dropout), addressing overdispersion in standard Poisson-based tools. Second, we impose a convex adaptive sparsity regularization penalty that leverages biological sparsity priors to shrink noise artifacts dynamically. Third, we implement a graph-theoretic refinement step using maximal clique enumeration to resolve haplotype collinearity. Benchmarking against StrainFinder and MixtureS on 702 synthetic data sets shows that ZILA-SRM achieves a 20% improvement in precision in high-complexity scenarios while maintaining over 80% recall for minor variants at 0.5% abundance. Re-analysis of deep-sequencing data from 195 Mycobacterium tuberculosis clinical samples reveals cryptic low-abundance drug-resistant variants in 12% of patients, including a minor clone carrying the rpoB S450L mutation. Furthermore, application to skin microbiome data sets further reveals a strong negative correlation between dominant Staphylococcus aureus and Staphylococcus epidermidis strains, providing genomic evidence for competitive exclusion. These findings establish ZILA-SRM as a robust tool for resolving strain-level diversity in complex metagenomes. IMPORTANCE: Understanding microbial communities at the strain level is critical because closely related strains can differ dramatically in traits such as drug resistance, virulence, and ecological interactions. However, resolving individual strains from metagenomic sequencing data remains difficult, especially when strains are highly similar or present at low abundance. As a result, biologically meaningful diversity is often obscured or misinterpreted as noise. In this study, we introduce a new framework that improves the reliability of strain reconstruction from complex metagenomic data. By reducing false-positive strain detection while preserving sensitivity to rare variants, our approach enables more accurate characterization of microbial populations. This improved resolution reveals previously hidden subpopulations in clinical and microbiome datasets, providing clearer insights into microbial evolution, competition, and the emergence of clinically relevant traits such as antibiotic resistance.

Metagenomics↗
PubMed2026

A One Health approach to Antimicrobial Resistance: Concepts, challenges, and advances in omics.

Antimicrobial resistance (AMR) is a global threat driven by the interplay between microbial evolution and human activity. Antimicrobial use in human and veterinary medicine, as well as in agriculture, accelerates the selection and dissemination of resistant bacteria and genes across interconnected human, animal, and environmental reservoirs. These dynamic exchanges render single-sector interventions ineffective. A One Health approach integrating human, animal, and environmental health is therefore essential to understand and mitigate the emergence and spread of AMR. This chapter focuses on bacterial antimicrobial resistance, addressing key concepts, major challenges, and emerging technologies within a One Health framework. Advances in next-generation sequencing and omics technologies have transformed our capacity to resolve AMR at unprecedented scale and resolution. These tools enable the tracking of resistance genes and high-risk clones across ecosystems, uncover transmission pathways, and identify key drivers of dissemination. Such insights support real-time epidemiological surveillance, outbreak detection, and targeted interventions. However, translating these advances into routine practice remains a major challenge, requiring harmonized methodologies, data integration, and cross-sector coordination. Addressing AMR demands sustained collaboration across disciplines and stakeholders, including clinicians, veterinarians, farmers, researchers, policymakers, industry, and the public. And framing AMR as a shared ecological and societal responsibility underscores the urgency of coordinated global action. We call for the urgent integration of One Health principles into surveillance, policy, and innovation to preserve antimicrobial effectiveness and safeguard future health.

Humans↗
PubMed2026

Boreal and subarctic freshwaters harbour a diversity of jumbophages.

Bacteriophages (phages) are major drivers of microbial evolution and ecology, yet their diversity and functional roles remain poorly characterized in many natural environments, such as in freshwater systems. In boreal and subarctic freshwater habitats, where bacteria are typically slow-growing and nutrient-limited, phages are predicted to have a critical role in host regulation and horizontal gene exchange. However, only a few isolates have been obtained from such environments, leaving the genetic and functional diversity of these phages largely unexplored. Here, we present a collection of 40 bacteriophages isolated from boreal lakes and rivers using a set of diverse freshwater bacterial hosts. Despite using conventional isolation methods, eight of the isolates possess genomes larger than 200 kilobases and are classified as jumbophages. All jumbophages exhibited myovirus morphology and comparatively slow infection dynamics. These jumbophages include the first known representatives infecting members of Janthinobacterium and Herbaspirillum. Comparative genomic and phylogenetic analyses show that nearly all genomes are distinct from previously described phages, indicating substantial novelty. Diverse auxiliary metabolic and anti-defence systems were identified, including putative NAD+ salvage and acyl carrier protein modules, along with predicted Anti-Thoeris and Anti-CBASS elements. The Pseudomonas-infecting jumbophage Ahti encoded homologues of all 21 core genes that define the nucleus-forming family Chimalliviridae. Additionally, Ahti displayed compartmentalization of DNA during infection, establishing it as the first freshwater nucleus-forming phage. These findings expand our understanding of the ecological, genomic, and functional diversity of phages in boreal environments and highlight the role of freshwater ecosystems as significant reservoirs of novel viral lineages.

anti-defence systems↗
PubMed2026

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstruction of transmission events, and identification of antimicrobial resistance mutations. Although many tools have been developed to identify single-nucleotide variants (SNVs) from whole-genome sequencing, they often suffer from high false-positive rates owing to the complexity of bacterial genomes and the need for different filtering cutoffs across sample types and sequencing depths. As data sets increase in size, the manual filtering required for high accuracy presents a significant obstacle. Here, we present AccuSNV, a novel deep learning-based tool for high-precision and automated bacterial SNV calling. Unlike traditional methods that process one sample at a time, AccuSNV leverages a convolutional neural network (CNN) that integrates alignment information across multiple samples, enhancing precision through learned across-sample patterns. We evaluate AccuSNV against seven popular SNV-calling tools using simulated data from six bacterial species with varied sequencing depths, numbers of isolates, mutations, and divergence levels. To further validate its real-world utility, we test AccuSNV on multiple curated bacterial data sets containing reported SNVs. In both simulated and real-world scenarios, AccuSNV consistently achieves the best performance. Moreover, AccuSNV provides comprehensive user-friendly downstream analysis modules and outputs, including mutation annotation information, phylogenetic inference, d N/d S calculations, and optional manual filtering. Together with the automated deep learning-based calling, these features make AccuSNV broadly accessible to users with different levels of computational expertise.

Deep Learning↗
PubMed2026

Interspecies Exchange of Mobile Genetic Elements During a Plant Disease Outbreak.

Outbreak sequencing provides insight into the origin and evolutionary processes acting on emerging pathogens. Sequencing a historic multihost outbreak of Ralstonia spp. in Martinique shows the outbreak was caused by two lineages that diverged at separate times from mainland populations. One lineage (Ralstonia pseudosolanacearum I-18) was originally introduced from Asia to South America, where it became well established prior to its dissemination to Martinique, where it retains a signature of specialization on solanaceous hosts. The novel lineage first identified during the outbreak (Ralstonia solanacearum IIB-4NPB) arose from a mainland population endemic to the Americas prior to its arrival in Martinique, where host-range expansion was observed. In contrast to minor changes in secreted effector protein repertoires, the emergent R. solanacearum IIB-4NPB acquired a novel integrative and conjugative element (ICERsoRUN1145). After identifying all Ralstonia spp. ICEs and mapping their spatial and phylogenetic distribution among Ralstonia spp. sampled during the outbreak, we found closely related ICEs circulating in mainland populations of R. pseudosolanacearum, indicating likely exchange between introduced and endemic Ralstonia spp. The family of ICEs in Ralstonia (ICERs) has a conserved bipartite structure and display a striking pattern of functional specialization in each cargo gene insertion hotspot: the first hotspot is a target for metabolic gene acquisition, and the second is a target for defense element acquisition. This work provides unparalleled phylogenetic and spatial resolution of an unusual outbreak and highlights the role of horizontal transfer in shaping the ecological success of an emerging pathogen.

Plant Diseases↗
PubMed2026

The antimicrobial gut resistome of the Wayampi reveals a shared background of antibiotic and metal resistance genes with industrialized populations, underscoring the "robust-yet-fragile" architecture of human gut microbiomes.

BACKGROUND: Metagenomics enables detailed profiling of genes encoding antimicrobial resistance. However, most studies focus exclusively on antibiotic resistance genes (ARGs), excluding those associated with non-antibiotic antimicrobials (metals, biocides), and often rely on methods with low-sensitivity and low-specificity. Furthermore, they rarely examine populations exposed to minimal anthropogenic pollution. We analyzed fecal resistomes of 95 Wayampi individuals, an Indigenous community in remote French Guiana, using a targeted metagenomic capture platform covering 8667 genes, including ARGs, metal resistance genes (MRGs) and biocide resistance genes (BRGs) (PMID: 29335005). Resistome profiles were compared with those of Europeans to assess population-level differences. RESULTS: ARG richness was similar between groups (259 in Wayampi vs. 264 in Europeans, 159 shared), but MRGs&#x2009;+&#x2009;BRGs gene richness was significantly higher in Wayampi (11,930 vs. 7419). Most genes appeared in a minority of individuals (mean 5% for ARGs, 2% for MRGs&#x2009;+&#x2009;BRGs), but several ARGs for tetracyclines [tet(32), tet(40), tet(O), tet(Q), tet(W), tet(X), tetAB(P)], aminoglycosides (ant6'-I, aph3-III), macrolides (ermB, ermF, mefA), and sulfonamides (sul2) were present in all individuals. Tetracycline resistance genes predominated overall, while beta-lactam resistance genes were more common in Wayampi, and genes conferring resistance to aminoglycosides, amphenicols, and folate inhibitors were more frequent in Europeans. Among MRGs, copper and arsenic resistance genes prevailed in both groups, followed by those for zinc, iron, cobalt, and nickel. Up to 76% of Wayampiis carried acquired MRGs for copper (pcoABCDRS and tcrB), silver (silACFPRS), arsenic (ars), and mercury (mer) detoxification. Shannon diversity indices were similar for ARGs, MRGs, and BRGs, but composition and evenness differed significantly. UMAP and ADONIS analyses distinguished cohorts based on ARG profiles (p&#x2009;<&#x2009;0.001), but not on MRGs or BRGs. Correlation analysis revealed conserved gene-sharing networks and introgression of acquired ARGs and MRGs within both gut microbiomes. CONCLUSIONS: The diverse and balanced Wayampi resistome reflects a less perturbed microbiome compared to industrialized populations, and reveals a background of "core" and "shell" acquired ARGs and MRGs, consistent with the "robust-yet-fragile" architecture of scale-free networks. The patchy yet resilient gene distribution suggests varying levels of conserved gene sharing highways among populations, likely shaped by long-term microbial-human evolution, and supports a broader view on acquired antimicrobial resistance. Video Abstract.

Humans↗
PubMed2025

Pseudoalteromonas is a novel symbiont of marine invertebrates that exhibits broad patterns of phylosymbiosis.

Despite growing insights into the composition of marine invertebrate microbiomes, our understanding of their ecological and evolutionary patterns remains poor, owing to limited sampling depth and low-resolution datasets. Previous studies have provided mixed results when evaluating patterns of phylosymbiosis between marine invertebrates and marine bacteria. Here, we investigated potential animal-microbe symbioses in Pseudoalteromonas, an overlooked bacterial genus consistently identified as a core microbiome taxon in diverse invertebrates. Using a pangenomic analysis of 236 free-living and invertebrate-associated bacterial strains (including two new nematode-associated isolates generated in this study), we confirm that Pseudoalteromonas is a novel symbiont with substantial evidence of phylosymbiosis across at least three marine invertebrate phyla (e.g., Nematoda, Mollusca, and Cnidaria). Patterns of symbiosis were consistent irrespective of geography (including in Antarctica), with FISH images from nematodes indicating that bacterial symbionts form biofilms in the mouth and esophagus. The evolutionary history of Pseudoalteromonas is marked by substantial host-switching and lifestyle transitions, and host-associated genomes suggest that these bacteria are facultative symbionts involved in nutritional mutualisms. In marine environments, we hypothesize that horizontally-acquired symbionts may have co-evolved with invertebrates, using host mucus as a physical niche and food source, while providing their animal hosts with Vitamin B, amino acids, and bioavailable carbon compounds in return.

Marine Invertebrates↗
PubMed2026

microntology: a lightweight, data-driven controlled vocabulary to describe earth's microbial habitats.

MOTIVATION: Data-enabled studies of microbial ecology and evolution depend on high-quality descriptions of microbial habitats, based on curated and consolidated vocabularies. RESULTS: We introduce microntology v1.0, a pragmatic controlled vocabulary of 148 terms to describe microbial habitats and lifestyles, and provide manually curated microntology annotations for >300k metagenomic samples from public repositories. AVAILABILITY: microntology controlled vocabulary terms and term hierarchies (doi: 10.5281/zenodo.19730167), and curated annotations for 305 626 metagenomic samples (doi: 10.5281/zenodo.18164252) are available via Zenodo and spire.embl.de/downloads. Underlying code is available via github.com/grp-schmidt/microntology and Zenodo (doi: 10.5281/zenodo.20323497). User feedback, suggestions and bug reports are welcome at github.com/grp-schmidt/microntology/issues.

Ecosystem↗
PubMed2026

De novo assembly and authentication of ancient DNA metagenomes with nf-core/mag.

Ancient DNA provides a direct window into the evolutionary processes that have shaped living microbial species today, as well as their now extinct relatives. Advances in both sequencing methods and de novo assembly techniques have not only resulted in a flood of modern metagenomic sequencing data, but they have also allowed palaeogenomicists to retrieve vast amounts of ancient DNA from past microorganisms, including species and strains without modern reference genomes. However, the degraded nature of ancient DNA means that the standard techniques of genome assembly developed for modern DNA are unlikely to perform effectively, unless heavily modified. This hinders the incorporation of ancient data into broader metagenomic studies that would otherwise benefit from having deep time information on the evolution of different microbial species. In this primer and protocol paper, we provide guidance on ways to adapt existing metagenomic de novo assembly processes, including data input, tools, and settings, in order to perform more robustly and effectively on ancient DNA. After assembly, we then further describe how ancient DNA contigs can be identified and validated. The key steps of ancient metagenomic assembly are now integrated in a dedicated ancient DNA mode in the established pipeline nf-core/mag. By introducing support for ancient DNA data in nf-core/mag, we aim to improve the ability of researchers to more regularly integrate de novo assembled ancient microbial data into broader metagenomics studies of microbial ecology and evolution.

DNA, Ancient↗
PubMed2025

The role of mobile genetic elements in adaptation of the microbiota to the dynamic human gut ecosystem.

The human intestinal microbiota is a dynamic ecosystem shaped by extensive horizontal gene transfer, particularly in individuals from industrialized populations. In this review, we discuss recent advances in our understanding of how mobile genetic elements (MGEs) contribute to microbial ecology and evolution in this diverse community, focusing on MGEs carrying fitness-conferring genes. Bacteroidales species can colonize individuals for decades and serve as major hubs for MGE exchange. Most MGEs are highly variable across individuals and geographies. Occasionally, conserved MGEs can spread across geography and lifestyles. Functional characterizations of MGEs reveal their roles in antibiotic resistance, interbacterial antagonism, biofilm formation, immune evasion, and nutrient acquisition, among others. Substantive progress in our understanding of MGEs in the gut microbiome offers promising avenues for therapeutic microbiome interventions. However, major challenges remain in functional prediction, host-MGE linkage, and experimental characterization.

Humans↗
PubMed2025

Laboratory Evolution Reveals Transcriptional Mechanisms Underlying Thermal Adaptation of Escherichia coli.

Adaptive laboratory evolution is able to generate microbial strains, which exhibit extreme phenotypes, revealing fundamental biological adaptation mechanisms. Here, we use adaptive laboratory evolution to evolve Escherichia coli strains that grow at temperatures as high as 45.3 &#xb0;C, a temperature lethal to wild-type cells. The strains adopted a hypermutator phenotype and employed multiple systems-level adaptations that made global analysis of the DNA mutations difficult. Given the challenge at the genomic level, we were motivated to uncover high-temperature tolerance adaptation mechanisms at the transcriptomic level. We employed independently modulated gene set (iModulon) analysis to reveal five transcriptional mechanisms underlying growth at high temperatures. These mechanisms were connected to acquired mutations, changes in transcriptome composition, sensory inputs, phenotypes, and protein structures. They are as follows: (i) downregulation of general stress responses while upregulating the specific heat stress responses, (ii) upregulation of flagellar basal bodies without upregulating motility and upregulation fimbriae, (iii) shift toward anaerobic metabolism, (iv) shift in regulation of iron uptake away from siderophore production, and (v) upregulation of yjfIJKL, a novel heat tolerance operon whose structures we predicted with AlphaFold. iModulons associated with these five mechanisms explain nearly half of all variance in the gene expression in the adapted strains. These thermotolerance strategies reveal that optimal coordination of known stress responses and metabolism can be achieved with a small number of regulatory mutations and may suggest a new role for large protein export systems. Adaptive laboratory evolution with transcriptomic characterization is a productive approach for elucidating and interpreting adaptation to otherwise lethal stresses.

Escherichia coli↗
PubMed2026

Transmission dynamics and driving mechanisms of antibiotic resistance genes through a chronosequence of saline-sodic rice cultivation.

Rice cultivation reclaims saline-sodic soils and improves fertility, but may also promote antibiotic resistance genes (ARGs) accumulation and horizontal transfer, posing ecological risks. This study investigated long-term co-evolution of soil properties, microbial communities, ARGs, and mobile genetic elements (MGEs) across a 1-78 year cultivation chronosequence in saline-sodic fields. Results indicated that prolonged cultivation effectively alleviated soil salinization and increased fertility. Microbial communities shifted directionally, with functional taxa enriched, while opportunistic pathogen-containing genera peaked during 5-20 years. ARGs abundance and diversity increased markedly after five years and peaked at 10-20 years. Multidrug efflux pump genes persisted throughout the chronosequence, whereas aminoglycoside resistance genes declined after 30 years. MGEs activity increased over time and was significantly correlated with key ARGs. Path analysis identified improved soil properties as the primary direct driver of ARGs accumulation, while cultivation-induced declines in microbial diversity indirectly promoted ARGs dissemination by weakening the community's suppression of MGEs-mediated horizontal transfer. Collectively, long-term rice cultivation not only ameliorated saline-sodic soils but also created a dynamic, stage-specific resistome, with the 5-20 year period representing a critical risk window for ARGs propagation. These findings highlight the need to integrate ARGs monitoring into soil health assessments for sustainable management of reclaimed saline-sodic lands.

Oryza↗
PubMed2026

Experimental evolution reveals contrasting adaptive landscapes in lab and field environments.

Experimental evolution is widely used to infer microbial responses to environmental change, yet most laboratory studies impose constant, well-mixed conditions that differ fundamentally from fluctuating, spatially structured field environments. We compared genomic evolution in the leaf litter-associated bacterium Curtobacterium strain MMLR14_002 under control and warming treatments in laboratory culture and in a complementary field experiment. Laboratory-derived isolates accumulated more mutations per genome and exhibited stronger locus-level parallelism, with mutations recurring in a small number of coding loci. Field-derived isolates accumulated fewer mutations per genome, and these mutations rarely occurred in the same coding loci across replicate populations. Instead, field isolates exhibited a higher proportion of intergenic mutations, with mutations recurring in the same intergenic regions across independent field deployments. When coding mutations were detected in the field, they were distributed across functionally diffuse targets and more often involved metabolic pathways than the core cellular processes repeatedly targeted during laboratory evolution. Warming itself did not consistently influence mutation accumulation or the genomic distribution of mutations; instead, laboratory and field contexts primarily shaped the accumulation, targets, and repeatability of genomic change. These results suggest that laboratory thermal evolution identifies adaptive routes favored under sustained selection but may overestimate coding-level parallelism under heterogeneous field conditions. Bridging laboratory and field evolution will likely require experimental designs that incorporate temporal variability and spatial heterogeneity characteristic of natural systems.IMPORTANCEA central goal of experimental evolution is to infer how microbes evolve in nature from laboratory studies. Here, we evaluate this assumption by comparing genomic evolution of a leaf litter-associated Curtobacterium strain in laboratory and field warming experiments to identify broad patterns rather than isolate the contribution of any single environmental factor. We find that the strong parallelism at coding loci observed under laboratory conditions is reduced in the field, while mutations recurring in the same intergenic regions across field deployments suggest that parallel evolution in nature may more often involve regulatory noncoding regions rather than coding targets. These results show that environmental context reshapes adaptive landscapes and may limit the parallelism of coding-level genomic responses inferred from homogeneous laboratory conditions.

experimental evolution↗