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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

Temporal evolution of minimally invasive pediatric urolithiasis treatment over 30 years.

Urolithiasis in children has increased substantially over the past 30 years, and surgical management maintains an important role in treatment. Technological advances such as lasers and miniaturization have broadened treatment options, and researchers investigate the best indications for each procedure. The aim was to identify publication trends in the field and explore reasons why Extracorporeal Shockwave Lithotripsy is being gradually less applied in the treatment of pediatric urolithiasis. A Reverse Systematic Review of the literature was conducted regarding the surgical treatment of urolithiasis in children. Five databases were screened, gathering all articles from inception that were evaluated in systematic reviews. We examined 123 publications, 197 reports, and 15,878 procedures, consisting of the largest studied population in the field. There was an increasing number of publications, although in progressively less prestigious journals. The number of studies on miniaturized percutaneous techniques and flexible ureteroscopy has increased closely with the rise in popularity of these procedures worldwide, mainly driven by studies from Asia, Europe, and North America. A trend of self-renewed interest is fueled by technological innovation and has led to fewer publications on Extracorporeal Shockwave Lithotripsy over the years. This review highlights the fact that, despite positive results in recent studies, the low popularity of ESWL within the scientific community is driving a decline in the technique's indications. Moreover, based on the findings of this study, key research priorities include continued reporting of high-quality outcomes, and technological progress in ESWL would contribute meaningfully to the field.

Humans

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics

Computational metabolomics at scale: from open data to insight.

Metabolomics data are currently generated at scale thanks to the evolution of technologies that have led to marked improvements in the number of metabolites detected, spanning all chemical classes. These data are increasingly submitted to public repositories for data reuse, integration, and interpretation. Despite the availability of public resources and associated computational tools, the field still lacks a widely adopted, consistent data and analytics infrastructure capable of transforming this wealth of information into scientific insight. Indeed, the metabolomics field is just now scratching the surface of being able to harness the power of new computational technologies. In this review, we summarize discussions from the "Dagstuhl-Seminar 24181 Computational Metabolomics: Towards Molecules, Models, and their Meaning" with a focus on public data availability, open data standards, data and knowledge integration, and education. Our goal is to raise awareness and adoption of the latest open science resources while highlighting key areas needing further development.

Metabolomics

Electrospun Nanofiber Dressings for Diabetic Wounds: From Single-Layer to Intelligent Composite Systems.

Diabetic chronic wounds have become a major challenge for clinical treatment due to their complex pathological microenvironment, including persistent inflammatory response, angiogenesis disorder, excessive oxidative stress, and susceptible infection. Traditional dressings as a passive barrier have difficulty meeting the above multiple treatment needs. Electrospinning technology, with its ability to mimic the fibrous network structure of the natural extracellular matrix (ECM), offers a high specific surface area, controllable porosity, and excellent drug-loading capacity, making it an ideal platform for developing a new generation of multifunctional wound dressings. This article provides a systematic review of the research progress on electrospun nanofiber dressings in the treatment of diabetic wounds, focusing on the design evolution from basic single-layer structures to advanced complex structures and elucidating the mechanisms of action and quantifiable effects of each structural type in addressing specific pathological challenges. We also compared the current status of clinical translation for electrospun dressings with that of other advanced wound care platforms and proposed a standardized preclinical evaluation framework. A large number of research data show that these advanced designs can effectively improve the quality of healing. Finally, this paper points out the challenges faced by this field, such as scalable fabrication, in vivo reliability of smart systems, and long-term biosafety, and provides theoretical basis and technical reference for the design of efficient and intelligent electrostatic spinning diabetic wound dressings.

Nanofibers

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny

GATA2 deficiency: enhancer deregulation, immune surveillance failure, and clonal evolution.

Germline mutations in GATA2 cause a syndromic inborn error of immunity characterized by cytopenia, infections, immune dysregulation, and a marked predisposition to myelodysplastic syndrome and acute myeloid leukemia. Initially defined by the DCML phenotype-dendritic cell, monocyte, B- and NK-cell deficiency-GATA2 deficiency is now recognized as a disorder of global immune-hematopoietic homeostasis. Recent multi-omics and experimental models reveal enhancer-driven inflammatory rewiring, IRF8-dependent lineage imbalance, and premature hematopoietic aging. In parallel, adaptive immune defects, including impaired B- and T-cell development and function, contribute to defective immune surveillance. These alterations not only explain susceptibility to infection but also shape clonal evolution and malignant transformation. Clinically, improved risk stratification and transplant outcomes underscore the importance of early recognition and monitoring of immune dysfunction. GATA2 deficiency thus represents a paradigm linking immune dysregulation, inflammatory stress, and cancer predisposition.

Humans

Evolution of maize recombination landscape during domestication.

Despite the plethora of knowledge about the benefits of meiotic recombination and numerous theoretical studies examining how recombination rates evolve, there is a general lack of empirical support and consensus across species. To fill this knowledge gap, we characterized the evolution of recombination landscape in maize during its domestication from teosinte and related the observed changes to established theoretical frameworks. Through examining recombination in experimental populations of maize and teosinte and the population genomics approach of identifying historical recombination events using ancestral recombination graph inference to generate saturated maize and teosinte recombination maps, we found that during domestication, maize experienced a 12% increase in its genome-wide recombination rate. Furthermore, maize evolved higher recombination rates on the long arms of chromosomes in regions closer to centromeres, where recombination is generally very low. The repatterning of crossover events came from changes in global crossover positioning rather than alterations in cis-acting chromatin factors. Consequently, we found evidence of selection acting on trans-acting recombination modifiers affecting crossover interference and controlling the interference-dependent class I crossover pathway. We show that CO repatterning was likely beneficial for maize fitness, as significant recombination rate increases were predominantly in gene-rich regions, which harbor domestication-related variation. This work suggests genomic and mechanistic processes leading to the evolution of meiotic recombination landscape in response to directional selection pressure and provides evidence for the evolutionary advantage of recombination.

Zea mays

Oropouche virus: viral evolution, epidemiological trends, and challenges for control.

PURPOSE OF REVIEW: In recent years, OROV has emerged as a significant public health threat beyond the Amazon region. Here we review current epidemiological, virological, clinical and ecological knowledge of OROV to inform health practitioners, public health authorities and the scientific community and to facilitate the development of effective control strategies for OROV. RECENT FINDINGS: We describe the epidemiological, virological, ecological and clinical characteristics of OROV, focusing on lessons from the recent expansion, and highlighting needs for control and management of this emerging arbovirus. SUMMARY: This review aims to inform health practitioners, public health authorities and the scientific community of the recent reemergence and expansion of OROV beyond the Amazon Basin. The ecology, epidemiology, virology of OROV and clinical presentations of OROV infection are discussed, and knowledge gaps are identified.

Humans

Evidence of genome-wide relaxed selection on mildly deleterious mutations in an ancient subterranean catfish.

About one hundred subterranean catfish species have been described, resulting from repeated colonization of cave environments by multiple surface lineages. Most cave-dwelling species are found in the Americas, in particular in South America, but a few species also live in Central and North America. Despite the availability of high-quality genome assemblies for two cave species, the Mexican blind catfish Prietella phreatophila and the Colombian blind catfish Trichomycterus rosablanca, genomic approaches to investigate genetic changes associated with subterranean life or to estimate cave colonization times remain largely unexplored. To fill this gap, we additionally sequenced the genomes of four blind and depigmented subterranean catfishes from Peru (three Trichomycterus and one Astroblepus), as well as the genomes of four close surface relatives. We first extracted a large set of light-related genes, such as phototransduction and crystallin genes, and found contrasting decays of these sequences in different cave species, from 1% of pseudogenes in T. rosablanca to 48% in P. phreatophila. Two independent molecular dating methods gave congruent ages, indicating that these catfishes colonized subterranean habitats at different times, ranging from Early Pliocene to Late Pleistocene, supporting the hypothesis that surface catfishes repeatedly and rapidly adapted to subterranean habitats. The oldest cave species, P. phreatophila, appears to have been thriving in the dark for over 3.5 million years. Moreover, a genome-wide analysis of protein-coding genes suggests weaker purifying selection on mildly deleterious mutations in this cavefish than in other catfish lineages, likely reflecting a long-term small effective population size.

cavefishes

Mapping the Molecular Evolution and Role of Wild Rice GLYIII Protein-Encoding Genes in Abiotic Stress Response.

To address the need for sustainable food production amid rapid global climate change, developing rice varieties that grow optimally even under harsh conditions is essential. An effective approach in this direction would be to harness the stress resilience traits of the crop wild relatives (CWRs) of rice. Among the various crucial stress-responsive genes, the Glyoxalase III (GLYIII) gene family is of utmost importance for its ability to detoxify the toxic glycolytic byproduct, methylglyoxal (MG), in a less energy-intensive, single-step process, as well as for its multifaceted cytoprotective role. In our study, a comprehensive genome-wide search across the Oryza genus revealed that GLYIII genes are conserved across wild rice genotypes. Their number has expanded during domestication, driven by gene duplications. Interestingly, only a few orthologous pairs showed positive selection, suggesting that the functions of most others need to be constrained and or conserved.We found that higher GLYIII activity, Total Antioxidant Capacity, endogenous glutathione (GSH) levels, and free radical scavenging activity contributes to the stress resilience of wild rices O. punctata, O. meridionalis, and O. nivara, in addition to other factors. , , . , . Our qRT-PCR analysis revealed differential expression of the OpGLYIII, OmGLYIII, and OnGLYIII genes across different developmental stages and in response to various abiotic stresses. Furthermore, we report that wild rice GLYIII proteins, specifically OpGLYIII-3, OmGLYIII-3, and OnGLYIII-5, exhibit high catalytic efficiency over a broad pH range and at higher temperatures under in vitro assay conditions. Overexpression of these proteins was found to impart substantial stress resilience to the transformed E. coli cells. These findings collectively suggest that GLYIII proteins constitute a key component of the abiotic stress response machinery in wild rice.

Oryza

Fructophilic lactic acid bacteria as a window into multi-scale convergent evolution.

Fructophilic lactic acid bacteria (FLAB) are a group of lactic acid bacteria with unique growth characteristics, that is, poor growth on glucose. Their growth is enhanced in the presence of fructose or external electron acceptors. These organisms inhabit fructose-rich environments such as flowers, fruits, and pollinating insects, particularly honey bees. Apilactobacillus spp. and Fructobacillus spp. are representatives of FLAB, although they belong to phylogenetically distant clades. These organisms commonly possess markedly small genomes with a low number of coding DNA sequences. Furthermore, their genomes are characterized by a markedly reduced number of genes involved in carbohydrate transport and metabolism. Genome reduction in FLAB reflects convergent adaptation to fructose-rich environments rather than general genome streamlining. The two distinct FLAB genera, Fructobacillus and Apilactobacillus, independently lost more than 100 genes in statistically similar orders. In contrast, genes involved in carbohydrate and amino acid metabolism exhibited reversed orders of loss between the two genera. Furthermore, FLAB genomes lack an intact bifunctional alcohol/aldehyde dehydrogenase gene (adhE), which causes their poor growth on glucose. A comparative genomic study suggested the evolutionary process underlying adhE gene decay during adaptation to the fructose-rich environments, including pollinating insects. In conclusion, FLAB represent a unique example of habitat-driven convergent reductive evolution that can be investigated across multiple biological scales - from individual genes to whole genomes - in the diverse LAB group with a wide range of habitats, and partially share the fructophilic evolution with eukaryotic yeasts found in fructose-rich habitats.

Fructose

Beyond species trees: pervasive gene flow limits phylogenomic resolution in the diversification of Juniperus from the Qinghai-Tibet Plateau.

Understanding how lineages diversify despite persistent ancestral polymorphism and recurrent gene flow remains a central challenge in evolutionary biology. Juniperus distributed across the Qinghai-Tibet Plateau provide an ideal system for addressing this question because repeated geological uplift and climatic oscillations have likely promoted cycles of lineage divergence, range shifts, and secondary contact. Here, we combined approximately 1.08 million genome-wide SNPs from 164 individuals representing thirteen Juniperus lineages with phylogenomic datasets comprising 3,381 nuclear single-copy genes and nearly complete plastomes. We detected extensive phylogenomic discordance and cytonuclear incongruence across genomic datasets. Topology weighting, coalescent simulations, quartet-based tests, and analyses of gene flow and reticulation collectively support the interpretation that these patterns were shaped by the combined effects of prolonged incomplete lineage sorting and gene flow during lineage diversification. Ecological niche analyses further provide a spatial and climatic context in which environmentally similar lineages may have had greater opportunities for secondary contact during historical range shifts. Collectively, our results reveal that the evolutionary history of Qinghai-Tibet Plateau Juniperus is characterized by reticulate diversification rather than strictly bifurcating evolution, and demonstrate how genome-wide discordance can provide biological insights into the evolutionary processes underlying lineage diversification.

Gene Flow