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144 recordsLinked to original sources
PubMed2026

Comparative genomic and proteomic analysis reveals orthogroup structured evolution of tick protease inhibitors.

Protease inhibitors (PIs) play central roles in regulating endogenous proteolysis and host-parasite interactions in ticks. However, the evolutionary architecture underlying their diversification across tick lineages remains insufficiently resolved. Here, we performed a genome-wide comparative analysis of predicted proteomes from 14 tick species to systematically characterize PI repertoires. In total, 4931 putative PIs were identified and grouped into 20 families using the MEROPS classification system. Further, PI families such as Antistasin, WAP-type, and Pacifastin, which have not previously been systematically reported in tick genomes, were classified. Orthogroup inference demonstrated that PI expansion is structured at the level of evolutionary lineages rather than uniformly across families. By stratifying orthogroups according to duplication burden and taxonomic conservation, we identified a broadly conserved single-copy core under strong purifying selection. Motif level analysis of serpin reactive center loops further revealed conservation of inhibitory specificity within single copy orthogroups and diversification of key functional residues in duplication-associated lineages. Integration of secretion prediction and tissue-resolved proteomics from Hyalomma anatolicum and Rhipicephalus microplus demonstrated that evolutionary stratification is reflected at the protein level. Together, these findings provide an orthogroup-resolved evolutionary framework linking duplication dynamics, molecular evolution, and tissue-level protein deployment. This integrative approach offers a systematic basis for prioritizing conserved and diversified PI lineages for future functional and anti-tick intervention studies.

Animals↗
PubMed2026

Transcriptomic and Metabolomic Profiling Identifies a Core Gene-Metabolite Axis Driving African Swine Fever Virus Replication in the Soft Tick Ornithodoros lahorensis.

African swine fever virus (ASFV) causes an incurable swine disease with nearly 100% mortality, posing a catastrophic threat to global pig production. The soft tick Ornithodoros lahorensis acts as a critical biological vector that sustains persistent ASFV replication and mediates long-distance viral transmission, yet the molecular mechanisms governing ASFV-tick interplay remain poorly understood. Here, we integrated transcriptomics and metabolomics to systematically dissect molecular changes in O.&#xa0;lahorensis across three infection stages: Uninfected control, early infection (7&#x2009;days post-infection, dpi), and late persistent infection (21 dpi). Multi-omics integration revealed that ASFV extensively remodels tick host metabolism, predominantly activating purine/pyrimidine metabolism, lipid biosynthesis, and energy metabolism. We further characterized a conserved regulatory module consisting of 12 core genes and 8 signature metabolites that collectively support ASFV genome replication and virion assembly. Three hub metabolic genes (TK1, ATP5F1B, and IMPDH) were selected for functional validation via siRNA silencing in ticks; individual gene silencing suppressed ASFV loads by 89.2%, 91.5%, and 87.8%, respectively (p&#x2009;<&#x2009;0.001***). This work represents the first comprehensive multi-omics investigation of ASFV infection in O. lahorensis. We identified tick-specific molecular targets to block vector-mediated ASFV spread and established a standardized multi-omics analytical pipeline for tick-virus interaction research. Our findings elucidate the mechanistic basis of long-term ASFV persistence in soft ticks and deliver novel actionable clues for developing vector-targeted ASF intervention strategies.

Animals↗
PubMed2026

Can host genetics transform the sustainable control of tropical theileriosis? Insights from the Tick-Theileria interface.

Tropical theileriosis, caused by the tick-transmitted apicomplexan parasite Theileria annulata, remains a major constraint on cattle production across North Africa, the Mediterranean basin, the Middle East and South Asia. Current control depends on acaricides, the theilericidal drug buparvaquone and live attenuated schizont vaccines, but acaricide resistance, buparvaquone-resistance mutations and the logistical demands of vaccination are eroding the sustainability of these tools. Host genetics offers a complementary and durable alternative. Indigenous Bos indicus breeds are consistently more resistant to ticks and tolerate T. annulata infection better than exotic Bos taurus cattle, and this advantage has a measurable heritable component. Unlike previous reviews, which treat tick resistance, T. annulata immunobiology and livestock genomic selection as separate subjects, we integrate all three and assess host genetics specifically against the failure modes of current control. We review the tick, parasite and host interface, the evidence for natural resistance, and the genetic and immunological mechanisms involved, including signal-regulatory protein, bovine major histocompatibility complex class II and inflammatory pathway genes. We then assess whether genomic selection, multi-omics, machine learning and gene editing can translate these mechanisms into resistant cattle, and we weigh the biological, economic and infrastructural barriers to implementation. The evidence indicates that host genetics will not replace existing control but could reduce reliance on acaricides and chemotherapy. That contribution remains prospective rather than demonstrated: no resistance marker for T. annulata has yet been validated, prediction accuracies are moderate and transfer poorly between breeds, and no endemic production system has implemented selection for resistance.

Animals↗
PubMed2026

Viral surveillance beyond detection: JMTV and the need for ensemble approaches in emerging virus discovery.

The recent report by T. Murillo, L. E. Enrique Chaves-Gonz&#xe1;lez, S. Temmam, S. Berm&#xfa;dez, et al. (Microbiol Spectr 14:e04078-25, 2026, https://doi.org/10.1128/spectrum.04078-25) expands the known geographic and ecological range of Jingmen tick virus (JMTV) by detecting the virus in Amblyomma mixtum ticks collected from horses in Costa Rica. This is an important finding because A. mixtum can feed on wildlife, domestic animals, and humans, creating a possible interface for virus movement across various hosts. The study also places the Costa Rican virus in a wider phylogenetic context, linking it to JMTV diversity reported from other regions. However, the detection of viral RNA in ticks should not be interpreted as proof of local disease, human infection, or active transmission, especially in the absence of supporting results. Instead, it reflects an important signal for careful viral surveillance. Here, I discuss how JMTV illustrates the need for ensemble approaches that combine field sampling, phylogeny, segment-level genome analysis, serology, experimental validation, and data-driven virus discovery tools.

emerging viruses↗
PubMed2026

Emergence of Babesia naoakii infection in Indonesian domestic cattle, a new host record in water buffaloes, and characterization of complete mitochondrial protein-coding genes.

Babesia (B.) naoakii, previously referred to as Babesia sp. Mymensingh, is a recently characterized tick-borne haemoprotozoan parasite of cattle. In Indonesia, we first reported its presence in 2022 from clinically affected cattle in Central Java. To investigate the wider epidemiology of this neglected ruminant-associated Babesia species, we surveyed apparently healthy cattle (Bos indicus) and water buffaloes (Bubalus bubalis) across three districts of Java, Indonesia. A PCR assay targeting the B. naoakii-specific apical membrane antigen 1 (ama1) gene detected the parasite occurrence in 34.39% of assessed cattle (87/253; 95% CI: 28.80-40.44%) and 30.77% of water buffaloes (12/39; 95% CI: 18.47-46.52%). These results represent the first record of B. naoakii infection in water buffaloes in the country and confirm that the parasite circulates in subclinically infected bovine hosts. To characterise this apicomplexan parasite further at the molecular level, we assembled in full length the three mitochondrial protein-coding genes (PCGs): cytochrome c oxidase subunits 1 (cox1) and 3 (cox3), as well as cytochrome b (cytb). These genes were reconstructed by next-generation sequencing of blood DNA collected during the acute haemolytic-phase of B. naoakii infection, from calves that subsequently succumbed to the disease in the endemic area. Phylogenetic analyses of the concatenated amino-acid sequences of cox1, cox3, and cytb placed the Indonesian isolates within a well-supported monophyletic clade, distinct from all previously characterised ruminant-associated Babesia species and sister to the Babesia bigemina/Babesia ovata lineage. This placement confirmed species identity and reinforced the genetic distinctiveness of B. naoakii in Indonesia. Notably, although B. naoakii circulates in peripheral blood and mirrors the diagnostic behaviour of the mild pathogen B. bigemina, its clinical impact more closely resembles that of the severe pathogenic B. bovis, particularly in young animals. This diagnostic-clinical discordance highlights the need for B. naoakii-specific molecular surveillance and species-level differentiation in regions of co-endemicity. Given the high prevalence in subclinically B. naoakii-infected adults, the documented severity of babesiosis in calves, and the potential for substantial economic losses, broader epidemiological investigations and species-specific control measures for B. naoakii are urgently performed. The same holds true for future epizootiological investigations of underdiagnosed B. naoakii-infections possibly circulating in Indonesian endemic ruminant bovids such as the banteng (Bos javanicus), the lowland anoa (Bubalus depressicornis) and the tamaraw (Bubalus mindorensis).

Animals↗
PubMed2026

Prevalence of Theileria luwenshuni in goats (Capra hircus) on Tarama Island, Okinawa, Japan.

Caprine theileriosis is an economically important tick-borne disease caused by various Theileria species, particularly Theileria lestoquardi, Theileria luwenshuni, and Theileria uilenbergi, in goats (Capra hircus). Goat farming plays an economically and culturally important role on Tarama Island, Okinawa, Japan. Because goats on the island are mainly managed under an extensive grazing system, tick infestation is common. However, Theileria infections have not previously been investigated in goats on Tarama Island. To address this, archived DNA samples prepared from blood collected from 44 goats on Tarama Island were screened using a universal PCR assay targeting 18S rRNA sequences of Theileria and Babesia species. Two DNA samples were positive, and sequencing analysis of the amplicons identified T. luwenshuni. To further investigate the epidemiology of T. luwenshuni on Tarama Island, blood samples were subsequently collected from 96 goats across 19 farms. From each blood sample, a thin blood smear was prepared and genomic DNA was extracted. Microscopic examination of Diff-Quik-stained smears detected intraerythrocytic Theileria-like organisms in 35 (36.5%) goats. In addition, screening of DNA samples using a newly developed T. luwenshuni-specific PCR assay detected 77 (80.2%) positive goats, and the subsequent sequencing analysis confirmed the PCR results. Given that T. luwenshuni can cause severe disease in small ruminants, our findings highlight the importance of managing T. luwenshuni infection in goats on Tarama Island.

Animals↗
PubMed2026

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms↗
PubMed2026

Measurable Residual Disease and the Unresolved Biology of Leukemic Stem Cells.

Measurable residual disease (MRD) testing has transformed the management of hematologic cancers by enabling detection of residual malignant cells after therapy. Current approaches rely on qPCR and next-generation sequencing to monitor leukemia-associated somatic mutations, while multiparameter flow cytometry identifies aberrant leukemic immunophenotypes. Although these methods provide valuable prognostic and therapeutic information, MRD negativity remains an imperfect surrogate for cure. Most MRD platforms evaluate CD45+, rapidly dividing leukemic populations and fail to detect quiescent cells that may survive cytotoxic therapies which efficiently target proliferating hematopoietic cells. Relapse frequently occurs despite deep molecular remission, suggesting persistence of rare leukemic stem cells (LSCs) that are intrinsically resistant to chemotherapy and targeted therapies. The paradox of relapse despite molecular remission could be explained by the presence of very small embryonic-like stem cells (VSELs) which are pluripotent, quiescent stem cells sitting at the top of cellular hierarchy in multiple adult tissues including bone marrow. A pluripotent VSEL divides through asymmetrical cell division to give rise to two cells of different sizes and fates, smaller cell is to self-renew while the bigger is lineage-restricted and tissue-committed progenitor which undergoes extensive epigenetic changes, divides rapidly and undergoes clonal expansion before further differentiation. Dysfunctions of VSELs initiate both solid and hematologic cancers. Based on this view, somatic mutations monitored during MRD assessment possibly represent downstream consequences of clonal expansion rather than the initiating drivers of disease persistence. Thus, exclusive monitoring of somatic mutations and CD45&#x2009;+&#x2009;leukemic populations possibly overlook rare, small-sized, CD45- VSELs that contribute to therapeutic resistance and relapse.

Humans↗
PubMed2026

Immune dysregulation in depression and psychosis: summary of current evidence and future perspectives.

Despite compelling epidemiological, genetic and cellular evidence linking immune dysregulation to depression and schizophrenia (and other psychotic disorders), causality remains contested and no immune biomarker has yet demonstrated robust clinical utility. Emerging methodological approaches - from target trial emulation on observational data to functional genomics - offer a potential path towards precision immunopsychiatry and stratified immunomodulatory treatment.

Neuroimmunology↗
PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗
PubMed2026

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗
PubMed2026

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics↗
PubMed2026

RNA dysregulation as a determinant of aging and neurodegenerative vulnerability.

In the nervous system, aging causes deterioration of cellular and molecular processes that are associated with declines in cognition, sensory perception, and motor coordination. Aging is also the strongest risk factor for neurodegenerative disease, yet the mechanisms by which aging predisposes neurons to dysfunction remain incompletely understood. While genomic instability, proteostasis decline, mitochondrial dysfunction, and chronic inflammation have dominated prevailing models, recent evidence highlights RNA dysregulation as a central component of age-associated decline. In this review, we summarize recent findings suggesting that aging progressively erodes RNA regulatory fidelity through alterations in RNA-binding protein abundance, localization, biophysical behavior, and RNA interactions. We argue that age-dependent RNA dysregulation represents an important mechanism that converges with genetic risk to drive neuronal vulnerability and neurodegeneration.

RNA dysregulation↗
PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗
PubMed2026

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↗
PubMed2026

Alternative genetic codes in bacteria and archaea identified with a fast k-mer-based algorithm.

The genetic code is conserved across all domains of life and is often described as universal. Nevertheless, many exceptions to the "universal" code have now been documented, most of these through manual or semiautomated inspection of highly conserved genes. Modern bioinformatics tools improved our ability to find alternative genetic codes but remain computationally expensive, preventing widespread use on thousands of new species identified by sequencing environmental samples. Here, I report a >100-fold accelerated method for inferring the genetic code directly from assembled genomes and apply it to thousands of previously uncharacterized assemblies from archaea and bacteria. I describe three candidate genetic code variations, one of which, an alternative genetic code used by a family of Asgard archaea, is a unique example of sense codon reassignments for this domain. Identifying genetic code variations is important for understanding evolution of the standard code and improving accuracy of protein databases and open reading frame identification.

Genetic Code↗
PubMed2026

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-&#x3b1;-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage↗