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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Phylogeny and Species Delimitation in Isoxylosteum, a Lonicera Clade Endemic to the Himalayan-Tibetan-Hengduan Region

The Himalayan-Tibetan-Hengduan (HTH) region is the richest biodiversity hotspot for high-elevation plants. However, owing to its remote and physically challenging topography as well as the trans-national nature of the region, many taxonomic problems in the area remain unresolved, particularly in the Himalaya. This, in turn, has impeded our understanding of the assembly of its extraordinary high-elevation flora. Here, we resolve phylogenetic relationships and delimit species in a distinctive clade of honeysuckles that is endemic to the HTH, the Isoxylosteum clade of Lonicera, using restriction-site associated DNA sequencing (RADseq) and morphological data. Five species complexes of Isoxylosteum have standardly been recognized. Three of these complexes are highly variable and have been divided into several varieties or species each. Phylogenetic, population structure, and morphological analyses of leaf and floral traits from samples collected across the range of the clade support the recognition of five species, including a species that has most often been recognized as a variety of L. rupicola (L. rupicola var. minuta). Instead, we find that it is sister to L. spinosa. This is surprising because the geographic range of L. minuta is contiguous with the other varieties of L. rupicola in the northern Hengduan region but widely separated from L. spinosa whose range lies mainly to the west of the Tibetan plateau. On close examination we find that several morphological and ecological traits also support a closer relation of L. minuta to L. spinosa. None of the other eight previously recognized varieties and species were supported. Floral traits showed high discriminatory power, correctly classifying 89% of samples to species. By comparison, leaf dimensions classified species with 59% accuracy. Our results identify diagnostic morphological apomorphies for each recognized species and major clade and provide a revised taxonomic framework for Isoxylosteum.

evolutionary biology↗

bioRxiv2026

Bioengineering of Pea (Pisum sativum) for the Expression of Myoglobin, a Heme-containing Animal Protein

Myoglobin, an oxygen-binding animal protein, was engineered in Pisum sativum (pea) to explore its potential as a food ingredient and balance the amino acid profile. In this study, minimal expression cassettes and binary vectors were used to express bovine myoglobin using particle gun and Agrobacterium-mediated transformation, respectively. Successful integration and expression of the myoglobin gene was achieved in P. sativum, with both methods yielding similar transformation efficiencies (~1%). Expression analysis of T2 seeds revealed that Agrobacterium-mediated transformation-derived transgenic lines that expressed myoglobin under the regulation of a Soybean 7S seed-specific promoter and Tobacco Etch Virus (TEV) translation enhancer and a chimeric Rb7MAR Terminator (Ps-BpRG13 events) consistently yielded the highest level of expression (0.32-1.57% of TSP), while transgenic lines with myoglobin expression under the regulation of a Soybean Phaseolin promoter and Rb7MAR Terminator (Ps-BpRG14 events) resulted in moderate levels of heterologous protein expression (0.13-0.83% TSP). Transgenic events with constitutive 2xCaMV35S promoter, TEV translation enhancer and Rb7MAR terminator (Ps-BpRG15 events) exhibited the lowest level of myoglobin expression (0.09-0.14% TSP). Co-bombardment of two minimal expression cassettes - one with myoglobin under the regulation of the Phaseolin promoter and Rb7MAR Terminator and the other with the nptII selectable marker under the regulation of a 2X constitutive CaMV35S promoter, TEV translational enhancer and TNOS Terminator, yielded lines that exhibited variable expression (0.03-0.77% TSP), with some events comparable in expression to Agrobacterium-derived Ps-pRG14 events. To the best of our knowledge, this is the first report of producing a heme-containing animal protein, myoglobin, in peas, with potential implications for sustainable production of food ingredients and nutritionally fortified and value-added plant products using molecular farming.

plant biology↗

bioRxiv2026

INFORME: coupling information-theoretic experimental design with nonlinear mixed-effects modeling for efficient observation scheduling

Mathematical models of treatment response can inform individualized therapy, but their calibration often requires longitudinal measurements that are costly, burdensome, and collected on fixed schedules. Such schedules may be inefficient, over-sampling patients whose response is already well characterized while delaying informative measurements for those whose model parameters remain uncertain. We present INFORME (INFORmation-theoretic design with Mixed Effects), a framework that combines Bayesian information-theoretic experimental design with nonlinear mixed-effects modeling to adaptively select each patients next measurement time. Population and response-subgroup parameter distributions learned from an existing cohort provide informative priors, allowing candidate measurement times to be ranked by their expected reduction in patient-specific parameter uncertainty. As observations accumulate, priors can be updated to reflect the response subgroup most consistent with the patients data. We evaluate INFORME in two radiotherapy datasets: 150 synthetic tumor volume trajectories from a hybrid cellular automaton model of prostate cancer spheroids (HD1) and longitudinal tumor volumes from 39 patients with head-and-neck cancer (HD2). In HD1, population priors allowed omission of both pretreatment scans, while adaptive scheduling reduced the protocol from nine scans to three or four, with the response group identified from a single post-treatment scan on day 27. In HD2, the adaptive schedule used three scans instead of six and improved prediction by delaying the first on-treatment scan from week 1 to week 2, avoiding transient dynamics that produced false-positive and false-negative response projections. Across both datasets, the adaptive schedules used a mean of 2.7 scans in stead of seven and advanced completion of the patient-specific prediction by a mean of 15.5 days (95% CI, 6.7-24.3) relative to the equidistant protocol, while treatment duration remained unchanged. INFORME therefore reduces measurement burden and accelerates patient-specific prediction by concentrating observations at times that are most informative for model calibration.

systems biology↗

bioRxiv2026

Systems-level proteomic reprogramming reveals mitochondrial restoration and inhibition of Rho GTPase-mediated cytoskeletal and inflammatory signaling in CKD

Chronic kidney disease (CKD) is a progressive disorder characterized by metabolic dysfunction, mitochondrial impairment, oxidative stress, and chronic inflammation, ultimately leading to irreversible renal damage. Despite advances in understanding CKD pathophysiology, effective therapies targeting these interconnected molecular processes remain limited. In this study, we performed a comprehensive data-independent acquisition (DIA)-based proteomic analysis to investigate the molecular alterations associated with CKD and to evaluate the therapeutic impact of DVA treatment. Using a CKD model with three treatment conditions (DVA, KY, and DVA+KY) alongside disease and healthy controls, we quantified global proteomic changes and applied statistical filtering (fold change [≥]2, p [≤]0.05) followed by K-means clustering (k=10). Distinct protein clusters revealed bidirectional modulation upon DVA treatment. Notably, Cluster 1 comprised proteins downregulated in CKD but significantly restored following DVA administration, while Cluster 2 included proteins elevated in CKD that were suppressed by DVA. Pathway enrichment and network analyses demonstrated that Cluster 1 proteins were predominantly associated with mitochondrial function, oxidative phosphorylation, and metabolic processes, whereas Cluster 2 proteins were enriched in immune signaling, oxidative stress, cytoskeletal remodeling, and proteostasis pathways. At the molecular level, DVA treatment restored key mitochondrial and metabolic regulators, including components of the electron transport chain (e.g., COX5A, NDUFS5, SDHB) and redox homeostasis proteins, indicating recovery of cellular bioenergetics. Concurrently, DVA suppressed inflammatory mediators (STAT2, IFI47, GBP2), oxidative stress-related proteins (CYBB, PRDX5), and cytoskeletal regulators linked to renal injury (ARHGEF12, FMNL2). Network and Reactome analyses further confirmed coordinated modulation of interconnected biological systems rather than isolated protein changes. Collectively, our findings demonstrate that DVA exerts a dual therapeutic effect by restoring essential mitochondrial and metabolic pathways while simultaneously suppressing inflammation, oxidative stress, and cytoskeletal dysregulation in CKD. This systems-level proteomic reprogramming highlights DVA as a promising candidate for CKD intervention and provides mechanistic insights into disease progression and therapeutic targeting.

systems biology↗

bioRxiv2026

Breeding cassava for intercropping with cowpea: monoculture selection captures most intercrop selection gain, but targeted testing remains necessary

Intercropping dominates smallholder cassava production in sub-Saharan Africa, yet cassava breeding programs evaluate genotypes exclusively under monoculture. Despite consistently reported system-level yield advantages, cassava yield is reduced by 17 to 51% under intercropping, indicating a need to reduce this competitive disadvantage through breeding. However, the quantitative-genetic foundations of intercrop breeding remain uncharacterized for tropical root crop systems. We hypothesized that monoculture selection would capture most, but not all, genetic merit for intercropping and that a limited tester set would be sufficient if general mixing ability predominated. We evaluated 120 cassava clones previously selected under monoculture in IITA advanced yield trials, testing them under monoculture and in intercrop with two contrasting cowpea varieties across two years at Ibadan, Nigeria. Spatial mixed models quantified genetic variation, genotype by cropping system interaction, cross system genetic relationships, realized selection gain, mixing ability, tester effects, and land equivalent ratio. Intercropping reduced cassava fresh root yield by 19%, but total land equivalent ratios exceeded 1.0 for all clones, confirming a system-level land use advantage. Cassava performance under intercropping was heritable, with estimates of 0.50 to 0.75, and genotype by cropping system interaction was not significant. Genetic correlations between monoculture and intercrop performance were high and approached unity (rg = 0.92 to 0.99), and selection efficiency was 26 to 44% at 10% intensity, confirming that high genetic correlation does not guarantee effective indirect selection. Monoculture selection captured approximately two-thirds of direct intercrop gain. General mixing ability dominated, specific mixing ability was negligible, and producer effects explained 20 to 47% of intercrop variance. The two architecturally and phenologically contrasting cowpea varieties had limited influence on cassava rankings. Here, we show for the first time that cassava breeding for intercropping can retain monoculture selection during early stages while adding two representative cowpea testers at the advanced trial stage. This staged strategy aligns cassava breeding with diversified smallholder systems without creating a separate pipeline.

plant biology↗

bioRxiv2026

Effects of spectral light quality on growth, photosynthetic pigments and bioactive compounds in Brassicaceae microgreens

LED spectral composition is an important tool for improving the growth and nutritional quality of microgreens cultivated in controlled environments. This study evaluated the effects of three LED light treatments on growth, morphology, pigments, primary metabolites, phenolic composition, and antioxidant capacity in arugula (Eruca sativa), mustard (Brassica juncea), and radish (Raphanus sativus) microgreens. Microgreens were cultivated under controlled environmental conditions and exposed to broad-spectrum white (W), blue-enriched white (WB), and red-enriched white (R) light at a photosynthetic photon flux density of 200 micromol/m2/s. Light quality did not affect yield in any species. However, R increased cotyledon area in arugula by 50 to 60% and promoted hypocotyl elongation in both arugula and radish, whereas W resulted in the longest hypocotyls in mustard. Photosynthetic pigment composition responded differently among species. In mustard, WB increased the chlorophyll a/b ratio (1.12 to 1.18), whereas lutein concentration decreased from 7.06 to 4.20 mg 100 g/FW. Primary metabolism also responded to light treatments in a species-dependent manner. In mustard, W increased glucose (0.43 vs. 0.26 and 0.29 g 100 g/ FW) and fructose (0.33 vs. 0.20 and 0.22 g 100 g/ FW) concentrations compared with WB and R. Organic acid composition was more responsive to light treatments in radish, with higher concentrations under R. Phenolic metabolism also responded in a species-dependent manner. In mustard, W increased total phenolic content to 0.25 mg GAE g/FW compared with 0.15 mg GAE g/FW under WB and R, and ABTS antioxidant capacity to 1.17 mg TE g/FW compared with 0.74 and 0.75 mg TE g/FW under WB and R, respectively. Individual phenolic compounds were also affected by light treatments, particularly in arugula and mustard. These findings demonstrate that the effects of LED spectral composition on microgreen quality are highly species-dependent. Therefore, LED light spectra should be optimized according to the target species and the desired quality attributes rather than applying a single lighting strategy to all Brassicaceae microgreens.

plant biology↗

bioRxiv2026

Multiscale modelling of drug-host-pathogen interaction: quantifying drug and immune contributions to treatment response

Background and Objective: Predicting treatment outcomes in infectious diseases requires accounting for the interplay between drug effects, pathogen dynamics, and host immunity. Integrating pharmacological and immunological approaches into a single simulation environment remains a fundamental challenge in both theory and practice. We aimed to develop and validate a multiscale in silico framework coupling these processes, and to quantify their respective contributions to bacterial clearance. Methods: We present the Drug-Host-Pathogen Interaction (DHPI) framework, combining three independent mechanistic components: a physiologically based pharmacokinetic model of drug disposition, a pharmacokinetic-pharmacodynamic model of drug-induced bacterial killing, and a stochastic agent-based model of the immune response. Continuous concentration profiles are time-averaged onto the agent-based time grid, assigned to bacterial phenotypic states, and converted into per-agent killing probabilities, so that drug-mediated and immune-mediated death events are recorded separately at each step. The framework was applied to simulate symptomatic pulmonary tuberculosis. Phenotype-specific drug-efficacy parameters were inferred using Approximate Bayesian Computation from historical clinical data on eight weeks of 600 mg rifampicin monotherapy, and validated against independent early bactericidal activity data over a disjoint time window. Results: The calibrated framework reproduced the observed decline in bacterial load, and matched reported early bactericidal activity over the first week. In a virtual cohort of symptomatic patients, drug-mediated killing accounted for 81-88% and immune-mediated killing for 12-19% of total bacterial elimination over the 60-day treatment course, while the dormant, granuloma-contained fraction rose from 0.20-0.29 in the first week to 0.85-0.89 at treatment completion. Over a follow-up of up to 50 years, patients reaching clinical cure had accumulated more memory lymphocytes during treatment than those progressing to clinical failure or death; moreover, the final outcome depended on the immune changes occurring during therapy rather than on the initial disease stage. Conclusions: The results show that the DHPI framework can reproduce treatment dynamics observed in patients and enable the analysis of how therapy reshapes host immune responses and subsequent disease trajectories. By explicitly representing drug-host-pathogen interactions, it provides a mechanistic basis for in silico treatment simulations and for the study of long-term immune consequences of antimicrobial therapy.

systems biology↗

bioRxiv2026

Postmortem Alterations of Metabotropic Glutamate Receptors across Neuropsychiatric Disorders: A Systematic Review

Metabotropic glutamate receptors (mGluRs) regulate glutamatergic transmission and have been implicated in diverse neuropsychiatric disorders, but human postmortem evidence remains fragmented. We aimed to map these findings across diagnoses, receptor subtypes, brain regions, and measurement modalities. Following PRISMA guidelines, we systematically searched MEDLINE, EMBASE, and Web of Science from inception to August 8, 2026, for studies assessing GRM transcripts, as well as mGluR protein abundance, localization, assembly, or receptor binding in human postmortem brain tissue. Of 532 records identified, 57 reports met eligibility criteria. Findings were synthesized narratively because of substantial heterogeneity in diagnoses, brain regions, receptor subtypes, and assays. Postmortem evidence was concentrated on mGluR5, mGluR2/3, and mGluR1, and on the prefrontal cortex, anterior cingulate cortex, and hippocampus. mGluR-related alterations were reported across disorders, including schizophrenia, major depressive disorder, Alzheimer disease, autism spectrum disorder, and alcohol use disorder. Although most analyses yielded null findings, the direction and magnitude of mGluR alterations varied across brain regions, receptor subtypes, and molecular endpoints. This inconsistency may partly reflect the distinct biological levels captured by transcript abundance, total protein, receptor assembly, localization, and ligand binding, together with regional, cell-type, disease-stage, and clinical heterogeneity. The available evidence therefore suggests context-dependent alterations in mGluR biology but not a uniform or disorder-specific molecular signature. Integration of postmortem findings with other approaches, including in vivo imaging, may clarify their biological and clinical significance.

neuroscience↗

bioRxiv2026

Evolution and Human Neural Individuality

Individuality is a defining feature of human biology. The functional network architecture of the human brain harbors person-specific qualities and forms individualized connectivity profiles that function as a neural fingerprint, both stable and unique across time. Here, using fMRI data from 431 Human Connectome Project participants, we examined whether neural individuality is more strongly exhibited in brain regions bearing signatures of recent human evolution. We calculated region-wise fingerprinting accuracy and associated it with four properties of evolutionary cortical organization: cortical expansion, myelin content estimate (T1w/T2w), human-specific gene-expression profiles, and functional homology to other primates. Across all four measures, neural individuality was strongest in cortical areas showing greater evolutionary novelty in humans, particularly frontoparietal control and default mode networks, and weaker in more conserved primary regions. Our findings connect evolutionary variation across species with stable functional variation among individuals.

neuroscience↗

bioRxiv2026

Both environmental filtering and intraspecific variation shape small mammals' elementomes

The biogeochemical niche hypothesis (BNH) proposes the multi-elemental composition of organisms - their elementome - as a new ecological dimension. However, which ecological factors shape elementome assembly remains little known, especially in animals. Here, we studied the mandibular elementome of two sympatric small mammals - Apodemus flavicollis and Clethrionomys glareolus - to assess how intraspecific variability (ontogenetic changes in body mass and sex under the vertebrate bone hypothesis; VBH) and environmental filtering (season and habitat) shape essential and non-essential elementome assembly. Species showed moderate elementome segregation and seasonal niche partitioning, with implications for coexistence. Ontogenetic body mass predicted elemental variation and calcium substitution, with several hypermetric scalings in autumn indicating strong departures from mass-invariant homeostasis. Finally, our results suggest a dichotomy: essential elementomes were mainly driven by intraspecific variation, whereas non-essential elementomes were rather shaped by environmental filtering. Our results position animal elementomes as an integrative ecological dimension linking organismal biology, species interactions, and environmental filtering across individuals, populations, and species.

ecology↗

bioRxiv2026

City life: airborne DNA metagenomic biodiversity monitoring reveals dynamic changes across time and space

Airborne environmental DNA can capture biodiversity across the tree of life, but low sample biomass makes rapid, untargeted detection technically challenging. We combined 45-min air collection, nanopore sequencing and real-time taxonomic analysis in a shotgun metagenomic workflow capable of producing results within 3 hours. Across 77 samples from 13 London sites, including a year of weekly sampling at the Natural History Museum Wildlife Garden, we detected 1,916 species spanning bacteria, fungi, plants and animals. Communities varied spatially and seasonally, shifting from plant dominance in spring to ascomycete dominance in summer and basidiomycete dominance in late autumn and winter. Plant read abundance increased with upwind vegetation, linking airborne signals to surrounding habitat. Detection of catalogued garden plants depended on reference availability, dispersal biology, plant size and proximity to the collector. Together, these findings establish airborne shotgun metagenomics as a platform for rapid, repeated and scalable biodiversity assessment across space and time.

ecology↗

bioRxiv2026

Proteome-wide crosslinking mass spectrometry reveals novel components of essential complexes in Toxoplasma

Protein-protein interactions underpin nearly all cellular processes, yet systematic definition of these networks remains limited outside a few model organisms. As a result, the architectures of essential complexes in many divergent lineages remain poorly characterized. Here we developed a high-coverage crosslinking mass spectrometry framework to map the proteome-wide interactome of the model apicomplexan parasite Toxoplasma gondii. From 29,624 crosslinked peptide pairs, we resolved a network of 2,859 protein-protein interactions that we integrated with structural modeling to resolve interaction interfaces. We identified and validated previously unrecognized components of essential protein complexes, including a structurally distinct ATP synthase subcomplex containing a highly divergent, apicomplexan-specific subunit essential for parasite fitness. Beyond revealing unexpected diversification of core mitochondrial machinery, these findings provide a general strategy to define the molecular architecture of divergent organisms and represent a foundational resource for hypothesis generation, structural inference, and discovery of lineage-specific vulnerabilities in pathogen biology.

microbiology↗

bioRxiv2026

Structural mechanism governing radiationless energy transfer in Renilla bioluminescence

The nonradiative transport of electronic excitation from one chromophore to another, known as resonance energy transfer, lies at the root of photochemical processes in biology. Unlike photosynthesis, bioluminescence converts chemical energy into light through an enzymatic oxygenation of an energy-rich luciferin. In glowing cnidarians, the energy is relocated from an excited oxyluciferin to a fluorescent protein, shifting the colour and enhancing the quantum yield of a photogenic reaction. How protein-chromophore complexes assemble during this interplay in real space, and what this association entails for function, are unknown. Here, we report co-crystal structures of a 120-kilodalton energy-transfer complex from the luminescent soft coral Renilla reniformis. We find a heterotetrameric 2:2 assembly composed of two coelenteramide-loaded luciferases (RrLuc) docked at opposite sides of a head-to-tail dimer of green fluorescent protein (RrGFP). The edge-to-edge distance between donor and acceptor chromophores is below 3 nm, favouring the Forster-type radiationless energy transfer. Furthermore, RrGFP serves not only as a colour-switchable antenna and luminescence amplifier but also tunes the efficiency of luciferase catalysis by controlling its inherent dynamics. Our results provide detailed spatial information about intermolecular dipole-dipole coupling in Renilla bioluminescence, including the arrangement of donor-acceptor pairs that secure excited-state energy transfer with exquisite precision.

biochemistry↗

bioRxiv2026

BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images

Standardized extraction of quantitative phenotypes from images is increasingly important across plant biology, from ecological and evolutionary studies to genetics, breeding, and functional genomics. However, as large image datasets are increasingly used for trait analysis, many biologically relevant traits, including size, shape, color, and spatial patterning, are still measured manually or using fragmented semi-automated workflows. These limitations reduce throughput, reproducibility, and accessibility, especially for researchers without computational expertise. Here, we present BioIMA, an open-source desktop tool for rapid and standardized phenotyping from biological images. BioIMA integrates foundation model-based segmentation with automated trait computation, allowing users to extract quantitative measurements from images through an intuitive graphical interface and without model training. To validate its performance, we quantified a set of knot morphological traits in two Populus species, as these measurements are typically time-consuming to perform manually. Automatic measurements showed strong agreement with manual ImageJ-based measurements (R2 > 0.95), while reducing per-image processing time by approximately 75% (from ~15 s to ~4 s). BioIMA was further applied to diverse plant datasets, including Helianthus and Rhododendron images with varying morphologies and background conditions. Although developed for plant phenotyping, BioIMA may also be extended to other biological samples where region-based size, shape, or color traits are of interest. By combining accessibility and standardization in a lightweight local application, BioIMA provides a practical community resource for image-based phenotyping in ecological and evolutionary studies.

bioinformatics↗

bioRxiv2026

Mural-VISTA: A tool for mural cell-vessel interaction assessment and multiscale single-cell topo-morphological analysis

Three-dimensional (3D) mural cell morphology is heterogeneous and coupled to vessel geometry, however, measurements from two-dimensional (2D) maximum intensity projections (MIP) obscure overlapping processes and cell-vessel contacts. Accordingly, we developed Mural-VISTA, a semi-automated Python workflow for mural cell-vessel interaction and single-cell topo-morphology analysis of reconstructed surface meshes. This workflow integrates mesh pretreatment, interactive centerline extraction, hierarchical segmentation of cell soma, main axis and secondary processes (branches), and extraction of 36 multiscale (cell process segment level, process level, and whole cell level) topo-morphological and vessel-referenced metrics. Mural-VISTA identified morphological changes in pericytes and vascular smooth muscle cells (vSMCs) with altered RhoA activity. Constitutive active RhoA (RhoA CA) over-expression reduced branch complexity and increased process alignment in both cell types, while increased whole-cell and branch solidity only in vSMCs. Dominant negative RhoA (RhoA DN) over-expression increased branch abundance and reduced branch solidity in pericytes but not vSMCs, suggesting cell-type specific effect of reduced RhoA activity. In conclusion, Mural-VISTA enables quantitative 3D profiling of mural cell architecture and its spatial relationship with the vessel.

bioinformatics↗

bioRxiv2026

Systematic Evaluation of Nasal Immune Cell Sampling and Antigen-specific T cell Detection using Cryopreserved Nasal Swabs

The upper respiratory tract is a key entry point for pathogens, yet local tissue-resident memory T cells (Trm) remain underexplored compared to peripheral blood. We systematically compared nasal curettes and 8 different swab types for immune cell collection, assessing yield, operator variability, and T cell phenotypes across the three turbinates and nasopharynx. The use of flocked swabs yielded higher immune cell numbers while being similarly tolerated, especially with reduced sampling duration. Nasal Trm subsets were consistent across the turbinates, whereas nasopharyngeal Trm displayed a more recently recruited phenotype. Multiple cryopreservation media were evaluated and all demonstrated high viability after thawing. Antigen-specificity was assessed using the activation induced marker (AIM) assay, peptideHLA tetramers and bulk TCR-sequencing following expansion. Notably, influenza-specific T cell frequencies were reliably detected by AIM and correlated between fresh and cryopreserved nasal samples. Downregulation of the CD3/TCR complex was observed in nasal samples. These findings establish a robust approach for nasal Trm profiling, demonstrating that cryopreservation preserves functional antigen-specific T cells. This work enables centralized, minimally invasive nasal T cell analysis for multicenter studies, including mucosal vaccination trials and controlled human infection models.

immunology↗

bioRxiv2026

Multivalent Adhesive Probe Atomic Force Microscopy (MAPA) for accessing dispersive adhesion of cells and biosurfaces.

Adhesion of cells is the key factor determining functioning of multicellular organisms. Viscoelastic properties of cells can be studied by multiple methods. However, attractiveness of cells or extracellular matrix without the elastic component (dispersive adhesion) is not accessible. We present an extension of force spectrometry technology: the Multivalent Adhesive Probe Atomic Force Microscopy (MAPA) that delivers dispersive adhesion maps of live cells and biosurfaces, and identifies differences unresolved by viscoelastic probing.

biophysics↗

bioRxiv2026

Antibody-dependent priming of spontaneous germinal centers by autoreactive B cells

Autoreactive germinal centers (GCs) are central to autoimmune pathogenesis, yet the mechanisms by which single autoreactive B cell clones prime systemic autoimmunity remain unclear. Using the 564Igi mixed chimera model, we demonstrate that autoreactive 564Igi B cells break tolerance in wild-type B cells through an unexpected mechanism independent of cognate T cell interactions. While B cell-intrinsic TLR7 signaling was essential for spontaneous GC formation, deletion of MHC class II, CD40, or CD80/86 on GC-priming 564Igi B cells failed to prevent GCs. Instead, CRISPR-mediated deletion of Prdm1 (encoding BLIMP-1) in 564Igi B cells ablated spontaneous GCs, implicating autoantibody production as the primary driver. These findings reveal that autoantibodies can initiate feed-forward mechanisms that propagate systemic autoimmunity, independent of B cell-intrinsic antigen presentation.

immunology↗