Biology subjects

Snyder, M.

Publications and source records attributed to Snyder, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Intracellular complement Factor B couples inflammatory sensing to metabolism, chromatin regulation and maladaptive tissue repair

Inflammatory signals are broadly conserved, yet how tissue context converts them into programs of recovery or maladaptive repair remains unclear. Using kidney injury as a model of inflammation-to-repair transitions, we identify an injury-induced proximal-tubule complement program in which cell-intrinsic complement proteins are repurposed across subcellular compartments to couple inflammation to metabolic and chromatin regulation and promote maladaptive fibrotic remodeling. Mechanistically, myeloid-derived IL-1b; signals through IL-1R1 on injured tubular cells to recruit NF-kB and AP-1 to C3 and Cfb, coordinately inducing complement component 3 (C3) and Factor B (FB). Cytoplasmic FB drives cleavage-activation of cell-intrinsic C3, which supports tubular cell mitochondrial metabolic adaptation to stress and accumulation of C3aR-expressing macrophages around injured tubules. Nuclear FB, on the other hand, binds chromatin through a previously unrecognized DNA-binding interface and mediates histone H3 proteolysis and the preferential remodeling of chromatin promotors enriched in transcriptional programs relevant to maladaptive repair. Key features of this injury-associated C3-FB response, including intranuclear FB, are conserved in human kidney disease, associate with kidney dysfunction, and distinguish diseased from healthy kidneys. Together, these findings suggest that extracellular complement-targeting therapies may miss disease-relevant intracellular functions and suggest nuclear FB as a distinct target whose chromatin interaction and processing capacity could selectively limit maladaptive tissue responses beyond conventional inhibition.

immunology↗

bioRxiv2026

AFIDs-Validator: An Open-Access AI-Guided Platform for Learning Anatomical Landmark Placement

Accurate localization of anatomical landmarks is a foundational skill in anatomy and imaging that is often taught informally through expert mentorship, requiring access to data and desktop software. There is no openly accessible, interactive resource that teaches neuroanatomy with quantitative feedback. We present the AFIDs-Validator (validator.afids.io), an open-access, browser-based platform that pairs guided instruction with quantitative assessment. The platform combines (1) a learning mode in which a language-model neuroanatomy tutor operates inside an MRI viewer, giving anatomy-first instruction that responds to the learner's current image slice, orientation, and cursor position; and (2) a validation engine that accepts a learner's landmark file and returns per-landmark Euclidean error against expert-annotated references spanning 21 brain templates. To make the feedback interpretable, we analyzed 15,000 landmark annotations across 132 human subjects and found that landmark difficulty varies fourfold (median error ranged from 0.37 mm at the anterior commissure to 1.50 mm at the temporal horns) with heavy-tailed distributions at every landmark. These distributions are compiled into per-landmark reliability priors, so learners are scored against the empirical spread of trained raters rather than an arbitrary threshold, and difficult landmarks are not mistaken for poor performance. The AFIDs-Validator requires no installation, licensed software, or local data, and all code, reference data, and tutor design are openly released.

scientific communication and education↗

bioRxiv2026

A surface-intrinsic framework for topology-preserving hippocampal alignment and precision morphometry

Accurate alignment of hippocampal anatomy across individuals remains challenging due to complex and highly variable folding patterns that are not well captured by conventional volumetric approaches. HippUnfold introduced a surface-based representation of the hippocampus, but key components--including coordinate estimation and inter-subject correspondence--were defined in the volumetric domain, making them susceptible to topological errors and interpolation artifacts. Here, we introduce a surface-intrinsic formulation of hippocampal unfolding in which geometry, intrinsic coordinates, and correspondence are defined directly on subject-specific surface manifolds. Intrinsic anterior-posterior and proximal-distal coordinates are computed by solving Laplace equations on the surface, and correspondence is established through surface-based resampling in unfolded space, replacing inverse volumetric warping. Relative to the original HippUnfold approach, this formulation improves test-retest consistency, subject identifiability, and mesh quality, while better preserving subject-specific gyral and sulcal morphology. Surface representations show reduced distortion between folded and unfolded spaces and eliminate misplaced or outlier vertices associated with volumetric warping. These improvements translate to enhanced sensitivity in a clinical application, improving lateralization of temporal lobe epilepsy. These results demonstrate that a surface-intrinsic formulation provides a principled and robust foundation for hippocampal unfolding, enabling topology-preserving alignment and more accurate characterization of inter-individual variability in health and disease.

neuroscience↗

bioRxiv2026

APOE4 genotype and old age interact to impact cerebrovascular function, brain volume, and neuroinflammation in mice

Old age and the apolipoprotein E {varepsilon}4 (APOE4) genotype are two of the greatest risk factors for late-onset Alzheimers disease (LOAD). However, the interaction between these is poorly understood, as most preclinical studies use young mice. Therefore, we assessed the interaction between APOE genotype and age across a comprehensive set of cerebrovascular and related outcomes. We performed in vivo imaging, ex vivo cerebral artery studies, behavioral tests, and molecular analyses in male and female homozygous APOE3 and APOE4 mice at [~]6 months (young) and [~]24 months (old). APOE4 interacted with old age to lead to deficits in brain volume and greater microglia content. Old APOE4 mice also exhibited greater cerebral artery vasoconstriction to endothelin-1 (ET-1) than old APOE3 mice, a response concomitant with age-and genotype-related differences in the expression of ET-1 receptors and endothelin-converting enzyme. While we found several interactions between age and APOE genotype, only age impacted cognitive function, cerebral artery endothelial function, and arterial stiffness. In summary, we found that brain volume, neuroinflammation, and ET-1-related outcomes were influenced by the interaction of APOE genotype and age, while other outcomes were affected only by age. As such, an altered ET-1 response and greater neuroinflammation may contribute to the increased risk for LOAD in APOE4 carriers.

neuroscience↗

bioRxiv2026

Multiscale harmonization and semantic integration of biomedical data enable biological insights through immersive exploration

Single-cell atlassing efforts like the Human BioMolecular Atlas Program (HuBMAP) and the Cellular Senescence Network (SenNet) are producing multiscale datasets across the healthy, adult, human body, but this data is typically explored only on 2D screens with limited 3D affordances, even though understanding a cells location within a tissue, organ, and body requires reasoning across many orders of spatial magnitude. The Human Reference Atlas (HRA) provides standard terminologies and a Common Coordinate Framework (CCF) for harmonizing such data spatially and semantically. Building on the HRA Organ Gallery in virtual reality (VR) application, we present "HRA: Powers of Ten," which integrates, harmonizes, and visualizes biological data from these efforts immersively in VR using a Multiscale Elevator System that lets users descend, like riding an elevator through an inverted skyscraper, from a whole body view of 81 reference organs to datasets across 5 organs (lymph node, brain, large intestine, small intestine, liver), 5 assay types (CODEX, Visium, v-CyCIF, Xenium, SBF-SEM), and 4 spatial scales. Contributed by Data Providers, these VR scenes enable biological insights into senescence patterns, cellular neighborhoods, 3D tissue reconstruction, and subcellular liver architecture. A standard operating procedure supports adding further datasets. Freely available on the Meta Store to over 20 million headset owners, the application, data, and code are open-source.

bioinformatics↗

bioRxiv2026

Fault-tolerant 3D reconstruction from 2D spatial proteomics sections

Reconstructing 3D molecular volumes from sparsely sampled 2D tissue sections is limited by per-section marker dropout and tissue loss. We present 3D-Omics-Flow, a generative pipeline that jointly repairs damaged sections and interpolates between them at single-cell resolution. Across datasets spanning health and disease, 3D-Omics-Flow expands 3D spatial proteomics to practical sampling regimes, enabling atlas construction and downstream analysis from imperfect 2D section stacks.

bioinformatics↗

bioRxiv2026

LOESS and DE-SWAN can induce artifactual "waves" of molecular aging

A growing body of literature has investigated the relationship between age and biomolecular changes, leading to conclusions that aging occurs in discrete molecular "waves." Data summary tools such as LOESS and sliding window analyses like DE-SWAN are common approaches that have gained acceptance in recent years. We demonstrate via simple simulations that these tools can identify non-linear patterns of aging where they do not exist. Specifically, we show that (i) clustering of molecular trajectories using LOESS can lead to artifactual characteristic patterns of molecular aging, (ii) "waves" of aging identified using the combination of LOESS and DE-SWAN in real data are not robust to changes in the underlying age distribution and are not supported by valid permutation testing, and (iii) DE-SWAN alone can generate pronounced "waves" of nonlinear molecular aging in linear data due to differences in statistical power along the age continuum. Our results specifically challenge the statistical support for discrete aging crests inferred in the literature, but do not rule out nonlinear molecular aging or age-associated transitions that may be detectable using other cohorts and statistical models.

bioinformatics↗

bioRxiv2026

Butyrate preserves cardiac health during aging

Aging promotes left ventricular hypertrophic remodeling and diastolic dysfunction, yet interventions that preserve cardiac function when initiated late in life remain limited. Butyrate, a gut microbiome derived short chain fatty acid, can act as both a metabolic substrate and an epigenetic modulator, but whether long term supplementation improves cardiac resilience in advanced age and through which multicellular programs is unclear. Here we treated male C57BL/6J mice with sodium butyrate beginning at 18 months of age and maintained treatment to 28 months. Compared with age matched controls, NaBu treated aged mice exhibited reduced left ventricular mass and improved cardiac diastolic function. Left ventricular bulk proteomics revealed a coordinated aging signature characterized by increased extracellular remodeling and innate immune/complement/hemostasis pathways and decreased metabolic and proteostasis networks; NaBu partially opposed age associated proteomic shifts and identified a subset of proteins that reversed direction between aging and NaBu axes. Single nucleus multiome profiling further resolved cellular and regulatory programs associated with aging and NaBu response. Aging induced extensive chromatin remodeling with the strongest coupled RNA and ATAC changes in cardiomyocytes. In aged hearts, NaBu was associated with a consistent reduction of endothelial IFN and MHCI antigen presentation and adhesion programs across endothelial subtypes, with concordant decreases in both RNA and chromatin accessibility/gene activity at key loci, consistent with reduced endothelial inflammatory priming. Together, physiological, proteomic, and multiome data support long term NaBu as a late life intervention that attenuates age-associated cardiac remodeling and reshapes multicellular molecular programs in the aged heart.

molecular biology↗

bioRxiv2026

Quantification of domain-specific intrinsic capacity using mortality data

Functional health is centered on five domains of Intrinsic Capacity (IC): locomotion, cognition, vitality, psychological and sensory capacity. Therefore, measuring IC at the domain-specific level is the cornerstone for developing preventive interventions to help individuals preserve their independence. In this study, we used 63 clinical features from the UK Biobank to develop IC age, an 18-year mortality risk estimator that approximates an individuals biological age associated with the decline of each IC domain. By establishing proteomic surrogates of IC age, we find immune system activation across domains and provide a proteomic framework that may facilitate scalable monitoring of functional health decline.

systems biology↗

bioRxiv2026

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-omics profiling of 71 deeply phenotyped adults, integrating repeated assessments of diet, metabolome, gut microbiome, clinical laboratory measures, and inflammatory markers. Using gold-standard insulin suppression tests and machine learning-derived dietary patterns, we examined how dietary patterns relate to metabolic and microbial landscapes by insulin resistance status. Insulin-sensitive individuals exhibited stronger and more numerous diet-omics associations than insulin-resistant individuals, identifying metabolic flexibility as a central determinant of dietary responsiveness. Parabacteroides emerged as a candidate microbial mediator between refined carbohydrate-rich dietary patterns and host metabolic signatures. Integrated into a cardiovascular risk prediction model, diet, metabolites, microbial taxa, and immune markers each contributed to 10-year atherosclerotic cardiovascular disease risk. These findings show that inter-individual variation in cardiometabolic risk partly reflects differences in molecular responsiveness to habitual diet, informing precision nutrition and cardiovascular prevention.

molecular biology↗

bioRxiv2026

A scalable approach to resolving variants of uncertain significance

Over 90% of missense variants across [~]4,000 disease-associated genes are variants of uncertain significance (VUS). Experimental variant effect measurements provide critical evidence about pathogenicity and inform disease biology, but most variants lack data and clinical translation has been limited. The Impact of Genomic Variation on Function Consortium generated experimental data for 62,215 variants across ten genes using multiplexed assays and 1,407 variants across 163 genes using arrayed assays, curated 193,139 additional community-generated variant effect measurements across 30 additional genes, and developed automated calibration methods for translating experimental data and variant effect predictions into clinical evidence. To reduce current VUS, we developed a scalable workflow using only experimental and predictive evidence, enabling reclassification of 75% of the 16,115 VUS in these genes as pathogenic or benign with <1% error. To minimize future VUS, we analyzed >90,000 unobserved variants; 62% had enough evidence to be "preclassified" as pathogenic or benign. We validated our data, evidence and classifications using All of Us and created interactive resources to enable clinical use of the calibrated data. Thus, for 40 genes, representing 1% of the clinical genome, we resolve most existing VUS and future variants, illustrating how systematic use of scalable evidence can empower genomic medicine.

genomics↗

bioRxiv2025

Temporal Multi-Omic Analysis Uncovers Sex-Biased Molecular Programs Underlying Skeletal Muscle Adaptation to Endurance Training

BackgroundExercise training is known to benefit health and reduce disease risk. While skeletal muscle adaptations are fundamental to many of the health benefits of exercise training, the common and sex-specific molecular regulators that mediate these adaptations remain to be fully elucidated. MethodsTo this end, we leveraged skeletal muscle multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), where 6 month-old male and female rats endurance trained for 1, 2, 4, or 8 weeks. Our objective was to identify shared and sex-specific multi-omic molecular responses to endurance training in skeletal muscle, and relate them to phenotypic adaptations. ResultsWe identified largely sexually-conserved transcriptomic and proteomic pathway enrichments in the gastrocnemius, which correlated with skeletal muscle responses from a published exercise study in humans. We uncovered sex-consistent post-translational modifications, including decreased oxidation of MYH2 and deacetylation of the {beta}-oxidation enzyme HADHA. Pathway enrichment analyses revealed sex-specific remodeling across the acetylome, redox proteome, and phosphoproteome; females decreased mitochondrial protein cysteine oxidation and increased mitochondrial cristae proteins, indicative of enhanced redox buffering and mitochondrial efficiency. Despite decreases in cysteine oxidation of key mitochondrial proteins, females displayed increases in the cysteine oxidation of proteins involved in glucose catabolism relative to males after 8 weeks of training, suggestive of sex-biased subcellular reactive oxygen species generation. Males demonstrated earlier induction of mitochondrial transcripts and predicted activation of mTOR. Although the increase in mitochondrial protein abundance was more modest in males, there was greater oxidation of mitochondrial proteins in response to training compared to females. ConclusionsThis work shows a large portion of the adaptive response to endurance training in skeletal muscle is shared between females and males, while there are distinct and nuanced sex-specific adaptations that are evident, particularly at the level of post-translational regulation.

physiology↗

bioRxiv2025

Evolution of the rate, spectrum, and fitness effects of mutation under minimal selection in Caenorhabditis elegans

The rate, molecular spectrum, and fitness effects of mutations vary at all levels of the biological hierarchy, from within individual genomes to among taxonomic domains. Understanding the evolutionary factors underpinning that variation is of fundamental importance to biology. Accurate quantification of the properties of mutations requires that other evolutionary forces, especially natural selection, be minimized as much as possible. To investigate the evolution of the mutational process in C. elegans, we propagated a set of 100 "first order" mutation accumulation (O1MA) lines under minimal selection for [~]150 generations, divided each O1MA line into two "second order" MA (O2MA) lines and propagated them for another [~]150 generations, at which time the genome of each O2MA line was sequenced, and a subset of 50 O1MA families was assayed for competitive fitness. Over the course of the experiment, the mean nucleotide substitution mutation rate did not change, but the variance increased. In contrast, the indel mutation rate increased significantly. The two types of mutations fulfill the predictions of different theoretical models for the evolution of mutation rate. These results reinforce previous findings that the rate of indels is more sensitive to endogenous stress than the rate of nucleotide substitutions. Several evolutionary quandaries could be resolved if deleterious mutations interact synergistically (negative epistasis). Evidence for synergistic epistasis is famously inconclusive, although there is reason to think it may be more detectable under competitive conditions. However, a model of constant mutational effects on competitive fitness explains the results significantly better than a model including epistasis.

evolutionary biology↗

bioRxiv2025

APOE4 genotype negates the benefits of 17β-estradiol on cerebrovascular endothelial and mitochondrial function

BackgroundPostmenopausal females who carry an APOE{varepsilon}4 allele are at higher risk of late-onset Alzheimers Disease compared to age-matched APOE{varepsilon}4 males. Estrogen deficiency predisposes females to an increased risk of vascular, cognitive, and metabolic impairments. While estrogen and APOE genotype are known to impact metabolic and mitochondrial function in the brain, their cerebrovascular effects are less understood. Thus, the purpose of this study was to determine the interaction between APOE genotype and estrogen on cerebrovascular endothelial and mitochondrial function. MethodsYoung female homozygous APOE{varepsilon}3 and APOE{varepsilon}4 mice (n=19-20/group; ~6 months old) fed a high-fat diet were ovariectomized (OVX), OVX and supplemented with 17{beta}-estradiol, or left intact. ResultsIn APOE{varepsilon}3 mice, OVX was associated with impaired posterior cerebral artery endothelium-dependent dilation, which was rescued by 17{beta}-estradiol. However, in APOE{varepsilon}4 mice, there was no effect of OVX or 17{beta}-estradiol on cerebral artery endothelial function. Carotid artery passive stiffness was greater with OVX and lower with 17{beta}-estradiol treatment in APOE{varepsilon}3 mice, but there was no impact of OVX or 17{beta}-estradiol in the APOE{varepsilon}4 mice. In cerebral arteries and arterioles, mitochondrial complexes I and I+II respiration were lower in APOE{varepsilon}4 mice compared with APOE{varepsilon}3 mice. 17{beta}-estradiol led to higher mitochondrial complex I respiration in APOE{varepsilon}3 but not APOE{varepsilon}4 mice. These functional differences were concomitant with group differences in mitochondrial DNA copy number, antioxidant enzymes, and pro-inflammatory factors. In contrast to other outcomes, we found that 17{beta}-estradiol treatment was associated with lower cerebral artery stiffness in APOE{varepsilon}4 but not APOE{varepsilon}3 mice. ConclusionsOverall, these results indicate that the APOE genotype modulates the impact of estrogen on the cerebral vasculature. We found that 17{beta}-estradiol enhances cerebrovascular endothelial and mitochondrial function in APOE{varepsilon}3 mice but not in APOE{varepsilon}4 mice. The results suggest that 17{beta}-estradiol supplementation has more cerebrovascular benefit for APOE{varepsilon}4 non-carriers. Novelty & SignificanceO_ST_ABSWhat is known?C_ST_ABSO_LIFemales have twice the risk of Alzheimers disease compared with males, and the APOE4 genetic variant is associated with a greater risk for Alzheimers disease compared with the APOE3 variant. C_LIO_LIThe risk for Alzheimers disease increases after menopause in females, suggesting that the loss of female sex hormones may play a role. C_LIO_LIThere are highly inconsistent results among past studies examining the interaction of APOE genotype and estrogens on cognitive function and other brain outcomes. C_LI What new information does this article contribute?Vascular outcomes were not measured in previous studies examining the interaction between APOE genotype and estrogens. As such, we aimed to determine the impact of APOE4 genotype on the cerebrovascular response to estradiol. We found that estradiol improved cerebral artery endothelial function and mitochondrial respiration in APOE3 mice following ovariectomy. In contrast, APOE4 mice were refractory to the beneficial effects of estradiol on cerebrovascular endothelial and mitochondrial function. The broader implication of this research is that APOE genotype may be a consideration when prescribing hormone replacement therapy to menopausal females due to the impact on vascular outcomes.

physiology↗

bioRxiv2025

Comprehensive Characterization of the Promoter Proximal Proteome of Single Copy Locus FOXP2

Determining the proteins interacting with sequence-defined chromatin segments is a critical step in understanding gene expression and developing experimental interventions in the process. We used genetically targeted proximity labeling with dCas9-APEX2 to specifically biotinylate the promoter proximal proteome of the single copy locus FOXP2 in live HEK293 cells. To identify labeled proteins in a discovery-based manner, we utilized quantitative mass spectrometry. Specifically, online 2D-LC coupled directly to a tribrid mass spectrometer to enable real-time database searching synchronous precursor selection MS3 provided deep proteome coverage and accurate quantitation via isobaric tandem mass tags. We inferred 6,039 proteins from our sample using Proteome Discoverer and performed bioinformatic analysis on quantified proteins to identify 373 significantly enriched proteins at the active promoter (Storey-q<.05, FC>1.2). These proteins were enriched for transcription factors and components of the spliceosome. To validate our candidate transcriptional regulators, we utilized computationally predicted transcription factor binding and the >200 ChIP-Seq experiments performed in HEK293 cells by ENCODE. In addition to validating several candidate transcription factors as binders of the targeted genomic locus, we identify IRF2BP2 as a negative regulator of FOXP2 transcription.

genetics↗

bioRxiv2025

Single Cell Proteomics in the Developing Human Brain

Proteins are the functional effectors of virtually all biological processes, and accurately measuring their abundance and dynamics is essential for understanding development and disease. Although mRNA levels have historically been used as proxies for protein expression, growing evidence, especially from studies of the human cerebral cortex, has revealed widespread discordance between transcript and protein abundance. To directly address this limitation, we developed a rigorously optimized workflow that combines single-cell mass spectrometry with precise sample preparation to resolve, for the first time, quantitative proteomes of individual cells from the developing human brain. Our platform achieved deep proteomic coverage ([~]800 proteins per cell) even in immature prenatal human neurons (5-10 m diameter, [~]100 pg of protein per cell), capturing major brain cell types and enabling proteome-wide characterization at single-cell resolution. This approach revealed extensive transcriptome-proteome discordance across cell types, with particularly strong discrepancies in genes associated with neurodevelopmental disorders, a finding validated through orthogonal experiments. Proteins exhibited markedly higher cell-type specificity than their mRNA counterparts, underscoring the importance of proteomic-level analysis for resolving cellular identity and function. By reconstructing developmental trajectories from radial glia to excitatory neurons at the proteomic level, we identified dynamic stage-specific protein co-expression modules and pinpointed the intermediate progenitor-to-neuron transition as a molecularly vulnerable phase linked to autism. Altogether, by enabling single cell proteomics, this study establishes a foundational resource and technological advance for developmental neuroscience. It demonstrates that single-cell proteomics can capture critical developmental events and disease mechanisms that are undetectable at the transcript level. As this technology continues to improve in sensitivity and scalability, single-cell proteomics will become an indispensable tool for uncovering the molecular logic of brain development and for illuminating pathophysiological processes underlying neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

LINE-1 ORF1p is a shared and immunogenic antigen in cancer

BackgroundRecent clinical trials are beginning to show the potential for therapeutic cancer vaccines directed against tumor associated antigens. However, there is a limited set of well-defined antigens that are shared across tumors. Noncanonical coding elements in the genome that are usually silenced in normal cells potentially represent a rich source of "dark" antigens when expressed and presented to the immune system. LINE-1 elements are repetitive, virus-like genomic sequences that can copy themselves to new genomic loci, and which are reactivated in many cancers. In this study, we explore ORF1p, a protein encoded by LINE-1 elements, as a potential shared cancer vaccine antigen. MethodsWe assessed the tumor specificity of LINE-1 expression in large scale public RNA-seq data sets and in a curated database of public immunopeptidomics studies. We validated these findings using cell line and tissue data and performed an in vitro vaccination assay using healthy donor PBMCs to test the immunogenicity of ORF1p. ResultsWe found widespread RNA expression of LINE-1 across many tumor types with esophageal cancer showing the most highly elevated expression. We also found widespread MHC class I presentation of ORF1p-derived peptides in a range of tumor types, including esophageal cancer. We validated the tumor specific protein expression of ORF1p in a small set of 5 tumor, 5 matched normal, and 5 healthy esophageal samples. Finally, we demonstrated that dendritic cells pulsed with ORF1p peptides were able to induce interferon gamma production in healthy donor human T cells after repeated stimulation in vitro. ConclusionsWe present data demonstrating that dark antigens derived from LINE-1 elements are 1) expressed in a cancer tissue-specific manner, 2) detected in immunopeptidomics data (both publicly available and newly generated for this study) and 3) immunogenic in vitro. The tumor specificity and immunogenicity of ORF1p peptides point to their potential as a cancer vaccine antigen.

cancer biology↗

bioRxiv2025

Biomni: A General-Purpose Biomedical AI Agent

Biomedical research underpins progress in our understanding of human health and disease, drug discovery, and clinical care. However, with the growth of complex lab experiments, large datasets, many analytical tools, and expansive literature, biomedical research is increasingly constrained by repetitive and fragmented workflows that slow discovery and limit innovation, underscoring the need for a fundamentally new way to scale scientific expertise. Here, we introduce Biomni, a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. To systematically map the biomedical action space, Biomni first employs an action discovery agent to create the first unified agentic environment - mining essential tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains. Built on this foundation, Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning and code-based execution, enabling it to dynamically compose and carry out complex biomedical workflows - entirely without relying on predefined templates or rigid task flows. Systematic benchmarking demonstrates that Biomni achieves strong generalization across heterogeneous biomedical tasks - including causal gene prioritization, drug repurposing, rare disease diagnosis, micro-biome analysis, and molecular cloning - without any task-specific prompt tuning. Real-world case studies further showcase Biomnis ability to interpret complex, multi-modal biomedical datasets and autonomously generate experimentally testable protocols. Biomni envisions a future where virtual AI biologists operate alongside and augment human scientists to dramatically enhance research productivity, clinical insight, and healthcare. Biomni is ready to use at https://biomni.stanford.edu, and we invite scientists to explore its capabilities, stress-test its limits, and co-create the next era of biomedical discoveries.

bioinformatics↗