Biology subjects

Zhang, J.

Publications and source records attributed to Zhang, J..

At least 199 records · Page 11Linked to original sources

bioRxiv2026

Short T1 Fraction as a Marker of Myelin Content: Evidence from Postmortem MRI and Histology

PurposeTo investigate the short-T1 fraction as a potential biomarker of white matter myelin integrity, using myelin histology as ground truth. MethodsMulti-inversion-time MRI data were acquired from four postmortem brain hemisphere specimens from donors with Alzheimers disease on a clinical 3T scanner, and from five dissected tissue blocks containing white matter hyperintensities (WMHs) on a preclinical 3T system. Short-T1 fraction maps were generated using inverse Laplace transform to isolate short-T1 components and were compared with T2-based myelin water imaging metrics through joint T1-T2 correlation analysis. Short-T1 fraction maps from the tissue blocks were further compared with myelin-stained histology. In addition, in vivo short-T1 fraction data were acquired from two elderly volunteers with WMHs to demonstrate translational feasibility. ResultsPostmortem MRI revealed reduced short-T1 fractions in WMHs. T1-T2 correlation analysis showed that the short-T1 fraction was closely associated with the short-T2 (myelin water) component. Strong correlations were observed between short-T1 fractions and optical densities from both Luxol Fast Blue- and myelin basic protein-stained histological sections, supporting the link between the short-T1 signal and myelin content. Consistent findings were also observed in vivo, where significant reductions in short-T1 fractions were detected within WMHs. ConclusionThe short-T1 fraction correlated with myelin content in postmortem brain white matter, supporting its potential as a clinically translatable biomarker of myelin integrity.

neuroscience↗

bioRxiv2026

Metal Coordination Dynamics Governs Selective Epoxidation in Hyoscyamine 6β-Hydroxylase: Integrated Experimental and Computational Insights

Iron(II)- and 2-oxoglutarate-dependent (Fe(II)/2OG) enzymes catalyze a wide range of C-H bond activation and functionalization reactions and play essential roles in biosynthesis and metabolic regulation. Despite extensive mechanistic studies, the principles governing selectivity between canonical hydroxylation and alternative transformations remain incompletely understood. Here, we investigate the catalytic mechanism of hyoscyamine 6{beta}-hydroxylase (H6H), a Fe(II)/2OG-dependent oxygenase that sequentially catalyzes the 6{beta}-hydroxylation of hyoscyamine followed by 6,7-exo-epoxidation of 6{beta}-hydroxyhyoscyamine to generate scopolamine. Combined molecular dynamics and QM/MM calculations reveal that an inline Fe(IV)-oxo intermediate initiates hydrogen atom abstraction from the substrate C7 position. The resulting Fe(III)-OH species subsequently deprotonates the substrate hydroxyl group in a process coupled to substrate coordination to the iron center and an in-line-to-off-line rearrangement of the Fe(III)-OH moiety. This coordination dynamics machinery is further supported by the observed chlorination reactivity on the same substrate. Importantly, this coordination switch favors epoxide formation over hydroxyl rebound, thereby directing the reaction toward selective epoxidation. Further computational analysis of the L290F variant demonstrates that steric constraints imposed by L290 are essential for suppressing hydroxylation, revealing a bidirectional regulatory mechanism governing epoxidation/hydroxylation selectivity. Whereas iron coordination dynamics promote epoxidation reactivity, precise substrate positioning and protein-derived steric effects suppress the competing hydroxylation pathway. These findings are consistent with available experimental observations and establish metal coordination dynamics as a key determinant of selective C-H functionalization in Fe(II)/2OG enzymes.

biochemistry↗

bioRxiv2026

Toward Large-Scale Preclinical Neuroimaging: Quantifying Inter-Scanner Variability in Mouse Brain MRI

Multi-site MRI studies in preclinical neuroimaging are emerging, but unlike in human studies, characterization of inter-scanner variability remains limited. In this study, we assessed intra- and inter-scanner variability between two similarly equipped 7 Tesla MRI scanners using a phantom and ex vivo mouse brain specimens. Diffusion-weighted imaging revealed slight differences in gradient amplitudes between the scanners, while estimated apparent diffusion coefficient (ADC) values showed a coefficient of variation below 1.5% and inter-scanner differences below 2% near the magnet center. Volumetric analysis based on proton density-weighted images showed negligible intra-scanner differences across sessions, while inter-scanner volumetric differences were mostly less than 2% and spatially non-uniform across the brain. Quantitative maps of R1, R2*, and MTsat showed inter-scanner relative differences of less than 5%, 10%, and 20%, respectively, with white matter exhibiting greater variability than gray matter. These findings provide a foundation for future large-scale, multi-scanner preclinical neuroimaging studies.

bioengineering↗

bioRxiv2026

Excess p50 induces Arp1-dependent dynactin clusters containing the assembly factor VezA

Dynactin, a complex essential for cytoplasmic dynein function, contains an Arp1 mini-filament with a pointed-end sub-complex including Arp11 and a shoulder sub-complex including p50 and p150. We recently identified in Aspergillus nidulans a vezatin homolog VezA that enhances dynactin assembly, but VezA does not co-localize with dynactin, suggesting a transient interaction. It was found that overexpression of p50 separates the shoulder from the mini-filament and causes late-onset neurodegeneration in mice, but its cellular effects in the context of VezA need to be studied. Here we found astonishingly that p50 overexpression in A. nidulans causes Arp11, p50 (but not p150), and VezA to form co-localized clusters whose presence depends on Arp1. Formation of the VezA cluster also depends on Arp11, and VezA significantly enhances the intensity of Arp11-GFP clusters but not that of p50-GFP clusters. Moreover, an evolutionarily conserved region of p50 (aa17-25) forming a beta-sheet structure with Arp1 as revealed in previous cryo-EM studies is critical for the formation of Arp11, p50 and VezA clusters. These results suggest that excess p50 induces cluster formation driven by p50-Arp1 interactions, and that this assembly intermediate without the full shoulder traps VezA, which is involved in the Arp11-Arp1-p50 interactions.

cell biology↗

bioRxiv2026

Graph-based pangenome provides insights into the adaptive evolution of Cucurbita pepo

Understanding how crops respond to environmental variation is crucial for biodiversity conservation and food security. Cucurbita pepo (pumpkin, squash, gourd) is one of the first domesticated crop species and exhibits remarkable phenotypic and ecological diversity, making it a powerful system for investigating the genomic basis of adaptation. Here, we constructed a graph-based C. pepo pangenome using nine chromosome-level assemblies and identified 229,431 high-confidence structural variants (SVs) that were genotyped across 206 wild and cultivated accessions. Our results demonstrate that C. pepo underwent parallel domestication, with two deeply diverged gene pools independently giving rise to the pepo and ovifera cultivated lineages, followed by expansion into diverse environments that produced strong signatures of differentiation largely mediated by young adaptive alleles. Single-nucleotide polymorphisms (SNPs) and SVs contribute complementary dimensions of environmental responsiveness. Biogeographical modeling predicts continued range contraction of wild relatives and elevated genetic offset in Eastern North American populations under projected future climates. Populations with higher genetic load harbor fewer adaptive variants and exhibit greater predicted maladaptation, indicating that deleterious mutations constrain adaptive potential. These findings highlight how genomic variants, adaptive diversity, and genetic load together shape environmental adaptation and inform conservation and crop improvement.

genomics↗

bioRxiv2026

UcTCRp: a TCRβ-based framework for quantitative MAIT- and iNKT-associated repertoire-state profiling

MAIT and iNKT cells are conventionally identified using invariant or semi-invariant TCR chains, antigen-loaded tetramers, or transcriptomic phenotypes. These requirements limit their detection in public and clinical immune-repertoire datasets that contain only TCR{beta} sequences. Here we present UcTCRp, a TCR{beta}-only framework for profiling MAIT- and iNKT-associated repertoire states in bulk immune repertoires. UcTCRp integrates V-gene context and CDR3{beta} sequence features using a transformer-based representation pretrained on more than one million TCR{beta} sequences and supervised with curated cross-species MAIT, iNKT and conventional T cell references. The framework defines conserved model-informative TCR{beta} features, uses V-matched negative sampling to reduce germline-segment shortcuts, and generalizes across independent human and mouse datasets. In paired scRNA-seq/scTCR-seq datasets, UcTCRp recovered transcriptome-defined MAIT and iNKT cells and identified additional MAIT-like candidates supported by receptor evidence but missed by expression-only annotation. Bulk calibration against paired single-cell references and synthetic spike-in experiments established operating characteristics for repertoire-level abundance estimation. These results establish unpaired TCR{beta} repertoires as an actionable substrate for reconstructing unconventional T cell-associated immune states, enabling archived repertoire resources to be repurposed for systems-level studies of tissue immunity, disease and therapeutic response.

bioinformatics↗

bioRxiv2026

IID-KG: An ontology-aligned literature-derived knowledge graph for infectious and immune-mediated diseases

Infectious and immune-mediated diseases (IIDs) represent a broad and rapidly expanding biomedical literature domain in which scalable evidence extraction, disease ontology refinement, and interpretable knowledge integration are essential for biomedical discovery. We constructed an IID-specific biomedical knowledge graph (IID KG) from PubMed abstracts and PMC full-text articles by integrating nested named entity recognition, ontology-guided identifier assignment, full-text relation extraction, and relation-resolution strategies. A gold-standard corpus of 500 PubMed abstracts and 8 PMC full-text articles was manually annotated for nested biomedical entities across six entity types. The resulting models were applied to 30,128,068 PubMed abstracts and 1,385,500 IID-related PMC full-text articles. A unified IID ontology was developed from 411,341 disease terms using hierarchical text classification, large language model-based refinement, ontology cross-referencing, and expert review, yielding 179,657 confirmed MeSH mappings. The final IID KG contains approximately 1,837,513 unique entities and 16,295,390 unique relations across eight relation types. The resource was released publicly together with repurposing workflows, supporting ontology-aligned literature mining, disease mechanism analysis, and drug-repurposing hypothesis generation for IID research.

bioinformatics↗

bioRxiv2026

Understanding the emergence of the influenza A/H3N2 K subclade in its historical and evolutionary context

The emergence in 2025/26 of the influenza A/H3N2 K substrain (H3N2/K) was the cause of significant public health concern. This genetically divergent virus was assessed to have a strongly decreased reactivity to contemporary vaccine strains. Respectively prolonged and early influenza seasons in the Southern and Northern Hemispheres contributed to concerns about vaccine efficacy. Here we retrospectively assessed the genetic and antigenic properties of this virus, combining epidemiological surveillance data, computational antigenic analysis, and serological data using samples from a well-stratified UK cohort. In contrast to initial indications, we found that despite the genetic distinctiveness of H3N2/K the virus had undergone limited antigenic change, suggesting that its emergence was instead the result of selection for non-antigenic properties. We confirmed previous results showing that contemporary vaccines produced an enhanced neutralising response to H3N2/K but, in a stratified serological analysis, showed that responses to the J and K substrains were age-dependent, largely driven by patterns of vaccination. Our results have implications for antigenic surveillance and for public communication strategies in future influenza seasons.

evolutionary biology↗

bioRxiv2026

Genos-m: a foundation model for human-associated microbial genomes

Human-associated microbial genomes encode extensive strain-level diversity and niche-specific gene repertoires that are critical to host health. However, these complex sequence features remain difficult to capture using general-purpose DNA foundation models, highlighting the need for dedicated representation learning tailored to the human microbiome. Here, we introduce Genos-m, an open-source foundation model for human-associated microbial genome representation. Genos-m was pretrained on approximately 1.2 trillion nucleotide tokens from a curated microbial genome corpus, including human-associated prokaryotic isolates, high-quality metagenome-assembled genomes (MAGs) and bacteriophages, supplemented with GTDB species-level representative genomes to broaden prokaryotic taxonomic breadth. The model uses a sparsely activated Mixture-of-Experts (MoE) Transformer architecture, with 4.7 billion total parameters, approximately 330 million activated parameters per forward pass and a maximum context length of one million base pairs. We evaluated frozen Genos-m representations across short-sequence and gene-level tasks, biosynthetic gene cluster (BGC)-based regional sequence tasks, whole-genome strain phenotype prediction, and zero-shot transfer on prokaryote-related RNAfitness assays. Across these benchmarks, Genos-m consistently ranked among the leading comparison models, with the best performance in five of eight gene-fitness regression tasks and in BGC type classification. Using sparse autoencoders, we identified sparse features in Genos-m hidden activations that aligned with annotated ORFs, intergenic regions, and tRNA and rRNA loci. In downstream applications, Genos-m-derived genome-informed species representations in-corporated into a human microbiome self-supervised learning model improved colorectal cancer (CRC)-control classification over conventional species-abundance random forest models. Genos-m also generated stable sample-level embeddings from as few as 10,000 metagenomic reads, retaining gut microbial community structure that distinguished geographic origin and aligned with enterotypes defined from full-depth taxonomic profiles. Together, these results support Genos-m as a reusable representation model for microbial genomes and metagenomes, with conclusions bounded by the reported datasets, task definitions and evaluation protocols. Genos-m model weights, inference code, and usage documentation are publicly available on GitHub (https://github.com/BGI-HangzhouAI/Genos-m) and Hugging-Face (https://huggingface.co/BGI-HangzhouAI/Genos-m).

bioinformatics↗

bioRxiv2026

Dynamic visualization of physiological CaMKII activity using sensitive FRET biosensors

Calcium-calmodulin (CaM)-dependent protein kinase II (CaMKII) is a key mediator of complex physiological processes throughout the body, from the brain to the reproductive system, where CaMKII translates spatiotemporally dynamic calcium elevations into specific biological functions. Directly visualizing CaMKII activity dynamics in living cells using genetically encoded fluorescent biosensors can thus provide crucial insights into the molecular regulation of health and disease. Yet the ability to sensitively and specifically monitor endogenous CaMKII activity in physiologically relevant contexts is limited by the lack of sensors that can achieve robust, quantitative visualization of CaMKII responses. Here, we leveraged a recent serine/threonine kinome-wide substrate atlas to rationally engineer a powerful suite of Forster resonance energy transfer (FRET)-based CaMKII kinase activity reporters with high specificity, sensitivity, and signal-to-noise ratio. Using these biosensors, we were able to sensitively and robustly visualize endogenous CaMKII activity dynamics in both cultured cell lines and primary cells, including cardiomyocytes, oocytes, and neurons. We further utilized 2pFLIM imaging of organotypic hippocampal slices to quantitatively track LTP-induced CaMKII activity within single dendritic spines, highlighting a major advance in the study of physiological CaMKII signaling.

bioengineering↗

bioRxiv2026

A community machine learning challenge to predict the effects of gene perturbations on T cell differentiation for cancer immunotherapy

Perturbations of genes with functional importance in T cells could be used to change the distribution of CD8 T cell states to enhance anti-tumor functions for cancer immunotherapies. We launched a world-wide computational challenge to predict the effects of gene perturbations and to devise objective functions for prioritizing gene perturbations that lead to desired T-cell state distributions. We supported the challenge by generating a single-cell Perturb-seq dataset profiling the effect of knocking out 73 individual expert-defined genes in T cells transferred into a mouse melanoma model. We compared the top algorithms developed by participants, and found that performance was primarily determined by the prior data used for gene feature representation, with perturbational data derived features, proving most effective. Experimental validation of the top 61 genes nominated by the algorithms revealed that perturbation of Ndufv2 and Dimt1 reached the defined objective and biased T cell differentiation toward desired states.

bioinformatics↗

bioRxiv2026

Combined Checkpoint Inhibition Amplifies Post-Infarction Injury via T Cell-Mediated Macrophage Activation

BackgroundThis study aimed to investigate whether combined PD-1/CTLA-4 immune checkpoint inhibition predisposes the heart to a hyperinflammatory state, thereby exacerbating cardiac injury following acute myocardial infarction (MI), a critical unresolved question in cardio-oncology. MethodsMyocardial infarction was induced in Pd1-/-Ctla4+/- mice, a genetic model mimicking combined checkpoint inhibition. Key mechanistic insights were gained through in vivodepletion of CD8+ T cells (using anti-CD8a antibody) and pharmacological inhibition of the JAK-STAT1 pathway (using Tofacitinib). Cardiac function, structural injury, and immune responses were comprehensively assessed via echocardiography, flow cytometry, immunofluorescence, and molecular analyses. ResultsCompared to wild-type controls, Pd1-/-Ctla4+/- mice exhibited significantly increased post-MI mortality, worse cardiac function, and larger infarct size. Mechanistically, the aggravated injury was driven by an amplified infiltration of activated, IFN-{gamma}-producing CD8+ T cells, which activated the JAK-STAT1 pathway in macrophages, polarizing them towards a pro-inflammatory state. Depleting CD8+ T cells or inhibiting the JAK-STAT1 pathway effectively attenuated macrophage-driven inflammation and improved all aspects of post-MI injury. ConclusionsCombined PD-1/CTLA-4 blockade exacerbates post-infarction cardiac injury by promoting CD8+ T cell-mediated activation of macrophages via the JAK-STAT1 axis. This work elucidates MI as a context-dependent immune-related adverse event in ICI therapy and identifies CD8+ T cells and the JAK-STAT1 pathway as promising therapeutic targets for cardioprotection in these patients. RESEARCH PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study identifies acute myocardial infarction (MI) as a potential, context-dependent immune-related adverse event in the setting of combined PD-1/CTLA-4 checkpoint inhibition, shifting the paradigm beyond the classic focus on myocarditis. C_LIO_LIIt elucidates a novel pathogenic axis where combined checkpoint deficiency exacerbates post-MI injury specifically through CD8+ T cell-derived IFN-{gamma}, which activates macrophages via the JAK-STAT1 pathway. C_LI What Question Should Be Addressed Next?O_LIFuture studies should employ anti-PD-1/CTLA-4 monoclonal antibodies in wild-type or humanized mouse models to validate findings and better recapitulate the pharmacokinetics of clinical ICI therapy, strengthening translational relevance. C_LIO_LIThe long-term consequences of this primed inflammatory state on chronic cardiac remodeling, heart failure development, and the potential interplay with atherosclerosis warrant further investigation. C_LI

immunology↗

bioRxiv2026

Metabolic control of smooth muscle cell phenotype switching in atherosclerosis

The loss of smooth muscle cell (SMC) contractile phenotype contributes to various diseases including atherosclerosis. However, its metabolic basis is not entirely elucidated. Since the transforming growth factor beta (TGF{beta}) signaling is among principal regulators of SMC contractility, we studied metabolic regulation of TGF{beta} signaling in SMCs in vitro and atherosclerotic mouse models and human lesions. We found that TGF{beta} induced Ac-CoA synthetase 2 (ACSS2)-dependent Ac-CoA production, by suppressing pyruvate dehydrogenase kinase 4 (PDK4). This stabilized R-SMADs and TGF{beta} receptor 1, preserving SMC contractile phenotype. SMC-specific PDK4 knockout mimicked the effect of TGF{beta} signaling both metabolically and phenotypically, increasing glucose-derived synthesis of Ac-CoA and SMC contractile phenotype. SMC-specific Pdk4 knockout in ApoE knockout mice reduced atherosclerosis. Furthermore, human specimens demonstrated a strong correlation between PDK4 level and atherosclerosis severity. These findings indicate that continuous TGF{beta} signaling, critical to the maintenance of the normal SMC contractile state and is regulated by PDK4 and carbohydrate metabolism. TeaserReducing PDK4 metabolically restricts aortic plaque growth via TGF{beta}-dependent SMC contractility.

cell biology↗

bioRxiv2026

Cryopreservation of brain organoids - a tool for on-demand organoid banking

Cryopreservation offers an option for long-term storage and global distribution of complex in vitro models, yet protocols for multicellular microphysiolgocial systems (MPS) such as brain organoids/spheroids remain limited. Here, we systematically compared three commercially available cryopreservation (mFreSR, CryoStorCS10, and 3dGRO) and two freezing time points, and established a robust workflow for freezing and recovering brain organoids. After defrosting, we assessed morphology and metabolic activity. We also evaluated electrophysiology, calcium transients, and neurite outgrowth. In addition, we measured astrocyte migration, apoptosis, mitochondrial integrity, microglia survival, and neural marker expression. We found that organoids require a 4-week recovery period to regain structural and functional stability. Although organoids frozen at week 6 showed higher metabolic activity after recovery, organoids cryopreserved at week 2 had clearly better functional outcomes. They exhibited stronger spontaneous network firing and maintained calcium transients. Finally, incorporated microglia-like cells survived the freezing and displayed comparable morphology to unfrozen controls. Across the endpoints measured here, 3dGRO showed the most favorable overall performance; formal ranking across media awaits harmonized normalization, single-organoid electrophysiology, and prespecified QC thresholds. Together, these results define a practical and reproducible cryopreservation strategy that preserves key physiological features of brain organoids and supports the establishment of ready-to-use organoid banks. The ability to reliably store and distribute complex brain-like tissues represents an essential step toward global standardization, scalable experimentation, and wider adoption of human-relevant microphysiological systems. Together, these results demonstrate recovery of key physiological features in the subset of organoids that remain viable after thaw and support the feasibility of brain organoid banking.

cell biology↗

bioRxiv2026

Spatiotemporal Transcriptomic Dissection Uncovers Age-Dependent Deceleration of Esophageal Cell Differentiation

Precise orchestration of stem and progenitor cells is essential for tissue homeostasis and regeneration but becomes dysregulated during aging. Despite the known markers, the age-related dynamics of esophageal epithelial cell lineages remain unclear. Using single-cell single cell transcriptomics, we analyzed human esophageal epithelia across different age groups. We identified two stem cell populations: quiescent (qeSCs) and proliferative (peSCs) esophageal stem cells. qeSCs from young donors showed higher WNT10A expression and Wnt signaling activity. Analysis of cell lineage trajectories combined with cell plastic potentials showed stronger connectivity between peSCs and differentiated cells in younger tissues, indicating more efficient and rapid epithelial turnover and homeostatic maintenance. Cell-cell interaction analysis further demonstrated that NOTCH signaling is more prominent within peSCs and qeSCs in younger esophagi, whereas in older tissues, NOTCH activity is preferentially retained in differentiated cells. Additionally, the inflammatory signaling, Interleukin-1 pathway, is more active in younger esophagi but is largely restricted to differentiated cells. Our findings suggest that age-related decline in esophageal homeostasis is primarily driven by impaired differentiation dynamics rather than by alterations in stem cell self-renewal capacity.

cell biology↗

bioRxiv2026

Subcortical recruitment dissociates isoflurane emergence from distinct wakeful states in mice

Emergence from general anesthesia, defined by a recovery of consciousness to the wakeful state, is a clinically consequential state transition that remains a passive process dependent on drug clearance. Despite the critical use of anesthesia, the neural circuitry underlying behavioral recovery remains poorly defined. Here, we map whole-brain neural activity during emergence from isoflurane anesthesia in mice using Fos immunolabeling, tissue clearing, and light-sheet microscopy. This approach enables unbiased quantification of neural activity at cellular resolution across the intact whole brain and supports subsequent network analysis. Rather than resembling wakefulness, emergence exhibits widespread cortical suppression alongside selective activation of discrete subcortical nuclei. This pattern of activity includes both previously implicated arousal-related regions and lesser-studied structures linked to respiratory, autonomic, interoceptive, and cerebellar function. By comparing emergence to two behaviorally distinct wakeful control states, we find that control state selection substantially shapes interpretation of whole-brain activity maps. This establishes dual-state comparisons as a broadly useful strategy for state-dependent circuit mapping. Functional network analysis further elucidates candidate central regions that strongly covary together during emergence, with the most integrated region being the ventral orbital cortex. This approach allows for targeted causal investigation, linking brain-wide circuit discovery with future hypothesis-driven mechanistic interrogation. Together, we find that emergence from isoflurane anesthesia reflects selective subcortical recruitment rather than broad global reactivation toward wakefulness. Significance StatementMillions of people undergo general anesthesia each year. While anesthetic unconsciousness is induced rapidly, emergence from altered consciousness is unpredictable. Neural mechanisms that underlie behavioral emergence remain poorly defined. Using whole-brain Fos mapping at cellular resolution, we found that emergence from isoflurane anesthesia is characterized by widespread cortical suppression alongside selective activation of discrete subcortical, autonomic, hindbrain, and cerebellar nuclei. This selective systems-level activity pattern identifies behavioral emergence as more than a simple global return toward wakefulness and highlights underappreciated neural circuitry involved in post-anesthetic recovery. Network analysis of the Fos maps further identifies candidate regions for targeted causal investigation of emergence-related regions.

neuroscience↗

bioRxiv2026

BioGAIP: A Scalable, User-Friendly and Robust LLM-Powered Multi-Agent System for Automated Bioinformatics Tasks

The rapid explosion of large-scale, high-throughput biological data has created an urgent demand for efficient analysis pipelines. Traditional bioinformatics approaches, while powerful, often require specialized computational expertise, placing them out of reach for bench biologists. Large Language Models (LLMs) offer new possibilities for automating complex reasoning and tool integration, yet existing LLM-based solutions have not sufficiently lowered this barrier, and expert-level analysis remains inaccessible to most nonexperts. Here, we present BioGAIP, an LLM-powered agent that integrates expert-level reasoning within an end-to-end platform for bioinformatics tasks. By coupling optimized autonomous agents with full graphical interfaces, BioGAIP transforms complex analytical workflows into an automated, user-friendly, and low-intervention process with natural language input. Key features of BioGAIP include dynamic information retrieval, automatic environment configuration, and self-directed design of analysis pipelines, making large-scale multi-omics analysis highly accessible. Built on agent-based client-server architecture, BioGAIP ensures secure resource management and supports heavy computational demands. Extensive evaluations on diverse published datasets demonstrate that BioGAIP reliably recapitulates established biological insights and shows strong potential for novel discovery. By democratizing complex bioinformatics workflows, BioGAIP accelerates accessible data-driven discovery for both experts and nonexperts.

bioinformatics↗

bioRxiv2026

TRMT6/61A-mediated m1A methylation facilitates human pre-tRNA maturation and prevents surveillance by XRN2

Transfer RNAs (tRNAs) are dynamically regulated by RNA modifications. The conserved TRMT6/61A catalyzes m1A (N1-methyladenosine) deposition at position 58. While TRMT6/61A dysregulation is linked to human diseases, its downstream processing consequences and molecular surveillance mechanisms remain unclear. Here we demonstrate that TRMT6/61A installs m1 A on precursor tRNAs prior to processing. Utilizing a dTAG rapid depletion system, we show that acute loss of TRMT6/61A swiftly reprograms the human tRNAome. Although elongator tRNA fluctuations are buffered by isodecoder redundancy, hypomethylated tRNAiMet is selectively and rapidly degraded by the exoribonuclease XRN2, reducing global protein synthesis and activating ATF4 expression. Furthermore, m1A58 is a prerequisite for tRNA end processing; its absence leads to the aberrant accumulation of unprocessed pre-tRNAs and disrupted tRNA-derived fragment (tRF) populations. Mechanistically, TRMT6/61A facilitates in vitro RNase Z cleavage, likely by promoting proper pre-tRNA folding. Lastly, XRN2 inhibition rescues tRNAiMet levels and reverses growth defects, identifying the XRN2-mediated surveillance of tRNAiMet as a primary driver of the cellular pathology. Collectively, our results uncover a pivotal role for TRMT6/61A-dependent m1A in human tRNA maturation and define the molecular checkpoints essential for translational homeostasis.

genetics↗