Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Molecular origins of heterogeneous aging and spatial organization in RNA condensates

The molecular origins of aging of biomolecular condensates, which play a central role in cellular organization, is poorly understood. Here, we use coarse-grained molecular simulations to investigate how RNA sequence and chain connectivity govern condensate aging over extended timescales. Condensates formed by CAG-repeat RNA undergo pronounced aging characterized by progressive dynamical slowing, loss of ergodicity, and the emergence of two distinct relaxation timescales. Aging proceeds heterogeneously in space, giving rise to a dynamically arrested, solid-like core surrounded by a more fluid shell. We demonstrate that aging is driven by sequence-encoded base pairing that favors RNA expansion, alignment and the formation of a dense interchain interaction network. These structural changes lead to increased topological entanglement, stabilizing long-lived conformations and reinforcing dynamic arrest in the condensate interior. Strikingly, a scrambled sequence with identical composition remains largely liquid-like. Our results establish RNA sequence patterning as a key determinant not only of phase separation but also of condensate aging and spatial organization. These findings provide a molecular framework for understanding the persistence and solidification of repeat RNA assemblies observed in diseases and suggest general physical principles by which entangled polymer networks drive aging in biomolecular condensates.

biophysics↗

bioRxiv2026

Multiple Particle Tracking via Velocity Filtering (MPT-vVF): a velocity filtering framework for robust tracking moving organelles in living cells

Living cells are highly dynamic and densely crowded environments in which organelles such as vesicles undergo continuous motion that is essential for cellular processes. Therefore, accurate tracking of individual organelles is crucial for understanding intercellular dynamics and functions. However, precise tracking of individual organelles in living cells remains challenging due to high organelle densities, frequent particle overlap, and the coexistence of stationary and motile organelles. In particular, stationary organelles can obscure the trajectories of moving organelles, leading to tracking errors and fragmented tracks. To overcome these challenges, we developed Multiple Particle Tracking via Velocity Filtering (MPT-vVF), an unbiased, semi-automated tracking framework that incorporates a mathematically derived velocity-filtering algorithm to selectively identify and track moving organelles with high accuracy in crowded intracellular environments. MPT-vVF integrates denoising, background subtraction, and a velocity-matching detection step that discriminates true particle motion from noise based on spatiotemporal continuity, followed by robust trajectory linking. We demonstrate that MPT-vVF can accurately resolve nanometer-scale displacements of immobilized beads, highlighting its high tracking precision. We also validate the robustness of MPT-vVF by quantifying the transport of brain-derived neurotrophic factor (BDNF)-mRFP-containing vesicles in living hippocampal neurons. Furthermore, MPT-vVF reveals that exposure to 50-nm nanoplastics impairs vesicular transport, reducing both travel length and speed of BDNF-containing vesicles in living neurons. These findings establish MPT-vVF as a powerful method for quantitative analysis of intracellular organelles in crowded living cells and suggest its broad application to biophysics, cell biology, and soft matter research.

biophysics↗

bioRxiv2026

In situ Discovery of Immune Repertoire Reveals Antitumor Immunity and Therapeutic Antibodies

Spatial transcriptomics offers a glimpse into the immunology of tissues. However, limitations in spatial transcriptomics preclude the detection of highly diverse, low-abundance, and previously unknown sequences, including immune repertoires and microbiota. Here, we introduce Archimap, a spatial transcriptomic platform that simultaneously profiles spatial transcriptomes, immune repertoires, and microbiota from formalin-fixed paraffin-embedded (FFPE) tissues. Using Archimap, we profile the spatial localization of TCRs, BCRs, and the microbiota landscape in archived clinical tissues at single-cell resolution. Through comprehensive benchmarking, we validate Archimaps performance and fidelity. Archimap in situ assembles the immune complex and reconstructs the clonal evolution of antibodies. Together, Archimap shows the power of in situ discovery of functional immune repertoires for their antitumor immunity.

bioinformatics↗

bioRxiv2026

Cytokinesis Arrest-induced Binucleation of Macrophages ProducesHighly Efficient Efferocytes

Efferocytosis, the phagocytic clearance of dying cells and debris, supports tissue homeostasis, immune tolerance, and inflammation resolution, whereas its failure contributes to autoimmunity, atherosclerosis, aging, and impaired tissue repair. Although many molecular regulators of efferocytosis have been defined, less is known about whether macrophages can be reprogrammed into a distinct cellular state with intrinsically enhanced efferocytosis capacity. Guided by a CRISPR screen, we found that Pdcd6ip loss induces cytokinesis arrest and binucleation, creating macrophages with superior efferocytic function. Binucleated Pdcd6ip-/- bone marrow-derived macrophages demonstrate a coordinately enhanced multi-corpse capture and processing, and resolution response, and acquired a distinct transcriptomic signature. In vivo, Pdcd6ip deletion enhanced splenic macrophage efferocytosis, reduced autoimmune responses after repeated apoptotic cell challenge, and promoted plaque stability without metabolic or hematologic changes. PDCD6IP perturbation similarly increased binucleation and engulfment in human macrophage-like cells. Thus, incomplete cytokinesis represents an unrecognized route to macrophage specialization with enhanced efferocytosis capacity.

cell biology↗

bioRxiv2026

siDiff: De Novo siRNA Design via Efficacy-Guided Discrete Masked Diffusion

Target-conditioned de novo siRNA design requires capturing both target mRNA binding context and internal siRNA sequence-activity rules. Traditional computational pipelines predominantly rely on discriminative prediction models that rank pre-filtered candidate pools. However, these approaches struggle with generalization on novel target genes and often overlook potent candidates due to dataset size constraints and motif overfitting. To reconcile generation precision with sequence diversity, we propose siDiff, an efficacy-guided discrete diffusion framework for target-conditioned de novo siRNA design. siDiff pairs a discrete-masked diffusion transformer--which models the underlying sequence distribution over functional duplexes--with a mask-robust efficacy guidance model. During inference, we introduce a biology-aware, three-stage sampling mechanism that performs structural candidate filtering, dynamic unmasking guidance, and cluster-aware redundancy mitigation. This dual mechanism enables the diffusion process to explore broad sequence spaces while the efficacy model prevents distributional shift toward non-functional candidates. Extensive experiments across four datasets, including the public Takayuki benchmark and three curated patent datasets, demonstrate that siDiff significantly outperforms state-of-the-art discriminative baselines and discrete diffusion models, achieving relative hit-rate improvements of over 30% and demonstrating superior generalization on out-of-distribution gene targets. The source code and related materials are available at https://github.com/cybericha/siDiff.

bioinformatics↗

bioRxiv2026

Stability of c-Myc protein differentiates Ras oncogene addiction and MAPK pathway dependency in Ras-mutant multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy that frequently harbors activating mutations in NRAS and KRAS oncogenes. Previous clinical trials targeting the Ras/MAPK oncogenic pathway with MEK inhibitors (MEKi) were met with limited efficacy, and newer generation of Ras inhibitors (RASi) have not been specifically evaluated in MM patients. To investigate the vulnerabilities of Ras-mutant MM to targeted therapies, we examined the sensitivity of a panel of human MM cell lines to the RASi RMC-6236 (daraxonrasib) and the MEKi trametinib. Although Ras-mutant MM cells are responsive to oncogenic Ras signaling and are sensitive to RAS inhibition, their sensitivity to MEK inhibition is heterogeneous. Mechanistic studies revealed that c-Myc protein is destabilized by MEK inhibition only in MEKi-sensitive MM cells but not in MEKi-resistant cells, and pharmacological and genetic stabilization of c-Myc is sufficient to confer MEKi resistance. In contrast, Ras inhibition reduced c-Myc protein across all MM cell lines tested, regardless of their dependency on the MAPK pathway, and c-Myc expression was insufficient to promote RASi resistance. Together, these findings demonstrate that c-Myc protein stability differentiates the response of Ras-mutant MM cells to Ras and MEK inhibition, and suggest that direct targeting of the Ras oncoprotein, rather than its downstream MAPK pathway, may present a more effective strategy.

cancer biology↗

bioRxiv2026

Repurposing the Antiviral Agent Pibrentasvir: In Vitro Synergistic Effects in Combination with Different Azole Antifungal Agents

ObjectiveTo investigate the combined effects of multiple drugs and provide more therapeutic options for invasive fungal infections, this study evaluated the in vitro susceptibility of Aspergillus spp., Candida auris, Cryptococcus neoformans, and Exophiala dermatitidis to pibrentasvir (PIB) in combination with itraconazole (ITR), voriconazole (VOR), posaconazole (POS), or fluconazole (FLU). MethodsAccording to the M27-A3 and M38-A2 guidelines established by the Clinical and Laboratory Standards Institute (CLSI), the in vitro antifungal activities of PIB combined with ITR, VOR, POS, or FLU against 78 clinical isolates, including Aspergillus spp., E. dermatitidis, C. auris, and C. neoformans, were determined. The minimum inhibitory concentrations (MICs) and fractional inhibitory concentration indices (FICIs) were calculated to evaluate the synergistic effects. ResultsPIB alone exhibited no antifungal activity. Significant synergistic effects were observed when PIB was combined with azole antifungal agents. The PIB-POS combination showed synergistic effects against Aspergillus spp. (27/41, 65.90%), C. auris (9/10, 90.00%), C. neoformans (2/9, 22.20%), and E. dermatitidis (11/18, 61.11%). The PIB-ITR combination also showed synergistic effects against Aspergillus spp. (18/41, 43.9%), C. auris (9/10, 90.0%), C. neoformans (2/9, 22.2%), and E. dermatitidis (10/18, 55.5%). Synergistic effects were less frequently observed with the PIB-VOR or PIB-FLU combinations, and no antagonistic effects were observed. ConclusionThis study demonstrates that PIB acts as an azole sensitizer, with the strongest synergistic effects observed when combined with POS or ITR, providing a new research direction for combination therapy against invasive fungal infections.

microbiology↗

bioRxiv2026

The solid tumor microenvironment changes the hierarchy of CD155 and CD112 receptors, shaping checkpoint blockade outcome

Reproducing a physiologically relevant tumor microenvironment in vitro is essential for developing effective immunotherapeutic treatments. By integrating the use of combinatorial receptor blockade and organoid models we provide a deep functional understanding of CD155 and CD112 receptors in solid tumors and their impact on cellular immunotherapy and infiltration. CD226 showed plasticity in response to the environment, being able to switch between CD155 and CD112 depending on the ligand availability. In addition, CD226 drove NK cell infiltration into tumor tissues via CD155 and CD112 ligation, with CD226-CD112 interaction specifically promoting migration from the periphery to the core. Downregulation of CD155 and TIGIT induced by the tumor microenvironment and previous drug exposure reduced the long-term efficacy of TIGIT blockade. Taken together, our findings point towards using CD112R blockade in primary tumors to simultaneously enhance NK cell killing activity and promote infiltration into the tumor core via CD226 and CD112 interaction. ONE SENTENCE SUMMARYTumors shape the hierarchy of CD155-CD112 receptors, reducing TIGIT blockade efficacy, while CD226 drives NK infiltration and shows binding plasticity

immunology↗

bioRxiv2026

The Capillary endothelial cell-governed niche sustains angiogenesis in proliferating infantile hemangioma via multilayer stromal support

Infantile hemangioma (IH), the most common benign vascular tumor in infants, is characterized by the aberrant proliferation of hemangioma endothelial cells (HemECs) and excessive angiogenesis. However, it is unclear how the tumor microenvironment sustains these active angiogenic signals. We performed single-cell RNA sequencing and spatial transcriptomic to profile 30 samples from proliferating IH, involuting IH, and normal skin. The results indicated that HemECs comprised distinct subpopulations. Among them, capillary endothelial cells (Cap.ECs) had an immature phenotype and functioned as the core drivers of IH. The endothelial-to-mesenchymal transition endothelial cells (endoMT-ECs) secreted collagen and engaged in CD44-mediated crosstalk with Cap.ECs to construct the angiogenesis-active niche in the tumor microenvironment (TME) of proliferating IH. Blockade of CD44-mediated intercellular communication effectively suppresses the angiogenesis of HemECs and promotes tumor regression. Beyond the endothelial layer, pericytes tightly enveloped Cap.ECs, with SERPINE2+ subtypes sustaining their angiogenic activity via ANGPT signaling. Pseudotime trajectory analysis revealed that the mesenchymal stem cells (MSCs)-enriched niche serves as a progenitor pool for Cap.ECs in proliferating IH. Our findings thus revealed that IH progression relies on CD44-mediated endoMT-EC-Cap.EC crosstalk and on both pericyte and MSC niches to sustain angiogenesis. HIGHLIGHTSO_LICapillary endothelial cells drive infantile hemangioma progression, with pericytes tightly ensheathing them. C_LIO_LICD44-mediated capillary and endoMT-derived endothelial cells crosstalk construct the angiogenic-active niche in the tumor microenvironment of proliferating infantile hemangioma. C_LIO_LIThe MSC-enriched niche provides a progenitor pool for the capillary endothelial cells in proliferating infantile hemangioma. C_LI

cancer biology↗

bioRxiv2026

Diatoms maintain metabolic activity in deep ocean twilight zones

Phytoplankton are primarily confined to the sunlit epipelagic zone, yet intact algal cells persist in the oceans mesopelagic twilight zone where light is minimal. However, their survival strategies in the deeper ocean remain unknown. Here, we isolate Chaetoceros sp. DS1 from 1000 m depth and reveal its survival mechanisms under prolonged darkness and high pressure, including membrane lipid remodeling and enhanced antioxidant defenses. Importantly, DS1 maintains a latent photosynthetic reserve that activates upon exposure to dim blue light and higher pressure typical of the twilight zone, enabling photosynthesis and nutrient uptake. It exhibits metabolic flexibility by utilizing stored carbon in darkness and assimilating organic carbon under dim light. Global meta-omics data show widespread, transcriptionally active Chaetoceros-like diatoms in the twilight zone, expressing blue-light sensors and protein synthesis genes. These findings identify the ocean twilight zone as a previously overlooked niche for metabolically active phytoplankton, expanding understanding of deep-ocean microbial ecology and carbon cycling.

ecology↗

bioRxiv2026

Graph in Graph (GiG): A novel graph AI framework for integrating and interpreting whole-person healthmedical and omics data

Medical records and omics data are rapidly becoming standard in healthcare settings, which characterize the whole-person from dysfunctional molecules to phenotypes, and thus offer potential for precise disease diagnosis and target discovery. Whereas, it remains an open problem to systematically integrate and interprete medical record and omics data of individual patients. In this study, for the first time, we propose a novel graph AI model framework, Graph in Graph (GiG), to integrate and interpret the whole-person medical and omic datasets. Specifically, the medical record data is modeled using a person-phenotype graph, followed by omics signaling graphs of invidival patients, which enables the integration of information learned from omic-signaling graph and medical phenotype features to characterize individual patients and to prioritize important omic biomarkers and phenotypes. As an exploratory study, we applied and evaluated the GiG model to study the type 2 diabetes (T2D) and pre-T2D vs healthy using the Long Life Family Study (LLFS) cohort, which enrolls families with exceptional longevity to uncover biological mechanisms of healthy aging with medical and omics data. The evaluation results showed that GiG not only achieve a high prediction but also can interpret the prediction by ranking the essential clinical and omic biomarkers. The GiG framework can be applied to other studies by effectively integrating and interpreting medical and omic datasets for disease diagnosis and pathogenesis discovery.

bioinformatics↗

bioRxiv2026

MetaClaw: an auditable AI agent for end-to-end, multi-directional metagenomic and multi-omics analysis

End-to-end omics analysis requires more than selecting tools: a usable agent must bind data correctly, execute long workflows without blocking, preserve provenance and recover the biological conclusions that motivate an analysis. Existing LLM-driven bioinformatics agents automate parts of this process, but their operational dependencies and conclusion-level validity are often unclear. Here we present MetaClaw, an auditable agent that maps a user request to a registered workflow, executes standardized upstream processing on FlowHub, and runs study-specific downstream analyses in network-isolated OpenClaw containers. A YAML registry and an explicit plan-submit-poll-finalise lifecycle record file bindings, parameters, scripts, environments and outputs in per-job bundles. Across the full cohorts of four published studies (769 metagenomic profiles), MetaClaw recovered 4/4 sorghum marker groups, 3/3 RRMS features, 4/5 canonical CRC markers among the top 20 classifier features and 5/5 permafrost marker groups. In 45 model-by-prompt runs, upstream completion was consistent whereas downstream validity depended on the backend and instruction detail; three decoy-tested endpoints showed no significant differences. In 48 ablation sessions, removing the registry, planning loop or manifest caused distinct losses, with registry removal increasing time, tool calls and token cost. MetaClaw therefore connects standardized upstream execution, local analytical flexibility and conclusion-level validation in a rerunnable framework for metagenomic and microbiome multi-omics analysis.

bioinformatics↗

bioRxiv2026

Large-scale functional coupling and computational modelling reveal frontotemporal hotspots in distributed network connectivity during working memory recognition, encoding, and retrieval

Working memory depends on coordinated activity across distributed brain networks, but how these interactions support recognition, encoding, and retrieval remains unclear. Here, we analyzed intracranial local field potentials from 1,652 sites in 36 epilepsy patients performing a naturalistic card-matching task. Phase-amplitude and phase-phase coupling revealed widespread condition-dependent interactions, with frontal and temporal regions emerging as recurrent network hubs. Event-related analyses showed reproducible within-trial coupling dynamics across participants. Directed phase transfer entropy further identified frequency-specific information flow, including frontal regions acting as a theta-band source and an alpha-band sink. Finally, a time-delay-embedded hidden Markov model identified task-locked latent states with condition-dependent occupancy trajectories and distinct coherence profiles. Together, these results suggest that working memory is implemented through dynamic, directionally organized large-scale networks, in which frontotemporal hubs coordinate flexible transitions among distributed neural states rather than operating in isolation.

neuroscience↗

bioRxiv2026

MGM2 as a Unified Foundation Model for Microbiome World Exploration

Microbiomes are information-rich biological systems, yet most computational analyses still reduce communities to cohort-specific abundance tables. Here we introduce MGM2, a multimodal foundation model pretrained on 1,821,291 MicrobeAtlas samples and 225,067 OTUs clustered at 99% sequence similarity. MGM2 couples NTv3-derived microbial sequence embeddings with abundance conditioning and community-semantic alignment to learn transferable sample- and token-level representations. Frozen MGM2 representations outperformed DeepPhylo by 0.06-0.21 macro-AUROC across five temporally held-out MGnify hierarchy levels, with the largest gains for rare and fine-grained labels. In fecal microbiota transplantation, MGM2-XLarge achieved a response ROC AUC of 0.79 and reduced post-transplant Bray-Curtis distance by 15% relative to the recipient baseline. The same representation supported ASV-level trend forecasting across 24 wastewater treatment plants. Sparse autoencoder analysis resolved MGM2-XLarge token states into a 4,096-feature dictionary spanning taxonomic identity, abundance state, ecological context and technical variation. MGM2 therefore provides a sequence-aware and interpretable representation layer for microbiome classification, paired-community prediction, forecasting and feature discovery. Highlights[bullet] MGM2 integrates sequence, abundance and community semantics through pretraining on 1.82 million microbiome samples. [bullet]Frozen MGM2 improved macro-AUROC over DeepPhylo by 0.06-0.21 across five temporally held-out MGnify levels. [bullet]MGM2-XLarge reached a response ROC AUC of 0.79 and reduced post-FMT Bray-Curtis distance by 15%. [bullet]A 4,096-feature sparse autoencoder atlas resolves taxonomic, abundance, ecological and technical signals.

bioinformatics↗

bioRxiv2026

DNA-Programmed Condensate-Membrane Wetting and Cellular Internalization

Deformable condensates offer dynamic interfaces for biomolecule delivery, yet membrane adhesion does not necessarily lead to cellular internalization. The physical transition that determines whether a membrane-bound soft material remains surface-anchored or proceeds through wetting towards productive uptake remains poorly understood, particularly at active living-cell membranes. Here, we engineer sequence-defined DNA condensates through liquid-liquid phase separation (LLPS) and program their interfacial behavior by tuning sticky-end valency and cholesterol organization. These molecular designs precisely regulate condensate fluidity, fusion dynamics and internal organization, generating distinct states of weak contact, persistent anchoring and rapid wetting. Increasing cholesterol-mediated affinity does not enhance uptake. Instead, productive internalization emerges from a balance between membrane adhesion and condensate fluidity and deformability. Native membrane composition further modulates condensate interfacial fate across mammalian cells and plant protoplasts. DNA condensates enrich and deliver CpG ODNs, mRNA ([~]2000 nt) and proteins, while cargo loading experiments reveal that preserving condensate architecture is essential for functional delivery. Our findings identify wetting competence as a design parameter for controlling soft material engagement and cellular entry.

biophysics↗

bioRxiv2026

A long-hidden prevalent PCR artifact and its application in DNA library screening

PCR artifacts can lead to aberrant DNA products and confound result interpretation, posing significant challenges in research and diagnostics. Traditionally, it has been blamed to misannealing of primers on unintended sites. However, by sequencing, we find that most PCR byproducts and artifacts actually have both primers bound correctly but lack a middle part of the target, a phenomenon we named as PCR leaping. The leaping occurs at random positions, is independent of sequence repeats and requires a single piece template, indicating an unprecedented mechanism. It is observed with various polymerases, template qualities, GC contents, and PCR programs, thus necessitating a reset of our PCR understanding and careful consideration in future studies, for example in CRISPR editing validations. On the other hand, it provides a simple way of DNA end pairing, based on which we develop a high throughput DNA library screening method for natural product discovery at substantially reduced cost.

molecular biology↗

bioRxiv2026

Time-dependent transcriptomic changes following protoplast isolation in plants

Protoplast isolation is widely used for plant functional genomics and single-cell analyses, but its impact on transcriptional and cell state dynamics remains incompletely understood. Here, we generated time-course RNA-seq data from leaf protoplasts of Arabidopsis, maize, and poplar, sampling at multiple time points following isolation, to systematically characterize global transcriptional dynamics across species. We identified two major drivers of transcriptional variation: a persistent protoplast isolation effect and a progressive time-dependent transcriptional program, which can be divided into early, middle, and late stages corresponding to an immediate stress response, metabolic and chromatin regulation dynamics, and sustained metabolic and proteostasis regulation, together with species-specific differences across stages. We observed a rapid loss of cell-type-specific transcriptional signatures within 6 hours in Arabidopsis and maize, whereas poplar showed a slower decline. Single-nucleus RNA-seq at 6 hours in maize confirmed attenuation of cell-type-specific transcriptional structure. Furthermore, leveraging this time-course dataset enables the identification of aberrant cell states in single-cell RNA-seq data, exemplified by clusters showing elevated activity of protoplast isolation-associated, middle-, and late-stage transcriptional programs characteristic of stress-like states. Together, our results provide a cross-species framework for dissecting protoplast-induced transcriptional and cell state dynamics and facilitate the systematic identification of stress-associated cell states in single-cell transcriptomic data.

plant biology↗

bioRxiv2026

The UPRMT is a critical mediator of nutrient immunity

Mitochondria serve as critical signaling hubs that monitor the intracellular environment to orchestrate cellular stress responses during pathogen infection. The mitochondrial unfolded protein response (UPRMT), a key surveillance pathway, is widely considered to be activated by pathogen-derived toxins that directly damage host mitochondria. In contrast to this prevailing model, we demonstrate that E. faecalis, which lacks specialized mitochondrial toxins, activates the UPRMT in C. elegans via a combination of metabolic and oxidative stress. As both C. elegans and E. faecalis are heme auxotrophs, E. faecalis-ingested animals result in severe heme deficiency, leading to the disruption of the electron transport chain and activation of the UPRMT. During live infection, this primary mitochondrial stress is further amplified due to the Fenton reaction, driven by host NADPH oxidase BLI-3-generated hydrogen peroxide. Ultimately, our findings position the UPRMT as a fundamental homeostatic sensor that monitors metabolic and oxidative imbalances at the host-pathogen interface.

immunology↗