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Zhang, Z.

Publications and source records attributed to Zhang, Z..

At least 55 records · Page 3Linked to original sources

MINT infers the latent single-cell spatial transcriptome from paired histology

Sequencing-based spatial transcriptomics captures transcriptome-wide molecular information, yet the corresponding cell-resolved tissue map remains incomplete. Histology records dense cellular morphology, tissue architecture and local context. Here, we present MINT (Morphological Integrative Network for Transcriptomics), which combines this latent cellular organisation with sample-specific spatial measurements to infer tissue-wide, cell-resolved transcriptomes without an external single-cell reference. MINT reconstructs expression from sparse Slide-tags profiles across unmatched adjacent sections; its shared nucleus-centred representation also resolves pooled Visium measurements into cell-level profiles. MINT improved Slide-tags alignment and expression recovery under controlled nuclear loss and cross-section perturbation. It also outperformed reference-free Visium disaggregation methods against Xenium ground truth and was validated with Visium HD sequencing. In human lung adenocarcinoma, MINT reconstructed the tumour immune microenvironment cell by cell and resolved tertiary lymphoid structures and their maturity. These results establish paired histology as a quantitative, sample-intrinsic complement to molecularly rich but cellularly incomplete spatial-transcriptomic assays.

bioinformatics↗

Functional reorganization of large-scale brain systems underlies emotion regulation maturation

Emotion regulation via cognitive reappraisal is essential for socioemotional development and mental health, yet the organizational logic of its supporting brain systems across youth remains unclear. Using a large multisite cohort, we demonstrate that maturation of reappraisal capacity reflects reorganization of a distributed architecture rather than progressive strengthening of prefrontal control. Reappraisal robustly reduced negative affect, with non-linear gains concentrated between 6 and 10.5 years. Bayesian systems identification resolved this architecture into four functionally distinct systems-reappraisal-specific, common-appraisal, modifiable-emotion, and non-modifiable-emotion components-spanning prefrontal-control, salience, default-mode and dorsal-attention networks. Age-related variation in anterior temporal cortex, emerged as essential hub, statistically accounted for developmental gains in reappraisal success. Multivariate modelling together with intersubject analyses further identified a cross-site-generalizable whole-brain reappraisal signature and revealed an age-dependent shift in brain-behaviour coupling, with neurobehavioural convergence increasing with age. These findings establish distributed network reorganization as a core mechanism of emotion regulation development and provide mechanistic targets for stage-matched interventions.

neuroscience↗

The RNA modification N6-methyladenosine restrains SIRPα to license myeloid efferocytosis in atherosclerosis

Background: Macrophages participate in atherosclerotic plaque development, progression and resolution, integrating lipid and inflammatory cues to balance tissue damage and repair. Despite considerable understanding of macrophage function in atherosclerosis, the underlying regulatory mechanisms governing these responses continue to evolve. Emerging evidence implicates epitranscriptomic gene regulation by the RNA modification N6-methyladenosine (m6A) in control of context specific immune responses, but its role in atherosclerosis is not well-defined. Methods: We integrated m6A quantitative trait loci (m6A QTLs) with Coronary Artery Disease (CAD) GWAS summary statistics. Using Oxford Nanopore direct RNA sequencing and MeRIP-seq, we constructed a high-resolution map of m6A modifications in macrophages. To determine the functional consequences of myeloid m6A loss in-vivo, we generated a myeloid-specific loss-of-function mouse model of m6A (Mettl14f/f LysMCre) and performed atherosclerosis studies using bone marrow transplantation into irradiated Ldlr-/- mice. Atherosclerosis lesions were analyzed using light microscopy and immunofluorescence imaging, with complementary in-vitro mechanistic studies performed in murine bone marrow derived macrophages (BMDMs). Results: m6A quantitative trait loci (m6A-QTLs) were enriched in CAD GWAS loci relevant to immune and lipid function, implicating m6A regulation in human CAD genetics. Using Oxford Nanopore direct RNA sequencing in conjunction with public MeRIP-sequencing data, we generated a single-base resolution, stoichiometric map of m6A modification in macrophages, nominating genes central to macrophage biology in atherosclerosis as high-confidence m6A targets. Myeloid specific deletion of the m6A "writer" complex subunit Mettl14 drove the development of larger, more necrotic and unstable atherosclerotic plaques on an Ldlr-/- background compared with Mettl14f/f controls, establishing an atheroprotective role for myeloid m6A. Loss of myeloid Mettl14 impaired macrophage efferocytosis in atherosclerotic plaques, in a dexamethasone-induced apoptosis in the thymus and in-vitro. Molecularly, m6A methylation of the "don't eat me" antiphagocytic receptor SIRP RNA suppressed its protein expression. Conclusions: These findings identify the myeloid m6A - SIRP axis as a novel homeostatic regulator of efferocytosis and establish epitranscriptomic remodeling as a crucial layer of macrophage regulation in atherosclerosis.

physiology↗

Loss of TDP-43 function drives cryptic circular RNAs in neurodegenerative diseases

TAR DNA-binding protein 43 (TDP-43) is a key pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) and a critical regulator of RNA splicing. While loss of TDP-43 induces aberrant splicing in linear transcripts, its impact on circular RNA (circRNA) biogenesis remains unexplored. Here, we show that TDP-43 depletion in human neurons induces widespread circRNA changes, especially upregulation of a distinct class of cryptic circRNAs that arise specifically upon loss of TDP-43. Some of these cryptic circRNAs incorporate cryptic exons derived from intronic sequences. Notably, these cryptic circRNAs exhibit greater stability than their corresponding linear RNA isoforms and accumulate progressively in neurons. Moreover, cryptic circRNAs are elevated in postmortem brain tissues from ALS, FTD and Alzheimer's disease (AD) patients. These findings reveal a previously unrecognized role for TDP-43 in repressing cryptic circRNA formation and establish these circRNAs as stable molecular signatures of TDP-43 dysfunction.

neuroscience↗

Hygrochastic Seedpods: Engineering Microclimates for Forest Restoration

Forest restoration at scale depends on sowing seeds directly onto the land, yet seedling establishment is often poor and inconsistent. Seed enhancement technologies, such as priming, coating, and pelleting, improve germination under water, temperature, and salinity stress by supplying polymers, nutrients, or microorganisms at the seed surface. Being mainly conformal films, they act continuously once wetted and cannot gate when a seed is exposed to the soil. They also enclose no air volume, so the microenvironment they create is inseparable from the surrounding soil and has been inferred from plant performance rather than measured directly. Whether an engineered carrier can instead set both the state and the duration of the post-dispersal microenvironment, and how such an effect can be directly quantified, remains unexplored. Here we show that hygrochastic seedpods hold seeds in a timed, directly measurable microclimate and accelerate seedling emergence. The pods are programmable, responsive conical shells enclosing an air cavity around the seed. Two design solutions were investigated in parallel: wooden seedpods that crack open upon hydration, and poly(vinyl alcohol)/boric acid seedpods that gradually disintegrate after sustained wetting. In both, wax coatings act as a programmable diffusion-limited timer that sets activation from hours to days. The pod cavity permits direct sensing and monitoring, which no coating geometries allow. As directly measured during the initial phase after deployment, seedpod interiors ran 2 - 3 C warmer and drier than the surrounding soil, and these differences persisted after opening. Across indoor and field trials in several tree species, pods accelerated early seedling emergence without penalizing subsequent growth. These results identify artificial hygrochastic seedpods as a transient ecological mediator that regulates both the timing of seed exposure and the microclimate around the seed, offering a strategy for improving forest restoration under variable environmental conditions.

bioengineering↗

Latent generative search unlocks de novo design of untapped biomolecular interactions at scale

De novo protein design has advanced rapidly, yet designing binders to polar, solvent-exposed epitopes and small, flexible ligands remains challenging. Such hydrated surfaces and flexible molecules, including carbohydrates, provide few of the hydrophobic contacts favoured by current methods and have largely resisted de novo binders. To address this challenge, here we introduce latent generative search for binder design, a novel framework that uses reward-guided search at inference time to steer the Proteina-Complexa generative model. The model codesigns sequence and structure - generating them together in a continuous latent space - and thereby removes the inverse-folding step on which current methods rely. In a screen of more than one million designs by multiplexed phage display, latent generative search produced more validated binders than every other method tested, its codesigned sequences surpassing post hoc redesign. It delivered high-affinity binders across therapeutic receptors, a viral attachment protein and intracellular signalling targets. Our approach also accessed previously untapped biology, generating the first de novo proteins that bind a free carbohydrate, including one that discriminates between blood-group antigens - a polar, flexible target class beyond the reach of current design methods.

bioengineering↗

Genomic splice-donor disruption rescues systemic disease in progeria

RNA splicing determines which protein isoforms a gene produces, and aberrant splice-site activation can cause severe disease. In Hutchinson-Gilford progeria syndrome, a synonymous LMNA mutation strengthens a cryptic 5' splice donor site to produce progerin, a toxic lamin A isoform driving premature cardiovascular death. Within this cryptic donor, the activating mutation lies near the canonical GT dinucleotide required for splice-site recognition. A single guide can therefore preferentially pair with the mutant sequence while positioning Cas9 cleavage at this dinucleotide. Here we show that CRISPR/Cas9-mediated disruption of this splice site suppresses progerin without requiring precise correction of the activating mutation and prolongs lifespan in progeroid mice. In patient-derived fibroblasts and induced pluripotent stem cell-derived mesenchymal stem cells, this intervention reduced progerin by 92.7-96.8% while retaining lamin A and lamin C expression. A single neonatal injection of AAV9 carrying the corresponding mouse guide increased median survival from 115 to 279 days in Cas9-expressing LmnaG609G/G609G mice. Treatment attenuated aortic, skeletal and multiorgan pathology. Treated homozygous pairs produced 52 offspring across seven litters. These findings establish pathogenic splice signals as genomic targets for sustained suppression of toxic isoforms while retaining canonical gene outputs.

cell biology↗

PAXIP1-PAGR1 directs cohesin recruitment during break-induced telomere repair

Cohesin is a conserved multiprotein complex (SMC1, SMC3, RAD21, and either STAG1 or STAG2) that organizes three-dimensional genome architecture and regulates chromosome segregation, gene expression, and DNA damage repair (1-4). Following double-strand breaks (DSBs), cohesin is recruited to sites of DNA damage - a process considered essential for efficient homologous recombination (5-15). Yet how DSB signaling elicits cohesin recruitment and subsequent cohesion establishment remains poorly understood. Here we show that telomere replication stress activates de novo STAG2-cohesin loading, thereby promoting break-induced telomeric DNA repair. We demonstrate that this DNA break-elicited cohesin recruitment is strictly controlled by the BRCT domain-containing DNA damage recognition factor PAXIP1 and its functional partner PAGR1. Cryo-electron microscopy structure reveals that PAGR1, together with PAXIP1, physically binds to a composite interface formed by the STAG2-RAD21 cohesin subcomplex. Complementary mutational and biochemical analyses define the molecular basis of this interaction and establish its essential role in break-induced cohesion establishment. Furthermore, we show that PAXIP1-PAGR1-enacted STAG2-cohesin recruitment complements with the PML body-associated pathway in orchestrating break-induced alternative lengthening of telomeres (ALT). Concurrent depletion of PML together with PAXIP1, PAGR1 or STAG2 disrupts ALT-mediated telomere maintenance, leading to end-to-end chromosomal fusion and mitotic cell death. Collectively, these findings uncover a distinctive molecular mechanism through which DSB signaling directs de novo cohesion establishment, and highlight its critical importance in break-induced telomere repair.

molecular biology↗

A Gene-Program Architecture of Mouse T cells

We present immgenT-GP, a gene-program framework for resolving mouse T cell heterogeneity across the immgenT atlas. On ~ 800,000 T cells spanning lineages, organs, and immune challenges, we defined 200 reproducible gene programs, discovered by empirical Bayes matrix factorization approach and validated through a new deep learning approach, that capture major axes of T cell variation, including lineage identity, activation states and tissue location. Gene-program analysis complemented cluster-based annotation by decomposing T cell states into molecular modules, revealing quantitative, shared, modules not represented with discrete labels alone. Across tissues, gene programs reflected both tissue-imposed programs and changes in cluster composition. Integrating GP activity with cell-surface marker expression from the CITE-seq data, revealed that markers can report different programs depending on lineage and context. Together, immgenT-GP extends the atlas from a map of T cell states to a molecular reference of the programs that underlie them.

genomics↗

ProteoformTracker: an interactive tool for planning proteoform detectability in top-down and middle-down proteomics

Characterizing proteome complexity in disease contexts is essential for understanding molecular mechanisms and advancing therapeutic development. Mass spectrometry (MS)-based top-down and middle-down proteomics (TDP/MDP) can resolve intact proteoforms - protein molecules carrying a unique combination of isoform sequence and post-translational modifications (PTMs); however, their technical complexity and modest throughput present challenges for experimental planning and limit their broader application. Here, we present ProteoformTracker, an online web tool that prospectively models MS signal and evaluates the feasibility of using TDP/MDP to distinguish a target proteoform from related isoforms and the background proteome. ProteoformTracker takes as input a gene's annotated isoforms, a novel long-read/assembled transcript, or an rMATS alternative-splicing event, with or without user-specified PTMs, and predicts each proteoform's MS1 charge-state envelope and exact isotope pattern, scores per-bond MS2 fragmentation propensity, and searches the full reference human proteome for confounding proteins that could share the target's intact mass or a charge-state m/z peak. ProteoformTracker also supports middle-down workflows via simulated partial protease digestion. Results are rendered as interactive, zoomable MS1 and MS2 visualizations with live resolvability and fragment-ion statistics, letting users incorporate outside evidence into which confounders they compare against. We envision ProteoformTracker as a useful tool for users to plan TDP/MDP experiments targeting specific proteoforms. ProteoformTracker is implemented in R (Shiny) with a Python backend for exact mass and isotope-pattern calculation and is freely available at http://www.proteoformtracker.org together with the documentation and a walkthrough.

bioinformatics↗

Site-resolved spatial and structural interactome of a human cell

The spatial and structural arrangement of proteins determine virtually every process in human cells. We combined gentle subcellular fractionation by differential ultracentrifugation with cross-linking mass spectrometry to systematically map this cellular proteome architecture with residue-level evidence, identifying 164,146 residue-to-residue links in HEK293 cells. These links capture spatial protein arrangement at a resolution sufficient to pinpoint protein localizations at sub-organelle level, determine protein orientations within cellular membranes, and identify inter-organelle contact sites. The residue-level information provides evidence for 18,074 direct protein-protein interactions (PPIs), which we integrate into AlphaFold-based pipelines to nominate PPI-mediating short linear motifs and generate assembly models of large protein complexes. Guided by these spatial and structural readouts, we discover new PPIs within the endomembrane system that regulate the compartmental localization of trafficking machinery. Leveraging a network topology-driven strategy, we augment our HEK293 dataset with PPI data from different cell lines and methods, expanding the spatial and structural interactome of human cells.

systems biology↗

In-cell structural analysis reveals a distinctive chloroplast ribosome in Chlamydomonas reinhardtii

Chloroplast ribosomes synthesize plastid-encoded components of photosynthetic machinery, yet their structure and organization remain poorly understood. We combined cryo-focused ion beam milling, cryo-electron tomography and subtomogram averaging to determine native chloroplast ribosomes in Chlamydomonas reinhardtii. The 4.4-4.9 [A] structure revealed a large arch-like extension on the small subunit (SSU). Comparisons with bacterial and plant chloroplast ribosomes, supported by proteomics, AlphaFold3 predictions and a recent atomic model, indicate that the arch is formed by insertions and extensions in SSU proteins. Classification resolved active, thylakoid-associated ribosomes with density adjacent to the nascent peptide exit and an arch-moved state enriched among thylakoid-associated particles, with coordinated displacement of the arch and beak. Phylogenetic analysis revealed an evolutionary mosaic: the uS3c insertion is broadly distributed across Chlorophyceae, whereas the uS2c insertion, uS5c and PSRP7 are concentrated in Chlamydomonadales, with PSRP7 also in Sphaeropleales. Nuclear-encoded components were recruited stepwise onto a plastid-encoded scaffold, with all four under comparable purifying selection. These findings link a lineage-specific SSU extension to ribosome dynamics, thylakoid association and evolution, highlighting the value of in-cell structural analysis.

plant biology↗

PathFold: Predicting the Entire Protein Folding Pathway from Protein Sequence Alone

Recent advances in protein structure prediction, exemplified by AlphaFold, have largely addressed the determination of static structures, one aspect of the protein folding problem. However, predicting folding pathways, by which proteins reach their native states, remains a significant challenge. Here, we present PathFold, a deep learning framework that predicts protein folding pathways directly from sequence information. PathFold leverages an AlphaFold-based module to extract structural information from the sequence and generates a progressive folding trajectory from an extended conformation using a diffusion model. By modeling the full trajectory, it enables prediction of folding intermediates and transition pathways, analogous to those observed in steered molecular dynamics (SMD) simulations. The predicted pathways reveal well-defined intermediates and sequential folding events, and show agreement with experimental folding data, including measured {Phi}-values.

bioinformatics↗

Novel Dissymmetric Ionizable Lipid-Assembled Lipid Nanoparticles for Delivery of Ferroptosis-Related siRNA in Diabetic Treatment

Small interfering RNA (siRNA) enables precise post-transcriptional gene silencing for refractory diseases, yet its clinical translation remains limited by the lack of safe and efficient delivery vectors. Inspired by the dissymmetric alkyl chain architecture of natural membrane phospholipids, we designed and synthesized 34 novel ionizable lipids with dissymmetric hydrophobic tails and formulated them into lipid nanoparticles (LNPs). Through systematic physicochemical and biological assessments, we established clear structure-activity relationships and identified two lead LNPs (O14-LNP, H18a-LNP) with superior endosomal escape capacity, enhanced in vivo gene silencing potency, and favorable biosafety relative to the clinical benchmark MC3-LNP. In both streptozotocin-induced and spontaneous db/db type 2 diabetes (T2D) mouse models, lead LNPs delivering ferroptosis-related siRNAs effectively ameliorated glucose and lipid metabolic disorders, restored islet function, and alleviated hepatic steatosis. This study not only lays a theoretical foundation for the rational design of novel ionizable lipids, but also validates the therapeutic potential of siRNA therapy targeting ferroptosis, providing a versatile delivery platform and targeted therapeutic strategy for the treatment of T2D.

pharmacology and toxicology↗

TigerAI: An AI-powered genetic evidence platform to support clinical development

Genetic evidence is a major determinant of clinical success in drug development, yet its aggregation has long relied on laborious human curation. Large language models (LLMs) have the potential to rapidly synthesize knowledge across biomedical resources, providing a route to scalable AI-driven genetic evidence generation. Here we develop a novel domain-grounded instruction framework to systematically evaluate GPT-5 for producing genetic evidence relevant to clinical trial success. Using 13,022 target-indication pairs from a comprehensive drug development database, we benchmark LLM-derived evidence against a recent exhaustive human expert-curated study. We find that GPT-5 yields genetic evidence that is at least as informative as expert curation for inferring clinical success, while substantially expanding coverage relative to traditional curation resources. Building on these results, we introduce TigerAI (https://tigerai.bio/), a dual-purpose platform for AI-powered genetic evidence that (i) benchmarks emerging state-of-the-art LLMs and (ii) provides an accessible service for querying reliable AI-generated genetic evidence. These contributions outline a practical, domain-grounded pathway for integrating AI-powered genetic evidence into drug development pipelines and for realizing the potential of LLMs to inform clinical success.

genetics↗

Spatial multi-omics analysis reveals vimentin-high macrophages-endothelial cells niche shapes CAFs heterogeneity in colorectal cancer metastasis

The spatial architecture of the tumor microenvironment (TME) is pivotal in the progression of colorectal cancer (CRC) liver metastasis. By applying high-plex spatial multi-omic mapping and neighborhood analysis to a discovery cohort of colorectal cancer primary tumor (PT) and paired liver metastases (LM), we identified a specialized vimentin-high macrophages-endothelial cells niche that orchestrates cancer-associated fibroblast (CAF) phenotypes. Mechanistically, in primary tumors, vimentin-high macrophages secrete INHBA to activate the ACVR2/TGF-{beta} axis in endothelial cells, driving CAFs toward a myCAF phenotype. Conversely, in liver metastases, these macrophages secrete CXCL9 to trigger the PI3K-Akt/NF-[kcy]B/CXCL12 cascade in endothelial cells, directing CAFs toward an iCAF state. Clinically, high niche activity predicts poor survival. Divergent endothelial signaling in primary versus metastatic lesions exposes site-specific stromal vulnerabilities for therapeutic targeting, with architectural features discernible from routine histopathology. These findings reveal a site-specific regulatory mechanism of the macrophage-endothelial niche, offering a novel and clinically significant biomarker for CRC prognosis.

cancer biology↗

A multi-tissue epigenomic atlas links the sheep non-coding genome to domestication and complex traits

Non-coding regulatory variation drives complex traits, domestication, and evolutionary adaptation, yet the sheep genome lacks high-resolution functional annotation. Here we present SheepEpimap, a multi-tissue regulatory atlas harmonizing 516 CUT&Tag histone modifications, ATAC-seq, and RNA-seq datasets across 43 adult tissues in sheep. We annotated 2.93 million cis-regulatory elements, yielding 557,441 enhancer-gene pairs and 145,407 variants with allele-specific effects. By training a sequence-to-function deep-learning model, we decoded the base-pair syntax of chromatin accessibility, annotated transcription factor motif instances genome-wide, and constructed 12,210 tissue-specific gene regulatory networks (GRNs). Integrating this resource with multi-tissue expression quantitative trait loci, selection sweeps, and genome-wide association studies prioritized non-coding variants driving domestication and complex traits. Finally, cross-species analysis revealed that sequence-conserved, tissue-matched enhancers were significantly enriched in the heritability of complex traits and diseases in humans. In summary, SheepEpimap (https://genome.ucsc.edu/s/mengzhu/SheepEpimap) provides an open-access foundational ecosystem for sheep functional genomics, precision breeding, and comparative biology.

genetics↗

AFP-R: An Open Resource Dedicated to Antifreeze Proteins

Antifreeze proteins (AFPs), lower the freezing point via thermal hysteresis activity and/or ice recrystallization inhibition, playing a crucial role in protecting organisms from freezing damage under sub-zero milieu. This property endows them with promising applications in biomedicine and agriculture, ranging from tissue-organ cryopreservation to the development of frost-resistant crops. However, the lack of comprehensive resources dedicated for AFPs hinders further progress in elucidating their functional mechanisms and advancing their applications. Here, we report AFP-R, an online resource comprising AFP-DB and AFP-Predictor. AFP-DB is a comprehensive database with manually curated proteins bearing experimentally validated antifreeze activity derived from published literature, whereas AFP-Predictor is a sequence-based machine-learning model to identify AFPs. AFP-DB stores diverse AFP-related information, including sequences, structures, post-translational modifications, taxonomy and annotations of antifreeze-activity experimental assays. It now holds 186 entries, 607 sub-entries, and 1444 experimental records. AFP-Predictor, an AFP-identification algorithm built on protein language model ESM2 (Evolutionary Scale Modeling2), is trained on data in AFP-DB and outperforms several existing models. This work offers a valuable resource for systematically dissecting the mechanisms underlying AFP antifreeze activity and will facilitate their broader applications.

bioinformatics↗