Biology subjects

Zhang, Z.

Publications and source records attributed to Zhang, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2026

PRRC2A, PRRC2B and PRRC2C are Stress Granule Proteins that Promote Translation Through Association with the eIF3 complex

Regulation of mRNA translation is essential for cellular homeostasis, and its dysregulation contributes to cancer, neurodegeneration, and developmental disorders. Stress granules are cytosolic condensates that form during stress-induced translation arrest and are enriched in mRNAs, translation factors, and RNA-binding proteins, but how stress granule proteins modulate translation remains poorly understood. Here, we identify the stress granule components Proline-Rich Coiled-Coil A, B, and C (PRRC2 proteins) as translation regulators. PRRC2 proteins are large, intrinsically disordered paralogs conserved across jawed vertebrates. Functional proteomics revealed that all PRRC2 proteins associate with the 48S translation initiation complex (PIC), whereas PRRC2B additionally interacts with nuclear proteins. Under stress, the proximal interaction network of PRRC2 proteins undergoes dynamic remodeling, including increased interactions with the stress granule scaffold G3BP1. Genetic perturbation shows that the PRRC2 proteins influence stress granule assembly in a context-specific manner, and are collectively required for cell growth in basal conditions due to their essential role in translation. Cells with reduced PRRC2 proteins exhibit a significant reduction in the abundance of more than half of the proteome, with a bias toward translational targets of eIF3d and eIF4G2. Interaction domain mapping and AlphaFold3 modeling revealed that an helix within the putative coiled-coil domain of PRRC2C mediates interactions with the eIF3 core complex. This modeling places the PRRC2C helix in a previously unassigned region of a published cryo-EM density map, validating the protein interaction and the mechanistic role of PRRC2C in translation control. Together, these findings establish PRRC2 proteins as components of the translation initiation machinery that regulate translation through their interactions with the eIF3 complex and other components of the 48S PIC factors, providing a direct mechanistic link between stress granule proteins and translational control.

cell biology↗

bioRxiv2026

A 5-hydroxymethylcytosine DNA glycosylase provides defense against T-even bacteriophages

The most abundant prokaryotic mechanisms of defense against phage predation involve the recognition and destruction of the infecting DNA. One method of counter-defense is the incorporation of modified nucleobases into the phage genome to avoid interaction with enzymes that target the viral DNA. T-even coliphages replace cytosine with 5-hydroxymethylcytosine (5hmC) that in some cases are further decorated with glucosyl groups. To explore the diversity of immunity genes that recognize 5hmC, we infected a library of metagenomic DNA inserts from uncultured, non-sequenced soil bacteria with a mutant T4 phage that harbored only non-glucosylated 5hmC on its genome. Bacteria that resisted infection carried a DNA glycosylase, Brig3, that specifically excises 5hmC nucleobases to generate abasic sites in the phage genome and prevent viral proliferation. The crystal structure of Brig3 bound to its substrate revealed a catalytic mechanism in which the 5hmC nucleobase is flipped out of the DNA into the active site and replaced by an asparagine residue that inserts into the double helix to contact the complementary guanosine. Brig3 is encoded within an operon that also encodes BapA, a hydrolase that removes glucosyl groups from glucosyl-5hmC present in the genome of otherwise Brig3-resistant T-even phages carrying this hypermodified base. Our results uncover a defense strategy in which the combined action of BapA and Brig3 widens the immune response to restrict the infection of T-even phages with genomes that are either partially or completely glucosylated.

microbiology↗

bioRxiv2026

Structural basis for repurposing a flexible phage tail into an Intraspecific bacterial competition weapon

The rise of multidrug-resistant bacteria poses a major threat to human health. Tailocins, which are phage tail-like bacteriocins, offer a way to kill specific bacteria without the risks of horizontal gene transfer found in phage therapy. While the mechanism of contractile R-type tailocins is well-established, the bactericidal action of non-contractile F-type tailocins remains unresolved. Here, we report the high-resolution cryo-EM structure of the F-pyocin from Pseudomonas aeruginosa. The structure reveals a complex nanomachine made of a terminator cap (AlpD/PA0910), a helical tube (PA0633), and a tail tip that mediates a symmetry transition from sixfold to threefold. Notably, the tail tip connects to an elongated central fiber (PA0641) decorated with trimeric side fibers (PA0643/PA0646) involved in host recognition. Through genetic deletion studies and proteomic analysis, we delineate the F-pyocin assembly pathway, establishing that the tape-measure protein (PA0636) serves as a central scaffold coordinating the assembly of the tube, cap, and tail-tip modules. Structural analysis reveals a localized register shift in the central fibers coiled-coil shaft, suggesting a metastable state that may facilitate conformational changes upon host recognition. Our findings detail the atomic structure of an F-type tailocin, uncovering its coordinated assembly pathway and specialized tail-fiber architecture, which establishes a structural framework for engineering next-generation, precision antimicrobials.

biophysics↗

bioRxiv2026

DNA replication initiation causally sets the added mass for cell division in Escherichia coli

Faithful genome inheritance requires cell division to be precisely coordinated with DNA replication. The classical Cooper-Helmstetter paradigm posited that division occurs at a roughly constant time after replication initiation (initiation-to-division "ID-timer" model). This has since been challenged by conflicting "adder" phenomena, leaving the primary signal for division a fundamental enigma. Here, we resolve these discrepancies by establishing that cell division in Escherichia coli obeys a universal "ID-adder" rule: addition of a defined size increment from replication initiation. This rule is invariant across the physiological range of nutrition-affected growth rates, whereas other versions of the adder phenomenon are emergent properties shaped by inter-cycle correlations. Through population-level perturbations of initiation mass, division machinery, and replication termination, we demonstrate that replication initiation directly and causally sets the division schedule. This principle operates independently of replication termination and division protein levels, providing a robust mechanism for coordinating the genome duplication with the cell division cycle.

microbiology↗

bioRxiv2026

NRF2 pathway activation and SPP1⁺TREM2⁺ macrophages drive chemoradiotherapy resistance in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most aggressive cancers, with low rates of durable response to chemoradiotherapy and limited therapeutic options for relapsed disease. To uncover mechanisms of treatment resistance and relapse, we performed comprehensive multi-omics profiling of >100 pre-treatment and post-relapse ESCC tumors from a prospective clinical trial (NCT04694391), integrating whole-exome/genome sequencing, bulk RNA-sequencing, single-cell RNA sequencing, and spatial transcriptomics. We identify somatic alterations in NFE2L2/KEAP1 in nearly 40% of relapsed patients, which are associated with upregulation of NRF2 signaling targets in resistant tumors and cell line models. At single-cell and spatial resolution, relapsed tumors are enriched for NRF2-activated epithelial cells that physically co-localize with immunosuppressive SPP1TREM2 macrophages. This co-localization suggests a synergistic interaction between NRF2-driven tumor programs and macrophage-mediated immune suppression that promotes relapse after chemoradiotherapy. Our findings nominate NFE2L2/KEAP1 mutations as predictive biomarkers for patient stratification and highlight therapeutic targeting of NRF2 signaling and SPP1TREM2 macrophages as rational strategies to overcome resistance in ESCC.

cancer biology↗

bioRxiv2026

TRU-PE: A Universal, Trackable Prime Editor Toolkit for Robust Single- and Multi-Locus Genome Engineering

Prime editing (PE) holds immense promise for precise genome editing, but its wider adoption is constrained by large payloads and inefficient delivery in recalcitrant cell types. Here, we present TRU-PE (Trackable, Robust, and Universal Prime Editor), a toolkit that overcomes these barriers via a split-vector architecture coupled with fluorescence-guided enrichment. This design ensures stoichiometric component expression, yielding marked improvements in editing efficiency and accelerated workflows compatible with both plasmid and viral delivery. By integrating a polycistronic hCtRNA-sgRNA/pegRNA array, the derivative TRU-MPE system enables simultaneous editing of up to ten genomic loci. Furthermore, it enhances the performance of evolved PE editors, allows flexible vector stoichiometry and inspires novel editing reporters. Leveraging these capabilities, we successfully generated a combinatorial human iPSC-based platform for GATA2 deficiency, which accurately recapitulates genotype-specific hematopoietic defects. TRU-PE thus provides a user-friendly, scalable framework for robust single- and multi-locus genome engineering, accelerating functional genomics and therapeutic development.

genetics↗

bioRxiv2026

Histone H2BK120 ubiquitination modulates PRC1 activity and H2AK119ub deposition on nucleosomes

Polycomb group and Trithorax group complexes antagonistically regulate developmental gene expression, yet the mechanisms coordinating their interplay remain poorly understood. Here, we uncover a synergistic histone crosstalk in which H2BK120ub (histone H2B ubiquitination at lysine 120), a Trithorax-associated active mark, enhances Polycomb repressive complex 1 (PRC1) activity by directly binding specific PCGF subunits of PRC1 on the nucleosome surface, as shown in cryo-electron microscopy (cryo-EM) analysis. Beyond regulating enzymatic activity, H2BK120ub also modulates the competitive binding between the catalytic RNF2-BMI1 module and the RYBP subunit of noncanonical PRC1.4 complexes to nucleosomes, potentially restricting H2AK119ub (histone H2A ubiquitination at lysine 119) spreading to neighboring nucleosomes. In mouse embryonic stem cells, H2BK120ub directs the deposition of H2AK119ub within the gene bodies of a subset of developmental genes, which exhibit more rapid activation compared to canonical H3K4me3/H3K27me3 bivalent genes. These findings reveal a previously unrecognized mechanism that links active and repressive histone modifications, providing new insights into the intricate chromatin regulation of gene expression during development.

molecular biology↗

bioRxiv2026

Integrated inference of cancer gene expression from cell-free plasma chromatin

Gene expression is a defining determinant of tumor identity, behavior, and therapeutic response, yet remains challenging to measure noninvasively. Here, we introduce APEX (Associating Plasma Epigenomic features with eXpression), a framework for inferring expression from circulating cell-free chromatin. Trained on [~]270,000 gene-sample pairs from matched tumor RNA-seq and plasma cfChIP-seq across multiple cancers and validated on >15 unseen cancer subtypes, APEX accurately infers cancer gene expression across a range of tumor fractions and outperforms existing plasma-based approaches by integrating positional histone mark and DNA fragmentation patterns across promoters and gene bodies. Using plasma alone, APEX enables classification of prognostically relevant basal and classical pancreatic cancer subtypes and identifies plasma-inferred NECTIN4 expression as a biomarker of response to enfortumab vedotin in metastatic bladder cancer. Together, these findings establish APEX as a biopsy-free approach for profiling tumor transcriptional states and extend liquid biopsy beyond genomic alterations to clinically relevant gene expression programs.

genomics↗

bioRxiv2026

Rab32/Rab38-positive Lysosome-Related Organelle degrades lipid droplet in hepatocytes by microautophagy

Rab32 and Rab38 are paralogous small GTPases involved in the biogenesis of lysosome-related organelles (LROs), yet their roles in hepatic lipid metabolism remain poorly defined. Here, Rab32 and Rab38 double-knockout (DKO) male mice exhibited an age-dependent increase in body weight accompanied by hepatic lipid accumulation, suggesting impaired hepatic lipid processing. In AML12 hepatocytes, Rab32 and Rab38 localized to ring-like, LAMP1-positive structures characteristic of LROs, whose size increased with cell confluence. Pharmacological inhibition of lysosomal acid lipase with orlistat led to the accumulation of lipid droplets (LDs) within Rab32/38-positive LROs, indicating that LD degradation occurs in these compartments. Additional treatment with bafilomycin A1 revealed invagination-like internal membrane structures within enlarged LROs. These processes were not affected by artificial inhibition of macroautophagy, highlighting the involvement of microautophagy. Ring-like signals positive for phosphatidylinositol 3-phosphate (PI3P) or phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2) were detected within or adjacent to LRO membranes, and LDs were frequently associated with these structures, suggesting a role for PI3P and PI(3,5)P2 in internal membrane formation. Vps4B was also required for efficient LD incorporation. Consistently, Rab32/38 double-knockdown (DKD) AML12 cells exhibited increased lipid accumulation, indicating impaired LD engulfment. Together, these findings identify Rab32/38-positive LROs as a structural platform for microautophagy-mediated lipid droplet degradation in hepatocytes.

cell biology↗

bioRxiv2026

Anti-IL1RAP Antibodies for Pan-Inhibition of IL-1 Family Cytokine Signaling in Inflammatory Diseases and Oncology

The interleukin-1 (IL-1) superfamily of cytokines--comprising the IL-1, IL-33, and IL-36 subfamilies--orchestrates a vast array of innate and adaptive immune responses. While physiological activation of these pathways is essential for host defense and tissue repair, their chronic dysregulation is pathognomonic of a broad spectrum of autoimmune diseases and malignancies. Current therapeutic modalities largely rely on the neutralization of single cytokines, an approach often limited by the functional redundancy and compensatory signaling loops inherent to the IL-1 superfamily. The Interleukin-1 Receptor Accessory Protein (IL1RAP) serves as an obligatory co-receptor for IL-1, IL-33, and IL-36 subfamilies, functioning as a molecular bottleneck for pro-inflammatory signaling. Herein, we report the development and comprehensive characterization of two humanized monoclonal antibodies, DXP-006 and DXP-106, which target a unique epitope on domain 2 of IL1RAP. Cryo-electron microscopy studies at 3.55 [A] resolution reveal that these antibodies lock the critical c2d2 loop of IL1RAP, sterically occluding its recruitment to IL-1R1, ST2 and IL-36R binary complexes and potently blockade IL-1, IL33, and IL-36 signaling. DXP-006, engineered with a half-life-extended and effector-silenced Fc, exerts profound efficacy in murine models of psoriasis, superior to the clinical benchmark bimekizumab. Conversely, DXP-106, engineered with a defucosylated Fc to enhance antibody-dependent cellular cytotoxicity, exhibits potent antitumor activity in non-small cell lung cancer xenografts. These findings position DXP-006 and DXP-106 as ideal therapeutics for IL-1 family-driven autoimmunity and IL1RAP-positive cancers. One Sentence SummaryAnti-IL1RAP antibodies block multiple IL-1 family cytokines simultaneously, showing superior efficacy in inflammation and cancer models.

immunology↗

bioRxiv2026

Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta

Cryogenic electron microscopy (cryo-EM) has become a widely used technique for determining the three-dimensional structures of biological macromolecules. Despite its advantages, building accurate structural models from cryo-EM data remains challenging, particularly at non-atomic resolutions. Here, we present CryoZeta, a de novo structure modeling program that leverages a diffusion-based generative deep neural network to integrate cryo-EM map density features with a biomolecular structure prediction pipeline similar to Alphafold3. By jointly leveraging sequence information and density-based features, CryoZeta generates highly accurate structural models that are consistent with the experimental map density. Evaluated on benchmark datasets covering protein complexes, protein-nucleic acid assemblies, and nucleic acid-only systems at resolutions up to 10 [A], CryoZeta consistently outperforms existing cryo-EM modeling methods in atomic accuracy. These results highlight the benefits of directly incorporating cryo-EM density into modern structure prediction pipelines and establish the method as a robust tool for automated, high-fidelity modeling from cryo-EM maps.

bioinformatics↗

bioRxiv2026

Visualizing single base RNA mutations in living cells through DNA nanostructure mediated amplification

Capturing RNA dynamics in living cells would provide critical insights into transcriptional control and cellular adaptation, but remains technically formidable -- particularly at single-base precision. Here, we introduce a DNA tetrahedron based three-dimensional catalytic hairpin assembly (3D@CHA) nanoplatform that couples target recognition with catalytic activation in a spatially organized framework. Three cascaded hairpins (H-AN, H1, and H2) then enable localized and efficient signal amplification. Without external carriers or transfection, the platform exhibits robust biocompatibility, distinguishing highly homologous insulin I (Ins1) and insulin II (Ins2) mRNAs in living cells and tracking their redistribution and intercellular transfer during metabolic changes. Introducing a single-base mismatch site into H1 and coupling it with a Forster resonance energy transfer (FRET) readout yielded a KRAS-3D@CHA probe capable of detecting KRASG12D mutations at the RNA level with single-base resolution. This platform establishes a programmable framework for precise RNA imaging and mutation discrimination, opening new avenues for RNA-level diagnostics and precision oncology.

cell biology↗

bioRxiv2026

Enhancing Pan-cancer Spatial Transcriptomics atSingle-cell Resolution with stPainter

Subcellular spatial transcriptomics technologies offer unprecedented views of tissue architecture but are fundamentally constrained by sparse gene panels and limited detection sensitivity. Current computational enhancement strategies typically rely on tissue-matched single-cell RNA sequencing (scRNA-seq) references and necessitate computationally intensive retraining for each dataset, impeding their scalability and clinical applicability. Here, we present STPAINTER, a conditional generative model that leverages a massive pretraining pan-cancer scRNA-seq atlas to universally enhance spatial transcriptomics data. Built upon a latent diffusion architecture with stochastic differential equation-guided generation, STPAINTER learns a universal manifold of cellular states to reconstruct genome-wide expression profiles from sparse spatial measurements. Uniquely, our pretraining paradigm enables zero-shot generalization and empowers downstream tasks by providing imputed transcriptomes and informative latent variables to enhance resolution at both the gene and cluster levels. Applied STPAINTER upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers high-fidelity downstream analyses, including fine-grained subpopulation clustering and pathway enrichment. Furthermore, cross-validation with spatially resolved proteomics (CODEX) confirms the biological veracity of the imputed cellular landscapes. STPAINTER provides a robust, scalable framework for decoding complex tumor microenvironments without the need for auxiliary sequencing data.

bioinformatics↗

bioRxiv2026

Disentangled multimodal evolutionary representations for cross-virus predictive modeling of antigenic change

Antigenic evolution drives immune escape and complicates early assessment of emerging pathogens, especially when genomic surveillance is sparse and functional measurements lag behind real-world spread. Early prediction and generalization to unknown viruses require faithful and information-rich representations of viral evolution, a need that is not fully addressed by existing protein language model-based approaches. Here we introduce DERIVE, a flow-based generative framework that learns a disentangled latent representation of multimodal evolutionary history by integrating sequence homology with physicochemical and structural features. Using only pre-pandemic SARS-CoV-2 sequences, DERIVE prioritizes high-risk mutations, reconstructs strain-level evolutionary trajectories, forecasts immune escape and prevalence trends, and produces mutation-level effect maps. The learned representation transfers robustly across viral families, with strong concordance to functional data for influenza virus, HIV, rabies lyssavirus and chikungunya virus. Together, these results position DERIVE as a generalizable and interpretable framework for anticipating antigenic evolution and supporting early, actionable assessment of future "Disease X" threats.

bioinformatics↗

bioRxiv2026

Spatiotemporal cell type deconvolution leveraging tissue structure

Spot-based spatial transcriptomics (ST) captures aggregated transcriptomic profiles at spatial locations (spots) in tissue slices. Cell type deconvolution methods decode each spot and estimate the proportion of every cell type in the spot, necessary for uncovering spatial cell type distributions for further downstream analyses. Existing methods utilize cell type markers or reference transcriptomic (scRNA-seq) atlases at single cell (sc) resolution, or by aggregating profiles of identified cell types. However, current methods fail to effectively utilize the 3D tissue layout and single cell resolution reference. Some leverage 2D spatial organization assuming proximal spots are similar, which may be violated around boundaries or isolated cell types. We present SpaDecoder, a parallelized matrix factorization-based per-spot deconvolution method for multiple 3D spatial or temporal ST tissue slices effectively leveraging tissue structure with an adaptively inferred 3D neighborhood Gaussian kernel. We additionally account for variability in sc-reference profiles, along with batch effects. The mathematical framework of SpaDecoder allows it to be used for a range of downstream analyses. It can decode anteroposterior variability, impute gene expression, uncover putatively key tissue regions, identify colocalized cell types and predict spatio-temporal scRNA-seq cell locations. Ablation tests along with comparisons against other methods on various metrics, datasets, and scenarios, collectively show that SpaDecoder effectively harnesses 3D tissue structure and sc-reference profiles to improve cell type deconvolution. SpaDecoder is available at https://github.com/ZhangLabGT/spadecoder.

bioinformatics↗

bioRxiv2026

Synergistic integration of inducible RNA switches enhances the manipulation of vector expression

Precise manipulation of gene expression is pivotal for gene function studies and the optimization of gene therapy. RNA-based gene switches are attractive tools due to their robust tunability by FDA-approved small molecules, the absence of exogenous immunogenic proteins, and the small size for gene delivery vectors such as adeno-associated virus (AAV). However, existing RNA switches only target a single step of gene expression such as transcription or RNA splicing, exhibiting intrinsic limitations in gene regulation. To overcome this issue, this study integrated the aptamer-based polyA regulator (pA), the drug-elicitable alternative splicing module (DreAM) and an engineered translation modulator with conditional upstream open reading frames (uORFs) to construct the DreAM-plus RNA switch. The pA-DreAM concatenation led to 1.5[~]5.0-fold and 1.2[~]4.4-fold increase of inducible fold changes than pA and DreAM, respectively. The uORF module further enhanced the switching performance by 1.4[~]6.3-fold. DreAM-plus-mediated transient transgene expression demonstrated a temporal resolution of about 24 hours and high tissue specificity to liver or heart. Critically, DreAM-plus achieved transient expression of an array of gene editors (SpCas9, SaCas9, Un1Cas12f1, OsCas12f1, AcCas12n, IsDra2 TnpB etc.) that significantly mitigated off-target effects by 1.4[~]2.8 folds in plasmids, lentivirus and AAV. In a new mouse model with lipid-nanoparticle-delivered pre-existing immunity, DreAM-plus attenuated AAV-delivered Cas-specific CD8 T cell immune toxicity in the liver and the heart. Therefore, multiple RNA switches could be synergistically integrated to build more sophisticated genetic cassettes for enhanced manipulation of gene expression.

bioengineering↗

bioRxiv2026

Between- and Within-subject Variability in Actigraphy Data: A Case Study on Sleep Patterns in Schizophrenia

Variability in longitudinal health outcomes provides critical insight into disease dynamics, yet most statistical analyses continue to prioritize mean trajectories. This limitation is particularly consequential in psychiatric and mobile health (mHealth) research, where intensive repeated measurements increasingly reveal pronounced heterogeneity and temporal instability that cannot be captured by average responses alone. Standard mixed-effects models typically impose homoscedastic variance assumptions and relegate variability to a nuisance component, despite mounting evidence that both variability information, at both between- and within-subject level, carry independent clinical significance. Here, we describe an improved mixed-effects location-scale model for longitudinal outcomes that simultaneously characterizes mean structure, between-subject heterogeneity, and within-subject fluctuations. The proposed framework explicitly links variance components to both time-invariant and time-varying covariates, extending classical mixed-effects models to accommodate heteroscedastic and dynamically evolving variability. By jointly modeling location and scale parameters, the method enables direct inference on variability (or stability) of the data alongside mean trends. We evaluated the approach using an actigraphy-based mHealth case study of sleep patterns in schizophrenia. Our results demonstrate that explicitly modeling variability uncovers clinically relevant structure obscured by mean-based analyses, underscoring the importance of variability-aware modeling for modern longitudinal and mHealth research.

neuroscience↗

bioRxiv2026

Mechanism of substrate recognition and catalysis in a mammalian phosphatidylserine synthase 2

Mammalian phosphatidylserine synthase-1 and -2 synthesize phosphatidylserine (PS) by replacing the headgroup of either phosphatidylcholine (PC, PTDSS1) or phosphatidylethanolamine (PE, PTDSS2) with a serine. We determined structures of PTDSS2 from Equus caballus in complex with either PE or serine substrates to resolutions of 2.8-3.2 [A]. The structures define substrate binding sites and reveal that the phosphate group of PE is coordinated by two Ca2+. In addition, we found that PTDSS2 has significant phospholipase D (PLD) activity in the absence of serine, which was not reported previously, and that Ca2+ is required for the PLD activity. These discoveries enrich our knowledge in the mechanism of mammalian PTDSS.

biochemistry↗