Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 361 records · Page 20Linked to original sources

bioRxiv2025

PRISM: A platform for illuminating viral dark matter

The exploration of bacteriophage diversity remains constrained by reliance on conventional plaque assays, which bias discovery toward phages that form visible plaques and propagate efficiently. The discovery process, as well as measuring correct phage concentrations and phage resistance frequencies, are also time-consuming and labor intensive. Here, we present PRISM (Phage Recovery and Investigation in Single-droplet Microenvironments), a droplet microfluidics-based, plating-independent platform for the high-throughput isolation, quantification, and characterization of bacteriophages. By encapsulating phage-host interactions in water-in-oil microdroplets at single-phase resolution, and then coupling them with fluorescence-based detection and sorting at million-droplet scale, PRISM enables rapid identification of novel phages, including those that evade detection in conventional assays. We demonstrate PRISMs capabilities across several key applications: (i) recovery of both novel "plaquing" and "non-plaquing" Salmonella phages from a concentrated environmental sample, where PRISM recovered multiple representatives of a non-plaquing genus completely missed by conventional plating-based approaches; (ii) accurate titering of poor-plaquing phages such as Rhodococcus phage ReqiDocB7, for which PRISM reported a 2-fold higher titer than conventional plaque assays; and (iii) plating-free determination of phage resistance frequency, with PRISM yielding resistance and lysogeny frequencies (e.g., 1 in 4.4 x 105 cells for T7 Escherichia phage resistance and 1 in 21 cells for Escherichia Lambda phage lysogeny) that closely match conventional estimates. These data highlight PRISMs enhanced resolution and accuracy, as well as its ability to detect rare, non-plaquing, or slow-replicating phages, in a high speed and automated fashion, thereby underscoring the platforms power to access viral "dark matter" traditionally overlooked using conventional methods.

microbiology↗

bioRxiv2025

FLEXTAG: A Small and Self-renewable Protein Labeling System for Anti-fading Multi-color Super-resolution Imaging

Super-resolution fluorescence imaging enables visualization of subcellular structures and molecular interactions at the nanoscale, but its broader application has been hindered by long-standing limitations in current protein tagging systems, including rapid photobleaching, tag-induced artifacts, poor post-fixation labeling efficiency, and restricted multiplexing capability. Here, we present FLEXTAG (Fluorescent Labeling for Exchangeable, X-resilient Tagging in Advanced Generic Nanoscopy), a comprehensive protein labeling system comprising three orthogonal, ultrasmall (12-18 kDa), and self-renewable protein tags that collectively overcome these major limitations of existing tagging systems, enabling optimized multi-color super-resolution imaging. Through continuous exchange of organic fluorophores, FLEXTAG supports unprecedented durations of high-resolution imaging in both live and fixed cells with minimal photobleaching. It is compatible with major super-resolution modalities, such as SIM, STED, STORM, and PAINT, and is applicable to a wide range of subcellular targets. To further address fixation-induced labeling inefficiency and background fluorescence, we developed a novel protection-based fixation method and chemical blocking strategies that significantly preserve tag accessibility and enhance signal-to-noise ratio, improvements that are broadly applicable to other protein tagging systems. Altogether, FLEXTAG enables long-term tracking of dynamic behaviors and interactions of subcellular targets, as well as mapping of nanoscale protein organizations and cellular architecture, advancing both basic research and translational applications in cell biology.

bioengineering↗

bioRxiv2025

From Dataset Curation to Unified Evaluation: Revisiting Structure Prediction Benchmarks with PXMeter

Recent advances in deep learning have significantly improved the accuracy of structure prediction for biomolecular complexes; however, robust evaluation of these models remains a major challenge. We introduce PXMeter, an open-source toolkit that support consistent and reproducible evaluation of diverse predictive models across a broad spectrum of biological complex structures. PXMeter provides a unified and reproducible benchmarking framework, offering valuable insights to support the ongoing improvement of structure prediction methods. We also present a high-quality benchmark dataset curated from recently deposited structures in the Protein Data Bank (PDB). These entries are manually reviewed to exclude non-biological interactions, ensuring reliable evaluation. Using these resources, we conducted a comprehensive benchmark of several structure prediction models, namely Chai-1, Boltz-1, and Protenix. Our benchmarking results demonstrate the advancements achieved by deep learning models, while also identifying ongoing challenges--especially in modeling protein-protein and protein-RNA interactions. Project Pagehttps://github.com/bytedance/PXMeter

bioinformatics↗

bioRxiv2025

Sphingomyelinase Licensing of Mesenchymal Stromal Cells Alters Lipid and Protein Metabolites for Immunomodulation

Mesenchymal stromal cells (MSCs) are widely studied for their immunomodulatory and tissue reparative capabilities, but clinical translation has been hampered by inconsistent efficacy and limited standardization in manufacturing. While cytokine-based priming methods, such as interferon-gamma (IFN-{gamma}) stimulation, have shown promise in enhancing MSC potency, alternative approaches targeting distinct biological metabolism integral to secretome and membrane architecture have not been explored in MSCs. In this study, we investigate sphingomyelinase (SMase), an enzyme that generates ceramide from sphingomyelin, as a novel lipid-based priming strategy to modulate MSC function. Here, human MSCs were treated with SMase and high-content imaging and morphological profiling revealed that SMase-treated cells adopted a phenotype overlapping with IFN-{gamma}-licensed MSCs, including increased cell compactness and solidity. Lipidomic analysis showed broad alterations in sphingolipid species, and dynamic flux estimation (DFE) modeling predicted distinct metabolic shifts in SMase-treated cells compared to untreated controls. These changes were sustained up to 35 hours post-stimulation, indicating stable metabolic reprogramming. SMase priming also altered the MSC secretome, enriching for factors implicated in immune regulation. Functionally, SMase-primed MSCs retained the ability to suppress T-cell activation and promote anti-inflammatory macrophage phenotypes. Collectively, these findings demonstrate that SMase stimulation induces a durable, immunomodulatory-like state in MSCs through coordinated changes in lipid metabolism and secretory activity. This lipid-centric priming approach represents a promising alternative to cytokine-based licensing strategies and may support therapeutic MSC products.

bioengineering↗

bioRxiv2025

Quality control of single-cell ATAC-seq data without peak calling using Chromap

In this work, we extend Chromap, an ultrafast method for single-cell ATAC-seq data alignment, to directly report peak-based quality control (QC) metrics, such as the fraction of reads in peaks, without calling peaks. Recent single-cell ATAC-seq analysis methods like SnapATAC2 utilize the genome-interval-based feature for data analysis, which disables filtering low-quality cells using common peak-based QC metrics. We show that Chromaps QC metrics capture additional low-quality cells missed by SnapATAC2 and improve downstream analysis results without sacrificing computational efficiency.

bioinformatics↗

bioRxiv2025

Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data

With the dramatic take-up of spatially resolved transcriptomics biotechnologies, performing spatially-aware analysis of the resulting data is crucial to maximise advances in biological understanding. Dimensionality reduction is a first step in almost any analysis of spatial transcriptomics data, regardless of whether the data is collected at the single-cell or spot level. While common approaches, such as principal component analysis, aim to identify low-dimensional scores that preserve total variances of gene expression features, such variances do not usually correspond to biologically relevant spatial variation. To this end, we have developed weighted sliced inverse regression (wSIR), a sufficient dimension reduction technique that performs dimensionality reduction and retains as much predictive power of the spatial coordinates as possible. As a linear dimensionality reduction approach, wSIR is applicable to multiple distinct spatial transcriptomic datasets, and is extremely scalable due to the algorithm and our Rcpp implementation, with over 100, 000 cells processed in under 2 minutes on a standard laptop. The feature loadings are interpretable, and new non-spatial data can be projected into the wSIR low-dimensional space for further downstream analyses. We examine wSIRs performance through benchmarking and demonstrate its capability of biological discovery through two case studies in breast cancer and early embryonic development.

genomics↗

bioRxiv2025

A Novel FNDC1-NAMPT-NAD axis is Implicated in Small and Large-vessel Arterial Disease and Drives Vascular Calcification

Vascular calcification represents a convergent pathological feature of diverse cardiovascular diseases, yet the upstream molecular programs orchestrating this process remain poorly defined. Here, we uncover fibronectin type III domain-containing 1 (FNDC1) as a previously unrecognized regulator of vascular calcification across both microvascular and macrovascular beds. Integrative transcriptomic profiling of human calciphylaxis lesions and atherosclerotic coronaries identified FNDC1 as one of the most significantly upregulated genes. In primary human vascular smooth muscle cells, FNDC1 drove osteogenic phenotype switch and vascular calcification through activation of PI3K/AKT signaling and metabolic reprogramming. Mechanistically, FNDC1 directly binds to nicotinamide phosphoribosyltransferase (NAMPT) resulting in elevated intracellular NAD levels, thus coupling vascular signaling to control of NAD biosynthesis. In murine models, genetic deletion of Fndc1 or pharmacologic inhibition of NAMPT suppressed arterial calcification and prolonged survival. Clinically, circulating FNDC1 levels were elevated in patients with both calciphylaxis and coronary artery disease and independently predicted cardiovascular risk in 42,687 UK Biobank participants. Together, these findings establish FNDC1 as a central mediator of vascular pathology and highlight the FNDC1- NAMPT-NAD+ axis as a promising target for therapeutic intervention.

cell biology↗

bioRxiv2025

Common Signatures of Neutrophils in Diverse Disease Conditions

Neutrophils are traditionally recognized for their pro-inflammatory roles. However, accumulating evidence has begun to highlight the plasticity of transcriptional states of neutrophils during pathological insults. Whether such unconventional neutrophils may share commonality across diverse disease conditions is incompletely understood. Here, we systematically profile over 500,000 neutrophils in key immune compartments and disease-inflicted tissues of the mouse models of metabolic disorder, autoimmunity, tissue damage, peripheral cancers, and intracranial gliomas. Of importance, we observe two distinct neutrophil clusters with unique immune features. The first cluster, characterized by Cd274, Vegfa, and antigen presentation, is highly enriched within the diseased tissues. In contrast, the second cluster with elevated Cd244 and type 2 immune response but reduced maturation markers primarily emerges in the peripheral blood and spleens of specific disease scenarios. These results have elucidated the common signatures of neutrophils in response to various pathological conditions, providing a valuable reference for diagnostic and therapeutic applications.

immunology↗

bioRxiv2025

Ulk1(S555) inhibition alters nutrient stress response by prioritizing amino acid metabolism

Metabolic flexibility, the capacity to adapt fuel utilization in response to nutrient availability, is essential for maintaining energy homeostasis and preventing metabolic disease. Here, we investigate the role of Ulk1 phosphorylation at serine 555 (S555), a site regulated by AMPK, in coordinating metabolic switching following short-term caloric restriction and fasting. Using Ulk1(S555A) global knock-in mice, we show loss of S555 phosphorylation impairs glucose oxidation in skeletal muscle and liver during short-term CR, despite improved glucose tolerance. Metabolomic, transcriptomic, and mitochondrial respiration analyses suggest a compensatory reliance on autophagy-derived amino acids in Ulk1(S555A) mice. These findings suggest Ulk1(S555) phosphorylation as a critical regulatory event linking nutrient stress to substrate switching. This work highlights an underappreciated role of Ulk1 in maintaining metabolic flexibility, with implications for metabolic dysfunction. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/662412v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@33a57aorg.highwire.dtl.DTLVardef@b518ccorg.highwire.dtl.DTLVardef@16f2693org.highwire.dtl.DTLVardef@4daac4_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2025

Latrophilin mediates flow activation of Notch to control vascular endothelial phenotype and atherosclerosis

Fluid shear stress (FSS) is a major determinant of endothelial cell (EC) phenotype, with physio-logical laminar FSS promoting arterial identity and stability, and disturbed FSS promoting atherosclerosis. We previously identified the adhesion G protein-coupled receptor (GPCR) Latrophilin-2 (LPHN2) as a junctional protein required for FSS activation of the PECAM1/VE-cadherin/VEGFR2/PlexinD1 junctional mechanosensory pathway, which regulates EC alignment to laminar blood flow and promotes EC inflammatory activation and atherogenesis under disturbed flow. Here, we demonstrate that Lphn2 endothelial cell-specific knockout hyperlipidemic mice develop larger atherosclerotic plaques than controls--opposite from the previously reported Pecam1 knockout model. Transcriptomic analysis revealed that LPHN2 contributes more than half of flow-responsive gene expression and suppresses pro-inflammatory pathways. Critically, LPHN2 is essential for FSS-induced Notch1 activation to suppress inflammation, via a GPCR-independent mechanism. Active Notch correlates with physical association of LPHN2 with Notch1 activator, {gamma}-secretase, and Notch1 in response to flow. Both the Notch1 intracellular domain (NICD) and transmembrane domain (NTMD) contribute to the anti-inflammatory gene program, with the non-canonical NTMD signaling specifically suppressing the pro-inflammatory YAP pathway. Together with the accompanying paper showing that LPHN2 also mediates flow activation of the Smad1/5 pathway, these data identify LPHN2 as a central mediator of EC flow responses through multiple independent mechanisms in vascular biology and disease.

molecular biology↗

bioRxiv2025

Plagl1 and Lrrc58 control mammalian body size by triggering target-directed microRNA degradation of miR-322 and miR-503

Precise control of microRNA (miRNA) expression is critical during development. An important mechanism of miRNA regulation is target-directed microRNA degradation (TDMD), a pathway in which the binding of miRNAs to specialized trigger RNAs induces ubiquitylation and decay of associated Argonaute (AGO) proteins by the ZSWIM8 ubiquitin ligase. Concomitant release of miRNAs results in their rapid turnover. ZSWIM8-deficient mice exhibit reduced body size, cardiopulmonary and neurodevelopmental defects, and perinatal lethality. Despite widespread dysregulation of miRNAs in these animals, the vast majority of presumptive trigger RNAs that induce decay of ZSWIM8-regulated miRNAs remain undefined. Here, using AGO crosslinking and sequencing of hybrids (AGO-CLASH), a high-throughput method for identifying miRNA binding sites, we report the identification of Plagl1 as a TDMD trigger for miR-322-5p, and Lrrc58 and Malat1 as TDMD triggers for miR-503-5p in mouse embryonic fibroblasts (MEFs). In mice, deletion of the miR-322-5p and miR-503-5p trigger sites in the Plagl1 and Lrrc58 3' UTRs, respectively, abrogated TDMD of these miRNAs and resulted in miR-322/503-dependent embryonic growth restriction, recapitulating a key feature of the Zswim8--/-- phenotype. Thus, Plagl1 and Lrrc58 act as triggers for degradation of miR-322-5p and miR-503-5p, revealing a noncoding function for these mRNAs as regulators of mammalian body size.

molecular biology↗

bioRxiv2025

Beach sand beneath our feet: an overlooked reservoir of antibiotic resistance genes and pathogens, revealed by metagenomic evidence from Qingdao's recreational beaches

Coastal beach environments, especially those with heavy tourist activity, represent a dynamic interface between terrestrial and marine microbiomes. However, beach sand is rarely considered in surveillance of antibiotic resistance. In this study, we combined 16S rRNA gene sequencing and shotgun metagenomics to characterize microbial communities and antibiotic resistance genes (ARGs) at four popular recreational beaches in Qingdao, China. We show that beach sands harbor highly diverse bacterial communities with significantly greater richness than adjacent seawater. Beach sand near sewage discharge points had microbial profiles intermediate between raw sewage and open-ocean water, reflecting contributions from both sources. Metagenomic analysis identified a broad "resistome" of over 300 distinct ARGs in these beach and water samples, spanning 33 antibiotic classes and 6 resistance mechanism categories. Notably, the rifampicin resistance gene rpoB2 was the most abundant ARG, and genes conferring resistance to peptide antibiotics were prevalent. Sewage outfalls were found to be major contributors of ARGs, with waste-influenced sand containing a larger and more diverse ARG pool than sand farther from pollution sources. We also detected a high diversity of bacterial virulence factor genes, particularly in sand. Our findings highlight that tourist beaches can serve as reservoirs and mixing zones for antibiotic-resistant and potentially pathogenic bacteria from land-based pollution. This underscores the need to include beach sand in environmental monitoring for antibiotic resistance and to improve wastewater management at recreational coastlines to mitigate public health risks. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/661489v1_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@18705f3org.highwire.dtl.DTLVardef@1979f8forg.highwire.dtl.DTLVardef@16c9029org.highwire.dtl.DTLVardef@6c778d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

EVODEX: A Mechanistic Framework for Extracting, Structuring, and Predicting Enzymatic Reactivity

Accurately modeling enzymatic reactivity is essential for synthesis planning, mass spectrometry interpretation, and biochemical knowledge extraction, but existing reaction datasets are often incomplete or inconsistently annotated. EVODEX introduces two abstractions to address this: partial reactions, which isolate atom-mapped substrate-product transformations from complex biochemical reactions, and Electronic Reaction Operators (EROs), which encode the bonding and orbital environment of atoms undergoing change. From 349,458 curated reactions in EnzymeMap, EVODEX constructs over 186,000 partial reactions and mines a core set of 1,404 EROs, each supported by at least 10 examples. Together, these explain 91 percent of test reactions at the formula level and 62 percent at the mechanistic level. A further filtered synthesis subset of 436 one-to-one operators that exclude ubiquitous metabolites provides a compact and generalizable vocabulary of single-step enzymatic transformations. EVODEX operators are auditable, reusable, and available as part of an open-source Python package with datasets, Jupyter notebooks, and a browsable website.

bioinformatics↗

bioRxiv2025

TWEAK Signaling Drives the Transition from Psoriasis to Atopic Dermatitis-like Inflammation in Paradoxical Skin Reactions

Targeted biologics have significantly advanced the treatment of inflammatory skin diseases such as psoriasis; however, some patients paradoxically develop eczematous skin reactions during or after anti-TNF, IL-17, or IL-23 therapy. Although these paradoxical reactions resemble atopic dermatitis clinically and histologically, the molecular mechanisms that drive their development are not fully understood. Here, we generated high-resolution cellular and spatial maps of healthy skin, psoriasis, atopic dermatitis, and paradoxical reactions using single-cell RNA sequencing, spatial transcriptomics, immunohistochemistry, and in vitro assays. In paradoxical reactions, we identified a distinct transcriptional landscape characterized by myeloid and T-cell expansion and an altered keratinocyte phenotype shaped by TWEAK signaling. Mechanistically, we showed that TWEAK synergizes with IL-13 to drive the Th2/type I interferon-polarized epithelial program. Notably, anti-TNF therapy induced TWEAK gene expression in myeloid cells, suggesting a compensatory inflammatory circuit. Together, these findings identify the TWEAK-IL-13 axis as a central driver of paradoxical skin reactions and provide a mechanistic framework for how cytokine blockade may rewire cutaneous immune responses. One Sentence Summary The TWEAK-IL-13 signaling axis is a key driver of immune reprogramming underlying paradoxical skin reactions.

immunology↗

bioRxiv2025

The bifunctional dynamin-like GTPase switch DynAB modulates both vegetative and sporulation cell division in Streptomyces.

As part of their complex developmental lifecycle, the multicellular filamentous bacteria Streptomyces have evolved two modes of cell division distinct from binary fission. In vegetative cell division, irregularly spaced cross-walls form within vegetative hyphae, whereas in sporogenic hyphae, regularly spaced sporulation septa form synchronously, leading to spore formation. However, the mechanisms controlling these processes largely remain unknown. The bacterial dynamin-like protein pair DynAB was previously reported to be a component of sporulation septa. Here, we reveal that DynA and DynB have critical roles in both cell division modes, regulating the formation of sporulation septa and cross-walls, with the Streptomyces cell division protein SsgB modulating their activities. dynAB deletion and overexpression, respectively, increased and abrogated cross-wall formation in vegetative hyphae, and Streptomyces DynAB also inhibited cell division in Escherichia coli, resulting in formation of unicellular filamentous cells and suggesting an ancient and conserved function for these proteins. Notably, SsgB could relieve the inhibition of cell division by DynAB in both Streptomyces and E. coli. In contrast to DynAB, SsgB overexpression generated spore-like compartments in vegetative hyphae, a phenomenon that required disruption of the DynAB complex. Fluorescent tags revealed dynamic localization of DynAB during development, and further analyses indicated that, in sporogenic hyphae, the timing of DynAB expression, their GTP-binding activity, and interaction with SsgB were associated with the synchronous initiation of sporulation septation. Our findings establish DynAB as an integrator of spatiotemporal cues in bacterial multicellularity and provide insights into the evolution of complex cell cycle regulation in prokaryotes. SignificanceThe evolution of multicellularity in bacteria involved the development of complex mechanisms to spatially and temporally coordinate cell division. Streptomyces, renowned for their production of bioactive secondary metabolites, exemplify bacterial complexity. This study reveals how Streptomyces employ the dynamin-like proteins DynAB as a bifunctional molecular switch, enabling transition between vegetative and reproductive growth through integrated interactions with developmentally regulated proteins and the availability of the energy supplier GTP. Importantly, DynAB could repress cell division in both Streptomyces and Escherichia coli, suggesting an evolutionary origin of these proteins prior to bacterial multicellularity. Our work reveals the dual function and switch mechanism of DynAB in Streptomyces, providing insights into the emergence of dynamic cell cycle control in prokaryotes.

microbiology↗

bioRxiv2025

An atlas of cell type specific regulatory effects in cattle

Understanding the genetic and molecular architecture of complex traits and artificial selection is crucial for advancing sustainable precision breeding in cattle and other livestock. Yet, how genetic variation affects cellular gene expression remains elusive in cattle. Here, by integrating 8,866 bulk RNA-seq samples and 999,192 single cells of 81 cell types in 22 bovine tissues, we presented a comprehensive atlas of regulatory variants at the cell type resolution in cattle. By colocalizing with bulk-tissue expression quantitative trait loci (beQTL), we detected 57,043 novel cell-type stratified eQTL and cell-type/state interaction eQTL in 18,153 genes, which also exhibited a stronger tissue/cell-type specificity than beQTL. By examining genome-wide associations (GWAS) of 44 complex traits, these cell-resolved eQTL were colocalized with 505 (24%) additional GWAS loci compared to beQTL. Through integrating this resource with selection signatures between dairy and beef cattle, we provided tissue/cell-specific regulatory insights into cattle breeding. Overall, the current atlas of cell-type-specific regulatory variants will serve as an invaluable resource for cattle genomics and selective breeding.

genetics↗

bioRxiv2025

High-throughput Single-cell Proteomics Enabled by an Integrated Hyperplexing and Automatic Labelling Approach without Fractionation

Single-cell proteomics (scProteomics) enables comprehensive analysis of protein composition, expression and functions at the single-cell level. While label-free techniques have generated promising results, achieving high-throughput scProteomics remains a substantial challenge. In this study, we present an approach that increases scProteomics throughput by approximately 30-fold through the true integration of isobaric tags (IBT) with tandem mass tags (TMT), a method we term Integral-Hyperplex. Due to remarkable differences in signal response between TMT16 and IBT16 reporter ions, we implemented two normalization strategies to ensure accurate and integrated quantification: (1) the inclusion of a normalization channel in both IBT and TMT groups to serve as internal standards; and (2) the generation of protein-specific conversion factors between IBT16 and TMT16 signals. We validated the quantification accuracy of the Integral-Hyperplex method by labeling HeLa digests at varying ratios. Furthermore, we demonstrated fully automated labeling on the active-matrix digital microfluidics chip, consuming only 12 nL of labeling reagent per single cell and with a reaction volume as low as 20 nL. Our approach was validated through proof-of-principle quantification experiments across three types of single cells. Approximately 2,000 protein groups were quantified per cell, and the three cell types can be well clustered, confirming the reliability of the Integral-Hyperplex approach. Approximately 300 samples can be analyzed per day due to insufficient resolution of timsTOF SCP. Throughput can be further enhanced using TMT32, additional labeling reagents, and more advanced mass spectrometers such as Orbitrap Astral and timsTOF Ultra 2, and our approach is theoretically capable of analyzing up to [~]2,000 single cells per day.

biochemistry↗

bioRxiv2025

Herpes simplex virus-1 fluidizes the nucleus enabling condensate formation

Molecular processes are profoundly influenced by the biophysical properties of the cell interior. However, the mechanisms that control these physical properties, and the processes they impact remain poorly understood, especially in the nucleus. We hypothesized that some viruses might change the biophysical properties of the nucleus to favor virus survival and replication and found that herpes simplex virus 1 (HSV-1) increases the mesoscale fluidity of the nucleus. The HSV-1 protein ICP4 caused fluidization and enabled growth of synthetic nuclear condensates. Conversely, conditions that decreased nuclear fluidity inhibited the growth of viral replication compartment condensates and reduced infectious virus production. Together, our data suggest that ICP4 increases nuclear fluidity to promote the formation of condensates that drive the progression of the HSV-1 life cycle. We speculate that a key function of ICP4 is to overcome the crowding and elastic confinement within cell nuclei that are a fundamental barrier to virus replication.

cell biology↗