Biology subjects

Zhou, S.

Publications and source records attributed to Zhou, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

New insights into the evolution of spider silk proteins illuminated by long-read transcriptomes

Spider silk has long fascinated scientists because of its exceptional mechanical properties, yet the evolutionary origins and diversification of spider silk proteins (spidroins) remain incompletely understood. By analyzing long-read spidroin transcripts from spiders representing key evolutionary lineages, we identify two ancestral proteins present in basal spiders: an alanine-serine-rich (AS-type) protein and a glycine-serine-rich (GS-type) protein. These ancestral proteins likely served as primary evolutionary templates for the diversification of modern spider silks. We show that the AS-type ancestral spidroin remained relatively conserved and ultimately gave rise to the specialized tubuliform spidroin (TuSp) used in eggcase silk. In contrast, the GS-type protein underwent extensive functional radiation, evolving into differentiated minor ampullate spidroins (MiSp) through the acquisition of distinct terminal domains and {beta}-sheet-associated structural innovations. Our results further suggest that major ampullate spidroins (MaSp) may have originated from MiSp, with the GS motif representing an evolutionarily favorable genetic substrate for the emergence of high-performance silk proteins. Finally, we propose a revised evolutionary trajectory for flagelliform spidroins (Flag), suggesting that they were co-opted as components of ampullate silk during functional degeneration in modern non-web-weaving RTA clade spiders. Together, these findings provide a high-resolution framework for understanding the genetic innovations that drove the diversification of spider silk.

evolutionary biology↗

bioRxiv2025

Identification of cis-Acting Elements that Regulate Influenza A Virus Segment 7 Differential mRNA Splicing

Influenza A virus segment 7 encodes the M1 matrix protein and M2 ion channel from an unspliced primary transcript mRNA1 and spliced mRNA2, respectively. Both proteins are essential for efficient virus replication, but the intrinsic sequences that determine segment 7 splicing balance are not fully defined. Here, we systematically investigated how conserved cis-acting splicing elements regulate 7 splicing. We found that while the splice acceptor sequence is optimal, both potential upstream polypyrimidine tracts regulate splicing, the 5 region acting positively and the 3 region negatively to maintain M1 expression. We could not unambiguously identify the mRNA2 branch point, but two closely spaced motifs can act redundantly. Saturation mutagenesis of the mRNA2 splice donor sequence showed that it is nearly optimal but that nucleotides 51 and 55 modestly downregulate splicing efficiency. Most introduced mutations that change splicing balance are nonsynonymous in M1. Nevertheless, mutations in the polypyrimidine tract and branch points that significantly perturbed M1:M2 balance resulted in viable viruses. In contrast, the splice donor sequence was intolerant of mutation. We conclude that M1:M2 balance is maintained via suboptimal splice donor and polypyrimidine tract splicing signals, with the latter allowing more evolutionary flexibility to vary the ratio and/or M1 sequence.

microbiology↗

bioRxiv2025

Ultrahigh-Throughput Forster Resonance Energy Transfer-Activated Droplet Sorting for Terminator Polymerase Engineering

Droplet microfluidic screening systems enable high-throughput, labor-saving enzyme directed evolution by employing fluorescence, absorbance, and Raman-activated sorting strategies for library screening. Forster resonance energy transfer (FRET) - a nanoscale technique for monitoring intramolecular/intermolecular conformational changes - is yet to be integrated into this process. We upgraded a single-channel sorter to a dual-channel one without redesigning the microscopy setup, which can monitor FRET signals during enzyme reactions in droplets at kilohertz rates. We applied this upgraded sorter to improve the incorporation efficiency of KOD DNA polymerase towards reversible terminator deoxyribonucleotides, a property crucial for its application in next-generation sequencing (NGS). Our data show that a single-round sorting can achieve 30-fold enrichment of active variants. Five KOD variants enabling 100-cycle single-end runs of DNA sequencing were identified using a novel cyclic reversible termination (CRT) substrate featuring a terminator group {approx} 5-fold bulkier than the classical azidomethyl moiety. We also engineered a metagenome-derived novel polymerase, and a variant achieving 90% terminator incorporation efficiency within 2 minutes was identified after two rounds of enrichment. In sum, we provide a practical setup for dual-channel FRET-based droplet sorting, and demonstrate its ability in terminator polymerases engineering, thereby broaden the scope of microfluidic applications.

biochemistry↗

bioRxiv2025

The NuRD complex shapes RNA polymerase III activity at highly expressed tRNA gene clusters, tuning the dynamic range of cellular tRNA pools

RNA polymerase III (Pol III) produces noncoding RNAs involved in diverse cellular activities, including translation (tRNA, 5S rRNA, 7SL RNA), RNA processing (U6 snRNA, RPPH1, RMRP), and transcription regulation (7SK snRNA). In this way, Pol III activity must be broadly coupled with cellular demands for protein accumulation and growth, increasing in response to nutrient availability and decreasing during differentiation and exit from proliferation. However, the currently established mechanisms of Pol III regulation remain relatively limited, due in part to the few Pol III-centered protein-protein interaction (PPI) studies performed to date. To address this gap, we first investigated PPIs shared by multiple Pol III subunits to understand the macromolecular interactome of Pol III, with special attention directed at potential regulatory candidates. Our proteomic survey uncovers interactions between Pol III and the NuRD (Nucleosome Remodeling and Deacetylase) complex. Taken further, we show that NuRD localizes to active Pol III-transcribed genes and that its recruitment is Pol III-dependent but nonrandom, with peak occupancy and regulatory hallmarks converging on tRNA gene clusters associated with notably high expression levels. Inhibiting NuRD-associated histone deacetylase function reduces Pol III transcription at these sites, suggesting NuRD restricts Pol III and thereby modulates the global dynamic range of Pol III-derived RNA species. These findings are congruent with the transcriptionally repressive nature of NuRD and bring-to-light a new regulatory mechanism that may couple signaling events and changes in metabolic needs with the dynamic availability of specific tRNA pools.

molecular biology↗

bioRxiv2025

Engineering immunotoxin-equipped effector cells and evaluation in primary human immune cells

Lethal toxins could become potent therapies against cancer, but their clinical utility is limited by adverse events upon systemic administration. These could be reduced if the toxins were delivered by effector cells that specifically infiltrate cancers, thereby releasing toxins locally into the tumor microenvironment. One of the challenges underlying this strategy is that cells delivering toxins would have to be resistant to them. We address this obstacle by showing that effectors derived from transformed human cell lines genetically engineered for resistance to bacterial adenosine diphosphate ribosylating toxins (ADPRTs), including Pseudomonas aeruginosa exotoxin A (PE), can produce targeted immunotoxins that specifically kill cancer cells expressing cognate tumor-associated antigens. Resistance to immunotoxins was achieved by knockout of genes in the diphthamide biosynthesis pathway (DPH1-4) required for the posttranslational modification of eukaryotic elongation factor 2 (EEF2) that is the target of ADPRTs, or by mutation of EEF2 itself. We show that engineering resistance to ADPRTs, one of the most potent toxins acting on human cells, is essential to achieve robust function of armored effector cell lines. This work establishes a first step on the path to equip effector cells with the ability to deliver powerful toxins to cancer cells and introduces a platform to investigate extension to primary autologous or allogeneic therapeutic cell types.

molecular biology↗

bioRxiv2025

Single-cell phenotypic analysis and multiplet detection through incorporation of microscopy data into cellenONE-based single-cell proteomic data analysis

The reliability of single-cell proteomics (SCP) is intrinsically linked to the fidelity of cell isolation; however, the identification of co-isolated cells (doublets or multiplets) remains a persistent challenge for single-cell (sc-) omics. While single-cell transcriptomics has established probabilistic frameworks for doublet detection, these methods are ill-suited for the sparser throughput of SCP datasets. This work presents scpImaging, a novel computational pipeline that repurposes the latent microscopy data routinely generated during cellenONE-based sample preparation to provide deterministic quality control (QC) and high-content phenotypic profiling. We demonstrate that standard proteomic quality metrics for SCP (e.g., peptide count, signal intensity) paradoxically favour retaining doublets. In contrast, scpImaging applies machine-learning-based cell segmentation (Cellpose-SAM) to identify and exclude these artefacts with high precision. Furthermore, the framework integrates morphological metrics generated using the open-source CellProfiler, with proteomic abundance data, enabling joint analysis that links cell shape and texture to molecular cell state. Provided as an open-source R package, scpImaging offers a scalable, automated solution for enhancing data integrity and adding a phenotypic dimension to SCP experiments without increasing experimental cost or complexity.

systems biology↗

bioRxiv2025

A SARS-CoV-2 entry inhibitor trimerizes to lock the spike protein in a closed conformation

The SARS-CoV-2 spike protein binds its receptor ACE2 to initiate target-cell infection. To engage ACE2, at least one of the three receptor-binding domains (RBDs) of the spike must adopt the up orientation. Here we describe S22, a potent, bioavailable, and non-toxic inhibitor of BA.2 and all subsequent Omicron variants. Cryo-EM analyses showed that S22 assembled as a trimer in a previously uncharacterized pocket of the spike apex, stabilizing all three RBDs in the down orientation, thereby preventing ACE2 association. Binding studies, especially those using mixed S22-sensitive and -resistant spikes, imply a cooperative assembly of three S22 molecules with three RBDs, resulting in an unusually slow S22 off-rate. Consistent with its slow dissociation and favorable pharmacokinetics, S22 suppressed viral replication 100-fold in the lungs of XBB.1.5-infected mice. Thus, S22 potently inhibits Omicron entry through a distinct mechanism whereby a small compound assembles cooperatively as a trimer to stabilize spike in an inactive conformation.

microbiology↗

bioRxiv2025

Seqwin: Ultrafast Identification of Signature Sequences in Microbial Genomes

MotivationPolymerase chain reaction (PCR) enables rapid, cost-effective diagnostics but requires prior identification of genomic regions that allow sensitive and specific detection of target microbial groups, herein referred to as microbial signature sequences. We introduce Seqwin, an open-source framework designed to automate microbial genome signature discovery. Tens of thousands of microbial genomes are now available for a single species, limiting the application of existing manual and automated approaches for identifying signatures. Modern approaches that are capable of leveraging all available microbial genomes will ensure sensitive and accurate DNA signature identification and enable robust pathogen detection for clinical, environmental, and public health applications. ResultsSeqwin builds weighted pan-genome minimizer graphs and uses a traversal algorithm to identify signature sequences that occur frequently in target genomes but remain rare in non-targets. Unlike earlier tools that depend on strict presence or absence of sequences, Seqwin accommodates natural sequence variation and scales to very large genome collections. When applied to genomes from C. difficile, M. tuberculosis, and S. enterica, Seqwin recovered more high-quality signatures than alternative methods with lower computational burden. Seqwins analysis of nearly 15,000 S. enterica genomes yielded over 200 candidate signatures in 5 minutes. Seqwin provides an open-source solution for the long-standing need for scalable microbial signature discovery and diagnostic assay design. Availability and ImplementationSeqwin is freely available for academic use (https://github.com/treangenlab/Seqwin) and can be installed via Bioconda. Benchmarking datasets, outputs, and scripts are available on Zenodo https://doi.org/10.5281/zenodo.19176444. Contacttreangen@rice.edu, xw66@rice.edu Supplementary MaterialsProvided as separate PDF and data files.

bioinformatics↗

bioRxiv2025

Blockade of associative spine enlargement impairs awake cortical function

Awake cognition is usually attributed to arousal systems and ongoing electrical activity, yet these do not explain how cortical processing is coupled to prior context and memory formation. Associative synaptic plasticity provides a cellular mechanism for such coupling, but is viewed as memory-related rather than an online requirement for cognition. Here we developed SynC, an A/C-activated chemogenetic perturbation that selectively and reversibly blocks associative spine enlargement while sparing non-associative spine dynamics, excitability, synaptic transmission and NMDA receptor-mediated responses. In mice with broad frontoparietal SynC expression, acute A/C reversibly impaired open-field centre exploration, abolished laser-dot chasing, and delayed feeding initiation. During quiet-wake immobile epochs, cortical firing rates and {gamma}-band power were preserved, but pairwise spike correlations were reduced. Mice also intermittently showed sudden behavioural arrest with reduced {gamma} activity but without the robust {delta} elevation of slow-wave sleep. Critically, in vivo two-photon glutamate uncaging induced seconds-scale associative spine enlargement in [~]24% of neocortical spines, acutely blocked by SynC-A/C. These A/C-induced behavioural, circuit and spine-enlargement effects recovered within 1 h. Thus, wake-like firing and {gamma} activity are not sufficient to sustain awake cognitive function. Rapid associative spine enlargement is required to maintain functional cortical coupling and stable wakefulness.

neuroscience↗

bioRxiv2025

Neuronal SET1/COMPASS-mediated epigenetic regulation of de novo transcription drives accelerated forgetting with age

Forgetting is a critical component of memory, but its molecular regulation - particularly with age - is not well understood. Epigenetic modifications are a candidate for this regulation and may further drive age-related behavioral decline, as they are dramatically altered in the aging brain. We found that multiple components of the SET1/COMPASS complex, a conserved histone methyltransferase complex associated with active gene transcription, are upregulated with age in the C. elegans nervous system. Neuronal knockdown of the SET1/COMPASS components improves memory in young adult animals and slows memory decline in old animals. By pharmacological and genetic inhibition, optogenetics, and neuronal mRNA and chromatin profiling, we demonstrate that SET1/COMPASS-mediated active transcription promotes forgetting. SET1/COMPASS regulates the de novo activity-dependent transcription and release of a neuropeptidergic signal from the AWC olfactory sensory neuron, which erases the associative memory trace in downstream motor neurons, resulting in forgetting. We further found that increased SET1/COMPASS-dependent chromatin accessibility at these gene loci with age primes these loci for transcription, resulting in accelerated forgetting. Our results reveal the role of active gene transcription in the regulation of forgetting and altered SET1/COMPASS-mediated gene transcription as a mechanism of cognitive decline, implicating increased expression of COMPASS components as a driver of increased forgetting in the aging brain. This mechanism may offer a new target for slowing loss of cognitive function with age.

neuroscience↗

bioRxiv2025

PlantScience.ai: An LLM-Powered Virtual Scientist for Plant Science

The accelerating growth of plant science literature presents a major challenge for researchers seeking to extract accurate, up-to-date knowledge from an increasingly fragmented and domain-specific corpus. General-purpose large language models (LLMs), while powerful, often misinterpret plant science terminology and lack mechanisms for source traceability. We created PlantScience.ai, a virtual plant biology scientist powered by our automated scientific knowledge graph construction pipeline (AutoSKG). PlantScience.ai exhibits expert-level reasoning in plant biology and maintains scholarly rigour in its citations. Through continuous learning, it integrates the latest research, ensuring that its knowledge base remains current and scientifically robust. Apart from providing the answers to the scientific questions, PlantScience.ai can interact with human scientists, follow instructions, and retrieve information with citation awareness, grounding each response in primary sources to ensure accuracy and verifiability. PlantScience.ai marks a pivotal advance toward a collaborative scientific paradigm in which virtual and human plant scientists work synergistically to accelerate discovery while preserving the unique value of human insight. PlantScience.ai is available at https://plantscience.ai.

plant biology↗

bioRxiv2025

DNACSE: Enhancing Genomic LLMs with Contrastive Learning for DNA Barcode Identification

DNA barcoding is a powerful tool for exploring biodiversity, and DNA language models have significantly facilitated its construction and identification. However, since DNA barcodes come from a specific region of mitochondrial DNA and there are structural differences between DNA barcodes and reference genomes used to train existing DNA language models, it is difficult to directly apply the existing DNA language models to the DNA barcoding task. To address this, this paper introduce DNACSE (DNA Contrastive Learning for Sequence Embeddings), an unsupervised noise contrastive learning framework designed to fine-tune the DNA language foundation model while enhancing the distribution of the embedding space. The results demonstrate that DNACSE outperforms direct usage of DNA language models in DNA barcoding-related tasks. Specifically, in fine-tuning and linear probe tasks, it achieves accuracy rates of 99.17% and 98.31%, respectively, surpassing the current state-of-the-art BarcodeBERT by 6.44% and 6.44%. In zero-shot clustering tasks, it raises the Adjusted Mutual Information (AMI) score to 92.25%, an improvement of 8.36%. In addition, zero-shot benchmarking and genomic benchmarking tests are evaluated, indicating that DNACSE enhances the performance of DNA language models in generalized genomic tasks. In summary, DNACSE has demonstrated excellent performance in DNA barcode species classification by making full use of multi-species information and DNA barcode information, providing a feasible way to further explore and protect biodiversity. The code repository is available at https://github.com/Kavicy/DNACSE.

bioinformatics↗

bioRxiv2025

Precision targeting of autoreactive B cells in systemic lupus erythematosus using anti-9G4 idiotope synthetic immune receptor T cells

Chimeric antigen receptor (CAR)-T cell therapies can induce drug-free remission in systemic lupus erythematosus (SLE), but indiscriminate B cell targeting causes immunosuppression, unnecessary infections, and cytokine toxicities that preclude widespread use. Here, we overcome this by targeting the 9G4 idiotope, a shared structural feature of pathogenic B cell receptors encoded by the IGHV4-34 gene. We engineered anti-9G4 CAR-T cells and chimeric TCR-T cells to selectively eliminate autoreactive B cells while preserving protective immunity. Both platforms eradicated autoreactive B cells and autoantibodies in vitro and in vivo, spared normal B cells, and markedly reduced cytokine release compared to conventional CAR-T cells. This precision extended to cold agglutinin disease and lymphoma. These findings establish a framework for IGHV idiotope-directed cellular therapies for treating autoimmune and neoplastic diseases while preserving immune competence.

immunology↗

bioRxiv2025

Axially swept dithered light-sheet microscope to reveal cardiac morphology

Understanding cardiac microstructure and vascular networks in their entirety is critical for assessing cardiovascular development, disease progression, and therapeutic interventions. Light-sheet microscopy combined with tissue clearing enables high-resolution volumetric imaging of intact organs but faces limitations in trabeculated myocardium due to trade-offs among light-sheet thickness, effective range, and frame rate. We exploit temporal dynamics that govern illumination-detection interplay to maintain uniform resolution across specimens. Building on this, we implemented high-speed dithered light-sheet (DiLS) illumination, extending the confocal region by over 40% and enhancing the space-bandwidth product while preserving optical sectioning. Integration of DiLS with a sweeping approach establishes the axially swept dithered light-sheet (AS-DiLS), which enhances imaging throughput while preserving axial resolution and enables uniform illumination up to 12.5-millimeter range. AS-DiLS delivers near-isotropic resolution (~2.5 m) for investigating intricate ventricular trabeculae, vasculature, and extracellular matrix, providing a scalable platform for comprehensive cardiovascular morphology and topology assessment from embryos to adults. TeaserVolumetric imaging reveals microstructure and vascular networks in their entirety with near-isotropic resolution.

bioengineering↗

bioRxiv2025

Prolactin links psychological stress to psoriasis via a fibroblast-chemokine pathway

Psoriasis is a chronic inflammatory skin disease that forms a vicious cycle with psychological stress. Whether and how the hypothalamic-pituitary (HP) axis-mediated neuroendocrine system regulates psoriasis remains obscure. Here, we report elevated levels of the pituitary hormone prolactin (PRL) in both psoriasis patients and imiquimod (IMQ)-induced psoriasis mice. Mechanistically, PRL acts on dermal PRLR-expressing fibroblasts to promote the production of the chemokines CCL2 and CCL7, which then recruit monocytes/macrophages into psoriatic lesional skin, thereby activating local IL-17A-producing T cells. Accordingly, pharmacological targeting of PRL signaling inhibits the recruitment of monocytes/macrophages, decreases the frequency of IL-17A-producing T cells, and alleviates IMQ-induced psoriasis in mice. In summary, our results delineate a mechanism by which the neuroendocrine hormone PRL aggravates psoriasis and highlight a potential therapeutic strategy of inhibiting PRL-PRLR signaling, particularly in psoriasis patients experiencing psychological stress.

immunology↗

bioRxiv2025

Agro-STARR-seq enables in planta genome-wide enhancer discovery and AI-empowerd enhancer design

Comprehensive enhancer screening is essential for dissecting gene regulatory networks. However, methods for such screening remain limited in plants. We present Agro-STARR-seq, an in planta enhancer screening platform using Agrobacterium-mediated delivery of STARR-seq libraries into Nicotiana benthamiana leaves. In the Arabidopsis genome, we identified 14,715 sequences with enhancer activity, of which 91.59% were located outside of open chromatin regions. This largest in planta enhancer dataset to date enabled AI-assisted design of highly active synthetic enhancers. For the large N. benthamiana genome, we pre-processed the genomic DNA with an Assay for Transposase Accessible Chromatin (ATAC) procedure before the Agro-STARR-seq protocol,and found that only one-third of open chromatin exhibited enhancer activity, 76.00% of which showed no canonical H3K27ac histone marks. Footprinting analysis further enables systematic linkage of transcription factor (TF) binding to enhancer function. Overall, Agro-STARR-seq provides a novel platform for dissecting and engineering plant enhancers.

genomics↗

bioRxiv2025

An image-based CRISPR screen reveals splicing-mediated control of HP1α condensates

Heterochromatin Protein 1 (HP1) is a fundamental component of constitutive heterochromatin, forming subnuclear condensates whose regulation and function remain poorly understood. Here, we present an image-based CRISPR screen targeting nuclear factors that identifies splicing as a pivotal pathway regulating HP1 condensates. We discovered that unspliced intronic RNA modulates HP1 condensates by interacting co-transcriptionally with HP1. By modulating the intron content, RNA processing restricts HP1-RNA interactions at chromatin, thus enabling heterochromatin organization. Disruption of HP1 condensates due to enhanced interactions with unspliced RNA leads to loss of heterochromatin and the activation of stress response protective genes. We propose that RNA is a central component of heterochromatin that modulates HP1 condensates, and that RNA processing enzymes act as a surveillance mechanism for condensates by dynamically regulating the network of multi-valent interactions between RNA and chromatin factors. This model underscores the crosstalk between chromatin organization, transcription, and RNA processing, potentially governing broader nuclear functions.

genetics↗

bioRxiv2025

An Interactive AI Agent for Adaptive Modeling of RNA Region-Ligand Interactions via LLM-Generated Machine Learning Workflows

Precise modeling of RNA-ligand interactions is essential for understanding RNA functionality and designing RNA-targeted therapeutics. Current computational approaches largely focus on predicting discrete binding sites, limiting their applicability to complex RNA regions that may harbor multiple or diffuse ligand binding motifs. Here, we present RLAgent, an interactive agent framework designed to predict ligand interactions at the RNA region level, enabling higher-resolution and more flexible modeling than conventional site-centric approaches. RLAgent reframes the RNA-ligand prediction workflow as a dialogue-driven process. Through a natural language interface, users can interactively configure modeling preferences without writing code. A locally hosted large language model (LLM) acts as the core orchestration agent, automating all key components of the modeling pipeline, including data validation, feature encoding, model training, evaluation, and visualization. This agent-based design lowers technical barriers and enhances reproducibility, making RNA-ligand prediction more accessible for both computational and experimental researchers.

bioinformatics↗