Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 361 records · Page 20Linked to original sources

bioRxiv2025

Harmful algal bloom species Microcystis aeruginosa releases thiamin antivitamins to suppress competitors

In environmental ecosystems, vitamin concentrations are often exceedingly low (1, 2) and auxotrophy, or reliance on exogenous vitamin or vitamin precursors, is widespread (3-5). We show here that the widespread harmful algal bloom (HAB) species Microcystis aeruginosa, threatening freshwater aquatic ecosystems globally, releases a complex mixture of thiamin antivitamins, including bacimethrin and methoxythiamin, which induce thiamin deficiency in the benign model green alga Chlamydomonas reinhardtii. Putative biosynthetic genes for bacimethrin were upregulated in M. aeruginosa when grown in co-culture resulting in greater production of bacimethrin. Bacimethrin, methoxythiamin, oxidized forms of thiamin and methoxythiamin, and a novel structural homolog of bacimethrin were all found at elevated levels in the co-culture exometabolome extracts and were all inhibitory to the growth of C. reinhardtii individually at very low concentrations and as a mixture in culture medium extracts. The thiamin-requiring mutant C. reinhardtii, CC-25, was much more sensitive to bacimethrin and methoxythiamin than the wildtype. Thiamin addition largely rescued the inhibitory effects of exposure to antivitamins in both the wildtype and mutant strain. Finally, we determined that bacimethrin is present in aquatic environments and is elevated during Microcystis blooms. Thus, allelopathic suppression of competitors, particularly those that are auxotrophic for thiamin, by M. aeruginosa via the production of antivitamins in environments where thiamin availability is low, could help this species to become dominant and form blooms.

microbiology↗

bioRxiv2025

CellLoop: Identifying single-cell 3D genome chromatin loops

Single-cell 3D genome mapping offers insights into chromatin architecture, yet the inherent sparsity and high dimensionality of contact maps hinder reliable identification of chromatin loops at the single-cell level. Here, we present CellLoop, a single-cell chromatin loop detection algorithm based on a density-based center detection framework that integrates intra-cellular and neighboring inter-cellular contacts via a re-voting strategy. Applied to Dip-C data from the mouse brain, CellLoop demonstrates superior accuracy based on the genome spatial distance and compartment signals at the single-cell level. It reveals cell-specific chromatin loops linked to transcriptional regulation and improved cell state classification. In HiRES embryogenesis data, CellLoop refines cell subtype definitions by minimizing cell cycle effects. Integrating GAGE-seq with MERFISH in mouse cortex, CellLoop redefines spatial domain functions through chromatin loop dynamics. Together, CellLoop enables robust, scalable, and biologically meaningful single-cell chromatin loop detection.

bioinformatics↗

bioRxiv2025

Customizable host and viral transcript enrichment using CRISPR-Cas9 long-read sequencing for isoform discovery and validation

Long-read RNA sequencing has been broadly utilized to examine the diversity of transcriptomes, understand differential expression and discover novel transcript isoforms. One of the major limitations of whole transcriptome sequencing is the difficulty in obtaining sufficient depth for low abundant transcripts. Methods which address this are either difficult to scale or customize: long- range PCR is customizable but difficult to scale beyond a few targets; probe hybridization panels are suited for scaling but require substantial investment to customize. In this study, we adopted RNA-guided CRISPR-Cas9 nuclease-based enrichment to target specific human and SARS-CoV-2 transcripts followed by long-read sequencing, utilizing minimal number of guide RNAs per target isoform. Our findings demonstrate that the CRISPR-Cas system is a highly effective method for customizable long-read sequencing of target transcripts while maintaining the accuracy of relative gene expression levels. The results highlight a valuable method for future research on transcript enrichment for isoform identification and low abundance transcript detection in infectious disease diagnosis.

genomics↗

bioRxiv2025

Influence of Macrocyclization Strategies on DNA-Encoded Cyclic Peptide Libraries

Discovery of cyclic peptide hits using DNA-encoded libraries (DELs) has recently been extensively researched, with significant efforts directed toward developing DEL-compatible macrocyclization methods. To investigate how different cyclic linkers influence DEL selection outcomes, we constructed eight distinct sub-libraries and screened them against two protein targets, MDM2 and GIT1, resulting in two representative yet contrasting scenarios. Validation studies for MDM2 revealed that structural similarity patterns observed across multiple sub-libraries could enhance confidence in the authenticity of identified hits. Notably, cmp-10 demonstrated potent inhibitory activity, exhibiting an inhibition constant of 11 nM. In contrast, selections against GIT1 produced discrete enrichment patterns. From these outcomes, two exemplary compounds were selected and validated through both on-DNA and off-DNA modes. cmp-17 was confirmed to bind specifically to the desired binding pocket, displaying a dissociation constant of 1.22 M. Furthermore, ITC experiments using mutant GIT1 proteins (GIT1L271A/L279A and GIT1L271L/L279L) provided additional insights into the mechanism by which cmp-17 disrupts the interaction between GIT1 and {beta}-Pix.

biochemistry↗

bioRxiv2025

Integration of the hammerhead ribozyme into structured RNAs to measure ligand-binding events for riboswitch candidates and aptamers

Some structured RNAs, such as riboswitches and aptamers, can bind their cognate ligands and have been used in biosensors and gene expression control elements. However, current methods for detecting ligand binding to structured RNAs are either severely limited or inconvenient. In this study, we design a multi-base pair bridge to integrate a hammerhead ribozyme into structured RNAs to detect ligand binding events. The experimental results demonstrate that the length of the bridge has a significant effect on the cleavage of the ribozyme; optimal cleavage can be achieved with three to six base pairs in the bridge. The dissociation constant (KD) values obtained through this method are in agreement with those determined by in-line probing techniques, and 1 pmol of allosteric ribozyme RNA is sufficient for measurement. We apply this method to evaluate the binding affinity of the riboswitch candidate Motif_9307. Our findings indicate that this motif has no binding affinity for S-adenosylmethionine or several other tested ligands, which is consistent with the results of the in-line probing experiments. Notably, our method reveals an increase in cleavage activity when yeast extract is added as a mixture of ligands, suggesting that the ligand of Motif_9307 is present in the extract. In conclusion, we develop an alternative approach for measuring ligand binding events associated with riboswitch candidates and aptamers.

molecular biology↗

bioRxiv2025

DTX4 regulates neural progenitor transitions during cortical development

Neural progenitors drive cellular diversification in the neocortex. Prolongation of their proliferative capacity and increased diversity underpins the evolutionary expansion and morphological complexity of the human neocortex. Here, we investigate the mechanisms that regulate maintenance of the highly proliferative early neural progenitor subtypes and transition to subsequent progenitors of limited proliferative capacity during human and murine neocortical development. We identify DTX4, a Deltex family member, as an evolutionarily conserved molecular determinant of neural progenitor identity in the mammalian neocortex. DTX4 sustains the identity of radial glia, a highly proliferative progenitor subtype. Loss of DTX4, on the other hand, is a prerequisite for the generation of intermediate progenitors which possess low proliferative capacity. Perturbing DTX4 expression in human cerebral organoids and in the murine neocortex, alters progenitor composition, thereby inducing changes in neuronal diversity and cortical morphology. Mechanistically, we reveal that DTX4 controls progenitor identity by regulating the length of the cell cycle. Our findings underscore the critical role of cell cycle dynamics and of DTX4 in determining progenitor identity and thereby defining neuronal outcome during mammalian development. Highlights[bullet] The Deltex family member, DTX4, is expressed in human and murine neuroepithelia and radial glial progenitors but is absent in intermediate progenitor cells. [bullet]DTX4 maintains radial glia identity and prevents generation of intermediate progenitors during murine and human development. [bullet]Disruption of DTX4 expression compromises neuronal composition and neocortical architecture [bullet]DTX4 regulates progenitor identity by regulating cell cycle length

neuroscience↗

bioRxiv2025

Spatial Metagene Discovery and Associated Molecular Pattern Characterization in Spatial Transcriptomics and Multi-Omics using SEPAR

Spatially resolved transcriptomics (SRT) has transformed biomedical research by enabling gene expression profiling at near- or sub-cellular resolution while preserving spatial context. However, interpreting SRT data to understand cellular and gene organization remains challenging. Current methods focus on identifying global spatial domains across all genes, but often miss localized structures driven by specific gene subsets. Here, we introduce SEPAR, an unsupervised computational framework designed to analyze SRT data using a limited number of spatial metagenes and their expression patterns. SEPAR integrates gene activity and spatial neighborhood relationships to summarize gene expression per spot/- cell, decomposing data into contributions from spatial metagenes. It supports downstream analyses, including metagene expression pattern-specific gene identification, spatially variable gene (SVG) detection, spatial domain delineation, and gene expression refinement. Applied to diverse datasets, SEPAR demonstrates high efficacy. Gene sets linked to spatial metagene patterns are enriched with meaningful cell types and gene ontologies. SVGs are detected with higher accuracy, and gene refinement enhances biological signals, improving correlation analysis of functionally related genes. In spatial multi-omics data, SEPAR excels at revealing strong correlations between co-localized molecules in spatial CITE-seq data and identifies coordinated gene-peak relationships in MISAR-seq data, offering insights into spatial molecular interactions.

bioinformatics↗

bioRxiv2025

The GSA Family in 2025: A Broadened Sharing Platform for Multi-Omics and Multimodal Data

The Genome Sequence Archive Family (GSA family) provides a suite of database resources for archiving, retrieving, and sharing multi-omics data for the global academic and industrial communities. It currently comprises four distinct database members: the Genome Sequence Archive (GSA, https://ngdc.cncb.ac.cn/gsa/), the Genome Sequence Archive for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human/), the open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix/), and the Open Biomedical Imaging Archive (OBIA, https://ngdc.cncb.ac.cn/obia). Compared to the 2021 version, the GSA family has significantly expanded by introducing a new database member, the OBIA, and through comprehensive upgrades to the existing ones. Notable enhancements to the existing members include broadening the range of accepted data types, enhancing the quality control systems, fine-tuning the data retrieval system, and refining the data-sharing management mechanisms.

genomics↗

bioRxiv2025

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

Biophysical modeling provides mechanistic insights into brain function, spanning single-neuron dynamics to large-scale circuit models. These models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing them improves fit to experimental data, enhancing biological plausibility. However, existing methods require repeated, computationally expensive numerical integration of differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learning for Surrogate Statistics Optimization in MEan field modeling), a framework that bypasses numerical integration by directly predicting whether parameter sets produce realistic brain dynamics. Across three large-scale circuit models, DELSSOME achieves a 1500-8000x speedup over numerical integration in predicting model realism. When embedded within an evolutionary optimization strategy, DELSSOME enables 50-100x faster parameter estimation without sacrificing agreement with numerical integration. Because of computational constraints, most studies simulate large-scale circuit models only at the group level. DELSSOME enables efficient individual-level optimization of the feedback inhibition control model. By collating 12,005 individuals across 14 datasets, we derive - for the first time - normative trajectories of cortical E/I ratio across the lifespan, revealing new insights into sex differences and network-specific patterns. This acceleration enables population-scale mechanistic modeling and unlocks new opportunities for understanding brain function.

neuroscience↗

bioRxiv2025

SpatialAgent: An Autonomous AI Agent for Spatial Biology

Advances in AI are transforming scientific discovery, yet spatial biology, a field that deciphers the molecular organization within tissues, remains constrained by labor-intensive workflows. Here, we present SpatialAgent, an autonomous AI agent for spatial biology research. SpatialAgent couples large language models with a Plan-Act-Conclude architecture, dynamic tool and skill retrieval, multimodal interpretation, and verification modules that audit generated claims. It supports the full discovery loop, from gene-panel design and multimodal annotation to trajectory inference, cell-cell communication analysis, imputation, and hypothesis generation. Across human and mouse brain, heart, tonsil, colon, and prostate datasets, SpatialAgent outperformed established computational baselines and matched or surpassed expert scientists in key tasks. In open-ended case studies, it recovered known tissue organization and generated spatially grounded hypotheses. In a prospective mouse prostate cancer Xenium study, it designed a compact 100-gene add-on panel that profiled 4.2 million cells across 21 samples, improved cell-type and malignant-state prediction, and captured spatially structured tumor and microenvironment programs. SpatialAgent establishes a framework for autonomous and collaborative discovery in spatial biology.

bioinformatics↗

bioRxiv2025

Novel multi-transmitter calyx-like giant synapse revealed in the extended amygdala

We have discovered a highly specialized innervation of the forebrain by pituitary adenylate cyclase activating polypeptide (PACAP) immunohistochemistry originating from the brain stem that uses glutamate, acetylcholine and PACAP and other peptides as neurotransmitters. The parent neurons of the axons are in the Kolliker-Fuse nucleus and their terminals form calyx-like multi-release site synapses in the rodent forebrain extended amygdala similar to the calyx of Held in the auditory brain stem. The latter is a giant, excitatory, cup-like axo-somatic high-fidelity synapse. The PACAP-positive terminals also form enveloping axo-somatic specialization with mixed glutamatergic and cholinergic molecular identities, co-expressing VGluT1, VGluT2, VAChT, and the neuropeptides PACAP, CGRP, and neurotensin, together with calretinin in the presynaptic compartment. We identified a distinct neuronal subpopulation in the pontine Kolliker-Fuse region of the parabrachial complex that gives rise to these calyceal terminals, which engulf PKC/GluD1 somata in the capsular central amygdala and oval bed nucleus of the stria terminalis. Strikingly, GluD1 immunolabeling is concentrated at axo-somatic contact zones apposed to VAChT presynaptic vesicle clusters zones but is absent from postsynaptic densities of conventional type I synapses within the same terminals. The results demonstrate a previously unrecognized multimodal calyx-like synapse in the forebrain, with parallel fast ionotropic and modulatory peptidergic neurotransmission mechanisms, which is a substrate for high-fidelity signal transmission within viscerosensory -emotional circuits. Significance StatementA high-fidelity axo-somatic glutamatergic synapse is exemplified by the calyx of Held in the auditory brainstem, but is unknown in the forebrain. Here we reveal a multimodal calyceal synapse in the extended amygdala formed by glutamatergic afferents of the pontine Kolliker-Fuse nucleus that contain also several neuropeptides. These giant terminals co-package glutamate, acetylcholine, PACAP, CGRP and neurotensin. They envelop select PKC/GluD1 neurons in the capsular central amygdala and oval BNST. These unique forebrain synapses link viscerosensory input from the hindbrain to limbic autonomic centers. Such high-fidelity multimodal transmission is likely to underlie the precise synchronization of emotional and homeostatic control circuits.

neuroscience↗

bioRxiv2025

EcDNA-borne PVT1 fusion stabilizes oncogenic mRNAs

Extrachromosomal DNA (ecDNA) amplifications are prevalent drivers of human cancers. We show that ecDNAs exhibit elevated structural variants leading to gene fusions that produce oncogene fusion transcripts. The long noncoding RNA (lncRNA) gene PVT1 is the most recurrent structural variant across cancer genomes, with PVT1-MYC fusions arising most frequently on ecDNA. PVT1 exon 1 is the predominant 5 partner fused to MYC or other oncogenes on the 3 end. Mechanistic studies demonstrate that PVT1 exon 1 confers enhanced RNA stability for fusion transcripts, which requires PVT1 exon 1 interaction with SRSF1 protein. Genetic rescue of MYC-addicted cancer models and isoform-specific single-cell RNA sequencing of tumors reveal that PVT1-MYC better supports MYC dependency and better activates MYC target genes in vivo. Thus, the mutagenic landscape of ecDNA contributes to genome instability and generates chimeric fusions of lncRNA and mRNA genes, selecting PVT1 5 region as a stabilizer of oncogene mRNAs.

cancer biology↗

bioRxiv2025

Machine learning-predicted chromatin organization landscape across pediatric tumors

Structural variants (SVs) are increasingly recognized as important contributors to oncogenesis through their effects on 3D genome folding. Recent advances in whole-genome sequencing have enabled large-scale profiling of SVs across diverse tumors, yet experimental characterization of their individual impact on genome folding remains infeasible. Here, we leveraged a convolutional neural network, Akita, to predict disruptions in genome folding caused by somatic SVs identified in 61 tumor types from the Childrens Brain Tumor Network dataset. Our analysis reveals significant variability in SV-induced disruptions across tumor types, with the most disruptive SVs coming from lymphomas and sarcomas, metastatic tumors, and germline cell tumors. Dimensionality reduction of disruption scores identified five recurrently disrupted regions enriched for high-impact SVs across multiple tumors. Some of these regions are highly disrupted despite not being highly mutated, and harbor tumor-associated genes and transcriptional regulators. To further interpret the functional relevance of high-scoring SVs, we integrated epigenetic data and developed a modified Activity-by-Contact scoring approach to prioritize SVs with disrupted genome contacts at active enhancers. This method highlighted highly disruptive SVs near key oncogenes, as well as novel candidate loci potentially implicated in tumorigenesis. These findings highlight the utility of machine learning for identifying novel SVs, loci, and genetic mechanisms contributing to pediatric cancers. This framework provides a foundation for future studies linking SV-driven regulatory changes to cancer pathogenesis.

genomics↗

bioRxiv2025

A pan-positive allosteric modulator that mediates sustainable GPCR activation

Approximately 1/3 of all clinical drugs exert their therapeutic effects by modulating the activity of G protein-coupled receptors (GPCRs). Thus, there is a constant interest in finding novel ways to modulate GPCR activity. In this work, through a newly established Survival Pressure Selection (SPS) method for high-throughput screening of GPCR agonists, we discover that atazanavir functions as an agonist for GPR119. Further studies suggest that atazanavir is capable of activating a number of Family A GPCRs, including the {beta}1 adrenergic receptor ({beta}1AR), the {beta}2 adrenergic receptor ({beta}2AR) and the opoioid receptor (OR). Cryo-EM structures reveal that atazanavir binds to an allosteric pocket near TM6/7 in both GPR119 and the {beta}1AR. Pharmacological studies suggest that atazanavir mediates non-canonical signaling of Family A GPCRs. During this process, G protein and {beta}-arrestin are spatially close, but {beta}-arrestin forms a complex with the receptor and G protein instead of desensitizing G protein signaling, thus resulting in sustained G protein signaling. The work expands the signal transduction modes and pharmacological properties of allosteric modulators for GPCRs and provides a general starting point for developing therapeutics targeting this allosteric site.

biochemistry↗

bioRxiv2025

A GPCR-G protein-β-arrestin megacomplex induced by an allosteric modulator

GPCRs signal through both G protein pathways and {beta}-arrestin pathways. Previous work suggests that {beta}-arrestins bind to GPCRs through different modes, including core engagement and tail engagement. Core engagement competes with G proteins and terminates G protein signaling, while tail engagement can coexist with G proteins, mediating sustained intracellular activation of the receptor - a process dependent on the high affinity between {beta}-arrestin and the phosphorylated C-terminus of the receptor. In this study, we determined the structure of a GPCR - G protein - {beta}-arrestin-1 complex stabilized by an allosteric modulator. The compound, atazanavir, acts like molecular glue to anchor {beta}-arrestin-1 to the receptors TM6 and TM7 regions. This pendulum binding mode is structurally compatible with simultaneous G protein binding. We further demonstrate that the atazanavir-mediated {beta}-arrestin recruitment does not require the receptors C-terminal region. This work illustrates a novel paradigm of GPCR-G protein-{beta}-arrestin1 megacomplex assembly and opens up new avenues for modulating GPCR function.

biochemistry↗

bioRxiv2025

Autism spectrum disorder risk genes have convergent effects on transcription and neuronal firing patterns in primary neurons

Autism spectrum disorder (ASD) is a highly heterogenous neurodevelopmental disorder with numerous genetic risk factors. Notably, a disproportionate number of risk genes encode transcription regulators including transcription factors and proteins that regulate chromatin. Here, we teste the function of nine such ASD-linked transcription regulators by depleting them in primary cultured neurons. We then define the resulting gene expression disruptions using RNA-sequencing and test effects on neuronal firing using multielectrode array recordings. We identify shared gene expression signatures across many ASD risk genes that converge on disruption of critical synaptic genes. Fitting with this, we detect robust disruptions to neuronal firing throughout neuronal maturation. Together, these findings provide evidence that loss of multiple ASD-linked transcriptional regulators disrupts transcription of synaptic genes and has convergent effects on neuronal firing that may contribute to enhanced ASD risk.

neuroscience↗

bioRxiv2025

Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation

Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.

genomics↗

bioRxiv2025

Altered Interpersonal Neural Synchronization during Social Interaction After Shared Excluded Experiences in Depressed Adolescents

BackgroundMajor depressive disorder (MDD) is common in adolescents, and the special development stage, during which adolescents brain and neuroendocrine system develop intensively, makes it subtly difficult to develop prevention and treatment strategies for depressed adolescents compared with depressed adults. Meanwhile, public psychosocial stressors significantly influence adolescents mental health and social interaction, rendering it essential to explore how a shared psychosocial stressor, i.e., shared excluded experiences, influences social interaction in depressed adolescents. MethodsWe designed a 4-player cyberball game to probe adolescents responses to shared excluded experiences and explore the underlying interpersonal neural synchronization (INS) with functional near-infrared spectroscopy (fNIRS). ResultsWe found that shared excluded experiences could enhance adolescents social interaction preferences but decreased INS in each pair of excluded adolescents, which indicates a reduced willingness to interact with others after the exclusion. However, no significantly different behavioral responses to the shared excluded experiences were found in depressed adolescents compared to adolescents as healthy controls (HC). Further analyses revealed that adolescents with MDD experienced more negative feelings than HC after exclusion. Of note, adolescents with MDD demonstrated stronger INS than HC, indicating the potential empathic stress in depressed adolescents. In addition, there existed altered brain-behavioral association patterns in responses to shared excluded experiences in depressed adolescents. ConclusionsIn summary, our study gives us deeper insights into how a shared psychosocial stressor impacts the INS in depressed adolescents, and it might be demonstrated that INS could be more sensitive than behavioral responses to detect social interaction deficits in depressed adolescents.

neuroscience↗