Biology subjects

Peng, Y.

Publications and source records attributed to Peng, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Digital Chromosome Banding Reveals Distinct Spatiotemporal Dynamics and Sexual Dimorphism in Meiotic Silencing

In mammals, meiotic silencing of unsynapsed chromatin (MSUC) is initiated by the DNA damage response (DDR) pathway, as marked by {gamma}H2AX. During normal male meiosis, MSUC is restricted to the unsynapsed sex chromosomes, a process known as meiotic sex chromosome inactivation (MSCI). While the initiation of MSCI has been well studied, its full silencing dynamics and underlying structural mechanisms remain unclear. In contrast to MSCI, broader MSUC can occur on autosomes in response to synapsis failure, but its cell-to-cell variability obscures its quantification. To address these challenges, we introduce "digital-chromosome-banding", a single-cell-based approach that allows quantitative analysis of MSCI and MSUC at chromosomal resolution. Using this approach, we identified two distinct silencing transitions during MSCI, occurring from zygonema to early pachynema and from early to mid-pachynema. The latter step coincides with mature sex body formation and involves a gel-like diffusion barrier to enforce transcriptional repression. Applying this approach to synapsis-defective mouse models (Spo11-/-, Tardbp cKO, and Nelfb cKO), we observed divergent MSUC patterns that correlate with the severity of asynapsis. Comparative analysis between sexes also uncovered notable sexual dimorphisms in meiotic silencing. Together, our data provide a quantitative framework to dissect the spatiotemporal dynamics and sexual differences of meiotic silencing.

cell biology↗

bioRxiv2026

STID: A Standardized Spatial Transcriptomic Analysis Framework for Infectious Diseases

Spatial transcriptomic studies of infectious diseases still rely on fragmented data analysis processes. Here, we developed STID, a standardized framework for spatial transcriptomic analysis of infectious diseases that leverages the Seurat ecosystem and incorporates Python-based modules. STID provides an extensible infection-specific data structure and supports a full suite of analyses, such as pathogen background correction, infection-associated spot and niche identification, single-sample niche characterization, and multi-sample comparative and temporal analyses. Moreover, STID is broadly applicable to spatial transcriptomic data from infectious diseases caused by bacteria, viruses, and parasites, and enables systematic characterization of the structural features, cellular composition, molecular functions, and host-pathogen interactions within pathogen-infected and/or host-responsive niches. Overall, STID provides an accessible, reproducible, and extensible framework for analyzing infection-associated spatial transcriptomic data and for dissecting host-pathogen interactions in their native spatial microenvironments. MotivationSpatial transcriptomics technologies have emerged as powerful approaches for dissecting the structural and functional features of spatial microenvironments. However, the current general-purpose tools remain fundamentally inadequate for resolving the spatial heterogeneity of infectious disease samples, where the intricacies of host-pathogen interactions render spatial microenvironments both challenging to dissect and largely inaccessible. Tools tailored to infectious diseases are critically lacking, including those for reducing pathogen-derived background noise, identifying and isolating infection{square}associated spots or niches, dissecting host-pathogen interactions, and supporting systematic multi-sample analyses. We therefore developed STID, a unified framework that integrates standardized workflows and addresses the analytical bottlenecks in spatial transcriptomic analysis of infectious diseases. HighlightsO_LISTID standardizes spatial transcriptomic analysis in infectious diseases C_LIO_LISTID improves pathogen-infected spot detection by correcting pathogen background C_LIO_LISTID distinguishes pathogen-infected and host-responsive niches C_LIO_LISTID supports multi-sample comparative and temporal analyses of niches C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/727492v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@167d351org.highwire.dtl.DTLVardef@1628848org.highwire.dtl.DTLVardef@1e157aforg.highwire.dtl.DTLVardef@143ca1b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Iron availability regulates PIN-mediated auxin transport and distribution to modulate root gravitropic growth in Arabidopsis

Iron (Fe) is an essential micronutrient for plant growth, and the hormone auxin is a key regulator of developmental processes, including root gravitropism. Here, we investigated the molecular mechanisms underlying the crosstalk between iron nutrition and auxin-mediated root growth in Arabidopsis thaliana. Phenotypic analysis revealed that iron deficiency strongly shaped root system architecture and root gravitropism, and these phenotypes were exacerbated in the iron uptake mutant irt1-1. Genetic analysis revealed that iron deficiency did not aggravate the gravitropic defect of the pin2 mutant, eir1-4, suggesting that iron availability modulates root gravitropism through a PIN2-dependent pathway. Further transcriptomic analysis confirmed that iron deficiency significantly altered the expression of numerous genes related to the auxin pathway, providing molecular evidence for the observed physiological connection. Collectively, this study revealed that iron availability regulates root gravitropic growth by modulating PIN-mediated auxin transport and distribution, providing insights into how plants integrate nutritional cues with developmental programs. Graphical abstract A brief descriptionIron modulates auxin transport and root tip distribution by regulating PIN2 protein, thereby mediating root gravitropism in Arabidopsis. Public summaryO_LIIron nutrition specifically regulates root gravitropism and architecture in Arabidopsis. C_LIO_LIIron deficiency disrupts local auxin homeostasis in root tips and impairs asymmetric distribution in response to gravity. C_LIO_LIIron deficiency stress significantly reduces the abundance of PIN2 protein in root tip cells and disrupts its polar localization pattern on the plasma membrane, thereby precisely modulating polar auxin transport by interfering with the vesicle trafficking and recycling efficiency of PIN2. C_LIO_LIRNA-seq results showed that iron deficiency induced differential expression of multiple auxin-related genes, indicating that iron nutrition affects root development through the auxin pathway. C_LI

plant biology↗

bioRxiv2026

How many genes can CRISPR edit to engineer complex adaptations?

Polygenic traits require the coordinated effects of multiple genes. Such complex traits have been a long-term target of study for geneticists, but multiplex CRISPR--the editing of multiple loci in the genome via multiple guide RNAs--is in its infancy. Reviewing 106 plant studies using multiplex CRISPR, we find that the multiplexing capacity has doubled every 5.4 years. Furthermore, a systematic experiment with 8, 16, and 24 simultaneous targets in Arabidopsis thaliana reveals efficiency of up to 75% in 24-plex editing in transformed plants confirmed by sequencing. We surprisingly found that the level of multiplexing, or the number of the targets, causes lesser efficiency reductions than other uncontrolled factors such as gRNA design or natural variation across plants. In fact, mathematical modeling of the decay in editing efficiency as a function of the gRNA numbers, showed a logistic model with sustained efficiency fits the data better than decay due to Cas9 competition or random editing. We then project that editing close to 100 genes in a plant can be feasible with reasonably large plant screens. However, feasible and reliable polygenic genome engineering will need developments outside of the CRISPR editing machinery itself, including innovations in gRNA vector delivery for large cargos, and a broader conceptual shift toward population-level poly-gene editing leveraging large distributions of mutations for breeding, natural selection, or experimental evolution. Author ContributionsM.E.-A. conceived the project and secured funding. M.E.-A. and M.Es. designed the experimental strategy. M.Es. established the multiplex CRISPR and transformation pipelines in the laboratory, propagation through the T1 and T2 generations, and oversaw the first amplicon sequencing. Y.P. established the in-house iSeq amplicon sequencing protocol and contributed to cloning and genotyping pilots. M.Es supervised K.P. to construct cloning, bacterial transformations, plant growth, floral-dip transformations, and selection of T1 plants. E.K. contributed to early amplicon genotyping. J.K. propagated and sampled the T3 and J.K. and J.M. conducted the final amplicon sequencing panel. J.K. and M.E.-A. performed gene editing variant mapping, dataset quality control, and summarized results from published multiplex CRISPR studies. M.E.-A. modeled editing efficiency. J.K and M.E.-A. generated figures and wrote the first draft. All authors revised and improved the manuscript. J.K. and M.Es. contributed equally to this work and are designated as co-first authors.

plant biology↗

bioRxiv2026

SigBridgeR: An Integrative Framework and Toolkit for Comprehensive Screening and Benchmarking of Phenotype-Associated Cell Subpopulations in Single-Cell Transcriptomics

Single-cell RNA sequencing has revolutionized our understanding of cellular heterogeneity, yet linking specific cell subpopulations to clinically relevant phenotypes remains a persistent challenge. Although multiple computational methods have been developed to bridge this gap, they are typically implemented as standalone packages with heterogeneous preprocessing pipelines, incompatible parameter conventions, and divergent output formats, thereby hindering rigorous cross-method benchmarking and reproducible multi-method workflows. Here, we present SigBridgeR, an extensible R framework and comprehensive toolkit that currently unifies eight state-of-the-art phenotype-associated cell screening algorithms within consistent workflows. We conducted a systematic benchmarking study across four cancer types HER2-positive breast cancer, triple-negative breast cancer, lung adenocarcinoma, and ovarian cancer using both binary phenotypes and patient survival endpoints. Our evaluation incorporated positive and negative control assessments based on differentially expressed genes and randomly selected marker panels, alongside quantitative accuracy comparisons using ground-truth cell labels. Building upon these insights, SigBridgeR provides standardized preprocessing for scRNA-seq and bulk transcriptomic data, unified algorithmic interfaces through a registry-based architecture, ensemble analysis via weighted voting, and comprehensive visualization utilities for multi-method comparison. By lowering technical barriers and promoting methodological standardization, SigBridgeR facilitates reliable discovery of phenotype-relevant cell subpopulations and enhances the translational potential of single-cell omics research.

bioinformatics↗

bioRxiv2026

On the state of protein function prediction: a report on the fourth CAFA challenge

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4). ResultsCAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.

bioinformatics↗

bioRxiv2026

MVCBench: A Multimodal Benchmark for Drug-induced Virtual Cell Phenotypes

Drugs induce coordinated phenotypic changes across multiple modalities, including transcriptional reprogramming and cellular morphological remodeling. Predicting these drug-induced modality changes is central to drug discovery, mechanism-of-action studies and precision therapeutics, however, prediction performance depends critically on how both drug compounds and cellular states are represented. Despite rapid advances in drug molecular and gene representation methods, a systematic evaluation of these methods remains lacking. Herein, we introduce MVCBench, a comprehensive benchmarking framework for evaluating drug molecular and gene representation methods in predicting drug-induced multimodal virtual cell (MVC) phenotypes. MVCBench leverages large-scale transcriptomic and high-content imaging data and systematically evaluates 24 representation methods (12 drug molecular and 12 gene representation methods) across nearly 1.1 million drug-induced profiles, under both in-distribution and out-of-distribution settings spanning unseen compounds, cell lines, assay plates and datasets. Our benchmarking reveals a pronounced modality-dependent asymmetry: advanced drug molecular representations substantially improve the prediction of drug-induced morphological phenotypes but provide only limited gains for gene expression prediction relative to classical fingerprints, whereas task-specific gene representations outperform general-purpose foundation models in predicting drug-induced transcriptomic responses. Predictive performance also deteriorates sharply under distribution shift, highlighting persistent challenges in cross-dataset and cross-platform generalization. We further show that integrating transcriptomic and morphological modalities consistently improves prediction accuracy, and derive practical design principles for MVC architectures, including modality-aware loss calibration and fusion strategies. Together, MVCBench provides a systematic foundation for evaluating representation methods and offers guidance for developing robust MVC models of drug-induced cellular responses.

bioinformatics↗

bioRxiv2026

Improved prediction of virus-human protein-protein interactions by incorporating network topology and viral molecular mimicry

The protein-protein interactions (PPIs) between viruses and human play crucial roles in viral infections. Although numerous computational approaches have been proposed for predicting virus-human PPIs, their performances remain suboptimal and may be overestimated due to the lack of benchmark dataset. To address these limitations, we first constructed a carefully curated benchmark dataset, ensuring non-overlapped PPIs and minimum sequences similarity of both human and viral proteins in the training and test sets. Based on this dataset, we developed vhPPIpred, a machine learning-based prediction method that not only incorporated sequence embedding and evolutionary information but also leveraged network topology and viral molecular mimicry of human PPIs. Comparative experiments demonstrated that vhPPIpred outperformed five state-of-the-art methods on both our benchmark dataset and three independent datasets. vhPPIpred also achieved high computational efficiency, requiring relatively low runtime and memory. Finally, vhPPIpred was demonstrated to have great potential in identifying human virus receptors, and in inferring virus phenotypes as the virus-human PPIs predicted by vhPPIpred can be used to effectively infer virus virulence. In summary, this study provides a valuable benchmark dataset and an effective tool for virus-human PPI prediction, with potential applications in antiviral drug discovery, host-pathogen interaction research and early warnings of emerging viruses.

bioinformatics↗

bioRxiv2026

Spatial multi-omics identify an immunosuppressive lipid-laden macrophage niche in primary CNS lymphoma

Primary central nervous system lymphoma (PCNSL) is histologically a subtype of diffuse large B-cell lymphoma (DLBCL), sharing genetic and transcriptomic similarity, but with distinct clinical features, particularly its confinement to the CNS and higher relapse risk. The microenvironmental basis for its divergence from systemic DLBCL remains unclear. Using spatial transcriptomic approaches (Xenium/GeoMx digital spatial profiling) in a comparative study of PCNSL (n=17) and DLBCL (n=76), we found that PCNSL, unlike systemic DLBCL, is dominated by an immunosuppressive macrophage compartment enriched for cholesterol-metabolism programs. In independent cohorts of PCNSL profiled by single-cell RNA sequencing, we validated the presence of a recurrent population of lipid-laden macrophages (LLMs): TREM2/GPNMB-expressing, lipid-remodeled cells transcriptionally distinct from resident microglia and consistent with an infiltrating monocyte origin, not previously characterized in CNS lymphoma. LLMs formed immunosuppressive niches with regulatory T cells, and using Cellscape hyperplex proteomic imaging we demonstrate that LLM-Treg spatial interactions are associated with chemotherapy response. To test whether LLMs are lymphoma-driven and functionally important, we developed an immunocompetent syngeneic PCNSL mouse model, driven by Myd88L252P and Cd79b mutations with Bcl2 overexpression. Monocyte-derived macrophages in lymphoma-bearing brain regions acquired an LLM-like state, not seen in lymphoma-free brain regions or in splenic tumors driven by the same oncogenic lesions. TREM2-SYK signaling sustained this state, and SYK inhibition reversed its tumor-supportive activity ex vivo. These findings identify the LLM program as a targetable immunosuppressive myeloid state in CNS lymphoma.

cancer biology↗

bioRxiv2026

eScreen: a deep learning framework for functionally decoding the regulatory genome at single-nucleotide resolution

The human genome is densely populated with cis-regulatory elements (CREs), yet deciphering their functional regulatory syntax and combinational logic remains a fundamental challenge. Here, we integrate 379 genome-scale CRISPR screen experiments, encompassing 21 million perturbations across 23 cell types, to construct a compendium of 41,239 high-confidence functional CREs from 530,527 candidates. Leveraging this resource, we develop eScreen, a deep learning model built on the StripedHyena2 architecture to functionally decode the regulatory genome at single-nucleotide resolution. eScreen achieves three primary functions: (1) predicts genome-wide cell-type-specific CRE functional activity with high accuracy, outperforming existing models; (2) provides mechanistic interpretation of regulatory syntax at single-nucleotide resolution; (3) dissects the functional organization of enhancer clusters through in silico perturbation analysis. We perform multiple independent CRISPR knockout, CRISPR interference (CRISPRi), and base editing screens to validate these functions of eScreen both at scale and on individual cases. Furthermore, we provide an interactive web server (https://escreen.huanglabxmu.com/) for the community to access the integrated CRISPR screen resources and eScreen functions. Collectively, our work establishes a highly precise and convenient tool to decode the causal effects of the regulatory genome.

genomics↗

bioRxiv2026

Higher-Order Thalamus is Pivotal in Schizophrenia-Associated Pathophysiology

Synaptic dysfunction has been proposed as cellular pathophysiology underlying schizophrenia, yet the brain-wide distribution of dysfunctional circuits at single-neuron resolution has remained unknown. Here, we perform comprehensive multi-probe electrophysiological investigations in vivo in the Grin2a+/- preclinical model for schizophrenia and control animals, recording across [~]45 brain regions spanning cortex, striatum, hippocampus, and thalamus. Mutants displayed distributed and graded alterations across regions, with prominent activity reductions in higher-order thalamus and cross-parameter alterations across prefrontal cortices, striatum, and hippocampus. Restoration of higher-order thalamic activity in mutants was sufficient to normalize alterations in connected prefrontal cortices and striatum and unexpectedly cascaded to hippocampus and sensory cortices. Thus, higher-order thalamus plays a pivotal role in schizophrenia pathophysiology and restoration of a single informed locus could present a potent therapeutic strategy.

neuroscience↗

bioRxiv2025

Flu Virus Infection in Juvenile Mice Leads to Lifelong Multi-Organ Damage and Parkinsonian Pathological Changes in Aging

The widespread prevalence of Long COVID underscores the potential for viral infections to exert prolonged effects on hosts long after initial recovery. Despite this recognition, the long-term and even lifelong consequences of viral infections remain poorly understood. In this study, we infected juvenile mice with influenza viruses and systematically examined the lifelong effects (from 4 to 450 days post-infection) of these infections. Pathological analysis revealed persistent lifelong damage in multiple organs, including chronic lung inflammation and fibrosis, along with significant cardiac and renal pathology. Viral infection led to substantial neuronal loss in key brain regions of mice (hippocampal CA1, CA3, and striatum) during middle and old age. Strikingly, we identified two hallmark pathological features of Parkinsons disease - dopaminergic neuron degeneration and Lewy body-like -synuclein inclusions - in middle and aged infected mice. Transcriptomic profiling demonstrated sustained upregulation of inflammation-related genes in both lung and blood tissues, correlating with observed pathological changes. Lung-derived secreted proteins, encoded by differentially expressed genes, may mediate cross-organ communication affecting cardiac, renal, and neurological function. Brain transcriptome analysis at three months post-infection revealed downregulation of neurodevelopmental genes, potentially contributing to subsequent neuronal loss and Parkinsonian pathology. These findings collectively suggest that pulmonary influenza infection can induce systemic multi-organ effects through both secretory pathways and chronic inflammatory responses. The study offers crucial insights for developing more effective strategies to prevent and manage infectious diseases and their long-term sequelae.

microbiology↗

bioRxiv2025

A neuron type-specific microexon in Ank3/ankyrin-G modulates calcium activity and neuronal excitability

Recent studies have revealed many alternative exons differentially spliced across diverse neuron types in the mammalian brain, but their links to neuronal physiology remain unclear. Here we characterize a deeply conserved microexon E35a in Ank3 encoding ankyrin-G (AnkG), a multifaceted adaptor protein best known as a master organizer of the axon initial segment (AIS) and as a leading genetic risk factor for bipolar disorder. E35a is predominantly skipped in cortical glutamatergic neurons but included in cortical GABAergic neurons and cerebellar neurons, which is dictated by multiple neuronal splicing factors. In E35a-deletion mice we generated, interneurons show increased excitability and somatic Ca2+ activity, without disruption in AIS. Biochemical analyses suggest that E35a inclusion facilitates AnkG interaction with a protein complex involving inositol trisphosphate receptors (InsP3Rs) important for intracellular Ca2+ signaling. Alternative splicing therefore allows AnkG to modulate neuron type-specific excitability in addition to its ubiquitous pan-neuronal role in organizing the AIS.

neuroscience↗

bioRxiv2025

Unlocking karst biodiversity with eDNA: a validated qPCR toolkit for discovery and monitoring the worlds largest cavefish radiation (Cyprinidae: Sinocyclocheilus)

Environmental DNA (eDNA) enables non-invasive detection of aquatic species through trace genetic material, but uncertainties regarding DNA persistence, detection accuracy, and the limited taxonomic resolution of stygian fauna have constrained its use in subterranean aquatic environments. The species-rich cavefish genus Sinocyclocheilus, endemic to the karst landscapes of southwestern China, offers an excellent model for understanding these issues. With over eighty species, many of which are endemics, and many still being described, this lineage is taxonomically rich, poorly understood, and highly threatened. However, access to these deep habitats remains challenging, making eDNA detection one of the most practical methods for documenting and monitoring them. We developed and validated a qPCR assay targeting a hypervariable region of the mitochondrial 16S rRNA gene, allowing for genus-specific detection and species-level identification. Laboratory and field evaluations involving 47 representative species confirmed high specificity and a detection limit of around 20 DNA copies per reaction (R{superscript 2} = 0.995). Controlled degradation studies indicated that temperature and pH strongly affect DNA persistence. Field surveys across 47 karst sites (37 caves and 10 surface sites) detected Sinocyclocheilus eDNA in only 33 caves. Dideoxy sequencing of qPCR amplicons provided species-level identification and phylogenetic validation, including detection of a new species. At three cave sites yielding multiple qPCR detections, 16S metabarcoding enabled species discrimination. By integrating qPCR assay validation, eDNA degradation modelling, hierarchical genetic identification via dideoxy sequencing, and selective NGS metabarcoding, this study presents a strategic framework for applying eDNA methods in subterranean environments.

evolutionary biology↗

bioRxiv2025

A global atlas of deep-sea cold seep viruses uncovers extensive genomic novelty, pervasive viral dark matter, and biotechnological potential

Cold seeps are globally distributed deep-sea ecosystems harboring diverse chemosynthetic microbial communities, yet their viral components remain poorly understood. Here, we establish the Global Cold Seep Virome, a comprehensive catalog of 191,937 species-level viral operational taxonomic units (vOTUs) and 2.44 million viral protein clusters reconstructed from 314 metagenomes spanning 18 cold seep sites worldwide. Most vOTUs are distinct from those in existing environmental viromes, suggesting that cold seeps harbor a largely unexplored viral reservoir. Host prediction suggests diverse viral associations with key prokaryotes, including anaerobic methanotrophic archaea. Protein annotation reveals that these viruses encode widespread uncharacterized proteins and viral hallmark proteins with divergent physicochemical properties, potentially contributing to their ecological adaptability. We also identify putative auxiliary metabolic genes, anti-defense genes, and lysins, and experimentally validate representative anti-defense proteins and lysins with strong activities. This resource expands current knowledge of deep-sea viral diversity and provides a foundation for studying virus-host interactions, testing biogeochemical hypotheses, and exploring biotechnological potential in cold seep ecosystems.

microbiology↗

bioRxiv2025

Structures of tRNA-bound CRISPR-Cas13 reveal universal HEPN RNase mechanisms

Ribonucleases (RNases) are ubiquitous drivers of RNA metabolism across life. Higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domain-containing RNases form a nuclease superfamily whose mechanisms of substrate selection and catalysis remain poorly understood. Here, we report substrate preferences for diverse Cas13 HEPN RNases, revealing precise cleavage of tRNA anticodons and acceptor stems. Using cryo-EM, we present a series of activated Leptotrichia buccalis Cas13a (LbuCas13a) structures engaged with substrate tRNA. We show LbuCas13a captures tRNA through shape- and sequence-specific recognition, cleaving U-rich anticodons independently of tRNA modifications. Leveraging these insights, we reprogram Cas13 specificity and engineer variants with accelerated RNase activity. These findings establish the molecular basis for Cas13 tRNase activity and indicate that the HEPN RNase superfamily obeys universally conserved mechanisms of substrate recognition and catalysis.

biochemistry↗

bioRxiv2025

Assessment of the Role of Telocyte Zbtb16 in Lymphatic Drainage using Efhd1-CreERT2 x Zbtb16flox/flox Mice

Lymphatic function is critical for maintaining fluid homeostasis and immune surveillance in synovial tissues, and its dysfunction is implicated in the progression of rheumatoid arthritis and osteoarthritis. Zbtb16, a transcription factor involved in cellular differentiation that is downregulated in mice with inflammatory arthritis and lymphatic defects, has been linked to skeletal development and immune regulation, but its direct role in lymphatic function remains unexplored. To investigate this, we generated Zbtb16fl/fl mice for conditional-inducible loss-of-function experiments. Initial validation studies demonstrated that CMV-Cre x Zbtb16fl/fl mice display the same skeletal phenotypes as previously reported Zbtb16-/- global knockout mice. To achieve telocyte-specific deletion, Efhd1-CreERT2 x Zbtb16fl/fl mice were treated with tamoxifen, and successful recombination was verified by PCR analysis of genomic DNA from popliteal lymphatic vessel tissue. Functional assessment using NIR-ICG imaging demonstrated that Zbtb16 deletion in telocytes partially impaired lymphatic clearance, suggesting a role in maintaining lymphatic function during homeostasis. These findings demonstrate the utility of Zbtb16fl/fl mice for their intended purpose and support future studies on the role of Zbtb16 within the synovial lymphatic system.

cell biology↗

bioRxiv2025

Spatial constraint drives negative frequency dependent selection of phage weaponization

Biofilm growth and phage exposure are common to diverse bacterial species. Studying phage-host interaction and population dynamics in biofilms with cellular resolution remains a significant challenge, especially when attempting to recapitulate the natural environments that microbes occupy. Here we study the population dynamics of phage K139 lysogenized and non-lysogenized Vibrio cholerae when growing in biofilms on the surface of chitin particles in seawater, replicating key features of V. cholerae ecology in the marine environment. We find that lysogenized V. cholerae, via spontaneous lytic induction and phage release, kill and displace non-lysogenized bacteria on chitin surfaces. After lysogens become common, however, they can no longer displace remaining non-lysogenized cells. Using a combination of modeling approaches and microscopy experiments, we show that the lysogens capacity to displace non-lysogens depends on the ability of phages released by spontaneous induction to reach susceptible non-lysogens. Phage access to non-lysogenized bacterial hosts declines once lysogens become common, and this occurs due to the spatial constraints inherent to biofilm growth as well as to superinfection immunity, which neutralizes phage particles adsorbed to lysogens. Once lysogens comprise the majority of the host population, they can be selected against, because they still incur the cost of spontaneous induction without gaining the benefit of killing non-lysogen cells via phage release. The cost of lytic induction, phage-mediated killing of non-lysogens, and constraints on phage mobility within host bacterial biofilms together yield population dynamics that are consistent with negative frequency dependent selection for lysogenized cells under physiologically realistic growth conditions. Significance StatementBacteria often produce and live within biofilm communities in natural environments, where they also encounter many threats including bacteriophages. Here we show how temperate phages can confer a competitive advantage to their hosts via lytic induction and phage release within biofilms of V. cholerae on lab-grown marine snow particles. However, the spatial constraints of biofilm architecture and phage-neutralizing superinfection immunity place limits on the extent to which lysogens can competitively displace non-lysogens via phage release.

microbiology↗