Biology subjects

Wu, R.

Publications and source records attributed to Wu, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Biohybrid Robots with Embedded Conductive Fibers for Actuation, Sensing, and Closed-loop Control

Living organisms achieve adaptive actuation through the seamless integration of neural motor control circuitry and proprioceptive feedback. While biohybrid robotics aims to replicate these capabilities by merging engineered muscle with synthetic scaffolds, the field remains limited by interfaces that lack the efficiency and closed-loop regulation of natural neuromuscular systems. Here, we introduce a biohybrid muscle actuator system featuring a bioelectronic interface based on soft poly(3,4-ethylenedioxythiophene) (PEDOT) fibers for stimulation and sensing. These fibers conformally couple to muscle tissues, eliciting robust contractions at voltages as low as 1 V--requiring ultra-low power (0.376 {+/-} 0.034 mW) and preserving long-term tissue viability. By leveraging the independent addressability of these fibers, we demonstrate selective actuation of individual muscle units to achieve precise spatiotemporal control of a two-muscle-powered walking biohybrid robot, reaching a locomotion speed of 5.43 {+/-} 0.79 mm/min. When configured as strain sensors, the fibers exhibit a high gauge factor of 155.45 {+/-} 6.59 and resolve contractile displacements within tens of micrometers. We demonstrate that this sensing modality can be integrated into a closed-loop controller to autonomously modulate stimulation based on real-time feedback, significantly mitigating muscle fatigue (p = 0.038) during continuous operation. This work establishes a versatile platform for efficient actuation and intrinsic feedback sensing, providing a blueprint for efficient, autonomous, and adaptive biohybrid machines. SummarySoft conductive fibers enable a bioelectronic interface for low-power actuation and closed-loop control in biohybrid robots.

bioengineering↗

bioRxiv2026

A truncated soil phage catechol 1,2-dioxygenase illustrates how viruses preserve and disseminate auxiliary catalytic functions in the soil microbiome

Bacteriophages can rewire host chemistry via auxiliary viral genes (AVGs). Using metagenomic and metatranscriptomic data from the native soil microbiome, we identified transcriptionally active AVGs, including a viral catechol 1,2-dioxygenase (V-C12DO). V-C12DO shares [~]40% sequence identity with its nearest bacterial homologs and lacks the helical dimerization domain. Despite truncation, V-C12DO retains more than [~]25% of the global consensus residues compared to C12DOs across domains of life, including the two tyrosines and two histidines that coordinate the non-heme Fe(III) active site. A 1.7 [A] crystal structure also showed the conservation of the canonical {beta}-sandwich scaffold for the iron. We next confirmed that V-C12DO cleaves catechol and remains highly active across a broad range of temperatures (30-60 {degrees}C), pH (5.5-9), and salinity (up to 2 M), exceeding those of known bacterial CD12Os. This work shows that truncated phage enzymes preserve the core catalytic chemistry and potentially further expand host metabolic versatility across dynamic environmental conditions.

microbiology↗

bioRxiv2026

EnzySeek: Efficient Exploration of Enzyme Reaction Pathways Using AI Agents

With the rapid development of Large Language Models (LLMs) and Agent technologies, AI can assist in solving a variety of real-world problems across multiple domains, such as autonomous driving, drug discovery, and materials design. In this work, we present EnzySeek, an enzyme catalysis AI agent designed to assist researchers in enzyme catalysis simulations. First, we constructed a domain-specific knowledge base by curating thousands of papers related to enzyme catalysis. Second, we customized Model Context Protocol (MCP) interfaces for each step of the enzyme catalysis simulation workflow, enabling these functions to be invoked by LLMs. Finally, we configured an agent capable of simultaneously referencing past empirical studies on enzyme catalysis, autonomously executing tool calls, and analyzing as well as presenting the results. EnzySeeks capabilities cover multiple aspects, including protein structure prediction, molecular docking, system preparation and parameterization, molecular dynamics (MD) simulations, and QM/MM calculations. The conclusions drawn by EnzySeek are primarily based on the results of QM/MM calculations. We employed the semi-empirical quantum mechanical method GFN2-xTB to calculate the QM region of the system. Benchmark results indicate that the GFN2-xTB method can achieve high efficiency while maintaining accuracy. The EnzySeek agent is designed to continuously learn from newly published literature and past computational tasks. During its operation, every AI decision is manually verified and scored by human experts. This human-in-the-loop validation provides the AI with sufficient case-based support, ultimately contributing to the full automation of enzyme catalysis computations. All data generated during the simulations are compiled into a dataset, which is used to establish evaluation criteria specific to enzyme catalysis computational results.

biochemistry↗

bioRxiv2026

Dynamic Consistency Reveals Predictable Genes in Cross-Cell Type Temporal scRNA-Seq Data

Understanding how gene expression evolves over time after trauma is central to modeling immune responses, yet single-cell temporal data remain sparse and heterogeneous across cell types. Using a temporal trauma scRNA-seq dataset, we formulate the task of predicting next-time gene expression from earlier observations under a cross-cell-type generalization setting. We introduce the Dynamic Consistency Index (DCI), which quantifies how consistently a genes temporal trajectory aligns across cell types, serving as a measure of biological regularity and predictability. High-DCI genes exhibit reproducible temporal dynamics and are markedly easier to model. By integrating DCI-based gene selection with a recurrent neural architecture trained under a Gaussian negative log-likelihood objective, we achieve superior accuracy and well-calibrated uncertainty compared to deterministic baselines. Overall, DCI reliably identifies dynamically consistent genes, and uncertainty-aware recurrent modeling provides a robust framework for capturing cross-cell-type gene-expression evolution.

bioinformatics↗

bioRxiv2026

Defining Aeromonas species boundaries with large-scale average nucleotide identity analyses and genomic phylogeny

Aeromonas taxonomy has long been complicated by overlapping phenotypic, biochemical, and protein profiles. Here, we establish a robust genome-based framework for Aeromonas genomic species delineation. We analysed average nucleotide identity (ANI) across 4,366 available Aeromonas genomes and demonstrated that at 96% ANI threshold, skANI and fastANI generated too many clusters (65 and 57 respectively) and these clusters were not supported by core genome phylogeny. We identified 95.4% skANI (equivalent to 95.6% fastANI) as an operational threshold for the delineating Aeromonas genomic species. Using the 95.4% skANI threshold, we identified 44 ANI clusters among the 4,366 genomes, of which 43 clusters were genomic species supported by the core-genome phylogeny. Thirty-four of the 43 genomic species corresponded to existing taxonomic species, whilst the remaining nine are currently not recognised as taxonomic species. All recognised taxonomic species represented in the dataset retained their existing species designation except Aeromonas mytilicola, which was not separated from Aeromonas rivipollensis in both ANI clusters and the core-genome phylogeny. The digital DNA-DNA hybridisation (dDDH) values between the genomic species were below 70%, further supporting genomic species delineation. We further developed AeromonasGStyper, a genomic species typing tool that assigns query genomes based on ANI similarity to medoid genomes. In conclusion, this study establishes a genomic species framework for genome-based classification of Aeromonas and provides a practical approach for future genomic surveillance. Impact StatementAeromonas species have gained increased attention as emerging human enteric pathogens. Aeromonas taxonomy has long been complicated by overlapping phenotypic, biochemical, and protein profiles. Although a 96% average nucleotide identity (ANI) threshold was proposed previously for Aeromonas species delineation, analysis of 4,366 Aeromonas genomes demonstrated that this threshold generated excessive genomic clusters that were not supported by the core-genome phylogeny. We identified 95.4% skANI (equivalent to 95.6% fastANI) as an operational threshold for delineating Aeromonas genomic species, supported by core-genome phylogeny and digital DNA-DNA hybridisation (dDDH). The framework identified 43 genomic species, including 34 corresponding to recognised taxonomic species and nine genomic species that do not correspond to currently recognised taxonomic species. In addition, our data showed that Aeromonas mytilicola was not separated from Aeromonas rivipollensis by ANI clustering and core-genome phylogeny, supporting further taxonomic reassessment of the distinction between these two species.

microbiology↗

bioRxiv2026

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET images as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the "dark complex," modulate metabolic flux at a conserved regulatory node of the Calvin-Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4. Significance StatementThis work advances 4D whole-cell modeling by presenting the first spatiotemporal simulation of a photosynthetic autotroph using the Lattice Microbes platform. Using Prochlorococcus marinus MED4, we show that subcellular spatial organization of organelles, diffusion constraints, and redox regulation collectively shape central carbon metabolism across orders of magnitude in space and time. Through a perturbation-based strategy that generates multi-omics data sets over time, we construct and validate a spatially and temporally resolved model of MED4, constrained by high-resolution (10 nm) cryo-electron tomography. Our results highlight the importance of localized biochemical reactions and redox-dependent post-translational modification of enzymes in regulating carbon fixation in a noisy environment under light disturbance. This study establishes a spatiotemporal, whole-cell physiology modeling framework as a transformative tool for uncovering multiscale regulatory responses to environmental gradients.

systems biology↗

bioRxiv2026

Divergent chromatin remodeling trajectories in CD66b⁺ MDSCs distinguishes recovery from chronic critical illness after sepsis

Sepsis survivors exhibit divergent clinical trajectories, including rapid recovery (RAP) or progression to chronic critical illness (CCI), yet how these outcomes are linked to epigenetic repression remains poorly defined. Here, we applied an optimized Omni-ATAC approach to profile chromatin accessibility in CD66b myeloid-derived suppressor cells (MDSCs) from healthy participants and longitudinally sampled sepsis cohorts stratified by outcome. RAP samples progressively restored healthy chromatin states, whereas CCI samples remained epigenetically fixed in aberrant configurations. Chromatin remodeling exhibited strong pathway specificity: promoters associated with MHC class II antigen presentation were coordinately repressed in CCI, while MHC class I antigen processing and presentation machinery remained preserved. Genome-wide analyses revealed extensive promoter remodeling during recovery in RAP, including immune regulatory loci such as ARG1, CD274, and S100A8/A9, contrasted with broad suppression of immune, metabolic, and chromatin regulatory programs in CCI. These findings define divergent epigenetic trajectories in post-sepsis MDSCs and implicate selective failure of antigen presentation as a mechanism of sepsis-induced immunoparalysis in CCI.

immunology↗

bioRxiv2026

Tonically active interneurons gate motor output in Drosophila larvae

Tonic inhibition and its transient removal are fundamental neural mechanisms for gating activity, suppressing out-of-phase excitation, and enhancing the temporal precision of behavior. However, their roles within locomotor central pattern generators (CPGs) remain poorly understood. Here, we identify A02l neurons--segmentally repeated excitatory interneurons in the Drosophila larval ventral nerve cord (VNC)--that regulate crawling behavior through tonic inhibition. A02l neurons exhibit high baseline activity and are transiently suppressed during motor output. They provide excitatory input to inhibitory premotor networks, enabling widespread silencing of motor neurons to maintain muscle relaxation. Optogenetic activation of A02l neurons reduced crawling frequency, whereas their inhibition induced transient whole-body contractions. Together, these findings reveal a cellular-resolution mechanism for tonic inhibition within the nerve cord and highlight its importance in gating motor output and maintaining motor quiescence.

neuroscience↗

bioRxiv2026

Murine Neutrophil Chemotaxis Following Burn Injury with Poloxamer 188 Treatment in a Microfluidic Platform

This study investigates the effects of Poloxamer 188 (P188) on neutrophil chemotaxis following burn injury in male and female mice using a microfluidic system. Utilizing male and female CD1 mice, we evaluated neutrophil migration towards two chemoattractants, N-formyl-l-methionyl-l-leucyl-l-phenylalanine (fMLP) and Leukotriene B4 (LTB4), and FPR1 and BLT1 G protein-coupled receptors after administering P188. Our findings revealed that P188 significantly increased the migration toward LTB4 in both sexes. Additionally, our findings highlight the upregulation of BLT1 and FPR1 markers due to burn injury in both female and male mice in the Burn vs. Sham groups. These results demonstrate the potential of P188 in modulating neutrophil behavior post-burn injury in therapeutic strategies for inflammation management. This microfluidic platform offers a precise and controlled microenvironment for studying neutrophil chemotaxis post-burn injury with and without P188 treatment.

bioengineering↗

bioRxiv2025

Prolonged Loss of Oxidative Phosphorylation and Mitochondrial Mass Characterize CD66b+ Leukocytes from Patients with Sepsis

IntroductionSepsis leads to expansion of myeloid-derived suppressor cells (MDSC) and their subtypes. These normally transitory MDSCs suppress T cell activation and alter T cell cytokine production while simultaneously promulgating systemic low-grade inflammation. Immune metabolism can shape cell responses, regulate immune suppression, and enhance effector activity. Although MDSC metabolism has been extensively studied in cancer, the metabolic phenotype of this heterogeneous population in sepsis remains unclear. Our goal was to assess metabolic flux in blood MDSCs during and after sepsis and to stratify these patients clinical features and outcome with differences in metabolic flux that may guide treatment decisions. MethodsPeripheral blood mononuclear cells (PBMC) from healthy subjects and sepsis patients at 4 days, 2-3 weeks, and 6 months underwent CD66b+ or CD3+ enrichment, followed by assessment of metabolic flux, flow cytometry, mRNA sequencing, and chromatin accessibility. ResultsMitochondrial basal oxygen consumption rates (OCR) and maximal oxygen consumption rates (SRC, spare respiratory capacity) were decreased in MDSC from septic patients at 4 days after infection and persisted for up to 6 months after sepsis onset. Sepsis was not associated with differences in glycolysis. In contrast, oxidative metabolism in CD3+ T cells was similar between sepsis patients and healthy subjects. Reduced MDSC oxidative metabolism was linked to adverse clinical outcomes. The decline in oxygen consumption from MDSCs in septic patients was also associated with significant reductions in MDSC mitochondrial content. Transcriptomic analysis of CD66b+ cells isolated from PBMC of healthy participants and patients with sepsis at 4 days, 2-3 weeks, and 6 months revealed 19 differentially expressed genes and three long non-coding RNAs as potentially responsible for this decline in mitochondrial mass. Specifically, NR4A3, NR4A2, and TAMLIN/NR4A1 expression, all critical for mitochondrial biogenesis, were persistently decreased with reduced chromatin accessibility indicative of gene silencing. DiscussionAfter sepsis, blood CD66b+ cells present with reduced mitochondrial mass and oxidative metabolism that continue at least 6 months after sepsis. These changes in mitochondrial function result from a reduced content of these organelles. We have also identified gene silencing, reduced gene expression of key transcription factors that regulate mitochondrial biogenesis, as well as increased long non-coding RNA as potential drivers of this unique metabolic phenotype. These results highlight the potential benefit of targeting metabolism in sepsis to promote immune homeostasis and recovery.

immunology↗

bioRxiv2025

EcoKMER: One-stop shop for spatio-temporal metagenomic exploration using DataFed

Spatially distributed environmental sampling generates highly complex and multidimensional datasets illuminating key insights into microbial diversity, evolutionary-coevolutionary processes, and host-pathogen interactions. While these sampling methods generate high value datasets, dataset size, the dataset integration, visualization, analysis, and provenance tracking present significant bottlenecks to scientific discovery. To address this bottleneck, we developed EcoKMER, an R-Shiny front-end application designed to streamline metagenomic data accessibility and provide geospatial context to data in support of hypothesis-driven investigations into environmental sampling, supported by DataFed as its back-end data management platform. EcoKMER enables interactive visualization and filtering of harmonized metagenomic data and metadata using an interoperable approach, allowing users to extract spatially distributed sample-based metadata on top of environmental parameters such as geolocation, temperature, pH, for investigating ecological changes across time and space enhancing sample processing methods. As an example, we deployed this tool to track analysis of metagenomes from the organisms in the Salish Sea Estuary, consistent with existing community-accepted standards. Built on top of DataFed, a flexible and robust scientific data management system built for data lakehouse architectures, EcoKMER is positioned as a powerful tool to improve sampling strategy decision making, accelerate new insights for collaborative biological and environmental research, and fostering AI-ready analyses designed to enhance discovery and guidance for bioeconomic engineering. The published manuscript is available at https://www.osti.gov/biblio/3412938

bioinformatics↗

bioRxiv2025

Multilevel HierCC typing scheme for global genomic epidemiology and antimicrobial resistance surveillance of Campylobacter jejuni

Campylobacter jejuni is the most common bacterial cause of human gastroenteritis around the world. The disease burden and financial cost associated with C. jejuni pose significant challenges to the global public health system. A stable, scalable and standardised typing scheme is essential for epidemiological and AMR surveillance for prevention and control of C. jejuni infections. We curated and assembled a C. jejuni global whole genome sequencing (WGS) dataset of 63,012 publicly available Illumina short-read genomes. A C. jejuni global cgMLST scheme with 1161 core loci was developed using a representative subset of 2,587 genomes. HierCC clustering of the cgMLST profiles was performed for all levels and suitable HierCC levels were selected to enable epidemiological analysis. Antimicrobial resistance (AMR) prediction was performed using AbritAMR. A HierCC cluster was classified as a resistant cluster if [≥]80% of the isolates were resistant to at least one antibiotic.We selected 9 HierCC levels (HC2, HC4, HC6, HC12, HC19, HC55, HC100, HC167 and HC264) to form the multilevel HierCC scheme. The multilevel design allowed natural and genetically discrete clusters to be described consistently at both global and local scale. We showcased the utility of the scheme with identification of country and continent specific clusters at HC264 to HC19 levels and differentiation of animal host specific (specialist) from human infection (generalist) clusters at HC264 to HC55 levels. In the USA dataset from 2016 to 2022, a total of 276 resistant clusters were identified with 22 resistant clusters increasing in frequence in recent years. An increased prevalence of C. jejuni carrying 50S_L22 mutations in the USA was observed from 2016 to 2022, suggesting continuing selection pressure from macrolide use in the farm animals. We developed a novel multilevel HierCC typing scheme to standardise AMR surveillance and provide flexible typing resolution for both short- and long-term epidemiological investigations of C. jejuni at global and local levels.

microbiology↗

bioRxiv2025

Full-length structure of CPR-containing self-sufficient cytochrome P450

Cytochrome P450 (P450s) are heme-thiolate monooxygenases that exploit electrons sourced from pyridine nucleotide to reduce the oxygen and heme iron to catalyze hydroxylation of inactivated C-H bond1-4. Self-sufficient P450s that contain the substrate-binding heme-domain and the electron-donating NADPH:cytochrome P450 reductase (CPR) domain in the same polypeptide chain are highly effective and have been engineered to catalyze various challenging reactions. The high efficacy attributes to the effective electron transfer rate, but how the electrons travel among the redox centers remains elusive owing to the lack of structural information of the full-length protein. Here, we report the structure of a homologue of the most extensively studied P450BM3 from Shimazuella soli (SoP450) resolved by single particle cryo-electron microscopy (cryo-EM) and X-ray crystallography. SoP450 primarily exists as a homodimer formed via the intertwined CPR-domains. The spatial alignment of the heme-domain that is linked via an extensive loop was also determined. Notably, a class of structure that lacks one heme-domain was identified from the cryo-EM analyses, indicating that the heme-domain is mobile. We suspected that the heme-domain could move to reach the CPR-domain for electron acquisition and built a model of putative catalytic state to reveal how the electrons are relayed from NADPH to heme. These results are of fundamental importance to understand the catalytic reaction of CPR-containing self-sufficient P450s, which shall provide critical information to the engineering and applications of these enzymes.

synthetic biology↗

bioRxiv2025

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aqueous environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogen coevolution. The Salish Sea, located in the Western coastal waters bordering the USA and Canada, is at the current northern boundary (defined by Prochlorococcus versus Synechococcus prevalence ratios) of the range of Prochlorococcus. Predictions suggest that this boundary will shift northward as warmer waters move northward, providing an excellent system to study host-pathogen dynamics and coevolution in a changing environmental context. In preparation for such studies, we developed and refined methods to sample and sequence cyanobacteria, cyanophages, and their abiotic environment. In addition to basic methodological questions focused on the physical sampling, filtering, viral precipitation, DNA extraction, and technical replicability, we explored how well our filtering and extraction protocols enrich for our main target, picocyanobacteria. The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol at the conclusion of these experiments based on yield and processing time is presented. We recovered substantial Prochlorococcus, Synechococcus and amoeba-like sequences in most samples, and preliminary exploration of relative taxon sequence read recoveries across locations, over time, and tidal conditions are also discussed. Approaches described here may be useful to other efforts such as harmful algal bloom monitoring, species isolation and enrichment, water quality assessments, anti-viral discovery, and understanding picocyanobacterial population changes over space and time.

microbiology↗

bioRxiv2025

Across-speaker articulatory reconstruction from sensorimotor cortex for generalizable brain-computer interfaces

ObjectiveSpeech brain-computer interfaces (BCIs) can restore speech features like articulatory movements from brain activity. However, for individuals with vocal tract paralysis, lack of articulatory movements can pose a challenge for speech BCI development. To address this challenge, our study aims at extracting generalizable articulatory features from a group of native Dutch speakers and reconstructing these features from brain data of a separate group of able-bodied individuals. ApproachWe applied a tensor component analysis (TCA) model to extract generalisable articulatory features from a publicly available articulatory movement dataset. To reconstruct articulatory features from the brain, we analyzed data of three able-bodied participants P1, P2 and P3 with high-density electrocorticography (HD-ECoG) electrode arrays implanted over the sensorimotor cortex. For each participant, a separate TCA model was applied to extract neural features. A gradient boosting regression model was used to reconstruct articulatory features from neural features. Reconstruction performance was measured as Pearsons correlation coefficient (PCC) between the reconstructed and the generalizable articulatory features. ResultsThe extracted articulatory features showed even contributions across participants, indicating that these features captured generalizable articulatory kinematic patterns. By using these features, we were able to reconstruct articulatory features from brain data. PCC between the reconstructed and original articulatory features were significantly above chance for all three participants, with mean PCCs of 0.80, 0.75 and 0.76 for P1, P2 and P3 respectively. SignificanceWith the rapid development of speech BCI, our research demonstrates that speech-related articulatory features can be restored from HD-ECoG signal using generalizable articulatory features derived from able-bodied individuals. With the potential to reconstruct audio or speech-related facial movements from the reconstructed articulatory features, our framework may provide a new way for developing speech BCIs for people unable to produce mouth movements.

neuroscience↗

bioRxiv2025

A deep learning and co-conservation framework enable discovery of non-canonical Cas proteins

CRISPR-Cas systems are central to prokaryotic adaptive immunity, widely harnessed for biotechnology. Yet, their vast and uncharacterized diversity, especially non-canonical variants, impedes full exploitation. Here we present BioPrinCRISPR, a class-agnostic computational framework leveraging gene co-conservation, protein domain co-occurrence, and embedding similarity to identify and characterize CRISPR-Cas systems across prokaryotic genomes. Applying BioPrinCRISPR to over one million bacterial genomes, we uncovered extensive canonical and uncharacterized systems, revealing a rich landscape of atypical Cas proteins and novel domain architectures. Notably, we identified recurrent fusion proteins with unique enzymatic combinations, suggesting roles in regulatory control or nucleic acid remodeling. Experimental validation of two divergent Cas13an-like effectors demonstrated RNA knockdown capacity in human cells, confirming our frameworks predictive power. These findings expand the functional repertoire of CRISPR-associated proteins and highlight unexplored modes of microbial immunity. BioPrinCRISPR thus stands as a powerful tool for comprehensively mapping CRISPR-Cas diversity, offering new insights into prokaryotic defense and facilitating discovery of novel candidates for next-generation genome engineering. An accompanying interactive web platform was also developed to facilitate data exploration.

synthetic biology↗

bioRxiv2025

DECREASE IN DNA METHYLATION 1-mediated epigenetic regulation maintains gene expression balance required for heterosis in Arabidopsis thaliana

Heterosis, or hybrid vigor, is characterized by superior phenotypic performance in F hybrids compared to their parental lines, and its expression is influenced by both genetic and epigenetic factors. In this study, we investigated the role of epigenetic regulation, particularly DNA methylation mediated by DECREASE IN DNA METHYLATION 1 (DDM1), in early seedling biomass heterosis using hybrids between Arabidopsis thaliana accessions Columbia-0 and C24. Loss of DDM1 function in F hybrids resulted in a significant reduction of rosette diameter, confirming that DDM1 is essential for heterosis. Transcriptomic and epigenomic analyses revealed extensive genotype-specific changes in gene expression and DNA methylation patterns in ddm1 mutants. Notably, ddm1-F hybrids exhibited upregulation of genes categorized into xyloglucan:xyloglucosyl transferase activity and downregulation of genes categorized into circadian rhythm, which may contribute to reduced growth vigor. Whole-genome bisulfite sequencing showed widespread hypomethylation in ddm1 mutants, yet the overlap between differentially methylated and expressed genes was limited, suggesting indirect or context-dependent regulatory effects. Additionally, we examined the role of salicylic acid (SA) in heterosis using SA-deficient mutants and found that variations in endogenous SA levels did not correlate with biomass heterosis under normal conditions. Our findings suggest that heterosis in A. thaliana is dependent on the maintenance of parental epigenetic divergence, particularly in DNA methylation patterns mediated by DDM1. Disruption of DDM1 compromises this epigenetic complementarity, leading to transcriptomic imbalances that reduce heterosis. HighlightLoss of DDM1 reduces biomass heterosis in Arabidopsis thaliana hybrids by disrupting DNA methylation and transcriptome stability, revealing a novel salicylic acid-independent epigenetic mechanism.

plant biology↗

bioRxiv2025

Translational control of innate barrier defense by the gut microbiota

The intestinal epithelium is protected by a mucus barrier, infused with antimicrobial proteins, that restricts microbial access to host tissue. Because assembling this barrier is energetically costly, its production must be tightly regulated. Here, we show that the microbiota regulates the translation of key mucus barrier components, including the structural glycoprotein mucin 2 and the antimicrobial enzyme lysozyme. This process is initiated by microbial induction of histone deacetylase 5 (HDAC5) in secretory epithelial cells of the intestine. HDAC5 promotes deacetylation of 14-3-3 proteins, enabling activation of the energy sensing kinase mTOR which enhances translation of mucus and antimicrobial proteins. These findings reveal a mechanism by which the microbiota controls barrier immunity at the level of protein synthesis and suggest that the HDAC5-mTOR axis integrates microbial and energetic signals to regulate intestinal defense. One sentence summaryThe gut microbiota enhances translation of innate barrier defense proteins through HDAC5-mediated activation of mTORC1 signaling.

immunology↗