Biology subjects

Wen, R.

Publications and source records attributed to Wen, R..

10 recordsLinked to original sources

bioRxiv2026

Cell-Based Sensor for Extracellular DNA

Detection of molecules with cell-based sensors allows for conversion of binding events into gene expression outputs. Here, we present a cell-based sensor that can detect extracellular double-stranded DNA. This sensor is based on an engineered receptor which we call Luminescent Ultrasensitive Nucleic Acid Reporter, or LUNAR. LUNAR is based on a recently developed Programmable Antigen-gated G-protein-coupled Engineered Receptor (PAGER). PAGERs are a genetic fusion of an auto-inhibitory peptide, a protein-binding domain, and a modified kappa opioid receptor. PAGERs are gated by two binding events. First, a protein ligand displaces an intramolecular inhibitor, Arodyn, then a second ligand activates the receptor. By replacing the protein-binding domain with a DNA binding zinc finger protein (ZFP) we could detect extracellular DNA in a dose-dependent fashion. Here, we show that first-generation LUNAR constructs can detect both oligonucleotides and plasmid double-stranded DNA with nanomolar sensitivity in mammalian cells. Future work will focus on improving sensitivity, fold-change, and multiplexing capabilities for sequence-specific DNA detection.

synthetic biology↗

bioRxiv2026

FiberLM: A Transformer-Based Model for Mouse Brain Diffusion MRI Tractography Guided by Viral Tracer Data

Diffusion MRI (dMRI) tractography provides a non-invasive method for mapping whole-brain structural connectivity. However, its application is limited by substantial false-positive and false-negative connections. While deep learning based methods have shown promise in improving tractography, most rely on training data derived from conventional dMRI tractography, therefore inheriting the same limitations. Here, we introduce FiberLM, an attention-based Transformer model for mouse brain tractography. The model was trained using a whole-brain streamline dataset based on viral tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA), allowing the model to learn the properties of both local and long-range axonal trajectories through self-attention. FiberLM was applied to predict anatomically plausible axonal trajectories from ex vivo high-resolution mouse brain dMRI data. Quantitative evaluations demonstrated that FiberLM significantly reduced false-positive and false-negative connections, improved spatial agreement with tracer-defined pathways, and generated whole-brain connectomes that more closely approximated AMBCA results compared to conventional tractography. These findings suggest FiberLM as a potential tool for accurate reconstruction of mouse brain structural connectomics.

neuroscience↗

bioRxiv2026

Deep learning framework ChIANet predicts protein-mediated chromatin architecture across functional contexts

The spatial organization of the genome is dynamically shaped by chromatin-binding proteins, yet how protein-mediated three-dimensional (3D) architectures are specified across functional contexts remains incompletely understood. Here we present ChIANet, a multimodal deep learning framework that enables de novo prediction of protein-mediated chromatin contact maps and loops from protein-binding profiles alone, using the reference genome sequence as a prior. By integrating transformer-based long-range modeling with multi-task learning, ChIANet accurately reconstructs protein-mediated 3D chromatin architectures and generalizes across diverse cellular contexts. Systematic application of ChIANet to CTCF, Cohesin and RNAPII across seven human cell types reveals that chromatin architectures follow conserved organizational principles while exhibiting pronounced context-dependent reconfiguration: CTCF- and Cohesin-mediated interactions predominantly support stable structural frameworks, whereas RNAPII-mediated loops display greater variability and are closely coupled to transcriptional programs and regulatory element activity. Functional analyses further uncover distinct regulatory biases and super-enhancer associations among the three proteins. Extending this framework to cancer genomes, ChIANet captures RNAPII-mediated chromatin looping networks associated with extrachromosomal DNA (ecDNA), revealing highly connected, transcription-associated architectures within amplified ecDNA regions across multiple cancer cell types. Together, these results demonstrate that protein-mediated 3D genome organization is not determined by protein identity alone but is flexibly shaped by functional context, regulatory targets and cellular environment, establishing ChIANet as a unified and scalable approach for decoding context-dependent principles of genome folding.

genomics↗

bioRxiv2025

Unraveling the archaeal virosphere: diversity, functional and virus-host interactions

Archaea, the third domain of life, play critical roles in global biogeochemical cycles. However, their virosphere, particularly the proviruses which integrated into host genomes, remains largely unexplored. To systematically reveal the landscape of archaeal proviruses, we conducted large-scale mining of public and in-house genomic datasets spanning all presently known archaeal phyla. We identified 9,697 archaeal proviruses across 19 archaeal phyla and 366 families, which clustered into 9,123 viral operational taxonomic units (vOTUs). Among these, 97.2% represent novel viruses, and 81.3% could not be classified at the family level, substantially expanding the known diversity of archaeal viruses. Host range analysis revealed that many proviruses exhibit broad infectivity across archaeal lineages, with some even capable of cross-domain infection. Genomic analysis identified 178 distinct types of antiviral systems in archaeal hosts, encompassing multiple CRISPR-Cas variants and restriction-modification (RM) systems. Meanwhile, we detected 747 anti-defense genes encoded by 710 proviruses, such as anti-CRISPR and anti-RM, directly corroborating the ongoing evolutionary arms race between archaeal hosts and their viruses. Additionally, we identified 532 auxiliary metabolic genes (AMGs) within archaeal proviruses that are involved in key processes including carbon, nitrogen, and sulfur metabolism, indicating their potential to reprogram host metabolic pathways and thereby influence biogeochemical cycling. This study establishes a systematic global genomic atlas of archaeal proviruses, advancing our understanding of their distribution and diversity while laying the groundwork for future investigations into how AMG-mediated processes influence archaeal metabolism and ecosystem functions.

ecology↗

bioRxiv2025

Impact of 2'-deoxyribo-purine substrates on nonenzymatic RNA template-directed primer extension

The composition of the primordial genetic material remains uncertain. Studies of duplex structure and stability, and of nonenzymatic template copying chemistry, provide insight into the viability of potentially primordial genetic polymers. Recent work suggests that 2'- deoxyribo-purine nucleotides may have been generated together with ribonucleotides on the early Earth. Since DNA/RNA duplexes are known to be less stable than RNA/RNA duplexes, we have examined the impact of dA, dI, and dG substitutions on RNA structure and nonenzymatic template copying. We find that single 2'-deoxyribo-purine substitutions reduce RNA duplex stability, as expected. Crystallographic studies show that such substitutions lead to minimal structural changes but point to diminished solvation as a likely reason for duplex destabilization. Kinetic studies show that dI and dG substrates exhibit slightly weaker template binding and slower rates of template-directed primer extension than the corresponding ribo-purine substrates. In contrast, dA substrates exhibit much slower reaction kinetics but higher template affinity than rA substrates. Our results suggest that a mixed RNA/DNA primordial genetic polymer would have suffered from moderately slower rates of template copying, but that this could have been offset by an advantage due to more facile strand separation or exchange. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/673048v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@15bd09aorg.highwire.dtl.DTLVardef@dc49d4org.highwire.dtl.DTLVardef@730d20org.highwire.dtl.DTLVardef@162b84f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Functional and evolutionary characterization of potential auxiliary metabolic genes (AMGs) of the global RNA virome

RNA viruses play an important role in regulating their host and global biogeochemical cycling, and auxiliary metabolic genes (AMGs) are one of the main pathways by which viruses regulate hosts metabolism. However, the AMGs encoded by global RNA viruses are largely unexplored. Here, we annotated RNA viral genomes and identified AMGs from recently published global RNA virome datasets. We found 274 AMGs encoded by 243 RNA viral genomes, which accounts for only 0.008% of all 3,216,257 genomes investigated. These AMGs span 25 functional categories, the most prevalent being translation, energy metabolism, membrane transport, transcription, replication and repair, and signal transduction. Unlike DNA viruses, RNA viruses tend to encode AMGs influencing the genetic and environments information processing of their hosts, with fewer AMGs linked to nutrient cycling, such as carbon and nitrogen metabolism. In addition, RNA viruses encoding these AMGs were taxonomically diverse, spanning five established phyla, the newly proposed phylum "Taraviricota" and fourteen LucaProt supergroups. Host prediction indicated that most of these RNA viruses encoding AMGs infect eukaryotes, while only a few of them, including Leviviricetes and Vidaverviricetes, infect prokaryotes. Interestingly, the potential host phylum for most of these RNA viruses were different from the likely source phylum of their AMGs, suggesting the possibility that these RNA viruses acquired AMGs from organisms outside their predicted host range. This study provides the first comprehensive analysis of AMGs from global RNA virome, which greatly expands our understanding of their function roles, evolutionary history and virus-host interactions.

ecology↗

bioRxiv2024

Loss of PMR4 callose synthase results in salicylic acid-independent and broad-spectrum resistance to clubroot in Arabidopsis and Brassica napus

The clubroot disease caused by protist Plasmodiophora brassicae is one of the most important diseases of Brassica crops. Growing clubroot-resistant cultivars remains the most effective and practical approach to managing clubroot disease. However, resistance gene-mediated immunity is rapidly overcome in the field when new pathotypes arise. In this study, we identified PMR4 as a potential gene target for creating a novel clubroot-resistant source. Recessive PMR4 mutations in Arabidopsis thaliana conferred broad-spectrum resistance to multiple P. brassicae pathotypes, independent of salicylic acid-mediated plant immunity. CRISPR/Cas9-mediated gene-editing was employed to create mutations in two PMR4 orthologs in the B. napus genome, and resulting homozygous mutants exhibited dual resistance to powdery mildew and clubroot. PMR4 is required for the callose deposition at wound and powdery mildew infection sites in leaves. This study reveals that callose deposition in roots is induced by P. brassicae infection and requires PMR4. It appears that the clubroot disease progression is arrested at the primary-to-secondary infection phase in pmr4-1 mutants. Together, this study demonstrates that PMR4-encoded callose synthase is a host susceptibility factor required for P. brassicae to complete its life cycle, and that PMR4 can be targeted against both powdery mildew and clubroot diseases in Brassica crops.

plant biology↗

bioRxiv2024

Diversity and ecological roles of RNA viral communities in the cryosphere of the Tibetan Plateau

RNA viruses play crucial roles in modulating host communities, but their diversity and ecological roles in the cryosphere are poorly understood. We investigated the RNA virome from the cryosphere of the Tibetan Plateau (TPC), the largest area of the cryosphere in the mid-low latitude regions, which includes 79 metatranscriptomes from ecosystems including glaciers, proglacial lake sediments, permafrost wetland and upland soils. We obtained 8,799 RNA-dependent RNA polymerase encoding contigs, which clustered into 5,333 viral species, adding more than 4,900 new RNA viral species to the global RNA virome database. The recovered RNA viruses primarily infect prokaryotes, distinctively different from the dominance of eukaryotic RNA viruses in oceanic ecosystems. In addition to the known taxa such as Leviviricetes, we identified novel clades of putative prokaryotic RNA viruses, which greatly extended our understanding of their diversity. We further expanded the host of RNA virus by 20 additional prokaryotic phylum- or class-level taxonomic groups. Moreover, the TPC RNA viruses encoded dozens of auxiliary metabolic genes that could reprogram the metabolisms of diverse hosts, including photosynthesis in glacier eukaryotic algae and cyanobacteria, which may exert great impacts on glacier dynamics through modulating host adaptation. Furthermore, we identified potential pathogenic RNA viruses in various cryosphere environments, though their overall risks are low. This study provides the first comprehensive view of cryosphere RNA virome, highlighting their high diversity, vital ecological functions, and potential health impacts.

ecology↗

bioRxiv2022

The RNA m6A reader YTHDF1 promotes hematopoietic malignancy by maintaining oncogenic translation

N6-methyladenosine (m6A), the most abundant modification in mRNAs, has been defined as a crucial modulator in the progression of acute myeloid leukemia (AML), while the detailed mechanism remains elusive. Here we report that YTHDF1, an m6A reader protein, is overexpressed in human AML samples with enrichment in leukemia stem cells (LSCs). Whereas YTHDF1 is dispensable for normal hematopoiesis in mice, depletion of YTHDF1 attenuates self-renewal and proliferation of patient-derived LSCs, and impedes leukemia establishment in immunodeficient mice. Mechanistically, YTHDF1 promotes the translation of diverse m6A-modified oncogene mRNAs particularly cyclin E2. We applied a structure-based virtual screening of FDA-approved drugs and identified tegaserod as a potential YTHDF1 inhibitor. Tegaserod blocks the direct binding of YTHDF1 with m6A-modified mRNAs and inhibits YTHDF1-regulated mRNA translation. Moreover, tegaserod inhibits leukemogenesis in vitro and in mice, phenocopying the loss of YTHDF1. Together, our study defines YTHDF1 as an integral regulator of AML progression at the translational level and identifies tegaserod as a potential therapeutic agent for AML by targeting YTHDF1. Statement of SignificanceO_LIThe RNA m6A reader YTHDF1 is an oncoprotein in AML. C_LIO_LIYTHDF1 promotes the translation of m6A-modified oncogene mRNAs. C_LIO_LITegaserod, an FDA-approved drug for irritable bowel syndrome, inhibits YTHDF1-regulated mRNA translation and leukemogenesis. C_LI Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cancer biology↗

bioRxiv2022

Mouse primary T cell phosphotyrosine proteomics enabled by BOOST

The Broad Spectrum Optimization of Selective Triggering (BOOST) approach was recently developed to increase the quantitative depth of the tyrosine phosphoproteome by mass spectrometry-based proteomics. While BOOST has been demonstrated in the Jurkat T cell line, it has not been demonstrated in scarce mice primary T cells. Here, we show the first phosphotyrosine proteomics experiment performed in mice primary T cells using BOOST. We identify and precisely quantify more than 2,000 unique pTyr sites from more than 3,000 unique pTyr peptide PSMs using only 1 mg of protein from T cell receptor-stimulated primary T cells from mice. We further reveal the importance of the phase-constrained spectrum deconvolution method ({Phi}SDM) parameter on Orbitrap instruments that, when disabled, enhances quantitation depth, accuracy, and precision in low-abundance samples. Using samples with contrived ratios, we find that disabling {Phi}SDM allows for up to a two-fold increase in the number of statistically significant intensity ratios detected while enabling {Phi}SDM degrades quantitation, especially in low-abundance samples. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/491817v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@4a2742org.highwire.dtl.DTLVardef@57645borg.highwire.dtl.DTLVardef@17dbfacorg.highwire.dtl.DTLVardef@b2df00_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗