Biology subjects

Hu, K.

Publications and source records attributed to Hu, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Valine Engages a Prefrontal mGluR5 Allosteric Site to Preserve Social Behavior

Branched-chain amino acid metabolism is linked to neurodevelopmental disorders, but whether a defined amino acid directly modulates cortical receptor signaling to control behavior is unknown. Here, we show that valine is uniquely required for sociability through medial prefrontal cortex (mPFC) circuitry. Partial dietary valine restriction, but not comparable leucine or isoleucine restriction, or mPFC-restricted acceleration of BCAA catabolism through Bckdk loss, disrupts social interaction, and local valine supplementation rescues behavior. LiP-SMap, surface plasmon resonance, cryo-EM, and mutagenesis identify metabotropic glutamate receptor 5 (mGluR5) as a direct valine target and reveal a valine-selective allosteric pocket distinct from the glutamate site. Valine is signaling-biased: it drives {beta}-arrestin-linked output yet has little standalone Gq efficacy, instead potentiating glutamate-evoked mGluR5 signaling to recruit endocannabinoid/CB1 feedback, gate inhibitory transmission, and preserve mPFC-dependent social behavior. Together, these findings identify valine as a diet-derived allosteric ligand that links amino acid availability to cortical circuit control of social behavior.

neuroscience↗

bioRxiv2026

Predictive Modeling of Cancer Cell Growth Kinetics with Machine Learning

Quantitative characterization of cell proliferation is central to preclinical drug discovery. Here, we evaluated Random Forest (RF) regression for predicting confluence-based cell growth trends using data from human cancer cell lines and benchmarked its performance against the widely used logistic and Gompertz models. The RF model achieved higher predictive accuracy within the evaluated dataset, particularly at higher initial seeding densities. We further extended the RF framework to predict growth curves across seeding densities. Collectively, these findings highlight the potential of data-driven modeling to complement conventional mathematical approaches and support more informed cell-culture design.

bioinformatics↗

bioRxiv2026

HDA6-mediated histone deacetylation restricts premature tapetal PCD to maintain male fertility during early flowering in Arabidopsis

Histone deacetylation regulates plant development, yet its role in male gametophyte development and fertility remains unclear. Here, we show that histone deacetylase 6 (HDA6), an RPD3-like histone deacetylase, epigenetically regulates timely tapetal programmed cell death (PCD) and male fertility, predominantly during early flowering in Arabidopsis. Loss of HDA6 in axe1-4 causes early-stage male sterility followed by fertility recovery, accompanied by premature tapetal PCD, impaired pollen development and defective pollen wall formation. HDA6 interacts with squamosa promoter binding protein-like 8 (SPL8) to repress Arabidopsis NAC domain containing protein 087 (ANAC087) through H3K9/K14 deacetylation. In axe1-4, ANAC087 derepression activates cysteine endopeptidase 1 (CEP1), triggering precocious tapetal PCD. Genetic suppression of ANAC087 or CEP1 restores male fertility. Thus, HDA6-SPL8 establishes a stage-dependent epigenetic checkpoint that restrains the ANAC087-CEP1 cell death pathway and ensures timely tapetal PCD. Our study reveals how chromatin regulation integrates with developmental timing to safeguard plant male fertility.

plant biology↗

bioRxiv2026

High-throughput physics-based enzyme engineering

Enzyme engineering aims to tailor natural enzymes for industrial and therapeutic applications, yet physically grounded rational design has been limited by a trade-off between accuracy and cost, leaving the field heavily dependent on expert intuition. Here we present a scalable physics-based framework that combines field-aware machine learning with molecular mechanics to capture enzyme electrostatics at quantum-mechanical accuracy while enabling efficient, atomistic exploration of reaction free-energy landscapes. Coupled with microkinetic modelling, the framework translates molecular free-energy landscapes into catalytic rates and selectivity across competing, multistep reaction pathways. Applied to a newly engineered oxidative amidase (OxiAm), the framework predicts catalytic rate constants with near-experimental accuracy, quantitatively resolves the selectivity between hydrolysis and aminolysis, and generalizes across substrates, mutations and enzyme homologues. Transition-state ensemble analysis further reveals the reaction mechanism and guides the design of enzyme variants for pharmaceutical synthesis. By bringing chemical accuracy and high-throughput sampling to enzyme catalysis, this approach shifts rational design from static, empirical practice toward dynamic, free-energy-driven design, and should accelerate the engineering of biocatalysts.

biophysics↗

bioRxiv2026

High frame rate in vivo two-photon microscopy to quantify murine cerebrospinal fluid flow heterogeneity

Cerebrospinal fluid (CSF) flows through perivascular spaces (PVSs) surrounding brain vasculature, and impaired flow has been linked to neurodegenerative diseases such as Alzheimer's. However, the mechanisms driving CSF flow and its oscillatory dynamics remain poorly understood. Using high frame rate two-photon imaging (up to 113 Hz), we show that CSF flow is spatially heterogeneous and highly pulsatile, quantified using a regional CSF pulsatility index (PI). Reduced-order simulations with realistic domain length and Windkessel boundary conditions show that arterial pulsations generate peak CSF velocities but contribute negligibly to net transport. PI varies non-monotonically in space and substantially with downstream hydraulic resistance and compliance, indicating that CSF pulsatility is an emergent property of the hydraulic network rather than simply a consequence of local arterial wall motion. Measurements and simulations of the phase between arterial wall motion and CSF velocity further constrain proposed CSF driving mechanisms. Finally, we perform mouse-specific simulations to estimate average and peak wall shear stresses which support the potential role of pulsatile CSF flow in perivascular mechanotransduction. Together, these results establish CSF pulsatility as a measurable signature of network-scale CSF dynamics.

neuroscience↗

bioRxiv2026

Proteome-wide crosslinking mass spectrometry reveals novel components of essential complexes in Toxoplasma

Protein-protein interactions underpin nearly all cellular processes, yet systematic definition of these networks remains limited outside a few model organisms. As a result, the architectures of essential complexes in many divergent lineages remain poorly characterized. Here we developed a high-coverage crosslinking mass spectrometry framework to map the proteome-wide interactome of the model apicomplexan parasite Toxoplasma gondii. From 29,624 crosslinked peptide pairs, we resolved a network of 2,859 protein-protein interactions that we integrated with structural modeling to resolve interaction interfaces. We identified and validated previously unrecognized components of essential protein complexes, including a structurally distinct ATP synthase subcomplex containing a highly divergent, apicomplexan-specific subunit essential for parasite fitness. Beyond revealing unexpected diversification of core mitochondrial machinery, these findings provide a general strategy to define the molecular architecture of divergent organisms and represent a foundational resource for hypothesis generation, structural inference, and discovery of lineage-specific vulnerabilities in pathogen biology.

microbiology↗

bioRxiv2026

Half-match recombination drives bridge RNA-guided excision and off-target insertion

IS110-family bridge recombinases are a recently identified class of compact, RNA-guided editors in which a bridge RNA (bRNA) directs the recombination of a donor DNA into a target site. In the current model, the bRNA engages fully complementary donor and target sequences within a single synaptic complex to drive double-stranded recombination, implying that the transposon is cut from its donor site rather than copied, yet neither the strandedness of the excised intermediate nor the requirement for full complementarity has been tested directly. Here we reconstituted IS621 recombination in a cell-free transcription-translation system, building representative arrangements of the excision and insertion reactions and characterizing the outcomes. We find that IS621 predominantly excises a single strand, releasing a single-stranded circle and leaving the donor site intact, consistent with copy-and-paste transposition. By introducing mismatches into the bRNA target sequences, we further find that excision proceeds independently of target-site complementarity, relying strictly on donor-arm recognition; we term this "half-match" recombination, because a substrate matching only half of the bRNA is sufficient. We also find half-match activity during insertion, both in vitro and in a published genome-editing experiment, where it accounts for approximately half of non-target insertion reads. Half-match recombination provides both a mechanistic explanation for off-target insertion and a framework for the rational design of high-fidelity bridge recombinases.

molecular biology↗

bioRxiv2026

Canonically minimal RNA-guided insertion sequences expand into large elements that disseminate antimicrobial resistance

IS110 has emerged as a powerful genome-editing tool because it is the smallest RNA-guided system capable of diverse programmable insertions. Naturally existing elements are conventionally modeled as compact[~] 1.5-kb systems comprising a single transposase and a bridge RNA (bRNA). Using high-throughput junction mapping together with large-scale comparative genomics, we redefined the in vivo structural boundaries, growth, and mobilization of IS110 elements. We uncovered a previously unrecognized size continuum extending to[~] 100 kb, driven by progressive local expansion, with expanded loci being widespread across bacterial genomes. Experiments confirmed the activity of natural IS110s both well below and above the size range of previously characterized elements. These large systems preferentially accumulate adaptive cargo, including antimicrobial resistance determinants and heavy-metal detoxification systems, and are strongly enriched for plasmid-derived DNA. Boundary configurations at expanded loci and the range of partial excision intermediates they produce both indicate flexible sequence recognition by IS110, most commonly through half-matches between the bRNA and complementary DNA sequence. This sequence tolerance allows loci to expand with diverse cargo. Together, these findings redefine IS110 from a compact insertion sequence into a dynamic platform that disseminates adaptive cargo.

microbiology↗

bioRxiv2026

Mechano-Piezoelectric F-Peptide Hydrogels Enable In Situ Stem Cell and Immune Niche Modulation for Cartilage Regeneration

Osteoarthritis, characterized by cartilage degradation and synovial inflammation, has spurred interest in mechano-piezoelectric bio-hydrogel therapies that can both relieve symptoms and reverse progression. However, current approaches lack sufficient piezoelectric output and dual cartilage/inflammation targeting. To address this, we demonstrated a mechano-piezoelectric peptide hydrogel composed of nanofibers integrating piezoelectric cues with mesenchymal stromal cells (MSCs) recruitment and PIEZO2 mechanosignaling. Molecularly, the hydrogel's seed peptide incorporated four functions: COL2A1 targeting, MMP-13 responsiveness, MSCs homing, and self-assembly. Overexpressed MMP-13 in the osteoarthritis niche triggers gelation, promoting MSCs recruitment and drug retention. Fluorination modulates hierarchical nanofiber assembly, enhancing mechanical and piezoelectric properties, as confirmed by morphological, biophysical, and computational analysis. The trifluoromethyl-modified, 4-octyl itaconate (4-OI) loaded formulation reverses osteoarthritis via PI3K/AKT activation and Wnt/{beta}-catenin suppression, as shown by improved Osteoarthritis Research Society International (OARSI) scores, bone microarchitecture, and cartilage matrix. This synergy of mechano-piezoelectric cues and 4-OI offers a clinically promising strategy for osteoarthritis.

biophysics↗

bioRxiv2026

Benchmarking confidence estimation and rescoring for cyclic peptide-protein complex predictions

Cyclic peptides are a rapidly expanding class of therapeutics, but the reliability of deep-learning structure prediction for cyclic peptide-protein complexes has not been systematically evaluated. We assembled a curated benchmark of 111 nonredundant complexes spanning five cyclization chemistries and assessed two co-folding models, Boltz and Protenix, each generating 100 poses per target (22,200 total). Stratifying all poses by complex attributes, we found that disulfidecyclized peptides and small protein targets (200 or fewer target residues) were predicted significantly worse by both tools, with target size the largest and most consistent effect; overall accuracy nevertheless remained high (median top-pose DockQ of about 0.89, 96-98% of targets Acceptable or better), indicating that pose generation is rarely the bottleneck. Conversely, native model ranking scores correlated only moderately with pose quality (Spearman rank correlations of 0.53-0.66): approximately 12% of poses showed high model ranking score/confidence despite poor pose DockQ quality, and the highest-quality pose was not ranked first for nearly every target. We therefore augmented the native score with externally computed interface descriptors normalized by chain length, principally the per-residue density of inter-chain hydrogen bonds, in a gradient-boosted rescoring model evaluated under target-grouped cross-validation that prevents leakage, improving out-of-fold ROC-AUC for both tools, significantly so for Protenix. Together, these findings identify pose ranking, rather than pose generation, as the major limitation of current cyclic peptide-protein complex prediction and demonstrate that complementary structural features can improve confidence-based pose selection.

bioinformatics↗

bioRxiv2026

Comprehensive analysis of mulberry genetic diversity based on 1-DNJ content and SNP markers

Mulberry trees have high economic and ecological value, and a robust molecular marker system plus germplasm genetic diversity analysis is critical for innovative utilization of high-quality medicinal and economic mulberry germplasm. Here, 51 mulberry samples were used to develop SNP primers via genome resequencing, with the SNP-PCR system optimized by single-factor and orthogonal assays. The phenotypic diversity and SNP molecular marker genetic diversity of 1-deoxynojirimycin (1-DNJ) in mulberry leaves were analyzed respectively, and the genetic correlation between molecular markers and phenotypic traits was evaluated by Mantel test. Tested germplasm showed marked 1-DNJ variation (0.4805-2.5300 mg/g, CV=0.4241), reflecting rich genetic diversity. The optimal SNP-PCR system included Buffer (containing Mg{superscript 2}+) 2.2 L, 2.5 mM dNTP 0.4 L, forward and reverse primers (10 mol{middle dot}L-1) totaling 2.75 L, Taq DNA polymerase (5 U{middle dot}L-1) 0.3 L, DNA (50 ng{middle dot}L-1) 1.1 L, and ddH2O 13.65 L. 23 highly polymorphic ones amplified 91 loci (81 polymorphic, 89.10% polymorphism rate). Genetic diversity analysis showed that the average genetic distance was 0.3010, and the average expected heterozygosity (H) and Shannon information index (I) reached 0.4667 and 0.3104 respectively, indicating that the genetic differentiation among the tested mulberry germplasms was significant and the population had a moderate to upper level of genetic diversity. UPGMA clustering divided 51 germplasms into 6 major groups at a genetic similarity coefficient of about 0.7, while phenotypic clustering based on 1-DNJ content divided them into 2 major categories and 4 subcategories, with high 1-DNJ germplasm clustered independently. Mantel correlation analysis showed that 6 SNP sites were significantly weakly correlated with 1-DNJ content (r < 0.3, p < 0.05), and can be used as candidate molecular markers for subsequent genetic analysis of 1-DNJ content.This study established a stable mulberry SNP-PCR system, Analyze the molecular genetic characteristics of mulberry germplasm and DNJ phenotypic variation rules respectively, and provide basic data for cluster comparison. and provided a scientific basis for marker database improvement, germplasm identification and molecular-assisted breeding.

genetics↗

bioRxiv2026

Rapid and efficient generation of human 8-cell-like cells for embryo modelling

8-cell blastomeres of human embryos possess broad lineage potential and undergo major zygotic genome activation (ZGA), yet experimental access to this transient cell state remains limited. Rare 8-cell-like cells (8CLCs) arise spontaneously in naive pluripotent stem cell cultures, but their low abundance has constrained mechanistic and functional studies. Here, we develop a chemically defined strategy for rapid and robust induction of 8CLCs. Through sequential small-molecule screens focused on chromatin regulators, we identify five compounds acting through distinct pathways that generate up to 40% 8CLCs within 48 hours. The resulting cells, which we term rapidly induced 8CLCs (ri8CLCs), recapitulate key molecular features of 8-cell blastomeres, including induction of ZGA-associated genes, cleavage-stage transposable elements, and 8-cell-stage transcriptional signatures in bulk and single-cell transcriptomic analyses. Functionally, ri8CLCs exhibit enhanced developmental competence, acquiring the ability for spontaneous extraembryonic differentiation and assembly into well-cavitated blastoids on an accelerated 72-hour timeline. Notably, ri8CLC induction enables blastoid formation even in the absence of MEK inhibition, TGF-{beta}/Activin/Nodal inhibition and exogenous LIF, revealing a developmental competence consistent with an early embryonic state. Together, these findings establish a rapid, defined, and highly efficient platform for generating human ri8CLCs and provide a tractable model for studying early human embryogenesis.

developmental biology↗

bioRxiv2026

Optimized Multiple Circular Sequence Alignment for Cyclic Peptide Motif Discovery

Head-to-tail (H2T) cyclized peptides are an increasingly important modality in drug discovery, combining high target affinity and selectivity with metabolic sta-bility. Because their underlying chemistry is still that of a linear amino-acid chain, their linear sequence representation is the native input format of main- stream sequence generative models now driving de novo peptide design (Slough et al., 2018; Rettie et al., 2025a;b). Discovering the conserved motifs responsible for a family's function across a library of such candidates requires a multiple sequence alignment (MSA). Because a cyclic peptide can be linearised at any residue, the alignment must additionally solve for the unknown rotation of each sequence, which is the multiple circular sequence alignment (MCSA) problem. However, leading MCSA heuristics (e.g. Ayad & Pissis, 2017) were tuned for the genomic regime (a few tens of long sequences) and become prohibitively slow on the cyclic peptide library regime (hundreds to thousands of shorter sequences). We close this gap by identifying quality-preserving optimisation opportunities, notably the library-scale preset tailored to short-sequence inputs (algorithmic details in Appendix A), and by adding an orthogonal multi-core and SIMD backend for further performance tuning, which gives near-linear thread scaling on the pairwise-comparison stage. We validate the pipeline on a library of 1,000 H2T cyclized peptides of length 18 targeting the oncoprotein Mouse double minute 2 human homolog (MDM2) produced by an internal peptide-design engine. In this practical setup, the optimised MCSA recovers the underlying positional motif of MDM2 binders at the same fidelity as the original MCSA implementation while running over 650x faster. Our optimised MCSA tool thus enables library-scale cyclic peptide sequence alignment and is publicly available at https://github.com/IVB-Generative-Biology/mars-turbo.

bioinformatics↗

bioRxiv2026

OTTR-CLASH: improved biochemical and bioinformatic identification of Argonaute 2-mediated microRNA-target RNA interactions

Various methods have detected miRNA-target interactions via immunoprecipitation of UV-crosslinked Argonaute ribonucleoprotein complexes, followed by intermolecular ligation of bound miRNAs to target strands, forming chimeric RNAs. To date, these methods have relied on conventional viral reverse transcriptases (RTs) to generate cDNAs for sequencing. However, crosslinked RNAs often retain adducts after purification, which can make them poor templates for viral RTs. Here, we adapted OTTR (Ordered Two-Template Relay) techniques to generate cDNAs from Ago2-bound RNAs. OTTR makes use of a modified retroelement-encoded RT, which is strongly processive even on templates with modifications or adducts. We show that this "OTTR-CLASH" method increases the frequency of generating chimeric RNAs compared to previous methods. We also developed an improved bioinformatic pipeline for analysis of these data, and we use this to catalog miRNA-target interactions not previously described in the literature. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=147 HEIGHT=200 SRC="FIGDIR/small/738487v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@16d62f8org.highwire.dtl.DTLVardef@7c8da4org.highwire.dtl.DTLVardef@13727fborg.highwire.dtl.DTLVardef@21f443_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

A vascular chip for disease-relevant flow shear stress topology

Vascular chips have advanced endothelial mechanobiology by enabling controlled responses to hemodynamic cues, yet disease-relevant wall shear stress (WSS) modeling remains limited. Simplified one-dimensional flow shear systems, designed mainly for physiological mechanobiology, miss the topological organization of pathological flow, whereas patient-specific vascular models capture complex hemodynamics but sacrifice generality and imaging compatibility. Here we develop a programmable vascular chip that converts disease-associated WSS topology into a physiologically parameterized experimental input. The device reconstructs a representative pathological shear-topology field on endothelial layer, supports stationary and physiologically paced oscillatory flow modes, and integrates matched unidirectional-shear references within the same chip. Using this system, we show that oscillatory WSS topology destabilizes endothelial monolayers, drives asymmetric collective emergent behaviors, impairs actin-nuclear mechanotransduction, accompanied by nuclear softening and enhanced perinuclear nanoparticle uptake. Integrated live-cell imaging, fluorescence analysis, Brillouin microscopy, and transport assays enable multimodal phenotyping across collective, subcellular mechanical and functional scales. By making disease-relevant WSS topology experimentally controllable, this vascular-chip framework bridges computational hemodynamics and experimental mechanomedicine, supporting standardized vascular disease modeling and functional screening.

bioengineering↗

bioRxiv2026

Histone modifications analysis reveals enhancers reprogramming during maternal-to-zygotic transition

Enhancers are important epigenetic regulatory components that coordinate spatiotemporal gene expression and play a crucial role in mammalian development, gene regulation, and illness. During early mammalian embryogenesis, histone modifications including H3K4me1, a canonical enhancer mark, and H3K27ac, which identifies active enhancers, are still poorly understood. This study profiles the genome-wide H3K4me1 and H3K27ac patterns in mouse oocytes and pre-implantation embryos using low-input CUT&RUN (cleavage under targets and release using nuclease) with input as low as 50 cells. Both markers are enriched in distal regions and exhibit distinct sequence preferences and reprogramming dynamics in pre-implantation embryos. H3K27ac, a mark of active enhancers, is reprogrammed at the 2-cell stage, whereas H3K4me1 is remodeled at the 4-cell stage and overlaps with H3K27ac, coinciding with accessible chromatin regions. Interestingly, H3K4me1 and H3K27ac are co-localized in promoter regions, where they are mutually exclusive to H3K4me3. Enhancers are dynamically remodeled during maternal-to-zygotic transition (MZT). there are three enhancer types: active enhancers (H3K4me1/H3K27ac), primed enhancers (H3K4me1), and poised enhancers (H3K4me1/H3K27me3). Active enhancers increase significantly after zygotic genome activation. Further, super-enhancers are present across the genome and are mainly enriched in promoters. The specific motifs enriched by super-enhancers may be associated with the variations of gene expressions at different stages.

developmental biology↗

bioRxiv2026

Comprehensive characterization of V(D)J recombination from long-read transcriptomic data with VDJcraft

V(D)J recombination generates antigen receptor diversity in developing B and T cells. Long-read transcriptome technologies (e.g., PacBio Iso-Seq, Nanopore RNA/cDNA) capture full-length transcripts and thus resolve V(D)J events more accurately than short-read platforms. However, existing short-read tools are not applicable to or optimized for long-read data. We developed VDJcraft, the first integrated pipeline designed for V(D)J recombination analysis using long-read transcriptome sequencing data. The workflow uses a two-pass alignment strategy: global alignment to the GENCODE reference with minimap2, followed by local realignment and annotation using the international ImMunoGeneTics information system (IMGT). A customized module enhances D-gene detection sensitivity and positional precision. Sequencing errors are reduced through consensus-based correction toward the predominant subclass. Antigen-binding regions are annotated using IMGT-defined motifs to characterize CDRs and binding site composition. VDJcraft was validated on simulated and Human Genome Structural Variation Consortium (HGSVC) datasets and applied to disease datasets. It accurately recovered full-length V(D)J-C sequences and outperformed existing methods in gene detection and recombination accuracy. Long-read calls also showed significantly higher concordance with high-confidence short-read calls (Mann-Whitney U test, p = 1.55 x 10-4). Additionally, we identified 31 putative novel gene subclasses absent from the IMGT database from HGSVC datasets. Analyses of longitudinal blood samples from a COVID-19 patient revealed distinct V(D)J recombination patterns and segment enrichment, characterized by increased IGHV1-2 usage, enrichment of the IGHV3-7/IGHD6-9/IGHJ5_02 rearranged clonotype, and a transient peak in IgG2 levels at day 4 followed by a gradual return to baseline. In conclusion, VDJcraft provides a robust framework for long-read V(D)J characterization and enables the discovery of disease-associated immune signatures.

bioinformatics↗

bioRxiv2026

Engineering armoured in vivo CAR T cells through targeted delivery and transient mRNA gating

In vivo generation of chimeric antigen receptor (CAR) T cells offers an off-the-shelf, scalable alternative to ex-vivo therapies, but is constrained by inefficiency, toxicity and durability. We report the first armoured in-vivo CAR T platform with tunable, transient activity, that enhances safety and efficacy. Our platform utilises CD8 targeted lipid nanoparticles (LNP) to transiently deliver CAR and armouring membrane-bound IL12 mRNAs. Payloads utilize a T-cell-restricted (T-trex) strategy to constrain CAR and IL-12 expression to T cells, enabling potent antigen-dependent activity with spatio-temporal control. Selective targeting of T-cells with a T-trex CAR showed enhanced expression. The addition of T-trex IL12 mRNA provides a tunable, localised amplification of CAR function, enhancing antigen-dependent cytotoxicity and cytokine production with robust tumour control. These findings establish a novel dose-efficient armoured in-vivo CAR T approach and general framework for programmable immune cell engineering.

immunology↗