Biology subjects

Liu, P.

Publications and source records attributed to Liu, P..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Mapping Tumor-Microenvironment dependencies with TMEformer: A spatial foundation framework enabling in silico perturbation

Despite the fundamental role of spatial context in driving tumor progression, most current computational models for virtual perturbation have largely overlooked its importance. Here, we introduce TMEformer, a tumor microenvironment-aware deep learning framework that leverages high-resolution spatial transcriptomics to jointly model intrinsic tumor cell programs and local microenvironmental signals by explicitly incorporating spatial architecture. Validated across diverse tumor spatial transcriptomic cohorts, TMEformer enables virtual perturbations that capture functional dependencies within local cellular ecosystems. Despite being trained on cancer-specific spatial datasets, TMEformer outperforms baseline models pretrained on large-scale corpora in capturing key tumor transitions, including lineage plasticity and the emergence of therapy resistance. Systematic perturbation analyses prioritize tumor-intrinsic transcription factors and TME-derived ligands that drive disease progression, recovering established regulators and revealing novel candidates. Furthermore, TME- derived embeddings improve the spatial stratification of tumor cells and align more closely with pathological architecture. Together, TMEformer establishes a general framework for modeling tumors as spatially coupled, perturbable ecosystems. An online TMEformer web platform for perturbation prediction, analysis, and visualization is available at http://www.pradcellatlas.com.

bioinformatics↗

bioRxiv2026

NuGraph: Graph-Based Reasoning over 3D Primitives for Nucleus Segmentation Correction

Correcting segmentation errors in large-scale 3D nuclei reconstructions requires reasoning about which fragments belong to the same nucleus across densely packed regions. Existing correction methods rely on local pairwise fragment matching, which cannot resolve the global topology of nuclear clusters and fails to recover missing morphology. We propose NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW, a graph-based reasoning framework that operates over atomic 3D primitives obtained by decomposing erroneous masks. NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW encodes primitive geometry via a 3D point-cloud backbone and performs global relational reasoning through graph attention, capturing inter-primitive dependencies across entire clusters rather than isolated pairs. A primitive-proposal contrastive loss aligns local primitive features with nucleuslevel semantics, improving grouping accuracy in dense regions. The resulting proposals are then refined by a shaperefinement network that predicts signed distance fields to restore smooth morphology. To train without manual error annotations, we develop a self-supervised data engine that synthesizes realistic segmentation errors from clean nuclei labels. To benchmark correction at brain scale, we curate NucEMFix, the first brain-wide EM benchmark of nuclei error cases across FAFB and MICrONS (8,000+ annotated error nuclei). NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW attains 87.99% F1 on NucEMFix-F (FAFB) and 86.20% on NucEMFix-M (MICrONS), outperforming both re-segmentation baselines (e.g., +8.6% over nnU-Net) and pairwise correction methods, while reducing curation effort by over 100x relative to manual proofreading. Code and data are available at https://mingzhiwang618.github.io/NucEMFix.

neuroscience↗

bioRxiv2026

Structure and inhibition of the sperm TMEM95-FIMP complex in mammalian fertilization

TMEM95 is a sperm acrosomal membrane protein essential for mammalian fertilization. How TMEM95 facilitates sperm-egg interaction has largely remained unknown. Analogous sperm fertilization proteins function as complexes, leading us to hypothesize that TMEM95 may have a binding partner on sperm. Here, we surveyed interactions between TMEM95 and individual proteins in a curated library of testis-expressed proteins using AlphaFold3. We identify FIMP, a fertilization-essential acrosomal membrane protein, as a high-confidence interaction partner of TMEM95. These two proteins form a high-affinity complex through their ectodomains. Using single-particle cryo-EM, we determine the structure of the human TMEM95-FIMP ectodomain complex at high resolution. An aromatic motif of FIMP binds to a conserved surface of TMEM95, and amino acid substitutions within this motif ablate the TMEM95-binding activity of FIMP. We isolate an anti-TMEM95 antibody, termed 3A02, that binds to human and murine TMEM95 and disrupts the interaction between TMEM95 and FIMP. By determining the cryo-EM structure of human TMEM95 bound to the 3A02 fragment antigen-binding region, we find that 3A02 recognizes the FIMP-binding site on TMEM95. 3A02 inhibits fusion of murine sperm with eggs, independent of antibody size, suggesting that the TMEM95-FIMP interface is critical for sperm-egg interaction. Together, these results establish the human sperm TMEM95-FIMP complex and suggest that a FIMP-mediated interaction of TMEM95 facilitates membrane fusion during mammalian fertilization.

biochemistry↗

bioRxiv2026

MSAgent: An Evidence Grounded Agentic Framework for LLM-driven Scientific Exploration in Mass Spectrometry-based Metabolomics

Mass spectrometry (MS) is a cornerstone high-throughput technology for molecular discovery, yet the reliable elucidation of chemical structures remains a formidable, expert-dependent bottleneck. Currently, achieving a reliable molecular identification from raw mass spectra necessitates a manual assembly--a labor-intensive ordeal of heuristic reasoning and the tedious integration of siloed computational tools, perpetuating a profound throughput gap between rapid data acquisition and the glacial pace of structural annotation. Here we present MSAgent, an autonomous agentic framework that bridges the gap between computational automation and expert intuition by emulating the cognitive logic of human specialists. By orchestrating a MSToolbox of over 50 domain-specific tools via Large Language Models (LLMs), MSAgent dynamically unifies the analytical pipeline into a scalable, evidence-grounded workflow, allowing for intent-aware planning, cross-resources outputs synthesis, and visual mechanistic interpretation within traceable reasoning chains and evidence-backed analytical reports. We evaluated MSAgent across multiple open benchmarks, including the established community challenges - Critical Assessment of Small Molecule Identification (CASMI) 2016/2022, CANOPUS, and LLM-oriented test cases. On CASMI, MSAgent consistently boosts retrieval performance by over 10% MRR across diverse benchmarks while ensuring high reliability--improving or preserving ranks in 95% of cases. For more challenging molecular de novo tasks on CANOPUS, MSAgent builds upon the outputs of baseline models with consistent refinement, yielding over a 40% average gain in Tanimoto similarity for ground-truth recovery. In addition, MSAgent demonstrates remarkable advantages in eliminating the hallucination phenomenon over LLMs without domain tool support, producing better-calibrated confidence (Pearson r = 0.438 vs -0.219 for gpt-4o). It improves exact-match rate by 38.8% over gpt-4o in candidate discrimination tasks, and achieved a 64% success rate in recommending high-quality candidate structures with Tanimoto similarity more than 0.7, where gpt-4o predominantly selected candidates with similarity below 0.3. Our work enables high-throughput mass spectrometry data to be analyzed in an intent-driven and automated manner, lowering the analysis barrier for no-expert to deliver molecular identification result with transparent analytical process, and accelerating discovery in metabolism and related fields by bridging the gap between experimental data acquisition and computational interpretation.

bioinformatics↗

bioRxiv2026

N-3 Polyunsaturated Fatty Acids Ameliorate Post-infarction Cardiac Dysfunction Through Modulation Of Adiponectin-Ceramide Metabolism

BackgroundIt has been shown that n-3 polyunsaturated fatty acids (n-3 PUFA) of marine origin exert significant beneficial effects on myocardial infarction (MI); however, the underlying mechanisms remained unclear. Ceramides play a vital role in the regulation of energy metabolism, mitochondrial function, and apoptosis. Through the integration of clincial studies and animal experiments, this study aimed to determine whether n-3 PUFA improved myocardial function by modulating ceramide metabolism. MethodsIn a case-control study, 100 patients with AMI and 100 healthy pariticipants were enrolled to measure serum ceramide concentrations. Meanwhile, mice were randomly allocated into 4 groups and administrated to a 3-week intervention with n-3 PUFA in triglyceride and phospholipid forms. A mouse model of MI was then established, followed by an additional 4 weeks of continuous intervention. Subsequent comprehensive assessments of cardiac function were performed in the mice. Finally, the mice were euthanized to conduct targeted ceramide lipidomic analysis and other relevant assays. ResultsThe levels of serum C16:0-, C18:0-, C20:0-, C24:1-ceramides and total ceramides in patients with acute myocardial infarction (AMI) were significantly higher compared with the healthy controls. In the murine model of myocardial infarction, pathological analysis via TTC staining demonstrated that interventions with fish oil (triglyceride form) and krill oil (phospholipid form) both significantly reduced myocardial infarct size. Concomitant echocardiographic assessment confirmed that both treatments markedly elevated left ventricular ejection fraction (LVEF), with the magnitude of improvement being significantly superior to that of the model control group. Concurrently, compared with the model group, the concentrations of ceramides in cardiac tissue and serum were significantly lower in the groups with fish oil and krill oil intervention. Western blot analysis further confirmed that n-3 PUFA intervention upregulated adiponectin expression, reduced ceramide accumulation in myocardial tissue, and inhibited mitochondria-mediated cardiomyocyte apoptosis, thereby improving cardiac function and prognosis following myocardial infarction. ConclusionsThis work demonstrates that n-3 PUFA exert cardioprotective effects following MI mediated by adiponectin-ceramide axis. However, there is no significant difference regarding therapeutic efficacy of n-3 PUFA in triglyceride or phospholipid forms.

pharmacology and toxicology↗

bioRxiv2026

TFBindFormer:A Cross-Attention Transformer for Transcription Factor--DNA Binding Prediction

Transcription factors (TFs) are central regulators of gene expression, and their selective recognition of genomic DNA underlies various biological processes. Experimental profiling of TF-DNA interactions using chromatin immunoprecipitation followed by sequencing (ChIP-seq) provides high-resolution maps of in vivo TF-DNA binding but remains costly, labor-intensive, and inherently low-throughput, limiting their scalability across different transcription factors, cell types, and regulatory conditions. Computational modeling therefore plays an essential role in inferring TF-DNA interactions at genome scale. However, most existing computational models rely solely on DNA sequence and chromatin features to predict TF-DNA binding, neglecting TF-specific protein information. This omission limits their ability to capture protein-dependent binding specificity. Here, we present TFBindFormer, a hybrid cross-attention transformer that explicitly integrates genomic DNA features with TF-specific representations derived from protein sequences and structures. By modeling protein-conditioned, position-specific TF-DNA interactions, TFBindFormer enables direct learning of molecular determinants underlying DNA recognition. Evaluated across hundreds of cell-type-specific TFs and hundreds of millions of genome-wide DNA bins, TFBindFormer consistently outperforms DNA-only baselines, achieving substantial gains in both area under precision-recall curve (AUPRC) and area under receiver operating characteristic curve (AUROC). Together, these results demonstrate that integrating TF and DNA features via cross-attention enables TFBindFormer to serve as an effective and scalable framework for large-scale TF-DNA binding prediction.

bioinformatics↗

bioRxiv2026

Visual Emotion Perception in a Deep Neural Network Model with Both Bottom-Up and Top-Down Connections

Emotion reshapes perception by modulating sensory processing through top-down feedback--a process referred to as emotional perception. The computational mechanisms by which distinct affective signals influence visual representations however remain poorly understood. Here, we use a deep neural network to simulate this process and test mechanistic hypotheses about how top-down feedback guides emotional peception. Most existing models treat the perception of emotional content as a static, feedforward task, overlooking the dynamic interplay between internal states, external goals, and sensory input that characterizes affective perception in the brain. We introduce EmoFB, a biologically inspired model that integrates an affective system with a visual processing hierarchy through two functionally distinct feedback signals: intrinsic feedback, arising from the models own affective appraisal of perceptual input, and external steering, conveying contextual priors such as task expectations or target categories. We evaluated EmoFB on three tasks varying in perceptual ambiguity (Single Image, Side-by-Side, and Overlay). External steering exerted the strongest influence, not only improving recognition under challenging conditions but also restructuring internal representations by sharpening category-specific clustering in feature space. Crucially, top-down feedback increased brain-model representational similarity, strengthening alignment with human fMRI responses across early visual cortex, ventral visual areas, and the amygdala. EmoFB provides a computational framework for testing neurocognitive theories of emotion appraisal and top-down feedback modulation. It bridges affective neuroscience and artificial intelligence, offering mechanistic insight into how emotional signals shape perception in both brains and machines.

neuroscience↗

bioRxiv2026

NucleoNet and DropNet: Generalist deep learning models for instance segmentation of nuclei and lipid droplets from electron microscopy images

Automating cellular organelle segmentation is key to increasing the throughput in electron microscopy (EM) and volume EM (vEM) workflows. Deep learning (DL) has accelerated this process, but model development has predominately centered on mitochondria, partly because of a scarcity of suitable training datasets for other features. Here, we crowdsourced the manual step of labeling nuclei and lipid droplets (LDs) from complex cellular EM images and trained Panoptic DeepLab (PDL) models on these large, heterogenous annotated datasets as well as on publicly available vEM datasets. NucleoNet and DropNet, the resulting instance segmentation models for nuclei and LDs, respectively, yield high-quality results on varied benchmarks. We applied these models to quantify differences between 2D and 3D in vitro cancer models versus in vivo tumors, highlighting a path toward robust quantitation in EM. NucleoNet and DropNet are publicly available on our napari plugin, empanada v1.2, for easy point-and-click segmentation of 2D and 3D cellular EM images.

cell biology↗

bioRxiv2026

A lateral linker histone binding mode scaffolds dinucleosome stacking in chromatin fibers

Linker histones are essential for chromatin compaction, yet how they contribute to higher-order fiber assembly remains poorly understood. Here, we determined cryo-electron microscopy structures of Arabidopsis dodeca-nucleosome fibers containing distinct H2A/H3 variants and linker histone H1.3, revealing a noncanonical binding mode that a laterally positioned H1.3 connects the acidic patch of one nucleosome and the DNA of the neighboring nucleosome, thereby scaffolding dinucleosomes into two-start chromatin fibers. This noncanonical binding mode is structurally conserved when H1.3 is replaced by Gallus gallus H5. Furthermore, incorporation of H2A.W and H3.3 further induces back-to-back fiber dimerization. Cryo-electron tomography and in vivo cross-linking mass spectrometry analyses support the physiological relevance of H1 lateral engagement. Our findings establish that linker histones act as active architectural scaffolds in higher-order chromatin organization.

molecular biology↗

bioRxiv2026

A feed-forward loop between niche adenosine and Gzmk⁺ CD8 T cells propagates systemic inflammaging

The causal link between the aging microenvironment and T cell aging remains elusive. Here, we demonstrate that adenosine within aging tissues actively reprograms CD8+ T cells into a pro-aging Granzyme K+ (Gzmk+) population. Mechanistically, senescent cells create an adenosine-rich niche via p16-dependent CD39 upregulation, triggering A2aR signaling to induce Gzmk+ T cell differentiation. Once released, Gzmk promotes systemic inflammaging through PAR1 and complement activation. Crucially, targeting this axis--either via genetic Gzmk ablation or pharmacological A2aR blockade--reverses multi-organ aging phenotypes and significantly extends healthy lifespan in mice. Human analysis reveals age-dependent Gzmk+ T cell accumulation in multi organs, while coffee intake (an A2aR antagonist) inversely correlates with plasma Gzmk levels. Our findings uncover how metabolic niche changes drive T cell aging and establish the adenosine-Gzmk axis as a pivotal therapeutic target for combating age-related diseases.

immunology↗

bioRxiv2026

Bioabsorbable Magnesium Metal ScaffoldsImprove Dermal Wound Healing and Tissue Regeneration

ObjectiveEvaluate the effects of bioabsorbable magnesium wires on dermal wound healing and tissue regeneration in a murine full-thickness wound model. Approach6 mm diameter stented dorsal skin wounds were created in C57BL/6J mice and treated with implanted WE43B magnesium alloy wires or PBS control. Wound healing was evaluated on days 7 and 28 by histology, immunohistochemistry, and micro-CT. Finite element analysis modeled mechanical strain distribution due to wire degradation during healing. ResultsAt day 7, magnesium wire-treated wounds showed 100% improved granulation tissue formation, reduced inflammation (37% fewer CD45+ leukocytes and 37% fewer F4/80+ macrophages), increased neovascularization (91% more CD31+ lumens), and 74% more nerve bundles. Improved wound closure (mean difference -1.48 mm) did not reach statistical significance (d = 1.06). By day 28, magnesium-treated wounds showed improved collagen organization and normalized epidermal thickness. The increase in dermal appendages (247%), and vascular density (41%) did not reach statistical significance. Micro-CT confirmed progressive wire degradation. Modeling revealed that degrading wires dynamically altered strain gradients in healing tissue, thereby modulating the spatial mechanical cues that govern fibroblast migration and extracellular matrix (ECM) remodeling. InnovationMagnesium is an essential trace element involved in cellular processes critical to wound repair, including angiogenesis, nerve growth, inflammation modulation, and ECM remodeling. Previous magnesium delivery systems incorporated polymers or other confounding materials that degrade rapidly. We directly applied bioabsorbable pure magnesium metal to provide sustained ion release and favorable mechanical properties to support regenerative healing. ConclusionBioabsorbable magnesium wires support regenerative wound healing by reducing inflammation, enhancing neovascularization, and promoting favorable ECM remodeling without adverse inflammatory reactions. These findings provide a strong rationale to harness magnesium metal use in wound healing applications.

bioengineering↗

bioRxiv2026

Exploring differences across pangenome-graph representations using Escherichia coli O157:H7 as a model

Pangenome graphs are increasingly used to represent population-scale bacterial diversity, yet construction methods span fundamentally different representation paradigms whose outputs and sensitivities to assembly quality remain poorly quantified. We systematically reviewed microbial pangenome graph tools and benchmarked six representative methods spanning gene-cluster, compacted coloured de Bruijn graph (ccDBG), multiple sequence alignment, and hybrid approaches. Using a repeat-rich Escherichia coli O157:H7 dataset with complete genomes and matched short-read data, we constructed graphs from identical inputs and observed orders-of-magnitude differences in graph size and fragmentation, indicating that global topology is driven by representation strategy. Varying completeness composition revealed that assembly fragmentation is a first-order determinant of graph structure: gene-cluster graphs contracted as draft assemblies replaced complete genomes, whereas unitig graphs expanded, with distinct degree-prevalence fingerprints across tools. Computational cost mirrored these shifts and depended strongly on completeness composition, including a pronounced runtime penalty for one ccDBG implementation on all-draft inputs. Finally, analysis of Shiga toxin loci showed that pangenome-level reconciliation does not reliably correct assembly artefacts at challenging multi-copy genes and that performance varies by locus. Together, these findings show that pangenome graphs are representation-dependent models of bacterial diversity, and that assembly completeness is a primary determinant of their topology, scalability, and locus-level accuracy. Authors SummaryBacterial populations are often described using "pangenome graphs," which aim to capture all genetic variation across many genomes in a single structure. However, different tools build these graphs in fundamentally different ways, and little is known about how those differences affect the results. In this study, we systematically compared several widely used approaches using a clinically important strain of Escherichia coli that is rich in repeated and mobile DNA. We found that the size, connectivity, and overall structure of the resulting graphs varied dramatically depending on the method used. Importantly, we also show that incomplete genome assemblies (common in large sequencing studies) strongly alter graph structure, and that different tools respond to incomplete data in different ways. In some cases, this affects the detection of medically relevant genes, including Shiga toxin genes linked to severe disease. Our results demonstrate that pangenome graphs are not interchangeable representations of bacterial diversity. Instead, their structure depends on both the method and the quality of the input data. We argue that researchers should choose graph-building tools carefully and report structural properties explicitly to ensure reproducible and interpretable results.

bioinformatics↗

bioRxiv2026

Potent and Selective IL-4 Inhibitors with Anti-Tumor Activity

Interleukin-4 (IL-4) is an important immunoregulatory cytokine involved in T-cell maturation, B-cell activation, and macrophage polarization. Dysregulated IL-4 signaling contributes to several immune-mediated diseases such as cancer, allergic inflammation, and autoimmunity. The clinical use and indication expansion of the anti-IL-4R antibody dupilumab has made IL-4 signaling an attractive target for therapeutic modulation. We previously discovered a first-in-class small molecule inhibitor to the soluble cytokine IL-4, which we named Nico-52, that inhibits the soluble IL-4 cytokine with single-digit micromolar potency. Here, we determined structure-activity relationships around the Nico-52 scaffold that impact potency and selectivity and evaluated the in vivo anti-tumor potential of small molecule IL-4 inhibition. Improved analogs featured structural changes to the p-fluorophenyl group ranging from submicromolar to double-digit nanomolar potency. Our two most potent analogs showed selective binding to IL-4 over other related cytokines in thermal shift assays and more potent inhibition of IL-4 over IL-13 in a HEK Blue IL-4/IL-13 reporter assay. We further established that our lead analogs inhibit both type I and type II IL-4 receptor signaling. Nico-52 and an optimized lead analog exhibited favorable in vitro ADME/T properties, such as high stability and low cytotoxicity. Furthermore, Nico-52 and a lead analog were investigated for their tumor suppressive effects in syngeneic murine tumor models, where small-molecule IL-4 inhibition yielded significant tumor inhibition, shifted macrophage polarization, and our optimized lead analog improved animal survival. These studies show the promise of small-molecule cytokine inhibitors for IL-4 mediated processes of disease.

cancer biology↗

bioRxiv2026

YY1-Mediated Polycomb Group Function Safeguards Hematopoietic Stem Cells from Premature Aging

Hematopoietic stem cells (HSCs) undergo functional decline with age, characterized by myeloid-biased differentiation, loss of quiescence, and altered metabolic homeostasis. The molecular mechanisms driving these changes remain incompletely understood. Yin Yang 1 (YY1) is a multifunctional transcription factor and mammalian Polycomb group (PcG) protein that recruits PcG complexes to specific genomic loci via its 26-amino acid REPO (Recruitment of Polycomb) domain. To define the role of YY1 PcG function in adult HSCs, we generated a conditional YY1 REPO domain knockout mouse model (Yy1-/{Delta}REPO). Deletion of the REPO domain led to premature HSC aging, with expansion of immunophenotypic HSCs but loss of long-term self-renewal capacity. Yy1-/{Delta}REPO HSCs exhibited myeloid-biased output, expansion of myeloid-primed multipotent progenitors, increased myeloid colony formation, and an elevated myeloid-to-lymphoid ratio in peripheral blood. These cells displayed reduced quiescence, elevated reactive oxygen species, increased mitochondrial oxidative capacity, and enhanced {beta}-galactosidase activity--hallmarks of cellular aging. RNA-seq demonstrated dysregulation of gene networks governing HSC metabolism. Together, these findings establish YY1 PcG activity as a key epigenetic mechanism that preserves metabolic quiescence, sustains long-term self-renewal, and delays HSC aging. Our studies reveal a fundamental PcG-dependent epigenetic mechanism that dictate cell fate decisions and function decline during HSC aging.

molecular biology↗

bioRxiv2026

The endoderm cell trajectory of urochordate Styela clava reveals the dual developmental origin and evolution of digestive tract

The digestive system exhibits extensive diversity in developmental mechanisms and morphology across metazoans, yet the evolutionary origins underlying its organ differentiation remain unclear. Here, single-cell RNA sequencing was employed to investigate endodermal cell lineage specification during metamorphosis in the urochordate Styela clava, a newly established model for chordate evolution. By profiling 26,099 cells across five stages, we identified 21 major cell clusters and reconstructed the endodermal differentiation trajectories. Our analysis reveals two larval endodermal progenitor populations with distinct differentiation potentials. Pseudotime and RNA velocity analyses indicate that these progenitors give rise to stomach and intestinal lineages, respectively. Cross-species comparisons reveal putative homologous relationships between ascidian endodermal lineages and mouse definitive and visceral endodermal lineages, suggesting dual origins of digestive tract in chordates. We also identified conserved TGF-{beta} and FGF regulatory programs in digestive organ patterning and highlight earlier fate restriction of stomach and intestinal progenitors in ascidians compared to vertebrates. These findings provide insights into how chordate digestive organs evolved from ancestral endodermal patterning programs.

evolutionary biology↗

bioRxiv2026

Engaging Unstabilized Alkyl Radicals with Pyridoxal Radical Biocatalysis: Enantiodivergent Synthesis of Aliphatic Non-Canonical Amino Acids

Harnessing transient, unstabilized alkyl radical intermediates for the enantioselective construction of valueadded chemical entities remains a fundamental challenge in biocatalysis. Through the repurposing and directed evolution of pyridoxal phosphate (PLP)-dependent tryptophan synthases, we advanced an open-shell enzyme platform capable of intercepting transient alkyl radicals for the efficient and enantioselective synthesis of aliphatic non-canonical amino acids. Engineering an orthogonal pair of radical PLP enzymes allowed unstabilized alkyl radicals, generated from diverse aliphatic organoboronates, to undergo dehydroxylative C(sp3)-C(sp3) coupling with a common L-serine donor, affording either L- or D-amino acids with excellent enantiopurity in an enzyme-controlled fashion. Mechanistic and computational investigations employing radical clock substrates and unusual radical-mediated rearrangement processes revealed that the radical intermediates generated in this system exhibit unexpectedly long lifetimes, highlighting the power of this dual enzyme-photocatalyst platform to engage unactivated alkyl radicals. Collectively, these findings delineate a potentially general strategy for generating and utilizing unstabilized alkyl radicals and underscore the synthetic potential of radical pyridoxal biocatalysts for stereodivergent amino acid construction.

biochemistry↗

bioRxiv2026

Joint Segmental Duplication Co-option Drives Human-specific Transcriptional Readthrough and Expression Fine-tuning of NPEPPS-TBC1D3

Segmental duplication (SD) is a major driver of functional changes in evolution and disease. Many genes embedded within SDs, such as NPEPPS and TBC1D3, display substantial copy number variation (CNV) across individuals. Yet, the precise identification of the functional copies and their transcriptional outputs remains largely unstudied. Focusing on NPEPPS and TBC1D3, we illustrate human-specific expression fine-tuning mechanisms associated with readthrough transcripts. We identified a human-specific NPEPPS-TBC1D3 digenic genomic structure that originated from a joint SD pair and became fixed across populations. Experiments demonstrate that this structure generates NPEPPS-TBC1D3 readthrough transcripts, which are the predominant isoforms of TBC1D3 expression in various cell types, fine-tuning its protein level. Furthermore, a human-specific hypomethylation signal within an upstream CpG island of NPEPPS precisely pinpoints the expressed TBC1D3 paralog. Moreover, we reveal transcriptional readthrough events are [~]3-fold enriched for joint-SD-associated transcriptional readthrough (JSDTR) and identify 109 JSDTR gene pairs, including neurodevelopmentally important pairs and clinically interesting SERF1A/B-SMN1/2. Taken together, our findings comprehensively describe an example of how a joint SD event shaped evolution and suggest that JSDTR is a broad mechanism for the emergence of new functions.

genetics↗

bioRxiv2026

Effects of atmospheric CO2 levels on the susceptibility of maize to diverse pathogens

Rising atmospheric CO2 has profound implications for crop productivity and food security. Based on studies in C3 plants, elevated CO2 (eCO2) can shape plant-pathogen interactions, although the outcomes are often variable. The question of how eCO2 influences immunity and disease development in C4 plants, such as the globally important cereal crop maize (Zea mays L.), has not been systematically examined. We challenged maize plants grown under ambient CO2 (aCO2, 420 ppm) and eCO2 (550 ppm) with bacterial, viral, fungal, and oomycete pathogens. Plants grown in eCO2 were more susceptible to sugarcane mosaic virus, suggesting compromised antiviral defenses, less susceptible to Clavibacter nebraskensis, Exserohilum turcicum, and Colletotrichum graminicola, and susceptibility to Puccinia sorghi and Pythium sylvaticum was unchanged. Reduced susceptibility to C. nebraskensis was associated with enhanced basal immune responses. These results establish a foundation for dissecting eCO2-responsive defense mechanisms, and they highlight a critical need to understand how eCO2 will impact plant responses to microbes, pests, and abiotic stresses under future conditions.

plant biology↗