Biology subjects

Yang, W.

Publications and source records attributed to Yang, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Impact of aldehyde dehydrogenase 2 deficiency on tissue-specific mitochondrial metabolism in aging mice

Age-related diseases arise from prolonged exposure to genetic and/or environmental factors, ultimately leading to cumulative and irreversible degeneration of tissues and the organism as a whole. We previously reported that accumulation of mitochondrially-generated aldehydes (i.e., 4-hydroxynonenal and acetaldehyde) causes mitochondrial dysfunction and accelerates the progression of age-related diseases. However, the contribution of mitochondrial aldehyde metabolism to aging (via aldehyde dehydrogenase 2, ALDH2) remains elusive. Here, we provide a comprehensive analysis of aldehyde metabolism and mitochondrial bioenergetics across different tissues in aging mice. We also address how mitochondrial function is influenced by the highly prevalent human inactivating ALDH2 E504K point mutation (ALDH2E504K) during aging. The liver metabolism was relatively resilient to aging, showing enhanced ALDH2 activity and improved mitochondrial coupling. Strikingly, aging-associated liver resilience was lost in ALDH2E504K mice. Aged hearts exhibited mixed outcomes including impaired mitochondrial basal respiration, improved ADP-driven respiration, and decreased ALDH2 detox capacity. The ALDH2E504K mutation exacerbated the already impaired cardiac ALDH2 detox capacity in aging. Strikingly, aging brain displayed pronounced vulnerability, with decreased ALDH2 activity, impaired mitochondrial bioenergetics and defective ALDH2 detox capacity. These changes were paralleled by impaired cognitive and behavioral functions in aged mice. As proof of concept, either the presence of ALDH2E504K mutation or acute ethanol challenge worsened cognitive and behavioral dysfunction in aging mice. Finally, we assessed in vitro efficacy of pharmacological ALDH2 activation in aging tissues. Collectively, these findings unravel the contribution of ALDH2E504K mutation to mitochondrial metabolism during aging; highlighting the detrimental synergy between genetic ALDH2 deficiency and aging in brain metabolism and physiology.

molecular biology↗

bioRxiv2026

Effects of Phthalate Metabolite Mixture Exposure on Mouse Oocyte Development

Phthalates are pervasive endocrine-disrupting chemicals widely used in consumer products. The wide use of many phthalates results in chronic human exposure to complex mixtures rather than single compounds. Despite extensive studies on individual compounds, the combined effects of phthalate metabolites on oogenesis remain poorly understood. Here, we developed a precise microinjection-based single-oocyte toxicological assay to examine the impact of a defined phthalate metabolite mixture on meiotic progression. Phthalate mixture exposure markedly impaired oocyte maturation, as most oocytes failed to extrude the first polar body. Mechanistic analyses revealed severe meiotic defects, including disrupted spindle morphology, chromosome misalignment, disorganized actin cytoskeleton, and impaired mitochondrial function, accompanied by excessive reactive oxygen species (ROS) accumulation and DNA damage. Single-cell transcriptomic profiling further identified differentially expressed genes enriched in biological processes related to exocytosis, secretory pathway regulation, and cytoskeletal organization, as well as in MAPK, JAK-STAT, cGMP-PKG, and GnRH signaling pathways that are essential for follicular development and oocyte maturation. Together, these findings demonstrate that combined phthalate exposure directly compromises female gamete quality and underscore the importance of evaluating mixture effects when assessing risks to womens reproductive health.

cell biology↗

bioRxiv2026

Molecular Structure and DNA Binding Mode of Unsymmetric Cyanine Dyes RiboGreen and OliGreen

The binding of fluorescent dyes to nucleic acids and their fluorogenic properties are indispensable tools for nucleic acid detection, quantification, and imaging, yet the molecular structures of several widely used commercial dyes have remained unknown. Here, we de novo determined the molecular structures of RiboGreen and OliGreen and confirmed the previously proposed structure of PicoGreen using high-field NMR spectroscopy and ultra-high resolution mass spectrometry. All three dyes were identified as unsymmetric cyanine dyes, where benzazolium and 4-quinolinium moieties are linked by a monomethine bridge. Complete 1H and 13C resonance assignments enabled us to expand the existing chemical shift reference set for this important class of dyes. Photophysical characterization with standardized single- and double-stranded DNA and RNA targets indicated that all dyes performed similarly upon binding despite being marketed towards different nucleic acid types. NMR spectroscopy and long-timescale molecular dynamics simulations showed that RiboGreen interacts with double-stranded DNA predominantly by two binding modes, electrostatic interactions with the phosphodiester backbone and {pi}-{pi} stacking with accessible nucleobases of the DNA molecule. These results establish the molecular structures of three widely used commercial dyes and provide a structural and mechanistic framework for understanding the fluorogenic properties of this class of dyes. HighlightsO_LIDetermination of the molecular structures of nucleic acid dyes RiboGreen, OliGreen, and PicoGreen C_LIO_LINMR spectroscopic characterization of all three dyes. C_LIO_LINMR and MD data indicate binding to be dominated by electrostatic and {pi}-{pi} stacking interactions C_LI

molecular biology↗

bioRxiv2026

Reactivation of a TAL1 progenitor cell enhancer region by non-coding somatic variants in T-lineage acute lymphoblastic leukemia

Aberrant activation of TAL1, a key oncogenic driver, defines a major subgroup comprising [~]30% of childhood T-lineage acute lymphoblastic leukemias (T-ALLs). We and others have shown that somatic non-coding mutations within upstream and intronic cis-regulatory regions of TAL1 contribute to transformation by creating binding sites for MYB and other transcription factors. Here we investigated cis-regulatory mechanisms mediated by somatic mutations occurring in an intergenic region located 29 kilobase pairs downstream of the canonical TAL1 transcription initiation site, implicated in 6% of TAL1-expressing T-ALLs. These somatic variants include i) complex indels resulting in de novo MYB transcription factor binding sites (TFBSs) and ii) internal tandem duplications (ITDs) encompassing canonical MYB TFBSs. Chromatin immunoprecipitation sequencing (ChIP-seq) revealed binding of the TAL1 core regulatory circuit (CRC) transcription factors MYB, GATA3, and RUNX1, resulting in enhancer activity mediated by sequences with the mutant allele. Strikingly, ChIP-seq peaks for the repressive H3K27me3 mark and the active H3K27ac mark co-existed across TAL1 regulatory sequences but enriched for different haplotypes. TAL1 transcription from the mutant haplotype initiated from a promoter located within exon 4 of the canonical TAL1 transcript, resulting in a short isoform normally expressed by hematopoietic stem cells (HSC). Interestingly, neither the isoform expression nor the enhancer activity could be predicted by the sequence-to-function deep learning artificial intelligence (AI) model AlphaGenome, emphasizing the importance of experimental validation. Our findings indicate that selection for cis-regulatory, non-coding variants leads to reactivation of enhancers normally active in HSC but silenced in differentiated lineages during normal hematopoietic cell development.

cancer biology↗

bioRxiv2026

3D-PAULM: Integrated Photoacoustic Tomography and Ultrasound Localization Microscopy for Multiparametric Brain and Tumor Imaging

Understanding processes such as blood-brain barrier (BBB) disruption and tumor progression can greatly benefit from simultaneous molecular, functional, and hemodynamic imaging in deep tissue, yet few existing imaging modalities can provide all three in a single system. Here, we present an integrated imaging platform that combines 3D photoacoustic tomography with ultrasound localization microscopy (3D-PAULM) to enable intrinsically co-registered, multiparametric imaging. 3D-PAULM unifies multispectral photoacoustic molecular imaging, ultrasound B-mode imaging, microbubble-enhanced power Doppler, and ultrasound localization microscopy, and concurrently measures blood oxygenation, blood perfusion, microvascular flow dynamics, and molecular probes from near-infrared dyes and photoswitchable phytochromes. We apply 3D-PAULM to quantify BBB leakage in focal ischemia and systemic inflammation, and to perform high-sensitivity molecular imaging of solid tumors alongside functional mapping of tumor hypoxia and super-resolved vascular remodeling. Together, these results establish 3D-PAULM as a versatile platform for integrated functional and molecular imaging in deep tissue.

bioengineering↗

bioRxiv2026

An Essential Role of the AMPK-Related Kinase SNRK in Regulating Drosophila Sleep

Protein kinases are important regulators of sleep in animals, but their loss-of-function mutations usually show moderate phenotypes. We report here that sucrose non-fermenting related kinase (SNRK), a member of the AMP-activated protein kinase-related kinase (ARK) family, plays an essential role in sleep regulation: Snrk gene knockout resulted in a profound loss of night-time sleep phenotype, much stronger than that of the well-known ARK member Sik3. This phenotype was completely rescued by neuronal SNRK expression. SNRK in adulthood was required for sleep. Catalytic and regulatory sites in SNRK were important for sleep. A chemoconnectomic (CCT) screen revealed SNRK functioning in cholinergic neurons whose activation is known to inhibit sleep. Sleep loss in SNRK mutants was rescued by pharmacological blockade of nicotinic acetylcholine receptors. Our findings have uncovered a fundamental role for SNRK in cholinergic neurons to regulate sleep.

neuroscience↗

bioRxiv2026

ExMODE: A Multi-Omics Repository for Extremophile Adaptation and Bioprospecting

Extreme environments, though hostile to most life forms, host specialized extremophile communities that have redefined biological cognition and emerged as vital biotechnological resources, with their unique adaptive traits and bioactive molecules driving advances in multiple scientific and industrial fields. However, research on extremophiles is hindered by limitations in culture-based methods, fragmented multi-omics data with non-uniform annotation standards across repositories, the lack of cross-extreme comparative research in existing resources, and the singularity of data dimensionality that neglects key structural information, all of which restrict the functional interpretation of extremophile microbes and the exploitation of their bioprospecting potential. To tackle these challenges, we developed ExMODE (https://db.genomics.cn/exmode/), a comprehensive multi-omics database platform dedicated to extremophiles. It centrally integrates multi-omics data from diverse extreme habitats with a standardized annotation framework, resolving data fragmentation and enabling systematic cross-environment comparative analyses to elucidate extremophile adaptive mechanisms. Moreover, ExMODE aggregates multi-dimensional datasets including genes, genomes, secondary metabolite sequences and protein structures, overcoming the constraints of single-dimensional data and significantly improving the efficiency of biotechnological resource discovery from extreme microorganisms.

microbiology↗

bioRxiv2026

16S ribosomal RNA modification drives transcript-specific translation efficiency

Bacterial ribosomal RNAs (rRNAs) are decorated with conserved nucleotide modifications, but the functionality of these modifications is often underexplored. MraW (RsmH) is a 16S rRNA methyltransferase that fine-tunes ribosomal function. We identified a loss-of-function allele in mraW that corrected a late-stage sporulation defect in Bacillus subtilis by bypassing a key sporulation checkpoint via altered translational regulation. Purified ribosomes isolated from {Delta}mraW cells displayed a [~]2-fold decrease in translation efficiency; in vivo, {Delta}mraW cells produced decreased levels of the sporulation checkpoint protein CmpA. This regulation was mediated by sequences from the 5 untranslated region and the coding sequence of cmpA, which form a step-loop structure that occlude early codons of the mRNA. Proteomic analysis revealed that MraW directly or indirectly regulates the production of multiple proteins, some of which form similar structural elements as the cmpA transcript. We propose that MraW modification of 16S rRNA enhances translation efficiency in general, and that specific transcripts, whose gene products are likely required in limiting quantities, have evolved structural features that act as a regulatory mechanism to govern protein levels. This type of regulation may be most apparent in bacteria which exhibit uncoupled transcription and translation. HIGHLIGHTSO_LIA conserved 16S rRNA modification enhances translation of structured mRNAs C_LIO_LIEarly mRNA stem-loops impose translational control dependent on ribosome modification C_LIO_LImRNA structure and rRNA modifications likely co-evolved to fine-tune protein dosage C_LI

microbiology↗

bioRxiv2026

The compartmentalized activity of a legume subtilase SBT12a allows symbiosome stabilization

The stabilization of rhizobia in specialized organelles, called symbiosomes, is an evolutionary hallmark for maintaining high rates of nitrogen fixation in legumes. This is achieved by releasing thousands of bacteria from nodular infection threads within in a single plant cell, which poses a great challenge for the host to keep control over these differentiated bacteria. Considering the importance of proteolytic degradation of antimicrobial proteins or generation of symbiosis-promoting peptides, proteolytic activity may represent a key regulatory system. Indeed, we identified the Medicago truncatula subtilisin-like protease (subtilase, SBT) 12a acting as a novel regulator of symbiosome functionality and maintenance. Loss-of-function mutations in SBT12a led to severe symbiotic defects with nodules of sbt12a being characterized by high level induction of defense/senescence-related genes. Using untargeted proteomic High-efficiency Undecanal-based N-Termini EnRichment (HUNTER) we identified and individually confirmed specific SBT12a target proteins that are involved in plant defense responses and symbiosome maintenance. This positions SBT12a as a central host factor controlling symbiosome performance.

plant biology↗

bioRxiv2026

Dysregulation of Hippo Signaling Pathway as a Convergent Mechanism Underlying Choroid Plexus Defects in Bipolar Disorder

Bipolar disorder (BD) is a prevalent and highly heritable psychiatric condition. Developmental mechanisms are implicated but the specific molecular origins remain unclear. The choroid plexus (ChP), which regulates cerebrospinal fluid (CSF) and brain homeostasis, has been implicated in BD, but its role is poorly understood. Here, we identify aberrant expansion of ChP in human cortical (hCOs) and ChP organoids (hChPOs) derived from, and in vivo structural magnetic resonance imaging (sMRI) scans of, individuals with BD compared to healthy comparison individuals. Single-cell transcriptomics revealed a lineage bias toward ChP fate in BD hCOs, accompanied by structural enlargement observed in both BD hChPOs and ChP in sMRI scans from individuals with BD. Comprehensive transcriptomic profiling implicates early hyperactivation of the Hippo signaling pathway in neural progenitor cells as a convergent mechanism driving ChP overgrowth. Whole-genome and genome-wide association study analyses highlight recurrent genetic variants in Hippo regulators, including STK4 and YAP1, suggesting genetic priming. BD hChPOs exhibit disrupted epithelial junctions and altered in vitro CSF secretion. These findings position the ChP as a genetically and developmentally predisposed to pathology in BD and highlight organoids as a platform for translational discovery in diagnostics and therapeutics.

developmental biology↗

bioRxiv2026

Topological Entanglement in Intrinsically Disordered Proteins: Sequence, Structural, and Functional Determinants

Intrinsically disordered proteins (IDPs) populate heterogeneous conformational ensembles that are difficult to characterize using conventional structural descriptors. As a result, it remains unclear which ensemble features meaningfully connect sequence composition to biological function. Here, we employ entanglement-based measures derived from knot theory to provide complementary insight into IDP organization. Using the human IDRome database, we analyze two continuous entanglement descriptors, the writhe and the second Vassiliev invariant (V2), across more than 28,000 simulated disordered sequences. We show that these entanglement measures exhibit structured, low-dimensional variation across the database and display distinct relationships with sequence composition and ensemble geometry. Writhe primarily reflects compaction-dependent coiling tendencies that are largely recoverable from coarse sequence and structural features, whereas V2 captures higher-order topological organization that is less predictable from simple metrics. Embedding the resulting distribution features reveals functionally enriched regions of entanglement space, and ortholog simulations demonstrate that these signatures are evolutionarily conserved. Together, these results establish entanglement as a biologically relevant dimension of IDP organization and provide a rigorous, complementary framework for linking its sequence, ensemble structure, and molecular function.

biophysics↗

bioRxiv2026

Selective activation of IRE-1 safeguards restoration of translation and organismal rejuvenation from adult reproductive diapause

In C. elegans, prolonged food deprivation during early larval development results in aging-like phenotypes that can be fully reversed upon refeeding, but it remains unknown whether and how this ability persists into later life stages. Here we subjected C. elegans of the last larval stage to starvation, driving them into adult reproductive diapause (ARD). During starvation, ARD worms exhibited a wide spectrum of aging-like phenotypes, including transcriptomic reprogramming accompanying cellular and functional declines. These phenotypes are largely restored within one day of refeeding, suggesting a rejuvenation effect. Time-series transcriptomics, proteomics, and follow-up analyses of the refeeding/rejuvenation process uncovered an intricate coordination between: (1) activation of the IRE-1 branch of UPRER (unfolded protein response of endoplasmic reticulum) to induce chaperone expression; (2) quiescence of the PEK-1 branch of UPRER to avoid translation suppression; (3) up-regulation of the translation machinery to boost protein synthesis. IRE-1, together with its downstream effector, XBP-1, play an essential role in boosting protein synthesis, which is required for complete rejuvenation from the ARD state. These findings indicate that coordination between a high protein synthesis activity and a high protein folding capacity is key to refeeding-associated rejuvenation. HighlightsO_LIRefeeding rapidly reverses aging-like phenotypes in adult reproductive diapause C_LIO_LIRefeeding selectively activates the IRE-1 branch of UPRER C_LIO_LIRefeeding restores protein synthesis in an IRE-1 dependent manner C_LIO_LIRejuvenation requires enhanced translation activity and protein folding capacity C_LI

cell biology↗

bioRxiv2026

RNASTOP: A Deep Learning Framework for mRNA Chemical Stability Prediction and Optimization

Messenger RNA (mRNA) vaccines offer promising therapeutics for combating various diseases, yet their inherent chemical instability hampers their long-term efficacy. Although several methods have been developed to predict mRNA degradation, they exhibit limited accuracy and lack the capability for rational sequence optimization. Here, we propose RNASTOP, a novel framework integrating deep learning with heuristic search to simultaneously predict and optimize mRNA chemical stability. RNASTOP achieves a 13% accuracy improvement over the top-performing model on the Stanford OpenVaccine competition dataset and demonstrates robust generalization in predicting full-length mRNA degradation. Applied to mRNA codon optimization, RNASTOP reduces the minimum free energy of the Varicella-Zoster Virus vaccine sequence by 75.73% while maintaining high translation efficiency. Overall, RNASTOP serves as a powerful tool for predicting and optimizing mRNA chemical stability, poised to expedite the development of mRNA therapeutics. The source code of RNASTOP can be accessed at https://github.com/xlab-BioAI/RNASTOP.

bioinformatics↗

bioRxiv2026

A bivalent lysine-acetylated small-molecule binding site in MYC

MYC is an important, yet challenging target in oncology as it lacks traditional druggable pockets. Here, we show that two regions of MYC, the basic-helix-loop-helix (bHLH) domain, and extended MYC Box II (eMBII) come together to form a bivalent, high-affinity small-molecule MYC inhibitor (MYCi) binding site. CRISPR-tiling mutagenesis identified mutations in the vicinity of the eMBII and bHLH regions that together confer MYCi resistance. Importantly, acetylation of K148 in eMBII, which is essential for MYC oncogenicity in vivo, enhanced MYCi binding affinity and is predicted to increase the structural order of this region. Furthermore, MYCi selectively modulated the expression of the same genes regulated by lysine-acetylated MYC in cancer cells. These studies provide a rationale for selective targeting of acetylated, oncogenic MYC with small molecules.

cancer biology↗

bioRxiv2026

Transient signaling of free ADP-ribose monitored with an intracellular biosensor

We have developed a biosensor enabling the dynamic, compartmentalized, and longitudinal measurements of intracellular ADP-ribose (ADPR) in live cells. Free ADPR is a critical signaling metabolite derived from nicotinamide adenine dinucleotide (NAD+). As an agonist for Transient Receptor Potential Melastatin 2 (TRPM2), ADPR levels can regulate immune responses during infection, as well as nociception and adjustment of core body temperature. The study of ADPR signaling has been limited, however, by a lack of methods to measure this metabolite in situ. Using the biosensor and its paired non-responsive control, we determine that intracellular ADPR accumulation was transient and tunable. We found that basal concentrations were in the nanomolar range and could be stimulated [~]30-fold to activate TRPM2. We identified that TRPM2 activation, measured by calcium influx, required an intracellular ADPR threshold concentration between 2 - 4 {micro}M at physiological temperature. We observed that the timing of the ADPR rise coincided with TRPM2 activation, thus providing support for ADPR fluctuations being a critically regulated aspect for channel activation. Notably, transient fluctuations of ADPR were not accurately reflected by measurements of intracellular NAD+ loss or calcium levels. Significance StatementWe have developed a unique real-time biosensor for free ADP-ribose that is tuned to physiological concentrations and capable of intracellular measurements in individual cells. Using a calibrated system we determined that concentrations and timing of induced intracellular ADPR aligned with the thermosensitive TRPM2 activity. The data support ADPR as a critical component whose intracellular levels are regulated to control TRPM2 channel opening in cells.

biochemistry↗

bioRxiv2026

Resolving Conformational Heterogeneity in IntrinsicallyDisordered Proteins via Experimentally Guided Multi-Replica Simulations

The conformational landscapes of intrinsically disordered proteins (IDPs) remain obscured by the ensemble averaging inherent to experimental observables. Here, we present Multi-replica Averaged Restraint Simulation (MARS), a data-driven modeling framework that reconstructs these landscapes by enforcing ensemble-averaged restraints across multiple replicas without imposing prior structural knowledge. Using the N-terminal domain of estrogen receptor alpha (ER-NTD) as a model system, MARS simultaneously integrates small-angle X-ray scattering (SAXS) and six paramagnetic relaxation enhancement (PRE) profiles, comprising over 600 pairwise restraints, to generate ensembles that quantitatively fit all input structural restraints. The resulting ensemble is consistent with independent backbone relaxation measurements and reveals two major conformational states: a dominant extended state and a low-populated yet functionally relevant compact state whose structural features align with prior mutagenesis studies. Systematic benchmarking demonstrates that SAXS and PRE provide orthogonal global and local constraints, that each PRE profile contributes non-redundant structural information, and that multi-replica sampling is essential for preserving conformational heterogeneity. MARS offers a scalable framework for integrating orthogonal biophysical measurements to resolve both dominant and rare functional states in IDPs.

biophysics↗

bioRxiv2026

A human-in-the-loop explanation framework for morphologically transparent AI predictions from whole-slide images

Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as "black boxes", lacking transparency about whether and which histomorphological patterns drive their predictions, hindering interpretability and clinical adoption. Here we propose a human-in-the-loop explanation framework, MorphoXAI, which provides both local and global interpretability for deep learning models by incorporating human-expert interpretations. At the global level, it reveals the histomorphological patterns on which the model consistently relies to distinguish between classes of WSIs, as well as the patterns associated with confusion between classes. At the local level, it indicates which of these patterns are used in the prediction of an individual WSI and which regions within the slide correspond to such patterns. We validated our method on a deep learning model trained for ovarian tumor histologic subtype prediction. The results show that our framework generates explanations that accurately reflect the histomorphology underlying the models predictions at both global and local levels. For interpretability and clinical utility in diagnostic contexts, human evaluation results showed that our explanations were easy to interpret, rich in diagnostic features, and directly helpful for diagnostic decision-making, thereby enhancing pathologist-AI collaboration. Our work highlights that unifying global and local explanations and grounding them in expert-interpreted morphology enhances the interpretability and verifiability of deep learning models, thereby facilitating the transparent deployment of such models in clinical practice.

pathology↗

bioRxiv2026

AMPBAN: A Deep Learning Framework Integrating Protein Sequence and Structural Features for Antimicrobial Peptide Prediction

The escalating crisis of antimicrobial resistance poses a devastating and immediate threat to human life. Antimicrobial peptides (AMPs) are a promising antibiotic substitute to combat antimicrobial resistance. Compared with the traditional wet-lab screening approaches, computational models have largely improved the efficiency of predicting antimicrobial peptide. However, most computational models overlook or underutilize the evolution and structural information of peptides, which is crucial for understanding the peptide functions. Here, we proposed a sophisticated deep learning model to predict AMPs, Antimicrobial Peptide Bilinear Attention Network (AMPBAN), which incorporates peptide evolution features from ESM3 protein language model, structure features from ESMFold predicted with equivariant graph neural network (EGNN), and the joint information from sequence and structure learned via Bilinear Attention Network. AMPBAN consistently demonstrated superior accuracy and generalization compared to nine state-of-the-art AMP prediction models across multiple independent benchmarks. Furthermore, an ablation study confirms that our multimodal fusion strategy significantly refines the integration of sequence and structural signals, yielding superior predictive balance over single-modality models. This framework provides a robust tool for the accelerated discovery of novel AMPs and the advancement of next-generation antimicrobial drug development. The datasets, source code and models are available at https://github.com/baiwenhuim/ampban.

bioinformatics↗