Biology subjects

Lin, X.

Publications and source records attributed to Lin, X..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Depression symptoms are associated with affective neural processing during sleep and rest

Sleep supports offline information processing and is essential for cognitive and emotional functioning. Abnormal sleep patterns are a hallmark of affective disorders. We hypothesized that affective symptoms occur with maladaptive neural processing during offline periods. To test this idea, we used multivariate EEG decoding with cross-state classification. A model trained on EEG data acquired while participants (N = 52) viewed emotional images was used to classify stimulus valence. Applying this model to data collected during a nap revealed the re-emergence of affective neural patterns. Critically, offline reinstatement of patterns reflecting negatively valenced processing predicted greater depressive symptoms across participants. These associations reflected both cognitive-affective and somatic-performance depression subscales, and they generalized across sleep stages and wakeful rest. The finding that offline neural information processing is linked with emotional well-being supports a model whereby maladaptive negative biases can be perpetuated during rest, potentially shaping the progression of affective disorders.

neuroscience↗

bioRxiv2026

The structure and catalytic mechanism of new cellular and viral HDV ribozymes

We have determined the molecular structure and investigated the catalytic mechanism of two new ribozymes of the Hepatitis delta virus family, found in the nematode Caenorhabditis briggsae and virus Ackermannviridae. Crystal structures of both conform to the double-pseudoknot architecture adopted by the viral HDV ribozyme. The C. briggsae ribozyme has been determined both pre- and post-cleavage. In the former both nucleotides flanking the scissile phosphate are observed, along with a metal ion, and cytosine 75 N3 bound to the O5 leaving group. The pH dependence of cleavage rate reveals a pKa of 6.6 and together with the inactivity of a C75U mutant provides evidence for its role as general acid. In contrast to other nucleolytic ribozymes that use catalytic metal ions, reaction rate does not depend on the pKa of the divalent metal ion. Limited adjustment of structure of the active center is consistent with direct bonding of the metal ion to the O2 and non-bridging O, suggesting that the ion acts as a Lewis acid to activate nucleophilic attack. This mechanism appears to be general for the HDV ribozyme class, and distinguishes it from the majority of nucleolytic ribozymes that use general base catalysis.

biochemistry↗

bioRxiv2026

A T-cell engager platform induces deep plasma cell depletion in autoimmune dry eye

Bispecific T cell engagers (TCEs) have transformed targeted immunotherapy but remain constrained by ex vivo manufacturing and systemic delivery, limiting their application in autoimmune disorders. Here, we introduce the first in vivo TCE platform, utilizing a T cell-targeted integration-deficient lentiviral vector (T-IDLE) to reprogram endogenous T cells into engineered T cells secreting BCMAxCD3 TCEs (STCEs) directly in vivo. In murine Sjogrens syndrome-associated dry eye model, a single intravenous administration of T-IDLESTCE achieved deep and sustained depletion of plasmablasts and plasma cells, reversing lacrimal gland inflammation and restoring tear production without detectable off-target transduction. Longitudinal studies in cynomolgus monkeys confirmed translational promise, demonstrating potent plasma cell clearance and favorable safety profiles over 12 weeks post-vector dosing. Mechanistic analyses demonstrated attenuation of Th1/Th17-mediated inflammation and controlled cytokine responses, accompanied by negligible vector integration in non-T cell lineages, thereby substantiating the safety profile of the integration-deficient design. This first-in-class in vivo TCE approach represents a manufacturing-free, scalable immunotherapy strategy for autoantibody-mediated diseases.

bioengineering↗

bioRxiv2026

A Functional Genetic Atlas of Parkin Resolves Variants of Uncertain Significance and Predicts Parkinson's Disease Age at Onset

Autosomal recessive mutations in the Parkin gene (PRKN) cause early-onset Parkinsons disease (PD). Parkin functions as a ubiquitin E3 ligase acting downstream of the PINK1 kinase to promote phosphorylated ubiquitin at sites of mitochondrial damage. Yet the functional effects of most PRKN gene variants remain unknown. Here we use a pooled cellular assay measuring phosphorylated ubiquitin accumulation to quantify the activity of [~]9,200 PRKN missense and nonsense variants. Our screen identifies thousands of loss- and gain-of-function variants, including activating variants mainly residing at autoinhibitory interfaces. Functional scores accurately distinguish known PD pathogenic and benign variants, and enable reclassification of 173/184 variants of uncertain significance (VUS). When combined into biallelic genotype scores, these data predict the age at disease onset in patients, revealing a quantitative link between Parkin activity and clinical manifestation. Our results provide a comprehensive functional genetic map of Parkin and demonstrate the power of multiplexed assays of variant effects (MAVEs) for variant interpretation and precision medicine in PD.

genetics↗

bioRxiv2026

A biophysical framework for accurately identifying antigen single-amino acid escape variants and corresponding variant-specific compensatory TCR sequences

The impact of single amino acid substitution on T-cell receptor (TCR) recognition is central to understanding the molecular determinants of TCR specificity and degeneracy during viral mutational escape, cancer recognition, and autoimmunity. In this study, we developed a biophysics-informed computational approach integrating experimental alanine-scan mutagenesis data from the autoimmune-associated ALWGPDPAAA peptide bound to HLA-A*02:01 together with coarse-grained structural modeling. Our approach reconstructs the energetics and structural determinants underpinning the observed loss of recognition by the diabetogenic 1E6 TCR upon single-point mutations, specifically at the critical Pro5 and Asp6 residues. Leveraging the computational models ability to incorporate multiple structural templates into binding predictions, this approach quantitatively reproduces experimentally measured affinity disruptions. Additionally, we apply our approach to identify potential compensatory interactions capable of restoring binding affinity through alternative residue interactions. This integrative computational framework contributes a strategy for inferring TCR-peptide binding energetics at the single amino acid level, guiding the rational design of peptide-based immunotherapeutics, and predicting the functional impacts of clinically relevant peptide variants.

biophysics↗

bioRxiv2026

Endothelial MRG15 Is a Mechanosensitive Suppressor of Atherosclerosis

Disturbed blood flow induces early endothelial inflammation in atherosclerosis, yet the precise mechanisms of endothelial sensing of disturbed flow remain incompletely understood. In this study, we integrated proteomic profiling of human endothelial cells (ECs) subjected to disturbed flow with coronary artery disease risk related genes from large-scale genome-wide association studies (GWAS). We identified mortality factor 4-like protein 1 (MORF4L1, also called MRG15) as a critical modulator in the pathogenesis of atherosclerosis induced by disturbed flow. We show that the expression of MRG15 is markedly reduced in ECs of human aortic atherosclerotic plaques, as well as in ECs exposed to disturbed flow in mouse carotid artery and in cultured human umbilical vein endothelial cells (HUVECs). Endothelial-specific deletion of Mrg15 significantly worsened, while its overexpression attenuated endothelial inflammation and atherosclerotic lesions in turbulent blood flow- or Western diet-induced mouse atherosclerosis model. Single-cell transcriptomics showed that Mrg15 deficiency increased endothelial inflammation and intercellular adhesion molecule 1 (Icam1) expression, and enhanced integrin-mediated adhesion pathways. Mechanistically, MRG15 facilitated the recruitment of enhancer of zeste homolog 2 (EZH2) to maintain repressive histone H3 lysine 27 trimethylation (H3K27me3) marks on the promoters of ICAM1 and integrin subunit alpha 5 (ITGA5). Disturbed blood flow rapidly led to an elevation of protein neddylation, which subsequently induced neddylation-dependent degradation of MRG15 within endothelial cells. This degradation of MRG15 alleviated the transcriptional repression of ICAM1 and ITGA5, thereby enhancing monocyte adhesion to ECs. These findings highlight endothelial MRG15 as a mechanosensitive suppressor of atherosclerosis induced by disturbed flow. Consequently, MRG15 emerges as a promising novel therapeutic target for atherosclerosis.

molecular biology↗

bioRxiv2026

Single-cell transcriptomic landscapes reveal cell-type-specific regulatory mechanisms of nutrient accumulation and transport in wheat grain

To elucidate the transcriptional regulatory mechanisms underlying wheat grain development, we constructed single-cell transcriptomic atlases of wheat grains at 4 and 8 days after pollination (DAP) using single-nucleus RNA sequencing. A total of 58,546 high-quality nuclei were clustered into 16 distinct cell populations representing all major seed tissues, including the embryo, aleurone layer, transfer cells, endosperm, inner pericarp, seed coat, and embryo surrounding region. Comparative analysis revealed a dynamic transcriptional reprogramming from growth-related pathways at DAP 4 to nutrient accumulation at DAP 8, which coincided with shifts in the expression of hormone signaling and organ development genes, as well as starch and storage protein genes. Pseudotime trajectory analysis identified two major differentiation branches, highlighting distinct roles in nutrient storage and support. Notably, the transcription factor TaMADS58 was found to regulate pericarp cell number while simultaneously enhancing protein content and processing quality. Concurrently, TaJEKLL, specifically expressed in nucellar projection cells, was demonstrated to influence nucellar projection development and nutrient transport. Natural variation in TaMADS58 and TaJEKLL revealed their potential to decouple yield from quality traits, offering promising applications for crop improvement. Collectively, this study provides a high-resolution single-cell resource for wheat seed biology and demonstrates that investigating gene expression with spatiotemporal precision at the single-cell level can facilitate the discovery of key genes for precisely regulating individual traits.

plant biology↗

bioRxiv2025

mRNA transcription in skeletal muscle drives growth and determines nuclear accretion

Multinucleation of skeletal muscle cells (myofibers) is a determinant of size and fundamental for function. While it is established that myofibers need to accrue adequate numbers of nuclei for optimal growth, the molecular circuitry linking myonuclei to growth and why myofibers need additional nuclei remains unknown. We found that growth is still possible after restriction of nuclear content in myofibers and this was associated with increased levels of RNA Polymerase II (Polr2a) leading to elevated mRNA content. Through development of a genetic mouse model where endogenous Polr2a is upregulated in myofibers, we established that increased transcriptional output is sufficient to drive functional growth of myofibers. Notably, we discovered that Polr2a overexpression curtails the need for additional nuclei for myofiber growth. These data reveal a previously neglected driver of functional muscle growth and highlight that increasing Polr2a-mediated transcription from the vast numbers of nuclei within myofibers could be leveraged to combat muscle wasting conditions.

cell biology↗

bioRxiv2025

Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI

The prioritization of highly-variable genes is an important step in single-cell trajectory inference. However, when variability arises from a continuous latent cell development trajectory, standard methods may fail to differentiate trajectory-relevant from uninformative genes. SEEK-VFI is an ensemble topic-modeling machine learning algorithm for trajectory inference preprocessing that prioritizes trajectory-relevant genes. It outperforms existing methods, and identifies key genes that improve trajectory topology reconstruction, enhance visualization, and augment downstream trajectory analyses.

bioinformatics↗

bioRxiv2025

SEEK-VEC: Robust Latent Structure Discovery via Ensemble Topic Modeling

Count data are ubiquitous across many applications in which understanding latent patterns is of interest. Topic modeling is a powerful tool for detecting latent structure in count data. However, standard topic modeling methods are often constrained by their restrictive assumptions, susceptible to noise, and sensitive to misspecification of the number of topics. Here, we introduce SEEK-VEC (Spectral Ensembling of topic models with Eigenscore for K-agnostic Vocabulary Embedding and Classification), an ensemble topic modeling framework that integrates insights from multiple candidate topic models through a spectral ensembling procedure. SEEK-VEC produces a meta-structure matrix containing prioritization scores and grouping scores that enable variable classification, interactive pattern discovery, and model diagnostics. Through simulations, we demonstrate that SEEK-VEC augments the performance of standard topic models for identifying important vocabulary words and understanding the relationships among them, particularly when signal strength is weak. We apply SEEK-VEC to the MADStat dataset of statistical abstracts and demonstrate its utility for evaluating the proposed interpretation of a topic model.

bioinformatics↗

bioRxiv2025

Efficient RNA Folding Simulation via a Structure-Based Single-Site-Per-Nucleotide Model

Computational modeling of large RNA structures and their dynamics is essential for uncovering the molecular mechanisms underlying various genomic processes and RNA-regulated cellular functions. Residue-resolution modeling is an effective approach for simulating large biomolecular structures while preserving essential sequence and struc-tural features presented in atomic structures. Here, we implemented a structure-based single-site-per-nucleotide (SSPN) RNA model using the GPU-accelerated OpenMM 1 software and evaluated its computational efficiency and accuracy by simulating RNA hairpins unfolding under force. Our simulations compare favorably with an earlier, more detailed RNA model and quantitatively reproduce experimentally measured ther-modynamic properties of RNA under mechanical stretching. This SSPN model enables scalable and accurate simulations of large RNA ensembles, such as long non-coding RNAs and RNA liquid-liquid phase separation.

biophysics↗

bioRxiv2025

A Site-Specific Organometallic Approach for Installing Tyrosine Phosphorylation Mimics to Decipher the Role of Phosphorylation in Alpha-Synuclein (aSyn) Aggregation and Seeding

Several studies have identified phosphorylation of alpha-synuclein (aSyn) at multiple tyrosine residues (Y39, Y125, Y133, and Y136) within Lewy bodies, which are the pathological hallmarks of Parkinsons disease (PD). However, understanding the specific role of phosphorylation at each site, or how multiple phosphorylation sites interact, has been challenging. Herein, we present an efficient method that leverages an organometallic Pd-complex to site-specifically attach phosphomimetic groups via Cys-arylation, closely mimicking natural phosphorylation. Using this approach, we successfully incorporated native-like tyrosine phosphorylation mimics into cysteine-containing proteins like synthetic transcription factor Max and recombinant aSyn, in good yields. To demonstrate the methods versatility, we created a focused library of mono-, di-, and tri-phosphorylated aSyn analogues. This development enabled, for the first time, the investigation of the effect of site-specific phosphorylation at multiple C-terminal tyrosine residues on aSyn fibrillization and aggregation. Our results show that mono-phosphorylation at any of the C-terminal sites has little effect on aggregation, while di- and tri-phosphorylation slows down the process, extending the lag phase compared to wild-type aSyn. Additionally, phosphorylation at Y39 reduces the seeding activity of aSyn fibrils by almost threefold in both mammalian and neuronal models of synuclein pathology. Overall, our strategy provides a rapid, selective, and scalable way to introduce aromatic PTMs, producing homogeneous protein libraries essential for mechanistic studies, biomarker development, and exploring the therapeutic potential of targeting aSyn-phosphorylation for PD and related disorders.

biochemistry↗

bioRxiv2025

Dynamic alterations of DNA methylation and transcriptome in adaptation to and recovery from the space environment

Space exploration presents tremendous health challenges. Here, we report time series of multi-omic and phenotypic profiles of seventeen astronauts from six China Manned Space missions with continuous spaceflight durations ranging from 13 to 180 days. We revealed a key role of DNA methylation regulation in reshaping gene expression patterns to adapt to the space environment. Long-duration spaceflight showed more alterations in epigenetic modifications correlated with alternative splicing and protein acetylation. During recovery, an "overrange rebound" phenomenon was observed, furthermore, a mathematical model was established to describe this implying important phenomenon. Moreover, we revealed the correlations between molecular alterations and phenotypic changes such as coagulation activation and bone intensity loss. Additionally, we performed ground-based simulation experiments to estimate the impacts of individual stressors in the space environment on DNA methylation. In summary, our study highlights the importance and complexity of epigenetic regulation in adaptation to and recovery from the space environment.

genomics↗

bioRxiv2025

AI-based Predictive Signaling Pathway Profiling in Cardiac Fibrosis Suggests a Novel Combinatorial Treatment Strategy

BackgroundCardiovascular disease (CVD) remains the leading cause of global mortality, with myocardial fibrosis characterized by excessive extracellular matrix (ECM) deposition representing a common endpoint associated with progressive cardiac dysfunction. While studies in animal models of heart disease suggest that preventing or reducing fibrosis can antagonize negative ventricular remodeling, current therapeutic strategies remain clinically limited and ineffective, in part due to an incomplete understanding of the multifactorial nature of the fibrotic process. Methods and ResultsWe employed artificial intelligence (AI) trained from 6,528 cardiac fibrosis publications over the past decade, which suggested 10 nodal signaling pathways underlying the fibrotic process. Single-cell RNA sequencing was used to quantify pathway activities across mouse models and clinical samples encompassing acute and chronic cardiac injury. Dynamic enrichment analysis revealed 2 critical pathways involved in acute myocardial infarction (MI) injury driven temporally-regulated fibrosis whereby Janus kinase - Signal transducer and activator of transcription (JAK-STAT) signaling peaked early (day 7) while transforming growth factor-{beta} (TGF-{beta}) pathway activity peaked mid-phase (day 14). With more chronically-driven fibrosis, JAK-STAT signaling again emerged, which this time was persistently active during chronic transverse aortic constriction (TAC) injury. Experimentally, single-cell analysis identified a pathogenic myofibroblast subpopulation characterized by high JAK-STAT signaling and ECM secretion capacity. Fibroblast-specific Jak1/2 gene-deleted mice significantly reduced TAC-induced fibrosis by blocking myofibroblast formation from this subpopulation, although these same mice failed to show attenuated fibrosis following MI injury, suggesting a pathway that would be ideal to therapeutically target for chronic fibrosis without affecting necessary acute scar formation. Indeed, based on the predictive AI driven algorithm, a temporal inhibitory strategy was generated for JAK-STAT and TGF-{beta} that permitted compensatory scar formation while more effectively preventing progressive fibrosis and worsened cardiac function versus either singular pathway or chronic antagonism. ConclusionHere we employed the wealth of past signaling pathway data underlying cardiac fibrosis to train an AI model, which suggested an optimized approach of inhibiting 2 nodal signaling pathways but with differential timing as a more effective therapeutic strategy that reduces pathologic cardiac fibrosis without negatively impacting compensatory fibrotic activity with acute MI injury. The therapeutic approach involves altering the timing of JAK-STAT signaling blockade with ruxolitinib (RUX) in combination with delayed and temporary TGF-{beta} signaling inhibition post MI injury with pirfenidone (PFD).

cell biology↗

bioRxiv2025

Fungal Mst3-proteins are involved in fungal innate immunity needed for the recognition of bacteria surrounding the hyphae, as well as for plant pathogenicity

Fungal innate immunity overall responses are as fast as and resemble mammalian innate immunity. It does not, however, employ membrane toll-like receptors (TLRs), but should employ endocytosis of non-fungal molecular patterns recognized by nuclear-localizing receptors (NLR). Downstream, both types of receptors in mammals are Mammalian Ste20 kinases (MSTs). We identified single MST3 orthologs in the plant pathogens Fusarium graminearum (FgMST3) and Magnaporthe oryzae (MoMST3). We knocked out both genes and investigated mutants using a standard panel of tests for growth, development, and pathogenicity for each respective fungus. Both{Delta} FgMST3 and{Delta} MoMST3 strains showed reduced pathogenicity. The deletions negatively affected conidia production and conidia germination but had little effect on growth rate. However, the two mutants reacted differently to some stress treatments, such as Zn2+ and gentamicin. Furthermore, we constructed an innate immunity reporter system for F. graminearum based on a gene with fast responses to bacterial MAMPs to detect less than 4-hour responses to non-self-molecular patterns (NSMP) like bacterial outer membrane vesicles (OMVs) as well as trace levels of sucrose, as a plant NSMP. The reporter gene responses to OMVs of MST3 mutant strains were severely reduced. Our results suggest that both MoMst3 and FgMst3 are involved in fungal innate immunity downstream of unknown NLR proteins, motivating studies to try to identify genes for the NLR-like receptors. Finding such and investigating how they work and vary between fungal species and strains should be useful for understanding fungal biotic interactions with viruses, bacteria, plants, and animals.

immunology↗

bioRxiv2025

Cryptococcus neoformans adapts to host CO2 concentrations through the coordinated remodeling of central carbon metabolism, oxidative stress resistance, and membrane homeostasis.

Cryptococcus neoformans is an environmental pathogen that remodels its cellular physiology to survive within mammals and, in susceptible hosts, cause life-threatening meningoencephalitis. Of the many distinctions between the external environment and mammalian tissues, CO2 concentration in the host is 2 orders of magnitude higher than in the environment and represent a critical stress for C. neoformans. C. neoformans strains that do not replicate at host CO2 concentrations are less virulent in mouse models of infection, further supporting CO2 tolerance as a virulence trait. To further understand the genetic determinants of C. neoformans CO2 tolerance, we performed a near genome-wide screen for deletion mutants with altered CO2 fitness using a competitive growth assay. A total of 301 of 4698 deletion mutants showed altered CO2 tolerance (245 reduced fitness; 51 increased fitness) demonstrating the global effect of host CO2 on C. neoformans physiology. Based on this data set as well as a metabolomic analysis of C. neoformans adaptation to host CO2, we show that remodeling of central carbon metabolism, oxidative stress buffering and membrane homeostasis represent an integrated response to CO2 stress that is mediated in part by the TOR-Ypk1 signaling axis. We propose that CO2-induced capsule formation leads to reduced cellular glucose which, in turn, triggers remodeling of central carbon metabolism toward utilization of alternative carbon sources and increased mitochondrial respiration/reactive oxygen generation. Thus, these data provide a near genome-wide profile of the genetic determinants of C. neoformans CO2 tolerance as well as a model for how this important environmental human fungal pathogen alters its physiology to proliferate in the host.

microbiology↗

bioRxiv2025

Adaptive Partial Conjunction Hypothesis: Identifying Pleiotropy Across Heterogeneous Effect Units

Pleiotropy arises when a single SNP, gene, or locus affects multiple traits, and in many applications the key scientific question is which specific subset of traits shares a non-null effect. We introduce the Adaptive Partial Conjunction Hypothesis (APCH), an empirical Bayes framework that uses summary statistics to test, for each effect unit, which subsets of features are jointly non-null while controlling the false discovery rate for subset selection. APCH combines adaptive shrinkage priors with a hierarchical model that accounts for correlation among effect estimates and computes local false discovery rates for all candidate subsets. A top-down search over subset size then selects at most one maximally informative jointly significant subset per effect unit. In simulations, APCH maintained well-calibrated FDR and, in most settings, achieved higher power than both empirical Bayes methods that learn across effects and subset-based procedures that test each effect unit separately. It remained reliable with heterogeneous effect sizes, correlated estimation errors across features, and sparse jointly significant patterns. We apply APCH to GWAS summary statistics for five type 2 diabetes-related traits and identify co-occurring trait subsets that go beyond what single-trait genome-wide scans reveal. In particular, APCH brings in traits that fall short of genome-wide significance on their own but repeatedly appear in the same jointly significant subsets, revealing stable cross-trait co-association patterns and sharpening our overall picture of how loci act across these traits. More broadly, APCH is directly applicable to other multi-feature settings, such as multi-tissue or multi-omic association analyses, using only summary statistics.

genetics↗

bioRxiv2025

Ferrapoptosis: Discovery of a Hybrid Programmed Cell Death

Traditional taxonomies classify ferroptosis and apoptosis as distinct forms of regulated cell death. Here, we challenge this view by defining and validating a previously unrecognized neuronal death entity in traumatic brain injury (TBI), which we term "Ferrapoptosis". This hybrid mode of death is characterized by the coexistence of ferroptotic and apoptotic molecular and ultrastructural features within the same neuron-- ultrastructural alterations that cannot be fully characterized by any known cell death modalities. By integrating single-cell transcriptomics with multi-layered functional assays, we show that Ferrapoptosis dominates in severe injury and the acute phase, and is critically driven by mitochondrial oxidative stress. Over time, its predominance is gradually replaced by death modes in which either ferroptosis or apoptosis alone becomes the major pathway. Genome-wide CRISPR screening further identifies Smg7 as a key regulator that synchronously activates both death programs to drive the hybrid phenotype, whereas genetic or viral inhibition of Smg7 reduces Ferrapoptosis and promotes neurological recovery after TBI in mice. Our work systematically delineates a previously unrecognized form of cell death and its pathogenetic mechanisms, providing experimental evidence to refine cell death classification, and suggesting a conceptual strategy for treating complex diseases such as TBI by targeting shared regulatory nodes. HIGHLIGHTSO_LIDefined and validated a previously unrecognized cell death modality, termed "Ferrapoptosis". C_LIO_LIElucidated the ordered pattern of Ferrapoptosis across key stages of TBI pathogenesis. C_LIO_LIRevealed mitochondrial oxidative stress as the pivotal hub integrating ferroptosis and apoptosis. C_LIO_LIIdentify Smg7 as a core driver of Ferrapoptosis and a promising neuroprotective target. C_LI

cell biology↗