Biology subjects

Lei, Q.

Publications and source records attributed to Lei, Q..

14 recordsLinked to original sources

bioRxiv2026

OmniTCR: a foundation model unifying T cell receptor recognition prediction and conditional sequence generation

T cell receptor (TCR) recognition prediction and receptor generation are traditionally modelled separately, leaving vast TCR sequence collections disconnected from smaller TCR-peptide-MHC datasets. Here we present OmniTCR, a 113-million-parameter autoregressive foundation model pretrained on 328 million formatted human immune-sequence records. Sequence-type tokens and complementary component orders enable joint learning from individual TCR chains and partial or complete TCR-pMHC associations. On unseen epitopes, OmniTCR achieved AUPRCs of 0.7009 for peptide-TCR{beta}; recognition and 0.8235 for TCR-pMHC interaction prediction, exceeding the strongest evaluated comparators by 0.3396 and 0.3451, respectively. It distinguishes cancer from healthy repertoires across 11 independent pan-cancer cohorts (mean AUROC, 0.9436). The model achieved the highest sequence recovery on internal and external generation benchmarks. Structural modelling supported the plausibility of selected pMHC-conditioned CDR3{beta}; candidates. OmniTCR bridges heterogeneous immune sequence data, providing a foundation for computational immunology and receptor design.

bioinformatics↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Predicting TCR-pMHC Binding by Reinforcement Learning

The binding between T cell receptors (TCRs) and peptide-major histocompat-ibility complexes (pMHCs) is fundamental to the immune systems ability to recognize and eliminate pathogens. Accurate prediction of TCR-pMHC inter-actions holds significant promise for advancing cancer immunotherapy, vaccine design, and autoimmune disease research. However, existing approaches often treat the sequences, structures, and functions of TCRs, peptides, and MHC molecules in isolation, neglecting their interdependencies and hence limiting the prediction accuracy. In this study, we present ProTCR, a novel approach that integrates sequence, structural, and functional information within a reinforce-ment learning framework, offering a new paradigm for predicting TCR-pMHC binding. The reinforcement learning optimization enables ProTCR to generate TCR-pMHC sequences with enhanced binding propensity, thereby improving prediction accuracy. On benchmark datasets such as IEDB and VDJdb, ProTCR achieves an AUROC of 0.75, outperforming state-of-the-art methods by 32.7%, while offering interpretable insights into the structural and sequence determi-nants of binding. We further validate ProTCR using TCRs and neoantigens derived from a cervical cancer patient via proteogenomic profiling. Our analysis reveals a strong correlation between T cell clonal expansion and ProTCR-predicted TCR-peptide binding scores, supporting the biological relevance of the model. Additionally, ProTCR demonstrates robust performance in predict-ing SARS-CoV-2 TCR-pMHC complexes and generating MHC-specific peptides with potential applications in peptide-based immunotherapies. Collectively, these findings establish ProTCR as a powerful and interpretable tool for TCR-pMHC binding prediction, with broad utility across immunology research and translational applications.

bioinformatics↗

bioRxiv2025

Sialoglycans on human T cells attenuate death programs executed through the Fas pathway

T cells are critical executors of adaptive immune responses and their persistence is tightly regulated. Part of this regulation relies on programmed cell death driven by the Tumor Necrosis Factor (TNF) receptor superfamily. The addition of glycans that terminate in the monosaccharide sialic acid (sialoglycans) to these cell death receptors has been shown to attenuate their apoptotic functions. While this is now understood to be a pro-survival mechanism in settings of cancer pathophysiology, the specific roles of sialoglycans in regulating cell death receptor activity on human T cells remains unexplored. This is of particular importance given the rising interest in T cell glycan editing for therapeutic benefit. Here, we address this gap using both immortalized (Jurkat) and primary human T cells deficient in sialoglycans. We found that T cell sialoglycans suppressed apoptosis induced by the Fas receptor (FasR) but not other TNF receptor superfamily members such as TNFR1 and TRAIL-R1. Dynamic reorganization of FasR was increased on sialoglycan-deficient Jurkat cells, suggesting that these glycans limit receptor clustering. This model was further supported by phosphoproteomics results, which confirmed that loss of sialoglycans negatively regulated the pro-survival MAPK/ERK signalling pathway. Finally, we used a recombinant sialic acid cleaving enzyme (sialidase) to confirm that sialoglycans on primary human T cells are bona fide immunophysiological regulators of FasR-driven programmed cell death. Combined, our results demonstrate that sialoglycan remodelling on T cells influences cell fate driven by the Fas pathway and provide motivation to further characterize the immunoregulatory roles of the glycocalyx in health and disease.

immunology↗

bioRxiv2025

TopoLa: A Universal Framework to Enhance Cell Representations for Single-cell and Spatial Omics through Topology-encoded Latent Hyperbolic Geometry

Recent advances in cellular research demonstrate that scRNA-seq characterizes cellular heterogeneity, while spatial transcriptomics reveals the spatial distribution of gene expression. Cell representation is the fundamental issue in the two fields. Here, we propose Topology-encoded Latent Hyperbolic Geometry (TopoLa), a computational framework enhancing cell representations by capturing fine-grained intercellular topological relationships. The framework introduces a new metric, TopoLa distance (TLd), which quantifies the geometric distance between cells within latent hyperbolic space, capturing the networks topological structure more effectively. With this framework, the cell representation can be enhanced considerably by performing convolution on its neighboring cells. Performance evaluation across seven biological tasks, including scRNA-seq data clustering and spatial transcriptomics domain identification, shows that TopoLa significantly improves the performance of several state-of-the-art models. These results underscore the generalizability and robustness of TopoLa, establishing it as a valuable tool for advancing both biological discovery and computational methodologies.

bioinformatics↗

bioRxiv2024

The assembly of Y chromosome reveals amplification of genes regulating male fertility in Bactrocera dorsalis

BACKGROUNDThe oriental fruit fly Bactrocera dorsalis is an invasive pest causing considerable ecological and economic damage worldwide. The Y chromosome is an important target for the sterile insect technique (SIT) but its sequence and structure has been poorly explored. RESULTSWe assembled the genome of B. dorsalis at the chromosome level with a total size of 562.6 Mb. The assembly includes a [~]7.6 Mb Y chromosome sequence, being the first reported Y chromosome in Tephritidae. The assembled Y chromosome is highly repetitive, and contains 61 genes, including 9 multi-copy genes. We surprisingly found that the M factor (MoY) in Tephritidae has multiple copies, verified by our droplet digital PCR (ddPCR) analysis. Besides, we identified 32 copies of gyf-like on the Y chromosome (gyfY) that were highly expressed in testis. RNAi targeting the gyfY resulted in depletion of live sperms, suggesting that the amplification of gyfY is essential for male fertility, which facilitated the understanding of high fecundity of this invasive insect. CONCLUSIONWe reported firstly the Y chromosome of Bactrocera dorsalis. Our results will also provide target genes for CRISPR/Cas9 based SIT, leading to the development of novel control strategies against tephritid flies.

zoology↗

bioRxiv2022

Perturbation of mitochondrial Ca2+ homeostasis activates cross-compartmental proteostatic response in Arabidopsis

Mitochondrial Ca2+ (mtCa2+) homeostasis is essential to mitochondrial functions. However, how mtCa2+ homeostasis is achieved and the consequences of impaired mtCa2+ homeostasis in plants is poorly understood. Here, we demonstrate a critical role for mitochondrial Ca2+ uniporter (MCU) in the control of mtCa2+ uptake for mtCa2+ homeostasis in planta by characterizing MCU mutants and overexpressed plants. Impaired MCU-controlled mtCa2+ homeostasis (iMUCH) in gain-of-function and loss-of-function MCU plants causes the misregulation of mitochondrial gene expression that triggers mitonuclear protein imbalance. Transcriptome integrated with proteomics analysis reveal activation of multiple compartmental UPR gene expression and decrease of cytosolic translation with selective repression of ribosome and RNA modification protein synthesis upon iMUCH. Intriguingly, TOR signalling is not involved in cytosolic translational response to iMUCH, but the reduction of eIF phosphorylation is evident under iMUCH induced mitochondrial stress. Thus, our study unveils the essential functions of MCU proteins for mtCa2+ homeostasis, and the involvement of MCU-controlled mtCa2+ homeostasis in mitochondrial stress dependent regulation of protein synthesis for cellular proteostasis that is connected to plant growth and stress resistance.

plant biology↗

bioRxiv2021

Coordinated DNA and Histone Dynamics Drive Accurate Histone H2A.Z Exchange

Nucleosomal histone H2A is exchanged for its variant H2A.Z by the SWR1 chromatin remodeler, but the mechanism and timing of histone exchange remain unclear. Here, we quantify DNA and histone dynamics during histone exchange in real-time using a three-color single-molecule FRET assay. We show that SWR1 operates with timed precision to unwrap DNA with large displacement from one face of the nucleosome, remove H2A-H2B from the same face, and rewrap DNA, all within 2.3 seconds. Such productive DNA unwrapping requires full SWR1 activation and differs from unproductive, smaller-scale DNA unwrapping caused by SWR1 binding alone. On an asymmetrically positioned nucleosome, SWR1 intrinsically senses long-linker DNA to preferentially exchange H2A.Z on the distal face as observed in vivo. The displaced H2A-H2B dimer remains briefly associated with the SWR1-nucleosome complex and is dissociated by histone chaperones. These findings reveal how SWR1 coordinates DNA unwrapping with histone dynamics to rapidly and accurately place H2A.Z at physiological sites on chromatin. One-Sentence SummaryMulticolor single-molecule FRET reveals how SWR1 unwraps DNA to exchange nucleosomal H2A-H2B for H2A.Z-H2B.

biophysics↗

bioRxiv2021

COVID-ONE-humoral immune: The One-stop Database for COVID-19-specific Antibody Responses and Clinical Parameters

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.

microbiology↗

bioRxiv2021

Nanocharacterisation of extracellular vesicles uncovers the correlation between isolation methods, physicochemical composition and their biological function

Extracellular vesicles (EVs) have been lauded as next generation medicines, but very few EV-based therapeutics have progressed to clinical use. Limited clinical translation is largely due to technical barriers that hamper our ability to mass-produce EVs, i.e. to isolate, purify and characterise them effectively. Technical limitations in comprehensive characterisation of EVs leads to unpredicted biological effects of EVs. Here, using a range of optical and non-optical techniques, we showed that the differences in molecular composition of EVs isolated using two isolation methods correlated with the differences in their biological function. Our results demonstrated that the isolation method determines the composition of isolated EVs at single and sub-population levels. Besides the composition, we measured for the first time the dry mass and predicted sedimentation of EVs. These parameters were shown to correlate well with the biological and functional effects of EVs on single cell and cell cultures. We anticipate that our new multiscale characterisation approach, which goes beyond traditional experimental methodology, will support fundamental understanding of EVs as well as elucidate the functional effects of EVs in in vitro and in vivo studies. Our findings and methodology will be pivotal for developing optimal isolation methods and establishing EVs as mainstream therapeutics and diagnostics. This innovative approach is applicable to a wide range of sectors including biopharma and biotechnology as well as to regulatory agencies.

cell biology↗

bioRxiv2020

Expression from DIF1-motif promoters of hetR and patS is dependent on HetZ and modulated by PatU3 during heterocyst differentiation

HetR and PatS/PatX-derived peptides are the activator and diffusible inhibitor for cell differentiation and patterning in heterocyst-forming cyanobacteria. HetR regulates target genes via HetR-recognition sites. However, some genes (such as patS/patX) upregulated at the early stage of heterocyst differentiation possess DIF1 (or DIF+) motif (TCCGGA) promoters rather than HetR-recognition sites; hetR possesses both regulatory elements. How HetR controls heterocyst-specific expression from DIF1 motif promoters remains to be answered. This study presents evidence that the expression from DIF1 motif promoters of hetR, patS and patX is more directly dependent on hetZ, a gene regulated by HetR. The HetR-binding site upstream of hetR is not required for its autoregulation. PatU3 (3 portion of PatU) that interacts with HetZ may modulate HetZ-dependent gene expression. These findings contribute to understanding of the mutual regulation of hetR, hetZ-patU and patS/patX in a large group of multicellular cyanobacteria.

microbiology↗

bioRxiv2019

ImmuCellAI: a unique method for comprehensive T-cell subsets abundance prediction and its application in cancer immunotherapy

The distribution and abundance of immune cells, particularly T-cell subsets, play pivotal roles in cancer immunology and therapy. There are many T-cell subsets with specific function, however current methods are limited in estimating them, thus, a method for predicting comprehensive T-cell subsets is urgently needed in cancer immunology research. Here we introduce Immune Cell Abundance Identifier (ImmuCellAI), a novel gene set signature-based method, for precisely estimating the abundance of 24 immune cell types including 18 T-cell subsets, from gene expression data. Performance evaluation on both our sequencing data with flow cytometry results and public expression data indicated that ImmuCellAI can estimate immune cells with superior accuracy than other methods especially on many T-cell subsets. Application of ImmuCellAI to immunotherapy datasets revealed that the abundance of dendritic cells (DC), cytotoxic T, and gamma delta T cells was significantly higher both in comparisons of on-treatment vs. pre-treatment and responders vs. non-responders. Meanwhile, we built an ImmuCellAI result-based model for predicting the immunotherapy response with high accuracy (AUC 0.80~0.91). These results demonstrated the powerful and unique function of ImmuCellAI in tumor immune infiltration estimation and immunotherapy response prediction. The ImmuCellAI online server is freely available at http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/.

bioinformatics↗

bioRxiv2019

Directed robust generation of functional retinal ganglion cells from Muller glia

Glaucoma and optic neuropathies cause progressive and irreversible degeneration of retinal ganglion cells (RGCs) and the optic nerve and are currently without any effective treatment. Previous research into cell replacement therapy of these neurodegenerative diseases has been stalled due to the limited capability for grafted RGCs to integrate into the retina and project properly along the long visual pathway to reach their brain targets. In vivo RGC regeneration would be a promising alternative approach but mammalian retinas lack regenerative capacity even though cold-blood vertebrates such as zebrafish have the full capacity to regenerate a damaged retina using Muller glia (MG) as retinal stem cells. Nevertheless, mammalian MG undergo limited neurogenesis when stimulated by retinal injury. Therefore, a fundamental question that remains to be answered is whether MG can be induced to efficiently regenerate functional RGCs for vision restoration in mammals. Here we show that without stimulating proliferation, the transcription factor (TF) Math5 together with a Brn3 TF family member are able to reprogram mature mouse MG into RGCs with exceedingly high efficiency while either alone has no or limited capacity. The reprogrammed RGCs extend long axons that make appropriate intra-retinal and extra-retinal projections through the entire visual pathway including the optic nerve, optic chiasm and optic tract to innervate both image-forming and non-image-forming brain targets. They exhibit typical neuronal electrophysiological properties and improve visual responses in two glaucoma mouse models: Brn3b null mutant mice and mice with the optic nerve crushed (ONC). Together, our data provide evidence that mammalian MG can be reprogrammed by defined TFs to achieve robust in vivo regeneration of functional RGCs as well as a promising new therapeutic approach to restore vision to patients with glaucoma and other optic neuropathies.

neuroscience↗

bioRxiv2019

PI3K/AKT inhibition in tumor propagating cells of DLBCL reverses R-CHOP resistance by destabilizing SOX2

Drug resistance is a major obstacle for the success of conventional anticancer therapy, and the development of drug resistance is at least partly attributed to tumor propagating cells (TPCs). Up to one-third of diffuse large B cell lymphoma (DLBCL) patients eventually develop resistance to R-CHOP regimen. We found that the TPC proportion was remarkably increased in resistant germinal center B cell-like (GCB) and activated B cell-like (ABC) DLBCL subtypes. Elevated SOX2 was the determinant for resistance development, and SOX2 was phosphorylated by activated PI3K/AKT1 signaling, thus preventing ubiquitin-mediated SOX2 degradation. Furthermore, multiple factors, including BCR, integrins, chemokines and FGFR1/2 signaling, regulated PI3K/AKT1 activation. CDK6 in the GCB subtype and FGFR1/2 in the ABC subtype were SOX2 targets in the PI3K/AKT1 pathway. Chemical inhibition of PI3K/AKT1 in both subtypes, CDK6 in the GCB subtype, and FGFR1/2 in the ABC subtype significantly enhanced the susceptibility of resistant cells to CHO treatment. More importantly, PI3K and FGFR1/2 inhibitors but not a CDK6 inhibitor effectively suppressed the tumor growth of R-CHO-resistant DLBCL cells, most likely by converting TPCs to chemo-sensitive differentiated cells. Therefore, this pro-differentiation therapy against TPCs warrants further study in clinical trials for the treatment of resistant DLBCL.

cancer biology↗