Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 361 records · Page 20Linked to original sources

bioRxiv2025

Aromatic Patch in WhiB-Like Transcription Factors Facilitates Primary Sigma Factor Interaction in Mycobacterium tuberculosis

WhiB-like (Wbl) family proteins are a unique family of iron-sulfur ([4Fe-4S]) cluster-bound transcription factors found exclusively in Actinobacteria and actinobacteriophages, including the notoriously persistent pathogen Mycobacterium tuberculosis (Mtb). Despite their critical roles in cell development, stress response and antibiotic resistance, the mechanisms of gene regulation by the Wbl family proteins are not fully understood due to the lack of a canonical DNA-binding motif in most Wbl proteins. Here, we present structural and biochemical evidence demonstrating that all Mtb Wbl proteins bind to the same site in the conserved region 4 of the primary sigma 70 factor facilitated by a previously unrecognized structural motif, the aromatic patch, in the Wbl family. Our phylogenetic findings provide compelling evidence for a complex evolutionary relationship of Wbls between actinobacteria and the associated phages. Together, this work fills a critical gap in our understanding of the function, mechanism and evolutionary origin of Wbls.

biochemistry↗

bioRxiv2025

Towards Unified Neural Decoding with Brain Functional Network Modeling

Recent achievements in implantable brain-computer interfaces (iBCIs) have demonstrated the potential to decode cognitive and motor behaviors with intracranial brain recordings; however, individual physiological and electrode implantation heterogeneities have constrained current approaches to neural decoding within single individuals, rendering interindividual neural decoding elusive. Here, we present Multi-individual Brain Region-Aggregated Network (MIBRAIN), a neural decoding framework that constructs a whole functional brain network model by integrating intracranial neurophysiological recordings across multiple individuals. MIBRAIN leverages self-supervised learning to derive generalized neural prototypes and supports group-level analysis of brain-region interactions and inter-subject neural synchrony. To validate our framework, we recorded stereoelectroencephalography (sEEG) signals from a cohort of individuals performing Mandarin syllable articulation. Both real-time online and offline decoding experiments demonstrated significant improvements in both audible and silent articulation decoding, enhanced decoding accuracy with increased multi-subject data integration, and effective generalization to unseen subjects. Furthermore, neural predictions for regions without direct electrode coverage were validated against authentic neural data. Overall, this framework paves the way for robust neural decoding across individuals and offers insights for practical clinical applications.

neuroscience↗

bioRxiv2025

Circular van Krevelen diagram for visualizing metabolic pathways

Emerging biochemical data require effective pathway visualization. However, traditional metabolic maps were based on manual layouts, falling behind new scientific discoveries. Automated visualization of metabolic pathways has been investigated heavily, but resulted in few consensuses. We report here a new approach based on circularized van Krevelen diagram. This method is based on chemical principles, providing the consistency critical for community exchanges and collaborations. Example applications include metabolomics data interpretation and a new set of metabolic maps.

bioinformatics↗

bioRxiv2025

PLM-OMG: Protein Language Model-Based Ortholog Detection for Cross-Species Cell Type Mapping

Understanding conserved and divergent cell types across plant species is essential for ad- vancing comparative genomics and improving crop traits. Accurate and scalable ortholog detection is central to this goal, particularly in cross-species single-cell analysis. However, conventional methods are time-consuming and perform poorly with distantly related species, limiting their effectiveness. To address these limitations, we introduce PLM-OMG, a protein language model-based framework for orthogroup classification and cross-species cell type mapping. We benchmark five deep learning models including ESM2, ProGen2, ProteinBERT, ProtGPT2, and LSTM, using a curated 15-species dataset and large-scale monocot and dicot datasets from PLAZA. Transformer-based models, particularly ProtGPT2 and ESM2, achieve superior accuracy and generalization across evolutionary distances. Our results show that PLM-OMG enables scalable and reusable orthogroup detection without recomputing existing groups, significantly reducing computational overhead and highlighting its potential to transform cross-species transcriptomic analysis in plant genomics.

bioinformatics↗

bioRxiv2025

Peptides alleviate cognitive impairment by inhibiting and disassembling amyloid-beta aggregates in Alzheimer disease

Alzheimers disease (AD) is a devasting neurodegenerative disorder characterized by {beta}-amyloid formation, further exacerbated by RIPK1/RIPK3 necrosome-induced programmed necrosis (necroptosis). We previously showed that the RIPK1/RIPK3 necrosome forms a functional amyloid complex using its RIP homotypic interaction motifs (RHIMs). Here, we discovered that the core RIPK1/RIPK3 necrosome shares strikingly structural similarity to the C-terminal region of {beta}-amyloid (A{beta}42), and the RHIM-derived tetrapeptides (IQIG or VQVG) directly inhibit A{beta} aggregation, disassemble preformed A{beta} fibrils (PFFs), and reduce RIPK1 polymerization. Also, the peptides exhibit effective membrane permeability and could reduce A{beta}40 or A{beta}42-induced neural death and TNF-induced necroptosis in SH-SY5Y cells. IQIG and VQVG injected by ICV increase learning and memory abilities by reducing A{beta} plaques and hyperphosphorylated tau in the cortex and hippocampus of APP/PS1 double-transgenic mice. Mechanistically, the peptides directly interact with A{beta} to block A{beta} aggregation and alleviate microglia-mediated neuroinflammation. Strikingly, single-cell RNA sequencing revealed that the peptides-treated AD transgenic mice restored neuronal homeostasis with increased GABAergic neurons and decreased glutamatergic neurons. Furthermore, total cell-cell interaction strength increased while the AD risk gene Apoe expression decreased in the specific oligodendrocyte subtype of peptides-treated AD mice. Thus, our findings revealed that the peptides could improve cognition and memory capabilities and serve as promising structural templates for potential drugs against AD.

neuroscience↗

bioRxiv2025

Rational design of respiratory syncytial virus dimeric F-subunit vaccines in protein and mRNA forms

BackgroundRespiratory syncytial virus (RSV) poses a significant public health threat, particularly to children and the elderly. Two protein-based vaccines and one mRNA vaccine have been approved, all targeting the prefusion conformation of the fusion (F) glycoprotein. However, it has been reported that the F protein transitions to the post-fusion state during storage, resulting in a reduction of the vaccines immunogenicity. MethodsIn this study, we engineered novel pre-F-based antigens to preserve pre-F-specific immunodominant epitopes while eliminating sub-potent ones. Based on this, we constructed a series of single-chain dimers and selected the one with the highest expression yield and melting temperature (Tm). Next, we created a heterodimer, scDimer AB. Structural and protein characterization analyses were conducted to verify our design. All monomeric and scDimer antigens were used to immunize rodent models. Additionally, we prepared the antigens in mRNA form and immunized BALB/c mice. Finally, we combined both antigen forms, administering intramuscular mRNA priming followed by intranasal protein delivery in mice. In all immunization strategies, viral challenges were performed in animals to evaluate the immunologic protective effects. FindingsThrough rational design, we developed a monomeric and two single-chain dimeric (scDimer) proteins with the expected characteristics, including complete II, V, and O epitopes and a partial III epitope. The scDimers elicited stronger binding and neutralizing antibody responses in rodent models compared to the monomer, and they also boosted T cell responses when combined with appropriate adjuvants. After three doses of scDimer immunization, live RSV was barely detectable in the tissues of infected animals. The copies of RNA encoding N-gene were significantly reduced in the immunized groups compared to the PBS-injected control groups. We also engineered mRNA versions of the antigens and verified their protective efficacy in mice. Notably, there were no significant differences between intranasal boost and intramuscular two doses after RSV challenged, suggesting that intranasal boost provided equivalent protection to intramuscular vaccination and could reduce the risk of vaccine-enhanced disease (VED) potentially. InterpretationThe scDimer-based RSV vaccines effectively protected rodents from RSV infections, highlighting their clinical potential. Our antigen design removed certain suboptimal epitope regions, enhancing the efficiency of antigen presentation and increasing the proportion of the most potent pre-F-specific neutralizing antibodies. This approach provides a novel perspective for future vaccine design. FundingNational Key R&D Program of China, National Science Foundation of China, Young Scientists in Basic Research, Chinese Academy of Sciences, and Special Program of China National Tobacco Corporation. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe licensed respiratory syncytial virus (RSV) vaccines were based on RSV pre-F structure. We conducted a PubMed search for articles published in English from databases inception to March 31, 2025, using the search terms "RSV" (interchanged with "respiratory syncytial virus"), "pre-F" (interchanged with "prefusion F") and "vaccine". Our search revealed that most of the articles focus on combining pre-F with RSV G protein or other proteins to form viral-like particles (VLPs) or nanoparticles. The second-largest category of articles examined the antibodies level elicited by the pre-F antigens in animal model or some special cohorts. Other studies addressed topics such as optimization of injection dosage and immunization strategies, methodologies for detecting pre-F-specific antibodies, and the development of mRNA-LNP vaccines. Notably, only 4 articles described novel designs of RSV pre-F antigens, all of which were trimeric and based exclusively on the RSV A subtype F protein sequence. Added value of this studyTo our knowledge, our design is the first single-chain dimer version of RSV pre-F antigen. The engineered antigens demonstrated high yield, thermostability, and immunogenicity comparable to that of DS-Cav1. Additionally, we developed the first chimeric RSV-antigen covering both subtype A and B, thereby broadening the potential protective spectrum. We further validated the immunogenicity of our designs in mRNA form and as a protein-mRNA combination. This research emphasizes the potential of constructing and combining minimized, stable antigen modules, offering a novel approach for future vaccine development. Implications of all the available evidenceIn this study, we present a novel approach for constructing and combining minimized, stable antigen modules for future vaccine design. The strong immunogenicity of our antigens underscores their potential for clinical application. Furthermore, given the structural similarities between the RSV antigen and those of other Pneumoviruses, such as human metapneumovirus (hMPV), our design strategy could be extended to the development of multivalent vaccines.

immunology↗

bioRxiv2025

scCoBench: Benchmarking single cell RNA-seq co-expression using promoter-reporter lines

Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for uncovering transcriptomic heterogeneity and reconstructing gene regulatory networks in complex tissues. However, the sparsity, high noise levels, and dropout events inherent to scRNA-seq data pose challenges for accurate inference of gene-gene relationships. In this study scCoBench, we systematically benchmark correlation metrics, pseudo bulk analysis, and imputation methods using promoter-reporter and native gene pairs as internal controls to evaluate the performance of ten widely used gene-gene co-expression measurements. Interestingly, we found that commonly used data scaling and normalization approaches lead to lower correlation between promoter reporter and native gene pairs in most of the co-expression methods. Moreover, we assess the impact of five popular imputation techniques, including scImpute, SAVER, Autoencoder (AE), Variational Autoencoder (VAE), and Generative Adversarial Network (GAN) on recovering biologically relevant co-expression patterns. Our results demonstrate that imputation models not only markedly enhance correlation between each promoter-reporter and native gene pair but also increase the number of cells co-expressing both genes. Imputation also improved transcription factor target gene correlations and revealed stronger associations among genes within the same protein complex. This work highlights the utility of promoter-reporter systems for benchmarking computational methods and underscores the potential of deep learning-based imputation to improve the biologically relevant signals of scRNA-seq data.

bioinformatics↗

bioRxiv2025

Aptamer-Enabled Discovery and Clinical Analysis of Exosomal Surface Biomarkers in Hepatocellular Carcinoma

Exosomal membrane proteins hold promise as cancer biomarkers but face detection challenges due to low abundance and conformational sensitivity. We developed AptEx-ID, a microbead-displayed aptamer platform enabling high- throughput screening of hepatocellular carcinoma (HCC)-specific exosomal surface proteins. Aptamers, selected via competitive binding to tumor-derived versus healthy exosomes, demonstrated high affinity and specificity. Clinical validation using 50 HCC and 30 control plasma samples identified a 7-aptamer panel via machine learning, achieving 93.75% accuracy and 0.95 ROC-AUC. These aptamers further revealed HCC-associated biomarkers (e.g., IMPDH1, ASCC3, GTSE1), validated by siRNA knockdown and biophysical assays. Post-treatment monitoring showed aptamer signal reduction in responsive patients, highlighting their prognostic utility. This platform integrates biomarker discovery, diagnostics, and therapeutic monitoring, offering a robust approach for HCC management through exosomal surface proteome profiling.

molecular biology↗

bioRxiv2025

Stromal SRD5A2 promotes prostate growth through WNT5A-LEF1-IGF1 signaling in benign prostatic hyperplasia

Steroid 5-reductase type 2 (SRD5A2) is a key enzyme in androgen metabolism and a pharmacologic target in benign prostatic hyperplasia (BPH). While SRD5A2 is known to mediate stromal-epithelial interactions that influence prostate growth, the relationship between baseline SRD5A2 expression and prostate volume remains unclear. In this study, we analyzed SRD5A2 expression in human prostate tissues from the Medical Therapy of Prostatic Symptoms (MTOPS) trial and institutional biorepository cohorts. Quantitative assessments were performed and correlations were evaluated between expression level of SRD5A2, WNT5A, prostate volume, and tissue signaling profiles. SRD5A2 expression was significantly associated with total prostate and transition zone volume in both human cohorts. Stromal-specific WNT5A expression showed a strong positive correlation with SRD5A2, while neither serum nor tissue dihydrotestosterone levels correlated with SRD5A2 expression. In Srd5a2-null mice, Wnt5a expression in the prostate stroma was dependent on Srd5a2 and showed region-specific regulation. Mechanistically, SRD5A2 overexpression in human prostate stromal cells upregulated WNT5A and Lymphoid Enhancer-Binding Factor 1 (LEF1), activated insulin-like growth factor 1 (IGF1) signaling, increased proliferation, and reduced apoptosis. Conditioned media from these cells enhanced epithelial proliferation through paracrine IGF1 activity, independent of epithelial WNT signaling. This study provides the first evidence that SRD5A2 promotes prostate growth through a stromal WNT5A-LEF1-IGF1 paracrine signaling axis, functioning independently of androgen levels. These findings suggest a novel therapeutic mechanism relevant for BPH patients with resistance to conventional 5-reductase inhibitor therapy.

pathology↗

bioRxiv2025

Contrastive Representation Learning for Single Cell Phenotyping in Whole Slide Imaging of Enrichment-free Liquid Biopsy

Tumor-associated cells derived from a liquid biopsy are promising biomarkers for cancer detection, diagnosis, prognosis, and monitoring. However, their rarity, heterogeneity and plasticity make precise identification and biological characterization challenging for clinical utility. Enrichment-free approaches using whole slide imaging of all circulating cells offer a comprehensive and unbiased strategy for capturing the full spectrum of tumor-associated cell phenotypes. However, current analysis methods often depend on engineered features and manual expert review, making them sensitive to technical variations and subjective biases. These limitations highlight the need for a better feature representation to improve performance and reproducibility of applications in large-scale patient cohort analyses. In this study, we present a deep contrastive learning framework for learning features of all circulating cells, enabling robust identification and stratification of single cells in whole slide immunofluorescence microscopy images. We demonstrate performance of learned features in classification of diverse cell phenotypes in the liquid biopsy, achieving an accuracy of 92.64%. We further demonstrate that learned features improve performance in downstream applications such as outlier detection and clustering. Lastly, our feature representation enables automated identification and enumeration of distinct rare cell phenotypes, achieving average F1-score of 0.93 across cell lines mimicking circulating tumor cells and endothelial cells in contrived samples and average F1-score of 0.858 across CTC phenotypes in clinical samples. This workflow has significant implications for scalable analysis of tumor-associated cellular biomarkers in clinical prognosis and personalized treatment strategies.

cancer biology↗

bioRxiv2025

Age-informed, attention-based weakly supervised learning for neuropathological image assessment

Chronic Traumatic Encephalopathy (CTE) and other neurodegenerative disorders (NDs) pose diagnostic challenges due to their diffuse and subtle pathological changes. Traditional diagnostic methods relying on manual histopathological slide inspection are labor-intensive and prone to variability, often missing subtle structural alterations. This study introduces an age-informed, attention-based multiple instance learning (MIL) pipeline to predict AT8 density, a key marker of p-tau aggregation in CTE. Using Luxol Fast Blue and Hematoxylin & Eosin (LH&E) stained images, our model identifies critical pathological regions and generates interpretable attention maps highlighting structural changes linked to tau pathology. Incorporating patient age enhances predictive accuracy and contextual understanding, addressing agings confounding effects. We also develop quantitative evaluation procedures for foundation models (FMs), assessing attention map smoothness, faithfulness, and robustness to perturbations like stain variability and noise. These benchmarks facilitate informed FM selection and optimization for neuropathological tasks. By enabling scalable, automated whole-slide image (WSI) analysis, our approach advances digital neuropathology, supporting earlier and more precise ND diagnoses and uncovering subtle markers with potential applications in clinical imaging.

bioinformatics↗

bioRxiv2025

A hierarchy of time constants and reliable signal propagation in the marmoset cortex

A hierarchy of timescales in the cerebral cortex is functionally desirable for rapid information processing in sensory areas and slow time integration in association areas. Here, through an analysis of electrocorticography (ECoG) data, we identified a timescale hierarchy in the neocortex of marmoset, a primate species commonly used in neuroscience. Constrained by the anatomical and electrophysiological data, we developed a multi-regional model of the marmoset neocortex that captures the observed timescale hierarchy phenomenon. Furthermore, we used the model to investigate how the neocortex reconciles information integration on distinct timescales in local areas with reliable signal propagation globally across regions. We found that a near-criticality state is optimal for both localized signal integration within areas and reliable signal propagation across areas in the multi-regional neocortex. Our model also mechanically explains recent experimental observations that the structural and functional connectivities are less correlated in association areas than in sensory areas.

neuroscience↗

bioRxiv2025

Two-Dimensional Nonlinear Structured Illumination Microscopy with rsEGFP2

Superresolution microscopy enables imaging of subcellular structures and dynamics with nanoscale detail. Among the various superresolution techniques, structured illumination microscopy (SIM) stands out for its compatibility with live-cell imaging. Linear SIM is restricted to a resolution improvement of a factor of two, improving the resolution to about 100 nm. Nonlinear SIM (NSIM) utilizes reversibly switchable fluorescent proteins to generate a nonlinear response, allowing for the collection of higher spatial frequency information and theoretically extending the resolution without limit. By employing rsEGFP2 and patterned depletion illumination (PD) to generate the desired nonlinearity in the fluorescent response, we have successfully achieved 2D PD-NSIM imaging of actin in live U2OS cells with sub-80 nm resolution.

bioengineering↗

bioRxiv2025

Development of a cross-protective common cold coronavirus vaccine

Common cold coronaviruses, such as OC43 and HKU1, generally cause mild respiratory infections in healthy people. However, they can lead to severe illness in high-risk groups, including immunocompromised individuals and older adults. Currently, there is no clinically approved vaccine to prevent infection by common cold coronaviruses. Here, we developed an mRNA vaccine expressing a stabilized spike protein derived from OC43 and tested its efficacy in different challenge models in C57BL/6 mice. This novel OC43 vaccine elicited OC43-specific immune responses, as well as cross-reactive immune response against other embecoviruses, including HKU1 and mouse hepatitis virus (MHV-A59). Interestingly, this OC43 vaccine protected mice not only against a lethal OC43 infection, but also against MHV-A59, which is only 65% matched. Vaccine cross-protection appeared to be mechanistically mediated by non-neutralizing antibodies, but not by CD8 and CD4 T cells. These findings provide insights for the development of common cold coronavirus vaccines, demonstrating the potential for a single vaccine to target different members of a coronavirus subgenus.

immunology↗

bioRxiv2025

Aird-MSI: a high compression rate and decompression speed format for mass spectrometry imaging data

Mass spectrometry imaging has emerged as a pivotal tool in spatial metabolomics, yet its reliance on the imzML format poses critical challenges in data storage, transmission, and computational efficiency. While imzML ensures cross-platform compatibility, its lower compressed binary architecture results in large file sizes and high parsing overhead, hindering cloud-based analysis and real-time visualization. This study introduces an enhanced Aird compression format optimized for spatial metabolomics through two innovations: (1) a dynamic combinatorial compression algorithm for integer-based encoding of m/z and intensity data; (2) a coordinate-separation storage strategy for rapid spatial indexing. Experimental validation on 47 public datasets demonstrated significant performance gains. Compared to imzML, Aird achieved a 70% reduction in storage footprint (mean compression ratio: 30.03%) while maintaining near-lossless data precision (F1-score = 99.26% at 0.1 ppm m/z tolerance). For high-precision-controlled datasets, Aird accelerated loading speeds by 15-fold in MZmine. The Aird format overcomes crucial bottlenecks in spatial metabolomics by harmonizing storage efficiency, computational speed, and analytical precision, reducing I/O latency for large cohorts. By achieving near-native feature detection accuracy, Aird establishes a robust infrastructure for translational applications, including disease biomarker discovery and pharmacokinetic imaging.

bioinformatics↗

bioRxiv2025

Constructing a consensus serum metabolome

Blood analysis is the most common in biomedical applications and a reference metabolome will be critical for effective annotation and for guiding scientific investigations. However, compiling such a reference is hindered by many technical challenges, despite the availability of large amount of metabolomics data today. Based on a new set of data structures and tools, we have assembled a consensus serum metabolome (CSM) from over 100,000 mass spectrometry acquisitions of more than 200 million spectra. This provides a comprehensive survey of human blood chemistry, revealing the frequency dependent nature of metabolome and exposome. Major gaps are found between CSM and the current databases. The CSM enables community-level data alignment and significantly improves annotation quality of LC-MS metabolomics. HighlightsO_LIA reference of human biochemistry linked to observation frequency C_LIO_LIMajor gaps revealed in current databases and experimental methods C_LIO_LIEnabling cross-laboratory, cross-platform data alignment C_LIO_LIAccelerated and cumulative metabolite annotation C_LI

biochemistry↗

bioRxiv2025

Human Messenger RNA Harbors Widespread Noncoding Splice Isoforms

Pre-messenger RNA transcribed from canonical protein-coding genes is frequently alternatively spliced into diverse mature mRNA isoforms, thus translating into various protein products. However, it remains unknown whether human mRNA from a protein-coding gene harbors noncoding splice isoforms in the genome. Herein, we discovered 15,836 mRNA noncoding splice isoforms across 7,298 protein-coding genes in human. mRNA noncoding isoforms are mainly produced by alternative splicing and polyadenylation, which display tissue-specific distributions and involve in RNA processing pathways. Notably, mRNA noncoding isoforms are frequently upregulated in cancer. Differentially expressed mRNA noncoding isoforms are associated with the cancer hallmarks and can independently predict patient survival. These findings unraveled human mRNA harbors widespread noncoding splice isoforms, and highlight the dual characters of mRNA including protein-translation isoforms and noncoding splice isoforms, providing a new dimension to our understanding of mRNA functional property.

genomics↗

bioRxiv2025

Intracellular Delivery of Bone Nanoparticles to Mitigate Irradiation-Induced Damage in Bone Marrow Mesenchymal Stem Cells

Ionizing radiation (IR)-induced bone damage presents a major clinical challenge by impairing bone marrow function and disrupting normal bone remodeling. Bone regeneration depends on bone marrow-derived mesenchymal stem cells (BMSCs), which are highly sensitive to IR that causes DNA damage, oxidative stress, apoptosis, and a shift from osteogenesis to adipogenesis, ultimately leading to bone loss and impaired healing. This study evaluated the therapeutic potential of intracellularly delivered bone-derived nanoparticles (BPs) in mitigating IR-induced BMSCs damage. We found that IR exposure caused significant BMSCs dysfunction, including reduced proliferation, increased apoptosis, persistent DNA damage, and a shift toward adipogenic differentiation. Treatment with BPs led to efficient intracellular uptake, improved cell morphology, enhanced proliferation, reduced apoptosis, and preservation of balanced differentiation capacity. Transcriptomic analysis via RNA sequencing revealed that BPs restored key molecular pathways disrupted by IR, particularly those involved in cell cycle regulation, extracellular matrix (ECM) remodeling, and apoptosis. By reversing these transcriptional impairments, BPs supported genomic stability and the regenerat ive function of BMSCs. Overall, these findings suggest that BPs effectively counteract IR-induced cellular damage and enhance the regenerative capacity of BMSCs, offering a promising therapeutic strategy for radiation -induced skeletal injuries.

bioengineering↗