Biology subjects

Lin, J.

Publications and source records attributed to Lin, J..

At least 145 records · Page 8Linked to original sources

bioRxiv2025

High-throughput MicroED for probing ion channel dynamics

Ion channels play a crucial role in ion transport and are integral to fundamental physiological processes. Therefore, understanding channel structures is essential for elucidating the mechanisms of ion permeation and selectivity beyond what can be predicted by computational simulations. Visualizing dynamics at high resolution, however, remains a significant challenge by structural techniques. In this study, we apply high-throughput Microcrystal Electron Diffraction (MicroED) to explore the structural dynamics of two ion channels, the non-selective ion channel NaK and its mutant, NaK2CNG. This approach utilizes automated data collection and processing to capture distinct structural substates from a large number of microcrystals, offering a deeper understanding of ion channel mechanisms. From a subset of NaK structures, we observed consistent sodium binding at specific sites. In contrast, NaK2CNG appears more dynamic and undergoes dilation of the selectivity filter upon potassium binding. Further, the conduction state of NaK2CNG appears to be influenced by channel gating. Comparative analysis of these structures reveals that non-selectivity arises from the plasticity of the selectivity filter, allowing dynamic control over ion passage. These studies, demonstrate the potential to employ high-throughput MicroED as a technique to address persistent questions regarding ion channel permeation, complementing current computational molecular dynamics studies. We anticipate that this approach will enhance future computational models, leading to more accurate predictions of ion channel behavior and providing a more comprehensive view of transport dynamics.

biochemistry↗

bioRxiv2025

Ligand Screening and Discovery using Cocktail Soakingand Automated MicroED

Cocktail soaking using single-crystal X-ray diffraction (SC-XRD) has previously allowed high-throughput crystallographic screening of ligands against protein targets. However, protein microcrystals are not amenable to this approach if they are too small to yield strong diffraction patterns. In this study, we developed a workflow integrating cocktail soaking with automated microcrystal electron diffraction (MicroED) to allow rapid ligand screening, structure determination, and binding analysis directly from microcrystals. This can improve the successful hit rate, because binding is often more efficient when smaller crystals are soaked in the ligand. The approach was validated with known ligands of thermolysin and identified novel binding interactions for ligands of proteinase K. The structures of multiple protein-ligand complexes, including ligands with weak binding affinities, could be solved quickly. Their estimated relative binding affinities are in good agreement with previous work and independent microscale thermophoresis (MST) measurements.

biochemistry↗

bioRxiv2025

KYLO-0603, a novel liver-targeting, thyroid hormone recep-tor-β agonist for the treatment of MASH

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease associated with liver-related complications and death. Kylo-0603 is a novel agonist for the thyroid hormone receptor {beta} (THR-{beta}) that has been developed by merging the structures of three acetylgalactosamine (GalNAc)-modified ASPGR ligands with a triiodothyronine (T3) analog. This unique design allows for both THR-{beta} activation and targeted delivery to hepatocytes, significantly reducing the risk of adversed effects related to increased systemic thyroid hormone-like effects. Additionally, it effectively lowers serum cholesterol by as much as 69.2% and low-density lipoprotein cholesterol (LDL-C) levels by up to 88.2% in the MASH mouse model. Meanwhile, Kylo-0603 was shown to reduce steatosis by up to 1.3 points (P < 0.001), inflammation by 1.8 points (P < 0.0001), and ballooning by 0.8 points (P < 0.01). The non-alcoholic steatohepatitis (NASH) activity score (NAS) decreased by up to 3.7 points (P < 0.0001), and the fibrosis score dropped by 0.6 points (P < 0.05). These findings suggest that Kylo-0603 is effective in enhancing liver tissue NASH status and inhibiting fibrosis progression. In summary, Kylo-0603, as a highly both tissue and target selective and low-toxicity THR-{beta} agonist, shows significant promise for treating MASH and is likely to emerge as a new therapeutic option for patients with this condition.

biochemistry↗

bioRxiv2025

mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite generates a local immunostimulatory niche for cancer immunotherapy

Hydrogel materials have emerged as versatile platforms for various biomedical applications. Notably, the engineered nanofiber-hydrogel composite (NHC) has proven effective in mimicking the soft tissue extracellular matrix, facilitating substantial recruitment of host immune cells and the formation of a local immunostimulatory microenvironment. Leveraging this feature, here we report an mRNA lipid nanoparticle (LNP)-incorporated NHC microgel matrix, termed LiNx, by incorporating LNPs loaded with mRNA encoding tumour antigens. Harnessing the potent transfection efficiency of LNPs in antigen-presenting cells (APCs), LiNx demonstrates remarkable immune cell recruitment, antigen expression and presentation, and cellular interaction. These attributes collectively create an immunostimulating milieu and yield a potent immune response achievable with a single dose, comparable to the conventional three-dose LNP immunization regimen. Further investigations reveal that the LiNx not only generates heightened Th1 and Th2 responses but also elicits a distinctive Type 17 T helper cell-mediated response pivotal for bolstering antitumour efficacy. Our findings elucidate the mechanism underlying LiNxs role in potentiating antigen-specific immune responses, presenting a new strategy for cancer immunotherapy.

bioengineering↗

bioRxiv2025

Identification of Scaffold Specific Energy Transfer Networks in the Enthalpic Activation of Orotidine 5'-Monophosphate Decarboxylase

AbstractOrotidine 5-monophosphate decarboxylase (OMPDC) is one of the most efficient enzyme systems studied, enhancing the decarboxylation of OMP to uridine 5-monophosphate (UMP) by ca. 17 orders of magnitude, primarily by reducing the enthalpy of activation by ca. 28 kcal/mol. Despite a substantial reduction in activation enthalpy, OMPDC requires 15 kcal/mol of activation energy post- ES complex formation. This study investigates the physical basis of how thermal energy from solvent collisions is directed into the active site of enzyme to enable efficient thermal activation of the reaction. Comparative study of temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX) for WT and mutant forms of enzymes has recently been shown to uncover site specific protein networks for thermal energy transfer from solvent to enzyme active sites. In this study, we interrogate region-specific changes in the enthalpic barrier for local protein flexibility using a native OMPDC from Methanothermobacter thermautotrophicus (Mt-OMPDC) and a single site variant (Leu123Ala) that alters the activation enthalpy for catalytic turnover. The data obtained implicate four spatially resolved, thermally sensitive networks that originate at different protein/solvent interfaces and terminate at sites surrounding the substrate near the substrate phosphate-binding region (R203), the substrate- ribose binding region (K42), and a reaction enhancing loop5 (S127). These are proposed to act synergistically, transiently optimizing the position and electrostatics of the reactive carboxylate of the substrate to facilitate activated complex formation. The uncovered complexity of thermal activation networks in Mt-OMPDC distinguishes this enzyme from other members of the TIM barrel family previously investigated by TDHDX. The new findings extend the essential role of protein scaffold dynamics in orchestrating enzyme activity, with broad implications for the design of highly efficient biocatalysts.

biochemistry↗

bioRxiv2025

Feature-Driven Whole-Tissue Imaging with Subcellular Resolution

Understanding how subcellular structures and events shape tissue-wide phenomena remains a central challenge in biology. We present Multiscale Cleared Tissue Axially Swept Light-Sheet Microscopy (MCT-ASLM), a platform combining cm-scale imaging with targeted high-resolution interrogation of intact tissues in human-guided or autonomous modes. Capable of capturing fields of view up to 21 mm at micron-scale resolution, MCT-ASLM can seamlessly transition to submicron (~300 nm) isotropic resolution for targeted imaging. This versatility enables comprehensive studies of hierarchical organization and spatially complex processes, including mapping neuronal circuits in rat brains, visualizing glomerular innervation in mouse kidneys, and examining metastatic tumor microenvironments. By bridging subcellular to tissue-level scales, MCT-ASLM offers a powerful method for unraveling how local events contribute to global biological phenomena.

biophysics↗

bioRxiv2025

Super-omics and PCAS reveal rheumatoid arthritis as a tumor-like disease

Rheumatoid arthritis (RA) is a debilitating systemic autoimmune disorder that significantly impairs quality of life. To elucidate the molecular alterations in RA progression, we performed comprehensive super-omics analyses on synovial tissues from patients with joint trauma, arthritis, and RA. These analyses included transcriptomics, proteomics, metabolomics, microbiomics, and fourteen PTMs (phosphorylation, acetylation, lactylation, O-GlcNAc glycosylation, arginine monomethylation, lysine monomethylation, lysine dimethylation, lysine trimethylation, succinylation, malonylation, glutarylation, tyrosine nitration, N-glycosylation, and O-glycosylation). Additionally, we developed a protein-centered association study (PCAS) method to integrate these complex datasets. Using this approach, we identified key proteins, such as STK17B, and its interactors, which may be crucial in RA pathogenesis. Tumor-like features, including aberrant angiogenesis and epithelial-mesenchymal transition, were observed in RA, alongside the potential involvement of oncogenes and tumor suppressor genes. Finally, we constructed a molecular interaction blueprint of RA, providing a comprehensive framework for advancing RA pathogenesis, diagnosis, and therapy.

immunology↗

bioRxiv2025

Toward a privacy-preserving predictive foundation model of single-cell transcriptomics with federated learning and tabular modeling

The ability to pre-train on vast amounts of data to build foundation models (FMs) has achieved remarkable success in numerous domains, including natural language processing, computer vision, and, more recently, single-cell genomics--epitomized by GeneFormer, scGPT, and scFoundation. However, as single-cell FMs begin to train on increasingly large corpora, significant privacy and ethical concerns arise. Moreover, unlike text data, single-cell data is unordered and exhibits a unique tabular structure that most existing single-cell FMs overlook. In this study, we propose Tabula, a privacy-preserving and tabular-structure aware FM designed with federated learning (FL) and tabular modeling. Tabula combines the advantages of FMs and FL, enabling collaborative model training across multiple clients without compromising data privacy. In contrast to earlier single-cell FMs--which treat single-cell data like natural language (viewing cells as "words" defined by genes)--Tabula introduces a novel pretraining strategy that explicitly models the tabular structure of single-cell data. Extensive experimental results show that Tabula outperforms state-of-the-art methods in various downstream tasks (including cell type annotation, gene imputation, gene perturbation, multi-batch integration, and multi-omics integration) while requiring only half the data for pretraining and preserving data privacy. Furthermore, Tabula accurately reveals pairwise and even combinatorial regulatory logic across diverse biological systems, including hematopoiesis, pancreatic endogenesis, neurogenesis, and cardiogenesis. Thus, Tabula provides a new foundation model that explicitly incorporates the tabular nature of single-cell data alongside FL, paving the way for creating a "virtual cell" for human health under critical privacy preservation.

bioinformatics↗

bioRxiv2024

Development of a monoclonal antibody against duck IFN-γ protein and the application for Intracellular Cytokine Staining

ABSTRACTInterferon-{gamma} (IFN-{gamma}), a member of the type II IFN family, is a crucial cytokine in the immune system and serves as an important indicator of immune response. Intracellular Cytokine Staining (ICS) is a technique used to analyze the production of cytokines within individual cells, and it has a wide range of applications in the fields of immunological monitoring, vaccine trials, and the study of infectious diseases. This study aimed to prepare monoclonal antibodies against duck IFN-{gamma} protein and to establish an ICS protocol for detecting the duck IFN-{gamma} protein. The duIFN-{gamma}-His or duIFN-{gamma}-Fc gene was cloned into the pEE12.4 expression vector and expressed as a recombinant protein of size 20.2 KDa or 54.9 KDa in 293F cells. The purified recombinant proteins were inoculated into BALB/c mice to generate splenic lymphocytes capable of secreting anti-duIFN-{gamma} antibodies, and hybridoma cells were obtained after fusion with SP2/0 cells. A new hybridoma cell line named 24H4, which stably secreted IgG3 {kappa} subtype antibody against duck IFN-{gamma}. This monoclonal antibody (mAb) was identified by Western Blot to recognize duck IFN-{gamma} antibodies, and the indirect ELISA results showed that its ability to recognize IFN-{gamma} protein reached 0.001 g/ml. The established ICS method was used to stain PBMCs after ConA stimulation, and duck IFN-{gamma} protein was successfully detected by flow cytometry, indicating that the ICS method was successfully established. This study we use the monoclonal antibody, 24H4, provides a crucial tool for subsequent research on duck cellular immune responses.

immunology↗

bioRxiv2024

Osteoporosis with different causation exhibits different changes in bone tissue mineral and organic matrix

Osteoporosis (OP) which is a common skeletal disease with different causation is prevalent in aging population. Postmenopause women generally suffer from OP with bone loss due to estrogen deficiency. Diabetes are also associated with OP by complex metabolic mechanisms. Bone qualities of OP caused by aging were compared with the ovariectomy (OVX) model and the Type 2 diabetic model using Sprague-Dawley (SD) rats in our study. Combining with micro-computed tomography (-CT) and solid-state NMR (SSNMR) methods, this research studied bone changes in SD rats from tissue level to the molecular level. The studies revealed bone loss was most significant for cancellous bones, but not for cortical bones in OP rats. However, at the molecular level, the content of HAP in cortical bone increased with aging, contributing to the brittleness of the bone. Triglyceride, as a senescence maker of osteocyte in cortical bone, was also identified to be closely associated with OP in aging and OVX rats, but not in diabetic rats. This research suggests differing bone qualities in molecular level of OP with various causes more objectively reflect the bone tissue reconstruction rather than bone loss in -CT analysis.

biochemistry↗

bioRxiv2024

EpiAgent: Foundation model for single-cell epigenomic data

Large-scale foundation models have recently opened new avenues for artificial general intelligence. Such a research paradigm has recently shown considerable promise in the analysis of single-cell sequencing data, while to date, efforts have centered on transcriptome. In contrast to gene expression, chromatin accessibility provides more decisive insights into cell states, shaping the chromatin regulatory landscapes that control transcription in distinct cell types. Yet, challenges also persist due to the abundance of features, high data sparsity, and the quasi-binary nature of these data. Here, we introduce EpiAgent, the first foundation model for single-cell epigenomic data, pretrained on a large-scale Human-scATAC-Corpus comprising approximately 5 million cells and 35 billion tokens. EpiAgent encodes chromatin accessibility patterns of cells as concise "cell sentences," and employs bidirectional attention to capture cellular heterogeneity behind regulatory networks. With comprehensive benchmarks, we demonstrate that EpiAgent excels in typical downstream tasks, including unsupervised feature extraction, supervised cell annotation, and data imputation. By incorporating external embeddings, EpiAgent facilitates the prediction of cellular responses to both out-of-sample stimulated and unseen genetic perturbations, as well as reference data integration and query data mapping. By simulating the knockout of key cis-regulatory elements, EpiAgent enables in-silico treatment for cancer analysis. We further extended zero-shot capabilities of EpiAgent, allowing direct cell type annotation on newly sequenced datasets without additional training.

bioinformatics↗

bioRxiv2024

Detecting Amino Acid Variants Using Next-Generation Protein Sequencing (NGPS)

Next-Generation Protein Sequencing (NGPS) is a single-molecule approach for characterizing protein variants, offering detailed insight into proteoforms and amino acid substitutions not easily discerned by mass spectrometry. The novel data type produced by NGPS, which is based on binding of N-terminal amino acids by fluorescently tagged recognizer proteins, requires the development of new data analysis methods and bioinformatic tools. Here, we present ProteoVue, a comprehensive bioinformatics pipeline for Single Amino Acid Variant (SAAV) detection and quantification using the Quantum-Si Platinum(R) NGPS platform. ProteoVue integrates multiple analytical components, including robust pulse-calling, recognition segment detection, fluorescence dye classification, and a neural network-driven kinetic signature database for pulse duration prediction. These components feed into a scoring-based alignment and clustering framework that enables accurate variant calling within binary peptide mixtures. We demonstrate that ProteoVue recovers expected variant ratios across diverse substitution types including residues that lack direct amino acid recognizers. While some extreme cases remain challenging, the pipeline consistently captures the key kinetic features required for variant discrimination, underscoring its potential as a versatile and powerful tool for proteomic studies. As NGPS technology matures and recognizer libraries expand, ProteoVue provides a foundation for increasingly refined variant analysis in basic research, biomarker discovery, and clinical applications.

bioinformatics↗

bioRxiv2024

Ultrasensitive tuning of cytoplasmic viscosity via active noise

The mechanical properties of cytoplasm are crucial for cellular functions. While active processes significantly alter cytoplasmic viscoelasticity, the physical mechanisms remain elusive. Here, we model the cytoplasm as a colloidal suspension subject to passive and active noise, coarse-grained as an effective temperature. We show that a jammed cytoplasm transitions from a solid to a liquid phase at a critical effective temperature. Intriguingly, the simulated complex shear modulus at the critical state exhibits a 1/2 power-law scaling with frequency and quantitatively matches the experimental data of live cells without fitting parameters, given that the cytoplasmic volume fraction is slightly above the jamming transition. We further reveal the biological significance for the cytoplasm to be slightly above jamming: it is a regime in which the viscosity is ultrasensitive to changes in the effective temperature. Our results suggest that cells actively regulate their volume fractions in the sensitive regime in which they can tune cytoplasmic viscosity efficiently via active processes.

biophysics↗

bioRxiv2024

Structural and functional interrelationship of histone H2A and its variants H2A.Z and H2A.W in Arabidopsis

Multiple histone H2A variants are known in eukaryotes. However, the functional relationship between H2A and its variants in plants remains largely obscure. Using CRISPR/Cas9 editing, we generated a mutant lacking four H2A isoforms in Arabidopsis and analyzed the functional and structural relationship between H2A and its variants H2A.Z and H2A.W. RNA-sequencing and phenotype analyses revealed mild changes in gene transcription and plant development in the mutants lacking H2A, H2A.Z, or H2A.W compared with the wild-type plants. Chromatin immunoprecipitation sequencing analysis showed that H2A is able to substitute for both H2A.Z and H2A.W across the genome, including in euchromatin and heterochromatin regions. However, H2A.Z replaced both H2A and H2A.W primarily within the euchromatin regions. By using DNA and histones derived from Arabidopsis, we constructed nucleosomes containing H2A, H2A.Z, or H2A.W and resolved their cryogenic electron microscopy structures at near-atomic resolution. Collectively, the results reveal the structural similarity and functional redundancy of H2A and H2A variants in Arabidopsis.

plant biology↗

bioRxiv2024

Efficient creation and characterization of multi-kilobase knockins by CRISPR/Cas9 and multiple rAAVs

Multi-kilobase knock-ins (KIs) are a necessary, yet challenging type of genome editing to create and characterize in cell lines and animals. The combination of rAAV donor transduction and electroporation of single-cell mouse embryos with Cas9/gRNA ribonucleoprotein complex (RNP) enables highly efficient KI, but the insert size is limited by the viral packaging capacity. Here, we report the creation of up to 6.6 kb precise KI achieved in one step by using three rAAVs designed to insert one after the other. To fully characterize the edited genome with large KIs, we developed LOCK-seq (LOng-read sequencing of Captured Kilo-base targets), where relevant genomic regions are enriched via hybridization, achieving over 100-fold greater coverage compared to other long-read methods with enrichment. LOCK-seq simultaneously detects the presence of the KI allele, genotypes non-KI alleles and more importantly, uniquely identifies donor concatenation in the KI allele, and localizes random integration of the full or partial donor. Additionally, the multi-rAAV donor approach is successfully applied to cell lines, including lines intolerant of plasmid DNA, whereas LOCK-seq reliably and efficiently screens for KI clones. Together, the two approaches significantly improve the creation and precision of knock-in models. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/625457v3_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1619b77org.highwire.dtl.DTLVardef@125b0b2org.highwire.dtl.DTLVardef@173b12dorg.highwire.dtl.DTLVardef@7519b1_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2024

Effects of Bacterial Wilt on Community Composition and Diversity of Culturable Endophytic Fungi in Alpinia galanga

Hongdoukou plant (Alpinia galanga Willd.) is a perennial herbaceous plant that usually has a stable microflora living in the inter-root and stem and leaf tissues, which assists the host in normal growth and development. The bacterial wilt disease that had been investigated in planting bases of A. galanga, was a new soil-borne disease infected by pathogenic bacteria (Ralstonia solanacearum (Smith) Yabuuchi et al.), which disrupts the A. galanga-microbe-soil microecological balance. For this reason, it is important to study the changes of the community composition and diversity of endophytic fungi in healthy and diseased A. galanga (HDK_J and HDK_B), and to mine the active endophytic fungal resources in order to lay the foundation for exploring the functional microbial communities for artificial synthesis. All experimental materials were from the healthy and diseased plant clusters of A. galanga in the traditional planting areas in Guangdong Province. The endophytic fungi were isolated from the stems and leaves of A. galanga by separated plant tissue blocks cultured in PDA medium. The colonization rate (CR) was calculated, and the isolated strains were amplified by PCR with the ITS1/ITS4 genes as the fungal molecular markers, to identify the endophytic fungi species, and to analyze the diversity of endophytic fungi in the healthy and diseased clusters of HDK_J and HDK_B, and the indexes included: relative segregation frequency (SF), relative abundance (RA) plotted by ggplot2 under R language, Shannon-Wiener diversity index (H'), Simpson index (D), Margalef richness index (R) and Pielou uniformity index (J), and finally, a phylogenetic tree of the endophytic fungi of healthy and diseased A. galanga was constructed by MEGA. A total of 685 endophytic fungal strains were isolated from the stems and leaves of healthy (HDK_J) and diseased (HDK_B) A. galanga, of which 27 endophytic fungal species were identified in healthy A. galanga. and 8 in diseased A. galanga, which belonged to 3 Phyla, 6 Classes and 13 Families. At the genus level, the RA of HDK_B endophytic fungi were only 38.93% of HDK_J, with significant difference (P<0.05), indicating that the composition and abundance of endophytic fungi in HDK_B were lower than that in HDK_J. Meanwhile, the endophytic fungi species isolated from the stems and leaves of the HDK_J and HDK_B were the same, but the RA of leaf organs was higher than that of stems, with the RA in the leaves in HDK_J higher than that of stems by 124.23%, and the RA of leaves in HDK_B higher than that of stems by 78.23%. The RA of HDK_J leaves was 78.08% higher than that of stems. all the diversity indexes of HDK_J were higher than that of HDK_B, with significant differences (P<0.05), and the Shannon-Wiener index (H'), Simpsons index (D), and Margalefs index (R) behaved as follows: HDK_J leaves (1.16, 0.87, 5.12) > HDK_J stems (0.82, 0.72, 4.22) > HDK_B leaves (0.57, 0.24, 2.97) > HDK_B stems (0.33, 0.14, 2.25), whereas Pielous index (J) indicated that the endophytic fungal species were more uniformly distributed in HDK_J leaves, and there was not much difference in the homogeneity of the leaves of the HDK_J stems and the HDK_B stems. The mapping phylogenetic trees showed there were 4 major development branches of the species on endophytic fungi in HDK_J, and especially, there were many long development branches under the Ascomycota. The genetic relationships among different species were completely revealed in phylogenetic trees. The average genetic similarity among genera was 52.80%. Conversely, there only were1major branch (Ascomycota), and few sub-branches under the Ascomycota in HDK_B. The average genetic similarity among genera was 84.59%, and the difference was small. The bacterial wilt significantly affected the composition and RA of endophytic fungi in A. galanga. The diversity indices showed decreasing trend in A. galanga after infected by R. solanacearum. The dominant species were changed. The parts of sensitive endophytic fungi were disappeared. This result will be helpful for the study on the relationship between the artificial minimal microbial community and the role of the host as well as the study on synthetic microbiomics.

microbiology↗

bioRxiv2024

PTBP1 is upregulated by Zika virus infection via HIF-1alpha signal and hijacks NS1 protein to induce NS1 degradation to restrain viral replication

Zika virus (ZIKV), belonging to the Flaviviridae family, has been a severe threat to human health since the worldwide outbreak. ZIKV is capable of inducing fetal microcephaly, Guillain-Barre syndrome, and other serious neurological complications. Polypyrimidine tract-binding protein 1 (PTBP1) is a key member of the heterogeneous nuclear ribonucleoproteins (hnRNPs) family, functioning in selective mRNA splicing and gene expression regulation. Our previous study has indicated that the expression of PTBP1 increases in astrocytes upon ZIKV infection, yet the precise regulatory mechanisms underlying its role in viral replication remain elusive. In this study, we elucidated the specific pathway by which ZIKV upregulates PTBP1 expression through the activation of Hypoxia-inducible factor-1 (HIF-1) expression. Further investigation revealed that overexpression of PTBP1 effectively inhibits viral replication, whereas knockdown of PTBP1 significantly enhances viral replication. Mechanistically, using co-immunoprecipitation assays for protein interaction screening, we identified an interaction between PTBP1 and ZIKV non-structural protein NS1. Detailed studies demonstrated that PTBP1 bound and colocalized with NS1 to lead to the degradation of NS1 protein via a lysosomal pathway. Collectively, our findings unveil a novel mechanism underlying that ZIKV infection induces the expression of PTBP1 via the HIF-1 pathway, subsequently the accumulated PTBP1 binds to ZIKV NS1 protein to promote NS1 degradation, thereby effectively inhibiting viral replication. The study illustrates a distinct restricted cellular factor that regulates ZIKV replication, which provides a potential target for the control of the viral replication and pathogenesis during the ZIKV epidemic. ImportanceSince the outbreak of ZIKV infection among human in 2014, a Zika epidemic has caused Zika fever accompanied with fetal microcephaly, Guillain-Barre syndrome, and other neurological symptoms. Emerging evidence reveals that ZIKV infects astrocytes to specially induce the expression of polypyrimidine tract-binding protein 1 (PTBP1), one of hnRNPs members. However, the interplay between PTBP1 and ZIKV replication is highly concerned. Here, we uncover a distinct manner that ZIKV infection induces PTBP1 expression through the activation of hypoxia-inducible factor-1 (HIF-1) signal. Additionally, activation of HIF-1 signal hinders ZIKV replication relying on PTBP1 accumulation. Further investigations suggest that PTBP1 restrains ZIKV replication by interacting with ZIKV NS1 protein, thereby leading to the degradation of NS1 protein via a lysosomal pathway. Collectively, our findings illustrate a novel restricted cellular factor PTBP1 mediated by HIF-1 that regulates ZIKV replication, which provides a potential therapeutic target of the viral replication and pathogenesis against ZIKV pandemic.

microbiology↗

bioRxiv2024

DDA-BERT: leveraging transformer architecture pre-training for data-dependent acquisition mass spectrometry-based proteomics

In data-dependent acquisition mass spectrometry (DDA-MS)-based proteomics, machine learning based rescoring methods are often employed to integrate multiple scores measuring quality of peptide-spectrum matches (PSMs) from different aspects. Existing rescoring tools face limitations incurred by manual feature extraction, shallow machine learning models, and limited training data. Here, we introduce DDA-BERT, a transformer-based end-to-end deep learning model trained with 95 million human spectra for PSM rescoring. DDA-BERT demonstrates superior performance across various sample types, mass spectrometer platforms, trace sample proteomics, and multiple species proteome data. It consistently outperforms state-of-the-art methods of its kind for DDA-MS spectra analysis with up to 103.5% increased protein group identifications. For single cell proteomics, DDA-BERT identifies up to 85.6% more protein groups compared to existing tools. In addition, DDA-BERT can be effectively extended to proteome of non-human species. DDA-BERT offers a robust and scalable solution for enhancing PSM rescoring in proteomics.

bioinformatics↗