Biology subjects

Xin, J.

Publications and source records attributed to Xin, J..

18 recordsLinked to original sources

bioRxiv2026

CWF19L2 couples pre-mRNA alternative splicing with the maternal-to-zygotic transition to safeguard female fertility

The maternal-to-zygotic transition (MZT) requires precise spatiotemporal execution of pre-mRNA alternative splicing (AS), yet the core splicing machinery driving this developmental reprogramming remains incompletely understood. Here, we identify the CWF19-like protein 2 (CWF19L2) as an indispensable pre-mRNA AS regulator that safeguards against oocyte and early embryo competence defects (OECD). While murine germline-specific depletion of Cwf19l2 spares morphological folliculogenesis, oocyte maturation, or fertilization, it induces complete female sterility characterized by profound developmental arrest at the 2-cell stage. Mechanistically, maternal deficiency of CWF19L2 localized to nuclear speckles disrupts transcription-splicing-translation coupling, collapsing AS homeostasis during maternal reserves and zygotic genome activation. We further demonstrate that CWF19L2 orchestrates the pre-mRNA splicing network through directly binding to target transcripts and indirectly modulating via interacting with the core spliceosomal factor PRPF8. Importantly, exogenous Cwf19l2 mRNA partially rescues the embryonic arrest. Together, our findings establish CWF19L2 as an indispensable AS engine during the MZT, providing a mechanistic foundation for OECD and a novel molecular etiology for female infertility.

Cell Biology↗

bioRxiv2026

Cost-Effective Purification of Endotoxin-Free LIF, IL-2, and IL-33

We describe a cost-effective Escherichia coli (E. coli)-based platform for producing endotoxin-free cytokines. As a proof of concept, we applied this protocol to purify four representative human and mouse cytokines - mouse leukemia inhibitory factor (mLIF), human interleukin-2 (hIL-2), and human and mouse interleukin-33 (hIL-33 and mIL-33) - and demonstrated their bioactivity to be equivalent to commercial counterparts for direct use in stem cell culture and immune cell activation, both in vitro and in vivo. Reagent costs for producing these proteins are approximately 5%-10% of commercial list prices. This platform is readily adaptable to other costly cytokines and growth factors, providing a scalable and affordable approach to accelerate research in cell biology, tissue engineering, and biomanufacturing.

bioengineering↗

bioRxiv2025

c-Rel drives pancreatic cancer metastasis through Fibronectin-Integrin signaling-induced isolation stress resistance and EMT activation

Pancreatic ductal adenocarcinoma remains one of the deadliest malignancies, with limited treatment options and a high recurrence rate. Recurrence happens often with metastasis, for which cancer cells must adapt to isolation stress to successfully colonize distant organs. While the fibronectin-integrin axis has been implicated in this adaptation, its regulatory mechanisms require further elaboration. Here, we identify c-Rel as an oncogenic driver in PDAC, promoting epithelial-to-mesenchymal transition (EMT) plasticity, extracellular matrix (ECM) remodeling, and resistance to isolation stress. Mechanistically, c-Rel directly regulates fibronectin (Fn1) and CD61 (itgb3) transcription, enhancing cellular plasticity and survival under anchorage-independent conditions. Fibronectin is not essential for EMT, but its absence significantly impairs metastatic colonization, highlighting a tumor-autonomous role for FN1 in isolation stress adaptation. These findings establish c-Rel as a key regulator of PDAC metastasis by controlling circulating tumor cell (CTC) niche and survival, suggesting that targeting the c-Rel-fibronectin-integrin axis could provide new therapeutic strategies to mitigate disease progression and recurrence.

cancer biology↗

bioRxiv2024

Androgen receptor interactions provide insight into steroid mediated metabolic shifts in endocrine resistant breast cancer.

PurposeAromatase Inhibitors (AI) are standard therapy for hormone receptor positive breast cancers in post-menopausal patients. Disease recurrence is common and previous studies suggest that the altered steroid environment may be a driver of resistance. Using label-free mass-spectrometry we explored the unique androgen receptor (AR) interactome that supervenes in AI resistant breast cancer and the associated hyperandrogenic environment. Experimental DesignAR expression was evaluated in a primary breast cancer tissue-microarray (n=875) with nuclear and cytoplasmic localization quantified. Liquid-chromatography tandem mass-spectrometry (LC-MS/MS) analysis was utilized to identify proteins interacting with the AR in models of AI-resistance. Validation was carried out by co-immunoprecipitation and co-localisation studies. Live-cell imaging, Seahorse MitoStress Assays and flow cytometry were used to quantify changes in mitochondria and cell metabolism arising in models of AI-resistance. ResultsUtilising digital pathology we detected that abundant cytoplasmic AR protein was associated with poor survival only in the post-menopausal cohort, and most significantly, in the therapy-refractory Luminal B subtype (p=0.0085). Models of AI-resistance and androgen excess highlight diffuse AR localisation throughout the cytoplasm and nucleus accompanied by increased mitochondrial mass and membrane potential, and increased oxidative phosphorylation and glycolysis. Exploration of the AR protein interactome identified G3BP1, SLIRP, and IGFBP5 as AR protein partners which are associated with stress, adaptive metabolic response and estrogen receptor repression. ConclusionsThe findings of this study highlight the prognostic potential of cytoplasmic AR immunoreactivity in specific breast cancer subtypes and uncover novel extra-nuclear AR protein interactions that may mediate metabolic adaptations during the development of endocrine-resistance.

cancer biology↗

bioRxiv2023

Structural insights into abscisic acid exporter AtABCG25

Cellular hormone homeostasis is essential for the precise spatial and temporal signaling responses and plant fitness. Abscisic acid (ABA) plays pivotal roles in orchestrating various developmental and stress responses and confers fitness benefits over ecological and evolutionary timescales in terrestrial plants. Cellular ABA levels is regulated by complex processes including biosynthesis, catabolism, and transport. AtABCG25 is the first identified ABA exporter through genetic screen which affects diverse ABA responses. Resolving the structure basis of ABCG25 in ABA exporting is critical for further manipulating ABA homeostasis and plant fitness. We utilized cryo-electron microscopy to elucidate the structural dynamics of AtABCG25, and successfully characterized different states including apo AtABCG25, ABA-bound AtABCG25 and ATP-bound AtABCG25(E232Q). Notably, AtABCG25 forms a homodimer, featuring a deep, slit-like cavity in the transmembrane domain. The critical residues in the cavity where ABA binds are precisely characterized. Moreover, ATP binding triggers the closure of nucleotide-binding domains and conformational transitions in the transmembrane domains. Collectively, these findings provide valuable insights into the intricate substrate recognition and transport mechanisms of ABA exporter ABCG25, paving the way towards genetical manipulating of ABA homeostasis and plant fitness.

plant biology↗

bioRxiv2023

scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data

Single-cell technologies offer unprecedented opportunities to dissect gene regulatory mecha-nisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal datasets, we demonstrate scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome dataset we generated from differentiating mouse embryonic stem cells over time, we demonstrate scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.

bioinformatics↗

bioRxiv2023

Carotenoid assembly regulates quinone diffusion and the Roseiflexus castenholzii reaction center-light harvesting complex architecture

Carotenoid (Car) pigments perform central roles in photosynthesis-related light harvesting (LH), photoprotection, and assembly of functional pigment-protein complexes. However, the relationships between Car depletion in the LH, assembly of the prokaryotic reaction center (RC)-LH complex, and quinone exchange are not fully understood. Here, we analyzed native RC-LH (nRC-LH) and Car-depleted RC-LH (dRC-LH) complexes in Roseiflexus castenholzii, a chlorosome-less filamentous anoxygenic phototroph that forms the deepest branch of photosynthetic bacteria. Newly identified exterior Cars functioned with the bacteriochlorophyll B800 to block the proposed quinone channel between LH{beta} subunits in the nRC-LH, forming a sealed LH ring that was disrupted by transmembrane helices from cytochrome c and subunit X to allow quinone shuttling. dRC-LH lacked subunit X, leading to an exposed LH ring with a larger opening, which together accelerated the quinone exchange rate. We also assigned amino acid sequences of subunit X and two hypothetical proteins Y and Z that functioned in forming the quinone channel and stabilizing the RC-LH interactions. This study reveals the structural basis by which Cars assembly regulates the architecture and quinone exchange of bacterial RC-LH complexes. These findings mark an important step forward in understanding the evolution and diversity of prokaryotic photosynthetic apparatus.

biochemistry↗

bioRxiv2023

Retrieved Sequence Augmentation for Protein Representation Learning

The advancement of protein representation learning has been significantly influenced by the remarkable progress in language models. Accordingly, protein language models perform inference from individual sequences, thereby limiting their capacity to incorporate evolutionary knowledge present in sequence variations. Existing solutions, which rely on Multiple Sequence Alignments (MSA), suffer from substantial computational overhead and suboptimal generalization performance for de novo proteins. In light of these problems, we introduce a novel paradigm called Retrieved Sequence Augmentation (RSA) that enhances protein representation learning without necessitating additional alignment or preprocessing. RSA associates query protein sequences with a collection of structurally or functionally similar sequences in the database and integrates them for subsequent predictions. We demonstrate that protein language models benefit from retrieval enhancement in both structural and property prediction tasks, achieving a 5% improvement over MSA Transformer on average while being 373 times faster. Furthermore, our model exhibits superior transferability to new protein domains and outperforms MSA Transformer in de novo protein prediction. This study fills a much-encountered gap in protein prediction and brings us a step closer to demystifying the domain knowledge needed to understand protein sequences. Code is available at https://github.com/HKUNLP/RSA.

bioinformatics↗

bioRxiv2022

Developing a standardized but extendable framework to increase the findability of infectious disease datasets

Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

bioinformatics↗

bioRxiv2022

Heritability enrichment in context-specific regulatory networks improves phenotype-relevant tissue identification

Systems genetics holds the promise to decipher complex traits by interpreting their associated SNPs through gene regulatory networks derived from comprehensive multi-omics data of cell types, tissues, and organs. Here, we propose SpecVar to integrate paired chromatin accessibility and gene expression data into context-specific regulatory network atlas and regulatory categories, conduct heritability enrichment analysis with GWAS summary statistics, identify relevant tissues, and depict shared heritability and regulations by relevance correlation. Our method improves power upon existing approaches by associating SNPs with context-specific regulatory elements to assess heritability enrichments and by explicitly prioritizing gene regulations underlying relevant tissues. Experiments on GWAS of six phenotypes show that SpecVar can improve heritability enrichment, accurately detect relevant tissues, and reveal causal regulations. Furthermore, SpecVar correlates the relevance patterns for pairs of phenotypes and better reveals shared heritability and regulations of phenotypes than existing methods. Studying GWAS of 206 phenotypes in UK-Biobank demonstrates that SpecVar leverages the context-specific regulatory network atlas to prioritize phenotypes relevant tissues and shared heritability for biological and therapeutic insights. SpecVar provides a powerful way to interpret SNPs via context-specific regulatory networks and is available at https://github.com/AMSSwanglab/SpecVar.

genetics↗

bioRxiv2021

Dopamine and GPCR-mediated modulation of DN1 clock neurons gates the circadian timing of sleep

The metronome-like circadian regulation of sleep timing must still adapt to an uncertain environment. Recent studies in Drosophila indicate that neuromodulation not only plays a key role in clock neuron synchronization but also affects interactions between the clock network and brain sleep centers. We show here that the targets of neuromodulators, G-Protein Coupled Receptors (GPCRs), are highly enriched in the fly brain circadian clock network. Single cell sequencing indicates that they are not only differentially expressed but also define clock neuron identity. We generated a comprehensive guide library to mutagenize individual GPCRs in specific neurons and verified the strategy with a targeted sequencing approach. Combined with a behavioral screen, the mutagenesis strategy revealed a novel role of dopamine in sleep regulation by identifying two dopamine receptors and a clock neuron subpopulation that gate the timing of sleep.

neuroscience↗

bioRxiv2021

BioThings SDK: a toolkit for building high-performance data APIs in biomedical research

SummaryTo meet the increased need of making biomedical resources more accessible and reusable, Web APIs or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info, and MyChem.info for integrating annotations on genes, variants, and chemical compounds, respectively. These APIs are used by both individual researchers and application developers to simplify the process of annotation retrieval and identifier mapping. Here, we describe the BioThings Software Development Kit (SDK), a generalizable and reusable toolkit for integrating data from multiple disparate data sources and creating high-performance APIs. This toolkit allows users to easily create their own BioThings APIs for any data type of interest to them, as well as keep APIs up-to-date with their underlying data sources. Availability and implementationThe BioThings SDK is built in Python and released via PyPI (https://pypi.org/project/biothings/). Its source code is hosted at its github repository (https://github.com/biothings/biothings.api).

bioinformatics↗

bioRxiv2021

Schema Playground: A tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data

BackgroundBiomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging schema.org could benefit biomedical research resource providers, but it can be challenging to apply schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize schema.org or other biomedical schema projects. ResultsOur browser-based tool includes features which can help address many of the barriers towards schema.org-compliance such as: The ability to easily browse for relevant schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema--a large multi-class schema for harmonizing various COVID-19 related resources. ConclusionsWe have created a browser-based tool to empower biomedical research resource providers to leverage schema.org classes to make their research outputs more FAIR.

bioinformatics↗

bioRxiv2020

Analysis of the Functional Differentiation Sites in Vertebrate Neuronal Nicotinic Acetylcholine Receptor Subunits

The nicotinic acetylcholine receptors (nAChR) belong to a large family of ligand-gated ion channels and are involved in the mediation of fast synaptic transmission. Each receptor is made up of five subunits that arrange symmetrically around a central pore. Despite the similarity in their sequences and structures, the properties of these subunits vary significantly. Thus, identifying the function-related sites specific to each subunit is essential for understanding the characteristics of the subunits and the receptors assembled by them. In this study, we examined the sequence features of the nine neuronal nAChRs subunits from twelve representative vertebrate species. Analysis revealed that all the subunits were subject to strong purifying selection in evolution, and each was under a unique pattern of selection pressures. At the same time, the functional constraints were not uniform within each subunit, with different domains in the molecule being subject to different selection pressures. Via evolutionary analyses, we also detected potential positive selection events in the subunits or subunit clusters, and identified the sites might be associated with the function specificity of each subunit. Furthermore, positive selection at some domains might contributed to the diversity of subunit function; for example, the {beta}9 strand might be related to the agonist specificity of subunit in heteromeric receptor and {beta}4-{beta}5 linker could be involved in Ca2+ permeability. Subunits 7, 4 and {beta}2 subunits possess a strong adaptability in vertebrates. Our results highlighted the importance of tracking functional differentiation in protein sequence underlying functional properties of nAChRs. In summary, our work may provide clues on understanding the diversity and the function specificity of the nAChR subunits, as well as the receptors co-assembled by them.

evolutionary biology↗

bioRxiv2020

Molecularly Targeted Magnetic Resonance Imaging and Spectroscopy

Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) have tremendous utility in many fields, such as clinical diagnosis, medical research and brain science. MRI provides high resolution anatomic images of tissues/organs, and MRS provides functional molecular information related to specific regions of tissues/organs. However, it is often difficult for conventional MRI/MRS to selectively image/probe a specific metabolite molecule other than water and fat. This greatly limits study of the molecular mechanisms underlying metabolism and disease. Herein, we report a novel method for obtaining an exact molecularly targeted MRI and MRS. This method uses the nuclear spin singlet state to select the signals from a specific molecule. Several endogenous molecules in living organism such as N-acetylaspartate and dopamine have been exemplarily imaged and probed as the targeted molecules in the MRI and MRS experiments, demonstrating the unique molecular selectivity of the developed method. Endogenous-molecule-targeted MRI and MRS can be achieved by using the new pulse sequences O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/026252v2_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@483ca2org.highwire.dtl.DTLVardef@84d4c0org.highwire.dtl.DTLVardef@abca24org.highwire.dtl.DTLVardef@6423ae_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2019

Explaining the genetic causality for complex diseases via deep association kernel learning

The genetic effect explains the causality from genetic mutation to the development of complex diseases. Existing genome-wide association study (GWAS) approaches are always built under a linear assumption, restricting their generalization in dissecting complicated causality such as the recessive genetic effect. Therefore, a sophisticated and general GWAS model that can work with different types of genetic effects is highly desired. Here, we introduce a Deep Association Kernel learning (DAK) model to enable automatic causal genotype encoding for GWAS at pathway level. DAK can detect both common and rare variants with complicated genetic effects that existing approaches fail. When applied to real-world GWAS data, our approach discovered potential casual pathways that could be explained by alternative biological studies.

bioinformatics↗

bioRxiv2019

Neuron-specific knockouts indicate the importance of network communication to Drosophila rhythmicity

Animal circadian rhythms persist in constant darkness and are driven by intracellular transcription-translation feedback loops. Although these cellular oscillators communicate, isolated mammalian cellular clocks continue to tick away in darkness without intercellular communication. To investigate these issues in Drosophila, we assayed behavior as well as molecular rhythms within individual brain clock neurons while blocking communication within the ca. 150 neuron clock network. We also generated CRISPR-mediated neuron-specific circadian clock knockouts. The results point to two key clock neuron groups: loss of the clock within both regions but neither one alone has a strong behavioral phenotype in darkness; communication between these regions also contributes to circadian period determination. Under these dark conditions, the clock within one region persists without network communication. The clock within the famous PDF-expressing s-LNv neurons however was strongly dependent on network communication, likely because clock gene expression within these vulnerable sLNvs depends on neuronal firing or light.

neuroscience↗

bioRxiv2017

Cross-linking BioThings APIs through JSON-LD to facilitate knowledge exploration

BackgroundApplication Programming Interfaces (APIs) are now widely used to distribute biological data. And many popular biological APIs developed by many different research teams have adopted Javascript Object Notation (JSON) as their primary data format. While usage of a common data format offers significant advantages, that alone is not sufficient for rich integrative queries across APIs.\n\nResultsHere, we have implemented JSON for Linking Data (JSON-LD) technology on the BioThings APIs that we have developed, MyGene.info, MyVariant.info and MyChem.info. JSON-LD provides a standard way to add semantic context to the existing JSON data structure, for the purpose of enhancing the interoperability between APIs. We demonstrated several use cases that were facilitated by semantic annotations using JSON-LD, including simpler and more precise query capabilities as well as API cross-linking.\n\nConclusionsWe believe that this pattern offers a generalizable solution for interoperability of APIs in the life sciences.

bioinformatics↗