Biology subjects

Chao, H.

Publications and source records attributed to Chao, H..

At least 19 recordsLinked to original sources

bioRxiv2026

A Brugada-related KCNT1 mutation unveils its conductance-independent activation of store-operated Ca 2+ entry

BackgroundPotassium sodium-activated channel subfamily T member 1 (KCNT1) is a Na+-activated K+ channel, associated with epilepsy and cardiac diseases. Besides K+ conductance, KCNT1 is also involved in Ca2+ handling. KCNT1:R1106Q was identified in a Brugada Syndrome (BrS) patient; however, its pathological characteristics regarding either K+ or Ca2+ homeostasis remain to be fully elucidated. MethodsFura-2-loaded HEK293T cells were used for intracellular Ca2+ investigations, and whole-cell patch-clamp technique were used as complementary tests. Stromal interaction molecule 1 (STIM1) aggregation and endoplasmic reticulum (ER)-plasma membrane (PM) junctions in HeLa cells were visualized using spinning disc confocal microscope. Multielectrode array (MEA) assays were utilized to assess the field potential duration (FPD) and spontaneous beating rate of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). ResultsKCNT1 overexpression increased SOCE, which was further upregulated by the KCNT1R1106Q mutant. Furthermore, KCNT1 upregulated ER Ca2+ release and was found to localize at ER-PM junctions. The ER Ca2+ dynamics in KCNT1R1106-overexpressing cells was disrupted, while its SOCE remained intact. The KCNT1 cytoplasmic tail alone sufficiently modulated Ca2+ homeostasis. Given that KCNT1 possesses prominent charge-concentrated segments within its cytoplasmic domain, we substituted charged amino acids in either the 740-DDE-742 or 1114-RRLSR-1118 motifs with alanine; these substitutions abolished the KCNT1-mediated increases in ER Ca2+ release and ER-PM contact formation. MEA recordings of hiPSC-CMs revealed that the overexpression of KCNT1 shortened the FPD and accelerated the cardiomyocyte beating rate compared to baseline. However, the magnitude of beating rate acceleration induced by KCNT1R1106Q was significantly attenuated compared to that of KCNT1WT. ConclusionsOur findings indicate that, independent of KCNT1-mediated ion conductance, the charged motifs located at both ends of the KCNT1 cytoplasmic tail serve as structural anchors to facilitate ER-PM contact formation. This non-conducting role endows KCNT1 with a K+ current-independent mechanism to modulate intracellular Ca2+ homeostasis and cardiomyocyte physiology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/731813v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@104e234org.highwire.dtl.DTLVardef@19eceb3org.highwire.dtl.DTLVardef@1148512org.highwire.dtl.DTLVardef@2c8118_HPS_FORMAT_FIGEXP M_FIG C_FIG Novelty and SignificanceO_ST_ABSWhat is known?C_ST_ABSO_LIKCNT1 is a Na+-activated K+ channel, and mutations within this gene are often associated with epilepsy and epilepsy-related cardiac diseases. C_LIO_LIBesides functioning as a rectifier, KCNT1 is implicated in cellular Ca2+ handling, such as regulating Ca2+ oscillations in rat cortical neurons. C_LIO_LIKCNT1:R1106Q missense mutation has been identified in a patient with Brugada Syndrome (BrS); however, its pathophysiological characteristics and underlying mechanisms remain uncharacterized. C_LI What New Information Does This Article Contribute?O_LIKCNT1 overexpression upregulates both ER Ca2+ release and store-operated Ca2+ entry (SOCE). KCNT1R1106Q further increased SOCE intensity, however, its increase in ER Ca2+ release and [Ca2+]ER were attenuated. C_LIO_LIThe cytoplasmic tail of KCNT1 alone is suNicient to modulate Ca2+ closely mimicking the eNects of full-length KCNT1. C_LIO_LIThe charged clusters distributed along the KCNT1 cytoplasmic tail facilitate ER-PM contact. Alanine substitutions abolish the enhancements in ER Ca2+ release and ER-PM contact formation, while SOCE modulation remains intact. C_LIO_LIThe KCNT1 cytoplasmic tail alone shortens the field potential duration (FPD) and accelerates the spontaneous beating rate in hiPSC-CMs. However, the magnitude of beating rate acceleration induced by KCNT1R1106Q is significantly attenuated compared to KCNT1WT. C_LI This study uncovers a novel, conductance-independent role for the KCNT1 channel in structural organization, demonstrating that the charged motifs on its cytoplasmic tail serve as physical anchors facilitating ER-PM junctions. This structural mechanism regulates intracellular Ca2+ homeostasis and subsequently alters cardiomyocyte electrophysiology. By decoupling KCNT1s structural impact from its ion-conducting function, these findings provide new mechanistic insights into how specific KCNT1 variants, such as the BrS-associated KCNT1:R1106Q mutation, may contribute to arrhythmogenesis through imbalanced Ca2+ handling rather than classical K+ current alterations.

Molecular Biology↗

bioRxiv2026

Multi-Omics Characterization of Human Molecular Responses to Spaceflight Across Two Independent Missions

Human spaceflight has historically been led by government agencies, but the emergence of commercial organizations is enabling broader participation and new research opportunities. In this study, we present a comprehensive molecular characterization of early human responses to spaceflight, leveraging multi-omics data across the first three weeks of two commercial missions. Biospecimens from six individuals, four from the Axiom 2 mission (10 days) and two from Axiom 3 (21 days), were analyzed using single-cell and bulk RNA sequencing, alongside proteomic profiling. Individual and integrative analyses of these datasets reveal systemic changes in cell types, transcripts, and proteins related to immune regulation, osteoclast differentiation, NF-{kappa}B signaling, and blood homeostasis pathways. Importantly, several of the detected pathways align with physiological patterns observed in longer-duration missions. This work establishes a foundational resource for understanding early adaptation to spaceflight at the cellular and molecular levels, providing insights to reduce future space-travel health risks. HighlightsO_LIFirst integrated multi-omics analysis using single-cell, bulk RNA sequencing and proteomic profiling of early human spaceflight responses across two commercial missions (Ax-2 and Ax-3). C_LIO_LIDistinct PBMC clustering was observed across Ax-2 and Ax-3, and post-flight samples. It showed fewer monocytes, dendritic cells, and megakaryocytes with increased naive CD4 and cytotoxic T cells. C_LIO_LIMulti-omics integration identifies shared biological signatures, including osteoclast differentiation, metabolic stress, and coagulation changes. C_LIO_LIThese findings lay the foundation for developing countermeasures to protect immune, skeletal, and vascular health during spaceflight. C_LI

molecular biology↗

bioRxiv2026

Hemodynamic phenotypes linked to high-altitude subclinical organ damage

BackgroundChronic exposure to high-altitude hypoxia imposes sustained cardiovascular stress, yet hemodynamic adaptation among healthy high-altitude dwellers is heterogeneous and remains poorly characterized. This study aimed to identify distinct hemodynamic phenotypes in a healthy high-altitude population using unsupervised machine learning and to evaluate their association with multi-system subclinical target organ damage. MethodsThis cross-sectional study enrolled 694 healthy adults permanently residing at [≥]3300 m on the Qinghai-Tibet Plateau. Unsupervised K-means clustering was performed on nine hemodynamic variables, including peripheral and central blood pressures, augmentation index (AIx), pulse pressure amplification ratio (pPP/cPP), and systolic pressure amplification (pSBP-cSBP). Differences across phenotypes in carotid intima-media thickness (IMT), estimated glomerular filtration rate (eGFR), left ventricular mass index (LVMI), and pulse wave velocity (PWV) were assessed using one-way ANOVA with Bonferroni-corrected post-hoc tests. ResultsThree distinct hemodynamic phenotypes were successfully identified. The C2 (Balanced Adaptation) phenotype (n = 245) demonstrated the most favorable hemodynamic profile, characterized by the lowest blood pressure and augmentation index (AIx) values, along with the highest peripheral-to-central pulse pressure ratio (pPP/cPP). The C1 (Vascular Stress) phenotype (n = 267) presented with normal peripheral systolic blood pressure (125.9 {+/-} 11.3 mmHg) but exhibited markedly elevated wave reflection indices, including the highest heart rate-adjusted augmentation index (AIx@HR75: 31.9 {+/-} 9.7%) and the lowest pPP/cPP ratio (1.29 {+/-} 0.08). The C3 (High-Load Decompensation) phenotype (n = 182) displayed significantly elevated blood pressures and the greatest overall hemodynamic load. Regarding target organ damage, a clear gradient was observed across the three phenotypes. The C3 phenotype showed the highest carotid intima-media thickness (IMT: 1.162 {+/-} 0.23 mm) and left ventricular mass index (LVMI: 69.18 {+/-} 40.73 g/m{superscript 2}). Conversely, the C2 phenotype exhibited the highest estimated glomerular filtration rate (eGFR: 97.38 {+/-} 16.38 mL/min/1.73m{superscript 2}) and the lowest IMT (0.994 {+/-} 0.26 mm). The C1 phenotype consistently displayed intermediate values for all organ damage indicators. After Bonferroni correction, all pairwise comparisons for LVMI and pulse wave velocity (PWV) reached statistical significance (all P < 0.05). ConclusionsHealthy high-altitude individuals manifest three distinct hemodynamic phenotypes arrayed along a cardiovascular risk continuum. The novel Vascular Stress (C1) phenotype represents a "masked" high-risk state characterized by normal peripheral blood pressure but elevated arterial stiffness and wave reflection, challenging sole reliance on brachial pressure for risk assessment. This phenotype-based stratification provides a framework for precision prevention and early intervention in high-altitude populations.

physiology↗

bioRxiv2025

Benchmarking of duplex sequencing approaches to reveal somatic mutation landscapes

Detecting somatic mutations in normal tissues is challenging due to sequencing errors and the low allele fractions of post-zygotic variants. Duplex sequencing greatly reduces errors and can detect mutations at any allele fraction, but systematic, cross-platform comparisons are lacking. We present a comprehensive benchmarking of six duplex sequencing technologies used by the SMaHT Network: CODEC, CompDuplex-seq, HiDEF-seq, NanoSeq, ppmSeq, and VISTA-seq. We evaluated their performance using cord blood DNA, a tumor-normal cell line mixture, and homogenates from six human tissues. Each method shows distinct profiles in genomic footprint, sensitivity, and cost. Despite differences in library construction and sequencing platforms, estimates of mutation rates and mutational signatures are highly concordant. Integration with ultra-deep whole-genome sequencing shows that duplex approaches sensitively capture mutations and signatures beyond embryonic or clonally expanded variants. These results provide a foundation for selecting duplex methods and interpreting their data, enabling scalable single-molecule analyses of somatic mutation landscapes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/692823v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@123b221org.highwire.dtl.DTLVardef@83ba0aorg.highwire.dtl.DTLVardef@2b0ab0org.highwire.dtl.DTLVardef@1cae35e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Expanding the Genome in a Bottle Truth Set: Detection and Validation of Novel Low-frequency Variants Using High-accuracy NanoSeq

HighlightsO_LINanoSeq-MBN achieves near-genome, Poisson-like coverage with minimal trinucleotide bias. C_LIO_LIExpands the GIAB truth set by up to 160k de novo variants. C_LIO_LIAdds a somatic layer to GIAB, enabling benchmarking and calibration of rare variants. C_LIO_LIHigh-CADD exonic and splice variants highlight value for surveillance and clinical triage. C_LI Somatic mutations record tissue molecular history and inform risk, prognosis, and therapy, yet their variant allele fractions often fall below the reliable detection limit of conventional short-read sequencing. In contrast, duplex sequencing technology featured by NanoSeq applies the principle of single molecule detection and thereby overcomes the limitation. However, the original NanoSeq protocol relies on the restriction enzyme-based genome fragmentation, which constrained its genome coverage to 30-40%. To enable whole-genome discovery with duplex-level fidelity, we pursued two complementary approaches to optimize the NanoSeq protocol: (i) a restriction-enzyme strategy densifies accessible sites using orthogonal 4-bp cutters; and (ii) a workflow using sonication followed by mung bean nuclease with T4 polynucleotide kinase, Klenow fragment and dATP/ddBTP mixture (NanoSeq-MBN) to blunt and repair/A-tailing DNA, while minimizing repair artifacts. We systematically benchmarked their performance using Genome in a Bottle (GIAB) gold-standard sample mixtures. As a result, NanoSeq-MBN achieved near genome-wide, Poissonlike coverage with minimal trinucleotide-context bias and ultra-high accuracy. Beyond variants already present in the GIAB truth set, NanoSeq-MBN identified approximately 120,000-160,000 de novo mutations per sample missing in the truth set, Notably, over 98% had orthogonal support in reanalyzed GIAB bulk Illumina HiSeq libraries. These novel variants extended GIAB from germline benchmarking to rare-variant discovery and calibration of subclonal detection. Functional annotation revealed enrichment of high Combined Annotation Dependent Depletion (CADD) scores mutations in exonic and splice-related regions. Variants intersecting ClinVar entries and OMIM genes highlighted potential for surveillance and clinical triage. Collectively, these results add a somatic layer to GIAB, enabling calibration of burdens and mutational signatures in lymphoblastoid lines and provide reference material for rare-variant assays. The NanoSeq-MBN workflow offers a path to whole-genome, high-fidelity discovery of ultra-rare somatic variation with relevance to clinical assay validation.

molecular biology↗

bioRxiv2025

Pre-Sequencing Assessment of RNA-Seq Library Quality Using Real-Time qPCR

RNA sequencing (RNA-Seq) is an essential sequencing assay for studying transcriptome profiling. Ribosomal RNA (rRNA) comprises more than 80 - 90% of total cellular RNA, efficient rRNA removal is essential for accurately capturing the transcriptome, particularly to sequence low-abundance mRNAs. Inefficient rRNA removal during library preparation can result from variations in sample quality, preparation methods and handling. Estimating rRNA content in RNA-Seq libraries pre-sequencing is therefore challenging due to the absence of a reliable and cost-effective assessment method. This study addresses the issue by introducing a scalable qPCR-based assay targeting 18S rRNA to evaluate rRNA depletion efficiency pre-sequencing. qPCR efficiency was optimized using serial dilutions of Universal Human Reference (UHR) control and Ct thresholds were established using pilot data from 644 libraries. Following this optimization, analysis of 1,748 Total RNA-Seq libraries and 445 Poly A+ two widely used RNA-Seq library methods, demonstrated a strong correlation between 18S rRNA qPCR results and post-sequencing rRNA rates. This assay was also used to evaluate the performance of Oligo dT beads from four different vendors to enrich mRNA. This 18S rRNA qPCR assay is a cost-effective, scalable approach for reliably predicting rRNA read percentage in RNA-Seq libraries pre-sequencing. Method SummaryThe 18S rRNA-specific qPCR assay is a cost-effective method for evaluating rRNA depletion efficiency in RNA-Seq libraries prior to sequencing by targeting the 18S ribosomal RNA. qPCR efficiency was optimized, and Ct thresholds were set from pilot data and validated across 1,748 Total RNA and 445 Poly A+ RNA-Seq libraries. A Ct threshold of [≥]16 for Total RNA and Ct 13-14 or greater for Poly A+ libraries demonstrates a strong correlation between qPCR results and post-sequencing rRNA read percentages. The assay enables early identification of poorly depleted samples, reducing unnecessary sequencing costs. Additionally, the method was employed to benchmark oligo-dT beads from four vendors, showing its utility in evaluating RNA-seq library preparation kits. This scalable approach supports quality control in both research and high-throughput sequencing environments.

molecular biology↗

bioRxiv2025

CellReasoner: A reasoning-enhanced large language model for cell type annotation

We present CellReasoner, a lightweight, open-source large language model (LLM) tailored for single-cell type annotation. We introduced a compact training strategy that activates the reasoning capabilities of 7B-parameter LLMs using only 380 high-quality chain-of-thought exemplars. CellReasoner directly maps cell-level gene expression profiles to cell type labels, exhibiting robust zero- and few-shot generalization. The model further demonstrates expert-level, marker-by-marker reasoning, enabling structured, interpretable annotations and offering a practical solution for intelligent single-cell analysis.

bioinformatics↗

bioRxiv2025

Cross-Species Prediction of Histone Modifications in Plants via Deep Learning

The regulation of gene expression in plants is governed by complex interactions between cis-regulatory elements and epigenetic modifications such as histone marks. While deep learning models have achieved success in predicting regulatory features from DNA sequence, their cross-species generalizability in plants remains largely unexplored. In this study, we systematically evaluated the ability of deep learning models to predict histone modifications across plant species using a multi-stage framework based on the Sei architecture. We trained species-specific models for Arabidopsis (A. thaliana), rice (O. sativa), and maize (Z. mays), achieving high within-species predictive performance (AUROC > 0.94) and strong agreement between predictions and experimental ChIP-seq profiles. However, cross-species predictions showed reduced performance with increasing phylogenetic distance, highlighting limited model transferability between monocots and dicots. To improve generalization, we built family-level models by training on multiple species across the Poaceae and Brassicaceae families. These models demonstrated robust predictive power in completely unprofiled species--those entirely unused in training set--highlighting the models adaptability to novel plant genomes based solely on conserved regulatory syntax. In contrast, cross-family models produced inconsistent results, with reliable performance only in species sharing conserved regulatory features. Lastly, we developed an easy-to-use pipeline that predicts genome-wide chromatin signals directly from DNA sequences. Our findings demonstrate that phylogenetically informed model training significantly improves cross-species epigenomic prediction, offering a scalable computational strategy for functional annotation in non-model and agriculturally important plants.

bioinformatics↗

bioRxiv2025

Improved Prediction of Bacterial Type VI Secretion Effector Proteins Using an Integrated Convolutional Neural Network Model Combining N-terminal Signal Sequences, Evolutionary Information and Pre-Trained Protein Language Features

Type VI secretion system effectors (T6SEs) are crucial for bacterial pathogenicity, making their accurate identification essential for understanding bacterial virulence mechanisms. This study analyzed the differences in amino acid composition of N-terminal signal sequences between T6SEs and non-T6SEs, uncovering distinct positional amino acid preferences in T6SEs. Using a combination of unsupervised and supervised analysis, we evaluated feature encoding methods and developed T6CNN, an ensemble model that integrates N-terminal signal sequences, evolutionary information, and pre-trained protein language features for T6SE prediction. T6CNN demonstrated outstanding performance in independent testing, outperforming existing tools with a 7.9% accuracy increase (to 0.953), a 13.2% sensitivity improvement (to 0.964), and a 6.6% specificity enhancement (to 0.951). The T6CNN model offers a reliable and accurate solution for T6SE prediction, with significant potential to advance research on bacterial pathogenicity. ImportanceThis study introduces T6CNN, a new computational model for identifying Type VI secretion system effectors used by harmful bacteria. By analyzing early protein sequences, T6CNN uncovers unique features that reliably distinguish effector proteins. Integrating evolutionary data and pre-trained protein language features, the model outperforms existing methods in accuracy, sensitivity, and specificity. This enhanced prediction tool deepens our understanding of bacterial infection mechanisms and offers researchers a valuable resource for pinpointing key virulence factors. Ultimately, T6CNN may help drive the development of more targeted antibacterial treatments and strategies to combat bacterial diseases.

bioinformatics↗

bioRxiv2025

CK2 directly controls CARD9 protein homeostasis

CARD9 is an attractive target for therapeutic intervention because the human genetic data provides strong evidence for the causal role of CARD9 in both protection and susceptibility to autoimmune disease. Expression quantitative trait loci (eQTLs) link higher CARD9 expression to increased disease risk and lower CARD9 expression to protection. Additionally, a rare allele variant leading to a C-terminal truncation of CARD9 (CARD9{Delta}11) and subsequent loss-of-function is also protective for inflammatory bowel disease (IBD). The mechanism of CARD9-driven inflammation through scaffold assembly with BCL10 and MALT1 (CBM complex) suggests a durable inflammatory signal driven by increasing levels of CARD9. Therefore, CARD9 depletion is a desired therapeutic strategy for drug discovery, yet a difficult one due to the nature of CARD9 as an adaptor protein target and the limited number of chemical tools available to engage it. Here, we uncover through a protein homeostasis screen that casein kinase 2 (CK2/CSNK2) inhibition leads to cellular CARD9 depletion. Following up with arrayed CRISPR screening, we identify key casein kinase isoforms/subunits responsible for CARD9 depletion. We find that CK2 directly binds to CARD9 and phosphorylates S424/S425 as well as S483/S484. Orthosteric CK2 inhibition prevents CK2 binding to CARD9 and leads to CARD9 destabilization. We show that the interaction between CK2 and CARD9{Delta}11 is significantly attenuated and not sensitive to CK2-mediated protein stabilization. The CK2-driven CARD9 depletion mechanism is preserved outside of immortalized cell lines and conserved between primary, differentiated mouse and human dendritic cells. Finally, we demonstrate therapeutic proof of concept in vivo using CK2 inhibition to deplete CARD9 in murine whole blood, peritoneum, and colon. Our study expands the scope of cellular consequences dealt by kinase inhibition, offers an unconventional approach for engaging a therapeutically intractable target, and identifies a novel mechanism that could contribute to disease protection conferred by the CARD9{Delta}11 allele.

immunology↗

bioRxiv2024

SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research

Soybean is a globally important crop for food, feed, oil, and nitrogen fixation. A variety of multi-omics research has been carried out generating datasets ranging from genotype to phenotype. To utilise this data, a soybean multi-omics database that has broad data coverage and comprehensive data analysis tools would be of value for basic and applied research. We present the soybean omics database (SoyOD), which integrates significant new datasets with existing public datasets for the most comprehensive collection of soybean multi-omics information. Compared to the existing soybean database, SoyOD incorporates an extensive collection of novel data derived from the deep-sequencing of 984 germplasms, 162 novel transcriptome datasets from seeds at different developmental stages, 53 phenotypic datasets, and over 2500 phenotypic images. In addition, SoyOD integrates existing data resources, including 59 assembled genomes, genetic variation data from 3904 soybean accessions, 225 sets of phenotypic data, and 1097 transcriptomic sequences covering 507 different tissues and treatment conditions. SoyOD is a novel tool, as it can be used to mine and analyze candidate genes for important agronomic traits, as shown in a case study on plant height. Additionally, powerful analytical and easy-to-use toolkits enable users to easily access the available multi-omics datasets, and to rapidly search genotypic and phenotypic data in a particular germplasm. The novelty, comprehensiveness, and user-friendly features of SoyOD make it a valuable resource for soybean molecular breeding and biological research. SoyOD is publicly accessible at https://bis.zju.edu.cn/soyod.

plant biology↗

bioRxiv2024

Complete Genomic Characterization of Global Pathogens, Respiratory Syncytial Virus (RSV), and Human Norovirus (HuNoV) Using Probe-based Capture Enrichment.

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections in children worldwide, while human noroviruses (HuNoV) are a leading cause of epidemic and sporadic acute gastroenteritis. Generating full-length genome sequences for these viruses is crucial for understanding viral diversity and tracking emerging variants. However, obtaining high-quality sequencing data is often challenging due to viral strain variability, quality, and low titers. Here, we present a set of comprehensive oligonucleotide probe sets designed from 1,570 RSV and 1,376 HuNoV isolate sequences in GenBank. Using these probe sets and a capture enrichment sequencing workflow, 85 RSV positive nasal swab samples and 55 (49 stool and six human intestinal enteroids) HuNoV positive samples encompassing major subtypes and genotypes were characterized. The Ct values of these samples ranged from 17.0-29.9 for RSV, and from 20.2-34.8 for HuNoV, with some HuNoV having below the detection limit. The mean percentage of post-processing reads mapped to viral genomes was 85.1% for RSV and 40.8% for HuNoV post-capture, compared to 0.08% and 1.15% in pre-capture libraries, respectively. Full-length genomes were>99% complete in all RSV positive samples and >96% complete in 47/55 HuNoV positive samples--a significant improvement over genome recovery from pre-capture libraries. RSV transcriptome (subgenomic mRNAs) sequences were also characterized from this data. Probe-based capture enrichment offers a comprehensive approach for RSV and HuNoV genome sequencing and monitoring emerging variants. IMPORTANCERespiratory syncytial virus (RSV) and human noroviruses (HuNoV) are NIAID category C and category B priority pathogens, respectively, that inflict significant health consequences on children, adults, immunocompromised patients, and the elderly. Due to the high strain diversity of RSV and HuNoV genomes, obtaining complete genomes to monitor viral evolution and pathogenesis is challenging. In this paper, we present the design, optimization, and benchmarking of a comprehensive oligonucleotide target capture method for these pathogens. All 85 RSV samples and 49/55 HuNoV samples were patient-derived with six human intestinal enteroids. The methodology described here results has a higher success rate in obtaining full-length RSV and HuNoV genomes, enhancing the efficiency of studying these viruses and mutations directly from patient-derived samples.

molecular biology↗

bioRxiv2024

iSeq: An integrated tool to fetch public sequencing data

High-throughput sequencing technologies (Next Generation Sequencing; NGS) are increasingly utilized by researchers to tackle a diverse array of biological inquiries. Leveraging the remarkable scale and efficiency of modern sequencing, significant advancements are made across various fields, spanning from genome analysis to the intricate dynamics of protein-nucleic acid interactions. Recognizing that NGS data harbors rich biological information, the International Nucleotide Sequence Database Collaboration (INSDC) was established nearly 40 years ago to collect and disseminate public nucleotide sequence data and associated metadata. The National Genomics Data Center (NGDC) has also provided open access to vast amounts of raw sequence data. These databases have greatly enhanced the capacity for reanalyzing NGS data. In recent years, amid the rise of large language models, biological sequences and data have emerged as inputs for training models to address biological challenges. However, methods for programmatically accessing this public sequencing data remain limited. To address this gap, we have developed iSeq, an integrated tool that allows for quick and straightforward retrieval of metadata and NGS data via the command-line interface. iSeq is currently the only tool that supports simultaneous retrieval from multiple databases (GSA, SRA, ENA, DDBJ, and GEO). Additionally, iSeq supports a wide range of accession formats as input and features parallel downloads, multi-threaded processes, and FASTQ file merging. It is freely available on Bioconda (https://anaconda.org/bioconda/iseq) and GitHub (https://github.com/BioOmics/iSeq). HighlightsO_LIiSeq supports multiple databases for accessing a wide range of raw sequencing data and metadata. C_LIO_LIiSeq supports at least 25 different accession formats as input. C_LIO_LIiSeq supports parallel downloads, multi-threaded processes, FASTQ file merging, and integrity verification. C_LI

bioinformatics↗

bioRxiv2023

PDB NextGen Archive: Centralising Access to Integrated Annotations and Enriched Structural Information by the Worldwide Protein Data Bank

The Protein Data Bank (PDB) archive is the global repository for public-domain 3D biomolecular structural information. The archival nature of the PDB presents certain challenges pertaining to updating or adding associated annotations from trusted external biodata resources. While each Worldwide PDB (wwPDB) partner has made best efforts to provide up-to-date external annotations, accessing and integrating information from disparate wwPDB data centers can be an involved process. To address this issue, the wwPDB has established the PDB Next Generation or NextGen Archive, developed to centralize and streamline access to enriched structural annotations from wwPDB partners and trusted external sources. At present, the archive provides mappings between experimentally determined 3D structures of proteins and UniProt amino acid sequences, together with domain annotations from Pfam, SCOP2, and CATH databases, and intra-molecular connectivity information. Since launch, the PDB NextGen Archive has seen substantial user engagement with over 3.5 million data file downloads, ensuring researchers have access to accurate, up-to-date, and easily accessible structural annotations. Database URLhttp://www.wwpdb.org/ftp/pdb-nextgen-archive-site

bioinformatics↗

bioRxiv2023

T4SEpp: a pipeline integrated with protein language models effectively predicting bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems(T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causeing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs, and compared their performance. An integrated model T4SEpp was assembled by a module searching full-length, signal sequence and effector domain homologs of known T4SEs, a machine learning module based on the hand-crafted features extracted from the signal sequences, and the third module containing three best-performing protein language pre-trained models. T4SEpp outperformed the other state-of-the-art (SOTA) software tools, achieving [~]0.95 sensitivity at a high specificity of [~]0.99, based on the assessment of an independent testing dataset. Additionally, we performed a comprehensive search among 8,761 bacterial species, leading to the discovery of 227 species belonging to 3 phyla and 117 genera that possess T4SSs. Furthermore, leveraging the power of T4SEpp, we successfully identified a grand total of 12,622 plausible T4SEs. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs, and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

bioinformatics↗

bioRxiv2023

Systematic single-cell analysis reveals dynamic control of transposable element activity orchestrating the endothelial-to-hematopoietic transition

BackgroundThe endothelial-to-hematopoietic transition (EHT) process during definitive hematopoiesis in vertebrate is highly conserved. Stage-specific expression of transposable elements (TEs) has been detected during zebrafish EHT and may promote hematopoietic stem cell formation by activating inflammatory signaling. However, little is known about how TEs contribute to the EHT process in human and mouse. ResultsWe reconstructed the single-cell EHT trajectories of human and mouse, and resolved the dynamic expression patterns of TEs during EHT. Most TEs presented a transient co-upregulation pattern along the conserved EHT trajectories. Enhanced TE activation was tightly associated with the temporal relaxation of epigenetic silencing systems. TE products can be sensed by multiple pattern recognition receptors, triggering inflammatory signaling to facilitate the emergence of hematopoietic stem cells. Furthermore, we observed that hypoxia-related signals were enriched in cells with higher TE expression. Additionally, we constructed the hematopoietic cis-regulatory network of accessible TEs and identified potential enhancers derived by TEs, which may boost the expression of specific EHT marker genes. ConclusionsOur study provides a systematic vision on how TEs are dynamically controlled to promote the hematopoietic fate decision through transcriptional and cis-regulatory networks, and pre-train the immunity of nascent hematopoietic stem cells.

bioinformatics↗

bioRxiv2022

Decoding frontotemporal and cell type-specific vulnerabilities to neuropsychiatric disorders and psychoactive drugs

Abnormalities in temporal and frontal lobes (TL and FL) have been linked to cognition and neuropsychiatric disorders. While structural and functional differences between the brain lobes have been documented in disease, the cellular heterogeneity in FL and TL and its impact to the vulnerability to genetic risk factors for neuropsychiatric disorders is not well studied. We hypothesize that intrinsic cellular-level differences between TL and FL explain the vulnerability of specific cell types to genetic risk factors and psychoactive drugs. To test this, we integrated single-nucleus transcriptome analysis in fresh human FL and TL with data related to genetic susceptibility and gene dysregulation in neuropsychiatric disease, and response to psychoactive drugs. We also investigate how these differences are associated with gene dysregulation in disease brain. Neuronal cell populations were the most vulnerable to psychiatric genetic risk factors, and more specifically parvalbumin interneurons (PVALB neurons). These PVALB-expressed genetic risk factors were mostly upregulated in the TL compared with FL, and dysregulated in the brain of patients with obsessive-compulsive disorder, bipolar disorder and schizophrenia. We found GRIN2A and HCN1, implicated in schizophrenia by genome-wide association studies, to be significantly upregulated in PVLAB from the TL and in brain cortex from schizophrenia patients. Our analysis provides comprehensive evidence for PVALB neurons as the most vulnerable cell type that is implicated in several psychiatric disorders. PVALB neurons showed the highest vulnerability to psychoactive drug response, which was 3.6-fold higher than the vulnerability to genetic risk factors. In summary, we show high vulnerability of PVALB neurons that is specific to the temporal lobe, implying that differences between TL and FL greatly influence the cell vulnerability to genetic risk factors as well as the response to psychoactive drugs. These findings offer insights into how regional brain differences affect the cell type vulnerabilities in neuropsychiatric disorders.

neuroscience↗

bioRxiv2020

Oligonucleotide Capture Sequencing of the SARS-CoV-2 Genome and Subgenomic Fragments from COVID-19 Individuals

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

genomics↗