Biology subjects

Bu, F.

Publications and source records attributed to Bu, F..

14 recordsLinked to original sources

bioRxiv2025

A SARS-CoV-2 entry inhibitor trimerizes to lock the spike protein in a closed conformation

The SARS-CoV-2 spike protein binds its receptor ACE2 to initiate target-cell infection. To engage ACE2, at least one of the three receptor-binding domains (RBDs) of the spike must adopt the up orientation. Here we describe S22, a potent, bioavailable, and non-toxic inhibitor of BA.2 and all subsequent Omicron variants. Cryo-EM analyses showed that S22 assembled as a trimer in a previously uncharacterized pocket of the spike apex, stabilizing all three RBDs in the down orientation, thereby preventing ACE2 association. Binding studies, especially those using mixed S22-sensitive and -resistant spikes, imply a cooperative assembly of three S22 molecules with three RBDs, resulting in an unusually slow S22 off-rate. Consistent with its slow dissociation and favorable pharmacokinetics, S22 suppressed viral replication 100-fold in the lungs of XBB.1.5-infected mice. Thus, S22 potently inhibits Omicron entry through a distinct mechanism whereby a small compound assembles cooperatively as a trimer to stabilize spike in an inactive conformation.

microbiology↗

bioRxiv2025

Helicobacter pylori genome aggregation database reveals complex evolutionary forces shaping its genomic landscape and clinical impact in East Asia

We assembled HPgnomAD, a comprehensive global genome aggregation database of Helicobacter pylori (H. pylori) featuring 7,544 high-quality genomes from 278 populations, along with the first species-wide haplotype reference panel for genotype imputation. The panel provides high accuracy across diverse H. pylori populations, including those from low-coverage data, and is openly accessible with integrated analysis tools (https://www.hpgnomad.top/). Variant discovery revealed 1.82 million SNPs and 0.65 million InDels, with African strains exhibiting the most tremendous diversity and East Asian strains showing unexpectedly high novel variation. Fine-scale analysis of the hpEAsia lineage revealed six new sublineages shaped by altitude-, latitude-related divergence and region-specific admixture. Phylogenomic dating revealed two divergence waves in East Asia, paralleling Upper Paleolithic settlement and Neolithic human expansions, with highland-lowland separation at [~]18.8 kya, followed by the formation of complex geography-related population substructures. Genome-wide scans revealed adaptive loci related to metal acquisition, nitrogen metabolism, surface adhesion, and membrane transport, including altitude-associated highly differentiated variants linked to antibiotic resistance and gastric disease. By integrating genomic, evolutionary, environmental, and clinical data, HPgnomAD offers a framework for understanding H. pylori evolution, host-pathogen adaptation, and precision medicine worldwide.

evolutionary biology↗

bioRxiv2024

GDC: An Integrated Resource to Explore the Pathogenesis of Hearing Loss through Genetics and Genomics

Effective research and clinical application in audiology and hearing loss (HL) often require the integration of diverse data. However, the absence of a dedicated database impeded understanding and insight extraction in HL. To address this, the Genetic Deafness Commons (GDC) was developed by consolidating extensive genetic and genomic data from 51 public databases and the Chinese Deafness Genetics Consortium, encompassing 5,983,613 variants across 201 HL genes. This comprehensive dataset detailed the genetic landscape of HL, identifying six novel mutational hotspots within DNA binding domains of transcription factor genes, which were eligible for evidence-based variant pathogenicity classification. Comparative phenotypic analyses highlighted considerable disparities between human and mouse models, with only 130 human HL genes exhibiting hearing abnormality in mice. Moreover, gene expression analyses in the cochleae of mice and rhesus macaques demonstrated a notable correlation (R2 = 0.76). Utilizing gene expression, function, pathway, and phenotype data, a SMOTE-Random Forest model identified 18 candidate HL genes, including TBX2 and ERCC2, newly confirmed as HL genes. The GDC, as a comprehensive and unified repository, significantly advances audiology research and clinical practice by enhancing data accessibility and usability, thereby facilitating deeper insights into hearing disorders.

genetics↗

bioRxiv2023

A chromosome-level reference genome of a Fabaceae species yam bean (Pachyrhizus erosus)

Yam bean (Pachyrhizus erosus L.), belonging to the family Fabaceae, is an important but underutilized root crop. Here, we generated a high-quality chromosome-level reference genome of yam bean by PacBio HiFi and Hi-C sequencing, with assembly size of 539.0 Mb, contig N50 of 25.6 Mb, and BUSCO complete rate of 99.3%. Then, we anchored 94.4% of the contig sequences into 11 pseudo-chromosomes, and assembled the telomeres at 86.4% (19/22) of the chromosome-ends. A total of 44,692 protein-coding genes were predicted, with the BUSCO complete rate of 99.3%, comparable to that of the genome assembly. Compared to the previously reported yam bean genome, the current assembly has a 1,388-fold increase in contig N50 size, and 12.2% and 24.3% increase in BUSCO complete rate for the genome sequence and gene set, respectively. Evolutionary analysis revealed that yam bean diverged from the clade of soybean and Pueraria lobata var. montana 22.5 MYA. This high-quality genome assembly will greatly facilitate the breeding of yam bean based on the genetic and genomic methods.

genomics↗

bioRxiv2023

Circulating Small Extracellular Vesicle RNA Profiling for the Detection of T1a stage Colorectal Cancer and Precancerous Advanced Adenoma

It takes more than twenty years for normal colorectal mucosa to develop into metastatic carcinoma. The long time window provides a golden opportunity for early detection to terminate the malignant progression. Here we aim to enable liquid biopsy of T1a stage colorectal cancer (CRC) and precancerous advanced adenoma (AA) by profiling circulating small extracellular vesicle (sEV)-derived RNAs. We exhibited a full RNA landscape for the circulating sEVs isolated from 60 participants. A total of 58,333 annotated RNAs were detected from plasma sEVs, among which 1,615 and 888 sEV-RNAs were found differentially expressed in plasma from T1a stage CRC and AA compared to normal controls (NC). Then we further categorized these sEV-RNAs into 6 modules by a weighted gene coexpression network analysis and constructed a 60-gene t-SNE model consisting of the top 10 RNAs of each module that could well distinguish T1a stage CRC/AA from NC samples. Some sEV-RNAs were also identified as indicators of specific endoscopic and morphological features of different colorectal lesions. The top-ranked biomarkers were further verified by RT-qPCR, proving that these candidate sEV-RNAs successfully identified T1a stage CRC/AA from NC in another cohort of 124 participants. Finally, we adopted different algorithms to improve the performance of RT-qPCR-based models and successfully constructed an optimized classifier with 79.3% specificity and 99.0% sensitivity. In conclusion, circulating sEVs of T1a stage CRC and AA patients have distinct RNA profiles, which successfully enable the detection of both T1a stage CRC and AA via liquid biopsy.

bioinformatics↗

bioRxiv2023

Assessment of three-dimensional RNA structure prediction in CASP15

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and X-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as non- canonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

biophysics↗

bioRxiv2023

Comparative Phylogenomics and Phylotranscriptomics Provide Insights into the Genetic Complexity of Nitrogen Fixing Root Nodule Symbiosis

Plant root nodule symbiosis (RNS) with mutualistic nitrogen-fixing bacteria is restricted to a single clade of angiosperms, the Nitrogen-Fixing Nodulation Clade (NFNC), and is best understood in the legume family. It is widely accepted that nodulation originated through the assembly of modules recruited from existing functions, such as mycorrhizal symbiosis, polar growth, and lateral root development. Because nodulating species are scattered within the NFNC, the number of times nodulation has evolved or has been lost has been a matter of considerable speculation. This interesting evolutionary question has practical implications concerning the ease with which nodulation might be engineered in non-nodulating crop plants. Nodulating species share many commonalities, due either to divergence from a common ancestor over 100 million years ago or to convergence or deep homology following independent origins over that same time period. In either case, comparative analyses of diverse nodulation syndromes can provide insights into constraints on nodulation--what must be acquired or cannot be lost for a functional symbiosis--and what the latitude is for variation in the symbiosis. However, much remains to be learned about nodulation, especially outside of legumes. Here we present new information across the spectrum of nodulating groups. We find no evidence for convergence at the level of amino acid residues or gene family expansion across the NFNC. Our phylogenomic analyses further emphasize the uniqueness of the transcription factor, NIN, as a master regulator of nodulation, and identify key mutations affecting its function across the NFNC. We find that nodulation genes are over-represented among orthologous gene groups (OGs) present in the NFNC common ancestor, but that lineage-specific OGs play major roles in nodulation. We identified over 900,000 conserved noncoding elements (CNEs), of which over 300,000 were unique to NFNC species. A significant proportion of these are associated with nodulation-related genes and thus are candidates for transcriptional regulators.

evolutionary biology↗

bioRxiv2023

HCC-1 accelerates atherosclerosis by inducing endothelial cells and macrophages pyroptosis and serves as an early diagnostic biomarker

BACKGROUNDHCC-1 (Hemofiltrate CC chemokine-1), a CC-type chemokine, exerts function to change intracellular calcium concentration, induce leukocyte and manipulate enzyme release especially in monocytes. It has been reported that HCC-1 could predict the persistent acute kidney injury (AKI) or suppress hepatocellular carcinoma (HCC) by modulating cell cycle and promoting apoptosis, but the effect of HCC-1 on atherosclerosis is poorly understood. Here, we aimed to clarify the function and mechanism of HCC-1 in atherosclerosis and whether it could serve as a novel biomarker for the diagnosis of atherosclerosis. METHODSHCC-1 expression in serum, atherosclerotic plaques and normal arterial tissue from patients with atherosclerosis and control group was assessed by enzyme-linked immunosorbent assay, immunohistochemistry and con-focal microscope. The atherosclerotic model of HCC-1 overexpressing mice and control mice were generated by infection of AAV9-HCC-1 on an ApoE-/- background. Cell adhesion, polarization and pyroptosis were evaluated in vitro. The relationship between HCC-1 concentration in serum and atherosclerosis was analyzed in patients with atherosclerosis. RESULTSHCC-1 expression increased in patients with atherosclerosis both in serum and atherosclerotic plaque. HCC-1 overexpression mice had an enhancement in macrophage accumulation in plaque, higher levels of inflammatory factors, increased pyroptotic rate in ECs and Macrophages in plaque and decreased atherosclerotic plaque stability. In vitro, HCC-1 promoted monocytes to adhere to endothelial cells and M1 polarization, induced inflammation and pyroptosis both in ECs and Macrophages. CONCLUSIONSHCC-1 expression markedly increased in patients with atherosclerosis and HCC-1 overexpression accelerated atherosclerotic burden via an enhancement in monocytes recruitment, M1 polarization and pyroptosis both in ECs and Macrophages. Our findings suggested that HCC-1 may serve as an early biomarker for the diagnosis of atherosclerosis, with the capacity to reflect the degree of stenosis. GRAPHIC ABSTRACTA graphic abstract is available for this article.

cell biology↗

bioRxiv2023

Identification of mobile element insertion from whole genome sequencing data using deep neural network model

Mobile element insertions (MEIs) are a major contributor to genome evolution and play an essential role in the regulation of gene expression, as well as being implicated in various human diseases. This study introduces DeepMEI, a tool based on a convolutional neural network model that transforms the MEI identification process into an image recognition problem and automatically learns complex and abstract representations of MEI features in whole genome sequencing data. DeepMEI outperformed existing tools in the benchmark dataset from the Genome in a Bottle consortium, with a precision of 0.90 and recall of 0.70. Moreover, factors such as sequencing depth, ME integrity, and genome mappability can affect MEI identification accuracy. Using DeepMEI, we reanalyzed 3,202 high-coverage whole-genome sequencing samples from the 1000 Genome Project (1kGP) phase 4 release, discovering 1.71-fold more non-reference MEIs, totaling 6,218,088, with 92.2% of the increase coming from rare MEIs (allele frequency <1%). This enhances our understanding of MEIs role in human disease and evolution. The DeepMEI tool and the updated 1kGP MEI dataset can be accessed at https://github.com/xuxif/DeepMEI.

bioinformatics↗

bioRxiv2023

High-throughput screening of functional neo-antigens and their specific TCRs via the Jurkat reporter system combine with droplet microfluidics

T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications.

bioengineering↗

bioRxiv2022

Structural basis for BIRC6 to balance apoptosis and autophagy

Caspase-9 is the initiator caspase for the intrinsic apoptotic cell death pathway, and is critical to the activation of effector caspases during apoptosis, but how its levels and activities are maintained remains unclear. The gigantic Inhibitor of Apoptosis Protein (IAP) BIRC6/BRUCE/Apollon not only inhibits apoptosis, but also promotes ubiquitination of the key autophagic protein LC3 and inhibits autophagy. Here we show that BIRC6 forms an anti-parallel U-shaped dimer in a 3.6-[A] cryo-EM structure with multiple previously unannotated domains, including a ubiquitin-like domain, and discover that the mitochondria-derived pro-apoptotic factor Smac/DIABLO binds BIRC6 by interacting with one BIR domain, two carbohydrate-binding modules and two helices in the central cavity. Notably, Smac outcompetes the effector caspase 3 and the pro-apoptotic protease HtrA2, but not caspase 9, for binding BIRC6. BIRC6 strongly inhibits cellular activity of caspase 9, but weakly suppresses that of caspase 3. Meanwhile, BIRC6 binds LC3 through an LC3-interacting region, probably following dimer disruption of this BIRC6 region. Deficiency in LC3 ubiquitination promotes autophagy and autophagic degradation of BIRC6, and inhibits apoptosis. Moreover, induction of autophagy promotes autophagic degradation of both procaspase-9 and active caspase-9, but not of effector caspases. These results are important to understand how the balance between apoptosis and autophagy is regulated under pathophysiological conditions.

cell biology↗

bioRxiv2021

seGMM: a new tool to infer sex from massively parallel sequencing data

Inspecting concordance between self-reported sex and genotype-inferred sex from genomic data is a significant quality control measure in clinical genetic testing. Numerous tools have been developed to infer sex for genotyping array, whole-exome sequencing, and whole-genome sequencing data. However, improvements in sex inference from targeted gene sequencing panels are warranted. Here, we propose a new tool, seGMM, which applies unsupervised clustering (Gaussian Mixture Model) to determine the gender of a sample from the called genotype data integrated aligned reads. seGMM consistently demonstrated > 99% sex inference accuracy in publicly available (1000 Genomes) and our in-house panel dataset, which achieved obviously better sex classification than existing popular tools. Compared to including features only in the X chromosome, our results show that adding additional features from Y chromosomes (e.g. reads mapped to the Y chromosome) can increase sex classification accuracy. Notably, for WES and WGS data, seGMM also has an extremely high degree of accuracy. Finally, we proved the ability of seGMM to infer sex in single patient or trio samples by combining with reference data and pinpointing potential sex chromosome abnormality samples. In general, seGMM provides a reproducible framework to infer sex from massively parallel sequencing data and has great promise in clinical genetics.

bioinformatics↗

bioRxiv2021

High performance of a GPU-accelerated variant calling tool in genome data analysis

Rapid advances in next-generation sequencing (NGS) have facilitated ultralarge population and cohort studies that utilized whole-genome sequencing (WGS) to identify DNA variants that may impact gene function. Massive sequencing data require highly efficient bioinformatics tools to complete read alignment and variant calling as the fundamental analysis. Multiple software and hardware acceleration strategies have been developed to boost the analysis speed. This study comprehensively evaluated the germline variant calling of a GPU-based acceleration tool, BaseNumber, using WGS datasets from several sources, including gold-standard samples from the Genome in a Bottle (GIAB) project and the Golden Standard of China Genome (GSCG) project, resequenced GSCG samples, and 100 in-house samples from the China Deafness Genetics Consortium (CDGC) project. Sequencing data were analyzed on the GPU server using BaseNumber, the variant calling outputs of which were compared to the reference VCF or the results generated by the Burrows-Wheeler Aligner (BWA) + Genome Analysis Toolkit (GATK) pipeline on a generic CPU server. BaseNumber demonstrated high precision (99.32%) and recall (99.86%) rates in variant calls compared to the standard reference. The variant calling outputs of the BaseNumber and GATK pipelines were very similar, with a mean F1 of 99.69%. Additionally, BaseNumber took only 23 minutes on average to analyze a 48X WGS sample, which was 215.33 times shorter than the GATK workflow. The GPU-based BaseNumber provides a highly accurate and ultrafast variant calling capability, significantly improving the WGS analysis efficiency and facilitating time-sensitive tests, such as clinical WGS genetic diagnosis, and sheds light on the GPU-based acceleration of other omics data analyses.

bioinformatics↗

bioRxiv2017

Parallel loss of symbiosis genes in relatives of nitrogen-fixing non-legume Parasponia

Rhizobium nitrogen-fixing nodules are a well-known trait of legumes, but nodules also occur in other plant lineages either with rhizobium or the actinomycete Frankia as microsymbiont. The widely accepted hypothesis is that nodulation evolved independently multiple times, with only a few losses. However, insight in the evolutionary trajectory of nodulation is lacking. We conducted comparative studies using Parasponia (Cannabaceae), the only non-legume able to establish nitrogen fixing nodules with rhizobium. This revealed that Parasponia and legumes utilize a large set of orthologous symbiosis genes. Comparing genomes of Parasponia and its non-nodulating relative Trema did not reveal specific gene duplications that could explain a recent gain of nodulation in Parasponia. Rather, Trema and other non-nodulating species in the Order Rosales show evidence of pseudogenization or loss of key symbiosis genes. This demonstrates that these species have lost the potential to nodulate. This finding challenges a long-standing hypothesis on evolution of nitrogen-fixing symbioses, and has profound implications for translational approaches aimed at engineering nitrogen-fixing nodules in crop plants.

plant biology↗