Biology subjects

Zhong, B.

Publications and source records attributed to Zhong, B..

31 records · Page 2Linked to original sources

bioRxiv2023

Pretrainable Geometric Graph Neural Network for Antibody Affinity Maturation

Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity maturation. Leveraging multi-relational graph construction, multi-level geometric message passing and contrastive pretraining on mass-scale, unlabeled protein structural data, GearBind outperforms previous state-of-the-art approaches on SKEMPI and an independent test set. A powerful ensemble model based on GearBind is then derived and used to successfully enhance the binding of two antibodies with distinct formats and target antigens. ELISA EC50 values of the designed antibody mutants are decreased by up to 17 fold, and KD values by up to 6.1 fold. These promising results underscore the utility of geometric deep learning and effective pretraining in macromolecule interaction modeling tasks.

bioinformatics↗

bioRxiv2022

Citrus genomic resources unravel putative genetic determinants of Huanglongbing, a pathogen-triggered immune disease

Citrus is one of the most important tree crops worldwide and citrus production is threatened by Huanglongbing (HLB), a devasting citrus disease caused by Candidatus Liberibacter. HLB is a pathogen-triggered immune disease, in which the pathogen initiates systemic and chronic immune responses including the excessive production of reactive oxidative species, which subsequently lead to cell death of phloem tissues and HLB disease symptoms. Here, we identified putative genetic determinants of HLB pathogenicity by integrating citrus genomic resources to characterize the pan-genome of accessions that differ in their response to HLB. Genome-wide association mapping and analysis of allele-specific expression between susceptible, tolerant, and resistant accessions further refined candidates underlying the response to HLB. To enable these analyses we first developed a phased diploid assembly of Citrus sinensis Newhall genome and produced resequencing data for 91 citrus accessions that differ in their response to HLB. These data were combined with previous resequencing data from 356 sequenced accessions for genome-wide association mapping of the HLB response. Genes with HLB pathogenicity were associated with the host immune response, ROS production, and antioxidants. Overall, this study has provided a significant recourse of citrus genomic data and we have identified candidate genes to be further explored to understand the genetic determinants of HLB pathogenicity and to generate HLB resistant/tolerant citrus varieties.

genomics↗

bioRxiv2022

Single cell Transcriptome and T cell Repertoire Mapping of the Mechanistic Signatures and T cell Trajectories Contributing to Vascular and Dermal Manifestations of Behcet Disease

Behcets disease (BD) is a form of vasculitis characterized by complex multi-organ manifestations that may frequently recur and induce major tissue damage. Although genetic association studies have identified a number of risk factors, the etiology of BD and its tissue manifestations remains unknown, and the landscape of immune responses in BD is opaque, particularly in terms of inflammatory recurrence. In this study, we mapped the transcriptomes of the immune cell compartment in BD at single-cell resolution, sampling both circulation and affected skin in order to chart the immune interplay driving pathogenesis. Through comprehensive expression and communication analysis of the twenty major cell types identified, we observe striking mechanistic differences in immune response between BD skin lesions and peripheral circulation involving TNF signaling and T cell migration. Through integrated TCR sequencing, we further discover a pattern of clonal sharing between circulating and skin CD8+T cell populations along a trajectory defined by the acquisition of tissue-residential properties. In addition, we also identify a population of expanded CD4+ Tregs with the propensity to produce IL-32. Instead of suppressing effector T cell proliferation and function, IL-32 triggers increased expression of CD97, and may thus encourage prolonged local T cell activity in the skin. Collectively, our data serve to advance understandings of contributions of varying immune cell types to BD pathogenesis in the vasculature and skin, as well as the lifecycle patterns of T cells clones in this context. These data may also assist in further investigations of the mechanisms contributing to Treg dysfunction in systemic autoimmunity, while generating a conceptual model of T cell function contributing to BD recurrence.

immunology↗

bioRxiv2022

Tyrosine phosphorylation tunes chemical and thermal sensitivity of TRPV2 ion channel

Transient receptor potential vanilloid 2 (TRPV2) is a multimodal ion channel widely regulating central and peripheral functions. Its important involvement in immune responses has been suggested such as in the macrophages phagocytosis process. However, the endogenous signaling cascades controlling the gating of TRPV2 remain to be understood. Here, we report that enhancing tyrosine phosphorylation remarkably alters the chemical and thermal sensitivities of TRPV2 endogenously expressed in rat bone marrow-derived macrophages. We identify that the protein tyrosine kinase JAK1 mediates TRPV2 phosphorylation at the molecular sites Tyr(335), Tyr(471), and Tyr(525). JAK1 phosphorylation is required for maintaining TRPV2 activity and the phagocytic ability of macrophages. We further show that TRPV2 phosphorylation is dynamically balanced by protein tyrosine phosphatase non-receptor type 1 (PTPN1). PTPN1 inhibition increases TRPV2 phosphorylation, further reducing the activation temperature threshold to [~]40 {degrees}C. Our data thus unveil an intrinsic mechanism where the phosphorylation/dephosphorylation dynamic balance sets the basal chemical and thermal sensitivity of TRPV2. Targeting this pathway will aid therapeutic interventions in physiopathological contexts.

physiology↗

bioRxiv2021

ARIC: Accurate and robust inference of cell type proportions from bulk gene expression or DNA methylation data

Quantifying the cell proportions, especially for rare cell types in some scenarios, is of great value to track signals related to certain phenotypes or diseases. Although some methods have been pro-posed to infer cell proportions from multi-component bulk data, they are substantially less effective for estimating rare cell type proportions since they are highly sensitive against feature outliers and collinearity. Here we proposed a new deconvolution algorithm named ARIC to estimate cell type proportions from bulk gene expression or DNA methylation data. ARIC utilizes a novel two-step marker selection strategy, including component-wise condition number-based feature collinearity elimination and adaptive outlier markers removal. This strategy can systematically obtain effective markers that ensure a robust and precise weighted {upsilon}-support vector regression-based proportion prediction. We showed that ARIC can estimate fractions accurately in both DNA methylation and gene expression data from different experiments. Taken together, ARIC is a promising tool to solve the deconvolution problem of bulk data where rare components are of vital importance.

bioinformatics↗

bioRxiv2021

Chromatin accessibility dynamics of neurogenic niche cells reveal a reversible decline in neural stem cell migration during aging

Aging is accompanied by a deterioration in the regenerative and repair potential of stem cell niches in the brain1-5. However, the mechanisms underlying this decline are largely unknown. Here we characterize genome-wide chromatin accessibility in young and old neurogenic niche cells in vivo, revealing defects in neural stem cell (NSC) adhesion and migration during aging. Interestingly, chromatin accessibility at cell adhesion and migration genes decreases with age in quiescent NSCs but increases with age in activated (proliferative) NSCs, and this is accompanied by corresponding expression changes in these genes. We experimentally validate that quiescent and activated NSCs exhibit opposing adhesion and migration behaviors with age: quiescent NSCs become less adhesive (and more migratory) whereas activated NSCs and progeny become more adhesive (and less migratory) during aging. We also show that the ability of activated NSCs and progeny to mobilize out of the niche during in vivo neurogenesis diminishes during aging. Using tension sensors with single molecule resolution, we find that one of the cellular mechanisms by which aging impairs the migration of old activated NSCs and progeny involves increased force-producing adhesions. We identify inhibition of the cytoskeletal-regulating kinase ROCK6, 7 as a way to reduce force-producing adhesions and restore migration in old activated NSCs in vitro. Interestingly, inhibition of ROCK in the neurogenic niche of old mice boosts neurogenesis to the olfactory bulb in vivo. These results have important implications for restoring the migratory potential of NSCs and progeny and for improving neurogenesis in the aged brain.

neuroscience↗

bioRxiv2021

Molecular dynamics simulation study of effects of key mutations in SARS-CoV-2 on protein structures

SARS-CoV-2 has been spreading rapidly since 2019 and has produced large-scale mutations in the genomes. The mutation in genes may lead to changes in protein structure, which would have a great impact on the epidemiological characteristics. In this study, we selected the key mutations of SARS-CoV-2 from a real-time monitoring tool, including D614G, A222V, N501Y, T716I, S982A, D1118H of spike (S) protein, and performed molecular dynamics (MD) simulations on single-site mutant D614G, double-site mutant D614G&A222V and penta-site mutant N501Y&D614G&T716I&S982A&D1118H to investigate their effects on protein structure and stability using molecular dynamics (MD) simulations. The results suggested that D614G improved the stability of S protein, while D614G&A222V and N501Y&D614G&T716I&S982A&D1118H showed an increased solvent accessible surface area and they might enhance the ability of protein to react with the outside environment. Our findings could complement the mechanistic link between genotype--phenotype--epidemiological characteristics in the study of SARS-CoV-2. We also found no significant difference between the antigenicity of S protein and the mutants through Ellipro, which may reference for vaccine development and application.

bioinformatics↗

bioRxiv2021

DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads

Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as "switching region" to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

bioinformatics↗

bioRxiv2020

Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2

The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Author summaryIn this study, we compared SARS-CoV-2 populations of 13 Chinese COVID-19 patients. Those viral populations contained a considerable proportion of viral sub-genomic messenger RNAs (sgmRNA), reflecting an active viral replication activity in the respiratory tract tissues. The comparison of 66 identified intra-host variants further showed a low viral genetic distance between intra-household patients and a narrow transmission bottleneck size. Despite the co-existence of genetically distinct viruses within the same host, most intra-host minor variants were not shared between transmission pairs, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Furthermore, the narrow bottleneck and active viral activity in the respiratory tract show that the passage of a small number of virions can cause infection. Our data have therefore delivered a key genomic resource for the SARS-CoV-2 transmission research and enhanced our understanding of the evolutionary dynamics of SARS-CoV-2.

genetics↗

bioRxiv2020

Population genomic analyses of schistosome parasites highlight critical challenges facing end-game elimination efforts

Schistosomiasis persists in some Asian regions despite targeted end-game elimination measures. To determine the causes of this persistence, we performed reduced representation genome sequencing on Schistosoma japonicum miracidia collected across multiple years from transmission hotspots in Sichuan, China. We discovered strong geographic structure, suggesting that local rather than imported reservoirs are key sources of infection persistence. At the village level, parasites collected after praziquantel treatment are closely related to local pre-treatment populations. Schistosomes within villages are also highly related, suggesting that only a few parasites from a limited number of hosts drive re-infection. The close familial relationships among miracidia from different human hosts also implicates short transmission routes among humans. At the individual host level, genetic evidence indicates that multiple humans retain infections following referral for treatment. Our findings suggest that end-game schistosomiasis control measures should focus on completely extirpating local parasite reservoirs and confirming successful treatment of infected human hosts. One Sentence SummaryLocal reservoirs are the source for persistent schistosomiasis infections despite continuous efforts aimed at complete elimination.

evolutionary biology↗

bioRxiv2020

Prediction and Evolution of B Cell Epitopes of Surface Protein in SARS-CoV-2

The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine. The sequences of the surface protein of SARS-CoV-2 and its proximal sequences were obtained by BLAST, the sequences of the whole genome of SARS-CoV-2 were obtained from the GenBank. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed. 7 epitopes were predicted, including 5 linear epitopes and 2 conformational epitopes, one of the linear and one of the conformational were coincide. The epitope D mutated easily, but the other epitopes were very conservative and the epitope C was the most conservative. It is worth mentioning that all of the 6 dominated epitopes were absolutely conservative in nearly 1000 SARS-CoV-2 genomes, and they deserved further study. The findings would facilitate the vaccine development, had the potential to be directly applied on the treatment in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus.

bioinformatics↗

bioRxiv2019

Comparative analyses of 3654 chloroplast genomes unraveled new insights into the evolutionary mechanism of green plants

BackgroundChloroplast are believed to arise from a cyanobacterium through endosymbiosis and they played vital roles in photosynthesis, oxygen release and metabolites synthesis for the plant. With the advent of next-generation sequencing technologies, until December 2018, about 3,654 complete chloroplast genome sequences have been made available. It is possible to compare the chloroplast genome structure to elucidate the evolutionary history of the green plants.\n\nResultsWe compared the 3654 chloroplast genomes of the green plants and found extreme conservation of gene orders and gene blocks in the green plant such as ATP synthase cluster, Phytosystem, Cytochrome cluster, and Ribosomal cluster. For the chloroplast-based phylogenomics, we used three different data sets to recover the relationships within green plants which accounted for biased GC content and could mitigate the bias in molecular data sets by increasing taxon sampling. The main topology results include: I) Chlorokybales + Mesostigmatales as the earliest-branching lineage and a clade comprising Zygnematales+ Desmidiales formed a grade as the sister group to the land plants, II) Based on matrix AA data, Bryophytes was strongly supported as monophyletic but for matrix nt123 data, hornworts, mosses and liverworts were placed as successive sister lineages of Tracheophytes with strong support, III) Magnoliids were placed in the outside of Monocots using the matrix nt123 data and the matrix AA data, IV) Ceratophyllales + Chloranthales as sister to the Eudicots using matrix nt123 data, but when using matrix nt12 data and AA data, only Ceratophyllales sister to the Eudicots.\n\nConclusionWe present the first of its kind large scale comparative analyses of the chloroplast coding gene constitution for 3654 green plants. Some important genes likely showed co-occurrence and formed gene cluster and gene blocks in Streptophyta. We found a clear expansion of IRs (Inverted Repeats) among seed plants. The comprehensive taxon sampling and different data sets recovered a strong relationship for green plants.

plant biology↗

bioRxiv2019

Ribosomal DNA methylation as stable biomarkers for detection of cancer in plasma

BackgroundRecently, liquid biopsy for cancer detection has pursued great progress. However, there are still a lack of high quality markers. It is a challenge to detect cancer stably and accurately in plasma cell free DNA (cfDNA), when the ratio of cancer signal is low. Repetitive genes or elements may improve the robustness of signals. In this study, we focused on ribosomal DNA which repeats hundreds of times in human diploid genome and investigated performances for cancer detection in plasma.\n\nResultsWe collected bisulfite sequencing samples including normal tissues and 4 cancer types and found that intergenic spacer (IGS) of rDNA has high methylation levels and low variation in normal tissues and plasma. Strikingly, IGS of rDNA shows significant hypo-methylation in tumors compared with normal tissues. Further, we collected plasma bisulfite sequencing data from 224 healthy subjects and cancer patients. Means of AUC in testing set were 0.96 (liver cancer), 0.94 (lung cancer and), 0.92 (colon cancer) with classifiers using only 10 CpG sites. Due to the feature of high copy number, when liver cancer plasma WGBS was down-sampled to 10 million raw reads (0.25x whole genome coverage), the prediction performance decreased only a bit (mean AUC=0.93). Finally, methylation of rDNA could also be used for monitor cancer progression and treatment.\n\nConclusionTaken together, we provided the high-resolution map of rDNA methylation in tumors and supported that methylation of rDNA was a competitive and robust marker for detecting cancer and monitoring cancer progression in plasma.

genomics↗