Biology subjects

Shang, J.

Publications and source records attributed to Shang, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

HIV-1 infection is associated with depletion of germinal center B cells and a decrease in IgA+ plasma cells in the GI tract

Gastrointestinal (GI) B cells and plasma cells (PCs) are critical to mucosal homeostasis and the host response to HIV-1 infection. Here, high resolution mapping of human B cells and PCs sampled from the colon and ileum during both viremic and suppressed HIV-1 infection identified a reduction in germinal center (GC) B cells and follicular dendritic cells (FDCs) during HIV-1 viremia. IgA+ PCs are the major cellular output of intestinal GCs and were significantly reduced during viremic HIV-1 infection. PC-associated transcriptional perturbations, including type I interferon signaling, persisted in antiretroviral therapy (ART)-treated individuals, suggesting ongoing disruption of the intestinal immune milieu during ART. GI humoral immune perturbations were associated with changes in the intestinal microbiome composition and systemic inflammation. These findings highlight a key immune defect in the GI mucosa due to HIV-1 viremia. One Sentence SummaryIntestinal germinal center B cell reduction in HIV-1 infection linked to reduced IgA+ plasma cells and systemic inflammation.

immunology↗

bioRxiv2024

Unanticipated mechanisms of covalent inhibitor and synthetic ligand cobinding to PPARgamma

Peroxisome proliferator-activated receptor gamma (PPAR{gamma}) is a nuclear receptor transcription factor that regulates gene expression programs in response to ligand binding. Endogenous lipids and synthetic ligands, including covalent antagonist inhibitors such as GW9662 and T0070907, are thought to compete for the orthosteric pocket in the ligand-binding domain (LBD). However, we previously showed that synthetic PPAR{gamma} ligands can cooperatively cobind with and reposition a bound endogenous orthosteric ligand to an alternate site, synergistically regulating PPAR{gamma} structure and function (Shang et al., 2018). Here, we reveal the structural mechanism of cobinding between a synthetic covalent antagonist inhibitor with other synthetic ligands. Biochemical and NMR data show that covalent antagonist inhibitors weaken--but do not prevent--the binding of other synthetic ligands via an allosteric mechanism rather than direct ligand clashing. The covalent ligands shift the LBD ensemble toward a transcriptionally repressive conformation, which structurally clashes with and reduces the orthosteric binding affinity of non-covalent synthetic ligands. Crystal structures reveal different non-covalent synthetic ligand-specific cobinding mechanisms ranging from alternate site binding to unexpectedly adopting an orthosteric binding mode by altering the covalent ligand binding pose. Our findings not only highlight the significant flexibility of the PPAR{gamma} orthosteric pocket and its ability to accommodate multiple ligands simultaneously, but also demonstrate that GW9662 and T0070907 should not be used as reliable chemical tools to inhibit the binding of other ligands to PPAR{gamma}.

biochemistry↗

bioRxiv2024

Ligand efficacy shifts a nuclear receptor conformational ensemble between transcriptionally active and repressive states

Nuclear receptors (NRs) are thought to dynamically alternate between transcriptionally active and repressive conformations, which are stabilized upon ligand binding. Most NR ligand series exhibit limited bias, primarily consisting of transcriptionally active agonists or neutral antagonists, but not repressive inverse agonists--a limitation that restricts understanding of the functional NR conformational ensemble. Here, we report a NR ligand series for peroxisome proliferator-activated receptor gamma (PPAR{gamma}) that spans a pharmacological spectrum from repression (inverse agonism) to activation (agonism) where subtle structural modifications switch compound activity. While crystal structures provide snapshots of the fully repressive state, NMR spectroscopy and conformation-activity relationship analysis reveals that compounds within the series shift the PPAR{gamma} conformational ensemble between transcriptionally active and repressive conformations that are populated in the apo/ligand-free ensemble. Our findings reveal a molecular framework for minimal chemical modifications that enhance PPAR{gamma} inverse agonism and elucidate their influence on the dynamic PPAR{gamma} conformational ensemble.

biophysics↗

bioRxiv2024

Discovery of orally bioavailable SARS-CoV-2 papain-like protease inhibitor as a potential treatment for COVID-19

The RNA-dependent RNA polymerase (RdRp), 3C-like protease (3CLpro), and papain-like protease (PLpro) are pivotal components in the viral life cycle of SARS-CoV-2, presenting as promising therapeutic targets. Currently, all FDA-approved antiviral drugs against SARS-CoV-2 are RdRp or 3CLpro inhibitors. However, the mutations causing drug resistance have been observed in RdRp and 3CLpro from SARS-CoV-2, which makes it necessary to develop antivirals with novel mechanisms. Through the application of a structure-based drug design (SBDD) approach, we discovered a series of novel potent non-covalent PLpro inhibitors with remarkable in vitro potency and in vivo PK properties. The co-crystal structures of PLpro with leads revealed that the residues D164 and Q269 around the S2 site are critical for improving the inhibitors potency. The lead compound GZNL-P36 not only inhibited SARS-CoV-2 and its variants at the cellular level with EC50 ranging from 58.2 nM to 306.2 nM, but also inhibited HCoV-NL63 and HCoV-229E with EC50 of 81.6 nM and 2.66 M, respectively. Oral administration of the compound resulted in significantly improved survival and notable reductions in lung viral loads and lesions in SARS- CoV-2 infection mouse model, consistent with RNA-seq data analysis. Our results indicate that PLpro inhibitor is a promising SARS-CoV-2 therapy.

microbiology↗

bioRxiv2024

Profound synthetic lethality between SMARCAL1 and FANCM

DNA replication stress is a threat to genome integrity. The large SNF2-family of ATPases participates in preventing and mitigating DNA replication stress by employing their ATP-driven motor to remodel DNA or DNA-bound proteins. To understand the contribution of these ATPases in genome maintenance, we undertook CRISPR-based synthetic lethality screens with three SNF2-type ATPases: SMARCAL1, ZRANB3 and HLTF. Here we show that SMARCAL1 displays a profound synthetic lethal interaction with FANCM, another ATP-dependent translocase involved in DNA replication and genome stability. Their combined loss causes severe genome instability that we link to chromosome breakage at loci enriched in simple repeats, which are known to challenge replication fork progression. Our findings illuminate a critical genetic buffering mechanism that provides an essential function for maintaining genome integrity.

molecular biology↗

bioRxiv2024

Highly efficient in vivo mutagenesis method based on the endonuclease and exonuclease activity of Bacillus alcalophilus RecJ (BaRecJ)

With the continual advancement of technologies such as microbial cultivation, DNA sequencing, bioinformatics, and genetic engineering, methods for microbial breeding have become increasingly diverse. We identified a RecJ enzyme (BaRecJ) with both endonuclease and exonuclease activities from B. alcalophilus. Differing from traditional physical-chemical mutagenesis approaches and the methods based on perturbation factor. this research established a novel mutagenesis method utilizing the endonuclease and exonuclease activities of BaRecJ. Mutagenesis of E. coli was conducted using the BaRecJ method, followed by screening for rifampicin-resistant mutants, rpoB sequencing results demonstrated a broader, more uniform spectrum of mutations and a higher frequency of substitution mutations with this mutagenesis approach. Furthermore, this mutagenesis method was applied to S cerevisiae, resulting in mutants with enhanced tolerance to acetic acid and ethanol, exhibiting improved fermentation performance and flocculation abilities Genomic resequencing analysis summarized genes possibly associated with the tolerance of mutants. Therefore, this approach not only holds immense potential in microbial mutagenesis breeding and adaptive evolution but also, when coupled with genomic resequencing, allows for the rapid identification of genetic loci associated with specific traits.

bioengineering↗

bioRxiv2024

ViraLM: Empowering Virus Discovery through the Genome Foundation Model

MotivationViruses, with their ubiquitous presence and high diversity, play pivotal roles in ecological systems and have significant implications for public health. Accurately identifying these viruses in various ecosystems is essential for comprehending their variety and assessing their ecological influence. Metagenomic sequencing has become a major strategy to survey the viruses in various ecosystems. However, accurate and comprehensive virus detection in metagenomic data remains difficult. Limited reference sequences prevent alignment-based methods from identifying novel viruses. Machine learningbased tools are more promising in novel virus detection but often miss short viral contigs, which are abundant in typical metagenomic data. The inconsistency in virus search results produced by available tools further highlights the urgent need for a more robust tool for virus identification. ResultsIn this work, we develop a Viral Language Model, named ViraLM, to identify novel viral contigs in metagenomic data. By employing the latest genome foundation model as the backbone and training on a rigorously constructed dataset, the model is able to distinguish viruses from other organisms based on the learned genomic characteristics. We thoroughly tested ViraLM on multiple datasets and the experimental results show that ViraLM outperforms available tools in different scenarios. In particular, ViraLM improves the F1-score on short contigs by 22%. AvailabilityThe source code of ViraLM is available via: https://github.com/ChengPENG-wolf/ViraLM. Contactyannisun@cityu.edu.hk

bioinformatics↗

bioRxiv2023

Multifrequency control of Faraday wave bioassembly for constructing multiscale hPSC-derived neuronal networks

Bioassembly is recently regarded as a critical alternative biofabrication technical route to bioprinting since it can directly manipulate millions of live cells to form multicellular structures with close intercellular proximity, improving contact-dependent cell communication and promoting the emergence of tissue-specific functions. However, acoustic bioassembly techniques are currently limited to generating cytoarchitecture with a single characteristic length which cannot faithfully mimic the multiscale cellular structures in native tissues. To overcome this challenge, herein we report a novel acoustic bioassembly technique that employs multifrequency control of Faraday waves to form multiscale cellular structures. By superimposing multiple sine wave signals with proper amplitude ratios, Faraday waves containing multiple wavelengths can be induced and enabled to generate multiscale structures in few seconds. Using this technique, we construct functional neuronal networks with multiscale connectivity that display spontaneous neuroelectrical activities. We anticipate this technique will find wide applications in tissue engineering and regenerative medicine.

bioengineering↗

bioRxiv2023

GDmicro: classifying host disease status with GCN and Deep adaptation network based on the human gut microbiome data

MotivationWith advances in metagenomic sequencing technologies, there are accumulating studies revealing the associations between the human gut microbiome and some human diseases. These associations shed light on using gut microbiome data to distinguish case and control samples of a specific disease, which is also called host disease status classification. Importantly, using learning-based models to distinguish the disease and control samples is expected to identify important biomarkers more accurately than abundance-based statistical analysis. However, available tools have not fully addressed two challenges associated with this task: limited labeled microbiome data and decreased accuracy in cross-studies. The confounding factors such as the diet, technical biases in sample collection/sequencing across different studies/cohorts often jeopardize the generalization of the learning model. ResultsTo address these challenges, we develop a new tool GDmicro, which combines semi-supervised learning and domain adaptation to achieve a more generalized model using limited labeled samples. We evaluated GDmicro on human gut microbiome data from 10 cohorts covering 5 different diseases. The results show that GDmicro has better performance and robustness than state-of-the-art tools. In particular, it improves the AUC from 0.783 to 0.949 in identifying inflammatory bowel disease. Furthermore, GDmicro can identify potential biomarkers with greater accuracy than abundance-based statistical analysis methods. It also reveals the contribution of these biomarkers to the hosts disease status. Availability and implementationhttps://github.com/liaoherui/GDmicro Contactyannisun@cityu.edu.hk Supplementary informationSupplementary data are available at XXX online

bioinformatics↗

bioRxiv2022

Polyethylene glycol (PEG)-associated immunological effects triggered by clinically relevant lipid nanoparticles

With the large-scale vaccination of lipid nanoparticles (LNP)-based COVID-19 mRNA vaccines, elucidating the potential polyethylene glycol (PEG)-associated immune responses triggered by clinically relevant LNP has become imminent. However, inconsistent findings were observed across very limited population-based studies. Herein we initiated a study using LNP carrier of Comirnaty(R) as a representative, and simulated real-world clinical practice covering a series of time points and various doses correlated with approved LNP-delivered drugs in a rat model. We demonstrated the time- and dose-dependency of LNP-induced anti-PEG antibodies in rats. As a thymus-independent antigen, LNP unexpectedly induced isotype switch and immune memory, leading to rapid enhancement and longer lasting time of anti-PEG IgM and IgG upon re-injection in rats. Importantly, initial LNP injection accelerated the blood clearance of subsequent dosing in rats. These findings refine our understandings on LNP and possibly other PEG derivatives, and may promote optimization of related premarket guidelines and clinical protocols.

immunology↗

bioRxiv2022

A comparative atlas of single-cell chromatin accessibility in the human brain

The human brain contains an extraordinarily diverse set of neuronal and glial cell types. Recent advances in single cell transcriptomics have begun to delineate the cellular heterogeneity in different brain regions, but the transcriptional regulatory programs responsible for the identity and function of each brain cell type remain to be defined. Here, we carried out single nucleus ATAC-seq analysis to probe the open chromatin landscape from over 1.1 million cells in 42 brain regions of three neurotypical adult donors. Integrative analysis of the resulting data identified 107 distinct cell types and revealed the cell-type-specific usage of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly 1/3 of them displayed sequence conservation as well as chromatin accessibility in the mouse brain. On the other hand, nearly 40% cCREs were human specific, with chromatin accessibility associated with species-restricted gene expression. Interestingly, these human specific cCREs were enriched for distinct families of retrotransposable elements, which displayed cell-type-specific chromatin accessibility. We uncovered strong associations between specific brain cell types and neuropsychiatric disorders. We futher developed deep learning models to predict regulatory function of non-coding disease risk variants.

neuroscience↗

bioRxiv2022

Molecular basis of ligand-dependent Nurr1-RXRα activation

Small molecule compounds that activate transcription of Nurr1-RXR (NR4A2-NR2B1) nuclear receptor heterodimers are implicated in the treatment of neurodegenerative disorders, but function through poorly understood mechanisms. Here, we show that RXR ligands activate Nurr1-RXR through a mechanism that involves ligand-binding domain (LBD) heterodimer proteinprotein interaction (PPI) inhibition, a paradigm distinct from classical pharmacological mechanisms of ligand-dependent nuclear receptor modulation. NMR spectroscopy, protein-protein interaction, cellular transcription assays show that Nurr1-RXR transcriptional activation by RXR ligands is not correlated with classical RXR agonism but instead correlated with weakening Nurr1-RXR LBD heterodimer affinity and heterodimer dissociation. Our data inform a model by which pharmacologically distinct RXR ligands (agonists and Nurr1-RXR selective agonists that function as RXR antagonists) operate as allosteric PPI inhibitors that release a transcriptionally active Nurr1 monomer from a repressive Nurr1-RXR heterodimeric complex. These findings provide a molecular blueprint for ligand activation of Nurr1 transcription via small molecule targeting of Nurr1-RXR.

biochemistry↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

The Quartet Data Portal: integration of community-wide resources for multiomics quality control

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible at https://chinese-quartet.org. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

systems biology↗

bioRxiv2022

Quartet DNA reference materials and datasets for comprehensively evaluating germline variants calling performance

Current methods for evaluating the accuracy of germline variant calls are restricted to easy-to-detect high-confidence regions, thus ignoring a substantial portion of difficult variants beyond the benchmark regions. We established four DNA reference materials from immortalized cell lines derived from a Chinese Quartet including parents and monozygotic twins. We integrated benchmark calls of 4.2 million small variants and 15,000 structural variants from multiple platforms and bioinformatic pipelines for evaluating the reliability of germline variant calls inside the benchmark regions. The genetic built-in-truth of the Quartet family design not only improved sensitivity of benchmark calls by removing additional false positive variants with apparently high quality, but also enabled estimation of the precision of variants calls outside the benchmark regions. Batch effects of variant calling in large-scale DNA sequencing efforts can be effectively identified with the concurrent use of the Quartet DNA reference materials along with study samples, and can be alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Matched RNA and protein reference materials were also established in the Quartet project, thereby enabling benchmark calls constructed from DNA reference materials for evaluation of variants calling performance on RNA and protein data. The Quartet DNA reference materials from this study are a resource for objective and comprehensive assessment of the accuracy of germline variant calls throughout the whole-genome regions.

bioinformatics↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

A chemical molecule promotes Trop2+ biliary duct organoids differentiation into insulin-secreting cells

Cell replacement therapy is a hopeful strategy for diabetes treatment, whereas lack of pancreas donors leads this strategy to a dilemma. Here, we demonstrate that Trop2 is a useful marker to enrich the progenitors with a long-term organoid formation capability from extrahepatic bile ducts in both mouse and human. Based on BMP7 initiation, the Trop2-positive mouse extrahepatic bile duct organoids (mBDOs) could be induced to produce 8.49 {+/-} 0.45% of insulin-secreting cells. We further screened out a chemical small molecule TLY142, which significantly increased the proportion of insulin-secreting cells to 19.9 {+/-} 0.62% and 25.50 {+/-} 4.82% in induced mouse and human extrahepatic bile duct organoids (hBDOs) in vitro, and transplantation of these differentiated organoids into STZ-induced diabetic nude mice remarkably improved their blood glucose and enhanced glucose sensitivity. This study provides a novel strategy that using small molecules promotes biliary duct organoids differentiation into {beta} cells to cure diabetes. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/483710v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@3c85b5org.highwire.dtl.DTLVardef@16e3874org.highwire.dtl.DTLVardef@13c509corg.highwire.dtl.DTLVardef@d0608f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

RIF1-ASF1-mediated high-order chromatin structure safeguards genome integrity

The 53BP1-RIF1 pathway antagonizes resection of DNA broken ends and confers PARP inhibitor sensitivity on BRCA1-mutated tumors. However, it is unclear how this pathway suppresses initiation of resection. Here, we identify ASF1 as a partner of RIF1 via an interacting manner similar to its interactions with histone chaperones CAF-1 and HIRA. ASF1 is recruited to distal chromatin flanking DNA breaks by 53BP1-RIF1 and promotes non-homologous end joining (NHEJ) using its histone chaperone activity. Epistasis analysis shows that ASF1 acts in the same NHEJ pathway as RIF1, but via a parallel pathway with the shieldin complex, which suppresses resection after initiation. Moreover, defects in end resection and homologous recombination (HR) in BRCA1- deficient cells are largely suppressed by ASF1 deficiency. Mechanistically, ASF1 compacts adjacent chromatin by heterochromatinization to protect broken DNA ends from BRCA1-mediated resection. Taken together, our findings identified a RIF1-ASF1 histone chaperone complex that promotes changes in high-order chromatin structure to stimulate the NHEJ pathway for DSB repair.

molecular biology↗