Biology subjects

Dong, M.

Publications and source records attributed to Dong, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Extensive remodelling of XIST regulatory networks during primate evolution

Unravelling how gene regulatory networks are remodelled during evolution is crucial to understand how species adapt to environmental changes. We addressed this question for X-chromosome inactivation, a process essential to female development that is governed, in eutherians, by the XIST lncRNA and its cis-regulators. To reach high resolution, we studied closely related primate species, spanning 55 million years of evolution. We show that the XIST regulatory circuitry has diversified extensively over such evolutionary timeframe. The insertion of a HERVK transposon has reshuffled XIST 3D interaction network in macaque embryonic stem cells (ESC) and XIST expression is maintained by the additive effects of the JPX lncRNA gene and a macaque specific enhancer. In contrast, JPX is the main contributor to XIST expression in human ESCs but is not significantly involved in XIST regulation in marmoset ESCs. None of these entities are however under purifying selection, which suggests that neutrally evolving non-coding elements harbour high adaptive potentials.

genomics↗

bioRxiv2023

Deep identifiable modeling of single-cell atlases enables zero-shot query of cellular states

How to identify true biological differences across samples while overcoming batch effects has been a persistent challenge in single-cell RNA-seq data analysis, hindering analyses across datasets for transferable biological findings. In this work, we show that scaling up deep identifiable models leads to a surprisingly effective solution for this challenging task. We developed scShift, a deep variational inference framework with theoretical support in disentangling batch-dependent and independent variations. By training the model with compendiums of scRNA-seq atlases, scShift shows remarkable zero-shot capabilities in revealing representations of cell types and biological states in single-cell data while overcoming batch effects. We employed scShift to systematically compare lung fibrosis states across different datasets, tissues and experimental systems. scShift uniquely extrapolates lung fibrosis states to previously unseen post-COVID-19 fibrosis, characterizing universal myeloid-fibrosis signatures, potential repurposing drug targets and fibrosis-associated cell interactions. Evaluations of over 200 trained scShift models demonstrate emergent zero-shot capabilities and a scaling law beyond a transition threshold, with respect to dataset diversity. With its scaling performance on massive single-cell compendiums and exceptional zero-shot capabilities, scShift represents an important advance toward next-generation computational models for single-cell analysis.

bioinformatics↗

bioRxiv2023

SIMVI reveals intrinsic and spatial-induced states in spatial omics data

Spatial omics technologies enable the analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing computational methods may not properly distinguish cellular intrinsic variability and intercellular interactions, and may thus fail to capture spatial regulations for further biological discoveries. Here, we present Spatial Interaction Modeling using Variational Inference (SIMVI), an annotation-free framework that disentangles cell intrinsic and spatial-induced latent variables for modeling gene expression in spatial omics data. We derive theoretical support for SIMVI in disentangling intrinsic and spatial-induced variations. By this disentanglement, SIMVI enables estimation of spatial effects (SE) at a single-cell resolution, and opens up various opportunities for novel downstream analyses. To demonstrate the potential of SIMVI, we applied SIMVI to spatial omics data from diverse platforms and tissues (MERFISH human cortex, Slide-seqv2 mouse hippocampus, Slide-tags human tonsil, spatial multiome human melanoma, cohort-level CosMx melanoma). In all tested datasets, SIMVI effectively disentangles variations and infers accurate spatial effects compared with alternative methods. Moreover, on these datasets, SIMVI uniquely uncovers complex spatial regulations and dynamics of biological significance. In the human tonsil data, SIMVI illuminates the cyclical spatial dynamics of germinal center B cells during maturation. Applying SIMVI to both RNA and ATAC modalities of the multiome melanoma data reveals potential tumor epigenetic reprogramming states. Application of SIMVI on our newly-collected cohort-level CosMx melanoma dataset uncovers space-and-outcome-dependent macrophage states and the underlying cellular communication machinery in the tumor microenvironments.

bioinformatics↗

bioRxiv2023

Identification of a botulinum neurotoxin-like gene cluster in Bacillus toyonensis

Clostridial neurotoxins, which include botulinum neurotoxins (BoNTs) and tetanus neurotoxin (TeNT) are the most potent toxins known, and are the causative agents of the neuroparalytic diseases, botulism and tetanus. Until recently, the clostridial neurotoxin family was restricted to the genus Clostridium, but members of this protein family have been found in a growing number of non-Clostridium species including Weissella, Enterococcus, and Paraclostridium. Here, we report the bioinformatic identification and analysis of a novel clostridial neurotoxin homolog in a Bacillus toyonensis genome recently deposited into the NCBI Genbank database. This putative toxin shares 26-29% identity with its closest BoNT relatives, suggesting that it is likely a novel BoNT-like toxin. It possesses key functional motifs (e.g., HExxH) indicative of toxin protease activity, contains the four characteristic BoNT domains, and is located in a BoNT-like genomic neighborhood containing the upstream non-toxic non-hemagglutinin (NTNH) gene as well as several P47-related genes. Phylogenetically, the toxin clusters as a divergent member of the recently discovered lineage of BoNT-like toxins that includes BoNT/X, BoNT/En, and the insecticidal PMP1. Genomic analysis of the B. toyonensis isolate CH177 revealed additional virulence factors and toxin genes indicative of potential pathogenicity targeting an unknown host species. The Bacillus toyonensis BoNT-like protein (BTNT) adds to a growing number of non-clostridial BoNT-like toxins, adding further information on the intriguing phylogenetic distribution and evolutionary history of the most potent toxins known.

bioinformatics↗

bioRxiv2023

Structure and activity of botulinum neurotoxin X

Botulinum neurotoxins (BoNTs) are the most potent toxins known and are used to treat an increasing number of medical disorders. All BoNTs are naturally co-expressed with a protective partner protein (NTNH) with which they form a 300 kDa complex, to resist acidic and proteolytic attack from the digestive tract. We have previously identified a new botulinum neurotoxin serotype, BoNT/X, that has unique and therapeutically attractive properties. We present the cryo-EM structure of the BoNT/X-NTNH/X complex at 3.1 [A] resolution. Unexpectedly, the BoNT/X complex is stable and protease resistant at both neutral and acidic pH and disassembles only in alkaline conditions. Using the stabilizing effect of NTNH, we isolated BoNT/X and showed that it has very low potency both in vitro and in vivo. Given the high catalytic activity and translocation efficacy of BoNT/X, low activity of the full toxin is likely due to the receptor-binding domain, which presents weak ganglioside binding and exposed hydrophobic surfaces.

biochemistry↗

bioRxiv2023

Epigenetically silenced DACT3 promotes tumor growth via affecting Wnt/beta-catenin signaling and supports chidamide plus azacitidine therapy in acute myeloid leukemia

BackgroundDACT gene is a potential Wnt antagonist and tumor suppressor gene. However, the expression of DACT gene in acute myeloid leukemia (AML) and its role are still unknown. MethodsIn this study, we first multidimensionally analyzed the expression of DACT gene in AML through RNA seq, qRT-PCR and Western blotting analysis as well as TCGA database analysis. Then DACT3 was identified as playing a critical role in AML, and its clinical significance was further explored. The molecular mechanism of DACT3 down-regulation in AML from aspects of DNA methylation and histone acetylation were inquired. Finally, the biological functions of DACT3 in AML were investigated by cell models in vitro and animal experiments in vivo. ResultsCompared with DACT1 and DACT2, DACT3 was the most differentially expressed DACT family member in AML, suggesting that DACT3 plays the major role. The mRNA and protein expression levels of DACT3 were significantly decreased and positively correlated in AML. Moreover, low expression of DACT3 is associated with no remission disease status and poor prognosis in AML patients. In addition, down-regulation of DACT3 in AML was not completely dependent on promoter methylation, but also affected by histone deacetylation. We found that loss of DACT3 in AML is related to activation of Wnt signaling pathway. Furthermore, DACT3 inhibits the growth of AML cells in vitro and in severe immunodeficiency (SCID) mice. Importantly, DACT3 improved the sensitivity of adriamycin in treating AML cells. Further research showed that co-treatment of chidamide and azacytidine up-regulates DACT3 expression and promotes cell apoptosis via inhibiting Wnt/{beta}-catenin signaling in AML, suggesting a promising therapeutic prospects in FLT3-mutant AML. ConclusionThis is the first study revealing the epigenetic regulatory molecular mechanism of the down regulated expression of DACT3 in AML. Our data also shows that DACT3 is a candidate gene for therapeutic target and targeting DACT3 has the potential to validate the combination therapy of DNMT inhibitors and HDAC inhibitors.

molecular biology↗

bioRxiv2022

Identification of divergent botulinum neurotoxin homologs in Paeniclostridium ghonii

Botulinum neurotoxins (BoNTs) are the most potent family of toxins known to science. Bioinformatic studies in recent years have revealed that they are members of a broader toxin family, with an increasing number of divergent homologs identified in genomes of organisms outside of the Clostridium genus. Here, we report the identification of two putative divergent BoNT-like homologs in the genomes of two strains of Paeniclostridium ghonii. We designated them PG-toxin 1 (PGT1) and PG-toxin 2 (PGT2), which share ~54% protein sequence identity. Unlike any other known BoNT homologs, PGT1 and PGT2 are composed of two separate subunits encoded on two neighboring genes: one encoding the protease domain (light chain, LC) with a conserved HExxH motif, and the second encoding the heavy-chain (HC) containing the putative translocation domain and receptor-binding domain. Phylogenetic analysis of both the LC and HC reveal that it is a divergent member of the lineage of BoNT that also includes BoNT/X, BoNT/En and the insecticidal PMP1. The gene clusters harboring PGT1 and PGT2 also include a putative insecticidal delta-endotoxin, Cry8Ea1, as well as putative endolysin and bacteriocin genes that may facilitate lytic toxin secretion, suggesting a possibility that this gene cluster might serve an insecticidal purpose.

bioinformatics↗

bioRxiv2022

Ori-Finder 2022: A Comprehensive Web Server for Prediction and Analysis of Bacterial Replication Origins

The replication of DNA is a complex biological process that is essential for life. Bacterial DNA replication is initiated at genomic loci referred to as replication origins (oriCs). Integrating the Z-curve method, DnaA box distribution, and comparative genomic analysis, we developed a web server to predict bacterial oriCs in 2008 called Ori-Finder, which contributes to clarify the characteristics of bacterial oriCs. The oriCs of hundreds of sequenced bacterial genomes have been annotated in their genome reports using Ori-Finder and the predicted results have been deposited in DoriC, a manually curated database of oriCs. This has facilitated large-scale data mining of functional elements in oriCs and strand-biased analysis. Here, we describe Ori-Finder 2022 with updated prediction framework, interactive visualization module, new analysis module, and user-friendly interface. More species-specific indicator genes and functional elements of oriCs are integrated into the updated framework, which has also been redesigned to predict oriCs in draft genomes. The interactive visualization module displays more genomic information related to oriCs and their functional elements. The analysis module includes regulatory protein annotation, repeat sequence discovery, homologous oriC search, and strand-biased analyses. The redesigned interface provides additional customization options for oriC prediction. Ori-Finder 2022 is freely available at http://tubic.tju.edu.cn/Ori-Finder2022 and https://tubic.org/Ori-Finder2022.

bioinformatics↗

bioRxiv2022

Causal identification of single-cell experimental perturbation effects with CINEMA-OT

Recent advancements in single-cell technologies allow characterization of experimental perturbations at single-cell resolution. While methods have been developed to analyze such experiments, the application of a strict causal framework has not yet been explored for the inference of treatment effects at the single-cell level. In this work, we present a causal inference based approach to single-cell perturbation analysis, termed CINEMA-OT (Causal INdependent Effect Module Attribution + Optimal Transport). CINEMA-OT separates confounding sources of variation from perturbation effects to obtain an optimal transport matching that reflects counterfactual cell pairs. These cell pairs represent causal perturbation responses permitting a number of novel analyses, such as individual treatment effect analysis, response clustering, attribution analysis, and synergy analysis. We benchmark CINEMA-OT on an array of treatment effect estimation tasks for several simulated and real datasets and show that it outperforms other single-cell perturbation analysis methods. Finally, we perform CINEMA-OT analysis of two newly-generated datasets: (1) rhinovirus and cigarette smoke-exposed airway organoids, and (2) combinatorial cytokine stimulation of immune cells. In these experiments, CINEMA-OT reveals potential mechanisms by which cigarette smoke exposure dulls the airway antiviral response, as well as the logic that governs chemokine secretion and peripheral immune cell recruitment.

bioinformatics↗

bioRxiv2022

Ancient Clostridium DNA and variants of tetanus neurotoxins associated with human archaeological remains

The analysis of microbial genomes from human archaeological samples offers a historic snapshot of ancient pathogens and provides insights into the origins of modern infectious diseases. Here, through a large-scale metagenomic analysis of archeological samples, we discovered bacterial species related to modern-day Clostridium tetani, which produces the tetanus neurotoxin (TeNT) and causes the disease tetanus. We assembled draft genomes from 38 distinct human archeological samples spanning five continents and dating to as early as ~4000 BCE. These genomes had varying levels of completeness and a subset of them displayed hallmarks of ancient DNA damage. While 24 fall into known C. tetani clades, phylogenetic analysis revealed novel C. tetani lineages, as well as two novel Clostridium species ("Clostridium sp. X and Y") closely related to C. tetani. Within these genomes, we found 13 TeNT variants with unique substitution profiles, including a subgroup of TeNT variants found exclusively in ancient samples from South America. We experimentally tested a TeNT variant selected from a ~6000-year-old Chilean mummy sample and found that it induced tetanus muscle paralysis in mice with potency comparable to modern TeNT. Our work identifies neurotoxigenic C. tetani in ancient DNA, new Clostridium species unique to ancient human samples, and a novel variant of TeNT that can cause disease in mammals.

genomics↗

bioRxiv2021

Monospecific and bispecific monoclonal SARS-CoV-2 neutralizing antibodies that maintain potency against B.1.617

COVID-19 pathogen SARS-CoV-2 has infected hundreds of millions and caused over 5 million deaths to date. Although multiple vaccines are available, breakthrough infections occur especially by emerging variants. Effective therapeutic options such as monoclonal antibodies (mAbs) are still critical. Here, we report the development, cryo-EM structures, and functional analyses of mAbs that potently neutralize SARS-CoV-2 variants of concern. By high-throughput single cell sequencing of B cells from spike receptor binding domain (RBD) immunized animals, we identified two highly potent SARS-CoV-2 neutralizing mAb clones that have single-digit nanomolar affinity and low-picomolar avidity, and generated a bispecific antibody. Lead antibodies showed strong inhibitory activity against historical SARS-CoV-2 and several emerging variants of concern. We solved several cryo-EM structures at [~]3 [A] resolution of these neutralizing antibodies in complex with prefusion spike trimer ectodomain, and revealed distinct epitopes, binding patterns, and conformations. The lead clones also showed potent efficacy in vivo against authentic SARS-CoV-2 in both prophylactic and therapeutic settings. We also generated and characterized a humanized antibody to facilitate translation and drug development. The humanized clone also has strong potency against both the original virus and the B.1.617.2 Delta variant. These mAbs expand the repertoire of therapeutics against SARS-CoV-2 and emerging variants.

immunology↗

bioRxiv2021

Systems immune profiling of variant-specific vaccination against SARS-CoV-2

Lipid-nanoparticle(LNP)-mRNA vaccines offer protection against COVID-19. However, multiple variant lineages caused widespread breakthrough infections. There is no report on variant-specific vaccines to date. Here, we generated LNP-mRNAs specifically encoding wildtype, B.1.351 and B.1.617 SARS-CoV-2 spikes, and systematically studied their immune responses in animal models. All three LNP-mRNAs induced potent antibody responses in mice. However, WT-LNP-mRNA vaccination showed reduced neutralization against B.1.351 and B.1.617; and B.1.617-specific vaccination showed differential neutralization. All three vaccine candidates elicited antigen-specific CD8 and CD4 T cell responses. Single cell transcriptomics of B.1.351-LNP-mRNA and B.1.617-LNP-mRNA vaccinated animals revealed a systematic landscape of immune cell populations and global gene expression. Variant-specific vaccination induced a systemic increase in reactive CD8 T cell population, with a strong signature of transcriptional and translational machineries in lymphocytes. BCR-seq and TCR-seq unveiled repertoire diversity and clonal expansions in vaccinated animals. These data provide direct systems immune profiling of variant-specific LNP-mRNA vaccination in vivo.

immunology↗

bioRxiv2021

Integrative annotation of genomic features reveal functional elements and epigenetic landscapes in the developing zebrafish

Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals.

developmental biology↗

bioRxiv2021

Joint Gene Network Construction by Single-Cell RNA Sequencing Data

SO_SCPLOWUMMARYC_SCPLOWIn contrast to differential gene expression analysis at single gene level, gene regulatory networks (GRN) analysis depicts complex transcriptomic interactions among genes for better understandings of underlying genetic architectures of human diseases and traits. Recently, single-cell RNA sequencing (scRNA-seq) data has started to be used for constructing GRNs at a much finer resolution than bulk RNA-seq data and microarray data. However, scRNA-seq data are inherently sparse which hinders direct application of the popular Gaussian graphical models (GGMs). Furthermore, most existing approaches for constructing GRNs with scRNA-seq data only consider gene networks under one condition. To better understand GRNs under different but related conditions with single-cell resolution, we propose to construct Joint Gene Networks with scRNA-seq data (JGNsc) using the GGMs framework. To facilitate the use of GGMs, JGNsc first proposes a hybrid imputation procedure that combines a Bayesian zero-inflated Poisson (ZIP) model with an iterative low-rank matrix completion step to efficiently impute zero-inflated counts resulted from technical artifacts. JGNsc then transforms the imputed data via a nonparanormal transformation, based on which joint GGMs are constructed. We demonstrate JGNsc and assess its performance using synthetic data. The application of JGNsc on two cancer clinical studies of medulloblastoma and glioblastoma identifies novel findings in addition to confirming well-known biological results.

genetics↗

bioRxiv2021

A SARS-CoV-2 spike ferritin nanoparticle vaccine protects against heterologous challenge with B.1.1.7 and B.1.351 virus variants in Syrian golden hamsters

The emergence of SARS-CoV-2 variants of concern (VOC) requires adequate coverage of vaccine protection. We evaluated whether a spike ferritin nanoparticle vaccine (SpFN), adjuvanted with the Army Liposomal Formulation QS21 (ALFQ), conferred protection against the B.1.1.7 and B.1.351 VOCs in Syrian golden hamsters. SpFN-ALFQ was administered as either single or double-vaccination (0 and 4 week) regimens, using a high (10 g) or low (0.2 g) immunogen dose. Animals were intranasally challenged at week 11. Binding antibody responses were comparable between high- and low-dose groups. Neutralizing antibody titers were equivalent against WA1, B.1.1.7, and B.1.351 variants following two high dose two vaccinations. SpFN-ALFQ vaccination protected against SARS-CoV-2-induced disease and viral replication following intranasal B.1.1.7 or B.1.351 challenge, as evidenced by reduced weight loss, lung pathology, and lung and nasal turbinate viral burden. These data support the development of SpFN-ALFQ as a broadly protective, next-generation SARS-CoV-2 vaccine.

immunology↗

bioRxiv2021

Cysteine dependence in Lactobacillus iners constitutes a novel therapeutic target to modify the vaginal microbiota

Vaginal microbiota composition affects several important reproductive health outcomes. Lactobacillus crispatus-dominant bacterial communities have favorable associations whereas anaerobe-dominant communities deficient of lactobacilli are linked to poor outcomes, including bacterial vaginosis (BV). Lactobacillus iners, the most abundant vaginal species worldwide, has adverse associations compared to L. crispatus, but standard metronidazole treatment for BV promotes L. iners-dominance, likely contributing to post-treatment relapse. L. iners is under-studied because it fails to grow in standard Lactobacillus media in vitro. Here we trace this in vitro phenotype to a species-specific cysteine requirement associated with limitations in cysteine-related transport mechanisms and show that vaginal cysteine concentrations correlate with Lactobacillus abundance in vivo. We demonstrate that cystine uptake inhibitors selectively impede L. iners growth and that combining an inhibitor with metronidazole thus promotes L. crispatus dominance of defined BV-like communities. These findings identify a novel target for therapeutic vaginal microbiota modulation to improve reproductive health.

microbiology↗

bioRxiv2021

Distribution and vulnerability of transcriptional outputs across the genome in Myc-amplified medulloblastoma cells

Myc plays a central role in tumorigenesis by orchestrating the expression of genes essential to numerous cellular processes1-4. While it is well established that Myc functions by binding to its target genes to regulate their transcription5, the distribution of the transcriptional output across the human genome in Myc-amplified cancer cells, and the susceptibility of such transcriptional outputs to therapeutic interferences remain to be fully elucidated. Here, we analyze the distribution of transcriptional outputs in Myc-amplified medulloblastoma (MB) cells by profiling nascent total RNAs within a temporal context. This profiling reveals that a major portion of transcriptional action in these cells was directed at the genes fundamental to cellular infrastructure, including rRNAs and particularly those in the mitochondrial genome (mtDNA). Notably, even when Myc protein was depleted by as much as 80%, the impact on transcriptional outputs across the genome was limited, with notable reduction mostly only in genes involved in ribosomal biosynthesis, genes residing in mtDNA or encoding mitochondria-localized proteins, and those encoding histones. In contrast to the limited direct impact of Myc depletion, we found that the global transcriptional outputs were highly dependent on the activity of Inosine Monophosphate Dehydrogenases (IMPDHs), rate limiting enzymes for de novo guanine nucleotide synthesis and whose expression in tumor cells was positively correlated with Myc expression. Blockage of IMPDHs attenuated the global transcriptional outputs with a particularly strong inhibitory effect on infrastructure genes, which was accompanied by the abrogation of MB cells proliferation in vitro and in vivo. Together, our findings reveal a real time action of Myc as a transcriptional factor in tumor cells, provide new insight into the pathogenic mechanism underlying Myc-driven tumorigenesis, and support IMPDHs as a therapeutic vulnerability in cancer cells empowered by a high level of Myc oncoprotein.

cancer biology↗

bioRxiv2021

TMPs Interaction Domain: A Discovery of Structural Universality Among TMPs Interaction Sites Using Deep Learning Method

Transmembrane proteins (TMPs) serve as important drug targets and accounts for nearly half of the drugs currently available in the market. Research into TMPs interactions and their structural basis will provide key information for drug research and new drug development. Based on previous works like a binding pocket or binding site, our main purpose in this study is to find whether the structural universality (Interaction Domain) exists in all kinds of TMPs interaction regions through a computational approach. After implementing the experiments using our 3D deep learning model and achieve the Matthews correlation coefficient (MCC) of 0.36, we found strong evidence for the existence of the structural basis among TMPs interaction regions. That means those regions, or we call them interaction domains, are structural specific distinguishing to the domains without any interaction. According to this, this work provides a new theoretical basis for TMPs interaction research and can greatly boost the development of the drug industry.

bioinformatics↗