Biology subjects

Zhou, H.

Publications and source records attributed to Zhou, H..

At least 217 records · Page 12Linked to original sources

bioRxiv2023

CRISPR-HOLMES-based NAD+ detection

Studies have indicated that intracellular nicotinamide adenine dinucleotide (NAD+) level is associated with the occurrence and development of many diseases. While traditional NAD+ detection techniques are time-consuming and may require large and expensive instruments. We recently found that the CRISPR-Cas12a protein can be inactivated by AcrVA5-mediated acetylation and reactivated by CobB, using NAD+ as the co-factor. Therefore, here in this study, we created a CRISPR-Cas12a-based one-step HOLMES(NAD) system for rapid and convenient NAD+ detection with the employment of both acetylated Cas12a and CobB. In HOLMES(NAD), acetylated Cas12a losses its trans-cleavage activates and can be reactivated by CobB at the presence of NAD+, cutting ssDNA reporters to generate fluorescence signals. HOLMES(NAD) shows both sensitivity and specificity in NAD+ detection and can be used for quantitative determination of intracellular NAD+ concentrations. Therefore, HOLMES(NAD) not only provides a convenient and rapid approach for target NAD+ quantitation but also expands the application scenarios of HOLMES to non-nucleic acid detection.

molecular biology↗

bioRxiv2023

Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing

A comprehensive understanding of the human pluripotent stem cell (hPSC) differentiation process stands as a prerequisite for the development hPSC-based therapeutics. In this study, single-cell RNA-sequencing (scRNA-seq) was performed to decipher the heterogeneity during differentiation of three hPSC lines towards corneal limbal stem cells (LSCs). The scRNA-seq data revealed nine clusters encompassing the entire differentiation process, among which five followed the anticipated differentiation path of LSCs. The remaining four clusters were previously undescribed cell states that were annotated as either mesodermal-like or undifferentiated subpopulations, and their prevalence was hPSC line-dependent. Distinct cluster-specific marker genes identified in this study were confirmed by immunofluorescence analysis and employed to purify hPSC-derived LSCs, which effectively minimized the variation in the line-dependent differentiation efficiency. In summary, scRNA-seq offered molecular insights into the heterogeneity of hPSC-LSC differentiation, allowing a data-driven strategy for consistent and robust generation of LSCs, essential for future advancement toward clinical translation. HighlightsO_LIhPSCs to LSCs spans epithelial, mesodermal, and undifferentiated cell states. C_LIO_LIscRNA-seq reveals the cell line-dependent differentiation heterogeneity. C_LIO_LIITGA6 and AREG can be used to select pure LSC-like subpopulation. C_LI

cell biology↗

bioRxiv2023

Whole genome association testing in 333,100 individuals across three biobanks identifies rare non-coding single variant and genomic aggregate associations with height

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N=200,003), TOPMed (N=87,652) and All of Us (N=45,445). We performed rare (<0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal, intergenic and deep-intronic annotation. We observed 29 independent variants associated with height at P < 6 x 10-10 after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed a novel approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

genetics↗

bioRxiv2023

Lymphatic muscle cells are unique cells that undergo aging induced changes

Lymphatic muscle cells (LMCs) within the wall of collecting lymphatic vessels exhibit tonic and autonomous phasic contractions, which drive active lymph transport to maintain tissue-fluid homeostasis and support immune surveillance. Damage to LMCs disrupts lymphatic function and is related to various diseases. Despite their importance, knowledge of the transcriptional signatures in LMCs and how they relate to lymphatic function in normal and disease contexts is largely missing. We have generated a comprehensive transcriptional single-cell atlas--including LMCs--of collecting lymphatic vessels in mouse dermis at various ages. We identified genes that distinguish LMCs from other types of muscle cells, characterized the phenotypical and transcriptomic changes in LMCs in aged vessels, and uncovered a pro-inflammatory microenvironment that suppresses the contractile apparatus in advanced-aged LMCs. Our findings provide a valuable resource to accelerate future research for the identification of potential drug targets on LMCs to preserve lymphatic vessel function as well as supporting studies to identify genetic causes of primary lymphedema currently with unknown molecular explanation.

cell biology↗

bioRxiv2023

Leveraging Graph Machine Learning for Moonlighting Protein Prediction: A Local PPI Network and Physiochemical Feature Approach

Moonlighting proteins are those proteins that perform more than one distinct function in the body. They are pivotal in various metabolic pathways and disease mechanisms. Identifying moonlighting proteins remains a challenge in Computational Biology. In this work, we propose the first graph neural network based models to identify moonlighting proteins. Our models work on large protein-protein interaction (PPI) networks with sparse labels of moonlighting and non-moonlighting proteins. In addition to PPI network, the models make use of features derived from the amino acid sequences of the proteins. We propose two frameworks: one as graph classification based on the local neighborhood of the query protein; and the other node classification based on the entire graph. These GNN-based methods outperform traditional machine learning methods that have previously been used for moonlighting prediction. The global full network-based model, operating on Homo sapiens data achieves accuracy of 88.4% and F1 score of 88.8%. The local neighborhood method is more lightweight and can be applied to larger protein sets with multiple species. CCS CONCEPTS* Applied computing [->] Computational proteomics.

bioinformatics↗

bioRxiv2023

Renal Angptl4 is a key fibrogenic molecule in progressive diabetic kidney disease

Angiopoietin-like 4 (ANGPTL4) is the key protein involved in lipoprotein metabolism and has been shown to have diverse effects on tissue protection. In clinical settings, there is a reported association between higher levels of plasma Angptl4 and features of diabetic kidney disease, however, the association between kidney Angptl4 with features of diabetic kidney disease has not been well investigated. We show that both podocyte-and tubule-specific ANGPTL4 are crucial fibrogenic molecules in diabetes. Results from mRNA-array analysis in control (non-fibrotic) and diabetic (fibrotic) kidneys suggest time-dependent emergence of Angplt4 expression. Diabetes accelerates the fibrogenic phenotype in control mice but not in ANGPTL4 mutant mice. The protective effect observed in ANGPTL4 mutant mice is correlated with a reduction in the levels of pro-inflammatory cytokines, epithelial-to-mesenchymal transition, endothelial-to-mesenchymal transition and augmented fatty acid oxidation. Mechanistically, we demonstrate that podocyte-or tubule-secreted Angptl4 interacts with Integrin-{beta}1 and influences the association between dipeptidyl-4 with Integrin-{beta}1 and promotes heterodimerization of transforming growth factor-{beta} receptor 1 (TGF{beta}R1) and TGF{beta}R2 in cultured cells. This in turn results in Smad3 phosphorylation and subsequent downregulation of the expression of genes involved in fatty acid oxidation; these cumulative effects led to the activation of fibrogenic phenotypes. We demonstrate the utility of a targeted pharmacologic therapy that specifically inhibits Angptl4 gene expression in the kidneys and protects diabetic kidneys from proteinuria and fibrosis. Importantly, use of this kidney-specific targeted strategy is beneficial and does not cause any harmful effect suggesting it can be used as a novel drug molecule for treatment of diabetic kidney disease. Taken together, these data demonstrate that podocyte-and tubule-derived Angptl4 is fibrogenic in diabetic kidneys.

cell biology↗

bioRxiv2023

Identification of A Potential Inhibitor for Anticancer Target MTHFD2 by Consensus Docking and Molecular Dynamics

The bifunctional methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD2) has been recognized as a promising anticancer drug target because it is overexpressed in various types of cancer and is associated with poor prognosis. In the present study, we aimed to discover potential inhibitors from the Enamine HTS library which consists of over one million compounds. A consensus docking-based virtual screening workflow was adopted and two hits, E96 and E41, were identified for being ranked in the top 5 in all docking programs used. To validate the virtual screening result, the binding modes of the two hits were visually inspected with reference to previously published inhibitors B01 and D56, and a similar pattern of binding was observed between the hits and established ligands, indicating the reliability of the docking protocol. The subsequent molecular dynamics simulation and a series of analyses including root mean square deviation, root mean square fluctuation, and radius of gyration reveal that E96 achieved a more stable binding to the receptor than E41. The binding free energy predicted by MM/GBSA calculation confirms E96s potential to be a potent inhibitor for the target MTHFD2 as it outperforms E41 and the established ligands. In conclusion, this computational study contributes to the drug discovery efforts for the anticancer drug target MTHFD2 by suggesting ligand E96 for further structure-based optimization and in vitro/vivo experimental validation.

biochemistry↗

bioRxiv2023

DeepVASP-S: a deep-learning tool for explaining steric mechanism that controls binding specificity

DeepVASP-S is a computational tool that leverages the capabilities of convolutional neural networks (CNNs) to analyze steric aspects of protein-ligand interactions and predict amino acid contributions to binding specificity. This tool combines structural bioinformatics with machine learning to address the complex problem of understanding how specific amino acids contribute to the specificity of binding. Here, we use this tool to predict subclasses for Enolase and Serine Protease according to their binding specificity, and explain it through the underlying steric mechanism. The strength of DeepVASP-S lies in its ability to identify and highlight these specific regions, providing researchers with insights into the molecular determinants of protein function and interaction. Such information is extremely valuable for the field of drug design, as it enables the creation of more targeted and effective therapeutics with minimized side effects. The approach taken by DeepVASP-S represents a significant step forward in computational biochemistry, merging high-resolution 3D structural data with the predictive power of machine learning to unlock a deeper understanding of protein-ligand interactions.

bioinformatics↗

bioRxiv2023

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

genetics↗

bioRxiv2023

Deletion of CD44 promotes adipogenesis by regulating PPARγ and cell cycle-related pathways

CD44, a cell surface adhesion receptor and stem cell biomarker, is recently implicated in chronic metabolic diseases. Ablation of CD44 ameliorates adipose tissue inflammation and insulin resistance in obesity. Here, we investigated cell type specific CD44 expression in human and mouse adipose tissue and further studied how CD44 in preadipocytes regulates adipocyte function. Using Crispr Cas9-mdediated gene deletion and lentivirus-mediated gene re-expression, we discovered that deletion of CD44 promotes adipocyte differentiation and adipogenesis, whereas re-expression of CD44 abolishes this effect and decreases insulin responsiveness and adiponectin secretion in 3T3-L1 cells. Mechanistically, CD44 does so via suppressing Pparg expression. Using quantitative proteomics analysis, we further discovered that cell cycle-regulated pathways were mostly decreased by deletion of CD44. Indeed, re-expression of CD44 moderately restored expression of proteins involved in all phases of the cell cycle. Our data suggest that CD44 plays a crucial role in regulating adipogenesis and adipocyte function possibly through regulating PPAR{ballotbox} and cell cycle-related pathways. This study provides evidence for the first time that CD44 expressed in preadipocytes plays key roles in regulating adipocyte function outside immune cells where CD44 is primarily expressed. Therefore, targeting CD44 in (pre)adipocytes may provide therapeutic potential to treat obesity-associated metabolic complications.

cell biology↗

bioRxiv2023

Multi-omics analysis reveals novel interplays between intratumoral bacteria and glioma

Emerging evidence highlights the potential impact of intratumoral microbiota on cancer. However, the microbial composition and function in glioma remains elusive. Consequently, our study aimed to investigate the microbial community composition in glioma tissues and elucidate its role in glioma development. We parallelly performed microbial profiling, transcriptome sequencing and metabolomics detection on tumor and adjacent normal brain tissues obtained from 50 glioma patients. We employed immunohistochemistry, multicolor immunofluorescence and FISH staining to observe the presence and location of bacteria. Furthermore, an animal model was employed to validate the impact of key bacteria on glioma development. Six genera were found to be significantly enriched in glioma tissues compared to its adjacent normal brain tissues, including Fusobacterium, Longibaculum, Intestinimonas, Pasteurella, Limosilactobacillus and Arthrobacter. Both bacterial RNA and LPS were observed in glioma tissues. Multicolor immunofluorescence analysis showed higher bacterial LPS levels in tumor cells than in macrophages and in glioma tissue than in adjacent normal brain tissue. Integrated microbiomics, transcriptomics, and metabolomics revealed that genes associated with intratumoral microbes were enriched in multiple synapse-associated pathways and that metabolites associated with intratumoral microbes were (R)-N-methylsalsolinol, N-acetylaspartylglutamic acid, and N-acetyl-L-aspartic acid. Further mediation analysis suggested that intratumoral microbiome may affect the expression of neuron-related genes through bacteria-associated metabolites. In addition, a glioma mouse model suggested that Fusobacterium nucleatum promoted glioma growth by increasing the levels of N-acetylneuraminic acid and the expression levels of CCL2, CXCL1, and CXCL2. In conclusion, our findings shed light on the intricate interplays between intratumoral bacteria and glioma.

neuroscience↗

bioRxiv2023

SONATA: Disambiguated manifold alignment of single-cell data

Recent advances in single-cell multimodal omics technologies enable the exploration of cellular systems at unprecedented resolution, leading to the rapid generation of multimodal datasets that require sophisticated integration methods. Diagonal integration has emerged as a flexible solution for integrating heterogeneous single-cell data without relying on shared cells or features. However, the absence of anchoring elements introduces the risk of artificial integrations, where cells across modalities are incorrectly aligned due to ambiguous mapping. To address this challenge, we propose SONATA, a novel diagnostic method designed to detect potential artificial integrations resulting from ambiguous mappings in diagonal data integration. SONATA identifies ambiguous alignments by quantifying cell-cell ambiguity within the data manifold, ensuring that biologically meaningful integrations are distinguished from spurious ones. It is worth noting that SONATA is not designed to replace any existing pipelines for diagonal data integration; instead, SONATA works simply as an add-on to an existing pipeline for achieving more reliable integration. Through comprehensive evaluation on both simulated and real multimodal single-cell datasets, we observe that artificial integrations in diagonal data integration are widespread yet surprisingly overlooked, occurring across all mainstream diagonal integration methods. We demonstrate SONATAs ability to safeguard against misleading integrations and provide actionable insights into potential integration failures across mainstream methods. Our approach offers a robust framework for ensuring the reliability and interpretability of multimodal single-cell data integration. 1

bioinformatics↗

bioRxiv2023

mtx-COBRA: Subcellular localization prediction for bacterial proteins

BackgroundBacteria can have beneficial effects on our health and environment; however, many are responsible for serious infectious diseases, warranting the need for vaccines against such pathogens. Bioinformatic and experimental technologies are crucial for the development of vaccines. The vaccine design pipeline requires identification of bacteria-specific antigens that can be recognized and induce a response by the immune system upon infection. Immune system recognition is influenced by the location of a protein. Methods have been developed to determine the subcellular localization (SCL) of proteins in prokaryotes and eukaryotes. Bioinformatic tools such as PSORTb can be employed to determine SCL of proteins, which would be tedious to perform experimentally. Unfortunately, PSORTb often predicts many proteins as having an "Unknown" SCL, reducing the number of antigens to evaluate as potential vaccine targets. MethodWe present a new pipeline called subCellular lOcalization prediction for BacteRiAl Proteins (mtx-COBRA). mtx-COBRA uses Metas protein language model, Evolutionary Scale Modeling, combined with an Extreme Gradient Boosting machine learning model to identify SCL of bacterial proteins based on amino acid sequence. This pipeline is trained on a curated dataset that combines data from UniProt and the publicly available ePSORTdb dataset. ResultsUsing benchmarking analyses, nested 5-fold cross-validation, and leave-one-pathogen-out methods, followed by testing on the held-out dataset, we show that our pipeline predicts the SCL of bacterial proteins more accurately than PSORTb. Conclusionsmtx-COBRA provides an accessible pipeline with greater efficiency to classify bacterial proteins with currently "Unknown" SCLs than existing bioinformatic and experimental methods.

bioinformatics↗

bioRxiv2023

Arrested Agonist Paradigm For Selective Radiosensitization of Prostate Cancer

As a prototypical nuclear hormone receptor, the androgen receptor (AR) signals via a sequential cascade triggered by binding to androgenic ligands such as testosterone and dihydrotestosterone (DHT). This cascade includes dimerization of the ligand-receptor complex, nuclear translocation, chromatin binding to response elements, recruitment of TOP2B and co-activator complexes, and induction of an effector transcriptional program. In prostate cancers, this AR signaling cascade is an essential driver of growth and survival, yet its activity confers potential vulnerabilities through transient TOP2B-mediated DNA double strand breaks. We investigated the ability of non-steroidal AR ligands to activate initial steps of the AR signaling cascade up to the point of AR- and TOP2B-mediated double strand breaks, with subsequent arrest of the signaling cascade to prevent induction of pro-growth/survival transcriptional programs in prostate cancer cells. We identified hydroxyflutamide (FLU) as such an androgen receptor arrested agonist; in androgen-deprived conditions, FLU induced AR nuclear translocation, chromatin binding, and TOP2B-mediated double strand breaks, but failed to induce AR target gene expression and prostate cancer cell growth. The FLU-mediated arrest in the signaling cascade could be attributed to the inability of FLU to allow association of AR with SMARCD2, a critical component of the BAF chromatin remodeling complex required for androgen induced AR co-activation. Interestingly, the FLU-induced, AR- and TOP2B-mediated double strand breaks could be used to selectively sensitize AR-positive prostate cancer cells to ionizing radiation in vitro and in vivo. These findings support a novel arrested agonist paradigm for selective radiosensitization of prostate cancer cells without inducing AR-mediated pro-growth and survival transcriptional programs.

cancer biology↗

bioRxiv2023

Central pore-opening structure and gating of the mechanosensitive PIEZO1 channel

PIEZO1 is a mechanically activated cation channel that undergoes force-induced activation and inactivation to control diverse physiological processes1-4. However, the distinct functional states and gating transitions remain structurally undefined. In response to changes in membrane forces, PIEZO1 transitions from a curved to a flattened shape, which might lead to opening and subsequent inactivation of the ion-conducting pore5,6. Here we employed a PIEZO1 mutant to capture various conformational states including an intermediate state with an opened central pore, allowing us to reveal the gating dynamics of this multiple-gate system. Upon transition from the curved to the partially flattened intermediate state, the trimeric cap undergoes a downward and rotational motion to open the lateral cap-gate, while the loop that connects the cap to the pore-lining inner helix acts as a spring-linker, switching from an extended to a compressed state. Along with the partial flattening of the peripheral blades, these conformational changes collectively dilate the cap-gate, spring-gate and the hydrophobic transmembrane-gate, leading to ion permeation through the transmembrane pore. Upon inactivation, while the blades remain flattened, the cap and spring-linker return to an up and extended state. Molecular dynamics simulations verify the ion-permeating pathway and the distinct ion-conducting states of the assigned close, intermediate, open, and inactivated structures. Mutagenesis and electrophysiological characterizations reveal that domains and residues involved in conformational dynamics of the cap and spring-linker are critical for mechanical activation of PIEZO1. Together, these studies have structurally defined the distinct functional states and the curvature-based activation and inactivation mechanisms of PIEZO1.

neuroscience↗

bioRxiv2023

Bacterial antiviral defense pathways encode eukaryotic-like ubiquitination systems

Ubiquitination and related pathways play crucial roles in protein homeostasis, signaling, and innate immunity1-3. In these pathways, an enzymatic cascade of E1, E2, and E3 proteins conjugates ubiquitin or a ubiquitin-like protein (Ubl) to targetprotein lysine residues4. Bacteria encode ancient relatives of E1 and Ubl proteins involved in sulfur metabolism5,6 but these proteins do not mediate Ubl-target conjugation, leaving open the question of whether bacteria can perform ubiquitination-like protein conjugation. Here, we demonstrate that a bacterial antiviral immune system encodes a complete ubiquitination pathway. Two structures of a bacterial E1:E2:Ubl complex reveal striking architectural parallels with canonical eukaryotic ubiquitination machinery. The bacterial E1 encodes an N-terminal inactive adenylation domain (IAD) and a C-terminal active adenylation domain (AAD) with a mobile -helical insertion containing the catalytic cysteine (CYS domain). One structure reveals a pre-reaction state with the bacterial Ubl C-terminus positioned for adenylation, and the E1 CYS domain poised nearby for thioester formation. A second structure mimics an E1-to-E2 transthioesterification state, with the E1 CYS domain rotated outward and its catalytic cysteine adjacent to the bound E2. We show that a deubiquitinase (DUB) in the same pathway pre-processes the bacterial Ubl, exposing its C-terminal glycine for adenylation. Finally, we show that the bacterial E1 and E2 collaborate to conjugate Ubl to target-protein lysine residues. Together, these data reveal that bacteria possess bona fide ubiquitination systems with strong mechanistic and architectural parallels to canonical eukaryotic ubiquitination pathways, suggesting that these pathways arose first in bacteria.

biophysics↗

bioRxiv2023

Estimation of Genetic Admixture Proportions via Haplotypes

Estimation of ethnic admixture is essential for creating personal genealogies, studying human history, and conducting genome-wide association studies (GWAS). Three methods exist for estimating admixture coefficients. The frequentist approach directly maximizes the binomial loglikelihood. The Bayesian approach adds a reasonable prior and samples the posterior distribution. Finally, the nonparametric approach decomposes the genotype matrix algebraically. Each approach scales successfully to data sets with a million individuals and a million single nucleotide polymorphisms (SNPs). Despite their variety, all current approaches assume independence between SNPs. To achieve independence requires performing LD (linkage disequilibrium) filtering before analysis. Unfortunately, this tactic loses valuable information and usually retains many SNPs still in LD. The present paper explores the option of explicitly incorporating haplotypes in ancestry estimation. Our program, HaploADMIXTURE, operates on adjacent SNP pairs and jointly estimates their haplotype frequencies along with admixture coefficients. This more complex strategy takes advantage of the rich information available in haplotypes and ultimately yields better admixture estimates and better clustering of real populations in curated data sets.

bioinformatics↗

bioRxiv2023

Cancer immunotherapy responses persist after lymph node resection

Lymphatic transport facilitates the presentation of cancer antigens in tumor-draining lymph nodes (tdLNs), leading to T cell activation and the generation of systemic anti-cancer immune surveillance. Surgical removal of tdLNs to control cancer progression is routine in clinical practice. However, whether removing tdLNs impairs immune checkpoint blockade (ICB) is still controversial. Our analysis demonstrates that melanoma patients remain responsive to PD-1 checkpoint blockade after regional LN dissection. We were able to recapitulate the persistent response to ICB after regional LN resection in murine melanoma and mammary carcinoma models. Mechanistically, soluble antigen is diverted to distant LNs after tdLN dissection. Consistently, robust ICB responses in patients with head and neck cancer after primary tumor and tdLN resection correlated with the presence of reactive LNs in distant sites. These findings indicate that distant LNs sufficiently compensate for the removal of direct tdLNs and sustain the response to ICB.

cancer biology↗