Biology subjects

Gao, X.

Publications and source records attributed to Gao, X..

At least 181 records · Page 10Linked to original sources

bioRxiv2023

Gut microbial genomes with paired isolates from China signify probiotic and cardiometabolic effects

The gut microbiome displays significant genetic differences between populations while systematic characterization of the genomic landscape of the gut microbiome in Asia populations remains limited. Here, we present the Chinese gut microbial reference (CGMR) set, comprising 101,060 high quality metagenomic assembled genomes (MAGs) of 3,707 non-redundant species paired with 1,376 live isolates from a national wide collection of 3,234 fecal samples across China. This improved reference set contains 987 novel species compared with existing resources worldwide. By associating MAGs with geographic and phenotypic characteristics, we observed regional-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. We further conducted mice experiments to confirm the probiotic effects of two Faecalibacterium intestinalis isolates in alleviating constipation, the cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and the functional potential of isolates from the two new species belonging to the genera Parabacteroides and Lactobacillus in host lipids metabolism. Our study not only expands the current microbial genomes with paired isolates but also demonstrates their probiotic and cardiometabolic effects on hosts, contributing to the mechanistic understanding of host-microbe interactions and the translation of microbiome-based personalized therapies.

microbiology↗

bioRxiv2023

Single-Cell Analysis Reveals Cryptic Prophage Protease LfgB Protects Escherichia coli During Oxidative Stress by Cleaving Antitoxin MqsA

Although toxin/antitoxin (TA) systems are ubiquitous, beyond phage inhibition and mobile element stabilization, their role in host metabolism is obscure. One of the best-characterized TA systems is MqsR/MqsA of Escherichia coli, which has been linked previously to protecting this gastrointestinal species during the stress it encounters from the bile salt deoxycholate as it colonizes humans. However, some recent whole-population studies have challenged the role of toxins such as MqsR in bacterial physiology, since the mqsRA locus is induced over a hundred-fold during stress, but a phenotype was not found upon its deletion. Here, we investigate further the role MqsR/MqsA by utilizing single cells and demonstrate that upon oxidative stress, the TA system MqsR/MqsA has a heterogeneous effect on the transcriptome of single cells. Furthermore, we discovered that MqsR activation leads to induction of the poorly-characterized yfjXY ypjJ yfjZF operon of cryptic prophage CP4-57. Moreover, deletion of yfjY makes the cells sensitive to H2O2, acid, and heat stress, and this phenotype was complemented. Hence, we recommend yfjY be renamed to lfgB (less fatality gene B). Critically, MqsA represses lfgB by binding the operon promoter, and LfgB is a protease that degrades MqsA to derepress rpoS and facilitate the stress response. Therefore, the MqsR/MqsA TA system facilitates the stress response through cryptic phage protease LfgB.

molecular biology↗

bioRxiv2023

Proteonano: a novel deep proteomics platform with 1000-plex profiling capacity and picogram sensitivity and its application in diabetic kidney disease

The development of blood-based multi-biomarker panels for screening diabetic patients, and as an easy-to-access tool for identifying individuals at greatest risk of developing diabetic kidney disease (DKD) and its progression, is essential. However, conventional blood biomarker-based methodologies (e.g. clinical tests and ELISA) are unable to predict DKD progression with high sensitivity and specificity. To overcome these challenges, we developed a deep, untargeted plasma proteome profiling technology (Proteonano platform) to identify potential multiple protein biomarkers involved in DKD progression. The Proteonano technology is an affinity selective mass spectrometric platform that comprises nanoparticle-based affinity binders (nanobinders) for low abundant protein enrichment, automated workflow for parallel sample preparation, and machine learning empowered bioinformatic software for data analysis. Using the Proteonano platform, we performed untargeted proteomics on 75 subjects (DKD progressors, n = 30; DKD non-progressors, n = 45) and identified an average of 953 {+/-} 80 (AVG {+/-} SD) protein groups, with a wide dynamic range of 8 orders of magnitude (with the lowest concentration down to 3.00 pg/mL). Among these, 38 proteins were differentially expressed between DKD progressors relative to non-progressors, and the predictive power for these proteins were assessed. Further, we performed random forest and LASSO analyses for additional variable selection. Variables selected by these approaches were assessed by Akaike information criterion method followed by ROC analysis, which identified a combination of multiple proteins (including VWF, PTGDS, B2M, BT3A2, and LCAT) that showed excellent predictive power over current methods, with an area under the curve value up to 0.97. Some of these plasma proteins are not previously recognized in the context of DKD progression, suggesting they are novel biomarkers. Our studies pave the way to develop multi-biomarker panels for DKD progression management. This study suggests that the Proteonano technology platform reported here can be employed as an established workflow enabling untargeted deep proteomic analysis to identify highly discriminative biomarkers for precise medicine.

bioinformatics↗

bioRxiv2023

Automated Bioinformatics Analysis via AutoBA

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the bioinformatics analysis continues to grow. In response to this need, we introduce Automated Bioinformatics Analysis (AutoBA), an autonomous AI agent designed explicitly for fully automated multi-omic analyses based on large language models. AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. Through rigorous validation by expert bioinformaticians, AutoBAs robustness and adaptability are affirmed across a diverse range of omics analysis cases, including whole genome/exome sequencing (WGS/WES), chromatin immunoprecipitation assays with sequencing (ChIP-seq), RNA sequencing (RNA-seq), single-cell RNA-seq, spatial transcriptomics and so on. AutoBAs unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi-omic analyses.

bioinformatics↗

bioRxiv2023

Pathological mutations reveal the key role of the iRhom2 N-terminus for ADAM17 binding, stability and activity.

The protease ADAM17 plays an important role in inflammation and cancer and is regulated by iRhom2. Mutations in the cytosolic N-terminus of human iRhom2 cause tylosis with oesophageal cancer (TOC). In mice, partial deletion of the N-terminus results in a curly hair phenotype (cub). These pathological consequences are consistent with our findings that iRhom2 is highly expressed in keratinocytes and in oesophageal cancer. Cub and TOC are associated with hyperactivation of ADAM17-dependent EGFR signalling. However, the underlying molecular mechanisms are not understood. We have identified a non-canonical, phosphorylation-independent 14-3-3 interaction site that encompasses all known TOC mutations. Disruption of this site dysregulates ADAM17 activity. The larger cub deletion also includes the TOC site and thus also dysregulated ADAM17 activity. The cub deletion, but not the TOC mutation, also causes severe reductions in stimulated shedding, binding, and stability of ADAM17, demonstrating the presence of additional regulatory sites in the N-terminus of iRhom2. Overall, this study contrasts the TOC and cub mutations, illustrates their different molecular consequences, and reveals important key functions of the iRhom2 N-terminus in regulating ADAM17.

molecular biology↗

bioRxiv2023

Rationally designed multimeric nanovaccines using icosahedral DNA origami for molecularly controlled display of SARS-CoV-2 receptor binding domain

Multivalent antigen display on nanoparticles can enhance the immunogenicity of nanovaccines targeting viral moieties, such as the receptor binding domain (RBD) of SARS-CoV-2. However, particle morphology and size of current nanovaccines are significantly different from those of SARS-CoV-2. Additionally, surface antigen patterns are not controllable to enable the optimization of B cell activation. Herein, we employed an icosahedral DNA origami (ICO) as a display particle for SARS-CoV-2 RBD nanovaccines. The morphology and diameter of the particles were close to those of the virus (91 {+/-} 11 nm). The surface addressability of the DNA origami permitted facile modification of the ICO surface with numerous RBD antigen clusters (ICO-RBD) to form various antigen patterns. Using an in vitro screening system, we demonstrate that the antigen spacing, antigen copies within clusters and cluster number parameters of the surface antigen pattern all impact the ability of the nanovaccines to activate B cells. Importantly, the optimized ICO-RBD nanovaccines evoked stronger and more enduring humoral and T cell immune responses in mouse models compared to soluble RBD antigens. Our vaccines activated similar humoral immunity and slightly stronger cellular immunity compared to mRNA vaccines. These results provide reference principles for the rational design of nanovaccines and exemplify the utility of DNA origami as a display platform for vaccines against infectious disease.

bioengineering↗

bioRxiv2023

AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties, and represent a potentially effective therapeutic target towards long-term remission by means of differentiation induction. By leveraging an Artificial Intelligence (AI) approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the LINCS database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of 5 out of 6 tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron, and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

bioinformatics↗

bioRxiv2023

Duhuo Jisheng Decoction Regulates Intracellular Zinc Homeostasis by Enhancing Autophagy via PTEN/Akt/mTOR to Improve Knee Cartilage Degeneration

BackgroundArticular cartilage degeneration as well as cartilage matrix degradation is one of the key pathological changes in the early stage of knee osteoarthritis (KOA). However, currently, there are limited early prevention and treatment options available. Duhuo Jisheng Decoction (DHJSD) is a formula from Bei Ji Qian jin Yao Fang compiled by Sun Simiao in the Tang Dynasty of China. As a complementary therapy, it is widely used to treat early-stage KOA in China, but its mechanism has not been fully elucidated. ObjectiveThis study is aiming at investigating the potential role and mechanism of DHJSD in protecting cartilage from degradation. MethodsThe mechanism of DHJSD in alleviating OA was explored by gene silencing technology combined with a series of functional experiments in primary rat chondrocytes. Next, 25 wistar rats were used to validate the results obtained in vitro. The PTEN, Akt, mTOR, MMP13, Zn, collagen II, autophagy and apoptosis were determined. ResultsDHJSD reduced the phosphorylation of Akt and mTOR and the expression of zinc, MMP13, Bax and Bcl2. DHJSD increased the level of autophagy and the expression of autophagy proteins LC3 and Beclin1. After silencing PTEN gene, the phosphorylation levels of Akt and mTOR and the effects of Bax, Bcl2, LC3 and Beclin1 were weakened by DHJSD. DHJSD increased the formation of autophagosomes in chondrocytes. Histopathological staining revealed that DHJSD had a protective effect on cartilage. ConclusionDHJSD inhibits Akt/mTOR signaling pathway by targeting PTEN to promote autophagy in chondrocytes, which may be closely to repress the formation of MMP-13 by regulating the level of zinc in chondrocytes.

pharmacology and toxicology↗

bioRxiv2023

Deep Learning Enhanced Tandem Repeat Variation Identification via Multi-Modal Conversion of Nanopore Reads Alignment

Identification of tandem repeat (TR) variations plays a crucial role in advancing our understanding of genetic diseases, forensic analysis, evolutionary studies, and crop improvement, thereby contributing to various fields of research and practical applications. However, traditional TR identification methods are often limited to processing genomes obtained through sequence assembly and cannot directly start detection from sequencing reads. Furthermore, the inflexibility of detection mode and parameters hinders the accuracy and completeness of the identification, rendering the results unsatisfactory. These shortcomings result in existing TR variation identification methods being associated with high computational cost, limited detection sensitivity, precision and comprehensiveness. Here, we propose DeepTRs, a novel method for identifying TR variations, which enables direct TR variation identification from raw Nanopore sequencing reads and achieves high sensitivity, accuracy, and completeness results through the multi-modal conversion of Nanopore reads alignment and deep learning. Comprehensive evaluations demonstrate that DeepTRs outperform existing methods.

bioinformatics↗

bioRxiv2023

Wiskott-Aldrich Syndrome Protein Regulates Nucleolar Organization and Function in Innate Immune Response

Wiskott-Aldrich syndrome (WAS) is a primary immunodeficiency disorder caused by the dysfunction of the WAS protein (WASP). Using an isogenic macrophage model derived from genome edited induced pluripotent stem cells we demonstrated that WASP functions in the nucleolus, which plays important roles in immune regulation. The absence of WASP resulted in smaller and misshapen nucleoli, decreased fibrillar center territory, and impaired ribosomal RNA (rRNA) transcription. The nucleolar and rRNA phenotypes were confirmed in WAS patient samples. Furthermore, WASP interacts with nucleolar proteins, including nucleophosmin 1 (NPM1) and fibrillarin (FBL). NPM1 deficiency is known to cause elevated cytokine expression following lipopolysaccharide (LPS) stimulation. Consistently, WASP deficient cells displayed lower levels of NPM1 and a heightened inflammatory cytokine response to LPS, which was rescued by overexpressing NPM1. Together, our research provides novel insights into the critical role of WASP in nucleolar function and the modulation of inflammatory cytokine production.

cell biology↗

bioRxiv2023

ccTCM: a quantitative component and compound platform for promoting the research of traditional Chinese medicine

Traditional Chinese medicine (TCM) databases play a vital role in bridging the gap between TCM and modern medicine, as well as in promoting the popularity of TCM. Elucidating the bioactive ingredients of Chinese medicinal materials is key to TCM modernization and new drug discovery. However, one drawback of current TCM databases is the lack of quantitative data on the constituents of Chinese medicinal materials. Herein, we present ccTCM, a web-based platform designed to provide a component and compound-content-based resource on TCM and analysis services for medical experts. In terms of design features, ccTCM combines resource distribution, similarity analysis, and molecular-mechanism analysis to accelerate the discovery of bioactive ingredients in TCM. ccTCM contains 273 Chinese medicinal materials commonly used in clinical settings, covering 29 functional classifications. By searching and comparing, we finally adopted 2043 studies, from which we collected the compounds contained in each TCM with content greater than 0.001%, and a total of 1 449 were extracted. Subsequently, we collected 40767 compound-target pairs by integrating multiple databases. Taken together, ccTCM is a versatile platform for that can be used by TCM scientists to perform scientific and clinical TCM studies based on quantified ingredients of Chinese medicinal materials. ccTCM is freely accessible at http://www.cctcm.org.cn.

bioinformatics↗

bioRxiv2023

Patient-derived organoids assist personalized treatment for a patient with multiple metastatic neuroendocrine carcinoma of the cervix

Neuroendocrine carcinoma of the cervix (NECC) is a rare subtype of cervical cancer with rapid metastasis. Lack of treatment regimens for metastatic NECC highlights the need for preclinical models and personalized treatment. Here, we established two patient-derived NECC organoid lines from lung metastases from the same patient, one of which was drug-free and the other exhibited tolerance to carboplatin plus etoposide (EP). The two organoids recapitulated the histopathology and genomic spectrum of the original tumors. Whole-genome sequencing revealed genomic structural variations (SVs), including HPV16 infection, NEUROD2, and ERBB2 amplification. The sensitivity phenotype of organoids to ERBB2 inhibitors coincides with the genomic features of ERBB2 amplification. In addition, the patient after relapse responded well to the paclitaxel plus carboplatin (TC) regimen as recommended by organoid drug screening, underscoring the utility of organoids as preclinical models. We first provide two NECC organoids of lung metastases with comprehensive molecular characteristics as valuable resources for this rare cancer and give a typical application for personalized treatment based on organoids.

cancer biology↗

bioRxiv2023

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans

Recently, there has been rapid development in model-induced drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models are commonly used in early drug discovery to predict drug properties. However, basic PBPK models require a large number of molecule-specific inputs from in vitro experiments, which hinders the efficiency and accuracy of these models. To address this issue, this paper introduces a new computational platform that combines ML and PBPK models. The platform predicts molecule PK profiles with high accuracy and without the need for experimental data. This study developed a whole-body PBPK model and ML models of plasma protein unbinding (fup), Caco-2 cell permeability, and total plasma clearance to predict the PK of small molecules. Pharmacokinetic profiles were simulated using a "bottom-up" PBPK modeling approach with ML inputs. Additionally, 40 compounds were used to evaluate the platforms accuracy. Results showed that the ML-PBPK model predicted the area under the concentration-time curve (AUC) with 62.5% accuracy within a 2-fold range, which was higher than using in vitro inputs with 47.5% accuracy. The ML-PBPK model platform provides high accuracy in prediction and reduces the number of experiments and time required compared to traditional PBPK approaches. The platform successfully predicts human PK parameters without in vitro and in vivo experiments and can potentially guide early drug discovery and development.

pharmacology and toxicology↗

bioRxiv2023

CircRNAs and their regulatory networks associated with the antioxidant enzymes and immune responses of Asian honey bee larvae to fungal infection

Non-coding RNA (ncRNA) plays an important role in the regulation of immune responses, growth, and development in plants and animals. Here, the identification, characteristic investigation, and molecular verification of circRNAs in Apis cerana cerana larval guts were conducted, and the expression pattern of larval circRNAs during Ascosphaera apis infection was analyzed. This was followed by exploration of the potential regulatory part of differentially expressed circRNAs (DEcircRNAs) in host immune responses. A total of 3178 circRNAs in the larval guts of A. c. cerana were identified, with a length distribution ranging from 15 nt to 96007 nt. Additionally, 45, 33, and 48 up-regulated circRNAs, as well as 110, 62, and 38 down-regulated circRNAs were identified in the A.-apis-inoculated 4-, 5-, and 6-day-old larval guts in comparison with the corresponding uninoculated larval guts. These DEcircRNAs were predicted to target 29, 25, and 18 parental genes, which were relative to 12, 20, and 17 GO terms as well as 144, 114, and 61 KEGG pathways, including five cellular and four humoral immune pathways containing melanization, phagosomes, lysosomes, endocytosis, apoptosis, MAPK, Ras, and Jak-STAT signaling pathways. Furthermore, complex competing endogenous RNA (ceRNA) regulatory networks were detected as being formed among DEcircRNAs, DEmiRNAs, and DEmRNAs. The target DEmRNAs were engaged in 36, 47, and 47 GO terms as well as 331, 332, and 331 pathways, including six cellular and six humoral immune-related pathways. In total, nineteen DEcircRNAs, five DEmiRNAs, and three mRNAs were included in the sub-networks relative to three antioxidant enzymes, including superoxide dismutase (SOD), catalase (CAT), and glutathione S-transferase (GST). Finally, back-splicing sites within 15 circRNAs and the difference in the 15 DEcircRNAs expression between uninoculated and A.-apis-inoculated larval guts were confirmed utilizing molecular methods. These findings not only enrich our understanding of bee host-fungal pathogen interactions, but also lay a foundation for illuminating the mechanism underlying the DEcircRNA-mediated immune defense of A. c. cerana larvae against A. apis invasion.

molecular biology↗

bioRxiv2023

METTL16 Controls Kaposi's Sarcoma-Associated Herpesvirus Replication by Regulating S-Adenosylmethionine Cycle

Oncogenic Kaposis sarcoma-associated herpesvirus (KSHV) consists of latent and lytic replication phases, both of which are important for the development of KSHV- related cancers. As one of the most abundant RNA modifications, N6-methyladenosine (m6A) and its related complexes regulate KSHV life cycle. However, the role of METTL16, a new RNA methyltransferase, in KSHV life cycle remains unknown. In this study, we have identified a suppressive role of METTL16 in KSHV lytic replication. METTL16 knockdown increased while METTL16 overexpression reduced KSHV lytic replication. METTL16 binding to and writing of m6A on MAT2A transcript are essential for its splicing, maturation and expression. As a rate-limiting enzyme in the methionine- S-adenosylmethionine (SAM) cycle, MAT2A catalyzes the conversion of L-methionine to SAM required for the transmethylation of protein, DNA and RNA, transamination of polyamines, and transsulfuration of cystathionine. Consequently, knockdown or chemical inhibition of MAT2A reduced intracellular SAM level and enhanced KSHV lytic replication. In contrast, SAM treatment was sufficient to inhibit KSHV lytic replication and reverse the effect of the enhanced KSHV lytic program caused by METTL16 or MAT2A knockdown. Mechanistically, METTL16 or MAT2A knockdown increased while SAM treatment decreased the intracellular reactive oxygen species level by altering glutathione level, which is essential for efficient KSHV lytic replication. These findings demonstrate that METTL16 suppresses KSHV lytic replication by modulating the SAM cycle to maintain intracellular SAM level and redox homeostasis, thus illustrating the linkage of KSHV life cycle with specific m6A modifications, and cellular metabolic and oxidative conditions.

microbiology↗

bioRxiv2023

RealSeq2: a software integrated with UMI identification, error correction, and methylation modifications storing

High-throughput UMI technology sequencing is widely used in early tumor screening, detection, recurrence monitoring, etc. Detecting extremely low-frequency mutations is especially important for monitoring tumor recurrence, so high-precision data, as well as high-quality data, are required. We developed RealSeq2, a new integrated data-preprocessing software based on fastp and gencore, to achieve adapter removal, quality control, UMI identification, and generate consensus reads by clustering and error correction using multithreading in high-throughput next-generation sequencing background. RealSeq2 also supports methylation data of 5-methylcytosine bisulfite-free sequencing. RealSeq2 defined a new tag in SAM for storing methylation information, which is beneficial for co-identifying methylation sites and mutation sites for downstream analysis. RealSeq2 includes three submodules: ReadsProfiler, ReadsCleaner, and ReadsRecycler. In addition, the output format file (BAM or SAM) is universal for downstream analyses. RealSeq2 is the preferred upstream analysis software for the co-detection of ultra-low frequency mutations and bisulfite-free methylation data. The error profile provides data support for downstream analysis. Additionally, XM tags will become a standard protocol for recording methylation signals.

bioinformatics↗

bioRxiv2023

An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor cell heterogeneities. However, these studies only enable gene-level expression quantification but neglect alterations in transcript structures, which arise from alternative end processing or splicing, and are frequently observed in cancer. In this study, we integrated short- and long-read scRNA-seq of CRC patient samples to build the first isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of multiple splicing events. Secondly, we characterized genes and isoforms associated with epithelial lineages and subpopulations that exhibit distinct prognoses. Finally, we built an algorithm that integrated novel peptides derived from predicted ORFs of recurrent tumor-specific transcripts with mass spectrometry data and identified a panel of recurring neoepitopes that may aid the development of neoantigen-based cancer vaccines.

cancer biology↗

bioRxiv2023

Plasma cells are formed in waning germinal centers via an affinity-independent process

Long-lived plasma cells (PCs) secrete antibodies that can provide sustained immunity against infection. It has been proposed that high affinity cells are preferentially selected into this compartment, potentiating the immune response. Here we used single cell RNA-seq to track the development of Ighg2A10 cells, specific for the Plasmodium falciparum circumsporozoite protein (PfCSP) within the germinal center (GC). We identified cells differentiating into memory B cells (MBC) or PCs and estimated their affinity by V(D)J sequencing. While pre-memory cells were of lower affinity than GC B cells generally, the affinity of pre-PC cells was indistinguishable. Rather, a larger proportion of cells differentiated into PCs in waning GCs. These later emigrants replaced early arrivals in the bone marrow allowing the development of a high affinity PC compartment.

immunology↗