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Hydrogels are widely used as excellent drug carriers in the field of biomedicine. However, their application in medicine is limited by their poor mechanical properties and softness. To improve the mechanical properties of hydrogels, a novel triple-network amphiphilic hydrogel with three overlapping crosslinking methods using a one-pot free-radical polymerization was synthesized in this study. Temperature-sensitive and pH-sensitive monomers were incorporated into the hydrogel to confer stimulus responsiveness, making the hydrogel stimuli-responsive. The successful synthesis of the hydrogel was confirmed using techniques, such as proton nuclear magnetic resonance spectroscopy (1H NMR), Fourier-transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD). In order to compare and analyze the properties of physically crosslinked hydrogels, physically-chemically double-crosslinked hydrogels, and physically-chemically clicked triple-crosslinked hydrogels, various tests were conducted on the gels' morphology, swelling behavior, thermal stability, mechanical properties, and drug loading capacity. The results indicate that the triple-crosslinked hydrogel maintains low swelling, high mechanical strength, and good thermal stability while not significantly compromising its drug delivery capability.
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We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.
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Algoritmos , Metabolômica , Software , Espectrometria de Massas em Tandem , Metabolômica/métodos , Cromatografia Líquida , Humanos , Bases de Dados FactuaisRESUMO
The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and interpretation. This protocol covers three key components involved in multi-omics analysis, including single-omics data analysis, knowledge-driven integration using biological networks and data-driven integration through joint dimensionality reduction. Using the dataset from a recent multi-omics study of human pancreatic islet tissue and plasma samples, the first section introduces how to perform transcriptomics/proteomics data analysis using ExpressAnalyst and lipidomics data analysis using MetaboAnalyst. On the basis of significant features detected in these workflows, the second section demonstrates how to perform knowledge-driven integration using OmicsNet. The last section illustrates how to perform data-driven integration from the normalized omics data and metadata using OmicsAnalyst. The complete protocol can be executed in ~2 h. Compared with other available options for multi-omics integration, the Analyst software suite described in this protocol enables researchers to perform a wide range of omics data analysis tasks via a user-friendly web interface.
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Internet , Metabolômica , Proteômica , Software , Humanos , Metabolômica/métodos , Proteômica/métodos , Ilhotas Pancreáticas/metabolismo , Biologia Computacional/métodos , Lipidômica/métodos , Genômica/métodos , MultiômicaRESUMO
ExpressAnalyst is a web-based platform that enables intuitive, end-to-end transcriptomics and proteomics data analysis. Users can start from FASTQ files, gene/protein abundance tables, or gene/protein lists. ExpressAnalyst will perform read quantification, gene expression table processing and normalization, differential expression analysis, or meta-analysis with complex study designs. The results are presented via various interactive visualizations such as volcano plots, heatmaps, networks, and ridgeline charts, with built-in functional enrichment analysis to allow flexible data exploration and understanding. ExpressAnalyst currently contains built-in support for 29 common organisms. For non-model organisms without good reference genomes, it can perform comprehensive transcriptome profiling directly from RNA-seq reads. These common tasks are covered in 11 Basic Protocols. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: RNA-seq count table uploading, processing, and normalization Basic Protocol 2: Differential expression analysis with linear models Basic Protocol 3: Functional analysis with volcano plot, enrichment network, and ridgeline visualization Basic Protocol 4: Hierarchical clustering analysis of transcriptomics data using interactive heatmaps Basic Protocol 5: Cross-species gene expression analysis based on ortholog mapping results Basic Protocol 6: Proteomics and microarray data processing and normalization Basic Protocol 7: Preparing multiple gene expression tables for meta-analysis Basic Protocol 8: Statistical and functional meta-analysis of gene expression data Basic Protocol 9: Functional analysis of transcriptomics signatures Basic Protocol 10: Dose-response and time-series data analysis Basic Protocol 11: RNA-seq reads processing and quantification with and without reference transcriptomes.
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Perfilação da Expressão Gênica , Transcriptoma , Análise de Sequência de RNA/métodos , Perfilação da Expressão Gênica/métodos , RNA-SeqRESUMO
Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn's disease, as well as between glycine and coronary heart disease.
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Microbiome studies have become routine in biomedical, agricultural and environmental sciences with diverse aims, including diversity profiling, functional characterization, and translational applications. The resulting complex, often multi-omics datasets demand powerful, yet user-friendly bioinformatics tools to reveal key patterns, important biomarkers, and potential activities. Here we introduce MicrobiomeAnalyst 2.0 to support comprehensive statistics, visualization, functional interpretation, and integrative analysis of data outputs commonly generated from microbiome studies. Compared to the previous version, MicrobiomeAnalyst 2.0 features three new modules: (i) a Raw Data Processing module for amplicon data processing and taxonomy annotation that connects directly with the Marker Data Profiling module for downstream statistical analysis; (ii) a Microbiome Metabolomics Profiling module to help dissect associations between community compositions and metabolic activities through joint analysis of paired microbiome and metabolomics datasets; and (iii) a Statistical Meta-Analysis module to help identify consistent signatures by integrating datasets across multiple studies. Other important improvements include added support for multi-factor differential analysis and interactive visualizations for popular graphical outputs, updated methods for functional prediction and correlation analysis, and expanded taxon set libraries based on the latest literature. These new features are demonstrated using a multi-omics dataset from a recent type 1 diabetes study. MicrobiomeAnalyst 2.0 is freely available at microbiomeanalyst.ca.
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Biologia Computacional , Técnicas Microbiológicas , Microbiota , Biomarcadores , Biologia Computacional/métodos , Metabolômica/métodos , Técnicas Microbiológicas/instrumentação , Técnicas Microbiológicas/métodos , Internet , Interface Usuário-ComputadorRESUMO
The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst ( www.expressanalyst.ca ), a web-based platform for processing, analyzing, and interpreting RNA-sequencing data from any eukaryotic species. ExpressAnalyst contains a series of modules that cover from processing and annotation of FASTQ files to statistical and functional analysis of count tables or gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst allows researchers to obtain global expression profiles and gene-level insights from raw RNA-sequencing reads within 24 h. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-sequencing data from multiple non-model salamander species, including two that do not have a reference transcriptome.
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Algoritmos , Biologia Computacional , Bases de Dados Factuais , Eucariotos , RNA/genéticaRESUMO
Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.
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COVID-19 , Humanos , SARS-CoV-2 , Transcriptoma , Células Matadoras Naturais , Ciclo CelularRESUMO
Human Immunodeficiency virus (HIV-1) fusion is mediated by glycoprotein-41, a protein that has not been widely exploited as a drug target. Small molecules directed at the gp41 ectodomain have proved to be poorly drug-like, having moderate efficacy, high hydrophobicity and/or high molecular weight. We recently investigated conversion of a fairly potent hydrophobic inhibitor into a covalent binder, by modifying it to react with a lysine residue on the protein. We demonstrated a 10-fold improvement in antiviral efficacy. Here, we continue this study, utilizing instead molecules with better inherent drug-like properties. Molecules possessing low to no antiviral activity as equilibrium binders were converted into µM inhibitors upon addition of an electrophilic warhead in the form of a sulfotetrafluorophenyl (STP) activated ester. We confirmed specificity for gp41 and for entry. The small size of the inhibitors described here offers an opportunity to expand their reach into neighboring pockets while retaining drug-likeness. STP esterification of equilibrium binders is a promising avenue to explore for inhibiting HIV-1 entry. Many gp41 targeting molecules studied over the years possess carboxylic acid groups which can be easily converted into the corresponding STP ester. It may be worth the effort to evaluate a library of such inhibitors as a way forward to small molecule inhibition of fusion of HIV and possibly other enveloped viruses.
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Inibidores da Fusão de HIV , HIV-1 , Humanos , Inibidores da Fusão de HIV/farmacologia , Inibidores da Fusão de HIV/química , HIV-1/metabolismo , Antivirais/farmacologia , Antivirais/metabolismo , Lisina/metabolismo , Proteína gp41 do Envelope de HIV/química , Interações Hidrofóbicas e HidrofílicasRESUMO
Tens of thousands of single-nucleotide polymorphisms (SNPs) have been identified to be significantly associated with metabolite abundance in over 65 genome-wide association studies with metabolomics (mGWAS) to date. Obtaining mechanistic or functional insights from these associations for translational applications has become a key research area in the mGWAS community. Here, we introduce mGWAS-Explorer, a user-friendly web-based platform to help connect SNPs, metabolites, genes, and their known disease associations via powerful network visual analytics. The application of the mGWAS-Explorer was demonstrated using a COVID-19 and a type 2 diabetes case studies.
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Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become a workhorse in global metabolomics studies with growing applications across biomedical and environmental sciences. However, outstanding bioinformatics challenges in terms of data processing, statistical analysis and functional interpretation remain critical barriers to the wider adoption of this technology. To help the user community overcome these barriers, we have made major updates to the well-established MetaboAnalyst platform ( www.metaboanalyst.ca ). This protocol extends the previous 2011 Nature Protocol by providing stepwise instructions on how to use MetaboAnalyst 5.0 to: optimize parameters for LC-HRMS spectra processing; obtain functional insights from peak list data; integrate metabolomics data with transcriptomics data or combine multiple metabolomics datasets; conduct exploratory statistical analysis with complex metadata. Parameter optimization may take ~2 h to complete depending on the server load, and the remaining three stages may be executed in ~60 min.
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Metabolômica , Software , Cromatografia Líquida , Biologia Computacional/métodos , Espectrometria de Massas , Metabolômica/métodosRESUMO
Researchers are increasingly seeking to interpret molecular data within a multi-omics context to gain a more comprehensive picture of their study system. OmicsNet (www.omicsnet.ca) is a web-based tool developed to allow users to easily build, visualize, and analyze multi-omics networks to study rich relationships among lists of 'omics features of interest. Three major improvements have been introduced in OmicsNet 2.0, which include: (i) enhanced network visual analytics with eleven 2D graph layout options and a novel 3D module layout; (ii) support for three new 'omics types: single nucleotide polymorphism (SNP) list from genetic variation studies; taxon list from microbiome profiling studies, as well as liquid chromatography-mass spectrometry (LC-MS) peaks from untargeted metabolomics; and (iii) measures to improve research reproducibility by coupling R command history with the release of the companion OmicsNetR package, and generation of persistent links to share interactive network views. We performed a case study using the multi-omics data obtained from a recent large-scale investigation on inflammatory bowel disease (IBD) and demonstrated that OmicsNet was able to quickly create meaningful multi-omics context to facilitate hypothesis generation and mechanistic insights.
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Metabolômica , Multiômica , Software , Internet , Espectrometria de Massas , Reprodutibilidade dos Testes , Cromatografia LíquidaRESUMO
We describe a low molecular weight covalent inhibitor targeting a conserved lysine residue within the hydrophobic pocket of HIV-1 glycoprotein-41. The inhibitor bound selectively to the hydrophobic pocket and exhibited an order of magnitude enhancement of anti-fusion activity against HIV-1 compared to its non-covalent counterpart. The findings represent a significant advance in the quest to obtain non-peptide fusion inhibitors.
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Fármacos Anti-HIV/farmacologia , Proteína gp41 do Envelope de HIV/antagonistas & inibidores , Inibidores da Fusão de HIV/farmacologia , HIV/efeitos dos fármacos , Bibliotecas de Moléculas Pequenas/farmacologia , Ésteres do Ácido Sulfúrico/farmacologia , Fármacos Anti-HIV/química , HIV/metabolismo , Proteína gp41 do Envelope de HIV/metabolismo , Inibidores da Fusão de HIV/química , Interações Hidrofóbicas e Hidrofílicas , Testes de Sensibilidade Microbiana , Estrutura Molecular , Peso Molecular , Bibliotecas de Moléculas Pequenas/química , Relação Estrutura-Atividade , Ésteres do Ácido Sulfúrico/químicaRESUMO
Data analysis and interpretation remain a critical bottleneck in current multi-omics studies. Here, we introduce OmicsAnalyst, a user-friendly, web-based platform that allows users to perform a wide range of well-established data-driven approaches for multi-omics integration, and visually explore their results in a clear and meaningful manner. To help navigate complex landscapes of multi-omics analysis, these approaches are organized into three visual analytics tracks: (i) the correlation network analysis track, where users choose among univariate and multivariate methods to identify important features and explore their relationships in 2D or 3D networks; (ii) the cluster heatmap analysis track, where users apply several cutting-edge multi-view clustering algorithms and explore their results via interactive heatmaps; and (iii) the dimension reduction analysis track, where users choose among several recent multivariate techniques to reveal global data structures, and explore corresponding scores, loadings and biplots in interactive 3D scatter plots. The three visual analytics tracks are equipped with comprehensive options for parameter customization, view customization and targeted analysis. OmicsAnalyst lowers the access barriers to many well-established methods for multi-omics integration via novel visual analytics. It is freely available at https://www.omicsanalyst.ca.
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Metabolômica , Proteômica , Software , Animais , Análise por Conglomerados , Feminino , Perfilação da Expressão Gênica , Humanos , Internet , Camundongos , Análise Multivariada , GravidezRESUMO
Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC-MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca.
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Espectrometria de Massas/métodos , Metabolômica/métodos , Software , Cromatografia Líquida , Perfilação da Expressão Gênica , Bases de ConhecimentoRESUMO
The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather than the viral load or its genetic variations. A growing number of omics studies have been conducted to characterize the host immune and metabolic responses underlying the disease progression. Meta-analyses of these datasets have great potential to identify robust molecular signatures to inform clinical care and to facilitate therapeutics development. In this study, we performed a comprehensive meta-analysis of publicly available global metabolomics datasets obtained from three countries (United States, China and Brazil). To overcome high heterogeneity inherent in these datasets, we have (a) implemented a computational pipeline to perform consistent raw spectra processing; (b) conducted meta-analyses at pathway levels instead of individual feature levels; and (c) performed visual data mining on consistent patterns of change between disease severities for individual studies. Our analyses have yielded several key metabolic signatures characterizing disease progression and clinical outcomes. Their biological interpretations were discussed within the context of the current literature. To the best of our knowledge, this is the first comprehensive meta-analysis of global metabolomics datasets of COVID-19.
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BACKGROUND: The hydrophobic pocket (HP) of HIV-1 glycoprotein-41 ectodomain is defined by two chains of the N-heptad repeat trimer, within the protein-protein interface that mediates 6HB formation. It is a potential target for inhibitors of viral fusion, but its hydrophobic nature and proximity to membrane in situ has precluded ready analysis of inhibitor interactions. METHODS: We evaluated the sensitivity of 19F NMR and fluorescence for detecting peptide and small molecule binding to the HP and explored the effect of non-denaturing detergent or phospholipid as cosolvents and potential mimics of the membrane environment surrounding gp41. RESULTS: Chemical shifts of aromatic fluorines were found to be sensitive to changes in the hydrogen bonding network that occurred when inhibitors transitioned from solvent into the HP or into ordered detergent micelles. Fluorescence intensities and emission maxima of autofluorescent compounds responded to changes in the local environment. CONCLUSIONS: Gp41 - ligand binding occurred under all conditions, but was diminished in the presence of detergents. NMR and fluorescence studies revealed that dodecylphosphocholine (DPC) was a poor substitute for membrane in this system, while liposomes could mimic the membrane surroundings. GENERAL SIGNIFICANCE: Our findings suggest that development of high potency small molecule binders to the HP may be frustrated by competition between binding to the HP and binding to the bilayer membrane.
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Detergentes/metabolismo , Proteína gp41 do Envelope de HIV/metabolismo , HIV-1/metabolismo , Fosfolipídeos/metabolismo , Bibliotecas de Moléculas Pequenas/metabolismo , Colesterol/metabolismo , Proteína gp41 do Envelope de HIV/química , Infecções por HIV/tratamento farmacológico , Infecções por HIV/virologia , HIV-1/química , Humanos , Bicamadas Lipídicas/metabolismo , Lipossomos/metabolismo , Modelos Moleculares , Ligação Proteica , Desdobramento de ProteínaRESUMO
The relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) has attracted wide attention. Studies have reported that ginsenoside Rb1 can improve human cognitive ability and glucose tolerance during the development of diabetes. The mechanism behind the improvement in cognitive ability and glucose tolerance still remains unclear. In this study, streptozotocin- (STZ-) injected mice were used as models to explore the mechanisms behind the cognitive improvement of ginsenoside Rb1. According to the results of behavioral tests, ginsenoside Rb1 improved memory and cognitive ability of STZ-lesioned mice. In addition to that, ginsenoside Rb1 also relieved glucose intolerance induced by STZ injection by enhancing insulin sensitivity. These beneficial effects of ginsenoside Rb1 is most likely mediated by upregulating the expression of NMDAR1 and IDE in the hippocampus through inhibiting the activity of Cdk5/p35. This work will be of great importance in illustrating the mechanisms of ginsenoside Rb1 for improving cognitive ability, as well as revealing the relationship between diabetes and AD.
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Disfunção Cognitiva/metabolismo , Quinase 5 Dependente de Ciclina/metabolismo , Ginsenosídeos/farmacologia , Resistência à Insulina/fisiologia , Memória/efeitos dos fármacos , Animais , Glicemia/efeitos dos fármacos , Insulisina/metabolismo , Masculino , Aprendizagem em Labirinto/efeitos dos fármacos , Camundongos , Camundongos Endogâmicos C57BL , Fosfotransferases/metabolismo , Receptores de N-Metil-D-Aspartato/metabolismo , Transdução de Sinais/efeitos dos fármacosRESUMO
miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with â¼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.