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- Advani, Jayshree, et al.
(author)
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Rise of Clinical Microbial Proteogenomics : A Multiomics Approach to Nontuberculous Mycobacterium-The Case of Mycobacterium abscessus UC22
- 2018
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In: Omics. - : MARY ANN LIEBERT, INC. - 1536-2310 .- 1557-8100. ; 23:1, s. 1-16
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Journal article (peer-reviewed)abstract
- Nontuberculous mycobacterial (NTM) species present a major challenge for global health with serious clinical manifestations ranging from pulmonary to skin infections. Multiomics research and its applications toward clinical microbial proteogenomics offer veritable potentials in this context. For example, the Mycobacterium abscessus, a highly pathogenic NTM, causes bronchopulmonary infection and chronic pulmonary disease. The rough variant of the M. abscessus UC22 strain is extremely virulent and causes lung upper lobe fibrocavitary disease. Although several whole-genome next-generation sequencing studies have characterized the genes in the smooth variant of M. abscessus, a reference genome sequence for the rough variant was generated only recently and calls for further clinical applications. We carried out whole-genome sequencing and proteomic analysis for a clinical isolate of M. abscessus UC22 strain obtained from a pulmonary tuberculosis patient. We identified 5506 single-nucleotide variations (SNVs), 63 insertions, and 76 deletions compared with the reference genome. Using a high-resolution LC-MS/MS-based approach (liquid chromatography tandem mass spectrometry), we obtained protein coding evidence for 3601 proteins, representing 71% of the total predicted genes in this genome. Application of proteogenomic approach further revealed seven novel protein-coding genes and enabled refinement of six computationally derived gene models. We also identified 30 variant peptides corresponding to 16 SNVs known to be associated with drug resistance. These new observations offer promise for clinical applications of microbial proteogenomics and next-generation sequencing, and provide a resource for future global health applications for NTM species.
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- Cavalli, Marco, et al.
(author)
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A Multi-Omics Approach to Liver Diseases : Integration of Single Nuclei Transcriptomics with Proteomics and HiCap Bulk Data in Human Liver
- 2020
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In: Omics. - : Mary Ann Liebert Inc. - 1536-2310 .- 1557-8100. ; 24:4, s. 180-194
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Journal article (peer-reviewed)abstract
- The liver is the largest solid organ and a primary metabolic hub. In recent years, intact cell nuclei were used to perform single-nuclei RNA-seq (snRNA-seq) for tissues difficult to dissociate and for flash-frozen archived tissue samples to discover unknown and rare cell subpopulations. In this study, we performed snRNA-seq of a liver sample to identify subpopulations of cells based on nuclear transcriptomics. In 4282 single nuclei, we detected, on average, 1377 active genes and we identified seven major cell types. We integrated data from 94,286 distal interactions (p < 0.05) for 7682 promoters from a targeted chromosome conformation capture technique (HiCap) and mass spectrometry proteomics for the same liver sample. We observed a reasonable correlation between proteomics and in silico bulk snRNA-seq (r = 0.47) using tissue-independent gene-specific protein abundancy estimation factors. We specifically looked at genes of medical importance. The DPYD gene is involved in the pharmacogenetics of fluoropyrimidine toxicity and some of its variants are analyzed for clinical purposes. We identified a new putative polymorphic regulatory element, which may contribute to variation in toxicity. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and we investigated all known risk genes. We identified a complex regulatory landscape for the SLC2A2 gene with 16 candidate enhancers. Three of them harbor somatic motif breaking and other mutations in HCC in the Pan Cancer Analysis of Whole Genomes dataset and are candidates to contribute to malignancy. Our results highlight the potential of a multi-omics approach in the study of human diseases.
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- Cavalli, Marco, et al.
(author)
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The Thioesterase ACOT1 as a Regulator of Lipid Metabolism in Type 2 Diabetes Detected in a Multi-Omics Study of Human Liver
- 2021
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In: Omics. - : Mary Ann Liebert. - 1536-2310 .- 1557-8100. ; 25:10, s. 652-659
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Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) is characterized by pathophysiological alterations in lipid metabolism. One strategy to understand the molecular mechanisms behind these abnormalities is to identify cis-regulatory elements (CREs) located in chromatin-accessible regions of the genome that regulate key genes. In this study we integrated assay for transposase-accessible chromatin followed by sequencing (ATAC-seq) data, widely used to decode chromatin accessibility, with multi-omics data and publicly available CRE databases to identify candidate CREs associated with T2D for further experimental validations. We performed high-sensitive ATAC-seq in nine human liver samples from normal and T2D donors, and identified a set of differentially accessible regions (DARs). We identified seven DARs including a candidate enhancer for the ACOT1 gene that regulates the balance of acyl-CoA and free fatty acids (FFAs) in the cytoplasm. The relevance of ACOT1 regulation in T2D was supported by the analysis of transcriptomics and proteomics data in liver tissue. Long-chain acyl-CoA thioesterases (ACOTs) are a group of enzymes that hydrolyze acyl-CoA esters to FFAs and coenzyme A. ACOTs have been associated with regulation of triglyceride levels, fatty acid oxidation, mitochondrial function, and insulin signaling, linking their regulation to the pathogenesis of T2D. Our strategy integrating chromatin accessibility with DNA binding and other types of omics provides novel insights on the role of genetic regulation in T2D and is extendable to other complex multifactorial diseases.
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- Clish, Clary B., et al.
(author)
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Integrative biological analysis of the APOE*3-leiden transgenic mouse
- 2004
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In: Omics. - : Mary Ann Liebert. - 1536-2310 .- 1557-8100. ; 8:1, s. 3-13
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Journal article (peer-reviewed)abstract
- Integrative (or systems biology) is a new approach to analyzing biological entities as integrated systems of genetic, genomic, protein, metabolite, cellular, and pathway events that are in flux and interdependent. Here, we demonstrate the application of intregrative biological analysis to a mammalian disease model, the apolipoprotein E3-Leiden (APO*E3) transgenic mouse. Mice selected for the study were fed a normal chow diet and sacrificed at 9 weeks of age-conditions under which they develop only mild type I and II atherosclerotic lesions. Hepatic mRNA expression analysis showed a 25% decrease in APO A1 and a 43% increase in liver fatty acid binding protein expression between transgenic and wild type control mice, while there was no change in PPAR-alpha expression. On-line high performance liquid chromatography-mass spectrometry quantitative profiling of tryptic digests of soluble liver proteins and liver lipids, coupled with principle component analysis, enabled rapid identification of early protein and metabolite markers of disease pathology. These included a 44% increase in L-FABP in transgenic animals compared to controls, as well as an increase in triglycerides and select bioactive lysophosphatidylcholine species. A correlation analysis of identified genes, proteins, and lipids was used to construct an interaction network. Taken together, these results indicate that integrative biology is a powerful tool for rapid identification of early markers and key components of pathophysiologic processes, and constitute the first application of this approach to a mammalian system.
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- Davidov, Eugene, et al.
(author)
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Methods for the differential integrative omic analysis of plasma from a transgenic disease animal model
- 2004
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In: Omics. - : Mary Ann Liebert. - 1536-2310 .- 1557-8100. ; 8:4, s. 267-288
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Journal article (peer-reviewed)abstract
- Multitiered quantitative analysis of biological systems is rapidly becoming the desired approach to study hierarchical functional interactions between proteins and metabolites. We describe here a novel systematic approach to analyze organisms with complex metabolic regulatory networks. By using precise analytical methods to measure biochemical constituents and their relative abundance in whole plasma of transgenic ApoE*3-Leiden mice and an isogenic wild-type control group, simultaneous snapshots of metabolic and protein states were obtained. Novel data processing and multivariate analysis tools such as Impurity Resolution Software (IMPRESS) and Windows-based linear fit program (WINLIN) were used to compare protein and metabolic profiles in parallel. Canonical correlations of the resulting data show quantitative relationships between heterogeneous components in the TG animals. These results, obtained solely from whole plasma analysis allowed us, in a rapid manner, to corroborate previous findings as well as find new events pertaining to dominant and peripheral events in lipoprotein metabolism of a genetically modified mammalian organism in relation to ApoE3, a key mediator of lipoprotein metabolism.
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