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Orlic-Milacic M, Rothfels K, Matthews L, Wright A, Jassal B, Shamovsky V, Trinh Q, Gillespie ME, Sevilla C, Tiwari K, Ragueneau E, Gong C, Stephan R, May B, Haw R, Weiser J, Beavers D, Conley P, Hermjakob H, Stein LD, D’Eustachio P, Wu G. Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes. Database (Oxford) 2024; 2024:baae031. [PMID: 38713862 PMCID: PMC11184451 DOI: 10.1093/database/baae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/23/2024] [Accepted: 04/01/2024] [Indexed: 05/09/2024]
Abstract
Germline and somatic mutations can give rise to proteins with altered activity, including both gain and loss-of-function. The effects of these variants can be captured in disease-specific reactions and pathways that highlight the resulting changes to normal biology. A disease reaction is defined as an aberrant reaction in which a variant protein participates. A disease pathway is defined as a pathway that contains a disease reaction. Annotation of disease variants as participants of disease reactions and disease pathways can provide a standardized overview of molecular phenotypes of pathogenic variants that is amenable to computational mining and mathematical modeling. Reactome (https://reactome.org/), an open source, manually curated, peer-reviewed database of human biological pathways, in addition to providing annotations for >11 000 unique human proteins in the context of ∼15 000 wild-type reactions within more than 2000 wild-type pathways, also provides annotations for >4000 disease variants of close to 400 genes as participants of ∼800 disease reactions in the context of ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, described in wild-type reactions and pathways, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Reactome's data model enables mapping of disease variant datasets to specific disease reactions within disease pathways, providing a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity. Database URL: https://reactome.org/.
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Affiliation(s)
- Marija Orlic-Milacic
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Karen Rothfels
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Lisa Matthews
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA
| | - Adam Wright
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Bijay Jassal
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Veronica Shamovsky
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA
| | - Quang Trinh
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Marc E Gillespie
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
- College of Pharmacy and Health Sciences, St. John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
| | - Cristoffer Sevilla
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Krishna Tiwari
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Eliot Ragueneau
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Chuqiao Gong
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Ralf Stephan
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
- Institute for Globally Distributed Open Research and Education (IGDORE)
| | - Bruce May
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Robin Haw
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Joel Weiser
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
| | - Deidre Beavers
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, 3181 S.W. Sam Jackson Park Rd., Portland, OR 97239, USA
| | - Patrick Conley
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, 3181 S.W. Sam Jackson Park Rd., Portland, OR 97239, USA
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Lincoln D Stein
- Adaptive Oncology, Ontario Institute for Cancer Research, 661 University Avenue Suite 510, Toronto, ON M5G 0A3, Canada
- Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Room 4386, Toronto, ON M5S 1A8, Canada
| | - Peter D’Eustachio
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA
| | - Guanming Wu
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, 3181 S.W. Sam Jackson Park Rd., Portland, OR 97239, USA
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Orlic-Milacic M, Rothfels K, Matthews L, Wright A, Jassal B, Shamovsky V, Trinh Q, Gillespie M, Sevilla C, Tiwari K, Ragueneau E, Gong C, Stephan R, May B, Haw R, Weiser J, Beavers D, Conley P, Hermjakob H, Stein LD, D'Eustachio P, Wu G. Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.18.562964. [PMID: 37904913 PMCID: PMC10614924 DOI: 10.1101/2023.10.18.562964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of ∼800 disease reactions constituting ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactome's pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.
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Kochuthakidiyel Suresh P, Sekar G, Mallady K, Wan Ab Rahman WS, Shima Shahidan WN, Venkatesan G. The Identification of Potential Drugs for Dengue Hemorrhagic Fever: Network-Based Drug Reprofiling Study. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2023; 4:e37306. [PMID: 38935956 PMCID: PMC11135182 DOI: 10.2196/37306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 09/30/2022] [Accepted: 03/28/2023] [Indexed: 06/29/2024]
Abstract
BACKGROUND Dengue fever can progress to dengue hemorrhagic fever (DHF), a more serious and occasionally fatal form of the disease. Indicators of serious disease arise about the time the fever begins to reduce (typically 3 to 7 days following symptom onset). There are currently no effective antivirals available. Drug repurposing is an emerging drug discovery process for rapidly developing effective DHF therapies. Through network pharmacology modeling, several US Food and Drug Administration (FDA)-approved medications have already been researched for various viral outbreaks. OBJECTIVE We aimed to identify potentially repurposable drugs for DHF among existing FDA-approved drugs for viral attacks, symptoms of viral fevers, and DHF. METHODS Using target identification databases (GeneCards and DrugBank), we identified human-DHF virus interacting genes and drug targets against these genes. We determined hub genes and potential drugs with a network-based analysis. We performed functional enrichment and network analyses to identify pathways, protein-protein interactions, tissues where the gene expression was high, and disease-gene associations. RESULTS Analyzing virus-host interactions and therapeutic targets in the human genome network revealed 45 repurposable medicines. Hub network analysis of host-virus-drug associations suggested that aspirin, captopril, and rilonacept might efficiently treat DHF. Gene enrichment analysis supported these findings. According to a Mayo Clinic report, using aspirin in the treatment of dengue fever may increase the risk of bleeding complications, but several studies from around the world suggest that thrombosis is associated with DHF. The human interactome contains the genes prostaglandin-endoperoxide synthase 2 (PTGS2), angiotensin converting enzyme (ACE), and coagulation factor II, thrombin (F2), which have been documented to have a role in the pathogenesis of disease progression in DHF, and our analysis of most of the drugs targeting these genes showed that the hub gene module (human-virus-drug) was highly enriched in tissues associated with the immune system (P=7.29 × 10-24) and human umbilical vein endothelial cells (P=1.83 × 10-20); this group of tissues acts as an anticoagulant barrier between the vessel walls and blood. Kegg analysis showed an association with genes linked to cancer (P=1.13 × 10-14) and the advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications (P=3.52 × 10-14), which indicates that DHF patients with diabetes and cancer are at risk of higher pathogenicity. Thus, gene-targeting medications may play a significant part in limiting or worsening the condition of DHF patients. CONCLUSIONS Aspirin is not usually prescribed for dengue fever because of bleeding complications, but it has been reported that using aspirin in lower doses is beneficial in the management of diseases with thrombosis. Drug repurposing is an emerging field in which clinical validation and dosage identification are required before the drug is prescribed. Further retrospective and collaborative international trials are essential for understanding the pathogenesis of this condition.
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Affiliation(s)
| | - Gnanasoundari Sekar
- Department of Biotechnology, Bharathidasan Institute of Technology Campus, Anna University, Tiruchirappalli, India
| | - Kavya Mallady
- Centre for Toxicology and Developmental Research, Sri Ramachandra Institute of Higher Education and Research, Chennai, India
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Wright AJ, Orlic-Milacic M, Rothfels K, Weiser J, Trinh QM, Jassal B, Haw RA, Stein LD. Evaluating the predictive accuracy of curated biological pathways in a public knowledgebase. Database (Oxford) 2022; 2022:6555052. [PMID: 35348650 PMCID: PMC9216552 DOI: 10.1093/database/baac009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/04/2022] [Accepted: 02/15/2022] [Indexed: 11/14/2022]
Abstract
Abstract Reactome is a database of human biological pathways manually curated from the primary literature and peer-reviewed by experts. To evaluate the utility of Reactome pathways for predicting functional consequences of genetic perturbations, we compared predictions of perturbation effects based on Reactome pathways against published empirical observations. Ten cancer-relevant Reactome pathways, representing diverse biological processes such as signal transduction, cell division, DNA repair and transcriptional regulation, were selected for testing. For each pathway, root input nodes and key pathway outputs were defined. We then used pathway-diagram-derived logic graphs to predict, either by inspection by biocurators or using a novel algorithm MP-BioPath, the effects of bidirectional perturbations (upregulation/activation or downregulation/inhibition) of single root inputs on the status of key outputs. These predictions were then compared to published empirical tests. In total, 4968 test cases were analyzed across 10 pathways, of which 847 were supported by published empirical findings. Out of the 847 test cases, curators’ predictions agreed with the experimental evidence in 670 and disagreed in 177 cases, resulting in ∼81% overall accuracy. MP-BioPath predictions agreed with experimental evidence for 625 and disagreed for 222 test cases, resulting in ∼75% overall accuracy. The expected accuracy of random guessing was 33%. Per-pathway accuracy did not correlate with the number of pathway edges nor the number of pathway nodes but varied across pathways, ranging from 56% (curator)/44% (MP-BioPath) for ‘Mitotic G1 phase and G1/S transition’ to 100% (curator)/94% (MP-BioPath) for ‘RAF/MAP kinase cascade’. This study highlights the potential of pathway databases such as Reactome in modeling genetic perturbations, promoting standardization of experimental pathway activity readout and supporting hypothesis-driven research by revealing relationships between pathway inputs and outputs that have not yet been directly experimentally tested. Database URL www.reactome.org
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Affiliation(s)
- Adam J Wright
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Marija Orlic-Milacic
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Karen Rothfels
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Joel Weiser
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Quang M Trinh
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Bijay Jassal
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Robin A Haw
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Lincoln D Stein
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
- Department of Molecular Genetics, University of Toronto, Room 4396, Medical Sciences Building, 1 King’s College Circle, Toronto, ON M5S 1A1, Canada
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The Pharmacological Activity of the Wenjing Decoction in Recurrent Spontaneous Abortion. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:8861394. [PMID: 33936247 PMCID: PMC8060116 DOI: 10.1155/2021/8861394] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 03/18/2021] [Accepted: 04/01/2021] [Indexed: 12/16/2022]
Abstract
Background Recurrent spontaneous abortion (RSA) is intractable infertility and can be ameliorated with the use of traditional Chinese medicine preparation, the Wenjing decoction. This study aimed to identify the therapeutic mechanism of Wenjing decoction on specific target proteins involved in RSA. Methods Wenjing decoction contains Wuzhuyu, Danggui, Chuanxiong, Guizhi, Shengjiang, Banxia, Gancao, Ejiao, Mudanpi, Chishao, Dangshen, and Maidong. Using TCMSP and BATMAN databases, we queried for active ingredients and predicted their target proteins by BATMAN. Using the edgeR package, we analyzed the differentially expressed genes (DEGs) in the GSE121950 database between control samples and RSA (n = 3). The interaction between DEGs and the predicted target proteins was identified by the Venn diagram. Using the Cytoscape software and clusterProfiler package, enrichment analysis was conducted for the intersected target proteins. Additionally, the protein-protein interaction (PPI) network and pharmacological network were generated using the Cytoscape software. Results In total, 31, 2, 7, 7, 5, 13, 93, 11, 29, and 21 active ingredients were identified from Wuzhuyu, Danggui, Chuanxiong, Guizhi, Shengjiang, Banxia, Gancao, Mudanpi, Chishao, and Dangshen, respectively. Additionally, 100 intersected target proteins were revealed by the Venn diagram. Moreover, 98 functional terms and 24 pathways (including C-type lectin receptor signaling pathway, chemokine signaling pathway, leukocyte transendothelial migration, fluid shear stress, and atherosclerosis, and AGE-RAGE signaling pathway in diabetic complications) were enriched. In the PPI network, 10 proteins involved in these five pathways were identified, namely, TNF-α (tumor necrosis factor-α), IL-10 (interleukin-10), TLR4 (Toll-like receptor 4), JUN (Jun proto-oncogene), IL-1B (interleukin-1-beta), CYBB (cytochrome b558 heavy chain gene), PTGS2 (prostaglandin-endoperoxide synthase 2), APOE (apolipoprotein E), SPI1 (salmonella pathogenicity island 1), and MPO (myeloperoxidase) which showed higher degrees. Conclusion The abovementioned genes and pathways might be involved in the pharmacological activity of Wenjing decoction in RSA.
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Khan MT, Irfan M, Ahsan H, Ali S, Malik A, Pech-Cervantes A, Cui Z, Zhang Y, Wei D. CYP1A2, 2A13, and 3A4 network and interaction with aflatoxin B 1. WORLD MYCOTOXIN J 2021. [DOI: 10.3920/wmj2020.2621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Aspergillus fungi are known to produce aflatoxins, among which aflatoxin B1 (AFB1) is the most potent carcinogen that is metabolised by cytochrome P450 (CYP450). In the liver, AFB1 is metabolised into exo-8,9-epoxide by the CYP1A2 enzymes. The resulting epoxide can react with guanine to cause DNA damage. Natural inhibitors are being identified. However, the modes of action are poorly understood. In the current study, we have investigated the mode of action of AFB1 with CYP1A2, CYP3A4 and CYP2A13 using molecular dynamic simulation (MD simulation) approaches. The interaction network and paths among CYP1A2, CYP3A4, and CYP2A13 have been investigated using the STRING database and PathLinker plugin of Cytoscape. CYP3A4 is the most active protein involved in interactions with AFB1 during its metabolism. Residues 362ARG, 445SER, 450LEU and 451PHE of CYP1A2 are important, interacting with AFB1 and converting it to toxic exo-AFB1-8,9-epoxide (AFBEX). The pathway shows that microsomal epoxide hydrolase (EPHX1) may acts as initiator in the signalling pathway where CYP1A2, CYP3A4 and CYP2A13 interact in a sequential order. The interaction network shows there to be a strong association in expression among CYP1A2, CYP3A4 and CYP2A13 along with other metabolising enzymes. The complex of AFB1 and CYP1A2 was found to be stable during the MD simulation. This study provides a better understanding of the mode of action between AFB1 and CYP1A2, CYP3A4 and CYP2A13 which relates to the effective management of AFB1 toxicity. EPHX1 in the protein network may be an ideal target when designing inhibitors to prevent the toxin’s activation. Peptide inhibitors may be designed to block the substrate site residues of CYP1A2 in order to prevent the conversion from AFB1 into AFBEX. This would either neutralise or reduce its toxicity.
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Affiliation(s)
- M. Tahir Khan
- Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore-Pakistan, 54000 Lahore, Pakistan
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, and Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China P.R
| | - M. Irfan
- Department of Oral Biology, College of Dentistry, University of Florida, Gainesville, FL 32611-7011, USA
| | - H. Ahsan
- Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan
| | - S. Ali
- Quaid-i-Azam University Islamabad, Pakistan
- Provincial Tuberculosis Reference Lab, Hayatabad Peshawar, Pakistan
| | - A. Malik
- Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore-Pakistan, 54000 Lahore, Pakistan
| | - A.A. Pech-Cervantes
- Agricultural Research Station, Fort Valley State University, 9000 Watson Blvd, Fort Valley, GA 31030, USA
| | - Z. Cui
- Department of Respiratory Medicine, XinHua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China P.R
| | - Y.J. Zhang
- College of Life Sciences, Chongqing Normal University, Chongqing 401331, China P.R
| | - D.Q. Wei
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, and Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China P.R
- Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nanshan District, Shenzhen, Guangdong, 518055, China P.R
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Bow A. A Streamlined Approach to Pathway Analysis from RNA-Sequencing Data. Methods Protoc 2021; 4:mps4010021. [PMID: 33802642 PMCID: PMC8006023 DOI: 10.3390/mps4010021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/12/2021] [Accepted: 03/12/2021] [Indexed: 11/16/2022] Open
Abstract
The reduction in costs associated with performing RNA-sequencing has driven an increase in the application of this analytical technique; however, restrictive factors associated with this tool have now shifted from budgetary constraints to time required for data processing. The sheer scale of the raw data produced can present a formidable challenge for researchers aiming to glean vital information about samples. Though many of the companies that perform RNA-sequencing provide a basic report for the submitted samples, this may not adequately capture particular pathways of interest for sample comparisons. To further assess these data, it can therefore be necessary to utilize various enrichment and mapping software platforms to highlight specific relations. With the wide array of these software platforms available, this can also present a daunting task. The methodology described herein aims to enable researchers new to handling RNA-sequencing data with a streamlined approach to pathway analysis. Additionally, the implemented software platforms are readily available and free to utilize, making this approach viable, even for restrictive budgets. The resulting tables and nodal networks will provide valuable insight into samples and can be used to generate high-quality graphics for publications and presentations.
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Affiliation(s)
- Austin Bow
- Department of Large Animal Clinical Sciences, University of Tennessee, Knoxville, TN 37996, USA
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Feltes BC, Poloni JDF, Nunes IJG, Faria SS, Dorn M. Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types. Front Genet 2020; 11:586602. [PMID: 33329726 PMCID: PMC7719697 DOI: 10.3389/fgene.2020.586602] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 10/09/2020] [Indexed: 12/19/2022] Open
Abstract
Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer. By applying systems biology approaches, combined with machine learning analysis, we investigated possible frequently deregulated molecular mechanisms underlying the tumoral process. Our multi-approach analysis of 99 curated datasets, composed of 5,406 samples, revealed 47 differentially expressed genes in all analyzed cancer types, which were all in agreement with the validation using TCGA data. Results suggest that the tumoral process is more related to the overexpression of core deregulated machinery than the underexpression of a given gene set. Additionally, we identified gene expression similarities between different cancer types not described before and performed an overall survival analysis using 20 cancer types. Finally, we were able to suggest a core regulatory mechanism that could be frequently deregulated.
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Affiliation(s)
- Bruno César Feltes
- Laboratory of Structural Bioinformatics and Computational Biology, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Joice de Faria Poloni
- Laboratory of Structural Bioinformatics and Computational Biology, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Sara Socorro Faria
- Laboratory of Immunology and Inflammation, Department of Cell Biology, University of Brasilia, Brasilia, Brazil
| | - Marcio Dorn
- Laboratory of Structural Bioinformatics and Computational Biology, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
- Center of Biotechnology, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
- National Institute of Science and Technology - Forensic Science, Porto Alegre, Brazil
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Corrêa T, Poswar F, Feltes BC, Riegel M. Candidate Genes Associated With Neurological Findings in a Patient With Trisomy 4p16.3 and Monosomy 5p15.2. Front Genet 2020; 11:561. [PMID: 32625234 PMCID: PMC7311770 DOI: 10.3389/fgene.2020.00561] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 05/11/2020] [Indexed: 12/12/2022] Open
Abstract
In this report, we present a patient with brain alterations and dysmorphic features associated with chromosome duplication seen in 4p16.3 region and chromosomal deletion in a critical region responsible for Cri-du-chat syndrome (CdCS). Chromosomal microarray analysis (CMA) revealed a 41.1 Mb duplication encompassing the band region 4p16.3-p13, and a 14.7 Mb deletion located between the bands 5p15.33 and p15.1. The patient's clinical findings overlap with previously reported cases of chromosome 4p duplication syndrome and CdCS. The patient's symptoms are notably similar to those of CdCS patients as she presented with a weak, high-pitched voice and showed a similar pathogenicity observed in the brain MRI. These contiguous gene syndromes present with distinct clinical manifestations. However, the phenotypic and cytogenetic variability in affected individuals, such as the low frequency and the large genomic regions that can be altered, make it challenging to identify candidate genes that contribute to the pathogenesis of these syndromes. Therefore, systems biology and CMA techniques were used to investigate the extent of chromosome rearrangement on critical regions in our patient's phenotype. We identified the candidate genes PPARGC1A, CTBP1, TRIO, TERT, and CCT5 that are associated with the neuropsychomotor delay, microcephaly, and neurological alterations found in our patient. Through investigating pathways that associate with essential nodes in the protein interaction network, we discovered proteins involved in cellular differentiation and proliferation, as well as proteins involved in the formation and disposition of the cytoskeleton. The combination of our cytogenomic and bioinformatic analysis provided these possible explanations for the unique clinical phenotype, which has not yet been described in scientific literature.
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Affiliation(s)
- Thiago Corrêa
- Post-Graduate Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Fabiano Poswar
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Bruno César Feltes
- Department of Theoritical Informatics, Institute of Informatics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Mariluce Riegel
- Post-Graduate Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
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Mathé E, Zhang C, Wang K, Ning X, Guo Y, Zhao Z. The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): conference summary and innovations in genomics. BMC Genomics 2019; 20:1005. [PMID: 31888451 PMCID: PMC6936133 DOI: 10.1186/s12864-019-6326-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The goal of this editorial is to summarize the 2019 International Conference on Intelligent Biology and Medicine (ICIBM 2019) conference that took place on June 9–11, 2019 in The Ohio State University, Columbus, OH, and to provide an introductory summary of the seven articles presented in this supplement issue. ICIBM 2019 hosted four keynote speakers, four eminent scholar speakers, five tutorials and workshops, twelve concurrent sessions and a poster session, totaling 23 posters, spanning state-of-the-art developments in bioinformatics, genomics, next-generation sequencing (NGS) analysis, scientific databases, cancer and medical genomics, and computational drug discovery. A total of 105 original manuscripts were submitted to ICIBM 2019, and after careful review, seven were selected for this supplement issue. These articles cover methods and applications for functional annotations of miRNA targeting, clonal evolution of bacterial cells, gene co-expression networks that describe a given phenotype, functional binding site analysis of RNA-binding proteins, normalization of genome architecture mapping data, sample predictions based on multiple NGS data types, and prediction of an individual’s genetic admixture given exonic single nucleotide polymorphisms data.
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Affiliation(s)
- Ewy Mathé
- Department of Biomedical Informatics, The Ohio State University, Columbus, 43210, USA.
| | - Chi Zhang
- Department of Medical & Molecular Genetics, School of Medicine, Indiana University, Indianapolis, Indiana, 46202, USA
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Xia Ning
- Department of Biomedical Informatics, The Ohio State University, Columbus, 43210, USA
| | - Yan Guo
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. .,Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
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11
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McConnell EW, Berg P, Westlake TJ, Wilson KM, Popescu GV, Hicks LM, Popescu SC. Proteome-Wide Analysis of Cysteine Reactivity during Effector-Triggered Immunity. PLANT PHYSIOLOGY 2019; 179:1248-1264. [PMID: 30510037 PMCID: PMC6446758 DOI: 10.1104/pp.18.01194] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 11/16/2018] [Indexed: 05/08/2023]
Abstract
A surge in the accumulation of oxidants generates shifts in the cellular redox potential during early stages of plant infection with pathogens and activation of effector-triggered immunity (ETI). The redoxome, defined as the proteome-wide oxidative modifications of proteins caused by oxidants, has a well-known impact on stress responses in metazoans. However, the identity of proteins and the residues sensitive to oxidation during the plant immune response remain largely unknown. Previous studies of the thimet oligopeptidases TOP1 and TOP2 placed them in the salicylic acid dependent branch of ETI, with a current model wherein TOPs sustain interconnected organellar and cytosolic pathways that modulate the oxidative burst and development of cell death. Herein, we characterized the ETI redoxomes in Arabidopsis (Arabidopsis thaliana) wild-type Col-0 and top1top2 mutant plants using a differential alkylation-based enrichment technique coupled with label-free mass spectrometry-based quantification. We identified cysteines sensitive to oxidation in a wide range of protein families at multiple time points after pathogen infection. Differences were detected between Col-0 and top1top2 redoxomes regarding the identity and number of oxidized cysteines, and the amplitude of time-dependent fluctuations in protein oxidation. Our results support a determining role for TOPs in maintaining the proper level and dynamics of proteome oxidation during ETI. This study significantly expands the repertoire of oxidation-sensitive plant proteins and can guide future mechanistic studies.
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Affiliation(s)
- Evan W McConnell
- Department of Chemistry, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Philip Berg
- Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, Mississippi 39762
| | - Timothy J Westlake
- Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Ithaca, New York 14850
| | - Katherine M Wilson
- Department of Chemistry, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - George V Popescu
- Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, Mississippi 39762
- The National Institute for Laser, Plasma & Radiation Physics, 077126 Măgurele, Ilfov, Romania
| | - Leslie M Hicks
- Department of Chemistry, the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Sorina C Popescu
- Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, Mississippi 39762
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