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Stiens J, Tan YY, Joyce R, Arnvig KB, Kendall SL, Nobeli I. Using a whole genome co-expression network to inform the functional characterisation of predicted genomic elements from Mycobacterium tuberculosis transcriptomic data. Mol Microbiol 2023; 119:381-400. [PMID: 36924313 DOI: 10.1111/mmi.15055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/08/2023] [Accepted: 03/09/2023] [Indexed: 03/18/2023]
Abstract
A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This data set provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.
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Affiliation(s)
- Jennifer Stiens
- Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK
| | - Yen Yi Tan
- Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK
| | - Rosanna Joyce
- Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK
| | - Kristine B Arnvig
- Division of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK
| | - Sharon L Kendall
- Royal Veterinary College, Centre for Emerging, Endemic and Exotic Diseases, Pathobiology and Population Sciences, Hatfield, UK
| | - Irene Nobeli
- Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK
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Naik S, Mohammed A. Coexpression network analysis of human candida infection reveals key modules and hub genes responsible for host-pathogen interactions. Front Genet 2022; 13:917636. [PMID: 36482897 PMCID: PMC9722774 DOI: 10.3389/fgene.2022.917636] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 11/08/2022] [Indexed: 07/30/2023] Open
Abstract
Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. Candida albicans is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients. Therefore, identifying and characterizing these genes would play a vital role in understanding the complex regulation of host-pathogen interactions. Using 32 RNA-sequencing samples of human cells infected with C. albicans, we developed WGCNA coexpression networks and performed DESeq2 differential gene expression analysis to identify the genes that positively correlate with human candida infection. Using hierarchical clustering, we identified 5 distinct modules. We studied the inter- and intramodular gene network properties in the context of sample status traits and identified the highly enriched genes in the correlated modules. We identified 52 genes that were common in the most significant WGCNA turquoise module and differentially expressed genes in human endothelial cells (HUVEC) infection vs. control samples. As a validation step, we identified the differentially expressed genes from the independent Candida-infected human oral keratinocytes (OKF6) samples and validated 30 of the 52 common genes. We then performed the functional enrichment analysis using KEGG and GO. Finally, we performed protein-protein interaction (PPI) analysis using STRING and CytoHubba from 30 validated genes. We identified 8 hub genes (JUN, ATF3, VEGFA, SLC2A1, HK2, PTGS2, PFKFB3, and KLF6) that were enriched in response to hypoxia, angiogenesis, vasculogenesis, hypoxia-induced signaling, cancer, diabetes, and transplant-related disease pathways. The discovery of genes and functional pathways related to the immune system and gene coexpression and differential gene expression analyses may serve as novel diagnostic markers and potential therapeutic targets.
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Affiliation(s)
- Surabhi Naik
- Department of Surgery, James D. Eason Transplant Institute, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Akram Mohammed
- Center for Biomedical Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
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3
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Integrative network analyses of transcriptomics data reveal potential drug targets for acute radiation syndrome. Sci Rep 2021; 11:5585. [PMID: 33692493 PMCID: PMC7946886 DOI: 10.1038/s41598-021-85044-5] [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: 09/16/2020] [Accepted: 02/17/2021] [Indexed: 11/25/2022] Open
Abstract
Recent political unrest has highlighted the importance of understanding the short- and long-term effects of gamma-radiation exposure on human health and survivability. In this regard, effective treatment for acute radiation syndrome (ARS) is a necessity in cases of nuclear disasters. Here, we propose 20 therapeutic targets for ARS identified using a systematic approach that integrates gene coexpression networks obtained under radiation treatment in humans and mice, drug databases, disease-gene association, radiation-induced differential gene expression, and literature mining. By selecting gene targets with existing drugs, we identified potential candidates for drug repurposing. Eight of these genes (BRD4, NFKBIA, CDKN1A, TFPI, MMP9, CBR1, ZAP70, IDH3B) were confirmed through literature to have shown radioprotective effect upon perturbation. This study provided a new perspective for the treatment of ARS using systems-level gene associations integrated with multiple biological information. The identified genes might provide high confidence drug target candidates for potential drug repurposing for ARS.
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Integrative computational approach identifies drug targets in CD4 + T-cell-mediated immune disorders. NPJ Syst Biol Appl 2021; 7:4. [PMID: 33483502 PMCID: PMC7822845 DOI: 10.1038/s41540-020-00165-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 12/08/2020] [Indexed: 12/12/2022] Open
Abstract
CD4+ T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immune-related diseases. CD4+ T cells’ metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease. Here, we develop genome-scale models of naïve, Th1, Th2, and Th17 CD4+ T-cell subtypes to map metabolic perturbations in rheumatoid arthritis, multiple sclerosis, and primary biliary cholangitis. We subjected these models to in silico simulations for drug response analysis of existing FDA-approved drugs and compounds. Integration of disease-specific differentially expressed genes with altered reactions in response to metabolic perturbations identified 68 drug targets for the three autoimmune diseases. In vitro experimental validation, together with literature-based evidence, showed that modulation of fifty percent of identified drug targets suppressed CD4+ T cells, further increasing their potential impact as therapeutic interventions. Our approach can be generalized in the context of other diseases, and the metabolic models can be further used to dissect CD4+ T-cell metabolism.
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Kernel Differential Subgraph Analysis to Reveal the Key Period Affecting Glioblastoma. Biomolecules 2020; 10:biom10020318. [PMID: 32079293 PMCID: PMC7072688 DOI: 10.3390/biom10020318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 02/05/2020] [Accepted: 02/10/2020] [Indexed: 12/26/2022] Open
Abstract
Glioblastoma (GBM) is a fast-growing type of malignant primary brain tumor. To explore the mechanisms in GBM, complex biological networks are used to reveal crucial changes among different biological states, which reflect on the development of living organisms. It is critical to discover the kernel differential subgraph (KDS) that leads to drastic changes. However, identifying the KDS is similar to the Steiner Tree problem that is an NP-hard problem. In this paper, we developed a criterion to explore the KDS (CKDS), which considered the connectivity and scale of KDS, the topological difference of nodes and function relevance between genes in the KDS. The CKDS algorithm was applied to simulated datasets and three single-cell RNA sequencing (scRNA-seq) datasets including GBM, fetal human cortical neurons (FHCN) and neural differentiation. Then we performed the network topology and functional enrichment analyses on the extracted KDSs. Compared with the state-of-art methods, the CKDS algorithm outperformed on simulated datasets to discover the KDSs. In the GBM and FHCN, seventeen genes (one biomarker, nine regulatory genes, one driver genes, six therapeutic targets) and KEGG pathways in KDSs were strongly supported by literature mining that they were highly interrelated with GBM. Moreover, focused on GBM, there were fifteen genes (including ten regulatory genes, three driver genes, one biomarkers, one therapeutic target) and KEGG pathways found in the KDS of neural differentiation process from activated neural stem cells (aNSC) to neural progenitor cells (NPC), while few genes and no pathway were found in the period from NPC to astrocytes (Ast). These experiments indicated that the process from aNSC to NPC is a key differentiation period affecting the development of GBM. Therefore, the CKDS algorithm provides a unique perspective in identifying cell-type-specific genes and KDSs.
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Hosseinkhan N, Mousavian Z, Masoudi-Nejad A. Comparison of gene co-expression networks in Pseudomonas aeruginosa and Staphylococcus aureus reveals conservation in some aspects of virulence. Gene 2017; 639:1-10. [PMID: 28987343 DOI: 10.1016/j.gene.2017.10.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 09/23/2017] [Accepted: 10/03/2017] [Indexed: 12/13/2022]
Abstract
Pseudomonas aeruginosa and Staphylococcus aureus are two evolutionary distant bacterial species that are frequently isolated from persistent infections such as chronic infectious wounds and severe lung infections in cystic fibrosis patients. To the best of our knowledge no comprehensive genome scale co-expression study has been already conducted on these two species and in most cases only the expression of very few genes has been the subject of investigation. In this study, in order to investigate the level of expressional conservation between these two species, using heterogeneous gene expression datasets the weighted gene co-expression network analysis (WGCNA) approach was applied to study both single and cross species genome scale co-expression patterns of these two species. Single species co-expression network analysis revealed that in P. aeruginosa, genes involved in quorum sensing (QS), iron uptake, nitrate respiration and type III secretion systems and in S. aureus, genes associated with the regulation of carbon metabolism, fatty acid-phospholipids metabolism and proteolysis represent considerable co-expression across a variety of experimental conditions. Moreover, the comparison of gene co-expression networks between P. aeruginosa and S. aureus was led to the identification of four co-expressed gene modules in both species totally consisting of 318 genes. Several genes related to two component signal transduction systems, small colony variants (SCVs) morphotype and protein complexes were found in the detected modules. We believe that targeting the key players among the identified co-expressed orthologous genes will be a potential intervention strategy to control refractory co-infections caused by these two bacterial species.
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Affiliation(s)
- Nazanin Hosseinkhan
- Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
| | - Zaynab Mousavian
- Department of Computer Science, School of Mathematics, Statistics, and Computer Science, University of Tehran, Tehran, Iran; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Ali Masoudi-Nejad
- Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
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Identification of prognostic markers of high grade prostate cancer through an integrated bioinformatics approach. J Cancer Res Clin Oncol 2017; 143:2571-2579. [PMID: 28849390 DOI: 10.1007/s00432-017-2497-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 08/07/2017] [Indexed: 10/19/2022]
Abstract
PURPOSE Prostate cancer is one of the leading causes of cancer death for male. In the present study, we applied an integrated bioinformatics approach to provide a novel perspective and identified some hub genes of prostate cancer. METHOD Microarray data of fifty-nine prostate cancer were downloaded from Gene Expression Omnibus. Gene Ontology and pathway analysis were applied for differentially expressed genes between high and low grade prostate cancer. Weighted gene coexpression network analysis was applied to construct gene network and classify genes into different modules. The most related module to high grade prostate cancer was identified and hub genes in the module were revealed. Ingenuity pathway analysis was applied to check the chosen module's relationship to high grade prostate cancer. Hub gene's expression profile was verified with clinical samples and a dataset from The Cancer Genome Atlas project. RESULT 3193 differentially expressed genes were filtered and gene ontology and pathway analysis revealed some cancer- and sex hormone-related results. Weighted gene coexpression network was constructed and genes were classified into six modules. The red module was selected and ingenuity pathway analysis confirmed its relationship with high grade prostate cancer. Hub genes were identified and their expression profile was also confirmed. CONCLUSION The present study applied integrate bioinformatics approaches to generate a holistic view of high grade prostate cancer and identified hub genes could serve as prognosis markers and potential treatment targets.
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Ghiraldi-Lopes LD, Campanerut-Sá PAZ, Meneguello JE, Seixas FAV, Lopes-Ortiz MA, Scodro RBL, Pires CTA, da Silva RZ, Siqueira VLD, Nakamura CV, Cardoso RF. Proteomic profile of Mycobacterium tuberculosis after eupomatenoid-5 induction reveals potential drug targets. Future Microbiol 2017; 12:867-879. [DOI: 10.2217/fmb-2017-0023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: We investigated a proteome profile, protein–protein interaction and morphological changes of Mycobacterium tuberculosis after different times of eupomatenoid-5 (EUP-5) induction to evaluate the cellular response to the drug-induced damages. Methods: The bacillus was induced to sub-minimal inhibitory concentration of EUP-5 at 12 h, 24 h and 48 h. The proteins were separated by 2D gel electrophoresis, identified by LC/MS-MS. Scanning electron microscopy and Search Tool for the Retrieval of Interacting Genes/Proteins analyses were performed. Results: EUP-5 impacts mainly in M. tuberculosis proteins of intermediary metabolism and interactome suggests a multisite disturbance that contributes to bacilli death. Scanning electron microscopy revealed the loss of bacillary form. Conclusion: Some of the differentially expressed proteins have the potential to be drug targets such as citrate synthase (Rv0896), phosphoglycerate kinase (Rv1437), ketol-acid reductoisomerase (Rv3001c) and ATP synthase alpha chain (Rv1308).
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Affiliation(s)
- Luciana D Ghiraldi-Lopes
- Postgraduate Program in Health Sciences, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Paula AZ Campanerut-Sá
- Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Jean E Meneguello
- Postgraduate Program in Biosciences & Phisiopatology, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Flávio AV Seixas
- Department of Biochemistry, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Mariana A Lopes-Ortiz
- Postgraduate Program in Biosciences & Phisiopatology, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Uningá University Center, Rod PR 317, 6114, 87035-510, Maringá, Paraná, Brazil
| | - Regiane BL Scodro
- Postgraduate Program in Health Sciences, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Claudia TA Pires
- Postgraduate Program in Biosciences & Phisiopatology, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Rosi Z da Silva
- State University of Ponta Grossa, Avenida General Carlos Cavalcanti, 4748, 84030-900, Ponta Grossa, Paraná, Brazil
| | - Vera LD Siqueira
- Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Postgraduate Program in Biosciences & Phisiopatology, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Celso V Nakamura
- Postgraduate Program in Pharmaceutical Sciences, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
| | - Rosilene F Cardoso
- Postgraduate Program in Health Sciences, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
- Postgraduate Program in Biosciences & Phisiopatology, Department of Clinical Analyses & Biomedicine, State University of Maringá, Avenida Colombo, 5790, 87020-900, Maringá, Paraná, Brazil
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Shrivastava P, Navratna V, Silla Y, Dewangan RP, Pramanik A, Chaudhary S, Rayasam G, Kumar A, Gopal B, Ramachandran S. Inhibition of Mycobacterium tuberculosis dihydrodipicolinate synthase by alpha-ketopimelic acid and its other structural analogues. Sci Rep 2016; 6:30827. [PMID: 27501775 PMCID: PMC4977564 DOI: 10.1038/srep30827] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 07/11/2016] [Indexed: 11/09/2022] Open
Abstract
The Mycobacterium tuberculosis dihydrodipicolinate synthase (Mtb-dapA) is an essential gene. Mtb-DapA catalyzes the aldol condensation between pyruvate and L-aspartate-beta-semialdehyde (ASA) to yield dihydrodipicolinate. In this work we tested the inhibitory effects of structural analogues of pyruvate on recombinant Mtb-DapA (Mtb-rDapA) using a coupled assay with recombinant dihydrodipicolinate reductase (Mtb-rDapB). Alpha-ketopimelic acid (α-KPA) showed maximum inhibition of 88% and IC50 of 21 μM in the presence of pyruvate (500 μM) and ASA (400 μM). Competition experiments with pyruvate and ASA revealed competition of α-KPA with pyruvate. Liquid chromatography-mass spectrometry (LC-MS) data with multiple reaction monitoring (MRM) showed that the relative abundance peak of final product, 2,3,4,5-tetrahydrodipicolinate, was decreased by 50%. Thermal shift assays showed 1 °C Tm shift of Mtb-rDapA upon binding α-KPA. The 2.4 Å crystal structure of Mtb-rDapA-α-KPA complex showed the interaction of critical residues at the active site with α-KPA. Molecular dynamics simulations over 500 ns of pyruvate docked to Mtb-DapA and of α-KPA-bound Mtb-rDapA revealed formation of hydrogen bonds with pyruvate throughout in contrast to α-KPA. Molecular descriptors analysis showed that ligands with polar surface area of 91.7 Å(2) are likely inhibitors. In summary, α-hydroxypimelic acid and other analogues could be explored further as inhibitors of Mtb-DapA.
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Affiliation(s)
- Priyanka Shrivastava
- Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), South Campus, New Delhi 110025, India
- Academy of Scientific and Innovative Research, CSIR-IGIB South Campus, New Delhi 110025, India
| | - Vikas Navratna
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India
| | - Yumnam Silla
- Biotechnology Group (BIF center), Biological Science & Technology Division (BSTD), CSIR-North-East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India
| | - Rikeshwer P. Dewangan
- Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), South Campus, New Delhi 110025, India
| | - Atreyi Pramanik
- Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), South Campus, New Delhi 110025, India
| | - Sarika Chaudhary
- Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), South Campus, New Delhi 110025, India
| | - GeethaVani Rayasam
- Open Source Drug Discovery Unit (OSDD), CSIR-IGIB, New Delhi, 110001, India
| | - Anuradha Kumar
- Open Source Drug Discovery Unit (OSDD), CSIR-IGIB, New Delhi, 110001, India
| | | | - Srinivasan Ramachandran
- Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), South Campus, New Delhi 110025, India
- Academy of Scientific and Innovative Research, CSIR-IGIB South Campus, New Delhi 110025, India
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Gómez-Vela F, Barranco CD, Díaz-Díaz N. Incorporating biological knowledge for construction of fuzzy networks of gene associations. Appl Soft Comput 2016. [DOI: 10.1016/j.asoc.2016.01.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Integration of Metabolic Modeling with Gene Co-expression Reveals Transcriptionally Programmed Reactions Explaining Robustness in Mycobacterium tuberculosis. Sci Rep 2016; 6:23440. [PMID: 27000948 PMCID: PMC4802306 DOI: 10.1038/srep23440] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 03/07/2016] [Indexed: 12/25/2022] Open
Abstract
Robustness of metabolic networks is accomplished by gene regulation, modularity, re-routing of metabolites and plasticity. Here, we probed robustness against perturbations of biochemical reactions of M. tuberculosis in the form of predicting compensatory trends. In order to investigate the transcriptional programming of genes associated with correlated fluxes, we integrated with gene co-expression network. Knock down of the reactions NADH2r and ATPS responsible for producing the hub metabolites, and Central carbon metabolism had the highest proportion of their associated genes under transcriptional co-expression with genes of their flux correlated reactions. Reciprocal gene expression correlations were observed among compensatory routes, fresh activation of alternative routes and in the multi-copy genes of Cysteine synthase and of Phosphate transporter. Knock down of 46 reactions caused the activation of Isocitrate lyase or Malate synthase or both reactions, which are central to the persistent state of M. tuberculosis. A total of 30 new freshly activated routes including Cytochrome c oxidase, Lactate dehydrogenase, and Glycine cleavage system were predicted, which could be responsible for switching into dormant or persistent state. Thus, our integrated approach of exploring transcriptional programming of flux correlated reactions has the potential to unravel features of system architecture conferring robustness.
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Puniya BL, Allen L, Hochfelder C, Majumder M, Helikar T. Systems Perturbation Analysis of a Large-Scale Signal Transduction Model Reveals Potentially Influential Candidates for Cancer Therapeutics. Front Bioeng Biotechnol 2016; 4:10. [PMID: 26904540 PMCID: PMC4750464 DOI: 10.3389/fbioe.2016.00010] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2015] [Accepted: 01/25/2016] [Indexed: 12/20/2022] Open
Abstract
Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. Computational approaches such as network analysis are important tools to understand system dynamics as well as to identify critical components that could be further explored as therapeutic targets. Here, we performed perturbation analysis of a large-scale signal transduction model in extracellular environments that stimulate cell death, growth, motility, and quiescence. Each of the model’s components was perturbed under both loss-of-function and gain-of-function mutations. Using 1,300 simulations under both types of perturbations across various extracellular conditions, we identified the most and least influential components based on the magnitude of their influence on the rest of the system. Based on the premise that the most influential components might serve as better drug targets, we characterized them for biological functions, housekeeping genes, essential genes, and druggable proteins. The most influential components under all environmental conditions were enriched with several biological processes. The inositol pathway was found as most influential under inactivating perturbations, whereas the kinase and small lung cancer pathways were identified as the most influential under activating perturbations. The most influential components were enriched with essential genes and druggable proteins. Moreover, known cancer drug targets were also classified in influential components based on the affected components in the network. Additionally, the systemic perturbation analysis of the model revealed a network motif of most influential components which affect each other. Furthermore, our analysis predicted novel combinations of cancer drug targets with various effects on other most influential components. We found that the combinatorial perturbation consisting of PI3K inactivation and overactivation of IP3R1 can lead to increased activity levels of apoptosis-related components and tumor-suppressor genes, suggesting that this combinatorial perturbation may lead to a better target for decreasing cell proliferation and inducing apoptosis. Finally, our approach shows a potential to identify and prioritize therapeutic targets through systemic perturbation analysis of large-scale computational models of signal transduction. Although some components of the presented computational results have been validated against independent gene expression data sets, more laboratory experiments are warranted to more comprehensively validate the presented results.
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Affiliation(s)
- Bhanwar Lal Puniya
- Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE , USA
| | - Laura Allen
- Department of Mathematics, University of Nebraska at Omaha , Omaha, NE , USA
| | | | - Mahbubul Majumder
- Department of Mathematics, University of Nebraska at Omaha , Omaha, NE , USA
| | - Tomáš Helikar
- Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE , USA
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Satpathy R, Konkimalla VB, Ratha J. In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene. J Pharm Bioallied Sci 2015; 7:212-7. [PMID: 26229356 PMCID: PMC4517324 DOI: 10.4103/0975-7406.160023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2015] [Revised: 03/20/2015] [Accepted: 04/21/2015] [Indexed: 11/04/2022] Open
Abstract
CONTEXT Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD) superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential. AIMS In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets. MATERIALS AND METHODS In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO) database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE) study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3. STATISTICAL ANALYSIS USED Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold. RESULTS The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology. CONCLUSIONS The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis.
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Affiliation(s)
- Raghunath Satpathy
- School of Life Science, Sambalpur University, Jyoti Vihar, Burla, Odisha, India
| | - V B Konkimalla
- School of Biological Sciences, National Institute of Science Education and Research, Bhubaneswar, Odisha, India
| | - Jagnyeswar Ratha
- School of Life Science, Sambalpur University, Jyoti Vihar, Burla, Odisha, India
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14
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Rawat N, Kiran SP, Du D, Gmitter FG, Deng Z. Comprehensive meta-analysis, co-expression, and miRNA nested network analysis identifies gene candidates in citrus against Huanglongbing disease. BMC PLANT BIOLOGY 2015; 15:184. [PMID: 26215595 PMCID: PMC4517500 DOI: 10.1186/s12870-015-0568-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Accepted: 07/07/2015] [Indexed: 05/20/2023]
Abstract
BACKGROUND Huanglongbing (HLB), the most devastating disease of citrus, is associated with infection by Candidatus Liberibacter asiaticus (CaLas) and is vectored by the Asian citrus psyllid (ACP). Recently, the molecular basis of citrus-HLB interactions has been examined using transcriptome analyses, and these analyses have identified many probe sets and pathways modulated by CaLas infection among different citrus cultivars. However, lack of consistency among reported findings indicates that an integrative approach is needed. This study was designed to identify the candidate probe sets in citrus-HLB interactions using meta-analysis and gene co-expression network modelling. RESULTS Twenty-two publically available transcriptome studies on citrus-HLB interactions, comprising 18 susceptible (S) datasets and four resistant (R) datasets, were investigated using Limma and RankProd methods of meta-analysis. A combined list of 7,412 differentially expressed probe sets was generated using a Teradata in-house Structured Query Language (SQL) script. We identified the 65 most common probe sets modulated in HLB disease among different tissues from the S and R datasets. Gene ontology analysis of these probe sets suggested that carbohydrate metabolism, nutrient transport, and biotic stress were the core pathways that were modulated in citrus by CaLas infection and HLB development. We also identified R-specific probe sets, which encoded leucine-rich repeat proteins, chitinase, constitutive disease resistance (CDR), miraculins, and lectins. Weighted gene co-expression network analysis (WGCNA) was conducted on 3,499 probe sets, and 21 modules with major hub probe sets were identified. Further, a miRNA nested network was created to examine gene regulation of the 3,499 target probe sets. Results suggest that csi-miR167 and csi-miR396 could affect ion transporters and defence response pathways, respectively. CONCLUSION Most of the potential candidate hub probe sets were co-expressed with gibberellin pathway (GA)-related probe sets, implying the role of GA signalling in HLB resistance. Our findings contribute to the integration of existing citrus-HLB transcriptome data that will help to elucidate the holistic picture of the citrus-HLB interaction. The citrus probe sets identified in this analysis signify a robust set of HLB-responsive candidates that are useful for further validation.
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Affiliation(s)
- Nidhi Rawat
- University of Florida, Institute of Food and Agricultural Sciences, Gulf Coast Research and Education Center, Wimauma, FL, 33598, USA.
| | - Sandhya P Kiran
- Ocimum BioSolutions, Banjara Hills Road No. 1, VI Floor Reliance Classic, Hyderabad, 500039, India.
| | - Dongliang Du
- University of Florida, Institute of Food and Agricultural Sciences, Citrus Research and Education Center, Lake Alfred, FL, 33850, USA.
| | - Fred G Gmitter
- University of Florida, Institute of Food and Agricultural Sciences, Citrus Research and Education Center, Lake Alfred, FL, 33850, USA.
| | - Zhanao Deng
- University of Florida, Institute of Food and Agricultural Sciences, Gulf Coast Research and Education Center, Wimauma, FL, 33598, USA.
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15
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Rodrigues RF, Zárate-Bladés CR, Rios WM, Soares LS, Souza PRM, Brandão IT, Masson AP, Arnoldi FGC, Ramos SG, Letourneur F, Jacques S, Cagnard N, Chiocchia G, Silva CL. Synergy of chemotherapy and immunotherapy revealed by a genome-scale analysis of murine tuberculosis. J Antimicrob Chemother 2015; 70:1774-83. [PMID: 25687643 DOI: 10.1093/jac/dkv023] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Accepted: 01/05/2015] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES Although TB immunotherapy improves the results of conventional drug treatment, the effects of combining chemotherapy and immunotherapy have never been systematically evaluated. We used a comprehensive lung transcriptome analysis to directly compare the activity of combined chemotherapy and immunotherapy with that of single treatments in a mouse model of TB. METHODS Mycobacterium tuberculosis-infected mice in the chronic phase of the disease (day 30) received: (i) isoniazid and rifampicin (drugs) daily for 30 days; (ii) DNA immunotherapy (DNA), consisting of four 100 μg injections at 10 day intervals; (iii) both therapies (DNA + drugs); or (iv) saline. The effects were evaluated 10 days after the end of treatment (day 70 post-infection). RESULTS In all groups a systemic reduction in the load of bacilli was observed, bacilli became undetectable in the drugs and DNA + drugs groups, but the whole lung transcriptome analysis showed 867 genes exclusively modulated by the DNA + drugs combination. Gene enrichment analysis indicated that DNA + drugs treatment provided synergistic effects, including the down-regulation of proinflammatory cytokines and mediators of fibrosis, as confirmed by real-time PCR, ELISA, histopathology and hydroxyproline assay. CONCLUSIONS Our results provide a molecular basis for the advantages of TB treatment using combined chemotherapy and DNA immunotherapy and demonstrate the synergistic effects obtained with this strategy.
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Affiliation(s)
- Rodrigo F Rodrigues
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Carlos R Zárate-Bladés
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Wendy M Rios
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Luana S Soares
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Patricia R M Souza
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Izaíra T Brandão
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Ana P Masson
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Frederico G C Arnoldi
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
| | - Simone G Ramos
- Department of Pathology, Ribeirão Preto School of Medicine, University of São Paulo, Ribeirao Preto, São Paulo, 14049-900, Brazil
| | - Franck Letourneur
- Université Paris-Descartes, Institut Cochin and INSERM U1016, CNRS (CMRS 8104), Paris, 75014, France
| | - Sébastien Jacques
- Université Paris-Descartes, Institut Cochin and INSERM U1016, CNRS (CMRS 8104), Paris, 75014, France
| | - Nicolas Cagnard
- Université Paris-Descartes, Institut Cochin and INSERM U1016, CNRS (CMRS 8104), Paris, 75014, France Hôpital Necker, Paris, 75015, France
| | - Gilles Chiocchia
- Université Paris-Descartes, Institut Cochin and INSERM U1016, CNRS (CMRS 8104), Paris, 75014, France
| | - Celio L Silva
- The Centre for Tuberculosis Research, Department of Biochemistry and Immunology, Ribeirão Preto School of Medicine, University of São Paulo, São Paulo, Ribeirao Preto, 14049-900, Brazil
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16
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Zhou Y, Xu J, Liu Y, Li J, Chang C, Xu C. Rat hepatocytes weighted gene co-expression network analysis identifies specific modules and hub genes related to liver regeneration after partial hepatectomy. PLoS One 2014; 9:e94868. [PMID: 24743545 PMCID: PMC3990548 DOI: 10.1371/journal.pone.0094868] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2013] [Accepted: 03/19/2014] [Indexed: 11/20/2022] Open
Abstract
The recovery of liver mass is mainly mediated by proliferation of hepatocytes after 2/3 partial hepatectomy (PH) in rats. Studying the gene expression profiles of hepatocytes after 2/3 PH will be helpful to investigate the molecular mechanisms of liver regeneration (LR). We report here the first application of weighted gene co-expression network analysis (WGCNA) to analyze the biological implications of gene expression changes associated with LR. WGCNA identifies 12 specific gene modules and some hub genes from hepatocytes genome-scale microarray data in rat LR. The results suggest that upregulated MCM5 may promote hepatocytes proliferation during LR; BCL3 may play an important role by activating or inhibiting NF-kB pathway; MAPK9 may play a permissible role in DNA replication by p38 MAPK inactivation in hepatocytes proliferation stage. Thus, WGCNA can provide novel insight into understanding the molecular mechanisms of LR.
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Affiliation(s)
- Yun Zhou
- College of Life Science, Henan Normal University, Xinxiang, Henan, China
- Key Laboratory of Cell Differentiation and Regulation, Henan Normal University, Xinxiang, Henan, China
- College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan, China
- * E-mail: (YZ); (CSX)
| | - Jiucheng Xu
- College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan, China
| | - Yunqing Liu
- College of Life Science, Henan Normal University, Xinxiang, Henan, China
- Key Laboratory of Cell Differentiation and Regulation, Henan Normal University, Xinxiang, Henan, China
| | - Juntao Li
- College of Mathematics and Information Science, Henan Normal University, Xinxiang, Henan, China
| | - Cuifang Chang
- College of Life Science, Henan Normal University, Xinxiang, Henan, China
- Key Laboratory of Cell Differentiation and Regulation, Henan Normal University, Xinxiang, Henan, China
| | - Cunshuan Xu
- College of Life Science, Henan Normal University, Xinxiang, Henan, China
- Key Laboratory of Cell Differentiation and Regulation, Henan Normal University, Xinxiang, Henan, China
- * E-mail: (YZ); (CSX)
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