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Wu J, Xia X, Hu Y, Fang X, Orsulic S. Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis. Front Genet 2021; 12:580190. [PMID: 33613630 PMCID: PMC7887323 DOI: 10.3389/fgene.2021.580190] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 01/04/2021] [Indexed: 12/19/2022] Open
Abstract
Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.
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Affiliation(s)
- Jingni Wu
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China.,Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Xiaomeng Xia
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ye Hu
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Xiaoling Fang
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sandra Orsulic
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Li KN, Zhang YY, Yu YN, Wu HL, Wang Z. Met-Controlled Allosteric Module of Neural Generation as A New Therapeutic Target in Rodent Brain Ischemia. Chin J Integr Med 2019; 27:896-904. [PMID: 31418133 DOI: 10.1007/s11655-019-3182-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/05/2019] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To investigate a Met-controlled allosteric module (AM) of neural generation as a potential therapeutic target for brain ischemia. METHODS We selected Markov clustering algorithm (MCL) to mine functional modules in the related target networks. According to the topological similarity, one functional module was predicted in the modules of baicalin (BA), jasminoidin (JA), cholic acid (CA), compared with I/R model modules. This functional module included three genes: Inppl1, Met and Dapk3 (IMD). By gene ontology enrichment analysis, biological process related to this functional module was obtained. This functional module participated in generation of neurons. Western blotting was applied to present the compound-dependent regulation of IMD. Co-immunoprecipitation was used to reveal the relationship among the three members. We used IF to determine the number of newborn neurons between compound treatment group and ischemia/reperfusion group. The expressions of vascular endothelial growth factor (VEGF) and matrix metalloproteinase 9 (MMP-9) were supposed to show the changing circumstances for neural generation under cerebral ischemia. RESULTS Significant reduction in infarction volume and pathological changes were shown in the compound treatment groups compared with the I/R model group (P<0.05). Three nodes in one novel module of IMD were found to exert diverse compound-dependent ischemic-specific excitatory regulatory activities. An anti-ischemic excitatory allosteric module (AME) of generation of neurons (AME-GN) was validated successfully in vivo. Newborn neurons increased in BJC treatment group (P<0.05). The expression of VEGF and MMP-9 decreased in the compound treatment groups compared with the I/R model group (P<0.05). CONCLUSIONS AME demonstrates effectiveness of our pioneering approach to the discovery of therapeutic target. The novel approach for AM discovery in an effort to identify therapeutic targets holds the promise of accelerating elucidation of underlying pharmacological mechanisms in cerebral ischemia.
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Affiliation(s)
- Kang-Ning Li
- Department of Traditional Chinese Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Ying-Ying Zhang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Ya-Nan Yu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Hong-Li Wu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Zhong Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
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Zhang Y, Zhao Z, Yu Y, Liu J, Wang P, Li B, Zhang X, Chen Y, Wang Z. Mining the Synergistic Core Allosteric Modules Variation and Sequencing Pharmacological Module Drivers in a Preclinical Model of Ischemia. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2018; 7:269-280. [PMID: 29464871 PMCID: PMC5915616 DOI: 10.1002/psp4.12281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 12/20/2017] [Accepted: 01/12/2018] [Indexed: 12/02/2022]
Abstract
Identifying the variation of core modules and hubs seems to be critical for characterizing variable pharmacological mechanisms based on topological alteration of disease networks. We first identified a total of eight core modules by using an approach of multiple modular characteristic fusing (MMCF) from different targeted networks in ischemic mice. Interestingly, the value of module disturbance intensity (MDI) increased in drug combination group. Second, we redefined a weak allosteric module and a strong allosteric module. Then, we identified 15 pharmacological module drivers (PMDs) by leave‐one‐out screening with a cutoff of two folds, which were at least, in part, validated by expression and variation of topological contribution. Finally, we revealed the fusional and emergent variation of PMD in core modules contributing to multidimensional synergistic mechanism in ischemic mice and rats. Our findings provide a new set of drivers that might promote the pharmacological modular flexibility and offer a potential avenue for disease treatment.
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Affiliation(s)
- Yingying Zhang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Haiyuncang, Beijing, China.,Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.,Shanxi Buchang Pharmaceutical Co. Ltd, Gaoxin Road, Xi'an, China
| | - Zide Zhao
- Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanan Yu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jun Liu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Pengqian Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.,Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Bing Li
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaoxu Zhang
- Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yinying Chen
- Guang 'anmen Hospital, China Academy of Chinese Medical Sciences, Beixiange, Beijing, China
| | - Zhong Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
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Li B, Liu J, Yu Y, Wang P, Zhang Y, Ni X, Liu Q, Zhang X, Wang Z, Wang Y. Network-Wide Screen Identifies Variation of Novel Precise On-Module Targets Using Conformational Modudaoism. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2017; 7:16-25. [PMID: 28925077 PMCID: PMC5784734 DOI: 10.1002/psp4.12253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 08/30/2017] [Accepted: 09/13/2017] [Indexed: 01/30/2023]
Abstract
Modular targeting is promising in drug research at the network level, but it is challenging to quantificationally identify the precise on-modules. Based on a proposed Modudaoism (MD), we defined conserved MD (MDc) and varied MD (MDv) to quantitatively evaluate the conformational and energy variations of modules, and thereby identify the conserved and discrepant allosteric modules (AMs). Compared to the Zsummary , MDc/MDv got an optimized result of module preserved ratio and modular structure. In the mice anti-ischemic networks, 3, 5, and 1 conserved AMs as well as 4, 1, and 3 on-modules of baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) were identified by MDc and MDv, 5 unique AMs and their characteristic actions were revealed. Besides, co-immunoprecipitation (Co-IP) experiments validated the representative modular structure. MDc/MDv method can quantitatively define the conformational variations of modules and screen the precise on-modules network-wide, which may provide a promising strategy for drug discovery.
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Affiliation(s)
- Bing Li
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.,Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.,ShanXi Buchang Pharmaceutical Co., Ltd., Heze, China
| | - Jun Liu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanan Yu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Pengqian Wang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yingying Zhang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Xumin Ni
- Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing, China
| | - Qiong Liu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaoxu Zhang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhong Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yongyan Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
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Xu Y, Guo M, Liu X, Wang C, Liu Y, Liu G. Identify bilayer modules via pseudo-3D clustering: applications to miRNA-gene bilayer networks. Nucleic Acids Res 2016; 44:e152. [PMID: 27484480 PMCID: PMC5741208 DOI: 10.1093/nar/gkw679] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Revised: 06/30/2016] [Accepted: 07/18/2016] [Indexed: 12/11/2022] Open
Abstract
Module identification is a frequently used approach for mining local structures with more significance in global networks. Recently, a wide variety of bilayer networks are emerging to characterize the more complex biological processes. In the light of special topological properties of bilayer networks and the accompanying challenges, there is yet no effective method aiming at bilayer module identification to probe the modular organizations from the more inspiring bilayer networks. To this end, we proposed the pseudo-3D clustering algorithm, which starts from extracting initial non-hierarchically organized modules and then iteratively deciphers the hierarchical organization of modules according to a bottom-up strategy. Specifically, a modularity function for bilayer modules was proposed to facilitate the algorithm reporting the optimal partition that gives the most accurate characterization of the bilayer network. Simulation studies demonstrated its robustness and outperformance against alternative competing methods. Specific applications to both the soybean and human miRNA-gene bilayer networks demonstrated that the pseudo-3D clustering algorithm successfully identified the overlapping, hierarchically organized and highly cohesive bilayer modules. The analyses on topology, functional and human disease enrichment and the bilayer subnetwork involved in soybean fat biosynthesis provided both the theoretical and biological evidence supporting the effectiveness and robustness of pseudo-3D clustering algorithm.
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Affiliation(s)
- Yungang Xu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Maozu Guo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Xiaoyan Liu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Chunyu Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Yang Liu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Guojun Liu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
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Quantitative assessment of gene expression network module-validation methods. Sci Rep 2015; 5:15258. [PMID: 26470848 PMCID: PMC4607977 DOI: 10.1038/srep15258] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Accepted: 09/21/2015] [Indexed: 02/01/2023] Open
Abstract
Validation of pluripotent modules in diverse networks holds enormous potential for systems biology and network pharmacology. An arising challenge is how to assess the accuracy of discovering all potential modules from multi-omic networks and validating their architectural characteristics based on innovative computational methods beyond function enrichment and biological validation. To display the framework progress in this domain, we systematically divided the existing Computational Validation Approaches based on Modular Architecture (CVAMA) into topology-based approaches (TBA) and statistics-based approaches (SBA). We compared the available module validation methods based on 11 gene expression datasets, and partially consistent results in the form of homogeneous models were obtained with each individual approach, whereas discrepant contradictory results were found between TBA and SBA. The TBA of the Zsummary value had a higher Validation Success Ratio (VSR) (51%) and a higher Fluctuation Ratio (FR) (80.92%), whereas the SBA of the approximately unbiased (AU) p-value had a lower VSR (12.3%) and a lower FR (45.84%). The Gray area simulated study revealed a consistent result for these two models and indicated a lower Variation Ratio (VR) (8.10%) of TBA at 6 simulated levels. Despite facing many novel challenges and evidence limitations, CVAMA may offer novel insights into modular networks.
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Nussinov R, Jang H. Dynamic multiprotein assemblies shape the spatial structure of cell signaling. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 116:158-64. [PMID: 25046855 PMCID: PMC4250281 DOI: 10.1016/j.pbiomolbio.2014.07.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Accepted: 07/07/2014] [Indexed: 11/25/2022]
Abstract
Cell signaling underlies critical cellular decisions. Coordination, efficiency as well as fail-safe mechanisms are key elements. How the cell ensures that these hallmarks are at play are important questions. Cell signaling is often viewed as taking place through discrete and cross-talking pathways; oftentimes these are modularized to emphasize distinct functions. While simple, convenient and clear, such models largely neglect the spatial structure of cell signaling; they also convey inter-modular (or inter-protein) spatial separation that may not exist. Here our thesis is that cell signaling is shaped by a network of multiprotein assemblies. While pre-organized, the assemblies and network are loose and dynamic. They contain transiently-associated multiprotein complexes which are often mediated by scaffolding proteins. They are also typically anchored in the membrane, and their continuum may span the cell. IQGAP1 scaffolding protein which binds proteins including Raf, calmodulin, Mek, Erk, actin, and tens more, with actin shaping B-cell (and likely other) membrane-anchored nanoclusters and allosterically polymerizing in dynamic cytoskeleton formation, and Raf anchoring in the membrane along with Ras, provides a striking example. The multivalent network of dynamic proteins and lipids, with specific interactions forming and breaking, can be viewed as endowing gel-like properties. Collectively, this reasons that efficient, productive and reliable cell signaling takes place primarily through transient, preorganized and cooperative protein-protein interactions spanning the cell rather than stochastic, diffusion-controlled processes.
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Affiliation(s)
- Ruth Nussinov
- Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA; Sackler Inst. of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Hyunbum Jang
- Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA
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