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2019 | OriginalPaper | Buchkapitel

System Network Biology Approaches in Exploring of Mechanism Behind Mutagenesis

verfasst von : Anukriti, Swati Uniyal, Anupam Dhasmana, Meenu Gupta, Kavindra Kumar Kesari, Qazi Mohd. Sajid Jamal, Mohtashim Lohani

Erschienen in: Networking of Mutagens in Environmental Toxicology

Verlag: Springer International Publishing

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Abstract

Mutagenesis is the alteration of the genetic material by the help of mutagens. Mutations that are capable of inducing any diseases have a large impact on the biological systems. Whenever mutation occurs, it not only affects any particular gene or protein, but also affects the whole system related to that gene. Changes in one system will further bring out changes in the adjacent systems, which works in coordination with the mutated system. Thus, a single mutation can have an impact on more than one system. System network biology helps in providing a new perspective of inspection of these biological systems in the form of networks with the help of mathematical representations. In this chapter, we deal with different properties of the networks that help in analyzing the network-graph and finding the most probable network that best describes the process. Here we tried to investigate the candidate protein molecule that may act as a target protein with the help of network analysis. For this, we used various datasets and software that would be used in the reconstruction of different biological networks and pathways.

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Literatur
Zurück zum Zitat Barabási LS, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113CrossRef Barabási LS, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113CrossRef
Zurück zum Zitat Borgattia SP, Everett MG (2006) A graph-theoretic perspective on centrality. Soc Netw 28(4):466–484CrossRef Borgattia SP, Everett MG (2006) A graph-theoretic perspective on centrality. Soc Netw 28(4):466–484CrossRef
Zurück zum Zitat Bosley AD, Das S, Andresson T (2013) A role for protein–protein interaction networks in the identification and characterization of potential biomarkers (Chap. 21). In: Proteomic and metabolomic approaches to biomarker discovery, pp 333–347CrossRef Bosley AD, Das S, Andresson T (2013) A role for protein–protein interaction networks in the identification and characterization of potential biomarkers (Chap. 21). In: Proteomic and metabolomic approaches to biomarker discovery, pp 333–347CrossRef
Zurück zum Zitat Brandes U (2008) On variants of shortest-path betweenness centrality and their generic computation. Soc Netw 2:136–145CrossRef Brandes U (2008) On variants of shortest-path betweenness centrality and their generic computation. Soc Netw 2:136–145CrossRef
Zurück zum Zitat Buisson B, Bertrand D (2002) Nicotine addiction: the possible role of functional upregulation. Trends Pharmacol Sci 23(3):130–136CrossRef Buisson B, Bertrand D (2002) Nicotine addiction: the possible role of functional upregulation. Trends Pharmacol Sci 23(3):130–136CrossRef
Zurück zum Zitat Bullmore DE, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRef Bullmore DE, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRef
Zurück zum Zitat Chang X, Xu T, Li Y, Wang K (2013) Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of ‘date’ and ‘party’ hubs. Sci Rep 3:1691CrossRef Chang X, Xu T, Li Y, Wang K (2013) Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of ‘date’ and ‘party’ hubs. Sci Rep 3:1691CrossRef
Zurück zum Zitat Dietz KJ, Jacquot JP, Harris G (2010) Hubs and bottlenecks in plant molecular signalling networks. New Phytol 188(4):919–936CrossRef Dietz KJ, Jacquot JP, Harris G (2010) Hubs and bottlenecks in plant molecular signalling networks. New Phytol 188(4):919–936CrossRef
Zurück zum Zitat Frank O (2010) Transitivity in stochastic graphs and digraphs. J Math Soc 7(2):199–213CrossRef Frank O (2010) Transitivity in stochastic graphs and digraphs. J Math Soc 7(2):199–213CrossRef
Zurück zum Zitat Frenz CM (2005) Neural network-based prediction of mutation-induced protein stability changes in Staphylococcal nuclease at 20 residue positions. Proteins Struct Funct Bioinform 59(2):147–151CrossRef Frenz CM (2005) Neural network-based prediction of mutation-induced protein stability changes in Staphylococcal nuclease at 20 residue positions. Proteins Struct Funct Bioinform 59(2):147–151CrossRef
Zurück zum Zitat Gavin AC et al (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature 440:631–636CrossRef Gavin AC et al (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature 440:631–636CrossRef
Zurück zum Zitat Goel A, Wilkins MR (2012) Dynamic hubs show competitive and static hubs non-competitive regulation of their interaction partners. PLoS ONE 7(10):e48209CrossRef Goel A, Wilkins MR (2012) Dynamic hubs show competitive and static hubs non-competitive regulation of their interaction partners. PLoS ONE 7(10):e48209CrossRef
Zurück zum Zitat He X, Zhang J (2006) Why do hubs tend to be essential in protein networks? PLoS Genet 2(6):e88CrossRef He X, Zhang J (2006) Why do hubs tend to be essential in protein networks? PLoS Genet 2(6):e88CrossRef
Zurück zum Zitat Hecht SS (2003) Tobacco carcinogens, their biomarkers and tobacco-induced cancer. Nat Rev Cancer 3(10):733–744CrossRef Hecht SS (2003) Tobacco carcinogens, their biomarkers and tobacco-induced cancer. Nat Rev Cancer 3(10):733–744CrossRef
Zurück zum Zitat Howard DJ, Briggs LA, Pritsos CA (1998) Oxidative DNA damage in mouse heart, liver, and lung tissue due to acute side-stream tobacco smoke exposure. Arch Biochem Biophys 352(2):293–297CrossRef Howard DJ, Briggs LA, Pritsos CA (1998) Oxidative DNA damage in mouse heart, liver, and lung tissue due to acute side-stream tobacco smoke exposure. Arch Biochem Biophys 352(2):293–297CrossRef
Zurück zum Zitat Kalna G, Higham DJ (2007) A clustering coefficient for weighted networks, with application to gene expression data. AI Commun—Netw Anal Nat Sci Eng 20(4):263–271 Kalna G, Higham DJ (2007) A clustering coefficient for weighted networks, with application to gene expression data. AI Commun—Netw Anal Nat Sci Eng 20(4):263–271
Zurück zum Zitat Kang U, Papadimitriou S, Sun J, Tong H (2011) Centralities in large networks: algorithms and observations. In: Proceedings of the 2011 SIAM international conference on data mining, pp 119–130 Kang U, Papadimitriou S, Sun J, Tong H (2011) Centralities in large networks: algorithms and observations. In: Proceedings of the 2011 SIAM international conference on data mining, pp 119–130
Zurück zum Zitat Lim E, Pon A, Djoumbou Y, Knox Craig, Shrivastava S, Guo AC, Neveu V, Wishart DS (2010) T3DB: a comprehensively annotated database of common toxins and their targets. Nucl Acids Res 38:D781–D786CrossRef Lim E, Pon A, Djoumbou Y, Knox Craig, Shrivastava S, Guo AC, Neveu V, Wishart DS (2010) T3DB: a comprehensively annotated database of common toxins and their targets. Nucl Acids Res 38:D781–D786CrossRef
Zurück zum Zitat Lu Z (2011) PubMed and beyond: a survey of web tools for searching biomedical literature. Database 2011(1):baq036CrossRef Lu Z (2011) PubMed and beyond: a survey of web tools for searching biomedical literature. Database 2011(1):baq036CrossRef
Zurück zum Zitat Lv YW, Jing Wang J, Sun L, Zhang JM, Cao L, Ding YY, Chen Y, Dou JJ, Huang J, Tang YF, Wu WT, Cui WR, Lv HT (2013) Understanding the pathogenesis of kawasaki disease by network and pathway analysis. Comput Math Methods Med 2013:1–17CrossRef Lv YW, Jing Wang J, Sun L, Zhang JM, Cao L, Ding YY, Chen Y, Dou JJ, Huang J, Tang YF, Wu WT, Cui WR, Lv HT (2013) Understanding the pathogenesis of kawasaki disease by network and pathway analysis. Comput Math Methods Med 2013:1–17CrossRef
Zurück zum Zitat Morlan J, Baker J, Sinicropi D (2009) Mutation detection by RT-PCR: a simple, robust and highly selective method. PLoS ONE 4(2):e4584CrossRef Morlan J, Baker J, Sinicropi D (2009) Mutation detection by RT-PCR: a simple, robust and highly selective method. PLoS ONE 4(2):e4584CrossRef
Zurück zum Zitat Opsahl T, Panzarasa P (2009) Clustering in weighted networks. Soc Netw 31(2):155–163CrossRef Opsahl T, Panzarasa P (2009) Clustering in weighted networks. Soc Netw 31(2):155–163CrossRef
Zurück zum Zitat Pfeifer GP, Denissenko MF, Olivier M, Tretyakova N, Hecht SS, Hainaut P (2002) Tobacco smoke carcinogens, DNA damage and p53 mutations in smoking-associated cancers. Oncogene 21(48):7435–7451CrossRef Pfeifer GP, Denissenko MF, Olivier M, Tretyakova N, Hecht SS, Hainaut P (2002) Tobacco smoke carcinogens, DNA damage and p53 mutations in smoking-associated cancers. Oncogene 21(48):7435–7451CrossRef
Zurück zum Zitat Pržulj N, Wigle DA, Jurisica I (2004) Functional topology in a network of protein interactions. Bioinformatics 20(3):340–348CrossRef Pržulj N, Wigle DA, Jurisica I (2004) Functional topology in a network of protein interactions. Bioinformatics 20(3):340–348CrossRef
Zurück zum Zitat Ran J, Li H, Fu J, Liu L, Xing Y, Li X, Shen H, Chen Y, Jiang X, Li Y, Li H (2013) Construction and analysis of the protein-protein interaction network related to essential hypertension. BMC Syst Biol 7:32CrossRef Ran J, Li H, Fu J, Liu L, Xing Y, Li X, Shen H, Chen Y, Jiang X, Li Y, Li H (2013) Construction and analysis of the protein-protein interaction network related to essential hypertension. BMC Syst Biol 7:32CrossRef
Zurück zum Zitat Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504CrossRef Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504CrossRef
Zurück zum Zitat Spirin V, Mirny LA (2003) Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci U S A 100(21):12123–12128CrossRef Spirin V, Mirny LA (2003) Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci U S A 100(21):12123–12128CrossRef
Zurück zum Zitat Stam CJ, Reijneveld JC (2007) Graph theoretical analysis of complex networks in the brain. Nonlinear Biomed Phys 1(3):1–19 Stam CJ, Reijneveld JC (2007) Graph theoretical analysis of complex networks in the brain. Nonlinear Biomed Phys 1(3):1–19
Zurück zum Zitat Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucl Acids Res 43:D447–D452CrossRef Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucl Acids Res 43:D447–D452CrossRef
Zurück zum Zitat Vallabhajosyula RR, Chakravarti D, Lutfeali S, Ray A, Raval A (2009) Identifying hubs in protein interaction networks. PLoS ONE 4(4):e5344CrossRef Vallabhajosyula RR, Chakravarti D, Lutfeali S, Ray A, Raval A (2009) Identifying hubs in protein interaction networks. PLoS ONE 4(4):e5344CrossRef
Zurück zum Zitat Vandereyken K, Leene JV, Coninck BD, Cammue BPA (2018) Hub protein controversy: taking a closer look at plant stress response hubs. Front Plant Sci 9:694CrossRef Vandereyken K, Leene JV, Coninck BD, Cammue BPA (2018) Hub protein controversy: taking a closer look at plant stress response hubs. Front Plant Sci 9:694CrossRef
Zurück zum Zitat Villaverde AF, Ross J, Banga JR (2013) Reverse engineering cellular networks with information theoretic methods. Cells 2(2):306–329CrossRef Villaverde AF, Ross J, Banga JR (2013) Reverse engineering cellular networks with information theoretic methods. Cells 2(2):306–329CrossRef
Zurück zum Zitat Wishart D, Arndt D, Pon A, Sajed T, Guo AC, Djoumbou Y, Knox C, Wilson M, Liang Y, Liu JGY, Goldansaz SA, Rappaport SM (2015) T3DB: the toxic exposome database. Nucl Acids Res 43(D1):D928–D934CrossRef Wishart D, Arndt D, Pon A, Sajed T, Guo AC, Djoumbou Y, Knox C, Wilson M, Liang Y, Liu JGY, Goldansaz SA, Rappaport SM (2015) T3DB: the toxic exposome database. Nucl Acids Res 43(D1):D928–D934CrossRef
Zurück zum Zitat Wu Q (2013) The maximum clique problems with applications to graph coloring. Artificial Intelligence [cs.AI]. Université d’Angers. English Wu Q (2013) The maximum clique problems with applications to graph coloring. Artificial Intelligence [cs.AI]. Université d’Angers. English
Zurück zum Zitat Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M (2007) The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol 3(4):e59CrossRef Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M (2007) The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol 3(4):e59CrossRef
Zurück zum Zitat Zhu CQ, Lam TH, Jiang CQ, Wei BX, Lou X, Liu WW, Lao XQ, Chen YH (1999) Lymphocyte DNA damage in cigarette factory workers measured by the Comet assay. Mutat Res/Genet Toxicol Environ Mutagen 444(1):1–6CrossRef Zhu CQ, Lam TH, Jiang CQ, Wei BX, Lou X, Liu WW, Lao XQ, Chen YH (1999) Lymphocyte DNA damage in cigarette factory workers measured by the Comet assay. Mutat Res/Genet Toxicol Environ Mutagen 444(1):1–6CrossRef
Zurück zum Zitat Zotenko E, Mestre J, O’Leary DP, Przytycka TM (2008) Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS Comput Biol 4(8):e1000140CrossRef Zotenko E, Mestre J, O’Leary DP, Przytycka TM (2008) Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS Comput Biol 4(8):e1000140CrossRef
Metadaten
Titel
System Network Biology Approaches in Exploring of Mechanism Behind Mutagenesis
verfasst von
Anukriti
Swati Uniyal
Anupam Dhasmana
Meenu Gupta
Kavindra Kumar Kesari
Qazi Mohd. Sajid Jamal
Mohtashim Lohani
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-319-96511-6_6