Abstract
In the last decade, several researchers have been using interaction networks resources to investigate of the role of biologic interactions in biodiversity maintenance. The conceptual foundations are the same as in Social Networks (such as Facebook), that have brought a set of metrics to study the network structure and the function of each node in the network. Thus, the aim of this work was to assess the application of Social Network Analysis (SNA) concepts and metrics in microbiological interaction networks, to identify patterns of cohesive subgroups, besides discovering new knowledge regarding the underlying structure of subgroups. We built a bipartite microbiological interaction database containing frequency of phylogenetic subgroups in water bodies and applied the following SNA metrics: dependence distribution, strength, betweenness centrality and clique. The sna package for the R program, Pajek, Dieta and Ucinet programs were the tools used. Among the results, we found that SNA concepts and metrics are extremely useful in microbiological studies to understand the correlation between each node in the network (the generalist and the predominant nodes), as well as to analyze the co-occurrence pattern of microorganisms in the network (cohesive subgroups).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Araújo, M.S., Guimarães, P.R., Svanbäck, R., Pinheiro, A., Guimarães, P., Reis, S.F., Bol-nick, D.I.: Network analysis reveals contrasting effects of intraspecific competition on indi-vidual vs. population diets. Ecology 89, 1981–1993 (2008)
Bapteste, E., Bicep, C., Lopez, P.: Evolution of genetic diversity using networks: the human gut microbiome as a case study. Clin. Microbiol. Infect. 18, 40–43 (2012)
Bascompte, J., Jordano, P.: Plant-Animal Mutualistic Networks: The Architecture of Biodi-versity. Annu. Rev. Ecol. Evol. Syst. 38, 567–593 (2007)
Batagelj, V., Mrvar, A.: Pajek – program for large network analysis. Connections 21, 47–57 (1998)
Blüthgen, N., Fründ, J., Vázquez, D.P., Menzel, F.: What do interaction network metrics tell us about specialization and biological traits. Ecology 89, 3387–3399 (2008), http://dx.doi.org/10.1890/07-2121.1
Borgatti, S.P., Everett, M.G., Freeman, L.C.: UCINET 5 for Windows: Software for Social Network Analysis (USER’S GUIDE) (1999), http://www.analytictech.com/ucinet6/Ucinet_Guide.doc (accessed in November 15, 2012)
Borgatti, S.P., Everett, M.G., Freeman, L.C.: Ucinet for Windows: Software for Social Network Analysis. Analytic Technologies, Harvard (2002)
Butts, C.T.: Social Network Analysis with sna. Journal of Statistical Software 24, 1–51 (2008)
Carlos, C., Pires, M.M., Stoppe, N.C., Hachich, E.M., Sato, M.I.Z., Gomes, T.A.T., Amaral, L.A., Ottoboni, L.M.M.: Escherichia coli phylogenetic group determination and its application in the identification of the major animal source of fecal contamination. BMC Microbiol. 10, 161 (2010)
Chen, M., Cho, J., Zhao, H.: Incorporating biological pathways via a Markov random field model in genome-wide association studies. PLoS Genet. 7, e1001353 (2011)
Clermont, O., Bonacorsi, S., Bingen, E.: Rapid and simple determination of the Escherichia coli phylogenetic group. Appl. Environ. Microbiol. 66, 4555–4558 (2000)
Escobar-Páramo, P., Grenet, K., LeMenac’h, A., Rode, L., Salgado, E., Amorin, C., Gouriou, S., Picard, B., Rahimy, C., Andremont, A., Denamur, E., Ruimy, R.: Large-scale population structure of human commensal Escherichia coli isolates. Appl. Environ. Micro-Biol. 70, 5698–5700 (2004)
Freeman, L.C.: Centrality in social networks: conceptual clarification. Social Networks 1(3), 215–239 (1979)
Hagedorn, C., Blanch, A.R., Harwood, V.J.: Microbial source tracking: methods, application, and case studies, 642 p. Springer, New York (2011)
Hanneman, R.A., Riddle, M.: Introduction to social network methods. University of California, Riverside, Riverside, CA (2005), published in digital form at http://faculty.ucr.edu/~hanneman/
Hansen, D.L., Shneiderman, B., Smith, M.A.: Analysing social media networks with NodeXL: insights from a connected world, 284 p. Morgan Kaufmann, Amsterdan (2011)
Jordano, P.: Patterns of mutualistic interactions in pollination and seed dispersal: connec-tance, dependence asymmetries, and coevolution. American Naturalist 129, 657–677 (1987)
Jordano, P., Vázquez, D., Bascompte, J.: Redes complejas de interacciones mutualistas planta-animal. In: Mendel, R., Aizen, M.A., Zamora, R. (eds.) Ecología y Evolución de Interacciones Planta-Animal, 1a ed., pp. 17–41. Universitaria, Santiago de Chile (2009)
Jostins, L., Ripke, S., Weersma, R.K., Duerr, R.H., McGovern, D.P., Hui, K.Y., Lee, J.C., Schumm, L.P., Sharma, Y., et al.: Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012)
Kumar, K., Novak, J., Tomkins, A.: Structure and evolution of online social networks. In: Proc. of ACM SIGKDD Intl. Conf. of Knowledge Discovery and Data Mining, New York, pp. 611–617 (2006)
Lee, J.E., Lee, S., Sung, J., Ko, G.P.: Analysis of human and animal fecal microbiota for microbial source tracking. The ISME J. 5, 362–365 (2011)
Ley, R.E., Hamady, M., Lozupone, C., Turnbaough, P.J., Ramey, R.R., Bircher, S., Schlegel, M., Tucker, T.A., Schrenzel, M.D., Knight, R., Gordon, J.I.: Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008)
Mello, M.A.R.: Guia para Análise de Redes Ecológicas. Version March 3 (2013), http://marcomello.casadosmorcegos.org/Redes.html (accessed in April 1, 2013)
Nooy, W., Mrvar, A., Batagelj, V.: Exploratory Network Analysis with Pajek, 334 p. Cambridge University Press (2005)
Roesch, L.F.W., Fulthorpe, R.R., Pereira, A.B., Pereira, C.K., Lemos, J.N., Barbosa, A.D., Suleiman, A.K.A., Gerber, A.L., Pereira, M.G., Loss, A., Costa, E.M.: Soil bacteria community abundance and diversity in ice-free areas of Keller Peninsula, Antarctica. Appl. Soil Ecol. 61, 7–15 (2012)
Scott, J.: Social Network Analysis: A handbook, 2nd edn. Sage, London (2000)
Stoppe, N.C., Silva, J.S., Torres, T.T., Carlos, C., Hachich, E.M., Sato, M.I.Z., Saraiva, A.M., Ottoboni, L.M.M.: Clustering of water bodies in unpolluted and polluted environments based on Escherichia coli phylogroup abundance using a simple interaction database. BMC Microbiology (unpublished)
Vázquez, D.P., Morris, W.F., Jordano, P.: Interaction frequency as a surrogate for the total effect of animal mutualists on plants. Ecology Letters 8, 1088–1094 (2005)
Vázquez, D.P., Blüthgen, N., Cagnolo, L., Chacoff, N.P.: Uniting pattern and process in plant–animal mutualistic networks: a review. Annals of Botany 103, 1445–1457 (2009)
Wootton, J.T., Emmerson, M.: Measurement of interaction strength in nature. Annual Review of Ecology, Evolution and Systematics 36, 419–444 (2005)
Yamada, T., Bork, P.: Evolution of biomolecular networks – lessons from metabolic and protein interactions. Nature Rev. Mol. Cell Biol. 10, 791–803 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Silva, J.S., de Castro Stoppe, N., Torres, T.T., Ottoboni, L.M.M., Saraiva, A.M. (2014). Social Network Analysis Metrics and Their Application in Microbiological Network Studies. In: Contucci, P., Menezes, R., Omicini, A., Poncela-Casasnovas, J. (eds) Complex Networks V. Studies in Computational Intelligence, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-05401-8_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-05401-8_24
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05400-1
Online ISBN: 978-3-319-05401-8
eBook Packages: EngineeringEngineering (R0)