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Systems biology in animal sciences

Published online by Cambridge University Press:  28 January 2011

H. Woelders ,
M. F. W. Te Pas ,
A. Bannink ,
R. F. Veerkamp  and
M. A. Smits
H. Woelders*
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
M. F. W. Te Pas
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
A. Bannink
Affiliation:
Animal Nutrition, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
R. F. Veerkamp
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
M. A. Smits
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
*
†E-mail: [email protected]
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Abstract

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed ‘omics’ technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A ‘system’ approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with ‘system approaches’ in animal sciences, providing exciting opportunities to predict and modulate animal traits.

Keywords

systems biologymathematical modelinganimal traits
Type
Full Paper
Information
animal , Volume 5 , Issue 7 , 31 May 2011 , pp. 1036 - 1047
Copyright
Copyright © The Animal Consortium 2011

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References

Aksenov, SV, Church, B, Dhiman, A, Georgieva, A, Sarangapani, R, Helmlinger, G, Khalil, IG 2005. An integrated approach for inference and mechanistic modeling for advancing drug development. FEBS Letters 579, 1878–1883.CrossRefGoogle ScholarPubMed
Amit, I, Garber, M, Chevrier, N, Leite, AP, Donner, Y, Eisenhaure, T, Guttman, M, Grenier, JK, Li, W, Zuk, O, Schubert, LA, Birditt, B, Shay, T, Goren, A, Zhang, X, Smith, Z, Deering, R, McDonald, RC, Cabili, M, Bernstein, BE, Rinn, JL, Meissner, A, Root, DE, Hacohen, N, Regev, A 2009. Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326, 257–263.CrossRefGoogle ScholarPubMed
Arakelyan, L, Vainstein, V, Agur, Z 2002. A computer algorithm describing the process of vessel formation and maturation, and its use for predicting the effects of anti-angiogenic and anti-maturation therapy on vascular tumor growth. Angiogenesis 5, 203–214.CrossRefGoogle Scholar
Asslaber, M, Zatloukal, K 2007. Biobanks: transnational, European and global networks. Briefings in Functional Genomics & Proteomics 6, 193–201.CrossRefGoogle ScholarPubMed
Bannink, A, Kogut, J, Dijkstra, J, France, J, Kebreab, E, Van Vuuren, AM, Tamminga, S 2006. Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows. Journal of Theoretical Biology 238, 36–51.CrossRefGoogle ScholarPubMed
Bionaz, M, Loor, JJ 2008. Gene networks driving bovine milk fat synthesis during the lactation cycle. BMC Genomics 9, 366.CrossRefGoogle ScholarPubMed
Boer, HMT, Stötzel, C, Röblitz, S, Deuflhard, P, Veerkamp, RF, Woelders, H 2010. Mathematical model of the bovine oestrous cycle. In Food, feed, energy and fibre from land, a vision for 2020. Annual Conference of the British Society of Animal Science, Agricultural Research Forum and the World Poultry Science Association, Belfast, UK, p. 163.CrossRefGoogle Scholar
Bruggeman, FJ, Westerhoff, HV 2007. The nature of systems biology. Trends in Microbiology 15, 45–50.CrossRefGoogle ScholarPubMed
Calus, MP, Meuwissen, TH, de Roos, AP, Veerkamp, RF 2008. Accuracy of genomic selection using different methods to define haplotypes. Genetics 178, 553–561.CrossRefGoogle ScholarPubMed
Feist, AM, Zielinski, DC, Orth, JD, Schellenberger, J, Herrgard, MJ, Palsson, BØ 2010. Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli. Metabolic Engineering 12, 173–186.CrossRefGoogle ScholarPubMed
Fell, DA, Small, JR 1986. Fat synthesis in adipose tissue. An examination of stoichiometric constraints. Biochemical Journal 238, 781–786.CrossRefGoogle ScholarPubMed
Finney, A, Hucka, M, Bornstein, BJ, Keating, SM, Shapiro, BE, Matthews, J, Kovitz, BL, Schilstra, MJ, Funahashi, A, Doyle, JC, Kitano, H 2006. Software infrastructure for effective communication and reuse of computational models. In System modeling in cellular biology: from concepts to nuts and bolts (ed. Z Szallasi, J Stelling and P Periwal), pp. 355–378. MIT Press, Cambridge, MA, USA.CrossRefGoogle Scholar
Fox, S, Filichkin, S, Mockler, TC 2009. Applications of ultra-high-throughput sequencing. Methods in Molecular Biology 553, 79–108.CrossRefGoogle ScholarPubMed
Gibson, JP, Bishop, SC 2005. Use of molecular markers to enhance resistance of livestock to disease: a global approach. Revue scientifique et technique (International Office of Epizootics) 24, 343–353.Google ScholarPubMed
Haanstra, JR, van Tuijl, A, Kessler, P, Reijnders, W, Michels, PA, Westerhoff, HV, Parsons, M, Bakker, BM 2008. Compartmentation prevents a lethal turbo-explosion of glycolysis in trypanosomes. Proceedings of the National Academy of Sciences of the United States of America 105, 17718–17723.CrossRefGoogle ScholarPubMed
Hunter, P, Nielsen, P 2005. A strategy for integrative computational physiology. Physiology (Bethesda) 20, 316–325.Google ScholarPubMed
Ideker, T, Thorsson, V, Ranish, JA, Christmas, R, Buhler, J, Eng, JK, Bumgarner, R, Goodlett, DR, Aebersold, R, Hood, L 2001. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929–934.CrossRefGoogle ScholarPubMed
Joyce, AR, Palsson, BO 2006. The model organism as a system: integrating ‘omics’ data sets. Nature Reviews Molecular Cell Biology 7, 198–210.CrossRefGoogle ScholarPubMed
Khalil, IG, Hill, C 2005. Systems biology for cancer. Current Opinion in Oncology 17, 44–48.CrossRefGoogle ScholarPubMed
Kholodenko, BN 2006. Cell-signalling dynamics in time and space. Nature Reviews Molecular Cell Biology 7, 165–176.CrossRefGoogle ScholarPubMed
Kitano, H 2000. Perspectives on systems biology. New Generation Computing 18, 199–216.CrossRefGoogle Scholar
Kittler, R, Pelletier, L, Buchholz, F 2008. Systems biology of mammalian cell division. Cell Cycle 7, 2123–2128.CrossRefGoogle ScholarPubMed
Klauschen, F, Angermann, BR, Meier-Schellersheim, M 2007. Understanding diseases by mouse click: the promise and potential of computational approaches in Systems Biology. Clinical and Experimental Immunology 149, 424–429.CrossRefGoogle ScholarPubMed
Kommadath, A, Mulder, HA, de Wit, AAC, Woelders, H, Smits, MA, Beerda, B, Veerkamp, RF, Frijters, ACJ, te Pas, MFW 2010. Gene expression patterns in anterior pituitary associated with quantitative measure of oestrous behaviour in dairy cows. Animal 4, 1297–1307.CrossRefGoogle ScholarPubMed
Lehner, B 2007. Modelling genotype-phenotype relationships and human disease with genetic interaction networks. Journal of Experimental Biology 210, 1559–1566.CrossRefGoogle ScholarPubMed
Lippolis, JD, Reinhardt, TA 2008. Centennial paper: proteomics in animal science. Journal of Animal Science 86, 2430–2441.CrossRefGoogle ScholarPubMed
Megason, SG, Fraser, SE 2007. Imaging in systems biology. Cell 130, 784–795.CrossRefGoogle ScholarPubMed
Meuwissen, TH, Hayes, BJ, Goddard, ME 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829.CrossRefGoogle ScholarPubMed
Noble, D 2008. Computational models of the heart and their use in assessing the actions of drugs. Journal of Pharmacological Sciences 107, 107–117.CrossRefGoogle ScholarPubMed
Pallen, MJ, Wren, BW 2007. Bacterial pathogenomics. Nature 449, 835–842.CrossRefGoogle ScholarPubMed
Palsson, B 2002. In silico biology through “omics”. Nature Biotechnology 20, 649–650.CrossRefGoogle ScholarPubMed
Pryce, JE, Royal, MD, Garnsworthy, PC, Mao, IL 2004. Fertility in the high-producing dairy cow. Livestock Production Science 86, 125–135.CrossRefGoogle Scholar
Quackenbush, J 2007. Extracting biology from high-dimensional biological data. Journal of Experimental Biology 210, 1507–1517.CrossRefGoogle ScholarPubMed
Raghunathan, A, Reed, J, Shin, S, Palsson, B, Daefler, S 2009. Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction. BMC Systems Biology 3, 38.CrossRefGoogle ScholarPubMed
Reinecke, I, Deuflhard, P 2007. A complex mathematical model of the human menstrual cycle. Journal of Theoretical Biology 247, 303–330.CrossRefGoogle ScholarPubMed
Schadt, EE, Lamb, J, Yang, X, Zhu, J, Edwards, S, Guhathakurta, D, Sieberts, SK, Monks, S, Reitman, M, Zhang, C, Lum, PY, Leonardson, A, Thieringer, R, Metzger, JM, Yang, L, Castle, J, Zhu, H, Kash, SF, Drake, TA, Sachs, A, Lusis, AJ 2005. An integrative genomics approach to infer causal associations between gene expression and disease. Nature Genetics 37, 710–717.CrossRefGoogle ScholarPubMed
Schokker, D, Smits, MA, Hoekman, AJ, Parmentier, HK, Rebel, JM 2010. Effects of Salmonella on spatial-temporal processes of jejunal development in chickens. Developmental & Comparative Immunology 34, 1090–1100.CrossRefGoogle ScholarPubMed
Schuetz, R, Kuepfer, L, Sauer, U 2007. Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. Molecular Systems Biology 3, 119.CrossRefGoogle ScholarPubMed
Shav-Tal, Y, Singer, RH, Darzacq, X 2004. Imaging gene expression in single living cells. Nature Reviews Molecular Cell Biology 5, 855–861.CrossRefGoogle ScholarPubMed
Shorten, PR, Pleasants, TB, Upreti, GC 2004. A mathematical model for mammary fatty acid synthesis and triglyceride assembly: the role of stearoyl CoA desaturase (SCD). Journal of Dairy Research 71, 385–397.CrossRefGoogle ScholarPubMed
Simao, E, Remy, E, Thieffry, D, Chaouiya, C 2005. Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in E. coli. Bioinformatics 21 (Suppl. 2), ii190–ii196.CrossRefGoogle Scholar
Snoep, JL 2005. The silicon cell initiative: working towards a detailed kinetic description at the cellular level. Current Opinion in Biotechnology 16, 336–343.CrossRefGoogle ScholarPubMed
Sordillo, LM, Contreras, GA, Aitken, SL 2009. Metabolic factors affecting the inflammatory response of periparturient dairy cows. Animal Health Research Reviews/Conference of Research Workers in Animal Diseases 10, 53–63.CrossRefGoogle ScholarPubMed
Te Pas, MFW, van Hemert, S, Hulsegge, B, Hoekman, AJW, Pool, MH, Rebel, JMJ, Smits, MA 2008. A pathway analysis tool for analyzing microarray data of species with low physiological information. Advances in Bioinformatics 2008 Article ID 719468, 1–7.CrossRefGoogle ScholarPubMed
van Eunen, K, Bouwman, J, Daran-Lapujade, P, Postmus, J, Canelas, AB, Mensonides, FI, Orij, R, Tuzun, I, van den Brink, J, Smits, GJ, van Gulik, WM, Brul, S, Heijnen, JJ, de Winde, JH, Teixeira de Mattos, MJ, Kettner, C, Nielsen, J, Westerhoff, HV, Bakker, BM 2010. Measuring enzyme activities under standardized in vivo-like conditions for systems biology. The FEBS Journal 277, 749–760.CrossRefGoogle ScholarPubMed
van Hemert, S, Hoekman, AJ, Smits, MA, Rebel, JM 2006. Gene expression responses to a Salmonella infection in the chicken intestine differ between lines. Veterinary Immunology and Immunopathology 114, 247–258.CrossRefGoogle ScholarPubMed
Veerkamp, RF, Beerda, B, van der Lende, T 2003. Effects of genetic selection for milk yield on energy balance, levels of hormones, and metabolites in lactating cattle, and possible links to reduced fertility. Livestock Production Science 83, 257–275.CrossRefGoogle Scholar
Wiltbank, M, Lopez, H, Sartori, R, Sangsritavong, S, Gumen, A 2006. Changes in reproductive physiology of lactating dairy cows due to elevated steroid metabolism. Theriogenology 65, 17–29.CrossRefGoogle ScholarPubMed
Wunder, F, Kalthof, B, Muller, T, Huser, J 2008. Functional cell-based assays in microliter volumes for ultra-high throughput screening. Combinatorial Chemistry & High Throughput Screening 11, 495–504.CrossRefGoogle ScholarPubMed
Yashiro, Y, Bannai, H, Minowa, T, Yabiku, T, Miyano, S, Osawa, M, Iwama, A, Nakauchi, H 2009. Transcriptional profiling of hematopoietic stem cells by high-throughput sequencing. International Journal of Hematology 89, 24–33.CrossRefGoogle ScholarPubMed
Young, D, Stark, J, Kirschner, D 2008. Systems biology of persistent infection: tuberculosis as a case study. Nature reviews. Microbiology 6, 520–528.Google Scholar