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The challenges of modeling mammalian biocomplexity

Abstract

Understanding the relationships between human genetic factors, the risks of developing major diseases and the molecular basis of drug efficacy and toxicity is a fundamental problem in modern biology. Predicting biological outcomes on the basis of genomic data is a major challenge because of the interactions of specific genetic profiles with numerous environmental factors that may conditionally influence disease risks in a nonlinear fashion. 'Global' systems biology attempts to integrate multivariate biological information to better understand the interaction of genes with the environment. The measurement and modeling of such diverse information sets is difficult at the analytical and bioinformatic modeling levels. Highly complex animals such as humans can be considered 'superorganisms' with an internal ecosystem of diverse symbiotic microbiota and parasites that have interactive metabolic processes. We now need novel approaches to measure and model metabolic compartments in interacting cell types and genomes that are connected by cometabolic processes in symbiotic mammalian systems.

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Figure 1: Time courses for two hypothetical gene–protein couples (relating transcription activity to protein level) that are up-regulated following a system stimulus, such as a drug intervention at time zero.
Figure 2: The 'genetic relaxation time' hypothesis.
Figure 3: Time-related concentrations of two metabolites, a and b, that are perturbed by dosing an animal with a drug (in this case, these are from real data sets generated from liquid chromatography-mass spectrometric analysis of sequential urine samples taken from an animal dosed with a model liver toxin).
Figure 4: The global systems approach.
Figure 5: Depiction of multiple genome interactions between mammalian host, macroparasites and gut microbiome in terms of exchange and cometabolism of substrates.
Figure 6

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Acknowledgements

We thank the Biotechnology and Biological Science Research Council, Engineering and Physical Sciences Research Council, The Wellcome Trust and the National Institutes of Health for funding this and related work. We also thank Paul Elliot and James Scott, Yueurg Utzinger and Burt Singer, Jeremy Everett and Felicity Nicholson for their helpful comments and discussion on this work and related subjects.

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Correspondence to Jeremy K Nicholson.

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Nicholson, J., Holmes, E., Lindon, J. et al. The challenges of modeling mammalian biocomplexity. Nat Biotechnol 22, 1268–1274 (2004). https://doi.org/10.1038/nbt1015

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