Unpredictability of metabolism-the key role of metabolomics science in combination with next-generation genome sequencing

Author(s)

Wolfram Weckwerth

Abstract

Next-generation sequencing provides technologies

which sequence whole prokaryotic and eukaryotic genomes in

days, perform genome-wide association studies, chromatin

immunoprecipitation followed by sequencing and RNA

sequencing for transcriptome studies. An exponentially

growing volume of sequence data can be anticipated, yet

functional interpretation does not keep pace with the amount

of data produced. In principle, these data contain all the secrets

of living systems, the genotype-phenotype relationship.

Firstly, it is possible to derive the structure and connectivity

of the metabolic network from the genotype of an organism in

the form of the stoichiometric matrix N. This is, however,

static information. Strategies for genome-scale measurement,

modelling and predicting of dynamic metabolic networks

need to be applied. Consequently, metabolomics science-

the quantitative measurement of metabolism in conjunction

with metabolic modelling-is a key discipline for the

functional interpretation of whole genomes and especially

for testing the numerical predictions of metabolism based on

genome-scale metabolic network models. In this context, a

systematic equation is derived based on metabolomics

covariance data and the genome-scale stoichiometric matrix

which describes the genotype-phenotype relationship.

Organisation(s)

Journal

Analytical and Bioanalytical Chemistry

Volume

400

Pages

1967-1978

No. of pages

ISSN

1618-2642

Publication date

2011

Peer reviewed

Yes

Austrian Fields of Science 2012

106014 Genomics, 106023 Molecular biology

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