TITLE:
A Systems Approach for Determining Gene Expression from Experimental Observation of Compound Presence and Absence
AUTHORS:
Sangaalofa T. Clark, Wynand S. Verwoerd
KEYWORDS:
Metabolic Networks; Elementary Modes; Minimal Cut Sets; Gene Sets
JOURNAL NAME:
Advances in Bioscience and Biotechnology,
Vol.5 No.5,
April
16,
2014
ABSTRACT: Different genes are
expressed in different tissues, depending on functional objectives and selection
pressures. Based on complete knowledge of the structure of the metabolic
network and all the reactions taking place in the cell, elementary modes (EMs)
and minimal cut sets (MCSs) can relate compounds observed in a tissue, to the
genes being expressed by respectively providing the full set of non-decomposable routes of
reactions and compounds that lead to the synthesis of external products, and the full set of possible target genes for blocking the synthesis of external
products. So, for a particular tissue, only the EMs containing the reactions
that are related to the genes being expressed in those tissues, are active for
the production of the corresponding compounds. This concept is used to develop
an algorithm for determining a
matrix of reactions (which
can be related to corresponding genes) taking place in a tissue, using
experimental observations of compounds in a tissue. The program is applied to the Arabidopsis flower and identified 20 core reactions occurring in all the viable EMs. They originate from the trans-cinnamate
compound and lead to the formation of kaempferol and quercetin compounds and
their derivatives, as well as anthocyanin compounds. Analyses of the patterns in
the matrix identify reaction sets related to certain functions such as the
formation of derivatives of the two anthocyanin compounds present, as well as
the reactions leading from the network’s external substrate erythrose-4P to
L-Phenylalanine, cinnamyl-alc to trans-cinnamate and so on. The program
can be used to successfully determine genes taking place in a tissue, and the patterns in the resulting matrix can be
analysed to determine gene
sets and the state of the tissue.