Contact: Dr. Jim Giovannoni
[email protected]
607-255-1414
American Society of Plant Biologists
Using systems biology to model the metabolic networks in tomato fruit development
When tomatoes ripen in our gardens, we watch them turn gradually
from hard, green globules to brightly colored, aromatic, and tasty
fruits. This familiar and seemingly commonplace transformation masks a
seething mass of components interacting in a well-regulated albeit
highly complex manner. For generations, agriculturalists and scientists
have bred tomatoes for size, shape, texture, flavor, shelf-life, and
nutrient composition, more or less, one trait at a time. With the
advent of molecular biology, mutagenesis and genetic transformation
could produce tomatoes that were more easily harvested or transported
or turned into tomato paste. Frequently, however, optimizing for one
trait led to deterioration in another. For example, improving flavor
could have a negative effect on yield.
The revolution in
genomics, with a wealth of data emerging from sequencing and
simultaneous expression analysis of thousands of genes, has made it
possible to study the numerous pathways and regulatory
networks—systems--that operate to produce a desirable fruit. This
systems approach in the new fields of metabolic and functional genomics
is producing the tools, information, and biological materials needed
for screening and breeding efforts in tomato and other members of the
Solanaceae.
Dr. Fernando Carrari and his colleagues, Laura Kamenetzky,
Ramon Asis, Luisa Bermudez, Ariel Bazzini, Sebastian Asurmendi,
Marie-Anne Van Sluys, Jim Giovannoni, Alisdair Fernie, and Magdalena
Rossi use a systems approach that integrates genomic, genetic, and
biochemical tools to model the metabolic networks that interact in the
process of tomato fruit development. Dr. Carrari, of the Instituto de
Biotecnologia, (INTA), Argentina, will be presenting this work at a
symposium on the Biology of Solanaceous Species at the annual meeting
of the American Society of Plant Biologists in Mérida, Mexico (June 29,
9:10 AM).
Tomato (
Solanum lycopersicum) is a member of the
Solanaceae or nightshade family, which also includes potato, eggplant,
tobacco, and chili peppers. The center of origin and diversity of
tomato species is in the northern Andes, where endemic populations of
wild tomato species still grow. These wild populations represent
considerable genetic diversity, whereas cultivated tomatoes are
genetically very narrow. The Tomato Genome Consortium is an
international collaboration that is sequencing, mapping and analyzing
the genomes of both wild and cultivated varieties. Carrari and his
co-workers, as well as other scientists, have begun to make use of this
wealth of sequence data in functional and metabolic analyses of tomato
and other crops.
Plants produce an immense variety of chemical compounds for
growth, metabolism, signaling, defense, and reproduction. These
metabolites function in complex networks and pathways in which they
regulate and are regulated by parallel networks of genes. It is not
possible to realistically model these metabolic systems one compound or
gene at a time. Moreover, many, if not most traits in tomato, are not
the result of one gene, but of many genes located together in
chromosomal regions called quantitative trait loci (QTLs), because they
produce a range of values in fruit or plant size or color, rather than
just two extremes. Thus metabolites, enzymes, and genes must be
analyzed simultaneously and in parallel in order to capture their
dynamic relationships. To accomplish this, Carrari and his colleagues
made use of the high genetic diversity of an ancestral tomato species,
Solanum pennellii.
Through crosses, chromosomal segments of
S. pennellii
were introgressed into the genome of the cultivar Solanum lycopersicum
var. Roma. Different lines of the cultivar were then created that
differed only in the chromosomal segment received from the wild
species. In this way, over 1200 metabolic QTLs or quantitative
metabolic loci (QMLs) were identified and analyzed. Almost 900 of these
QMLs were found to be associated with fruit metabolism.
The scientists then sampled a number of metabolites such as
carbohydrates, pigments, and hormones, among others, throughout flower
and fruit development. They also used microarrays to determine which
genes were expressed at those same times. Pairwise comparisons and
network analyses were then made to determine which of those genes and
metabolites are associated in possible functional networks. These
associations do not establish causality or regulatory direction,
because they are only correlational. Expression of certain genes may
regulate metabolite activity, but metabolites may also have a
regulatory effect on gene expression. To begin to define causal
direction, Carrari and his colleagues perturbed these systems by
treatment with external metabolites and followed the transmission of
information from metabolite to gene. In continuing research, Carrari
and co-workers are using these methods, as well as RNA interference and
transgenesis to map QMLs and to identify and utilize candidate genes
that function at network nodes.
These systems approaches make it possible to model the whole
organism throughout its development. Moreover, an understanding of
metabolic networks will make it possible to alter metabolic pathways to
produce fruits with different secondary compounds that influence
texture, taste, aroma, and nutrition, as well as to improve yield.
Metabolite analysis also has possible applications in drug discovery,
nutrient enhancement and biofuel production. One important goal is the
use of ancestral genetic resources in place of simplistic genetic
modification to avoid possible deleterious environmental effects as
well as resistance by consumers to genetically modified food.
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