Example 1: Supporting Metabolic Network Prediction
De novo pathway prediction: MetaCyc is an important aid for the computational prediction of metabolic
pathways. Using data stored in MetaCyc, pathway prediction software such as Pathologic
(a component of Pathway
Tools) can be applied to an organism's complete, annotated [def]
genomic sequence to infer its metabolic
pathway complement.
MetaCyc is an important component of the prediction process, because many computational
pathway prediction algorithms rely on pre-existing protein sequences associated with their corresponding enzyme activities
in order to identify the genes coding for these enzymes.
No need for pre-existing biochemistry: Computational pathway prediction is particularly helpful when
little or no biochemistry is available for an organism
of interest. The Pathway Tools software does not require biochemical knowledge about the organism of interest to
generate pathway complements. For this reason, computational prediction is particularly useful
in cases where an organism is resistant
to genetic manipulation, impeding its biochemical analysis, as demonstrated in
the application
of MetaCyc to understand sulfur assimilation
in the extremophile Acidithiobacillus ferrooxidans based on a bioinformatics approach
(Valdés et al, 2003).
Other examples include metabolic studies of the malaria pathogen
Plasmodium falciparum 3D7 (Yeh
et al, 2004), the prominent adult human gut symbiont Bacteroides
thetaiotaomicron (Bjursell
et al, 2006), the long-chain alkane degrading Geobacillus
thermodenitrificans NG80-2, which was isolated from a deep-subsurface
oil reservoir (Feng et
al, 2007), the cellulolytic gliding bacterium Cytophaga hutchinsonii
(Xie et al, 2007),
the succinic acid producer Mannheimia succiniciproducens (Kim
et al, 2007), the sap-feeding insect symbionts Sulcia muelleri
and Baumannia cicadellinicola (McCutcheon
and Moran, 2007), the pathogen Streptococcus pneumoniae (Aanensen
et al, 2007), the butanol producer Clostridium acetobutylicum (Lee
et al, 2008), the nitrogen fixer Azorhizobium caulinodans ORS571
(Lee et al, 2008),
and many other organisms.
A note of caution: Because these pathway complements are computationally predicted,
they should be treated as first drafts until they have been reviewed manually. The Pathway Tools suite
provides an extensive suite of editing tools to quickly fix errors and add custom annotations, including manually generated annotations,
to the repository.
[top]
Creating custom annotation of genomes: The downloadable version of Pathway Tools supports the editing of PGDBs
[def] by users who
want to generate and curate their own genome and pathway annotations. This approach provides a mechanism for capturing
a laboratory's particular understanding of a research area. For example, a laboratory may want to alter an existing PGDB, such as provided by
BioCyc,
to annotate particulars region of a genome according to data generated within the laboratory. In this way, Pathway Tools can be used to create a
repository of what a group "knows" about a particular area. Examples for PGDBs
that were created and curated by groups other that SRI is available at
this web page.
[top]
|
Example 2: Supporting Metabolic Engineering and Drug Target Development
Metabolic engineering is the targeted and purposeful alteration of an organism's metabolic pathways
for research or industrial purposes. Metabolic pathways for e.g., the biosynthesis or
degradation of substrates
of commercial significance can be introduced or modified through genetic engineering to achieve alterations in
pathway properties such as regulation and types of metabolites produced. Therefore,
metabolic engineering is heavily dependent on the
knowledge of all pathway variants and the availability of well-characterized enzymes and their genes as source materials for this
process. MetaCyc provides a rich repository of both pathway variations and highly curated enzymes,
and is routinely used in metabolic engineering projects as a reference (for
example, see
Drager et al 2007, Comparing various evolutionary algorithms on the
parameter optimization of the valine and leucine biosynthesis in
Corynebacterium glutamicum).
In addition, researchers are increasingly using pathway information for
both drug target development and pharmacogenomics, and the BioCyc PGDBs
provide a key tool for this task (see
Thorn et al 2007, Pathway-based Approaches to Pharmacogenomics).
[top]
|
Example 3: Supporting Global Analysis of Omics datasets
PGDBs, combined with the Omics Viewer feature of the Pathway Tools software,
provide an intuitive and efficient platform for evaluation of gene expression
results. An example for such a project is described in
Schramm et al 2007,
Using gene expression data and network topology to detect substantial pathways,
clusters and switches during oxygen deprivation of Escherichia coli. |
