Metabolomics aims to quantify all metabolites in a cellular system. The challenges are chemical complexity and heterogeneity of metabolites, dynamic range of measurements, and throughput. Metabolites can be analyzed using spectroscopy and mass spectrometry coupled with gas or liquid chromatography. NMR provides information on metabolites directly from biofluids with little sample preparation. GC-MS and LC-MS are commonly used, with LC-MS measuring a broader range of primary and secondary metabolites. Data integration and identification of specific metabolites remain challenges.

1. Senthil Natesan

2.  The ultimate starting point of a metabolomic
experiment is to quantify all of the
metabolites in a cellular system (i.e. the cell
or tissue in a given state at a given point in
time).
 The main challenges are the chemical
complexity and heterogeneity of
metabolites, the dynamic range of the
measuring technique, the throughput of the
measurements, and the extraction protocols.

4.  Metabolites are chemical entities and can be
analysed by the standard tools of chemical
analysis such as molecular spectroscopy and MS.
 The resolution, sensitivity and selectivity of these
technologies can be enhanced or modified by
coupling them to gas chromatograpy (GC) or
liquid chromatography (LC) steps
 NMR spectroscopy has been shown to provide
valuable information on metabolites, typically
directly from biofluids with little or no sample
preparation steps

5.  Gas-chromatography-mass-spectrometry (GC-MS), gas-
chromatography- time-of-flight-mass-spectrometry (GC-TOF-MS).GC-
MS technologies enable the identification and robust quantification of a
few hundred primary metabolites within a single extract.
 However, only volatile compounds (boiling point below 3008C) like
ketones and alcohols can be examined directly by GC–MS. Analysis of
Semi-volatile compounds such as amino acids and lipids require
additional chemical derivatization processes (typically silylation or
alkylation)
 Liquid-chromatography-mass-spectrometry (LC-MS) are currently the
standard mass-spectrometry methods for metabolite analyses. LC-MS
offers several distinct advantages, chiefly its adaptability to measure a
far broader range of metabolites encompassing both primary and
secondary metabolites.
 With the „„soft‟‟ ionization method of ESI, seamless interfacing of LC–MS
can be achieved. Thus, even non-volatile metabolites can be directly
subjected to mass analysis in this method

6.  Compared to the genome, transcriptome and
proteome, the metabolome is of much more
complexity, since a large diversity of molecules are
produced through metabolism and many of which
may participate in several different metabolic or
regulatory Pathways
 Two strategies for metabolomic studies, that
is, target analysis involves identification and
quantification of specific analytes while metabolite
profiling focuses on the characterization of a large
number of molecules either intracellularly (metabolic
fingerprinting) or extracellularly (metabolic
footprinting) (Allen et al., 2003, 2004) serving as an
unambiguous marker correlated to certain cellular
status

7. Common and envisaged technologies in metabolite
profiling

9. Wang et al 2006 Integrating metabolomics into systems biology
framework
to exploit metabolic complexity: strategies and applications in
microorganisms.
Appl Microbiol Biotechnol 70: 151–161

10. Wang et al 2006 Integrating metabolomics into systems biology
framework
to exploit metabolic complexity: strategies and applications in

12.  Pathway viewers KEGG (http://www.genome.ad.jp/kegg/ ),
 Atomic Reconstruction of Metabolism database (http://
www.metabolome.jp/),
 BioCyc (http://biocyc.org) (Paleyand Karp 2006),
 MetaCyc (http://metacyc.org/) (Caspiet al. 2006),
 AraCyc (http://www.Arabidopsis.org/tools/ aracyc/) (Zhang
et al. 2005), MapMan (http://gabi.rzpd.
de/projects/MapMan/)
 (Thimm et al. 2004), KaPPA-View
(http://kpv.kazusa.or.jp/kappa-view/) (Tokimatsu et al.2005)
and
 BioPathAT (http://www.ibc.wsu.edu/research/
lange/public%5Ffolder/) (Lange and Ghassemian 2005),
 the data model for plant metabolomics experiments ArMet
(http://www.armet.org/)

13.  A clear difference between the metabolome
patterns (NMR-based study) of chamomile tea
drinkers before and after dosing was
demonstrated, and the results suggested that the
effects of tea drinking lasted for at least two
weeks post-dosing.
 population and toxicogenomic studies should
benefit from the combination of “omics”, by
allowing connections to be drawn between
environmental factors in terms of diet and
exposure to toxicity and environmental induced
diseases

14.  One significant challenge for plant metabolomics is
the lack of a fully described and annotated
metabolome for any plant species. Estimates are that
the plant kingdom produce 90 000–200 000 different
metabolites
 Owing to technical limitations, researchers
traditionally focused on a single or, at most, a
handful of metabolic traits that were of greatest
importance either for industrial or nutritional value.
 Prime examples of these targeted approaches
include carotenoid content of tomato, protein content
of maize and starch content of potato and rice

15.  Metabolomics in systems biology mainly focus on quantifying
metabolite levels and flows in primary metabolism.
 By relying on predefined connections between genetic
sequences and metabolites, the information observed by
acquiring a snapshot of the cellular metabolic composition is
upgraded
 The use of LC-MS, for example, has been exploited to map
metabolic activity and flexibility through dynamic analysis of
intracellular metabolites during the yeast cell-cycle (Wittmann et
al. 2005) and the effect of culture age on metabolite pools
 To quantify metabolites containing an amino or carboxylic acid
group, Villas-Bôas et al. (2005) applied a sensitive GC-MS
method coupled to a statistical data-mining strategy for the
integrated analysis of clearly identified and quantified intra- and
extracellular metabolites in S. cerevisiae

16.  In yeast, the intracellular metabolites were
used to identify the phenotypes of several
silent mutants (Raamsdonk et al. 2001).
 Comparative comprehensive metabolite
studies were also used in authentication of
other strains (de Nijs et al. 1997).

17.  This level of qualification and quantification is of
increasing importance, as the significance of more
biosynthetic pathways is elucidated. GC-MS applications
have benefited from large databases such as the NIST
database.
 For LC-MS these databases are still in their infancy plant
metabolomic experiments this will be more
problematic, since the metabolite number and the
structural diversity of the metabolites that plants produce
is much greater
 Identification of specific metabolites in complex mixtures
by NMR is also problematic. However, it has been
demonstrated that many common metabolites can be
identified by the application of 2D NMR experiments
 Data analysis and integration remains problematic.
Simone Rochfort,2005 Metabolomics Reviewed: A New “Omics” Platform Technolo
Biology and Implications for Natural Products Research J. Nat. Prod. 68, 1813-182