spectral assignment and integration. In addition, the existence of
macromolecule in analytical samples could produce broader reso-
nances and cause difficulties in spectral assignment and integration.
Thus the signals of water and macromolecule should be suppressed
and filtered. Currently, NMR metabolomics are primarily con-
ducted with 1D NOESY presat for water suppression and 1D
Carr-Purcell-Meiboom-Gill (CPMG) presat as a T2 filter to remove
macromolecule signals [72].
Recently, 2D NMR spectrum experiments are applied since
signals of 1D^1 H NMR spectrum are seriously overlapped. One of
the most commonly used 2D experiments is^1 H-^1 H J-resolved
spectrum that separates chemical shifts and J coupling. In this
experiment, the peaks from macromolecules are attenuated, and
then multiplicity information and coupling patterns of the remain-
ing resonances are obtained. Correlation spectroscopy (COSY)
shows correlations between scalar coupled hydrogen atoms over
two to several (up to four in favorable cases) chemical bonds. Total
correlation spectroscopy (TOCSY) provides^1 H-^1 H spin-spin cou-
pling connectivity with all hydrogen atoms within a spin system,
forming an unbroken chain of couplings and thereby unraveling the
number and nature of the molecular fragments. Heteronuclear
single quantum coherence spectroscopy (HSQC) shows correla-
tions between hydrogen atoms and carbon atom to which they
are attached. Heteronuclear multiple bond correlation (HMBC)
provides correlations between hydrogen and heteronucleus (gener-
ally two or three bonds away). These 2D sequences are used for
signal assignments and identification of unknown metabolites
commonly.
In addition,^31 P and^13 C NMR technologies are also applied in
metabolomics studies recently. Nuclei^31 P has large gyromagnetic
ratio; therefore^31 P NMR has high sensitive in metabolite detec-
tion, which can be used for investigation of cellular energy states
[73].^13 C NMR signals have better resolution than^1 H NMR
signals for its large chemical shifts range.^13 C NMR technology is
utilized on indirect detecting [74] or isotope labeling [75] scenar-
ios commonly.5 Data Preprocessing and Analysis
Data preprocessing is an important step before data analysis, which
is crucial in metabolomics study. After acquiring data by MS or
NMR platform, the subsequent step is to translate these raw data
into available extracted data (e.g., peak tables) that can be applied in
statistical analysis for metabolite identification easily.278 Jing Cheng et al.