Report on FUSION OF NMR AND LC

Report on
FUSION OF NMR AND LC-MS/MS DATA
__________________________________________________________________________
As part of the research program 29 blood serum and equal number of human
amniotic fluid samples from women that underwent amniocentesis for prenatal
diagnosis were analyzed by two different and complementary analytical
techniques (NMR and LC-MS/MS). The initial scope was the unification and the
combination of all the information extracted from the two analytical techniques
and thus the better understanding of the studied clinical question.
The holistic NMR analysis of all samples was accomplished utilizing a 600 MHz
Varian NMR spectrometer by applying CPMG pulse sequence and using sodium
maleate as internal standard. Sample pretreatment included freeze-drying to
increase signal intensities. On the other hand, the LC-MS/MS analysis was
achieved by the ACQUITY Ultra Performance Liquid Chromatography System
Xevo TQD MS System (Waters). An ACQUITY HILIC, 2.1 × 150 mm, 1.7 µm,
BEH amide column together with a ACQUITY UPLC BEH Amide 1.7 µm
VanGuard pre-column was used under 500 µL/min. Gradient elution employed a
ramp of water vs ACN both buffered with formic acid and ammonia (10mM).
100 MRM channels were set in time windows of ca. 1-3 min for total analysis
time of 40 min.
Identified metabolites of each technique were integrated using the Chenomx
(identification) and the MestReNova 9.1 (integration) software for the 1Η-NMR
data and the Waters MassLynx XS software for the LC-MS/MS data. The NMR
signals were normalized to the signal of sodium maleate per sample. Venn
diagrams were applied to specify the common metabolites identified with both
analytical techniques (Fig.1). 17 metabolites out of the 51 and 37 metabolites
identified in HAF samples with LC-MS/MS and NMR respectively were
common. In serum samples the common metabolites were 17 out of the 55 and
27 metabolites identified with LC-MS/MS and NMR respectively. By using the
common metabolites identified in both techniques we tried to investigate the
correlation between their integrated areas and hence the correlation of the two
techniques. In this way, we could decide if it would be useful to combine the
extracted information of the areas of unique metabolites from each technique, in
order to form a single table containing all the extracted information.
For the correlation analysis, the Pearson correlation coefficient was used. The
resulted heatmap for HAF samples (Fig. 2) revealed low correlation between the
common integrated signals of targeted LC-MS/MS and NMR. The resulted
heatmap for serum samples (Fig. 4) revealed higher correlation between the
common integrated signals. Νevertheless, in both matrices, there are metabolites
such as leucine, isoleucine and glutamine that appear to be highly correlated. On
the contrary, creatinine appears to be one of the most non-correlated metabolites
in both matrices. The same results were reached by applying multivariate
statistical analysis for the common metabolites and by examining the loadings
plot (Fig. 3).
The above observations led us to the conclusion that the combination of the
information extracted from the two different examined techniques is not possible
for the HAF samples, as the correlation of the common metabolites identified by
them is very low. On the other hand, high correlation is observed on the common
metabolites found in the serum samples. On the other hand, high correlation is
observed on the common metabolites found in the serum samples. This
observation leads us to the next step, the fusion of the two datasets reached with
the different analytical techniques.
Chatziioannou A.C., Palachanis D., Liambas C.
2"Hydroxybutyrate/
2"Hydroxyvalerate/
Valine/
3"Hydroxyisobutyrate/
3"Hydroxybutyrate/
5,6"Dihydrothymine/
Acetate/
Acetoacetate/
N"acetylornithine/
Acetone/
Succinate/
Citrate/
2"Oxoglutarate/
Dimethyl/sulfone/
Methanol/
Mannose/
Maleate/
Fumarate/
π"Methylhis5dine/
Formate/
π"Methylhis6dine/
Ethanol/
Acetate/
Acetone/
Ascorbate/
Dimethyl/sulfone/
Formate/
Methanol/
Mannose/
Succinate/
/
2"Hydroxyisovaleric/acid/
Alanine/
Crea5ne/
Crea5nine/
Glucose/
Glutamine/
Glycine/
His5dine/
Isoleucine/
Lac5c/acid/
Leucine/
Lysine/
Methionine/
Phenylalanine/
Pyruvic/acid/
Threonine/
Tyrosine/
Alanine/
Citric/acid/
Crea6ne/
Crea6nine/
Glucose/
Glycine/
Glutamine/
Isoleucine/
Lac6c/acid/
Leucine/
Methionine/
Phenylalanine/
Proline/
Pyruvic/acid/
Threonine/
Tyrosine/
Valine/
2"Hydroxyisobutyric/acid/
Acetylcarni5ne/
Adenosine/
Allose/Mannose/Galactose/
Arginine/
Asparagine/
Betaine/
Caffeine/
Choline/
Citrulline/
Co5nine/
Cys5ne/
Dimethylamine/
Dulcitol/
Fructose/
Glutamic/acid/
Hippuric/acid/
Malic/acid/
Mannitol/
Nico5namide/
Norvaline/Valine/
Ornithine/
Pantothenate/
Proline/
Pyroglutamic/acid/
Ribose/
Serine/
Spermidine/
Taurine/
Theobromine/
Thiamine/
Trimethylamine"n"oxide/
Tryptophan/
Uridine/
2"Hydroxyisobutyric/
2"Hydroxyisovaleric/acid/
Acetylcarni6ne/
Allose/Mannose/Galactose/
Asparagine/
Aspar6c/acid/
Benzoic/acid/
Betaine/
Caffeine/
Choline/
Citrulline/
Co6nine/
Cys6ne/
Fumarate/
Glutamic/acid/
Hippuric/acid/
His6dine/
Hypoxanthine/
Inosine/
Lactose/
Lysine/
Nico6namide/
Ornithine/
Pyroglutamic/
Serine/
Spermidine/
Spermine/
Sucrose/
Taurine/
Theobromine/
Thiamine/
Thymidine/
Trimethylamine"n"oxide/
Tryptamine/
Tryptophan/
Uric/acid/
Uridine/
Xanthine/
Fig. 1. Venn diagrams of the metabolites identified on HAF (above) and blood serum samples (bottom) with both analytical
techniques.
Chatziioannou A.C., Palachanis D., Liambas C.
Fig. 2. Heatmap showing correlations of the areas of common metabolites identified with two analytical techniques, LC-MS/MS and
NMR, in HAF samples. The correlations of interest are located on the diagonal (blue dashed line).
Chatziioannou A.C., Palachanis D., Liambas C.
Fig. 3. Loadings plot of PCA model showing the same metabolites measured with LC-MS/MS and NMR in HAF samples. In this plot
it is obvious that metabolites glutamine, isoleucine and leucine are very close (correlated) with both techniques (black circles), while
others, like creatinine, are widely separated (non-correlated).
Chatziioannou A.C., Palachanis D., Liambas C.
Fig. 4. Heatmap showing correlations of the areas of common metabolites identified with two analytical techniques, LC-MS/MS and
NMR, in blood serum samples. The correlations of interest are located on the diagonal (blue dashed line).
Chatziioannou A.C., Palachanis D., Liambas C.
R2=0.685)
R2=0.002)
R2=0.743)
R2=0.070)
R2=0.236)
R2=0.473)
R2=0.298)
R2=0.385)
R2=0.557)
R2=0.414)
R2=0.056)
R2=0.033)
R2=0.257)
R2=0.297)
R2=0.312)
R2=0.417)
R2=0.700)
Fig. 5. Correlation of the areas of common metabolites identified with two analytical
techniques, LC-MS/MS and NMR, in blood serum samples. Alanine, Creatine,
Glutamine, Lactate, Leucine, Tyrosine and Valine have R2 > 0.4 and 13 out of 17
metabolites have R2 > 0.1.
Chatziioannou A.C., Palachanis D., Liambas C.