NMR and DGGE on faecal waters from UC and IBS patients

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NMR and DGGE on faecal waters
from UC and IBS patients
Samah Noor, Karyn Ridgway, Arjan Narbad, Ian. J. Colquhoun , Kate Kemsley, and Gwénaëlle Le Gall
[email protected]
Institute of Food Research, Norwich Research Park, Colney, Norwich, NR4 7UA, UK
Results
Introduction
•The causes of ulcerative colitis (UC) and
irritable bowel syndrome (IBS) are not fully
understood, however, gut microbiota has
been suggested as an important factor in the
pathogenesis of these conditions.
Consequently, the metabolic activity of gut
bacteria might also be altered
1. High correlation between
DGGE and NMR profiles
Canonical Correlation Analysis (CVA) between
NMR and DGGE data sets
C14-3
1
2
3
1
0
1H-13C
HSQC NMR spectrum of faecal extracts acquired at
600 MHz. One UC spectrum (green) and one control
spectrum (red) are displayed
1, Butyrate; 2, Propionate; 3, Valine; 4, Leucine;
5, Isoleucine; 6, Threonine; 7, Isobutyrate; 8, Iso
valerate; 9, Valetate; 10, Caproate; 11, Heptanoate?;
12, Alanine; 13, Lysine; 14, Arginine; 15, Acetate; 16,
Glutamate; 17, Aspartate; 18, Glycine; 19, 3-phenylpropionate; 20, Phloretate; 21, Tyrosine; 22,
Phenylalanine; 23, Trytophan; 24, Uridine; 25,
Succinate; 26, Trimethylamine; 27, Glycerol; 28,
Serine; 29, Taurine; 30, Cadaverine; 31, Putrescien;
32, Lactate; 33, Ethanol;34, Glucose; 35, 5aminopentanoate; 36, Methionine;37, Glutamine; 38,
2-methylbutyrate; 39, Proline;40, Ethanolamine; 41,
Choline; 42, 5-N-acetyl
neuraminate; + cystine, fucose, galactose…
-2
-2
R=0.85
UC11-1
10
UC11-2
P<0.002
controls
UC
IBS
C8-3
UC4-3
C8-2
5
IBS16-1
IBS4-3
C8-1
UC4-1
C12-1
IBS5-1
IBS4-1
IBS5-2IBS5-3
UC4-2
UC15-2
UC8-2
UC15-1
UC13-2
IBS3-3
UC13-1
UC3-3 C14-2
IBS16-2
IBS6-1
UC3-1
UC5-1
C14-1
C18-1
C24-1 IBS3-2
C10-1
C18-2 UC8-3
C15-3
UC3-2
UC5-2
IBS4-3
C24-2 C10-2
IBS3-1
UC7-2F
IBS14-2
C26-1
C24-3 IBS7-2
C3-3
C13-3
C9-2
C27-3
C22-2
C27-2
C9-3UC11-3
C3-2
C15-1
C11-1
C9-1
UC1-1
C14-3
C22-1
IBS16-1
UC14-1
C13-1 UC1-2
UC8-1
C13-2
C26-2
C22-3
UC1-3
C10-3
C4-3
C27-1
C4-2
C11-2
C5-3
C5-2
C15-2
C3-1
C21-2
C4-1
IBS14-1
UC7-2
C21-1
C19-1
C5-1
IBS4-2
CV score 2
First Canonical variate score - DGGE
2
-1
NMR assignment
CVA of combined (“fused”) DGGE and NMR
4
3
• Nuclear Magnetic Resonance (NMR)-based metabolomics
and PCR-Denaturating Gradient Gel Electrophoresis (DGGE)
were used to investigate the changes in bacterial presence
and activity in faecal extracts from UC and IBS patients
compared to healthy controls
2. UC and IBS patients separate
from healthy volunteers
C25-3
UC16-2
0
C9-1
-5
0
1
2
First Canonical variate score - NMR
C15-1
C21-1
-10
1
(using 16 PLS factors; cross-validated by person; success
rate of 67% comparable the PLS-LDA model)
2
3
C11-3
C18-3
-1
C18-2
IBS16-2
C11-1
C18-1
IBS4-1
IBS4-2
C24-3 IBS6-1
UC4-2
C15-3 IBS3-1
IBS5-1 C3-3
C5-2
C3-2 IBS14-2
C5-1 C18-3
C3-1
IBS14-1
IBS3-3
UC14-1
C12-1 C15-2
UC4-1
C11-3
UC11-1
C24-1
UC15-1
UC8-2
C10-3
C22-3
C24-2
IBS5-2
UC11-2
C10-1
C9-2
IBS3-2
C10-2
UC5-1
C9-3IBS7-2
C11-2
UC1-3
UC11-3
C14-1
C4-2
UC15-2
UC3-1
UC7-2F
C25-3
UC8-3
UC1-1 IBS5-3
C4-3 C19-1 C27-3
C22-2
C8-2
UC1-2 C5-3
C22-1
C8-3
UC13-2
C13-2
C27-2
C21-2
UC5-2
C14-2
C13-3
UC13-1
C27-1
UC16-2
UC3-3
C4-1
C8-1
UC4-3
C26-1
C26-2 C13-1 UC7-2
UC8-1
3
4
-10
-5
UC3-2
0
CV score 1
5
10
• Hierarchical clustering displayed some degree of conservation in
the individuals’ profile as the intra-individual variability was lower
than the inter-variability for both NMR and DGGE data (data not
shown). Strikingly, a high correlation is observed between the DGGE
and the NMR data suggesting a strong link between the metabolite
composition of the faecal waters and the microbial community
detected by DGGE (see 1). It is possible to model of UC, IBS and
the healthy groups but the UC group is more readily separated then
the IBS (2)
3. Selection of metabolite markers
Taurine (3.25 ppm)
Bile acids (0.71 ppm)
• Variable width bucketing was used to quantify the metabolite signals from the 1D spectra of
124 samples (1-4 separate collections from 22 controls, 11 IBS patients and 13 UC
patients). The data were subsequently analysed by univariate and multivariate analyses
p 1e-4
p 2e-6
PCR-DGGE
(a) DGGE profiles of faecal samples obtained from IBS, UC
and control subjects showing the number of bands
corresponding to amplicons of the V3 region of 16S rRNA of
faecal bacteria. (b) Box and whiskers plot presenting the
median and range of band counts of all faecal samples
taken from UC, IBS, and controls. (notches that do not
overlap have different medians at the 5% significance level)
• Univariate analysis highlighted several markers for UC (50
buckets/138 have significant p values) and IBS (37buckets/138).
These include taurine, glucose, cadaverine, putrescine, lactate, 2methylbutyrate, acetate and several more
Conclusions
• The study reveals that the DGGE and NMR-based metabolomics are
two global approaches that can be combined to give a new insight of
the biological events associated with irritable bowel diseases (IBD)
• There are differences in the microbial and metabolite compositions of
faecal extracts from healthy volunteers , IBS and UC patients
suggesting microflora might play a role in the disease aetiology
• The inter-individual variability is large .
Larger cohorts could help better define the
IBD conditions
We thank the Ministry of Higher Education of Saudi Arabia and the BBSRC as well as Louise Scovell and Jamieson Crawford from the Norfolk and Norwich University Hospital
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