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Non-Targeted LC-MSn Profiling of Compounds in Ileal Fluids that Decrease
After Raspberry Intake Identifies Consistent Alterations in Bile Acid
Composition
Gordon J. McDougall,† J. William Allwood,† Gema Pereira-Caro,‡ Emma M. Brown,§
Nigel Ternan,‖ Susan Verrall,† Derek Stewart,†⏊ Roger Lawther,‖ Gloria O’Connor,‖
Ian Rowland, Alan Crozier,○ and Chris I. R. Gill§
†Environmental and Biochemical Sciences Group, The James Hutton Institute,
Invergowrie, Dundee, DD2 5DA, Scotland
‡Postharvest, Technology and Agrifood Industry Area, IFAPA, Córdoba, Spain
§Centre for Molecular Biosciences, University of Ulster, Coleraine, BT52 1SA,
Northern Ireland
⏊School of Life Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland
‖Altnagelvin Area Hospital, Western Health and Social Care Trust, Londonderry,
BT47 6SB, Northern Ireland
Department of Food and Nutritional Sciences, University of Reading, Reading, RG6
6AP, England
○Department of Nutrition, University of California, Davis, 95616, CA, United States
1
ABSTRACT
Ileostomy studies provide a unique insight into the digestion of foods, allowing
identification of physiologically relevant dietary phytochemicals and their metabolites
that are important to gut health. We previously reported an increase of components,
including novel triterpenoids, in ileal fluids of 11 ileostomates following consumption
of raspberries using non-targeted LC-MSn techniques in combination with data
deconvolution software. The current study focused on components that consistently
decreased post-supplementation. After data deconvolution, 32 components were
identified that met exclusion parameters of m/z signals and which decreased
significantly in ileal fluids from eight of 11 participants post-raspberry
supplementation. Two-thirds of these components were identified putatively from
their MS properties. Consistent decreases were observed in components that
possibly reflected “washing out” of pre-supplementation intake of common
foods/drinks including (poly)phenol metabolites. Metabolites associated with fat
metabolism such as hydroxylated fatty acids and cholate-type bile acids were
specifically reduced. However, more directed re-examination of the data revealed
that although some cholates were consistently reduced, the more polar glyco- and
tauro-linked bile acid derivatives increased consistently, by as much as 100-fold over
pre-supplementation levels. The possible reasons for these substantial alterations in
bile acid composition in ileal fluids in response to raspberry intake are discussed.
2
Berry consumption has been shown to have beneficial effects on a range of chronic
diseases1-4 and their underlying pathophysiologies,5-7 are thought to be mediated
through the activity of various (poly)phenols.8 However, many of (poly)phenol
classes exhibit low bioavailability, for example, urinary recoveries of anthocyanins,
which reflect passage through the circulatory system, are, at best, <1% of intake,9
but if metabolites and colonic catabolites are taken into account, overall
bioavailability is much higher.10-12 This highlights that the beneficial effect previously
ascribed to anthocyanins in many studies may be partly delivered by their
catabolites, such as protocatechuic acid (3,4-dihydroxybenzoic acid).13-15 The other
major raspberry (poly)phenols, ellagitannins, are broken down to ellagic acid which
is metabolized by the colonic microbiota to form bioavailable urolithins which may
have systemic effects.16 Therefore, studies that investigate the metabolic fate of
berry constituents are crucial to determining the components that function in vivo.
If (poly)phenols and their derivatives are to be effective in vivo, they must first
survive the effects of the digestive system. Studies that simulate digestive
processes in vitro17, 18 have provided evidence that berry (poly)phenols have
different stabilities in the gastrointestinal tract (GIT) and that some components
survive and could therefore influence events in the colon.19 However, such
procedures can only give “broad brush stroke pictures” of relative stability in the gut
as they cannot mimic the active processes of digestion20 and in vivo evidence is,
therefore, more informative. Studies with ileostomy volunteers can provide unique
insight on events in the upper GI tract and can identify (poly)phenols and their
metabolites which, in volunteers with an intact colon, would pass from the small to
the large intestine.21-24
3
In previous studies,25 targeted liquid chromatography mass spectrometric (LC-
MSn) analysis confirmed that anthocyanins and ellagitannins were recovered in ileal
fluid after ingestion of raspberries [Rubus idaeus L. (Rosaceae)].23 Non-targeted
LC-MSn analysis, combined with an unbiased data handling procedure, was used to
determine which other metabolites consistently increased in the ileal samples after
raspberry intake and led to the discovery of novel (poly)phenolic components, their
potential breakdown products and other, previously unrecorded, components
including triterpenoids.26 In this investigation, the non-targeted approach has been
extended to examine components that consistently decreased after ingestion of
raspberries. This non-targeted approach highlighted decreases in various
components following raspberry intake, in particular certain bile acids, but also
unveiled consistent and substantial shifts in tauro- and glyco-conjugated bile acid
composition.
RESULTS AND DISCUSSION
Non-targeted LC-MSn analysis and data deconvolution techniques produced a list of
32 components that consistently decreased in the ileal samples after ingestion of
raspberries. Their MS and MS2 data and derived structural formulae provided
putative identities for most components (Table 1) but some could not be identified,
even tentatively. However, some of the unknowns gave predicted structural
formulas and MS2 data suggesting that they are similar compounds, e.g. the
metabolites at m/z 315 and 317 differ by only 2 amu and share common MS2
fragments. The abundance of various selected components is illustrated in the
Supporting Information.
4
Consistent decreases in certain components may reflect “washing-out” of
common food components taken prior to the supplementation. Phenolic metabolites
such as hippuric acid, dihydroxyphenylacetic acid, 3'-methoxy-4'-
hydroxyphenylacetic acid, 3-(4'-hydroxyphenyl)propionic acid, and
phenylacetylglycine (Figures S1A and B, Supporting Information) may arise from
intake of phenolic-rich foods or drinks. Indeed, LC-MSn-based metabolomics
studies identified hippuric acid as a possible urinary biomarker of tea intake27 and
indole carboxylic acid sulfate has been identified in urine after tea intake.28 The
presence of hippuric acid in ileal fluid was unexpected as it arises through hepatic
glycination of benzoic acid but, arguably, it may be returned to the GIT via biliary
excretion. The putative sulfated metabolites present (e.g. sulfates of
dihydroxyphenylglycol and indole carboxylic acid) are probably formed by phase II
metabolism in the gut wall and efflux back into the GI tract.29
Similarly, the putative identification and decline in hydroxyisocaproic acid could
arise from pre-supplementation intake from milk or yoghurt30 and 2-hydroxy-4-
(methylthio)-butanoic acid and methyl 4-acetamido-2-ethoxybenzoate may arise
from chicken, or possibly egg, intake. In addition, sulfoxy methylfurfural and sulfoxy
methylfurfuryl alcohol (Table 1) are sulfated metabolites of Maillard products formed
during heating of carbohydrates, and, perhaps, roasting of coffee.31 However, if
contrary to instructions, participants had drunk coffee, caffeoylquinic derivatives
would be readily apparent in the ileal samples.32 Methylfurfural derivatives have
been associated with carcinogenic effects in the gut33 and removal of these
potentially hazardous components is of note but again their diminution could be a
matter of metabolites being cleared from the gastrointestinal tract (GIT).
5
The observation that m/z signals consistent with leukotriene F4 were present
and declined after supplementation (Figure S2, Supporting Information) merits
further attention. The match was highly significant and the MS2 data fitted well with
predicted fragments (Table 1). Leukotriene F4 is an eicosanoid intermediate in
arachidonic acid metabolism and has been shown to induce contraction of guinea
pig ileal smooth muscle ex vivo.34 It was also intriguing that the unbiased data
selection also highlighted m/z signals characteristic of dihydroxyphenylglycol-O-
sulfate as consistently declining, as this is a metabolite of norepinephrine, a
neurotransmitter produced by sympathetic nerves especially noted in mesenteric
organs.35 Reduced levels of hydroxyhexanoic acid and hydroxypentanoic acid could
reflect changes in lipid metabolism. Two components that consistently decreased
each gave a [M-H]- peak at m/z 453 (Rt = 30.44 and 32.58 min; Table 1) and had
MS properties consistent with formic acid adducts of cholic acid (Figures 1A and
B).36, 37 Other putative bile acid derivatives including a glucoside and a
dehydrocholate derivative (also as a formate adduct) were also identified. Indeed, it
was confirmed that preparation of bile acid standards in acetonitrile/formic acid
solutions resulted in the formation of formate adducts (data not shown). Using
previous MS data36 as a guide, the fate of m/z values characteristic for other
potential bile acid derivatives was followed (Table 2). This more directed approach
led to discovery of peaks with m/z properties consistent with deoxy- or
chenodeoxycholates (m/z 437), glycocholates (m/z 464),
glyco(cheno)deoxycholates (m/z 448), tauro(cheno)deoxycholates (m/z 498), and
taurocholates (m/z 514). These compounds appeared to elute in a predictable order
with tauro-derivatives before the equivalent glyco-derivatives and the cholic forms
before the deoxycholic forms.36 The identities of the taurocholate, glycocholate and
6
main cholate peaks were established by co-chromatography with standards (Figure
2); however further work with additional reference compounds would be required to
identify unambiguously all components.
There were consistent changes in the profiles of bile acid derivatives after
supplementation with the raspberries (see Figures 1 A-J). Although the three
cholate peaks (Figures 1A-C; m/z 453) were all reduced, the glycine and taurine
derivatives of cholate and deoxycholate increased. In addition, the inter-individual
patterns of increases for the glycocholate and glycodeoxycholate derivatives were
very similar as were the tauro-forms of the cholate and the deoxycholate adducts.
The increases ranged from ~2 to 50-fold for most compounds but reached 120-fold
in participant 10 for taurodeoxycholate. This substantial increase in
taurodeoxycholate was noted as a component that increased after raspberry
supplementation25 but as that investigation concerned only components derived
from the raspberries, they were not reported. The levels of the three
(cheno)deoxycholate derivatives showed mixed behavior with two generally
increasing and the other decreasing. Increased levels of dihydroxyoctadecenoic
acid were also noted (Table 2) and, along with the decreases in hydroxyhexanoic
and hydroxypentanoic acids aleady noted, these may indicate alterations in lipid
digestion following raspberry consumption.
The mechanisms that could cause these specific shifts in bile acid composition
in the ileal fluid after raspberry intake are not known. Apart from general assertions
that bile acid production is increased in response to food intake,38, 39 there is little
information on the effect of different foods and drugs on specific bile acid
composition in the ileum. It is possible that the observed changes in bile acid
composition are a normal reflection of progressing from a resting to a post-meal
7
state and, indeed, there is some evidence for circadian variations in bile acid
content and composition in the liver from mice,40 with higher levels during feeding
times. The paucity of knowledge on the effects of foods is compounded by the fact
that bile acid composition data are often reported after deconjugation. An
investigation with rats that monitored the effects of chronic alcohol intake on bile
acid profiles found decreased taurine-conjugated bile acids but increased glycine-
conjugated and unconjugated bile acids in the small intestine.41
A number of possible underlying reasons for these dramatic and consistent
alterations in bile acids composition may be postulated. (Poly)phenols present in
the raspberries may interfere with fat digestion through inhibition of lipase activity42
or perhaps through direct effects on the micellarization of fats, as (poly)phenols
have been shown to have cholesterol micelle-disrupting activities.43 This raises
other questions. Would such interference in lipid digestion increase bile acid
synthesis, and would specific bile acids be produced? If more bile is required to
overcome disturbances in lipid handling, would there be changes in composition?
The increases in the more hydrophilic tauro- and glycoconjugated forms may lead
to more effective emulsification of fats as judged by critical micelle concentration
values.44
There is some evidence with rats45 for (poly)phenol intake influencing fecal
excretion of specific bile acids, mainly in beneficially reduced amounts of lithocholic
and deoxycholic acids, two secondary bile acids that are considered to be risk
factors for colon cancer.46 Indeed, in populations with enhanced incidences of colon
cancer, fecal bile acids tend to be higher.47 Mice fed diets containing deoxycholate
at levels found in human feces developed colonic adenomas and adenocarcinomas
whereas those fed deoxycholate-free control diets did not.48 (Poly)phenols have
8
been shown to protect colon epithelial cells from deoxycholate-induced damage,49
possibly through protecting against free radical-mediated mechanisms. A
metabolomic approach established that urinary taurodeoxycholic acid levels in mice
increased following intake of polyphenol-rich almonds.50 In contrast, the cecal
content of bile acid derivatives did not increase. This was suggested to be due to
modulation of bile acid synthesis by influencing farnesoid X receptor-regulated
metabolism.51 Using a non-targeted MS approach, changes in certain bile acids
were noted in feces of human volunteers after moderate daily consumption of red
wine.52 The wine intervention increased the fecal levels of deoxycholate and
reduced those of sulfolithocholate, both of which may be considered products
generated by the action of the colonic microbiota.
Pectins and/or other cell wall components from the raspberries may bind bile
acids,53 increase the bile acid pool sizes and alter their composition, with a shift to
more polar forms. However, these studies analyzed deconjugated bile acids and,
thus, it is known whether the increased pool size was caused by increases in
specific conjugated forms. Methylated pectins increased the total bile acid content
in the ileum of rats and some of this increase could be attributed to increased
taurodeoxycholate, but not to taurocholate, levels.54 Pectin is believed to bind bile
acids in the small intestine, which are subsequently voided in feces and the body
increases synthesis to compensate for loss of re-absorbed bile acids. Cholesterol
levels can be reduced as compensatory increases in bile acid synthesis reduce
cholesterol pools.55 Insoluble dietary fibers, such as cellulose, may also increase
total bile acid content in the small intestine and increase subsequent fecal
excretion.56 Considering that certain (poly)phenols have also been shown to bind
bile acids in vitro,57 it is possible that the enhanced levels of the glyco- and tauro-
9
conjugated forms are due to their binding to raspberry polysaccharides or
(poly)phenols with the consequent prevention of their re-absorption.
Another explanation for the increase in bile salts, i.e., tauro- and glyco- bile acid
derivatives, and the decrease in cholic and deoxycholic acids, is that it might be due
to inhibition of the enzyme bile salt hydrolase associated with the small intestine
microbiota58, 59 This enzyme deconjugates tauro- and glycoconjugated bile acids
and has been found in abundance in all the main gut microbial phyla, including
Firmicutes, Bacteroidetes, Actinonbacteria, and Proteobacteria.58 There is
increasing evidence that plant (poly)phenols can exert antibacterial activity and can
modulate intestinal microbiota composition.60 Studies of ileostomy participants have
revealed that the human small intestine has a diverse and variable microbiota59 and
that (poly)phenol-induced changes in microbiota composition could impact upon
bile salt hydrolase activity and consequently the ratio of conjugated to deconjugated
bile acids. It is also possible that the ileal sections have interfered with the efficient
recovery of bile acids that normally occur by active transport mechanisms in the
terminal ileum.38 However, interference in recovery does explain why these
components were increased, only that their particular enhancement would not be
noted in individuals with an intact ileum and colon.
In conclusion, a non-targeted LC-MSn-based examination of constituents that
consistently decreased in ileal fluids following dietary raspberry supplementation
revealed three main classes of components. First, there were compounds that
could not be identified from the MS data available. Second, there were those that
may decline (e.g., phenolics, Maillard products, lipids) as previously ingested
common foods are being “cleared” from the GIT. Finally, the levels of certain
endogenously produced components appeared to be modulated during digestion,
10
including a leukotriene derivative, a putative neurotransmitter metabolite, and
certain bile acids. Further examination indicated that the more polar glyco- and
tauro-conjugated bile acid derivatives were consistently and substantially elevated
in the post-raspberry supplementation samples. Although it is not possible to be
certain whether these alterations in bile acid profiles were due to the intake of
raspberries or part of a general response to food intake, their consistent and
substantial modulation has implications for digestion and gut health.
EXPERIMENTAL SECTION
Chemicals. All chemicals were sourced as described previously.25 Bile acids
(cholic acid, sodium taurocholate and sodium glycocholate) were obtained from
Sigma-Aldrich Chemical Co. Ltd, Poole, UK.
Plant Material and Processing. Raspberries (30 kg, Rubus idaeus variety Glen
Ample) were purchased locally and transported to the James Hutton Institute on the
day of picking, where they were pureed as described before.25 These were then
frozen, transported to the University of Ulster, and stored at -20 oC prior to use in
the ileostomy feeding studies.
Ileostomy Feeding Study. The ileal fluid samples were collected from a
raspberry puree ileostomy feeding study25 (Reg. No. 11/NI/0112) conducted with
the prior approval of the Office for Research Ethics Committees Northern Ireland
(ORECNI), the Ulster University Ethical Committee and with the informed consent
of participants who were recruited from Clinics at Altnagelvin Area Hospital, with the
assistance of Colorectal Consultant (Dr. R. Lawther) and Nurse Specialist (Dr. G.
O’Connor). In brief, following a diet low in (poly)phenolic compounds, 11
11
ileostomates provided a baseline ileal fluid sample (T = 0 h) then consumed 300 g
of pureed raspberries and a second ileal fluid sample collected at T= 8 h. 25 The ileal
fluid samples were collected, processed within 30 mins, and stored as aliquots at
−80 °C.
Non-Targeted Analysis of Metabolites in Ileal Fluids. Frozen ileal samples
were thawed, vortexed, and duplicate 2.0 ± 0.1 g samples weighed into 15 mL
centrifuge tubes. These were extracted using 3 mL of ultra-pure water (UPW)
containing aqueous 1% formic acid and 20 mM diethyldiothiocarbamate (DDC). The
tubes were vortex-mixed for 3 x 30 s then sonicated in a water bath for 1 min. All
procedures were carried out at 5 ˚C. After centrifugation (2500 g, 10 min, 5 ºC), the
supernatants were transferred to new tubes. The pellets were extracted twice using
3 mL of 1 % formic acid in methanol containing 20 mM DDC and the supernatants
combined and vortex-mixed. A sub-sample of 4 mL was removed and dried in a
Speed-Vac. The dried samples were resuspended in 1 mL of 10 % acetonitrile
containing 0.2 % formic acid and prepared in filter vials (0.45 M PTFE filters,
Bioprocess Engineering Services Ltd, Ashford, Kent, UK).
Non-targeted analysis of the ileal fluids was performed on an HPLC system
consisting of a quaternary pump (Thermo Fisher Scientific, Accella 600) and a PDA
detector (Thermo Fisher Scientific, Accella) coupled to an LTQ Orbitrap mass
spectrometer (Thermo Fisher Scientific San Jose, CA, USA). Duplicate 10 µL
samples were injected on to a 2 mm x 150 mm (4 µm) Synergy Hydro-RP 80 fitted
with a C18 4 x 2 mm Security GuardTM cartridge (Phenomenex Ltd, Macclesfield,
Cheshire, UK). Sample and column temperature were maintained at 6 oC and 30
oC, respectively. Samples were analyzed at a flow rate of 0.3 mL/min using a
gradient of (A) 0.1% aqueous formic acid and (B) 0.1% formic acid in
12
acetonitrile/water (1:1, v/v) (gradient: 0-4 min 5% B; 4-22 min 5-50%B; 22-32 min,
50-100%B). Mass detection was carried out using an LTQ Orbitrap mass
spectrometer in negative ionization mode. Two scan events were employed; full
scan analysis was followed by data-dependent MS/MS of the three most intense
ions using collision energies of 45 electron volts source voltage in wide-band
activation mode.25
Data Deconvolution and Statistical Analysis. Mass spectrometric (MS) data
from the Orbitrap was applied to the SIEVETM software programme
( http://www.thermoscientific.com/en/product/sieve-software-differential-
expression.html), as described previously.25 This method compares and contrasts
multiple samples. The samples were labeled either before or after supplementation
and the program set to discern MS signals that were consistently present in all
participants but decreased in the post-supplementation samples. Data were
obtained as peak areas from the SIEVE automatic integration software, and
consisted of 862 variables or potential peaks. Statistical analysis was carried out on
all the variables obtained from the HPLC-MSn analysis of the samples. In brief,
initially principal component analysis (PCA) was applied to all the samples and
components 1 to 4 described 42% of the variation. Secondly, a discriminant
Optimized Partial Least Squares (OPLS-DA) analysis was performed with two
classifications (before feeding and after feeding), resulting in a model that described
33% of the variation. The Q2 score for this model was 0.974. These analyses were
performed using SIMCA-P 12.0.1.0 software (see Supporting Information, Fig. S1A-
D). Using the loadings plot from PCA analysis, a list of >140 putative metabolites
was extracted (Figures S1A-D; Table S1, Supporting Information) that most
influenced the separation towards the pre-supplementation or “before” state. It
13
should be noted that use of the loadings plot from the OPLS-DA analysis gave the
same list. After removing possible adducts (such as formate), multiply charged
variants and in-source fragments, exclusion parameters were set to ensure that
components that were consistently reduced after raspberry supplementation were
selected. The parameters were that the components had to be reduced in eight out
the 11 volunteers with no significant difference in the other 3 volunteers. This took
into account the considerable inter-individual variation already noted in these
samples (Table S1, Supporting Information) and decreased the list to 32 putative
metabolites.
Lastly, pair-wise metabolite–metabolite correlations (using Genstat for
Windows, 16th Edition, VSN International Ltd., Hemel Hempstead, UK) was used to
confirm components that were generally reduced in abundance after
supplementation. This used Pearson’s correlation coefficient (r) test using two
samples sets, all samples and then using a subset consisting of the “before
feeding” samples. The abundance graphs produced in the process allowed the
dataset to be interrogated for specific components of known m/z values (such as
other putative bile acid components) to assess their relative abundance in the
before and after samples and provide the data shown in the figures.
ASSOCIATED CONTENT
Supporting Information
The Supporting Information is available free of charge on the ACS Publications
website at DOI:
14
AUTHOR INFORMATION
Corresponding Author
*Tel: (G.J. McDougall) +44 (0) 1382 568782. Fax: +44 (0) 844 928 5429. E-mail:
Present Address
†Environmental and Biochemical Sciences Group, The James Hutton Institute,
Invergowrie, Dundee, Scotland.
Notes: The authors declare no competing financial interests.
ACKNOWLEDGEMENTS
The authors thank the volunteers for their participation. C.G., R.L. and A.C.
acknowledge funding from the National Processed Raspberry Council, and Western
Health and Social Care Trust. D.S., J.W.A., S.V. and G.McD. acknowledge funding
from the Scottish Government's Rural and Environment Science and Analytical
Services Division (RESAS). G.P.C. was supported by a postdoctoral fellowship
from IFAPA (Programa Operativo del Fondo Social Europeo 2007−2013 de
Andalucıa).
15
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FIGURE LEGENDS
Figure 1. Abundance of bile acid derivatives in ileal fluids before and after
raspberry supplementation.
(A) Cholate peak 1, reduced in nine of 11 participants, not significantly different
(equivalent) in one participant, increased in one participant. (B) Cholate peak 2,
reduced in nine participants & equivalent in two participants. (C) Cholate peak 3,
reduced in eight participants, equivalent in three participants. (D) Glycocholate,
increased in 10 participants, equivalent in one participant. (E) Glycodeoxycholate,
increased in all 11 participants. (F) Taurodeoxycholate, increased in 10 participants,
22
equivalent in one participant. (G) Taurocholate, Increased in 10 participants,
equivalent in one participant. (H) Deoxycholate peak 1, increased in six
participants, equivalent in five participants. (I) Deoxycholate peak 2, reduced in six
participants, equivalent in three participants & increased in two participants. (J)
Deoxycholate peak 3, reduced in eight participants, equivalent in two participants,
increased in one participant.
Abundances are in MS response units and are averages of replicate samples ± SD.
The m/z values and retention times are given on each figure. Superscripts beside
bars represent: a = not significantly different from before value, p = 0.01. b =
significantly higher than before value, p = 0.01.
Figure 2. Structures of bile acid derivatives
23
Table 1. Mass Spectrometric Signals in Ileal Fluids that Decreased after Raspberry intake as identified by Non-Targeted LC-
MSn Approacha, b
Rt [M-H]– m/z] MS2 exact mass (ppm) putative identity comment5.06 249.0061 169c, 81, 80 C8H9O7S (0.250) 3, 4-dihydroxyphenylglycol-O-
sulfate (8 3 =)dihydroxyphenylglycol-O-sulfate is a potential metabolite of norepinephrine; a transmitter produced by sympathetic nerves, particularly in mesenteric organs (HMDB 01474d)
5.32 326.1227 282, 210c, 166, 141
C15H20O7N (0.778) L-phenylalanine, N-(1-deoxy-D-fructos -1-yl) (8, 3 =)
fructose phenylalanine is an Amadori rearrangement Maillard product (CAS 31105-03-0e)
6.01 206.9958 179c, 161, 127, 99, 81
C6H7O6S (0.035) sulfoxy hydroxymethyl furfuryl alcohol (9, 2=)
A potentially genotoxic metabolite of hydroxymethylfurfuryl alcohol (31f)
7.08 225.0869 207, 181c C10H13O4N2 (0.093) unknown (9, 2=) unknown
8.04 117.0553 71 C5H9O3 (0.689) hydroxyvaleric acid or hydroxypentanoic acid (9, 2=)
hydroxyvaleric acid noted in plasma and urine as a degradation product of fatty acids (HMDB 00531)
8.26 204.9801 125 C6H5O6S (0.085) sulfoxy methylfurfural
(9, 2=)
a potentially genotoxic metabolite of
hydroxymethyl furfural (33; CAS
136301)
8.46 149.0272 101 C5H9O3S (0.499) 2-hydroxy-4-(methylthio)-butanoic acid (9, 2=)
methionine analogue used in animal feed (HMDB 37115)
24
9.58 253.1180 223, 128, 124c, 94
C12H17O4N2 (0.415) unknown (9, 2=) unknown
10.30 333.0743 316, 288, 272, 253c, 244c, 236
C12H17O7N2S (0.788) sulfate of m/z 253? (10, 1=) unknown
10.58 181.0498 163c, 135 C9H9O4 (0.200) dihydroxyphenylpropionic acid (8, 3= )
often noted in urine after phenolic intake (26, 61; HMDB 00423)
12.77 178.0500 134 C9H8O3N (0.170) hippuric acid (8, 3=) often noted in urine after phenolic intake (26, 61; HMDB 00714)
12.89 567.2735 387c, 369, 351, 327, 253
C28H43O8N2S (0.057) leukotriene F4 (11) a cysteinyl-leukotriene, part of the eicosanoid family (34; HMDB 06465)
12.98 181.04967 137c, 119, 109
C9H9O4 (0.135) 3'-methoxy-(4’-hydroxyphenyl) acetic acid (9, 2=)
often noted in urine after phenolic intake (HMDB 04285)
14.03 239.9958 160 C9H6O5NS (0.389) indole carboxylic acid sulfate (11)
indole carboxylic acid is a metabolite of tryptophan found in urine after tea intake (27; HMDB 60002)
14.14 131.0707 113, 89, 85c C6H11O3 (0.539) hydroxyhexanoic acid or hydroxyisocaproic acid (10, 1=)
a degradation product of fatty acids or milk products (30; HMDB 00525)
14.61 192.06556 148, 74c C10H10O3N (0.040) phenylacetylglycine (10, 1 =) reported to be increased after intake of polyphenol-rich fruits/ vegetables (62; HMDB 00821)
15.62 363.1176 345, 257c C15H17O6N5 (0.315) unknown (9, 2 =) unknown, related to m/z 315
15.64 330.2014 300c, 256, 199, 130
C21H30OS (0.192) unknown (8, 3 =) unknown
16.50 184.0969 140, 74c C9H14O3N (0.080) heptenoyl glycine (10, 1 =) glycine conjugates often reported in
25
urine (62)
16.86 165.0547 147c, 121 C9H9O3 (0.279) 3-(4'-hydroxyphenyl)propionic acid (10 1=)
often noted in urine after phenolic intake (26; HMDB 02199)
18.95 204.0654 186c, 158c, 142, 116
C11H10O3N (0.140) indole-3-lactic acid (9, 2 =) possible metabolite of tryptophan (HMDB 00671)
19.01 236.0914 218, 192, 164, 147c, 88c
C12H14O4N (0.364) methyl 4-acetamido-2 ethyl benzoate or benzyl-L-glutamate (8, 3 =)
used as a coccidiostat in poultry feed (CS 5812g)
21.42 359.0420 279c, 193c C14H15O9S (1.139) sulfate of C14H15O6? (10, 1=) ethyl 6-(methoxymethoxy)-2-methyl-5-sulfooxy-1-benzofuran-3-carboxylate (CS
24.44 315.1330 300, 287c, 269, 243, 193, 164, 148c
C15H17O3N5 (0.409) unknown (10, 1=) high predicted N content suggests purine type structure
24.58 283.1171 239 C14H19O6, (0.495) unknown (8, 3=) unknown
24.89 317.1487 289c, 273, 271, 255, 193, 164, 148, 120c
C15H19O3N5 (0.489) unknown (9, 2 =) unknown, related to m/z 315
25.55 383.1511 365, 339,
303c
C19H27O6S (1.107) sulfated steroid? (9, 2=) hydroxy-17-oxoandrost-5-en-19-yl
sulphate (CS 2497931) or
dihydroxy-androstenone sulfate;
(CS 20171375)
29.73 569.3296 551, 407c, 389
C34H49O5S (0.078) glucoside of cholic acid (9. 2=) bile acid glucosides have been identified in human urine (63)
29.94 385.1303 305c, 261, 229
C16H23O6N3S (0.092) sulfate of C16H23O3N3 (9, 2 =) unknown
26
30.44b
453.2827 407 C25H41O7 (1.920) cholate formate adduct (9, 2=) (36, 37)
30.62 451.2674 405c, 335c C25H39O7 (1.530) formate adduct of 405 (9 2=) possibly a dehydrocholate derivative
32.58b
453.2826 407 C25H41O7 (1.931) cholate formate adduct (8, 3=) (36, 37)
aMS data were taken from participants 3, 6 and 9 depending on individual abundance but other participants gave similar data.
bMinimal criteria for inclusion are that levels must be reduced in eight/11 participants and not significantly different in others. Separate
components that are decreased in the same number of participants (e.g. 9 2=) are not necessarily decreased in the same
participants.
cMost abundant MS2 signals.
fNumbers in brackets denote references in the main reference section.
dHMDB = ID number in the Human Metabolome Database maintained by The Metabolomics Innovation Centre, Canada;
http://www.hmdb.ca/
eCAS = Registry Number in the Chemical Abstracts Service, Columbus, Ohio, USA, a division of the American Chemical Society;
https://www.cas.org/
27
fCS = ID number in ChemSpider database, owned and operated by the Royal Society of Chemistry, London, England, UK;
http://www.chemspider.com/
gPeaks at 30.44 and 32.58 are the same as noted in Table 2.
28
Table 2. Targeted Analysis of Bile Acid Components in Ileal Fluids after Raspberry Intakea
Rtexact mass
[M-H]– (m/z)
MS2 predicted formula
(ppm)
putative identity ( =) referencesb
28.37 514.2810 496c, 430,
412, 371, 353
C26H44O7NS (1.801) taurocholate (10, 1=) LM ST05040001d (35, 36)
28.90 453.2827 407 C25H41O7 (1.980) cholate formate adduct 1
(9, 1=, 1)
(36, 37)
29.92 464.2983 446, 420,
402c
C26H42O6N (1.964) glycocholate (11 ) LM ST05030001 (35, 36)
30.44e 453.2827 407 C25H41O7 (1.920) cholate formate adduct 2 (9, 2=) (36, 37)
30.91 498.2862 480c, 432c,
414c, 386,
372, 355
C26H44O6NS (1.819) taurodeoxycholate (10, 1=) LM ST05040013 (35, 36)
31.43 437.2880 391 C25H41O6 (1.745) deoxycholate formate adduct 1
(7, 4=)
(36, 37)
32.58e 453.2826 407 C25H41O7 (1.931) cholate formate adduct 3
(8 , 3=)
(35, 36)
33.10 448.3039 430, 404,
386c
C26H42O5N (1.870) glycodeoxycholate (11 ) LM ST05030006 (35, 36)
33.64 437.2882 391 C25H41O6 (1.585) deoxycholate formate adduct 2
(6, 4=, 1)
(36, 37)
35.93 437.2881 391 C25H41O6 (1.585) deoxycholate formate adduct 3
(8, 2=, 1)
(36, 37)
36.89 313.2365 295c,277, C18H33O4 (0.636) dihydroxyoctadecenoic acid LM FA02000225 (64)29
195, 183, 129 (8, 3=)
aMS data was taken from participants 3, 6 and 9 depending on individual abundance. bNumbers in brackets denote references in the main reference section.cMost abundant MS2 signals. dLM = ID number in LIPID MAPS® database, part of the Lipidomics Gateway supported by the Wellcome Trust;
http://www.lipidmaps.org/ePeaks at 30.44 and 32.58 are the same as noted in Table 1.
Figure 1. Abundance of Bile Acid Derivatives in Ileal Fluids Before and After Raspberry Supplementation
30
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
1.0E+08
2.0E+08
3.0E+08
4.0E+08
5.0E+08
6.0E+08
7.0E+08
m/z [email protected] BeforeAfter
a
A. Cholate peak 1.
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
1.0E+08
2.0E+08
3.0E+08
4.0E+08
5.0E+08
6.0E+08
7.0E+08
m/z [email protected] BeforeAfter
a
a
31
b
B. Cholate peak 2.
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
2.0E+08
4.0E+08
6.0E+08
8.0E+08
1.0E+09
1.2E+09
1.4E+09
1.6E+09
1.8E+09m/z [email protected] Before
After
C. Cholate peak 3
32
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
2.0E+08
4.0E+08
6.0E+08
8.0E+08
1.0E+09
1.2E+09
1.4E+09
1.6E+09
1.8E+09m/z [email protected]
After
D. Glycocholate
33
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
1.0E+08
2.0E+08
3.0E+08
4.0E+08
5.0E+08
6.0E+08
7.0E+08
8.0E+08
9.0E+08
1.0E+09m/z [email protected] Before
After
E. Glycodeoxycholate
34
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120
2000000000
4000000000
6000000000
8000000000
10000000000
12000000000
14000000000m/z [email protected] Before
After
a
F. Taurodeoxycholate
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
5.0E+09
1.0E+10
1.5E+10
2.0E+10
2.5E+10
3.0E+10
a
35
G Taurocholate
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
2.0E+08
4.0E+08
6.0E+08
8.0E+08
1.0E+09
1.2E+09
1.4E+09
1.6E+09m/z [email protected]
Aftera
a
a
a
a
H Deoxycholate peak 1
36
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
5.0E+07
1.0E+08
1.5E+08
2.0E+08
2.5E+08
3.0E+08
3.5E+08m/z [email protected]
After
aaa
a
b
I Deoxycholate peak 2.
37
S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120.0E+00
2.0E+07
4.0E+07
6.0E+07
8.0E+07
1.0E+08
1.2E+08
1.4E+08
1.6E+08m/z [email protected]
BeforeAfter
a
a
b
J. Deoxycholate peak 3
38
Figure 2. Structures of Bile Acid Derivatives
39
40