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:

Gordon.McDougall@hutton.ac.uk.

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

REFERENCES

(1) Rodriguez-Mateos, A.; Heiss, C.; Borges, G.; Crozier A. J. Agric. Food Chem.

2014, 62, 3842–3851.

(2) Zanini, S.; Marzotto, M.; Giovinazzo, F.; Bassi, C.; Bellavite, P. Crit. Rev. Food

Sci. Nutr. 2015, 55, 1870–1885.

(3) Dragan, S.; Andrica, F.; Serban, M.; Timar, R.; Curr. Med. Chem. 2015, 22, 14–

22.

(4) Watson, A. W.; Haskell-Ramsay, C. F.; Kennedy, D. O.; Cooney, J. M.; Trower,

T.; Scheepens, A. J. Funct. Foods 2015, 17, 524–539.

(5) Graf, D.; Seifert, S.; Jaudszus, A.; Bub, A.; Watzl, B. PLoS One 2013, 8

e66690.

(6) Tjelle, T. E.; Holtung, L.; Bøhn, S. K.; Aaby, K.; Thoresen, M.; Wiik, S. Å.; Paur,

I.; Karlsen, A. S.; Retterstøl, K.; Iversen, P. O.; Blomhoff R. Brit. J. Nutr. 2015, 114,

1054–1063.

(7) Joseph, S. V.; Edirisinghe, I.; Burton-Freeman, B. M. J. Agric. Food Chem.

2014, 62, 3886–3903.

(8) Seeram, N. P. J. Agric. Food Chem. 2014, 62, 3839–3841.

(9) Prior, R. L. In Flavonoids and Related Compounds. Bioavailability and

Function; Spencer, J. P. E.; Crozier, A., Eds.; CRC Press: Boca Raton, FL, 2012; pp

79–92.

16

(10) Czank, C.; Cassidy, A.; Zhang, Q.; Morrison, D. J.; Preston, T.; Kroon, P. A.;

Botting, N. P.; Kay, C. D. Am. J. Clin. Nutr. 2013, 97, 995–1003.

(11) de Ferrars, R. M.; Czank, C.; Zhang, Q.; Botting, N. P.; Kroon, P. A.; Cassidy,

A.; Kay, C. D. Br. J. Pharmacol. 2014, 171, 3268–3282.

(12) Peiffer, D. S.; Zimmerman, N. P.; Wang, L. S.; Ransom, B. W.; Carmella, S.

G., Kuo, C. T.; Siddiqui, J.; Chen, J. H.;, Oshima, K.; Huang, Y. W.; Hecht, S.;

Stoner, G. D. Cancer Prev. Res. 2014, 7, 574–584.

(12) Ludwig, I.A.; Mena, P.; Calani, L.; Borges, G.; Pereira-Caro, G.; Bresciani, L.;

Del Rio, D.; Lean, M. E. J.; Crozier, A. Free Radic. Biol. Med. 2015, 89, 758–769.

(13) Vitaglione, P.; Donnarumma, G.; Napolitano, A.; Galvano, F.; Gallo, A.; Scalfi,

L.; Fogliano, V. J. Nutr. 2007, 137, 2043–2048.

(14) Edwards, M.; Czank, C.; Woodward, G. M.; Cassidy A.; Kay, C. D. J. Agric.

Food Chem. 2015, 63, 2423–2431.

(15) Warner, E. F.; Zhang, Q.; Raheem, K. S.; O’Hagan, D.; O’Connell, M. A., Kay,

C. D. J. Nutr. 2016, 146, 465–473.

(16) Espín, J-C.; Larrosa, M.; García-Conesa, M.-T.; Tomás-Barberán, F. Evid.

Based Complement. Alternat. Med. 2013, e270418.

(17) Coates, E. M.; Popa, G.; Gill, C. I.; McCann, M. J.; McDougall, G. J.; Stewart,

D.; Rowland, I. J. Carcinogen. 2007, 18, 1–6.

(18) McDougall, G. J.; Dobson, P.; Fyffe, S.; Shapiro, F.; Stewart, D. Acta Hort.

2007, 744, 135–148.

17

(19) Brown, E. M.; McDougall, G. J.; Stewart, D.; Pereira-Caro, G.; González-

Barrio, R.; Allsopp, P.; Magee, P.; Crozier, A.; Rowland, I.; Gill, C. I. PLoS One

2012, 7, e49740.

(20) Bohn, T.; McDougall, G. J.; Alegría, A.; Alminger, M.; Arrigoni, E.; Aura, A.-M.;

Brito, C.; Cilla, A.; El, S. N.; Karakaya, S.; Martínez-Cuesta, M.-C.; Santos, C. N.

Mol. Nutr. Food Res. 2015, 59, 1307–1323.

(21) Kahle, K.; Kraus, M.; Scheppach, W.; Ackermann, M.; Ridder, F.; Richling, E.

Mol. Nutr. Food Res. 2006, 50, 418–423.

(22) Borges, G.; Mullen, W.; Mullan, A.; Lean, M. E.; Roberts, S. A.; Crozier, A.;

Mol. Nutr. Food Res. 2010, 54, S268–S277.

(23) González-Barrio, R.; Borges, G.; Mullen, W.; Crozier, A. J. Agric. Food Chem.

2010, 58, 3933–3939.

(24) Stalmach, A.; Edwards, C. A.; Wightman, J.; Crozier, A. Food Funct. 2013, 4,

52–62.

(25) McDougall, G. J.; Conner, S.; Pereira-Caro, G.; Gonzalez-Barrio, R.; Brown,

E. M.; Verrall, S.; Stewart, D.; Moffet, T.; Ibars, M.; Lawther, R.; O'Connor, G.;

Rowland, I.; Crozier, A.; Gill, C. I. J. Agric. Food Chem. 2014, 62, 7631–7641.

(26) McDougall, G. J.; Allwood, J. W.; Pereira-Caro, G.;, Brown, E. M.; Verrall, S.;

Stewart, D.; Latimer, C.; McMullan, G.; Lawther, R.; O'Connor, G.; Rowland, I.;

Crozier, A.; Gill, C. I. Mol. Nutr. Food Res. 2016, accepted.

(27) O'Gorman, A.; Gibbons, H.; Brennan, L. Comput. Struct. Biotechnol. J. 2013,

4, e201301004.

18

(28) van der Hooft, J. J.; de Vos, R. C.; Mihaleva, V.; Bino, R. J.; Ridder, L.; de

Roo, N.; Jacobs, D. M.; van Duynhoven, J. P.; Vervoort, J. Anal Chem. 2012, 84,

7263-7271.

(29) Del Rio, D.; Rodriguez-Mateos, A.; Spencer, J. P.; Tognolini, M.; Borges, G.;

Crozier, A. Antioxid. Redox Signal. 2013, 18, 1818–1892.

(30) Ehling, S.; Reddy, T. M. J. Agric. Food Chem. 2014, 62, 1506−1511.

(31) Monien, B. H.; Herrmann, K.; Florian, S.; Glatt, H. Carcinogenesis 2011, 32,

1533–1539.

(32) Erk, T.; Williamson, G.; Renouf, M.; Marmet, C.; Steiling, H.; Dionisi, F.;

Barron, D.; Melcher, R.; Richling, E. Mol. Nutr. Food Res. 2012, 56, 1488–1500.

(33) Svendsen, C.; Husøy, T.; Glatt, H.; Paulsen, J. E., Alexander, J. Anticancer

Res. 2009, 29, 1921–1926.

(34) Lord, A.; Charleson, S.; Letts, L. G. Prostaglandins 1985, 29, 651–660.

(35) Eisenhofer, G.; Aneman, A.; Hooper, D.; Rundqvist, B.; Friberg, P. J.

Neurochem. 1996, 66, 1565–1573.

(36) Martin, F. P.; Dumas, M. E,; Wang, Y.; Legido-Quigley, C.; Yap, I. K.; Tang, H.;

Zirah, S.; Murphy, G. M., Cloarec, O.; Lindon, J. C.; Sprenger, N.; Fay, L. B.;

Kochhar, S. van Bladeren, P.; Holmes, E.; Nicholson, J. K. Mol. Systems Biol. 2007,

3, 112–118.

19

(37) Chen, Y.; Ogundare, M.; Williams, C. M.; Wang, Y.; Wang, Y.; Sewell, G. W.;

Smith, P. J.; Rahman, F. Z.; O'Shea, N.; Segal, A. W.; Griffiths, W. J. Biochimie

2013, 95, 461–463.

(38) Hofmann, A. F. Arch. Intern. Med. 1999, 159, 2647-2658.

(39) Keating, N.; Keely S. J. Curr. Gastroenterol. Rep. 2009, 11, 375–382.

(40) Zhang, Y. K.; Guo, G. L.; Klaassen, C. D. PLoS One 2011, 6, e16683.

(41) Xie, G.; Zhong, W.; Li, H.; Li, Q.; Qiu, Y.; Zheng, X.; Chen, H.; Zhao, X.;

Zhang, S.; Zhou, Z.; Zeisel, S. H.; Jia, W. FASEB J. 2013, 27, 3583–3593.

(42) Boath, A.; Grussu D.; Stewart, D,; McDougall, G. J. Food Digest. 2012, 3, 1–

7.

(43) Tamura, T.; Inoue, N.; Ozawa, M.; Shimizu-Ibuka, A.; Arai, S.; Abe, N.;

Koshino, H.; Mura, K. Biosci. Biotechnol. Biochem. 2013, 77, 1306–1309.

(44) Marin, J. J.; Macias, R. I.; Briz, O.; Banales, J. M.; Monte, M. J Curr. Drug

Metab. 2015, 17, 4–29.

(45) Han Y.; Haraguchi, T.; Iwanaga, S.; Tomotake, H.; Okazaki, Y.; Mineo, S.;

Moriyama, A.; Inoue, J.; Kato, N. J. Agric. Food Chem. 2009, 57, 8587–8590.

(46) Bernstein, H.; Bernstein, C.; Payne, C. M.; Dvorakova, K.; Garewal, H. Mutat.

Res. 2005, 589, 47–65.

(47) Ou, J.; DeLany, J. P.; Zhang, M.; Sharma, S.; O'Keefe, S. J. Nutr. Cancer

2012, 64, 34–40.

20

(48) Bernstein, C.; Holubec, H.; Bhattacharyya, A. K.; Nguyen, H.; Payne, C. M.;

Zaitlin, B.; Bernstein, H. Arch. Toxicol. 2011, 85, 863–871.

(49) Longpre, J. M.; Loo, G. Apoptosis 2008, 13, 1162–1171.

(50) Jové, M.; Serrano, J. C.; Ortega, N.; Ayala, V.; Anglès, N.; Reguant, J.;

Morelló, J. R.; Romero, M. P.; Motilva, M. J.; Prat, J.; Pamplona, R.; Portero-Otín,

M. J. Proteome Res. 2011, 10, 3501–3512.

(51) Del Bas, J. M.; Ricketts, M. L.; Vaqué, M.; Sala, E.; Quesada, H.; Ardevol, A.;

Salvadó, M. J.; Blay, M.; Arola, L.; Moore, D. D.; Pujadas, G.; Fernandez-Larrea, J.;

Bladé, C. Mol. Nutr. Food Res. 2009, 53, 805–814.

(52) Jiménez-Girón, A.; Ibáñez, C.; Cifuentes, A.; Simó, C.; Muñoz-González, I.;

Martín-Álvarez, P. J.; Bartolomé, B.; Moreno-Arribas, M. V. J. Proteome Res. 2015,

14, 897–905.

(53) Matheson, H. B.; Story, J. A. J. Nutr. 1994, 124, 1161–1165.

(54) Dongowski, G.; Lorenz, A. J. Nutr. Biochem. 2004, 15, 196–205.

(55) Gunness, P.; Gidley, M. J. Food Funct. 2010, 1, 149–155.

(56) Lu, H.; Gui, Y.; Guo, T.; Wang, Q.; Liu, X. Food Funct. 2015, 6, 1185–1193.

(57) Wu, Z.; Teng, J.; Huang, L.; Xia, N.; Wei, B. RSC Advan. 2015, 5, 92089–

92095.

(58) Joyce, S. A.: Shanahan, F.; Hill, C; Gahan, C. G. Gut Microbes 2014, 5, 669–

674.

21

(59) El Aidy, A.; van den Bogert, B.; Kleerebezem, M. Curr. Opin. Biotech. 2015,

32, 14–20.

(60) Etxeberria, U.; Fernández-Quintela, A.; Milagro, F. I.; Aguirre, L.; Martínez, J.

A.; Portillo, M. P. J. Agric. Food Chem. 2013, 61, 9517–9533.

(61) Pekkinen, J.; Rosa N. N.; Savolainen, O. I.; Keski-Rahkonen, P.; Mykkänen,

H.; Poutanen, K.; Micard, V.; Hanhineva, K. Nutr. Metab. 2014, 11, 10101–10109.

(62) Lewis-Stanislaus, A. E.; Li, L. J. Amer. Soc. Mass Spectrom. 2010, 21, 2105–

2116.

(63) Marschall, H. U.; Egestad, B.; Matern, H.; Matern, S.; Sjövall, J. FEBS Lett.

1987, 213, 411–414.

(64) Nilsson, T.; Martínez, E.; Manresa, A.; Oliw, E. H. Rapid Commun. Mass

Spectrom. 2010, 24, 777–783.

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 453@RT28.90 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 453@RT30.44 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 453@RT32.58 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 464@RT30.00Before

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 448@RT33.10 Before

After

E. Glycodeoxycholate

34

S1 S2 S3 S4 S5 S6 S8 S9 S10 S11 S120

2000000000

4000000000

6000000000

8000000000

10000000000

12000000000

14000000000m/z 498@RT30.90 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

m/z 514@RT28.50BeforeAfter

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 437@RT31.40Before

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 437@RT33.60Before

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 437@RT35.90

BeforeAfter

a

a

b

J. Deoxycholate peak 3

38

Figure 2. Structures of Bile Acid Derivatives

39

40