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ORIGINAL ARTICLE

Metabonomic investigation of rat tissues following intravenousadministration of cyanidin 3-glucoside at a physiologicallyrelevant dose

Andreja Vanzo • Matthias Scholz • Mattia Gasperotti •

Federica Tramer • Sabina Passamonti •

Urska Vrhovsek • Fulvio Mattivi

Received: 23 December 2011 / Accepted: 24 April 2012 / Published online: 11 May 2012! Springer Science+Business Media, LLC 2012

Abstract Anthocyanins, which are dietary flavonoidsoccurring in fruit and beverages, are reported to have a

beneficial impact on a wide range of chronic diseases, such

as cardiovascular, neurodegenerative and neoplastic dis-eases. To understand the underlying mechanisms, a bio-

chemical description of the changes in cell metabolism

caused by anthocyanins can be provided by metabonomicstudies. The aim of this study was to detect changes in the

profiles of metabolites induced by the administration of

cyanidin 3-glucoside to adult male rats. A physiologicaldose of cyanidin 3-glucoside was intravenously adminis-

tered, and blood, kidneys and liver were collected after

5 min. The tissues were rapidly frozen in liquid nitrogen,stored briefly at -80 "C, homogenised under cryogenic

conditions and extracted in ice-cold methanol:water (95:5,

v/v). The extracts were then analysed using UPLC/QTOF-

MS. Multivariate statistical analysis of the data was per-formed using orthogonal projections to latent structures-

discriminant analysis (OPLS-DA). Discriminating vari-

ables were compared to the in-house standard database,considering matches in retention times, parent mass ions,

mass fragment patterns and isotopic patterns. This meta-

bolomic approach made it possible to identify as many aseight metabolite markers, including bile acids, reduced and

oxidised glutathione and some lipids. Such changes suggest

that cyanidin 3-glucoside has a major effect on tissueantioxidant status as well as on energy and glucose

metabolism.

Keywords Anthocyanins ! Cyanidin 3-glucoside !Metabolomics ! Metabonomics ! Wistar rats !Ultra performance liquid chromatography !Quadrupole-time-of-flight mass spectrometry

1 Introduction

In the past few decades scientists have recognised the posi-

tive value of dietary anthocyanins, red flavonoid pigmentsoccurring in fruit and vegetables, for human health. From

there on much progress was achieved by investigating the

presence of anthocyanins in food (Wu et al. 2006; U.S.Department of Agriculture 2007), estimating their daily

intake (Wu et al. 2006) and investigating their absorption,

distribution, metabolism, excretion and bioactivity (McGhieand Walton 2007; Manach and Donovan 2004; Manach et al.

2005; Hanhineva et al. 2010; Ichiyanagi 2008; Kay 2006).

Alongside such studies, epidemiologic studies have shownthe connection between consumption of food rich in antho-

cyanins and health benefits (Cassidy et al. 2011; Mursu et al.

2008; Spormann et al. 2008; Basu et al. 2010; Prior 2003;

Electronic supplementary material The online version of thisarticle (doi:10.1007/s11306-012-0430-8) contains supplementarymaterial, which is available to authorized users.

A. VanzoCentral Laboratory, Agricultural Institute of Slovenia,Hacquetova 17, 1000 Ljubljana, Slovenia

A. Vanzo ! M. Gasperotti ! U. Vrhovsek ! F. Mattivi (&)Department of Food Quality and Nutrition, Fondazione EdmundMach, Centro Ricerca e Innovazione, via E. Mach 1, 38010 SanMichele all’Adige, Italye-mail: fulvio.mattivi@fmach.it

A. Vanzo ! F. Tramer ! S. PassamontiDepartment of Life Sciences, University of Trieste, via L.Giorgieri 1, 34127 Trieste, Italy

M. ScholzDepartment of Computational Biology, Fondazione EdmundMach, Centro Ricerca e Innovazione, via E. Mach 1,38010 San Michele all’Adige, Italy

123

Metabolomics (2013) 9:88–100

DOI 10.1007/s11306-012-0430-8

Author's personal copy

Hertog et al. 1993). The recently updated recommendations

promote daily consumption of fresh fruit and fruit juice aspart of a healthy dietary plan to reduce the risk of chronic

diseases, such as cardiovascular diseases, type-2 diabetes,

osteoporosis and some forms of neurodegenerative diseases(Lichtenstein et al. 2006; WHO 2004; U.S. Department of

Health & Human services and U.S. Department of Agri-

culture 2010).The mechanisms underlying the reported observations

have still not been clarified. A mechanistic understanding ofthe action of anthocyanin in living organisms requires a

biochemical description of cell metabolism changes caused

by anthocyanins, which can be provided by metabolomic/metabonomic studies. Metabolomic/metabonomic is the

analysis of metabolome, a set of small molecular mass

organic compounds in a given biological medium, at givenconditions (Roux et al. 2011). At present, there is still no

absolute agreement over the exact differences between

metabolomics and metabonomics and the terminology isoften used interchangeably (Robertson 2005). Initially,

metabolomics refers to the measurements of the pools of

cellular metabolites (Fiehn 2002) and metabonomicsextends metabolic profiling to the quantitative measurement

of the time related multi-parametric metabolic response of

living systems to pathophysiological stimuli or geneticmodification (Nicholson et al. 1999). Finally, both meta-

bolomics and metabonomic employ similar methodologies

for analyzing the metabolome by using the state-of-the-artNMR- (Coen et al. 2008) or mass spectrometry-based

(Dettmer et al. 2007; Scalbert et al. 2009) technological

platforms. Beside selective and sensitive analytical tools,processing generated data creates a big challenge in ‘-omics’

approaches. The use of chemometric methods to analyze

complex spectral data sets can greatly affect the metabolitesthat are identified. Principal components analysis (PCA) has

been widely used in metabonomic studies and is an unsu-

pervised approach in that it allows inherent clusteringbehavior of samples to be ascertained with no a priori

knowledge of sample class membership (Jackson 1991).

Alternatively, one widely used supervised method is partialleast squares or projection to latent structures (PLS) (Wold

1985). A relatively new approach is orthogonal partial least

squares-discriminant analysis (OPLS-DA) that extends thetraditional supervised algorithm of PLS by prefiltering

classification-irrelevant orthogonal variation from data

(Trygg and Wold 2002; Trygg and Holmes 2007; Bylesjoet al. 2006). This prefiltered, structured noise in the data set is

modeled separately from the class variation and can also be

further interpreted via the loading matrices. The applicationof OPLS-DA improves the interpretability of spectral vari-

ation between classes and has been shown to successfully

discriminate metabolic profiles in a wide range of studies(Qiu et al. 2010; Moazzami et al. 2011; Ali et al. 2012; Stella

et al. 2006). So far, little is known about how the nutrient

content of the diet impact changes in metabolic profiles. Thecapacity of anthocyanins to affect the mammalian metabo-

lism has recently been demonstrated by investigating met-

abolomic changes in the brain and the plasma of elderly ratsafter dietary supplementation with blueberry extract. It was

found that metabolites connected to neurological functions

were selectively affected, i.e. choline, phosphocholine,taurine and GABA (Yang et al. 2011). The aim of this study

was a non-targeted mass spectrometry-based investigationof the metabolic effects induced by the intravenous admin-

istration of cyanidin 3-glucoside, a common dietary antho-

cyanin, at a physiologically relevant dose in adult male rats.The kinetics of cyanidin 3-glucoside transfer from the

plasma into tissues, and subsequent transformation in its

methylated derivative peonidin 3-glucoside is extraordi-narily fast (Vanzo et al. 2011). Shifts in the cellular meta-

bolic homeostasis induced by cyanidin 3-glucoside would be

expected to occur shortly after tissue uptake. Thus blood,kidneys and liver were collected 5 min after intravenous

(i.v.) administration. In order to identify reliable metabolic

markers, this study followed a carefully designed experi-mental protocol in terms of choosing animals, timing of

experiments, randomisation, repeatability and quenching.

Proper collection, preparation and extraction of sampleswere also strictly controlled (Fiehn 2001; Gika and Theo-

doridis 2011). Data were analysed by ultra performance

liquid chromatography (UPLC) coupled to a quadrupole-time-of-flight mass spectrometry (QTOF-MS). UPLC/

QTOF-MS is a highly sensitive and selective technique for

metabolite profiling (De Vos et al. 2007) allowing us iden-tifying metabolites by in-house made database on the basis

of parent mass ions, mass fragment patterns and isotopic

patterns. Data were then processed by multivariate OPLS-DA statistical approach. The results of presented study

showed that cyanidin 3-glucoside led to the alteration of

some important cellular metabolites, such as bile acids,glutathione, oxidised glutathione and some lipids in the

blood, kidneys and liver of rats.

2 Materials and methods

2.1 Chemicals and materials

Formic acid (LC–MS, Fluka), methanol (LC–MS, Chro-masolv) and ultra pure water of Milli Q gradient (Millipore

Corporation, Billerica, MA, USA) were used for chroma-

tography. Cyanidin 3-glucoside was obtained from Poly-phenol Laboratories AS (Sandnes, Norway) and Heparin

from Schwarz Pharma (Milan, Italy). Phosphate saline

buffer (PBS) was prepared as following: 6.03 mMNa2HPO4, 3.91 mM NaH2PO4 and 139 mM NaCl (Carlo

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Erba, Milan, Italy) were dissolved in Milli Q water (Mil-

lipore) and pH was adjusted to 7.4 with HCl. Anaesthetic:2,2,2-tribromoethanol (Sigma–Aldrich, Steinheim, Ger-

many) was dissolved in ethanol at 2.5 % (w/v) and then it

was 1:9 (v/v) diluted in 0.15 M NaCl. 0.22 lm PVDF fil-ters were from Millipore Corporation (MA, USA). For

tissue grinding under cryogenic conditions (-196 "C) a

CryoMill from Retsch (Haan, Germany) was used.

2.2 Study design

The rats (Rattus norvegicus, Wistar, Harlan Italy S.r.l.) were

bred at animal breeding facilities at the University of Trieste.The experiments on the animals were carried out in com-

pliance with the provisions of the European Community

Council Directive (no. 86/609/CEE) and Italian law (D.L.gs.116/92 and D.L.gs. 633/96, Ministry of Health). The

experiment passed evaluation by the bioethical committee of

the University of Trieste. Rats (n = 24) of the same age(12 weeks) and weight (290 ± 5 g) were maintained in

temperature-controlled rooms at 22–24 "C, 50–60 %

humidity and 12 h light/dark cycles. They were fed withstandard laboratory chow (Harland Teklad, 2018), which

ensures stability of metabolite profiles (Kind and Fiehn

2009). Prior to the tests, the rats were starved overnight, butprovided with water ad libitum. They were divided into two

groups, serving as the control and test groups (each n = 12).

They received i.v. administration of 0.2 mL PBS, with (test)or without (control) 0.67 lmol cyanidin 3-glucoside.

According to a previous study, the same dose of cyanidin

3-glucoside made it possible to observe a peak plasmaconcentration of about 1.5 lM cyanidin 3-glucoside 1 min

after i.v. administration (Vanzo et al. 2011). There are recent

reports that the metabolomic profile of blood may changeduring the 24 h cycle (Minami et al. 2009). Thus the

experiments were carried out within 3 days (n = 8 per day),

always in the morning (from 8 a.m. to 1 p.m.). Randomisa-tion was further implemented by alternative performing of

the experiment on test and control rats.

2.3 Surgical procedure

The rats were anesthetised with intra-peritoneal adminis-tration of 2,2,2-tribromoethanol (0.25 g/kg body weight).

During anaesthesia (15 min in all cases), the heart and

ventilation rate were controlled. The rats were placed ontheir backs, with the ventral side up and with the legs

spread separately on a thermo-isolated support. The left

iliac lateral vein was exposed and exactly 10 min afteranaesthesia 0.2 mL PBS with (test) or without (control)

0.67 lmol cyanidin 3-glucoside was injected using an

insulin syringe. One min before sacrificing the rats (i.e.14 min after anaesthesia) sodium heparin (0.1 ml, 500 IU)

was injected into the right lateral iliac vein, exposed in the

same way. Exactly 15 min after anaesthesia and 5 minafter i.v. administration, the rats were sacrificed by

decapitation. Blood draining and excision of the organs

were carried out according to the literature (Vanzo et al.2011). The kidneys and liver were immediately frozen in

liquid nitrogen and stored at -80 "C.

2.4 Tissue extraction

The choice of the solvent in which the metabolites are

extracted from tissues plays a crucial role in metabolomic

investigations (Cevallos-Cevallos et al. 2009). Our choicewas aqueous methanol (5:95, v/v), deoxygenated by

streaming nitrogen and pre-chilled to -20 "C. It is an

efficient solvent for protein precipitation, enzyme inacti-vation and extraction of polar to semi non-polar metabo-

lites from tissues (Shin et al. 2010; De Vos et al. 2007;

Villas-Boas 2006). When analysing different extractionsolvents for both reproducibility and suppression effects for

a wide range of targeted metabolites in different animal

tissue types including the liver, kidney, muscle, brain, andfat tissue from mice and cattle, it has been concluded that

for most metabolites simple methanolic extraction is best

suited for reliable results (Romisch-Margl et al. 2011).Methanol was reported to offer efficient and reproducible

extraction from the liver (Masson et al. 2010), from the

human blood plasma (Adhikari et al. 2005) and humanblood serum (Zelena et al. 2009).

2.4.1 Blood

Immediately after sampling, the blood was transferred into

ice-cold (-20 "C), deoxygenated aqueous 95 % methanolin a ratio 1:9 (v/v). The sample was vortexed and extracted

for 10 min by gentle shaking at room temperature. The

extract was then centrifuged for 5 min at 3,6009g at 4 "C,decanted under a stream of nitrogen in 50 mL dark glass

vessels and stored at -80 "C for less than a week. Samples

were filtered through 0.2 lm PVDF filters (Millipore) andinjected into a UPLC/QTOF-MS system, as described

below. The aim of extracting blood instead of plasma or

serum was to skip a centrifugation or blood clotting step,during which metabolic changes might occur ex vivo (Gika

and Theodoridis 2011). Both blood and plasma extracts

were compared using UPLC/QTOF-MS analysis to identifypossible adverse effects on resolution or sensitivity due to

the blood matrix. The data showed no matrix effect.

2.4.2 Kidneys and liver

The organs, frozen in liquid nitrogen immediately afterexcision, were stored at -80 "C. Unthawed kidneys (2.0 g)

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and liver (7.0 g) were ground under cryogenic conditions

to 5 lm particles in a CryoMill using a single 25 mm i.d.steel ball. The pulverised tissue was rapidly transferred

(without thawing) into ice-cold, deoxygenated aqueous

95 % methanol in tissue:solvent ratio 1:9 (w/v). Assumingthat tissue contained approximately 70 % of water the final

aqueous part in methanol after extraction was c.a. 12 %

what improved the solubility of hydrophilic metabolites.The sample was vortexed, extracted, centrifuged and dec-

anted as described above (Sect. 2.4.1). and stored at-80 "C for less than a week before being injected (5 lL)

into the UPLC/QTOF-MS system.

2.5 UPLC/QTOF-MS

Analysis was carried out using a Waters Acquity UPLC,coupled to a Synapt HDMS QTOF-MS (Waters, Man-

chester, UK) via an electrospray interface (ESI), operating

in W-mode. The software used was Masslynx 4.1. Thereverse phase method was performed on a ACQUITY

UPLC 1.8 lm 2.1 9 100 mm HSS T3 (Waters) column,

maintained at 30 "C for 60 min using 0.1 % formic acid inwater as solvent A and 0.1 % formic acid in methanol as

solvent B with a flow of 0.3 mL/min and the following

gradient: until 6 min isocratic at 100 % A, then increasinglinearly to 100 % B at 56 min and held isocratic at 100 %

B till 60 min (Theodoridis et al. 2012). A blank solution

(methanol, 5 lL) was injected every twelve samples. 24samples of each investigated tissue were randomised

before injection. The stability of the retention times, areas

and heights was checked in all injections for one impuritypresent in the solvent (methanol) used to prepare the

samples, which was considered suitable to check the global

stability of the process. Moreover, the stability of retentiontimes, areas and heights was monitored in all tissue from

the control rats, observing a few features of the chro-

matograms which in preliminary experiments wereobserved to be in homeostasis in the tissues analysed under

the condition of the experiments. Finally, the stability was

confirmed also by injecting a standard mixture of 11compounds (Theodoridis et al. 2012) at the beginning and

at the end of the analyses of each tissue both in positive and

in negative ESI mode. Results for positive mode are pre-sented in the online resource Table S1.

Spectra were collected in positive and negative ESI

mode over a mass range 50–3,000 amu with a scan dura-tion of 0.3 s in centroid mode. The transfer collision energy

and trap collision energy were set at 6 and 4 V, respec-

tively. The source parameters were: capillary 3 kV, sam-pling cone 25 V, extraction cone 3 V, source temperature

150 "C, desolvation temperature 500 "C, desolvation gas

flow 1,000 L/h and nebulizer gas flow 50 L/h. Externalcalibration of the instrument was performed at the

beginning of each batch of analysis by direct infusion of

a sodium formate solution (10 % formic acid/0.1 MNaOH/acetonitrile at a ratio of 1/1/8) by controlling the

mass accuracy (\5 ppm) and mass resolution (over

14,000 FWHM). Lock Mass calibration was applied usinga solution of leucine enkephaline (0.5 mg/L, m/z 556.2771

for positive and 554.2620 for negative ion mode) at

0.1 mL/min.

2.6 Data analysis

To eliminate the features [retention time (RT) and mass to

charge (m/z) data pairs] generated by the solvent, theinjected methanol fraction (i.e., the blank) was subtracted

from chromatograms. The features were detected by using

MarkerLynxTM

XS Application Manager for MasslynxTM

Mass Spectrometry software. AppexTrack peak integration

was used with a peak wide estimate of 10 s, peak to peak

base line noise of 30, minimum intensity of 10 counts,mass window of 0.05 Da, retention time window of

0.20 min, noise elimination level of 5 and mass tolerance

of 0.05 Da. The ion intensities for each peak were thennormalised within each sample to the sum of the peak

intensities in that sample. The resulting normalised peak

intensities were multiplied by 10,000 and the normaliseddata were statistically analysed.

In case of using unsupervised PCA, obtained results

might be influenced by factors, such as: biological vari-ability, pathological variations, instrumental drift, artifacts,

and other experimental variations which might divert the

focus of a PCA model to the systematic variation unrelatedto the scientific question of interest. In such cases, there is a

need for methods that make use of any a priori information

to refocus the analysis toward the studied objectives by useof, for example, PLS or OPLS (Wiklund et al. 2008). In

order to specify the metabolic variations associated with

cyanidin 3-glucoside, statistical analysis of Pareto-scaledand centered mode data was performed with MarkerLynx

statistics using OPLS-DA. OPLS (Trygg and Wold 2002) is

an extension to the supervised PLS regression methodfeaturing an integrated orthogonal signal correction-filter.

The OPLS-DA method combines the strengths of PLS-DA

and SIMCA classification (Bylesjo et al. 2006). As PLS-DA explains differences between overall class properties,

interpretation becomes progressively more complicated as

the number of classes increases. The main benefit of usingOPLS-DA as compared to PLS-DA in terms of interpre-

tation thus lies in the ability of OPLS-DA to separate

predictive from non-predictive (orthogonal) variation(Bylesjo et al. 2006).

Variable importance for projection (VIP) plots were

created for ESI positive and ESI negative records in orderto detect features differing for test and control rats. The

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VIP score reflects the variable’s contribution to the clas-

sification and can be used to discover the most relevantdifferential variables responsible for group separation.

Potential candidates for discrimination were selected on the

basis of the threshold VIP [ 1 which is shown to be aoptimal cut-off (Wold et al. 2001; Chong and Jun 2005)

and hence is frequently used in metabolomics data analysis

(Qiu et al. 2010; Moazzami et al. 2011; Ali et al. 2012).Discriminating features were then compared to an in-house

standard database prepared by injecting standard com-pounds under identical analytical conditions. Matches in

retention times, parent mass ions, mass fragment patterns

and isotopic patterns were considered for compoundidentification. Compounds having VIP [ 1 and matching

standards according to the above parameters were high-

lighted as putative markers for discrimination betweencyanidin 3-glucoside administered rats and control rats.

Identified markers from VIP lists (VIP [ 1) in positive

mode were also annotated in the Human MetabolomeDatabase (HMDB) (http://www.hmdb.ca) using MS search

(Wishart et al. 2007; Wishart et al. 2009). It was considered

that the accuracy of masses recorded was B3 ppm.

3 Results and discussion

3.1 Tissue extraction and number of features

Blood, kidneys and liver extracts were compared in terms

of the extracted features in ESI? and ESI- mode. The

total number of extracted features detected in ESI? was2,186 in blood, 3019 in kidney and 2,443 in liver extracts.

On the other hand, the total number of features detected in

ESI- was 926 in blood, 1,378 in kidney and 1,291 in liver

extracts. This is in accordance with other studies reporting

a higher number of features detected by the ESI? ionisa-tion interface than by ESI- (Sana et al. 2008; Yin et al.

2006). Kidney extracts showed the highest number of

detected features in both ionisation modes, ESI? andESI-. Although the number of features does not correlate

directly with the number of metabolites, it can be consid-

ered to be ‘‘proportional’’ to metabolites. The distributionin the space defined by the m/z ratio and chromatographic

retention time of the experimental features obtained in ESIpositive mode, evidenced that most of them were generated

from highly hydrophilic, polar compounds eluting in the

earliest part of the chromatogram, as well as hydrophobicmetabolites, eluting in the final part of the gradient (Fig. 1).

The number of features common to organs investigated

using ESI? is indicated in Fig. 2. Blood, kidneys and liverwere found to share 402 features, corresponding to c.a. 18,

13 and 16 % of their features respectively. Kidneys and

liver shared 1,036 features, corresponding to c.a. 34 and42 % of their features respectively. These results show that

both the liver and the kidney express related metabolic

functions.

3.2 Identification of markers matching with the internal

standard database

Giving names to the features obtained is a challenge in

metabolomic studies. In the event that the metabolite hasbeen identified only through a parent ion mass match in a

database, its identity should be considered very tentative. If

the retention time, parent ion mass, isotopic pattern andmass fragment pattern of a compound match the known

standard, then its identity is better established (Moco et al.

2007; Koulman et al. 2009). In this study, the in-house

Fig. 1 Distribution in the space defined by the m/z ratio andchromatographic retention time of the experimental features obtainedin ESI positive mode, for the extracts from blood, kidneys and liver of

adult male rats. The samples were collected 5 min after intravenousadministration of 0.67 lmol cyanidin 3-glucoside

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database of c.a. 500 commercially available primary andsecondary mammalian metabolites was prepared under

identical analytical conditions on the same analytical sys-

tem. This allowed us to compare retention times, parentmass ions, mass fragments and isotopic patterns of stan-

dards to features detected in the blood, kidneys and liver.

Figure 3 shows an example of positive TIC ion chro-matograms of oxidised glutathione detected in the blood,

kidneys and liver together with their corresponding mass

spectra. Features in the blood, kidneys and liver matchingstandards, together with a VIP value [1 from the OPLS-

DA model were considered as putative markers following

cyanidin 3-glucoside i.v. administration to rats. Differentialmetabolites in the blood, kidneys and liver are listed in

Table 1. Other identified metabolites having a VIP \ 1

from the OPLS-DA model are presented in the onlineresource (Table S2).

In a previous study, a dose of cyanidin 3-glucoside was

intravenously administered to anaesthetised rats using anidentical procedure to the one adopted here. By using a

targeted UPLC/MS/MS approach, cyanidin 3-glucoside

and its metabolites were analysed in the plasma, kidneysand liver. It was found that the kinetics of cyanidin

3-glucoside transfer from the blood to the kidneys and liver

was extremely rapid (t/2 = 0.36 min), followed by fast andmassive methylation to peonidin 3-glucoside and finally to

urinary and biliary excretion (Vanzo et al. 2011).

This non-targeted mass spectrometry-based metabolo-mic approach confirmed the powerful bioactivity of

cyanidin 3-glucoside within 5 min from i.v. administration,

with the identification of as many as 8 markers in theblood, kidneys and liver. Some of these, such as

glutathione (GSH), occur generally in the blood and organs

in mM concentration, thus demonstrating the capacity oflow (lM) and rapidly declining plasma concentrations of

cyanidin 3-glucoside to induce rapid and massive homeo-

static shifts of ubiquitous and pleiotropic metabolites.The key event is the increase in hepatic taurocholate, to

be regarded as a marker of intra-hepatic cholestasis. The

reason for taurocholate increasing might be the competitiveactivity of peonidin 3-glucoside and cyanidin 3-glucoside,

shown to be rapidly excreted into the bile (Fig. 4), mostprobably at the level of bile salt efflux transporters BSEP

(ABCB11) and MRP-2 (ABCC2). These ATP-dependent

efflux transporters transport taurocholate into the bile sys-tem (Klaassen and Aleksunes 2010). The increase in

intrahepatic taurocholate must have inhibited the hepatic

uptake of cholate from blood, mediated by basolateralinflux transporters, such as Osta-Ostb (OSTa-OSTb) (Kla-

assen and Aleksunes 2010) and Oatp1 (Slc21a1), Oatp2

(Slc21a5) and Oatp4 (Slc21a10) (St-Pierre et al. 2001).Cholate derives from the hydrolysis of taurocholate, cata-

lysed by ileal microflora; similarly, bacterial dehydrolases

are responsible for the appearance of deoxycholate anddeoxytaurocholate. These secondary bile salts normally

reach the liver via the portal circulation, but, under cho-

lestasis, they can escape into the general circulation and arethen taken up into the kidneys, as confirmed by the data

presented in Table 1. Uptake into the kidneys occurs by

tubular reabsorption catalysed by transporters similar tothose found in the liver (Dawson et al. 2010).

As a consequence of intra-hepatic cholestasis, bile salts

in blood were found to be up-regulated, a finding verysimilar to the rapid rise in total serum bile salts observed

after i.v. administration of hepatotoxic drugs (Kostrubsky

et al. 2003) and in line with the designation as sensitivemarkers of biliary pathology and cholestasis (Ennulat et al.

2010). Bile salts, besides their well-known function in

terms of digestive physiology, are also known to act assignalling molecules coordinating hepatic triglyceride,

glucose and energy homeostasis, therefore playing a role in

the metabolic syndrome, cardiovascular diseases and type 2diabetes (Lefebvre et al. 2009).

Cyanidin 3-glucoside induced intra-hepatic cholestasis

can also justify the finding of decreased blood GSH.Indeed, cholestasis is known to be associated with

decreased plasma GSH species, accompanied by increased

GSH in the kidneys (Purucker et al. 2002). This might bedue to inhibition of hepatic basolateral transporters that

export GSH and oxidised glutathione (GSSG), i.e. Oatp1

and MRP-1 (Ballatori et al. 2009). This hypothesis issupported by the finding of up-regulated GSH in both the

liver and kidneys. The down-regulation of GSSG in both

the liver and kidneys might result from the fact that, undermild cholestasis, GSSG could be exported into the blood by

Fig. 2 Total number of features detected in the blood, kidneys andliver methanol: water (95:5, v/v) tissue extracts using UPLC/QTOF-MS in positive ionisation mode. Numbers in overlapping circlesindicate common features

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the sinusoidal efflux pump MRP-1 (ABCC1) to a largerextent in comparison to GSH. Indeed, the affinity of

MRP-1 for GSSG is 50–100 times higher than for GSH

(Cole and Deeley 2006). The net effect is an apparentincrease of cellular GSH/GSSG in both the liver and

kidneys, thus allowing us to understand why dietary

anthocyanins are cellular antioxidants and protect againstoxidative-based diseases such as cancer, cardiovascular,

neurodegenerative and inflammatory diseases (Ballatori

et al. 2009).A further interesting effect of cyanidin 3-glucoside was

the decrease in blood a-tocopherol. It can reasonably be

surmised that this down-regulation resulted from a lowerrate of transfer of this antioxidant from the liver, the main

player in vitamin E homeostasis (Attilio 2007). It should

be noted that one of the most dynamic mechanisms ofa-tocoferol export from the liver is secretion by the cho-

lesterol-specific ABCA1, an ATP-dependent efflux pump

at the sinusoidal plasma membrane (Attilio 2007). Theabsence of a-tocopherol up-regulation in the liver might be

due to the limits of methanol extraction of metabolitesdissolved in cell membranes; by contrast, methanol seems

effective for the recovery of vitamin E from plasma lipo-proteins. Thus it seems reasonable to postulate that

cyanidin 3-glucoside probably induced an increase in

vitamin E in the liver, the only possible source of plasmaa-tocopherol, since the rats had fasted, thus explaining the

role of anthocyanins as antioxidants.

The up-regulation of phosphatidylethanolamine inplasma, liver and kidneys might result from multiple

mechanisms, including decreased conversion to phospha-

tidylcholine, due to consumption of S-adenosylmethionineto produce peonidin 3-glucoside (Vanzo et al. 2011).

The up-regulation of arachidonic acid is consistent with

the reported inhibition of cyclooxygenase activities bycyanidin 3-glucoside (Adhikari et al. 2005). In this way,

arachidonic acid would not be converted to prostaglandins.

The up-regulated biomakers identified in this study arelikely to be only transiently significant, due to the known

rapid urinary and biliary excretion of cyanidin 3-glucoside

(Vanzo et al. 2011). Such transient effects justify theobservation that only a regular intake of anthocyanin-rich

food confers protection against chronic, oxidative stress-based diseases.

Fig. 3 Positive TIC ion chromatograms of oxidised glutathione detected in the blood (a), kidney (b) and liver (c) extracts together with theircorresponding mass spectra

94 A. Vanzo et al.

123

Author's personal copy

Tab

le1

Dis

crim

inat

ing

com

poun

dsde

tect

edin

the

bloo

d,ki

dney

san

dli

ver

ofra

tsaf

ter

intr

aven

ous

adm

inis

trat

ion

ofcy

anid

in3-

gluc

osid

e(n

=12

)as

com

pare

dto

the

cont

rol

(n=

12)

Com

poun

dM

onoi

soto

pic

mas

sR

eten

tion

(min

)V

aria

ble

(m/z

)V

aria

ble

(m/z

)Is

otop

icpa

tter

nsa

mpl

eaIs

otop

icpa

tter

nst

anda

rdV

IPF

old

chan

geb

Cha

nge

tren

dH

MD

BID

and

shor

tde

scri

ptio

n

Blo

odE

SI?

,V

IP[

1B

lood

Sta

ndar

dB

lood

Sta

ndar

d

Glu

tath

ione

307.

0838

3.45

M?

H[1

?]

308.

0916

M?

H[1

?]

308.

0912

308.

0907

100

%

309.

0929

17%

310.

0887

5%

308.

0912

100

%

309.

0952

15%

310.

0916

8%

2.26

-1.

3;

HM

DB

0012

5co

mpo

und

synt

hesi

sed

from

cyst

eine

,an

impo

rtan

tpa

rtof

the

body

’sto

xic

was

tedi

spos

alsy

stem

Hyo

deox

ycho

lic

acid

392.

2927

46.2

935

7.27

8435

7.27

9135

7.28

0210

0%

358.

2866

28%

359.

2837

5%

357.

2791

100

%

358.

2833

28%

359.

2876

5%

2.25

2.5

:H

MD

B00

733

bile

acid

Pho

spha

tidy

l-et

hano

lam

ine

635.

4526

53.7

948

2.32

3848

2.32

4148

2.32

3610

0%

483.

3286

28%

484.

3336

7%

482.

3241

100

%

483.

3281

28%

484.

3339

7%

1.70

1.1

:H

MD

B08

821

glyc

erop

hosp

holi

pid,

aph

osph

oryl

etha

nola

min

em

oiet

yoc

cupi

esa

glyc

erol

subs

titu

tion

site

a-T

ocop

hero

l43

0.38

1059

.23

430.

3795

430.

3733

429.

3765

100

%

430.

3798

80%

431.

3880

45%

429.

3733

87%

430.

3805

100

%

431.

3863

68%

1.57

-2.

3;

HM

DB

0189

3th

em

ost

acti

vefo

rmof

vita

min

Ein

hum

ans

L-T

rypt

opha

n20

4.08

9816

.31

188.

0703

188.

0711

188.

0706

100

%

189.

0747

18%

190.

0769

2%

188.

0711

100

%

189.

0758

16%

190.

0775

2%

1.40

1.3

:H

MD

B00

929

anes

sent

ial

amin

oac

idw

hich

isth

epr

ecur

sor

ofse

roto

nin

Oxi

dize

dgl

utat

hion

e61

2.15

199.

65M

?H

[1?

]

613.

1596

M?

H[1

?]

613.

1596

613.

1594

100

%

614.

1609

29%

615.

1610

15%

613.

1596

100

%

614.

1667

25%

615.

1580

14%

1.39

-1.

8;

HM

DB

0333

7gl

utat

hion

edi

mer

form

edby

adi

sulfi

debo

ndbe

twee

nth

ecy

stei

nesu

lfhy

dryl

side

chai

ns

Cho

lic

acid

408.

2876

46.8

1M

?N

a[1

?]

431.

2764

M?

Na

[1?

]

431.

2768

431.

2762

100

%

432.

2787

33%

433.

2769

8%

431.

2768

100

%

432.

2808

35%

433.

2824

7%

1.24

1.5

:H

MD

B00

619

maj

orpr

imar

ybi

leac

idpr

oduc

edin

the

live

ran

dus

uall

yco

njug

ated

wit

hgl

ycin

eor

taur

ine

Deo

xych

olic

acid

392.

2927

49.6

235

7.27

7435

7.27

8735

7.28

0710

0%

358.

2805

28%

359.

2802

20%

357.

2787

100

%

358.

2848

28%

359.

2879

5%

1.22

2.6

:H

MD

B00

626

bile

acid

form

edby

bact

eria

lac

tion

from

chol

ate.

Itis

usua

lly

conj

ugat

edw

ith

glyc

ine

orta

urin

e

Kid

neys

ES

I?,

VIP

[1

Kid

neys

Sta

ndar

dK

idne

ysS

tand

ard

Pho

spha

tidy

l-et

hano

lam

ine

635.

4526

53.8

148

2.32

4048

2.32

3848

2.32

4610

0%

483.

3300

28%

484.

3334

5%

482.

3238

100

%

483.

3288

28%

484.

3338

5%

3.06

1.1

:H

MD

B08

821s

eeab

ove

Metabonomic investigation of rat tissues 95

123

Author's personal copy

Tab

le1

cont

inue

d

Com

poun

dM

onoi

soto

pic

mas

sR

eten

tion

(min

)V

aria

ble

(m/z

)V

aria

ble

(m/z

)Is

otop

icpa

tter

nsa

mpl

eaIs

otop

icpa

tter

nst

anda

rdV

IPF

old

chan

geb

Cha

nge

tren

dH

MD

BID

and

shor

tde

scri

ptio

n

Ara

chid

onic

acid

304.

2402

53.5

4M

?H

[1?

]

305.

2475

M?

H[1

?]

305.

2474

305.

2477

100

%

306.

2526

25%

307.

2575

3%

305.

2474

100

%

306.

2513

24%

307.

2545

3%

2.63

1.1

:H

MD

B01

043

poly

unsa

tura

ted,

esse

ntia

lfa

tty

acid

.It

isfo

rmed

bysy

nthe

sis

from

diet

ary

lino

leic

acid

Cho

lic

acid

408.

2876

46.8

5M

?N

a[1

?]

431.

2758

M?

Na

[1?

]

431.

2768

431.

2779

100

%

432.

2795

35%

433.

2957

5%

431.

2768

100

%

432.

2808

35%

433.

2824

7%

2.05

1.8

:H

MD

B00

619

see

abov

e

Deo

xych

olic

acid

392.

2927

49.4

135

7.27

7435

7.27

8735

7.27

8710

0%

358.

2807

20%

359.

2730

5%

357.

2787

100

%

358.

2848

28%

359.

2879

5%

1.47

3.9

:H

MD

B00

626

see

abov

e

Eic

osen

oic

acid

310.

2872

57.0

9M

?H

[1?

]

311.

2938

M?

H[1

?]

311.

2950

311.

2950

100

%

312.

2992

22%

313.

2955

5%

311.

2950

100

%

312.

2999

25%

313.

3062

5%

1.47

-2.

0;

HM

DB

0223

1m

onou

nsat

urat

edom

ega-

9fa

tty

acid

.It

isfo

und

inth

ere

dce

llm

embr

ane

Oxi

dize

dgl

utat

hion

e61

2.15

199.

66M

?H

[1?

]

613.

1589

M?

H[1

?]

613.

1596

613.

1597

100

%

614.

1629

28%

615.

1580

15%

613.

1596

100

%

614.

1667

25%

615.

1580

14%

1.40

-1.

2;

HM

DB

0333

7se

eab

ove

Glu

tath

ione

307.

0838

3.45

M?

H[1

?]

308.

0899

M?

H[1

?]

308.

0912

308.

0904

100

%

309.

0958

17%

310.

0915

8%

308.

0912

100

%

309.

0952

15%

310.

0916

8%

1.35

1.04

:H

MD

B00

125

see

abov

e

Hyo

deox

ycho

lic

acid

392.

2927

46.3

235

7.27

9435

7.27

8735

7.27

9410

0%

358.

2855

28%

359.

2930

7%

357.

2787

100

%

358.

2833

28%

359.

2881

5%

1.18

2.1

;H

MD

B00

733

see

abov

e

Liv

erE

SI?

,V

IP[

1L

iver

Sta

ndar

dL

iver

Sta

ndar

d

Glu

tath

ione

307.

0838

3.45

M?

H[1

?]

308.

0895

M?

H[1

?]

308.

0912

308.

0898

100

%

309.

0947

15%

310.

0914

8%

308.

0912

100

%

309.

0952

15%

310.

0916

8%

5.64

1.2

:H

MD

B00

125

see

abov

e

Pho

spha

tidy

l-et

hano

lam

ine

635.

4526

53.8

248

2.32

2648

2.32

3848

2.32

4610

0%

483.

3300

28%

484.

3334

5%

482.

3238

100

%

483.

3288

28%

484.

3338

5%

3.35

1.1

:H

MD

B08

821

see

abov

e

Oxi

dize

dgl

utat

hion

e61

2.15

199.

69M

?H

[1?

]

613.

1587

M?

H[1

?]

613.

1596

613.

1609

100

%

614.

1624

28%

615.

1588

15%

613.

1596

100

%

614.

1667

25%

615.

1580

14%

2.89

-1.

4;

HM

DB

0333

7se

eab

ove

Ara

chid

onic

acid

304.

2402

53.5

5M

?H

[1?

]

305.

2476

M?

H[1

?]

305.

2474

305.

2477

100

%

306.

2512

25%

307.

2527

5%

305.

2474

100

%

306.

2513

24%

307.

2545

3%

2.60

1.2

:H

MD

B01

043

see

abov

e

96 A. Vanzo et al.

123

Author's personal copy

Tab

le1

cont

inue

d

Com

poun

dM

onoi

soto

pic

mas

sR

eten

tion

(min

)V

aria

ble

(m/z

)V

aria

ble

(m/z

)Is

otop

icpa

tter

nsa

mpl

eaIs

otop

icpa

tter

nst

anda

rdV

IPF

old

chan

geb

Cha

nge

tren

dH

MD

BID

and

shor

tde

scri

ptio

n

Tau

roch

olic

acid

515.

2917

42.3

8M

?N

a[1

?]

538.

2796

M?

Na

[1?

]

538.

2789

538.

2802

100

%

539.

2842

30%

540.

2794

10%

538.

2789

100

%

539.

2834

30%

540.

2808

10%

2.22

1.1

:H

MD

B00

036

abi

leac

id;

the

prod

uct

ofco

njug

atio

nof

chol

icac

idw

ith

taur

ine

Tau

rode

oxy-

chol

icac

id49

9.29

6845

.18

M?

Na

[1?

]

522.

2844

M?

Na

[1?

]

522.

2859

522.

2896

100

%

523.

2906

30%

524.

2874

15%

522.

2859

100

%

523.

2909

30%

524.

2870

15%

1.99

1.1

:H

MD

B00

896

abi

lesa

ltfo

rmed

inth

eli

ver

byco

njug

atio

nof

deox

ycho

late

wit

hta

urin

e,us

uall

yas

the

sodi

umsa

lt

L-G

luta

min

e14

6.06

911.

28M

?H

[1?

]

147.

0765

M?

H[1

?]

147.

0759

147.

0761

100

%

148.

0651

30%

149.

0706

5%

147.

0759

100

%

148.

0818

9%

149.

0822

1%

1.58

1.1

:H

MD

B00

641

one

ofth

e20

amin

oac

ids

enco

ded

byth

est

anda

rdge

neti

cco

de

L-S

acch

arop

ine

276.

1321

1.34

M?

H[1

?]

277.

1405

M?

H[1

?]

277.

1396

277.

1416

100

%

278.

1409

15%

277.

1396

100

%

278.

1448

15%

279.

1547

3%

1.49

1.2

:H

MD

B00

279

inte

rmed

iate

inth

ede

grad

atio

nof

lysi

neby

cond

ensa

tion

ofly

sine

and

alph

a-ke

togl

utar

ate

The

com

poun

dsw

ere

iden

tifi

edby

the

OP

LS

-DA

mod

el(V

IP[

1)an

dby

com

pari

son

ofre

tent

ion

tim

es,

pare

ntm

ass

ions

,m

ass

frag

men

tpa

tter

nsan

dis

otop

icpa

tter

nsw

ith

the

in-h

ouse

stan

dard

data

base

am

/zof

feat

ures

inre

pres

enta

tive

sam

ple

isot

opic

patt

ern

mig

htdi

ffer

tova

riab

les

from

VIP

for*

±3

ppm

bF

old

chan

gew

asca

lcul

ated

from

the

arit

hmet

icm

ean

valu

esof

each

grou

p.A

posi

tive

valu

ein

dica

tes

are

lati

vely

high

erno

rmal

ized

peak

area

ofm

arke

rsin

cyan

idin

3-gl

ucos

ide

test

rats

whi

lea

nega

tive

valu

em

eans

are

lati

vely

low

erno

rmal

ised

peak

area

inte

stra

tsas

com

pare

dto

cont

rol

rats

Metabonomic investigation of rat tissues 97

123

Author's personal copy

This study shows that the markers identified in blood

consistently reflect unbalanced hepatic and renal metabolic

homeostasis. As a consequence, this study deserves to bereplicated in humans, so to assess if a similar panel of

blood biomarkers will be found in the early time window

following the oral administration of cyanidin 3-glucoside atphysiological relevant dose. While biomarkers found in

human fluids might not be easily interpreted in terms of

mechanisms of metabolic unbalance, biomarkers found inrat blood can be more easily understood, given the possi-

bility to relate them to biomarkers identified in rat liver and

kidney. Thus, this study paves the way to further analogousobservations in humans and has therefore an interesting

translational potential.

3.3 Annotation of compounds using the HMDB

Significantly differential variables in positive mode foundby the OPLS-DA model and identified by internal stan-

dards were also annotated using HMDB, as indicated in

Table 1. When the compounds found were protonated,identification using the in-house database and HMDB

matched very well. In cases when adduct was not a proton

but sodium for example, the compound identified by thein-house database was not the best match with HMDB, or

worse still the identifications were false. Finally, annota-

tion using HMDB was impossible in cases when the mol-ecule fragmented and its mass fragment was the

significantly differential variable. Therefore, for reliable

identification of features an internal database on the ana-lytical system is urgently required.

4 Concluding remarks

In this study we found that a small amount of cyanidin

3-glucoside caused some major changes in rat blood, kid-

ney and liver metabolic profile, detected 5 min afterintravenous administration and summarised in Fig. 4.

These alterations seem to stem from blocking of bile salt

efflux transporters in the liver and kidneys. A shift in theredox equilibrium of glutathione species involved both the

liver and the kidneys. Under experimental conditions,

chosen to simulate a normal situation, reduced and oxidisedglutathione were up- and down-regulated respectively, thus

suggesting that endogenous antioxidant cell defence

improved. Furthermore, other biochemical markers werefound, making it possible to conclude that cyanidin

3-glucoside must have had an impact on different meta-

bolic pathways in the mammalian organism. The markersarose because their specific metabolic pathways adapted to

cyanidin 3-glucoside i.v. administration through relatively

slow kinetics. Thus, the identification of markers and thepattern of markers might change on the basis of the

experimental protocol, so tests done by independent labo-

ratories might provide different and even contradictoryresults. For future perspectives, metabonomics is a pow-

erful tool through which alterations in diverse metabolic

pathways connected to nutrition rich in dietary anthocya-nins could be better understood. However, at this stage,

connections between the statistical differences in individ-ual metabolites and metabolic pathways have still to be

elucidated.

Acknowledgments The authors gratefully thank Domenico Masu-ero for his expert assistance in MS analysis. The study was carried outwith support of: the Slovenian Research Agency (project: Z4-2280),the ADP2010 MetaQuality projects, funded by the AutonomousProvince of Trento, Italy and the ‘‘Integrated and Sustainable Vine-Wine Management (GISVI)’’ project (L.R. 26/2010 – Support for theproduction and exploitation of knowledge) funded by the Autono-mous Region of Friuli Venezia Giulia.

References

Adhikari, D. P., Francis, J. A., Schutzki, R. E., Chandra, A., & Nair,M. G. (2005). Quantification and characterisation of cyclo-oxygenase and lipid peroxidation inhibitory anthocyanins infruits of Amelanchier. Phytochemical Analysis, 16(3), 175–180.

Ali, K., Iqbal, M., Korthout, H., Maltese, F., Fortes, A., Pais, M., et al.(2012). NMR spectroscopy and chemometrics as a tool for anti-TNFa activity screening in crude extracts of grapes and otherberries. Metabolomics. doi:10.1007/s11306-012-0406-8.

Attilio, R. (2007). Absorption, transport, and tissue delivery ofvitamin E. Molecular Aspects of Medicine, 28(5–6), 423–436.

Ballatori, N., Krance, S. M., Notenboom, S., Shi, S., Tieu, K., &Hammond, C. L. (2009). Glutathione dysregulation and the

Fig. 4 Scheme of the biochemical steps presumably occurred at thehepatic level and accounting for the appearance of the biomarkerslisted in Table 1. Bile salt export pump (BSEP) and multidrugresistance protein 2 (MRP-2) actively pump taurocholate (TC) intothe bile. Cyanidin 3-glucoside (C3G) and peonidin 3-glucoside (P3G)might also have been actively pumped into the bile, probably byBSEP and MRP-2. As a consequence of this competition, TC mighthave accumulated into the hepatocyte, inhibiting the MRP-2-mediatedefflux of glutathione (GSH, reduced; GSSG, disulfide) as well asuptake of cholic acid (CA) and deoxycholate (DOC) from the blood,mediated by the organic anion transporters Oatp and Oat

98 A. Vanzo et al.

123

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