Variation of glucoraphanin metabolism in vivo and ex vivo by human gut bacteria

Abstract

Glucosinolates, phytochemicals found in cruciferous vegetables, are metabolized to bioactive isothiocyanates (ITC) by certain bacteria in the human gut. Substantial individual variation in urinary ITC excretion has been observed in previous cruciferous-vegetable feeding studies. We hypothesized that individual differences in gut microbial community contribute to the observed variation in glucosinolate metabolism, i.e., gut microbiota composition between high- and low-ITC excreters differ. We recruited 23 healthy individuals and fed them a standardized meal containing 200 g cooked broccoli. 24-h urinary ITC excretion was measured after the meal. Study participants with the highest (n=5) and the lowest (n=5) ITC excretion provided fecal samples for ex vivo bacterial cultivation with 50 μM glucoraphanin, the major glucosinolate found in broccoli. When grown ex vivo, fecal bacteria from the selected high ITC excreters were able to degrade more glucoraphanin than those from the low excreters (P=0.05). However, bacterial fingerprints of fecal and ex vivo culture microbiota revealed no statistically significant differences between the high and low ITC excreters in terminal restriction fragment length polymorphism analysis of the bacterial 16S rRNA gene. In conclusion, glucosinolate degradation by fecal bacteria ex vivo may be associated with in vivo bacterial glucosinolate metabolism capacity but no direct link to specific bacterial species could be established, possibly due to the complexity and functional redundancy of the gut microbiota.

Introduction

Cruciferous vegetables are rich sources of glucosinolates. Isothiocyanates (ITC), the hydrolysis products of glucosinolates produced by plant myrosinase or by bacterial thioglucosidase, have been shown to have anticarcinogenic properties^(1–4). Myrosinase in cruciferous vegetables is deactivated by cooking⁽⁵⁾; therefore, when cooked cruciferous vegetables are consumed, gut bacteria are mainly responsible for ITC production in the human body^(6,7).

Interindividual differences in glucosinolate metabolism have been observed in previous feeding studies. The amounts of ITC excreted in urine varied substantially after participants consumed the same amount of cruciferous vegetables or glucosinolates^(6–11), but much less variation was observed if ITC were consumed directly⁽¹¹⁾. It has been proposed that part of the interindividual difference in glucosinolate metabolism is due to differences in gut bacterial composition. The importance of gut bacteria in glucosinolate metabolism was also confirmed in a feeding study which showed that urinary ITC excretion after cooked cruciferous vegetable consumption decreased significantly when participants were pretreated with oral antibiotics and bowel cleansing⁽⁶⁾. To date, in vitro experiments incubating mixed or pure cultures of bacteria with glucosinolates have confirmed that several bacterial species residing in the human gut, such as Escherichia coli, Bacteroides thetaiotaomicron, Enterococcus faecalis, Enterococcus faecium, Lactobacillus agilis, certain Peptostreptococcus spp. and Bifidobacterium spp., have the ability to metabolize glucosinolates in culture^(12–16). However, to our knowledge, no studies have evaluated glucosinolate conversion ex vivo by human gut bacteria with in vivo data of glucosinolate metabolism (i.e., urinary ITC excretion level in urine) from multiple individuals.

We hypothesized that differences in gut microbiota composition are partially responsible for differences in glucosinolate metabolism. Thus, not only the amount and processing of cruciferous vegetables consumed but also the gut microbiota composition contributes to the host exposure to bioactive ITC. Our aim was to explore the relationship between gut microbiota and glucosinolate metabolism, using terminal restriction fragment length polymorphism (tRFLP) analysis to describe human gut bacterial communities⁽¹⁷⁾. tRFLP takes advantage of the sequence variation of the 16S rRNA gene to generate sequence fragments. The tRFLP pattern, which includes both the number and the size of the tRFLP sequence fragments, is used to characterize the compositional differences in gut bacterial communities.

Specifically, we examined: 1) whether there were differences in fecal microbiota composition between selected high- and low-ITC excreters (based on the urinary ITC excretion level after one standardized broccoli meal) and 2) whether fecal bacteria from the high ITC excreters, compared to those of the low ITC excreters, were able to degrade more glucosinolate ex vivo. Additionally, we also explored the associations between habitual dietary cruciferous vegetable intake and fecal microbiota composition and between habitual dietary cruciferous vegetable intake and urinary ITC-excretion status after a prescribed broccoli dose.

Method

Participant Recruitment and Intervention

We recruited 23 individuals for this pilot study. Participants were healthy adults living in the Seattle area. Exclusion criteria included: 1) medical history of gastrointestinal, hepatic, or renal disorders; 2) pregnancy or lactation; 3) weight loss or gain > 4.5 kg within the past year; 4) major changes in eating habits within the past 3 months; 5) antibiotic use within the past 3 months; 6) current use of prescription medication (including oral contraceptives). This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Institutional Review Board of the Fred Hutchinson Cancer Research Center (FHCRC). Written informed consent was obtained from all participants.

Dietary intake, health and demographic data

All participants completed a self-administered demographic and health questionnaire and two FFQ: a general FFQ developed at FHCRC containing 114 food items and 8 beverage items with portion size estimation and a specific cruciferous vegetable intake FFQ containing 79 cruciferous vegetable items with portion size estimation and cooking method description (Arizona Cruciferous Vegetable FFQ, Arizona Diet and Behavioral Assessment Center, Tucson, AZ). The intakes of major nutrients were estimated from the general FHCRC FFQ based on the Nutrition Data System for Research software (Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN). Raw, cooked, and total cruciferous vegetable intakes were estimated from the Arizona cruciferous vegetable intake FFQ⁽¹⁸⁾. Demographic and health data included parameters such as age, gender, race, weight, height and intestinal health status (diarrhea and constipation).

Broccoli feeding

We instructed participants to avoid any foods or supplements containing cruciferous vegetable components from 3 d before until 24 h after the broccoli feeding. A detailed list of cruciferous vegetables was provided to participants for reference. In this way, all glucosinolate metabolites in urine were expected to originate from the broccoli we provided. All participants ate a standardized mid-day meal that included 200 g cooked broccoli (Food Services of America, Seattle, WA) and 283 g prepared macaroni and cheese (Lean Cuisine, Nestlé USA, Glendale, CA) at the FHCRC Human Nutrition Lab. The broccoli used in this study was purchased as a single lot and stored at −20°C before cooking. 200 g of individual frozen broccoli aliquots were weighed, steamed for 5 min to deactivate myrosinase and stored at −20°C again until the serving day. The frozen steamed broccoli was microwaved for 2 min before being served. A subset of 10 participants (5 with the highest and 5 with the lowest urinary ITC excretion after this broccoli feeding, defined as high- and low-ITC excreters) were selected to repeat the broccoli feeding 1–2 months after the first feeding.

Biological Sample Collection and Processing

Participants collected a fecal sample within 24 h prior to the broccoli feeding. Participants were provided with a collection guide and appropriate fecal collections supplies including a commode (Fisher Scientific, Fair Lawn, NJ) and a small collection vial with scooping spoon as well an outer transport vial (Sarstedt, Nümbrecht, Germany). Participants were asked to put a pea-sized aliquot of feces into a collection tube containing RNAlater solution (Ambion, Austin, TX) and 3 mm glass beads (Fisher Scientific), which helped disperse the feces in RNAlater. RNAlater protects the integrity of nucleic acids in fecal samples at room temperature [⁽¹⁹⁾ and unpublished results from our group]. If the participant completed the collection at home, we asked them to store the sample in the home refrigerator (~4°C) until delivery to the research clinic. For the 24 h following the broccoli meal, participants collected their urine continuously. For the 10 participants that were selected to receive the second broccoli meal, an additional fecal sample and 24-h urine sample were collected from each individual. All procedures remained the same except that participants were required to defecate at FHCRC for the second collection so that the fecal samples could be delivered immediately to the lab for bacteria cultivation. All fecal samples placed in RNAlater were stored at −80°C until DNA extraction. 24-h urine volumes were measured and urine aliquots were stored at −80°C until ITC analysis.

Bacterial Cultivation and Analysis

Fecal bacterial cultivation with glucoraphanin

We used a special cultivation medium designed to provide compounds that bacteria usually utilize in the human gut — a medium used previously for a simulation of the human intestinal microbial ecosystem (SHIME)⁽²⁰⁾. It contained 3 g/l yeast extract (Fisher Scientific), 3 g/l starch (Sigma-Aldrich, St. Louis, MO), 0.5 g/l cysteine (Sigma-Aldrich), 1 g/l arabinogalactan (Sigma-Aldrich), 0.4 g/l glucose (Sigma-Aldrich), 1 g/l xylan (MP Biomedicals, Solon, OH), 1 g/l gastric mucin (MP Biomedicals), 3 g/l proteose peptone (Oxoid, Basingstoke, England) and 2 g/l pectin (Acros Organics, Geel, Belgium). The medium pH was adjusted to 7.0 before incubation.1 g feces was weighed, series-diluted in SHIME medium into 10⁵ dilution, and then inoculated in 1 ml SHIME for ex vivo bacterial cultivation. Samples were incubated either with or without 50 μM glucoraphanin (C₂ Bioengineering, Hovedgaden, Denmark) anaerobically in duplicate using a GasPak 150 System (Becton, Dickinson and Company, Franklin Lakes, NJ) for 24 or 48 h at 37°C. Glucoraphanin was chosen particularly in this study because it is the major glucosinolate found in broccoli. We also added Trace Mineral Supplement and Vitamin Supplement (ATCC, Manassas, VA) into the medium to promote bacteria growth (1:100 v/v dilution). SHIME medium with 50 μM glucoraphanin but without any bacteria served as an abiotic control. After incubation was terminated, the fecal cultures were centrifuged at 20,000 g for 10 min to separate the bacteria from the medium. The supernatants were saved for ITC analysis. The bacterial pellets were stored in RNAlater at −80°C until DNA extraction.

tRFLP (terminal restriction fragment length polymorphism) analysis

We used the tRFLP method based on the bacterial 16S rRNA gene to compare the bacterial community fingerprinting patterns in both fecal samples and ex vivo cultivation samples⁽²¹⁾. RNAlater was removed from the samples by dilution with phosphate buffered saline, centrifugation at 20,000 g for 10 min, and removal of the supernatant. Bacterial genomic DNA was extracted following the methods described previously⁽²²⁾ using the Qiagen stool DNA minikit (Qiagen, Irvine, CA) and physical disruption. Extractions were conducted in triplicate for each fecal sample and singly for each cultivation sample. PCR was performed using bacterial 16S rRNA gene universal primers 27f (FAM labeled) and 519r^(17,23) and PCR conditions and post-PCR treatments were as described previously⁽¹⁷⁾. An aliquot of 20 ng digested DNA from each sample was mixed with formamide and the Genescan ROX 500 size internal standard (Applied Biosystems, Foster City, CA). The samples were run at the FHCRC Genetic Analysis Laboratory on an ABI Prism 3100 Genetic Analyzer in GeneScan mode for tRFLP analysis (Applied Biosystems).

Quantitative PCR

Because the initial bacterial cell numbers and bacterial growth in cultivation culture samples varied, we considered the difference in bacterial cell number in these samples when we compared the bacterial glucoraphanin degradation rates. We used quantitative PCR to estimate the total bacterial 16S rRNA gene copy number in each ex vivo cultivation sample and adjusted the glucoraphanin degradation rate by these numbers. Quantitative PCR was performed on these 20 samples using bacterial 16S rRNA gene universal primers 330f (5'- ACTCCT ACGGGA GGCAGC AGT-3') and 530r (5'-GTATTA CCGCGG CTGCTG GCAC-3') (Invitrogen, Carlsbad, CA). Bacterial genomic DNA from culture samples was amplified using SYBR Green qPCR SuperMix-UDG kit (Invitrogen) on ABI 7900-HT real-time PCR system (Applied Biosystems). Estimation of bacterial 16S rRNA gene copy numbers in these samples was based on the standard curve with different concentrations of bacterial genomic DNA with known 16S rRNA gene copy numbers⁽²⁴⁾.

Glucosinolate and ITC Analysis

ITC and derivatives (“total ITC”) in 24-h urine samples were converted to 1,3-benzodithione-2-thiole via a cyclocondensation reaction and measured by HPLC using an internal calibration of sulforaphane solution^(25–27). Briefly, 100 μl urine sample was incubated with 500 μl 100 mM K₂HPO₄ (pH 8.5) and 600 μl benzene dithiol (1.42 g/l in 2-propanol, Sigma-Aldrich) in a shaking water bath at 65°C for 1 h. A set of sulforaphane (MP Biomedicals) calibration standards (5 – 500 μM), a blank and a quality control sample were treated in the same manner. Chromatographic separation of the cyclocondensation product occurred under gradient conditions on a C18 μBondapak, 150 × 3.9 mm column (Waters Corporation, Milford, MA) which was attached to an 1100 UV-HPLC (Agilent Technologies, Santa Clara, CA). The mobile phase was methanol/H₂O 70:30 (v/v). The UV setting was 365 nm.

To measure the remaining glucoraphanin in the culture medium after 24 or 48 h incubation, 100 μl culture supernatant was treated with 0.1 mg thioglucosidase (Sigma-Aldrich) at 37°C pH 7 for 1 h. Time-series experiments showed that 1 h is enough to convert remaining glucoraphanin in the SHIME medium into sulforaphane (unpublished data from our group). After the thioglucosidase treatment, the cyclocondensation reaction was performed as described above. Because ITC is much less stable than glucosinolates in culture medium [⁽¹⁶⁾ and unpublished results from our group], the ITC produced by bacteria (i.e., sulforaphane from glucoraphanin) during the incubation did not accumulate so the final ITC concentration was negligible. Our pilot study showed that sulforaphane degraded quickly in SHIME media and were hardly detectable after 24 or 48 h incubation. The cyclocondensation products were extracted with 2 ml hexane twice to remove other components in the medium and blown dry under N₂. The residue was reconstituted in 70% methanol and analyzed by HPLC as described above. Freshly prepared glucoraphanin solutions in SHIME medium (5 to 100 μM) were used to generate the calibration curve. They were treated in the same manner as culture supernatant samples.

To measure the glucosinolate and ITC content in the broccoli used for the feeding, 200 g broccoli cooked in the same manner was homogenized with 100 ml of water for 2 h and then 1 g slurry was treated with 1 mg thioglucosidase (Sigma-Aldrich) at 37°C pH 7 for 1 h. Control samples without thioglucosidase were treated in the same manner. After the thioglucosidase treatment, the cyclocondensation reaction was performed as described above. The samples were centrifuged at 20,000 g for 1 min and the supernatants were then subjected to chromatographic analysis as described above.

Statistical Analysis

Student's t-tests were performed to compare age, BMI, 24-h urinary ITC after broccoli feeding, total energy intake, fiber intake (log-transformed), cooked cruciferous vegetable intake (log transformed) and total cruciferous vegetable intake (log-transformed) between the high- (n=5) and the low- ITC excreters (n=5). Fisher's exact tests were performed to compare raw cruciferous vegetable intake (binary coded as 0 = no intake, 1 = some intake) between the two groups.

The proportion of glucoraphanin degraded by bacteria in fecal culture samples (N=10, adjusted by the abiotic control samples, i.e., medium without fecal inoculation) was calculated, divided by the 16S rRNA gene copy number of the sample (determined by quantitative PCR as described above), and then plotted against incubation time. Student's t-tests were used to compare the adjusted glucoraphanin degradation percentage between the 5 fecal culture samples from the high ITC excreters and the 5 fecal culture samples from the low ITC excreters after 24 and 48 h incubation. Stata 9.0 (StataCorp LP, College Station, TX) was used for these statistical analyses. A p-value <0.05 was considered to be statistically significant. All tests were two-sided.

The tRFLP profiles were analyzed as described elsewhere⁽¹⁷⁾. Non-metric multidimensional scaling ordination analysis (NMS), Multi-Response Permutation Procedures (MRPP), Blocked Multi-Response Permutation Procedures (MRBP) and cluster analysis were performed based on the transformed P_i values using PC-ORD (MjM Software Design, Gleneden Beach, OR)⁽¹⁷⁾. Both NMS and cluster analysis were used to assess bacterial community composition of 20 fecal samples (from 10 participants, 2 collections per participant) and 20 fecal culture samples (from 10 participants, after 24 and 48 h incubation), respectively. MRPP was used to test: 1) whether fecal bacterial communities differed between the high- and low-ITC excreters; and 2) whether fecal culture bacterial communities after 48 h incubation differed between the high- and low-ITC excreters. MRBP was used to test: 1) whether fecal culture bacterial communities inoculated with glucoraphanin and without glucoraphanin differed after 48 h incubation; and 2) whether fecal culture bacterial communities incubated with glucoraphanin for 24 h differed from those incubated for 48 h.

In addition, we used linear regression models to assess the relationships between fecal bacterial community structure and habitual cruciferous vegetable intake, and between fecal bacterial community structure and urinary ITC excretion. The dependent variable was the NMS axis value of each fecal sample. The independent variables were cruciferous vegetable intake (log-transformed) or the 24-h urinary ITC excretion after the first broccoli feeding. All models were adjusted for daily energy intake and dietary fiber intake. If any associations between the NMS axis and cruciferous vegetable intake or urinary ITC were found, additional linear regressions were performed. The independent variable was cruciferous vegetable intake or urinary ITC and the dependent variable was the arcsin transformed value of the specific tRFLP peak(s) that was significantly associated with the corresponding axis in the NMS analysis. To determine the putative taxonomic affiliation the identified tRFLP fragment(s) belonging to, the fragment size was compared to the in silico digestion results of the SILVA 100 16S rRNA gene database⁽²⁸⁾ using Fragment Finder⁽²⁹⁾.

Results

Dietary intake, health, and demographic data

23 healthy individuals, ages 20–70 years, participated in this study. All, but one, were non-smokers. In the 10 participants selected for further evaluation (including the only smoker), t tests showed that there were no significant differences in age, BMI, total energy intake, dietary fiber intake, cooked and total cruciferous vegetable intake between the low- and high-ITC excreters. The mean raw cruciferous vegetable intake appears different between the two groups but was not statistically significantly different (P=0.23, Fisher's exact test), probably due to the high within-group variation (Table 1).

TABLE 1.

Demographic, health and dietary intake information of the high- and low-ITC excreters selected based on a standardized broccoli feeding

Variable	Low ITC excreters (n=5)		High ITC excreters (n=5)
	Mean	SD	Mean	SD
Age (year)	35.8	20.1	40.8	18.9
Males, number (%)	3 (60%)		4 (80%)
BMI (kg/m2)	24.9	3.4	23.4	1.9
Total energy (kJ/d)	6617	1246	7010	1329
Fiber (g/d)	20.1	6.2	19.2	4.0
Raw cruciferous vegetable (g/d)	5.7	8.1	14.4	12.4
Cooked cruciferous vegetable (g/d)	40.2	26.1	40.9	24.4
Total cruciferous vegetable (g/d)	45.9	31.3	55.2	31.0
Urinary ITC, 1st collection (μmol)	5.6*	2.7	23.4*	7.5
Urinary ITC, 2nd collection (μmol)	13.4	8.5	16.8	10.9

ITC, isothiocyanate.

^*P<0.01.

Broccoli glucosinolates and ITC

After thioglucosidase treatment, the ITC content in the examined broccoli sample was measured as 0.6 μmol/g, which was translated into approximately 120 μmol of total glucosinolates in the fed broccoli. In contrast, in broccoli samples that were not treated with thioglucosidase, the ITC content was only 0.0015 μmol/g. This confirmed that there was little conversion of glucosinolate to ITC during the homogenizing process of the cooked broccoli, indicating the plant myrosinase had been deactivated by cooking.

Urinary ITC

The inter-batch coefficient of variance for the quality control sample was approximately 6%, indicating good method reproducibility. Urinary total ITC excretion after the first broccoli meal was 12.7 ± 8.0 μmol/24-h for all 23 participants. There was substantial individual variation in the total ITC excretion (range: 1.2 – 34.7 μmol/24-h, approximately 1 – 29% of ingested glucosinolate dose). The 5 high excreters had 23.4 ± 7.5 μmol total ITC excretion /24-h while the 5 low excreters had 5.6 ± 2.7 μmol excretion /24 h (P<0.01). When these selected 10 participants were fed the second broccoli meal, there was no significant difference in 24-h urinary ITC excretion between the two groups (Table 1). This finding is contrary to our expectation.

Glucoraphanin degradation in fecal bacteria culture samples

The fecal bacteria from the low-ITC excreters (N=5) degraded 1.5 ± 1.7 % and 5.6 ± 4.8 % of glucoraphanin after the 24-h and 48-h incubation after correction for degradation in the abiotic control samples, while those of the high-ITC excreters (N=5) degraded 5.0 ± 3.6 % and 13.3 ± 5.9 % of glucoraphanin after the 24 and 48 h, respectively. Students' t-tests showed that, after total bacterial 16S rRNA gene copy number adjustment, there was a significant difference in the proportion of glucoraphanin degraded by bacteria from the high-ITC excreters as compared to the low-ITC excreters after 48 h (P=0.05), but not after 24 h (P=0.09) (Figure 1).

FIGURE 1.

Bacterial degradation of glucoraphanin in SHIME medium. Each line represents a fecal culture sample from one participant. Numbers in the box represent participant numbers. “L” and “H” indicate low- and high-ITC excreter after the first broccoli feeding. Glucoraphanin in the medium was measured indirectly after hydrolysis to ITC. The proportion of glucoraphanin remaining in the medium was corrected by the abiotic control samples (corrected percentage of glucoraphanin left in the medium=observed percentage left in the medium / percentage left in the abiotic control sample) and adjusted by 16S rRNA gene copy number (10⁸ gene copies).

Fecal and culture bacterial community analysis

The final NMS analysis solution of 20 fecal bacterial communities showed that three axes explained a cumulative variation in the dataset of 88% with 32.4%, 12% and 43.6% explained by each of the axes. The fecal bacterial community structure was usually similar within the two collection points of the same participants, i.e., the intra-individual fecal bacterial community remained relatively stable within the 1–2 month period between the two fecal collections. Cluster analysis showed that the two fecal bacterial communities of the same person clustered together for 7 out of 10 participants, with 6 participants showed a similarity of >90% between the two fecal bacterial communities (Figure 2A). However, there was no indication of fecal bacterial community clustering by ITC-excreter status. MRPP confirmed that there was no significant difference between the fecal bacterial community structure of the high- and low-ITC excreters, at either the first collection point (P=0.51) or the second collection point (P=0.81).

FIGURE 2.

Cluster analysis of the bacterial community tRFLP profiles. ▲, high-ITC excreters; Δ, low-ITC excreters. The Wishart's objective function was used to measure the bacterial community difference in the hierarchical dendrogram and was rescaled as % similarity. A) Fecal bacterial samples. The first number of the sample name indicates participant number and the second number of the sample name indicates the collection point (e.g., 1–1 represents sample of participant #1, first fecal collection). B) Ex vivo fecal bacterial culture samples. The first number of the sample name indicates participant number and the second number of the sample name indicates the day of incubation (e.g., 1–1 represents sample of participant #1, 1 d incubation).

NMS analysis of the 20 fecal ex vivo culture bacterial communities showed that two axes explained a cumulative variation in the dataset of 84.8% with 62.6% and 22.2% explained by each of the axes. Cluster analysis showed that the two culture samples of each person clustered more loosely compared to the fecal samples (Figure 2B) and that the fecal culture bacterial community did not cluster by ITC-excreter status (Figure 2A). MRPP confirmed that there was no significant difference between the fecal culture bacterial community structure of the high- and low-ITC excreters (P=0.16). MRBP analysis showed there was no difference between the fecal culture bacterial communities inoculated with glucoraphanin and those without glucoraphanin after 48 h incubation (P=0.53). MRBP also showed that there was no difference between the fecal culture bacterial communities incubated with glucoraphanin for 24 h and those incubated for 48 h (P=0.16).

Regression models showed that NMS axis 3 of the fecal bacterial communities was significantly inversely associated with habitual raw cruciferous vegetable intake (P=0.01, R²=0.37) but not cooked or total cruciferous vegetable intake. There was also a trend toward an association between tRFLP peak 244 bp (which was inversely associated with NMS axis 3) and raw cruciferous vegetable intake (P=0.06, R²=0.26). Through the in silico digestion of the previously sequenced bacterial 16S rRNA genes in the SILVA database, we identified that several bacteria including Alistipes putredinis (one of the most abundant bacterium found in the human gut), certain bacteria in the Lactococcus genus (e.g., Lactococcus lactis and Lactococcus piscium), and certain bacteria in the Desulfovibrio genus (e.g., Desulfovibrio desulfuricans and Desulfovibrio gigas), may represent this tRFLP fragment. No correlation was found between NMS axes of the fecal bacterial communities and urinary ITC excretion.

Discussion

In this pilot study, we examined the association between glucosinolate metabolism and gut bacterial community composition, both in vivo and ex vivo. We showed that: 1) glucoraphanin degradation by fecal bacteria ex vivo differed significantly between the fecal inoculated bacterial culture samples of the high- and low-ITC excreters after 48-h incubation; 2) overall bacterial community structure did not differ significantly between the selected high- and low-ITC excreters, either in fecal samples or in ex vivo fecal culture samples.

After 48-h incubation, fecal bacteria from the high ITC excreters degraded more glucoraphanin than those of the low excreters. We confirmed that the fecal bacteria from the high- as compared to the low-ITC excreters were more effective at metabolizing glucoraphanin, at least for those bacteria that were cultivated ex vivo. Other studies have shown that metabolites other than ITC can be formed from glucosinolates by bacteria^{(15,16,30,31)}. Therefore, in theory, higher bacterial glucosinolate degradation rates do not necessarily always translate into a higher ITC yield and higher ITC exposure for the host. Nonetheless, our results suggest that the capacity to hydrolyze glucoraphanin ex vivo may be related to overall ITC exposure in vivo. Due to the apparent instability of ITC in culture medium, we were unable to establish directly the relation between the ITC production in vivo and the bacterial conversion of glucosinolate to ITC ex vivo.

We did not observe any significant difference in overall fecal or culture bacterial community structure between the high- and low-ITC excreters, although we hypothesized that differences in gut microbiota may contribute to the interindividual variation in glucosinolate to ITC conversion. Several reasons may explain this discordance. Most importantly, there may be functional redundancy in glucosinolate metabolism for gut bacteria, i.e., bacterial species that have the same metabolic function may not be related closely phylogenetically. Previous in vitro studies have observed that bacteria able to hydrolyze glucosinolates belong to several different phylogenetic families, including Actinobacteria, Firmicutes, and Bacteroidetes^(12–16). Phylogenetic analysis of various glucosidase genes also showed that they are not solely attached to one bacterial phylogeny⁽³²⁾. Bacteria belonging to different phylogenetic groups may have relevant genes to code enzymes involved in releasing glucose from complex molecules in gut environment for energy utilization. Lateral gene transfer may also happen between different species. Thus, if different individuals harbor different types of distantly related bacteria having glucosinolate-metabolizing activity, it would be difficult to identify an overall difference in gut microbiota between the high- and low-ITC excreters. Moreover, the tRFLP analysis was based on the bacterial 16S rRNA gene, not functional genes involved in glucosinolate metabolism. This may explain in part why we did not find an association between the urinary ITC amount and the fecal microbiota NMS axis values, or a specific tRFLP fragment. Although the 16S rRNA gene is the best phylogenetic biomarker to examine community composition, it may not directly reflect the difference in gut bacterial glucosinolate metabolism among individuals.

The natural interindividual difference in gut microbiota may also conceal the difference between the two groups of low and high ITC-excreters. The tRFLP fingerprinting method applied in this study offered us a rapid and efficient snapshot of gut microbiota, yet it may not provide sufficiently fine resolution of this complex community. The relatively subtle differences of a few species out of hundreds of members in the community among individuals may need to be resolved by more comprehensive and thorough techniques, such as sequencing. Finally, besides the gut bacterial composition, other factors may have influenced glucosinolate metabolism^(11,33). The bioavailability of glucosinolate could be different when different processing and cooking methods are adapted⁽³⁴⁾. ITC may be further degraded by bacteria^(16,35) Polymorphisms in glutathione S-transferase genes influence the disposition of ITC in the body and thus ITC excretion in the urine^(36–39). Despite our efforts to minimize the variation of some of these factors in the study, we also observed variation in total ITC excretion within the same participant after the two broccoli feedings. Interestingly, for the four participants who had the greatest difference in urinary ITC excretion between the two broccoli feedings (participants #1, 11, 13 and 15), three of them (#1, 11 and 13) also showed the substantial changes in fecal bacterial community during the period between the two feedings (Figure 2A). These results suggest that the variation in ITC excretion may not be explained just by random variation, but that fluctuations in gut microbiota composition may contribute to the variation of in vivo glucosinolate metabolism. This supports the hypothesis that gut microbiota composition influences glucosinolate metabolism.

In this study, we observed an association between the habitual raw cruciferous vegetable intake and one NMS axis (axis 3), more specifically, bacteria that represented tRFLP fragment 244 bp. However, no studies have examined the role of Lactococcus bacteria, Desulfovibrio bacteria or Alistipes putredinis, the putative species representing this tRFLP fragment, in glucosinolate metabolism. One possible explanation is that gut bacteria might be exposed to higher level of ITC when raw cruciferous vegetables are consumed by the host compared to the cooked cruciferous vegetables, because partial degradation of glucosinolate by plant myrosinase may happen before it reaches the colon. Whether these species have a role in further utilizing ITC compounds in human gut need to be further examined. Desulfovibrio bacteria are sulfate-reducing bacteria, which utilize sulfate as their terminal electron acceptor for energy production⁽⁴⁰⁾. Sulfate formed during the metabolism of sulfur-containing compounds (e.g., glucosinolates and isothiocyanates) in cruciferous vegetables may serve as the substrates for these bacteria and promote their growth in human gut. It is also possible that other constituents in cruciferous vegetables (e.g., carbohydrates that can be utilized by Lactococcus and Alistipes putredinis) or even other dietary behavior associated with raw cruciferous vegetable consumption lead to this observed association between this tRFLP fragment and the habitual raw cruciferous vegetable intake.

Our study has several strengths. To our knowledge, this is the first human study that examines the relationships between gut microbiota composition, ITC production, and cruciferous vegetable intake within the same group of individuals. Habitual cruciferous vegetable intakes were estimated more precisely by using a validated cruciferous vegetable-specific FFQ⁽¹⁸⁾. Potential confounding factors such as total energy and fiber intakes were adjusted in the regression models. The amount of broccoli fed and cooking procedures were well controlled. Participants consumed all the broccoli provided under supervision of the study staff and reported no other cruciferous vegetable consumption 72 h before and during the urine collection; this helped to normalize glucosinolate intake across all participants. Glucoraphanin, the glucosinolate we used in the ex vivo incubation, is the major glucosinolate found in broccoli. Unlike some of the previous in vitro bacterial incubation studies which used glucosinolate concentrations in the range of 1 to 15 mM^(16,30,31); the concentration we used, 50 μM, could more accurately reflect luminal concentrations expected after consumption of 120 μmol glucosinolates. We used tRFLP, a high throughput molecular fingerprinting approach and geometric analysis methods to characterize the fecal and culture bacterial communities. These analyses offered rapid yet reliable data for a picture of overall community composition. Additionally, we were also able to link putative bacterial species to specific tRFLP fragments based on the available bacterial 16S sequences.

We recognize that energy intake and cruciferous vegetable intake collected through FFQ may be subject to recall bias which might lead to either over- or under-estimation of the strength of association between dietary intake and the biological measurements. Using SHIME medium for bacterial cultivation might be considered both a strength and a limitation of this study. SHIME medium was formulated to mimic substrate available to bacteria in the human gut and therefore maximize gut bacterial growth⁽²⁰⁾. In this regard, addition of glucoraphanin may not have been a sufficient enough perturbation in the substrate pool to select for glucosinolate-metabolizing bacteria. This may partially explain why we did not observe overall differences in gut bacterial communities between the fecal culture samples incubated with and without glucoraphanin. There are several other limitations to this study. The small sample size likely limits our ability to find existing differences in gut microbiota composition between the two ITC excreter groups. Nonetheless, this study further demonstrates the complexity of the human gut microbiota, both in terms of community composition as well as metabolic capacity. There are also large differences between the in vivo bacterial metabolism and in vitro bacterial incubation model. Because ≤30% of gut bacterial species can be cultivated and due to the lack of food-food interactions⁽⁴¹⁾, observations in vitro need to be carefully evaluated before links can be established to the in vivo results. Also, fecal samples differ in gut bacterial composition as compared to luminal contents. Bacterial community composition changes along the digestive tract and between different environments such as intestinal mucosa and lumen. Nonetheless, because the variation in gut bacterial community within a person is much less than the variation between individuals, fecal samples remain the best available samples for studies in healthy, intact humans⁽⁴²⁾.

In summary, we observed significant differences in the proportion of glucoraphanin degraded ex vivo by fecal bacteria obtained from high- and low-ITC excreters who were identified based on a standardized broccoli meal. However, no difference was observed in bacterial community structure between the two groups, either in fecal samples or ex vivo fecal bacterial cultivation samples. We also identified putative gut bacterial species that may be associated with raw cruciferous vegetable intake. More intensive bacterial sequencing may help further elucidate the community composition and possible differences that cannot be revealed by tRFLP fingerprinting. Identification of gut bacterial species associated with the conversion of glucosinolates to ITC may inform prebiotic and probiotic strategies to alter production of ITC in vivo, allowing individuals to derive more health benefits from cruciferous vegetable consumption.

Abbreviations used

FHCRC

Fred Hutchinson Cancer Research Center

ITC

isothiocyanate

MRBP

blocked multi-response permutation procedures

MRPP

multi-response permutation procedures

NMS

non-metric multidimensional scaling ordination

tRFLP

terminal restriction fragment length polymorphism