Diet, microbiota, and microbial metabolites in colon cancer

Diet,microbiota,and microbial metabolites in colon cancer risk in rural Africans and African Americans1–4

Junhai Ou,Franck Carbonero,Erwin G Zoetendal,James P DeLany,Mei Wang,Keith Newton,H Rex Gaskins,

and Stephen JD O’Keefe

ABSTRACT

Background:Epidemiologic studies have suggested that most cases of sporadic colon cancer can be attributed to diet.The recognition that colonic microbiota have a major in?uence on colonic health suggests that they might mediate colonic carcinogenesis. Objective:To examine the hypothesis that the in?uence of diet on colon cancer risk is mediated by the microbiota through their me-tabolites,we measured differences in colonic microbes and their metabolites in African Americans with a high risk and in rural native Africans with a low risk of colon cancer.

Design:Fresh fecal samples were collected from12healthy Afri-can Americans aged50–65y and from12age-and sex-matched native Africans.Microbiomes were analyzed with16S ribosomal RNA gene pyrosequencing together with quantitative polymerase chain reaction of the major fermentative,butyrate-producing,and bile acid–deconjugating bacteria.Fecal short-chain fatty acids were measured by gas chromatography and bile acids by liquid chromatography–mass spectrometry.

Results:Microbial composition was fundamentally different,with a predominance of Prevotella in native Africans(enterotype2)and of Bacteroides in African Americans(enterotype1).Total bacteria and major butyrate-producing groups were signi?cantly more abundant in fecal samples from native Africans.Microbial genes encoding for secondary bile acid production were more abundant in African Amer-icans,whereas those encoding for methanogenesis and hydrogen sul-?de production were higher in native Africans.Fecal secondary bile acid concentrations were higher in African Americans,whereas short-chain fatty acids were higher in native Africans. Conclusion:Our results support the hypothesis that colon cancer risk is in?uenced by the balance between microbial production of health-promoting metabolites such as butyrate and potentially car-cinogenic metabolites such as secondary bile acids.Am J Clin Nutr2013;98:111–20.

INTRODUCTION

There are wide geographic variations in colorectal incidence around the world,and most of these differences have been at-tributed to diet(1).Within the continental United States,the African American population shoulders the major burden,with an incidence of w65:100,000and a death rate of25:100,000

(2).In sharp contrast,rural Africans rarely get the disease

(3).Studies of ours have ascribed this difference to higher meat and fat intakes in Americans and to higher resistant starch in-takes in Africans(4).

Colonic microbiota are dependent on dietary residues that escape small intestinal digestion and absorption.Consumption of a normal balanced diet predominantly yields carbohydrate res-idues such as?ber,which stimulates saccharolytic fermentation and the production of the health-promoting short-chain fatty acids(SCFAs)5acetate,propionate,and butyrate.Butyrate is the preferred energy source for the colonic mucosa,and all3 SCFAs have antiin?ammatory and antiproliferative properties (5).Consumption of an unbalanced diet rich in meat and low in ?ber increases the delivery of proteinaceous residues,which promote proteolytic fermentation with the production of am-moniac compounds and branched-chain fatty acids,which are in?ammatory and may enhance colon cancer risk(5,6).

The in?uence of dietary fat on cancer risk may also be de-termined by microbial metabolism,because it increases the hepatic synthesis of bile acids(BAs)and the quantity of BAs that escape the enterohepatic circulation and enter the colon.This provides substrate for microbes with7a-dehydroxylating en-zymes,which convert primary BA into secondary BAs,which are proin?ammatory and have carcinogenic properties(7). Digestion of food is fundamentally different in the small and large intestine.In the small intestine,the enzymic digestion rate is determined by substrate concentrations,according to the Michaelis-Menten equation.In the colon,the fermentation rate is 1From the Department of Gastroenterology,Hepatology and Nutrition, School of Medicine,University of Pittsburgh,Pittsburgh,PA(JO and SJDO); the Departments of Animal Sciences(FC)and Food Science and Human Nutrition(MW),University of Illinois at Urbana–Champaign,Urbana,IL; the Laboratory of Microbiology,Wageningen University,Wageningen,Neth-erlands(EGZ);the Department of Medicine,Division of Endocrinology and Metabolism,University of Pittsburgh,Pittsburgh,PA(JPD);the Department of Gastroenterology,Nelson R Mandela School of Medicine,University of KwaZulu,Natal,South Africa(KN);and the Department of Animal Sci-ences,Division of Nutritional Sciences,Department of Pathobiology,Insti-tute for Genomic Biology and University of Illinois Cancer Center, University of Illinois at Urbana–Champaign,Urbana,IL(HRG).

2JO and FC contributed equally to this work.

3Supported by Public Health Service grant CA-135379from the NIH.

4Address reprint requests and correspondence to SJD O’Keefe,Depart-ment of Gastroenterology,University of Pittsburgh,570Scaife Hall,3550 Terrace Street,Pittsburgh,PA15213.E-mail:sjokeefe@https://www.sodocs.net/doc/381396194.html,.

5Abbreviations used:BA,bile acid;CA,cholic acid;LC,liquid chromatog-raphy;LCA,lithocholic acid;MS,mass spectrometry;qPCR,quantitative poly-merase chain reaction;rRNA,ribosomal RNA;SCFA,short-chain fatty acid. Received December19,2012.Accepted for publication April5,2013. First published online May29,2013;doi:10.3945/ajcn.112.056689.

Am J Clin Nutr2013;98:111–20.Printed in USA.ó2013American Society for Nutrition111

complex,termed autocatalytic,and is determined by using both the substrate concentration and the microbe concentration.In autocatalytic reactions,the maximal rate of reaction occurs at an intermediate,rather than at the highest,reactant concentration (8).Thus,SCFA and secondary BA production is codetermined by the microbiota composition.

To test our hypothesis that the higher risk of colon cancer in African Americans than in native Africans is related to the in-?uence of their diet on the microbiota composition and metabolic activity,we measured the differences in microbiota composition and speci?c bacteria known to in?uence SCFA and secondary BA production in fecal samples from these2populations. SUBJECTS AND METHODS

Study design

The relative contents of SCFAs,BAs,and microbes of speci?c interest were measured in fresh fecal samples from2populations of varying colon cancer risk,namely high-risk African Ameri-cans(Americans)and low-risk rural Africans(Africans)(3). Middle-aged subjects were selected because colon cancer affects that group most.Microbial analysis was?rst untargeted,based on high-throughput16S ribosomal RNA(rRNA)pyrosequencing, and secondly targeted based on quantitative polymerase chain reaction(qPCR)to measure numbers of microbes of speci?c interest,which included the major butyrate producers Faecali-bacterium prausnitzii,Clostridium cluster IV,and XIVa(9);the major starch fermenters Succinivibrio spp.and Prevotella spp.

(10);the Bacteroides fragilis group,lactic acid bacteria,and Lactobacillus spp.(11);and Bifdobacterium spp.(12).Finally, a functional gene analysis was performed to compare the po-tential for butyrogenesis,methanogenesis,hydrogen sul?de production,and secondary bile salt conversion.

Study populations

Normal healthy volunteers of either sex aged50–65y were selected on the basis of their medical history and results of a medical examination.African Americans rather than white Americans were chosen because their risk of colon cancer is higher and there is more genetic similarity.Subjects with a history of gastrointestinal disease or surgery were excluded, as were those with a history of antibiotic use within the past 6wk.First-morning fecal samples were collected from12 healthy Americans in the Pittsburgh area and from12age-, sex-,and BMI-matched Africans from a rural area outside the town of Empangeni in the KwaZulu-Natal Province of South Africa(Table1).Our earlier study showed that the dietary intake patterns of these2populations were widely different, with Americans consuming twice as much protein and3times as much fat[mean(6SEM)protein:9469compared with 5864g/d;mean(6SEM)fat:114611compared with386 3g/d](4).The protocol was reviewed and approved by the Institutional Review Boards of the University of Pittsburgh and the University of KwaZulu-Natal(Biomedical Research Ethics Committee).Materials

All BA and SCFA analytic chemicals were purchased from

Sigma-Aldrich.qPCR primers for different bacteria were syn-

thesized by Sigma-Aldrich.qPCR master mix was purchased

from Applied Biosystem.An Econo-Cap EC-1000gas chro-

matographic capillary column was purchased from Grace

Davison Discovery https://www.sodocs.net/doc/381396194.html,lex-GS0.22-m m syringe?lters

were purchased,and microconcentrators were purchased from

Millipore.The Luna C18column(3m m,2.0-mm internal di-

ameter3150mm)was purchased from Phenomenex.

Fecal collection,preservation,and transport

Freshly voided fecal samples were collected immediately into

airtight plastic vials and were transported on ice to be stored frozen

at2808C within2h.The samples collected in South Africa were

air-couriered frozen on dry ice to Pittsburgh for analysis. SCFA assay

Fecal samples(0.1g)were transferred into plastic tubes;2,2-

dimethylbutyric acid was added at1mmol/L as internal standard.

After undergoing vortex mixing and centrifugation(19003g,

10min),the supernatant?uid was?ltered through a Millex-GS

0.22-m m syringe?lter unit(Millipore).The solution was re?ltered

through a microconcentrator(Ultracel YM-10;Millipore)with

a molecular mass cutoff of10,000Da,by centrifugation(70003g

at48C for1.5h).The?ltrate was then analyzed by using an

Agilent Technologies6890N Network GC System with a?ame-

ionization detector for SCFA based on the method described by

Scheppach et al(23).Compounds were separated on a Grace

EC-1000(15m in length,1.20-m m?lm thicknesses,0.53mm

internal diameter)capillary column(Grace Davison Discovery

Science).The oven temperature of the gas chromatograph was

programmed at5min from808C to1758C,which was held for10min

with a total running time of25min.The temperatures of both

the detector and injector were2008C.The inlet was operated in

a splitless mode.High-purity helium was used as carrier gas.

A mixed-SCFA standard solution was prepared by using high

purity(.99%)reagents(Sigma).SCFA concentrations were

computed by using a peak area ratio of the sample pro?le rel-

ative to the internal standard.A good linear correlation was

found between the peak area ratio and the corresponding stan-

dard SCFA(r2.0.99for all SCFAs).The interday and intraday CVs ranged from2.4%to3.9%.This method does not separate

2-methylbutyric and isovaleric acids.

BA assay

Fecal BA concentrations were measured by using the method

described by Tagliacozzi et al(24),except that quanti?cation was

carried out by using liquid chromatography(LC)–mass spec-

trometry(MS)as opposed to LC-tandem MS.A125-m L colonic

evacuate was mixed with400m L acetonitrile,followed by1min

of vortex mixing.After15min of centrifugation at13,0003g,

450m L supernatant?uid was transferred to an autosampler vial

and blown to dryness with nitrogen.The residue was dissolved

with125m L methanol and water(1:1).Ten microliters of this

solution was injected into a Shimadzu HPLC-MS(model

2010A)for quanti?cation by using electrospray ionization in

112OU ET AL

negative ion mode by monitoring the(M-H)2ion.The analytic conditions for LC-MS were as follow:column,Luna3u,C18, 100A(2.0-mm internal diameter3150mm;Phenomenex); mobile phase A:20%acetonitrile-water containing10mmol ammonium acetate/L;mobile phase B:80%acetonitrile-water, gradient program;mobile phase B:0–6min15%,20min30%, 30min60%,40min80%,45min15%;?ow rate:0.2mL/min; column temperature:408C;probe voltage:4.5kv;curved des-olvation line temperature:2308C.BA concentrations were cal-culated based on standard curves run with each sample set. Microbial identi?cation

DNA isolation

Fecal bacterial DNA was isolated and puri?ed with the QIAamp DNA Stool Mini Kit(Qiagen)in combination with a bead-beating step(30s at30Hz3times)by using the FastPrep-24System (MP Biomedicals),as described by Zoetendal et al(25).

Microbiota composition

Samples for454FLX pyrosequencing were ampli?ed with universal forward519F(5#-Fusion A-Barcode-CAGCMGCC-GCGGTAATWC-3#)and reverse926R(5#-Fusion B-Barcode-CCGTCAATTCMTTTRAGTT-3#)primer pairs(Roche).PCR reaction mixtures were set up with the TopTaq PCR kit(Qiagen) according to the manufacturer’s recommendations with10 pmol/L each of forward and reverse primers in25m L reaction. Ampli?cation was carried out with30cycles of thermal program (denaturation,958C for30s;annealing,558C for45s;and ex-tension,728C for60s).All amplicons were gel-excised,con-centrated,and puri?ed with the Gel extraction kit(Qiagen),and

TABLE1

Real-time quantitative polymerase chain reaction primers used to determine the density of speci?c microbes and functional microbial genes

Target group and primer Sequence(5#-3#)

Annealing temperature Reference 8C

All bacteria60(13)

Uni331F TCCTACGGGAGGCAGCAGT

Uin797R GGACTACCAGGGTATCTATCCTGTT

Butyrate-production gene(BcoA)60(14)

BcoA-F GCIGAICATTTCACITGGAAYWSITGGCAY ATG

BcoA-R CCTGCCTTTGCAATRTCIACRAANGC

Clostridium cluster IV150(15)

Sg-Clept-F GCACAAGCAGTGGAGT

Sg-Clept-R3CTTCCTCCGTTTTGTCAA

Costridium cluster XIVa150(15)

g-Ccoc-F AAATGACGGTACCTGACTAA

g-Ccoc-R CTTTGAGTTTCATTCTTGCGAA

Bi?dobacterium spp.60(16)

Bif164F GGGTGGTAATGCCGGATG

Bif662R CCACCGTTACACCGGGAA

Succinivibrio60(17)

SucDex1F CGTCAGCTCGTGTCGTGAGA

SucDex1R CCCGCTGGCAACAAAGG

Prevotella spp.60(17)

PreGen4F GGTTCTGAGAGGAAGGTCCCC

PreGen4R TCCTGCACGCTACTTGGCTG

Bacteroides fragilis group60(15)

g-Bfra-F ATAGCCTTTCGAAAGRAAGAT

g-Bfra-R CCAGTATCAACTGCAATTTTA

Lactobacillus spp.60(18)

LactoF TGGAAACAGRTGCTAATACCG

LactoR GTCCATTGTGGAAGATTCCC

Faecalibacterium prausnitzii60(19)

FpF CCCTTCAGTGCCGCAGT

FpR GTCGCAGGATGTCAAGAC

Functional gene for hydrogen sul?de60

DSR1F+ACSCACTGGAAGCACGGCGG(20)

DSR-R GTGGMRCCGTGCAKRTTHG(20)

Functional gene for methanogenesis60

mcrA-F TTCGGTGGATCDCARAGRGC(21)

mcrA-R GBARGTCGW AWCCGTAGAATCC(21)

Functional gene for secondary bile acids60

BaiCD-F CAGCCCRCAGATGTTCTTTG(unpublished

observation)2

BaiCD-R GCATGGAATTCWACTGCYTC

1Number indicates phylogenetic cluster of Clostridium as de?ned by Collins et al(22).

2J Ou,A Heather,J Riddlon,S Curry,and SJD O’Keefe,April2012.

MICROBIOTA AND METABOLITES IN COLON CANCER RISK113

amplicon concentrations were measured with a Qubit?uorom-eter(Invitrogen).A454FLX Titanium was used for454py-rosequencing(454Life Sciences;Roche Applied Science).The paired-end pyrosequencing services were provided by Roy J Carver Biotechnology Center,University of Illinois.A total of 248,59416S rRNA sequences(also referred to as16S pyrotags) were obtained from the454Titanium pyrosequencing run.The 16S pyrotags were sorted based on their respective barcodes and handled by using the QIIME pipeline(26).RDP Classi?er was used for taxonomic assignments of the aligned16S pyrotags at the 95%con?dence level(27).

Real-time quantitative PCR

qPCR was performed with a7900HT Fast Real-Time PCR System(Applied Biosystem).16S rRNA gene-speci?c primers were used to target total and speci?c bacteria(F.prausnitzii, Clostridium cluster IV and XIVa,Lactobacillus spp.,Succini-vibrio spp.,Prevotella spp.,B.fragilis group,and Bifdobacte-rium spp.)(Table1).Cloned16S rRNA genes were used to construct standard curves:Clostridium leptum29065(represent-ing Clostridium cluster IV),Clostridium coccoides(representing Clostridium cluster XIVa),Clostridium sindense,Bi?dobacterium longum15707,Lactobacillus delbrueckii12315,Succinivibrio dextrinosolvens19716,Prevotella ruminicola19189,B.fragilis 25285,and F.prausnitzii27766(also a member of Clostridium cluster IV)(obtained from the American Type Culture Col-lection)were cultured on reinforced clostridial medium broth and incubated at378C in an anaerobic chamber.Genomic DNA was extracted from a2-mL culture by using the QIAamp DNA stool mini kit(Qiagen),and bacterial16S rRNA genes were ampli?ed with their respective primers(Table2).PCR prod-ucts were puri?ed by using the MinElute PCR puri?cation Kit (Qiagen)and cloned into pCR2.1TOPO vector with a TOPO-TA cloning kit(Invitrogen).Plasmid DNA was isolated with a QIAprep Spin Miniprep kit(Qiagen),and plasmid DNA concentrations were measured spectrophotometrically(Nano-Drop1000;Thermol Scienti?c).The number of target gene copies was calculated from the mass of DNA with consider-ation of the size of insert and plasmid.The plasmid standard for sulfate-reducing bacteria was obtained from a previous study(28).

Functional microbial genes

In the context of microbial metabolite production,analysis of functional genes rather than taxonomic groups based on the16S rRNA gene allows better quanti?cation(29).Thus,we also examined differences in the abundance of genes encoding the enzymes responsible for butyrate production,secondary BA synthesis,methanogenesis,and hydrogen sul?de production.The butyryl-coenzyme-A-CoA transferase(BcoA)gene was used for quanti?cation of butyrate producers(14).For secondary BA conversion potential,we measured the baiCD gene,which en-codes the enzyme that dehydroxylates the7a-hydroxy group in primary BAs to form secondary BAs(30).To compare meth-anogenic potential,we measured the gene that encodes the enzyme methyl coenzyme-M reductase(mcrA),which cata-lyzes the crucial removal of hydrogen produced from fer-mentation into methane(31).Finally,we measured the gene encoding the enzyme dissimilatory(bi)sul?te reductase(dsrA) that catalyzes a step in the reduction of inorganic sulfate to hydrogen sul?de(32).

The primer sequences are listed in Table1.All PCR experi-ments were done in triplicate with a reaction volume of10m L by using MicroAmp optical384-well reaction plates sealed with MicroAmp optical adhesive?lm(Applied Biosystems).Each reaction contained5m L2ΧPower SYBR Green PCR Master mix(Applied Biosystems),1m L bovine serum albumin(New England Biolabs)at1mg/mL(?nal concentration:100m g/mL), 0.5m M of each primer,and2m L template DNA.The cycling conditions were as follows:508C for2min and958C for10min followed by40cycles of958C for15s,primer-speci?c an-nealing temperature(Table1)for20s,and728C for45s.After ampli?cation,a dissociation step was included to analyze the melting pro?le of the ampli?ed products.Ten-fold dilution se-ries of the plasmid standard for the respective bacterial group or species were run along with the samples.Sample DNA con-centrations were calculated by using standard curves of the di-luted standards containing the respective gene target for each set of primers.Data analysis was processed with SDS v2.3software supplied by Applied Biosystems.

Statistical analysis

Statistical analysis was conducted by using SPSS16.0(SPSS Inc).The signi?cance of group differences for normally dis-tributed data was assessed with Student’s t test.The non-parametric data were analyzed with a Mann-Whitney U test.The signi?cance of the association was evaluated with Spearman’s rank correlation test.A level of P#0.05was accepted as statistically signi?cant.Data are presented as means6SEs. Pyrosequencing data were analyzed by several multivariate ordinations(principal component analyses,nonmetric multidi-mensional scaling),Kruskal-Wallis independent tests,and mul-tivariate ANOV A with Bonferroni correction.

RESULTS

Body weight and BMI were similar between the2groups (Table2).Four of the12Americans were obese[ie,BMI (in kg/m2).30],as were5of the12Africans.The compo-sition of the fecal microbiota,as shown by pyrosequencing analysis,was fundamentally different between Africans and Americans,as summarized in Figure1.Nonmetric multidi-mensional scaling showed an unequivocal distinction(multi-variate ANOV A:P,0.01)between the2groups based on their fecal microbiota(Figure1).This difference appeared to override interindividual differences between the groups shown in Figure 2.The most distinct feature was a predominance of Prevotella species in most Africans and Bacteroides in most Americans (Figure2).Thus,Africans correspond to enterotype1and Americans to enterotype2.Africans also had higher proportions

TABLE2

Demographic data of the research subjects

Female Male Age Weight BMI

y kg kg/m2

Native Africans845761.918064.73262.4 African Americans935862.57464.02861.8 1Mean6SEM(all such values).

114OU ET AL

of Succinivibrio and Oscillospira —microbes that might be in-volved,such as Prevotella —in starch,hemicellulose,and xylan degradation (Figure 3)(33,34).The African gut microbiota were also characterized by a large number of sequences that could not be af?liated to reference taxa.Less than one-third of the taxa was detected in comparable abundance between the groups.The American gut microbiota were characterized by a greater abundance of potentially pathogenic proteobacteria (Escherichia ,Acinetobacter ).Interestingly,the American gut microbiota were more diverse (Simpson index:0.7compared with 0.8;P =0.04),which presumably re?ects consumption of a more diversi?ed diet.

The targeted qPCR analysis showed that total bacteria,Prevotella spp.,Succinivibrio spp.F .prausnitzii,Clostridium cluster IV ,and Clostridium cluster XIVa bacterial counts were all signi?cantly higher in the fecal samples from Africans,but Lactobacillus spp.were more abundant in Americans (Table 3).With regard to functional gene analysis,the gene-encoding secondary BA production (baiCD )was detected in greater abundance in African Americans,whereas the functional genes targeting butyrate producers (BcoA ),methane producers (mcrA ),and hydrogen sul?de producers (dsrA)were more abundant in native Africans.

The chief SCFA products of saccharolytic fermentation,acetate,propionate,and butyrate were signi?cantly higher in stool samples from Africans (P ,0.05;Figure 4),whereas the products of proteolytic fermentation,namely the branched SCFAs isobutyric and 2-methylbutyric/isovaleric acids,

were

FIGURE 1.Illustration of the marked phylogenic differences in microbiota composition between AAs (n =12)and NAs (n =12)detected by 16S-rRNA-based taxonomic pyrosequencing.Nonmetric multidimensional scaling shows strong clustering (multivariate ANOV A:P ,0.01)according to ethnic group.AA,African American;NA,native African;rRNA,ribosomal

RNA.

FIGURE https://www.sodocs.net/doc/381396194.html,position was dominated by Bacteroides in the 12AAs,which indicated that they belonged to enterotype 1,and was dominated by Prevotella in the 12NAs,which categorized them as enterotype 2(10).AA,African American;NA,native African.

MICROBIOTA AND METABOLITES IN COLON CANCER RISK 115

signi?cantly higher in Americans (isobutyrate:1.7360.26com-pared with 1.2260.24m mol/g feces,P =0.02;2-methylbutyric/isovaleric acid:1.4960.19compared with 0.3360.19m mol/g feces,P =0.0002;Mann-Whitney U test).To assess the relation between production of SCFAs and the abundance of speci?c microbial groups,correlation analyses of fecal components were performed.The results showed that the total bacterial abundance was signi?cantly correlated (P ,

0.05;

FIGURE 3.Illustration of the similarities and differences in fecal microbial taxa between AAs and NAs.The solid circle encloses the taxa that were detected in NA and the dotted circle those identi?ed in AA.The overlap between the 2circles contains taxa common to both populations.Much of the shared taxa were signi?cantly (independent Kruskal-Wallis tests)more enriched in one group than in the other,indicated by the boxed text in AAs on the left and underlined text in NAs on the right.AA,African American;NA,native African.

TABLE 3

Bacterial abundance in fecal samples from native Africans and African Americans 1

Native African

African American P value gene copies/g feces gene copies/g feces Total bacteria

7.13101164.531010* 1.83101166.3310100.046Butyrate-production gene (BcoA) 5.43101061.131010* 1.43101062.731090.022Faecalibacterium prausnitzii 1.6310962.73108*8.3310862.731080.038Clostridium cluster IV 5.1310968.73108* 2.9310967.331080.032Clostridium cluster XIVa 9.5310961.73109* 5.1310969.331080.049Succinivibrio spp. 1.1310866.43107* 4.5310661.331060.021Prevotella spp.

8.23101061.431010* 3.53101066.431090.011Bacteroides fragilis group 5.7310961.63106 4.43101061.331070.177Lactobacillus spp. 5.9310663.43106*7.1310765.731070.021Bi?dobacterium spp.

6.8310762.83107 3.0310861.231080.291Hydrogen sul?de producers 1.1310761.53107* 4.1310661.43106

0.048Methane producers

3.1310662.13106UDL 2

Secondary bile acid producers

2.2310765.33106*

4.7310861.63108

0.037

1Values are means 6SEMs.*Mann-Whitney U test;the sample number was 12for each group.2

UDL,under detection limit.

116OU ET AL

Table 4)with concentrations of stool acetate (r 2=0.38),pro-pionate (r 2=0.33),and butyrate (r 2=0.37)(Figure 5).Second,stool butyrate concentrations were signi?cantly correlated with the abundance of the butyrate producers Clostridium cluster IV (r 2=0.29,P =0.047)and Clostridium cluster XIVa (r 2=0.29,P =0.047)(Table 4).

Amounts of the 4major BAs in feces were signi?cantly higher (P ,0.05)in Americans than in Africans (Figure 6).The fecal primary BAs cholic acid (CA)and chenodeoxycholic acid and the secondary BAs deoxycholic acid (formed from CA)and lithocholic acid (LCA,formed from CA and chenodeoxycholic acid)were signi?cantly higher (P ,0.05)in Americans than in Africans (Figure 6).The ratio of butyrate to LCA was signi?-cantly higher in Africans (39.2619.0compared with 6.063.2;P =0.047).A signi?cant correlation was also found between 7a -dehydroxylating bacteria and secondary BA concentrations in stool (r 2=0.65,P =0.01;Spearman’s test)as well (Figure 7),which likely indicated a higher microbial 7a -dehydroxylating capacity for colonic BAs in the Americans.

DISCUSSION

The ?ndings of the current study support the hypothesis that the balance between health-promoting and in?ammatory mi-crobial metabolites may determine colon cancer risk and that their production is dependent on both the composition of food and composition of the microbiota,as in an autocatalytic system.The data provide evidence that saccharolytic fermentation was lower,proteolytic fermentation was higher,and secondary BA pro-duction was higher in African Americans than in Africans.From

our earlier studies in the same populations,it is reasonable to postulate that these differences can be ascribed to differences in diet,with African Americans eating more dietary meat and fat and less complex carbohydrate and ?ber (4).

Fecal microbial composition was shown to be very different in Africans and African Americans,with the pattern in the former corresponding to enterotype 2and the latter to enterotype 1.Three enterotypes were recently described by a European con-sortium based on their pooled analysis of fecal samples obtained from healthy adults from 4European countries,the United States,and Japan (10).From this,they proposed that all human pop-ulations could be categorized into 1of 3enterotypes depending on their common networks of co-and anticorrelating genera,which are driven by the genus Bacteroides (type 1),Prevotella (type 2),or Ruminococcus (type 3).Interestingly,the composition in our African sample was remarkably similar to that shown in Central African children from Burkina Faso by De Filippo et al (35),dominated by Prevotella (type 2)and showing an overabundance of microbes that are likely involved in starch and cellulose deg-radation.They related these differences to differences in diet,with African children consuming a diet rich in coarse grains and vegetables that was somewhat similar to what Burkitt described as the “traditional African diet”that was associated with a low risk of colonic chronic diseases and colon cancer (36).Importantly,butyrate and the other SCFAs were also higher in the African children—as in our study;the authors proposed that this might help reduce the risk of enteric infections.

Interestingly in the current study,whereas the higher pro-portions of Prevotella ,Succinivibrio ,and Oscillospira in the African gut microbiome also represented higher numbers of these microbes in stool samples,as measured by qPCR,the higher compositional representation of bacteroides in African Americans did not appear to re?ect higher numbers.It is pos-sible that the total numbers of bacteroides were underestimated because the qPCR assay used targeted the B.fragilis group and not all human Bacteroides strains.On the other hand,the assay does include the 2major human gut species,namely B.fragilis and Bacteroides thetaiotamicron (15).Presumably,the greater numbers of total bacteria in the Africans was a consequence of the expansion of populations of microbes that degrade starches,hemicelluloses,and xylans—notably Prevotella ,Succinivibrio ,and Oscillospira —and those that ferment their products.

Our targeted microbe analysis showed that both the butyrate production gene and the recognized major butyrate-producing bacteria,including F .prausnitzii ,and those contained within Clostridium cluster IV and cluster XIVa were more abundant in stool samples from native Africans.Evidence that

these

FIGURE 4.Summary of the differences in mean (6SE)group con-centrations of the major short-chain fatty acids in fecal samples.Con-centrations were signi?cantly greater in NAs (n =12)than in AAs (n =12):Mann-Whitney U test for acetate (P =0.001),propionate (P =0.003),and butyrate (P =0.049).AA,African American;NA,native African.

TABLE 4

Nonparametric Spearman correlations (R )between fecal short-chain fatty acid concentrations and copy numbers of bacteria 1

Total SCFAs Acetic acid Propionic acid Butyric acid R

P R P R P R P Total bacteria

0.370.0110.380.0100.330.0260.370.042Bi?dobacterium spp.

20.230.11220.270.06620.170.23420.190.197Faecalibacterium prausnitzii 20.280.21520.170.10520.270.26520.200.246Clostridium IV 0.260.0740.250.0830.170.2340.290.047Clostridium XIVa

0.26

0.074

0.27

0.066

0.19

0.197

0.29

0.047

1

Sample number =24.SCFA,short-chain fatty acid.

MICROBIOTA AND METABOLITES IN COLON CANCER RISK 117

differences were of functional signi?cance was provided by our observation of positive correlations between the abundance of butyrate producers and butyrate concentrations in stool samples.Early cultural and molecular studies from Flint’s group (37,38)in Aberdeen,Scotland,indicated that the most numerous butyrate-producing bacteria found in human feces were highly oxygen-sensitive anaerobes belonging to the Clostridium clusters IV and XIV a.Their studies also highlighted cross-feeding between bacteria,with most butyrate producers consuming acetate produced by other microbes.Higher rates of fermentation in Africans might also have been facilitated by the higher numbers of the hydrogen-utilizing microbes,ie,sulfate reducers and methanogens,measured in stool samples,because it has been shown that the removal of the end product hydrogen increases fermentation potential (39).

Butyrate,propionate,and acetate have all have been shown in experimental models to have antineoplastic properties,but bu-tyrate appears to be the most potent (5).Butyrate has a unique role in the maintenance of colonic mucosal health:?rst,because of its position as the preferred energy source,and second,because of its protean antineoplastic properties.A wealth of experimental evidence,recently reviewed by ourselves (40,41),indicates the inhibitory effect of butyrate on tumorigenesis,possibly medi-ated by its antiin?ammatory and immunomodulatory effects and downregulation of the key canonical W nt -signaling pathway linked to colonic carcinogenesis (42).Butyrate may also play a role in primary prevention through the activation of different drug-metabolizing enzymes.This can reduce the burden of car-cinogens,such as BAs,and therefore decrease the number of mutations,which reduces cancer risk.Experimental studies have shown that it regulates colonic epithelial growth and protects against carcinogenesis by inhibiting the proliferation and mi-gration of neoplastic cells,restricting tumor angiogenesis,in-ducing apoptosis,and promoting differentiation of the neoplastic colonocytes (43–49).F .prausnitzii,a member of Clostridium cluster IV ,is one of the most dominant butyrate producers,but also may have independent antiin?ammatory properties related to secreted metabolites,which have been shown to block nuclear factor k B activation and IL-8production (50).

Food residues from an unbalanced diet de?cient in ?ber and high in meat promotes proteolytic rather than saccharolytic fermentation,with generation of the branched-chain SCFAs isobutyrate,isovaleric,and 2-methylbutyric acid (51,52)and nitrogenous metabolites.Whereas little is known about the functional signi?cance of branched SCFAs,proteolytic products such as hippurate,p -cresyl,ammonia,and phenols as well as sul?de metabolites have been shown to be in?ammatory and carcinogenic in experimental models (53,54).Thus,the lower risk of colon cancer in Africans could also be a consequence of lower proteolytic fermentation.We have also hypothesized that the high meat content of Westernized diets may increase colon cancer risk because of its stimulatory effect on

sulfate-reducing

FIGURE 5.The abundance of total bacteria correlated signi?cantly (Spearman’s test)with the concentrations of acetate (h ,dashed and dotted line;r 2=0.38,P =0.033),propionate (:,dashed line;r 2=0.33,P =0.039),and butyrate (3,continuous line;r 2=0.37,P =0.042)in fecal samples from African Americans and native Africans (n =

24).

FIGURE 6.Contents of major bile acids in feces were signi?cantly lower in NAs (n =12)than in AAs (n =12):Mann-Whitney U test for CA (P =0.027),CDCA (P =0.016),DCA (P =0.043),and LCA (P =0.031).*P ,0.05compared with AA.AA,African American;CA,cholic acid;CDCA,chenodeoxycholic acid;DCA,deoxycholic acid;LCA,lithocholic acid;NA,native African.

118OU ET AL

bacteria,which use the sulfur residues of meat to release hy-drogen sul?de,which has been shown to be genotoxic in ex-perimental models (54).Surprisingly,the opposite was observed,with higher numbers of sulfate-reducing bacteria in Africans,which suggests that increased saccharolytic fermentation with increased hydrogen production may be more stimulatory to these hydrogenotrophs.

Strong epidemiologic evidence links high fat consumption to increased colon cancer risk (55,56).Whereas experimental evidence indicates that fat,particularly fat high in n 26fatty acids,is proin?ammatory and that a Westernized diet high in fat and de?cient in vitamin D increases colonic tumors in normal mice (57),fat digestion and absorption are very ef?cient and little dietary fat enters the colon,which suggests that other mechanisms may be involved.Perhaps the strongest contender is BAs.Increased fat consumption stimulates the liver to synthe-size more BAs.This in turn increases the quantity of BAs that escape enterohepatic recirculation and enter the colon.Once in the colon,primary BAs,notably CA and chenodeoxycholic acid,are converted to secondary BAs,namely deoxycholic acid and LCA,by speci?c bacteria that contain 7a -dehydroxylating en-zymes.Our studies showed that not only were microbes containing this enzyme more common in high-risk African Americans,but so also were fecal secondary BAs.Human studies have associated increased fecal secondary BAs with colon polyps (58)and colon cancer (59),and there is substantial experimental evidence that they have carcinogenic properties (7).A further potential mecha-nism recently reported in a mouse model was the ability of a high-fat diet to stimulate the delivery of sulfur-rich taurine conjugates of BAs to the colon,where they produced a blossom of Biophila wadsworthia ,which released hydrogen sul?de from taurine that lead to acute in?ammation and colitis (60).

In summary,our study supports the hypothesis that colon cancer risk is determined by the interaction between diet and gut microbiota (61,62)and that the higher risk in African Americans could be attributed to their chronically lower consumption of ?ber and resistant starch and their higher consumption of dietary fat.Further studies are needed to assess the functional signi?cance of other differences noted in the pyrosequencing analysis (eg,Bacteroides )and the responsiveness of the identi?ed microbial and metabolomic differences to dietary change.

The authors’responsibilities were as follows—JO,SJDO,KN,and HRG:participated in the design and conduct of the study;JPD:conducted the BA and SCFA analyses;FC,EGZ,and MW:assisted with the microbiota anal-ysis;and JO,FC,and SJDO:performed the data analysis.All authors were involved in ?nalizing the manuscript.None of the authors had any con?icts of interest to declare.

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120OU ET AL

高中英语词组固定搭配(打印版)

高中英语词组固定搭配 a bit (of) 有一点,一会儿 a few 一些,少量 a great deal 大量,许多 a good/great many 大量,许多 a kind of 一种,一类 a little 一点,少许 a lot of 许多,大量 a number of 一些,许多 a pair of 一双,一副 a piece of 一块,一张,一根,一片above all 首先,首要 according to 根据,按照 add up to 合计达… after all 毕竟,终究 after class 课后 again and again 反复地,再三地agree to do sth. 同意做某事agree with sb. 同意某人的看法ahead of 在…之前 all in all 总的来说,总计 all kinds of 各种各样的 all over 到处,遍及,结束 all right 行了,好吧,(病)好了 all the best 一切顺利,万事如意answer for 对…负责 apart from 除去,除了 arrive at (in) a place 到达某地 as a matter of fact 事实上,其实 as a result (作为)结果 as...as 像,如同 as soon as 一…就… as far as (表示程度,范围)就…;尽…as if 好像,仿佛 as long as 只要 as though 好像,仿佛 as usual 通常,平常地 as well 也,还有 as well as 除…之外(也) belong to 属于 be proud of 骄傲,自豪 be strict with 对…严格要求both...and 两个都,既…又… break away from 脱离… break down 损坏; (化合物)分解,(汽车)抛锚break in 闯入,强行进入,插嘴,打断 break off 打断; 折断 break out (战争、火灾等)突然发生,爆发 break up 分解;分裂 bring in 引来,引进,吸收 bring on 引起,导致,使前进 bring up 教育,培养 build up 逐步建立 by accident 偶然 by air ( bus, train, ship ) 乘飞机(公共汽车,火 车,轮船) by and by 不久以后,逐渐地 by day 日间,在白天 by the way 顺便说 call for 提倡,号召, 需要 call in 召来,召集 call on 拜访,访问 call up 号召,打电话 care for 喜欢;照顾(病人) carry off 携走,夺走 carry on 继续下去; 继续开展 carry out 开展,执行 catch up with 赶上(或超过) change into 转换成,把…变成 check in 报到,登记 check out 查明; 结账 clear up 整理,收拾, (天气)放晴 come about 发生,产生 come across (偶然)遇见(或发现) come back 回来,想起来 come down 落,下来 come from 出生(于),来自 come in 进入,进来 come off 从…离开,脱落 come on 来吧,赶快 come out 出来,(书等)出版,发行 come to 共计,达到 come true 变为现实,成为事实 come up 上来,上升,抬头 come up with 追上;想出(主意);找出(答案) 1

初中英语所有重要的固定搭配、词组

1. put down 放下 shut down 把…关上 cut down 砍掉 come down 下来、落下 slow down 减缓、放慢 sit down 坐下 write down 写下 get down 下来,降落 2. after all 毕竟.终究 after that 于是.然后 day after day 日复一日地 one after another 相继.挨次 soon after 不久以后 the day after tomorrow 后天 3. come up with 找到、提出 catch up with 赶上 wake up 弄醒、醒来 send up 发射 open up 开设、开办 grow up 长大 pick up 拾起、捡起 hands up 举手 eat up 吃光 clean up 打扫干净 give up doing sth.=stop doing sth. 放弃做某事4. arrive at/in + n. 到达 get to +n. 到达 reach + n. 到达 arrive / get +adv. 到达 5. get…back 退还,送回去.取回 give back 归还 come back 回来 at the back of 在…的后面 on the way (back)home 在回家路上 6. at least 至少 at breakfast 早餐时 at desk 在桌前 at once立刻,马上 at school 在上学 at the same time 同时 at work 在工作 be good at=do well in 擅长 laugh at 嘲笑 not…at all 一点也不

浙江大学远程教育学院2012年秋冬第7次作业english

翻译: 请将下列五句英文分别翻译成中文。 1. Some people take no interest in country things: for them, happiness lies in the town, with its cinemas, shops, dance halls and restaurants. 有些人对乡村的事物不感兴趣:对他们来说,幸福在于城镇的电影院、商店、舞厅和餐馆。 那些热衷于城镇的电影院、商店、舞厅和餐馆的人对乡村的事物不感兴趣。 2. Soon it was time for my friend to take Jack for walk. 很快到了我的朋友帶杰克去散步的时间了。 3. To mark students' test papers, a checking machine is used. 为了给学生的试卷评分，用了一台阅卷机。 4. Whoever disobeys the law will be punished. 违者必罚。 5. With all his savings gone, he started to look for a job. 他用完了所有的存款，然后開始找工作了。 写作：请按照要求完成一篇英文作文，字数不少于80字。 标题：Parents Are the Best Teachers 内容需包括以下方面： 1.提出“父母是最好的老师”的观点，你的看法； 2.解释其中的原因； 3.重申观点。 As we all know, in our life, we have many different teachers, but the best teachers, I think, are our parents. My view is based on such reasons. They are the first people we meet. They teach us how to eat, and then how to walk. They teach us to speak, and they give us communication skills and so many others. They try their best to teach us, and develop our own learning skills. On the other hands, their words and actions will deeply affect our minds and decisions. Leading by example is an important way our parents teach us social skills, morals and how to get along with others. I believe that most of us have seen a public-interest advertisement on CCTV. The scene is about below: a young mother comes back home, after busy working for a whole day, she feels very tired. But she still washes feet carefully for her mother. All these have been seen by her little son behind the door. After his mother finish, the little child carries a basin of water slowly for his mother, and said “Mum please wash your feet.” All these tell us that the parents’ good actions will give a good example for their children. In our life, we follo w many people to study. Because every person we meet has something that we can learn. However, the greatest teachers in our lives will be our parents, because they were our first and most important teachers.

英语各类短语

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《英语写作》作业 Unit 1: 段落和篇章知识（Paragraph and whole composition）必做题 1.What is a paragraph? A paragraph is a division of writings expressing one central idea. It usually consists of several closely related sentences. It can also be called a unit of thought. It is a unit in itself and part of a larger whole. 2.What is a paragraph made up of? Paragraph is made up of a group of sentences which altogether express a controlling idea or central idea. It includes topic sentence, supporting sentences, and concluding sentence. The paragraph is the basic unit of a composition. 3.What are the features of an effective paragraph? l It focuses on one major idea. This major idea is called the topic sentence. l It provides enough details to develop the idea. An effe ctive paragraph does not waste the reader’s time. It doesn’t start something without finishing it. It contains enough specific details to enable the reader to understand the writer’s point. l It is sensibly organized: An effective paragraph does not bore the reader. It is organized so the reader has no trouble following the writer’s progression of thought—so the reader can see three parts in a paragraph—1) the topic sentence; 2) supporting details, and 3) the concluding sentence. 4.What is the topic sentence and why is it important? A topic sentence is a brief statement of the subject of the paragraph. It is very important because it determines the content of the whole paragraph. Therefore, special attention should be paid to it. 5.Which sentence is the topic sentence in the following paragraph? My mother has passed along to me certain rules for getting along with others. 6.The following topic sentences are not good ones, try to make them better. ●There is much to say about any problem. ●Time is money ●He found an old book in our library last Thursday afternoon 1 There is much to say about the problem of unemployment. 2 It is a shame to waste time in college years. 3 One of his interests is to spend time in libraries.