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How human microbiome is influenced by diet and ethnicity
Yuan Kun LEEDepartment of Microbiology,
Yong Loo Lin School of Medicine, National University of Singapore.
5 Science drive 2, Singapore 117597
Filippo, C. D. et al. PNAS (2010) 107, 14691‐14696
AlistipesBacteroidesAcetitomaculumFaecalibacterium
SubdoligranulumOthers
Roseburia
Bacteroidetes
Firmicutes
EU children (n=15, 1~6 y.)
PrevotellaXylanibacterAcetitomaculumFaecalibacteriumSubdoligranulumOthers
Bacteroidetes
Firmicutes
Children in Burkina Faso(n =14, 1~6 y.)
Linking long‐term dietary patterns with gut microbial enterotypesWu GD, Chen J, Hoffman C, et al. Science 2011, DOI: 10.1126/Science 1208344
Enterotypes:Type 1: Consumed lots of meat & saturated fat‐ more Bacteroides
Type 2: People who consumed lots of alcohol & polyunsaturated fats‐ Ruminicoccusprevailed
Type 3: Diet rich in carbohydrates‐ favored Prevotella
Intestinal microbiota profile is determined by:
i. Exposure during infancy
ii. Ability of the microbe to adhere to intestinal surface: Adhesin‐receptor interaction
ii. Ability to colonize intestinal surface: Intestinal micro‐environment (host physiology stage & dietary habit)
Asian diet and life style different from European, North American and African
0.001 0.01 0.1 1 10 100
Bifidobacterium catenulatum(p = 0.086)
Clostridium leptum(p = 0.031)
Akkermansia mucinphila(p = 0.166)
Catabacter hongkongensis(p = 0.056)
Clostridium disporicum(p = 0.44)
100
10
1
0.1
0.01
0.001
Female (average % / subject)
Male (average % / subject)
Asian Human Microbiome initiative, 13 cities: 2009‐Phase I (Male vs Female, youngsters 7‐11 years) Pyrosequencing: 16S rDNA abundance of each bacterial species
Storage stability of fecal RNA
Fecal samples can be kept stable for 4 weeks after sampling by using RNAstabilizing buffer: RNAlater®.
Log1
0ce
lls /
g fe
ces
● PBS, ● RNAprotect™, ● RNAlater™
Incubation time (days) *, **p<0.05, 0.01( Dunnett-test)Incubation time (days) *, **p<0.05, 0.01( Dunnett-test)
B. fragilis group
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Bifidobacterium
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4217 14310 28217 14310 28
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4217 14310 28217 14310 28
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B. fragilis group
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Bifidobacterium
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4217 14310 28217 14310 28
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4217 14310 28217 14310 28
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4217 14310 28217 14310 28
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4217 14310 28217 14310 28
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Phase I: Accuracy of 454 Pyrosequence data in comparison to Q‐PCR
y = 1.5818x ‐ 14.247R² = 0.777
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70
Pyrosequ
ence (%
)
Q‐PCR (%)
C. coccoides group
y = 1.4435x ‐ 1.8794R² = 0.5213
0
10
20
30
40
50
0 10 20 30 40 50Pyrosequ
ence (%
)Q‐PCR (%)
C. leptum group
y = 1.6041x ‐ 18.237R² = 0.8565
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70
Pyrosequ
ence
(%)
Q‐PCR (%)
y = 1.5902x ‐ 7.8816R² = 0.7835
0
10
20
30
40
50
0 10 20 30 40 50
pyrosequ
ence (%
)
Q‐PCR (%)
y = 0.558x ‐ 2.3655R² = 0.7848
0
5
10
15
20
25
30
0 10 20 30
Pyrosequ
ence (%
)
Q‐PCR (%)
y = 0.7667x + 0.1374R² = 0.9724
0
5
10
15
20
0 5 10 15 20Pyrosequ
ence (%
)Q‐PCR (%)
genus Bifidobacterium
Bacteroides fragilis Group Genus Prevotella Atopobium cluster
Outline of fecal sample collection, transportation, analysis, and data feedback
Laboratoryin each area
Japan, Singapore, China
Volunteer 30 children / area
Japan, Singapore, China
Collection and storing* of the fecal samples * Fecal sample in RNAlater® can be stocked at 4˚C for 3 months.
Fecal sampling
qPCR/RT‐qPCR analysis Pyrosequencing
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
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日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
検体
採取
日
[2
]月[ 2
6]日
お母
様名
[やく
ると
花子
]
YY使用後
蓄
無害ですYakultYakult
使用後は必ずご返却下さい
蓄 冷 剤
無害ですが、食べられません
YakultYakult
使用後は必ずご返却下さい
蓄
無害です
YY使用後
蓄
無害ですYakultYakult
使用後は必ずご返却下さい
蓄 冷 剤
無害ですが、食べられません
YakultYakult
使用後は必ずご返却下さい
蓄
無害です
YY使用後
蓄
無害ですYakultYakult
使用後は必ずご返却下さい
蓄 冷 剤
無害ですが、食べられません
YakultYakult
使用後は必ずご返却下さい
蓄
無害です
YY使用後
蓄
無害ですYakultYakult
使用後は必ずご返却下さい
蓄 冷 剤
無害ですが、食べられません
YakultYakult
使用後は必ずご返却下さい
蓄
無害です
Data & N.A.feedback
Sample transportation from each area to laboratories in Singapore, Beijing and Japan for RNA/DNA extraction
Samples & data sharing
RNAlater®
FLX454 titanium
(188295 reads / 16S rDNA;
163423 reads/ 16S rRNA)
BifidobacteriaceaeOther ActinobacteriaBacteroidaceaePrevotellaceaeOther BacteroidetesRuminococcusLachnospiraceaeStreptococcaceaeOther FirmicutesVeillonellaceaeEnterobacteriaceaeOther ProteobacteriaVerrucomicrobiaceaeFusobacteriaceaeErysipelotrichaceae
1
32
4 56 7 89
101114 13121615
19 212425172223
3120
2632 37
18272841
54
No. of carriers3002001001
No. of reads ( x 104)
16
9
4
1
0
3547
33344859
65628592
29364042 4344 45525657 5870 769698 93
0 200 400
Distribution of gut bacteria phylotypes among 303 Asian children.
Prevotella
Bacteroides
Bifidobacterium
PS = 0.90SW = 0.24
BB P
100
80
60
40
20
0
100
80
60
40
20
0
Taipei
Taichung
Beijing
YogyakartaBali
Bangkok
Khon Kaen
Fukuoka
Lanzhou
Tokyo
Bacteroidaceae
LachnospiraceaeRuminococcaceae
Prevotellaceae
Bifidobacateriaceae
Family‐level gut bacterial compositions of children in 12 different cities in Asia.
Seoul
Mongolia
Random forest clustering of 303 Asian children using species‐level phylotype composition data (Asian Microbiome Project Phase I)
China (80%)
Indonesia (86%)Japanese (97%)
Percentage = accuracyin random forest clustering
Dimension 1
Dimension 2
Beijing
Tokyo
TaipeiBangkok
Yogjakarta
Lanzhou
Fukuoka
Taichung
Khon Kaen
Bali
Seoul
Mongolia
J Nakayama, K Watanabe, JH Jiang, K Matsuda, SH Chao, P Haryono, O La‐ongkham, MA Sarwoko, IN Sujaya, L Zhao, KT Chen, YP Chen, HH Chiu, T Hidaka, NX Huang, C Kiyohara, T Kurakawa, N Sakamoto, K Sonomoto, K Tashiro, H Tsuji, MJ Chen, V Leelavatcharamas, CC Liao, S Nitisinprasert, ES Rahayu, FZ Ren, YC Tsai, YK Lee (2015) Diversity in gut bacterial community of school‐age children in Asia. Scientific Reports, 5:8397/DOI 10.1038/srep08397.
Size of the circle correspond to the abundanceRed line indicate negative correlationBlue lines indicate positive correlation
25 bacterial strains isolated from healthy Indonesia new born infants (1‐3 days) according to their 16sRNA sequences.
E. faecalis accounted for 90‐95% of the enterococci, and the remaining were E. faecium
Infants who developed allergy and necrotizing enterocolitis were less often colonized with enterococci during the first month of life as compared to healthy infants.
Wang SQ , Hibberd ML , Pettersson S, Lee YK. Enterococcus faecalis from Healthy Infants Modulates Inflammation through MAPK Signaling Pathways. PLOS One 2014, 9: e97523.*
IPA and Realtime PCR analysis. Ingenuity pathway analysis on E.faecalis treated HCT116 cells. All pathways and genes showed in the figure were significantly (p<0.05) regulated in HCT116 cells with the treatment of E. faecalisEC16 for 6h at a MOI of 100. Experiments were done on 3‐4 biological replicates and 2 technical replicates.
FASTING‐INDUCED ADIPOSE FACTOR (FIAF) INHIBITS ENZYME LIPOPROTEIN LIPASE (LPL). LPL CATALYZE RELEASE OF FATTY ACIDS AND TRICYGLEROL FROM CIRCULATING LIPOPROTEIN IN MUSCLE AND ADIPOSE TISSUE.
ADIPOCYTE DIFFERENTIATION‐RELATED PROTEIN (ADRP) IS ASSOCIATED WITH THE GLOBULE SURFACE MEMBRANE MATERIAL. THIS PROTEIN IS A MAJOR CONSTITUENT OF THE GLOBULE SURFACE. INCREASE IN MRNA LEVELS IS ONE OF THE EARLIEST INDICATIONS OF ADIPOCYTE DIFFERENTIATION
IL‐10, ALSO KNOWN AS HUMAN CYTOKINE SYNTHESIS INHIBITORY FACTOR (CSIF), IS AN ANTI‐INFLAMMATORY CYTOKINE.
ARE A, ARONSSON L, WANG SG, GREICIUS G, LEE YK, GUSTAFSSON JA, PETTERSSON S, ARULAMPALAM V (2008) ENTEROCOCCUS FAECALIS ISOLATED FROM NEWEBORN BABIES REGULATE ENDOGENOUS PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR‐GAMMA (PPARG) AND INTERLEUKIN‐10 IN COLONIC EPITHELIA CELLS. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES USA 105: 1943‐1948.
Intestinal microbiotawant the kids fat! Co‐evolution?PPAR‐1 phosphorylation is coupled to increased transcription of target genes:
Real time PCR experiment under a 6h influence of EC16 or Rosiglitazone, (A) Adipose differentiation‐related protein, ADRP, (B) Fasting‐induced adipose factor, FIAP, (C) interleukin‐10, (D) inhibition by siRNA for PPAR‐ (SiP‐) on FIAF compared to scrambled (Scr.), (E) FIAF with kinase inhibitors PD98059, LY294002 & SB203580.(F) Western of nuclear extracts stimulated by EC16 with LY294002 or SB203580 for 30 minutes. Ku70 is shown as loading control.
Taipei
Taichung
Beijing
YogyakartaBali
Bangkok
Khon Kaen
Fukuoka
Lanzhou
Tokyo
Bacteroidaceae
Lachnospiraceae
Ruminococcaceae
Bifidobacateriaceae
Seoul
MongoliaEnterotypes:Type 1: Consumed lots of meat & saturated fat‐ more Bacteroides?? Mongolian
Type 3: Diet rich in carbohydrates‐ favored Prevotella?? Chinese
Prevotellaceae
Mongolians classical diet high in meat, alcohol and fermented milk, which more resembles typical western diets.
Mongolian Firmicutes to Bacteroidetes (F/B) ratio 0.71Urbanised Italian children 2.81 Korean 2.95(Korean diets high fibre content: 19.8 g/day versus 15.1 g/day for Americans; low meat)
Zhang JC et al. 2014. Inner Mongolia seasonal Mongolians core gut microbiota and its correlation with seasonal dietary changes. Scientific reports 14: 56‐67.
De Filippo, C. et al. 2010. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl. Acad. Sci. U S A 107, 14691‐14696.
Nam, Y.‐D. et al. 2011. Comparative analysis of Korean human gut microbiota by barcoded pyrosequencing. PLoS One 6, e22109 .
Meat consumption per capital (kg)
In ascending order
Indonesia 8.3
Burkina Faso 11.2
Thailand 27.9
Korea 30.9
Japan 43.9
China 52.4
Italy 90.4
Mongolia 108.8
USA 124.8The Guardian Datablog 2002
Zhang JC, Guo Z, Lim AAQ, Zheng Y, Koh EY, Ho DL, Qiao JM, Huo DX, Hou QC, Huang WQ, Wang LF, Javzandulam C, Narangerel C, Menghebilige J, Lee YK & Zhang HP. Inner Mongolia seasonal Mongolians core gut microbiota and its correlation with seasonal dietary changes. Scientific reports 2014, 14: 56‐67.
Seasonal dietary changes in Mongolian population: more animal meat in Winter and more dairy products in Summer.
Prevotella, Bacteroides, Ruminococcus and Coprococcus, remain relatively constant in abundance throughout the year.These suggest that Westernised diet and lifestyle (rich in fat and meat) may not be direct determining factors for gut microbiota composition indicators.
Faecalibacterium, Bifidobacterium & Eubacterium vary with seasonal dietTable3 Significantly changed genera in Mongolians from Khentii, TUW and Ulan Bator due to seasonal change
Genus Relative contribution (%) Median, range (%) P-value January March June September November January March June September NovemberKhentii Faecalibacterium 4.150 2.646 1.639 2.347 3.638 2.838,0.956-17.658 2.537,0.594-7.618 1.435,0.36-3.535 2.253,1.157-3.576 3.604,2.473-5.853 0.01275000
Eubacterium 2.039 0.745 1.760 1.094 0.288 1.634,0.028-5.125 0.482,0-1.724 0.993,0.075-6.67 0.694,0.061-2.692 0.214,0-1.366 0.01275000 Dorea 0.571 0.503 0.520 0.327 0.222 0.454,0.056-1.652 0.488,0.143-1.046 0.46,0.084-1.177 0.298,0.139-0.775 0.165,0.019-0.688 0.03075455 Collinsella 1.082 0.235 0.770 0.355 0.173 0.28,0.014-4.603 0.092,0-1.177 0.49,0.057-1.767 0.326,0.104-1.08 0.114,0-0.658 0.03075455 Enterococcus 0.001 0.000 0.816 0.082 0.002 0,0-0.009 0,0-0 0,0-6 0.005,0-0.798 0,0-0.023 0.03075455 Solobacterium 0.967 0.278 0.277 0.217 0.336 0.504,0-3.041 0.182,0.02-1.251 0.216,0-0.576 0.147,0-0.765 0.163,0-2.25 0.03075455 Caldimonas 0.067 0.161 0.043 0.234 0.306 0.012,0-0.549 0.06,0-0.781 0.024,0-0.133 0.126,0-0.755 0.128,0-1.528 0.03831538 Escherichia coli / Shigella group 0.147 0.018 0.511 0.092 0.392 0.055,0-0.755 0,0-0.164 0.075,0-4.813 0.025,0-0.585 0.01,0-4.314 0.03831538
Subdoligranulum 1.397 0.563 0.685 0.381 0.851 0.927,0.112-4.963 0.535,0.219-1.46 0.5,0.038-2.496 0.327,0.139-1.026 0.477,0.241-3.596 0.04383571 TUW Anaerosporobacter 0.068 0.095 0.036 0.109 0.091 0.069,0-0.147 0.084,0-0.229 0.021,0-0.133 0.099,0.027-0.278 0.088,0-0.217 0.03075455 Butyricimonas 0.052 0.080 0.058 0.150 0.166 0.026,0-0.305 0.052,0-0.323 0.032,0-0.279 0.122,0-0.498 0.093,0-0.581 0.04845000
Collinsella 0.739 0.469 0.176 0.975 0.412 0.189,0.04-3.612 0.139,0.067-4.05 0.112,0.012-0.657 0.599,0.161-5.139 0.227,0-1.644 0.04870000
Faecalibacterium 5.510 6.799 4.154 6.036 8.759 3.688,0.16-22.854 4.937,0.727-24.375 2.887,0.56-21.906
5.805,0.494-14.927
6.774,1.694-22.308
0.04828000
Roseburia 2.697 5.532 2.094 4.496 1.740 1.717,0.424-9.691 3.012,0.419-21.063 2.357,0.269-4.53 3.176,0.55-10.605 1.71,0.383-3.336 0.03075455 Ulan Bator Enterococcus 0.006 0.001 0.003 0.017 0.409 0,0-0.196 0,0-0.004 0,0-0.025 0,0-0.182 0,0-14.696 0.00031620 Collinsella 0.691 0.257 0.296 0.639 0.461 0.255,0-4.916 0.121,0-3.214 0.187,0-1.486 0.444,0-4.761 0.286,0-1.398 0.01275000
Dorea 0.658 0.493 0.619 0.619 0.365 0.466,0.078-2.493 0.364,0.012-1.864 0.435,0.075-1.823 0.553,0-2.579 0.231,0-1.89 0.03075455
* Only genera representing more than 0.05% of the total number of sequences are included in the comparison.
Others showed that wheat (arabinoxylan) & animal protein have a long term (52 weeks) effect on Bacteroides, due to acidification of GI tract.
Indirect effect on Bacteroides population?
Neyrinck AM et al. 2011. Prebiotic Effects of Wheat Arabinoxylan Related to the Increase in Bifidobacteria, Roseburiaand Bacteroides/Prevotella in Diet‐Induced Obese Mice. PLoS ONE 6: e20944.
Bown RL etal. 1974. Effects of lactulose and other laxatives on ileal and colonic pH as measured by a radiotelemetrydevice. Gut 15: 999–1004.
Duncan SH et al. 2007. Reduced dietary intake of carbohydrates by obese subjects results in decreased DIET DETERMINE GUT MICROBIOTA PROFILE MODULATING STAGE OF HEALTH 11 concentrations of butyrate and butyrate‐producing bacteria in feces. Appl Environ Microbiol 73: 1073–1078.
Wu GD et al. 2011. Linking long‐term dietary patterns with gut microbial enterotypes. Science 334: 105–108.
David LA et al. 2014. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505(7484):559‐63.
Short‐term (4 days) consumption of diets composed entirely of animal products increased abundance of bile‐tolerant microorganisms (Alistipes, Bilophila and Bacteroides).
Bacteroides is the default gut microbiota!
Bacteroides‐host interactions: Bry L, Falk PG, Midtvedt T, Gordon JI (1996) A model of host‐microbial interactions in an open mammalian ecosystem. Science 273: 1380‐1383.
L‐fucose utilizing Bacteroides thetaiotaomicron induced fucosylation program in small intestine epithelium
Bacteroides within the distal GI tract degrades fibres, & it uses a series of membrane protein complexes (Sus‐like systems) to catabolize plant cell wall glycans in our diets.
Martens EC et al. 2011. Recognition and degradation of plant cell wall polysaccharides by two human gut symbionts. PLoS Biol 9: e1001221.
The human staple diet in the first 2.5 million years was probably plants.
Vegetable consumption per capital (kg)
In ascending order
Mongolia 39.1
Indonesia 39.5
Thailand 47.2
Japan 102
USA 123
Italy 157
Korea 233.5
China 322 HelgiLibrary 2009
What drives the gut microbiota? Family‐level gut bacterial compositions of children in different cities in the world.
Bacteroidaceae
Bifidobacteriaceae
Ruminococcaceae
Lachnospiraceae
Prevotellaceae
Fukuoka
TokyoKorea
Taipei
Taichung
BeijingLanzhou
Bangkok
Khon Kaen
Yogjakarta
Bali
Mongolia
Sichuan
Burkina Faso
Florence
High meat, fat & cereal,Low vegetable
Low meat, fatHigh vegetable & cereal
High meat, fat & cereal,High vegetable
USA
Bangladesh
Rice type
Javanica
Indica
Japonica
choloylglycine hydrolase
Staple carbohydrates
Insoluble fibre (g/100 g)
Amylose (% total starch)
Starch fraction (% dry matter)
Amylose Rapidly digestible
Slow digestible
Resistant
Mongolia Barley 12.0 29 24.9 12.1 18.2
wheat 14.7 26 38.1 29.0 1.7Oat 33.9 26 35.8 0.3 7.2Buckwheat 7.0 25 37
Millets 3.1 21 35.9 37.7 12.6Burkina Faso Millet 3.1 21 35.9 37.7 12.6
Sorghum 4.2 24 29.2 13.9 36.1Black‐eyed peas
32.4 38 18.5 18.5 17.7
Indonesia
Thailand
Indica rice 1.2 33 32.0 48.9 14.1
Japan
Korea
China
Japonica rice 20 0.2
Wheat flour 8.5 26 38.1 29.0 1.7
Italy
USA
Wheat flour 8.5 26 38.1 29.0 1.7
Potato 1.1 20 75.5 3.8 1.7
Resistant starch: RS1‐ starch in seeds or legumes and unprocessed whole grains; RS2‐ natural granular form, e.g. high amylose corn; RS3‐ retrograded cooked starch. Drives Prevotella!Badnar et al., 2001. Starch and fiber fractions in selected food and feed ingredients affect their small intestinal digestibility and fermentation and their large bowel fermentability in vitro in a canine model. J Nutr. 131:276‐286.
Behall et al. 1995. Effect of long term consumption of amylose vs amylopectin starch on metaboloic variables in human subject. Am J Clin Nutr 61:334‐340.
Lbaneiah et al. 1981. Changes of starch, crude fiber, and oligosaccharides in germinating dry beans. Cereal Chem. 58: 135‐138.
Differences in composition of the gut microflora of people (youngsters) from different geographical regions.
Bacteroidaceae
Bifidobacteriaceae
Ruminococcaceae
Lachnospiraceae
Prevotellaceae
Fukuoka
TokyoKorea
Taipei
Taichung
BeijingLanzhou
Bangkok
Khon Kaen
Yogjakarta
Bali
Mongolia
Sichuan
Burkina Faso
FlorenceUSA
Bangladesh
J Nakayama, K Watanabe, JH Jiang, K Matsuda, SH Chao, P Haryono, O La‐ongkham, MA Sarwoko, IN Sujaya, L Zhao, KT Chen, YP Chen, HH Chiu, T Hidaka, NX Huang, C Kiyohara, T Kurakawa, N Sakamoto, K Sonomoto, K Tashiro, H Tsuji, MJ Chen, V Leelavatcharamas, CC Liao, S Nitisinprasert, ES Rahayu, FZ Ren, YC Tsai, YK Lee (2015) Diversity in gut bacterial community of school‐age children in Asia. Scientific Reports| 5 : 8397 | DOI: 10.1038/srep08397
Family‐level gut bacterial compositions of children in different cities in the world.
Bacteroidaceae
Bifidobacteriaceae
Ruminococcaceae
Lachnospiraceae
Prevotellaceae
NewScientist 9 August 2014, pg 10.
Reyes‐Centeno H, Ghirotto S, Détroit F, Grimaud‐Hervé D, Barbujani G, Harvati K. Genomic and cranial phenotype data support multiple modern human dispersals from Africa and a southern route into Asia. Proc Natl Acad Sci U S A. 2014, 111:7248‐53.
Fukuoka
TokyoKorea
Taipei
Taichung
BeijingLanzhou
Bangkok
Khon Kaen
Yogjakarta
Bali
Mongolia
Sichuan
Burkina Faso
Florence
Genetic factor??
Bangladesh
USA
Thank you!
Dietary plant products facilitate the colonization of Prevotella.
Changes in microbiome composition detected within 24 hours of initiating controlled feeding.
Wu, GD et al. Linking long‐term dietary patterns with gut microbial enterotypes. Science 334, 105‐108 (2011).
Neyrinck AM et al. Prebiotic Effects of Wheat arabinoxylan related to the Increase in Bifidobacteria, Roseburia and Bacteroides/Prevotella in Ddet‐Induced obese mice. PLoS ONE 6: e20944 (2011).
Durban A et al. Effect of dietary carbohydrate restriction on an obesity‐related Prevotella‐dominated human fecal microbiota. Metagenomics 2, Article ID 235722 (2013).
Slowly digestible plant carbohydrates (oligosaccharides, wheat arabinoxylan =prebiotics) enrich the gut microbiota that are able to metabolize complex carbohydrates, such as certain Bifidobacterium strains (in particular B. infantis).
Two groups of butyrate‐producing bacteria, namely Faecalibacterium prausnitzii and a group of clostridial cluster XIVa bacteria, were found to increase following inulin/fructooligosaccharide (FOS) supplementation in a human intervention study.
The enrichment of Bifidobacteriumwas generally at the expense of Bacteroides.
Davis LMG et al. 2011. Barcoded pyrosequencing reveals that consumption of galactooligosaccharides results in a highly specific bifidogenic response in humans. PLoS ONE 6: e25200.
Ramirez‐Farias C et al. 2009. Effect of inulin on the human gut microbiota: stimulation of Bifidobacteriumadolescentis and Faecalibacterium prausnitzii. Br J Nutr 101: 541–550.
Louis P, et al. 2010. Diversity of human colonic butyrate‐producing bacteria revealed by analysis of the butyryl‐CoA:acetate CoAtransferase gene. Environ Microbiol 12: 304–314.