How human microbiome is influenced by diet and ethnicity
Yuan Kun LEE Department of Microbiology, Yong Loo Lin School of Medicine, National University of Singapore. 5 Science drive 2, Singapore 117597 EU children (n=15, 1~6 y.)
Alistipes Bacteroidetes Bacteroides Acetitomaculum Faecalibacterium Firmicutes Roseburia Subdoligranulum Others
Children in Burkina Faso Filippo, C. D. et al. PNAS (2010) 107, 14691‐14696 (n =14, 1~6 y.) Enterotypes: Prevotella Bacteroidetes Type 1: Consumed lots of Xylanibacter Acetitomaculum meat & saturated fat‐ more Faecalibacterium Firmicutes Subdoligranulum Bacteroides Others
Type 2: People who consumed lots of alcohol & polyunsaturated fats‐ Ruminicoccus prevailed
Type 3: Diet rich in carbohydrates‐ favored Prevotella Linking long‐term dietary patterns with gut microbial enterotypes Wu GD, Chen J, Hoffman C, et al. Science 2011, DOI: 10.1126/Science 1208344 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 Asian Human Microbiome initiative, 13 cities: 2009‐Phase I (Male vs Female, youngsters 7‐11 years) Pyrosequencing: 16S rDNA abundance of each bacterial species 100
10 Catabacter hongkongensis (p = 0.056) subject)
/ Clostridium1 leptum %
(p = 0.031) Akkermansia mucinphila 0.1 (p = 0.166) Clostridium disporicum (p = 0.44) (average
Bifidobacterium catenulatum 0.01 (p = 0.086) Female
0.001 0.001 0.01 0.1 1 10 100
Male (average % / subject) Storage stability of fecal RNA
B. fragilis group ● PBS, ● RNAprotect™, ● RNAlater™ 12 12 12 10 10 10 8 8 8 6 6 6 4˚C 25˚C 37˚C 4 4 4 0281 3 71421 0281 3 71421 0281 3 71421 Bifidobacterium cells / g feces cells / g 10 10 10 10 8 8 8 Log 6 6 6 4˚C 25˚C 37˚C 4 4 4 0281 3 71421 0281 3 71421 0281 3 71421 Incubation time (days) *, **p<0.05, 0.01（ Dunnett-test） Fecal samples can be kept stable for 4 weeks after sampling by using RNA stabilizing buffer: RNAlater®. Phase I: Accuracy of 454 Pyrosequence data in comparison to Q‐PCR C. coccoides group C. leptum group genus Bifidobacterium 70 50 70
60 60 40 (%) (%) 50 50
30 40 40
30 20 30
20 20 y = 1.4435x ‐ 1.8794 Pyrosequence (%) Pyrosequence 10 Pyrosequence y = 1.5818x ‐ 14.247 y = 1.6041x ‐ 18.237 10 R² = 0.5213 10 R² = 0.777 R² = 0.8565 0 0 0 0 10203040506070 0 10203040506070 0 1020304050 Q‐PCR (%) Q‐PCR (%) Q‐PCR (%) Bacteroides fragilis Group Genus Prevotella Atopobium cluster 30 20 50 25 y = 0.558x ‐ 2.3655 y = 0.7667x + 0.1374 40 R² = 0.7848 15 R² = 0.9724 (%) (%)
(%) 20
30 15 10
20 10 5 Pyrosequence Pyrosequence pyrosequence 10 y = 1.5902x ‐ 7.8816 5 R² = 0.7835 0 0 0 01020300 5 10 15 20 0 1020304050 Q‐PCR (%) Q‐PCR (%) Q‐PCR (%) Outline of fecal sample collection, transportation, analysis, and data feedback
Volunteer Fecal sampling 30 children / area 体取 [ 検体採取日 お母様名[ お母様名[ [ 検体採取日
くる 花子 ると やく 蓄 t 害です くると花子 と る やく ult 無 2 Yak 下さい Y ご返却 月[ ]月 必ず 用後は
2 使 蓄
月[ ]月 す lt 無害で 26 ku い ] Ya 下さ ご返却 Y は必ず
]日 後 26 使用 用後 ] 剤 使 蓄 冷 ません べられ
]日 食 すが、 無害で Y 剤 使用後 蓄 冷 ません べられ が、食 蓄 害です 無 す ult 無害で Yak 下さい ご返却 は必ず 使用後 蓄 す ult 無害で Yak 下さい Y ご返却 は必ず RNAlater® 使用後 Laboratory Collection and storing* of the fecal samples in each area * Fecal sample in RNAlater® can be stocked at 4˚C for 3 months.
Sample transportation from each area to laboratories in Singapore, Beijing and Japan for RNA/DNA extraction Data & N.A. feedback FLX454 titanium (188295 reads / 16S rDNA; 163423 reads/ 16S rRNA) Samples & data sharing Japan, Singapore, China Japan, Singapore, China qPCR/RT‐qPCR analysis Pyrosequencing Distribution of gut bacteria phylotypes among 303 Asian children.
16 Bifidobacteriaceae Other Actinobacteria
) 1 Bacteroidaceae 4 Prevotellaceae 10 9
x 02004002
Other Bacteroidetes (
3 Ruminococcus 5 4 8 Lachnospiraceae 4 6 7 9 reads
Streptococcaceae 1411 12 1310 15 of 16
Other Firmicutes 18 17 21 20 23 22 19 2425 Veillonellaceae 27 33 No. 26 35 37 3428 29 Bifidobacterium 32 41 31 4043 36 Enterobacteriaceae 1 47 48 54 52 4244 62 65 5756 58 45 9285 7059 76 Other Proteobacteria 9896 93 Verrucomicrobiaceae 0 Fusobacteriaceae 1 100 200 300 Erysipelotrichaceae BB P No. of carriers Prevotella 100 100 80 80 60 60 40 40 20 20 0 PS = 0.90 0 Bacteroides SW = 0.24 Family‐level gut bacterial compositions of children in 12 different cities in Asia.
Bacteroidaceae Lanzhou Bifidobacateriaceae Beijing Ruminococcaceae Lachnospiraceae Prevotellaceae Tokyo
Fukuoka Mongolia
Seoul Khon Kaen
Bangkok Taipei
Yogyakarta Taichung Bali Random forest clustering of 303 Asian children using species‐level phylotype composition data (Asian Microbiome Project Phase I)
Percentage = accuracy in random forest clustering Japanese (97%) Indonesia (86%)
Bali Yogjakarta Fukuoka
Tokyo Khon Kaen Mongolia Seoul Dimension 2 Taipei Bangkok
Taichung
Beijing
Lanzhou China (80%)
Dimension 1 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 abundance Red line indicate negative correlation Blue 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.
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. faecalis EC16 for 6h at a MOI of 100. Experiments were done on 3‐4 biological replicates and 2 technical replicates.
Wang SQ , Hibberd ML , Pettersson S, Lee YK. Enterococcus faecalis from Healthy Infants Modulates Inflammation through MAPK Signaling Pathways. PLOS One 2014, 9: e97523. * Intestinal microbiota want 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.
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. Mongolia Enterotypes: Lanzhou Type 1: Consumed lots of Beijing meat & saturated fat‐ more Bacteroides?? Mongolian Tokyo Type 3: Diet rich in carbohydrates‐ favored Prevotella?? Chinese Fukuoka
Seoul Khon Kaen Taipei
Bacteroidaceae Bangkok Bifidobacateriaceae Ruminococcaceae Yogyakarta Taichung Lachnospiraceae Bali Prevotellaceae Mongolians classical diet high in meat, alcohol and fermented milk, which more resembles typical western diets.
Mongolian Firmicutes to Bacteroidetes (F/B) ratio 0.71 Urbanised 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)
Meat consumption per capital (kg) Zhang JC et al. 2014. Inner Mongolia seasonal Mongolians In ascending order core gut microbiota and its correlation with seasonal Indonesia 8.3 dietary changes. Scientific reports 14: 56‐67. Burkina Faso 11.2 De Filippo, C. et al. 2010. Impact of diet in shaping gut microbiota revealed by a comparative study in children Thailand 27.9 from Europe and rural Africa. Proc. Natl. Acad. Sci. U S A 107, 14691‐14696. Korea 30.9 Japan 43.9 Nam, Y.‐D. et al. 2011. Comparative analysis of Korean human gut microbiota by barcoded pyrosequencing. PLoS One 6, e22109 . China 52.4
Italy 90.4 Mongolia 108.8 USA 124.8 The 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 diet
Table3 Significantly changed genera in Mongolians from Khentii, TUW and Ulan Bator due to seasonal change
Relative contribution (%) Median, range (%) Genus P-value January March Juner SeptembeNovembery JanuarMarch Juner November Septembe Khentii
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 / 0.03831538 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 Shigella group 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 0.112,0.012- 0.04870000 Collinsella 0.739 0.469 0.176 0.975 0.412 0.189,0.04-3.612 0.139,0.067-4.05 0.599,0.161-5.139 0.227,0-1.644 0.657 2.887,0.56- 5.805,0.494- 6.774,1.694- 0.04828000 Faecalibacterium 5.510 6.799 4.154 6.036 8.759 3.688,0.16-22.854 4.937,0.727-24.375 21.906 14.927 22.308
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 0.435,0.075- 0.03075455 Dorea 0.658 0.493 0.619 0.619 0.365 0.466,0.078-2.493 0.364,0.012-1.864 0.553,0-2.579 0.231,0-1.89 1.823
* 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, Roseburia and 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 radiotelemetry device. 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 High meat, fat & cereal, Ruminococcaceae Lachnospiraceae Low vegetable Prevotellaceae Mongolia USA Florence Rice type Korea Tokyo High meat, fat & cereal, Lanzhou Beijing High vegetable Sichuan Bangladesh Fukuoka Taipei Bangkok Taichung Indica Khon Kaen Japonica Javanica Burkina Faso
Yogjakarta choloylglycine hydrolase Bali Low meat, fat High vegetable & cereal Staple Insoluble fibre Amylose Starch fraction carbohydrates (g/100 g) (% total starch) (% dry matter)
Amylose Rapidly Slow Resistant digestible digestible
Mongolia Barley 12.0 29 24.9 12.1 18.2 wheat 14.7 26 38.1 29.0 1.7 Oat 33.9 26 35.8 0.3 7.2 Buckwheat 7.0 25 37
Millets 3.1 21 35.9 37.7 12.6 Burkina Faso Millet 3.1 21 35.9 37.7 12.6 Sorghum 4.2 24 29.2 13.9 36.1 Black‐eyed 32.4 38 18.5 18.5 17.7 peas Indonesia Indica rice 1.2 33 32.0 48.9 14.1
Thailand Japan Japonica rice 20 0.2
Korea Wheat flour 8.5 26 38.1 29.0 1.7 China
Italy Wheat flour 8.5 26 38.1 29.0 1.7
USA 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.
Mongolia USA Florence Korea Tokyo Lanzhou Beijing Sichuan Bangladesh Fukuoka Taipei
Bangkok Taichung Bacteroidaceae Khon Kaen Burkina Faso
Bifidobacteriaceae Yogjakarta
Ruminococcaceae Bali
Lachnospiraceae
Prevotellaceae 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
Mongolia USA Florence Korea Tokyo Lanzhou Beijing Sichuan Bangladesh Fukuoka Taipei Bangkok Taichung Khon Kaen Burkina Faso
Yogjakarta
Bali
NewScientist 9 August 2014, pg 10. Genetic factor?? 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. 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 Bifidobacterium was 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 Bifidobacterium adolescentis 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 CoA transferase gene. Environ Microbiol 12: 304–314.