Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Diet-induced extinctions in the gut microbiota compound over generations

Abstract

The gut is home to trillions of microorganisms that have fundamental roles in many aspects of human biology, including immune function and metabolism1,2. The reduced diversity of the gut microbiota in Western populations compared to that in populations living traditional lifestyles presents the question of which factors have driven microbiota change during modernization. Microbiota-accessible carbohydrates (MACs) found in dietary fibre have a crucial involvement in shaping this microbial ecosystem, and are notably reduced in the Western diet (high in fat and simple carbohydrates, low in fibre) compared with a more traditional diet3. Here we show that changes in the microbiota of mice consuming a low-MAC diet and harbouring a human microbiota are largely reversible within a single generation. However, over several generations, a low-MAC diet results in a progressive loss of diversity, which is not recoverable after the reintroduction of dietary MACs. To restore the microbiota to its original state requires the administration of missing taxa in combination with dietary MAC consumption. Our data illustrate that taxa driven to low abundance when dietary MACs are scarce are inefficiently transferred to the next generation, and are at increased risk of becoming extinct within an isolated population. As more diseases are linked to the Western microbiota and the microbiota is targeted therapeutically, microbiota reprogramming may need to involve strategies that incorporate dietary MACs as well as taxa not currently present in the Western gut.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Taxa reduction observed in low-MAC diet is largely reversible in a single generation.
Figure 2: Inefficient inter-generational transfer of taxa driven to low abundance by low dietary MACs.
Figure 3: Reintroduction of lost taxa and a high-MAC diet restores microbiota diversity and composition.

Similar content being viewed by others

Accession codes

Accessions

Sequence Read Archive

Data deposits

The 16S sequence data have been deposited in the Sequence Read Archive (SRA) under the accession PRJNA303185.

References

  1. Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012)

    Article  ADS  CAS  Google Scholar 

  2. Karlsson, F., Tremaroli, V., Nielsen, J. & Backhed, F. Assessing the human gut microbiota in metabolic diseases. Diabetes 62, 3341–3349 (2013)

    Article  CAS  Google Scholar 

  3. Sonnenburg, E. D. & Sonnenburg, J. L. Starving our microbial self: the deleterious consequences of a diet deficient in microbiota-accessible carbohydrates. Cell Metab. 20, 779–786 (2014)

    Article  CAS  Google Scholar 

  4. Schnorr, S. L. et al. Gut microbiome of the Hadza hunter-gatherers. Nature Commun. 5, 3654 (2014)

    Article  ADS  CAS  Google Scholar 

  5. Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012)

    Article  ADS  CAS  Google Scholar 

  6. De Filippo, C. et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl Acad. Sci. USA 107 , 14691–14696 (2010)

    Article  ADS  Google Scholar 

  7. Clemente, J. C. et al. The microbiome of uncontacted Amerindians. Science Advances 1 , e1500183 (2015)

    Article  ADS  Google Scholar 

  8. Obregon-Tito, A. J. et al. Subsistence strategies in traditional societies distinguish gut microbiomes. Nature Commun. 6, 6505 (2015)

    Article  ADS  CAS  Google Scholar 

  9. Martinez, I. et al. The gut microbiota of rural Papua New Guineans: composition, diversity patterns, and ecological processes. Cell Rep. 11, 527–538 (2015)

    Article  CAS  Google Scholar 

  10. McGill, C. R., Fulgoni, V. L. III & Devareddy, L. Ten-year trends in fiber and whole grain intakes and food sources for the United States population: National Health and Nutrition Examination Survey 2001–2010. Nutrients 7, 1119–1130 (2015)

    Article  Google Scholar 

  11. King, D. E., Mainous, A. G. III & Lambourne, C. A. Trends in dietary fiber intake in the United States, 1999–2008. J. Acad. Nutr. Diet. 112, 642–648 (2012)

    Article  Google Scholar 

  12. Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012)

    Article  ADS  CAS  Google Scholar 

  13. Kashyap, P. C. et al. Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota. Proc. Natl Acad. Sci. USA 110, 17059–17064 (2013)

    Article  ADS  CAS  Google Scholar 

  14. Lombard, V., Golaconda Ramulu, H., Drula, E., Coutinho, P. M. & Henrissat, B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 42, D490–D495 (2014)

    Article  CAS  Google Scholar 

  15. Tikhonov, M., Leach, R. W. & Wingreen, N. S. Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution. ISME J. 9, 68–80 (2015)

    Article  Google Scholar 

  16. El Kaoutari, A., Armougom, F., Gordon, J. I., Raoult, D. & Henrissat, B. The abundance and variety of carbohydrate-active enzymes in the human gut microbiota. Nature Rev. Microbiol. 11, 497–504 (2013)

    Article  CAS  Google Scholar 

  17. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010)

    Article  CAS  Google Scholar 

  18. Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

    Article  CAS  Google Scholar 

  19. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

    Article  CAS  Google Scholar 

  20. Kashyap, P. C. et al. Complex interactions among diet, gastrointestinal transit, and gut microbiota in humanized mice. Gastroenterology 144, 967–977 (2013)

    Article  Google Scholar 

  21. Turnbaugh, P. J. et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14 (2009)

    Article  Google Scholar 

  22. Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nature Methods 10, 57–59 (2013)

    Article  CAS  Google Scholar 

  23. Yin, Y. et al. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, W445–W451 (2012)

    Article  CAS  Google Scholar 

  24. Marchler-Bauer, A. et al. CDD: Specific functional annotation with the Conserved Domain Database. Nucleic Acids Res. 37, D205–D210 (2009)

    Article  CAS  Google Scholar 

  25. Aspeborg, H., Coutinho, P. M., Wang, Y., Brumer, H. & Henrissat, B. Evolution, substrate specificity and subfamily classification of glycoside hydrolase family 5 (GH5). BMC Evol. Biol. 12, 186 (2012)

    Article  CAS  Google Scholar 

  26. Stam, M. R., Danchin, E. G. J., Rancurel, C., Coutinho, P. M. & Henrissat, B. Dividing the large glycoside hydrolase family 13 into subfamilies: towards improved functional annotations of α-amylase-related proteins. Protein Eng. Des. Sel. 19, 555–562 (2006)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank M. St. Onge for technical assistance. This work was funded by a grant from National Institutes of Health NIDDK (R01-DK085025 to J.L.S.), an NSF graduate fellowship (to S.A.S.), a Stanford Graduate Fellowship (to S.A.S.), and the Simons Foundation (to M.T.). J.L.S. holds an Investigators in the Pathogenesis of Infectious Disease Award from the Burroughs Wellcome Fund.

Author information

Authors and Affiliations

Authors

Contributions

E.D.S. and J.L.S. conceived and designed the project. E.D.S., J.L.S. and S.K.H. designed and supervised the experiments. E.D.S. and S.K.H. performed the experiments. E.D.S., S.A.S. and M.T. analysed the experimental data. N.S.W. designed and supervised data analysis. E.D.S. and S.A.S. wrote the manuscript. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Justin L. Sonnenburg.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Collating data from studies of the microbiota of hunter–gatherers in Tanzania, agrarians from Malawi and Venezuela, and Westerners from the United States reveals that Western populations have depleted alpha-diversity from birth through childbearing years and are missing bacterial taxa present in the traditional groups.

a, Scatterplot of faecal microbiota of individuals plotted by phylogenetic diversity against age of the Hadza hunter–gatherers from Tanzania (n = 16, green), agrarians from Malawi (n = 81, red) and Venezuela (n = 78, purple) and Americans (n = 213, blue) b, Individuals plotted by unweighted UniFrac PC1 versus phylogenetic diversity. c, Individuals plotted by unweighted UniFrac PC1 versus age. d, Line plot of unique OTUs from faecal microbiota across populations (Americans, n = 315; Malawi and Venezuela, n = 213; Tanzania, n = 27). OTUs (x axis; black, present; white, absent) are considered present if represented by ≥0.001% of reads within each population. OTUs were sorted along the x axis by their relative abundance in the US and Tanzanian populations and further subdivided by their distributions within a population into tracks (red >0.05%, yellow ≤0.05%, and green ≤0.01%, relative abundance). The opacity of the line is the proportion of that population that meets the criteria for that respective track.

Extended Data Figure 2 Comparison of human donor and humanized mice.

a, Taxa summary plot of the relative abundance of taxa from humanized mice faeces (mice) (n = 10) and human donor faeces (human) (n = 1). b, Alpha-diversity of the faecal microbiota from humanized mice (mice) and human donor (human) expressed as number of OTUs (top) and phylogenetic diversity (bottom). Error bars are s.e.m.

Extended Data Figure 3 Detailed schematic of multigeneration experiment.

Generation one: humanized mice were fed a high-MAC diet for 4 weeks then switched to a low-MAC diet. One week after diet switch, the mice were bred to generate a litter of pups. After three additional weeks on the low-MAC diet, generation-two pups were born and remained in the cage with their mother, suckling for 3 weeks (generation one still consuming the low-MAC diet). After pups were weaned, generation-one mice were returned to the high-MAC diet for 6 weeks. Generation two: pups were weaned from their mother at 3 weeks old onto a low-MAC diet, which they consumed for 10 weeks. Breeding pairs for generation-two mice were set-up at 7 weeks old. After three additional weeks on the low-MAC diet, generation-three pups were born and remained in the cage with their mother, suckling for 3 weeks (generation-two mice still consuming the low-MAC diet). After pups were weaned, generation-two mice were returned to the high-MAC diet for 6 weeks. Generations three and four followed the same protocol as generation two described above.

Extended Data Figure 4 Microbiota diversity is not regained after direct weaning the diet-switching group onto the high-MAC diet.

a, Alpha-diversity as measured by Shannon index of faecal microbiota from generation-five mice from the high-MAC-diet control (control) (n = 6), generation-five diet-switching group that was weaned directly onto the high-MAC diet (Gen 5 diet switching) (n = 6), and generation-four mice from the diet-switching group after weaning and maintenance on the low-MAC diet for 13 weeks and returned to the high-MAC diet for 4 weeks (Gen 4 diet switching) (n = 5). Error bars are s.e.m. and P values are from a two-tailed Student’s t-test b, Principal coordinate analysis of unweighted UniFrac distance for 16S rRNA amplicon profiles from faecal samples collected from first-generation control mice on a high-MAC diet (green), fourth-generation diet-switching mice (purple), and fifth-generation mice from the diet-switching lineage weaned directly onto the high-MAC diet (orange). Control is plotted as weeks post-humanization and generations four and five are plotted as age.

Extended Data Figure 5 Fraction of high-confidence OTUs from the Clostridiales order increases and from the Bacteroidales order decreases over several generations in the low-MAC-consuming mice.

a, Percentage of high-confidence OTUs, grouped by order, detected in mice faeces over four generations in the diet-switching lineage on the low-MAC diet (lo) and high-MAC diet (hi) (n = 5 for Gen 1; n = 6 for Gen 2–4). b, Percentage of high-confidence OTUs, grouped by order, detected in mice faeces over four generations in the control high-MAC diet lineage at the equivalent time points to the high-MAC diet (a) and low-MAC diet (b) of the diet-switching group (n = 5 for Gen 1; n = 6 for Gen 2–4). c, Imputed gycloside hydrolase (GH) family members that show significant differences (at least twofold change and P < 0.05, Bonferroni-corrected t-test) between generation-four diet-switching mice after 4 weeks on the high-MAC diet (teal) (n = 5) and the starting generation-one mice (salmon) (n = 10). Error bars depict s.e.m. No glycoside hydrolase families showed significant changes in the control group.

Extended Data Figure 6 Inefficient inter-generational transfer of taxa driven to low abundance by low dietary MACs.

Heat map of abundance of high-confidence sub-OTUs (number of sequencing reads, columns) from faeces of the diet-switching (top) and control (bottom) group. Each row represents an individual mouse faecal microbiota from 4 weeks post-humanization (initial), while consuming the low-MAC diet (week 9, lo, shaded yellow), and 4 weeks after switching to the high-MAC diet (week 15, hi, shaded grey). Corresponding time points from controls are also shaded. Top row shows the taxonomic assignment for the OTUs plotted: Bacteroidetes are green, Firmicutes are orange, and others are grey.

Extended Data Figure 7 Reintroduction of lost taxa and a high-MAC diet restores microbiota diversity and composition with Clostridiales order decreasing and Bacteroidales order increasing in low-MAC-consuming mice that receive a faecal transplant.

a, Plot of percentage representation of high-confidence OTUs from generation-four mice faeces in the diet-switching group at day 0 before the FMT (starting) (n = 6) and then 3–14 days no-FMT control (n = 3) or post-FMT (n = 3). FMT donor is plotted on the right. b, Heat map of abundance of high-confidence sub-OTUs (number of sequencing reads, columns) from the faeces of the diet-switching group at day 0 (Gen 4), days 3–14 that did not receive an FMT (control) (n = 3 for each day), days 3–14 that received an FMT (+FMT), and the FMT donor. Each row represents an individual mouse faecal microbiota. Top row shows the taxonomic assignment for the OTUs plotted: Bacteroidetes are green, Firmicutes are orange, and others are grey.

Extended Data Table 1 Nutritional information of mouse diets
Extended Data Table 2 High-confidence OTUs at experiment start
Extended Data Table 3 Shannon index of glycoside hydrolase subfamilies

Related audio

Supplementary information

Supplementary Table 1

A table of high-confidence OTUs that dropped in abundance by at least two-fold in the first generation diet-switching mice after switch to the low-MAC diet and the control high-MAC diet mice. (XLSX 15 kb)

Supplementary Table 2

A table of high-confidence OTUs that dropped in abundance by at least two-fold in the first generation diet-switching mice after return to the high-MAC diet and the control high-MAC diet mice. (XLSX 12 kb)

Supplementary Table 3

A table of high-confidence OTUs lost through generation four while consuming the low MAC diet and after switch to the high MAC diet. (XLSX 9 kb)

Supplementary Table 4

A comparison of glycoside hydrolases from metagenomic data and imputed from 16S rRNA amplicon sequencing data. (XLSX 48 kb)

Supplementary Table 5

Table of fold change of glycoside hydrolase families from generation one to generation four in the diet-switching and control groups. (XLSX 43 kb)

Supplementary Table 6

Table of unique glycoside hydrolase sub-families in diet-switching mice between generations one and four by sampling depth. (XLSX 49 kb)

Supplementary Table 7

Table of low abundance taxa that were passed or not passed between each of four generations of mice. (XLSX 11 kb)

Supplementary Table 8

Table of number of high-confidence sub-OTUs present at the start of the experiment and the number of high-confidence sub-OTUs lost by the fourth generation and between the third and fourth generation. (XLSX 9 kb)

Supplementary Table 9

Table of high-confidence OTUs that were no longer detectable after four generations on the low MAC and return after FMT. (XLSX 11 kb)

Supplementary Table 10

Table of high-confidence sub-OTUs that were no longer detectable after four generations on the low MAC and return after FMT. (XLSX 12 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sonnenburg, E., Smits, S., Tikhonov, M. et al. Diet-induced extinctions in the gut microbiota compound over generations. Nature 529, 212–215 (2016). https://doi.org/10.1038/nature16504

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature16504

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing