The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Artificial sweeteners induce glucose intolerance by altering the gut microbiota
Abstract
Non-caloric artificial sweeteners (NAS) are among the most widely used food additives worldwide, regularly consumed by lean and obese individuals alike. NAS consumption is considered safe and beneficial owing to their low caloric content, yet supporting scientific data remain sparse and controversial. Here we demonstrate that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota. These NAS-mediated deleterious metabolic effects are abrogated by antibiotic treatment, and are fully transferrable to germ-free mice upon faecal transplantation of microbiota configurations from NAS-consuming mice, or of microbiota anaerobically incubated in the presence of NAS. We identify NAS-altered microbial metabolic pathways that are linked to host susceptibility to metabolic disease, and demonstrate similar NAS-induced dysbiosis and glucose intolerance in healthy human subjects. Collectively, our results link NAS consumption, dysbiosis and metabolic abnormalities, thereby calling for a reassessment of massive NAS usage.
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In the citing paper
“NNS consumption induced glucose intolerance in a microbiota-dependent manner (56).”
From The gut microbiota at the intersection of diet and human health (2018) · cites this paper as [56]
In the citing paper
“Emulsifiers and artificial sweeteners have been shown to be involved in the development of metabolic syndrome features through their modulation of the microbiota in mice46,47.”
From Diet–microbiota interactions as moderators of human metabolism (2016) · cites this paper as [47]
In the citing paper
“In a study in seven people, artificial sweeteners given at high doses resulted in insulin resistance after only 7 days47”
From Diet–microbiota interactions as moderators of human metabolism (2016) · cites this paper as [47]
In the citing paper
“Chronic NAS consumption in mice was shown to impact gut microbial community structure133, resulting in an increase in abundance of bacteria belonging to the Bacteroides genus and some members of the Clostridiales order.”
From The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism (2016) · cites this paper as [133]
In the citing paper
“germ-free mice colonized with gut microorganisms from NAS-treated mice or stool microorganisms exposed to NAS ex vivo develop glucose intolerance.”
From The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism (2016) · cites this paper as [133]
In the citing paper
“Consumption of artificial sweeteners in mice and humans has been shown to lead to deregulation of the intestinal microbiota, with altered glycan degradation capacity promoting decreased glucose tolerance, a pre-diabetic condition [58].”
From Antibiotic-Induced Changes in the Intestinal Microbiota and Disease (2016) · cites this paper as [58]
In the citing paper
“Other dietary compounds known to alter the composition of the gut microbiome include noncaloric artificial sweeteners such as saccharin, sucralose, and aspartame (Suez et al., 2015), a feature with functional implications associated with the induction of glucose intolerance in mice (Suez et al., 2014).”
From Gut reactions: Breaking down xenobiotic–microbiome interactions (2019) · cites this paper as Suez et al., 2014
In the citing paper
“Although earlier human studies indicated detrimental effects on microbial diversity and composition (99, 100) and a more recent study linked consumption of nonnutritive sweeteners to a “dysbiosis” [an increasingly redundant term in microbiome research (171)] and a decrease in butyrate concentration (172), some reports have concluded that no clear effects of sweeteners on the microbiota can be”
From Diet and the Microbiota–Gut–Brain Axis: Sowing the Seeds of Good Mental Health (2021) · cites this paper as [100]
Citations
Cites
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Diet rapidly and reproducibly alters the human gut microbiome
David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., et al. (2014) · Nature · doi:10.1038/nature12820 · Cited by 10,100
Human gut microbes associated with obesity
Ley, R. E., Turnbaugh, P. J., Klein, S., & Gordon, J. I. (2006) · Nature · doi:10.1038/4441022a · Cited by 8,785
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
Metabolic Endotoxemia Initiates Obesity and Insulin Resistance
Cani, P. D., Amar, J., Iglesias, M. A., Poggi, M., Knauf, C., Bastelica, D., Neyrinck, A. M., Fava, F., Tuohy, K. M., Chabo, C., et al. (2007) · Diabetes · doi:10.2337/db06-1491 · Cited by 6,638
Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., & Burcelin, R. (2008) · Diabetes · doi:10.2337/db07-1403 · Cited by 4,819
The impact of the gut microbiota on human health: an integrative view
Clemente, J. C., Ursell, L. K., Parfrey, L. W., & Knight, R. (2012) · Cell · doi:10.1016/j.cell.2012.01.035 · Cited by 3,710
Cited by
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Cryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286
Proteobacteria: Microbial signature of dysbiosis in gut microbiota
Shin, N.-R., Whon, T. W., & Bae, J.-W. (2015) · Trends in Biotechnology · doi:10.1016/j.tibtech.2015.06.011 · Cited by 3,954
Personalized nutrition by prediction of glycemic responses
Zeevi, D., Korem, T., Zmora, N., Israeli, D., Rothschild, D., Weinberger, A., Ben-Yacov, O., Lador, D., Avnit-Sagi, T., Lotan-Pompan, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.001 · Cited by 2,929
“Illumina compatible libraries were prepared as described (Suez et al., 2014).”
BackgroundMethodSelf-citationInfluence of diet on the gut microbiome and implications for human health
Singh, R. K., Chang, H.-W., Yan, D., Lee, K. M., Ucmak, D., Wong, K., Abrouk, M., Farahnik, B., Nakamura, M., Zhu, T. H., et al. (2017) · Journal of Translational Medicine · doi:10.1186/s12967-017-1175-y · Cited by 2,599
Role of the gut microbiota in nutrition and health
Valdes, A. M., Walter, J., Segal, E., & Spector, T. D. (2018) · BMJ · doi:10.1136/bmj.k2179 · Cited by 2,375
Self-citation
Metadata
- Authors
- Suez, J., Korem, T., Zeevi, D., Zilberman-Schapira, G., Thaiss, C. A., Maza, O., Israeli, D., Zmora, N., Gilad, S., Weinberger, A., Kuperman, Y., Harmelin, A., Kolodkin-Gal, I., Shapiro, H., Halpern, Z., Segal, E., & Elinav, E.
- Affiliations
- Weizmann Institute of Science (IL)
- Jerusalem Mental Health Center (IL)
- Tel Aviv University (IL)
- Corresponding author
- Segal, Eran
- Elinav, Eran
- ORCID
- Venue
- Nature
- Published
- 2014-09-17
- Volume
- 514
- Issue
- 7521
- Pages
- 181-186
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1989947363
- Cited by
- 2,067
- References
- 41
- Citations by year
- 2026: 145 · 2025: 182 · 2024: 175 · 2023: 166 · 2022: 218 · 2021: 190 · 2020: 189 · 2019: 182 · 2018: 159 · 2017: 159 · 2016: 153 · 2015: 123 · 2014: 24
- FWCI
- 62.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Nursing › Nutrition and Dietetics › Biochemical Analysis and Sensing Techniques
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- impaired glucose tolerance, gut microbiota, dysbiosis, saccharin, sucralose, aspartame, obesity, fecal microbiota transplantation, germ-free mice, antibiotic therapy, type 2 diabetes, microbial metabolic pathways, food additives
- MeSH terms
- Animals, Anti-Bacterial Agents, Aspartame, Body Weight, Dietary Fats, Feces, Female, Germ-Free Life, Glucose, Humans, Male, Mice, Inbred C57BL, Saccharin, Sucrose, Sweetening Agents, Glucose Intolerance, Metabolic Syndrome, Gastrointestinal Tract, Waist-Hip Ratio, Mice, Diet, High-Fat, Microbiota
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