scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Gut microbiomes of Malawian twin pairs discordant for kwashiorkor

TL;DR: The authors investigated the role of the gut microbiome in kwashiorkor, an enigmatic form of severe acute malnutrition that is the consequence of inadequate nutrient intake plus additional environmental insults, and found that RUTF produced a transient maturation of metabolic functions that regressed when administration of RUTF was stopped.
Abstract: Kwashiorkor, an enigmatic form of severe acute malnutrition, is the consequence of inadequate nutrient intake plus additional environmental insults. To investigate the role of the gut microbiome, we studied 317 Malawian twin pairs during the first 3 years of life. During this time, half of the twin pairs remained well nourished, whereas 43% became discordant, and 7% manifested concordance for acute malnutrition. Both children in twin pairs discordant for kwashiorkor were treated with a peanut-based, ready-to-use therapeutic food (RUTF). Time-series metagenomic studies revealed that RUTF produced a transient maturation of metabolic functions in kwashiorkor gut microbiomes that regressed when administration of RUTF was stopped. Previously frozen fecal communities from several discordant pairs were each transplanted into gnotobiotic mice. The combination of Malawian diet and kwashiorkor microbiome produced marked weight loss in recipient mice, accompanied by perturbations in amino acid, carbohydrate, and intermediary metabolism that were only transiently ameliorated with RUTF. These findings implicate the gut microbiome as a causal factor in kwashiorkor.
Citations
More filters
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
Evan Bolyen1, Jai Ram Rideout1, Matthew R. Dillon1, Nicholas A. Bokulich1, Christian C. Abnet2, Gabriel A. Al-Ghalith3, Harriet Alexander4, Harriet Alexander5, Eric J. Alm6, Manimozhiyan Arumugam7, Francesco Asnicar8, Yang Bai9, Jordan E. Bisanz10, Kyle Bittinger11, Asker Daniel Brejnrod7, Colin J. Brislawn12, C. Titus Brown5, Benjamin J. Callahan13, Andrés Mauricio Caraballo-Rodríguez14, John Chase1, Emily K. Cope1, Ricardo Silva14, Christian Diener15, Pieter C. Dorrestein14, Gavin M. Douglas16, Daniel M. Durall17, Claire Duvallet6, Christian F. Edwardson, Madeleine Ernst18, Madeleine Ernst14, Mehrbod Estaki17, Jennifer Fouquier19, Julia M. Gauglitz14, Sean M. Gibbons20, Sean M. Gibbons15, Deanna L. Gibson17, Antonio Gonzalez14, Kestrel Gorlick1, Jiarong Guo21, Benjamin Hillmann3, Susan Holmes22, Hannes Holste14, Curtis Huttenhower23, Curtis Huttenhower24, Gavin A. Huttley25, Stefan Janssen26, Alan K. Jarmusch14, Lingjing Jiang14, Benjamin D. Kaehler27, Benjamin D. Kaehler25, Kyo Bin Kang14, Kyo Bin Kang28, Christopher R. Keefe1, Paul Keim1, Scott T. Kelley29, Dan Knights3, Irina Koester14, Tomasz Kosciolek14, Jorden Kreps1, Morgan G. I. Langille16, Joslynn S. Lee30, Ruth E. Ley31, Ruth E. Ley32, Yong-Xin Liu, Erikka Loftfield2, Catherine A. Lozupone19, Massoud Maher14, Clarisse Marotz14, Bryan D Martin20, Daniel McDonald14, Lauren J. McIver24, Lauren J. McIver23, Alexey V. Melnik14, Jessica L. Metcalf33, Sydney C. Morgan17, Jamie Morton14, Ahmad Turan Naimey1, Jose A. Navas-Molina14, Jose A. Navas-Molina34, Louis-Félix Nothias14, Stephanie B. Orchanian, Talima Pearson1, Samuel L. Peoples20, Samuel L. Peoples35, Daniel Petras14, Mary L. Preuss36, Elmar Pruesse19, Lasse Buur Rasmussen7, Adam R. Rivers37, Michael S. Robeson38, Patrick Rosenthal36, Nicola Segata8, Michael Shaffer19, Arron Shiffer1, Rashmi Sinha2, Se Jin Song14, John R. Spear39, Austin D. Swafford, Luke R. Thompson40, Luke R. Thompson41, Pedro J. Torres29, Pauline Trinh20, Anupriya Tripathi14, Peter J. Turnbaugh10, Sabah Ul-Hasan42, Justin J. J. van der Hooft43, Fernando Vargas, Yoshiki Vázquez-Baeza14, Emily Vogtmann2, Max von Hippel44, William A. Walters32, Yunhu Wan2, Mingxun Wang14, Jonathan Warren45, Kyle C. Weber46, Kyle C. Weber37, Charles H. D. Williamson1, Amy D. Willis20, Zhenjiang Zech Xu14, Jesse R. Zaneveld20, Yilong Zhang47, Qiyun Zhu14, Rob Knight14, J. Gregory Caporaso1 
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.

8,821 citations

Journal ArticleDOI
TL;DR: This work reviews studies that explored the association between an abnormal expansion of Proteobacteria and a compromised ability to maintain a balanced gut microbial community and proposes that an increased prevalence of ProTeobacteria is a potential diagnostic signature of dysbiosis and risk of disease.

2,019 citations

Journal ArticleDOI
09 Oct 2014-Nature
TL;DR: It is demonstrated that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota, thereby calling for a reassessment of massive NAS usage.
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.

1,472 citations

Journal ArticleDOI
TL;DR: How the gut microbiota and derived microbial compounds may contribute to human metabolic health and to the pathogenesis of common metabolic diseases are discussed, and examples of microbiota-targeted interventions aiming to optimize metabolic health are highlighted.
Abstract: Observational findings achieved during the past two decades suggest that the intestinal microbiota may contribute to the metabolic health of the human host and, when aberrant, to the pathogenesis of various common metabolic disorders including obesity, type 2 diabetes, non-alcoholic liver disease, cardio-metabolic diseases and malnutrition. However, to gain a mechanistic understanding of how the gut microbiota affects host metabolism, research is moving from descriptive microbiota census analyses to cause-and-effect studies. Joint analyses of high-throughput human multi-omics data, including metagenomics and metabolomics data, together with measures of host physiology and mechanistic experiments in humans, animals and cells hold potential as initial steps in the identification of potential molecular mechanisms behind reported associations. In this Review, we discuss the current knowledge on how gut microbiota and derived microbial compounds may link to metabolism of the healthy host or to the pathogenesis of common metabolic diseases. We highlight examples of microbiota-targeted interventions aiming to optimize metabolic health, and we provide perspectives for future basic and translational investigations within the nascent and promising research field. In this Review, Fan and Pedersen discuss how the gut microbiota and derived microbial compounds may contribute to human metabolic health and to the pathogenesis of common metabolic diseases, and highlight examples of microbiota-targeted interventions aiming to optimize metabolic health.

1,445 citations

References
More filters
Journal ArticleDOI
01 Oct 2001
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Abstract: Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, aaa, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.

79,257 citations

Journal ArticleDOI
TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.

28,911 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
22 Jan 2009-Nature
TL;DR: The faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers are characterized to address how host genotype, environmental exposure and host adiposity influence the gut microbiome.
Abstract: The human distal gut harbours a vast ensemble of microbes (the microbiota) that provide important metabolic capabilities, including the ability to extract energy from otherwise indigestible dietary polysaccharides. Studies of a few unrelated, healthy adults have revealed substantial diversity in their gut communities, as measured by sequencing 16S rRNA genes, yet how this diversity relates to function and to the rest of the genes in the collective genomes of the microbiota (the gut microbiome) remains obscure. Studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet, and how this harvested energy is used and stored. Here we characterize the faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers, to address how host genotype, environmental exposure and host adiposity influence the gut microbiome. Analysis of 154 individuals yielded 9,920 near full-length and 1,937,461 partial bacterial 16S rRNA sequences, plus 2.14 gigabases from their microbiomes. The results reveal that the human gut microbiome is shared among family members, but that each person's gut microbial community varies in the specific bacterial lineages present, with a comparable degree of co-variation between adult monozygotic and dizygotic twin pairs. However, there was a wide array of shared microbial genes among sampled individuals, comprising an extensive, identifiable 'core microbiome' at the gene, rather than at the organismal lineage, level. Obesity is associated with phylum-level changes in the microbiota, reduced bacterial diversity and altered representation of bacterial genes and metabolic pathways. These results demonstrate that a diversity of organismal assemblages can nonetheless yield a core microbiome at a functional level, and that deviations from this core are associated with different physiological states (obese compared with lean).

6,970 citations

Journal ArticleDOI
TL;DR: It is shown that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
Abstract: DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.

6,840 citations

Related Papers (5)