Very low-carbohydrate, high-fat ketogenic diets (KDs) induce a pronounced shift in metabolic fuel utilization that elevates circulating ketone bodies; however, the consequences of these compounds for ...host-microbiome interactions remain unknown. Here, we show that KDs alter the human and mouse gut microbiota in a manner distinct from high-fat diets (HFDs). Metagenomic and metabolomic analyses of stool samples from an 8-week inpatient study revealed marked shifts in gut microbial community structure and function during the KD. Gradient diet experiments in mice confirmed the unique impact of KDs relative to HFDs with a reproducible depletion of bifidobacteria. In vitro and in vivo experiments showed that ketone bodies selectively inhibited bifidobacterial growth. Finally, mono-colonizations and human microbiome transplantations into germ-free mice revealed that the KD-associated gut microbiota reduces the levels of intestinal pro-inflammatory Th17 cells. Together, these results highlight the importance of trans-kingdom chemical dialogs for mediating the host response to dietary interventions.
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•Ketogenic diets (KDs) alter the gut microbiota in a manner distinct from high-fat diets•Gut microbial shifts on KDs are driven in part through host production of ketone bodies•β-hydroxybutyrate selectively inhibits bifidobacterial growth•The KD-associated gut microbiota reduces levels of intestinal Th17 cells
Ketogenic diets differ from high fat diets in that they alter the gut microbiome to affect the level of gut Th17 cells.
Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to ...which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models.
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•A generalizable approach is presented for meta-analysis of microbiome datasets•High-fat diets induce reproducible shifts in the mouse gut microbiome•Nonviable Lactococcus contamination is widespread in experimental diets•Phylogenetic and gene signatures translate to human microbiomes
Bisanz and Upadhyay et al. execute a meta-analysis of previous studies evaluating the effect of a high-fat diet on the gut microbiome. They define reproducible features across studies for mechanistic experimentation and uncover that residual DNA contamination in experimental diets should be measured and accounted for in study design.
A20 is an anti-inflammatory protein that is strongly linked to human disease. Here, we find that mice expressing three distinct targeted mutations of A20's zinc finger 7 (ZF7) ubiquitin-binding motif ...uniformly developed digit arthritis with features common to psoriatic arthritis, while mice expressing point mutations in A20's OTU or ZF4 motifs did not exhibit this phenotype. Arthritis in A20
mice required T cells and MyD88, was exquisitely sensitive to tumor necrosis factor and interleukin-17A, and persisted in germ-free conditions. A20
cells exhibited prolonged IκB kinase activity that drove exaggerated transcription of late-phase nuclear factor-κB response genes in vitro and in prediseased mouse paws in vivo. In addition, mice expressing double-mutant A20 proteins in A20's ZF4 and ZF7 motifs died perinatally with multi-organ inflammation. Therefore, A20's ZF4 and ZF7 motifs synergistically prevent inflammatory disease in a non-catalytic manner.
Emerging evidence suggests that the effect of dietary intake on human health and disease is linked to both the immune system and the microbiota. Yet, we lack an integrated mechanistic model for how ...these three complex systems relate, limiting our ability to understand and treat chronic and infectious disease. Here, we review recent findings at the interface of microbiology, immunology, and nutrition, with an emphasis on experimentally tractable models and hypothesis-driven mechanistic work. We outline emerging mechanistic concepts and generalizable approaches to bridge the gap between microbial ecology and molecular mechanism. These set the stage for a new era of precision human nutrition informed by a deep and comprehensive knowledge of the diverse cell types in and on the human body.
Alexander and Turnbaugh review the current understanding of the mechanisms linking diet, the microbiome, and immunity. In this context, the authors propose general mechanistic concepts defining these interactions and outline important gaps in knowledge at the intersection of immunology and microbiota research.
In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 ...pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms.
AmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high frequencies.
AmpliconNoise followed by Perseus is a very effective pipeline for the removal of noise. In addition the principles behind the algorithms, the inference of true sequences using Expectation-Maximization (EM), and the treatment of chimera detection as a classification or 'supervised learning' problem, will be equally applicable to new sequencing technologies as they appear.
Here I revisit our early experiments published in Cell Host & Microbe (Turnbaugh et al., 2008) showing that a diet rich in fat and simple sugars alters the gut microbiome in a manner that contributes ...to host adiposity, and reflect upon the remarkable advances and remaining challenges in this field.
Here I revisit our early experiments published in Cell Host & Microbe (Turnbaugh et al., 2008) showing that a diet rich in fat and simple sugars alters the gut microbiome in a manner that contributes to host adiposity, and reflect upon the remarkable advances and remaining challenges in this field.
The human microbiome plays a key role in a wide range of host-related processes and has a profound effect on human health. Comparative analyses of the human microbiome have revealed substantial ...variation in species and gene composition associated with a variety of disease states but may fall short of providing a comprehensive understanding of the impact of this variation on the community and on the host. Here, we introduce a metagenomic systems biology computational framework, integrating metagenomic data with an in silico systems-level analysis of metabolic networks. Focusing on the gut microbiome, we analyze fecal metagenomic data from 124 unrelated individuals, as well as six monozygotic twin pairs and their mothers, and generate community-level metabolic networks of the microbiome. Placing variations in gene abundance in the context of these networks, we identify both gene-level and network-level topological differences associated with obesity and inflammatory bowel disease (IBD). We show that genes associated with either of these host states tend to be located at the periphery of the metabolic network and are enriched for topologically derived metabolic "inputs." These findings may indicate that lean and obese microbiomes differ primarily in their interface with the host and in the way they interact with host metabolism. We further demonstrate that obese microbiomes are less modular, a hallmark of adaptation to low-diversity environments. We additionally link these topological variations to community species composition. The system-level approach presented here lays the foundation for a unique framework for studying the human microbiome, its organization, and its impact on human health.
Our associated microbial communities play a critical role in human health and predisposition to disease, but the degree to which they also shape therapeutic interventions is not well understood. ...Here, we integrate results from classic and current studies of the direct and indirect impacts of the gut microbiome on the metabolism of therapeutic drugs and diet-derived bioactive compounds. We pay particular attention to microbial influences on host responses to xenobiotics, adding to the growing consensus that treatment outcomes reflect our intimate partnership with the microbial world, and providing an initial framework from which to consider a more comprehensive view of pharmacology and nutrition.
Aging is often accompanied by an increased risk of an array of diseases spanning the cardiovascular, nervous, and immune systems, among others. Despite remarkable progress in understanding the ...cellular and molecular mechanisms involved in aging, the role of the microbiome remains understudied. In this Essay, we highlight recent progress towards understanding if and how the microbiome contributes to aging and age-associated diseases. Furthermore, we discuss the need to consider sexually dimorphic phenotypes in the context of aging and the microbiome. We also highlight the broad implications for this emerging area of interdisciplinary research to address long-standing questions about host-microbiome interactions across the life span.
The human gut microbiota metabolizes the Parkinson's disease medication Levodopa (l-dopa), potentially reducing drug availability and causing side effects. However, the organisms, genes, and enzymes ...responsible for this activity in patients and their susceptibility to inhibition by host-targeted drugs are unknown. Here, we describe an interspecies pathway for gut bacterial l-dopa metabolism. Conversion of l-dopa to dopamine by a pyridoxal phosphate-dependent tyrosine decarboxylase from
is followed by transformation of dopamine to
-tyramine by a molybdenum-dependent dehydroxylase from
These enzymes predict drug metabolism in complex human gut microbiotas. Although a drug that targets host aromatic amino acid decarboxylase does not prevent gut microbial l-dopa decarboxylation, we identified a compound that inhibits this activity in Parkinson's patient microbiotas and increases l-dopa bioavailability in mice.
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