Genetic determinants of in vivo fitness and diet responsiveness in multiple human gut
            <i>Bacteroides</i>

Wu, Meng; McNulty, Nathan P.; Rodionov, Dmitry A.; Khoroshkin, Matvei; Griffin, Nicholas W.; Cheng, Jiye; Latreille, Phil; Kerstetter, Randall A.; Terrapon, Nicolas; Henrissat, Bernard; Osterman, Andrei L.; Gordon, Jeffrey I.

doi:10.1126/science.aac5992

Cited by 217 publications

(237 citation statements)

References 44 publications

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“…These results highlight the importance of dietary macronutrients and exercise on positively shaping the gut microbiota composition. Fascinating discoveries have been made from the recently development multi-taxon Insertion Sequencing (INSeq) method, which monitors the genetic factors that enable members of the gut microbial community to flourish within this niche 75. This approach can be used to understand the mechanisms (gene-level characterisation) that determine gut microbial fitness and perturbation through diet, disease and clinical treatment.…”

Section: Diet and Obesitymentioning

confidence: 99%

Gut microbiota, obesity and diabetes

Patterson

Ryan

Cryan

et al. 2016

Postgraduate Medical Journal

443

281

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The central role of the intestinal microbiota in the progression and, equally, prevention of metabolic dysfunction is becoming abundantly apparent. The symbiotic relationship between intestinal microbiota and host ensures appropriate development of the metabolic system in humans. However, disturbances in composition and, in turn, functionality of the intestinal microbiota can disrupt gut barrier function, a trip switch for metabolic endotoxemia. This low-grade chronic inflammation, brought about by the influx of inflammatory bacterial fragments into circulation through a malfunctioning gut barrier, has considerable knock-on effects for host adiposity and insulin resistance. Conversely, recent evidence suggests that there are certain bacterial species that may interact with host metabolism through metabolite-mediated stimulation of enteric hormones and other systems outside of the gastrointestinal tract, such as the endocannabinoid system. When the abundance of these keystone species begins to decline, we see a collapse of the symbiosis, reflected in a deterioration of host metabolic health. This review will investigate the intricate axis between the microbiota and host metabolism, while also addressing the promising and novel field of probiotics as metabolic therapies.

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Section: Diet and Obesitymentioning

confidence: 99%

Gut microbiota, obesity and diabetes

Patterson

Ryan

Cryan

et al. 2016

Postgraduate Medical Journal

443

281

View full text Add to dashboard Cite

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“…In this study, protein consumption was associated with elevated microbial diversity (across 22 phyla), and athletes with a lower BMI had higher levels of Akkermansia , which has been inversely correlated with obesity in both mice [33] and humans [34] . Finally, a recent animal study has found, using a novel approach (multi-taxon insertion sequencing method), that the host genotype may influence dietmicrobiome interactions [35] .…”

Section: The Gut Microbiotamentioning

confidence: 99%

Gut Microbiota, Bacterial Translocation, and Interactions with Diet: Pathophysiological Links between Major Depressive Disorder and Non-Communicable Medical Comorbidities

Slyepchenko

Maes

Jacka

et al. 2016

Psychother Psychosom

211

136

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Background: Persistent low-grade immune-inflammatory processes, oxidative and nitrosative stress (O&NS), and hypothalamic-pituitary-adrenal axis activation are integral to the pathophysiology of major depressive disorder (MDD). The microbiome, intestinal compositional changes, and resultant bacterial translocation add a new element to the bidirectional interactions of the gut-brain axis; new evidence implicates these pathways in the patho-aetiology of MDD. In addition, abnormalities in the gut-brain axis are associated with several chronic non-communicable disorders, which frequently co-occur in individuals with MDD, including but not limited to irritable bowel syndrome (IBS), chronic fatigue syndrome (CFS), obesity, and type 2 diabetes mellitus (T2DM). Methods: We searched the PubMed/MEDLINE database up until May 1, 2016 for studies which investigated intestinal dysbiosis and bacterial translocation (the ‘leaky gut') in the pathophysiology of MDD and co-occurring somatic comorbidities with an emphasis on IBS, CFS, obesity, and T2DM. Results: The composition of the gut microbiota is influenced by several genetic and environmental factors (e.g. diet). Several lines of evidence indicate that gut-microbiota-diet interactions play a significant pathophysiological role in MDD and related medical comorbidities. Gut dysbiosis and the leaky gut may influence several pathways implicated in the biology of MDD, including but not limited to immune activation, O&NS, and neuroplasticity cascades. However, methodological inconsistencies and limitations limit comparisons across studies. Conclusions: Intestinal dysbiosis and the leaky gut may constitute a key pathophysiological link between MDD and its medical comorbidities. This emerging literature opens relevant preventative and therapeutic perspectives.

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“…Additionally, studies of the human gut microbiome have identified GH43 enzymes to be among the most abundant CAZymes present (16,17). Such abundance in both cases suggests an important role in accessing a wide range of complex substrates and highlights the need for accurate functional predictions for GH43 enzymes in genomic and metagenomic studies.…”

mentioning

confidence: 99%

“…The family is dominated by bacterial sequences (4,197), with eukaryotic (312) and archaeal (17) sequences also contained in the group. The functional characteristics of this family have been studied comparatively well, with 146 members that have been characterized biochemically against a natural or synthetic substrate, but this analysis still lags far behind the deposition of new sequences.…”

mentioning

confidence: 99%

Dividing the Large Glycoside Hydrolase Family 43 into Subfamilies: a Motivation for Detailed Enzyme Characterization

Mewis

Lenfant

Lombard

et al. 2016

Appl Environ Microbiol

Self Cite

188

167

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dThe rapid rise in DNA sequencing has led to an expansion in the number of glycoside hydrolase (GH) families. The GH43 family currently contains ␣-L-arabinofuranosidase, ␤-D-xylosidase, ␣-L-arabinanase, and ␤-D-galactosidase enzymes for the debranching and degradation of hemicellulose and pectin polymers. Many studies have revealed finer details about members of GH43 that necessitate the division of GH43 into subfamilies, as was done previously for the GH5 and GH13 families. The work presented here is a robust subfamily classification that assigns over 91% of all complete GH43 domains into 37 subfamilies that correlate with conserved sequence residues and results of biochemical assays and structural studies. Furthermore, cooccurrence analysis of these subfamilies and other functional modules revealed strong associations between some GH43 subfamilies and CBM6 and CBM13 domains. Cooccurrence analysis also revealed the presence of proteins containing up to three GH43 domains and belonging to different subfamilies, suggesting significant functional differences for each subfamily. Overall, the subfamily analysis suggests that the GH43 enzymes probably display a hitherto underestimated variety of subtle specificity features that are not apparent when the enzymes are assayed with simple synthetic substrates, such as pNP-glycosides. Carbohydrates serve a range of functional purposes in biological systems, including energy storage, signal transduction, and intracellular trafficking, among others (1). Importantly, carbohydrates are the main end product of plant primary production, representing a large of majority of carbon fixation by plants (2). As a photosynthetically renewable form of fixed carbon, plant biomass represents a prime target for the replacement of petroleumderived fuels for future sustainability efforts. The enzymatic degradation and modification of carbohydrates have thus been cast to the forefront of biofuel production research (3).As functional efforts to discover plant cell wall polysaccharide (PCWP)-degrading enzymes identify novel activities and mechanisms (4, 5), it is important to derive and maintain a concise classification system for these enzymes. A sequence-based classification of carbohydrate-active enzymes (CAZymes) began in 1991 (6), with the classification of 35 families of glycoside hydrolases (GHs). Today the CAZy database (7) comprises 5 separate enzyme classes, namely, the aforementioned GHs, glycosyltransferases (GTs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and auxiliary activities (AAs), as well as associated carbohydrate binding modules (CBMs), that together correspond to over 530,000 individual sequences (at the time of submission of this article). The largest of these classes are the glycoside hydrolases, currently represented by over 241,000 sequences classified into 133 families based on amino acid sequence similarity.The rapid advancements in DNA sequencing over the past decade have exponentially increased the number of sequences assigned to each family. Henc...

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Genetic determinants of in vivo fitness and diet responsiveness in multiple human gut Bacteroides

Cited by 217 publications

References 44 publications

Gut microbiota, obesity and diabetes

Gut microbiota, obesity and diabetes

Gut Microbiota, Bacterial Translocation, and Interactions with Diet: Pathophysiological Links between Major Depressive Disorder and Non-Communicable Medical Comorbidities

Dividing the Large Glycoside Hydrolase Family 43 into Subfamilies: a Motivation for Detailed Enzyme Characterization

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