The gut microbiota benefits humans via short-chain fatty acid (SCFA) production from carbohydrate fermentation, and deficiency in SCFA production is associated with type 2 diabetes mellitus (T2DM). We conducted a randomized clinical study of specifically designed isoenergetic diets, together with fecal shotgun metagenomics, to show that a select group of SCFA-producing strains was promoted by dietary fibers and that most other potential producers were either diminished or unchanged in patients with T2DM. When the fiber-promoted SCFA producers were present in greater diversity and abundance, participants had better improvement in hemoglobin A1c levels, partly via increased glucagon-like peptide-1 production. Promotion of these positive responders diminished producers of metabolically detrimental compounds such as indole and hydrogen sulfide. Targeted restoration of these SCFA producers may present a novel ecological approach for managing T2DM.

We investigated the relationship between gut health, visceral fat dysfunction and metabolic disorders in diet-induced obesity. C57BL/6J mice were fed control or high saturated fat diet (HFD). Circulating glucose, insulin and inflammatory markers were measured. Proximal colon barrier function was assessed by measuring transepithelial resistance and mRNA expression of tight-junction proteins. Gut microbiota profile was determined by 16S rDNA pyrosequencing. Tumor necrosis factor (TNF)-α and interleukin (IL)-6 mRNA levels were measured in proximal colon, adipose tissue and liver using RT-qPCR. Adipose macrophage infiltration (F4/80+) was assessed using immunohistochemical staining. HFD mice had a higher insulin/glucose ratio (P = 0.020) and serum levels of serum amyloid A3 (131%; P = 0.008) but reduced circulating adiponectin (64%; P = 0.011). In proximal colon of HFD mice compared to mice fed the control diet, transepithelial resistance and mRNA expression of zona occludens 1 were reduced by 38% (P<0.001) and 40% (P = 0.025) respectively and TNF-α mRNA level was 6.6-fold higher (P = 0.037). HFD reduced Lactobacillus (75%; P<0.001) but increased Oscillibacter (279%; P = 0.004) in fecal microbiota. Correlations were found between abundances of Lactobacillus (r = 0.52; P = 0.013) and Oscillibacter (r = −0.55; P = 0.007) with transepithelial resistance of the proximal colon. HFD increased macrophage infiltration (58%; P = 0.020), TNF-α (2.5-fold, P<0.001) and IL-6 mRNA levels (2.5-fold; P = 0.008) in mesenteric fat. Increased macrophage infiltration in epididymal fat was also observed with HFD feeding (71%; P = 0.006) but neither TNF-α nor IL-6 was altered. Perirenal and subcutaneous adipose tissue showed no signs of inflammation in HFD mice. The current results implicate gut dysfunction, and attendant inflammation of contiguous adipose, as salient features of the metabolic dysregulation of diet-induced obesity.

The isocaloric KD was not accompanied by increased body fat loss but was associated with relatively small increases in EE that were near the limits of detection with the use of state-of-the-art technology. This trial was registered at clinicaltrials.gov as NCT01967563.

Objective: To distinguish the effects of dietary fat profile on gut parameters and their relationships with metabolic changes and to determine the capacity of n-3 fatty acids to modify gut variables in the context of diet-induced metabolic dysfunctions. Methods: Mice received control or high-fat diets emphasizing saturated (HFD-sat), n-6 (HFD-n6), or n-3 (HFD-n3) fatty acids for 8 weeks. In another cohort, mice that were maintained on HFD-sat received n-3-rich fish oil or resolvin D1 supplementation. Results: HFD-sat and HFD-n6 induced similar weight gain, but only HFD-sat increased index of insulin resistance (HOMA-IR), colonic permeability, and mesenteric fat inflammation. Hydrogen sulfide-producing bacteria were one of the major groups driving the diet-specific changes in gut microbiome, with the overall microbial profile being associated with changes in body weight, HOMA-IR, and gut permeability. In mice maintained on HFD-sat, fish oil and resolvin D1 restored barrier function and reduced inflammation in the colon but were unable to normalize HOMA-IR. Conclusions: Different dietary fat profiles led to distinct intestinal and metabolic outcomes that are independent of obesity. Interventions targeting inflammation successfully restored gut health but did not reverse systemic aspects of diet-induced metabolic dysfunction, implicating separation between gut dysfunctions and disease-initiating and/or -maintaining processes.

Increased visceral fat, as opposed to subcutaneous/gluteal, most strongly relates to key metabolic dysfunctions including insulin resistance, hepatic steatosis, and inflammation. Mesenteric fat hypertrophy in patients with Crohn's disease and in experimental rodent models of gut inflammation suggest that impaired gut barrier function with increased leakage of gut‐derived antigens may drive visceral lipid deposition. The aim of this study was to determine whether increased intestinal permeability is associated with visceral adiposity in healthy humans. Normal to overweight female subjects were recruited from a population‐based cohort. Intestinal permeability was assessed using the ratio of urinary excretion of orally ingested sucralose to mannitol (S/M). In study 1 (n = 67), we found a positive correlation between waist circumference and S/M excretion within a time frame of urine collection consistent with permeability of the lower gastrointestinal tract (6–9 hours post‐ingestion; P = 0.022). These results were followed up in study 2 (n = 55) in which we used computed tomography and dual energy X‐ray absorptiometry to measure visceral and subcutaneous fat areas of the abdomen, liver fat content, and total body fat of the same women. The S/M ratio from the 6–12 h urine sample correlated with visceral fat area (P = 0.0003) and liver fat content (P = 0.004), but not with subcutaneous or total body fat. This novel finding of an association between intestinal permeability and visceral adiposity and liver fat content in healthy humans suggests that impaired gut barrier function should be further explored as a possible mediator of excess visceral fat accumulation and metabolic dysfunction.

Gut microbes comprise a high density, biologically active community that lies at the interface of an animal with its nutritional environment. Consequently their activity profoundly influences many aspects of the physiology and metabolism of the host animal. A range of microbial structural components and metabolites directly interact with host intestinal cells and tissues to influence nutrient uptake and epithelial health. Endocrine, neuronal and lymphoid cells in the gut also integrate signals from these microbial factors to influence systemic responses. Dysregulation of these host-microbe interactions is now recognised as a major risk factor in the development of metabolic dysfunction. This is a two-way process and understanding the factors that tip host-microbiome homeostasis over to dysbiosis requires greater appreciation of the host feedbacks that contribute to regulation of microbial community composition. To date, numerous studies have employed taxonomic profiling approaches to explore the links between microbial composition and host outcomes (especially obesity and its comorbidities), but inconsistent host-microbe associations have been reported. Available data indicates multiple factors have contributed to discrepancies between studies. These include the high level of functional redundancy in host-microbiome interactions combined with individual variation in microbiome composition; differences in study design, diet composition and host system between studies; and inherent limitations to the resolution of rRNA-based community profiling. Accounting for these factors allows for recognition of the common microbial and host factors driving community composition and development of dysbiosis on high fat diets. New therapeutic intervention options are now emerging.

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem’s higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same “guild” if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of “guild” to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases.

BackgroundObesity is a consequence of chronic energy imbalance. We need accurate and precise measurements of energy intake and expenditure, as well as the related behaviors, to fully understand how energy homeostasis is regulated in order to develop interventions and evaluate their effectiveness to combat the global obesity epidemic.Scope of reviewWe provide an in-depth review of the methodologies currently used to measure energy intake and expenditure in humans, including their principles, advantages, and limitations in the clinical research setting. The aim is to provide researchers with a comprehensive guide to conduct obesity research of the highest possible quality.Major conclusionsAn array of methodologies is available to measure various aspects of energy metabolism and none is perfect under all circumstances. The choice of methods should be specific to particular research questions with practicality and quality of data the priorities for consideration. A combination of complementary measurements may be preferable. There is an imperative need to develop new methodologies to improve the accuracy and precision of energy intake assessments.