Metabolomic insights into the intricate gut microbial–host interaction in the development of obesity and type 2 diabetes

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e. niacin), purines and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders

Comparison of commercial DNA preparation kits for the detection of Brucellae in tissue using quantitative real-time PCR

<p>Abstract</p> <p>Background</p> <p>The detection of Brucellae in tissue specimens using PCR assays is difficult because the amount of bacteria is usually low. Therefore, optimised DNA extraction methods are critical. The aim of this study was to assess the performance of commercial kits for the extraction of <it>Brucella </it>DNA.</p> <p>Methods</p> <p>Five kits were evaluated using clinical specimens: QIAamp™ DNA Mini Kit (QIAGEN), peqGold™ Tissue DNA Mini Kit (PeqLab), UltraClean™ Tissue and Cells DNA Isolation Kit (MoBio), DNA Isolation Kit for Cells and Tissues (Roche), and NucleoSpin™ Tissue (Macherey-Nagel). DNA yield was determined using a quantitative real-time PCR assay targeting IS<it>711 </it>that included an internal amplification control.</p> <p>Results</p> <p>Kits of QIAGEN and Roche provided the highest amount of DNA, Macherey-Nagel and Peqlab products were intermediate whereas MoBio yielded the lowest amount of DNA. Differences were significant (p < 0.05) and of diagnostic relevance. Sample volume, elution volume, and processing time were also compared.</p> <p>Conclusions</p> <p>We observed differences in DNA yield as high as two orders of magnitude for some samples between the best and the worst DNA extraction kits and inhibition was observed occasionally. This indicates that DNA purification may be more relevant than expected when the amount of DNA in tissue is very low.</p

Identification of Brucella by MALDI-TOF Mass Spectrometry. Fast and Reliable Identification from Agar Plates and Blood Cultures

BACKGROUND: MALDI-TOF mass spectrometry (MS) is a reliable method for bacteria identification. Some databases used for this purpose lack reference profiles for Brucella species, which is still an important pathogen in wide areas around the world. We report the creation of profiles for MALDI-TOF Biotyper 2.0 database (Bruker Daltonics, Germany) and their usefulness for identifying brucellae from culture plates and blood cultures. METHODOLOGY/PRINCIPAL FINDINGS: We created MALDI Biotyper 2.0 profiles for type strains belonging to B. melitensis biotypes 1, 2 and 3; B. abortus biotypes 1, 2, 5 and 9; B. suis, B. canis, B ceti and B. pinnipedialis. Then, 131 clinical isolates grown on plate cultures were used in triplicate to check identification. Identification at genus level was always correct, although in most cases the three replicates reported different identification at species level. Simulated blood cultures were performed with type strains belonging to the main human pathogenic species (B. melitensis, B. abortus, B. suis and B. canis), and studied by MALDI-TOF MS in triplicate. Identification at genus level was always correct. CONCLUSIONS/SIGNIFICANCE: MALDI-TOF MS is reliable for Brucella identification to the genus level from culture plates and directly from blood culture bottles

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels

BACKGROUND: Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE: To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS: In a case control study, forty male rats were randomly assigned to one of these four experimental groups: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS: In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides–E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides–Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS: Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism