Our microbiota presents peculiarities and characteristics that may be altered by multiple factors. The degree and consequences of these alterations depend on the nature, strength and duration of the perturbations as well as the structure and stability of each microbiota. The aim of this review is to sketch a very broad picture of the factors commonly influencing different body sites, and which have been associated with alterations in the human microbiota in terms of composition and function. To do so, first, a graphical representation of bacterial, fungal and archaeal genera reveals possible associations among genera affected by different factors. Then, the revision of sequence-based predictions provides associations with functions that become part of the active metabolism. Finally, examination of microbial metabolite contents and fluxes reveals whether metabolic alterations are a reflection of the differences observed at the level of population structure, and in the last step, link microorganisms to functions under perturbations that differ in nature and aetiology. The utilisation of complementary technologies and methods, with a special focus on metabolomics research, is thoroughly discussed to obtain a global picture of microbiota composition and microbiome function and to convey the urgent need for the standardisation of protocols.

AimThe aim of the study was to compare maternal and cord blood levels of betatrophin – a new peptide potentially controlling beta cell growth - as well as in its mRNA expression in subcutaneous adipose tissue, visceral adipose tissue and placental tissue obtained from pregnant women with normal glucose tolerance (NGT) and gestational diabetes (GDM).MethodsSerum betatrophin and irisin concentrations were measured by ELISA in 93 patients with GDM and 97 women with NGT between 24 and 28 week of gestation. Additionally, maternal and cord blood betatrophin and irisin, as well as their genes (C19orf80 and Fndc5) expression were evaluated in 20 patients with GDM and 20 women with NGT at term.ResultsIn both groups, serum betatrophin concentrations were significantly higher in the patients with GDM than in the controls (1.91 [1.40-2.60] ng/ml vs 1.63 [1.21-2.22] ng/ml, p=0.03 and 3.45 [2.77-6.53] ng/ml vs 2.78 [2.16-3.65] ng/ml, p=0.03, respectively). Cord blood betatrophin levels were also higher in the GDM than in the NGT group (20.43 [12.97-28.80] ng/ml vs 15.06 [10.11-21.36] ng/ml, p=0.03). In both groups betatrophin concentrations in arterial cord blood were significantly higher than in maternal serum (p=0.0001). Serum irisin levels were significantly lower in the patients with GDM (1679 [1308-2171] ng/ml) than in the healthy women between 24 and 28 week of pregnancy (1880 [1519-2312] ng/ml, p=0.03). Both C19orf80 and Fndc5 mRNA expression in fat and placental tissue did not differ significantly between the groups studied.ConclusionsOur results suggest that an increase in maternal and cord blood betatrophin might be a compensatory mechanism for enhanced insulin demand in GDM.

Due to many adverse effects of gestational diabetes mellitus (GDM) on the mother and fetus, its diagnosis is crucial. The presence of GDM can be confirmed by an abnormal fasting plasma glucose level (aFPG) and/or oral glucose tolerance test (OGTT) performed mostly between 24 and 28 gestational week. Both aFPG and abnormal glucose tolerance (aGT) are used to diagnose GDM. In comparison to measurement of FPG, OGTT is time-consuming, usually inconvenient for the patient, and very often needs to be repeated. Therefore, it is necessary to seek tests that will be helpful and convenient to diagnose GDM. For this reason, we investigated the differences in fasting serum metabolites between GDM women with abnGM and normal FPG (aGT-GDM group), with aFPG and normal glucose metabolism (aFPG-GDM group) as well as pregnant women with normal glucose tolerance (NGT) being a control group. Serum metabolites were measured by an untargeted approach using gas chromatography–mass spectrometry (GC–MS). In the discovery phase, fasting serum samples collected from 79 pregnant women (aFPG-GDM, n = 24; aGT-GDM, n = 26; NGT, n = 29) between 24 and 28 weeks of gestation (gwk) were fingerprinted. A set of metabolites (α–hydroxybutyric acid (α–HB), β–hydroxybutyric acid (β–HB), and several fatty acids) significant in aGT-GDM vs NGT but not significant in aFPG-GDM vs NGT comparison in the discovery phase was selected for validation. These metabolites were quantified by a targeted GC–MS method in a validation cohort consisted of 163 pregnant women (aFPG-GDM, n = 51; aGT-GDM, n = 44; and NGT, n = 68). Targeted analyses were also performed on the serum collected from 92 healthy women in the first trimester (8–14 gwk) who were NGT at this time, but in the second trimester (24–28 gwk) they were diagnosed with GDM. It was found that α–HB, β–HB, and several fatty acids were associated with aGT-GDM. A combination of α–HB, β–HB, and myristic acid was found highly specific and sensitive for the diagnosis of GDM manifested by aGT-GDM (AUC = 0.828) or to select women at a risk of aGT-GDM in the first trimester (AUC = 0.791). Our findings provide new potential markers of GDM and may have implications for its early diagnosis.

Multiple mechanisms have been suggested to confer to the pathophysiology of metabolic syndrome (MetS), however despite great interest from the scientific community, the exact contribution of each of MetS risk factors still remains unclear. The present study aimed to investigate molecular signatures in peripheral blood of individuals affected by MetS and different degrees of obesity. Metabolic health of 1204 individuals from 1000PLUS cohort was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, “healthy obese”, and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis were carried out. MetS obese and MetS lean study participants showed the upregulation of genes involved in inflammation and coagulation processes: granulocyte adhesion and diapedesis (p < 0.0001, p = 0.0063), prothrombin activation pathway (p = 0.0032, p = 0.0091), coagulation system (p = 0.0010, p = 0.0155). The results for “healthy obese” indicate enrichment in molecules associated with protein synthesis (p < 0.0001), mitochondrial dysfunction (p < 0.0001), and oxidative phosphorylation (p < 0.0001). Our results suggest that MetS is related to the state of inflammation and vascular system changes independent of excess body weight. Furthermore, “healthy obese”, despite not fulfilling the criteria for MetS diagnosis, seems to display an intermediate state with a lower degree of metabolic abnormalities, before they proceed to a full blown MetS.

The analysis of the microbial metabolome is crucial to fully understand the symbiotic relation between humans and microbes. That is why an explosion of metabolomics took place in the area. So far, at least several hundreds of microbial metabolites have been shown to be statistically altered when humans undergo a plethora of commonly faced perturbations. NMR and MS, usually coupled with GC, LC and CE have revealed their identities. CE is a robust analytical platform for the analysis of polar and ionic metabolites that are essential in order to assess the cells' activity. Due to its novelty, only 5% of the metabolomics studies investigate gut microbiota using CE, even though the metabolites found by CE as being significantly altered in human microbiota represent around 23% of the total number of metabolites identified by metabolomics tools. Herein, we discuss the advances of metabolomics in the frame of other OMICS techniques for human gut microbiota analysis. Afterwards, we focus on sample treatment, analytical methods and data processing in CE coupled to any detector that have been reported to date in order to enhance metabolite coverage in the art, and to identify metabolite markers that cannot be covered by other platforms but are of key importance for determining microbial activity and human health.