Analysis of the human breast milk microbiome and bacterial extracellular vesicles in healthy mothers

The microbiota of human breast milk (HBM) contribute to infant gut colonization; however, whether bacterial extracellular vesicles (EVs) are present in HBM or might contribute to this process remains unknown. In this study, we characterized the HBM microbiota of healthy Korean mothers and measured the key bacteria likely affecting infant gut colonization by analyzing both the microbiota and bacterial EVs. A total of 22 HBM samples were collected from lactating mothers. The DNA of bacteria and bacteria-derived EVs was extracted from each sample. In alpha-diversity analyses, bacterial samples showed higher richness and evenness than bacterial EV samples, and beta-diversity analyses showed significant differences between bacteria and bacterial EVs within identical individual samples. Firmicutes accounted for the largest proportion among the phyla, followed by Proteobacteria, Bacteroidetes, and Actinobacteria, in both bacteria and bacterial EV samples. At the genus level, Streptococcus (25.1%) and Staphylococcus (10.7%) were predominant in bacterial samples, whereas Bacteroides (9.1%), Acinetobacter (6.9%), and Lactobacillaceae(f) (5.5%) were prevalent in bacterial EV samples. Several genera, including Bifidobacterium, were significantly positively correlated between the two samples. This study revealed the diverse bacterial communities in the HBM of healthy lactating mothers, and found that gut-associated genera accounted for a high proportion in bacterial EV samples. Our findings suggest the existence of key bacteria with metabolic activity that are independent of the major bacterial populations that inhabit HBM, and the possibility that EVs derived from these bacteria are involved in the vertical transfer of gut microbiota.Subject terms: Immunogenetics, Immunization     

Bis-amino methylation for the synthesis of spiro-fused piperidines using iron(III) trifluroacetate in aqueous micellar medium

An environmentally benign, multicomponent integrated chemical process has been developed for the synthesis of 3,5-dispirosubstituted piperidines by cyclo-condensation reaction of amines, formaldehyde, and dimedone using iron(III) trifluroacetate [Fe(F₃CCO₂)₃] Lewis acid in aqueous micellar medium at ambient temperature (25–30 °C). The heterogeneous solid acid catalyst conveniently promotes this double amino methylation reaction in which six molecules condense in one pot to form six new covalent bonds. The synthesized 3,5-dispirosubstituted piperidines have been screened for their in vitro antibacterial activity using agar well method. Many of these compounds showed satisfactory antibacterial activity as compared to standard drugs against all the bacteria tested.     

Monitoring fuel quality: a case study for quinizarin marker content of unleaded petrol marketed in Greece

Fuel adulteration and cross-contamination lead to low-quality fuel products, which may cause increased environmental pollution, loss of taxes and engine problems. An establishment of a quality monitoring mechanism based on laboratory measurements may reveal problematic areas of the fuel supply chain. For the purposes of this work, 97 unleaded petrol samples were measured in order to quantify mass concentration of quinizarin, a substance used in Greece to easily mark the presence of 95 Research Octane Number unleaded petrol in other types of automotive fuels. The samples were obtained from petroleum retail stations selling different brands of fuels and located in different geographic regions of Greece. Statistical analysis of the results revealed quinizarin mass concentrations below the 3 mg L^?1 legislation specification limit and significant differences between brands and geographic regions, which may attributed to the structure of the fuel supply chain in Greece in combination with quinizarin properties and way of handling. Moreover, certain approaches were used for the calculation of decision limits for assessing compliance or non-compliance. These approaches take measurement reproducibility or estimated in-house uncertainty into account, in order to minimize the probability of false rejection.