Non-significant influence between aerobic and anaerobic sample transport materials on gut (fecal) microbiota in healthy and fat-metabolic disorder Thai adults.

Background: The appropriate sample handling for human fecal microbiota studies is essential to prevent changes in bacterial composition and quantities that could lead to misinterpretation of the data. Methods: This study firstly identified the potential effect of aerobic and anaerobic fecal sample collection and transport materials on microbiota and quantitative microbiota in healthy and fat-metabolic disorder Thai adults aged 23-43 years. We employed metagenomics followed by 16S rRNA gene sequencing and 16S rRNA gene qPCR, to analyze taxonomic composition, alpha diversity, beta diversity, bacterial quantification, Pearson's correlation with clinical factors for fat-metabolic disorder, and the microbial community and species potential metabolic functions. Results: Our study successfully obtained microbiota results in percent and quantitative compositions. Each sample exhibited quality sequences with a >99% Good's coverage index, and a relatively plateau rarefaction curve. Alpha diversity indices showed no statistical difference in percent and quantitative microbiota OTU richness and evenness, between aerobic and anaerobic sample transport materials. Obligate and facultative anaerobic species were analyzed and no statistical difference was observed. Supportively, the beta diversity analysis by non-metric multidimensional scale (NMDS) constructed using various beta diversity coefficients showed resembling microbiota community structures between aerobic and anaerobic sample transport groups (P = 0.86). On the other hand, the beta diversity could distinguish microbiota community structures between healthy and fat-metabolic disorder groups (P = 0.02), along with Pearson's correlated clinical parameters (i.e., age, liver stiffness, GGT, BMI, and TC), the significantly associated bacterial species and their microbial metabolic functions. For example, genera such as Ruminococcus and Bifidobacterium in healthy human gut provide functions in metabolisms of cofactors and vitamins, biosynthesis of secondary metabolites against gut pathogens, energy metabolisms, digestive system, and carbohydrate metabolism. These microbial functional characteristics were also predicted as healthy individual biomarkers by LEfSe scores. In conclusion, this study demonstrated that aerobic sample collection and transport (<48 h) did not statistically affect the microbiota and quantitative microbiota analyses in alpha and beta diversity measurements. The study also showed that the short-term aerobic sample collection and transport still allowed fecal microbiota differentiation between healthy and fat-metabolic disorder subjects, similar to anaerobic sample collection and transport. The core microbiota were analyzed, and the findings were consistent. Moreover, the microbiota-related metabolic potentials and bacterial species biomarkers in healthy and fat-metabolic disorder were suggested with statistical bioinformatics (i.e., Bacteroides plebeius).

Analysis of cutaneous bacterial microbiota of Thai patients with seborrheic dermatitis.

Seborrheic dermatitis (SD) is a chronic inflammatory skin condition that occurs in body areas that contain profuse sebaceous glands. Skin microbiota are diverse across ethnic groups and its dysbiosis has been implicated in the pathogenesis of SD. Here, we reported the contribution of cutaneous bacterial microbiota to SD in the Thai population. Healthy individuals and patients with scalp SD were recruited into the study. Normal skin, scalp skin lesion (SL) and non-lesion sites (SNL) samples were collected using a tape stripping method and next-generation sequencing of 16S rRNA for microbiome analysis. Although bacterial diversity in all sample groups was not statistically different, a population of bacteria commonly found on skin of scalp showed signs of dysbiosis. Apart from the reduction of Corynebacterium spp., SD-specific microbiota was dominated by Firmicutes at taxa level and Pseudomonas spp., Staphylococcus spp. and Micrococcus spp. at genus level. The dysbiosis of the skin microbiota in SD was specifically described as an alteration of bacteria populations commonly found on scalp skin, implying that managing and controlling the cutaneous bacterial microbiome can alleviate and prevent SD and pave the way for the development of new SD treatments.

First reported quantitative microbiota in different livestock manures used as organic fertilizers in the Northeast of Thailand.

Northeastern Thailand relies on agriculture as a major economic activity, and has used high levels of agrochemicals due to low facility, and salty sandy soil. To support soil recovery and sustainable agriculture, local farmers have used organic fertilizers from farmed animal feces. However, knowledge about these animal fecal manures remains minimal restricting their optimal use. Specifically, while bacteria are important for soil and plant growth, an abundance and a diversity of bacterial composition in these animal fecal manures have not been reported to allow selection and adjustment for a more effective organic fertilizer. This study thereby utilized metagenomics combined with 16S rRNA gene quantitative PCR (qPCR) and sequencing to analyze quantitative microbiota profiles in association with nutrients (N, P, K), organic matters, and the other physiochemical properties, of the commonly used earthworm manure and other manures from livestock animals (including breed and feeding diet variations) in the region. Unlike the other manures, the earthworm manure demonstrated more favorable nutrient profiles and physiochemical properties for forming fertile soil. Despite low total microbial biomass, the microbiota were enriched with maximal OTUs and Chao richness, and no plant pathogenic bacteria were found based on the VFDB database. The microbial metabolic potentials supported functions to promote crop growth, such as C, N and P cyclings, xenobiotic degradation, and synthesis of bioactive compounds. Pearson's correlation analyses indicated that the quantitative microbiota of the earthworm manure were clustered in the same direction as N, and conductivity, salinity, and water content were essential to control the microbiota of animal manures.

Inactivation of ahpC renders Stenotrophomonas maltophilia resistant to the disinfectant hydrogen peroxide.

Inactivation of ahpC, encoding alkyl hydroperoxide reductase, rendered Stenotrophomonas maltophilia more resistant to H2O2; the phenotype was directly correlated with enhanced total catalase activity, resulting from an increased level of KatA catalase. Plasmid-borne expression of ahpC from pAhpCsm could complement all of the mutant phenotypes. Mutagenesis of the proposed AhpC peroxidactic and resolving cysteine residues to alanine (C47A and C166A) on the pAhpCsm plasmid diminished its ability to complement the ahpC mutant phenotypes, suggesting that the mutagenized ahpC was non-functional. As mutations commonly occur in bacteria living in hostile environment, our data suggest that point mutations in ahpC at codons required for the enzyme function (such as C47 and C166), the AhpC will be non-functional, leading to high resistance to the disinfectant H2O2.