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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 (

Being ubiquitous, fungi are common opportunistic pathogens to humans that can lead to invasive and life-threatening infections in immunocompromised individuals. Eukaryote-resembling cell membrane and filamentous branches make the fungal diagnosis difficult. This study therefore developed a ready-to-use ITS1 loop-mediated isothermal amplification combined with hydroxynaphthol blue (LAMP-HNB) for rapid, sensitive and specific colorimetric detection of universal fungi in all phyla. The ITS1 LAMP-HNB could identify every evolutionary phylum of fungi according to sequence analyses. We tested a total of 30 clinically relevant fungal isolates (representing three major human pathogenic phyla of fungi, namely Zygomycota, Ascomycota and Basidiomycota) and 21 non-fungal isolates, and the ITS1 LAMP-HNB properly identified all isolates, with a detection limit of as low as 4.6 ag (9.6 copies), which was identical to ITS1 and 18S rDNA PCR. The assays were also validated on the feasibility of point-of-care diagnostic with real food (dry peanuts, chili and garlics) and blood samples. Furthermore, the shelf life of our ready-to-use ITS1 LAMP activity (≥50%) was more than 40 days at 30 °C with 3–5% polyvinyl alcohol or glycerol additive. The results supported the ready-to-use ITS1 LAMP-HNB for simple detection of fungi contamination with high sensitivity in local and resource-constrained areas to prevent opportunistic fungal species infections.

Background Skin microbiome varies from person to person due to a combination of various factors, including age, biogeography, sex, cosmetics and genetics. Many skin disorders appear to be related to the resident microflora, yet databases of facial skin microbiome of many biogeographies, including Thai, are limited. Methods Metagenomics derived B-RISA and 16S rRNA gene sequencing was utilized to identify the culture-independent bacterial diversity on Thai male faces (cheek and forehead areas). Skin samples were categorized (grouped) into (i) normal (teenage.hea) and (ii) acne-prone (teenage.acn) young adults, and normal (iii) middle-aged (middle.hea) and (iv) elderly (elderly.hea) adults. Results The 16S rRNA gene sequencing was successful as the sequencing depth had an estimated >98% genus coverage of the true community. The major diversity was found between the young and elderly adults in both cheek and forehead areas, followed by that between normal and acne young adults. Detection of representative characteristics indicated that bacteria from the order Rhizobiales, genera Sphingomonas and Pseudoalteromonas, distinguished the elderly.hea microbiota, along the clinical features of wrinkles and pores. Prediction of the metabolic potential revealed reduced metabolic pathways involved in replication and repair, nucleotide metabolism and genetic translation in the elderly.hea compared with that in the teenage.hea. For young adults, some unique compositions such as abundance of Propionibacterium acnes and Staphylococcus epidermidis, with a minor diversity between normal and acne skins, were detected. The metabolic potentials of the acne vs. normal young adults showed that teenage.acn was low in many cellular processes (e.g., cell motility and environmental adaptation), but high in carbohydrate metabolism, which could support acne growth. Moreover, comparison with the age-matched males from the US (Boulder, Colorado) to gain insight into the diversity across national biogeography, revealed differences in the distribution pattern of species, although common bacteria were present in both biogeographical samples. Furthermore, B-RISA served as a crosscheck result to the 16S rRNA gene sequencing (i.e., differences between teenage and elderly microbiota). Conclusions This study revealed and compared the microbial diversity on different aged Thai male faces, and included analyses for representing the bacterial flora, the clinical skin characteristics, and comparison with the US age-matched. The results represent the first skin microbiota of Thai males, and helps the design of a large-scale skin microbiome study of Thais. The findings of the diversity among ages, skin type and national biogeography supported the importance of these traits in the skin microbiome and in developing a safe and sustainable treatment for acne and aging skin diseases.

Coral reefs are among the most biodiverse habitats on Earth, but knowledge of their associated marinemicrobiome remains limited. To increase the understanding of the coral reef ecosystem in the lower Gulf of Thailand, this study utilized 16S and 18S rRNA gene-based pyrosequencing to identify the prokaryotic and eukaryotic microbiota present in the reef water at Kham Island, Trat province, Thailand (N6.97 E100.86). The obtained result was then compared with the published microbiota from different coral reef water and marine sites. The coral reefs at Kham Island are of the fringe type. The reefs remain preserved and abundant. The community similarity indices (i.e., Lennon similarity index, Yue & Clayton similarity index) indicated that the prokaryotic composition of Kham was closely related to that of Kra, another fringing reef site in the lower Gulf of Thailand, followed by coral reef water microbiota at GS048b (Cooks Bay, Fr. Polynesia), Palmyra (Northern Line Islands, United States) and GS108b (Coccos Keeling, Australia), respectively. Additionally, the microbial eukaryotic populations at Kham was analyzed and compared with the available database at Kra. Both eukaryotic microbiota, in summer and winter seasons, were correlated. An abundance of Dinophysis acuminata was noted in the summer season, in accordance with its reported cause of diarrhoeatic shellfish outbreak in the summer season elsewhere. The slightly lower biodiversity in Kham than at Kra might reflect the partly habitat difference due to coastal anthropogenic activities and minor water circulation, as Kham locates close to the mainland and is surrounded by islands (e.g., Chang and Kut islands). The global marine microbiota comparison suggested relatively similar microbial structures among coral sites irrespective of geographical location, supporting the importance of coral-associated marine microbiomes, and Spearman’s correlation analysis between community membership and factors of shore distance and seawater temperature indicated potential correlation of these factors (p-values < 0.05) with Kham, Kra, and some other coral and coastal sites. Together, this study provided the second marine microbial database for the coral reef of the lower Gulf of Thailand, and a comparison of the coral-associated marine microbial diversity among global ocean sites.