Maes et al. (2008) published the first paper demonstrating that major depressive disorder (MDD) is accompanied by abnormalities in the microbiota–gut–brain axis, as evidenced by elevated serum IgM/IgA to lipopolysaccharides (LPS) of Gram-negative bacteria, such as Morganella morganii and Klebsiella Pneumoniae. The latter aberrations, which point to increased gut permeability (leaky gut), are linked to activated neuro-immune and oxidative pathways in MDD. To delineate the profile and composition of the gut microbiome in Thai patients with MDD, we examined fecal samples of 32 MDD patients and 37 controls using 16S rDNA sequencing, analyzed α- (Chao1 and Shannon indices) and β-diversity (Bray–Curtis dissimilarity), and conducted linear discriminant analysis (LDA) effect size (LEfSe) analysis. Neither α- nor β-diversity differed significantly between MDD and controls. Rhodospirillaceae, Hungatella, Clostridium bolteae, Hungatella hathewayi, and Clostridium propionicum were significantly enriched in MDD, while Gracillibacteraceae family, Lutispora, and Ruminococcus genus, Ruminococcus callidus, Desulfovibrio piger, Coprococcus comes, and Gemmiger were enriched in controls. Contradictory results have been reported for all these taxa, with the exception of Ruminococcus, which is depleted in six different MDD studies (one study showed increased abundance), many medical disorders that show comorbidities with MDD, and animal MDD models. Our results may suggest a specific profile of compositional gut dysbiosis in Thai MDD patients, with increases in some pathobionts and depletion of some beneficial microbiota. The results suggest that depletion of Ruminococcus may be a more universal biomarker of MDD that may contribute to increased enteral LPS load, LPS translocation, and gut–brain axis abnormalities.

Ribosomal RNA gene amplicon sequencing is commonly used to evaluate microbiome profiles in health and disease and document the impact of interventional treatments. Nanopore sequencing is attractive since it can provide greater classification at the species level. However, optimized protocols to target marker genes for bacterial and fungal profiling are needed. To achieve an increased taxonomic resolution, we developed extraction and full-length amplicon PCR-based approaches using Nanopore sequencing. Three lysis conditions were applied to a mock microbial community, including known bacterial and fungal species: ZymoBIOMICS lysis buffer (ML) alone, incorporating bead-beating (MLB) or bead-beating plus MetaPolyzyme enzymatic treatment (MLBE). In profiling of bacteria in comparison to reference data, MLB had more statistically different bacterial phyla and genera than the other two conditions. In fungal profiling, MLB had a significant increase of Ascomycota and a decline of Basidiomycota, subsequently failing to detect Malassezia and Cryptococcus. Also, a principal coordinates analysis plot by the Bray–Curtis metric showed a significant difference among groups for bacterial (P=0.033) and fungal (P=0.012) profiles, highlighting the importance of understanding the biases present in pretreatment. Overall, microbial profiling and diversity analysis revealed that ML and MLBE are more similar than MLB for both bacteria and fungi; therefore, using this specific pipeline, bead-beating is not recommended for whole gene amplicon sequencing. However, ML alone was suggested as an optimal approach considering DNA yield, taxonomic classification, reagent cost and hands-on time. This could be an initial proof-of-concept study for simultaneous human bacterial and fungal microbiome studies.

The gut microbiota is pivotal to chickens’ overall health, influencing digestion, nutrient absorption, and immune function. Dietary compounds significantly impact gut microbiota composition. House crickets (Acheta domesticus) have emerged as an alternative protein source for animal feed, rich in proteins and beneficial fatty acids. This study compared the gut microbiota in the cecum and ileum of Thai indigenous chicken breeds (Betong Chicken, white feather with black bone chicken, and black feather with black bone chicken) fed with or without house crickets. Using Oxford Nanopore Technology of 16S rDNA, this study found a similar relative abundance of gut bacteria across groups, with dominant bacteria including Firmicute, Bacteroidetes, Proteobacteria, and Actinobacteria. LEfSe analysis identified differential abundance of beneficial bacteria, such as Ruminococcaceae, Rikenella, and Deferribacteres, in the cecum of the black feather with black bone chicken after cricket feeding. Additionally, Lactobacillaceae exhibited differential abundance in the ileum of this breed post-cricket diet. Consequently, this study provides new data into the gut microbiota of Thai indigenous chickens. It suggests that house cricket diets did not significantly alter microbiota diversity but may enhance beneficial bacteria in certain breeds.

Ribosomal RNA gene amplicon sequencing is commonly used to evaluate microbiome profiles in health and disease and document the impact of interventional treatments. Nanopore sequencing is attractive since it can provide greater classification at the species level. However, optimised protocols to target marker genes for bacterial and fungal profiling are needed. To achieve an increased taxonomic resolution, we developed extraction and full-length amplicon PCR-based approaches using Nanopore sequencing. Three lysis conditions were applied to a mock microbial community, including known bacterial and fungal species; the ZymoBIOMICSTM lysis buffer (ML) alone, incorporating bead-beating (MLB), or bead-beating plus MetaPolyzyme enzymatic treatment (MLBE). Profiling of bacterial comparison to reference data, MLB had more statistically different bacterial phyla and genera than the others. Fungal profiling, MLB had a significant increase of Ascomycota and a decline of Basidiomycota, subsequently failing to detect Malassezia and Cryptococcus. Also, the principal coordinates analysis (PCoA) plot by the Bray-Curtis metric showed a significant difference among groups for bacterial (p = 0.033) and fungal (p = 0.012) profiles, highlighting the importance of understanding the biases present in pretreatment. Overall, the microbial profiling and diversity analysis revealed that ML and MLBE have more similarity than MLB for both bacteria and fungi; therefore, using this specific pipeline, bead-beating is not recommended for whole gene amplicon sequencing. However, ML alone was suggested as an optimal approach considering DNA yield, taxonomic classification, reagent cost and hands-on time. This could be an initial proof-of-concept study for simultaneous human bacterial and fungal microbiome studies.