Association between the gut mycobiome and atopic dermatitis was investigated in 9–12-month-old infants using metagenomics. Two groups of atopic dermatitis infants were classified according to their symptom development as outgrown (recovered) and persisted (still undergoing). The evenness and diversity of the mycobiome in the persisted group were higher than in the healthy and outgrown groups. Dysbiosis of the microbiome in the persisted group was observed by a reduction in the Ascomycota/Basidiomycota ratio. Five fungi were selected as markers from each sample group. In the persisted group, Rhodotorula sp. abundance increased significantly, while Wickerhamomyces sp. and Kodamaea sp. abundance increased in the healthy group, and Acremonium sp. and Rhizopus sp. abundance increased considerably in the outgrown group. Metaproteomic analysis revealed that the persisted group had a high abundance of fungal proteins, particularly those from Rhodotorula sp. Unique proteins such as RAN-binding protein 1 and glycerol kinase from Rhodotorula sp. were hypothesized to be related to atopic dermatitis manifestation in infants.

Atopic dermatitis (AD) is a prevalent inflammatory skin disease that has been associated with changes in gut microbial composition in early life. However, there are limited longitudinal studies examining the gut microbiome in AD. This study aimed to explore taxonomy and metabolic functions across longitudinal gut microbiomes associated with AD in early childhood from 9 to 30 months of age using integrative data analysis within the Thai population. Our analysis revealed that gut microbiome diversity was not different between healthy and AD groups; however, significant taxonomic differences were observed. Key gut bacteria with short-chain fatty acids (SCFAs) production potentials, such as Anaerostipes, Butyricicoccus, Ruminococcus, and Lactobacillus species, showed a higher abundance in the AD group. In addition, metabolic alterations between the healthy and AD groups associated with vitamin production and host immune response, such as biosynthesis of menaquinol, succinate, and (Kdo)2-lipid A, were observed. This study serves as the first framework for monitoring longitudinal microbial imbalances and metabolic functions associated with allergic diseases in Thai children during early childhood.

The oomycete Pythium insidiosum infects humans and animals worldwide, and causes the life-threatening condition, called pythosis. Most patients lose infected organs or die from the disease. Comparative genomic analyses of different P. insidiosum strains could provide new insights into its pathobiology, and can lead to discovery of an effective treatment method. Several draft genomes of P. insidiosum are publicly available: three from Asia (Thailand), and one each from North (the United States) and Central (Costa Rica) Americas. We report another draft genome of P. insidiosum isolated from South America (Brazil), to serve as a resource for comprehensive genomic studies. In this study, we report genome sequence of the P. insidiosum strain CBS 101555, isolated from a horse with pythiosis in Brazil. One paired-end (180-bp insert) library of processed genomic DNA was prepared for Illumina HiSeq 2500-based sequencing. Assembly of raw reads provided genome size of 48.9 Mb, comprising 60,602 contigs. A total of 23,254 genes were predicted and classified into 18,305 homologous gene clusters. Compared with the reference genome (the P. insidiosum strain Pi-S), 1,475,337 sequence variants (SNPs and INDELs) were identified in the organism. The genome sequence data has been deposited in DDBJ under the accession numbers BCFP01000001–BCFP01060602.

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

Oomycetes form a unique group of the fungal-like, aquatic, eukaryotic microorganisms. Lifestyle and pathogenicity of the oomycetes are diverse. Many pathogenic oomycetes affect a broad range of plants and cause enormous economic loss annually. Some pathogenic oomycetes cause destructive and deadly diseases in a variety of animals, including humans. No effective antimicrobial agent against the oomycetes is available. Genomic data of many oomycetes are currently available. Comparative analyses of the oomycete genomes must be performed to better understand the oomycete biology and virulence, as well as to identify conserved and biologically important proteins that are potential diagnostic and therapeutic targets of these organisms. However, a tool that facilitates comparative genomic studies of the oomycetes is lacking. Here, we described in detail the Oomycete Gene Table, which is an online user-friendly bioinformatic tool, designed to search, analyze, compare and visualize gene contents of 20 oomycetes in a customizable table. Genomic contents of other oomycete species, when available, can be added to the existing database. Some of the applications of the Oomycete Gene Table include investigations of phylogenomic relationships, as well as identifications of biologically important and pathogenesis-related genes of oomycetes. In summary, the Oomycete Gene Table is a simple and useful tool for comparative genomic analyses of oomycetes.