The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies, accompanied by information on study geography, health outcomes, host body site, and experimental, epidemiological, and statistical methods using controlled vocabulary. BugSigDB is seeded for initial release with >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and co-exclusion, and consensus signatures, allowing assessment of microbiome differential abundance within and across experimental conditions, environments, or body sites. Database-wide analysis revealed experimental conditions with the highest level of consistency in signatures reported by independent studies and identified commonalities among disease-associated signatures including frequent introgression of oral pathobionts into the gut.
Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.
Background With the advent of long-term human habitation in space and on the moon, understanding how the built environment microbiome of space habitats differs from Earth habits, and how microbes survive, proliferate and spread in space conditions, is coming more and more important. The Microbial Tracking mission series has been monitoring the microbiome of the International Space Station (ISS) for almost a decade. During this mission series, six unique strains of Gram-positive bacteria, including two spore-forming and three non-spore-forming species, were isolated from the environmental surfaces of the International Space Station (ISS). Results The analysis of their 16S rRNA gene sequences revealed <99% similarities with previously described bacterial species. To further explore their phylogenetic affiliation, whole genome sequencing (WGS) was undertaken. For all strains, the gyrB gene exhibited <93% similarity with closely related species, which proved effective in categorizing these ISS strains as novel species. Average ucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values, when compared to any known bacterial species, were less than <94% and 50% respectively for all species described here. Traditional biochemical tests, fatty acid profiling, polar lipid, and cell wall composition analyses were performed to generate phenotypic characterization of these ISS strains. A study of the shotgun metagenomic reads from the ISS samples, from which the novel species were isolated, showed that only 0.1% of the total reads mapped to the novel species, supporting the idea that these novel species are rare in the ISS environments. In-depth annotation of the genomes unveiled a variety of genes linked to amino acid and derivative synthesis, carbohydrate metabolism, cofactors, vitamins, prosthetic groups, pigments, and protein metabolism. Further analysis of these ISS-isolated organisms revealed that, on average, they contain 46 genes associated with virulence, disease, and defense. The main predicted functions of these genes are: conferring resistance to antibiotics and toxic compounds, and enabling invasion and intracellular resistance. After conducting antiSMASH analysis, it was found that there are roughly 16 cluster types across the six strains, including β-lactone and type III polyketide synthase (T3PKS) clusters. Conclusions Based on these multi-faceted taxonomic methods, it was concluded that these six ISS strains represent five novel species, which we propose to name as follows: Arthrobacter burdickii IIF3SC-B10T (=NRRL B-65660T), Leifsonia virtsii, F6_8S_P_1AT (=NRRL B-65661T), Leifsonia williamsii, F6_8S_P_1BT (=NRRL B-65662T and DSMZ 115932T), Paenibacillus vandeheii, F6_3S_P_1CT(=NRRL B-65663T and DSMZ 115940T), and Sporosarcina highlanderae F6_3S_P_2 T(=NRRL B-65664T and DSMZ 115943T). Identifying and characterizing the genomes and phenotypes of novel microbes found in space habitats, like those explored in this study, is integral for expanding our genomic databases of space-relevant microbes. This approach offers the only reliable method to determine species composition, track microbial dispersion, and anticipate potential threats to human health from monitoring microbes on the surfaces and equipment within space habitats. By unraveling these microbial mysteries, we take a crucial step towards ensuring the safety and success of future space missions.
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