Providing insight into one’s health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.
Bacillus aryabhattai AB211 is a plant growth promoting, Gram-positive firmicute, isolated from the rhizosphere of tea (Camellia sinensis), one of the oldest perennial crops and a major non-alcoholic beverage widely consumed all over the world. The whole genome of B. aryabhattai AB211 was sequenced, annotated and evaluated with special focus on genomic elements related to plant microbe interaction. It’s genome sequence reveals the presence of a 5,403,026 bp chromosome. A total of 5226 putative protein-coding sequences, 16 rRNA, 120 tRNA, 8 ncRNAs, 58 non-protein coding genes, and 11 prophage regions were identified. Genome sequence comparisons between strain AB211 and other related environmental strains of B. aryabhattai, identified about 3558 genes conserved among all B. aryabhattai genomes analyzed. Most of the common genes involved in plant growth promotion activities were found to be present within core genes of all the genomes used for comparison, illustrating possible common plant growth promoting traits shared among all the strains of B. aryabhattai. Besides the core genes, some genes were exclusively identified in the genome of strain AB211. Functional annotation of the genes predicted in the strain AB211 revealed the presence of genes responsible for mineral phosphate solubilization, siderophores, acetoin, butanediol, exopolysaccharides, flagella biosynthesis, surface attachment/biofilm formation, and indole acetic acid production, most of which were experimentally verified in the present study. Genome analysis and experimental evidence suggested that AB211 has robust central carbohydrate metabolism implying that this bacterium can efficiently utilize the root exudates and other organic materials as an energy source. Genes for the production of peroxidases, catalases, and superoxide dismutases, that confer resistance to oxidative stresses in plants were identified in AB211 genome. Besides these, genes for heat shock tolerance, cold shock tolerance, glycine-betaine production, and antibiotic/heavy metal resistance that enable bacteria to survive biotic/abiotic stress were also identified. Based on the genome sequence information and experimental evidence as presented in this study, strain AB211 appears to be metabolically diverse and exhibits tremendous potential as a plant growth promoting bacterium.
Little is known about life in the boron-rich hot springs of trans-Himalayas. Here, we explore the geomicrobiology of a 4438-m-high spring which emanates ~70 °C-water from a boratic microbialite called Shivlinga. Due to low atmospheric pressure, the vent-water is close to boiling point so can entropically destabilize biomacromolecular systems. Starting from the vent, Shivlinga's geomicrobiology was revealed along the thermal gradients of an outflow-channel and a progressivelydrying mineral matrix that has no running water; ecosystem constraints were then considered in relation to those of entropically comparable environments. the spring-water chemistry and sinter mineralogy were dominated by borates, sodium, thiosulfate, sulfate, sulfite, sulfide, bicarbonate, and other macromolecule-stabilizing (kosmotropic) substances. Microbial diversity was high along both of the hydrothermal gradients. Bacteria, eukarya and Archaea constituted >98%, ~1% and <1% of Shivlinga's microbiome, respectively. Temperature constrained the biodiversity at ~50 °C and ~60 °C, but not below 46 °C. Along each thermal gradient, in the vent-to-apron trajectory, communities were dominated by Aquificae/Deinococcus-Thermus, then Chlorobi/Chloroflexi/Cyanobacteria, and finally Bacteroidetes/Proteobacteria/Firmicutes. interestingly, sites of >45 °C were inhabited by phylogenetic relatives of taxa for which laboratory growth is not known at >45 °C. Shivlinga's geomicrobiology highlights the possibility that the system's kosmotrope-dominated chemistry mitigates against the biomacromolecule-disordering effects of its thermal water. The microbial ecologies of habitats that are hydrothermal, or hypersaline, have been well-characterized, and can give insights into the origins of early life on Earth 1-3. Both chaotrope-rich hypersaline brines and high-temperature freshwater systems can entropically disorder the macromolecules of cellular systems, and are in this way analogous as microbial habitats 4-7. Indeed, highly-chaotropic and hydrothermal habitats are comparable at various scales of biology: the biomacromolecule, cellular system, and functional ecosystem 8,9. Chaotropic, hypersaline habitats include the MgCl 2-constrained ecosystems located at the interfaces of some of the stratified deep-sea hypersaline brines and their overlying seawater. Biophysical, culture-based, and metagenomic studies of the steep haloclines found at these interfaces have revealed that macromolecule-disordering (chaotropic) activities of MgCl 2 not only determine microbial community composition, but also limit Earth's functional biosphere 5,7,10 in such locations, as in situ microbial communities stop functioning at 2.2-2.4 M MgCl 2
Background Rapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut microbiome of patients with RA to identify features that are associated with, as well as predictive of, minimum clinically important improvement (MCII) in disease activity. Methods We conducted a retrospective, observational cohort study on patients diagnosed with RA between 1988 and 2014. Whole metagenome shotgun sequencing was performed on 64 stool samples, which were collected from 32 patients with RA at two separate time-points approximately 6–12 months apart. The Clinical Disease Activity Index (CDAI) of each patient was measured at both time-points to assess achievement of MCII; depending on this clinical status, patients were distinguished into two groups: MCII+ (who achieved MCII; n = 12) and MCII− (who did not achieve MCII; n = 20). Multiple linear regression models were used to identify microbial taxa and biochemical pathways associated with MCII while controlling for potentially confounding factors. Lastly, a deep-learning neural network was trained upon gut microbiome, clinical, and demographic data at baseline to classify patients according to MCII status, thereby enabling the prediction of whether a patient will achieve MCII at follow-up. Results We found age to be the largest determinant of the overall compositional variance in the gut microbiome (R2 = 7.7%, P = 0.001, PERMANOVA). Interestingly, the next factor identified to explain the most variance in the gut microbiome was MCII status (R2 = 3.8%, P = 0.005). Additionally, by looking at patients’ baseline gut microbiome profiles, we observed significantly different microbiome traits between patients who eventually showed MCII and those who did not. Taxonomic features include alpha- and beta-diversity measures, as well as several microbial taxa, such as Coprococcus, Bilophila sp. 4_1_30, and Eubacterium sp. 3_1_31. Notably, patients who achieved clinical improvement had higher alpha-diversity in their gut microbiomes at both baseline and follow-up visits. Functional profiling identified fifteen biochemical pathways, most of which were involved in the biosynthesis of L-arginine, L-methionine, and tetrahydrofolate, to be differentially abundant between the MCII patient groups. Moreover, MCII+ and MCII− groups showed significantly different fold-changes (from baseline to follow-up) in eight microbial taxa and in seven biochemical pathways. These results could suggest that, depending on the clinical course, gut microbiomes not only start at different ecological states, but also are on separate trajectories. Finally, the neural network proved to be highly effective in predicting which patients will achieve MCII (balanced accuracy = 90.0%, leave-one-out cross-validation), demonstrating potential clinical utility of gut microbiome profiles. Conclusions Our findings confirm the presence of taxonomic and functional signatures of the gut microbiome associated with MCII in RA patients. Ultimately, modifying the gut microbiome to enhance clinical outcome may hold promise as a future treatment for RA.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.