Trans-ethnic gut microbiota signatures of type 2 diabetes in Denmark and India.

BACKGROUND: Type 2 diabetes (T2D), a multifactorial disease influenced by host genetics and environmental factors, is the most common endocrine disease. Several studies have shown that the gut microbiota as a close-up environmental mediator influences host physiology including metabolism. The aim of the present study is to examine the compositional and functional potential of the gut microbiota across individuals from Denmark and South India with a focus on T2D. Many earlier studies have investigated the microbiome aspects of T2D, and it has also been anticipated that such microbial associations would be dependent on diet and ethnic origin. However, there has been no large scale trans-ethnic microbiome study earlier in this direction aimed at evaluating any "universal" microbiome signature of T2D. METHODS: 16S ribosomal RNA gene amplicon sequencing was performed on stool samples from 279 Danish and 294 Indian study participants. Any differences between the gut microbiota of both populations were explored using diversity measures and negative binomial Wald tests. Study samples were stratified to discover global and country-specific microbial signatures for T2D and treatment with the anti-hyperglycemic drug, metformin. To identify taxonomical and functional signatures of the gut microbiota for T2D and metformin treatment, we used alpha and beta diversity measures and differential abundances analysis, comparing metformin-naive T2D patients, metformin-treated T2D patients, and normoglycemic individuals. RESULTS: Overall, the gut microbial communities of Danes and Indians are compositionally very different. By analyzing the combined study materials, we identify microbial taxonomic and functional signatures for T2D and metformin treatment. T2D patients have an increased relative abundance of two operational taxonomic units (OTUs) from the Lachnospiraceae family, and a decreased abundance of Subdoligranulum and Butyricicoccus. Studying each population per se, we identified T2D-related microbial changes at the taxonomic level within the Danish population only. Alpha diversity indices show that there is no significant difference between normoglycemic individuals and metformin-naive T2D patients, whereas microbial richness is significantly decreased in metformin-treated T2D patients compared to metformin-naive T2D patients and normoglycemic individuals. Enrichment of two OTUs from Bacteroides and depletion of Faecalibacterium constitute a trans-ethnic signature of metformin treatment. CONCLUSIONS: We demonstrate major compositional differences of the gut microbiota between Danish and South Indian individuals, some of which may relate to differences in ethnicity, lifestyle, and demography. By comparing metformin-naive T2D patients and normoglycemic individuals, we identify T2D-related microbiota changes in the Danish and Indian study samples. In the present trans-ethnic study, we confirm that metformin changes the taxonomic profile and functional potential of the gut microbiota.

Trans-ethnic gut microbial signatures of prediabetic subjects from India and Denmark.

BACKGROUND: Recent studies have indicated an association of gut microbiota and microbial metabolites with type 2 diabetes mellitus (T2D). However, large-scale investigation of the gut microbiota of "prediabetic" (PD) subjects has not been reported. Identifying robust gut microbiome signatures of prediabetes and characterizing early prediabetic stages is important for the understanding of disease development and could be crucial in early diagnosis and prevention. METHODS: The current study performed amplification and sequencing on the variable regions (V1-V5) of the 16S rRNA genes to profile and compare gut microbiota of prediabetic individuals (N = 262) with normoglycemic individuals (N = 275) from two cohorts in India and Denmark. Similarly, fasting serum inflammatory biomarkers were profiled from the study participants. RESULTS: After correcting for strong country-specific cohort effect, 16 operational taxonomic units (OTUs) including members from the genera Prevotella9, Phascolarctobacterium, Barnesiella, Flavonifractor, Tyzzerella_4, Bacteroides, Faecalibacterium, and Agathobacter were identified as enriched in normoglycaemic subjects with respect to the subjects with prediabetes using a negative binomial Wald test. We also identified 144 OTUs enriched in the prediabetic subjects, which included members from the genera Megasphaera, Streptococcus, Prevotella9, Alistipes, Mitsuokella, Escherichia/Shigella, Prevotella2, Vibrio, Lactobacillus, Alloprevotella, Rhodococcus, and Klebsiella. Comparative analyses of relative abundance of bacterial taxa revealed that the Streptococcus, Escherichia/Shigella, Prevotella2, Vibrio, and Alloprevotella OTUs exhibited more than fourfold enrichment in the gut microbiota of prediabetic subjects. When considering subjects from the two geographies separately, we were able to identify additional gut microbiome signatures of prediabetes. The study reports a probable association of Megasphaera OTU(s) with impaired glucose tolerance, which is significantly pronounced in Indian subjects. While the overall results confirm a state of proinflammation as early as in prediabetes, the Indian cohort exhibited a characteristic pattern of abundance of inflammatory markers indicating low-grade intestinal inflammation at an overall population level, irrespective of glycemic status. CONCLUSIONS: The results present trans-ethnic gut microbiome and inflammation signatures associated with prediabetes, in Indian and Danish populations. The identified associations may be explored further as potential early indicators for individuals at risk of dysglycemia.

ProViDE: A software tool for accurate estimation of viral diversity in metagenomic samples.

Given the absence of universal marker genes in the viral kingdom, researchers typically use BLAST (with stringent E-values) for taxonomic classification of viral metagenomic sequences. Since majority of metagenomic sequences originate from hitherto unknown viral groups, using stringent e-values results in most sequences remaining unclassified. Furthermore, using less stringent e-values results in a high number of incorrect taxonomic assignments. The SOrt-ITEMS algorithm provides an approach to address the above issues. Based on alignment parameters, SOrt-ITEMS follows an elaborate work-flow for assigning reads originating from hitherto unknown archaeal/bacterial genomes. In SOrt-ITEMS, alignment parameter thresholds were generated by observing patterns of sequence divergence within and across various taxonomic groups belonging to bacterial and archaeal kingdoms. However, many taxonomic groups within the viral kingdom lack a typical Linnean-like taxonomic hierarchy. In this paper, we present ProViDE (Program for Viral Diversity Estimation), an algorithm that uses a customized set of alignment parameter thresholds, specifically suited for viral metagenomic sequences. These thresholds capture the pattern of sequence divergence and the non-uniform taxonomic hierarchy observed within/across various taxonomic groups of the viral kingdom. Validation results indicate that the percentage of 'correct' assignments by ProViDE is around 1.7 to 3 times higher than that by the widely used similarity based method MEGAN. The misclassification rate of ProViDE is around 3 to 19% (as compared to 5 to 42% by MEGAN) indicating significantly better assignment accuracy. ProViDE software and a supplementary file (containing supplementary figures and tables referred to in this article) is available for download from http://metagenomics.atc.tcs.com/binning/ProViDE/