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Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics. Measurement(s) mock community • Metagenomic profiling Technology Type(s) Illumina HiSeq 3000 • ThermoFisher Ion Proton and GeneStudio S5 • MGI DNBseq G400 and T7 • Oxford Nanopore Sequencing • PacBio Sequel System • Genome mapping and assembly Sample Characteristic - Organism Synthetic microbial communities • Bacteria • Archaea [ABSTRACT FROM AUTHOR]

Complex gene-environment interactions are considered important in the development of obesity. The composition of the gut microbiota can determine the efficacy of energy harvest from food and changes in dietary composition have been associated with changes in the composition of gut microbial populations. The capacity to explore microbiota composition was markedly improved by the development of metagenomic approaches, which have already allowed production of the first human gut microbial gene catalogue and stratifying individuals by their gut genomic profile into different enterotypes, but the analyses were carried out mainly in non-intervention settings. To investigate the temporal relationships between food intake, gut microbiota and metabolic and inflammatory phenotypes, we conducted diet-induced weight-loss and weight-stabilization interventions in a study sample of 38 obese and 11 overweight individuals. Here we report that individuals with reduced microbial gene richness (40%) present more pronounced dys-metabolism and low-grade inflammation, as observed concomitantly in the accompanying paper. Dietary intervention improves low gene richness and clinical phenotypes, but seems to be less efficient for inflammation variables in individuals with lower gene richness. Low gene richness may therefore have predictive potential for the efficacy of intervention. [ABSTRACT FROM AUTHOR]

Introduction: Low gut microbiome richness is associated with dyslipidemia and insulin resistance, and ceramides and other sphingolipids are implicated in the development of diabetes. Objectives: Determine whether circulating sphingolipids, particularly ceramides, are associated with alterations in the gut microbiome among obese patients with increased diabetes risk. Methods: This was a cross-sectional and longitudinal retrospective analysis of a dietary/weight loss intervention. Fasted serum was collected from 49 participants (41 women) and analyzed by HPLC–MS/MS to quantify 45 sphingolipids. Shotgun metagenomic sequencing of stool was performed to profile the gut microbiome. Results: Confirming the link to deteriorated glucose homeostasis, serum ceramides were positively correlated with fasting glucose, but inversely correlated with fasting and OGTT-derived measures of insulin sensitivity and β-cell function. Significant associations with gut dysbiosis were demonstrated, with SM and ceramides being inversely correlated with gene richness. Ceramides with fatty acid chain lengths of 20–24 carbons were the most associated with low richness. Diet-induced weight loss, which improved gene richness, decreased most sphingolipids. Thirty-one MGS, mostly corresponding to unidentified bacteria species, were inversely correlated with ceramides, including a number of Bifidobacterium and Methanobrevibacter smithii. Higher ceramide levels were also associated with increased metagenomic modules for lipopolysaccharide synthesis and flagellan synthesis, two pathogen-associated molecular patterns, and decreased enrichment of genes involved in methanogenesis and bile acid metabolism. Conclusion: This study identifies an association between gut microbiota richness, ceramides, and diabetes risk in overweight/obese humans, and suggests that the gut microbiota may contribute to dysregulation of lipid metabolism in metabolic disorders. [ABSTRACT FROM AUTHOR]

A correction to the article "Dietary intervention impact on gut microbial gene richness" that was published in a 2013 issue is presented.