Gut microbiome diversity detected by high-coverage 16S and shotgun sequencing of matched stool and colon biopsy samples

Abstract

The gut microbiome has a fundamental role in human health and disease. However, studying the complex structure and function of the gut microbiome using next generation sequencing is challenging and prone to reproducibility problems due to the heterogeneity of sample sets. Here, we obtained cross-sectional colon biopsies and faecal samples from nine participants in our COLSCREEN study and sequenced them in high coverage using Illumina pair-end shotgun (for faecal samples) and IonTorrent 16S (for paired feces and colon biopsies) technologies. The metagenomes consisted of between 47 and 92 million reads per sample and the targeted sequencing covered more than 300K reads per sample across seven hypervariable regions of the 16S gene. Our data is freely available and coupled with code for the presented metagenomic analysis using up-to-date bioinformatics algorithms. These results will add up to the informed insights into designing comprehensive microbiome analysis and also provide data for further testing for unambiguous gut microbiome analysis.

Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data

“…Consistent with recent work on stool and colon biopsy samples comparing between 16S versus pairend shotgun data [5], we reported variation in abundance results between taxonomic classification tools and databases in addition to sequencing technologies. Our results further showed higher variation between technologies for taxa with lower abundance, and demonstrated that zero inflation in abundance is dependent on both experimental and analytical approaches.…”

“…The 16S ribosomal RNA (rRNA) amplicon sequencing approach targets and specifically sequences the 16S rRNA gene of bacteria and archaea; whereas the shotgun whole genome sequencing approach sequences all genetic material present in a sample, potentially allowing identification to the level of species, detection of the presence of functional units, and concurrent identification of eukaryotes, fungi and DNA viruses. Comparisons between 16S amplicon and shotgun sequencing data have been examined previously, but discrepancy exists among studies regarding which technique provides better robustness and higher biodiversity [4][5][6][7]. Despite the pros and cons of each technique, successes in extracting meaningful biological information have been found for disease and environmental studies [2,[8][9][10][11][12].…”

The role of the microbiome in gastrointestinal inflammation

“…Over the past few decades, research related to the microbiome has intensified, facilitated by rapid advances in culture-independent, high-throughput genomic and metabolomic techniques (10)(11)(12). Consequently, a greater understanding of microbiota population composition and host-microbe interactions has been achieved, especially in the context of human health and disease (11,13,14). Whereas a balanced microbiota has been shown to play an important role in the maintenance of human health, impairment or imbalance in the makeup of the human microbiota (dysbiosis) can disrupt homeostasis and lead to the onset or exacerbation of human disease (15).…”

Gut Microbiota Profile and Changes in Body Weight in Elderly Subjects with Overweight/Obesity and Metabolic Syndrome

“…A customized Python script [ 14 ] was used to separate the reads according to the different hypervariable regions of the 16S rRNA gene, and the V4 data selected and individually processed with the software QIIME (Quantitative Insight into Microbial Ecology) 2, version 2020.2 [ 15 ]. Sequenced reads were demultiplexed, trimmed to 265 bp, and denoised into ASVs (amplicon sequence variants) using the denoise-pyro method of the DADA2 plugin [ 16 ].…”