Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing

Abstract

The human microbiome has emerged as a major player in regulating human health and disease. Translation studies of the microbiome have the potential to indicate clinical applications such as fecal transplants and probiotics. However, one major issue is accurate identification of microbes constituting the microbiota. Studies of the microbiome have frequently utilized sequencing of the conserved 16S ribosomal RNA (rRNA) gene. We present a comparative study of an alternative approach using shotgun whole genome sequencing (WGS). In the present study, we analyzed the human fecal microbiome compiling a total of 194.1×106 reads from a single sample using multiple sequencing methods and platforms. Specifically, after establishing the reproducibility of our methods with extensive multiplexing, we compared: 1) The 16S rRNA amplicon versus the WGS method, 2) the Illumina HiSeq versus MiSeq platforms, 3) the analysis of reads versus de novo assembled contigs, and 4) the effect of shorter versus longer reads. Our study demonstrates that shotgun whole genome sequencing has multiple advantages compared with the 16S amplicon method including enhanced detection of bacterial species, increased detection of diversity and increased prediction of genes. In addition, increased length, either due to longer reads or the assembly of contigs, improved the accuracy of species detection.

Insights into study design and statistical analyses in translational microbiome studies

“…Profiling the 16S (and ITS) variable regions enables researchers to catalog the taxonomic composition of the bacteria (or fungi) in the samples, up to a genus-level resolution. However, the information contained in these short sequences do not directly reveal if these bacteria (or fungi) are alive, or provide information about their metabolic states or their functions within living systems (55,56). Additionally, sequence read-counts do not directly correlate with the absolute bacterial load in the samples, in part, due to the variable copy numbers of the 16S gene in any given organism, dissimilarities of the universal 16S primers to the target genes of some of the microbes, and amplificationrelated artefacts introduced by the polymerase chain reaction (PCR), which is used to extract and amplify the 16S DNA fragments prior to sequencing (38).…”

“…The limitations of 16S profiling are, in part, addressed by metagenomic sequencing (56) in which whole genomes of microbes in biological samples are fractionated and sequenced in a shotgun manner. Since bacterial (and fungal) genomes can have a wide range of genomic sizes, a large number of sequencing reads per sample (i.e., sequencing depth) is required for attaining sufficient coverage of all genes in a community of microbes.…”

“…Sequencing depth also determines the number of organisms in the samples for which whole-genome profiles can be completely indexed (58). The most distinct advantage of metagenomic sequencing is the ability to use the sequencing reads to construct a catalog of genes in a sample and use this information to arrive at species and strain-level identification (56). Additionally, the relative gene-content enables a direct profiling of the functional attributes of the organisms in the sample.…”

Impact of environmental factors on alloimmunity and transplant fate

“…Analysis of the microbiota has mostly focused on bacterial communities, using either cultivation techniques, amplicon sequencing of hypervariable regions in the 16S rRNA gene, or shotgun metagenome sequencing of the microbial genome (116). In…”

The gut microbiota and immune checkpoint inhibitors

“…Advantages in gene prediction, accurate bacterial species detection, and thorough diversity measurements in shotgun sequencing DNA have been recognized over 16s rRNA sequencing. 39 Furthermore, there are variations in the techniques of 16s ribosomal RNA sequencing and many proposed algorithms for clustering of genetic sequences into operational taxonomic units (OTUs) to measure the diverse profile of the microbiome, some of which are found to have a negative impact on downstream analyses. 40-48 Zitvogel and colleagues proceeded to demonstrate the functional relationship between microbiota and antitumor T-cell immunity by performing a series of FMT tests on mice using the patient stool samples.…”