Figure 1.

Schematics of standard techniques used in microbiome studies. (A) Marker gene sequencing techniques can use primers to target certain conserved regions of a genome to capture intermittent variable regions, which can then be used to identify organisms in a sample rapidly and inexpensively. The 16S rRNA gene is the most commonly used marker gene in bacteria and archaea, and in the figure, primers are used to capture the V3 and V4 variable regions together, a common approach for 16S sequencing. The internal transcribed spacer (ITS) region of the nuclear rRNA cistron in fungi is made of two segments, which can be captured with primers targeting the 18S, 5.8S, and 28S rRNA sections that surround them. (B–D) Instead of targeting one small segment of the genome, these techniques capture the entirety of the genetic material from an organism. (B) Single virus genomics (SVG) uses a fluorescent stain to isolate individual virus particles in a sample by fluorescence-activated virus sorting (FAVS), wherein they are embedded in an agarose bead before undergoing whole genome amplification and sequencing. (C) Whole metagenome shotgun sequencing (WMS) involves the fragmentation of all DNA in a sample, sequencing of the fragments, and assembly of the sequences, which can then be mapped to reference genomes, or de novo assembly can be performed. (D) Metatranscriptomics also involves a shotgun sequencing approach, but it is performed after mRNA extraction. The outputs then allow for differential gene expression analysis. (E) Metabolomics and metaproteomics allow for quantification of the metabolites and proteins produced by the microbiome in a sample, respectively. Mass spectrometry is a common approach to quantification. Mock metabolite shapes in Figure 1 were generated using the JSME Molecular Editor by Peter Ertl and Bruno Bienfait licensed under CC-BY-NC-SA 3.0. Images of body sites and organs in Figure 1 and Figure 2 were obtained from Servier Medical Art by Servier licensed under CC-BY 3.0.Traditionally, 16S sequences were clustered into groups with at least 97% identity, called operational taxonomic units (OTUs), which have been used as proxies for species-level or, more commonly, genus-level taxonomic identification. A number of software tools are available, which convert reads to sample-by-OTU feature tables, such as QIIME [55] and mothur [56]. However, newer approaches are better able to control for amplicon sequencing errors, and thereby obviate the use of arbitrary identity thresholds, allowing for single-nucleotide resolution with amplicon sequence variants (ASVs) [57]. Software options for ASV methods include DADA2 [58] and Deblur [59].