How to analyse the gut microbiome?

For over 100 years, culture-based techniques were the gold standard for classifying microbes. However, these approaches are restricted to the small subset of microbes that survive isolation and specific laboratory growth conditions. Contemporary genomic classification approaches offered a solution to the limitations of culture-based techniques. Unique to prokaryotic organisms, the 16S ribosomal RNA (rRNA) gene is a highly conserved region within the bacterial genome. Interestingly, within the highly conserved 16S rRNA gene are nine hypervariable regions with species-specific signatures. Sequences of the 16S rRNA gene can therefore be compared with the “reference library” for taxonomic classification. The 16S rRNA gene is an ideal and simple tool for profiling gut bacteria.

Standard human gut microbiome studies involve the extraction and sequencing of microbial DNA from a faecal sample collected in a stool container with DNA stabilizer, followed by DNA extraction, gene sequencing and computational bioinformatics analysis (Figure 2). Early human microbial studies relied upon fingerprinting techniques or Sanger sequencing of the amplified 16S rRNA gene. In the past decade, next-generation sequencing (NGS) platforms have offered faster and more efficient sequencing at much lower cost.

16S rRNA analysis is useful for understanding the composition and structural role (anatomy) of microbes in healthy and disease states. However, full assessment of microbial function (physiology) requires other genomic technologies like metagenomic shotgun sequencing. Metagenomics is the analysis of genetic content from the whole microbial ecosystem, and the entire “meta” genome of all microorganisms combined is studied. The term “shotgun sequencing” refers to the generation of sequencing libraries by randomly fragmenting DNA templates of all microbial agents, irrespective of differences between microbial genomes. Metagenomic shotgun sequencing could potentially reveal all the functional genetic content of the microbiota, but the cost and bioinformatics requirement are likely to be much higher than for the usual 16S rRNA analysis. Moreover, if this strategy is employed, there will be significant human DNA contamination in the resulting data. Other ‘omics‘ technologies that could provide insight into the gene expression and metabolic activities of the gut microbiota include metatranscriptomics (RNA expression), metaproteomics (protein) and metabolomics (metabolites). Interestingly, microbial culture remains relevant as an essential tool for functional studies of specific species following ‘omics’ analysis.

Author: Dr Steven Loo, Professor Tsui Kwok Wing, Stephen