Microbial ecology used to be a small and specialized field that struggled to identify more than a tiny proportion of the Earth's microbial biodiversity.
Previous MFC microbial ecology studies have used Sanger-based 16S rRNA sequencing for microbial community characterization.
In microbial ecology, sequencing is used routinely for 16S rRNA gene amplicon surveys (Tringe and Hugenholtz, 2008), metagenomics (Handelsman, 2004) and metatranscriptomics (Frias-Lopez et al., 2008).
Conversely, microbial ecology and other disciplines using metabarcoding tools for species identification have had no organized standardization efforts until recently.
For example, numerous studies of microbial ecology show that WGA using phi29 DNA polymerase enriches environmental template DNAs with the highest amplification efficiency [ 13, 14], and the amplified DNA can be used to characterize the microbial community structure in low-biomass environments [ 15– 17].
The most important revolution in microbial ecology was the use of molecular techniques and DNA sequencing in phylogenetic studies and their applications to uncultured organisms [ 26].
The most important revolution in microbial ecology was the use of DNA sequencing in phylogenetic studies and the application of this technology to uncultured organisms in the 1980s and the 1990s.
We use microbial ecology terminology rather than statistical conventions, so that a 'population' is a collection of all organisms of a given species, a 'community' is a collection of 'populations' that share a specific ecosystem, and a 'sample' or 'specimen' is a physical extract from a given microbiome.
Details are given in the study by Gevers et al. Selection of unique bacterial sequences, so-called operational taxonomic unit (OTU) picking, was performed using the QIIME (the toolbox for Quantitative Insights Into Microbial Ecology) reference optimal picking, which uses UCLUST (an algorithm to cluster sequence reads based on similarity) (version 1.2.22q) to perform the clustering.
Quantitative Insights Into Microbial Ecology (QIIME), investigates microbial diversity using 16S rRNAs data.
