Quantification with Spike DNA and Common Pitfalls of 16S rRNA Gene Amplicon Data Analysis in Microbiome Research

Quantification with Spike DNA and Common Pitfalls of 16S rRNA Gene Amplicon Data Analysis in Microbiome Research

Abstract
Short-amplicon 16S rRNA gene sequencing is currently the method of choice for studies investigating microbiomes. However, despite many years of development, several issues are often observed in literature. First, most data are acquired using a relative abundance, e.g., scaling to 100% for each sample. Using spike DNA, the relative abundance between samples can be achieved within a study with low cost and minimal effort. Thus, the fold change in bacterial cell number is accessible for between, e.g., control and treatment. Next, major bias occurs by choosing DNA isolation method and suitable primer. It is suggested to create a suitable mock community for testing before starting a study and to include negative and positive control in the study. Finally, choices in bioinformatic analysis will affect the result. It is imperative to understand the influence of parameter settings, but also to apply suitable tool and calculations. A brief overview on how to avoid the most common pitfalls is given. Finally, I will briefly touch on current tools and give hints for best practice.