Figure 3
Workflow for SLST typing (graphical abstract of this AD substudy). This flow chart summarizes our proposed best practices for SLST. For this, we discuss the example of Staphylococcus involvement in AD as an SLST use case. It involves the selection of representative genomes for any taxonomy-of-interest, and analyzing them in a straightforward fashion with TaxPhlAn for Discovery & Design (Module A) of suitable SLST targets for optimal discrimination between input genomes. A small selection of the best-discriminating SLST candidates (i.e. primer pairs for PCR) will be tested in the laboratory by PCR on relevant strain collections. SLST candidates for which primer pairs survive both in silico and laboratory selection procedures can in principle be adopted as marker genes for typing of microbiota in next-generation sequencing (NGS) initiatives. Our TaxPhlAn SLST Oligotyping pipeline (Module B) allows for the analysis of SLST reads from NGS data, including typing of known and identification of unknown biodiversity, and reporting of results in comprehensible format, including automated visualization and clustering of samples. Altogether, this entire process facilitates the potential discovery of study parameters that associate with high-resolution microbiota data. Importantly, in order to “close the experimental circle”, microbiota leads from SLST data can be adopted in an attempt to unravel or further understand underlying biological processes. This is mainly based on pinpointing in high-resolution the most relevant microbial (sub)species, or even strains, for application in follow-up experiments or studies.
