Table 1.

Important end-to-end considerations for a successful skin microbiome study. rRNA: ribosomal RNA.

Step	Key Considerations
Study design	Skin site and condition of interest (when applicable)
	Study power (i.e., number of participants and/or samples collected; relative abundance of signal(s) of interest)
	Participant metadata (e.g., ethnicity, age, biological sex, health status, use of medications, hygiene products, and/or cosmetics)
	Robust sampling procedure: area size vs. bioload, impact of hygiene, bioburden, etc.
	End-to-end review of the methods for compatibility and optimal sample performance
	Downstream analysis strategy compatibility
	Additional control(s): environmental/non-collected control
Sample collection/ storage	Means of sample collection (e.g., swab, scraping, biopsy, and tape-stripping) Validated and standardized for skin
	Low bioburden within device and contamination during collection
	Need for immediate freezing vs. inclusion of stabilization solution Storage length and conditions
Sample processing: nucleic acid extraction	Validated and standardized Optimized nucleic acid recovery
	Recovery of Gram-positive and Gram-negative bacteria and fungal species
	Effective clean-up of nucleic acids and removal of enzymatic inhibitors
	Low bioburden
	Extraction negative control
Sample processing: amplification and library preparation	Optimized for taxa (e.g., bacterial vs. fungal) of interest and biomass/host content Accurate capture of microbiome composition Optimal DNA input (for shotgun metagenomic and amplicon sequencing) and amplification conditions (for amplicon sequencing) Efficient removal of host and microbial rRNA and sufficient RNA input for metatranscriptomic sequencing
	Library preparation negative control
Bioinformatics: database selection	Updated and curated content source and data quality, removal or consolidation of redundant sequences, and comprehensiveness
	Level of taxonomic or functional resolution supported (e.g., genus, species, strain, and functional hierarchies)
	Suitability towards analysis strategy
Bioinformatics: annotation	Sensitivity and specificity of tool/approach Low false positive/false negative rate
	Database-dependent and database-independent approaches