Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.

Author contributions MGDB, PCD and RK conceived and designed the study. MGDB, JFRC, HSP, JH, RR, OLB, MJB, LCP, AN, HC collected the samples and metadata. AB acquired LC-MS data. LIM led LC-MS data analysis. CC led taxonomy and metadata analysis. QZ led DNA data and multi-omics analysis. JJM performed qPCR. SJS, ME, HC, AN, AB, JJM provided additional contributions to data analysis. LIM

The metabolome is a system of small biomolecules (metabolites) and a direct result of human bioculture. Consequently, metabolomics is well poised to impact anthropological and biomedical research for the foreseeable future. Overall, we provide a perspective on the ethical, legal, and social implications (ELSI) of metabolomics, which we argue are often more alarming than those of genomics. Given the current mechanisms to fund research, ELSI beyond human DNA is stifled and in need of considerable attention.

Workplace chemical exposures are a major source of occupational injury. Although over half of these are skin exposures, exposomics research often focuses on chemical levels in the air or in worker biofluids such as blood and urine. Until now, one limitation has been the lack of methods to quantitatively measure surface chemical transfer. Outside the realm of harmful chemicals, the small molecules we leave behind on surfaces can also reveal important aspects of human behavior. In this study, we developed a swab-based quantitative approach to determine small molecule concentrations across common surfaces. We demonstrate its utility using one drug, cyclobenzaprine, and two human-derived metabolites, carnitine and phenylacetylglutamine, on four common surfaces: linoleum flooring, plastified laboratory workbench, metal and Plexiglass. This approach enabled linear small molecule recovery and quantification of molecule abundance on workplace built environment surfaces. Overall, this method paves the way for future quantitative exposomics studies.