Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g., skin swabs, tissue biopsies, ice, water, degraded forensic samples or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high‐throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no‐template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over 5 years to characterize long‐term contaminant diversity. We additionally compared the contaminant content within a home‐made silica‐based extraction method, commonly used to analyse low endogenous content samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to modern molecular biology laboratories, and changed over time according to researcher, month and season. The commercial kit also contained higher microbial diversity and several human‐associated taxa in comparison to the home‐made silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low‐biomass metagenomic studies: (a) extraction blank controls should be included and sequenced with every batch of extractions and (b) the contributions of laboratory contamination should be assessed and reported in each high‐throughput metagenomic study.

High-Throughput DNA Sequencing (HTS) technologies have changed the way in which we detect and assess DNA contamination in ancient DNA studies. Researchers use computational methods to mine the large quantity of sequencing data to detect characteristic patterns of DNA damage, and to evaluate the authenticity of the results. We argue that unless computational methods can confidently separate authentic ancient DNA sequences from contaminating DNA that displays damage patterns under independent decay processes, prevention and control of DNA contamination should remain a central and critical aspect of ancient human DNA studies. Ideally, DNA contamination can be prevented early on by following minimal guidelines during excavation, sample collection and/or subsequent handling. Contaminating DNA should also be monitored or minimised in the ancient DNA laboratory using specialised facilities and strict experimental procedures. In this paper, we update recommendations to control for DNA contamination from the field to the laboratory, in an attempt to facilitate communication between field archaeologists, anthropologists and ancient DNA researchers. We also provide updated criteria of ancient DNA authenticity for HTS-based studies. We are confident that the procedures outlined here will increase the retrieval of higher proportions of authentic genetic information from valuable archaeological human remains in the future.

Numerous important environments harbour low levels of microbial biomass, including certain human tissues, the atmosphere, plant seeds, treated drinking water, hyper-arid soils and the deep subsurface, with some environments lacking resident microbes altogether. These low microbial biomass environments pose unique challenges for standard DNA-based sequencing approaches, as the inevitability of contamination from external sources becomes a critical concern when working near the limits of detection. Likewise, lower-biomass samples can be disproportionately impacted by cross-contamination and practices suitable for handling higher-biomass samples may produce misleading results when applied to lower microbial biomass samples. This Consensus Statement outlines strategies to reduce contamination and cross-contamination, focusing on marker gene and metagenomic analyses. We also provide minimal standards for reporting contamination information and removal workflows. Considerations must be made at every study stage, from sample collection and handling through data analysis and reporting to reduce and identify contaminants. We urge researchers to adopt these recommendations when designing, implementing and reporting microbiome studies, especially those conducted in low-biomass systems.

In industrialized countries, non-communicable diseases have been increasing in prevalence since the middle of the 20th century. While the causal mechanisms remain poorly understood, increased population density, pollution, sedentary behavior, smoking, changes in diet, and limited outdoor exposure have all been proposed as significant contributors. Several hypotheses (e.g. Hygiene, Old Friends, and Biodiversity Hypotheses) also suggest that limited environmental microbial exposures may underpin part of this rise in non-communicable diseases. In response, the Microbiome Rewilding Hypothesis proposes that adequate environmental microbial exposures could be achieved by restoring urban green spaces and could potentially decrease the prevalence of non-communicable diseases. However, the microbial interactions between humans and their surrounding environment and the passaging of microbes between both entities remains poorly understood, especially within an urban context. Here, we survey human skin (n = 90 swabs) and nasal (n = 90 swabs) microbiota of three subjects that were exposed to air (n = 15), soil (n = 15), and leaves (n = 15) from different urban green space environments in three different cities across different continents (Adelaide, Australia; Bournemouth, United Kingdom; New Delhi, India). Using 16S ribosomal RNA metabarcoding, we examined baseline controls (pre-exposure) of both skin (n = 16) and nasal (n = 16) swabs and tracked microbiota transfer from the environment to the human body after exposure events. Microbial richness and phylogenetic diversity increased after urban green space exposure in skin and nasal samples collected in two of the three locations. The microbial composition of skin samples also became more similar to soil microbiota after exposure, while nasal samples became more similar to air samples. Nasal samples were more variable between sites and individuals than skin samples. We show that exposure to urban green spaces can increase skin and nasal microbial diversity and alter human microbiota composition. Our study improves our understanding of human-environmental microbial interactions and suggests that increased exposure to diverse outdoor environments may increase the microbial diversity, which could lead to positive health outcomes for non-communicable diseases.