Contamination in DNA extraction kits and laboratory reagents can significantly affect sequence-based microbiome analyses. This study shows that contaminating DNA is common in commonly used kits and varies between different kits and batches. Contamination can greatly impact results from samples with low microbial biomass, affecting both PCR-based 16S rRNA gene surveys and shotgun metagenomics. The study provides a list of potential contaminating genera and guidelines to mitigate contamination effects. Contaminating DNA is a major challenge for researchers working with low biomass samples, as the low amount of starting material may be overwhelmed by contaminating DNA, leading to misleading results. Although contamination has been reported in the literature, its impact on high-throughput 16S rRNA gene-based profiling and shotgun metagenomics has not been widely studied. The study highlights the importance of sequencing negative control samples to identify and mitigate contamination. The study demonstrates that contamination is a significant issue in microbiota studies, particularly in low biomass environments. Contamination can dominate sequence data, leading to incorrect conclusions. The study recommends that researchers should be cautious when applying sequence-based techniques to low biomass samples and that concurrent sequencing of negative control samples is strongly advised. The study also shows that contamination can vary between laboratories and is influenced by differences in reagent/kit batches or contaminants introduced from the wider laboratory environment. Many contaminating operational taxonomic units (OTUs) represent bacterial genera normally found in soil and water, while others are common human skin-associated organisms. By sequencing PCR 'blank' negative controls, researchers can distinguish between taxa originating from DNA extraction kits and those from other sources. The study also shows that contamination can have a significant impact on the results of microbiota studies, even in the absence of a PCR amplification step. Reducing input biomass increases the impact of these contaminants on the observed microbiota. The study provides recommendations to reduce the impact of contaminants in sequence-based, low-biomass microbiota studies, including maximizing sample biomass, minimizing contamination at sample collection, and using technical controls. The study emphasizes the importance of monitoring contamination and being aware of common contaminating species to ensure accurate results.Contamination in DNA extraction kits and laboratory reagents can significantly affect sequence-based microbiome analyses. This study shows that contaminating DNA is common in commonly used kits and varies between different kits and batches. Contamination can greatly impact results from samples with low microbial biomass, affecting both PCR-based 16S rRNA gene surveys and shotgun metagenomics. The study provides a list of potential contaminating genera and guidelines to mitigate contamination effects. Contaminating DNA is a major challenge for researchers working with low biomass samples, as the low amount of starting material may be overwhelmed by contaminating DNA, leading to misleading results. Although contamination has been reported in the literature, its impact on high-throughput 16S rRNA gene-based profiling and shotgun metagenomics has not been widely studied. The study highlights the importance of sequencing negative control samples to identify and mitigate contamination. The study demonstrates that contamination is a significant issue in microbiota studies, particularly in low biomass environments. Contamination can dominate sequence data, leading to incorrect conclusions. The study recommends that researchers should be cautious when applying sequence-based techniques to low biomass samples and that concurrent sequencing of negative control samples is strongly advised. The study also shows that contamination can vary between laboratories and is influenced by differences in reagent/kit batches or contaminants introduced from the wider laboratory environment. Many contaminating operational taxonomic units (OTUs) represent bacterial genera normally found in soil and water, while others are common human skin-associated organisms. By sequencing PCR 'blank' negative controls, researchers can distinguish between taxa originating from DNA extraction kits and those from other sources. The study also shows that contamination can have a significant impact on the results of microbiota studies, even in the absence of a PCR amplification step. Reducing input biomass increases the impact of these contaminants on the observed microbiota. The study provides recommendations to reduce the impact of contaminants in sequence-based, low-biomass microbiota studies, including maximizing sample biomass, minimizing contamination at sample collection, and using technical controls. The study emphasizes the importance of monitoring contamination and being aware of common contaminating species to ensure accurate results.