Quantifying and Understanding Well-to-Well Contamination in Microbiome Research.
16S rRNA gene
automation
built environment
contamination
genomics
low biomass
metagenomics
microbiome
microbiota
study design
Journal
mSystems
ISSN: 2379-5077
Titre abrégé: mSystems
Pays: United States
ID NLM: 101680636
Informations de publication
Date de publication:
25 Jun 2019
25 Jun 2019
Historique:
entrez:
27
6
2019
pubmed:
27
6
2019
medline:
27
6
2019
Statut:
epublish
Résumé
Microbial sequences inferred as belonging to one sample may not have originated from that sample. Such contamination may arise from laboratory or reagent sources or from physical exchange between samples. This study seeks to rigorously assess the behavior of this often-neglected between-sample contamination. Using unique bacteria, each assigned a particular well in a plate, we assess the frequency at which sequences from each source appear in other wells. We evaluate the effects of different DNA extraction methods performed in two laboratories using a consistent plate layout, including blanks and low-biomass and high-biomass samples. Well-to-well contamination occurred primarily during DNA extraction and, to a lesser extent, in library preparation, while barcode leakage was negligible. Laboratories differed in the levels of contamination. Extraction methods differed in their occurrences and levels of well-to-well contamination, with plate methods having more well-to-well contamination and single-tube methods having higher levels of background contaminants. Well-to-well contamination occurred primarily in neighboring samples, with rare events up to 10 wells apart. This effect was greatest in samples with lower biomass and negatively impacted metrics of alpha and beta diversity. Our work emphasizes that sample contamination is a combination of cross talk from nearby wells and background contaminants. To reduce well-to-well effects, samples should be randomized across plates, samples of similar biomasses should be processed together, and manual single-tube extractions or hybrid plate-based cleanups should be employed. Researchers should avoid simplistic removals of taxa or operational taxonomic units (OTUs) appearing in negative controls, as many will be microbes from other samples rather than reagent contaminants.
Identifiants
pubmed: 31239396
pii: 4/4/e00186-19
doi: 10.1128/mSystems.00186-19
pmc: PMC6593221
pii:
doi:
Types de publication
Journal Article
Langues
eng
Informations de copyright
Copyright © 2019 Minich et al.
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