Quantifying and understanding well-to-well contamination in microbiome research

Abstract

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 appears in other wells. We evaluate the effects of different DNA extraction methods performed in two labs using a consistent plate layout including blanks, 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. Labs differed in the levels of contamination. DNA extraction methods differed in their occurrences and levels of well-to-well contamination, with robotic methods having more well-to-well contamination while manual methods having higher background contaminants. Well-to-well contamination was observed to occur primarily in neighboring samples, with rare events up to 10 wells apart. The effect of well-to-well 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 crosstalk from nearby wells and background contaminants. To reduce well-to-well effects, samples should be randomized across plates, and samples of similar biomass processed together. Researchers should evaluate well-to-well contamination in study design and avoid removal of taxa or OTUs appearing in negative controls, as many will be microbes from other samples rather than reagent contaminants.ImportanceMicrobiome research has uncovered magnificent biological and chemical stories across nearly all areas of life science, at times creating controversy when findings reveal fantastic descriptions of microbes living and even thriving in once thought to be sterile environments. Scientists have refuted many of these claims because of contamination, which has led to robust requirements including use of controls for validating accurate portrayals of microbial communities. In this study, we describe a previously undocumented form of contamination, well-to-well contamination and show that contamination primarily occurs during DNA extraction rather than PCR, is highest in plate-based methods as compared to single tube extraction, and occurs in higher frequency in low biomass samples. This finding has profound importance on the field as many current techniques to ‘decontaminate’ a dataset simply relies on an assumption that microbial reads found in blanks are contaminants from ‘outside’ namely the reagents or consumables.

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis

“…Although the last sample set was processed without any DNA, the well-to-well contamination that occurred during the DNA extraction step yielded these sequences. We removed these samples since the DNA was biological and not representative of a type of actionable contamination (43, 44).…”

Microbial ecology of Atlantic salmon, Salmo salar, hatcheries: impacts of the built environment on fish mucosal microbiota

“…DNA extraction was performed at University of Tasmania Hobart using the EarthMicrobiomeProject protocols (earthmicrobiome.org), specifically using the ‘manual single-tube’ MoBio PowerSoil kit as to reduce well-to-well contamination (33). A total of 21 positive controls of a microbial isolate (replicates of 10 fold serial dilutions) were processed alongside the samples and then used to determine sample success rate by calculating the sample exclusion criteria based on read counts described in the Katharoseq method (27).…”

Prediction of False-Positive Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Molecular Results in a High-Throughput Open-Platform System

“…pipetting of samples left to right or starting at well A1 and going to well A12). Stochastic contamination can occur due to aerosolization of RNA or amplicon to surrounding wells and has been shown to occur in plate-based bacterial 16s RNA sequencing 12 . Even with stochastic contamination, there was still reproducible patterns of contamination in the 16s sequencing as abutting wells were more likely to exchange material than distant wells 12 .…”