Quantifying technical confounders in microbiome studies

Abstract

Aims Recent technical developments have allowed the study of the human microbiome to accelerate at an unprecedented pace. Methodological differences may have considerable impact on the results obtained. Thus, we investigated how different storage, isolation, and DNA extraction methods can influence the characterization of the intestinal microbiome, compared to the impact of true biological signals such as intraindividual variability, nutrition, health, and demographics. Methods and results An observative cohort study in 27 healthy subjects was performed. Participants were instructed to collect stool samples twice spaced by a week, using six different methods (naive and Zymo DNA/RNA Shield on dry ice, OMNIgene GUT, RNALater, 95% ethanol, Zymo DNA/RNA Shield at room temperature). DNA extraction from all samples was performed comparatively using QIAamp Power Fecal and ZymoBIOMICS DNA Kits. 16S rRNA sequencing of the gut microbiota as well as qPCRs were performed on the isolated DNA. Metrics included alpha diversity as well as multivariate and univariate comparisons of samples, controlling for covariate patterns computationally. Interindividual differences explained 7.4% of overall microbiome variability, whereas the choice of DNA extraction method explained a further 5.7%. At phylum level, the tested kits differed in their recovery of Gram-positive bacteria, which is reflected in a significantly skewed enterotype distribution. Conclusion DNA extraction methods had the highest impact on observed microbiome variability, and were comparable to interindividual differences, thus may spuriously mimic the microbiome signatures of various health and nutrition factors. Conversely, collection methods had a relatively small influence on microbiome composition. The present study provides necessary insight into the technical variables which can lead to divergent results from seemingly similar study designs. We anticipate that these results will contribute to future efforts towards standardization of microbiome quantification procedures in clinical research.

Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis

“…These aspects are interrelated, since it is thought that both sample collection and preservation methods may have a profound effect on the output of high-throughput sequencing-based technologies used for microbiome determination [ 22 , 48 ]. For example, a cohort study, which quantified technical factors during sample preparation that may affect the characterization of the gut microbiome, showed that DNA extraction methods had the highest impact on the observed microbiome variability, precluding a clear picture of the microbiome signatures of various health and nutrition factors [ 48 ]. Research in food, diet and the gut microbiome would largely benefit from initiatives joining efforts to propose guidelines to standardize stool collection and preservation methods.…”

“…Despite these limitations, our collection of studies enables comparisons since multiple studies amplified the same region, e.g., V4 ( n = 3 studies) and V3–V4 ( n = 11), and five have conducted both marker gene and shotgun metagenome sequencing. This underlines the importance of standardizing, providing detailed descriptions of methods, and determining technical factors that are critical for the comparability of studies [ 48 ].…”

“…Technical factors cover stool sampling and preservation methods, as well as DNA isolation and extraction. These aspects are interrelated, since it is thought that both sample collection and preservation methods may have a profound effect on the output of highthroughput sequencing-based technologies used for microbiome determination [22,48]. For example, a cohort study, which quantified technical factors during sample preparation that may affect the characterization of the gut microbiome, showed that DNA extraction methods had the highest impact on the observed microbiome variability, precluding a clear picture of the microbiome signatures of various health and nutrition factors [48].…”

Effect of a probiotic on blood pressure in grade 1 hypertension (HYPRO): protocol of a randomized controlled study

“…All biomaterials, in particular, stool samples, are collected with the highest scientific standards to allow for high-quality microbiome analyses [23].…”

Correcting for Background Noise Improves Phenotype Prediction from Human Gut Microbiome Data

“…One major challenge is that several covariates are known to introduce unwanted variation and systematically bias the relative abundances of taxonomic units in microbiome samples [10][11][12][13][14][15][16] . These covariates include host diet and sex [17][18][19] , sample storage 20 , cell lysis protocol 10,21 , DNA preservation and storage protocol 22 , preparation kit 23 , extraction method 24,25 , and primer choice 21 . This variation can substantially reduce the ability to predict host phenotypes from microbiome data.…”