Theda U P Bartolomaeus1,2,3,4, Till Birkner1,2,3, Hendrik Bartolomaeus1,2,3,4,5, Ulrike Löber1,2,3,4, Ellen G Avery1,2,3,4,5,6, Anja Mähler1,4,5, Daniela Weber7,8, Bastian Kochlik7,8, András Balogh1,2,3,4,5, Nicola Wilck1,2,3,4,5,9, Michael Boschmann1,3,5, Dominik N Müller1,2,3,4,5, Lajos Markó1,2,3,4,5, Sofia K Forslund1,2,3,4,5,10. 1. Experimental and Clinical Research Center, a Cooperation of Charité-Universitätsmedizin Berlin, Max Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125 Berlin, Germany. 2. Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany. 3. Max Delbrück Center for Molecular Medicine, Helmholtz Association, Robert-Rössle-Straße 10, 13125 Berlin, Germany. 4. DZHK (German Center for Cardiovascular Research), partner site Berlin, Hessische Strasse 3-4, 10115 Berlin, Germany. 5. Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Straße 2, 10178 Berlin, Germany. 6. Freie Universität Berlin, Kaiserswerther Str. 16-18, 14195 Berlin, Germany. 7. Department of Molecular Toxicology, German Institute of Human Nutrition (DIfE), Potsdam Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany. 8. NurtiAct-Competence Cluster Nutrition Research Berlin-Potsdam, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany. 9. Medizinische Klinik mit Schwerpunkt Nephrologie und Internistische Intensivmedizin, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. 10. European Molecular Biology Laboratory, Structural and Computational Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
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. Published on behalf of the European Society of Cardiology. All rights reserved.
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. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Elinor Shvartsman; Meika E I Richmond; John J Schellenberg; Alana Lamont; Catia Perciani; Justen N H Russell; Vanessa Poliquin; Adam Burgener; Walter Jaoko; Paul Sandstrom; Kelly S MacDonald Journal: PLoS One Date: 2022-01-13 Impact factor: 3.240