What are the microbiome biases created by using different nucleic acid extraction or amplification methods? How do technical parameters such as beadbeating, choice of primers, PCR cycle number etc change the ratio of microbial taxa in the analyzed community?  Also see my pages on Sample Storage and Contamination Issues.

Created August 2016, updated March 2018.

Inspired by this post: The unbearable madness of microbiome – Mick Watson – Opiniomics, which has since then been published as The madness of microbiome: Attempting to find consensus “best practice” for 16S microbiome studies – Jolinda Pollock – AEM February 2018

General papers (addressing multiple technical issues)

Methodology challenges in studying human gut microbiota – effects of collection, storage, DNA extraction and next generation sequencing technologies – Marina Panek – Scientific Reports – March 2018

The madness of microbiome: Attempting to find consensus “best practice” for 16S microbiome studies – Jolinda Pollock – Applied and Environmental Microbiology – February 2018

Gut Microbiota Analysis Results Are Highly Dependent on the 16S rRNA Gene Target Region, Whereas the Impact of DNA Extraction Is Minor – Anniina Rintala – J Biomol Techn – April 2017

Considerations for optimizing microbiome analysis using a marker gene –  Jacobo de la Cuesta-Zuluaga – Frontiers in Nutrition – August 2016

Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies – Daryl M Gohl – Nature Biotechnology – July 2016

The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies – J Paul Brooks – BMC Microbiology – March 2015

DNA extraction methods 

Optimization of DNA extraction for advancing coral microbiota investigations – Laura Weber – Microbiome – February 2017

DNA extraction protocols may influence biodiversity detected in the intestinal microbiome: a case study from wild Prussian carp, Carassius gibelio – Elena N. Kashinskaya – FEMS Microbiology Ecology – February 2017

Evaluating the Impact of DNA Extraction Method on the Representation of Human Oral Bacterial and Fungal Communities – Anna Vesty – PLOS ONE – January 2017

Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition – Berith Knudsen – mSystems – October 2016

Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods – Santosh Keisam – Scientific Reports –  September 2016

Evaluation of Lysis Methods for the Extraction of Bacterial DNA for Analysis of the Vaginal Microbiota – Christina Gill – PLOS ONE – September 2016

A method for assessing efficiency of bacterial cell disruption and DNA release – Olle M. de Bruin – BMC Microbiology – August 2016

Bead-beating artefacts in the Bacteroidetes to Firmicutes ratio of the human stool metagenome – Heidi C. Vebø – Journal of Microbiological Methods – August 2016

The effect of DNA extraction methodology on gut microbiota research applications – Konstantinos Gerasimidis – BMC Research Notes – July 2016

Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition – Berith E Knudsen – bioRxiv – July 2016

High stability of faecal microbiome composition in guanidine thiocyanate solution at room temperature and robustness during colonoscopy – Yuichiro Nishimoto – Gut – June 2016

16S rRNA gene-based profiling of the human infant gut microbiota is strongly influenced by sample processing and PCR primer choice – Alan W. Walker – Microbiome – June 2016

An Improved Method for High Quality Metagenomics DNA Extraction from Human and Environmental Samples – Satyabrata Bag – Scientific Reports – May 2016

Glycans affect DNA extraction and induce substantial differences in gut metagenomic studies – Emmanouil Angelakis – Scientific Reports – May 2016

Comparison of two commercial DNA extraction kits for the analysis of nasopharyngeal bacterial communities  – Marcos Pérez-Losada – AIMS Microbiology – April 2016

Methods for Improving Human Gut Microbiome Data by Reducing Variability through Sample Processing and Storage of Stool – Monika Gorzelak – PLOS ONE – August 2015

DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure – Benjamin Rubin – Microbiology Open – September 2014

Choice of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis – Agata Wesolowska-Andersen – Microbiome – June 2014

Evaluation of Methods for the Extraction and Purification of DNA from the Human Microbiome – Sanqing Yuan – PLOS ONE – March 2012

Improved extraction of PCR-quality community DNA from digesta and fecal samples – Zhongtang Yu  – Biotechniques – May 2004

DNA Extraction from Soils: Old Bias for New Microbial Diversity Analysis Methods – F. Martin-Laurent – Applied and Environmental Microbiology – May 2001

16S rRNA gene primer pairs

Optimisation of methods for bacterial skin microbiome investigation: primer selection and comparison of the 454 versus MiSeq platform – Madhura Castelino – BMC Microbiology – January 2017

Choice of molecular barcode will affect species prevalence but not bacterial community composition – Karen Lebret – Marine Genomics – September 2016

Evaluation of 16S rRNA gene primer pairs for monitoring microbial community structures showed high reproducibility within and low comparability between datasets generated with multiple archaeal and bacterial primer pairs – Martin A. Fischer – Frontiers in Microbiology – August 2016

Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys – William Walters – mSystems – December 2015

18S / ITS primer pairs (fungi and other eukaryotes)

Fungal identification biases in microbiome projects – Leho Tedersoo – Environmental Microbiology Reports – July 2016

New Primers for Discovering Fungal Diversity Using Nuclear Large Ribosomal DNA – Asma Asemaninejad – PLOS ONE – July 2016

Microbial community assembly and metabolic function during mammalian corpse decomposition – Jessica L. Metcalf – Science – January 2016

Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys – William Walters – mSystems – December 2015

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide – Suzanne M. Prober – Ecology Letters – November 2014

Meeting Report: Fungal ITS Workshop (October 2012) – Scott T. Bates – Standards in Genomic Sciences – April 2013

Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi – Conrad L. Schoch – PNAS – March 2012

Library prep and Sequencing platform

Library preparation methodology can influence genomic and functional predictions in human microbiome research – Marcus B Jones – PNAS – November 2015

Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates – Victor Kunin – Environmental Microbiology  – August 2009

Bioinformatics pipeline

Evaluating the accuracy of amplicon-based microbiome computational pipelines on simulated human gut microbial communities – Jonathan L Golob – BMC Bioinformatics – May 2017

Mock communities and spike in controls

Design and Analysis of a Microbiome Mock Community: Understanding and Mitigating Methodological BiasesDesign and Analysis of a Microbiome Mock Community: Understanding and Mitigating Methodological Biases – Suquoia Mosby – The Faseb Journal – April 2017

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing – Dieter M Tourlousse – Nucleic Acids Research  – February 2017