Considerations For Optimizing Microbiome Analysis Using a Marker Gene

Abstract

Next-generation sequencing technologies have found a widespread use in the study of host–microbe interactions due to the increase in their throughput and their ever-decreasing costs. The analysis of human-associated microbial communities using a marker gene, particularly the 16S rRNA, has been greatly benefited from these technologies – the human gut microbiome research being a remarkable example of such analysis that has greatly expanded our understanding of microbe-mediated human health and disease, metabolism, and food absorption. 16S studies go through a series of in vitro and in silico steps that can greatly influence their outcomes. However, the lack of a standardized workflow has led to uncertainties regarding the transparency and reproducibility of gut microbiome studies. We, here, discuss the most common challenges in the archetypical 16S rRNA workflow, including the extraction of total DNA, its use as template in PCR with primers that amplify specific hypervariable regions of the gene, amplicon sequencing, the denoising and removal of low-quality reads, the detection and removal of chimeric sequences, the clustering of high-quality sequences into operational taxonomic units, and their taxonomic classification. We recommend the essential technical information that should be conveyed in publications for reproducibility of results and encourage non-experts to include procedures and available tools that mitigate most of the problems encountered in microbiome analysis.

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models

“…In particular, it is well-known that each step of the 16S rRNA gene NGS workflow may lead to pitfalls and biases that affect, for example, a study’s design and sample collection, the nucleic acid extraction and sequencing, and the bioinformatic and statistical analyses 64 , 65 . This lack of a standardised workflow has led to uncertainty regarding the transparency, reproducibility and comparability of 16S-based microbiome research 66 . In the present study, other factors that should also be taken into account are the type of saliva sample analysed (stimulated vs non-stimulated) 67 , as well as the different clinical criteria used to define the dental and periodontal health status.…”

Nasopharyngeal Microbiota in Children With Invasive Pneumococcal Disease: Identification of Bacteria With Potential Disease-Promoting and Protective Effects

“…Samples were classified in Operational Taxonomic Units (OTUs) at 97% sequence identity as the standard species-level boundary (Yarza et al, 2008). Only the OTUs representing over 0.1% of the total sequences of each sample were considered for further statistical analysis, as low-frequency reads, including singletons, are more likely to represent sequencing errors, contaminants, or transient organisms without a biological role at the niche under study (de la Cuesta-Zuluaga and Escobar, 2016). Bacterial taxonomic composition was determined for each sample and means for each group (cases and controls) were calculated.…”

Exploring the Archaeome: Detection of Archaeal Signatures in the Human Body

“…It has been recognized that methodological issues in sample processing can significantly influence the outcome of microbiome studies, affecting comparability between different studies (Clooney et al, 2016; de la Cuesta-Zuluaga and Escobar, 2016) or leading to an over-and/or under-estimation of certain microbial clades (Eloe-Fadrosh et al, 2016; Eisenstein, 2018). For better comparability among different studies, standard operational procedures for sampling, storing samples, DNA extraction, amplification and analysis were set-up [e.g., the Earth Microbiome Project (Gilbert et al, 2014) and the Human Microbiome Project (Methé et al, 2012)].…”