An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities

Abstract

Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

Meta-analysis of the autism gut microbiome identifies factors influencing study discrepancies and machine learning classification

“…Microbial compositions are known to vary across different human populations 27 . Additionally, the various techniques used to analyze the microbiome can impact the estimated biological diversity 52; 55 . Our study contextualizes the ASD microbiome field by evaluating how both technical choices and cohort demographics alter reported results.…”

“…While some large-scale efforts such as the earth microbiome project endorse the amplification of the V4 region, a standard in the field is lacking 58 . This lack of standardization has been shown to impact reproducibility especially in metrics estimating biological diversity 52; 55 . We found that the 16S hypervariable region of choice indeed contributed to cohort discrepancies regarding taxonomic associations to ASD.…”

Metrological framework to support accurate, reliable, and reproducible nucleic acid measurements

“…Developed capacities will also be of value to the other sectors such as industrial biotechnology where novel methods, such as CRISPR CAS-9-based genetic modification, are being applied [118,119]. Biotechnology, especially the biopharmaceutical industry, performs numerous measurements to ensure the safety, quality, and efficiency of manufactured products [120]. Well-defined procedures for nucleic acid analysis are listed in almost all national and international pharmacopeias (e.g., IP, EP, USP, BP, JP, RSP, and others).…”

“…The increasing need for genomic, transcriptomic, and epigenomic analyses means that the NAWG will need to explore the development of strategies to support advanced sequencing capabilities, including for purity analysis. The metrological support in this area is lacking [120], and challenges associated with these types of "non-targeted" methods are likely to increase with the development of newer, simplified sequencing technologies more suitable to less specialized settings.…”

Characterization and Demonstration of Mock Communities as Control Reagents for Accurate Human Microbiome Community Measurements

“…In the microbiome field, reference materials have generally taken the form of defined mixtures of genomic DNA or whole cells from several to a few tens of distinct microorganisms. Such mock communities have been used to characterize protocol-dependent biases and optimize or validate methods ( 11 – 15 ), to assess interlaboratory reproducibility in collaborative studies ( 16 – 18 ), and to evaluate run-to-run variability ( 19 ). In addition to mock communities, human whole stool samples have also been employed in several of the above studies and their development as reference materials is ongoing ( 20 , 21 ).…”