Evaluation of 16S rRNA and Shotgun Metagenomic Analytical Methods for Community Profiling using ATCC Microbiome Standards

Light purple DNA strand.

ASM Microbe

New Orleans, Louisiana, United States

June 01, 2017


Complexities involved in 16S rRNA and shotgun metagenomic analysis methods pose significant challenges in microbiome research as various biases can be introduced during PCR amplification, library preparation, sequencing, and analysis. One of the primary obstacles in assay standardization is the limited availability of reference materials. To support this need, we developed microbiome reference standards from fully sequenced and characterized ATCC strains and evaluated their use in a proof-of-concept study. Here, 4 standards were created comprising mixtures of 10 or 20 genomic DNAs in equal or staggered quantities prepared from a diverse set of bacteria that were selected based on relevant attributes such as Gram stain, genome size, GC content, and other special characteristics. Initially, we performed an interlaboratory comparison of the 16S rRNA V4 region from 3 different commercial laboratories. Analysis of the resulting sequencing data using One Codex revealed variability in the number of true positives and false positives as well as the relative abundances. A subsequent comparison of 3 different regions of the 16S rRNA gene—V1V2 (27f-YM+3 338R), V3V4 (341F & 806R), and V4 (515F & 806R)—revealed that only the analysis of the V1/V2 region using One Codex was able to profile the bacteria to the species level. Following this analysis, we evaluated a shotgun metagenomics approach and compared it to the 16S rRNA V1/V2 results. Here, the shotgun metagenomics approach showed a high correlation between the expected vs. observed ratios as compared to the 16S rRNA results, which had variable correlation for 3 standards with equal and staggered ratios. These results demonstrate that 16S rRNA community profiling of the V1V2 region and the shotgun metagenomic approach could identify bacterial strains to the species level, with the latter method generating relative abundances statistically close to the expected. Taken together, this proof-of-concept study demonstrates the potential use of ATCC Microbiome Standards in the identification of potential biases and methodology drawbacks associated with microbiome studies.

Download the poster to explore the use of standards in identifying potential biases associated with microbiome studies.