The Need for Standards in Microbiome Research
By Cara N. Wilder, Ph.D., Juan Lopera, Ph.D., Dev Mittar, Ph.D., and Carol Horton, M.S.
White Paper
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The human body harbors a series of diverse, dynamic microbial communities comprising bacteria,
archaea, viruses, and eukaryotes. These communities, collectively termed the human
microbiome, play a vital role in human health and disease, particularly with regard to physiology
and development, immunomodulation, metabolic regulation, and protection against
pathogenic strains.1,2 By understanding how the human microbiome develops and changes
over time with respect to lifestyle and environmental changes or various disease states, and
how this in turn affects individual biology, we are offered a powerful tool for personalized
healthcare and precision medicine.
Early studies on the human microbiome have been predominantly dependent on microbial
cultivation; however, this approach is limited as many microorganisms cannot be cultured in
vitro.1 Thus, culture-independent methods for the analysis of microbial communities have
been sought out. Accelerated advancements in sequencing have facilitated the use of a
metagenomics-based approach for profiling whole microbial genomes directly from their
natural environment. This technology has provided further understanding on the genetic
potential of microbial communities, how the human microbiome may evolve over time with
regard to species abundance and community composition, and how dysbiosis could potentially
affect an individual’s predisposition to disease.
Though metagenomic studies have offered a wealth of information on the human microbiome,
the complexities associated with commonly used methods have posed significant challenges
toward assay standardization. Here, bias can be introduced at every stage of a metagenomics
workflow, from sample collection, DNA extraction, amplification, library preparation, sequencing,
to data analysis.1,3 Consequently, this bias can obscure the true composition of a microbial
community, leading to inaccurate analyses and incorrect conclusions.
One of the primary challenges hindering assay standardization is the limited availability of
reference materials. Here, the use of mock microbial communities as controls can help identify
issues, determine error rates, and normalize sources of assay bias during sample processing
and analysis, in turn improving result interpretation. These mixed communities are typically
defined in composition, represent an appropriate level of diversity, and may include a variety
of genera sourced on or within the human body, each exhibiting different, relevant phenotypic
and genotypic attributes.
To support the need for microbiome reference standards, ATCC has developed ATCC®
Microbiome Standards, which are fully sequenced, characterized, and authenticated mock
microbial communities comprising genomic DNA or whole cell mixtures prepared from ATCC® Genuine Cultures. In fact, these are the only metagenomics reference materials on the market
that are manufactured entirely from validated cultures from ATCC. These products are
available with even or staggered abundance, and medium or high levels of mock community
complexity ranging from 10 to 20 strains per sample. ATCC® Microbiome Standards enable
the optimization of metagenomics workflows and microbiome research applications, providing
reliable comparative data while improving assay consistency. The inclusion of these mock
community controls throughout a metagenomics study is essential for the identification of
potential biases, and can help further elucidate the impact of assay variation on the profiles
of microbial communities obtained from microbiome samples.
To further enhance the use of these microbiome standards, ATCC has collaborated with One Codex to combine the power of physical laboratory standards with the leading bioinformatics platform for microbial genomics and metagenomics. Through this collaboration, ATCC has worked in conjunction with One Codex to develop an
easy-to-use data analysis module for the ATCC® Microbiome Standards that includes pre-loaded metadata; the ability to analyze both shotgun
and 16S rRNA data; automated quality scores assessing true positives, false positives, and relative abundance; and data management, storage,
sharing, and graphing capabilities. The combination of the standards and data analysis platform provides an ideal tool for standardizing data
from a wide range of sources as well as generating consensus among various microbiome applications and analyses.
Overall, a metagenomics-based approach for profiling the human microbiome has greatly enhanced our knowledge of microbial communities
and how these communities affect human health and disease. However, because biases can be introduced throughout the metagenomics
workflow, the true species abundance and community composition can be obscured. ATCC® Microbiome Standards combined with the One
Codex data analysis platform offer a unique solution for assay standardization and eliminating bias during data analysis. Together, these tools
enable you to optimize your metagenomics research applications with confidence, and improve the consistency and reproducibility of your
data run after run.
References
- Committee on Metagenomics: Challenges and Functional Applications. The New Science of Metagenomics: Revealing the secrets of our
Microbial Planet. The National Academies Press, Washington, DC, 2007.
- Wang W L, et al. Application of metagenomics in the human gut microbiome. World J Gastroenterol 21(3): 803-814, 2015.
- Brooks JP, et al. The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies. BMC Microbiol 15: 66, 2015.
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