Posted Wed, Aug, 03,2016
One of the most important paradigm shifts of our time is realizing how very small organisms produce very big changes in the environment. An excellent illustrating example is the Great Oxygenation Event that transformed an anoxic atmosphere into the oxygen-rich atmosphere that we enjoy today. Microscopic cyanobacteria managed to transform the whole planet. However, only now we are starting to realize the extent of the influence that microbes living within our bodies can exert in our health or even our personality. The relationship between our microbes and ourselves seems to be much more intimate than expected.
The collection of bacteria, virus and fungi that can be found in a biological sample is referred to as the microbiota. We can study what the composition of our microbiota is using specific DNA sequencing methods like the 16S rRNA, which provide the identification of the different species or strains in the sample. But what is it that they are doing at a given moment? How are the interactions within the microbial community? Those are different questions altogether and different data is required to address them.
Although the terms "microbiota" (the microbial taxa associated with humans) and "microbiome" (the catalog of these microbes and their genes, as well as the environmental conditions that surround them) are often used interchangeably, their meanings differ substantially. One critical difference in these definitions is the inclusion of the microbial genomes as part of the microbiome. Genomes are far from being homogeneous within taxa and they are highly mobile across individuals via horizontal gene transfer mechanisms. In other words, the microbiome classifies individuals not only based on their ID but also based on their complete and particular genetic make up under specific circumstances.
This conceptual difference is a big deal. In order to understand how microbial communities can alter the balance of our health or whole ecosystems, we need more information than just the general identification of their members. We need to consider their specific genotype, and the appropriate technique to accomplish this is metagenomics. Furthermore, we may be interested in knowing what their specific gene expression patterns are under given environmental conditions so we would use metatranscriptomics for that. Lastly, if we want to know exactly what chemicals they are producing, we may want to characterize their specific metabolic activity using metabolomics. Each one of these techniques provides complementary information relevant to fully understand what microbiomes do.
However, integrating this multi-omic data is not a trivial task. Elucidating the complex and dynamic interactions among microbes is still largely uncharted territory. In this sense, heterogeneous networks modeled across multi-omic datasets represent a promising approach towards a more comprehensive understanding of the nature and dynamics of microbiomes as well as their implications for health and the environment.
Dr. Victoria Suarez-Ulloa and Dr. Vanessa Aguiar-Pulido are authors of the recently published paper Metagenomics, Metatranscriptomics, and Metabolomics Approaches for Microbiome Analysis, available for download now in Evolutionary Bioinformatics.
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