Microbiome Big-Data Mining and its Applications
Pharma Tech Outlook

Microbiome Big-Data Mining and its Applications

Pharma Tech Outlook | Monday, July 06, 2020

The term human microbiome has several definitions, depending on the end-use application of the research line. The significant use of microbiology in developing new treatment lines for diseases and infections has generated new revenues. Below given are some of the analytical strategies used for big data mining like the single-cell sequencing and metagenomics.

FREMONT, CA: The human gut microbiome has been confirmed to correlate with human health and diseases by influencing human metabolism, nutrition, physiology, and immune function.  The characterization of the human gut microbiome, and its correlation with conditions, has fascinated a significant number of researchers to explore. The gut microbiome contains over 100 times more genes, compared with 25,000 genes in humans.

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Considering the big data of the gut microbiome, sequencing would be a potentially impactful technology for mining, unlike conventional methods. Sequencing is basically the precondition for getting raw genetic materials of the gut microbiome prior to genetic assembly and taxonomic and functional annotations.

Metagenomic Sequencing

[vendor_logo_first]The metagenomic sequencing process consists of extraction, fragmentation, and sequencing of DNA from all cells in a community, like marker gene analysis, binning, or contig assembly to acquire the taxonomic composition. Metagenomic sequencing can provide insights on who is there at a high resolution to strain level and what they are doing. It is possible to predict the metagenomic reads encoding proteins for functional annotation through several methods, such as protein family classification, gene fragment recruitment, and de novo gene prediction.

Single-Cell Sequencing

One of the essential benefits of single-cell sequencing is the possibility of generation of a high-quality genome for low abundance species, which might be lost by the metagenomic sequencing. Additionally, this method can discriminate and validate individuals' functions within the community, linking them to specific species. Moreover, single-cell sequencing can simultaneously recover bacterial genomes and extrachromosomal genetic materials in a cell, dissecting virus-host interactions at the cell level. Single-cell sequencing has helped novel findings such as the discovery of bacteria with an alternative genetic code and the ability to observe which gut microbial cells use host-derived compounds.

Integrating Single-Cell Genomics and Metagenomics

Metagenomics represents the entire genome containing all microbes in the environment. Single-cell genomics is the genomes of individuals cells that may or may not contain the full genetic repertoire in the microbiota. The integration of these two technologies can compensate for the shortcomings. Several studies have generated much-improved microbe genome assemblies from various microbial communities, using the integration of single-cell genomics and metagenomics. The disadvantage of this integration is that both methods' potential errors would be gathered, thus requiring more sophisticated approaches.

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