Our microbiome metagenomics platform is built on the largest collection of deep-sequenced human gut samples assembled with our pioneering metagenomics species (MGS) concept published in Nature Biotechnology. The platform provides our clients with significant advantages compared to competing solutions;
Superior information from shotgun metagenomics
Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. Therefore, we have developed a method for identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes (Nature biotechnology, 2014).
Using this metagenomics species (MGS) concept, we can capture up to 80% of the diversity in the samples while reference-based approaches only capture around 25%. This allows for studying the very large unknown part of the microbiome as we can assign it to distinctive species and investigate their functional and metabolic potential.
To date, we have identified more than 1500 metagenomic species from deep-sequenced shotgun sequencing data of the human and mouse gut microbiome, ocean water, soil etc.
Imputed shotgun metagenomics
By leveraging our vast collection of deep-sequenced human gut samples we can impute the microbiome composition at up to 40 times reduced sequencing depth without any significant reduction in quality compared to traditional shotgun metagenomics. Imputed metagenomics is ideal for comparative studies normally associated with high costs for sequencing or which alternatively would rely on inferior 16S metagenomics due to cost concerns. With imputed metagenomics you get the full shotgun metagenomics picture of the microbiome including its functional potential, but at a fraction of the sequencing cost.
Advanced bioinformatics analyses
The microbiome metagenomics platform further allows for a suite of advanced analyses, which enable detailed insights of the microbiomes in pre-clinical and clinical projects. From regular deep-sequencing shotgun metagenomics, we can obtain strain-level resolution of the microbiome, assess growth dynamics, colonization and persistence probabilities and integrate shotgun metagenomics with other -omics data and clinical data for biomarker discovery and etiology identification.
These advanced analyses significantly improve our understanding of the microbiome in health, disease and treatment and are ideal for research activities related to microbiome drug discovery, pre- and probiotics and microbiome-drug interactions. With these tools we are able to move from the standard association studies towards revolutionizing insights about microbiome dynamics.
More in-depth descriptions of the various techniques enabled by shotgun sequencing are discussed under following links: