Microbiome Metagenomics Platform

Our microbiome metagenomics platform is built on the largest collection of deep-sequenced human (infant and adult) and mouse 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 20%. 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, and furhter provides our clients with a market-leading platform for studying the microbiome in relation to health, disease and treatment interventions. In addition, it allows for diverse applications, such as biomarker and drug target discovery, disease aetiology investigation and subject stratification.

To date, we have identified more than 1500 metagenomic species from deep-sequenced shotgun sequencing data of the human and mouse gut microbiome.

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:

 

The functional overlapping species concept
– A way to overcome the functional redundancy and complexity of the microbiome

Most microbiomes consist of many microbial species with overlapping functional niches, and across many instances e.g. with individuals, different species may fill a given niche (see figure). Untamed, this property of microbiomes is an obstacle to classical microbiome-wide association studies. However, by grouping the species that have potential to fill equivalent ecological or functional niches, this challenge can be overcome. Furthermore, group association of functional overlapping species is often much more informative than association to individual species, as the shared properties of the species-group may give hints towards underlying mechanisms behind the association.

Figure: The association between the occurrence of species and a clinical parameter is strengthened when species that share a critical property are grouped

 

Multi-omics data Integration

Integration of multiple omics data - like microbiome, metabolite and clinical data - can generate critical insight to biomedical mechanistic relationships. Data integration typically includes complexity reduction, functional annotation and association linking, and almost always requires customization to the specific customer needs. Clinical-Microbiomics has leading experience with data integration of multiple different omics types, including clinical, microbiome and metabolomics (Nature, 2016); metatranscriptomics and metagenomics (Nature Microbiology, 2016), as well as intervention studies with clinical and microbiome data. On top of all this, we also offer tailored multi-omics data integration and analyses.

Figure: Overview of the workflow integrating human phenotypes, fasting serum metabolome and gut microbiome data (Nature, 2016)

 

Ultra-high-resolution microbiomics

With our ultra-high-resolution microbiomics protocol we can profile a microbiome down to single nucleotide variations (SNVs). For example, we have called 1.4 billion SNVs across 766 human gut microbiome samples. Combined with our metagenomic species binning protocol we can de-novo extract population structures and identify novel strains from shotgun metagenomics, resulting in an unmatched microbiome resolution that facilitates studies of real-time evolution, strain level association studies, and tracking of clonal populations.