If you are planning to start a new project in which you plan to get biological samples from animals, you should consider developing it within the framework of the EHI. But also, if you are sampling animals for research or training purposes, and you can get biological samples that may contribute to existing projects, we encourage you to contact us and request sampling kits. Participate in the EHI and make the most of your field work!
If you want to participate in the EHI, contact us. We anticipate three main types of participation, although we are open to discuss all means of collaboration. Just let us know what you are willing to provide to the initiative and what you want to get from the EHI. We will then formalise the collaboration in the EHI Participation agreement.
Let's work together to make sure all required permits are in place before the sampling campaign!
Familiarise yourself with the EHI sampling requirements. Samples must be frozen within 14 days, and the time and conditions before freezing must be acknowledged. Samples need to be collected as sterile as possible as the laboratory procedures used in the EHI (shotgun sequencing) are very sensitive to contamination. Inform yourself about the sampling options.
The EHI follows the GSC-developed data reporting standard designed for accurate reporting of contextual information for samples associated with genomic and metagenomic sequencing. We request four types of metadata per sample: sampling event, host animal, environment, sample. Metadata collection sheets and instructions can be found here.
After the sampling is done, the samples need to be shipped to the EHI in Denmark. We will assist you as much as possible with the required paperwork, the boxing, and the shipping of the samples.
to break down the complex matrix of the sample.
to isolate DNA molecules from the rest of organic materials in the mixture.
to achieve desired molecule sizes for optimal short-read sequencing.
to convert fragmented DNA molecules into a format that is compatible with the sequencing platform.
to amplify the library using primers containing unique identifiers.
to create a single sequencing pool containing multiple libraries in desired proportions.
The bioinformatic pipeline begins by assessing and filtering raw sequencing data to remove low-quality reads, adapters, and contaminants. This step ensures the data’s reliability and quality. Then, host and non-host data are being split: the metagenomic fraction is separated from the host, by mapping the reads against a reference host genome.
Next is the metagenomic assembly: the remaining non-host reads are assembled into contigs or scaffolds using metagenomic assembly software. This step results in a set of contigs representing the genetic material of the microbial community. The assembled contigs are then binned: clustered into metagenome-assembled genomes (MAGs) based on sequence composition, coverage, and other characteristics.
The MAGs are annotated to determine their taxonomic identity and functional potential.
MAGs are dereplicated to remove redundancy and retain only unique genomic representatives. This step ensures that each MAG represents a distinct microbial population or genome. Finally, to understand the composition of the gut microbiota in individual samples, the pre-processed reads from each sample are mapped against the dereplicated MAG catalogue. This step quantifies the abundance of each MAG in each sample, allowing for a comprehensive view of the microbial community composition.
Bioinformatic hologenomic approaches require reference genome sequences of host species to be available in order to split host DNA from metagenomic DNA and generate whole genome sequence profiles of analysed individuals.
Generating some general statistics to obtain an overview of the data. Further, production of general MAG statistics and investigation of the geographic distribution of the sample.
Exploring the characteristics of the MAG catalogue generated through the EHI pipeline. Analysing the MAG phylogeny, quality, and functional attributes. Using the MAG functional annotation, it is possible to ordinate prokaryotic genomes on a bidimentional space. In doing so, one can assess how close any group of bacteria are in functional terms, or how functionally diverse the members of a given phylum can be.
Investigating the distribution of reads across samples and the estimated vs. mapped prokaryotic fraction, in order to estimate whether a prokaryotic community has been properly represented, or whether further sequencing is required.
Transformation and visualisation of the quantitative information of the MAGs. Including minimum coverage filtering to minimise artificial inflation of diversity. Also performing genome size normalisation to account for genome size biases: read-counts can be normalised by applying a normalisation factor that modifies the read numbers according to the size of each genome compared to the average genome size in the dataset. Finally, generating a count table to visualise the relative MAG abundances per sample.
Exploration of the taxonomic characteristics of the MAG catalogue across samples.
Performing alpha and beta diversity analyses of the count data generated through the EHI pipeline.
Center for Evolutionary Hologenomics, GLOBE Institute
University of Copenhagen
Øster Farimagsgade 5, 7
1353 Copenhagen K, Denmark
Coordinator: Antton Alberdi, PhD
Email: ehi@sund.ku.dk