TETRA: Metatec
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TETRA: Metatec
Metagenomics or metagenome analysis is the study of all DNA present from an isolated sample and involves the simultaneous identification of multiple (micro-)organisms for numerous applications. DNA sequencing technologies have made it possible to obtain the complete DNA of uncultivated microorganisms. However, the identification of organisms from mixed populations using traditional short-read sequencing technologies remains a challenge. The latest nanopore sequencing technology consists of real-time, long read sequencing that can overcome limitations of these methods. In this project we will develop new metagenomics applications using nanopore sequencing with various field partners. Furthermore, automation of sample preparation and artificial intelligence (AI) for data analysis will also be investigated.
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Quick facts
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TETRA PROJECT
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2 YEARS (2022-2024)
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PROJECT OF BIKC (BIOINFORMATICS KNOWLEDGE CENTER)
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COLLABORATION WITH CYBER 3.0 (AI PART)
Why is this project so relevant?
(Micro)organisms are found everywhere in nature and thrive over an immensely wide range of conditions. For example, the majority of MOs are traditionally difficult or impossible to grow. Metagenomics based on high-throughput sequencing (HTS) enables the study of all (micro-)organisms, regardless of whether they can be cultivated or not, by performing genomic analysis on their extracted DNA. It helps researchers to analyze specific organisms from many samples, such as clinical and environmental samples. This provides knowledge about the species present and makes it possible to extract information about the functionality and properties of certain communities
Metagenomics has been extensively used in the last decade for numerous applications across various domains, such as in clinical microbiology, in industry and for ecological applications. It can be divided into two well-defined methods: whole genome and targeted metagenomics.
The first method involves processing the entire DNA of a sample. This provides a complete picture of all organisms in the sample and offers the opportunity to investigate, for example, the types and functions of the organisms. However, with conventional short read sequencing techniques, it is expensive to sequence all the DNA and involves challenging data analysis due to the size and complexity of the data. For example, databases containing reference DNA with which the DNA must be compared (in order to identify the DNA to be examined) can be immense, which is a limiting factor because many research facilities are not able to store and process such a large amount of data.
Targeted metagenomics, on the other hand, focuses on certain pieces of DNA in the sample (e.g. 16S rRNA gene). This can be done by specifically copying the pieces of DNA of interest to determine, for example, what type of organism they belong to. By amplifying this region before DNA determination, the amount of data to sequence and analyze is greatly reduced. However, the disadvantage is that an amplification step can introduce bias into the obtained data and only information is obtained about the amplified regions.
Metagenomics is therefore on the rise, but plenty of research is still required per application.
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Contributors
Researchers
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Kyra Van Den Eynde, AI/CS Researcher, AI Lead
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