Microbiome services

This project aims to strengthen the basis for a one-stop shop connecting databases, datasets and tools for the deployment of the engineering Design-Build-Test-Learn (DBTL) framework in biotechnology. It will do so by surveying the tools and data landscape, pinpointing gaps and opportunities, and establishing design patterns for task-specific workflows for analysis, integration and sharing of multimodal data. 

It will provide a resource that will allow users to navigate the complex landscape of biotechnology tooling and data, as well as to establish solutions that fit their specific DBTL requirements. Use cases from ongoing programmes in various communities will be used to ascertain and establish the pragmatic value of the solutions. 

The work will be carried out through hands-on activities, dedicated workshops and hackathons, providing training and resources, as well as fostering industrial engagement. The experience of the communities and platforms involved in systems biology, industrial biotechnology, metabolic modelling, metabolomics, enzymes, bioprospecting and data management will be particularly valuable in this respect, as well as their respective industrial relations. Accordingly, the project engages participants from seven ELIXIR nodes and connects researchers and their activities from six communities. 

The project outcomes will contribute to advancing the ambition of connecting the latest developments and established data resources across ELIXIR to realise the potential of cellular and molecular biology, particularly in the fields of industrial biotechnology and biomanufacturing.

Workflow finalisation, training material development, real data evaluation and resource allocation tool creation

Metagenomics Assembled Genomes (MAGs) are crucial for understanding biodiversity, enhancing food security and combating pathogens by providing insight on uncultured and unexplored genomes. This proposal outlines a comprehensive project aimed at advancing metagenomics research through the advancement, optimisation, evaluation and dissemination of robust FAIR workflows for building MAGs. 

Leveraging the Galaxy platform, our primary objectives include finalising a user-friendly state-of-the-art Galaxy workflow tailored for MAG construction, and ensuring its accessibility and reusability through integration with WorkflowHub. To support user adoption and proficiency, we will create FAIR educational materials hosted on the Galaxy Training Network (GTN), empowering researchers with the skills necessary to use the workflow effectively. 

The efficacy of the developed workflow will be rigorously evaluated by analysing MAGs generated from simulated and real-world data-spanning diverse environments: atmosphere, marine and cow gut microbiomes. This evaluation will provide valuable insights into the workflow's performance and its applicability across different sample types, complexities and ecosystems.

We will also investigate the computational resources required for executing the assembly step of the workflow using data provided by several Galaxy servers and the MGnify team on various input datasets. The aim would be to optimise resource allocation to ensure efficient and cost-effective MAGs construction. A novel tool will be developed to facilitate this process, allowing researchers to accurately estimate and allocate resources for each step of the assembly pipeline. 

By addressing these objectives, our project aims to accelerate metagenomics research by providing researchers with a comprehensive and accessible framework for MAGs construction. This framework will not only streamline the workflow for building MAGs but also facilitate reproducibility, collaboration and innovation within the ELIXIR Microbiome Community.