CARDIOMyogenisis In Silico (CARDIOMIS): A computational framework for the study of stem cell differentiation towards cardiomyocytes
EXPL/CCI-BIO/1650/2021
EXPL/CCI-BIO/1650/2021
Summary
One of the most fascinating questions in biology is how multicellular organisms achieve an astonishing diversity in cell types despite having essentially the same underlying genetic blueprint, the DNA, in each cell. How this cellular diversity is “bootstrapped” during development has been the focus of biological research for centuries, but only recently technological advents provided us with the tools to study the molecular details on a comprehensive level.
In this project, we will tackle this formidable challenge and obtain models for molecular circuits underlying stem cell differentiation. We will focus on cardiomyogenesis i.e. the differentiation of stem cells into cardiomyocytes. Although major components of cardiomyogenesis are known, many details of how these components interact in a tightly regulated manner during development and maturation are still to be discovered. Besides of its importance during development, cardiomyogensis is also of key interest in regenerative medicine.
The specific objectives are following:
- To derive gene regulatory networks for cardiomyogenesis including the maturation process
- To validate the functional relevance of importance of individual network components
- To predict the implications of these gene networks for cardiovascular diseases and to identify potential therapeutic targets
We will achieve these objectives by combining a wide range of computational and statistical approaches within a systems biology framework. In particular, we will apply and integrate methods of sequence analysis, motif detection, bulk and single cell transcriptomics, reverse engineering, and deep learning. Furthermore, we will develop novel approaches for the identification of activated or repressed regulons and for the consolidation of networks derived from cell population and single cell data. For the construction of gene networks, regulatory interactions will be combined with gene expression and epigenetic profiles. Additionally, potential interactions will be gained through the application of probabilistic, machine and deep learning techniques. Approaches of network biology will be applied to determine the structure, dynamics and functioning of the derived gene regulatory networks. To assess the medical relevance, included genes will be screened for genetic variants associated with cardiovascular disease human phenotypes. Importantly, the validity of the selected predictions for cardiomyogenic regulators will be validated by in vitro experiments and functional assays.
The project is hosted at the Chronic Diseases Research Centre (CEDOC) of the NOVA Medical School in Lisbon. Project Team
- Matthias Futschik (PI), CEDOC, NOVA Medical School
- Fernando Cristo (Co-PI), CEDOC, NOVA Medical School
- José Belo, CEDOC, NOVA Medical School
- Sofia de Sousa Torres , CEDOC, NOVA Medical School
News
Sofia de Sousa Torres joins the CARDIOMIS team
A warm welcome to Sofia, who will be joining our team to work on the computational analysis of gene regulation in cardiogenesis. She holds an MSc in Bioinformatics and Computational Biology from the University of Lisbon and has worked on modeling gene regulatory networks for her Master's thesis. With her expertise, she will be a great asset to our project.
First publication
Our first publication within the framework of our projects has been published in the journal Genes. In this work, we derived gene signatures for stemness that help minimize false positives and increase confidence in the association of genes with stem cell maintenance and differentiation. This research builds on our previously established StemChecker database. Additionally, we implemented a text-mining approach to efficiently identify genes that have not yet been investigated in stem cell biology but are supported by the collected evidence.
- 4 - 14 September 2023 -
The CARDIOMIS team partipated at the Coimbra Summer School for Computational Biology
Matthias and Sofia served as tutors at the Summer School, where they led two mini-research projects. These projects allowed students to apply and expand their knowledge from the lectures to real datasets. Despite the challenging topics, the students enthusiastically embraced the deep dive into bioinformatics, demonstrating creativity and coming up with innovative solutions.
- 11 - 13 October 2023 -
Poster presentation by Sofia at the ETRS & SPCE-TC meeting
The CARDIOMIS team made another trip to Coimbra to participate in the ETRS & SPCE-TC joint meeting 2023. Sofia presented her latest findings on the in silico reconstruction of gene networks from bulk and single-cell RNA-seq data, capturing significant attention from the audience. The meeting provided an excellent platform for the CARDIOMIS team to network with other experts in the field, exchange ideas, and discuss future research directions. The team's participation underscored their commitment to pushing the boundaries of systems biology and their pivotal role in the advancement of gene network analysis for the study of cardiogenesis.
Publications
Tânia Barata, Isabel Duarte and Matthias E. Futschik (2023) Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes. Genes 14 3: 745-745. (html+pdf)
Presentations
Sofia de Sousa Torres, José A. Belo & Matthias E. Futschik (2023) Comparison of methods for inference of gene regulatory networks underlying cardiac cell differentiation, ETRS and SPCE-TC meeting