The Computational Biology Group is dedicated to developing computational models spanning various levels of biological organization, including cellular, tissue, and organ levels. Our overarching goal is to address challenges in the fields of stem cell research, aging, and disease modeling. Our computational models employ methodologies from different areas of mathematics, engineering, and physics, and integrate multiple sources of biological information (e.g., transcriptomics, epigenomics, proteomics) to study biological processes at different levels of organization.
Research line 1: Stem cell research and regenerative medicine
Cell therapy, promising for treating diseases by replacing damaged cells, faces a challenge in generating specific cell subpopulations. Our computational platform, based on a gene regulatory network model, identifies optimal conversion factors. Currently applied to projects like in-vitro corneal limbus stem cell generation, it aims to treat patients with corneal injuries. The platform is also used for producing corticospinal tract neuron progenitors for spinal cord injury cases. Predictions for converting cardiac cells are being validated, with potential implications for treating cardiovascular diseases.
Research line 2: Aging and rejuvenation
Quantifying cellular biological age holds promise for discovering rejuvenation strategies. We have developed a multi-tissue RNA clock to assess the biological age of cells based on transcriptional profiles, emphasizing key cellular processes. Additionally, a fibroblast-specific RNA clock predicts rejuvenation factors. In addressing brain aging, we have identified dysregulated pathways and molecules, predicting chemical cocktails for brain rejuvenation. Experimental validation is underway in human cells and animal models. Our goal is to apply this approach to Alzheimer's and Parkinson's disease models as a therapeutic strategy against neurodegenerative diseases linked to aging.
Research line 3: Disease modeling
Addressing the cytokine storm in inflammatory diseases, we identified therapeutic targets by mapping immune responses in COVID-19 patients. This approach will be extended to modulate hyperinflammation in systemic inflammatory response syndrome (SIRS), utilizing computational predictions for drug repurposing. In another initiative, we tackle congenital disorders by predicting malfunctioning transcription factors affecting progenitor cell differentiation. Our method identified determinants in cardiac development and mitochondrial DNA-associated Leigh syndrome, suggesting potential therapeutic targets. Ongoing validation in an EU-funded consortium aims to identify repurposable compounds for treating MILS and related conditions.
Collaborations
George Church (Harvard Medical School, USA), Marius Wernig (Stanford University, USA), Michele de Luca (University of Modena and Reggio Emilia, Modena, Italy), Mark H. Tuszynski (University of California San Diego, USA), Ruben Nogueiras (University Santiago de Compostela, Spain), Anne Grapin-Botton (Max Planck Institute of Molecular Cell Biology and Genetics, Germany), Hongkui Deng (Beijing University, China), Carol Schuurmans (University of Toronto, Canada), Magdalena Götz (Ludwig-Maximilians-Universität München, Germany), Deepak Srivastava (Gladstone Institutes, San Francisco, USA).
Links
Webpage: https://www.uni.lu/lcsb-en/research-groups/computational-biology/people/
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Group Leader
Antonio Del Sol Mesa
Ikerbasque Research Professor POSTDOCTORAL RESEARCHER -
Martín Parga Pazos
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Sascha Jung
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Champi Thusangi Wannige
TECHNICIANS / DOCTORAL CANDIDATES -
Javier Arcos Hodar
Members
Latest Publications
Ice recrystallization inhibitors enable efficient cryopreservation of induced pluripotent stem cells: A functional and transcriptomic analysis
Mommaerts, K; Okawa, S; Schmitt, M; Kofanova, O; Turner, TR; Ben, RN; Del Sol, A; Mathieson, W; Schwamborn, JC; Acker, JP; Betsou, F;
STEM CELL RESEARCH
2024-12-01
Detecting expressed genes in cell populations at the single-cell level with scGeneXpress
Jung, SS; Barlier, C; Perez, AM; del Sol, A;
BRIEFINGS IN BIOINFORMATICS
2024-10-05
The cell rejuvenation atlas: leveraging network biology to identify master regulators of rejuvenation strategies.
Arcos Hodar, Javier; Jung, Sascha; Soudy, Mohamed; Barvaux, Sybille; Del Sol, Antonio;
Aging
2024-09-09
Pten regulates endocytic trafficking of cell adhesion and Wnt signaling molecules to pattern the retina
Touahri, Y; Hanna, J; Tachibana, N; Okawa, S; Liu, H; David, LA; Olender, T; Vasan, L; Pak, A; Mehta, DN; Chinchalongporn, V; Balakrishnan, A; Cantrup, R; Dixit, R; Mattar, P; Saleh, F; Ilnytskyy, ...
CELL REPORTS
2024-03-27
SinCMat: A single-cell-based method for predicting functional maturation transcription factors
Barvaux, S; Okawa, S; del Sol, A;
STEM CELL REPORTS
2024-02-13
Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq
Raevskiy, M; Yanvarev, V; Jung, SS; Del Sol, A; Medvedeva, YA;
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
2023-04-01
Measuring biological age using a functionally interpretable multi-tissue RNA clock
Jung, SS; Hodar, JA; del Sol, A;
AGING CELL
2023-03-16
Transcriptional and Chromatin Accessibility Profiling of Neural Stem Cells Differentiating into Astrocytes Reveal Dynamic Signatures Affected under Inflammatory Conditions
Pavlou, MAS; Singh, K; Ravichandran, S; Halder, R; Nicot, N; Birck, C; Grandbarbe, L; del Sol, A; Michelucci, A;
CELLS
2023-03-01
A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion
Zheng, ML; Xie, BQ; Okawa, S; Liew, SY; Deng, HK; del Sol, A;
STEM CELL REPORTS
2023-01-10
Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration
Moiseeva, V; Cisneros, A; Sica, V; Deryagin, O; Lai, YW; Jung, SC; Andrés, E; An, J; Segalés, J; Ortet, L; Lukesova, V; Volpe, G; Benguria, A; Dopazo, A; Aznar-Benitah, S; Urano, Y; del Sol, ...
NATURE
2022-12-21
ChemPert: mapping between chemical perturbation and transcriptional response for non-cancer cells
Zheng, ML; Okawa, S; Bravo, M; Chen, F; Martínez-Chantar, ML; Del Sol, A;
NUCLEIC ACIDS RESEARCH
2022-10-06
Neural network learning defines glioblastoma features to be of neural crest perivascular or radial glia lineages
Hu, YZ; Jiang, YW; Behnan, J; Ribeiro, MM; Kalantzi, C; Zhang, MD; Lou, DH; Häring, M; Sharma, N; Okawa, S; Del Sol, A; Adameyko, I; Svensson, M; Persson, O; Ernfors, P;
SCIENCE ADVANCES
2022-06-10
Combinatorial analysis reveals highly coordinated early-stage immune reactions that predict later antiviral immunity in mild COVID-19 patients
Capelle, CM; Ciré, S; Domingues, O; Ernens, I; Hedin, F; Fischer, A; Snoeck, CJ; Ammerlaan, W; Konstantinou, M; Grzyb, K; Skupin, A; Carty, CL; Hilger, C; Gilson, G; Celebic, A; Wilmes, P; Del ...
CELL REPORTS MEDICINE
2022-04-19
Fostering experimental and computational synergy to modulate hyperinflammation
Potapov, I; Kanneganti, TD; del Sol, A;
TRENDS IN IMMUNOLOGY
2022-01-01
Computational Methods to Identify Cell-Fate Determinants, Identity Transcription Factors, and Niche-Induced Signaling Pathways for Stem Cell Research.
Ali, Muhammad; Ribeiro, Mariana Messias; Del Sol, Antonio;
Methods in molecular biology (Clifton, N.J.)
2022-01-01
Computational modelling of stem cell-niche interactions facilitates discovery of strategies to enhance tissue regeneration and counteract ageing
Potapov, I; García-Prat, L; Ravichandran, S; Muñoz-Cánoves, P; del Sol, A;
FEBS JOURNAL
2021-05-14
Proneural genes define ground-state rules to regulate neurogenic patterning and cortical folding
Han, SS; Okawa, S; Wilkinson, GA; Ghazale, H; Adnani, L; Dixit, R; Tavares, L; Faisal, I; Brooks, MJ; Cortay, V; Zinyk, D; Sivitilli, A; Li, SQ; Malik, F; Ilnytskyy, Y; Angarica, VE; Gao, JH; ...
NEURON
2021-09-16
A Catalogus Immune Muris of the mouse immune responses to diverse pathogens
Barlier, C; Barriales, D; Samosyuk, A; Jung, S; Ravichandran, S; Medvedeva, YA; Anguita, J; del Sol, A;
CELL DEATH & DISEASE
2021-08-17
FunRes: resolving tissue-specific functional cell states based on a cell-cell communication network model
Jung, S; Singh, K; del Sol, A;
BRIEFINGS IN BIOINFORMATICS
2021-07-01
A 3D system to model human pancreas development and its reference single-cell transcriptome atlas identify signaling pathways required for progenitor expansion
Gonçalves, CA; Larsen, M; Jung, SC; Stratmann, J; Nakamura, A; Leuschner, M; Hersemann, L; Keshara, R; Perlman, S; Lundvall, L; Thuesen, LL; Hare, KJ; Amit, I; Jorgensen, A; Kim, YH; del Sol, ...
NATURE COMMUNICATIONS
2021-05-25