Antonio Del Sol Mesa
adelsol
Antonio Del Sol Mesa
GROUP LEADER
Ikerbasque Research Professor
Ikerbasque Research Professor
Computational Biology Lab
Address: Bizkaia Science and Technology Park, building 801A, Derio (Bizkaia)

Antonio del Sol obtained his BSc in Physics from the Moscow State University "M.V. Lomonosov" and continued his scientific pursuits by completing his PhD in Mathematical Physics from the National Autonomous University of Mexico.

In 1995, Dr. Del Sol joined the Instituto de Física, UNAM (Mexico) as a postdoctoral researcher and by 1996, he became a full-time researcher and was honored with the “Cátedra Patrimonial de Excelencia, Nivel II” by CONACYT. Following this, Dr. Del Sol pursued further postdoctoral studies at the Protein Design Group at Centro Nacional de Biotecnología (CSIC) in Madrid until 2001. Subsequently, he embarked on a BBSRC Research Fellowship at the Bioinformatics Unit at the Computer Science Department at the University College London, UK.

In 2018, Dr. Del Sol joined CIC bioGUNE as an Ikerbasque Research Professor and Group Leader, leading the Computational Biology Group. His laboratory's primary focus lies in computational systems biology, particularly in the realms of stem cell research, aging, and disease modeling. He is also Professor of Bioinformatics at the University of Luxembourg and head of the Computational Biology group at the Luxembourg Centre for Systems Biomedicine (LCSB).

Awards & recognitions
FNR award for Outstanding Scientific Publication for the research article entitled “Transcriptional synergy as an emergent property defining cell subpopulation identity enables population shift” published in the journal Nature Communications, 2018 (DOI: 10.1038/s41467-018-05016-8) (2019). Fujirebio Award for Drug Research and Development (2007). BBSRC Research Fellowship at the University College London (2003-2001). Cátedra Patrimonial de Excelencia, Nivel II, CONACYT, National Autonomous University of Mexico (1997-1996). Medal of Distinction "Gabino Barreda" issued to the best Ph.D. graduated at the National Autonomous University of Mexico (1994).

Latest Publications

2023

2022

2021

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/

Latest Publications

SinCMat: A single-cell-based method for predicting functional maturation transcription factors.

Barvaux, Sybille; Okawa, Satoshi; Del Sol, Antonio;

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 modelling of stem cell-niche interactions facilitates discovery of strategies to enhance tissue regeneration and counteract ageing

Potapov, I; Garcia-Prat, L; Ravichandran, S; Munoz-Canoves, 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

Altered sphingolipid function in Alzheimer's disease; a gene regulatory network approach

Giovagnoni, C; Ali, M; Eijssen, LMT; Maes, R; Choe, K; Mulder, M; Kleinjans, J; del Sol, A; Glaab, E; Mastroeni, D; Delvaux, E; Coleman, P; Losen, M; Pishva, E; Martinez-Martinez, P; van den ...

NEUROBIOLOGY OF AGING

2021-03-25

A computer-guided design tool to increase the efficiency of cellular conversions

Jung, S; Appleton, E; Ali, M; Church, GM; del Sol, A;

NATURE COMMUNICATIONS

2021-03-12

Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19

Jung, S; Potapov, I; Chillara, S; del Sol, A;

SCIENCE ADVANCES

2021-02-01

The Importance of Computational Modeling in Stem Cell Research

del Sol, A; Jung, S;

TRENDS IN BIOTECHNOLOGY

2021-01-13

Computational Stem Cell Biology: Open Questions and Guiding Principles

Cahan, P; Cacchiarelli, D; Dunn, SJ; Hemberg, M; Lopes, SMCD; Morris, SA; Rackham, OJ; del Sol, A; Wells, CA;

CELL STEM CELL

2021-01-07