PID2020-113203RB-I00

TITLE OF THE PROJECT (ACRONYM): (MODCRE) Modelling of Cis-Regulatory Elements: Structural modelling of protein-DNA interactions to predict DNA-binding modulation. Applications in gene-therapy and systems medicine.

SUMMARY

Transcriptional regulatory elements in complex genomes are key players of the genome during development, cell and tissue homeostasis, responses to external stimuli, and disease. High-throughput experiments of genomics and proteomics have provided a plethora of activating regulatory elements, promoters and enhancers, of the genome. However, very few proteins in human occupy most of their motif matches under physiological conditions, which highlights the importance of the balance between the co-operativity of transcription factors (TFs), their strength upon binding and the environment (such as chromatin state and epigenetic marks). Co-operative recognition of DNA by multiple TFs defines unique genomic positions on the genome and confers a robust regulation. Most eukaryotic TFs recruit cofactors as coactivators or corepressors forming large complexes formed by protein-protein and protein-DNA interactions to regulate transcription. Of particular interest is the co-operation of pioneer factors (the first to engage target sites in chromatin, culminating in transcription by displacing nucleosomes). Protein-DNA binding strength has been of extraordinary importance for understanding cooperativity and transcription regulation. Variable TF-DNA interactions are increasingly considered as key drivers of phenotypic variation. Overall, about 19% of the human TFs are currently associated with at least one phenotype and a significant number of mutations associated with diseases are within or near genes encoding TFs. In the last years, different models for representing TF motifs, such as machine learning models combining multiple layers of genomic, transcriptomic, DNase hyper-sensitivity (DHS) and epigenomic information, were developed to score new putative regulatory sequences or calculate the 'gainability' and 'disruptability' of Single Nucleotide Variant (SNV) alleles. The strength of binding of TFs may not only be affected by mutations, but also by epigenetic modifications of chromatin, such as methylation of cytosine bases. With the emergence of new methods to outline DNA binding, methylation was found to be abundant throughout the genome except at active regulatory regions bound by TFs, such as gene promoters and distal enhancers. There are also few examples where modification of a single CpG dinucleotide directly affects transcription factor binding and regulation of a target gene in vivo.Therefore, understanding the features that determine the binding strength between TFs and TF Binding Sites and the co-operation between TFs is crucial to explain gene cis-regulation and the genotype-phenotype relationship. The main objective of our proposal is to understand, model and predict the effect of changes, genetic and/or epigenetic, in the DNA sequence. Our study will help us to understand the mechanisms of pioneer factors and on the re-design of DNA-binding proteins, not only TFs but also integrases, transposases and nucleases, with increasing relevance in genome-editing. Some examples are the re-design of homing endonuclease I-Msol or the potential use of PiggyBac (PB) cut-and-paste DNA transposase in genome-editing. The lack of a DNA footprint left behind after piggyBac transposition has boosted its exploitation for genome engineering, while nucleases have been used since the early applications in genome-editing and gene therapy in combination with Zinc-fingers or CRISPR.

KEY WORDS: Transcription Factors, cis-regulation, homology modelling, genome-editing, gene-therapy, Protein-DNA binding, SNVs in genetic diseases, co-operative binding sites, methylation of cytosines

CardioStressCI

ERA-CVD Joint Transnational Call 2020

TITLE OF THE PROJECT: Cardiovascular stress impacts on neuronal function: intracellular pathways to cognitive impairment

ACRONYM: CardioStressCI

SUMMARY

Vascular Cognitive Impairment (vCI) is known to be tightly linked to cardiovascular disease (CVD). The main purpose of the CardioStressCI project is to identify and validate causative mechanisms connecting both conditions. We will use an interdisciplinary approach that combines in vitro research with bioinformatics, systems biology modeling and clinical database analysis. We will use network-based disease gene prioritization algorithms to rank the relevance of genes in CI and CVD, and correlate the results to establish interaction networks, which will be modeled using systems biology approaches. Predictions will be validated experimentally with human samples and cell and animal models, to investigate and confirm how individual components of these networks may influence the responses to the different CVD pathological stresses that lead to CI.

The main aims of CardioStressCI are: i) to identify proteins linked to CI and CVD; ii) to establish the contribution of nitro-oxidative stress to CVD and CI; iii) to study how CVD induces neuronal dysfunction; iv) to elucidate the pattern of the inflammasome activation in CI and CVD; v) to determine vCI biomarkers.

Our studies will consider gender aspects, age, and socio-economic and lifestyle factors as potential modulators of CI pathophysiology. We aim at increasing the knowledge of the molecular mechanisms that contribute to CI when CVD happens. Such knowledge can inform new directions to potentially improve diagnosis, prevention and new therapeutic targets against CI, and even CVD preventing its consequences in brain function.

KEY WORDS: Nitro-oxidative stress; Calcium; Inflammasome; Amyloidosis; Atherosclerosis; Atrial fibrillation; Neuronal dysfunction.

BIO2017-85329-R

TITLE OF THE PROJECT: isPBM (in silico protein binding micro-arrays): Structural modelling of the binding between transcription-factors and DNA with biomedical applications in networks and systems medicine

ACRONYM: isPBM

SUMMARY

Interactions between transcription factors (TFs) and their binding sites play important roles in many biological processes. Genomic analyses often involve scanning for potential TF binding sites (named motifs) using models of the specificity of the DNA binding domain (DBD) of the TF. Although a large number of TFs have been identified, it is not well known which motifs they can recognize. A major difficulty in studying TF-DNA binding specificity and, therefore, in evaluating models for representing this specificity has been scarcity of structural data. Several studies have attempted to characterize the motifs of a TF by summarizing all its DNA binding sites as a position weight matrix (PWM) using experimental methods. A large amount of data from these experiments is collected in the database CIS-BP. In this project, we will use homology modelling to span the number of structures of known TF-DNA bindings in CIS-BP. We will use these structures to calculate family-specific statistic potentials for the amino-acid-nucleotide interactions. Then, we will use these potentials to characterize, from a theoretical view, the specificity of the interactions between TFs and their DNA motifs, starting by obtaining theoretical PWMs for all modelled TFs. First, the prediction of the correspondence between TFs and their DNA motifs; second, a potential change of specificity caused by mutations; and third, the protein-engineering of a TF highly specific for a DNA motif, have all ultimate impact on the study of mechanistic insights of diseases and phenotypes and for the use of gene-therapies. We will analyse how the changes of specificity of TF-DNA interactions caused by mutations affect the rewiring of the protein-interaction network. As an example, recent works have evinced that positive selection of mutations in transcription factor binding sites affect the regulation of important cancer cell functions. Likewise, for the study of the cross-species interactome, some proteins can act as transcription factors in another specie, thus affecting the regulatory network. Our goal is to understand the mechanisms of recognition and interaction of TFs with their corresponding DNA binding site, focused in the biomedical applications in networks and systems medicine. With this porpose, we will develop the bioinformatics tools to: 1) predict and model TF-DNA bindings in enhancer and promoter regions; and 2) predict the effect of mutations in both sides of the interface of the interaction. Finally, programmable nucleases for genome editing are synthetically constructed by the fusion of a nuclease and a highly specific DNA binder (such as transcription-activator like effectors, TALE, zinc-finger transcription factors, C2H2-zinc fingers, or RNA-guided using the CRISPR system). Thus, we propose a third application: a bioinformatic tool to obtain the theoretical best sequence of a TF targeting a DNA motif with high specificity, that can be used to construct new programmable nucleases, using the scaffold of other TFs different from zinc-fingers or TALE.

KEY WORDS: transcription factors; protein-DNA interaction; macromolecular modeling; genome editing; regulatory network; DNA mutations

Awards

2007 Drugs for Ageing. Award Pyme of “Red de Fundaciones Universidad-Empresa” for the collaboration in a Singular Specific Project (PSE) of Spanish Ministry of Science and Education (MEC) with Infociencia S.A.

2014 DREAM Challenge Award Best Performer in the DREAM 8.5:Rheumatoid Arthritis Responder Prediction Challenge". Sub-challenge 2

Old Grants

Búsqueda y caracterización automática de las posibles interacciones proteína-proteína como herramienta de ayuda al estudio de micro-matrices de DNA. Finance provider: Fundación Ramón Areces

BIO2002-03609 Desarrollo de modelos bioinformáticos para analizar interacciones entre proteínas en redes de señalización intracelulares: aplicación al estudio de MAP quinasas. Ministerio de Ciencia y Tecnologia & FEDER

Gaspar de Portolà Grant. Finance provider: CIRIT

INFOBIOMED: Structuring European Biomedical Informatics to Support Individualised Healthcare Finance provider: FP6-EC

Patogénesis de la metástasis del cáncer de mama: Análisis proteómico de rutas metabólicas influenciadas por Bcl-xL Finance provider: Redes de investigación cooperativa (FIS)

BIO2005-00533 Desarrollo de modelos bioinformáticos para analizar interacciones entre proteínas (II): Aplicaciones en la predicción de estructura y función de proteínas.Finance provider: Ministerio de Educación y Ciencia & FEDER

Evaluador de riesgo poblacional mediante análisis de microarrays e inteligencia artificial.FIT-350300-2006-40 Finance provider: Ministerio de Industria Turismo y Comercio ( PROFIT)

FIT-350300-2006-41 Prototipo de telemedicina para el seguimiento de alteraciones cardíacas y manchas sospechosas en la piel mediante terminales 3g comerciales y conexión umts. sistema prediagnóstico por inteligencia artificial y tecnologia grid. Ministerio de Industria Turismo y Comercio (PROFIT)

FIT-350300-2006-42 HAND-HEALTH FRIEND: Proyecto de investigación para el diseño de una nueva plataforma inteligente para el control de la salud personal y comunitaria sobre terminales móviles comerciales.Finance provider: Ministerio de Industria Turismo y Comercio (PROFIT)

ANEURIST Finance provider: European Commission FP6

PSE-010000-2007-1 Identificación de dianas secundarias y diseño de fármacos para enfermedades relacionadas con el envejecimiento mediante análisis estructural y funcional de rutas biológicas. Ministerio de Educación Ciencia & FEDER

FIT-350300-2007-72 Prototipo de telemedicina para el seguimiento de alteraciones cardíacas y manchas sospechosas en la piel mediante terminales 3g comerciales y conexión umts. sistema prediagnóstico por inteligencia artificial y tecnologia grid. Ministerio de Industria Turismo y Comercio ( PROFIT)

FIT-350300-2007-67 Evaluador de riesgo poblacional mediante análisis de microarrays e inteligencia artificial. Finance provider: Ministerio de Industria Turismo y Comercio ( PROFIT )

TSI-020100-2008-473 Playing Doctor: la revision médica completa en el PC domestco. Ealuación del sistema cardiovascular, respiratorio, auditivo, y otras afecciones de alta pre-valencia Finance provider: Ministerio de Industria Turismo y Comercio (PROFIT)

BIO2008-00205 Integración, análisis y modelado de redes de rutas biologicas: interaccion proteina-proteina, vias de señalización y regulación de la transcripcion. Finance provider: Ministerio de Educación y Ciencia & FEDER