Biology subjects

Ortega, G.

Publications and source records attributed to Ortega, G..

4 recordsLinked to original sources

bioRxiv2026

BaSiCPy: Scalable and Robust Shading Correction for Optical Microscopy Images

Quantitative fluorescence microscopy is frequently confounded by spatially varying illumination and temporal intensity drift. Although BaSiC is a widely adopted retrospective correction method, it can fail when foreground content is strongly correlated across images--a common regime in time-lapse, tiled and volumetric acquisitions--and its application often requires manual parameter tuning that limits reproducibility and scalability. We introduce BaSiCPy, a foreground-aware implementation of BaSiC that improves illumination profile estimation under correlated foreground structures, provides automatic hyperparameter selection and accelerates large-scale processing through GPU support. BaSiCPy is distributed as an open-source Python package with graphical and programmatic interfaces, facilitating integration into contemporary bioimage analysis workflows.

bioengineering↗

bioRxiv2024

Electrostatic Trade-Off between Mesophilic Stability and Adaptation in Halophilic Proteins

Extremophile organisms have adapted to extreme physicochemical conditions. Halophilic organisms, in particular, survive at very high salt concentrations. To achieve this, they have engineered the surface of their proteins to increase the number of short, polar and acidic amino acids, while decreasing large, hydrophobic and basic residues. While these adaptations initially decrease the thermodynamic stability in the absence of salt, they grant halophilic proteins remarkable stability in environments with extremely high salt concentrations, where non-adapted proteins unfold and aggregate. The molecular mechanisms by which halophilic proteins achieve this, however, are not yet clear. Here, we test the hypothesis that the halophilic amino acid composition destabilizes the surface of the protein, but in exchange improves the stability in the presence of salts. To do that, we have measured the folding thermodynamics of various protein variants with different degrees of halophilicity in the absence and presence of different salts, and at different pH values to tune the ionization state of the acidic amino acids. Our results show that, although electrostatic interactions decrease the stability of halophilic proteins, in exchange they induce a significant salt-induced stabilization and improve solubility. Besides electrostatic interactions, we also show that other general contributions, such as hydrophobic effect and preferential exclusion, are important. Overall, our findings suggest a trade-off between folding thermodynamics and halophilic adaptation to optimize the stability of halophilic proteins in hypersaline environments. Significance statementThis work explores how extreme halophiles adapt their proteins for survival in hypersaline environments. By engineering the protein surface, evolution has selected proteins adapted to high salt concentrations. Our findings suggest a delicate balance between protein stability and haloadaptation modulated in part by electrostatic interactions, furthering our understanding of life adaptation to extreme environments.

biophysics↗

bioRxiv2023

Thermodynamic Stabilization of Human Frataxin

Recombinant proteins and antibodies are routinely used as drugs to treat prevalent diseases such as diabetes or cancer, while enzyme replacement and gene therapies are the main therapeutic intervention lines in rare diseases. In protein-based therapeutics, optimized in vivo stability is key as intrinsic denaturation and intracellular proteostatic degradation will limit potency, particularly in treatments requiring a sustained action, while clearance mechanisms may limit the amount of circulating protein. In vivo stability is ultimately correlated with the intrinsic thermodynamic stability of the biomolecule, but this is difficult to optimize because it often goes at the expense of reducing protein activity. Here, we have used in silico engineering approaches to thermodynamically stabilize human frataxin, a small mitochondrial protein that acts as an allosteric activator for the biosynthesis of Fe-S clusters, whose genetically-driven impairment results in a rare disease known as Friedreich ataxia. Specifically, we developed an efficient thermostability engineering computational approach that combines information on amino acid conservation, the Rosetta energy function, and two recent artificial intelligence tools - AlphaFold and ProteinMPNN - to produce thermodynamically stabilized variants of human frataxin. Such protein variants rescued the large destabilization exerted by well-known pathological mutations, with an increase over 20 {degrees}C in the melting temperature and a thermodynamic stabilization of more than 3 kcal{middle dot}mol-1 at the physiological temperature. This stability surplus is translated into an enhanced resistance to proteolysis, while maintaining the protein fully functional. This case-study highlights the power of our combined computational approach to generate optimized variants, adequate for protein-based therapeutics.

biophysics↗

bioRxiv2019

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer disease and three causality networks of AD: the GR@ACE project.

BackgroundGenetics plays a major role in Alzheimers Disease (AD). To date, 40 genes associated with AD have been identified, although most remain undiscovered. Clinical, neuropathological and genetic variability might impact genetic discoveries and complicate dissection of the biological pathways underlying AD. MethodsGR@ACE is a genome-wide study of dementia and its clinical endophenotypes that encompasses 4,120 cases and 3,289 controls from Spain. GR@ACE phenotypes were defined according to ADs clinical certainty and the presence of vascular co-morbidity. To explore whether clinical endophenotypes reflect variation in underlying biological pathways, we first assessed the impact of known AD loci across endophenotypes to generate three loci categories. Next, we incorporated gene co-expression data and conducted pathway analysis on each category. To assess the impact of heterogeneity in the GWAS findings, the GR@ACE series were meta-analyzed with: 1) genotype-level data from dbGaP (N=21,235); and 2) summary statistics from IGAP Stages I and II (n=61,571 and n=81,455 respectively). FindingsWe classified known AD loci in three categories, which might reflect the disease clinical heterogeneity, from vascular and mixed forms to pure AD pathology. Immune system pathways were detected in all categories. Intriguingly, vascular processes were only detected as a causal mechanism in probable AD. A meta-analysis of GR@ACE with additional GWAS datasets revealed the ANKRD31-rs4704171 signal in the HMGCR genomic region. We confirmed NDUFAF6-rs10098778 and SCIMP-rs7225151, which were previously detected by IGAP, to be suggestive signals. We also confirmed CD33-rs3865444 to be genome-wide significant. InterpretationThe regulation of vasculature is a prominent causal component of probable AD. In that context, cerebral amyloid angiopathy, the unique identified link between the vascular and amyloid hypotheses, deserves further investigation. The GR@ACE meta-analysis revealed novel AD genetic signals. GWAS results are strongly driven by the presence of clinical heterogeneity in the AD series. FundingGrifols SA, Fundacion bancaria "La Caixa", Fundacio ACE and ISCIII (Instituto de Salud Carlos III).

neuroscience↗