Biology subjects

Lobo, A.

Publications and source records attributed to Lobo, A..

4 recordsLinked to original sources

bioRxiv2026

Thermodynamic Profiling of Glucose Translocation in POPC embedded GLUT-4 protein models

The facilitative transport of hexose through the GLUcose Transporter type 4 (GLUT4) is essential for cellular metabolism and is regulated by allosteric nucleotide interactions. In this study, we conducted a comparative biophysical analysis of glucose translocation using both the native Cryo-EM structure (7WSN) and the AI-predicted AlphaFold model using Steered Molecular Dynamics (SMD) at physiological (310.15 K) and attenuated (303.15 K) temperatures with two different allosteric modulators, ATP and ADP. While the AlphaFold model managed to capture baseline static topologies, dynamic profiling revealed that it intrinsically over-optimizes for static stability, immediately collapsing into a sterically occluded, hyper-packed artifact. Translocation through this constricted geometry forces severe steric solvent exclusion, abruptly stripping the substrates hydration shell and resulting in immediate and immense thermodynamic friction (>300 kJ/mol). Under ATP-bound physiological strain, this hyper-bonded structural clamp prevents functional relaxation, ultimately inducing a catastrophic kinematic failure. Furthermore, ensemble Dynamic Cross-Correlation Matrix (DCCM) analysis demonstrates that the AI-predicted model suffers from persistent rigid-body locking, forcing the transmembrane domain to behave as a kinetically trapped conformation. In contrast, the functionally hydrated Cryo-EM architecture actively maintains a dual-gating pore and successfully isolates the exact mechanical lever driving transport: a native Proline hinge (PRO379) that seamlessly routes allosteric signals from the nucleotide anchor to the pore gate. Within the AlphaFold model, this critical allosteric wiring is disrupted, forcing mechanical coupling through an unphysiological, hyper-correlated aromatic pathway. These findings yield novel atomistic insights into GLUT4 gating mechanics, while definitively establishing that rigid AI-generated architectures lack the essential internal free volume and conformational plasticity required to sustain accurate thermodynamic profiling of dynamic membrane transporters.

biophysics↗

bioRxiv2025

Genomic selection for accelerated heartwood formation in Pedunculate oak (Quercus robur L.) using whole-genome sequencing

Heartwood traits in trees are critical for timber quality but are notoriously difficult to phenotype due to their late expression and the need for destructive sampling. In this proof-of-concept study, we demonstrate that combining genome-wide association studies (GWAS) with Bayesian genomic prediction models provides an effective strategy to overcome these challenges. By using GWAS to preselect trait associated SNPs and integrating them into predictive models, we substantially improve the accuracy of genomic predictions for heartwood related traits in oaks. Our approach allows for reliable selection of superior genotypes at the seedling stage, long before heartwood traits can be directly measured, thus enabling early and cost-effective breeding decisions. We also identify the number of rings in sapwood as a genetically controlled, easily measured proxy trait that enhances selection strategies for heartwood content. Together, these findings provide a scalable framework for integrating genomics into operational tree breeding programs and demonstrate how combining GWAS and genomic prediction can accelerate the improvement of complex wood traits in long lived forest tree species.

genetics↗

bioRxiv2023

Multiple, single trait GWAS and supervised machine learning reveal the genetic architecture of Fraxinus excelsior tolerance to ash dieback in Europe

Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at epidemic levels throughout Europe. Previous studies have found significant genetic variation among clones in ash dieback susceptibility and that host phenology, such as autumn yellowing, is correlated with susceptibility of ash trees to H. fraxineus; however, the genomic basis of ash dieback tolerance in F. excelsior remains poorly understood. Here, we integrate quantitative genetics and genome-wide association analyses with machine learning to reveal the genetic architecture of ash dieback tolerance and its relationship to phenological traits in F. excelsior populations in six European countries (Austria, Denmark, Germany, Ireland, Lithuania, Sweden). We use whole-genome sequencing of 486 F. excelsior genotypes to confirm the genotypic correlation between crown damage caused by ash dieback and intensity of autumn leaf yellowing within multiple sampling sites. Although, our results suggest that the examined traits are polygenic, a relatively small number of single nucleotide polymorphisms (SNPs) explained a large proportion of the variation in both disease tolerance and autumn leaf yellowing. We could explain up to 63% (based on 9155 unlinked SNPs) of variation in individual response to ash dieback crown damage and up to 72% (based on 3740 unlinked SNPs) of variation in autumn yellowing. We identified eight SNPs encoding non-synonymous substitutions, of which those with the highest predictive power were located within genes related to plant defence (pattern triggered immunity, pathogen detection) and phenology (regulation of flowering and seed maturation, auxin transport). Overall, our results provide insights of a multifaceted defence response, according to which a combination of direct defence mechanisms and phenological avoidance of pathogen spread constitute tolerance to ash dieback.

plant biology↗

bioRxiv2018

Understanding the impact of crosslinked PCL/PEG/GelMA electrospun nanofibers on bactericidal activity

Herein, we report the design of electrospun ultrathin fibers based on polycaprolactone (PCL), polyethylene glycol (PEG), and gelatin methacryloyl (GelMA), and their potential bactericidal activity against three different bacteria Staphylococcus aureus, Pseudomonas aeruginosa, and Methicillin-resistant Staphylococcus aureus (MRSA). We evaluated the morphology, chemical structure and wettability before and after UV photocrosslinking of the produced scaffolds. Results showed that the developed scaffolds presented hydrophilic properties after PEG and GelMA incorporation. Our developed scaffolds were thus able to significantly reduce gram-positive, negative, and MRSA bacteria. Furthermore, we performed a series of study for better mechanistic understanding of the scaffolds bactericidal activity through protein adsorption study and analysis of the reactive oxygen species (ROS) levels. In summary, we have demonstrated the design and generation of electrospun fibers with improved hydrophilicity and efficient bactericidal activity without the association of any antibiotics.

bioengineering↗