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Ferrada, E.

Publications and source records attributed to Ferrada, E..

3 recordsLinked to original sources

Intra-host IRES heterogeneity shapes hepatitis C virus translation through epistatic and population-level effects

Hepatitis C virus (HCV) circulates within each patient as a diverse population of closely related genomes, yet RNA functional properties are commonly inferred from a single consensus or dominant genome. The contribution of non-coding intra-host variability, particularly within the internal ribosome entry site (IRES), to translational efficiency remains poorly defined. Here we investigated how naturally occurring HCV IRES variation influences viral RNA translation. Complete IRES sequences from chronically infected patients were analyzed using molecular cloning, bicistronic reporters, full-length replication-deficient viral RNAs and reconstructed intra-host populations. We found that natural IRES mutations displayed context-dependent effects, and combinations of mutations produced translational phenotypes that could not be predicted from the corresponding single mutations, consistent with intragenic epistasis. Moreover, several variants behaved differently in bicistronic reporters and full-length viral RNAs, demonstrating that both genomic and cellular context shape IRES function. Reconstructed genotype 1a populations largely reproduced the activity of their dominant haplotypes. In contrast, reconstructed genotype 3a populations translated substantially more efficiently than their corresponding dominant sequences, showing that low-frequency variants can collectively modulate translation at the population level. These findings demonstrate that the translational phenotype of HCV cannot always be inferred from the dominant sequence alone and identify epistasis, genomic context, and intra-host population composition as interacting determinants of viral RNA translation. ImportanceHepatitis C virus (HCV) exists within each infected person as a diverse population of closely related viruses rather than as a single genetic sequence. This study shows that natural variation in a key RNA region controlling viral protein production can alter how efficiently the virus functions, and that these effects depend on combinations of mutations rather than on individual changes alone. By analyzing complete viral RNAs in addition to widely used reporter systems, we demonstrate that the full viral genome can substantially influence the activity of this regulatory region, providing a more realistic view of how translation occurs during natural infection. Our findings also reveal that rare viral variants can collectively shape the behavior of the viral population, challenging the common practice of relying on a single dominant sequence to represent an infection. These results provide new insight into how genetic diversity drives HCV evolution and adaptation.

molecular biology↗

The topology of transmembrane protein-protein interaction interfaces is encoded in their physicochemical features

Transmembrane (TM) protein-protein interactions (PPIs) are essential mediators of signal transduction, transport of solutes and communication, yet the biophysical features that characterize their diverse topologies remain poorly understood. To reduce this knowledge gap we use the human solute carrier (SLC) interactome to study whether physicochemical features of PPI interfaces encode information about their TM topology (i.e., their position and arrangement with respect to the membrane). To this end we predicted structures for 2, 055 experimentally validated PPIs using AlphaFold v3.0, performed molecular dynamics simulations and annotated the PPI interfaces by TM coverage. As a result every interface is characterized by 63 physicochemical, structural and energy features. A reproducible machine learning workflow allows us to study the interdependence between these interface properties and interface topology. We found that amino acid composition and secondary structure contributed most to distinguishing soluble from fully membrane-embedded interfaces. Membrane-embedded interfaces contained a larger fraction of hydrophobic residues and -helices, while charged residues were depleted. For partially and full membrane-embedded interfaces, amino acid composition and secondary structure get more similar and differences are increasingly observed in charge and energy related features. As particularly noteworthy we find that PPI interface characteristics vary with the number of annotated TM segments mainly through differences in proportions of secondary structure, charge, and flexibility. We hence conclude that PPI interface characteristics harbor substantial information about TM interface topology and provide a framework for the study and design of membrane protein interaction interfaces.

bioinformatics↗

Data- and knowledge-derived functional landscape of human solute carriers

Research on the understudied solute carrier (SLC) superfamily of membrane transporters would greatly profit from a comprehensive knowledgebase, synthesizing data and knowledge on different aspects of SLC function. We consolidated multi-omics data sets with selected curated information from the public domain, such as structure prediction, substrate annotation, disease association and subcellular localization. This SLC-centric knowledge is made accessible to the scientific community via a web portal, featuring interactive dashboards and a tool for family-wide, tree-based visualization of SLC properties. Making use of the systematically collected and curated data sets, we selected eight feature-dimensions to compute an integrated functional landscape of human SLCs. This landscape represents various functional aspects, harmonizing local and global features of the underlying data sets, as demonstrated by inspecting structural folds and subcellular locations of selected transporters. Based on all available data sets and their integration, we assigned a biochemical/biological function to each SLC, making it one of the largest systematic annotations of human gene function and likely acting as a blueprint for future endeavours.

systems biology↗