Biology subjects

Diez Benavente, E.

Publications and source records attributed to Diez Benavente, E..

4 recordsLinked to original sources

bioRxiv2026

Sex-Specific Regulation of Endothelial-to-Mesenchymal Transition (EndMT) During Atherosclerosis

Sex differences in atherosclerotic plaque biology underlie clinically distinct manifestations of acute coronary syndromes, yet the molecular mechanisms driving these differences remain incompletely understood. Endothelial-to-mesenchymal transition (EndMT) is increasingly recognized as a contributor to plaque remodeling, but whether EndMT is regulated in a sex-specific and stage-dependent manner across atherosclerosis has not been systematically examined. Here, we integrated bulk RNA sequencing with single-cell transcriptomic analyses in endothelial cells and human atherosclerotic plaques to define sex-specific EndMT regulation across healthy and advanced-stage disease. Using trajectory analyses in endothelial cells undergoing EndMT, we observed pronounced sex-specific regulation in healthy endothelium, with females exhibiting stronger early EndMT activation, whereas endothelial cells derived from atherosclerotic plaques displayed markedly attenuated sex differences with disease progression. Consistent sex-divergent pseudotime trajectories were observed in human carotid plaque endothelial single-cell RNA-seq data, with females showing greater EndMT activation at earlier stages and males at later stages. Together, these findings support a stage-dependent model of sex-specific EndMT regulation, indicating that the functional consequences of EndMT are highly context dependent and may differ across early and late disease stages. Integration of these datasets prioritized high-confidence sex-specific EndMT regulators, including COL4A1, PECAM1, CD151, JAG1, FN1, NEDD9, PODXL, MAFB, PROCR, and CDH13, providing a mechanistic framework to explain clinically observed sex differences in plaque biology and to guide targeted functional interrogation.

genomics↗

bioRxiv2024

Genomic epidemiology of Plasmodium knowlesi reveals putative genetic drivers of adaptation in Malaysia.

Sabah, Malaysia, has amongst the highest burden of human Plasmodium knowlesi infection in the country, associated with increasing encroachment on the parasites macaque host habitat. However, the genomic make-up of P. knowlesi in Sabah was previously poorly understood. To inform on local patterns of transmission and putative adaptive drivers, we conduct population-level genetic analyses of P. knowlesi human infections using 52 new whole genomes from Sabah, Malaysia, in combination with publicly available data. We identify the emergence of distinct geographical subpopulations within the macaque-associated clusters using IBD-based connectivity analysis. Secondly, we report on introgression events between the clusters, which may be linked to differentiation of the subpopulations, and that overlap genes critical for survival in human and mosquito hosts. Using village-level locations from P. knowlesi infections, we also identify associations between several introgressed regions and both intact forest perimeter-area ratio and mosquito vector habitat suitability. Our findings provide further evidence of the complex role of changing ecosystems and sympatric macaque hosts in Malaysia driving distinct genetic changes seen in P. knowlesi populations. Future expanded analyses of evolving P. knowlesi genetics and environmental drivers of transmission will be important to guide public health surveillance and control strategies. Author SummaryThe zoonotic P. knowlesi parasite is an emerging, yet understudied, cause of malaria in Southeast Asia. Sabah, Malaysia, has amongst the highest burden of human P. knowlesi infection in the country, however, the region is currently understudied. Thus, we produced a collection of high-quality P. knowlesi genomes from Sabah, and in combination with publicly available data, performed an extensive population genetics analysis. Our work contributes novel insights for Plasmodium knowlesi population genetics and genetic epidemiology.

genomics↗

bioRxiv2019

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a one-stop test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.\n\nMethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ( participants) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.\n\nResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.\n\nConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

microbiology↗

bioRxiv2019

Rapid and iterative genome editing in the zoonotic malaria parasite Plasmodium knowlesi: New tools for P. vivax research

Tackling relapsing Plasmodium vivax and zoonotic Plasmodium knowlesi infections is critical to reducing malaria incidence and mortality worldwide. Understanding the biology of these important and related parasites was previously constrained by the lack of robust molecular and genetic approaches. Here, we establish CRISPR-Cas9 genome editing in a culture-adapted P. knowlesi strain and define parameters for optimal homology-driven repair. We establish a scalable protocol for the production of repair templates by PCR and demonstrate the flexibility of the system by tagging proteins with distinct cellular localisations. Using iterative rounds of genome-editing we generate a transgenic line expressing P. vivax Duffy binding protein (PvDBP), a lead vaccine candidate. We demonstrate that PvDBP plays no role in reticulocyte restriction but can alter the macaque/human host cell tropism of P. knowlesi. Critically, antibodies raised against the P. vivax antigen potently inhibit proliferation of this strain, providing an invaluable tool to support vaccine development.

microbiology↗