Biology subjects

R

Publications and source records attributed to R.

4 recordsLinked to original sources

bioRxiv2025

Estimating the replicability of Brazilian biomedical science

Concerns over the replicability and reproducibility of published research have grown in many research fields, but empirical data to inform policies are still scarce. Biomedical research in Brazil expanded rapidly over the last three decades, with no systematic assessment of the replicability of its findings. With this in mind, we set up the Brazilian Reproducibility Initiative, a multicenter replication of published experiments from Brazilian science using three common experimental methods: the MTT assay, the reverse transcription polymerase chain reaction (RT-PCR) and the elevated plus maze (EPM). A total of 56 laboratories performed 143 replications of 56 experiments; of these, 90 replications of 45 experiments were considered valid by an independent committee. Replication rates for these experiments varied between 20 and 44% according to five predefined criteria. In median terms, ratios between group means were 58% lower in replications than in original experiments, while coefficients of variation were 82% higher. Effect size decrease was smaller for MTT experiments, original results with less variability and those considered more challenging to replicate, while t values for replications were positively correlated with researcher predictions about replicability, and negatively correlated with the rate of publications by the original articles last author. Deviations from preregistered protocols were very common in replications, most frequently due to reasons inherent to the experimental model or related to infrastructure and logistics. Our results highlight factors that limit the replicability of results published by researchers in Brazil and suggest ways by which this scenario can be improved.

scientific communication and education↗

bioRxiv2024

Evaluation of enzyme activity predictions for variants of unknown significance in Arylsulfatase A

Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfa-tase A (ARSA) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning tools in Python, demonstrated superior performance among sub-missions. Furthermore, the study observed that state-of-the-art deep learning methods provided small but statistically significant improvement in predictive performance compared to less elaborate techniques. These findings underscore the utility of variant effect prediction, and the potential for models trained with modest resources to accurately classify VUS in genetic and clinical research.

genetics↗

bioRxiv2023

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors of a wide-range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed DrugMap, an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF{kappa}B1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF{kappa}B1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription factor activity.

systems biology↗

bioRxiv2017

Genome sequencing reveals Zika virus diversity and spread in the Americas

Despite great attention given to the recent Zika virus (ZIKV) epidemic in the Americas, much remains unknown about its epidemiology and evolution, in part due to a lack of genomic data. We applied multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analyzed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental US. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of viral surveillance. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those potentially relevant to the effectiveness of diagnostic tests.

genomics↗