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The triple combination therapy for cystic fibrosis (CF), including elexacaftor, tezacaftor and ivacaftor (ETI or Trikafta), has been shown to improve lung function and reduce pulmonary exacerbations, thereby enhancing the quality of life for most CF patients. Recent findings suggest that both the individual components and ETI may have potential off-target effects, highlighting the need to understand how these modulators impact cellular physiology, particularly in cells that do not express CF transmembrane conductance regulator (CFTR). We used HEK293 cells, as a cell model not expressing the CFTR protein, to evaluate the effect of ETI and each of its components on autophagic machinery and on the Rab5/7 components of the Rab pathway. We firstly demonstrate that the single modulators Teza and Iva, and the combinations ET and ETI, increased ROS production in the absence of their target while decreasing it in cells expressing the CFTR ∆F508del. This increase in cellular stress was followed by an increase in the total level of polyubiquitinated proteins as well as the p62 level and LC3II/LC3I ratio. Furthermore, we found that ETI had the opposite effect on Rabs by increasing Rab5 levels while decreasing Rab7. Interestingly, these changes were abolished by the expression of mutated CFTR. Overall, our data suggest that in the absence of their target, both the individual modulators and ETI increased ROS production and halted both autophagic flux and plasma membrane protein recycling.
The triple combination therapy for cystic fibrosis (CF), including elexacaftor, tezacaftor and ivacaftor (ETI or Trikafta), has been shown to improve lung function and reduce pulmonary exacerbations, thereby enhancing the quality of life for most CF patients. Recent findings suggest that both the individual components and ETI may have potential off-target effects, highlighting the need to understand how these modulators impact cellular physiology, particularly in cells that do not express CF transmembrane conductance regulator (CFTR). We used HEK293 cells, as a cell model not expressing the CFTR protein, to evaluate the effect of ETI and each of its components on autophagic machinery and on the Rab5/7 components of the Rab pathway. We firstly demonstrate that the single modulators Teza and Iva, and the combinations ET and ETI, increased ROS production in the absence of their target while decreasing it in cells expressing the CFTR ∆F508del. This increase in cellular stress was followed by an increase in the total level of polyubiquitinated proteins as well as the p62 level and LC3II/LC3I ratio. Furthermore, we found that ETI had the opposite effect on Rabs by increasing Rab5 levels while decreasing Rab7. Interestingly, these changes were abolished by the expression of mutated CFTR. Overall, our data suggest that in the absence of their target, both the individual modulators and ETI increased ROS production and halted both autophagic flux and plasma membrane protein recycling.
Bioinformatics is a scientific field that uses computer technology to gather, store, analyze, and share biological data and information. DNA sequences of genes or entire genomes, protein amino acid sequences, nucleic acid, and protein–nucleic acid complex structures are examples of traditional bioinformatics data. Moreover, proteomics, the distribution of proteins in cells, interactomics, the patterns of interactions between proteins and nucleic acids, and metabolomics, the types and patterns of small-molecule transformations by the biochemical pathways in cells, are further data streams. Currently, the objectives of bioinformatics are integrative, focusing on how various data combinations might be utilized to comprehend organisms and diseases. Bioinformatic techniques have become popular as novel instruments for examining the fundamental mechanisms behind neonatal diseases. In the first few weeks of newborn life, these methods can be utilized in conjunction with clinical data to identify the most vulnerable neonates and to gain a better understanding of certain mortalities, including respiratory distress, bronchopulmonary dysplasia, sepsis, or inborn errors of metabolism. In the current study, we performed a literature review to summarize the current application of bioinformatics in neonatal medicine. Our aim was to provide evidence that could supply novel insights into the underlying mechanism of neonatal pathophysiology and could be used as an early diagnostic tool in neonatal care.
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