Biology subjects

Fukutani, K. F.

Publications and source records attributed to Fukutani, K. F..

4 recordsLinked to original sources

bioRxiv2024

Gene expression responses of CF airway epithelial cells exposed to elexacaftor/tezacaftor/ivacaftor (ETI) suggest benefits beyond improved CFTR channel function

The combination of elexacaftor/tezacaftor/ivacaftor (ETI, Trikafta) reverses the primary defect in Cystic Fibrosis (CF) by improving CFTR mediated Cl- and HCO3- secretion by airway epithelial cells (AEC), leading to improved lung function and less frequent exacerbations and hospitalizations. However, studies have shown that CFTR modulators like ivacaftor, a component of ETI, has numerous effects on CF cells beyond improved CFTR channel function. Because little is known about the effect of ETI on CF AEC gene expression we exposed primary human AEC to ETI for 48 hours and interrogated the transcriptome by RNA-seq and qPCR. ETI increased defensin gene expression (DEFB1) an observation consistent with reports of decreased bacterial burden in the lungs of people with CF (pwCF). ETI also decreased MMP10 and MMP12 gene expression, suggesting that ETI may reduce proteolytic induced lung destruction in CF. ETI also reduced the expression of the stress response gene heme oxygenase (HMOX1). qPCR analysis confirmed DEFB1, HMOX1, MMP10 and MMP12 gene expression results observed by RNA-seq. Gene pathway analysis revealed that ETI decreased inflammatory signaling, cellular proliferation and MHC Class II antigen presentation. Collectively, these findings suggest that the clinical observation that ETI reduces lung infections in pwCF is related in part to drug induced increases in DEFB1, and that ETI may reduce lung damage by reducing MMP10 and MMP12 gene expression, which is predicted to reduce matrix metalloprotease activity. Moreover, pathway analysis also identified several genes responsible for the ETI induced reduction in inflammation observed in people with CF. New and NoteworthyGene expression responses by CF AEC exposed to ETI suggest that in addition to improving CFTR channel function, ETI is likely to increase resistance to bacterial infection by increasing levels of beta defensin 1 (hBD-1). ETI may also reduce lung damage by suppressing MMP10, and reduce airway inflammation by repressing proinflammatory cytokine secretion by AEC cells.

pharmacology and toxicology↗

bioRxiv2024

E.PathDash, pathway activation analysis of public cystic fibrosis pathogen gene expression data

E.PathDash facilitates re-analysis of gene expression data from pathogens clinically relevant to chronic respiratory diseases, including a total of 48 studies, 548 samples, and 404 unique treatment comparisons. The application enables users to assess broad biological stress responses at the KEGG pathway or Gene Ontology level and also provides data for individual genes. E.PathDash reduces the time required to gain access to data from multiple hours per dataset to seconds. Users can download high quality images such as volcano plots and boxplots, differential gene expression results and raw count data, making it fully interoperable with other tools. Importantly, users can rapidly toggle between experimental comparisons and different studies of the same phenomenon, enabling them to judge the extent to which observed responses are reproducible. As a proof of principle, we invited two cystic fibrosis scientists to use the application to explore scientific questions relevant to their specific research areas. Reassuringly, pathway activation analysis recapitulated results reported in original publications, but it also yielded new insights into pathogen responses to changes in their environments, validating the utility of the application. All software and data are freely accessible and the application is available at scangeo.dartmouth.edu/EPathDash. ImportanceChronic respiratory illnesses impose a high disease burden on our communities and people with respiratory diseases are susceptible to robust bacterial infections from pathogens, including Pseudomonas aeruginosa and Staphylococcus aureus, that contribute to morbidity and mortality. Public gene expression datasets generated from these and other pathogens are abundantly available and an important resource for synthesizing existing pathogenic research, leading to interventions that improve patient outcomes. However, it can take many hours or weeks to render publicly available datasets usable; significant time and skills are needed to clean, standardize, and apply reproducible and robust bioinformatic pipelines to the data. Through collaboration with two microbiologists we have shown that E.PathDash addresses this problem, enabling them to elucidate pathogen responses to a variety of over 400 experimental conditions and generate mechanistic hypotheses for cell-level behavior in response to disease-relevant exposures, all in a fraction of the time.

bioinformatics↗

bioRxiv2020

Aging increases the systemic molecular degree of inflammatory perturbation in patients with tuberculosis

Tuberculosis (TB) in a chronic infection that can affect individuals of all ages. The description of determinants of immunopathogenesis in TB is a field of tremendous interest due to the perspective of finding a reliable host-directed therapy to reduce disease burden. The association between specific biomarker profiles related to inflammation and the diverse clinical disease presentations in TB has been extensively studied in adults. However, relatively scarce data on profiling the inflammatory responses in pediatric TB are available. Here, we employed the molecular degree of perturbation (MDP) score adapted to plasma biomarkers in two distinct databanks from studies that examined either adults or children presenting with pulmonary or extrapulmonary disease. We used multidimensional statistical analyses to characterize the impact of age on the overall changes in the systemic inflammation profiles in subpopulation of TB patients. Our findings indicated that TB results in significant increases in MDP values, with the highest values being detected in adult patients. Furthermore, there were unique differences in the biomarker perturbation patterns and the overall degree of inflammation according to disease site and age. Importantly, the molecular degree of perturbation was not influenced by sex. Our results revealed that aging is an important determinant of the differences in quality and magnitude of systemic inflammatory perturbation in distinct clinical forms of TB.

immunology↗

bioRxiv2019

Systems biology analysis of publicly available transcriptomic data reveals a critical link between AKR1B10 gene expression, smoking and occurrence of lung cancer

BackgroundCigarette smoking is associated with increased risk of developing respiratory diseases and various types of cancer. Early identification of such unfavorable outcomes in patients who smoke is critical for optimizing personalized medical care.\n\nMethodsHere, we perform a comprehensive analysis using Systems Biology tools of publicly available data from a total of six transcriptomic studies, which examined different specimens of lung tissue and/or cells of smokers and nonsmokers to identify potential markers associated with lung cancer.\n\nResultsExpression level of twenty-two genes was capable of classifying smokers from non-smokers. A machine learning algorithm revealed that AKR1B10 was the most informative gene among the 22 DEGs accounting for the classification of the clinical groups. AKR1B10 expression was higher in smokers compared to non-smokers in datasets examining small and large airway epithelia, but not in the data from a study of sorted alveolar macrophages. We next tested whether AKR1B10 expression could be useful in identification of cancer tissue in patients who were not exposed to smoking. AKR1B10 expression was substantially higher in lung cancer specimens compared to matched healthy tissue obtained from nonsmoking individuals (accuracy: 80%, p<0.0001). Finally, we searched the expression of 11 single nucleotide polymorphisms (SNPs) of AKR1B10 worldwide. We found that the SNP rs782881 was the most frequent mutant allele in the majority of continents. Africa was the continent which exhibited higher frequency of SNPs associated with lower AKR1B10 expression and displayed lower lung cancer incidence and deaths attributable to tobacco.\n\nConclusionThe systematic analysis of transcriptomic studies performed here revealed a potential critical link between AKR1B10 expression, smoking and occurrence of lung cancer.

genomics↗