Ontology highlight
ABSTRACT:
PROVIDER: PRJNA722614 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14264086.fastq.gz | Fastqsanger.gz | |||
| SRR14264087.fastq.gz | Fastqsanger.gz | |||
| SRR14264088.fastq.gz | Fastqsanger.gz | |||
| SRR14264788_1.fastq.gz | Fastqsanger.gz | |||
| SRR14264788_2.fastq.gz | Fastqsanger.gz |
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Project description:Glucocorticoids are extensively used to treat inflammatory diseases, however their chronic intake increases the risk of mycobacterial infections. Meanwhile, the effects of glucocorticoids on innate host responses are incompletely understood. Here, we studied the direct effects of glucocorticoids on antimycobacterial host defense in primary human macrophages. We found that glucocorticoids triggered the expression of cathelicidin, an antimicrobial critical for antimycobacterial response, independent of the intracellular vitamin D metabolism. Despite upregulating cathelicidin, glucocorticoids failed to promote macrophage antimycobacterial activity. Gene expression profiles of human macrophages treated with glucocorticoids and/or IFN-gamma, which promotes induction of cathelicidin, as well as antimycobacterial activity, were investigated. Using weighted gene coexpression network analysis (WGCNA), we identified a module of highly connected genes that was strongly inversely correlated with glucocorticoid treatment and associated with IFN-gamma stimulation. This module was linked to the biological functions “autophagy”, “phagosome maturation” and “lytic vacuole/lysosome”, and contained the vacuolar H+-ATPase (v-ATPase) subunit a3, alias TCIRG1, a known antimycobacterial host defense gene, as a top hub gene. We next found that glucocorticoids, in contrast to IFN-gamma, failed to trigger expression and phagolysosome recruitment of TCIRG1, as well as to promote lysosome acidification. Finally, we demonstrated that the tyrosine kinase inhibitor imatinib induces lysosome acidification and antimicrobial activity in glucocorticoid-treated macrophages without reversing the anti-inflammatory effects of glucocorticoids. Taken together, we provide evidence that the induction of cathelicidin by glucocorticoids is not sufficient for macrophage antimicrobial activity, and identify the v-ATPase as a potential target for host-directed therapy in the context of glucocorticoid therapy.
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Project description:Identifying the mode of action (MOA) of antibacterial compounds is the fundamental basis for the development of new antibiotics, and the challenge increases with the emerging secondary and indirect effect from antibiotic stress. Although various omics-based system biology approaches of defining antibiotic MOA are currently available, they still need improved throughput, accuracy and comprehensiveness. Using high resolution accurate mass (HR/AM) based proteomics, we present here a comprehensive reference map of proteomic signatures of Escherichia coli under antibiotics challenge. With state-of-the-art label-free approach, we quantified > 1,500 protein groups in response to 19 FDA-approved antibiotics. Applying several machine learning techniques, we derived a panel of 14 proteins that can be used to classify antibiotics into different MOAs with nearly 100% accuracy. Interestingly, these proteins tend to mediate diverse bacterial cellular and metabolic processes. Transcriptomic level profiling correlates well with changes in protein expression in discriminating different antibiotics. Such expression signatures will aid future studies in identifying MOA of unknown compounds and facilitate the discovery of novel antibiotics. In summary, our study offers a practical approach for effective and rapid proteomic profiling, establishes a high quality reference compendium of microbial proteome in response to a wide range of antibiotics exposure, and provides a previously undescribed group of proteins and RNAs that allows rapid antibiotic classification and MOA determination.
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