The genetic signature of variability in drug response in Drosophila melanogaster
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ABSTRACT:
PROVIDER: PRJNA497999 | ENA |
REPOSITORIES: ENA
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Project description:Knowledge of the genetic mechanisms underlying among-individual variation in response to environmental variables or treatment is important in many research areas; for example, acquaintance of the set of causal genetic variants for drug responses could revolutionize the field of personalized medicine. We used Drosophila melanogaster to investigate the genetic signature underlying variability in response to methylphenidate (MPH), a drug used in treatment of ADHD. We exposed a wild type D. melanogaster population to MPH or a control treatment and observed an increase in locomotor activity in individuals exposed to MPH. Whole-genome transcriptomic analyses revealed that the behavioral response to MPH was associated with abundant gene expression alterations. To confirm these patterns in a different genetic background, and to further advance knowledge on the genetic signature of drug response variability, we used a system of sequenced inbred lines, the Drosophila Genetic Reference Panel. Utilizing an integrative genomic approach we incorporated the transcriptomic data as well as gene interactions into the genomic analyses, from which we identified putative candidate genes for drug response variability. We successfully validated 70% of the investigated putative candidate genes by gene expression knockdown. Furthermore, we showed that MPH has cross generational behavioral- and transcriptomic effects.
2018-10-24 | GSE121643 | GEO
Project description:LINCS-Drug Toxicity Signature Generation Center
| PRJNA657093 | ENA
Project description:LINCS-Drug Toxicity Signature Generation Center
| PRJNA657092 | ENA
Project description:Therapies targeting signaling molecules mutated in cancers can often have striking short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures. Resistance can sometimes result from a secondary mutations in rare cells, but other times, there is no clear genetic cause, raising leaving the possibility of non-genetic rare cell variability. Here, we show that melanoma cells can display profound transcriptional variability at the single cell level that predicts which cells will ultimately resist drug treatment. This variability involves semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces an epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins withis a progressive process consisting of a loss of SOX10-mediated differentiation followed by activation of new signaling pathways, partially mediated by activity of Jun-AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general rare-cell expression program.
2017-04-13 | GSE97680 | GEO
Project description:Therapies targeting signaling molecules mutated in cancers can often have striking short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures. Resistance can sometimes result from a secondary mutations in rare cells, but other times, there is no clear genetic cause, raising leaving the possibility of non-genetic rare cell variability. Here, we show that melanoma cells can display profound transcriptional variability at the single cell level that predicts which cells will ultimately resist drug treatment. This variability involves semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces an epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins with a progressive process consisting of a loss of SOX10-mediated differentiation followed by activation of new signaling pathways, partially mediated by activity of Jun-AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general rare-cell expression program.
2017-04-13 | GSE97679 | GEO
Project description:Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance
| PRJNA382641 | ENA
Project description:Thermal acclimation study on Drosophila melanogaster reared at 3 different temperatures (12, 25, and 31oC). The proteomic profiles of D. melanogaster under these different temperatures were analyzed and compared using label-free tandem mass spectrometry.
2016-03-15 | PXD003755 | Pride
Project description:Molecular differences between individual cells can lead to dramatic differences in cell fate, such as the difference between death versus survival of cancer cells upon treatment with anti-cancer drugs. Despite some progress, these originating differences have largely remained hidden due to the difficulty in determining precisely what variable molecular features lead to which cellular fates. Here, we trace drug-resistant cell fates back to differences in the molecular profiles of their drug-naive melanoma precursors, revealing a rich substructure of variability underlying a number of resistant phenotypes at the single cell level. We make these connections using Rewind, a methodology that combines genetic barcoding with an RNA-based readout to directly capture rare cells that give rise to cellular behaviors of interest. We performed extensive single cell analysis to identify differences in gene expression and MAP-kinase signaling that mark a rare population of drug-naive cells (initial frequency of ~1:1000-1:10,000 cells) that ultimately gives rise to drug resistant clones. We demonstrate that this rare subpopulation has rich substructure and is composed of several distinct subpopulations, and the molecular differences between these subpopulations predict future differences in phenotypic behavior, such as the ultimate proliferative capacity of drug resistant cells. Similarly, we show that treatments that modify the frequency of resistance can allow otherwise non-resistant cells in the drug-naive population to become resistant, and that these new populations are marked by the variable expression of distinct genes. Together, our results reveal the presence of hidden, rare-cell variability that can underlie a range of latent phenotypic outcomes upon drug exposure.
2020-11-12 | GSE161299 | GEO
Project description:Molecular differences between individual cells can lead to dramatic differences in cell fate, such as the difference between death versus survival of cancer cells upon treatment with anti-cancer drugs. Despite some progress, these originating differences have largely remained hidden due to the difficulty in determining precisely what variable molecular features lead to which cellular fates. Here, we trace drug-resistant cell fates back to differences in the molecular profiles of their drug-naive melanoma precursors, revealing a rich substructure of variability underlying a number of resistant phenotypes at the single cell level. We make these connections using Rewind, a methodology that combines genetic barcoding with an RNA-based readout to directly capture rare cells that give rise to cellular behaviors of interest. We performed extensive single cell analysis to identify differences in gene expression and MAP-kinase signaling that mark a rare population of drug-naive cells (initial frequency of ~1:1000-1:10,000 cells) that ultimately gives rise to drug resistant clones. We demonstrate that this rare subpopulation has rich substructure and is composed of several distinct subpopulations, and the molecular differences between these subpopulations predict future differences in phenotypic behavior, such as the ultimate proliferative capacity of drug resistant cells. Similarly, we show that treatments that modify the frequency of resistance can allow otherwise non-resistant cells in the drug-naive population to become resistant, and that these new populations are marked by the variable expression of distinct genes. Together, our results reveal the presence of hidden, rare-cell variability that can underlie a range of latent phenotypic outcomes upon drug exposure.
2020-11-12 | GSE161298 | GEO
Project description:A deep peptidomics workflow was used to identify alternative proteins in Drosophila melanogaster samples.
2022-01-07 | MSV000088656 | MassIVE