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Cell Death and Differentiation
Article . 2007 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Proteomic analysis of steroid-triggered autophagic programmed cell death during Drosophila development

Authors: D N, Martin; B, Balgley; S, Dutta; J, Chen; P, Rudnick; J, Cranford; S, Kantartzis; +3 Authors

Proteomic analysis of steroid-triggered autophagic programmed cell death during Drosophila development

Abstract

Two morphological forms of programmed cell death, apoptosis and autophagic cell death, remove unneeded or damaged cells during animal development. Although the mechanisms that regulate apoptosis are well studied, little is known about autophagic cell death. A shotgun proteome analysis of purified dying larval salivary glands in Drosophila was used to identify proteins that are expressed during autophagic programmed cell death. A total of 5661 proteins were identified from stages before and after the onset of cell death. Analyses of these data enabled us to identify proteins from a number of interesting categories including regulators of transcription, the apoptosis, autophagy, lysosomal, and ubiquitin proteasome degradation pathways, and proteins involved in growth control. Several of the identified proteins, including the serine/threonine kinase warts (Wts), were not detected using whole-genome DNA microarrays, providing support for the importance of such high-throughput proteomic technology. Wts regulates cell-cycle arrest and apoptosis, and significantly, mutations in wts prevent destruction of salivary glands.

Keywords

Proteomics, Proteome, Intracellular Signaling Peptides and Proteins, Protein Serine-Threonine Kinases, Salivary Glands, Drosophila melanogaster, Autophagy, Animals, Drosophila Proteins, Intercellular Signaling Peptides and Proteins, Steroids, Lysosomes, Protein Kinases

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    37
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Top 10%
bronze