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Inferring stress-activated signaling networks in Saccharomyces cerevisiae reveals complex pathway integration.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Inferring stress-activated signaling networks in Saccharomyces cerevisiae reveals complex pathway integration./
作者:	MacGilvray, Matthew Edward.
面頁冊數:	1 online resource (184 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
標題:	Microbiology. -
電子資源:	click for full text (PQDT)
ISBN:	9780355246674

Inferring stress-activated signaling networks in Saccharomyces cerevisiae reveals complex pathway integration.
MacGilvray, Matthew Edward.

Inferring stress-activated signaling networks in Saccharomyces cerevisiae reveals complex pathway integration. - 1 online resource (184 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. In this thesis, we developed a computational approach to infer the stress-activated signaling network that regulates phosphorylation changes in response to salt stress and the ER stressor dithiothreitol (DTT). The method uses integer linear programming (ILP) to integrate stress-responsive phospho-proteome responses in wild-type and mutant strains, predicted phosphorylation motifs on groups of coregulated peptides, and published protein interaction data. The inferred salt-network predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. Further, kinase inference during DTT suggested new functions for the HOG and PKA pathways in augmenting the unfolded protein response (UPR). Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during diverse stress responses.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355246674Subjects--Topical Terms:

591510
Microbiology.
Index Terms--Genre/Form:

554714
Electronic books.

Inferring stress-activated signaling networks in Saccharomyces cerevisiae reveals complex pathway integration.
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504 $a Includes bibliographical references
520 $a Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. In this thesis, we developed a computational approach to infer the stress-activated signaling network that regulates phosphorylation changes in response to salt stress and the ER stressor dithiothreitol (DTT). The method uses integer linear programming (ILP) to integrate stress-responsive phospho-proteome responses in wild-type and mutant strains, predicted phosphorylation motifs on groups of coregulated peptides, and published protein interaction data. The inferred salt-network predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. Further, kinase inference during DTT suggested new functions for the HOG and PKA pathways in augmenting the unfolded protein response (UPR). Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during diverse stress responses.
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538 $a Mode of access: World Wide Web
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