How Saccharomyces responds to nutrients.
Identifieur interne : 001631 ( Main/Exploration ); précédent : 001630; suivant : 001632How Saccharomyces responds to nutrients.
Auteurs : Shadia Zaman [États-Unis] ; Soyeon Im Lippman ; Xin Zhao ; James R. BroachSource :
- Annual review of genetics [ 0066-4197 ] ; 2008.
Descripteurs français
- KwdFr :
- Acides aminés (métabolisme), Azote (métabolisme), Cyclic AMP-Dependent Protein Kinases (métabolisme), Facteurs de transcription (MeSH), Glucose (métabolisme), Gènes fongiques (MeSH), Modèles biologiques (MeSH), Protein-Serine-Threonine Kinases (métabolisme), Protéines G ras (métabolisme), Protéines de Saccharomyces cerevisiae (métabolisme), Protéines de liaison à l'ADN (MeSH), Protéines de répression (métabolisme), Saccharomyces (croissance et développement), Saccharomyces (cytologie), Saccharomyces (génétique), Saccharomyces (métabolisme), Stress physiologique (MeSH), Transactivateurs (métabolisme), Transcription génétique (MeSH), Transduction du signal (MeSH), Voies et réseaux métaboliques (MeSH).
- MESH :
- croissance et développement : Saccharomyces.
- cytologie : Saccharomyces.
- génétique : Saccharomyces.
- métabolisme : Acides aminés, Azote, Cyclic AMP-Dependent Protein Kinases, Glucose, Protein-Serine-Threonine Kinases, Protéines G ras, Protéines de Saccharomyces cerevisiae, Protéines de répression, Saccharomyces, Transactivateurs.
- Facteurs de transcription, Gènes fongiques, Modèles biologiques, Protéines de liaison à l'ADN, Stress physiologique, Transcription génétique, Transduction du signal, Voies et réseaux métaboliques.
English descriptors
- KwdEn :
- Amino Acids (metabolism), Cyclic AMP-Dependent Protein Kinases (metabolism), DNA-Binding Proteins (MeSH), Genes, Fungal (MeSH), Glucose (metabolism), Metabolic Networks and Pathways (MeSH), Models, Biological (MeSH), Nitrogen (metabolism), Protein-Serine-Threonine Kinases (metabolism), Repressor Proteins (metabolism), Saccharomyces (cytology), Saccharomyces (genetics), Saccharomyces (growth & development), Saccharomyces (metabolism), Saccharomyces cerevisiae Proteins (metabolism), Signal Transduction (MeSH), Stress, Physiological (MeSH), Trans-Activators (metabolism), Transcription Factors (MeSH), Transcription, Genetic (MeSH), ras Proteins (metabolism).
- MESH :
- chemical , metabolism : Amino Acids, Cyclic AMP-Dependent Protein Kinases, Glucose, Nitrogen, Protein-Serine-Threonine Kinases, Repressor Proteins, Saccharomyces cerevisiae Proteins, Trans-Activators, ras Proteins.
- chemical : DNA-Binding Proteins, Transcription Factors.
- cytology : Saccharomyces.
- genetics : Saccharomyces.
- growth & development : Saccharomyces.
- metabolism : Saccharomyces.
- Genes, Fungal, Metabolic Networks and Pathways, Models, Biological, Signal Transduction, Stress, Physiological, Transcription, Genetic.
Abstract
Yeast cells sense the amount and quality of external nutrients through multiple interconnected signaling networks, which allow them to adjust their metabolism, transcriptional profile and developmental program to adapt readily and appropriately to changing nutritional states. We present our current understanding of the nutritional sensing networks yeast cells rely on for perceiving the nutritional landscape, with particular emphasis on those sensitive to carbon and nitrogen sources. We describe the means by which these networks inform the cell's decision among the different developmental programs available to them-growth, quiescence, filamentous development, or meiosis/sporulation. We conclude that the highly interconnected signaling networks provide the cell with a highly nuanced view of the environment and that the cell can interpret that information through a sophisticated calculus to achieve optimum responses to any nutritional condition.
DOI: 10.1146/annurev.genet.41.110306.130206
PubMed: 18303986
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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We present our current understanding of the nutritional sensing networks yeast cells rely on for perceiving the nutritional landscape, with particular emphasis on those sensitive to carbon and nitrogen sources. We describe the means by which these networks inform the cell's decision among the different developmental programs available to them-growth, quiescence, filamentous development, or meiosis/sporulation. We conclude that the highly interconnected signaling networks provide the cell with a highly nuanced view of the environment and that the cell can interpret that information through a sophisticated calculus to achieve optimum responses to any nutritional condition.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">18303986</PMID><DateCompleted><Year>2009</Year><Month>02</Month><Day>05</Day></DateCompleted><DateRevised><Year>2017</Year><Month>11</Month><Day>26</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0066-4197</ISSN><JournalIssue CitedMedium="Print"><Volume>42</Volume><PubDate><Year>2008</Year></PubDate></JournalIssue><Title>Annual review of genetics</Title><ISOAbbreviation>Annu Rev Genet</ISOAbbreviation></Journal><ArticleTitle>How Saccharomyces responds to nutrients.</ArticleTitle><Pagination><MedlinePgn>27-81</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1146/annurev.genet.41.110306.130206</ELocationID><Abstract><AbstractText>Yeast cells sense the amount and quality of external nutrients through multiple interconnected signaling networks, which allow them to adjust their metabolism, transcriptional profile and developmental program to adapt readily and appropriately to changing nutritional states. We present our current understanding of the nutritional sensing networks yeast cells rely on for perceiving the nutritional landscape, with particular emphasis on those sensitive to carbon and nitrogen sources. We describe the means by which these networks inform the cell's decision among the different developmental programs available to them-growth, quiescence, filamentous development, or meiosis/sporulation. We conclude that the highly interconnected signaling networks provide the cell with a highly nuanced view of the environment and that the cell can interpret that information through a sophisticated calculus to achieve optimum responses to any nutritional condition.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zaman</LastName><ForeName>Shadia</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lippman</LastName><ForeName>Soyeon Im</ForeName><Initials>SI</Initials></Author><Author ValidYN="Y"><LastName>Zhao</LastName><ForeName>Xin</ForeName><Initials>X</Initials></Author><Author ValidYN="Y"><LastName>Broach</LastName><ForeName>James R</ForeName><Initials>JR</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>R01 GM076562</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Annu Rev Genet</MedlineTA><NlmUniqueID>0117605</NlmUniqueID><ISSNLinking>0066-4197</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D000596">Amino Acids</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D004268">DNA-Binding Proteins</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="C102114">RGT1 protein, S cerevisiae</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D012097">Repressor 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MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012440" MajorTopicYN="N">Saccharomyces</DescriptorName><QualifierName UI="Q000166" MajorTopicYN="N">cytology</QualifierName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000254" MajorTopicYN="N">growth & development</QualifierName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D029701" MajorTopicYN="N">Saccharomyces cerevisiae Proteins</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015398" MajorTopicYN="N">Signal Transduction</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013312" MajorTopicYN="N">Stress, Physiological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015534" MajorTopicYN="N">Trans-Activators</DescriptorName><QualifierName UI="Q000378" 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PubStatus="entrez"><Year>2008</Year><Month>2</Month><Day>29</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">18303986</ArticleId><ArticleId IdType="doi">10.1146/annurev.genet.41.110306.130206</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>New Jersey</li></region><settlement><li>Princeton (New Jersey)</li></settlement><orgName><li>Université de Princeton</li></orgName></list><tree><noCountry><name sortKey="Broach, James R" sort="Broach, James R" uniqKey="Broach J" first="James R" last="Broach">James R. Broach</name><name sortKey="Lippman, Soyeon Im" sort="Lippman, Soyeon Im" uniqKey="Lippman S" first="Soyeon Im" last="Lippman">Soyeon Im Lippman</name><name sortKey="Zhao, Xin" sort="Zhao, Xin" uniqKey="Zhao X" first="Xin" last="Zhao">Xin Zhao</name></noCountry><country name="États-Unis"><region name="New Jersey"><name sortKey="Zaman, Shadia" sort="Zaman, Shadia" uniqKey="Zaman S" first="Shadia" last="Zaman">Shadia Zaman</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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