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Deep Interrogation of Metabolism Using a Pathway-Targeted Click-Chemistry Approach.
Hoki, Jason S; Le, Henry H; Mellott, Karlie E; Zhang, Ying K; Fox, Bennett W; Rodrigues, Pedro R; Yu, Yan; Helf, Maximilian J; Baccile, Joshua A; Schroeder, Frank C.
Afiliação
  • Hoki JS; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Le HH; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Mellott KE; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Zhang YK; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Fox BW; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Rodrigues PR; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Yu Y; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Helf MJ; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
  • Baccile JA; Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37996, United States.
  • Schroeder FC; Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.
J Am Chem Soc ; 142(43): 18449-18459, 2020 10 28.
Article em En | MEDLINE | ID: mdl-33053303
Untargeted metabolomics indicates that the number of unidentified small-molecule metabolites may exceed the number of protein-coding genes for many organisms, including humans, by orders of magnitude. Uncovering the underlying metabolic networks is essential for elucidating the physiological and ecological significance of these biogenic small molecules. Here we develop a click-chemistry-based enrichment strategy, DIMEN (deep interrogation of metabolism via enrichment), that we apply to investigate metabolism of the ascarosides, a family of signaling molecules in the model organism C. elegans. Using a single alkyne-modified metabolite and a solid-phase azide resin that installs a diagnostic moiety for MS/MS-based identification, DIMEN uncovered several hundred novel compounds originating from diverse biosynthetic transformations that reveal unexpected intersection with amino acid, carbohydrate, and energy metabolism. Many of the newly discovered transformations could not be identified or detected by conventional LC-MS analyses without enrichment, demonstrating the utility of DIMEN for deeply probing biochemical networks that generate extensive yet uncharacterized structure space.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sondas Moleculares / Caenorhabditis elegans / Metaboloma Limite: Animals Idioma: En Revista: J Am Chem Soc Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sondas Moleculares / Caenorhabditis elegans / Metaboloma Limite: Animals Idioma: En Revista: J Am Chem Soc Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos