Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth.

Autor: Colton J Lloyd, Jonathan Monk, Laurence Yang, Ali Ebrahim, Bernhard O Palsson

Publikováno v: PLoS Computational Biology, Vol 17, Iss 6, p e1007817 (2021)

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allo

Externí odkaz: https://doaj.org/article/db47ee9d62014445834e690cd817d41c

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data.

Autor: Jean-Christophe Lachance, Colton J Lloyd, Jonathan M Monk, Laurence Yang, Anand V Sastry, Yara Seif, Bernhard O Palsson, Sébastien Rodrigue, Adam M Feist, Zachary A King, Pierre-Étienne Jacques

Publikováno v: PLoS Computational Biology, Vol 15, Iss 4, p e1006971 (2019)

Genome-scale metabolic models (GEMs) are mathematically structured knowledge bases of metabolism that provide phenotypic predictions from genomic information. GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass ob

Externí odkaz: https://doaj.org/article/1a370b2fe7874bbdbe6b6fc1d0f8fbb2

COBRAme: A computational framework for genome-scale models of metabolism and gene expression.

Autor: Colton J Lloyd, Ali Ebrahim, Laurence Yang, Zachary A King, Edward Catoiu, Edward J O'Brien, Joanne K Liu, Bernhard O Palsson

Publikováno v: PLoS Computational Biology, Vol 14, Iss 7, p e1006302 (2018)

Genome-scale models of metabolism and macromolecular expression (ME-models) explicitly compute the optimal proteome composition of a growing cell. ME-models expand upon the well-established genome-scale models of metabolism (M-models), and they enabl

Externí odkaz: https://doaj.org/article/533a1c804675454ba81e419452b929d3

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers

Autor: Marvic Carrillo-Terrazas, Patrick V. Phaneuf, Ying Hefner, David Heckmann, Anaamika Campeau, David Gonzalez, Bernhard O. Palsson, Adam M. Feist, Colton J. Lloyd

Publikováno v: Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America, vol 117, iss 37
Heckmann, D, Campeau, A, Lloyd, C J, Phaneuf, P V, Hefner, Y, Carrillo-Terrazas, M, Feist, A M, Gonzalez, D J & Palsson, B O 2020, ' Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers ', Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 37, pp. 23182-23190 . https://doi.org/10.1073/pnas.2001562117

Significance Enzyme kinetic parameters are crucial for a quantitative understanding of metabolism, but traditionally have to be measured in laborious low-throughput assays. To solve this problem, the enzyme turnover number, kcat, can be estimated in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9665f237f67f515443f113fe1b070aa9
http://europepmc.org/articles/PMC7502767

Cellular responses to reactive oxygen species are predicted from molecular mechanisms

Autor: Troy E. Sandberg, Ying Hefner, David Heckmann, Ye Gao, Jonathan M. Monk, Adam M. Feist, Bernhard O. Palsson, Justin Tan, Laurence Yang, Donghyuk Kim, Colton J. Lloyd, Ke Chen, Sang Woo Seo, James T. Yurkovich, Richard Szubin, Joon Ho Park, Patrick V. Phaneuf, Amitesh Anand, Jared T. Broddrick, Anand V. Sastry, Nathan Mih

Publikováno v: Proceedings of the National Academy of Sciences of the United States of America, vol 116, iss 28
Yang, L, Mih, N, Anand, A, Park, J H, Tan, J, Yurkovich, J T, Monk, J M, Lloyd, C J, Sandberg, T E, Seo, S W, Kim, D, Sastry, A V, Phaneuf, P, Gao, Y, Broddrick, J T, Chen, K, Heckmann, D, Szubin, R, Hefner, Y, Feist, A M & Palsson, B O 2019, ' Cellular responses to reactive oxygen species are predicted from molecular mechanisms ', Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 28, pp. 14368-14373 . https://doi.org/10.1073/pnas.1905039116

Catalysis using iron–sulfur clusters and transition metals can be traced back to the last universal common ancestor. The damage to metalloproteins caused by reactive oxygen species (ROS) can prevent cell growth and survival when unmanaged, thus eli

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::308315ec685ded5028db7ea5b64fd540
https://doi.org/10.1073/pnas.1905039116