An integrated analysis of enzyme activities, cofactor pools and metabolic fluxes in baculovirus-infected Spodoptera frugiperda Sf9 cells

2010 ◽  
Vol 150 (3) ◽  
pp. 332-342 ◽  
Author(s):  
Vicente Bernal ◽  
Francisca Monteiro ◽  
Nuno Carinhas ◽  
Raquel Ambrósio ◽  
Paula M. Alves
Virology ◽  
2013 ◽  
Vol 436 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Yulia V. Lyupina ◽  
Svetlana B. Abaturova ◽  
Pavel A. Erokhov ◽  
Olga V. Orlova ◽  
Svetlana N. Beljelarskaya ◽  
...  

2017 ◽  
Vol 29 (1) ◽  
pp. 171-181 ◽  
Author(s):  
Wenping Xu ◽  
Mingjun Yang ◽  
Jufang Gao ◽  
Yang Zhang ◽  
Liming Tao

2020 ◽  
Vol 211 ◽  
pp. 103573 ◽  
Author(s):  
Gaofeng Cui ◽  
Ranran Sun ◽  
Sethuraman Veeran ◽  
Benshui Shu ◽  
Haiqi Yuan ◽  
...  

2018 ◽  
Vol 20 (4) ◽  
pp. 1590-1603 ◽  
Author(s):  
Gaoyang Li ◽  
Huansheng Cao ◽  
Ying Xu

Abstract We present here an integrated analysis of structures and functions of genome-scale metabolic networks of 17 microorganisms. Our structural analyses of these networks revealed that the node degree of each network, represented as a (simplified) reaction network, follows a power-law distribution, and the clustering coefficient of each network has a positive correlation with the corresponding node degree. Together, these properties imply that each network has exactly one large and densely connected subnetwork or core. Further analyses revealed that each network consists of three functionally distinct subnetworks: (i) a core, consisting of a large number of directed reaction cycles of enzymes for interconversions among intermediate metabolites; (ii) a catabolic module, with a largely layered structure consisting of mostly catabolic enzymes; (iii) an anabolic module with a similar structure consisting of virtually all anabolic genes; and (iv) the three subnetworks cover on average ∼56, ∼31 and ∼13% of a network’s nodes across the 17 networks, respectively. Functional analyses suggest: (1) cellular metabolic fluxes generally go from the catabolic module to the core for substantial interconversions, then the flux directions to anabolic module appear to be determined by input nutrient levels as well as a set of precursors needed for macromolecule syntheses; and (2) enzymes in each subnetwork have characteristic ranges of kinetic parameters, suggesting optimized metabolic and regulatory relationships among the three subnetworks.


2020 ◽  
Vol 171 ◽  
pp. 107340 ◽  
Author(s):  
Supanee Nimsanor ◽  
Monrudee Srisaisup ◽  
Pasin Jammor ◽  
Boonhiang Promdonkoy ◽  
Panadda Boonserm

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