CHO cell productivity improvement by genome-scale modeling and pathway analysis: Application to feed supplements

2020 ◽  
Vol 160 ◽  
pp. 107638 ◽  
Author(s):  
Zhuangrong Huang ◽  
Jianlin Xu ◽  
Andrew Yongky ◽  
Caitlin S. Morris ◽  
Ashli L. Polanco ◽  
...  
2020 ◽  
Vol 25 (6) ◽  
pp. 931-943
Author(s):  
Sanjeev Dahal ◽  
Jiao Zhao ◽  
Laurence Yang
Keyword(s):  

2016 ◽  
pp. 111-123 ◽  
Author(s):  
Jürgen Zanghellini ◽  
Matthias P. Gerstl ◽  
Michael Hanscho ◽  
Govind Nair ◽  
Georg Regensburger ◽  
...  

2016 ◽  
Vol 2 (3) ◽  
pp. 39-42 ◽  
Author(s):  
Zhaobin Xu ◽  
Nicholas Ribaudo ◽  
Xianhua Li ◽  
Thomas K. Wood ◽  
Zuyi Huang

2012 ◽  
Vol 60 ◽  
pp. 1-8 ◽  
Author(s):  
Silvana Becerra ◽  
Julio Berrios ◽  
Nelson Osses ◽  
Claudia Altamirano

Metabolites ◽  
2015 ◽  
Vol 5 (4) ◽  
pp. 536-570 ◽  
Author(s):  
Ratul Chowdhury ◽  
Anupam Chowdhury ◽  
Costas Maranas

2019 ◽  
Vol 21 (6) ◽  
pp. 1875-1885
Author(s):  
Ehsan Ullah ◽  
Mona Yosafshahi ◽  
Soha Hassoun

Abstract While elementary flux mode (EFM) analysis is now recognized as a cornerstone computational technique for cellular pathway analysis and engineering, EFM application to genome-scale models remains computationally prohibitive. This article provides a review of aspects of EFM computation that elucidates bottlenecks in scaling EFM computation. First, algorithms for computing EFMs are reviewed. Next, the impact of redundant constraints, sensitivity to constraint ordering and network compression are evaluated. Then, the advantages and limitations of recent parallelization and GPU-based efforts are highlighted. The article then reviews alternative pathway analysis approaches that aim to reduce the EFM solution space. Despite advances in EFM computation, our review concludes that continued scaling of EFM computation is necessary to apply EFM to genome-scale models. Further, our review concludes that pathway analysis methods that target specific pathway properties can provide powerful alternatives to EFM analysis.


2020 ◽  
Vol 20 (5) ◽  
Author(s):  
Zhiqiang Wen ◽  
Sufang Zhang ◽  
Chuks Kenneth Odoh ◽  
Mingjie Jin ◽  
Zongbao K Zhao

ABSTRACT The red yeast Rhodosporidium toruloides naturally produces microbial lipids and carotenoids. In the past decade or so, many studies demonstrated R. toruloides as a promising platform for lipid production owing to its diverse substrate appetites, robust stress resistance and other favorable features. Also, significant progresses have been made in genome sequencing, multi-omic analysis and genome-scale modeling, thus illuminating the molecular basis behind its physiology, metabolism and response to environmental stresses. At the same time, genetic parts and tools are continuously being developed to manipulate this distinctive organism. Engineered R. toruloides strains are emerging for enhanced production of conventional lipids, functional lipids as well as other interesting metabolites. This review updates those progresses and highlights future directions for advanced biotechnological applications.


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