Literature DB >> 26319892

Engineering of oleaginous organisms for lipid production.

Jennifer Levering1, Jared Broddrick1, Karsten Zengler2.   

Abstract

Phototrophs are attractive candidates for commercial lipid production. Lipid biosynthetic pathways in these organisms have been largely characterized but the mechanisms partitioning resources toward storage lipids are poorly understood. One promising strategy to study and enhance biomass lipid bioproduction in oleaginous microorganisms is to combine genome-scale metabolic modeling and genetic and metabolic engineering. Here we describe recent advances in in vitro, in vivo, and in silico manipulations of phototrophic metabolism that increase total lipid content or redirect lipid production toward more favorable products such as polyunsaturated fatty acids used as nutritional supplements or in biofuel production.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26319892     DOI: 10.1016/j.copbio.2015.08.001

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  15 in total

1.  Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

Authors:  Jared T Broddrick; David G Welkie; Denis Jallet; Susan S Golden; Graham Peers; Bernhard O Palsson
Journal:  Metab Eng       Date:  2018-11-13       Impact factor: 9.783

Review 2.  Engineering modular polyketide synthases for production of biofuels and industrial chemicals.

Authors:  Wenlong Cai; Wenjun Zhang
Journal:  Curr Opin Biotechnol       Date:  2017-09-22       Impact factor: 9.740

3.  Co-culturing of oleaginous microalgae and yeast: paradigm shift towards enhanced lipid productivity.

Authors:  Neha Arora; Alok Patel; Juhi Mehtani; Parul A Pruthi; Vikas Pruthi; Krishna Mohan Poluri
Journal:  Environ Sci Pollut Res Int       Date:  2019-04-27       Impact factor: 4.223

Review 4.  Synthetic biology, systems biology, and metabolic engineering of Yarrowia lipolytica toward a sustainable biorefinery platform.

Authors:  Jingbo Ma; Yang Gu; Monireh Marsafari; Peng Xu
Journal:  J Ind Microbiol Biotechnol       Date:  2020-07-04       Impact factor: 3.346

Review 5.  Research advances on arachidonic acid production by fermentation and genetic modification of Mortierella alpina.

Authors:  Huidan Zhang; Qiu Cui; Xiaojin Song
Journal:  World J Microbiol Biotechnol       Date:  2021-01-04       Impact factor: 3.312

6.  Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

Authors:  Cristal Zuñiga; Chien-Ting Li; Tyler Huelsman; Jennifer Levering; Daniel C Zielinski; Brian O McConnell; Christopher P Long; Eric P Knoshaug; Michael T Guarnieri; Maciek R Antoniewicz; Michael J Betenbaugh; Karsten Zengler
Journal:  Plant Physiol       Date:  2016-07-02       Impact factor: 8.340

7.  Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

Authors:  Jennifer Levering; Jared Broddrick; Christopher L Dupont; Graham Peers; Karen Beeri; Joshua Mayers; Alessandra A Gallina; Andrew E Allen; Bernhard O Palsson; Karsten Zengler
Journal:  PLoS One       Date:  2016-05-06       Impact factor: 3.240

8.  Mutations That Alter the Bacterial Cell Envelope Increase Lipid Production.

Authors:  Kimberly C Lemmer; Weiping Zhang; Samantha J Langer; Alice C Dohnalkova; Dehong Hu; Rachelle A Lemke; Jeff S Piotrowski; Galya Orr; Daniel R Noguera; Timothy J Donohue
Journal:  MBio       Date:  2017-05-23       Impact factor: 7.867

9.  Long-duration effect of multi-factor stresses on the cellular biochemistry, oil-yielding performance and morphology of Nannochloropsis oculata.

Authors:  Likun Wei; Xuxiong Huang
Journal:  PLoS One       Date:  2017-03-27       Impact factor: 3.240

10.  solveME: fast and reliable solution of nonlinear ME models.

Authors:  Laurence Yang; Ding Ma; Ali Ebrahim; Colton J Lloyd; Michael A Saunders; Bernhard O Palsson
Journal:  BMC Bioinformatics       Date:  2016-09-22       Impact factor: 3.169

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