TY - JOUR
T1 - High-Throughput Metabolic Profiling for Model Refinements of Microalgae
AU - Alzahmi, Amnah
AU - Daakour, Sarah
AU - El Assal, Diana Charles
AU - Dohai, Bushra S.
AU - Chaiboonchoe, Amphun
AU - Fu, Weiqi
AU - Nelson, David R.
AU - Mystikou, Alexandra
AU - Salehi-Ashtiani, Kourosh
N1 - Funding Information:
Major support for this work was provided by the NYUAD Center for Genomics and Systems Biology (CGSB), funded by Tamkeen under New York University Abu Dhabi Research Institute grant (73 71210 CGSB9) and NYU Abu Dhabi Faculty Research Funds (AD060). W.F. was additionally supported by the Hundred Talents Program of Zhejiang University. We thank Ashish Jaiswal for help in recording the video. We thank Hong Cai for generating the metabolic phenotype data.
Publisher Copyright:
© 2021 JoVE Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
PY - 2021/12
Y1 - 2021/12
N2 - Metabolic models are reconstructed based on an organism's available genome annotation and provide predictive tools to study metabolic processes at a systemslevel. Genome-scale metabolic models may include gaps as well as reactions that are unverified experimentally. Reconstructed models of newly isolated microalgal species will result in weaknesses due to these gaps, as there is usually sparse biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology is an effective, high-throughput method that functionally determines cellular metabolic activities in response to a wide array of entry metabolites. Combining the high throughput phenotypic assays with metabolic modeling can allow existing metabolic network models to be rapidly reconstructed or optimized by providing biochemical evidence to support and expand genomic evidence. This work will show the use of PM assays for the study of microalgae by using the green microalgal model species Chlamydomonas reinhardtii as an example. Experimental evidence for over 254 reactions obtained by PM was used in this study to expand and refine a genome-scale C. reinhardtii metabolic network model, iRC1080, by approximately 25 percent. The protocol created here can be used as a basis for functionally profiling the metabolism of other microalgae, including known microalgae mutants and new isolates.
AB - Metabolic models are reconstructed based on an organism's available genome annotation and provide predictive tools to study metabolic processes at a systemslevel. Genome-scale metabolic models may include gaps as well as reactions that are unverified experimentally. Reconstructed models of newly isolated microalgal species will result in weaknesses due to these gaps, as there is usually sparse biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology is an effective, high-throughput method that functionally determines cellular metabolic activities in response to a wide array of entry metabolites. Combining the high throughput phenotypic assays with metabolic modeling can allow existing metabolic network models to be rapidly reconstructed or optimized by providing biochemical evidence to support and expand genomic evidence. This work will show the use of PM assays for the study of microalgae by using the green microalgal model species Chlamydomonas reinhardtii as an example. Experimental evidence for over 254 reactions obtained by PM was used in this study to expand and refine a genome-scale C. reinhardtii metabolic network model, iRC1080, by approximately 25 percent. The protocol created here can be used as a basis for functionally profiling the metabolism of other microalgae, including known microalgae mutants and new isolates.
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U2 - 10.3791/61913
DO - 10.3791/61913
M3 - Article
C2 - 34927618
AN - SCOPUS:85122845425
SN - 1940-087X
VL - 2021
JO - Journal of Visualized Experiments
JF - Journal of Visualized Experiments
IS - 178
M1 - e61913
ER -