Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; Ng, Patrick; Khraiwesh, Basel; Jaiswal, Ashish; Jijakli, Kenan; Koussa, Joseph; Nelson, David R.; Cai, Hong; Yang, Xinping; Chang, Roger L.; Papin, Jason; Yu, Haiyuan; Balaji, Santhanam; Salehi-Ashtiani, Kourosh

doi:10.1039/c6mb00237d

Title: Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

Journal Article · Tue Jun 14 00:00:00 EDT 2016 · Molecular BioSystems

DOI:https://doi.org/10.1039/c6mb00237d· OSTI ID:1434909

Chaiboonchoe, Amphun ^[1]; Ghamsari, Lila ^[2]; Dohai, Bushra ^[1]; Ng, Patrick ^[3];

^[1]; Jaiswal, Ashish ^[1]; Jijakli, Kenan ^[1]; Koussa, Joseph ^[1]; Nelson, David R. ^[1]; Cai, Hong ^[1]; Yang, Xinping ^[2]; Chang, Roger L. ^[2]; Papin, Jason ^[4]; Yu, Haiyuan ^[3]; Balaji, Santhanam ^[5]; Salehi-Ashtiani, Kourosh ^[6]

New York Univ. Abu Dhabi Institute, Abu Dhabi (United Arab Emirates)
Harvard Medical School, Boston, MA (United States)
Cornell Univ., Ithaca, NY (United States)
Univ. of Virginia, Charlottesville, VA (United States)
New York Univ. Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Harvard Medical School, Boston, MA (United States); MRC Lab. of Molecular Biology, Cambridge (United Kingdom)
New York Univ. Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Harvard Medical School, Boston, MA (United States)

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. As a result, the defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

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Research Organization:: Harvard Medical School, Boston, MA (United States). Dana-Farber Cancer Institute, Inc.

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: FG02-07ER64496

OSTI ID:: 1434909

Journal Information:: Molecular BioSystems, Vol. 12, Issue 8; ISSN 1742-206X

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 9 works

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