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Title: Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [6] ;  [2] ;  [7]
  1. Univ. of California, San Diego, CA (United States). Dept. of Bioengineering. Division of Biological Sciences
  2. Univ. of California, San Diego, CA (United States). Division of Biological Sciences. Center for Circadian Biology
  3. Univ. of California, San Diego, CA (United States). Center for Circadian Biology
  4. Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; J. Craig Venter Inst., La Jolla, CA (United States)
  5. Univ. of California, San Diego, CA (United States). Bioinformatics and Systems Biology Graduate Program
  6. Univ. of California, San Diego, CA (United States). Division of Biological Sciences
  7. Univ. of California, San Diego, CA (United States). Dept. of Bioengineering. Bioinformatics and Systems Biology Graduate Program
Publication Date:
Grant/Contract Number:
SC0008593; T32GM00724; 2-P3071; MCB1244108
Type:
Published Article
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 113; Journal Issue: 51; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Research Org:
J. Craig Venter Inst., La Jolla, CA (United States); Univ. of California, San Diego, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Inst. of Health (NIH) (United States); Univ. of California (United States); National Science Foundation (NSF)
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; cyanobacteria; constraint-based modeling; TCA cycle; photosynthesis; Synechococcus elongatus
OSTI Identifier:
1334350
Alternate Identifier(s):
OSTI ID: 1423793

Broddrick, Jared T., Rubin, Benjamin E., Welkie, David G., Du, Niu, Mih, Nathan, Diamond, Spencer, Lee, Jenny J., Golden, Susan S., and Palsson, Bernhard O.. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis. United States: N. p., Web. doi:10.1073/pnas.1613446113.
Broddrick, Jared T., Rubin, Benjamin E., Welkie, David G., Du, Niu, Mih, Nathan, Diamond, Spencer, Lee, Jenny J., Golden, Susan S., & Palsson, Bernhard O.. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis. United States. doi:10.1073/pnas.1613446113.
Broddrick, Jared T., Rubin, Benjamin E., Welkie, David G., Du, Niu, Mih, Nathan, Diamond, Spencer, Lee, Jenny J., Golden, Susan S., and Palsson, Bernhard O.. 2016. "Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis". United States. doi:10.1073/pnas.1613446113.
@article{osti_1334350,
title = {Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis},
author = {Broddrick, Jared T. and Rubin, Benjamin E. and Welkie, David G. and Du, Niu and Mih, Nathan and Diamond, Spencer and Lee, Jenny J. and Golden, Susan S. and Palsson, Bernhard O.},
abstractNote = {The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.},
doi = {10.1073/pnas.1613446113},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 51,
volume = 113,
place = {United States},
year = {2016},
month = {12}
}

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