Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis
Abstract
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:
-
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093,, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093,
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093,, Center for Circadian Biology, University of California, San Diego, La Jolla, CA 92093,
- Center for Circadian Biology, University of California, San Diego, La Jolla, CA 92093,
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093,, Microbial and Environmental Genomics, J. Craig Venter Institute, La Jolla, CA 92037,
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093,
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093,, Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093
- Publication Date:
- 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); National Inst. of Health (NIH) (United States); Univ. of California (United States); National Science Foundation (NSF)
- OSTI Identifier:
- 1334350
- Alternate Identifier(s):
- OSTI ID: 1423793
- Grant/Contract Number:
- SC0008593; T32GM00724; 2-P3071; MCB1244108
- Resource Type:
- Published Article
- Journal Name:
- Proceedings of the National Academy of Sciences of the United States of America
- Additional Journal Information:
- Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Volume: 113 Journal Issue: 51; Journal ID: ISSN 0027-8424
- Publisher:
- Proceedings of the National Academy of Sciences
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; cyanobacteria; constraint-based modeling; TCA cycle; photosynthesis; Synechococcus elongatus
Citation Formats
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., 2016.
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. https://doi.org/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. Tue .
"Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis". United States. https://doi.org/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 = {Tue Dec 20 00:00:00 EST 2016},
month = {Tue Dec 20 00:00:00 EST 2016}
}
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