期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2016
卷号：113
期号：51
页码：E8344-E8353
DOI：10.1073/pnas.1613446113
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：SignificanceGenome-scale models of metabolism are important tools for metabolic engineering and production strain development. We present an experimentally validated and manually curated model of metabolism in Synechococcus elongatus PCC 7942 that (i) leads to discovery of unique metabolic characteristics, such as the importance of a truncated, linear TCA pathway, (ii) highlights poorly understood areas of metabolism as exemplified by knowledge gaps in nucleotide salvage, and (iii) accurately quantifies light input and self-shading. We now have a metabolic model that can be used as a basis for metabolic design in S. elongatus. 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. Here, 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. 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.
