ArticleProceedings of the National Academy of Sciences of the United States of America2016
Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.
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Who cites it
69 citing papers in PubMed.
- Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression.Current issues in molecular biology · 2026Review
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophages.Science advances · 2026Article
- Review
- Natural color biofactories: advancing the spectrum of pigment production in phototrophic microbes.FEMS microbes · 2025Review
- Article
- Insufficient Acetyl-CoA Pool Restricts the Phototrophic Production of Organic Acids in Model Cyanobacteria.International journal of molecular sciences · 2024Review
- Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light.Nature communications · 2024Article
- Double blocking of carbon metabolism causes a large increase of Calvin-Benson cycle compounds in cyanobacteria.Plant physiology · 2024Article
- Article
- A Novel Strain of the Cyanobacterial Growth-promoting Bacterium, Rhodococcus sp. AF2108, Enhances the Growth of Synechococcus elongatus.Microbes and environments · 2024Article
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- FreeFlux: A Python Package for Time-Efficient Isotopically Nonstationary Metabolic Flux Analysis.ACS synthetic biology · 2023Article
- The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions.PLoS computational biology · 2023Article
- Morphological and metabolomics profiling of intraspecific Arabidopsis hybrids in relation to biomass heterosis.Scientific reports · 2023Article
- Transcriptomic profiling of near-isogenic lines reveals candidate genes for a significant locus conferring metribuzin resistance in wheat.BMC plant biology · 2023Article
- The Special and General Mechanism of Cyanobacterial Harmful Algal Blooms.Microorganisms · 2023Review
- Light and carbon: Synthetic biology toward new cyanobacteria-based living biomaterials.Materials today. Bio · 2023Article
- Incorporation, fate, and turnover of free fatty acids in cyanobacteria.FEMS microbiology reviews · 2023Review
- Current Metabolic Engineering Strategies for Photosynthetic Bioproduction in Cyanobacteria.Microorganisms · 2023Review
9 more citing papers are in PubMed but not listed here.
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9 authors.
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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. 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.
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