Applications of genome-scale metabolic reconstructions

By Matthew A. Oberhardt, Bernhard O. Palsson, Jason A. Papin. Molecular Systems Biology, 2009

849 citations recorded by the source corpus.

The availability and utility of genome‐scale metabolic reconstructions have exploded since the first genome‐scale reconstruction was published a decade ago. Reconstructions have now been built for a wide variety of organisms, and have been used toward five major ends: (1) contextualization of high‐throughput data, (2) guidance of metabolic engineering, (3) directing hypothesis‐driven discovery, (4) interrogation of multi‐species relationships, and (5) network property discovery. In this review, we examine the many uses and future directions of genome‐scale metabolic reconstructions, and we highlight trends and opportunities in the field that will make the greatest impact on many fields of biology.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0a2b49f51fd6b65e26c458fdd3592f88b63a3b08

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Citations in the corpus

Advances in plant disease and pest management (2010, background): “Genomescale metabolic reconstructions are already available for a range of species (Oberhardt et al. 2009), including yeast (Herrgård et al. 2008) and other fungi of industrial importance (Andersen et al. 2008), and within the next few years should also extend to some pests and pathogens.”
Predicting Network Activity from High Throughput Metabolomics (2013, background): “On the other hand, genome-scale metabolic models have been largely driven by genomics, as the total list of metabolic enzymes of a species can be derived from its genome sequence [11,12].”
Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli (2013, background): “Similarly, Oberhardt et al (2009) have reviewed applications enabled by GEMs for organisms other than E. coli through 2009, and speciﬁc reviews on GEM-enabled studies in plants (Sweetlove and Ratcliffe, 2011) and Saccharomyces cerevisiae (Osterlund et al , 2012) have recently appeared.”
An atlas of human metabolism (2020, methodology): “This challenge has been addressed by building genome-scale metabolic models (GEMs), which have been used, for instance, in industrial applications involving Saccharomyces cerevisiae and Escherichia coli to understand metabolism, engineer new cellular objectives (such as biofuel production), and incr”
Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods (2012, background): “This mathematical representation enables the computation of phenotypic state”
Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease (2011, background): “In silico models of microbial communities are currently still scarce (19) and mostly focus on simulated communities comprising a handful of species and on pair-wise interactions among Fig.”
iMAT: an integrative metabolic analysis tool (2010, background): “†The authors wish it to be known that, in their opinion, the last two authors should be regarded as joint First Authors. significant changes in measured flux may not reflect transcriptional changes (Ovacik and Androulakis, 2008).”
Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism (2014, background): “These reconstructions range from microbes to higher organisms, and have been used for myriad applications, including the prediction of cellular phenotypes, design of microbial cell factories, studies of evolution, and model-driven discovery of novel drug targets [2,6].”
The problem of pattern and scale in ecology: what have we learned in 20 years? (2013, background): “Together these studies suggest that the 'reverse ecology' approach does not only help rethink classical questions in ecology, it is also an umbrella for a novel integration between ecology and cell biology (Oberhardt et al. 2009; Gudelj et al. 2010).”
Fast automated reconstruction of genome-scale metabolic models for microbial species and communities (2018, background): “To this end, genome-scale metabolic models provide a mechanistic basis allowing to predict the effects of, e.g. gene knockouts, or nutritional changes (1,2).”
Using Genome-Scale Models to Predict Biological Capabilities (2015, positive): “It has been successfully applied to a multitude of species for modeling their cellular metabolisms (Feist and Palsson, 2008; McCloskey et al., 2013; Oberhardt et al., 2009) and therefore enabled a variety of applications such as metabolic engineering for the over-production of biochemicals (Yim et a”