Metabolic Model of Methanosarcina Acetivorans
Author Information
Author(s): Satish Kumar Vinay, Ferry James G, Maranas Costas D
Primary Institution: Joint BioEnergy Institute
Hypothesis
Can a genome-scale metabolic model be reconstructed for Methanosarcina acetivorans?
Conclusion
The iVS941 model represents the most comprehensive effort to catalogue methanogenic metabolism, achieving 93.3% prediction agreement with in vivo growth data.
Supporting Evidence
- The model accounts for 941 genes, 705 reactions, and 708 metabolites.
- It achieves 93.3% prediction agreement with in vivo growth data.
- The model is available in spreadsheet and SBML formats for dissemination.
- Unique biochemical characteristics of M. acetivorans were captured in the model.
- The model includes regulatory constraints for substrate-specific activation.
- High confidence in model entries due to stringent e-value cutoffs.
- Model predictions were validated against experimental data across 60 conditions.
Takeaway
Scientists created a detailed model of a tiny organism that makes methane, helping us understand how it grows and survives.
Methodology
The model was generated using a systematic workflow that included draft model generation, model correction, and evaluation against in vivo growth data.
Potential Biases
The model may over-predict metabolic capabilities based on in silico predictions.
Limitations
The model may not capture all metabolic pathways due to potential omissions in the draft reconstruction.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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