Generated April 3, 2023

Formation and interaction network of a constructed microbial community in a nutrient-rich environment

This narrative was used to generate metabolic model of strain Pantoea sp. YR343 gapfilled by R2A medium environment. The metabolic model of strain YR343 (YR343_ReSeq_MetabolicModel_R2A004Gapfilled) was further used for dynamic flux balance analysis (dFBA) simulation by Computation of Microbial Ecosystems in Time and Space (COMETS) tool.

Annotate or re-annotate genome/assembly using RASTtk (Rapid Annotations using Subsystems Technology toolkit).
This app completed without errors in 5m 49s.
Objects
Created Object Name Type Description
YR343_ReSeq_Annotation_01 Genome RAST re-annotated genome
Summary
The RAST algorithm was applied to annotating a genome sequence comprised of 3 contigs containing 5391843 nucleotides. No initial gene calls were provided. Standard features were called using: glimmer3; prodigal. A scan was conducted for the following additional feature types: rRNA; tRNA; selenoproteins; pyrrolysoproteins; repeat regions; crispr. The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity. In addition to the remaining original 0 coding features and 0 non-coding features, 5141 new features were called, of which 156 are non-coding. Output genome has the following feature types: Coding gene 4985 Non-coding repeat 56 Non-coding rna 100 The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Links
Construct a draft metabolic model based on an annotated genome.
This app completed without errors in 2m 35s.
Objects
Created Object Name Type Description
YR343_ReSeq_MetabolicModel_R2A004Gapfilled FBAModel FBAModel-14 YR343_ReSeq_MetabolicModel_R2A004Gapfilled
YR343_ReSeq_MetabolicModel_R2A004Gapfilled.gf.1 FBA FBA-13 YR343_ReSeq_MetabolicModel_R2A004Gapfilled.gf.1
Report
Summary
RefGlucoseMinimal media.
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/117919
Predict metabolite fluxes in a metabolic model of an organism grown on a given media using flux balance analysis (FBA).
This app completed without errors in 1m 2s.
Objects
Created Object Name Type Description
YR343_ReSeq_FBA_R2A004Gapfilled_Carbon60 FBA FBA-13 YR343_ReSeq_FBA_R2A004Gapfilled_Carbon60
Report
Summary
A flux balance analysis (FBA) was performed on the metabolic model 117919/6/1 growing in 117919/3/1 media.
Output from Run Flux Balance Analysis
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/117919

Apps

  1. Annotate Genome/Assembly with RASTtk - v1.073
    • [1] Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. doi:10.1186/1471-2164-9-75
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, et al. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5. doi:10.1038/srep08365
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    • [11] Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11: 119. doi:10.1186/1471-2105-11-119
    • [12] Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics. 2007;23: 673 679. doi:10.1093/bioinformatics/btm009
    • [13] Akhter S, Aziz RK, Edwards RA. PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res. 2012;40: e126. doi:10.1093/nar/gks406
  2. Build Metabolic Model
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [4] Dreyfuss JM, Zucker JD, Hood HM, Ocasio LR, Sachs MS, Galagan JE. Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM. PLOS Computational Biology. 2013;9: e1003126. doi:10.1371/journal.pcbi.1003126
    • [5] Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5: 264 276.
  3. Run Flux Balance Analysis
    • Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • Orth JD, Thiele I, Palsson B . What is flux balance analysis? Nature Biotechnology. 2010;28: 245 248. doi:10.1038/nbt.1614