The Complete Genome Sequence and Structure of the Oleaginous Rhodococcus opacus Strain PD630 Through Nanopore Technology

Firrincieli, Andrea; Grigoriev, Beatrice; Dostálová, Hana; Cappelletti, Martina

doi:10.3389/fbioe.2021.810571

Cited by 1 publication

(4 citation statements)

References 32 publications

(47 reference statements)

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“…iGR1773 was generated from a recent genome annotation 27 and the genome-to-GSM tool CarveMe 32 ( Figure 1 ). The draft model produced by CarveMe was accurate but required manual changes: two reactions needed to have their flux bounds adjusted to match known thermodynamic patterns.…”

Section: Resultsmentioning

confidence: 99%

“…CarveMe follows a top-down approach where a universal model and genome sequence are the only required inputs to construct a model in a fast and reproducible manner. The GSM was based on a recent genomic sequence of the Rhodococcus opacus PD630 (Refseq ID: GCF_020542785.1) . The initial model was made using the command line command “carve r_opacus_bologna.faa -u grampos -o r_opacus_bologna_raw.xml”.…”

Section: Methodsmentioning

confidence: 99%

“…The GSM was based on a recent genomic sequence of the Rhodococcus opacus PD630 (Refseq ID: GCF_020542785.1). 27 The initial model was made using the command line command “carve r_opacus_bologna.faa -u grampos -o r_opacus_bologna_raw.xml”. After the model generation, this initial draft model was also gap-filled to ensure growth on M9 and LB media using the command “gapfill r_opacus_bologna.xml -m M9,LB -o r_opacus_bologna_gapfilled.xml”.…”

Section: Methodsmentioning

confidence: 99%

“…Here, we present and validate iGR1773, the first GSM for R. opacus derived from its genome, providing a comprehensive description of its internal metabolism and a valuable tool to integrate omics data into metabolic flux predictions. iGR1773 consists of 3025 reactions and 1956 metabolites obtained from annotating its completed genome, adding the corresponding metabolic reactions, and testing the predictions derived by it. Although previous publications have reported a GSM for R. opacus PD630, , this model did not use an annotation of the R. opacus PD630 genome.…”

Section: Introductionmentioning

confidence: 99%

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A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

et al. 2023

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Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R 2 value of 0.54, while predictions based on pFBA had an inferior R 2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R 2 of 0.96 while pFBA showed an R 2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%