Journal: mSystems

Article Title: A temperature-induced metabolic shift in the emerging human pathogen Photorhabdus asymbiotica

doi: 10.1128/msystems.00970-23

Figure Lengend Snippet: Metabolic reconstruction of Photorhabdus asymbiotica (iEC1073). (a) Schematic for reconstructing the metabolic model of P. asymbiotica . It includes the generation of a draft reconstruction using the genome sequence by the Model SEED, integration of BiGG identifiers, and extensive manual curation. (b) iEC1073 contains 1,073 genes; 1,770 metabolites; and 2,033 reactions. These genes, metabolites, and reactions were added throughout the reconstruction process at different stages of curation (i). The number of genes, metabolites, and reactions in iEC1073 is comparable with other high quality, thoroughly curated prokaryotic GEMs available on the BiGG database (ii). The proportion of active and inactive reactions in iEC1073, in unconstrained conditions, is comparable with those for five selected published prokaryotic GEMs ( ) (iii).

Article Snippet: The genome-scale metabolic model of P. asymbiotica, iEC1073, has been uploaded to BioModels ( https://www.ebi.ac.uk/biomodels/ ) with the ID MODEL2309110001.

Techniques: Sequencing

Journal: mSystems

Article Title: A temperature-induced metabolic shift in the emerging human pathogen Photorhabdus asymbiotica

doi: 10.1128/msystems.00970-23

Figure Lengend Snippet: Comparing the predicted essential genes with experimental data. (a) Schematic of in silico single gene knockouts of iEC1073 compared to experimental data for validation. Experimental gene essentiality data were obtained from the online gene essentiality (OGEE) database for five comparative organisms ( B. subtilis, E. coli, H. pylori, M. tuberculosis, and Y. pestis ). In silico single-gene knockout experiments were conducted for iEC1073 and predicted essentiality status compared with orthologous genes in comparison organisms. (b) Concordance of gene essentiality in iEC1073 compared to orthologous genes in comparative organisms (cyan), concordance of the published metabolic reconstruction of these organisms with their own experimental data (red), and the total number of orthologous genes compared between iEC1073 and the comparative organism (green). iEC1073 is 81%, 86%, 65%, 62%, and 76% concordant with B. subtilis, E. coli, H. pylori, M. tuberculosis, and Y. pestis, respectively. Quite similarly, the published metabolic network reconstructions for B. subtilis, E. coli, H. pylori, M. tuberculosis, and Y. pestis are 82%, 91%, 52%, 87%, and 68% concordant with experimental data sets of the same species, respectively. (c) Pathway distribution of essential genes in iEC1073 concordant with the essentiality status of E. coli orthologs . The majority of these genes have an unannotated role, while the remaining genes are evenly distributed among the major annotated metabolic categories.

Article Snippet: The genome-scale metabolic model of P. asymbiotica, iEC1073, has been uploaded to BioModels ( https://www.ebi.ac.uk/biomodels/ ) with the ID MODEL2309110001.

Techniques: In Silico, Biomarker Discovery, Gene Knockout, Comparison

Journal: mSystems

Article Title: A temperature-induced metabolic shift in the emerging human pathogen Photorhabdus asymbiotica

doi: 10.1128/msystems.00970-23

Figure Lengend Snippet: Model validation using experimental phenotype microarray data . In silico carbon and nitrogen utilization predictions were used to validate iEC1073 with experimental phenotype microarray data. (a) 51 carbon sources were tested in iEC1073. A total of 37 (72.5%) of these carbon sources are concordant with the experimental data (i). Of the carbon sources discordant between the reconstruction and experimental data, for only three can the reconstruction not produce biomass despite respiration observed experimentally (i). Of the 51 carbon sources tested, 39 sources increased metabolic activity and 12 decreased this activity experimentally (ii), and 39 sources increased biomass production by iEC1073 while 12 could not support an increase in biomass production (iii). N -Acetyl- d -glucosamine (GlcNAc), an amide derivative of glucose, best supported metabolic activity of the organism in the lab and also increased in silico growth, though the dipeptide Ala-Gly most increased biomass production in iEC1073 (ii, iii) . (b) Twenty-nine nitrogen sources were tested in iEC1073. A total of 18 (62%) of these nitrogen sources are concordant with the experimental data (i). For only one of the discordant nitrogen sources, the dipeptide Ala-Leu was the reconstruction unable to produce biomass despite respiration observed experimentally (i). Of the 29 nitrogen sources tested, 23 sources increased metabolic activity and 6 decreased this activity experimentally (ii), and 20 sources increased biomass production by iEC1073 while 9 could not support an increase in biomass production (iii). The dipeptide Gly-Gln most increases experimental metabolic activity and this dipeptide, along with Gly-Asn, Ala-His, and Gly-Gln, best support biomass production by the reconstruction (ii, iii).

Article Snippet: The genome-scale metabolic model of P. asymbiotica, iEC1073, has been uploaded to BioModels ( https://www.ebi.ac.uk/biomodels/ ) with the ID MODEL2309110001.

Techniques: Biomarker Discovery, Microarray, In Silico, Activity Assay

Journal: mSystems

Article Title: A temperature-induced metabolic shift in the emerging human pathogen Photorhabdus asymbiotica

doi: 10.1128/msystems.00970-23

Figure Lengend Snippet: Adjusting reaction bounds in iEC1073 to create temperature-specific reconstructions. Integrating gene expression data for growth of P. asymbiotica at 28°C and 37°C to create temperature-specific networks. Flux variability analysis (FVA) was performed on iEC1073 and the upper and lower bounds of each reaction in the reconstruction set as the maximum and minimum flux determined by FVA, respectively, to create the 28°C model. This model was used as a template to create the 37°C model. Log2fold gene expression changes at 37°C compared to 28°C were mapped to each reaction in the network, accounting for the gene-protein-reaction association. The bounds of reactions in the template 28°C model were adjusted according to this mapped log2fold expression change to create the 37°C model. All analyses were performed in the COBRA Toolbox v 3.0 implemented in Matlab (R2019b).

Article Snippet: The genome-scale metabolic model of P. asymbiotica, iEC1073, has been uploaded to BioModels ( https://www.ebi.ac.uk/biomodels/ ) with the ID MODEL2309110001.

Techniques: Gene Expression, Expressing, Combined Bisulfite Restriction Analysis Assay