Project description:Kamminga2017 - Metabolic model of Mycoplasma hyopneumoniae growth This model is described in the article: Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate. Kamminga T, Slagman SJ, Bijlsma JJE, Martins Dos Santos VAP, Suarez-Diez M, Schaap PJ. Biotechnol. Bioeng. 2017 Jun; : Abstract: Mycoplasma hyopneumoniae is cultured on large-scale to produce antigen for inactivated whole-cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint-based genome-scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time-series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non-growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model-driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3-4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;9999: 1-9. © 2017 Wiley Periodicals, Inc. This model is hosted on BioModels Database and identified by: MODEL1704250001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Streptococcus pneumoniae is a strictly fermentative human pathogen that relies on carbohydrate metabolism to generate energy for growth. The nasopharynx colonised by the bacterium is poor in free sugars, but mucosa lining glycans can provide a source of sugar. In blood and inflamed tissues glucose is the prevailing sugar. As a result during progression from colonisation to disease S. pneumoniae has to cope with a pronounced shift in carbohydrate nature and availability. Thus, we set out to assess the pneumococcal response to sugars found in glycans and the influence of glucose (Glc) on this response at the transcriptional, physiological and metabolic levels. Galactose (Gal), N-acetylglucosamine (GlcNAc) and mannose (Man) affected the expression of 8 to 14% of the genes covering cellular functions including central carbon metabolism and virulence. The pattern of end-products as monitored by in vivo 13C-NMR is in good agreement with the fermentation profiles during growth, while the pools of phosphorylated metabolites are consistent with the type of fermentation observed (homolactic vs. mixed) and regulation at the metabolic level. Furthermore, the accumulation of -Gal6P and Man6P indicate metabolic bottlenecks in the metabolism of Gal and Man, respectively. Glc added to cells actively metabolizing other sugar(s)was readily consumed and elicited a metabolic shift towards a homolactic profile. The transcriptional response to Glc was large (over 5% of the genome). In central carbon metabolism (most represented category), Glc exerted mostly negative regulation. The smallest response was observed on a sugar mix, suggesting that exposure to varied sugars improves the fitness of S. pneumoniae. The expression of classical virulence factors was negatively controlled by Glc in a sugar-dependent manner. Overall, our results shed new light on the link between carbohydrate metabolism, adaptation to host niches and virulence. Two conditions with the same strain (D39), including a dye swap

Dataset Information

Wodke2013 - Genome-scale constraint-based model of M.pneumoniae energy metabolism (iJW145)

Publications

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.

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