scholarly journals Understanding the metabolism of the tetralin degrader Sphingopyxis granuli strain TFA through genome-scale metabolic modelling

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Inmaculada García-Romero ◽  
Juan Nogales ◽  
Eduardo Díaz ◽  
Eduardo Santero ◽  
Belén Floriano
2018 ◽  
Author(s):  
Nhung Pham ◽  
Ruben Van Heck ◽  
Jesse van Dam ◽  
Peter Schaap ◽  
Edoardo Saccenti ◽  
...  

Genome scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in eleven biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.


2019 ◽  
Vol 22 (1) ◽  
pp. 255-269 ◽  
Author(s):  
Juan Nogales ◽  
Joshua Mueller ◽  
Steinn Gudmundsson ◽  
Francisco J. Canalejo ◽  
Estrella Duque ◽  
...  

2019 ◽  
Author(s):  
Macauley Coggins

Genome-Scale metabolic models have proven to be incredibly useful.Allowing researchers to model cellular functionality based upon gene expression. However as the number of genes and reactions increases it can become computationally demanding. The first step in genome-scale metabolic modelling is to model the relationship between genes and reactions in the form of Gene-Protein-Reaction Associations (GPRA). In this research we have developed a way to model GPRAs on an Altera Cyclone II FPGA using Quartus II programmable logic device design software and the VHDL hardware description language. The model consisting of 7 genes and 7 reactions was implemented using 7 combinational functions and 14 I/O pins. This model will be the first step towards creating a full genome scale metabolic model on FPGA devices which we will be fully investigating in future studies.


2020 ◽  
Author(s):  
Kaja Blagotinšek Cokan ◽  
Žiga Urlep ◽  
Miha Moškon ◽  
Miha Mraz ◽  
Xiang Y. Kong ◽  
...  

AbstractMultifactorial metabolic diseases, such as non-alcoholic fatty liver disease, are a major burden of modern societies and frequently present with no clearly defined molecular biomarkers. Herein we used systems medicine approaches to decipher signatures of liver fibrosis in mouse models with malfunction in genes from unrelated biological pathways. Enrichment analyses of KEGG, Reactome and TRANSFAC databases complemented with genome-scale metabolic modelling revealed fibrotic signatures highly similar to liver pathologies in humans. The diverse genetic models of liver fibrosis exposed a common transcriptional programme with activated ERα signalling, and a network of interactions between regulators of lipid metabolism and transcription factors from cancer pathways and immune system. The novel hallmarks of fibrosis are downregulated lipid pathways, including fatty acid, bile acid, and steroid hormone metabolism. Moreover, distinct metabolic subtypes of liver fibrosis were proposed, supported by unique enrichment of transcription factors based on the type of insult, disease stage, or sex.


mSystems ◽  
2022 ◽  
Author(s):  
Carolin C. M. Schulte ◽  
Vinoy K. Ramachandran ◽  
Antonis Papachristodoulou ◽  
Philip S. Poole

Rhizobia are soil bacteria that induce nodule formation on plant roots and differentiate into nitrogen-fixing bacteroids. A detailed understanding of this complex symbiosis is essential for advancing ongoing efforts to engineer novel symbioses with cereal crops for sustainable agriculture.


2019 ◽  
Author(s):  
Macauley Coggins

AbstractGenome-Scale metabolic models have proven to be incredibly useful. Allowing researchers to model cellular functionality based upon gene expression. However as the number of genes and reactions increases it can become computationally demanding. The first step in genome-scale metabolic modelling is to model the relationship between genes and reactions in the form of Gene-Protein-Reaction Associations (GPRA). In this research we have developed a way to model GPRAs on an Altera Cyclone II FPGA using Quartus II programmable logic device design software and the VHDL hardware description language. The model consisting of 7 genes and 7 reactions was implemented using 7 combinational functions and 14 I/O pins. This model will be the first step towards creating a full genome scale metabolic model on FPGA devices which we will be fully investigating in future studies.


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