scholarly journals Genome-scale metabolic network reconstruction of the chloroform-respiring Dehalobacter restrictus strain CF

2018 ◽  
Author(s):  
Kevin Correia ◽  
Hanchen Ho ◽  
Radhakrishnan Mahadevan
Keyword(s):  
Metabolic Network ◽  
Formate Dehydrogenase ◽  
Tca Cycle ◽  
Metabolic Model ◽  
Network Reconstruction ◽  
Acetyl Coa ◽  
Metabolic Network Reconstruction ◽  
Future Studies ◽  
Transport Chain ◽  
Genome Scale

ABSTRACTBackgroundOrganohalide-respiring bacteria (OHRB) play an important role in the global halogen cycle and bioremediation of industrial sites contaminated with chlorinated organics. One notable OHRB is Dehalobacter restrictus strain CF, which is capable of respiring chloroform to dichloromethane. Improved bioremediation strategies could be employed with a greater understanding of D. restrictus’ metabolism in isolate and community cultures. To this end, we reconstructed the genome-scale metabolic network of D. restrictus to study its metabolism in future studies using flux balance analysis.MethodThe RAST annotation server and Model SEED framework were used to obtain a draft metabolic network reconstruction. Additional curation was required for its acetyl-CoA sources, the Wood-Ljungdahl pathway, TCA cycle, electron transport chain, hydrogenase complexes, and formate dehydrogenase complexes.ResultsiHH623 is the first curated genome-scale metabolic model in the Peptococcaceae family. It spans 1087 reactions and 983 metabolites, covering 623 genes (21% of all ORF’s). Its potential sources of acetyl-CoA are pyruvate ferredoxin oxidoreductase, pyruvate formate lyase, acetyl-CoA synthetase, phosphate acetyltransferase, and CO-methylating acetyl-CoA synthase. NADPH may be regenerated by isocitrate dehydrogenase, malic enzyme, NADP-reducing hydrogenase, cytosolic formate dehydrogenase, ferredoxin-dependent bifurcating transhydrogenase, 5-methyltetrahydrofolate dehydrogenase, and 5-10-methylenetetrahydrofolate. Additional reactions that were added or removed to the D. restrictus reconstruction are discussed.ConclusionsWe reconstructed the genome-scale metabolic network of D. restricus by obtaining an initial draft with the RAST server and Model SEED framework. Curation was required for D. restricus’ acetyl-CoA sources, TCA cycle, electron transport chain, hydrogenase complexes, and formate dehydrogenase complexes. This metabolic model can be used to decipher D. restrictus’ metabolism in isolate and community cultures in future studies, or as a template to reconstruct the metabolic network of other Peptococcaceae species. The extensive curation of the draft metabolic network reconstruction highlights the need to be cautious of automated metabolic network reconstruction.

scholarly journals A genome‐scale metabolic network reconstruction of tomato ( Solanum lycopersicum L.) and its application to photorespiratory metabolism

2016 ◽  
Vol 85 (2) ◽  
pp. 289-304 ◽  
Author(s):  
Huili Yuan ◽  
C.Y. Maurice Cheung ◽  
Mark G. Poolman ◽  
Peter A. J. Hilbers ◽  
Natal A. W. Riel
Keyword(s):  
Metabolic Network ◽  
Solanum Lycopersicum ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Solanum Lycopersicum L ◽  
A Genome ◽  
Genome Scale

scholarly journals An updated genome-scale metabolic network reconstruction of Pseudomonas aeruginosa PA14 to characterize mucin-driven shifts in bacterial metabolism

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dawson D. Payne ◽  
Alina Renz ◽  
Laura J. Dunphy ◽  
Taylor Lewis ◽  
Andreas Dräger ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
Infection Prevention ◽  
Network Reconstruction ◽  
The Body ◽  
Carbon Source Utilization ◽  
Metabolic Network Reconstruction ◽  
Propionate Metabolism ◽  
Context Specific ◽  
Genome Scale

AbstractMucins are present in mucosal membranes throughout the body and play a key role in the microbe clearance and infection prevention. Understanding the metabolic responses of pathogens to mucins will further enable the development of protective approaches against infections. We update the genome-scale metabolic network reconstruction (GENRE) of one such pathogen, Pseudomonas aeruginosa PA14, through metabolic coverage expansion, format update, extensive annotation addition, and literature-based curation to produce iPau21. We then validate iPau21 through MEMOTE, growth rate, carbon source utilization, and gene essentiality testing to demonstrate its improved quality and predictive capabilities. We then integrate the GENRE with transcriptomic data in order to generate context-specific models of P. aeruginosa metabolism. The contextualized models recapitulated known phenotypes of unaltered growth and a differential utilization of fumarate metabolism, while also revealing an increased utilization of propionate metabolism upon MUC5B exposure. This work serves to validate iPau21 and demonstrate its utility for providing biological insights.

scholarly journals Genome scale metabolic network reconstruction of the pathogen Enterococcus faecalis

2013 ◽  
Vol 46 (31) ◽  
pp. 131-136
Author(s):  
Carla Portela ◽  
Silas Villas-Bôas ◽  
Isabel Rocha ◽  
Eugénio C. Ferreira
Keyword(s):  
Metabolic Network ◽  
Enterococcus Faecalis ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Genome Scale

scholarly journals GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogen Mycobacterium leprae

2020 ◽  
Vol 14 (7) ◽  
pp. e0007871
Author(s):  
Khushboo Borah ◽  
Jacque-Lucca Kearney ◽  
Ruma Banerjee ◽  
Pankaj Vats ◽  
Huihai Wu ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Mycobacterium Leprae ◽  
Network Reconstruction ◽  
Human Pathogen ◽  
Metabolic Network Reconstruction ◽  
A Genome ◽  
Genome Scale

scholarly journals Functional Anabolic Network Analysis of Human-associated Lactobacillus Strains

2019 ◽  
Author(s):  
Thomas J. Moutinho ◽  
Benjamin C. Neubert ◽  
Matthew L. Jenior ◽  
Maureen A. Carey ◽  
Gregory L. Medlock ◽  
...  
Keyword(s):  
Network Analysis ◽  
Metabolic Network ◽  
Health Benefits ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Metabolic Network Analysis ◽  
A Genome ◽  
Direct Interpretation ◽  
The Difference ◽  
Genome Scale

AbstractMembers of the Lactobacillus genus are frequently utilized in the probiotic industry with many species conferring demonstrated health benefits; however, these effects are largely strain-dependent. We designed a method called PROTEAN (Probabilistic Reconstruction Of constituent Anabolic Networks) to computationally analyze the genomic annotations and predicted metabolic production capabilities of 144 strains across 16 species of Lactobacillus isolated from human intestinal, oral, and vaginal body sites. Using PROTEAN we conducted a genome-scale metabolic network comparison between strains, revealing that metabolic capabilities differ by isolation site. Notably, PROTEAN does not require a well-curated genome-scale metabolic network reconstruction to provide biological insights. We found that predicted metabolic capabilities of lactobacilli isolated from the vaginal microbiota cluster separately from intestinal and oral isolates, and we also uncovered an overlap in the predicted metabolic production capabilities of intestinal and oral isolates. Using machine learning, we determined the most informative metabolic products driving the difference between predicted metabolic capabilities of intestinal, oral, and vaginal isolates. Notably, intestinal and oral isolates were predicted to have a higher likelihood of producing D-alanine, D/L-serine, and L-proline, while the vaginal isolates were distinguished by a higher predicted likelihood of producing L-arginine, citrulline, and D/L-lactate. We found the distinguishing products to be consistent with published experimental literature. This study showcases a systematic technique, PROTEAN, for comparing the predicted functional metabolic output of microbes using genome-scale metabolic network analysis and computational modeling and provides unique insight into human-associated Lactobacillus biology.ImportanceThe Lactobacillus genus has been shown to be important for human health. Lactobacilli have been isolated from human intestinal, oral, and vaginal sites. Members of the genus contribute significantly to the maintenance of vaginal health by providing colonization resistance to invading pathogens. A wide variety of clinical studies have indicated that Lactobacillus-based probiotics confer health benefits for several gut- and immune-associated diseases. Microbes interact with the human body in several ways, including the production of metabolites that influence physiology or other surrounding microbes. We have conducted a strain-level genome-scale metabolic network reconstruction analysis of human-associated Lactobacillus strains, revealing that predicted metabolic capabilities differ when comparing intestinal/oral isolate to vaginal isolates. The technique we present here allows for direct interpretation of discriminating features between the experimental groups.

scholarly journals Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

2017 ◽  
Vol 1 (Special Issue) ◽  
pp. 134-134
Author(s):  
Bharat Manna ◽  
Amit Ghosh
Keyword(s):  
Metabolic Network ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Genome Scale

scholarly journals Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides

2021 ◽  
Vol 8 ◽  
Author(s):  
Joonhoon Kim ◽  
Samuel T. Coradetti ◽  
Young-Mo Kim ◽  
Yuqian Gao ◽  
Junko Yaegashi ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Network Models ◽  
Metabolic Model ◽  
Network Reconstruction ◽  
Rhodosporidium Toruloides ◽  
Model Organisms ◽  
Omics Data ◽  
Carbon Utilization ◽  
Metabolic Network Reconstruction ◽  
Protein Mapping

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides. High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.

scholarly journals iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE

2018 ◽  
Vol 9 ◽  
Author(s):  
Charles J. Norsigian ◽  
Erol Kavvas ◽  
Yara Seif ◽  
Bernhard O. Palsson ◽  
Jonathan M. Monk
Keyword(s):  
Acinetobacter Baumannii ◽  
Metabolic Network ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Genome Scale
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