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genome scale metabolic modeling

Amornpan Klanchui, Nachon Raethong, Peerada Prommeenate, Wanwipa Vongsangnak, Asawin Meechai
Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored...
October 26, 2016: Advances in Biochemical Engineering/biotechnology
W S Hambright, Jie Deng, James M Tiedje, Ingrid Brettar, Jorge L M Rodrigues
In bacterial populations, subtle expressional differences may promote ecological specialization through the formation of distinct ecotypes. In a barrier-free habitat, this process most likely precedes population divergence and may predict speciation events. To examine this, we used four sequenced strains of the bacterium Shewanella baltica, OS155, OS185, OS195, and OS223, as models to assess transcriptional variation and ecotype formation within a prokaryotic population. All strains were isolated from different depths throughout a water column of the Baltic Sea, occupying different ecological niches characterized by various abiotic parameters...
September 2016: MSphere
Xianhua Li, Yanhong Liu, Qian Jia, Virginia LaMacchia, Kathryn O'Donoghue, Zuyi Huang
Oleuropein and its hydrolysis products are olive phenolic compounds that have antimicrobial effects on a variety of pathogens, with the potential to be utilized in food and pharmaceutical products. While the existing research is mainly focused on individual genes or enzymes that are regulated by oleuropein for antimicrobial activities, little work has been done to integrate intracellular genes, enzymes and metabolic reactions for a systematic investigation of antimicrobial mechanism of oleuropein. In this study, the first genome-scale modeling method was developed to predict the system-level changes of intracellular metabolism triggered by oleuropein in Staphylococcus aureus, a common food-borne pathogen...
October 22, 2016: Journal of Industrial Microbiology & Biotechnology
Amit Ghosh, David Ando, Jennifer Gin, Weerawat Runguphan, Charles Denby, George Wang, Edward E K Baidoo, Chris Shymansky, Jay D Keasling, Héctor García Martín
Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined (13)C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption...
2016: Frontiers in Bioengineering and Biotechnology
Matthew A Richards, Thomas J Lie, Juan Zhang, Stephen W Ragsdale, John A Leigh, Nathan D Price
: Hydrogenotrophic methanogenesis occurs in multiple environments ranging from the intestinal tracts of animals to anaerobic sediments and hot springs. Energy conservation in hydrogenotrophic methanogens was long a mystery; only within the last decade, it was reported that net energy conservation for growth depends on electron bifurcation. In this work we focus on Methanococcus maripaludis, a well-studied hydrogenotrophic marine methanogen. To better understand hydrogenotrophic methanogenesis and compare it with methylotrophic methanogenesis that utilizes oxidative phosphorylation rather than electron bifurcation, we have built iMR539, a genome scale metabolic reconstruction that accounts for 539 of the 1722 protein-coding genes of M...
October 10, 2016: Journal of Bacteriology
Rémi Peyraud, Ludovic Cottret, Lucas Marmiesse, Jérôme Gouzy, Stéphane Genin
Bacterial pathogenicity relies on a proficient metabolism and there is increasing evidence that metabolic adaptation to exploit host resources is a key property of infectious organisms. In many cases, colonization by the pathogen also implies an intensive multiplication and the necessity to produce a large array of virulence factors, which may represent a significant cost for the pathogen. We describe here the existence of a resource allocation trade-off mechanism in the plant pathogen R. solanacearum. We generated a genome-scale reconstruction of the metabolic network of R...
October 2016: PLoS Pathogens
Jahangir Imam, Puneet K Singh, Pratyoosh Shukla
Deciphering plant-microbe interactions is a promising aspect to understand the benefits and the pathogenic effect of microbes and crop improvement. The advancement in sequencing technologies and various 'omics' tool has impressively accelerated the research in biological sciences in this area. The recent and ongoing developments provide a unique approach to describing these intricate interactions and test hypotheses. In the present review, we discuss the role of plant-pathogen interaction in crop improvement...
2016: Frontiers in Microbiology
Jin Chen, Michael A Henson
Synthesis gas fermentation is one of the most promising routes to convert synthesis gas (syngas; mainly comprised of H2 and CO) to renewable liquid fuels and chemicals by specialized bacteria. The most commonly studied syngas fermenting bacterium is Clostridium ljungdahlii, which produces acetate and ethanol as its primary metabolic byproducts. Engineering of C. ljungdahlii metabolism to overproduce ethanol, enhance the synthesize of the native byproducts lactate and 2,3-butanediol, and introduce the synthesis of non-native products such as butanol and butyrate has substantial commercial value...
October 5, 2016: Metabolic Engineering
Daniel Machado, Markus J Herrgård, Isabel Rocha
Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene...
October 2016: PLoS Computational Biology
Ewelina Stefanovic, Gerald Fitzgerald, Olivia McAuliffe
The Lactobacillus genus represents the largest and most diverse genera of all the lactic acid bacteria (LAB), encompassing species with applications in industrial, biotechnological and medical fields. The increasing number of available Lactobacillus genome sequences has allowed understanding of genetic and metabolic potential of this LAB group. Pangenome and core genome studies are available for numerous species, demonstrating the plasticity of the Lactobacillus genomes and providing the evidence of niche adaptability...
February 2017: Food Microbiology
Hongzhong Lu, Weiqiang Cao, Liming Ouyang, Jianye Xia, Mingzhi Huang, Ju Chu, Yingping Zhuang, Siliang Zhang, Henk Noorman
Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology...
October 3, 2016: Biotechnology and Bioengineering
Jonathan M Monk, Anna Koza, Miguel A Campodonico, Daniel Machado, Jose Miguel Seoane, Bernhard O Palsson, Markus J Herrgård, Adam M Feist
Escherichia coli strains are widely used in academic research and biotechnology. New technologies for quantifying strain-specific differences and their underlying contributing factors promise greater understanding of how these differences significantly impact physiology, synthetic biology, metabolic engineering, and process design. Here, we quantified strain-specific differences in seven widely used strains of E. coli (BL21, C, Crooks, DH5a, K-12 MG1655, K-12 W3110, and W) using genomics, phenomics, transcriptomics, and genome-scale modeling...
September 21, 2016: Cell Systems
Sol Choi, Hyun Uk Kim, Tae Yong Kim, Sang Yup Lee
To address climate change and environmental problems, it is becoming increasingly important to establish biorefineries for the production of chemicals from renewable non-food biomass. Here we report the development of Escherichia coli strains capable of overproducing a four-carbon platform chemical 4-hybroxybutyric acid (4-HB). Because 4-HB production is significantly affected by aeration level, genome-scale metabolic model-based engineering strategies were designed under aerobic and microaerobic conditions with emphasis on oxidative/reductive TCA branches and glyoxylate shunt...
September 20, 2016: Metabolic Engineering
Laurence Yang, Ding Ma, Ali Ebrahim, Colton J Lloyd, Michael A Saunders, Bernhard O Palsson
BACKGROUND: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. RESULTS: Here, we address these computational challenges...
2016: BMC Bioinformatics
Abdellah Tebani, Carlos Afonso, Stéphane Marret, Soumeya Bekri
The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations...
2016: International Journal of Molecular Sciences
Ana Sofia Carvalho, Rune Matthiesen
DNA-based technologies such as RNAi, chemical-genetic profiling, or gene expression profiling by DNA microarrays combined with other biochemical methods are established strategies for surveying drug mechanisms. Such approaches can provide mechanistic information on how drugs act and affect cellular pathways. By studying how cancer cells compensate for the drug treatment, novel targets used in a combined treatment can be designed. Furthermore, toxicity effects on cells not targeted can be obtained on a molecular level...
2016: Methods in Molecular Biology
Poonam Phalak, Jin Chen, Ross P Carlson, Michael A Henson
BACKGROUND: Chronic wounds are often colonized by consortia comprised of different bacterial species growing as biofilms on a complex mixture of wound exudate. Bacteria growing in biofilms exhibit phenotypes distinct from planktonic growth, often rendering the application of antibacterial compounds ineffective. Computational modeling represents a complementary tool to experimentation for generating fundamental knowledge and developing more effective treatment strategies for chronic wound biofilm consortia...
2016: BMC Systems Biology
R Adam Thompson, Sanjeev Dahal, Sergio Garcia, Intawat Nookaew, Cong T Trinh
BACKGROUND: Clostridium thermocellum is a gram-positive thermophile that can directly convert lignocellulosic material into biofuels. The metabolism of C. thermocellum contains many branches and redundancies which limit biofuel production, and typical genetic techniques are time-consuming. Further, the genome sequence of a genetically tractable strain C. thermocellum DSM 1313 has been recently sequenced and annotated. Therefore, developing a comprehensive, predictive, genome-scale metabolic model of DSM 1313 is desired for elucidating its complex phenotypes and facilitating model-guided metabolic engineering...
2016: Biotechnology for Biofuels
Xun Yue, Xing Guo Li, Xin-Qi Gao, Xiang Yu Zhao, Yu Xiu Dong, Chao Zhou
BACKGROUND: Phytohormone synergies and signaling interdependency are important topics in plant developmental biology. Physiological and genetic experimental evidence for phytohormone crosstalk has been accumulating and a genome-scale enzyme correlation model representing the Arabidopsis metabolic pathway has been published. However, an integrated molecular characterization of phytohormone crosstalk is still not available. RESULTS: A novel modeling methodology and advanced computational approaches were used to construct an enzyme-based Arabidopsis phytohormone crosstalk network (EAPCN) at the biosynthesis level...
2016: BMC Systems Biology
Max Sajitz-Hermstein, Nadine Töpfer, Sabrina Kleessen, Alisdair R Fernie, Zoran Nikoloski
MOTIVATION: Understanding the rerouting of metabolic reaction fluxes upon perturbations has the potential to link changes in molecular state of a cellular system to alteration of growth. Yet, differential flux profiling on a genome-scale level remains one of the biggest challenges in systems biology. This is particularly relevant in plants, for which fluxes in autotrophic growth necessitate time-consuming instationary labeling experiments and costly computations, feasible for small-scale networks...
September 1, 2016: Bioinformatics
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