scholarly journals Tn-Core: context-specific reconstruction of core metabolic models using Tn-seq data

2017 ◽  
Author(s):  
George C diCenzo ◽  
Alessio Mengoni ◽  
Marco Fondi
Keyword(s):  
Sinorhizobium Meliloti ◽  
Metabolic Networks ◽  
De Novo ◽  
Supplementary Information ◽  
Data Sets ◽  
Microbial Cell Factories ◽  
Cell Factories ◽  
Functional Models ◽  
Metabolic Models ◽  
Context Specific

ABSTRACTMotivationTn-seq (transposon mutagenesis and sequencing) and constraint-based metabolic modelling represent highly complementary approaches. They can be used to probe the core genetic and metabolic networks underlying a biological process, revealing invaluable information for synthetic biology engineering of microbial cell factories. However, while algorithms exist for integration of –omics data sets with metabolic models, no method has been explicitly developed for integration of Tn-seq data with metabolic reconstructions.ResultsWe report the development of Tn-Core, a Matlab toolbox designed to generate gene-centric, context-specific core reconstructions consistent with experimental Tn-seq data. Extensions of this algorithm allow: i) the generation of context-specific functional models through integration of both Tn-seq and RNA-seq data; ii) to visualize redundancy in core metabolic processes; and iii) to assist in curation ofde novodraft metabolic models. The utility of Tn-Core is demonstrated primarily using aSinorhizobium melilotimodel as a case study.Availability and implementationThe software can be downloaded fromhttps://github.com/diCenzo-GC/Tn-Core. All results presented in this work have been obtained with Tn-Core v. [email protected],[email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals Modular, synthetic chromosomes as new tools for large scale engineering of metabolism

2021 ◽  
Author(s):  
Eline Postma ◽  
Else-Jasmijn Hassing ◽  
Venda Mangkusaputra ◽  
Jordi Geelhoed ◽  
Pilar de la Torre ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
Metabolic Networks ◽  
De Novo ◽  
Microbial Cell ◽  
Cell Factory ◽  
Microbial Cell Factory ◽  
Microbial Cell Factories ◽  
Cell Factories

The construction of powerful cell factories requires intensive genetic engineering for the addition of new functionalities and the remodeling of native pathways and processes. The present study demonstrates the feasibility of extensive genome reprogramming using modular, specialized de novo-assembled neochromosomes in yeast. The in vivo assembly of linear and circular neochromosomes, carrying 20 native and 21 heterologous genes, enabled the first de novo production in a microbial cell factory of anthocyanins, plant compounds with a broad range pharmacological properties. Turned into exclusive expression platforms for heterologous and essential metabolic routes, the neochromosomes mimic native chromosomes regarding mitotic and genetic stability, copy number, harmlessness for the host and editability by CRISPR/Cas9. This study paves the way for future microbial cell factories with modular genomes in which core metabolic networks, localized on satellite, specialized neochromosomes can be swapped for alternative configurations and serve as landing pads for the addition of functionalities.

scholarly journals On the inconsistent treatment of gene-protein-reaction rules in context-specific metabolic models

2019 ◽  
Vol 36 (6) ◽  
pp. 1986-1988 ◽  
Author(s):  
Miguel Ponce-de-León ◽  
Iñigo Apaolaza ◽  
Alfonso Valencia ◽  
Francisco J Planes
Keyword(s):  
Supplementary Information ◽  
Supplementary Data ◽  
Metabolic Models ◽  
Context Specific ◽  
Protein Reaction

Abstract Supplementary information: Supplementary data are available at Bioinformatics online.

scholarly journals Genome Scale Constraint-Based Metabolic Reconstruction of Propionibacterium Freudenreichii DSM 20271

2021 ◽  
Author(s):  
Mahsa Sadat Razavi Borghei ◽  
Meysam Mobasheri ◽  
Tabassom Sobati
Keyword(s):  
Metabolic Networks ◽  
Metabolic Model ◽  
Physiological Data ◽  
Metabolic Reconstruction ◽  
Modeling And Analysis ◽  
Microbial Cell Factories ◽  
Culture Optimization ◽  
Cell Factories ◽  
Functional Features ◽  
Genome Scale

Abstract Propionibacterium is an anaerobic bacterium with a history of use in the production of Swiss cheese and, more recently, several industrial bioproducts. While the use of this strain for the production of organic acids and secondary metabolites has gained growing interest, the industrial application of the strain requires further improvement in the yield and productivity of the target products. Systems modeling and analysis of metabolic networks are widely leveraged to gain holistic insights into the metabolic features of biotechnologically important strains and to devise metabolic engineering and culture optimization strategies for economically viable bioprocess development. In the present study, a high-quality genome-scale metabolic model of P. freudenreichii ssp. freudenreichii strain DSM 20271 was developed based on the strain’s genome annotation and biochemical and physiological data. The model covers the functions of 23% of the strain’s ORFs and accounts for 711 metabolic reactions and 647 unique metabolites. Literature-based reconstruction of the central metabolism and rigorous refinement of annotation data for establishing gene-protein-reaction associations renders the model a curated omic-scale knowledge base of the organism. Validation of the model against experimental data indicates that the reconstruction can capture the key structural and functional features of P. freudenreichii metabolism, including the growth rate, the pattern of flux distribution, the strain’s aerotolerance behavior, and the change in the mode of metabolic activity during the transition from an anaerobic to an aerobic growth regime. The model also includes an accurately curated pathway of cobalamin biosynthesis, which was used to examine the capacity of the strain to produce vitamin B12 precursors. Constraint-based reconstruction and analysis of the P. freudenreichii metabolic network also provided novel insights into the complexity and robustness of P. freudenreichii energy metabolism. The developed reconstruction, hence, may be used as a platform for the development of P. freudenreichii-based microbial cell factories and bioprocesses.

scholarly journals Comparative genomics study reveals Red Sea Bacillus with characteristics associated with potential microbial cell factories (MCFs)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
G. Othoum ◽  
S. Prigent ◽  
A. Derouiche ◽  
L. Shi ◽  
A. Bokhari ◽  
...  
Keyword(s):  
Red Sea ◽  
Metabolic Networks ◽  
Genomic Region ◽  
Microbial Cell ◽  
Microbial Cell Factories ◽  
Cell Factories ◽  
Ecological Features ◽  
Bacillus Paralicheniformis ◽  
Protein Secretion System ◽  
Potential Use

AbstractRecent advancements in the use of microbial cells for scalable production of industrial enzymes encourage exploring new environments for efficient microbial cell factories (MCFs). Here, through a comparison study, ten newly sequenced Bacillus species, isolated from the Rabigh Harbor Lagoon on the Red Sea shoreline, were evaluated for their potential use as MCFs. Phylogenetic analysis of 40 representative genomes with phylogenetic relevance, including the ten Red Sea species, showed that the Red Sea species come from several colonization events and are not the result of a single colonization followed by speciation. Moreover, clustering reactions in reconstruct metabolic networks of these Bacillus species revealed that three metabolic clades do not fit the phylogenetic tree, a sign of convergent evolution of the metabolism of these species in response to special environmental adaptation. We further showed Red Sea strains Bacillus paralicheniformis (Bac48) and B. halosaccharovorans (Bac94) had twice as much secreted proteins than the model strain B. subtilis 168. Also, Bac94 was enriched with genes associated with the Tat and Sec protein secretion system and Bac48 has a hybrid PKS/NRPS cluster that is part of a horizontally transferred genomic region. These properties collectively hint towards the potential use of Red Sea Bacillus as efficient protein secreting microbial hosts, and that this characteristic of these strains may be a consequence of the unique ecological features of the isolation environment.

scholarly journals A supernumerary designer chromosome for modular in vivo pathway assembly in Saccharomyces cerevisiae

2020 ◽  
Author(s):  
Eline D. Postma ◽  
Sofia Dashko ◽  
Lars van Breemen ◽  
Shannara K. Taylor Parkins ◽  
Marcel van den Broek ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genome Engineering ◽  
De Novo ◽  
Transcriptional Unit ◽  
Dna Assembly ◽  
Cellular Processes ◽  
Microbial Cell Factories ◽  
Cell Factories ◽  
Expression Platform

ABSTRACTThe construction of microbial cell factories for sustainable production of chemicals and pharmaceuticals requires extensive genome engineering. Using Saccharomyces cerevisiae, this study proposes Synthetic Chromosomes (SynChs) as orthogonal expression platforms for rewiring native cellular processes and implementing new functionalities. Capitalizing the powerful homologous recombination capability of S. cerevisiae, modular SynChs of 50 and 100 Kb were fully assembled de novo from up to 44 transcriptional-unit-sized fragments in a single transformation. These assemblies were remarkably efficient and faithful to their in silico design. SynChs made of non-coding DNA were stably replicated and segregated irrespective of their size without affecting the physiology of their host. These non-coding SynChs were successfully used as landing pad and as exclusive expression platform for the essential glycolytic pathway. This work pushes the limit of DNA assembly in S. cerevisiae and paves the way for de novo designer chromosomes as modular genome engineering platforms in S. cerevisiae.

scholarly journals De novo Biosynthesis of Tyrosol Acetate and Hydroxytyrosol Acetate from Glucose in Engineered Escherichia Coli

2021 ◽  
Author(s):  
Daoyi Guo ◽  
Xiao Fu ◽  
Yue Sun ◽  
Xun Li ◽  
Hong Pan
Keyword(s):  
Escherichia Coli ◽  
De Novo ◽  
Virgin Olive Oil ◽  
Carbon Sources ◽  
Acetate Production ◽  
E Coli ◽  
Microbial Cell Factories ◽  
Cell Factories ◽  
Alcohol Acetyltransferase ◽  
First Time

Abstract Background: Tyrosol and hydroxytyrosol derived from virgin olive oil and olives extract, have wide applications both as functional food components and as nutraceuticals. However, they have low bioavailability due to their low absorption and high metabolism in human liver and small intestine. Acetylation of tyrosol and hydroxytyrosol can effectively improve their bioavailability and thus increase their potential use in the food and cosmeceutical industries. There is no report on the bioproductin of tyrosol acetate and hydroxytyrosol acetate so far. Thus, it is of great significance to develop microbial cell factories for achieving tyrosol acetate or hydroxytyrosol acetate biosynthesis.Results: In this study, two de novo biosynthetic pathways for the production of tyrosol acetate and hydroxytyrosol acetate were constructed in Escherichia coli. First, an engineered E. coli that allows production of tyrosol from simple carbon sources was established. Four aldehyde reductases were compared, and it was found that yeaE is the best aldehyde reductase for tyrosol accumulation. Subsequently, the pathway was extended for tyrosol acetate production by further overexpression of alcohol acetyltransferase ATF1 for the conversion of tyrosol to tyrosol acetate. Finally, the pathway was further extended for hydroxytyrosol acetate production by overexpression of 4-hydroxyphenylacetate 3-hydroxylase HpaBC.Conclusion: We have successfully established the artificial biosynthetic pathway of tyrosol acetate and hydroxytyrosol acetate from fermentable sugars and demonstrated for the first time the direct fermentative production of tyrosol acetate and hydroxytyrosol acetate from glucose in engineered E. coli

scholarly journals Taxonomic weighting improves the accuracy of a gap-filling algorithm for metabolic models

2019 ◽  
Vol 36 (6) ◽  
pp. 1823-1830
Author(s):  
Wai Kit Ong ◽  
Peter E Midford ◽  
Peter D Karp
Keyword(s):  
Metabolic Networks ◽  
Metabolic Model ◽  
Error Rates ◽  
Supplementary Information ◽  
Gap Filling ◽  
Frequency Method ◽  
Metabolic Models ◽  
Genome Annotations ◽  
Taxonomic Groups ◽  
The Cost

Abstract Motivation The increasing availability of annotated genome sequences enables construction of genome-scale metabolic networks, which are useful tools for studying organisms of interest. However, due to incomplete genome annotations, draft metabolic models contain gaps that must be filled in a time-consuming process before they are usable. Optimization-based algorithms that fill these gaps have been developed, however, gap-filling algorithms show significant error rates and often introduce incorrect reactions. Results Here, we present a new gap-filling method that computes the costs of candidate gap-filling reactions from a universal reaction database (MetaCyc) based on taxonomic information. When gap-filling a metabolic model for an organism M (such as Escherichia coli), the cost for reaction R is based on the frequency with which R occurs in other organisms within the phylum of M (in this case, Proteobacteria). The assumption behind this method is that different taxonomic groups are biased toward using different metabolic reactions. Evaluation of the new gap-filler on randomly degraded variants of the EcoCyc metabolic model for E.coli showed an increase in the average F1-score to 99.0 (when using the variable weights by frequency method at the phylum level), compared to 91.0 using the previous MetaFlux gap-filler and 80.3 using a basic gap-filler. Evaluation on two other microbial metabolic models showed similar improvements. Availability and implementation The Pathway Tools software (including MetaFlux) is free for academic use and is available at http://pathwaytools.com. Additional code for reproducing the results presented here is available at www.ai.sri.com/pkarp/pubs/taxgap/supplementary.zip. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals De Novo Biosynthesis of C-Arabinosylated Flavones by Utilization of Indica Rice C-Glycosyltransferases

2021 ◽  
Author(s):  
Zhuo Chen ◽  
Yuwei Sun ◽  
Guangyi Wang ◽  
Ying Zhang ◽  
Qian Zhang ◽  
...  
Keyword(s):  
De Novo ◽  
Indica Rice ◽  
Fed Batch ◽  
Rice Varieties ◽  
E Coli ◽  
De Novo Biosynthesis ◽  
Microbial Cell Factories ◽  
Cell Factories ◽  
Fed Batch Fermentation ◽  
Heterologous Pathway

Abstract Flavone C-arabinosides/xylosides are plant-originated glycoconjugates with various bioactivities. However, the potential utility of these molecules is hindered by their low abundance in nature. Engineering biosynthesis pathway in heterologous bacterial chassis provides a sustainable source of these C-glycosides. We previously reported bifunctional C-glucosyl/C-arabinosyltransferases in Oryza sativa japonica and O. sativa indica, which influence the C-glycoside spectrum in different rice varieties. In this study, we proved the C-arabinosyltransferring activity of rice C-glycosyltransferases (CGTs) on the mono-C-glucoside substrate nothofagin, followed by taking advantage of specific CGTs and introducing heterologous UDP-pentose supply, to realize the production of eight different C-arabinosides/xylosides in recombinant E. coli. Fed-batch fermentation and precursor supplement maximized the titer of rice-originated C-arabinosides to 20~110 mg/L in an E. coli chassis. The optimized final titer of schaftoside and apigenin di-C-arabinoside reached 19.87 and 113.16 mg/L respectively. We demonstrate here the success of de novo bio-production of C-arabinosylated and C-xylosylated flavones by heterologous pathway reconstitution. These results lay a foundation for further optimal manufacture of complex flavonoid compounds in microbial cell factories.

scholarly journals SAMMI: a semi-automated tool for the visualization of metabolic networks

2019 ◽  
Vol 36 (8) ◽  
pp. 2616-2617
Author(s):  
Andre Schultz ◽  
Rehan Akbani
Keyword(s):  
Large Scale ◽  
Metabolic Networks ◽  
Source Code ◽  
Supplementary Information ◽  
Network Partitioning ◽  
Web Based ◽  
Constraint Based Modeling ◽  
Context Specific ◽  
Genome Scale ◽  
Automated Tool

Abstract Summary Here we present a browser-based Semi-Automated Metabolic Map Illustrator (SAMMI) for the visualization of metabolic networks. While automated features allow for easy network partitioning, navigation, and node positioning, SAMMI also offers a wide array of manual map editing features. This combination allows for fast, context-specific visualization of metabolic networks as well as the development of standardized, large-scale, visually appealing maps. The implementation of SAMMI with popular constraint-based modeling toolboxes also allows for effortless visualization of simulation results of genome-scale metabolic models. Availability and implementation SAMMI has been implemented as a standalone web-based tool and as plug-ins for the COBRA and COBRApy toolboxes. SAMMI and its COBRA plugins are available under the GPL 3.0 license and are available along with documentation, tutorials, and source code at www.SammiTool.com. Supplementary information Supplementary data are available at Bioinformatics online.

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