CARMEN - Comparative Analysis and in silico Reconstruction of organism-specific MEtabolic Networks

Schneider, Jessica; Vorhölter, Frank-Jörg; Trost, Eva; Blom, Jochen; Musa, Yaarub; Neuweger, Heiko; Niehaus, Karsten; Schatschneider, Sarah; Tauch, Andreas; Goesmann, Alexander

doi:10.4238/vol9-3gmr901

Cited by 19 publications

(18 citation statements)

References 43 publications

(40 reference statements)

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“…Functional characterization of the predicted proteins was performed by automated searches in public databases, including Swiss-Prot, TrEMBL, Pfam, TIGRFAM, KEGG, COG, CDD, and Interpro (49). Metabolic pathways were annotated by means of in silico reconstructions of metabolic networks with the software CARMEN using metabolic pathway information from the KEGG database and manually curated SBML templates (64). The predicted C. diphtheriae proteins were mapped onto the SBML templates using bidirectional best BLASTP hits and the scoring matrix BLOSUM62 with an E-value cutoff of 1 ϫ 10 Ϫ10 .…”

Section: Methodsmentioning

confidence: 99%

Pangenomic Study of Corynebacterium diphtheriae That Provides Insights into the Genomic Diversity of Pathogenic Isolates from Cases of Classical Diphtheria, Endocarditis, and Pneumonia

et al. 2012

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Corynebacterium diphtheriae is one of the most prominent human pathogens and the causative agent of the communicable disease diphtheria. The genomes of 12 strains isolated from patients with classical diphtheria, endocarditis, and pneumonia were completely sequenced and annotated. Including the genome of C. diphtheriae NCTC 13129, we herewith present a comprehensive comparative analysis of 13 strains and the first characterization of the pangenome of the species C. diphtheriae . Comparative genomics showed extensive synteny and revealed a core genome consisting of 1,632 conserved genes. The pangenome currently comprises 4,786 protein-coding regions and increases at an average of 65 unique genes per newly sequenced strain. Analysis of prophages carrying the diphtheria toxin gene tox revealed that the toxoid vaccine producer C. diphtheriae Park-Williams no. 8 has been lysogenized by two copies of the ω tox + phage, whereas C. diphtheriae 31A harbors a hitherto-unknown tox + corynephage. DNA binding sites of the tox -controlling regulator DtxR were detected by genome-wide motif searches. Comparative content analysis showed that the DtxR regulons exhibit marked differences due to gene gain, gene loss, partial gene deletion, and DtxR binding site depletion. Most predicted pathogenicity islands of C. diphtheriae revealed characteristics of horizontal gene transfer. The majority of these islands encode subunits of adhesive pili, which can play important roles in adhesion of C. diphtheriae to different host tissues. All sequenced isolates contain at least two pilus gene clusters. It appears that variation in the distributed genome is a common strategy of C. diphtheriae to establish differences in host-pathogen interactions.

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Section: Methodsmentioning

confidence: 99%

Pangenomic Study of Corynebacterium diphtheriae That Provides Insights into the Genomic Diversity of Pathogenic Isolates from Cases of Classical Diphtheria, Endocarditis, and Pneumonia

et al. 2012

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“…This restricted its usefulness as a foundation for the mathematical models that underlie computational simulations of metabolic flux. Hence, data incorporated in this network were re-used to generate an independent large-scale metabolic network [43] using a bottom-up approach with CARMEN software [199]. Following manual revision, this large-scale metabolic network was suitable for obtaining metabolic models for the simulation of metabolic fluxes by flux balance analysis (FBA) or 13 C metabolic flux analysis (see below) (Fig.…”

Section: Reconstruction Of the Metabolic Networkmentioning

confidence: 99%

“…Specialized tools facilitate the genome-based interpretation of microarray-based transcriptome data (d; EMMA; [129]), proteome data (e; QuPE; [172]), and gas chromatography-mass spectrometry (GC-MS)-based metabolome data (f; MeltDB; [181]). Recently, in addition, the ALLocator software (g) became available for liquid chromatography (LC)-MS-based metabolite analyses [184], as well as applications for enhanced data visualization (h; ProMeTra; [172]) and for the automated generation of metabolic networks in Systems Biology Markup Language (SBML) format (i; CARMEN; [199]). For systems biology, further third-party software applications have been used, which are depicted in the upper part of the figure by symbols with light grey shading.…”

Section: Genomic Basicsmentioning

confidence: 99%

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Systems and synthetic biology perspective of the versatile plant-pathogenic and polysaccharide-producing bacterium Xanthomonas campestris

et al. 2017

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Bacteria of the genus Xanthomonas are a major group of plant pathogens. They are hazardous to important crops and closely related to human pathogens. Being collectively a major focus of molecular phytopathology, an increasing number of diverse and intricate mechanisms are emerging by which they communicate, interfere with host signalling and keep competition at bay. Interestingly, they are also biotechnologically relevant polysaccharide producers. Systems biotechnology techniques have revealed their central metabolism and a growing number of remarkable features. Traditional analyses of Xanthomonas metabolism missed the Embden-Meyerhof-Parnas pathway (glycolysis) as being a route by which energy and molecular building blocks are derived from glucose. As a consequence of the emerging full picture of their metabolism process, xanthomonads were discovered to have three alternative catabolic pathways and they use an unusual and reversible phosphofructokinase as a key enzyme. In this review, we summarize the synthetic and systems biology methods and the bioinformatics tools applied to reconstruct their metabolic network and reveal the dynamic fluxes within their complex carbohydrate metabolism. This is based on insights from omics disciplines; in particular, genomics, transcriptomics, proteomics and metabolomics. Analysis of high-throughput omics data facilitates the reconstruction of organism-specific large-and genome-scale metabolic networks. Reconstructed metabolic networks are fundamental to the formulation of metabolic models that facilitate the simulation of actual metabolic activities under specific environmental conditions. SYSTEMS BIOLOGYIn recent years, systems and synthetic biology have substantially increased our understanding of many processes in life sciences at molecular and cellular levels [1][2][3]. Systems biology intends to understand the cell from a system-wide perspective. For over 100 years, life sciences have aimed at elucidating the details of molecular processes in organisms. In systems biology, scientists have started to inter-relate this data on a large scale in order to analyse the interactions of all elements [4,5], and thus initiate the decoding of entire systems, aiming at their quantitative understanding. This became possible with the development of high-throughput techniques associated with diverse computational methods and the availability of faster computing. Fundamental highthroughput methods are now routinely available in the fields of genomics, transcriptomics, metabolomics and proteomics, while additional specialized branches of omics disciplines have been developed, such as lipidomics [6][7][8], glycomics [9][10][11] and 13 C fluxomics [12,13].

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“…The transcriptional regulatory subnetwork was arranged into five hierarchical layers , and the metabolic subnetwork presented a clear bow-tie structure (Jiang et al 2012). In silico reconstructions of metabolic networks in Corynebacterium species can be performed almost automatically with the software tool CARMEN (Schneider et al 2010). This tool supports the visualization of metabolic networks based on pathway information from the KEGG database or from user-defined templates and supports the interpretation of genome data in a functional context.…”

Section: Metabolic Pathways and Metabolismmentioning

confidence: 99%

The Family Corynebacteriaceae

Tauch

Sandbote

2014

The Prokaryotes

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CARMEN - Comparative Analysis and in silico Reconstruction of organism-specific MEtabolic Networks

Cited by 19 publications

References 43 publications

Pangenomic Study of Corynebacterium diphtheriae That Provides Insights into the Genomic Diversity of Pathogenic Isolates from Cases of Classical Diphtheria, Endocarditis, and Pneumonia

Pangenomic Study of Corynebacterium diphtheriae That Provides Insights into the Genomic Diversity of Pathogenic Isolates from Cases of Classical Diphtheria, Endocarditis, and Pneumonia

Systems and synthetic biology perspective of the versatile plant-pathogenic and polysaccharide-producing bacterium Xanthomonas campestris

The Family Corynebacteriaceae

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