scholarly journals DEMETER: Efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations

Author(s):  
Almut Heinken ◽  
Stefanía Magnúsdóttir ◽  
Ronan M T Fleming ◽  
Ines Thiele

Abstract Motivation Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results We developed DEMETER, a COBRA Toolbox extension, that enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data, and refinement of pathways based on manually refined genome annotations. Availability DEMETER and tutorials are freely available at https://github.com/opencobra.

Parasitology ◽  
2015 ◽  
Vol 143 (1) ◽  
pp. 1-17 ◽  
Author(s):  
THOMAS J. TEMPLETON ◽  
ARNAB PAIN

SUMMARYThe recent completion of high-coverage draft genome sequences for several alveolate protozoans – namely, the chromerids, Chromera velia and Vitrella brassicaformis; the perkinsid Perkinsus marinus; the apicomplexan, Gregarina niphandrodes, as well as high coverage transcriptome sequence information for several colpodellids, allows for new genome-scale comparisons across a rich landscape of apicomplexans and other alveolates. Genome annotations can now be used to help interpret fine ultrastructure and cell biology, and guide new studies to describe a variety of alveolate life strategies, such as symbiosis or free living, predation, and obligate intracellular parasitism, as well to provide foundations to dissect the evolutionary transitions between these niches. This review focuses on the attempt to identify extracellular proteins which might mediate the physical interface of cell–cell interactions within the above life strategies, aided by annotation of the repertoires of predicted surface and secreted proteins encoded within alveolate genomes. In particular, we discuss what descriptions of the predicted extracellular proteomes reveal regarding a hypothetical last common ancestor of a pre-apicomplexan alveolate – guided by ultrastructure, life strategies and phylogenetic relationships – in an attempt to understand the evolution of obligate parasitism in apicomplexans.


2017 ◽  
Author(s):  
Bernat Gel ◽  
Eduard Serra

AbstractMotivationData visualization is a crucial tool for data exploration, analysis and interpretation. For the visualization of genomic data there lacks a tool to create customizable non-circular plots of whole genomes from any species.ResultsWe have developed karyoploteR, an R/Bioconductor package to create linear chromosomal representations of any genome with genomic annotations and experimental data plotted along them. Plot creation process is inspired in R base graphics, with a main function creating karyoplots with no data and multiple additional functions, including custom functions written by the end-user, adding data and other graphical elements. This approach allows the creation of highly customizable plots from arbitrary data with complete freedom on data positioning and representation.AvailabilitykaryoploteR is released under Artistic-2.0 License. Source code and documentation are freely available through Bioconductor (http://www.bioconductor.org/packages/karyoploteR)[email protected]


2021 ◽  
Vol 118 (30) ◽  
pp. e2102344118
Author(s):  
Hao Wang ◽  
Jonathan L. Robinson ◽  
Pinar Kocabas ◽  
Johan Gustafsson ◽  
Mihail Anton ◽  
...  

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer’s disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.


2019 ◽  
Vol 15 (4) ◽  
pp. e1006971 ◽  
Author(s):  
Jean-Christophe Lachance ◽  
Colton J. Lloyd ◽  
Jonathan M. Monk ◽  
Laurence Yang ◽  
Anand V. Sastry ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Javad Aminian-Dehkordi ◽  
Seyyed Mohammad Mousavi ◽  
Arezou Jafari ◽  
Ivan Mijakovic ◽  
Sayed-Amir Marashi

AbstractBacillus megaterium is a microorganism widely used in industrial biotechnology for production of enzymes and recombinant proteins, as well as in bioleaching processes. Precise understanding of its metabolism is essential for designing engineering strategies to further optimize B. megaterium for biotechnology applications. Here, we present a genome-scale metabolic model for B. megaterium DSM319, iJA1121, which is a result of a metabolic network reconciliation process. The model includes 1709 reactions, 1349 metabolites, and 1121 genes. Based on multiple-genome alignments and available genome-scale metabolic models for other Bacillus species, we constructed a draft network using an automated approach followed by manual curation. The refinements were performed using a gap-filling process. Constraint-based modeling was used to scrutinize network features. Phenotyping assays were performed in order to validate the growth behavior of the model using different substrates. To verify the model accuracy, experimental data reported in the literature (growth behavior patterns, metabolite production capabilities, metabolic flux analysis using 13C glucose and formaldehyde inhibitory effect) were confronted with model predictions. This indicated a very good agreement between in silico results and experimental data. For example, our in silico study of fatty acid biosynthesis and lipid accumulation in B. megaterium highlighted the importance of adopting appropriate carbon sources for fermentation purposes. We conclude that the genome-scale metabolic model iJA1121 represents a useful tool for systems analysis and furthers our understanding of the metabolism of B. megaterium.


Author(s):  
Charles J Norsigian ◽  
Neha Pusarla ◽  
John Luke McConn ◽  
James T Yurkovich ◽  
Andreas Dräger ◽  
...  

Abstract The BiGG Models knowledge base (http://bigg.ucsd.edu) is a centralized repository for high-quality genome-scale metabolic models. For the past 12 years, the website has allowed users to browse and search metabolic models. Within this update, we detail new content and features in the repository, continuing the original effort to connect each model to genome annotations and external databases as well as standardization of reactions and metabolites. We describe the addition of 31 new models that expand the portion of the phylogenetic tree covered by BiGG Models. We also describe new functionality for hosting multi-strain models, which have proven to be insightful in a variety of studies centered on comparisons of related strains. Finally, the models in the knowledge base have been benchmarked using Memote, a new community-developed validator for genome-scale models to demonstrate the improving quality and transparency of model content in BiGG Models.


2019 ◽  
Author(s):  
Laura Avino Esteban ◽  
Lyubov R Lonishin ◽  
Daniil Bobrovskiy ◽  
Gregory Leleytner ◽  
Natalya S Bogatyreva ◽  
...  

Abstract Motivation Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a “combinatorially complete dataset”. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. Results We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199,847,053 unique combinatorially complete genotype combinations of dimensionality ranging from two to twelve. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data. Availability https://github.com/ivankovlab/HypercubeME.git Supplementary information Supplementary data are available at Bioinformatics online.


2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  

Abstract Background Lactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data. Results A genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden–Meyerhof–Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden–Meyerhof–Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies. Conclusion We have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.


2019 ◽  
Vol 8 (16) ◽  
Author(s):  
Yane F. Neves ◽  
Samuel A. Santos ◽  
Lúcio M. S. Guimarães ◽  
Pedro M. P. Vidigal ◽  
Jorge L. Badel ◽  
...  

Here, we report the annotated draft genome sequence of Xanthomonas axonopodis pv. eucalyptorum pathotype strain LPF602 (synonym Xanthomonas axonopodis BSC45a), isolated from eucalypt leaves showing bacterial blight symptoms in Brazil. The availability of these genomic data will help improve the understanding of the evolution and molecular mechanisms involved in the pathogenesis of this microorganism.


2015 ◽  
Vol 28 (3) ◽  
pp. 298-309 ◽  
Author(s):  
Alyssa Burkhardt ◽  
Alex Buchanan ◽  
Jason S. Cumbie ◽  
Elizabeth A. Savory ◽  
Jeff H. Chang ◽  
...  

Pseudoperonospora cubensis is an obligate pathogen and causative agent of cucurbit downy mildew. To help advance our understanding of the pathogenicity of P. cubensis, we used RNA-Seq to improve the quality of its reference genome sequence. We also characterized the RNA-Seq dataset to inventory transcript isoforms and infer alternative splicing during different stages of its development. Almost half of the original gene annotations were improved and nearly 4,000 previously unannotated genes were identified. We also demonstrated that approximately 24% of the expressed genome and nearly 55% of the intron-containing genes from P. cubensis had evidence for alternative splicing. Our analyses revealed that intron retention is the predominant alternative splicing type in P. cubensis, with alternative 5′- and alternative 3′-splice sites occurring at lower frequencies. Representatives of the newly identified genes and predicted alternatively spliced transcripts were experimentally validated. The results presented herein highlight the utility of RNA-Seq for improving draft genome annotations and, through this approach, we demonstrate that alternative splicing occurs more frequently than previously predicted. In total, the current study provides evidence that alternative splicing plays a key role in transcriptome regulation and proteome diversification in plant-pathogenic oomycetes.


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