scholarly journals Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Prasansah Shrestha ◽  
Min-Su Kim ◽  
Ermal Elbasani ◽  
Jeong-Dong Kim ◽  
Tae-Jin Oh
Keyword(s):  
Metabolic Pathway ◽  
Pathway Database ◽  
Entire Genome ◽  
Trehalose Synthase ◽  
Kegg Pathway Database ◽  
Bioinformatics Tools ◽  
Online Databases ◽  
Alternative Carbon Source ◽  
Living Organisms ◽  
Pathway Databases

Abstract Background Metabolism including anabolism and catabolism is a prerequisite phenomenon for all living organisms. Anabolism refers to the synthesis of the entire compound needed by a species. Catabolism refers to the breakdown of molecules to obtain energy. Many metabolic pathways are undisclosed and many organism-specific enzymes involved in metabolism are misplaced. When predicting a specific metabolic pathway of a microorganism, the first and foremost steps is to explore available online databases. Among many online databases, KEGG and MetaCyc pathway databases were used to deduce trehalose metabolic network for bacteria Variovorax sp. PAMC28711. Trehalose, a disaccharide, is used by the microorganism as an alternative carbon source. Results While using KEGG and MetaCyc databases, we found that the KEGG pathway database had one missing enzyme (maltooligosyl-trehalose synthase, EC 5.4.99.15). The MetaCyc pathway database also had some enzymes. However, when we used RAST to annotate the entire genome of Variovorax sp. PAMC28711, we found that all enzymes that were missing in KEGG and MetaCyc databases were involved in the trehalose metabolic pathway. Conclusions Findings of this study shed light on bioinformatics tools and raise awareness among researchers about the importance of conducting detailed investigation before proceeding with any further work. While such comparison for databases such as KEGG and MetaCyc has been done before, it has never been done with a specific microbial pathway. Such studies are useful for future improvement of bioinformatics tools to reduce limitations.

Using metabolic pathway databases for functional annotation

1998 ◽  
Vol 14 (8) ◽  
pp. 332-333 ◽  
Author(s):  
Michael Y Galperin ◽  
Steven E Brenner
Keyword(s):  
Metabolic Pathway ◽  
Functional Annotation ◽  
Pathway Databases

scholarly journals Simulation and visualization of multiple KEGG pathways using BioNSi

F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 2120
Author(s):  
Adva Yeheskel ◽  
Adam Reiter ◽  
Metsada Pasmanik-Chor ◽  
Amir Rubinstein
Keyword(s):  
Network Simulation ◽  
Expression Data ◽  
Proof Of Concept ◽  
Pathway Database ◽  
Simulation Tools ◽  
Kegg Pathways ◽  
Kegg Pathway Database ◽  
Disease Condition ◽  
Inflammatory Bowel ◽  
Experimental Expression

Motivation: Many biologists are discouraged from using network simulation tools because these require manual, often tedious network construction. This situation calls for building new tools or extending existing ones with the ability to import biological pathways previously deposited in databases and analyze them, in order to produce novel biological insights at the pathway level. Results: We have extended a network simulation tool (BioNSi), which now allows merging of multiple pathways from the KEGG pathway database into a single, coherent network, and visualizing its properties. Furthermore, the enhanced tool enables loading experimental expression data into the network and simulating its dynamics under various biological conditions or perturbations. As a proof of concept, we tested two sets of published experimental data, one related to inflammatory bowel disease condition and the other to breast cancer treatment. We predict some of the major observations obtained following these laboratory experiments, and provide new insights that may shed additional light on these results. Tool requirements: Cytoscape 3.x, JAVA 8 Availability: The tool is freely available at http://bionsi.wix.com/bionsi, where a complete user guide and a step-by-step manual can also be found.

scholarly journals Metabolic pathway databases and model repositories

2017 ◽  
Vol 6 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Abraham A. Labena ◽  
Yi-Zhou Gao ◽  
Chuan Dong ◽  
Hong-li Hua ◽  
Feng-Biao Guo
Keyword(s):  
Metabolic Pathway ◽  
Pathway Databases

scholarly journals Systems Glycobiology: Past, Present, and Future

2020 ◽  
Author(s):  
Songül Yaşar Yıldız
Keyword(s):  
Systems Biology ◽  
Computational Modeling ◽  
Structure Function ◽  
Leading Edge ◽  
Research Area ◽  
Basic Knowledge ◽  
Bioinformatics Tools ◽  
Wet Lab ◽  
Living Organisms ◽  
The Impact

Glycobiology is a glycan-based field of study that focuses on the structure, function, and biology of carbohydrates, and glycomics is a sub-study of the field of glycobiology that aims to define structure/function of glycans in living organisms. With the popularity of the glycobiology and glycomics, application of computational modeling expanded in the scientific area of glycobiology over the last decades. The recent availability of progressive Wet-Lab methods in the field of glycobiology and glycomics is promising for the impact of systems biology on the research area of the glycome, an emerging field that is termed “systems glycobiology.” This chapter will summarize the up-to-date leading edge in the use of bioinformatics tools in the field of glycobiology. The chapter provides basic knowledge both for glycobiologists interested in the application of bioinformatics tools and scientists of computational biology interested in studying the glycome.

scholarly journals miRNAs Copy Number Variations repertoire as hallmark indicator of cancer species predisposition

2021 ◽  
Author(s):  
Chiara Vischioni ◽  
Fabio Bove ◽  
Federica Mandreoli ◽  
Riccardo Martoglia ◽  
Valentino Pisi ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Copy Number ◽  
Molecular Mechanisms ◽  
Gene Families ◽  
Copy Number Variations ◽  
Gene Copy ◽  
Cancer Resistance ◽  
Entire Genome ◽  
Significant Gene ◽  
Living Organisms

Aging is one of the hallmarks of multiple human diseases, including cancer. However, the molecular mechanisms associated with high longevity and low cancer incidence percentages characterizing long-living organisms have not been fully understood yet. In this context, we hypothesized that variations in the number of copies (CNVs) of specific genes may protect some species from cancer onset. Based on the statistical comparison of gene copy numbers within the genomes of cancer -prone and -resistant organisms, we identified novel gene targets linked to the tumor predisposition of a species, such as CD52, SAT1 and SUMO protein family members. Furthermore, for the first time, we were able to discover that, considering the entire genome copy number landscape of a species, microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. However, their roles in ageing and cancer resistance from a comparative perspective remains largely unknown. To this end, we identified through bioinformatics analysis, several alterations in miRNAs copy number patterns, represented by duplication of miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31 among others. Therefore, our analysis provides the first evidence that an altered copy number miRNAs signature is able to statistically discriminate species more susceptible to cancer than those that are tumor resistant, helping researchers to discover new possible therapeutic targets involved in tumor predisposition.

scholarly journals Meta-Analysis of Differential miRNA Expression after Bariatric Surgery

2019 ◽  
Vol 8 (8) ◽  
pp. 1220 ◽  
Author(s):  
Gladys Langi ◽  
Lukasz Szczerbinski ◽  
Adam Kretowski
Keyword(s):  
Bariatric Surgery ◽  
Target Genes ◽  
Web Of Science ◽  
Kegg Pathway ◽  
Meta Analysis ◽  
Obese Patients ◽  
Pathway Database ◽  
Efficient Treatment ◽  
Kegg Pathway Database ◽  
Before And After

Bariatric surgery is an efficient treatment for weight loss in obese patients and for resolving obesity comorbidities. However, the mechanisms behind these outcomes are unclear. Recent studies have indicated significant alterations in the transcriptome after surgery, specifically in the differential expression of microRNAs. In order to summarize the recent findings, we conducted a systematic summary of studies comparing microRNA expression levels before and after surgery. We identified 17 animal model and human studies from four databases (Ovid, Scopus, Web of Science, and PubMed) to be enrolled in this meta-analysis. From these studies, we identified 14 miRNAs which had the same direction of modulation of their expression after surgery in at least two studies (downregulated: hsa-miR-93-5p, hsa-miR-106b-5p, hsa-let-7b-5p, hsa-let-7i-5p, hsa-miR-16-5p, hsa-miR-19b-3p, hsa-miR-92a-3p, hsa-miR-222-3p, hsa-miR-142-3p, hsa-miR-140-5p, hsa-miR-155-5p, rno-miR-320-3p; upregulated: hsa-miR-7-5p, hsa-miR-320c). Pathway analysis for these miRNAs was done using database resources (DIANA-TarBase and KEGG pathway database) and their predicted target genes were discussed in relation with obesity and its comorbidities. Discrepancies in study design, such as miRNA source, bariatric surgery type, time of observation after surgery, and miRNA profiling methods, were also discussed.

Integration of metabolic pathway database based on similarity derivation

2011 ◽  
Vol 31 (4) ◽  
pp. 882-884
Author(s):  
Li-hua YUE ◽  
Qi-zhou WANG ◽  
Rong-feng CAI
Keyword(s):  
Metabolic Pathway ◽  
Pathway Database

Chemoinformatics on Metabolic Pathways

2011 ◽  
pp. 318-339
Author(s):  
Masahiro Hattori ◽  
Masaaki Kotera
Keyword(s):  
Metabolic Pathway ◽  
Chemical Space ◽  
Research Area ◽  
Chemical Information ◽  
Prediction System ◽  
Future Directions ◽  
Heterogeneous Information ◽  
Research Areas ◽  
Living Organisms ◽  
Product Pair

Chemical genomics is one of the cutting-edge research areas in the post-genomic era, which requires a sophisticated integration of heterogeneous information, i.e., genomic and chemical information. Enzymes play key roles for dynamic behavior of living organisms, linking information in the chemical space and genomic space. In this chapter, the authors report our recent efforts in this area, including the development of a similarity measure between two chemical compounds, a prediction system of a plausible enzyme for a given substrate and product pair, and two different approaches to predict the fate of a given compound in a metabolic pathway. General problems and possible future directions are also discussed, in hope to attract more activities from many researchers in this research area.

Chemoinformatics on Metabolic Pathways

2013 ◽  
pp. 986-1009
Author(s):  
Masahiro Hattori ◽  
Masaaki Kotera
Keyword(s):  
Metabolic Pathway ◽  
Chemical Space ◽  
Research Area ◽  
Chemical Information ◽  
Prediction System ◽  
Future Directions ◽  
Heterogeneous Information ◽  
Research Areas ◽  
Living Organisms ◽  
Product Pair

Chemical genomics is one of the cutting-edge research areas in the post-genomic era, which requires a sophisticated integration of heterogeneous information, i.e., genomic and chemical information. Enzymes play key roles for dynamic behavior of living organisms, linking information in the chemical space and genomic space. In this chapter, the authors report our recent efforts in this area, including the development of a similarity measure between two chemical compounds, a prediction system of a plausible enzyme for a given substrate and product pair, and two different approaches to predict the fate of a given compound in a metabolic pathway. General problems and possible future directions are also discussed, in hope to attract more activities from many researchers in this research area.

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