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

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...

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Autores principales: Shrestha, Prasansah, Kim, Min-Su, Elbasani, Ermal, Kim, Jeong-Dong, Oh, Tae-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734048/
https://www.ncbi.nlm.nih.gov/pubmed/34991451
http://dx.doi.org/10.1186/s12863-021-01020-y
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author Shrestha, Prasansah
Kim, Min-Su
Elbasani, Ermal
Kim, Jeong-Dong
Oh, Tae-Jin
author_facet Shrestha, Prasansah
Kim, Min-Su
Elbasani, Ermal
Kim, Jeong-Dong
Oh, Tae-Jin
author_sort Shrestha, Prasansah
collection PubMed
description 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.
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spelling pubmed-87340482022-01-07 Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711 Shrestha, Prasansah Kim, Min-Su Elbasani, Ermal Kim, Jeong-Dong Oh, Tae-Jin BMC Genom Data Research 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. BioMed Central 2022-01-06 /pmc/articles/PMC8734048/ /pubmed/34991451 http://dx.doi.org/10.1186/s12863-021-01020-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Shrestha, Prasansah
Kim, Min-Su
Elbasani, Ermal
Kim, Jeong-Dong
Oh, Tae-Jin
Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title_full Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title_fullStr Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title_full_unstemmed Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title_short Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711
title_sort prediction of trehalose-metabolic pathway and comparative analysis of kegg, metacyc, and rast databases based on complete genome of variovorax sp. pamc28711
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734048/
https://www.ncbi.nlm.nih.gov/pubmed/34991451
http://dx.doi.org/10.1186/s12863-021-01020-y
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