Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data
13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments i...
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| Format: | Article |
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Elsevier
2020-06-01
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| Series: | Metabolic Engineering Communications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214030119300203 |
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| author | Manohar C. Dange Vivek Mishra Bratati Mukherjee Damini Jaiswal Murtaza S. Merchant Charulata B. Prasannan Pramod P. Wangikar |
| author_facet | Manohar C. Dange Vivek Mishra Bratati Mukherjee Damini Jaiswal Murtaza S. Merchant Charulata B. Prasannan Pramod P. Wangikar |
| author_sort | Manohar C. Dange |
| collection | DOAJ |
| description | 13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which 13C enrichment can be quantified accurately. Experimental techniques for tracking 13C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current 13C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X13CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested. |
| first_indexed | 2024-04-14T07:59:14Z |
| format | Article |
| id | doaj.art-25073b37ea014269a1d06ecc411b9015 |
| institution | Directory Open Access Journal |
| issn | 2214-0301 |
| language | English |
| last_indexed | 2024-04-14T07:59:14Z |
| publishDate | 2020-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Metabolic Engineering Communications |
| spelling | doaj.art-25073b37ea014269a1d06ecc411b90152022-12-22T02:04:56ZengElsevierMetabolic Engineering Communications2214-03012020-06-0110e00120Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS dataManohar C. Dange0Vivek Mishra1Bratati Mukherjee2Damini Jaiswal3Murtaza S. Merchant4Charulata B. Prasannan5Pramod P. Wangikar6Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, India; DBT-Pan IIT Center for Bioenergy, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, India; DBT-Pan IIT Center for Bioenergy, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, IndiaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 40076, India; DBT-Pan IIT Center for Bioenergy, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India; Wadhwani Research Center for Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India; Corresponding author. Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, 400076, Mumbai, India.13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which 13C enrichment can be quantified accurately. Experimental techniques for tracking 13C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current 13C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X13CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested.http://www.sciencedirect.com/science/article/pii/S221403011930020313C metabolic flux analysisSynechococcus sp. PCC 7002CyanobacteriaReticulocytesMethanolicusUntargeted analysis |
| spellingShingle | Manohar C. Dange Vivek Mishra Bratati Mukherjee Damini Jaiswal Murtaza S. Merchant Charulata B. Prasannan Pramod P. Wangikar Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data Metabolic Engineering Communications 13C metabolic flux analysis Synechococcus sp. PCC 7002 Cyanobacteria Reticulocytes Methanolicus Untargeted analysis |
| title | Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data |
| title_full | Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data |
| title_fullStr | Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data |
| title_full_unstemmed | Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data |
| title_short | Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data |
| title_sort | evaluation of freely available software tools for untargeted quantification of 13c isotopic enrichment in cellular metabolome from hr lc ms data |
| topic | 13C metabolic flux analysis Synechococcus sp. PCC 7002 Cyanobacteria Reticulocytes Methanolicus Untargeted analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2214030119300203 |
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