Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i>
Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in thi...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
|
| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/10/6/636 |
| _version_ | 1797596051726663680 |
|---|---|
| author | Yuki Kuriya Masahiro Murata Masaki Yamamoto Naoki Watanabe Michihiro Araki |
| author_facet | Yuki Kuriya Masahiro Murata Masaki Yamamoto Naoki Watanabe Michihiro Araki |
| author_sort | Yuki Kuriya |
| collection | DOAJ |
| description | Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in this study, we aimed to extract and estimate important variables and necessary numbers for predicting metabolic flux distribution as the state of cell metabolism by flux sampling using a genome-scale metabolic model (GSM) and its analysis. Acetic acid production from glucose in <i>Escherichia coli</i> with GSM iJO1366 was used as a case study. Flux sampling obtained by OptGP using 1000 pattern constraints on substrate, product, and growth fluxes produced a wider sample than the default case. The analysis also suggested that the fluxes of iron ions, O<sub>2</sub>, CO<sub>2</sub>, and NH<sub>4</sub><sup>+</sup>, were important for predicting the metabolic flux distribution. Additionally, the comparison with the literature value of <sup>13</sup>C-MFA using CO<sub>2</sub> emission flux as an example of an important flux suggested that the important flux obtained by this method was valid for the prediction of flux distribution. In this way, the method of this research was useful for extracting variables that were important for predicting flux distribution, and as a result, the possibility of contributing to the reduction of measurement variables in experiments was suggested. |
| first_indexed | 2024-03-11T02:46:05Z |
| format | Article |
| id | doaj.art-c6c30968cb9d4af491c9472bb4f36294 |
| institution | Directory Open Access Journal |
| issn | 2306-5354 |
| language | English |
| last_indexed | 2024-03-11T02:46:05Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj.art-c6c30968cb9d4af491c9472bb4f362942023-11-18T09:20:41ZengMDPI AGBioengineering2306-53542023-05-0110663610.3390/bioengineering10060636Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i>Yuki Kuriya0Masahiro Murata1Masaki Yamamoto2Naoki Watanabe3Michihiro Araki4Artificial Intelligence Center for Health and Biomedical Research, National Institute of Biomedical Innovation, Health and Nutrition, 3-17 Senrioka-shinmachi, Settsu 566-0002, JapanGraduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, JapanArtificial Intelligence Center for Health and Biomedical Research, National Institute of Biomedical Innovation, Health and Nutrition, 3-17 Senrioka-shinmachi, Settsu 566-0002, JapanArtificial Intelligence Center for Health and Biomedical Research, National Institute of Biomedical Innovation, Health and Nutrition, 3-17 Senrioka-shinmachi, Settsu 566-0002, JapanArtificial Intelligence Center for Health and Biomedical Research, National Institute of Biomedical Innovation, Health and Nutrition, 3-17 Senrioka-shinmachi, Settsu 566-0002, JapanOmics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in this study, we aimed to extract and estimate important variables and necessary numbers for predicting metabolic flux distribution as the state of cell metabolism by flux sampling using a genome-scale metabolic model (GSM) and its analysis. Acetic acid production from glucose in <i>Escherichia coli</i> with GSM iJO1366 was used as a case study. Flux sampling obtained by OptGP using 1000 pattern constraints on substrate, product, and growth fluxes produced a wider sample than the default case. The analysis also suggested that the fluxes of iron ions, O<sub>2</sub>, CO<sub>2</sub>, and NH<sub>4</sub><sup>+</sup>, were important for predicting the metabolic flux distribution. Additionally, the comparison with the literature value of <sup>13</sup>C-MFA using CO<sub>2</sub> emission flux as an example of an important flux suggested that the important flux obtained by this method was valid for the prediction of flux distribution. In this way, the method of this research was useful for extracting variables that were important for predicting flux distribution, and as a result, the possibility of contributing to the reduction of measurement variables in experiments was suggested.https://www.mdpi.com/2306-5354/10/6/636genome-scale metabolic modelflux samplingflux distribution predictionimportant flux extraction |
| spellingShingle | Yuki Kuriya Masahiro Murata Masaki Yamamoto Naoki Watanabe Michihiro Araki Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> Bioengineering genome-scale metabolic model flux sampling flux distribution prediction important flux extraction |
| title | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> |
| title_full | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> |
| title_fullStr | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> |
| title_full_unstemmed | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> |
| title_short | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in <i>Escherichia coli</i> |
| title_sort | prediction of metabolic flux distribution by flux sampling as a case study acetate production from glucose in i escherichia coli i |
| topic | genome-scale metabolic model flux sampling flux distribution prediction important flux extraction |
| url | https://www.mdpi.com/2306-5354/10/6/636 |
| work_keys_str_mv | AT yukikuriya predictionofmetabolicfluxdistributionbyfluxsamplingasacasestudyacetateproductionfromglucoseiniescherichiacolii AT masahiromurata predictionofmetabolicfluxdistributionbyfluxsamplingasacasestudyacetateproductionfromglucoseiniescherichiacolii AT masakiyamamoto predictionofmetabolicfluxdistributionbyfluxsamplingasacasestudyacetateproductionfromglucoseiniescherichiacolii AT naokiwatanabe predictionofmetabolicfluxdistributionbyfluxsamplingasacasestudyacetateproductionfromglucoseiniescherichiacolii AT michihiroaraki predictionofmetabolicfluxdistributionbyfluxsamplingasacasestudyacetateproductionfromglucoseiniescherichiacolii |