Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli
The current problem for metabolic engineering is how to identify a suitable set of genes for knockout that can improve the production of certain metabolites and sustain the growth rate from the thousands of metabolic networks which are complex and combinatorial. Some approaches, such as OptKnock and...
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| Format: | Article |
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Korean Society of Industrial Engineering Chemistry
2015
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| _version_ | 1796860194765930496 |
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| author | Pooi, San Chua Mohamed Salleh, Abdul Hakim Mohamad, Mohd. Saberi Deris, Safaai Omatu, Sigeru Yoshioka, Michifumi |
| author_facet | Pooi, San Chua Mohamed Salleh, Abdul Hakim Mohamad, Mohd. Saberi Deris, Safaai Omatu, Sigeru Yoshioka, Michifumi |
| author_sort | Pooi, San Chua |
| collection | ePrints |
| description | The current problem for metabolic engineering is how to identify a suitable set of genes for knockout that can improve the production of certain metabolites and sustain the growth rate from the thousands of metabolic networks which are complex and combinatorial. Some approaches, such as OptKnock and OptGene, are developed to enhance the production of desired metabolites. However, the performances of these approaches are suboptimal and the obtained results are unsatisfactory because of computational limitations such as local minima. In this paper, we propose a hybrid of Bat Algorithm and Flux Balance Analysis (BATFBA) to enhance succinate and lactate production by identifying a set of genes for knock out. The Bat Algorithm is an optimisation algorithm, whereas Flux Balance Analysis (FBA) is a mathematical approach to analyse the flow of metabolites through a metabolic network. The Escherichia coli iJR904 dataset was used to determine optimal knockout genes, production rate, and growth rate. By applying this hybrid method to the iJR904 dataset, we found that BATFBA yielded better results than existing methods, such as OptKnock and a hybrid of Artificial Bee Colony algorithms and Flux Balance Analysis (ABCFBA), at predicting succinate and lactate production |
| first_indexed | 2024-03-05T19:38:18Z |
| format | Article |
| id | utm.eprints-55652 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:38:18Z |
| publishDate | 2015 |
| publisher | Korean Society of Industrial Engineering Chemistry |
| record_format | dspace |
| spelling | utm.eprints-556522017-08-20T08:05:28Z http://eprints.utm.my/55652/ Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli Pooi, San Chua Mohamed Salleh, Abdul Hakim Mohamad, Mohd. Saberi Deris, Safaai Omatu, Sigeru Yoshioka, Michifumi QA75 Electronic computers. Computer science The current problem for metabolic engineering is how to identify a suitable set of genes for knockout that can improve the production of certain metabolites and sustain the growth rate from the thousands of metabolic networks which are complex and combinatorial. Some approaches, such as OptKnock and OptGene, are developed to enhance the production of desired metabolites. However, the performances of these approaches are suboptimal and the obtained results are unsatisfactory because of computational limitations such as local minima. In this paper, we propose a hybrid of Bat Algorithm and Flux Balance Analysis (BATFBA) to enhance succinate and lactate production by identifying a set of genes for knock out. The Bat Algorithm is an optimisation algorithm, whereas Flux Balance Analysis (FBA) is a mathematical approach to analyse the flow of metabolites through a metabolic network. The Escherichia coli iJR904 dataset was used to determine optimal knockout genes, production rate, and growth rate. By applying this hybrid method to the iJR904 dataset, we found that BATFBA yielded better results than existing methods, such as OptKnock and a hybrid of Artificial Bee Colony algorithms and Flux Balance Analysis (ABCFBA), at predicting succinate and lactate production Korean Society of Industrial Engineering Chemistry 2015-04 Article PeerReviewed Pooi, San Chua and Mohamed Salleh, Abdul Hakim and Mohamad, Mohd. Saberi and Deris, Safaai and Omatu, Sigeru and Yoshioka, Michifumi (2015) Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli. Biotechnology and Bioprocess Engineering, 20 (2). pp. 349-357. ISSN 1226-8372 http://dx.doi.org/10.1007/s12257-014-0466-x DOI:10.1007/s12257-014-0466-x |
| spellingShingle | QA75 Electronic computers. Computer science Pooi, San Chua Mohamed Salleh, Abdul Hakim Mohamad, Mohd. Saberi Deris, Safaai Omatu, Sigeru Yoshioka, Michifumi Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title | Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title_full | Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title_fullStr | Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title_full_unstemmed | Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title_short | Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli |
| title_sort | identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in escherichia coli |
| topic | QA75 Electronic computers. Computer science |
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