A Review of Gene Knockout Strategies for Microbial Cells

Author(s): Phooi Wah Tang, Pooi San Chua, Shiue Kee Chong, Mohd Saberi Mohamad, Yee Wen Choon, Safaai Deris, Sigeru Omatu, Juan Manuel Corchado, Weng Howe Chan, Raha Abdul Rahim.

Journal Name: Recent Patents on Biotechnology

Volume 9 , Issue 3 , 2015

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Abstract:

Background: Predicting the effects of genetic modification is difficult due to the complexity of metabolic net- works. Various gene knockout strategies have been utilised to deactivate specific genes in order to determine the effects of these genes on the function of microbes. Deactivation of genes can lead to deletion of certain proteins and functions. Through these strategies, the associated function of a deleted gene can be identified from the metabolic networks.

Methods: The main aim of this paper is to review the available techniques in gene knockout strategies for microbial cells. The review is done in terms of their methodology, recent applications in microbial cells. In addition, the advantages and disadvantages of the techniques are compared and discuss and the related patents are also listed as well.

Results: Traditionally, gene knockout is done through wet lab (in vivo) techniques, which were conducted through laboratory experiments. However, these techniques are costly and time consuming. Hence, various dry lab (in silico) techniques, where are conducted using computational approaches, have been developed to surmount these problem.

Conclusion: The development of numerous techniques for gene knockout in microbial cells has brought many advancements in the study of gene functions. Based on the literatures, we found that the gene knockout strategies currently used are sensibly implemented with regard to their benefits.

Keywords: Gene knockout strategies, metabolic network, bi-level modelling framework, metabolic engineering, bioinformatics, artificial intelligence.

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Article Details

VOLUME: 9
ISSUE: 3
Year: 2015
Page: [176 - 197]
Pages: 22
DOI: 10.2174/1872208310666160517115047
Price: $65

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