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Recent Advances in Function-based Metagenomic Screening / 基因组蛋白质组与生物信息学报·英文版
Genomics, Proteomics & Bioinformatics ; (4): 405-415, 2018.
Article in English | WPRIM | ID: wpr-772964
ABSTRACT
Metagenomes from uncultured microorganisms are rich resources for novel enzyme genes. The methods used to screen the metagenomic libraries fall into two categories, which are based on sequence or function of the enzymes. The sequence-based approaches rely on the known sequences of the target gene families. In contrast, the function-based approaches do not involve the incorporation of metagenomic sequencing data and, therefore, may lead to the discovery of novel gene sequences with desired functions. In this review, we discuss the function-based screening strategies that have been used in the identification of enzymes from metagenomes. Because of its simplicity, agar plate screening is most commonly used in the identification of novel enzymes with diverse functions. Other screening methods with higher sensitivity are also employed, such as microtiter plate screening. Furthermore, several ultra-high-throughput methods were developed to deal with large metagenomic libraries. Among these are the FACS-based screening, droplet-based screening, and the in vivo reporter-based screening methods. The application of these novel screening strategies has increased the chance for the discovery of novel enzyme genes.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Plants / Bacteria / Gene Library / Enzymes / Metagenome / High-Throughput Screening Assays / Metagenomics / Genetics / Methods Type of study: Diagnostic study / Screening study Limits: Animals Language: English Journal: Genomics, Proteomics & Bioinformatics Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Plants / Bacteria / Gene Library / Enzymes / Metagenome / High-Throughput Screening Assays / Metagenomics / Genetics / Methods Type of study: Diagnostic study / Screening study Limits: Animals Language: English Journal: Genomics, Proteomics & Bioinformatics Year: 2018 Type: Article