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突变体文库和宏基因组文库中酯酶、脂肪酶及磷脂酶的高通量筛选:综述

High Throughput Screening of Esterases, Lipases and Phospholipases in Mutant and Metagenomic Libraries: A Review.

作者信息

Peña-García Carlina, Martínez-Martínez Mónica, Reyes-Duarte Dolores, Ferrer Manuel

机构信息

Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Av. Vasco de Quiroga 4871, Col. Santa Fe, Deleg, Cuajimalpa, 05348, CDMX, México.

Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Marie Curie 2, 28049 Madrid, Spain.

出版信息

Comb Chem High Throughput Screen. 2016;19(8):605-615. doi: 10.2174/1386207319666151110123927.

Abstract

Nowadays, enzymes can be efficiently identified and screened from metagenomic resources or mutant libraries. A set of a few hundred new enzymes can be found using a simple substrate within few months. Hence, the establishment of collections of enzymes is no longer a big hurdle. However, a key problem is the relatively low rate of positive hits and that a timeline of several years from the identification of a gene to the development of a process is the reality rather than the exception. Major problems are related to the time-consuming and cost-intensive screening process that only very few enzymes finally pass. Accessing to the highest possible enzyme and mutant diversity by different, but complementary approaches is increasingly important. The aim of this review is to deliver state-of-art status of traditional and novel screening protocols for targeting lipases, esterases and phospholipases of industrial relevance, and that can be applied at high throughput scale (HTS) for at least 200 distinct substrates, at a speed of more than 105 - 108 clones/day. We also review fine-tuning sequence analysis pipelines and in silico tools, which can further improve enzyme selection by an unprecedent speed (up to 1030 enzymes). If the hit rate in an enzyme collection could be increased by HTS approaches, it can be expected that also the very further expensive and time-consuming enzyme optimization phase could be significantly shortened, as the processes of enzyme-candidate selection by such methods can be adapted to conditions most likely similar to the ones needed at industrial scale.

摘要

如今,可以从宏基因组资源或突变文库中高效地鉴定和筛选酶。使用一种简单的底物,在几个月内就能发现几百种新酶。因此,建立酶库已不再是一个大障碍。然而,一个关键问题是阳性命中率相对较低,而且从基因鉴定到工艺开发需要数年时间是现实情况而非个例。主要问题与耗时且成本高昂的筛选过程有关,最终只有极少数酶能够通过。通过不同但互补的方法获取尽可能高的酶和突变体多样性变得越来越重要。本综述的目的是介绍针对具有工业相关性的脂肪酶、酯酶和磷脂酶的传统和新型筛选方案的最新状态,这些方案可以以每天超过105 - 108个克隆的速度,针对至少200种不同底物进行高通量筛选(HTS)。我们还将综述微调序列分析流程和计算机工具,它们可以以前所未有的速度(高达1030种酶)进一步改善酶的选择。如果通过高通量筛选方法提高酶库中的命中率,那么可以预期,由于通过此类方法进行酶候选物选择的过程可以适应与工业规模所需条件最相似的条件,因此非常昂贵且耗时的酶优化阶段也可以显著缩短。

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