Next-generation sequencing technologies enable doubling of the genomic databases every 2.5 years. Collected sequences represent a rich source of novel biocatalysts. However, the rate of accumulation of sequence data exceeds the rate of functional studies, calling for acceleration and miniaturization of biochemical assays. Here, we present an integrated platform employing bioinformatics, microanalytics, and microfluidics and its application for exploration of unmapped sequence space, using haloalkane dehalogenases as model enzymes. First, we employed bioinformatic analysis for identification of 2,905 putative dehalogenases and rational selection of 45 representative enzymes. Second, we expressed and experimentally characterized 24 enzymes showing sufficient solubility for microanalytical and microfluidic testing. Miniaturization increased the throughput to 20,000 reactions per day with 1000-fold lower protein consumption compared to conventional assays. A single run of the platform doubled dehalogenation toolbox of family members characterized over three decades. Importantly, the dehalogenase activities of nearly one-third of these novel biocatalysts far exceed that of most published HLDs. Two enzymes showed unusually narrow substrate specificity, never before reported for this enzyme family. The strategy is generally applicable to other enzyme families, paving the way towards the acceleration of the process of identification of novel biocatalysts for industrial applications but also for the collection of homogenous data for machine learning. The automated in silico workflow has been released as a user-friendly web-tool EnzymeMiner: https://loschmidt.chemi.muni.cz/enzymeminer/.

中文翻译：

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通过将生物信息学与微分析和微流技术相结合的集成策略对酶家族进行功能注释

下一代测序技术可使基因组数据库每2.5年翻一番。收集的序列代表了新型生物催化剂的丰富来源。但是，序列数据的积累速度超过了功能研究的速度，这要求生物化学测定法的加速和小型化。在这里，我们介绍一个利用生物信息学，微分析学和微流体学的综合平台，并将其应用卤代烷脱卤酶作为模型酶，用于探索未映射的序列空间。首先，我们利用生物信息学分析来鉴定2905种推定的脱卤素酶并合理选择45种代表性酶。其次，我们表达和实验表征了24种酶，它们显示出足够的溶解度，可用于微分析和微流体测试。与常规测定相比，小型化将通量提高到每天20,000个反应，蛋白质消耗降低了1000倍。该平台的一次运行使过去三十年来家庭成员的脱卤工具箱翻了一番。重要的是，这些新型生物催化剂中近三分之一的脱卤素酶活性远远超过大多数已发表的HLD。两种酶显示出异常狭窄的底物特异性，这一酶家族从未有过报道。该策略通常适用于其他酶家族，为加速工业应用中新型生物催化剂的鉴定过程铺平了道路，也为机器学习的同质数据收集铺平了道路。自动化的计算机软件工作流程已作为用户友好的Web工具EnzymeMiner发布：https：// loschmidt。