Nucleic Acid Chemistry and Engineering Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa 904-0495, Japan.
Acc Chem Res. 2020 Dec 15;53(12):2903-2912. doi: 10.1021/acs.accounts.0c00546. Epub 2020 Nov 9.
Ribozymes and deoxyribozymes are catalytic RNA and DNA, respectively, that catalyze chemical reactions such as self-cleavage or ligation reactions. While some ribozymes are found in nature, a larger variety of ribozymes and deoxyribozymes have been discovered by in vitro selection from random sequences. These catalytic nucleic acids, especially ribozymes, are of fundamental interest because they are crucial for the RNA world hypothesis, which suggests that RNA played a central role in both the propagation of genetic information and catalyzing metabolic reactions in primordial life prior to the emergence of proteins and DNA. On the practical side, catalytic nucleic acids have been extensively engineered for various applications, such as biosensors and genetic devices for synthetic biology. Therefore, it is important to gain a deeper understanding of the sequence-function relationships of ribozymes and deoxyribozymes.Mutational analysis, or measurements of activities of catalytic nucleic acid mutants, is one of the most fundamental approaches for that purpose. Mutations that abolish, reduce, retain, or even increase activity provide useful information about nucleic acid catalysts for engineering and other purposes. However, methods for mutational analysis of ribozymes and deoxyribozymes have not evolved much for decades, requiring tedious and low-throughput assays (e.g., gel electrophoresis) of individually prepared mutants. This has prevented researchers from performing quantitative mutational analysis of ribozymes and deoxyribozymes on a large scale.To address this limitation, we developed a massively parallel ribozyme and deoxyribozyme assay strategy that allows >10 assays using high-throughput sequencing (HTS). We used HTS to literally count the number of cleaved (or ligated) and uncleaved (or unligated) ribozyme (or deoxyribozyme) sequences and calculated the activities of each mutant in a reaction mixture. This simple yet powerful strategy was applied to analyze the mutational effects of various natural and synthetic ribozymes and deoxyribozymes at scales impossible for conventional mutational analysis. These large-scale sequence-function data sets were used to better understand the functional consequences of mutations and to engineer ribozymes for practical applications. Furthermore, these newly available data are motivating researchers to employ more rigorous computational methods to extract additional insights such as structural information and nonlinear effects of multiple mutations. The new HTS-based assay strategy is distinct from and complementary to a related strategy that uses HTS to analyze ribozyme and deoxyribozyme populations subjected to in vitro selection. Postselection sequencing can cover a larger sequence space, although it does not directly quantify the activities of ribozyme and deoxyribozyme mutants. With further advances in DNA sequencing technologies and computational methods, there should be more opportunities to harness the power of HTS to deepen our understanding of catalytic nucleic acids and enhance our ability to engineer them for even more applications.
核酶和脱氧核酶分别是催化 RNA 和 DNA 的酶,能够催化自身切割或连接等化学反应。虽然自然界中存在一些核酶,但通过体外从随机序列中选择,发现了更多种类的核酶和脱氧核酶。这些催化性核酸,特别是核酶,具有重要的基础研究意义,因为它们是 RNA 世界假说的关键,该假说表明,在蛋白质和 DNA 出现之前的原始生命中,RNA 在遗传信息的传播和代谢反应的催化中发挥了核心作用。从实际应用的角度来看,人们已经对催化性核酸进行了广泛的工程设计,例如用于生物传感器和合成生物学的遗传器件。因此,深入了解核酶和脱氧核酶的序列-功能关系非常重要。突变分析,即测量催化性核酸突变体的活性,是实现这一目标的最基本方法之一。那些导致活性完全丧失、降低、保留甚至增强的突变,为工程设计和其他目的提供了有关核酸催化剂的有用信息。然而,几十年来,核酶和脱氧核酶的突变分析方法并没有太大的发展,需要对个别制备的突变体进行繁琐且通量低的凝胶电泳等检测。这使得研究人员无法对核酶和脱氧核酶进行大规模的定量突变分析。为了解决这一限制,我们开发了一种大规模并行的核酶和脱氧核酶测定策略,该策略允许使用高通量测序 (HTS) 进行 >10 项测定。我们使用 HTS 直接计数切割 (或连接) 和未切割 (或未连接) 的核酶 (或脱氧核酶) 序列的数量,并计算反应混合物中每个突变体的活性。这种简单而强大的策略已被应用于分析各种天然和合成核酶和脱氧核酶的突变效应,其规模是传统突变分析无法企及的。这些大规模的序列-功能数据集有助于更好地理解突变的功能后果,并设计用于实际应用的核酶。此外,这些新获得的数据促使研究人员采用更严格的计算方法来提取更多的见解,如结构信息和多个突变的非线性效应。新的基于 HTS 的测定策略与另一种策略不同,后者使用 HTS 分析经历体外选择的核酶和脱氧核酶群体。选择后测序可以覆盖更大的序列空间,尽管它不能直接定量核酶和脱氧核酶突变体的活性。随着 DNA 测序技术和计算方法的进一步发展,应该有更多的机会利用 HTS 的力量来加深我们对催化性核酸的理解,并增强我们设计它们以应用于更多领域的能力。