Development of LC/MS-Based Direct RNA Sequencing with Concomitant Basecalling and Modification Analysis Capability

项目摘要 异常的RNA修饰，特别是甲基化和假尿嘧啶基化，已经与主要的 乳腺癌、2型糖尿病和肥胖症等疾病，每一种都影响着数百万美国人。尽管 它们的重要性，可用来可靠地识别、定位和量化RNA修饰的工具非常有限。 因此，我们只知道几个修饰的功能，而不是100多个RNA修饰 已经被确认的。质谱仪(MS)是研究蛋白质修饰的重要工具，其中 肽的断裂产生了揭示修饰的身份和位置的“梯形图”。然而，类似的 对于RNA来说，这种方法还不可行，因为原位片段技术提供了令人满意的序列 覆盖范围不存在。绕过这个问题的一种方法是在之前进行化学降解，以便更好地- 在进入分光计之前，可以形成限定的质量梯子。然而，结构上的一致性 由先决条件RNA降解产生的梯形序列不能令人满意，从而使下游复杂化 数据分析。我们带头开发了基于LC/MS的二维从头RNA 通过利用LC分离优化的RNA酶切中的可预测的规律性来进行测序的工具 大大简化了复杂MS数据的解释。这种方法可以同时测序多达三个 多达30个核苷酸的不同RNA，以及识别、定位和量化广泛的修饰 在RNA样本中。我们假设这种基于MS的RNA测序方法可以进一步优化以 成为一种健壮、易于使用和广泛适用的从头测序方法，并且这样的平台 将是一种非常有用和创新的工具，可以补充现有的下一代RNA测序 由内源RNA携带的化学修饰的深入功能研究的协议。在此应用程序中， 我们建议(A)将RNA加载量减少到一个最小阈值，在该阈值上从头测序 内源RNA变得可行(目标1)，(B)开发简化的数据分析/测序生成 将增强我们的排序方法(目标2)的稳健性的算法，以及(C)提供概念验证 该方法在内源RNA样本从头测序中的使用实例(目标3)。建议数 这项工作意义重大，因为它将把基于MS的梯形技术的力量带给RNA，从而提供一种 可与蛋白质组学中的多肽修饰分析相媲美的方法，可以揭示其身份和位置 不同的RNA修饰。该项目具有很高的创新性，因为它成功地完成了拟议中的 工作将1)允许基于MS的平台以常规方式自动和从头测序细胞RNA 时尚，2)扩大其在从研究到生物技术行业的广泛应用中的效用，以及3) 消除了互补DNA链合成的需要，并允许建立一个完整的， RNA中各种结构修饰的明确时空和定量轮廓 样本。

Project Summary Aberrant RNA modifications, especially methylations and pseudouridinylations, have been correlated to major diseases like breast cancer, type-2 diabetes, and obesity, each of which affects millions of Americans. Despite their significance, the available tools to reliably identify, locate, and quantify RNA modifications are very limited. As a result, we only know the function of a few modifications in contrast to the more than 100 RNA modifications that have been identified. Mass spectrometry (MS) is an essential tool for studying protein modifications, where peptide fragmentation produces “ladders” that reveal the identity and position of modifications. However, a similar approach is not yet feasible for RNA as in situ fragmentation techniques that provide satisfactory sequence coverage do not exist. One way to circumvent this issue is to perform prior chemical degradation so that well- defined mass ladders can be formed before entering the spectrometer. However, the structural uniformity of ladder sequences generated by the prerequisite RNA degradation is unsatisfactory, complicating downstream data analysis. We have spearheaded the development of a two-dimensional LC/MS-based de novo RNA sequencing tool by taking advantage of predictable regularities in LC separation of optimized RNA digests to greatly simplify the interpretation of complex MS data. This method can simultaneously sequence up to three distinct RNAs of up to 30 nucleotides, as well as identify, locate, and quantify a broad spectrum of modifications in the RNA sample. We hypothesize that this MS-based RNA sequencing method could be further optimized to become a robust, easy-to-use, and broadly-applicable de novo sequencing approach, and that such a platform would be a highly useful and innovative tool that can complement existing next-generation RNA sequencing protocols for in-depth functional study of chemical modifications carried by endogenous RNAs. In this application, we propose to (a) reduce the RNA loading amount to a minimum threshold at which de novo sequencing of endogenous RNAs becomes practicable (Aim 1), (b) develop a streamlined data analysis/sequencing generation algorithm that will enhance the robustness of our sequencing method (Aim 2), and (c) provide proof-of-concept examples of the method’s usage in de novo sequencing of endogenous RNA samples (Aim 3). The proposed work is significant because it will bring the power of MS-based laddering technology to RNA, thus providing a method comparable to analysis of peptide modifications in proteomics that can reveal the identity and position of various RNA modifications. This project is highly innovative as successful accomplishment of the proposed work will 1) allow the MS-based platform to routinely sequence cellular RNA automatically and in a de novo fashion, 2) broaden its utility across a wide range of applications from research to biotech industries, and 3) eliminate the need for complementary DNA strand synthesis and permit the establishment of a complete, unambiguous spatiotemporal and quantitative profile for a wide variety of structural modifications in RNA samples.