LC/MS-Based Direct RNA Sequencing with Concomitant Capability to Sequence Multiple Base Modifications at Single-base Resolution

基于 LC/MS 的直接 RNA 测序，同时能够以单碱基分辨率对多个碱基修饰进行测序

• 批准号: 10217648
• 负责人: Shenglong Zhang
• 金额: $ 35万
• 依托单位: NEW YORK INST OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-03 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10217648
• 关键词: 16S ribosomal RNA sequencing; Address; Affect; American; Communities; Complementary DNA; Complex; Databases; Development; Diabetes Mellitus; Disease; Disease model; Escherichia coli; Frequencies; Genetic Transcription; Goals; Gold; Health; High-Throughput RNA Sequencing; Human; Hydrophobicity; Knowledge; Label; Length; Link; Location; Mass Spectrum Analysis; Metabolic Diseases; Methods; Methylation; Modification; Mus; Non-Insulin-Dependent Diabetes Mellitus; Nucleotides; Obesity; Organism; Peptides; Performance; Phenylalanine-Specific tRNA; Population; Positioning Attribute; Post-Transcriptional RNA Processing; Protein Isoforms; Proteomics; RNA; RNA Sequences; Reading; Regulation; Research; Research Personnel; Resolution; Ribosomal RNA; Running; Sampling; Site; Tail; Techniques; Technology; Testing; Time; Tissues; Transcript; Transfer RNA; Variant; Work; Yeasts; automated algorithm; base; cell type; comparative; epitranscriptomics; experimental study; genome-wide; human disease; improved; in vivo; instrument; malignant breast neoplasm; nervous system disorder; nucleobase; reading difficulties; reconstruction; reference genome; tool; transcriptome; transcriptome sequencing; two-dimensional

Project Summary Aberrant RNA base modifications have been correlated with the development of major diseases including breast cancer, type-2 diabetes, obesity, and neurological disorders, each affecting millions of Americans. However, these modifications are undetectable by current high-throughput RNA sequencing technologies, which do not directly sequence RNAs, but instead sequence cDNAs that only contain the four canonical deoxynucleotides. Other tools to sequence nucleobase modifications in RNA are usually tailored for a single specific modified nucleotide and cannot provide single-base-resolution spatial information for modifications. Thus, very few of the over 160 identified RNA modifications have been studied. To better understand RNA with its rich modifications, we have been developing a mass spectrometry (MS)-based 2-dimensional hydrophobic end-labeling sequencing strategy (2-D HELS MS Seq) as: 1) a de novo and accurate method to directly sequence RNA and 2) a general method to sequence all base modifications in any RNA type at single-base resolution. The method can currently sequence purified or mixed samples of short synthetic RNAs and simultaneously identify, locate, and quantify the frequency of a specific modification in a population. In this proposal, we focus on improving read-length, throughput, and sensitivity to sequence rare RNA modifications, quantify post-transcriptional base modifications, and detect active isoforms of mixed cellular RNA samples. We propose to (a) de novo MS sequence specific and total cellular tRNA (<100 nt) as proof-of-concept examples (Aim 1), (b) de novo sequence complex endogenous RNA samples (up to 100 strands, 950 nt per run) (Aim 2), and (c) quantify genome wide post- transcriptional RNA modifications in metabolic disease models (Aim 3). This project is highly significant as successful accomplishment of the proposed work will 1) 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, 2) allow direct and de novo RNA sequencing without cDNA synthesis, and 3) allow accurate reading of multiple base modifications at single nucleotide resolution in one experiment without prior knowledge of sequences and modifications, helping to address a long-standing unmet need in the broad field of epitranscriptomics. Our tool will promote better understanding of functions of post- transcriptional modifications and isoforms including their correlations to human diseases; we will develop the method into a gold standard for verifying other techniques for sequencing and annotating genome-wide base modifications, thereby helping to build more accurate and inclusive reference epitranscriptomic databases.

项目概要 异常的RNA碱基修饰与包括乳腺癌在内的主要疾病的发生有关 癌症、2 型糖尿病、肥胖和神经系统疾病，每一种都影响着数百万美国人。然而， 目前的高通量 RNA 测序技术无法检测到这些修饰，而这些技术无法检测到这些修饰。 直接对 RNA 进行测序，而是对仅包含四种典型脱氧核苷酸的 cDNA 进行测序。 对 RNA 中核碱基修饰进行测序的其他工具通常是针对单个特定修饰而定制的 核苷酸，不能提供用于修饰的单碱基分辨率空间信息。因此，很少有 超过 160 个已识别的 RNA 修饰已被研究。为了更好地了解 RNA 及其丰富的修饰， 我们一直在开发基于质谱 (MS) 的二维疏水末端标记测序 策略（2-D HELS MS Seq）为：1）一种直接对 RNA 进行测序的从头且准确的方法，2）一种通用方法 以单碱基分辨率对任何 RNA 类型中的所有碱基修饰进行测序的方法。该方法目前可以 对短合成 RNA 的纯化或混合样品进行测序，并同时进行识别、定位和定量 群体中特定修饰的频率。在这个提案中，我们重点关注提高阅读长度， 通量和对罕见 RNA 修饰测序的敏感性，量化转录后碱基修饰， 并检测混合细胞 RNA 样品的活性异构体。我们建议 (a) de novo MS 序列特异性 和总细胞 tRNA (<100 nt) 作为概念验证示例（目标 1），(b) de novo 序列复合体 内源 RNA 样本（最多 100 条链，每次运行 950 nt）（目标 2），以及 (c) 量化全基因组范围的后处理 代谢疾病模型中的转录 RNA 修饰（目标 3）。该项目意义重大 拟议工作的成功完成将 1) 将基于 MS 的梯形技术的力量带入 RNA，从而提供了一种与蛋白质组学中肽修饰分析相当的方法，可以揭示 各种 RNA 修饰的身份和位置，2) 无需 cDNA 即可直接进行从头 RNA 测序 合成，3) 允许在一个核苷酸分辨率下准确读取多个碱基修饰 在不事先了解序列和修饰的情况下进行实验，有助于解决长期未满足的问题 表观转录组学广泛领域的需求。我们的工具将促进更好地理解后功能 转录修饰和异构体，包括它们与人类疾病的相关性；我们将开发 方法成为验证其他全基因组碱基测序和注释技术的黄金标准 修改，从而有助于建立更准确和更具包容性的参考表观转录组数据库。

项目成果

A General LC-MS-Based Method for Direct and De Novo Sequencing of RNA Mixtures Containing both Canonical and Modified Nucleotides.

一种基于 LC-MS 的通用方法，用于对含有规范和修饰核苷酸的 RNA 混合物进行直接和从头测序。

• 发表时间: 2021
• 作者: Zhang, Ning;Shi, Shundi;Yuan, Xiaohong;Ni, Wenhao;Wang, Xuanting;Yoo, Barney;Jia, Tony Z;Li, Wenjia;Zhang, Shenglong
• 通讯作者: Zhang, Shenglong

Parent tRNA Modification Status Determines the Induction of Functional tRNA-Derived RNA by Respiratory Syncytial Virus Infection.

亲本 tRNA 修饰状态决定呼吸道合胞病毒感染对功能性 tRNA 衍生 RNA 的诱导。

• 发表时间: 2022-12-24
• 作者: Choi, Eun;Wu, Wenzhe;Zhang, Ke;Yuan, Xiaohong;Deng, Junfang;Ismail, Deena;Buck, Darby L;Thomason, Kerrie S;Garofalo, Roberto P;Zhang, Shenglong;Bao, Xiaoyong
• 通讯作者: Bao, Xiaoyong