Agnostic Framework for the Classification/Identification of Organisms Based on RNA Post-Transcriptional Modifications.
Agnostic Framework for the Classification/Identification of Organisms Based on RNA Post-Transcriptional Modifications.
复制标题
DOI：
10.1021/acs.analchem.1c00359
复制
发表时间：
2021-06-08
影响因子：
7.4
通讯作者：
Fabris D
中科院分区：
文献类型：
--
作者：
McIntyre WD;Nemati R;Salehi M;Aldrich CC;FitzGibbon M;Deng L;Pazos MA;Rose RE;Toro B;Netzband RE;Pager CT;Robinson IP;Bialosuknia SM;Ciota AT;Fabris D
我们提出了一种新的方法，用于建立一个分类/鉴定框架的基础上，由生物体在基础条件下表达的RNA转录后修饰（rPTM）的完整补充。该方法依赖于先进的质谱技术来表征总RNA提取物的核酸外切酶消化产物。使用包括所有检测到的rPTM的身份和相对丰度的样品概况来训练和测试不同机器学习（ML）算法的能力。每个算法证明能够识别严格的决策规则，区分密切相关的类和正确分配未标记的样本。ML分类器分辨肠杆菌科的不同成员，备选E. coli血清型、一系列S.酿酒酵母基因敲除突变体和H. sapiens中枢神经系统，共享非常相似的遗传背景。当类的数量显著增加以升级复杂性时，通过在有限数量的类上训练所实现的出色的准确性和分辨率水平被成功地复制。从ML策划的数据生成的树状图显示出一个层次结构，非常类似于已建立的分类系统所提供的。更精细的聚类模式揭示了单一关键基因缺失引起的广泛影响。这些信息为探索rPTM在其各自的调控网络中的作用提供了一个假定的路线图，这对于破译epitranscriptomics代码至关重要。RNA在几乎所有生物体中的普遍存在有望实现最广泛的应用范围，在RNA相关疾病的诊断中具有重要意义。
We propose a novel approach for building a classification/identification framework based on the full complement of RNA post-transcriptional modifications (rPTMs) expressed by an organism at basal conditions. The approach relies on advanced mass spectrometric techniques to characterize the products of exonuclease digestion of total RNA extracts. Sample profiles comprising identities and relative abundances of all detected rPTM were used to train and test the capabilities of different of machine learning (ML) algorithms. Each algorithm proved capable of identifying rigorous decision rules for differentiating closely related classes and correctly assigning unlabeled samples. The ML classifiers resolved different members of the Enterobacteriaceae family, alternative E. coli serotypes, a series of S. cerevisiae knockout mutants, and primary cells of H. sapiens central nervous system, which shared very similar genetic backgrounds. The excellent levels of accuracy and resolving power achieved by training on a limited number of classes were successfully replicated when the number of classes was significantly increased to escalate complexity. A dendrogram generated from ML-curated data exhibited a hierarchical organization that closely resembled those afforded by established taxonomic systems. Finer clustering patterns revealed the extensive effects induced by the deletion of a single pivotal gene. This information provided a putative roadmap for exploring the roles of rPTMs in their respective regulatory networks, which will be essential to decipher the epitranscriptomics code. The ubiquitous presence of RNA in virtually all living organisms promises to enable the broadest possible range of applications, with significant implications in the diagnosis of RNA-related diseases.
登录
查看更多内容
影响因子：
7.3
作者：
Limbach, Patrick A.;Paulines, Mellie June
通讯作者：
Paulines, Mellie June
影响因子：
16.6
作者：
Brandmayr, Caterina;Wagner, Mirko;Brueckl, Tobias;Globisch, Daniel;Pearson, David;Kneuttinger, Andrea Christa;Reiter, Veronika;Hienzsch, Antje;Koch, Susanne;Thoma, Ines;Thumbs, Peter;Michalakis, Stylianos;Mueller, Markus;Biel, Martin;Carell, Thomas
通讯作者：
Carell, Thomas
影响因子：
5
作者：
D'Argenio, Valeria;Salvatore, Francesco
通讯作者：
Salvatore, Francesco
影响因子：
3.8
作者：
GRAHAM, FL;SMILEY, J;NAIRN, R
通讯作者：
NAIRN, R
影响因子：
3.5
作者：
Kolitz SE;Lorsch JR
通讯作者：
Lorsch JR