Department of Integrative Physiology, University of Colorado, Boulder, CO 80303, USA.
Department of Health and Exercise Science, Center for Healthy Aging, Colorado State University, Fort Collins, CO 80523, USA.
G3 (Bethesda). 2021 Sep 6;11(9). doi: 10.1093/g3journal/jkab141.
Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.
大量报告表明，感染因子可能在神经退行性疾病中起作用，但尚未令人信服地证明具体的病因。为了以无偏倚的方式寻找候选因子，我们开发了一种生物信息学管道，可在哺乳动物 RNA-seq 数据中识别微生物序列，包括在 GenBank 中没有显著核苷酸相似性命中的序列。使用公开可用的 RNA-seq 数据和使用合成数据的重建实验测试了该管道的有效性。然后，我们将该管道应用于从肌萎缩侧索硬化症患者和对照者的 120 个样本的新型 RNA-seq 数据集，鉴定出与已知细菌和病毒以及新型类似病毒序列相对应的序列。通过定量 RT-PCR 证实了这些新型类似病毒序列的存在，这些序列存在于患者和对照者亚组中。我们相信，该管道将成为当前生成的许多 RNA-seq 数据集中鉴定潜在病因因子的有用工具。
