Why the study?
Infectious agents have been suggested to play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated.
A novel bioinformatic pipeline can successfully identify both known and novel virus-like sequences in human blood RNA-seq data, providing a tool for unbiased pathogen discovery.
New pipeline enables unbiased microbial sequence detection in RNA-seq; leaves open infectious triggers in neurodegeneration pending validation.
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. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis (ALS) 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 data sets currently being generated.
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Melnick et al. (2021) studied this question.
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