bioRxivCell Biology
Distinct stress-dependent signatures of cellular and extracellular tRNA-derived small RNAs (tDRs)
G. Li, A. Manning, A. Bagi, X. Yang, J. Howard, P. P. Chan, T. Sweeney, H. Li, B. D. Laurent, M. I. Kontaridis, L. C. Laurent, K. V. K. Jensen, S. F. Aranki, J. D. Muehlschlegel, R. Kitchen, T. M. Lowe, S. Das
Abstract
The cellular response to stress is an important determinant of disease pathogenesis. Uncovering the molecular fingerprints of distinct stress responses may yield novel biomarkers for different diseases, and potentially identify key signaling pathways important for disease progression. tRNAs and tRNA-derived small RNAs (tDRs) comprise one of the most abundant RNA species in cells and have been associated with cellular stress responses. The presence of RNA modifications on tDRs has been an obstacle for accurately identifying tDRs with conventional small RNA sequencing. Here, we use AlkB-facilitated methylation sequencing (ARM-seq) to uncover a comprehensive landscape of cellular and extracellular tDR expression in a variety of human and rat cells during common stress responses, including nutritional deprivation, hypoxia, and oxidative stress. We found that extracellular tDRs have a distinct fragmentation signature with a predominant length of 31-33 nts and a highly specific termination position when compared with intracellular tDRs. Importantly, we found these signatures are better discriminators of different cellular stress responses compared to extracellular miRNAs. Distinct extracellular tDR signatures for each profiled stressor are elucidated in four different types of cells. This distinct extracellular tDR fragmentation pattern is also noted in plasma extracellular RNAs from patients on cardiopulmonary bypass. The observed overlap of these patient tDR signatures with the signatures of nutritional deprivation and oxidative stress in our cellular models provides preliminary in vivo corroboration of our findings and demonstrates the potential to establish novel extracellular tDR biomarkers in human disease models.
- organism: human
- organism: rat
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- research focus: benchmarking
- approach: deep learning
- approach: statistical model
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