2'O-ribose methylation of ribosomal RNA (rRNA 2'Ome) in primary human T cells from septic shock and COVID-19 patients
Authors/Creators
Contributors
Researchers:
- 1. Centre de Recherche en Cancérologie de Lyon
Description
Abstract
T cell exhaustion plays a central role in sepsis-induced immunosuppression. Deciphering the precise mechanism of this cellular dysfunction could lead to new therapies. In several pathophysiological contexts, the 2’O-ribose methylation of ribosomal RNA (rRNA 2’Ome) has emerged as a level of epitranscriptomic regulation. Here, we report for the first time site-specific alterations of rRNA 2’Ome epitranscriptomic marks in T cells after sepsis, associated with impaired functionality. Using primary human T cells from septic shock and COVID-19 patients, we identified a subset of sites with high inter-individual variability, the levels of which correlated with lymphocyte effector functions. This was recapitulated in an ex vivo model of stimulated T lymphocytes from healthy donors. Finally, 2’Ome signature discriminated samples from septic patients from those of healthy donors. We describe rRNA 2’Ome regulation as a new molecular mechanism that controls T lymphocyte effector function in sepsis with high potential as biomarker and therapeutic target.
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Description of the data and file structure
Each folder contains the read-end counts in the sub-directory RiboMethSeq_ReadEnd_Counts and the metadata file. The metadata file describe each file contained in this sub-directory.
The read-end count file structure:
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The name of the RNA on which the read end counting was performed.
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The number of the position on the RNA.
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The value of the read end counts at the position.
Code/Software
Using ribomethseq-nf pipeline, fastq were used to align reads on the human rRNA sequence (NR_046235), compute 5’/3’-end read counts.
These files can be the input of rRMSAnalyzer package to adjust batch effect (ComBat-seq method) and calculate C-score corresponding to the end read count at the genomic position of interest normalized to the median of end read counts of the local environment (6 upstream and 6 downstream nucleotides).
Additional details
Software
- Repository URL
- https://github.com/RibosomeCRCL/rRMSAnalyzer
- Programming language
- R