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Parsing digital or analogue TCR performance through piconewton forces

GSE240414 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/08/21 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
18 samples: 6 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Parsing digital or analog TCR performance through piconewton forcesScience advances · 2024
Summary (written by the submitters)
T lymphocytes leverage T-cell receptor (TCR) recognition of aberrant peptides bound to major histocompatibility complex molecules (pMHCs) on altered cells to protect the mammalian host from infectious pathogens and cancerous transformations. While adaptive immunity requires efficient TCR performance, comparison metrics are widely limited to force-free assays.
Read the full summary ↓
Recent data reveals, however, that mechanical load on the TCR-pMHC bond resulting from cellular motions between a T cell-antigen presenting cell conjugate formed during immune surveillance tunes TCR specificity and sensitivity. Here, we cloned TCRs from lung resident CD8 T cells following influenza A virus (IAV) infection directed against two immunodominant epitopes, the luminous nucleoprotein NP366-374 /Db and sparse acid polymerase PA224-233/Db pMHCs, arrayed at >1000 vs <10 copies/cell, respectively. Using optical tweezers-based methods to apply biologically relevant loads, we observe that certain TCRs belonging to the NP repertoire require many ligands for activation while others only few, functioning in analogue or digital modes, correspondingly. In contrast, prevalent TCRs tested in the PA repertoire all perform digitally. When held at a critical force, moreover, even digital TCRs are distinguishable, exhibiting dramatic increases in bond lifetime and performance relating to their structural transition rate and distance. Digital performance is best for both specificities in vitro and in vivo, but undiscernible using conventional functional avidity or TCR sequence distance metrics. Correlates of optimal biophysical parameters include magnitudes of ERK phosphorylation, CD3 surface loss, and activation marker upregulation. Our findings underscore the requirement to match TCR performance quality with pMHC copy number, as nature does. Given tumor antigen array paucity, engaging choice digital TCRs appears critical for T-cell adoptive cancer therapies and vaccines.
Published in
Parsing digital or analog TCR performance through piconewton forces
Akitsu A, Kobayashi E, Feng Y et al. · Science advances 2024 · PMID 39141734 · doi:10.1126/sciadv.ado4313
This dataset
Open GSE240414 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE240414_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1003535 and SRA study SRP454097. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39141734) ↗
Study design
6 conditions, mostly in triplicate
PA25 TCR CD8 T cell, lymph node, influenza, ×3 PA25 TCR CD8 T cell, lung, influenza, ×3 PA27 TCR CD8 T cell, lymph node, influenza, ×3 PA27 TCR CD8 T cell, lung, influenza, ×3 PA59 TCR CD8 T cell, lymph node, influenza, ×3 PA59 TCR CD8 T cell, lung, influenza, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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