Apologies in advance for a long post, I'm catching up.
I am fairly sure the ME work is looking for clonal expansion - so identical cDNA sequences retrieved from individual cells. That makes things simple because there is none of the fuzziness you would get with similar sequences or similar peptide binding. Clonal expansion would make sense to me and would be very interesting.
I think the pie charts are based on identical TCRs from single-cell work and so are clonal. The earlier "Charlie Brown" graph is based on similar (as in predicted to bind the same peptides) TCRs, though the high level in the top cluster seen for mecfs, but not controls, still indicate clonal expansion, as far as I can tell.
As an aside, I think if we are talking about TCRs just being similar in the sense of nearly the same that does not translate well into recognising the same peptide. Two peptides with one amino acid difference are likely to come from totally unrelated proteins. TCRs bdingin the two peptides may well only differ in one amino acid similarly. There are not doubt correlations you can find in vitro but these may be artefacts of the libraries used and the detection systems. T cells need to be able to tell one amino acid difference very precisely.
Of course, and that's what makes the new approach so impressive. I promise I won't mention it again, but here's the abstract. The validation on TB argues against it being an artefact.
Identifying specificity groups in the T cell receptor repertoire : Nature)
Abstract T cell receptor (TCR) sequences are very diverse, with many more possible sequence combinations than T cells in any one individual
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3,
4. Here we define the minimal requirements for TCR antigen specificity, through an analysis of TCR sequences using a panel of peptide and major histocompatibility complex (pMHC)-tetramer-sorted cells and structural data. From this analysis we developed an algorithm that we term GLIPH (grouping of lymphocyte interactions by paratope hotspots) to cluster TCRs with a high probability of sharing specificity owing to both conserved motifs and global similarity of complementarity-determining region 3 (CDR3) sequences. We show that GLIPH can reliably group TCRs of common specificity from different donors, and that conserved CDR3 motifs help to define the TCR clusters that are often contact points with the antigenic peptides. As an independent validation, we analysed 5,711 TCRβ chain sequences from reactive CD4 T cells from 22 individuals with latent
Mycobacterium tuberculosis infection. We found 141 TCR specificity groups, including 16 distinct groups containing TCRs from multiple individuals. These TCR groups typically shared HLA alleles, allowing prediction of the likely HLA restriction, and a large number of
M. tuberculosis T cell epitopes enabled us to identify pMHC ligands for all five of the groups tested. Mutagenesis and
de novo TCR design confirmed that the GLIPH-identified motifs were critical and sufficient for shared-antigen recognition. Thus the GLIPH algorithm can analyse large numbers of TCR sequences and define TCR specificity groups shared by TCRs and individuals, which should greatly accelerate the analysis of T cell responses and expedite the identification of specific ligands.
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More about it in a presentation
here.
I'm sure Davis used this technique because Dr Joseph Breen at the NIH said it was - he'd seen Davis's presentation at an earlier (FOCIS?) conference, and presumably had seen the supplementary grant applicatiion too (see below). I checked with Breen that it was this specific paper.
Looks to me like the graph based on similar TCR sequences is the only place where this approach would apply.
I was disappointed not to see any controls for the ME patient data. Normal levels are given as if they have been taken from historical literature. That suggests that this is preliminary data. It is a bit of a worry that even at this stage ME patients are not being processed blind alongside controls. Maybe they are but why no control data?
This work was funded by the NIH as a supplementary grant, specifically aimed at researchers already doing other work who could tag a mecfs group onto an existing study. That might explain things: it literally was an afterthought.
As far as I know the clonal expansions in cancer occur within the tumour tissue. Clonal expansion in local tissue is a normal universal feature of a defence response. It just means that some cells have stopped there and divided. Clonal expansion in blood would be something entirely different.
That's actually what he showed, clonal expansion in tumour tissue vs not in adjacent tissue. Though looking again, I see that data is for CD4 cells, not CD8.
For MS I am unclear where the data come from. Pubmed shows a few papers indicating CD8 T cell expansion in brain lesions, but as before, this simply implies that some cells have stopped by and divided. They might be recognising degraded host protein with post-translational changes like citrullination or free radical damage so might be non-specific healthy T cells.
There are a couple of papers suggesting CD8 T cell clonal expansion in blood but it does not look like a very big effect. The interest is mostly in that the clones seem to be the same ones as in the brain. Again I would wonder if benign clearing up T cells might not be expanded during an episode of tissue damage.
Davis showed slides of mouse EAE with similar clonal expansion levels in blood and CNS for both CD4 and CD8. I think he may have said there, or somewhere else, they were the same clones in blood and brain, but I'm not totally sure. He suggested the mouse model data meant the same was likely to be true for humans (how do you check for humans: CSF, or are brain biopsies needed?).
Clonality is normally associated with a response to specific antigen and in some sense it probably always is. However, I can envisage a situation where there is a general disturbance of clonal regulation in a compartment that means that instead of CD8 cells settling back to all being different after each insult, as they should do, they go on being very asymmetrical in clonal size. You would then get evidence for clonal expansion but it might not matter very much which clones were expanded.
Somewhere else, possibly in the discussion, Davis does suggest it could be a non-specific T cell effect.
I think it is computationally impossible because we are talking about recognising something like decamer peptides with 20 amino acid options at each point ( peptide alternatives = 100,000,000,000,000,000,000).
Ah, 10^13, that's a good point. I'm sure that somewhere Davis refers to the same number; he saays the library is up to 10^9 and suggests that's just about enough, though it's still only 0.01% of the theoretical possibility.