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Paul Thomas @pgtimmune.bsky.social · Jul 14

This was a collaborative effort between led by Phil Bradley (not on the socials) and @sschattgen, with Kasi Vegesana, @Asya_Minervina, @villanilab, the MGH COVID-19 team, @s_valkiers and many others!

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Paul Thomas @pgtimmune.bsky.social · Jul 14

In short, you can think of MetaCoNGA as our first draft of the human TCR repertoire. Beta code for matching your T cell populations to those from metaCoNGA is available on Github (github.com/phbradley/me...).

GitHub - phbradley/metaconga: Scripts and files for meta-analysis with conga

Scripts and files for meta-analysis with conga. Contribute to phbradley/metaconga development by creating an account on GitHub.

github.com

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Paul Thomas @pgtimmune.bsky.social · Jul 14

Alternatively, maybe you’ve matched TCRs and GEX to a newly curated regulatory unconventional population (previously difficult to match w/TCR sequence). These vary substantially across donors & conditions & may be highly predictive of immune states relevant to health and disease.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

Maybe you’ve identified a novel condition-associated population and you want to see where it falls–is it a conventional epitope specific response? If so, we might be able to tell you the pathogen, the epitope, or the HLA-restriction (or all 3)?

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Paul Thomas @pgtimmune.bsky.social · Jul 14

Finally, can we put these two analyses together to make a useful tool for the field? We introduce a mapping tool that allows you to take a new data set and match it to the classifications we’ve defined in MetaCoNGA. This has many uses-

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Paul Thomas @pgtimmune.bsky.social · Jul 14

For each population we define a TCR motif and GEX profile, curating known natural Treg, NKT, ILTCK and similar populations, and several novel populations that we can isolate with similar resolution. The result displays the breadth of the unconventional T cell kingdom.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

What do these represent? Lots of known unconventional T cell subsets (MAITs, NKTs, various thymic developmental subsets, KIR+ CD8s, and Tregs) and lots of unknown discrete unconventional populations.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

The idea here is that within GEX space, we look for regions where a subset of neighbors have strongly statistically biased usage of specific TCR amino acids (in no particular order). We find a lot of these neighborhoods! (Over 70K for CD8 & 50K for CD4).

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Paul Thomas @pgtimmune.bsky.social · Jul 14

So that accounts for a big chunk of the conventional memory repertoire for both CD4 and CD8 T cells…but what about the rest of the repertoire? The second major analysis we perform is a GEX neighborhood-based amino acid bias assessment of the TCR.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

This convergence also suggests a shared biology across humans in the functional memory generated against each of these pathogens. One question we are exploring is whether individuals that diverge from this pattern might have worse (or better) pathogen control.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

As a result of this convergence, we have multiple clusters of known specificity (e.g. SARS, EBV, flu, or CMV) in close association with clusters of unknown specificity that we hypothesize are targeting the same pathogen. Experimental de-orphanization is underway.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

As we described in CoNGA 1.0, these TCR clusters converge in GEX space as well, demonstrating the profound effects of shared priming history. Even more dramatically, distinct epitopes targeting the same pathogen also converge in CoNGA GEX space.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

For some of these motifs, we have “re-discovered” classic immunodominant epitopes from flu (M1 58) or CMV (pp65 NLV). Many others are novel, though we can often assign an HLA restriction and may have a clue about the pathogen they target…

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Paul Thomas @pgtimmune.bsky.social · Jul 14

First, we perform an extensive “TCR convergence” analysis, finding regions of TCR space spanning individuals enriched for classic epitope-specific TCR motifs. We identify over 2000 such groups, representing the breadth of shared immunodominant responses across humans

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Paul Thomas @pgtimmune.bsky.social · Jul 14

MetaCoNGA merges data from diverse tissues, conditions (cancer, infections, healthy donors) and applies various applications of the CoNGA approach to this vast dataset. Here I’ll focus on three major results reported in the manuscript.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

Previously we released the CoNGA algorithm, linking TCR sequence and GEX to identify structure-function relationships in the T cell repertoire. After extensive curation of a wide array of public data (1900 subjects, 6 million cells) we present metaCoNGA.

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Paul Thomas @pgtimmune.bsky.social · Jul 14

How much of the TCR repertoire can we make sense of? Can your TCR and GEX data be put in the context of other conditions/tissues? How many varieties of T cells are in the repertoire zoo? All these questions (& more) addressed in our latest preprint: MetaCoNGA www.biorxiv.org/content/10.1... . a 🧵

Diverse modes of T cell receptor sequence convergence define unique functional and cellular phenotypes

Single-cell techniques allow concurrent study of gene activity and T cell receptor (TCR) sequences, identifying connections between TCR structure and cell traits. Expanding on our CoNGA software, we p...

www.biorxiv.org

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Reposted by Paul Thomas

David M. Perry @lollardfish.bsky.social · Apr 14

For transporting us beyond Seas to be tried for pretended offences

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Paul Thomas @pgtimmune.bsky.social · Apr 4

Thank you all again for the invitation and your amazing hospitality. This was a terrific meeting.

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Paul Thomas @pgtimmune.bsky.social · Mar 29

I love rancho gordo

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Reposted by Paul Thomas

Thomas Ramey Watson, Ph.D. @thomasrameywatson.bsky.social · Mar 28

Now is a uniquely terrible time to cut funding for HIV www.motherjones.com/politics/202...

Now is a uniquely terrible time to cut funding for HIV

New breakthrough drugs could eradicate AIDS. Why are we hobbling their distribution?

www.motherjones.com

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Reposted by Paul Thomas

Waggoner Lab @labwaggoner.bsky.social · Mar 28

Hematopoietic aging drives lung fibrosis and profibrotic macrophage influx, stalling their maturation via reduced Treg-derived IL-10 @sciimmunology.bsky.social @asmafarhat.bsky.social
www.science.org/doi/10.1126/...

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Reposted by Paul Thomas

Stacey Ogden 🦔 @labogden.bsky.social · Mar 28

Eric Skaar presented this week's hospital-wide Danny Thomas Lecture, and it was a spectacular talk! So far outside what I normally think about and my mind was blown 🤯 Such innovative use of imaging modalities! THIS is why it is important for all of us to attend talks outside our usual science lanes🧪

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Reposted by Paul Thomas

smtflu.bsky.social @smtflu.bsky.social · Mar 28

A collaborative work resulting in an exciting paper on influenza B virus and the differential immunity elicited by the Vic and Yam lineages.

Neuraminidase-specific antibodies drive differential cross-protection between contemporary FLUBV lineages | Science Advances www.science.org/doi/10.1126/...

Neuraminidase-specific antibodies drive differential cross-protection between contemporary FLUBV lineages

FLUBV Victoria infection elicits NA-specific antibodies that provide cross-lineage protection, possibly driving Yamagata decline.

www.science.org

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Reposted by Paul Thomas

TRAstonDrs @castltrastondrs.bsky.social · Mar 28

#MedSky🧪 #IDsky #immunosky #publichealth Age-associated changes to the bone marrow impact immune regulation in the lungs, which promotes inflammation and #fibrosis after lung injury.
@knapplab.bsky.social via @sciimmunology.bsky.social

www.science.org/doi/10.1126/...

An aging bone marrow exacerbates lung fibrosis by fueling profibrotic macrophage persistence

Hematopoietic aging drives lung fibrosis and profibrotic macrophage influx, stalling their maturation via reduced Treg-derived IL-10.

www.science.org

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