Paul Thomas
@pgtimmune.bsky.social
Division of Vaccine and Infectious Disease, Fred Hutchinson Cancer Center
TCRs, influenza virus, anti-tumor immunity, books, dogs, Venice
TCRs, influenza virus, anti-tumor immunity, books, dogs, Venice
Thank you Stacey!! They have all kinds of different birds out here, you need to visit.
November 7, 2025 at 9:10 PM
Thank you Stacey!! They have all kinds of different birds out here, you need to visit.
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!
July 14, 2025 at 11:52 PM
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!
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
July 14, 2025 at 11:52 PM
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...).
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.
July 14, 2025 at 11:52 PM
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.
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)?
July 14, 2025 at 11:52 PM
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)?
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-
July 14, 2025 at 11:52 PM
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-
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.
July 14, 2025 at 11:52 PM
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.
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.
July 14, 2025 at 11:52 PM
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.
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).
July 14, 2025 at 11:52 PM
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).
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.
July 14, 2025 at 11:52 PM
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.
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.
July 14, 2025 at 11:52 PM
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.
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.
July 14, 2025 at 11:52 PM
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.
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.
July 14, 2025 at 11:52 PM
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.
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…
July 14, 2025 at 11:52 PM
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…
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
July 14, 2025 at 11:52 PM
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
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.
July 14, 2025 at 11:52 PM
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.
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.
July 14, 2025 at 11:52 PM
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.