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!
14.07.2025 23:52 — 👍 1 🔁 0 💬 0 📌 0@pgtimmune.bsky.social
Department of Host-Microbe Interactions, St. Jude Children’s Research Hospital Memphis, TN TCRs, influenza virus, anti-tumor immunity, books, dogs, Venice
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!
14.07.2025 23:52 — 👍 1 🔁 0 💬 0 📌 0In 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...).
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0Alternatively, 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.
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0Maybe 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)?
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0Finally, 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-
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0For 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.
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0What 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.
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0The 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).
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0So 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.
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0This 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.
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0As 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.
14.07.2025 23:52 — 👍 2 🔁 1 💬 1 📌 0As 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.
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0For 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…
14.07.2025 23:52 — 👍 2 🔁 1 💬 1 📌 0First, 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
14.07.2025 23:52 — 👍 1 🔁 1 💬 1 📌 0MetaCoNGA 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.
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0Previously 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.
14.07.2025 23:52 — 👍 1 🔁 0 💬 1 📌 0How 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 🧵
14.07.2025 23:52 — 👍 28 🔁 10 💬 1 📌 0For transporting us beyond Seas to be tried for pretended offences
14.04.2025 16:42 — 👍 3595 🔁 1201 💬 42 📌 149Thank you all again for the invitation and your amazing hospitality. This was a terrific meeting.
04.04.2025 11:52 — 👍 1 🔁 0 💬 1 📌 0I love rancho gordo
29.03.2025 21:48 — 👍 1 🔁 0 💬 1 📌 0Now is a uniquely terrible time to cut funding for HIV www.motherjones.com/politics/202...
28.03.2025 19:14 — 👍 3 🔁 5 💬 1 📌 0Hematopoietic 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/...
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🧪
28.03.2025 19:28 — 👍 9 🔁 2 💬 1 📌 0A 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/...
#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/...
great thread on a great podcast!
27.03.2025 22:51 — 👍 4 🔁 1 💬 0 📌 0really only one right answer though
27.03.2025 23:13 — 👍 1 🔁 0 💬 0 📌 0Assessing CAR T cells cytotoxic capacity at the single-cell level can be tricky.
Here we provide a method for encapsulating >500.000 single CAR T cells with single target cells in droplets together with reagents to examine killing using standard flow cytometry:
app.jove.com/t/67657/drop...
I've got a new book extract in Wired!
The book also has lots of stories about the history of controlled trials, case-control studies, cohort studies, confounding, causal inference and more - most of which I suspect you won't have heard before! You can order from: proof.kucharski.io
"Nothing which was being done, no matter how stupid, no matter how many people knew and foretold the consequences, could be undone or prevented."
- Hannah Arendt about Germany sliding to fascism in the 1920s and 30s.