amitava banerjee

amitava banerjee

@amitava-immuno.bsky.social

@cshlnews.bsky.social postdoc with @hannahvmeyer.bsky.social and Saket Navlakha • How your T cells know it's you • Develops immuno tools named after Gotham characters: github.com/meyer-lab-cshl/BATMAN 🦇

834 Followers 2,798 Following 21 Posts Joined Apr 2025
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1 month ago

Amazing work, wondering if genome-wide antigen screens like TScan would reveal any new targets!

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4 months ago

Best conference I attended in a while, captures the full breadth of biophysics. So many refreshing ideas to understand living systems 🦋🐦‍⬛🪰🦠🪸🐙

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4 months ago

Amazing! If this is useful, we developed an active learning framework in our BATMAN paper to identify the binding motifs rapidly by testing only a few mutant antigens. Happy to chat more..

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4 months ago

Sounds so exciting! Any plans of doing antigen mutagenesis to find cross-reactivity patterns of these TCRs?

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6 months ago
Mechanistic insights into MET exon 14 skipping mutations and their role in tumor progression The MET receptor tyrosine kinase is a pivotal regulator of cellular survival, motility, and proliferation. Mutations leading to skipping of exon 14 (METΔex14) within the juxtamembrane domain of MET im...

Authoritative review from The one and only @ghoshonthemove.bsky.social ☺️on her doctoral work on NSCLC 🫁 @mcgillgci.bsky.social

portlandpress.com/biochemsoctr...

Need to stay tuned to see if these mutations can generate targetable neoantigens in tricky low-TMB cancers

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7 months ago

Thanks for the shout-out!!🦇

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7 months ago
Illustration of the expression-controlled trade-off between the benefit of protection range and the cost of autoimmunity in anti-phage defense systems. Model integrating the relationship between T cell function, TCR affinity, and positive/negative regulators modulating cell responsiveness. A panel of CD8 T lymphocytes engineered to express antitumoral TCRs with incremental affinities toward the HLA-A2/NY-ESO-1 epitope (x-axis) was assessed for functional capacity (y-axis). An optimal window of TCR-pMHC affinity can be detected in the upper natural range (K D from 5 to 1 μM), corresponding to the range where most peripheral nonself-/virus-specific T cells can be detected. We recently described how positive regulators of T cell function including CD28 and TNFR cofactors are enriched in T cells lying within the optimal affinity window and how the inhibitory receptor PD-1 and SHP-1 phosphatase are involved in restricting T cell activation and responsiveness in TCR-engineered CD8 T cells of very high supraphysiological affinities. On-target toxicity is known to follow the functional and activatory signatures of CD8 T cells, while off-target responsiveness and toxicity are described to increase along TCR-pMHC affinity, within the supranatural affinity range. With differing binding affinities of the T cell receptor (TCR) repertoires of Treg and Tconv cells to self- and non-self-antigens, the Treg-Tconv cellular circuit can mount an effective anti-pathogen immune response without causing excessive immunopathology. Infection by a foreign pathogen, accompanied by innate immune activation and presentation of foreign antigens, promotes an effector Tconv response which is needed for pathogen clearance. However, if pathogen clearance by effector Tconv cells results in excessive self-tissue damage, the self-antigens generated and presented to Tregs can strengthen Treg-mediated immunosuppression, helping to reign in the effector Tconv response and tissue damage. The circuit is capable of striking a delicate balance between Tconv and Treg responses, allowing for effective pathogen clearance while restraining immunopathology.

Autoimmunity vs cross-reactive protection against evolving pathogens by immune systems

1. www.nature.com/articles/s41...
2. oncohemakey.com/assessing-t-...
3. pmc.ncbi.nlm.nih.gov/articles/PMC...

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7 months ago
Preview
BATMAN Signals T Cell Receptor Crossreactivity A new AI tool that models how variations in peptides change T cell receptor binding could help design immunotherapies with fewer off-target effects.

Our latest work featured in The Scientist! Sneha Khedkar Did a great job in summarizing the work accessibly while retaining some of the fine details. Happy reading!

www.the-scientist.com/batman-signa...

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7 months ago

Looking forward to seeing immune systems included in these lectures one day. Hopefully that is not too ambitious...

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7 months ago

So cool but did you skip the tangled worms 🪱?

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7 months ago
Cold Spring Harbor Laboratory website screenshot showing ribbons in blue, and a cartoon of bats emerging from a cave with a bright red round object looking like a virus in the back. Title reads "BATMAN brings TCR therapy out of the shadows". Subtitle reads "A new AI model developed by CSHL quantitative biologists could help improve immunotherapy treatments not only for cancer but all human illness."

Gotta say the cshl.edu website looks extra cool today

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7 months ago

@cshlnews.bsky.social @samueldiamond.bsky.social Thanks for the feature 🧡

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7 months ago

Got new #TCR-pMHC data to send our way into BATCAVE? Wanna try BATMAN to predict targets of your #TCR? We would love to hear from you!

💽Database+codes: github.com/meyer-lab-cs...

💻BATMAN software + tutorials: github.com/meyer-lab-cs...

🦇Lets decode TCR-pMHC logic, one mutation at a time🦇

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7 months ago
Alt Text: Infographic summarizing a study on T cell receptor (TCR) activation by mutant epitopes. The graphic is divided into three sections: Database (top panel): Describes a dataset with over 22,000 TCR-pMHC pairs, involving more than 150 activated TCRs and 25 mutagenized epitopes, covering both MHC class I and II, aggregated from 20+ years of experiments. A heatmap of epitope mutations and TCR structures is illustrated. Model (middle panel): Shows the BATMAN model for predicting TCR activation. The model combines an amino acid mutation similarity matrix with a learned mutation position weight profile and an MHC binding factor, outputting a prediction of TCR activation. Predictions (bottom panel): Highlights two applications — predicting tissue targets of cancer-specific TCRs and T cell responses to mutant viral antigens — accompanied by illustrative icons of organs, T cells, and viruses.

First postdoc paper with @hannahvmeyer.bsky.social on #TCR cross-reactivity database & modeling out now in Cell Systems: doi.org/10.1016/j.ce...

BATCAVE database + Paper codes: github.com/meyer-lab-cs...

BATMAN + Tutorial Notebooks: github.com/meyer-lab-cs...

#ImmunoSky #T-cells #CancerImmunology

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7 months ago

Thrilled to visit @hhmijanelia.bsky.social to share how fine mapping of large-scale TCR-antigen interaction networks are revealing design principles and physical biology of the adaptive immune system! #ImmunoSky

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9 months ago
Network Science Resources | COMBINE

We compiled some of our favorites here (might be slightly outdated now): www.combine.umd.edu/network-scie...

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9 months ago
Post image

Third #ATCR25 talk by Hannah Meyer on using BATMAN to model the TCR cross reactivity space.

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9 months ago

Catch our latest work on modeling TCR cross-reactivity here

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10 months ago

Really amazing work, looking forward to the mutational scan data for our TCR cross-reactivity modeling work: pmc.ncbi.nlm.nih.gov/articles/PMC... :)

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10 months ago
Holding an abstract book for "Systems Immunology" conference, blossoms in the background

Nice day to start the CSHL #cshlsysimm @cshlmeetings.bsky.social Meeting

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10 months ago

Starting tomorrow with an exciting speaker lineup! Catch up with our work on thymic negative selection and T cell cross-reactivity! @cshlmeetings.bsky.social

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10 months ago

Catch up with some of my latest TCR work, to be presented by my PI, Dr. Hannah Meyer

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1 year ago
Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction Figure 1 Figure 2 Figure 3

Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction [updated]
BATCAVE & BATMAN predict TCR activation, off-target effects, & polyclonal responses.

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