Publications From the Birnbaum Lab

The latest publications are found below. To review older publications from Michael Birnbaum, access them here:

Publication Archive

Identification of highly cross-reactive mimotopes for a public T cell response in murine melanoma. Grace, B. E., Backlund, C. M., Morgan, D. M., Kang, B. H., Singh, N. K., Huisman, B. D., Rappazzo, C. G., Moynihan, K. D., Maiorino, L., Dobson, C. S., Kyung, T., Gordon, K. S., Holec, P. V., Mbah, O. C., Garafola, D., Wu, S., Love, J. C., Wittrup, K. D., Irvine, D. J., & Birnbaum, M. E. Frontiers in Immunology, 13 (2022).

DOI: https://doi.org/10.3389/fimmu.2022.886683

A high-throughput yeast display approach to profile pathogen proteomes for MHC-II binding. Huisman, B. D., Dai, Z., Gifford, D. K., & Birnbaum, M. E. ELife, 11 (2022).

DOI: https://doi.org/10.7554/elife.78589

Screening for CD19-specific chimaeric antigen receptors with enhanced signalling via a barcoded library of intracellular domains.Gordon, K. S., Kyung, T., Perez, C. R., Holec, P. V., Ramos, A., Zhang, A. Q., Agarwal, Y., Liu, Y., Koch, C. E., Starchenko, A., Joughin, B. A., Lauffenburger, D. A., Irvine, D. J., Hemann, M. T., & Birnbaum, M. E. Nature Biomedical Engineering, 6(7), 855–866 (2022).

DOI: https://doi.org/10.1038/s41551-022-00896-0

Proteome-scale screening to identify high-expression signal peptides with minimal N-terminus biases via yeast display. Holec, P. V., Camacho, K. V., Breuckman, K. C., Mou, J., & Birnbaum, M. E. ACS Synthetic Biology, 11(7), 2405–2416 (2022).

DOI: https://doi.org/10.1021/acssynbio.2c00101

Yeast display for the identification of peptide-MHC ligands of immune receptors. Huisman, B. D., Grace, B. E., Holec, P. V., & Birnbaum, M. E. Methods in Molecular Biology, 263–291 (2022).

DOI: https://doi.org/10.1007/978-1-0716-2285-8_15

Antigen identification and high-throughput interaction mapping by reprogramming viral entry. Dobson, C. S., Reich, A. N., Gaglione, S., Smith, B. E., Kim, E. J., Dong, J., Ronsard, L., Okonkwo, V., Lingwood, D., Dougan, M., Dougan, S. K., & Birnbaum, M. E. Nature Methods, 19(4), 449–460 (2022).

DOI: https://doi.org/10.1038/s41592-022-01436-z

Machine learning optimization of peptides for presentation by class II MHCs. Dai, Z., Huisman, B. D., Zeng, H., Carter, B., Jain, S., Birnbaum, M. E., & Gifford, D. K. Bioinformatics, 37(19), 3160–3167 (2021).

DOI: https://doi.org/10.1093/bioinformatics/btab131

Repertoire-scale determination of class II MHC peptide binding via yeast display improves antigen prediction. Rappazzo, C. G., Huisman, B. D., & Birnbaum, M. E. Nature Communications, 11(1) (2020).

DOI: https://doi.org/10.1038/s41467-020-18204-2

A Bayesian framework for high-throughput T cell receptor pairing. Holec, P. V., Berleant, J., Bathe, M., & Birnbaum, M. E. Bioinformatics, 35(8), 1318–1325 (2018).

DOI: https://doi.org/10.1093/bioinformatics/bty801