Ayla N.

Authors: Matthew J Spindler, Ayla L Nelson, Ellen K Wagner, Natasha Oppermans, John S Bridgeman, James M Heather, Adam S Adler, Michael A Asensio, Robert C Edgar, Yoong Wearn Lim, Everett H Meyer, Robert E Hawkins, Mark Cobbold, David S Johnson

T cells engineered to express antigen-specific T cell receptors (TCRs) are potent therapies for viral infections and cancer. However, efficient identification of clinical candidate TCRs is complicated by the size and complexity of T cell… Show more

Authors: Matthew J Spindler, Ayla L Nelson, Ellen K Wagner, Natasha Oppermans, John S Bridgeman, James M Heather, Adam S Adler, Michael A Asensio, Robert C Edgar, Yoong Wearn Lim, Everett H Meyer, Robert E Hawkins, Mark Cobbold, David S Johnson

T cells engineered to express antigen-specific T cell receptors (TCRs) are potent therapies for viral infections and cancer. However, efficient identification of clinical candidate TCRs is complicated by the size and complexity of T cell repertoires and the challenges of working with primary T cells. Here, we present a high-throughput method to identify TCRs with high functional avidity from diverse human T cell repertoires. The approach uses massively parallel microfluidics to generate libraries of natively paired, full-length TCRαβ clones, from millions of primary T cells, which are then expressed in Jurkat cells. The TCRαβ-Jurkat libraries enable repeated screening and panning for antigen-reactive TCRs using peptide:MHC binding and cellular activation. We captured >2.9 million natively paired TCRαβ clonotypes from six healthy human donors and identified rare (<0.001% frequency) viral antigen–reactive TCRs. We also mined a tumor-infiltrating lymphocyte (TIL) sample from a melanoma patient and identified several tumor-specific TCRs, which, after expression in primary T cells, led to tumor cell killing. Show less

Authors: Matthew J Spindler, Ayla L Nelson, James M Heather, Ellen K Wagner, Adam S Adler, David S Johnson.

A major goal of T cell research is to profile the repertoire of antigen-reactive TCRs targeting specific peptide:MHCs (pMHC). Single cell sorting of pMHC-binding T cells using multimers and ex vivo antigen expansion are the current gold standards for identifying antigen-reactive primary T cells. However, functional validation of the TCRs identified by these approaches requires… Show more

Authors: Matthew J Spindler, Ayla L Nelson, James M Heather, Ellen K Wagner, Adam S Adler, David S Johnson.

A major goal of T cell research is to profile the repertoire of antigen-reactive TCRs targeting specific peptide:MHCs (pMHC). Single cell sorting of pMHC-binding T cells using multimers and ex vivo antigen expansion are the current gold standards for identifying antigen-reactive primary T cells. However, functional validation of the TCRs identified by these approaches requires resource intensive cloning of each individual TCRαβ pair. Additionally, primary T cells, especially tumor infiltrating lymphocytes (TILs), are a limited resource, which restricts the number of antigens that can be screened.

To address this, we developed a microfluidic approach to capture and functionally express natively-paired TCRαβ libraries from millions of single T cells. Unlike DNA barcoding approaches that mark single cells by adding a sequence tag, we physically link the TCRα-TCRβ chains to generate sequencing and full-length expression libraries which we introduce into Jurkat cells for functional testing.

Using these methods, we captured over 2.9 million TCRαβ clonotypes from six healthy PBMC donors and over 0.5 million from expanded melanoma TIL samples. We applied pMHC binding and cellular activation screens to identify and validate 14 TCRs reactive to common viral and tumor associated antigens with starting library frequencies of <0.0001 – 0.3% and functional avidities ranging from 0.3 – 592nM. We found that including the cellular activation screen reduced our false-positive TCR discovery rate from 65% for pMHC binding alone to 18%. We are further developing these cellular activation enrichment approaches and applying them to broadly profile anti-tumor TCR reactivity from TILs. Show less

Authors: Angélica V Medina-Cucurella, Rena A Mizrahi, Michael A Asensio, Robert C Edgar, Jackson Leong, Renee Leong, Yoong Wearn Lim, Ayla Nelson, Ariel R Niedecken, Jan Fredrik Simons, Matthew J Spindler, Kacy Stadtmiller, Nicholas Wayham, Adam S Adler, David S Johnson


To discover therapeutically relevant antibody candidates, many groups use mouse immunization followed by hybridoma generation or B cell screening. One modern approach is to screen B cells by generating natively paired… Show more

Authors: Angélica V Medina-Cucurella, Rena A Mizrahi, Michael A Asensio, Robert C Edgar, Jackson Leong, Renee Leong, Yoong Wearn Lim, Ayla Nelson, Ariel R Niedecken, Jan Fredrik Simons, Matthew J Spindler, Kacy Stadtmiller, Nicholas Wayham, Adam S Adler, David S Johnson


To discover therapeutically relevant antibody candidates, many groups use mouse immunization followed by hybridoma generation or B cell screening. One modern approach is to screen B cells by generating natively paired single chain variable fragment (scFv) display libraries in yeast. Such methods typically rely on soluble antigens for scFv library screening. However, many therapeutically relevant cell-surface targets are difficult to express in a soluble protein format, complicating discovery. In this study, we developed methods to screen humanized mouse-derived yeast scFv libraries using recombinant OX40 protein in cell lysate. We used deep sequencing to compare screening with cell lysate to screening with soluble OX40 protein, in the context of mouse immunizations using either soluble OX40 or OX40-expressing cells and OX40-encoding DNA vector. We found that all tested methods produce a unique diversity of scFv binders. However, when we reformatted forty-one of these scFv as full-length monoclonal antibodies (mAbs), we observed that mAbs identified using soluble antigen immunization with cell lysate sorting always bound cell surface OX40, whereas other methods had significant false positive rates. Antibodies identified using soluble antigen immunization and cell lysate sorting were also significantly more likely to activate OX40 in a cellular assay. Our data suggest that sorting with OX40 protein in cell lysate is more likely than other methods to retain the epitopes required for antibody-mediated OX40 agonism. Show less

Authors: Baohua Li, Michelle Tang, Céline Caseys, Ayla Nelson, Marium Zhou, Xue Zhou, Siobhan M Brady, Daniel J Kliebenstein

Plants integrate internal and external signals to finely coordinate growth and defense allowing for maximal fitness within a complex environment. One common model for the relationship between growth and defense is a trade-off model in which there is a simple negative interaction between growth and defense theoretically driven by energy costs. However, there is a… Show more

Authors: Baohua Li, Michelle Tang, Céline Caseys, Ayla Nelson, Marium Zhou, Xue Zhou, Siobhan M Brady, Daniel J Kliebenstein

Plants integrate internal and external signals to finely coordinate growth and defense allowing for maximal fitness within a complex environment. One common model for the relationship between growth and defense is a trade-off model in which there is a simple negative interaction between growth and defense theoretically driven by energy costs. However, there is a developing consensus that the coordination of growth and defense likely involves a more conditional and intricate connection. To explore how a transcription factor network may coordinate growth and defense, we used high-throughput phenotyping to measure growth and flowering in a set of single and pairwise mutants previously linked to the aliphatic glucosinolate defense pathway. Showing the link between growth and aliphatic glucosinolate defense, 17 of the 20 tested TFs significantly influence plant growth and/or flowering time. These effects were conditional upon the environment, age of the plant and more critically varied amongst the phenotypes when using the same genotype. The phenotypic effects of the TF mutants on SC GLS accumulation and on growth were not correlated, which indicating that there is not a simple energetic trade-off for growth and defense. We propose that large transcription factor networks create a system to integrate internal and external signals and separately modulate growth and defense traits. Show less

Authors: Baohua Li, Michelle Tang, Ayla Nelson, Hart Caligagan, Xue Zhou, Caitlin Clark-Wiest, Richard Ngo, Siobhan M. Brady, and Daniel J. Kliebenstein

Plants use diverse mechanisms influenced by vast regulatory networks of indefinite scale to adapt to their environment. These regulatory networks have an unknown potential for epistasis between genes within and across networks. To test for epistasis within an adaptive trait genetic network, we generated and tested 47 Arabidopsis thaliana… Show more

Authors: Baohua Li, Michelle Tang, Ayla Nelson, Hart Caligagan, Xue Zhou, Caitlin Clark-Wiest, Richard Ngo, Siobhan M. Brady, and Daniel J. Kliebenstein

Plants use diverse mechanisms influenced by vast regulatory networks of indefinite scale to adapt to their environment. These regulatory networks have an unknown potential for epistasis between genes within and across networks. To test for epistasis within an adaptive trait genetic network, we generated and tested 47 Arabidopsis thaliana double mutant combinations for 20 transcription factors, which all influence the accumulation of aliphatic glucosinolates, the defense metabolites that control fitness. The epistatic combinations were used to test if there is more or less epistasis depending on gene membership within the same or different phenotypic sub-networks. Extensive epistasis was observed between the transcription factors, regardless of sub-network membership. Metabolite accumulation displayed antagonistic epistasis, suggesting the presence of a buffering mechanism. Epistasis affecting enzymatic estimated activity was highly conditional on the tissue and environment and shifted between both antagonistic and synergistic forms. Transcriptional analysis showed that epistasis shifts depend on how the trait is measured. Because the 47 combinations described here represent a small sampling of the potential epistatic combinations in this genetic network, there is potential for significantly more epistasis. Additionally, the main effect of the individual gene was not predictive of the epistatic effects, suggesting that there is a need for further studies. Show less