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The ability to selectively bind to antigenic peptides and secrete effector molecules can define rare and low-affinity populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs inducing the secretion of effector molecules including IFN-γ and granzyme B that are accumulated on nanovials, allowing sorting based on both binding and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αβ-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes and secretions with oligo-barcoded detection antibodies, we could accurately link TCR sequences to specific targets and rank each TCR based on the corresponding cells secretion level. Using the technique, we identified an expanded repertoire of functional TCRs targeting viral antigens with high specificity and found rare TCRs with activity against cancer-specific splicing-enhanced epitopes.

CAR (chimeric antigen receptor) T cell therapy has shown clinical success in treating hematological malignancies, but its treatment of solid tumors has been limited. One major challenge is on-target, off-tumor toxicity, where CAR T cells also damage normal tissues that express the targeted antigen. To reduce this detrimental side-effect, Boolean-logic gates like AND-NOT gates have utilized an inhibitory CAR (iCAR) to specifically curb CAR T cell activity at selected nonmalignant tissue sites. However, the strategy seems inefficient, requiring high levels of iCAR and its target antigen for inhibition. Using a TROP2-targeting iCAR with a single PD1 inhibitory domain to inhibit a CEACAM5-targeting CAR (CEACAR), we observed that the inefficiency was due to a kinetic delay in iCAR inhibition of cytotoxicity. To improve iCAR efficiency, we modified three features of the iCAR-the avidity, the affinity, and the intracellular signaling domains. Increasing the avidity but not the affinity of the iCAR led to significant reductions in the delay. iCARs containing twelve different inhibitory signaling domains were screened for improved inhibition, and three domains (BTLA, LAIR-1, and SIGLEC-9) each suppressed CAR T function but did not enhance inhibitory kinetics. When inhibitory domains of LAIR-1 or SIGLEC-9 were combined with PD-1 into a single dual-inhibitory domain iCAR (DiCARs) and tested with the CEACAR, inhibition efficiency improved as evidenced by a significant reduction in the inhibitory delay. These data indicate that a delicate balance between CAR and iCAR signaling strength and kinetics must be achieved to regulate AND-NOT gate CAR T cell selectivity.

Alternative splicing (AS) is prevalent in cancer, generating an extensive but largely unexplored repertoire of novel immunotherapy targets. We describe Isoform peptides from RNA splicing for Immunotherapy target Screening (IRIS), a computational platform capable of discovering AS-derived tumor antigens (TAs) for T cell receptor (TCR) and chimeric antigen receptor T cell (CAR-T) therapies. IRIS leverages large-scale tumor and normal transcriptome data and incorporates multiple screening approaches to discover AS-derived TAs with tumor-associated or tumor-specific expression. In a proof-of-concept analysis integrating transcriptomics and immunopeptidomics data, we showed that hundreds of IRIS-predicted TCR targets are presented by human leukocyte antigen (HLA) molecules. We applied IRIS to RNA-seq data of neuroendocrine prostate cancer (NEPC). From 2,939 NEPC-associated AS events, IRIS predicted 1,651 epitopes from 808 events as potential TCR targets for two common HLA types (A*02:01 and A*03:01). A more stringent screening test prioritized 48 epitopes from 20 events with "neoantigen-like" NEPC-specific expression. Predicted epitopes are often encoded by microexons of ≤30 nucleotides. To validate the immunogenicity and T cell recognition of IRIS-predicted TCR epitopes, we performed in vitro T cell priming in combination with single-cell TCR sequencing. Seven TCRs transduced into human peripheral blood mononuclear cells (PBMCs) showed high activity against individual IRIS-predicted epitopes, providing strong evidence of isolated TCRs reactive to AS-derived peptides. One selected TCR showed efficient cytotoxicity against target cells expressing the target peptide. Our study illustrates the contribution of AS to the TA repertoire of cancer cells and demonstrates the utility of IRIS for discovering AS-derived TAs and expanding cancer immunotherapies.

The ability to selectively bind to antigenic peptides and secrete cytokines can define populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with millions of peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs and secrete cytokines on nanovials, allowing sorting based on both affinity and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αβ-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes we could link TCR sequence to targets with 100% accuracy. We identified with high specificity an expanded repertoire of functional TCRs targeting viral antigens compared to standard techniques.

Tissue-specific antigens can serve as targets for adoptive T cell transfer-based cancer immunotherapy. Recognition of tumor by T cells is mediated by interaction between peptide-major histocompatibility complexes (pMHCs) and T cell receptors (TCRs). Revealing the identity of peptides bound to MHC is critical in discovering cognate TCRs and predicting potential toxicity. We performed multimodal immunopeptidomic analyses for human prostatic acid phosphatase (PAP), a well-recognized tissue antigen. Three physical methods, including mild acid elution, coimmunoprecipitation, and secreted MHC precipitation, were used to capture a thorough signature of PAP on HLA-A*02:01. Eleven PAP peptides that are potentially A*02:01-restricted were identified, including five predicted strong binders by NetMHCpan 4.0. Peripheral blood mononuclear cells (PBMCs) from more than 20 healthy donors were screened with the PAP peptides. Seven cognate TCRs were isolated which can recognize three distinct epitopes when expressed in PBMCs. One TCR shows reactivity toward cell lines expressing both full-length PAP and HLA-A*02:01. Our results show that a combined multimodal immunopeptidomic approach is productive in revealing target peptides and defining the cloned TCR sequences reactive with prostatic acid phosphatase epitopes.

Cross-reactivity and direct killing of target cells remain underexplored for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-specific CD8+ T cells. Isolation of T cell receptors (TCRs) and overexpression in allogeneic cells allows for extensive T cell reactivity profiling. We identify SARS-CoV-2 RNA-dependent RNA polymerase (RdRp/NSP12) as highly conserved, likely due to its critical role in the virus life cycle. We perform single-cell TCRαβ sequencing in human leukocyte antigen (HLA)-A∗02:01-restricted, RdRp-specific T cells from SARS-CoV-2-unexposed individuals. Human T cells expressing these TCRαβ constructs kill target cell lines engineered to express full-length RdRp. Three TCR constructs recognize homologous epitopes from common cold coronaviruses, indicating CD8+ T cells can recognize evolutionarily diverse coronaviruses. Analysis of individual TCR clones may help define vaccine epitopes that can induce long-term immunity against SARS-CoV-2 and other coronaviruses.

T cell receptors (TCRs) are generated by somatic recombination of V/D/J segments to produce up to 1015 unique sequences. Highly sensitive and specific techniques are required to isolate and identify the rare TCR sequences that respond to antigens of interest. Here, we describe the use of mRNA sequencing via cross-linker regulated intracellular phenotype (CLInt-Seq) for efficient recovery of antigen-specific TCRs in cells stained for combinations of intracellular proteins such as cytokines or transcription factors. This method enables high-throughput identification and isolation of low-frequency TCRs specific for any antigen. As a proof of principle, intracellular staining for TNFα and IFNγ identified cytomegalovirus (CMV)- and Epstein-Barr virus (EBV)-reactive TCRs with efficiencies similar to state-of-the-art peptide-MHC multimer methodology. In a separate experiment, regulatory T cells were profiled based on intracellular FOXP3 staining, demonstrating the ability to examine phenotypes based on transcription factors. We further optimized the intracellular staining conditions to use a chemically cleavable primary amine cross-linker compatible with current single-cell sequencing technology. CLInt-Seq for TNFα and IFNγ performed similarly to isolation with multimer staining for EBV-reactive TCRs. We anticipate CLInt-Seq will enable droplet-based single-cell mRNA analysis from any tissue where minor populations need to be isolated by intracellular markers.

BackgroundIn drug-drug interactions, there are surprising cases in which the growth inhibition of bacteria by a single antibiotic decreases when a second antibiotic is added. These interactions are termed suppressive and have been argued to have the potential to limit the evolution of resistance. Nevertheless, little attention has been given to suppressive interactions because clinical studies typically search for increases in killing efficiency and because suppressive interactions are believed to be rare based on pairwise studies.ResultsHere, we quantify the effects of single-, double-, and triple-drug combinations from a set of 14 antibiotics and 3 bacteria strains, totaling 364 unique three-drug combinations per bacteria strain. We find that increasing the number of drugs can increase the prevalence of suppressive interactions: 17% of three-drug combinations are suppressive compared to 5% of two-drug combinations in this study. Most cases of suppression we find (97%) are "hidden" cases for which the triple-drug bacterial growth is less than the single-drug treatments but exceeds that of a pairwise combination.ConclusionsWe find a surprising number of suppressive interactions in higher-order drug combinations. Without examining lower-order (pairwise) bacterial growth, emergent suppressive effects would be missed, potentially affecting our understanding of evolution of resistance and treatment strategies for resistant pathogens. These findings suggest that careful examination of the full factorial of drug combinations is needed to uncover suppressive interactions in higher-order combinations.

Understanding how multiple stressors interact is needed to predict the dynamical outcomes of diverse biological systems, ranging from drug-resistant pathogens that are combated and treated with combination drug therapies to ecosystems impacted by environmental toxicants or disturbances. Nevertheless, extensive studies of higher-order (more than two component) interactions have been lacking. Here, we conduct experiments using 20 three-drug combinations and their effects on the bacterial growth of Escherichia coli We report our measurements of growth rates in single, pairwise and triple-drug combinations. To uncover emergent interactions, we derive a simple framework to calculate expectations for three-way interactions based on the measured impact of each individual stressor and of each pairwise interaction. Using our framework, we find that (i) emergent antagonisms are more common than emergent synergies and (ii) emergent antagonisms are more common and emergent synergies are more rare than would be inferred from measures of net effects that do not disentangle pairwise interactions from three-way interactions.

We examined the mutagenic specificity of the widely used antibiotic ciprofloxacin (CPR), which displays weak to moderate mutagenic activity in several bacteria and generates short in-frame deletions in rpoB in Staphylococcus aureus To determine the spectrum of mutations in a system where any gene knockout would result in a recovered mutant, including frameshifts and both short and long deletions, we examined CPR-induced mutations in the thymidylate synthase-encoding thyA gene. Here, any mutation resulting in loss of thymidylate synthase activity generates trimethoprim (Trm) resistance. We found that deletions and insertions in all three reading frames predominated in the spectrum. They tend to be short deletions and cluster in two regions, one being a GC-rich region with potential extensive secondary structures. We also exploited the well-characterized rpoB-Rif(r) system in Escherichia coli to determine that cells grown in the presence of sublethal doses of CPR not only induced short in-frame deletions in rpoB, but also generated base substitution mutations resulting from induction of the SOS system. Some of the specific point mutations prominent in the spectrum of a strain that overproduces the dinB-encoded Pol IV were also present after growth in CPR. However, these mutations disappeared in CPR-treated dinB mutants, whereas the deletions remained. Moreover, CPR-induced deletions also occurred in a strain lacking all three SOS-induced polymerases. We discuss the implications of these findings for the consequences of overuse of CPR and other antibiotics.

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions-ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions.

Gram-negative bacteria are normally resistant to the antibiotic vancomycin (VAN), which cannot significantly penetrate the outer membrane. We used Escherichia coli mutants that are partially sensitive to VAN to study synergies between VAN and 10 other antibiotics representing six different functional categories. We detected strong synergies with VAN and nitrofurantoin (NTR) and with VAN and trimethoprim (TMP) and moderate synergies with other drugs, such as aminoglycosides. These synergies are powerful enough to show the activity of VAN against wild-type E. coli at concentrations of VAN as low as 6.25 μg/ml. This suggests that a very small percentage of exogenous VAN does enter E. coli but normally has insignificant effects on growth inhibition or cell killing. We used the results of pairwise interactions with VAN and the other 10 antibiotics tested to place VAN into a functional category of its own, as previously defined by Yeh et al. (P. Yeh, A. I. Tschumi, and R. Kishony, Nat Genet 28:489-494, 2006, http://dx.doi.org/10.1038/ng1755).