DOI: 10.5061/dryad.np5hqc02v
title: High-throughput screen to identify and optimize NOT gate receptors for cell therapy

description: Logic-gated engineered cells are an emerging therapeutic modality that can
 take advantage of molecular profiles to focus medical interventions on
 specific tissues in the body.  However, the increased complexity
 of these engineered systems may pose a challenge for prediction and
 optimization of their behavior.  Here we describe the design and
 testing of a flow-cytometry-based screening system to rapidly select
 functional inhibitory receptors from a pooled library of candidate
 constructs. In proof-of-concept experiments, this approach identifies
 inhibitory receptors that can operate as NOT gates when paired with
 activating receptors.  The method may be used to generate large
 datasets to train machine-learning models to better predict and optimize
 the function of logic-gated cell therapeutics.
description: <strong>Flow cytometry</strong>
   To evaluate surface expression of
 CARs, cells were stained with soluble EGFR-Fc or CEA-fc followed by
 APC-labeled anti-human IgG Fc. Briefly, 0.25-0.5 ug/mL of protein was
 incubated for 40-60 min at RT (room temperature). Two additional washes
 with FACS buffer (PBS + 2% BSA), were then performed, followed by staining
 with streptavidin-fluorophore (fluorophore = PE or APC, as indicated) at
 0.1 mg/mL at room temperature for 30 min. Washed twice with FACS buffer,
 cells were analyzed via flow cytometry for CAR expression (based on % of
 APC or PE-positive staining compared to unstained UTD cells, as
 indicated). To evaluate surface expression of the blocker, cells were
 labeled with biotinylated-pMHC probes, generated as described previously
 [16], tetramerized and prelabeled with streptavidin conjugated to an
 appropriate fluorochrome. After staining at 4C, median fluorescence
 intensity (MFI) was determined using a FACS Canto II flow cytometer. To
 evaluate surface expression of proteins on target cells, transiently
 transfected cells were tested with primary antibody. Briefly, after one
 wash with FACS buffer (PBS + 2% BSA), cells were stained with primary
 antibodies for 40-60 min at room temperature (1:100 dilution, according to
 the manufacturer’s instructions). After one wash with FACS buffer cells
 were incubated with secondary antibody (Anti-mouse IgG Alexa Fluor™ 647)
 for 40-60 min at room temperature (1:2000 dilution). After two additional
 washes with FACS buffer (including 1 ug/mL DAPI to stain dead cells),
 cells were analyzed via flow cytometry for target expression.
   <strong>FACS Co-culture
 Assays</strong>  
 CAR-expressing cells were co-cultured in a 1:1 ratio with
 target EGFR or CEA-expressing cells (HeLa WT, HeLa CEA+) or non EGFR or
 CEA-expressing cells (HeLa EGFR KO, HeLa WT) in RPMI medium for 18 hrs.
 Jurkat suspension cells were collected, washed in DPBS with EDTA 2mM and
 GFP fluorescence was assessed at FACSAria (BD) to quantify activation. In
 a similar fashion, Tmod-expressing cells were co-cultured in a 1:1 ratio
 with activator and blocker antigens expressing cells and GFP fluorescence
 was assessed to quantify blocking.  Median MFI and % activation and
 blocking was used to compare several conditions and optimize the best
 conditions for the assay.  
 Maximal activator enrichment was calculated from the flow data
 as %GFP(+) in the activated population to the right of the gate divided by
 %GFP(+) of the uninduced population to the right of the gate. Maximal
 blocker enrichment was calculated as %GFP(-) in the blocked population
 divided by %GFP(-) in the unblocked population.
description: # # High-throughput screen to identify and optimize NOT gate receptors for
 cell therapy
 \[[https://doi.org/10.5061/dryad.np5hqc02v](https://doi.org/10.5061/dryad.np5hqc02v)] Here we designed a flow-cytometry-based screening system to rapidly select functional inhibitory receptors from a pooled library of candidate constructs. This screen incorporates an NFAT-responsive reporter cell line to allow selection of reporter (+) and (-) cell populations by FACS after exposure to different stimuli. A library of blocker variants was constructed to test the concept of Tmod optimization and structure-activity inference from this cell-based functional screen. A Jurkat reporter clone was identified that maintained low background expression of green fluorescent protein (GFP) in the absence of a stimulus, and strong GFP induction by antigen. This Jurkat screening system for Tmod blockers was robust across multiple constructs, with signal:noise properties suggesting that enrichment of up to 15-fold was possible. Proof-of-concept experiments using a library of blocker variants demonstrated enrichment of active blockers. ## Description of the data and file structure Each folder correspond to the Figures indicated. Generally there is indication of the antigen to which the cells were exposed. Gating strategy: FSC vs SSC to gate for cells, when present DAPI positive correspond to live cells. ###### Abbreviation used: A = activator (EGFR or CEA), AB = activator and blocker (EGFR or CEA + HLA/NYESO or MSLN as indicated), A-B-  = activator and blocker negative  WT= Wild Type, JKT=Jurkat, CTL= Control, Pre-sort= Cells before round of sorting, ON= overnight ### **Description of each figure** ###### Fig 2C-EGFR CAR HLA02 Data are used in Figure 2C; CAR= EGFR, Blocker= HLA-A*02 Validation of Jurkat reporter cell line. HeLa cells that express A antigen (EGFR) were presented to the Jurkat reporter cell lines (transduced with EGFR CAR), to activate the NFAT promoter and GFP signal.  Maximal activator enrichment was calculated from the flow data as %GFP(+) in the activated population to the right of the gate divided by %GFP(+) of the uninduced population to the right of the gate. Next, Jurkat cells that expressed both the EGFR CAR and an HLA-A*02 blocker were cocultured with HeLa cells that express both target antigens (A(+)B(+)). Maximal blocker enrichment was calculated as %GFP(-) in the blocked population divided by %GFP(-) in the unblocked population.   ###### Fig 2C-CEA CAR MSLN Data are used in Figure 2C; CAR= CEA, Blocker= MSLN Validation of Jurkat reporter cell line. HeLa cells that express A antigen (CEA) were presented to the Jurkat reporter cell lines (transduced with CEA CAR), to activate the NFAT promoter and GFP signal.  Maximal activator enrichment was calculated from the flow data as %GFP(+) in the activated population to the right of the gate divided by %GFP(+) of the uninduced population to the right of the gate. Next, Jurkat cells that expressed both the CEA CAR and an MSLN blocker were cocultured with HeLa cells that express both target antigens (A(+)B(+)). Maximal blocker enrichment was calculated as %GFP(-) in the blocked population divided by %GFP(-) in the unblocked population.  ###### Fig 2C-EGFR CAR NYESO Data are used in Figure 2C; CAR= EGFR, Blocker= NYESO Validation of Jurkat reporter cell line. HeLa cells that express A antigen (EGFR) were presented to the Jurkat reporter cell lines (transduced with EGFR CAR), to activate the NFAT promoter and GFP signal.  Maximal activator enrichment was calculated from the flow data as %GFP(+) in the activated population to the right of the gate divided by %GFP(+) of the uninduced population to the right of the gate. Next, Jurkat cells that expressed both the EGFR CAR and an NYESO blocker were cocultured with HeLa cells that express both target antigens (A(+)B(+)). Maximal blocker enrichment was calculated as %GFP(-) in the blocked population divided by %GFP(-) in the unblocked population.  ###### Fig 3.Jurkat\_EGFR\_STRONG\_activation round Data are used in Figure 3. GFP signal of pre-sort and post-sorting (GFP positive (activated cells)) Jurkat reporter cells that express the strong EGFR CAR and blocker library were cocultured with A(+) HeLa cells that express EGFR, sorted for the GFP(+) population to enrich for cells able to activate.  ###### Fig 3.Jurkat\_EGFR\_STRONG\_Blocking round1 Data are used in Figure 3. GFP signal of pre-sort and post-sorting for blocking round 1(GFP positive (activated cells) and GFP negative (blocked cells)) Jurkat reporter activated cells were cocultured with A(+)B(+) HeLa cells that express EGFR and NY-ESO-1 trimer and sorted for GFP(+) and GFP(-) fractions.  ###### Fig 3.Jurkat\_EGFR\_STRONG\_Blocking round2 Data are used in Figure 3. GFP signal of pre-sort and post-sorting for blocking round 2(GFP positive (activated cells) and GFP negative (blocked cells)) Jurkat reporter sorted for GFP - fraction in the Blocking round 1, were cocultured with A(+)B(+) HeLa cells that express EGFR and NY-ESO-1 trimer and sorted for GFP(+) and GFP(-) fractions.