ENGINEERING CYCLE

Wet Lab

Explore our step-by-step development of a modular phosphorylation-based signaling platform for programmable cancer cell therapies. Follow our engineering cycles as we engineer and validate custom receptors, expression systems and protein secretion platforms, building a standardized part collection that functions both independently and in integrated circuits. Learn how we achieved proof-of-concept by demonstrating sensing of tumor-relevant ligands like VEGF and TNF-α and coupling them to therapeutic outputs such as secretion of IL-12.

Dry Lab

Learn how we developed SPARC, our comprehensive digital companion for PHOENICS cell design. Discover how we integrated BindCraft for de novo binder design, implemented molecular dynamics simulations for binding affinity characterization, and built mathematical models of receptor dimerization and circuit dynamics. Find out how we created accurate dose-response predictions validated against wet-lab data, and developed a digital database that maps the behavior space of all possible circuit architectures for rapid prototyping.

HP

Discover our mission of a science-based, sustainable, and holistic approach to bridging the translational gap. Explore how we evolved from identifying crucial needs in translational education over hosting a high-profile panel discussion to developing a comprehensive roadmap of the regional innovation landscape. Learn about our journey through stakeholder engagement and dive into our Summer School program, School Workshops and an interactive learning platform that empowers young scientists with the knowledge and network to turn discovery into real-world impact.

Processing

Characterization of the PHOENICS Circuit Components

We directly validated phosphorylation of the SynSubstrate and confirmed that interaction between SynSubstrate and SynPhosphobinder depends on phosphorylation and increases with SynKinase levels. Finally, we seeked to connect the SH2 domain to a transcriptional reporter and identified promising constructs for future phosphorylation assays.

Iteration 1
Iteration 2
Iteration 3
Results Image

Figure 1: Schematic representation of SynSubstrate and SynKinase constructs designed the Western Blot.

DESIGN

The PHOENICS circuit relies on the phosphorylation of a tyrosine residue within a synthetic substrate (SynSubstrate) composed of three CD3ζ-derived ITAM repeats. Both the SynSubstrate and the truncated ABL kinase (SynKinase) catalyzing its phosphorylation were adapted from Yang et al. (2025). In this system, phosphorylation occurs through proximity-induced interaction mediated by complementary coiled-coils. SynKinase is a truncated ABL kinase fused to one half of the coiled-coil (ABL-bZipEE) and the SynSubstrate is fused to the other coiled-coil (CD3ζ-bZipRR). This kinase truncation prevents intrinsic binding between the enzyme and the substrate, ensuring that phosphorylation occurs exclusively upon their coiled-coil-mediated proximity. To validate these literature-derived components, we first designed a Western blot experiment to confirm protein expression in the cells and phosphorylation. We fused the SynSubstrate to triple Myc tag (3×Myc) to enable the detection of both phosphorylation and expression via immunostaining in a single experiment.

BUILD

For experimental validation, cells in a 12-well plate were transfected either with the substrate fused to a triple Myc tag (3×Myc) or with both the substrate and truncated ABL kinase carrying the complementary coiled-coil (Fig. 1). 48 hours post transfection, cells were lysed and total protein content was quantified. Equal amounts of protein (17 µg) from each sample were loaded into the wells of an SDS-PAGE gel and transferred on a membrane after running the PAGE. The blot was first probed with primary antibodies specific to phosphorylated tyrosine (pY) within the ITAM motif of the substrate, followed by secondary staining. Subsequently, an anti-Myc antibody was used to confirm the presence of the substrate in the samples.

Results Image

Figure 2: Western blot verification of SynSubstrate phosphorylation by SynKinase. HEK293T cells were transfected with 60 ng of SynSubstrate either alone or together with 55 ng of SynKinase. Phosphorylation was detected using a phospho-tyrosine-specific antibody. A strong phospho-tyrosine signal was observed only in the presence of SynKinase, confirming kinase-dependent phosphorylation of the SynSubstrate.

TEST

The immunoblot demonstrated the phosphorylation of the SynSubstrate only when SynKinase is co-expressed. In the α-pY staining (top panel), no phosphorylation was observed for the substrate expressed alone (lane 1), whereas a vivid phospho-tyrosine signal was detected only when SynKinase was present (lane 2). This suggests that the tyrosine on the substrate was phosphorylated by the SynKinase. In the α-Myc staining (bottom panel), it is not possible to directly compare the levels of expressed substrate between conditions, as the signal is influenced by residual anti-pY signal due to the reuse of the same secondary antibody without stripping. However, the presence of a distinct Myc band in both lanes demonstrates that SynSubstrate is present in both samples. Importantly, the sensitive anti-pY staining detects phosphorylation only in the SynKinase co-transfection, confirming that the substrate is not phosphorylated when SynKinase is absent (Fig. 2). This confirms that SynKinase specifically mediates tyrosine phosphorylation of the substrate.

LEARN

We were able to confirm that SynSubstrate phosphorylation only occurs when SynKinase is present. This indicates that native cellular kinases do not phosphorylate the substrate, confirming the orthogonality of phosphorylation.

Results Image

Figure 3: Design of the SpliFAST assay for the fluorescence readout of phosphorylation-mediated SynSub and SH2 interaction. The SynSubstrate, fused to the N-terminal fragment of SplitFAST (RspA[N]), is phosphorylated in the cytosol by SynKinase. The SH2 domain, acting as SynPhosphobinder, is fused to the complementary C-terminal fragment (RspA[C]) of SplitFAST. Upon phosphorylation, SynSubstrate interacts with the SH2 domain, promoting reconstitution of SplitFAST. Addition of the HMBR fluorogen induces fluorescence, which visualizes the phosphorylation-dependent protein–protein interaction and can be quantified by flow cytometry.

DESIGN

After successful validation of the SynSubstrate’s phosphorylation we aimed to investigate the semi-physiological interaction between the phosphorylated substrate and the signal-propagating SH2 domain, also referred to as SynPhosphobinder. It is considered semi-physiological because the pY-SH2 interaction is native, but the phosphorylation is driven by a different cellular kinase, not our SynKinase. We selected a recently published switchable fluorescence complementation reporter, SplitFAST (Tebo and Gautier, 2019). SplitFAST allows rapid and reversible detection of protein-protein interactions. The N-RspA(N) half of the split protein was fused to the SynSubstrate, and the complementary C-RspA(N) to the SH2 (Fig. 3). Only when the phosphorylated SynSubstrate interacts with the SH2 domain, the reporter protein is reassembled. Addition of the fluorogen HMBR triggers fluorescence in the reconstituted complex, visualizing the phosphorylation-mediated interaction.

BUILD

To evaluate the dynamic range of the SynSubstrate and SH2 interaction, cells were transfected with SplitFAST constructs alongside increasing amounts of ABL kinase. 100 ng of both RspA(N)-CD3𝜁-bZipRR and RspA(C)-SH2 were co-transfected. After 48 hours of expression, cells were trypsinized to generate a single-cell suspension, and the HMBR fluorogen was added. The fluorescence from reconstituted SplitFAST complexes was then quantified by flow cytometry, enabling detection of phosphorylation-dependent SynSubstrate and SH2 interactions.

TEST

Flow cytometry analysis revealed a clear shift toward higher fluorescence intensity in cells co-transfected with SynKinase, indicating successful reconstitution of the fluorescence reporter (Fig. 4). This shift demonstrates that phosphorylation of the SynSubstrate enables interaction with SH2, leading to SplitFAST complementation and fluorescence. Without SynKinase, fluorescence remained at background levels, confirming the specificity of the interaction. Additionally, increasing SynKinase expression produced a corresponding increase in fluorescence, indicative of a dose-dependent effect on phosphorylation and dimerization. At the highest SynKinase amounts, fluorescence plateaued, consistent with saturation of SynSubstrate phosphorylation and SH2 binding.

Results Image

Figure 4: Validation of the phosphorylation-dependent dimerization using SplitFAST.Y-axis description corresponds to the ng amounts of SynKinase (0-250 ng). 48 hours post-transfection, dimerization-dependent SplitFAST fluorescence was quantified by flow cytometry, employing excitation lasers at 488 nm and 561 nm. Emission was recorded at 525 nm for splitFAST (Ligand: TF Lime) and at 610 nm for constitutively expressed mCherry, serving as a transfection control. Data is depicted as the geometric mean of fluorescence +/- SEM with ~30000 single cells.

LEARN

These results demonstrate that phosphorylation induces a specific interaction between SynSubstrate and the SH2 domain (SynPhosphobinder). This provides a strong foundation for extending the SH2 module with additional signal transduction functionalities in future designs.

DESIGN

Results Image

Figure 5: Improved design of the phosphorylation-dependent transcription activator cleavage assay. Panel A: Final system design; Panel B: Rapalog-induced. Panel A: Upon phosphorylation-induced dimerization SynSubstrate, and SH2 fused to nTEV and cTEV fragments are brought together, restoring TEV protease activity. This enables cleavage of a membrane-tethered transcriptional activator at a TEV site, thereby releasing the activator. The released activator translocates to the nucleus to bind the 5x UAS sequence and drive NanoLuc expression.Panel B: Design of validation of TEV proteolytic activity upon rapalog-induced reconstitution.

Having successfully validated SynSubstrate phosphorylation and the phosphorylation-dependent interaction with the SH2 domain, we sought to translate a phosphorylation event into a quantifiable, high-throughput reporter output. To achieve a cost-effective and scalable readout, we engineered a system in which reporter gene expression is conditionally activated upon the interaction between the phosphorylated substrate and SH2.

We designed a membrane-anchored transcriptional activator coupled to a phosphorylation-dependent cleavage system. Specifically, the C-terminus of the split TEV protease (cTEV) was fused to the Synthetic Substrate (3xCD3ζ), and the N-terminus (nTEV) was fused to the SH2 domain. Upon phosphorylation, the substrate binds SH2, bringing the two parts of the splitTEV protease into proximity and reconstituting its enzymatic activity. The active TEV protease then cleaves the Gal4 DNA-binding domain (Gal4DBD) fused to a VP64 transcription factor (Gal4DBD-VP64) from the membrane tether. The released Gal4DBD-VP64 translocates to the nucleus and activates expression of the nano luciferase (NanoLuc) reporter gene under the 5x UAS binding site with minimal CMV promoter. This system would convert substrate phosphorylation into a measurable luminescent signal (Fig. 5A).

To validate rapalog-dependent reconstitution of TEV protease activity, we first tested whether rapalog-induced dimerization could restore proteolytic function. For this purpose, we fused the cTEV to FRB and the nTEV to FKBP, following designs reported in a recent publication (Vlahos et al., 2022). This construct enables chemically induced proximity between FKBP and FRB upon addition of rapalog, which is expected to bring together the splitTEV fragments and reconstitute enzymatic activity (Fig. 5B).

BUILD

After confirming successful cloning by sequencing, HEK293T cells were transfected with the constructs. 24 hours post-transfection, cells were induced with 200 nM AP21967 (Rapalog) or vehicle control (ethanol). 48 hours after transfection, cells were lysed and subjected to the Nano-Glo assay to measure luminescence. The NanoLuc luminescence readout was normalized to constitutively expressed firefly luciferase (FFLuc) levels present in all conditions to control for variation in transfection efficiency and cell number.

Results Image

Figure 6: Quantification of reporter expression activation using the Nano-Glo luminescence readout of membrane tethered transcription activator assay. For the Rapa-inducible Split TEV condition, HEK293T cells were transfected 24 hours post-seeding, with FRB-cTEV, FKBP-nTEV, and 5xUAS-NanoLuc plasmids, each at 20 ng per well. The positive control consisted of a construct encoding a fused Gal4DBD-VP64 transcription factor to provide constitutive NanoLuc expression. Additional control groups included a negative control lacking the Gal4DBD-VP64 membrane-tethered construct, a No TEV condition, and a Full TEV construct. All transfection conditions incorporated a FFLuc plasmid to normalize results. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates. Statistical significance was determined with Ordinary one-way ANOVA with Tukey’s multiple comparison test, with a single pooled variance. *p < 0.05, ****p < 0.001.

TEST

The transcriptional reporter assay demonstrated robust performance of the controls, with high luminescence observed in the positive control and no detectable signal in the negative control, confirming the absence of transcriptional leakage. Comparison of the ‘No TEV’ and ‘Full TEV’ conditions revealed no significant difference in reporter activity, indicating that the TEV protease system as configured could not detect phosphorylation-dependent events. Furthermore, induction with rapalog did not produce a significant increase in luminescence in the splitTEV group compared to the uninduced condition, suggesting that rapalog-induced dimerization failed to enable the desired transcriptional activation under these experimental parameters (Fig. 7).

LEARN

Overall, we were satisfied that the NanoLuc reporter showed high expression in the positive control and demonstrated no leakage in the negative control, confirming the reliability of the transcriptional readout. However, to circumvent the potential issues related to membrane embedding and rapid degradation observed with the initial design, we decided to focus on establishing an alternative system as discussed in a second cycle.

Optimization of Phosphorylation Readout Assay

We engineered a robust cytosolic phosphorylation reporter using split Gal4DBD/VP64 transcriptional activators. Signal sensitivity and specificity were enhanced through iterative optimization of SynKinase/SynPhosphatase concentration, nuclear-cytoplasmic localization of reporters, and fine-tuning of component stoichiometry, enabling simple and reliable detection of the substrate phosphorylation level.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Iteration 5
Iteration 6
Results Image

Figure 1: Improved design of the phosphorylation-dependent transcriptional reporter circuit. SynSubstrate undergoes phosphorylation in the cytosol by SynKinase and dephosphorylation by SynPhosphatase. Upon phosphorylation, the substrate translocates into the nucleus where it interacts with the nuclear-resident SynPhosphobinder. This interaction facilitates UAS-NanoLuc binding, producing the luminescence signal proportional to substrate phosphorylation.

DESIGN

Building on lessons from the previous engineering cycle, we moved forward with a new design focused on a fully cytosolic system to improve signal robustness and avoid issues related to membrane localization. We continued using the SynSubstrate, consisting of three CD3ζ-derived ITAM repeats, alongside the truncated ABL kinase (SynKinase). Additionally, a truncated form of PTPN1 (SynPhosphatase) was adapted from Yang et al., (2025). In this system, phosphorylation and dephosphorylation are controlled through proximity-induced interactions mediated by complementary coiled-coils. SynKinase is fused to one half of the coiled-coil (bZipEE), and SynPhosphatase is fused to the same bZipEE module. Both enzymes compete for the SynSubstrate, which is fused to the complementary coiled-coil (bZipRR), allowing proximity-dependent phosphorylation and dephosphorylation.

The new transcriptional readout is based on the proximity-driven assembly of a transcriptional activator complex composed of VP64 and the Gal4DBD. In this design, Gal4DBD is fused to the substrate (CD3z-Gal4DBD), while VP64 is fused to the SH2 domain (SH2-VP64, referred to as SynPhosphobinder). Upon phosphorylation of the substrate by the kinase, the SH2 domain binds the phosphorylated substrate, bringing VP64 and Gal4DBD together. This assembled complex translocates into the nucleus, where it activates transcription of the Nanoluciferase (NanoLuc) reporter gene under the 5xUAS repeats (UAS-NanoLuc), producing a luminescent readout of phosphorylation-dependent signaling (Fig. 1).

Results Image

Figure 2: Kinase and phosphatase activity assessment experiment. Quantification of phosphorylation-dependent transcriptional activation using the Nano-Glo luminescence readout. For the cytosolic transcriptional readout system, HEK293T cells were transfected with 20 ng 5xUAS-NanoLuc, 20 ng Gal4DBD-CD3ζ (substrate fusion), and 20 ng SH2-VP64 (transcriptional activator fusion) plasmids per well, 24 hours post-seeding. Experimental conditions included the addition of 30 ng kinase plasmid or/and 20 ng SynPhosphatase plasmid as indicated. The positive control contained Gal4DBD-VP64 fusion constructs for constitutive NanoLuc expression, and the negative control lacked the transcriptional activator components. All samples were co-transfected with 10 ng of FFLuc plasmid for normalization. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates.

BUILD

After confirming successful cloning by sequencing, HEK293T cells were transfected with the constructs. 48 hours after transfection, cells were lysed and subjected to the Nano-Glo assay to measure luminescence. The NanoLuc luminescence readout was normalized to constitutively expressed firefly luciferase (FFLuc) levels present in all conditions to control for variation in transfection efficiency and cell number.

TEST

The SynKinase condition produced a strong luminescence signal, matching the positive control with constitutively activated NanoLuc, demonstrating that phosphorylation of the substrate efficiently induces reporter expression through proximity-driven assembly of Gal4DBD-VP64. There was no detectable luminescence in the negative control, confirming the system’s switchability and tightness. Importantly, the addition of the SynPhosphatase completely abolished the phosphorylation-induced signal, despite the higher amount of kinase transfected relative to the SynPhosphatase (Fig. 2). These results confirm that the reporter reliably detects phosphorylation and that this signal can be fully suppressed by SynPhosphatase-mediated dephosphorylation, validating effective dynamic control in the circuit.

LEARN

In this second iteration, we created a reliable cytosolic transcriptional readout for phosphorylation that distinguishes specific activation from background and is switched off upon dephosphorylation. Having shown robust reporter induction and switchability by SynKinase and SynPhosphatase addition, the next step was to characterize this system more thoroughly.

DESIGN

For this titration experiment, the same plasmid components were used as before, but this iteration expanded the range of conditions to allow for more precise characterization of the dynamic range of phosphorylation-dependent reporter activation. Our goal was to determine the kinase concentration that produces a robust 'on' state - indicative of reporter sensitivity, and the minimal SynPhosphatase concentration required to fully suppress reporter activation, defining the 'off' state by canceling the phosphorylation signal. This enabled a quantitative assessment of system sensitivity, specificity, and effective thresholds for modulating the cytosolic transcriptional readout.

BUILD

Constructs for the new assay were cloned, sequenced, and transfected into HEK293T cells. For kinase titration, increasing amounts of kinase were used. For SynPhosphatase titration, each condition contained 20 ng of kinase to saturate phosphorylation, with increasing amounts of SynPhosphatase. The reporter system components - 20 ng 5xUAS NanoLuc, 20 ng Gal4DBD-CD3ζ, and 20 ng SH2-VP64 - were constant in all conditions. 48 hours after transfection, cells were lysed and NanoLuc expression was quantified using the Nano-Glo Luciferase Assay.

Results Image

Figure 3: Kinase titration experiment. Quantification of phosphorylation-dependent transcriptional activation using the Nano-Glo luminescence readout. HEK293T cells were transfected 24 hours post-seeding, with increasing amounts of SynKinase plasmid (5, 10, 20, 30 ng) and increasing amounts of SynPhosphatase (3, 5, 10, 15 ng) with 20 ng of kinase present to measure the phosphorylation-dependent activation of the NanoLuc reporter system. Each condition included 20 ng of reporter components (Gal4DBD-CD3ζ, SH2-VP64, and UAS-NanoLuc) and 10 ng of FFLuc for normalization. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates.

TEST

Phosphorylation-dependent reporter activation was detected with as little as 10 ng of kinase plasmid, and the signal increased in a dose-dependent manner, demonstrating good sensitivity of an assay. Dephosphorylation became apparent with as little as 3 ng SynPhosphatase, and full suppression of the phosphorylation signal was achieved with 10 ng.

LEARN

The assay showed the expected and desirable pattern: Nano Lucsignal increased with higher kinase amounts, indicating successful detection of phosphorylation, and decreased as additional SynPhosphatase was introduced, reflecting efficient dephosphorylation recording.

DESIGN

With kinase and SynPhosphatase conditions optimized, our next step was to titrate the concentrations of 5xUAS NanoLuc, Gal4DBD-CD3ζ (substrate), and SH2-VP64, previously held constant, to identify the combination that maximizes reporter signal in the presence of the 20 ng kinase.

BUILD

We have tested a range of CD3ζ-Gal4DBD to SH2-VP64 ratios by varying the amounts of each component across multiple conditions while keeping the kinase concentration constant at 20 ng. Each transfection included 20 ng of UAS NanoLuc as the reporter. By systematically changing the relative abundance of CD3ζ and SH2-VP64, we aimed to identify the optimal stoichiometry for maximum reporter activation. 48 hours after transfection, NanoLuc activity was assessed using the Nano-Glo Luciferase Assay to evaluate transcriptional output across the tested ratios.

Results Image

Figure 4: SH2-VP64: Gal4DBD-CD3ζ ratio tuning experiment. Quantification of phosphorylation-dependent transcriptional activation using the Nano-Glo luminescence readout. HEK293T cells were transfected 24 hours post-seeding, with 20 ng of SynKinase and varying ratios of CD3ζ-Gal4DBD to SH2-VP64 constructs to identify the conditions yielding the strongest luminescence signal driven by kinase-mediated phosphorylation. Each condition included 10 ng of the 5xUAS-NanoLuc reporter plasmid and 10 ng of FFLuc for normalization. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates.

TEST

We observed large differences in reporter expression strength depending on the CD3ζ-Gal4DBD to SH2-VP64 ratio. In all tested conditions, a greater amount of SH2-VP64 relative to the substrate consistently resulted in stronger NanoLuc signal, whereas the opposite ratios produced weaker responses. The highest luminescence signal was recorded with 5 ng CD3ζ-Gal4DBD and 25 ng SH2-VP64 (Fig. 4).

LEARN

The best signal amplification was achieved with 5 ng CD3ζ-Gal4DBD and 25 ng SH2-VP64, indicating this ratio provides optimal conditions for reporter activation in our system. These amounts were consistently used in the following experiments.

Results Image

Figure 5: Schematic overview of the transcriptional readout assay and its successive modifications. The original and modified variants differ by the positioning of nuclear localization signal (NLS) and nuclear export signal (NES) relative to Gal4DBD and CD3ζ domains within the SynSubstrate construct. In modification 1, NES is fused to the 5′ end of SynSubstrate; in modification 2, NES is inserted between Gal4DBD and CD3ζ. For both modifications, SynSubstrate can shuttle between cytoplasm and nucleus, while SynPhosphobinder remains nuclear due to its NLS and absence of NES. Phosphorylation of SynSubstrate in the cytosol allows its interaction with nuclear SynPhosphobinder upon entry, triggering NanoLuc reporter activation through proximity-mediated assembly of the transcriptional activation complex.

DESIGN

We revisited our construct designs, as illustrated in the attached scheme, to address the spatial logic of substrate and binder localization in the nucleus and cytosol. We realized that having the substrate permanently in the nucleus while the SH2-containing SynPhosphobinder continually shuttles between compartments might not be optimal for rapid and efficient signal transduction. Instead, we hypothesized that configuring the system so the substrate undergoes nucleo-cytoplasmic shuttling, SH2-VP64 remains resident in the nucleus, would allow the phosphorylated substrate to efficiently interact with SH2 upon nuclear entry and immediately drive transcriptional activation. This approach should optimize the detection process and enhance reporter responsiveness.

BUILD

For both modification 1 and modification 2, we engineered new substrate constructs by inserting a NES to promote nucleocytoplasmic shuttling. In modification 1, the NES was added to the 5' end of the NLS-Gal4DBD-CD3ζ-bZipRR substrate, while in modification 2, the NES was positioned internally between the Gal4DBD and 3xCD3ζ domains. For both designs, we removed the NES sequence from the SH2-VP64 construct, ensuring that SH2-VP64 remains resident in the nucleus to interact with the phosphorylated substrate when it enters (Fig. 5). Instead of normalizing the NanoLuc against the FFLuc their values were plotted separately to independently assess the signal strength of transcriptional readout modifications (NanoLuc signal) and to evaluate cell viability (Firefly signal). This allowed clear comparison of reporter expression and viability across tested conditions.

Results Image

Figure 6: Quantification of phosphorylation-dependent transcriptional activation using the Nano-Glo luminescence readout. Panel A: Raw NanoLuc; Panel B: Raw FFLuc. HEK293T cells were transfected were transfected 24 hours post-seeding, with the 5xUAS-NanoLuc reporter plasmid and either 15 ng SH2-VP64 plus 15 ng Gal4DBD-CD3ζ, or 25 ng SH2-VP64 plus 5 ng Gal4DBD-CD3ζ per well, as indicated for each condition. In all cases, 25 ng of kinase plasmid was included to drive substrate phosphorylation. All samples were also co-transfected with 10 ng of FFLuc plasmid for normalization of luminescence signals. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates. Statistical significance was determined with Ordinary one-way ANOVA with Tukey’s multiple comparison test, with a single pooled variance. *p < 0.05, ****p < 0.001.

TEST

Analysis of raw NanoLuc values revealed that both construct modifications outperformed the original assay, with modification 1 yielding the highest reporter signal when 25 ng SH2-VP64 and 5 ng Gal4DBD-CD3ζ were co-transfected (Fig. 6). However, the Firefly luciferase cell viability assay indicated increased cellular stress for both modifications relative to the original construct.

LEARN

We learned that, as predicted, redesigning the system so the substrate shuttles between the cytosol and nucleus while SH2-VP64 remains nuclear significantly improved transcriptional readout performance. This spatial arrangement enhanced the efficiency of phosphorylation-dependent reporter activation. To balance the maximized signal and cell viability, we proceeded with modification 1 for future experiments.

Results Image

Figure 7: Kinase titration experiment for assay modification 1. Quantification of phosphorylation-dependent transcriptional activation using the Nano-Glo luminescence readout. HEK293T cells were transfected 24 hours post-seeding, with increasing kinase plasmid amounts (0.4 to 60 ng), together with fixed amounts of modified reporter assay plasmids: 25 ng Gal4DBD-CD3ζ, 5 ng SH2-VP64, and 10 ng 5xUAS-NanoLuc., along with 10 ng FFLuc. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates.

DESIGN

Having optimized all aspects of the transcriptional readout for substrate phosphorylation, we repeated the SynKinase and SynPhosphatase titration experiment for the best-performing modification 1 of the assay.

BUILD

In the kinase titration experiment, we again transfected the cells with increasing amounts of kinase. In SynPhosphatase titration, each condition contained 20 ng kinase to saturate phosphorylation, with varying SynPhosphatase levels. Amounts of the reporter components were constant: 25 ng SH2-VP64, 5 ng Gal4DBD-CD3ζ, and 10 ng 5xUAS-NanoLuc. 48 hours after transfection, cells were lysed and NanoLuc expression measured by the Nano-Glo assay.

Results Image

Figure 8: Phosphatase titration experiment for assay modification 1. HEK293T cells were transfected 24 hours post-seeding, with a fixed 20 ng of kinase to saturate the phosphorylation of the substrate, and increasing SynPhosphatase amounts ranging from 1 ng to 20 ng. The same reporter amounts were used: 25 ng of Gla4DBD-Cd3Z, 5 ngSH2-VP64, 10 ng of UAS-NanoLuc, along with 10 ng FFLuc. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates.

TEST

Phosphorylation-dependent reporter activation was already detectable with 0.4 ng of kinase plasmid, and NanoLuc expression reached a plateau at 15 ng of kinase, proving high sensitivity and a broad dynamic range of the readout system (Fig. 8).

In the SynPhosphatase titration, dephosphorylation was visible at a concentration of 3 ng SynPhosphatase , and complete suppression of the phosphorylation signal was achieved with 15 ng SynPhosphatase (Fig. 9). These results confirm that the assay is capable of resolving kinase-mediated 'on' states and SynPhosphatase-induced 'off' states with well-defined thresholds.

LEARN

From this iteration, we learned that the transcriptional readout assay was sensitive even at low kinase levels, with a detectable signal starting at 0.4 ng kinase and plateauing at 20 ng, which we adopted for subsequent experiments to minimize cellular stress. Similarly, phosphatase titration revealed that dephosphorylation was evident at 3 ng SynPhosphatase and complete substrate dephosphorylation occurred beyond 10 ng. This defined the functional dynamic range of our assay for both phosphorylation and dephosphorylation activities.

Results Image

Figure 9: Test of the dPhosphatase (Panel A) and the dKinase (Panel B) catalytic activity. Panel A: Transfection of 20 ng of kinase to saturate the phosphorylation, and either dead or active phosphatase variant (as stated on figure). Additionally, fixed amounts of modified reporter assay plasmids were transfected: 25 ng Gal4DBD-CD3ζ, 5 ng SH2-VP64, and 10 ng UAS-NanoLuc, along with 10 ng Firefly Luciferase. Panel B: Transfection of 25 ng Gal4DBD-CD3ζ, 5 ng SH2-VP64, 10 ng UAS-NanoLuc, and with 10 ng Firefly Luciferase. On Y axis the increasing amounts (20 ng, 30 ng) of either active SynKinase or catalytically dead SynKinase are labeled.HEK293T cells were transfected 24 hours post-seeding. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates. Statistical significance was determined with Ordinary one-way ANOVA with Tukey’s multiple comparison test, with a single pooled variance. *p < 0.05, ****p < 0.001.

DESIGN

Having our assay fully optimized and characterized, we introduced the final touchups. We observed differences in cell viability, reflected by FFLuc signal, between transfection conditions. Conditions with higher total amounts of coding constructs tended to have reduced viability. Although DNA amounts were equalized using pBlueScript filler plasmid, this did not fully normalize cellular stress due to differences in expressed protein load. To control for this, we cloned catalytically inactive variants of both SynKinase and SynPhosphatase enzymes and tested their impact in the optimized luminescence readout assay, checking if they produced any non-specific signal independent of catalytic activity. In parallel, we cloned enzyme versions without the coiled-coils to see if there is any affinity to the substrate that is not proximity-induced through complementary coiled-coils dimerization.

BUILD

We performed PCR deletions of the catalytic residues of the kinase, followed by KLD circularization to create inactive enzyme variants. To eliminate kinase catalytic activity while preserving the structural integrity of the ABL kinase domain, we introduced two point mutations: K271R and Y393A. Similarly, we generated a catalytically inactive SynPhosphatase variant by PCR deletion and KLD cloning. As a stringent control, we introduced D181A and R221M substitutions in the phosphatase domain. Similarly, we deleted the coiled-coil domains (bZipEE) from both enzymes, resulting in truncated SynKinase and SynPhosphatase variants. This allowed us to evaluate the impact of coiled-coil-mediated proximity on catalytic activity within the assay.

Results Image

Figure 10: Test of the role of the bZipEE coiled-coil in SynKinase-mediated phosphorylation. HEK293T cells were transfected 24 hours post-seeding, with increasing amounts (0, 10, 20, or 30 ng) of SynKinase either with or without the bZipEE coiled-coil domain, as indicated. Fixed amounts of modified reporter assay plasmids were also included: 25 ng Gal4DBD-CD3ζ, 5 ng SH2-VP64, and 10 ng 5xUAS-NanoLuc along with 10 ng FFLuc for normalization. Luminescence was measured 48 hours post-transfection with Tecan plate reader. Data are presented as the mean ± SEM from n = 3 technical replicates. Statistical significance was determined with Ordinary one-way ANOVA with Tukey’s multiple comparison test, with a single pooled variance. *p < 0.05, ****p < 0.001.

TEST

As expected, conditions with catalytically dead phosphatase (dSynPhosphatase) exhibited significantly higher luminescence compared to those with active phosphatase. This indicates effective dephosphorylation only occurs in the presence of functional SynPhosphatase, confirming that the phosphatase activity was successfully abolished (Fig. 10A). Conversely, conditions containing catalytically inactive SynKinase (dSynKinase) showed negligible signal compared to robust reporter activation with active SynKinase (Fig. 10B) also confirming successful deletion of catalytic activity.

In all tested transfection amounts, the SynKinase lacking the bZipEE coiled-coil domain produced a significantly lower luminescence signal compared to the SynKinase containing the coiled-coil (Fig. 11). This confirms that the great majority of kinase activity in the system requires coiled-coil-mediated proximity for efficient substrate phosphorylation. Notably, a significant increase in signal from 0 to 30 ng of the kinase without coiled-coil was observed, corresponding to a residual background enzymatic activity, but this level remained far below that seen with the fully functional, coiled-coil-containing SynKinase. These results demonstrate that loss of the coiled-coil domain effectively disables the engineered interaction and substrate targeting for the kinase, suppressing most of its activity in the assay.

LEARN

This iteration demonstrated that dSynPhosphatase and dSynKinase, as catalytically dead variants, can now serve as optimal filler constructs to balance metabolic load across conditions, ensuring more consistent cell viability measurements across experimental conditions. Their lack of luminescent signal confirms they do not contribute to phosphorylation or dephosphorylation activity in the assay. Furthermore, the significantly abolished activity of kinase without coiled-coil variants confirms that efficient substrate phosphorylation is strictly proximity-based, mediated by engineered coiled-coil interactions.

Responding

Optimization of PhosphoTEV

We designed and developed a phosphorylation inducible TEV protease variant, based on a split TEV system. The first two iterations focused on validating existing TEV systems working with the NanoLuc-RELEASE reporter. The following four iterations include the engineering of the initial split PhosphoTEV design and the following adaptation of a single chain version. The final iteration shows an application of PhosphoTEV-RELEASE for the secretion of IL-12 as a proof-of-concept for the integration of the system into circuits including receptors and therapeutically relevant output proteins.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Iteration 5
Iteration 6
Results Image

Figure 1: Secreted NanoLuc of first RELEASE transfection. NanoLuc luminescence in 10 µL of supernatant was measured 48 hours post-transfection. Data is depicted as the mean +/- SEM with n = 3 technical replicates.

DESIGN

To validate the RELEASE system working in our hands, we started with plasmids from the original publication by Vlahos et al. (2022), containing the SEAP-RELEASE construct, a full TEV and split TEV halves fused to FKBP and FRB, both fused to a p450 sequence for ER localization. Upon recommendation by Dr. Leo Scheller to use a NanoLuc luciferase (NanoLuc) readout, we designed a RELEASE construct where we added an IL-10 secretion tag and replaced SEAP with a NanoLuc-IgG-Fc fusion protein for which he provided the sequence. As we wanted to test a split TEV system as early as possible, we also planned to use the Rapalog (AP21967) -inducible FKBP-nTEV and FRB-cTEV split TEV. For this, we needed to remove the p450 signal from the plasmids we already had, to keep it closer to the final system.

BUILD

After acquiring the plasmids and planning the cloning, we PCR amplified the RELEASE vector and the NanoLuc-IgG insert and prepared the IL-10 secretion signal through oligo anneal. The NanoLuc-RELEASE plasmid was then assembled by golden gate assembly with BsaI. To remove the p450 signal from the FKBP/FRB split TEV, we did a PCR to amplify everything but the signal, followed by KLD to circularize the PCR products. To test our reporter in a minimal system, we co-transfected it with different amounts of full TEV and Rapalog-inducible split TEV.

TEST

The conditions with rapalog-inducible split TEV were induced with 100 nM Rapalog 42 hours post-transfection. NanoLuc luminescence in the supernatant was measured another 6 hours later. This experiment was also used to establish our secreted NanoLuc assay protocol, reducing the amount of reagent used in all following experiments. Luciferase signal increased with more transfected full TEV, but there was no visible induction of split TEV with Rapalog induction beyond background levels.

LEARN

The increasing NanoLuc signal with more protease showed that the RELEASE system with our NanoLuc construct worked as intended and demonstrated a fairly low leakage without protease. As there was no activity beyond background in both the induced and uninduced split TEV, it suggested that either the induction was too short, or the constructs didn’t work as intended, perhaps due to the removal of the p450 signal, preventing ER localization.

Results Image

Figure 2: Rapalog induced NanoLuc secretion NanoLuc luminescence measured in supernatant, 24 hours after induction with 100 nM Rapalog. Data is depicted as the mean +/- SEM with n = 3 technical replicates.

DESIGN

As the Rapalog-inducible split TEV system without p450 did not work in the previous experiment, we wanted to test the original plasmids with p450, as this was the exact system Vlahos et al. (2022) used with RELEASE before. Additionally, we planned to induce for longer than 6 hours to allow for signal accumulation, making an induction more visible.

BUILD

In order to get the inducible split TEV to work, we increased the transfected plasmid amount from 5, 10 and 20 ng of each half to 20 and even 50 ng. Additionally, we included conditions with the same amount of ER-localized split TEV. To achieve more signal accumulation, we induced 24 hours after transfection and measured 24 hours after induction.

TEST

In contrast to the first experiment, there was a visible change in secreted NanoLuc for both the induced and uninduced conditions when comparing them to the negative control without any protease. However, while there was no increase with induction for the ER-localized versions, there was a 2-fold increase in signal for the 20 ng of cytosolic split TEV condition.

LEARN

We could clearly see an increase in secreted NanoLuc with both the ER-tethered and the cytosolic split TEV. As there was no induction for the ER variants, we hypothesized that the system was saturated, because we transfected significantly more plasmid than in the original publication (Vlahos et al., 2022). As we saw a 2-fold increase in signal with Rapalog induction, we concluded that our split TEV itself worked and we moved on towards tailoring a split TEV towards our phosphorylation circuit.

Results Image

Figure 3: Schematic of the split PhosphoTEV design and Kinase dose response of split PhosphoTEV. (A) The CD3ζ-domain fused to cTEV can be phosphorylated by the SynKinase through the dimerization of bZipEE and -RR. Thus, SH2 fused to nTEV binds to the phosphorylated substrate, reconstituting the split TEV. (B) HEK293T cells were co-transfected with NanoLuc RELEASE, 20 ng of each TEV half or 10 ng of full TEV, and increasing amounts of SynKinase. Supernatant with secreted NanoLuc was measured 48 h post transfection. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Ordinary Two-way ANOVA with Tukey's multiple comparison's test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001; ns, not significant.

DESIGN

With our split TEV validated, we next designed an initial version of a phosphorylation-inducible TEV. For this, we planned to exchange the FKBP and FRB fused to nTEV and cTEV with the 2xSH2 (SynPhosphobinder) and 3xCD3ζ-bZipRR (SynSubstrate), respectively. This design allows phosphorylation of SynSubstrate through the bZip-mediated proximity to SynKinase which in turn leads to the phosphorylation-dependent binding of SH2 to the SynSubstrate, reconstituting the split TEV halves (Fig. 3). The resulting split TEV system is referred to as split PhosphoTEV.

BUILD

We cloned the proposed split PhosphoTEV by PCR amplifying the FKBP-nTEV and FRB-cTEV vectors so that we excluded the Rapalog-responsible domains. Then we amplified the 2xSH2 and bZipRR-3xCD3ζ domains from the already cloned expression system plasmids and assembled both the 2xSH2-nTEV and bZipRR-3xCD3ζ-cTEV by golden gate assembly with BsaI.

TEST

To test our first split PhosphoTEV constructs, they were co-transfected with increasing amounts of cytosolic bZipEE-ABL (SynKinase). NanoLuc luminescence in the supernatant was measured 48 hours post-transfection (Fig. 4). There was a significant increase in TEV activity already at 5 ng of SynKinase and the NanoLuc signal increased further with more kinase. At the same time, the amount of SynKinase did not have a significant impact on the negative control where no TEV was transfected and there was no significant difference in signal between the negative control and the split TEV condition without kinase.

LEARN

We could successfully induce the activation of split PhosphoTEV with a cytosolic kinase. This opens the door to the integration of RELEASE as a post-translational output module into phosphorylation circuits. However, the overall activity of the split PhosphoTEV was rather low when compared to the negative control. Therefore, further efforts focused on improving on this.

Results Image

Figure 4: Schematic of the single chain PhosphoTEV design and Effect of hinge composition on PhosphoTEV performance (A) The CD3ζ-domain can be phosphorylated by the SynKinase through the dimerization of bZipEE and -RR. Thus, SH2 binds to the phosphorylated substrate, reconstituting the previously separated TEV halves. The hinge can be rather rigid or flexible. (B) Six hinge variants were tested in the presence of 0, 20, or 40 ng of cytosolic ABL. Secreted NanoLuc signal was measured 48 h after transfection. Data is depicted as the mean +/- SEM with n = 2 independent biological replicates. Ordinary Two-way ANOVA with Tukey’s multiple comparison’s test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns, not significant.

DESIGN

After establishing the successful engineering of the split PhosphoTEV, we wanted to design a new version that could achieve higher protease activity. For this, we attempted to integrate results from a recent preprint by Cao & Toettcher (2025) where they developed a phosphorylation dependent allosteric switch and inserted it into the Gal4 transcription factor. Inspired by this, we planned a design where the two split PhosphoTEV constructs would be fused into one construct by linking the SH2 and SynSubstrate domains with a variable hinge (Fig. 5). As shown by Cao & Toettcher, the composition plays an important role in the switching behavior of the resulting fusion protein, which is why we designed the construct with a GS-rich, a more rigid AP-repeat linker and a helical, very rigid EAAAK linker and each of them of length 7 and 17.

BUILD

Assembly of the different PhosphoTEV required the reordering of SH2 and nTEV. For this, the bZipRR-3xCD3ζ-cTEV vector, the nTEV and 2xSH2 fragments were PCR amplified and the variable hinges were prepared by oligo anneal. These four fragments were then assembled using golden gate assembly with BsaI. This resulted in six plasmids, each with a different hinge between SH2 and bZipRR, referred to by the composition and length of the hinge.

TEST

The six PhosphoTEV variants were each co-transfected with NanoLuc-RELEASE and 0, 20 and 40 ng of SynKinase to screen them for switching behavior and find the optimal variant. 48 hours after transfection, NanoLuc luminescence in the supernatant was measured (Fig. 6). All variants except 17EAK could successfully be activated using SynKinase. However, the switching behavior is different between them, with the 7AP variant showing the highest induction and coming closer to the full TEV positive control, while having a background on the same level as the negative control without protease.

LEARN

Due to these results, we selected the 7AP variant as the lead candidate and as the canonical PhosphoTEV. Compared to the split PhosphoTEV, the 7AP variant resulted in a higher secretion in the activated state. Despite both TEV halves being located on the same construct, the background did not significantly differ from the background of the RELEASE system itself. This may be due to the large size of the 2xSH2-7AP-bZipRR-3xCD3ζ insertion (867 amino acids) resulting in a lot of sterical hindrance.

Results Image

Fig. 5: Trace showing the ProDomino predictions for insertion tolerance and Functional evaluation of TEV domain insertion variants. (A) Higher values indicate better predicted insertion tolerance. The previously used insertion position is indicated with a dashed line, the 6 newly chosen positions with orange lines. (B) HEK293T cells were co-transfected with NanoLuc RELEASE, 10 ng SynKinase and §§ ng of the PhosphoTEV insertion variants containing the 7AP-PhosphoDomain inserted at different positions predicted by ProDomino (H28, F100, D136, N174, L190, K215) or the original site T118. Secreted NanoLuc was measured 48 h post transfection. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Ordinary Two-way ANOVA with Tukey's multiple comparison's test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001; ns, not significant.

DESIGN

Instead of a split protein system, as in the split PhosphoTEV, the 7AP-PhosphoTEV is rather a domain-insertion system, albeit a very large insertion. In such systems, the activity of a protein is allosterically controlled by inserting a sensing domain into the protein. However, the properties of the allostery are strongly affected by the site where the sensing domain is inserted within the effector protein. To optimize the insertion site and further improve switching behavior of the PhosphoTEV, we used the machine learning model ProDomino, which predicts the domain insertion tolerance of proteins at every residue (Wolf et al., 2024). Based on the predictions, we selected six new insertion sites: H28, F100, D136, N174, L190 and K215.

BUILD

The 2xSH2-7AP-bZipRR-3xCD3ζ fusion domain was PCR amplified to generate the insertion for all variants. Then the full TEV plasmid was opened at the different positions through PCR amplification and the six plasmids were assembled by golden gate assembly with BsaI.

TEST

To benchmark the performance of the new constructs, we co-transfected the six new insertion sites, as well as the original insertion into T118, each with 0 and 10 ng of SynKinase and NanoLuc-RELEASE. NanoLuciferase in the supernatant was measured 48 hours-post transfection (Fig. 8). Among the active variants, D136, L190, and K215 showed moderate induction with fold changes of 3.3x, 3.1x, and 3.4x, respectively. . L190 and K215 had a higher induced activity than D136, but also displayed increased background levels. In contrast, the H28 insertion variant showed the strongest induction (7.6x), exceeding the previously used T118 variant (6x). However, this was due to a slightly reduced background secretion compared to the original T118 PhosphoTEV.

LEARN

We could successfully identify four tolerated insertion sites into the TEV protease. While they did not result in a better PhosphoTEV version, judging by overall activity, they are a promising result, especially H28. Future efforts may try different insertion sites in close proximity to it and use these results as a starting point.

Results Image

Figure 9: Secreted IL-12 can be significantly increased by SalB induction. HEK293T cells were co-transfected with IL-12-RELEASE, PhosphoTEV and KORD-ABL plasmids. Cells were induced with 3 µM SalB 24h post-transfection. IL-12 in 100 µL of supernatant was measured by ELISA 48h post-transfection. Exact quantification of IL-12 was not possible, therefore, no conclusive fold change could be calculated, due to experimental setup. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Ordinary Two-way ANOVA with Sidak's multiple comparisons test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001; ns, not significant. Negative control was excluded from tests and is only shown for reference.

DESIGN

The goal of all previous iterations of this cycle was to optimize the PhosphoTEV-RELEASE system using NanoLuc-RELEASE for ease of readout. Including these optimized conditions, we sought to demonstrate the system with a therapeutically relevant protein instead. For this, we replaced NanoLuc in the RELEASE construct with a single chain IL-12. The amino acid sequence for the linked IL-12 was taken from BBa_K554005 and codon optimized for expression in mammalian cells.

BUILD

After planning out the cloning and waiting for the IL-12 gene fragment, we PCR amplified the RELEASE vector and inserted IL-12 through golden gate assembly with BsaI.

TEST

To test the IL-12-RELEASE construct, we co-transfected it with the 7AP-PhosphoTEV and either 50 or 70 ng of KORD-ABL, which could induce phosphorylation and thus secretion in dependence of SalB in previous experiments. Cells were induced with SalB 24 hours post-transfection and secreted IL-12 in 100 µL of supernatant was measured through ELISA with a chemiluminescent readout. There was a significant increase with SalB induction for both the 50 and 70 ng ABL-KORD conditions, with a better induction at 70 ng.

LEARN

With this experiment, we could successfully show that we can secrete a therapeutically relevant cytokine in IL-12 and even use it in a ligand-inducible system with KORD-ABL. However, we faced several limitations in the methodology as we did not have the exact material recommended by the manufacturer, for example the horse radish peroxidase substrate. For this reason, and because we could not get a proper standard curve to work, we were unable to exactly quantify the IL-12 concentration in mg/mL.

Sensing — GPCR

Controlling Phosphorylation in a Switch-like Manner Using a GPCR-based Synthetic Receptor

Starting from the PAGERTF, we engineered switch like synthetic receptors that is able to regulate cellular behaviour by sensitively and specifically phosphorylating the CD3𝜁 of our proessing core module. We established two receptor classes, one sensitive to a small molecule and the other sensing both a small molecule and a peptide ligand in an AND logic gate like manner.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Results Image

Figure 1: Initial Validation of KORD-ABL functionality. HEK293T cells were transfected 24 hours after seeding. NanoLuc and Firefly Luciferase expression was measured using the Dual Luciferase assay 24 hours after induction. Induction occurred 24h after transfection with either DMSO, or SalB [500 nM] . Two negative controls are shown. Negative 1 corresponds to 40 ng of KORD-ABL without 𝛽-Arrestin2-bZipEE. Negative 2 corresponds to 40 ng of 𝛽-Arrestin2-bZipEE without KORD-ABL. Test conditions contained 20 ng of KORD-ABL + 20 ng of 𝛽-Arrestin2-bZipEE and 40 ng of KORD-ABL + 40 ng of 𝛽-Arrestin2-bZipEE from left to right. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Two-way ANOVA with Sidak's multiple comparison test. ****P<0.0001

DESIGN

To increase the modularity of the sensing layer of our phosphorylation circuit, we wanted to establish an alternative receptor architecture to the modular extracellular sensing architecture (MESA). By choosing synthetic GPCRs as a scaffold we consciously selected a receptor that does not depend on dimerization, but instead on recruitment of an accessory protein. Furthermore, as GPCRs are highly studied, with many different variants, they represent a good starting point for engineering. To develop a modular, but most importantly tightly regulated receptor, we wanted to adapt the programmable antigen-gated G protein coupled engineered receptor (PAGER) as our scaffold.

BUILD

We assembled the KORD-ABL receptor, by amplifying the GPCR backbone of a PAGERTF construct. We then performed Golden Gate Assembly between our truncated ABL and the KORD. Primers were chosen to achieve a 22 amino acid long linker between KORD and ABL. We initially chose to omit the extracellular domains to facilitate easier testing and troubleshooting of the functionality of our SynKinase, a truncated ABL. We also assembled a modified version of the 𝛽-Arrestin2 used by Kalogriopoulos et al. (2025). We replaced the C-terminally fused TEV by the bZipEE coiled coil and removed the N-terminally fused NanoLuciferase.To investigate the ability of KORD-ABL to facilitate transfection by interacting with our phosphorylation circuit upon SalB induction, we transfected HEK293T cells 24 hours after seeding with two different amounts but identical ratios between KORD-ABL and 𝛽-Arrestin2-bZipEE. Previously determined, ideal amounts of our phosphorylation circuit were co-transfected.

TEST

Our test conditions were induced with SalB [500 nM] 24 hours after transfection. Nanoluciferase luminescence of all conditions was measured 48 hours after transfection using the Nano-Glo Dual Luciferase Reporter Assay System. The results are depicted in the associated figure. Induction of both amounts of KORD-ABL and 𝛽-Arrestin2-bZipEE resulted in a significant (p < 0.0001) increase in expression level of 15.4-fold and 20.1-fold for 20/20 ng and 40/40 ng, respectively (Figure 1).

LEARN

The first measurement provided a valuable proof-of-concept for combining our phosphorylation construct with a modified version of the KORD-ABL construct. As expression activation upon receptor activation was not yet satisfactory, future assays will focus on improving this. A valuable insight was the already existing tightness of the system, with no significant expression over background in uninduced conditions.

Results Image

Figure 2: Further ratio optimization of KORD-ABL to 𝛽-Arrestin2-bZipEE HEK293T cells were transfected 24 hours after seeding. NanoLuc and Firefly Luciferase expression was measured using the Dual Luciferase assay 24 hours after induction. Induction occurred 24 h after transfection with either DMSO, or SalB [1 µM] . The first value of each test conditions corresponds to the ng amount of KORD-ABL and the second value corresponds to the ng amount of of 𝛽-Arrestin2-bZipEE, from left to right. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Two-way ANOVA with Sidak's multiple comparison test.***P<0.0001

DESIGN

One of the key limitations we suspected was that overexpression of 𝛽-Arrestin2 facilitated increased receptor internalization, reducing the dynamic range of the receptor by reducing the total achievable phosphorylation and subsequent expression. After validating that of increasing 𝛽-Arrestin2 amounts decrease total signal, likely due to enhanced GPCR internalization we wanted to explore viable ratios between KORD-ABL and 𝛽-Arrestin2.

BUILD

For this, we co-transfected varying ratios of KORD-ABL and 𝛽-Arrestin2-bZipEE along with our phosphorylation circuit and a cell viability normalization control. While we kept 𝛽-Arrestin2 amount constant at 5 ng per well, we increased KORD-ABl concentration from 30 ng to 80 ng. The starting point at 30 ng was chosen due to a previous assay achieving significantly higher fold change with it.

TEST

Increasing KORD-ABL amount in relation to 𝛽-Arrestin2-bZipEE is able to significantly increase total output (p<0.0001) and also increases the dynamic range of the receptor, achieving up to a 149-fold induction of gene expression (Figure 2).

LEARN

This highlights, that the ratio between KORD-ABL and 𝛽-Arrestin2-bZipEE, as well as the total amount of KORD-ABL can be modified to effectively tune receptor activity. Interestingly, the background signal of uninduced conditions stayed consistent even at high amounts of KORD-ABL transfected. Overall, having shown consistent functionality of ABL fused to the C-terminal tail of the KORD, the receptor architecture can be expanded to be able to sense extracellular peptide ligands using a fused nanobody.

Results Image

Figure 3: SDS-PAGE of different Steps during GFP purification and expressed NanoLuc (NLuc) as induced by GFP-PAGER-ABL activation. (A) SDS-PAGE showing protein fractions at different steps during the purification process. Labels above the plot indicate the purification step at which the sample was aliquoted. (B) NanoLuc and Firefly Luciferase expression was measured with Dual Luciferase assay and using a plate reader 48 hours after transfection. HEK293T cells were transfected 24 hours after seeding. Induction occurred 24h after transfection with either DMSO, DMSO + GFP [1 µM], SalB [500 nM] or SalB [500 nM] + GFP [1 µM]. Conditions from left to right: Negative control with only 35 ng of GFP-PAGER-ABL; 35 ng of GFP-PAGER-ABL with 5 ng of 𝛽-Arrestin2-bZipEE; 45 ng of GFP-PAGER-ABL with 5 ng of 𝛽-Arrestin2-bZipEE; 50 ng of GFP-PAGER-ABL with 5 ng of 𝛽-Arrestin2-bZipEE. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Two-way ANOVA with Tukey's multiple comparison test was performed ****P<0.0001; NS, not significant

DESIGN

After validating the functionality of the truncated ABL on the GPCR scaffold, we wanted to expand our design to facilitate extracellular antigen sensing in addition to SalB.Thus, we wanted to adapt the original PAGERTF system in a similar manner to KORD. We selected the PAGER platform for its high modularity, which allows for the detection of diverse extracellular antigens through nanobody interfaces. Moreover, given the thorough characterization by Kalogriopoulos et al. (2025), we anticipate that other computationally designed binders could also be integrated into this system. For our initial tests, we chose to utilize a PAGER with the anti-GFP nanobody Lag2. Lag2 was selected due to the higher accessibility and improved experimental workflow when working with GFP compared to disease-associated proteins.

BUILD

Using Golden Gate Assembly, we replaced the intracellular signaling machinery of Lag2-PAGERTF with our SynKinase. Similarly to KORD-ABL, the truncated ABL is linked to KORD by a 22 amino acid linker. The engineered construct now contains an N-terminal Arodyn fused to Lag2. The anti-GFP nanobody is fused to the KORD by a flexible GS linker. C-terminally KORD is fused to the SynKinase. To ensure cost-effectiveness during engineering and characterization of our receptor construct, we also purified GFP after bacterial expression.

TEST

To purify GFP, we transformed BL21 E. coli cells and inoculated 2 L of growth medium. Following incubation, the cells were lysed, and the lysate was centrifuged to remove debris. The clarified supernatant was applied to an affinity column, washed to remove non-specific proteins, and GFP was subsequently eluted. Protein concentration was determined using a Bradford assay, and purity was assessed by SDS-PAGE (Figure 3A).Transfection of three different GFP-PAGER-ABL amounts was done to investigate dose-dependency similarly to KORD-ABL. Compared to the negative control, GFP-PAGER-ABL was inducible by SalB only as well as by SalB+GFP (Figure 3B). Although the leakiness in the absence of its peptide ligands shows limited AND-gate functionality, significant induction of up to 2.6-fold between SalB only and SalB+GFP was promising. With no, or only the peptide ligand present, gating remains highly effective.

LEARN

The GFP-PAGER-ABL shows interesting behaviour. It appears to exhibit significant leakiness in the presence of SalB but without GFP. Simultaneously, some gating occurs, as shown by the significant, up to 2.6-fold induction between SalB and SalB+GFP. To improve gating, several strategies are promising. First and foremost, titrating different ligand concentrations would give a good insight into gating and saturation behaviour. Engineering the Arodyn also offers a strategy that has the potential to improve auto-inhibition. Moreover, swapping the nanobody could also impact gating behaviour and thus affect leakiness.

Results Image

Figure 4: SalB and GFP titration with the GFP-PAGER-ABL. NanoLuc and Firefly Luciferase expression was measured with Dual Luciferase assay and using a plate reader 48 hours after transfection. HEK293T cells were transfected 24 hours after seeding. (A) Induction occurred 24h after transfection with either DMSO, DMSO + GFP [1 µM], SalB or SalB + GFP [1 µM]. Each condition contained 50 ng of GFP-PAGER-ABL with 5 ng of

DESIGN

To better characterize the leakiness of GFP-PAGER-ABL, and thus gain a better understanding about the receptor behaviour, we titrated both GFP and its small molecule ligand SalB. Ligand titration was done in large steps from 10 nM to 1 µM to observe receptor behaviour at both extremes. The maximum concentration was chosen according to observation from an initial SalB titration on KORD-ABL (BBa_25K9JYDQ).

BUILD

Both titrations were transfected with 50 ng of GFP-PAGER-ABL and 5 ng 𝛽-Arrestin2.

TEST

Figure (4A) shows the SalB titration with constant GFP on GFP-PAGER-ABL. Noticeably, at intermediate SalB concentrations (50 nM; 100 nM), full binary switch-like behaviour can be observed with nonsignificant expression above background when induced with just SalB, but 13.8-fold and 11.6-fold increase in expression upon both SalB and GFP induction, respectively. GFP titration showed significant inducibility down to a concentration of 10 nM GFP (Figure 4B). Expression upon only SalB induction is significantly higher than background for all conditions.

LEARN

Titrating both ligands showed that GFP-PAGER-ABL is able to show full AND logic gate functionality at low SalB concentration. This also highlights that the inducibility of the GFP-PAGER-ABL construct is mainly dependent on SalB, whereas GFP concentration can determine total output but not affect leakiness. Engineering the construct further using an anti-VEGF nanobody changed the Arodyn gating to an extent, where the receptor does not show significant induction in the presence of just SalB until 500 nM (shown in Results and BBa_250PWRGF).

Engineering a GPCR Based Synthetic Receptor Able to Act as a Repressor on a Post-translational Level

By adapting the GPCR scaffold, effectively utilized for inducing phosphorylation upon ligand sensing, we engineered a receptor that is able to directly interact with, and quench our phosphorylation circuit on a fully post-translational level using our SynPhosphatase.

Iteration 1
Iteration 2
Results Image

Figure 1: Titration of KORD-PTPN1 against KORD-ABL HEK293 T cells were transfected 24 hours after seeding. NanoLuc and Firefly Luciferase expression was measured using the Dual Luciferase assay 24 hours after induction. Induction occurred 24 h after transfection, using either DMSO or SalB [500 nM]. Each condition was transfected with 30 ng of KORD-ABL and 5 ng of 𝛽-Arrestin2-bZipEE. Data is depicted as the mean +/- SEM with n = 3 technical replicates. Two-way ANOVA with Sidak's multiple comparison test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001; NS, not significant.

DESIGN

To expand our modular receptor system and enable it to directly transduce an inhibitory signal on a post-translational level, we wanted to engineer the KORD-PTPN1: a synthetic GPCR fused with our SynPhosphatase, a truncated version of PTPN1. Similar to the rationale behind the engineering of KORD-ABL, we consciously selected synthetic GPCRs as one of our architectures due to their ability to recruit an intracellular accessory protein for signal transduction instead of relying on dimerization. To develop a modular, but most importantly tightly regulated receptor, we also wanted to adapt the programmable antigen-gated G protein coupled engineered receptor (PAGER) as our scaffold for our inhibitory receptor.

BUILD

To validate the functionality of the SynPhosphatase on a membrane bound receptor, we initially set out to engineer the KORD-PTPN1 variant as a simplified receptor model. The construct was assembled by Golden Gate Assembly from the cytosolic SynPhosphatase and the Lag2-PAGERTF. After fusion of the PTPN1 phosphatase to intracellular C-terminal tail of KORD, connected by a 22 amino acid linker, KLD was done to excise the extracellular GFP sensing domain. To test the construct for inducible phosphatase activity, it was first titrated against the KORD-ABL construct, as the cytosolic enzyme variants exhibit significantly stronger activity.

TEST

The titration showed that the Synphosphatase is active at the membrane and able to effectively quench KORD-ABL phosphorylation in a dose dependent manner (Figure 1). Equal ratios of KORD-ABL and KORD-PTPN1 result in a 3.0-fold reduction of expressed NanoLuciferase compared to only KORD-ABL.

LEARN

The transfection successfully showed the functionality of our SynPhosphatase when membrane bound, and more specifically the functionality of the KORD-PTPN1 construct. To expand upon this, the truncated PTPN1 can be fused to the GFP-PAGER construct, allowing for a peptide ligand gated, inducible receptor phosphatase.

Results Image

Figure 2: Validation of GFP-PAGER-PTPN1 functionality on a single cell level HEK293T cells were transfected 24 hours after seeding. Induction occurred 24 hours after transfection. mCherry expression was measured 24 hours after induction using flow cytometry. Excitation lasers at 488 nm and 561 nm were used, and fluorescence was measured at 525 nm and 610 nm for GFP and mCherry, respectively. Induction occurred 24 h after transfection with either DMSO, GFP [1 µM] + SalB [500 nM], or SalB [500 nM] or GFP [1 µM]. Data is depicted as the geometric mean of fluorescence +/- geometric SEM with >20000 single cells.

DESIGN

Expanding on the previous KORD-PTPN1 construct we wanted to facilitate extracellular antigen sensing in addition to SalB. Thus, we wanted to adapt the original PAGERTF system in a similar manner to KORD. We selected the PAGER platform for its high modularity, which allows for the detection of diverse extracellular antigens through nanobody interfaces. Moreover, given the thorough characterization by Kalogriopoulos et al. (2025), we anticipate that other computationally designed binders could also be integrated into this system.

BUILD

The construct was cloned using Golden Gate Assembly from the original Lag2-PAGERTF construct. The intracellularly fused transcription factor and AsLOV2 domain were replaced by the truncated PTPN1 also utilized on the KORD-PTPN1 with an identical linker length and make-up. We used a GFP sensing nanobody in order to retain cost-effectiveness and improve sample handling.

TEST

Analyzing the ability of the GFp-PAGER-PTPN1 to dephosphorylate upon SalB + GFP induction was measured at single cell resolution using flow cytometry (Figure 2). Phosphatase activity can be observed by a reduction in mean fluorescence intensity between the negative control (only KORD-ABL) and KORD-ABL with GFP-PAGER-PTPN1. It also appears to be dose dependent, with fluorescence decreasing further upon addition of more GFP-PAGER-PTPN1. However, AND logic gate functionality of the GFP-PAGER-PTPN1 does not appear to be present, with 1.1-fold reduction between SalB and SalB + GFP induction.

LEARN

While we assumed full functionality, and AND logic gate behaviour the construct displayed phosphatase activity without further inducibility from GFP. This could indicate a reduced activation dependent activity or an error with the construct, leading to reduced or abolished GFP sensitivity. Future engineering will focus on changing linker length and rigidity, as well as using differently truncated versions of PTPN1.

Sensing — MESA

Optimization of Kinase-based Gene Expression

We developed rapalog-sensing MESA receptors using kinase-mediated phosphorylation to drive gene expression. Iterative engineering of (i) intracellular circuit architecture, (ii) receptor stoichiometry, (iii) transmembrane domains selection (iv) extracellular/intracellular linker lengths, and (v) signal peptide selection achieved 3.4-fold ligand-dependent induction with improved cell viability.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Iteration 5
Results Image

Figure 1: Test of rapalog-induced transcription-factor cleavage. Quantification of reporter activation using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Neg. ctrl: reporter only. Receptor conditions contained 9:1, 3:1, and 1:1 ratios of TEV protease to transcription factor halves (20 ng total receptor plasmid). NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU) and display mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

DESIGN

Building on insights from Yang et al., (2025) and direct recommendations from Prof. Dr. Rebecca Wade, we initiated testing of our receptor architecture using the well-established MESA receptor system for the rapalog AP21967. We adapted a construct described by Zhou et al., (2023) in which the transcription factor Gal4-VP64, linked to a TEV cleavage site, was attached to the FKBP receptor half, while a full TEV protease was fused to the FRB receptor half. Upon ligand-induced dimerization, we hypothesized that the TEV protease would cleave the transcription factor, releasing it to activate NanoLuciferase expression, thereby providing a quantifiable readout of receptor dimerization.

BUILD

HEK293T cells were transfected with varying ratios of the FRB and FKBP receptor constructs (9:1, 3:1, and 1:1, with the transcription factor-containing construct in excess). This design was based on the hypothesis that a single TEV protease could cleave multiple transcription factors through cycles of receptor dissociation and re-dimerization, making transcription factor excess potentially advantageous. Twenty-four hours post-transfection, cells were treated with either 200 nM rapalog or vehicle control (ethanol). After an additional 24 hours, NanoLuciferase expression was measured via luminometry and normalized by Firefly luciferase, which was co-transfected on a separate plasmid under a constitutive promoter to control for transfection efficiency.

TEST

Normalized luminescence values revealed that both induced and uninduced signals increased as the transcription factor ratio decreased relative to the TEV protease construct. The highest signal was achieved with equimolar amounts of both receptor halves. A negative control containing only the reporter plasmid (no transcription factor) showed negligible luminescence, confirming assay sensitivity. The positive control, consisting of cytosolic TEV protease (5 ng) and transcription factor-FKBP construct (10 ng), produced the highest luminescence levels, which were comparable to those achieved with equal amounts of receptor constructs.

LEARN

We observed that different ratios of receptor halves strongly influenced overall NanoLuciferase expression and luminescence intensity. However, high background prevented detection of significant fold-change between induced and uninduced conditions, challenging the functionality of this synthetic receptor architecture. Additionally, our hypothesis that excess transcription factor would enhance signal output was disproved, as maximal luminescence occurred with equimolar amounts of both receptor constructs. These results parallel recent findings by Teng et al., (2020) who reported similar inducibility issues with MESA-based synthetic receptors. Their work demonstrated that MESA receptors failed to respond to membrane-permeable rapalog despite the ligand's ability to cross cellular membranes, suggesting that proper receptor localization and membrane environment may be critical for functionality. Multiple studies have indicated potential ER retention of MESA receptors rather than cell surface expression, which could compromise receptor dimerization even with membrane-permeable ligands due to differences in membrane composition, molecular crowding, or trafficking machinery in the ER versus plasma membrane Edelstein et al., (2020). Given the variability in reported MESA receptor localization and the ambiguity of our results, we decided to investigate the subcellular localization of our receptor constructs before proceeding further.

Results Image

Figure 2: Subcellular localization of sfGFP–Rapalog MESA fusion receptors. Fluorescence microscopy of HEK293T cells expressing sfGFP–FKBP (Rapalog) MESA constructs. Left panel A: DAPI (nuclei); right panel B: sfGFP signal. Cells were transfected with 60 ng FKBP-sfGFP. The fusion construct carries sfGFP at the C terminus, separated from the transmembrane domain by a 12-aa GS linker on the intracellular side. Medium: DMEM (10% FCS). Images acquired at 100× magnification. Scale bars, 10 µm.

DESIGN

To investigate whether faulty ER retention or impaired receptor trafficking explained the absence of ligand-induced response in Iteration 1, we designed a localization experiment. The intracellular domains were replaced with superfolder GFP (sfGFP), creating fluorescent fusion proteins that would reveal subcellular distribution in HEK293T cells.

BUILD

HEK293T cells were transfected with the sfGFP-tagged receptor constructs. Thirty-six hours post-transfection, cells were fixed with paraformaldehyde and nuclei were counterstained with DAPI. Fluorescence imaging was performed at 100x magnification using immersion oil.

TEST

Fluorescence microscopy showed sfGFP signal at the cell periphery in addition to intracellular accumulation, indicating that receptor fusion proteins reached the plasma membrane and were not retained entirely in the ER. While image quality limited precise quantification of membrane versus intracellular distribution, the observed peripheral localization was sufficient to rule out complete trafficking failure.

LEARN

These results confirmed plasma membrane localization of our receptor constructs, ruling out ER retention or other trafficking defects as the cause of failed ligand induction in Iteration 1. Given that receptor localization was not the issue, we hypothesized that the high background signal stemmed from the TEV protease-transcription factor readout architecture itself. Specifically, potential constitutive TEV activity or spontaneous transcription factor release may have obscured ligand-dependent changes. Consequently, we transitioned to our phosphorylation-dependent intracellular signaling system for subsequent iterations.

DESIGN

Results Image

Figure 3: Rapalog-induced reporter activation by MESA-coupled kinase receptor (CD28/CD28). (A) Quantification of SH2-mediated reporter activation using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicatead. Neg. ctrl: RAPA–ABL receptor half lacking the bZipEE half. Receptor conditions contained 20, 40, 60, or 80 ng total receptor plasmid. (B) Firefly luciferase values indicating cell viability under the same conditions. Cells were co-transfected with equimolar amounts of a Firefly construct under HSV promoter control. NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU), both are displayed as mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

Having confirmed membrane localization in Iteration 2, we hypothesized that the absence of ligand-induced response in Iteration 1 resulted from high background signal caused by basal TEV protease activity or constitutive transcription factor release. To address this, we implemented a phosphorylation-dependent signaling circuit requiring multiple conditional interactions for transcriptional activation.
We coupled a truncated, synthetic kinase domain (ABL) to the FRB receptor half and a coiled-coil domain (bZipEE) to the FKBP receptor half. The complementary coiled-coil (bZipRR) was fused to a synthetic ABL substrate (synSub) along with the Gal4 DNA-binding domain (Gal4DBD). The bZipEE-bZipRR pair exhibits moderate affinity, creating a dynamic equilibrium wherein the synSub-Gal4DBD construct shuttles between a membrane-proximal state (bound to receptor-associated bZipEE, enabling ABL phosphorylation) and a cytosolic state (dissociated, allowing interaction with SH2-VP64). Upon ligand-induced receptor dimerization, this proximity-driven phosphorylation creates a docking site for an SH2 domain fused to the VP64 activation domain. The phosphotyrosine-SH2 interaction reconstitutes full Gal4DBD-VP64 transcriptional activity. Nuclear localization signals (NLS) and nuclear export signals (NES) on circuit components facilitate shuttling between the cytosol and nucleus, ensuring that only the fully assembled, phosphorylation-activated transcription factor accumulates in the nucleus to drive gene expression. This multi-layered architecture was designed to minimize background signal through several orthogonal control mechanisms: (i) spatial separation of the kinase and substrate until ligand-induced dimerization, (ii) conditional transcription factor assembly dependent on phosphorylation state, and (iii) dynamic protein localization ensuring signal amplification occurs only when all components are properly activated.

BUILD

HEK293T cells were transfected with varying amounts of FRB-ABL and FKBP-bZipEE receptor constructs (20, 40, 60, 80ng; 1:1 ratio), along with bZipRR-synSub-Gal4DBD and SH2-VP64 constructs (20 ng each, 1:1 ratio). The induction protocol remained the same with rapalog or vehicle control (ethanol) being added twenty-four hours post transfection and NanoLuciferase expression being measured after subsequent twenty-four hours. NanoLuciferase expression was measured and normalized by constitutively expressed Firefly luciferase (HSV promoter). Cells transfected with the full circuit but with the RAPA–ABL receptor half lacking the bZipEE-domain served as a negative control.

TEST

A clear dose-dependent increase in luminescence was observed across conditions: rapalog-induced samples always displayed elevated expression, resulting in fold changes between 1.5x and 1.8x All fold changes with the exception of the 80ng condition, were not significant due to error bars. With increasing transfected plasmid amounts both uninduced and induced luminescence scaled roughly linearly. Admittedly the cell viability decreased to extremely low levels as indicated by Firefly luciferase values, with the exception of the negative control.

LEARN

The phosphorylation-dependent circuit successfully demonstrated ligand-responsive behavior with a clear increase from uninduced to induced conditions, confirming that engineered cells can sense and respond to environmental AP21967 through our synthetic signaling cascade. The negative control validated that transcriptional activation depends on receptor-mediated proximity and phosphorylation. The titration proved that by increasing plasmid amounts signal strength can be enhanced, while also increasing background. This kept the achieved fold changes consistent at 1.5x These results validated our circuit architecture but revealed the need for improved signal-to-noise ratio to achieve robust, significant fold changes after induction. Furthermore the dwindling cell viability challenged the functionality of our circuit. To address this, we focused on optimizing the receptor components themselves, specifically investigating the effects of linker length and transmembrane domain selection on receptor dimerization efficiency and signal transduction in subsequent iterations.

Results Image

Figure 4: Rapalog-induced reporter activation by MESA-like kinase receptor (CD28/CD28M3). (A) Quantification of SH2-mediated reporter activation using the Nano-Glo assay (Fig. 2). Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Neg. ctrl: RAPA–ABL receptor half lacking the bZipEE half. Receptor conditions contained 1:9, 1:4, and 1:1 ratios of ABL to bZipEE halves and either 10 or 20 ng total receptor plasmid. (B) Firefly luciferase values indicating cell viability under the same conditions. Cells were co-transfected with equimolar amounts of a Firefly construct under HSV promoter control. NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU), both are displayed as mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

DESIGN

Building on the validated circuit architecture from Iteration 3, we sought to improve signal-to-noise ratio and reduce variability by optimizing the MESA receptor components themselves. Guided by strategies described by (Yang et al., 2025). and (Edelstein et al., (2020)we systematically implemented three receptor engineering approaches: (i) receptor ratio optimization, (ii) transmembrane domain (TMD) engineering, and (iii) linker length variation.
We replaced the original TMDs with a CD28/CD28M3 heterodimer pair to suppress ligand-independent dimerization and reduce background signal. The receptor ratio was explored based on the hypothesis that a single FRB-ABL kinase could sequentially phosphorylate multiple FKBP-bZipEE-bound substrates through cycles of coiled-coil association and dissociation, suggesting that bZipEE excess might enhance signal output. Finally, we optimized linker lengths between extracellular and transmembrane domains, and between transmembrane and intracellular domains, to balance structural flexibility (enabling coiled-coil dimerization) with proximity (ensuring efficient substrate phosphorylation). Specifically, we implemented 10×GS linkers flanking the TMD for the FKBP-bZipEE construct, and 10×GS (extracellular) and 5×GS (intracellular) linkers for the FRB-ABL construct, compared to the original 12×GS linkers used previously for both receptor halves.

BUILD

HEK293T cells were transfected with varying ratios of FRB-ABL and FKBP-bZipEE receptor constructs: 1:4, 1:9 (bZipEE in excess), and 1:1, at total plasmid amounts of 10 ng or 20 ng per receptor pair. The cytosolic signaling components (bZipRR-synSub-Gal4DBD and SH2-VP64) were co-transfected as in Iteration 3. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, NanoLuciferase expression was measured and normalized by Firefly luciferase. As a negative control the full signaling circuit with FRB-ABL lacking the Rapalog receptor bZipEE domain (preventing substrate recruitment) was included.

TEST

Receptor optimization yielded significant improvements in assay performance. Statistically significant fold-changes were observed with reduced variability across replicates. The 20 ng transfection conditions produced approximately 2-fold induction with rapalog treatment across all tested receptor ratios. The 10 ng condition showed lower absolute signal (approximately half the luminescence of the 20 ng conditions) but also reduced background, resulting in fold-changes of 3.4x and 2.7x. The negative control (ABL without bZipEE) showed minimal activation, validating that substrate recruitment to the membrane is essential for circuit function.

LEARN

Systematic optimization of TMD selection and linker lengths successfully improved both signal-to-noise ratio and experimental reproducibility. The CD28/CD28M3 heterodimer effectively reduced ligand-independent background, while optimized linker lengths enhanced kinase-substrate proximity and coiled-coil-mediated recruitment dynamics. The achievement of statistically significant 3.4x fold induction represents a substantial improvement over Iteration 3, validating our receptor engineering strategy. However, cell viability inconsistencies indicated that further optimization of experimental conditions or receptor expression levels could yield additional improvements in subsequent iterations.

Results Image

Figure 5: Rapalog-induced reporter activation by MESA-like kinase receptors with different signal peptides (Iglam2SP/IgKSP). (A) Quantification of SH2-mediated reporter activation using the Nano-Glo assay (Fig. 2). Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Neg. ctrl: RAPA–ABL receptor half lacking the bZipEE half. Receptor conditions contained a 1:5 ratio of ABL to bZipEE halves and 30 ng total receptor plasmid. (B) Firefly luciferase values indicating cell viability under the same conditions. Cells were co-transfected with equimolar amounts of a Firefly construct under HSV promoter control. NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU), both are displayed as mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

DESIGN

Despite achieving statistically significant ligand-induced responses in Iteration 4, persistent variability in absolute signal intensity and cell viability across replicates prompted investigation of additional receptor optimization parameters. We hypothesized that inefficient receptor trafficking or protein folding stress might contribute to experimental inconsistency and reduced cell health. Signal peptides, which direct nascent proteins to the secretory pathway, critically influence membrane protein expression levels and cellular stress. Based on literature indicating that signal peptide selection can profoundly impact receptor surface expression and cell viability, we tested an alternative signal peptide (IgKSP) known for low cellular toxicity. We compared receptor constructs using the original signal peptide with those incorporating IGKSP, maintaining the optimized CD28/CD28M3 TMDs and linker configurations from Iteration 4.

BUILD

HEK293T cells were transfected with FRB-ABL and FKBP-bZipEE receptor constructs at a 5:25 ng ratio (1:5, bZipEE in excess). Receptor variants were tested with either the original signal peptide (Iglam2SP) or the IgKSP signal peptide. Cytosolic signaling components (bZipRR-synSub-Gal4DBD and SH2-VP64) were co-transfected as in previous iterations. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, both NanoLuciferase and Firefly luciferase were measured. Firefly luciferase expression served as an internal control for transfection efficiency and cell viability. Parallel assay planning and execution precluded the use of the optimal ratio and transfected amount (1:9 ratio, 10ng total plasmid amount) determined in Iteration 4 of this engineering cycle.

TEST

Signal peptide optimization did not yield substantial improvements in regards to the observed fold changes: We detected a 1.3x Fold change for the old signal peptide (Iglam2SP) and a 2.7x fold change for the newly adapted IgKSP signal peptide. However it must be noted that these fold changes were achieved with the suboptimal ratio and 30ng receptor plasmids transfected instead of the 10ng. The IgKSP-modified receptors demonstrated markedly improved Firefly luciferase values compared to the original constructs, indicating enhanced cell viability and more consistent transfection (right panel). Correspondingly, normalized NanoLuciferase expression showed robust ligand-induced responses with reduced error bars across replicates (left panel).

LEARN

The systematic optimization of signal peptide selection successfully addressed the persistent cell viability and variability issues that limited previous iterations. IGKSP incorporation not only improved cell health—as evidenced by elevated Firefly luciferase expression—but also enhanced overall assay robustness and reproducibility. These results underscore the importance of signal peptide selection in synthetic receptor engineering, particularly for applications requiring consistent, quantitative readouts. The combination of optimized TMDs (CD28/CD28M3), linker lengths, receptor ratios, and signal peptide (IgKSP) established a fully functional, reproducible MESA receptor platform capable of reliable ligand-dependent transcriptional control. This optimized system provides a robust foundation for subsequent applications, including testing with alternative ligands, integration of phosphatase-mediated signal termination, and adaptation to therapeutic contexts requiring precise environmental sensing and cellular response.

Phosphatase-Mediated Quenching of Gene Expression

We engineered phosphatase-fused MESA receptors for ligand-dependent signal termination. Systematic optimization of transmembrane domain configurations across three iterations—testing CD28-CD28, CD28-FGFR1, and CD28-CD28M3 pairs—achieved 2.8-fold rapalog-induced reporter quenching, establishing proof-of-concept for bidirectional cellular control.

Iteration 1
Iteration 2
Iteration 3
Results Image

Figure 1: Rapalog-induced reporter quenching by MESA-coupled phosphatase receptor. Quantification of reporter quenching using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Receptors contained CD28 homodimerizing transmembrane domains. Neg. ctrl: reporter only. Receptor conditions contained 1:9, 1:4, and 1:1 ratios of PTPN1 phosphatase to bZipEE coiled-coil construct (20 ng total receptor plasmid). NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU) and display mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

DESIGN

Having established ligand-induced phosphorylation in the previous engineering cycle, we next tested the complementary dephosphorylation arm of our MESA architecture. We replaced the ABL kinase domain with a truncated, synthetic phosphatase (PTPN1) to investigate ligand-dependent signal termination. The hypothesis was that rapalog-induced recruitment of PTPN1 would dephosphorylate the synthetic substrate, reducing transcriptional output. To optimize system performance, we systematically varied the stoichiometric ratio of PTPN1-FRB to FKBP-bZipEE receptor constructs (1:9, 1:4 and 1:1). A constitutively active cytosolic kinase was included to establish basal substrate phosphorylation, enabling detection of phosphatase-mediated signal reduction.

BUILD

HEK293T cells were transfected with PTPN1 and bZipEE receptor constructs at the mentioned ratios. The amount of receptor plasmids transfected was kept at 20ng for each condition. Cytosolic signaling components (bZipRR-synSub-Gal4DBD and SH2-VP64) were co-transfected as in previous iterations along a cytosolic Kinase to provide basal phosphorylation. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, both NanoLuciferase and Firefly luciferase were measured. Firefly luciferase expression served as an internal control for transfection efficiency and cell viability.

TEST

Rapalog treatment reduced normalized NanoLuciferase activity across all receptor ratios compared to uninduced controls. However, the magnitude of signal reduction was minimal and lacked statistical significance for all tested configurations. The 1:4 ratio exhibited the highest absolute reporter activity in both induced and uninduced states, while the 1:9 and 1:1 ratios showed comparable but lower overall expression levels. Firefly luciferase values were consistently low across all conditions, suggesting reduced cell viability or transfection efficiency, but remained uniform between receptor configurations and treatment groups, confirming that observed NanoLuciferase differences reflected signaling rather than cytotoxicity.

LEARN

The elevated NanoLuciferase expression in uninduced conditions confirmed successful basal phosphorylation by the constitutive kinase. The non-significant reduction of luminescence for Rapalog induced conditions however suggested inefficient dephosphorylation. We hypothesized that the homotypic CD28-CD28 TMD pair, while preventing unwanted constitutive interaction (as evidenced by high uninduced signal), may not optimally position the PTPN1 phosphatase domain for substrate access upon ligand-induced proximity. Thus, we decided to once again optimize the TMDs for optimal fold-changes.

DESIGN

Results Image

Figure 2: Successful rapalog-induced reporter quenching following TMD optimization. Quantification of reporter quenching using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Receptors contained CD28/FGFR1 heterodimerizing transmembrane domains. Neg. ctrl: reporter only. Receptor conditions contained 1:3 ratios of PTPN1 phosphatase to bZipEE coiled-coil construct (20 ng total receptor plasmid). NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU) and display mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

Following the suboptimal performance of the CD28-CD28 homotypic TMD pair in Iteration 1, we hypothesized that a heterotypic TMD combination might provide improved spatial positioning for phosphatase-substrate interaction upon ligand-induced dimerization. Based on literature precedent and our previous kinase receptor optimization (Rapalog-MESA-Kinase Engineering Cycle), we selected the CD28-FGFR1 heterotypic TMD pair.

BUILD

HEK293T cells were co-transfected with: (1) FRB-CD28-PTPN1 and FKBP-FGFR1-bZipEE receptor constructs at a 1:3 ratio (20 ng total receptor DNA); (2) cytosolic signaling components bZipRR-synSub-Gal4DBD and SH2-VP64; and (3) a constitutively active cytosolic kinase to establish basal substrate phosphorylation. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, NanoLuciferase and Firefly luciferase activities were quantified. Firefly luciferase served as an internal control for transfection efficiency and cell viability.

TEST

The CD28-FGFR1 TMD pair yielded a statistically significant 2.0-fold reduction in normalized NanoLuciferase expression upon rapalog treatment (p < 0.05), representing a substantial improvement over the CD28-CD28 configuration (Iteration 1). However, absolute NanoLuciferase levels in the induced state remained notably elevated compared to the negative control, indicating incomplete suppression of basal kinase activity. Firefly luciferase values were reduced in receptor-transfected conditions relative to controls, consistent with decreased cell viability observed across previous phosphatase receptor iterations. Interestingly, rapalog treatment slightly increased Firefly expression compared to the uninduced receptor condition.

LEARN

The CD28-FGFR1 heterotypic TMD pair significantly outperformed the CD28-CD28 homotypic configuration, yielding a significant reduction of expression. However, the elevated signal in the induced condition—well above negative control baseline—indicated that phosphatase activity remained insufficient to fully counteract constitutive kinase-mediated phosphorylation. The observation that different TMD pairs yielded markedly different functional outcomes underscored the critical importance of TMD selection in phosphatase-based receptor engineering. To further improve dynamic range, we opted to explore additional heterotypic TMD combinations with alternative geometries to enhance phosphatase-substrate engagement.

DESIGN

Results Image

Figure 3: Enhanced rapalog-induced reporter quenching with further TMD optimization. Quantification of reporter quenching using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Receptors contained CD28/CD28-M3 heterodimerizing transmembrane domains. Neg. ctrl: reporter only. Receptor conditions contained 1:4 ratios of PTPN1 phosphatase to bZipEE coiled-coil construct (20 ng total receptor plasmid). NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU) and display mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

As a last step to further optimize phosphatase-mediated signal termination, we implemented a CD28-CD28M3 heterotypic TMD pair, replacing the FGFR1 domain from Iteration 2. This TMD combination was also tested for TNF-alpha in the following engineering as it was reported to work reliably by Edelstein et al., (2020). Additionally, we reduced total receptor DNA from 20 ng to 10 ng to address the persistent cell viability concerns observed in previous iterations.

BUILD

HEK293T cells were co-transfected with: (1) FRB-CD28-PTPN1 and FKBP-CD28M3-ZipEE receptor constructs at a 1:4 ratio (10 ng total receptor DNA); (2) cytosolic signaling components bZipRR-synSub-Gal4DBD and SH2-VP64; and (3) constitutively active cytosolic kinase for basal substrate phosphorylation. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, NanoLuciferase and Firefly luciferase activities were quantified.

TEST

The CD28-CD28M3 TMD pair yielded a statistically significant 2.8-fold reduction in normalized NanoLuciferase expression upon rapalog treatment, representing a 40% improvement over the CD28-FGFR1 configuration (2.0-fold, Iteration 2). Induced NanoLuciferase levels approached but remained above the negative control baseline (which lacked constitutive kinase and reflected only basal substrate phosphorylation). Notably, Firefly luciferase values improved substantially compared to previous iterations, indicating enhanced cell viability at the reduced 10 ng transfection amount. Furthermore, rapalog-treated samples consistently exhibited higher Firefly expression than uninduced receptor-transfected cells, supporting the hypothesis that receptor overexpression—rather than ligand or vehicle toxicity—drives the observed viability reduction. This suggests that ligand-induced signaling may partially alleviate cellular stress associated with high receptor expression.

LEARN

The CD28-CD28M3 heterotypic TMD pair achieved the strongest phosphatase-mediated signal termination to date (2.8-fold reduction), validating this configuration as the optimal among tested TMD combinations for PTPN1. The progressive improvement across iterations—from non-significant reduction (CD28-CD28) to 2.0-fold (CD28-FGFR1) to 2.8-fold (CD28-CD28M3)—demonstrates that TMD selection critically influences phosphatase positioning and catalytic efficiency. The correlation between this TMD pair's superior performance in both kinase-based and phosphatase-based architectures suggests that CD28-CD28M3 provides favorable general properties for MESA receptors, including optimal membrane orientation, inter-domain spacing, and stability. While induced NanoLuciferase levels did not fully reach negative control baseline, the substantial signal reduction established a proof-of-concept for phosphatase-mediated repression within the MESA platform. These results validated the modularity of the receptor architecture, confirming compatibility with both kinase (signal amplification) and phosphatase (signal termination) effector domains—a critical capability for engineering bidirectional, tunable cellular responses. Residual signal in the induced state likely reflects incomplete kinase-phosphatase balancing and could be further optimized through: (1) fine-tuning constitutive kinase expression levels; (2) exploring alternative phosphatase domains with higher catalytic efficiency; or (3) adjusting linker lengths to enhance substrate accessibility.

Expanding Sensing Repertoire to Protein Ligands

We engineered TNF-α-responsive MESA receptors using homodimeric anti-TNF-α scFv domains to detect cancer-relevant protein ligands. Systematic transmembrane domain optimization across three iterations progressed from 1.8-fold induction to 3.7-fold TNF-α-dependent activation, demonstrating platform adaptability beyond small molecules.

Iteration 1
Iteration 2
Iteration 3

DESIGN

Results Image

Figure 1: Subcellular localization of scFv-sfGFP MESA fusion receptors. Fluorescence microscopy of HEK293T cells expressing scFv-TNFalpha MESA constructs. Left panel A: DAPI (nuclei); right panel B: sfGFP signal. Cells were transfected with 120 ng TNFalpha-scFv-sfGFP. The fusion construct carries sfGFP at the C terminus, separated from the transmembrane domain by a 12-aa GS linker on the intracellular side. Medium: DMEM (10% FCS). Images acquired at 100× magnification. Scale bars, 10 µm.

Following confirmation of membrane localization in Iteration 1, we proceeded to test ligand-dependent signaling by constructing functional TNF-α sensing receptors. We coupled the synthetic ABL kinase domain to one receptor half and the bZipEE coiled-coil to the other, both carrying identical anti-TNF-α scFv domains to create a homodimeric receptor pair (in regards to the extracellular domains). Since TNF-α is a homotrimeric ligand, we hypothesized that TNF-α binding would induce receptor clustering and proximity-driven ABL-mediated phosphorylation of the bZipEE-recruited substrate. The intracellular signaling cascade consisted of the bZipRR-synSub-Gal4DBD fusion protein and SH2-VP64 transcriptional activator, driving NanoLuciferase reporter expression as established in rapalog receptor iterations. To identify optimal receptor stoichiometry, we tested two different DNA amounts (10 ng and 20 ng total) with an ABL:ZipEE ratio of 1:4 (with bZipEE in excess based on rapalog optimization).

BUILD

HEK293T cells were transfected with varying amounts and ratios of TNF-scFv-ABL and TNF-scFv-ZipEE as described in the previous section. Twenty-four hours post-transfection cells were induced with either 20ng/ml TNF-alpha or vehicle control (H2O). NanoLuciferase expression was measured after subsequent twenty-four hours and normalized to constitutively expressed Firefly luciferase (HSV promoter).

TEST

Normalized NanoLuciferase values exhibited significant fold changes of 1.8x each for induction with TNF-α. The negative control (reporter only) showed no TNF-α response, confirming that the signal required both receptor halves. Firefly luciferase values remained consistent across conditions, indicating that observed differences reflected signaling rather than cytotoxicity.

LEARN

The 1.8-fold induction confirmed ligand-dependent receptor functionality, validating our homodimeric TNF-α sensing design. However, we observed that increasing total plasmid DNA from 10 ng to 20 ng elevated both induced signal and basal background proportionally, resulting in equivalent fold changes across conditions. This suggested that receptor expression levels alone would not improve dynamic range without addressing background activity. We hypothesized that alternative TMD pairs might reduce basal signaling while maintaining ligand responsiveness. Drawing from our rapalog receptor optimization, where systematic TMD screening yielded substantial performance improvements, we identified two promising candidates for testing: the FGFR1-FGFR1 homodimer and CD28-CD28M3 heterodimer configurations. We proceeded to evaluate these TMD variants using flow cytometry to assess their impact on receptor expression and background signaling before committing to full functional assays.

DESIGN

Results Image

Figure 2: TNF-α-dependent signaling validated with scFv-MESA receptors. Quantification of reporter quenching using the Nano-Glo assay. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Receptors contained CD28/CD28-M3 heterodimerizing transmembrane domains. Neg. ctrl: reporter only. Receptor conditions contained 1:4 and 1:9 ratios of ABL to bZipEE coiled-coil constructs (10 ng and 20 ng total receptor plasmid). NanoLuciferase luminescence values (AU) are normalized by Firefly luminescence (AU) and display mean ± SEM. Fluorescence was analyzed by two-way ANOVA. Medium: DMEM (10% FCS). P values: ns > 0.05; * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001.

Following the suboptimal performance of the CD28-CD28 homotypic TMD pair in Iteration 1, we hypothesized that a heterotypic TMD combination might provide improved spatial positioning for phosphatase-substrate interaction upon ligand-induced dimerization. Based on literature precedent and our previous kinase receptor optimization (Rapalog-MESA-Kinase Engineering Cycle), we selected the CD28-FGFR1 heterotypic TMD pair.

BUILD

HEK293T cells were co-transfected with: (1) FRB-CD28-PTPN1 and FKBP-FGFR1-bZipEE receptor constructs at a 1:3 ratio (20 ng total receptor DNA); (2) cytosolic signaling components bZipRR-synSub-Gal4DBD and SH2-VP64; and (3) a constitutively active cytosolic kinase to establish basal substrate phosphorylation. Twenty-four hours post-transfection, cells were treated with 200 nM AP21967 or vehicle control (ethanol). After an additional 24 hours, NanoLuciferase and Firefly luciferase activities were quantified. Firefly luciferase served as an internal control for transfection efficiency and cell viability.

TEST

The CD28-FGFR1 TMD pair yielded a statistically significant 2.0-fold reduction in normalized NanoLuciferase expression upon rapalog treatment (p < 0.05), representing a substantial improvement over the CD28-CD28 configuration (Iteration 1). However, absolute NanoLuciferase levels in the induced state remained notably elevated compared to the negative control, indicating incomplete suppression of basal kinase activity. Firefly luciferase values were reduced in receptor-transfected conditions relative to controls, consistent with decreased cell viability observed across previous phosphatase receptor iterations. Interestingly, rapalog treatment slightly increased Firefly expression compared to the uninduced receptor condition.

LEARN

The CD28-FGFR1 heterotypic TMD pair significantly outperformed the CD28-CD28 homotypic configuration, yielding a significant reduction of expression. However, the elevated signal in the induced condition—well above negative control baseline—indicated that phosphatase activity remained insufficient to fully counteract constitutive kinase-mediated phosphorylation. The observation that different TMD pairs yielded markedly different functional outcomes underscored the critical importance of TMD selection in phosphatase-based receptor engineering. To further improve dynamic range, we opted to explore additional heterotypic TMD combinations with alternative geometries to enhance phosphatase-substrate engagement.

DESIGN

Results Image

Figure 3: FGFR1 transmembrane domains achieve superior TNF-α receptor performance. Quantification of TNFα-induced phosphorylation-mediated CD3ζ-SH2 constitution. Cells were transfected with the complete expression-coupled PHOENICS circuit, varying only the receptor configuration as indicated. Neg. ctrl: No receptor. Receptor conditions contained specified ratios of ABL to bZipEE halves (170 ng total DNA in 12-well plate wells). SplitFast fluorescence was quantified with flow cytometry. Dimerization dependent SplitFAST fluorescence was quantified by flow cytometry 48 hours after transfection, employing excitation lasers at 488 nm and 561 nm. Emission was recorded at 525 nm for splitFAST (Ligand: TFLime) and at 610 nm for constitutively expressed mCherry, serving as a transfection control. (A) Fluorescence profiles of viable single cell populations are displayed in ridgeline plot, (B) geometric mean fluorescence (RFU) ± geometric SEM with ~9000 single cells are shown in barplot.

We selected two TMD combinations previously demonstrated to yield high signal-to-noise ratios in synthetic receptor applications: the heterotypic CD28-CD28M3 pair (1:4 ABL:ZipEE ratio) and the homotypic FGFR1-FGFR1 pair (1:9 ABL:ZipEE ratio). These ratios were chosen based on the stoichiometries reported for optimal performance with each TMD pair. We hypothesized that appropriate TMD selection would reduce constitutive receptor clustering while maintaining ligand-induced proximity, thereby improving dynamic range.

BUILD

HEK293T cells were transfected with either a 1:9 ratio of FGFR1-ABL to FGFR1-ZipEE or 1:4 ratio of CD28-ABL to CD28M3-ZipEE. Twenty-four hours post-transfection cells were induced with either 20ng/ml TNF-alpha or vehicle control (DMSO). After subsequent twenty-four hours cells were measured with Fluorescence Assisted Cell Sorting (FACS).

TEST

Flow cytometry revealed substantial differences in signal-to-noise ratios between TMD configurations. The FGFR1-FGFR1 receptor pair (1:9 ratio) exhibited basal fluorescence comparable to the negative control in the uninduced state, indicating minimal constitutive signaling. TNF-α treatment of this condition yielded a 3.7-fold increase in reporter expression. In contrast, the CD28-CD28M3 receptor pair (1:4 ratio) displayed elevated basal fluorescence in the uninduced state—exceeding even the TNF-α-induced FGFR1 condition—resulting in only a 1.5-fold induction upon ligand treatment. Both configurations showed TNF-α responsiveness, but the FGFR1 pair demonstrated superior dynamic range.

LEARN

TMD optimization substantially improved assay performance, with the FGFR1-FGFR1 homotypic pair outperforming the CD28-CD28M3 heterotypic pair in both fold-change (3.7× vs. 1.5×) and background suppression. The elevated basal activity of CD28-CD28M3 receptors likely reflects increased constitutive TMD association, consistent with the heterotypic interaction promoting spontaneous clustering independent of ligand. Conversely, the FGFR1-FGFR1 configuration maintained low background while preserving TNF-α responsiveness, suggesting that homotypic FGFR1 TMDs balance weak basal interaction with ligand-induced proximity. Based on these results, we selected the FGFR1-FGFR1 TMD pair at a 1:9 ratio for subsequent assays. Future work would focus on further reducing variability and improving statistical significance through additional parameter refinement, following the multi-dimensional optimization strategy validated in rapalog receptor development.

Additional Modules

Mutational Separation of EnvZ/OmpR Enzymatic Functions

We engineered a bacterial two-component system (TCS) as an orthogonal signaling module. Based on the EnvZ/OmpR pair, separate kinase and phosphatase variants were created to fine-tune OmpR phosphorylation in mammalian cells. Reporter assays confirmed specific activation by the kinase and revealed background binding of unphosphorylated OmpR, guiding further optimization of reversibility and signal strength.

Iteration 1
Iteration 2
Results Image

Figure 1: Reporter assay of the synthetic EnvZ/OmpR system. HEK293T cells were transfected with 10 ng of OmpR together with the indicated amounts of kinase (EnvZK) and phosphatase (EnvZP) variants. Reporter activity was measured 48 h post transfection using a Dual Luciferase assay, with Firefly luciferase normalized to constitutively expressed Renilla luciferase. Bars represent mean ± SEM, n = 3 technical replicates.

DESIGN

To establish an alternative signaling network alongside our PHOENICS circuit, we explored the use of two-component systems (TCS) as an orthogonal mechanism for intracellular communication. The major advantage of TCSs is their complete orthogonality to endogenous mammalian signaling pathways, making them ideal for modular and interference-free circuit design.
TCSs are widespread bacterial signal transduction systems that enable cells to sense and respond to environmental cues such as osmolarity, pH, or nutrients. They typically consist of a histidine kinase (HK) that detects a stimulus and autophosphorylates on a conserved histidine residue. The phosphate group is then transferred to an aspartate residue on a response regulator (RR), which subsequently activates or represses gene expression by binding specific promoter regions.
To build a synthetic and modular TCS in mammalian cells, we adapted the EnvZ/OmpR system described by Jones et al. (2022). In this design, the natural membrane-bound EnvZ, normally a dimeric enzyme with both kinase and phosphatase activity, was truncated and converted into cytosolic monomers with separate catalytic functions. Two variants were engineered: a kinase variant (EnvZK) that phosphorylates OmpR, and a phosphatase variant (EnvZP) that removes the phosphate group.
Both constructs consist of two Dimerization and Histidine Phosphotransfer domains (DHp; "A") and one Catalytic and ATP-binding domain (CA; "B") to enable modular interactions, a configuration that can be described as an AAB-version. Upon phosphorylation, OmpR acts as a transcriptional activator, inducing expression of a Firefly luciferase reporter under control of an OmpR-responsive promoter, providing a quantitative luminescent readout of signaling activity.

BUILD

Both enzyme variants were cloned following the design of Jones et (2022) as truncated cytosolic monomers carrying the respective catalytic mutations. Cloning was performed using Gibson Assembly to generate the AB-version constructs (residues 222-450; UniProt-ID: P0AEJ4), consisting of one DHp domain and one CA domain.
For both the kinase and phosphatase variants, the duplication and insertion of the DHp domain were achieved through PCR amplification followed by Golden Gate Assembly. The kinase construct additionally required the introduction of two point mutations via PCR. The specific point mutations introduced were T402K and Y287D for the kinase, and D244A and F390L for the phosphatase.

TEST

The reporter assay revealed measurable background activity in the absence of enzymes, indicating that unphosphorylated OmpR contributes to basal expression. Increasing amounts of the kinase variant (EnvZK) led to a dose-dependent rise in reporter activity, consistent with OmpR phosphorylation. Surprisingly, the phosphatase variant (EnvZP) also increased reporter output compared to the no-enzyme condition, suggesting residual kinase activity. Moreover, EnvZP was unable to quench the kinase-induced signal, indicating limited or inefficient dephosphorylation capacity in this variant.

LEARN

From these experiments, we learned that OmpR exhibits measurable background activity even in the absence of upstream enzymes (Kenney & Anand, 2020). This is likely due to its ability to bind DNA in an unphosphorylated state, leading to basal transcriptional activation; a phenomenon also confirmed during our interview with Dr. Jones.
In the same discussion, we received valuable feedback that the AAB-type phosphatase variant can retain residual kinase activity, which aligns with our observation of elevated reporter levels in the EnvZP condition. To address this issue, we decided to adopt an alternative phosphatase design (GCN4-EnvZP), in which two monomers are dimerized via N-terminal coiled-coils to maintain a certain configuration.

Results Image

Figure 2: Quantification of OmpR-dependent reporter activation by cytosolic EnvZ variants. HEK293T cells were transfected with 30 ng of OmpR together with the indicated amounts of kinase (EnvZK) and phosphatase (EnvZP) variants. The reporter plasmid contains an OmpR-binding site upstream of a Firefly luciferase gene, enabling transcriptional activation upon OmpR phosphorylation. Reporter activity was measured 48 hours post transfection using a Dual Luciferase assay, with Firefly luminescence normalized to constitutively expressed Renilla luciferase. Data are shown as mean ± SEM (n = 3 technical replicates). Statistical significance was determined using one-way ANOVA with Tukey’s multiple comparison test (***p < 0.001, ****p < 0.0001, ns = not significant).

DESIGN

Based on our previous findings, we redesigned the phosphatase component of the EnvZ/OmpR system to overcome the residual kinase activity observed in the AAB-type variant. In this improved version, the phosphatase is expressed as a dimer, in which two monomers are fused via N-terminal GCN4 coiled-coil domains, forcing the DHp domains into a fixed rotational state.

BUILD

Starting from the AB phosphatase backbone, an N-terminal GCN4 leucine-zipper was cloned to enforce dimerization via Golden Gate assembly. To create a single-chain dimer, we tandem-fused two phosphatase monomers by connecting the C-terminus of the first monomer to the N-terminus of the second via a long, flexible GS-linker. The resulting construct encodes an N-terminal GCN4-Phos-Linker-Phos architecture. All phosphatase-point mutations from the previous design were retained in each monomer to preserve the intended catalytic profile.

TEST

Reporter activity was measured using 30 ng of OmpR under varying kinase and phosphatase conditions. In the absence of enzymes, a basal signal confirmed OmpR background activity. Increasing amounts of EnvZK led to a dose-dependent rise in reporter output, with strong activation at 20 ng and maximal signal at 40 ng. Co-expression of the GCN4-phosphatase (EnvZP) with 20 ng kinase barely reduced activity, indicating inefficient dephosphorylation. EnvZP alone had minimal impact on basal levels, confirming that the cytosolic kinase strongly activates.

LEARN

From these experiments, we learned that the redesigned GCN4-Phos variant no longer exhibits residual kinase activity, confirming the effectiveness of the dimeric architecture. However, it still fails to efficiently dephosphorylate OmpR, as reporter activity remained largely unchanged when co-expressed with the kinase. Interestingly, co-expression of GCN4-Phos with OmpR alone resulted in a slightly lower signal than OmpR without enzymes. This effect may arise from the formation of a non-productive complex between OmpR and the phosphatase, transiently sequestering OmpR from the promoter, a behavior consistent with known EnvZ-OmpR interactions reported by Qin et al. (2001).

A Tunable Third Input for the PHOENICS Circuit

Our long-term design vision for the PHOENICS circuit is to integrate Melt40 as a third, tunable input. By coupling Melt40 to an SH2 domain, localization can be modulated not only by phosphotyrosine signaling but also by temperature, enabling transcriptional output only when the positive signal from SH2-mediated recruitment outweighs inhibitory input. Temperature tuning adds an environmental control layer to engineered cell circuits.

Iteration 1
Iteration 2
Iteration 3
Results Image

Figure 1: Temperature-gated transcription with fused Melt40 and transcription factor (Melt40_Gal4_VP64). At cooler temperatures, Melt40 oligomerizes and retains the fusion at the plasma membrane, preventing DNA binding. Heating to ~40 °C disrupts membrane association; the SV40 NLS drives nuclear import, Gal4DBD engages UAS sites, and VP64 activates mCherry expression. Cooling reverses the cycle. Elements are illustrative and not to scale.

DESIGN

Our long-term design vision for the PHOENICS circuit is to integrate Melt40 as a third, tunable input. By coupling Melt40 to an SH2 domain, localization can be modulated not only by phosphotyrosine signaling but also by temperature, enabling transcriptional output only when the positive signal from SH2-mediated recruitment outweighs inhibitory input. Temperature tuning adds an environmental control layer to engineered cell circuits.

To prototype this concept, we engineered a heat-gated transcription factor that is sequestered at the plasma membrane at baseline temperature, and released to the nucleus upon heating (~40 °C), applicable, for example, in a tumour-associated fever context. We used Melt40, a BcLOV4-derived thermal localization module reported to switch near 40 °C, and fused it to a Gal4DBD–VP64 transcription factor flanked by an SV40 NLS and an NES to promote reversible nuclear shuttling. The transcriptional activation is to be quantified by mCherry flow cytometry, but the system is readily adaptable to alternative reporters (Figure 1).

Results Image

Figure 2: Fluorescence microscopy of Melt40. HEK293T cells were transfected with Melt40 constructs at 200 ng and treated with three different temperatures for 3 hours: 25°C (left), 37°C (middle), and 40°C (right). For localization visualization of Melt40, we utilized an mCherry fusion construct (red). Nuclei were stained using Hoechst (grey). Images were captured using a Leica fluorescence microscope at 20x magnification—scale bars: 20 µm.

BUILD

Module validation. Before adding the transcription factor (TF), we validated Melt40 localization using fixed-cell fluorescence microscopy at temperatures of 25 °C, 37 °C, and 40 °C. As expected, Melt40 remained membrane-bound at 25 °C, beginning to dissociate and partly enriching in the nucleus at 37 °C, and completely nuclear at 40 °C - confirming the intended thermal translocation behavior used as the actuation basis for the TF.

Fusion assembly. In this configuration, temperature acts as a gating input: below the activation threshold, Melt40 sequesters Gal4–VP64 at the plasma membrane; at elevated temperature (~40 °C), the fusion protein is released to the nucleus, where Gal4, as a DNA binding domain (DBD), binds UAS elements and VP64 drives transcription. We quantified output by mCherry flow cytometry, but the system is readily adaptable to alternative reporters. The constructed architecture resulted in the first Version: NLS_Gal4_BcLOV4_STIM_VP64_NES_NLS, shortly Gal4_Melt40_VP64_NES_NLS.

Results Image

Figure 3: Flow Cytometry Analysis of Gal4_Melt40_VP64_NES_NLS Construct. Flow cytometry was used to assess gene expression and subcellular localization of the Melt40_TF construct under different conditions. No Melt control groups at 37°C and 40°C show similar geometric mean red fluorescence (RFU), indicating no positive expression and only background signal in the absence of Melt. The fluorescence levels for the control (no Melt) conditions are indistinguishable, suggesting that the construct does not induce transcriptional activity in the absence of Melt. Error bars represent the standard error of the mean (SEM).

TEST

The flow cytometry analysis was performed to evaluate gene expression and subcellular localization of the Melt40_TF construct at two different concentrations (40 ng and 160 ng) and at two temperatures (37°C and 40°C). The geometric mean red fluorescence (RFU) values were measured to quantify the level of reporter gene expression under these conditions

Results. The construct did not activate transcription above background under any of the tested conditions. At 40 ng, geometric means were ~83 RFU (37 °C) vs ~91 RFU (40 °C), comparable to the negative control whiteout Melt. At 160 ng, signals remained low (≈49 RFU at 37 °C vs ≈85 RFU at 40 °C) and again tracked background, indicating no temperature-separated activation. Density plots corroborated the lack of a responding subpopulation (Figure 3).

Notably, when comparing mCherry expression with the expression induced by a fused Gal4DBD-VP64 construct at 37°C and 40°C, only a minor (1.1-fold) increase of reporter expression was detected (Figure 4). Temperature differences alone thus do not induce a relevant increase in reporter expression.

Results Image

Figure 4: Minimal temperature-induced variation of reporter expression without Melt. Quantification of mCherry reporter expression via Gal4DBD-VP64 transcription factor. Cells were transfected with an mCherry reporter construct under UAS-promoter control and the Gal4DBD-VP64 transcription factor. Transfected cells were incubated for 16h at 37°C or 40°C before measurement. mCherry fluorescence was quantified with flow cytometry. Fluorescence profiles of viable single cell populations are displayed in a ridgeline plot on the left, geometric mean fluorescence (RFU) ± geometric SEM are shown in a barplot to the right. Medium: DMEM (10% FCS).

LEARN

A plausible explanation would be an insufficient nuclear accumulation upon heating due to continuous NES-driven export, despite Melt40 release from the membrane. In other words, our shuttling balance likely over-favored export, preventing Gal4DBD–VP64 from reaching an effective nuclear concentration at 40 °C. A second explanation could be dose-dependent background or toxicity at higher DNA input, which can flatten fold changes.

Results Image

Figure 5: Flow cytometry analysis and representative fluorescence microscopy image of Gal4_Melt40_VP64. Left, flow cytometry with two transfection concentrations (40 ng, 160 ng) and two temperatures (37 °C, 40 °C). Density plots (log RFU) show complete distributions; the bar chart reports geometric mean red fluorescence (RFU) with SEM. Negative Controls (Without Melt) at 37 °C and 40 °C are comparable and low , indicating background signal. At 40 ng, the construct shows a temperature response: mean RFU at 40 °C is ~1.9× higher than at 37 °C. At 160 ng, the effect is lower(~1.1×), consistent with dose dependent background. Right, a representative fluorescence microscopy image corresponds to the condition 40 °C, with 160 ng Gal4_Melt40_VP64. It shows a bright red signal (mCherry) with nuclear accumulation consistent with elevated fluorescence at 40 °C. Error bars represent the standard error of the mean (SEM) for triplicate samples.

DESIGN

Objective. Improve heat-ON transcription by re-ordering domains so that BcLOV4 (Melt40) sits N-terminal, followed by STIM polybasic, SV40 NLS, Gal4DBD, and VP64. This layout was chosen to firstly maximize membrane sequestration via the Melt40 module at baseline, secondly place the NLS immediately upstream of Gal-4DBD to favor rapid nuclear import on heat release, and lastly to separate Gal4DBD from the actuator to reduce steric hindrance during DNA binding, thereby enhancing activation at physiologically relevant temperatures (37–40 °C).

BUILD

To increase heat-induced nuclear retention, the NES from the first version of the construct was removed. This way, once Melt40 releases from the membrane at ~40 °C, the SV40 NLS can drive efficient nuclear import and retention of Gal4DBD–VP64 in the nucleus. The second version’s Gal4_Melt40_VP64 architectures are therefore, from N-terminal to C-terminal: NLS_Gal4DBD_BcLOV4_STIM_VP64.

TEST

Flow cytometry experiments were performed to evaluate gene expression and subcellular localization of the Melt40_TF construct at two different concentrations (40 ng and 160 ng) and at two temperatures (37°C and 40°C). The geometric mean red fluorescence (RFU) values were measured to quantify the level of reporter gene expression under these conditions.

Result: For the higher concentration (160 ng), a high background at both temperatures with minimal fold change (≈1.1×; 37 °C ≈1502 RFU, 40 °C ≈1666 RFU), indicating low temperature-induced separation at high doses. For the lower concentration (40 ng), clear temperature responsiveness is detected. The mean RFU at 40 °C showed a nearly 2-fold change, higher than at 37 °C (Figure 5).

LEARN

Interpretation: Removing the NES successfully uncovered a heat-ON response at lower DNA input (40 ng), consistent with improved nuclear retention on heating. However, overexpression (160 ng) produced a high background that compresses fold change, likely from a dose-related cellular stress that raises baseline reporter levels.

DESIGN

Objective. Improve heat-ON transcription by re-ordering domains so that BcLOV4 (Melt40) sits N-terminal, followed by STIM polybasic, SV40 NLS, Gal4DBD, and VP64. This layout was chosen to firstly maximize membrane sequestration via the Melt40 module at baseline, secondly place the NLS immediately upstream of Gal-4DBD to favor rapid nuclear import on heat release, and lastly to separate Gal4DBD from the actuator to reduce steric hindrance during DNA binding, thereby enhancing activation at physiologically relevant temperatures (37–40 °C).

BUILD

Optimization. We incorporated the transcription factor with an N-terminal, yielding the NES-free Melt40_Gal4_VP64 . The detailed composition of the final construct resulting in: BcLOV_STIM_NLS_Gal4DBD_VP64. The finalized plasmid encodes the actuator, import cue, and TF in the optimized order to couple heat-driven membrane release to rapid nuclear import and UAS-dependent activation.

Results Image

Figure 6: Flow cytometry analysis and representative fluorescence microscopy image of optimized Melt40_Gal4_VP64. Left, flow cytometry at two DNA inputs (40 ng, 160 ng) and two temperatures (37 °C, 40 °C). Density plots (log RFU) show full distributions; the bar chart reports geometric mean red fluorescence (RFU) with SEM. The negative control whiteout Melt at 37 °C and 40 °C remains low and comparable, indicating background signal. . The optimized construct displays strong temperature separation: at 40 ng, the mean RFU at 40 °C is ~6.6× higher than at 37 °C; at 160 ng, the 40 °C signal is ~4.9× higher than 37 °C. Right, a representative fluorescence microscopy image (condition 40 °C, with 160 ng Melt40_Gal4_VP64) shows a bright nuclear red signal (mCherry) consistent with the elevated 40 °C fluorescence measured by flow cytometry. Error bars represent the standard error of the mean (SEM) for triplicate samples.

TEST

Results. The optimized construct exhibited strong temperature separation: at 40 ng, the mean RFU at 40 °C was ~6.6× higher than at 37 °C; at 160 ng, the 40 °C signal was ~4.9× higher than 37 °C. The distributional shifts indicate a broad population response rather than a small responding subfraction. A representative fluorescence microscopy image (condition: 40 °C, 160 ng Melt40_Gal4_VP64) shows bright nuclear mCherry, consistent with the elevated 40 °C fluorescence measured by flow cytometry, which supports temperature-gated nuclear accumulation and transcriptional activation (Figure 6).

Results Image

Figure 7: Mechanism of temperature-gated transcription with Melt40. Schematic of the working model. At cooler temperatures, Melt40 (purple) oligomerizes and is recruited to the plasma membrane via the STIM polybasic segment, sequestering the fused Gal4DBD–VP64 away from DNA. Upon heating (red arrow), Melt disengages from the membrane, and the SV40 NLS drives nuclear import of Gal4DBD–VP64. In the nucleus, Gal4DBD binds UAS sites and VP64 activates transcription of the mCherry reporter, which accumulates in the cytosol (red). Cooling reverses the process (blue arrow), returning the fusion to the membrane and reducing transcriptional output. Elements are illustrative and not to scale.

LEARN

Further optimization, achieved by redesigning the order of the functional parts, resulted in the Melt40_Gal4_VP64 construct, which demonstrated significantly enhanced performance and a clear dose-dependent effect. This dose-dependent profile confirms that the system's dynamic range and output can be finely tuned by plasmid concentration, offering greater flexibility for application-specific needs.

These results collectively demonstrate that the optimized Melt40_Gal4_VP64 construct functions as an effective and tunable temperature-inducible gene expression system, with potential applications in synthetic biology, thermogenetic controls, and precision gene regulation under mild hyperthermic conditions.

Our results establish Melt40 as a reliable heat-ON actuator for nuclear translocation and transcriptional control, and the engineering cycles clarified how expression level, tag balance, and domain order shape performance. To realize our long-term vision, using Melt40 as a third, tunable input in signaling circuits via SH2-guided recruitment, we still need to do further cloning. Specifically, we will construct SH2–Melt40 fusion variants (testing orientation and linkers) and integrate these modules with our Gal4/UAS transcriptional output, allowing temperature to tune response strength only when SH2-mediated positive signals outweigh inhibitory inputs. These additional constructs will enable us to characterize the full temperature-by-phosphotyrosine input matrix and finalize an environmentally tunable, multi-input control layer for the PHOENICS circuits (Figure 7).

Dry Lab

Binder Design and Characterization Pipeline for Novel Targets

This engineering cycle describes how we progressively built a robust computational pipeline for designing, testing, and ranking de novo protein binders for our MESA and GPCR receptors. From initial BindCraft generation and molecular dynamics stability tests to optimized umbrella sampling and thermodynamic corrections, we established a reliable workflow for identifying the most promising binders based on binding affinities for further wet lab validation.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Iteration 5

DESIGN

We started by generating de novo binders for several ligands using BindCraft (Pacesa et al., 2025), aiming to explore how input ligand structure affects the quality of predicted binders. We also tested multiple bindcraft settings to find the optimal design for our binders, as advised in the interview with the first author of BindCraft, Dr. Martin Pacesa.

BUILD

For each ligand (GDF15, OGN and LY6K), we predicted 3D structures of the ligand usingAlphaFold3 . For GDF15 we additionally tested binder creation using the available crystal structure (PDB ID: 5VT2). Then we generated 10 binders for each ligand, with different selected binding interfaces and various binder lengths.

TEST

We observed that different ligands yielded very different numbers and qualities of binders. Some ligands performed exceptionally well and yielded many binders, while others resulted in no binders at all. A correlation was visible between selected interfaces with high pLDDT scores and faster generation of more binders . In contrast, BindCraft was unable to generate binders for structures with many flexible or poorly predicted. For the GDF15 crystal structure, BindCraft also performed poorly and generated a low amount of binders.

LEARN

We learned that BindCraft’s success depends heavily on the structural quality of the input ligand. Poorly resolved structures or high flexibility in AlphaFold predictions can negatively influence binder generation. Ligand choice and structure accuracy are therefore key factors for successful binder design. As a result we decided to go ahead with standard BindCraft settings (60-150 residues) with predefined well-structured hotspots.

DESIGN

In this cycle, we focused on studying the interaction interfaces and structural stability of binder-ligand complexes to understand how well different binders hold up during simulations.

BUILD

We performed 40 ns steered MD simulations for each binder–ligand pair, with 4 replicas per system to ensure reproducibility. After this, we performed trajectory analysis, where we looked at the root-mean-squared deviation (RMSD), radius of gyration, as well as secondary structure analysis using Defined Secondary Structure of Proteins (DSSP) algorithm.

TEST

The stability of the binding interface varied across ligands. For LY6K, the interaction interface remained well preserved, while for GDF15, we observed much more variability. However, the binders themselves were structurally stable across all replicas (low RMSD and radius of gyration).

LEARN

We learned that while BindCraft can produce structurally stable binders, the interaction quality depends strongly on the ligand. The target structure and interface play a major role in how consistent and strong the binding becomes. Also the choice of ligand dictates the heterogeneity and variance between binders for the same ligand. As a result, we sought out to better characterize and rank the generated binders using a more sophisticated ranking pipeline or metric.

Results Image

Figure 1: Binding energy estimation for initial US run. Resulting PMF curve G(ξ) generated using WHAM for the umbrella sampling simulation. The binding free energy of -101 kJ/mol was calculated from the energy in the bound state Δ Gbound(ξ) and unbound state ΔGunbound(ξ).

DESIGN

In the interview with Dr. Martin Pacesa, we additionally learned that the BindCraft built-in ranking system, the i_pTM metric, is not a great affinity-based predictor, but rather a binary predictor for binding. Because of this, we wanted to establish a new ranking method based on binding affinities, which would be required for better characterization of binders for use in SPARC’s mathematical model. After literature research and consulting Prof. Dr. Rebacca Wade, we decided to estimate binding free energies using molecular dynamic (MD) simulations, especially Umbrella Sampling (US), to identify the most promising binders before experimental validation.

BUILD

Using the Gromacs program and the Amber99sb-ildn force field, which we found to be ideal for protein complexes (Lindorff-Larsen et al., 2010). We carried out energy minimization, NVT and NPT equilibration, followed by a short 10 ns steered MD pulling run to generate the reaction coordinate. Umbrella windows were extracted every 0.1 nm for PMF reconstruction.

TEST

The resulting PMF (Potential of Mean Force) curves showed extremely high and unrealistic energies, indicating poor convergence. This led to very unrealistic binding affinities in the picomolar range, indicating a fault within our US workflow.

LEARN

We realized that this happened because the 1D reaction coordinate (COM-distance) was not sufficient to capture all the relevant motions (translation, rotation, folding, etc.). The system was simply undersampled, leading to an overestimation of the binding strength.

Results Image

Figure 2: Binding energy estimation for US run with restrained pulling. Resulting PMF curve G(ξ) generated using WHAM for the umbrella sampling simulation. The binding free energy of -25.8 kJ/mol was calculated from the energy in the bound state Δ Gbound(ξ) and unbound state ΔGunbound(ξ). The binder was restrained in the x and y direction during the SMD.

DESIGN

To fix the unrealistic PMFs, we looked into literature, which had documented established US workflows. We realized that adding restraints during pulling would reduce lateral movement and improve convergence speed (Aho et al., 2024). For better histogram overlap, we also sought out to alter pulling/SMD conditions.

BUILD

We applied orthogonal harmonic restraints in the x and y directions during the pulling simulations, pulling along the z-axis for 100 ns instead of 10 ns. The increased pulling force to k = 1000 kJ/nm2 and reduced pull rate to k= 0.0033 kJ/nm2*s were also intended to improve histogram overlap and provide PMF better convergence.

TEST

This setup produced far more realistic results. Unnaturally high PMFs and increasing pulling forces were no longer observed, and the resulting histograms showed clear overlap. The free-energy profiles converged much better than in the previous cycle.

LEARN

We learned that restraints help the system converge faster by limiting unnecessary movement. However, we realized that we also artificially restrict entropy, which can make binding appear stronger (i.e., lower ΔG) than it really is.

DESIGN

To recover realistic thermodynamic values for biological interpretation and ranking, we applied entropy and volume corrections to the restrained systems following (Govind Kumar et al., 2023).

BUILD

We calculated the final binding free energies (ΔG°) from the PMF and applied corrections for both volume (ΔGV) and restraints (ΔGR), effectively restoring lost degrees of freedom.

TEST

After correction, the results became biologically meaningful and thermodynamically realistic. We could now rank binders by their corrected ΔG° and KD The corrected affinities were slightly weaker (more positive ΔG° as expected).

LEARN

We learned that strong restraints suppress entropy and can bias the results. Applying corrections gives back the degrees of freedom and ensures realistic thermodynamics, although the corrections can become large when the restraints are too strong, leading to higher, less favorable ΔG°.

Predictive Mathematical Model for Phosphorylation Circuit Design

This engineering cycle outlines our step-by-step process of constructing and refining a mathematical framework to simulate receptor dimerization and circuit behavior in PHOENICS cells. Through five design–build–test–learn iterations, we evolved from an unsolvable analytical model to a high-throughput, prediction pipeline capable of predicting circuit performance and guiding experimental design.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Iteration 5

DESIGN

To understand the processes involved in our system and guide the development of its architecture, we aimed to construct a mathematical model that could simulate the complex interactions between the protein components. In order to tackle this, we decided on a modular approach. Specifically, we identified two distinct models: one for receptor dimerization in the sensing layer and another for the phosphorylation-based computational cycle in the processing layer. This modular approach ensured that each component was thoroughly understood and optimized before integrating them into a single, cohesive system. For the circuit model, we drew from a similar existing design, which served as a valuable reference for adapting it to our specific requirements (Yang et al., 2025). To begin with, we decided to address receptor dimerization by defining an ordinary differential equation (ODE) and solving it using Python, allowing us to model the process in detail before combining it with the other system components.

BUILD

To implement the model, we began by documenting all the reactions involved in the receptor system, carefully accounting for each interaction as well as for background dimerization processes. From these reactions, we derived a system of ODEs to describe the dynamic behavior of the system. To reflect realistic biological conditions, we made a steady-state assumption, which allowed us to simplify the system into a quintic form. This simplification was achieved by utilizing partition functions for each reaction species, ensuring that the equilibrium behavior of the system was accurately captured.

TEST

The system of equations was solved using Python, but we faced challenges in obtaining a solution. Due to the complexity of the equations, an analytical solution was not attainable. Moreover, attempts to solve the system with a numerical integrator failed to converge, suggesting the need for further refinement of the model. To address this issue, we sought guidance from multiple experts in systems biology and the modeling of biological processes, aiming to identify potential solutions and improve the model’s accuracy and convergence.

LEARN

The initial approach for modeling receptor dimerization proved too complex to solve analytically. Consulting with experts, including Dr. Stefan Kallenberger, indicated that a simpler approach would be more feasible, guiding us to reduce complexity while preserving the key dynamics of receptor dimerization.

DESIGN

Based on expert advice, we decided to pursue a numerical approach to model receptor dimerization that explicitly considers heterodimerization. This allows us to model a broader spectrum of receptors, which is key to ensure the modularity of our system.

BUILD

To implement this approach, we took an existing mathematical model of heterodimerization as a reference (Lu & Wang, 2017) and integrated it into our existing Python framework. This allowed us to leverage prior work while adapting it to the specific requirements of our receptor system and processing circuit.

TEST

Initial tests using dummy parameter values produced rapid and plausible results, confirming that the numerical model behaves as expected. These preliminary outputs validated the approach and demonstrated that the model could reliably simulate receptor dimerization dynamics.

LEARN

From this iteration, we concluded that the numerical model successfully captures receptor heterodimerization in a way that meets our system requirements. With a working model in place, we are now ready to integrate it into the broader circuit framework for further simulations and analyses.

DESIGN

The next step involved combining the receptor and circuit models into a larger framework, with the goal of calculating phosphorylated substrate concentrations based on input ligand levels. To characterize the cell architecture, it was important to determine both the point at which the cell switches from the OFF to the ON state and the speed of this transition. This required integrating the dynamics of receptor heterodimerization with the phosphorylation-based computational cycle.

BUILD

To implement this integration, we modified the circuit model to accept the output of the receptor model as its input. We duplicated the receptor model to create two identical copies representing the positive and negative inputs. By varying the ratio of positive to negative ligands and calculating the resulting phosphorylation levels, we generated dose-response curves for specific architectures. From these curves, we inferred the EC50 values, representing the switching point, and the Hill coefficient, reflecting the switching speed.

TEST

After some fine-tuning, we were able to define a set of parameters that allowed the phosphorylated substrate concentration to be calculated quickly and as intended. However, when varying the input concentrations, we observed discontinuities and jumps in the results, indicating issues in the current solving approach.

LEARN

This iteration demonstrated that phosphorylation levels can, in principle, be predicted from ligand concentrations. However, the current method for solving the quintic equation of the receptor model does not correctly handle root selection. These discontinuities prevent reliable calculation of the Hill coefficient and EC50, highlighting a key challenge that was crucial to be addressed in further refinement.

DESIGN

Following the issues we faced, our goal was then to model dose-response curves confidently and without artifacts. The model needed to account for additional factors, such as baseline phosphorylation, which can influence the Hill coefficient calculation. To improve performance and precision, we decided to first identify the switching point and then perform a more detailed sampling around it, ensuring accurate calculations.

BUILD

To achieve this, we refined the root selection process to produce smooth curves and implemented baseline correction to account for background phosphorylation. A two-layer calculation strategy was introduced: initial coarse sampling across a broad range of ligand ratios identifies the switching point, followed by finer sampling to capture the transition in detail. These improvements were integrated into the existing Python framework.

TEST

Testing with defined parameters confirmed that the improvements were effective. Both the Hill coefficient and EC50 were calculated correctly, and overlaying a Hill curve using the extracted parameters showed excellent agreement with the modeled dose-response data.

LEARN

Testing our established model demonstrated that it can reliably extract circuit characteristics for a given architecture. With accurate and high-resolution dose-response calculations now achievable, the framework is ready to be applied in a high-throughput manner to systematically characterize multiple circuit designs.

DESIGN

Characterizing system architectures experimentally by building them in the wet lab is laborious and costly. To circumvent this restriction, we intended to leverage the developed mathematical mode as a predictive tool to guide the cell architecture and reduce the number of architectures that are constructed and tested in the wet lab. Due to the analytical intractability of the system, we decided to create a database encompassing all possible combinations of components and varying input concentrations, providing a comprehensive reference for downstream analysis.

BUILD

To implement this, we developed a pipeline that takes a structured table of parameters and iterates over every possible permutation to calculate the Hill coefficient and EC50 value for each configuration. The results are then compiled to visualize the parameter space. For efficient computation across many architectures, the pipeline was parallelized to run on a high-performance computing (HPC) cluster, enabling rapid high-throughput analysis.

TEST

Initial tests with dummy parameters confirmed that the pipeline functions as intended. Subsequently, we ran simulations using biologically relevant parameters that reflect the components employed in the wet lab, ensuring that the output is directly applicable to experimental design.

LEARN

This pipeline provides a robust tool to systematically guide the design of PHOENICS cells. By mapping the effects of component combinations and concentrations, it enables informed decisions for tailoring cell architectures to specific experimental needs, streamlining the design process for future wet lab implementation.

Conducting Functional Membrane-bound MESA Receptor Simulations

This engineering cycle outlines our step-by-step process to develop a reliable computational workflow for modeling MESA receptor dimerization. Through multiple design–build–test–learn iterations, we moved from failed AlphaFold predictions to alignment-based structure generation, leading to refined, membrane-embedded coarse-grained simulations of CD28/CD28 and CD28/CD28(M3) transmembrane domains.

Iteration 1
Iteration 2
Iteration 3
Iteration 4
Results Image

Figure 1: Alphafold-generated tertiary structure of FKBP-CD28 receptor half. Extracellular FKBP domain (orange) linked to the CD28 TM domain (red), which is predicted as a disordered region by AF3.

DESIGN

We sought to computationally evaluate the propensity for ligand-independent dimerization of alternative MESA transmembrane (TM) domain combinations because subtle differences in TM pairing can produce substantial differences in basal signaling of synthetic receptors (Daringer et al., 2014; Levintov et al., 2024). For these analyses we required atomic-level models of the extracellular rapalog-responsive halves (FRB and FKBP) connected via a flexible linker to either the native CD28 TM sequence or the CD28(M3) TM variant. The realistic geometry at the TM–linker junction is critical because it governs helix registry and the relative orientations sampled when the constructs are embedded in a bilayer. Generating a single, end-to-end structural model that captures both the folded extracellular domains and the membrane-spanning helices was therefore the primary modelling objective of this cycle.

BUILD

As an initial strategy we attempted whole-protein structure prediction with AlphaFold-3 by providing the complete receptor sequences from the extracellular N-termini through the TM segments. This approach leverages state-of-the-art neural network prediction to produce a single atomic modelfrom sequence, and we hoped it would simultaneously resolve the globular FKBP/FRB folds and produce sensible TM helices and linkers for downstream simulation (Abramson et al., 2024).

TEST

AlphaFold3 accurately reconstructed the globular FKBP and FRB domains with well folded cores that matched expected topology, but the predicted models systematically failed to produce stable, canonical TM helices and instead returned largely unstructured or poorly defined conformations in the membrane region; the linker geometry was likewise uncertain. The absence of clear helical registry and membrane-embedded geometry rendered these models unsuitable as starting coordinates for membrane simulations where helix tilt, rotation and packing are decisive.

LEARN

From this iteration we concluded that end-to-end prediction in its out-of-the-box form is inadequate for reliably modelling membrane-embedded receptor segments because it does not explicitly represent the lipid environment or enforce membrane-specific helix restraints. This limitation made it necessary to adopt a complementary, template-guided approach that can impose helical restraints and preserve TM geometry.

Results Image

Figure 2: Modeller-generated tertiary structure of FKBP-CD28 receptor half. Extracellular FKBP domain (orange) linked to the CD28 TM domain (red), which is modelled with a helical structure restraint using Modeller.

DESIGN

To obtain starting structures with well defined TM helices and realistic linkers we adopted comparative modelling using Modeller, a template-based program that constructs models by sequence alignment to experimentally determined structures and allows the imposition of geometric restraints (Webb & Sali, 2016). This approach is well suited for our system because the extracellular FKBP/FRB dimer is available as crystal structures, and Modeller can be instructed to treat TM segments as constrained helices while permitting the linker to retain conformational flexibility.

BUILD

We used the crystallographic FKBP–FRB dimer (PDB ID: 3FAP) as the structural template after manually removing the rapalog ligand to focus on ligand-independent interactions. The full receptor sequences were provided as targets and an alignment to the template guided backbone construction. During model building we applied explicit helical restraints to the CD28 and CD28(M3) TM regions and loop restraints to the interdomain linker so that the TM segments adopted canonical helical geometry while the linker retained realistic flexibility for later sampling in dynamics.

TEST

The Modeller-generated, loop-refined models displayed correctly folded extracellular FKBP/FRB domains consistent with the template, flexible but geometrically plausible linker conformations, and well-formed helical TM segments for both CD28 and CD28(M3). Quality checks and visual inspection confirmed that the TM helices had reasonable length, registry and orientation for membrane insertion, producing a set of starting structures that were appropriate for coarse-graining and subsequent membrane simulation.

LEARN

This cycle showed that sequence-alignment guided comparative modelling can reliably produce the membrane-competent topologies that AlphaFold-3 failed to deliver for our constructs. Modeller therefore provided structurally robust inputs for the dynamical studies and highlighted that combining template information with targeted restraints is an effective strategy for mixed soluble/membrane proteins.

DESIGN

To probe membrane-mediated dimerization on biologically relevant timescales without excessive computational cost, and following consultation with expert Dr. Fabian Grünewald, we elected to switch from all-atom molecular dynamics to coarse-grained (CG) simulations using the Martini 3 force field (Souza et al., 2021). The coarse-grained approach reduces particle count and smooths energy landscapes, enabling multi-microsecond sampling of large membrane systems where slow association events and lipid-mediated interactions are of interest.

BUILD

Receptor halves were converted to a Martini-compatible representation using martinize2 (Kroon et al., 2025), which maps atomic coordinates to coarse-grained beads and preserves secondary structure constraints, and these coarse-grained proteins were then embedded into a model plasma membrane assembled with the Insane membrane builder to generate complete protein–bilayer systems with specified lipid composition (Wassenaar et al., 2015).

TEST

Automated insertion using INSANE produced systems in which the receptor halves were incorrectly oriented and incompletely embedded in the bilayer for both CD28/CD28 and CD28/CD28(M3) constructs, resulting in nonphysical starting configurations that prevented the reliable initiation of production CG simulations. The misorientation suggested that, while Insane excels at creating complex membranes, its default insertion routines are not always robust for asymmetric or extended protein shapes derived from coarse-graining.

LEARN

We determined that Insane reliably constructs membrane patches with desired lipid mixtures but can fail to place and orient nontrivial protein geometries correctly, and thus automated insertion cannot be relied upon for complex synthetic receptor halves. This necessitated developing a manual placement workflow to precisely control protein orientation and separation prior to production runs.

Results Image

Figure 3: Coarse-grained background dimerization of MESA receptors for different TM domain pairs. The distance plot shows the center-of-mass (COM) distance between the Modeller-generated FKBP/FRB receptor halves over the course of the 2 𝜇⁢𝑠 simulation for the CD28/CD28 (orange) and CD28/CD28(M3) (purple) domain pairs.

DESIGN

To address the insertion problem we designed a manual preparation protocol in which the coarse-grained receptor halves would be explicitly oriented relative to the bilayer normal and positioned at a defined initial separation, thereby producing a controlled and reproducible starting ensemble for CG dynamics and enabling the direct comparison of background dimerization between TM variants.

BUILD

Using PyMOL we translated and rotated the coarse-grained coordinate sets to align the TM helices with the membrane normal and corrected any tilt or rotational offsets (Schrödinger, LLC, 2015). The two receptor halves were positioned with an initial center-of-mass separation of 10 nm to avoid artifactual interactions at t = 0, and these manually oriented systems were simulated for 2 μs under the Martini 3 force field to allow sampling of membrane-mediated approach and association.

TEST

Manual insertion produced well embedded and stably oriented receptor halves throughout the 2 μs trajectories and the simulations ran without the insertion artefacts observed previously. Analysis of the time-dependent center-of-mass distances between receptor halves revealed reproducible differences in baseline membrane-mediated dimerization between the CD28/CD28 and CD28/CD28(M3) pairs, supporting the hypothesis that TM sequence variation modulates ligand-independent association.

LEARN

This final iteration confirmed that manual orientation and placement are required when dealing with complex, asymmetric coarse-grained proteins and that Martini3 CG simulations provide a computationally efficient, robust platform to quantify relative background dimerization tendencies. Moving forward, these results motivate systematic replicate simulations and free-energy calculations to quantify association energetics and support rational design of low-background MESA constructs.

Human Practices

Empowering Young Scientists to Think Translationally

From an expert panel to a regional roadmap. First, we hosted a successful panel discussion that brought together leaders in translation, regulation, and patient advocacy, opening a vital dialogue and educating students on the challenges of bringing research to patients. The success of this event and the audience's call for "what's next?" directly led to our second initiative: the creation of a regional roadmap, a practical guide designed to help students navigate the local innovation ecosystem and take concrete steps with their ideas.

Iteration 1
Iteration 2
Iteration 3

DESIGN

Our project began with a foundational goal: to learn what it takes to translate a project. Our method was to conduct exploratory interviews with leaders in the field. These conversations rapidly converged on a recurring, critical theme: the immense challenge of navigating the regulatory landscape. This allowed us to define a specific focus: the "the translation gap." Based on this finding, we wanted to design a project to convene senior regulatory experts to tackle "red tape" in Germany at a policy level.

BUILD

To execute this design, we created the project's initial framework. This involved drafting a formal proposal for the expert-level round table event and identifying a list of high-profile stakeholders in regulation and policy to invite. Prof. Dr. Rienk Offringa (DKFZ Drug Discovery Lab) gave us insights on the practical regulatory bottlenecks in Germany.

TEST

We tested the core concept of our project by presenting the idea to experienced mentors and stakeholders. Prof. Dr. Platten challenged this idea, explaining that these essential discussions already occur at an extremely high level, involving seasoned policymakers, pharmaceutical companies, and major research organizations. He gently emphasized that the level of expertise required to meaningfully contribute is immense, making direct influence an unrealistic, if admirable, goal for a student team.

LEARN

We learned that while we couldn't contribute to the experts' conversation, we could address a massive gap at our own level. This led to our project's foundational pivot: we would focus on introducing the very topics that are not taught in the research lab, like regulation, ethics, and entrepreneurship—to students in the format of a panel discussion.

DESIGN

Following our pivot to student education, our new goal was to create an accessible forum for these topics. We designed a public panel discussion to bring the conversation about translation, ethics, and regulation directly to students. A key part of our design process involved conducting preparatory interviews, such as consulting with moderation expert Dr. Carmen Sanges for her advice on crafting effective questions and structuring the panel for maximum engagement.

BUILD

We successfully recruited our target speakers and developed a comprehensive panel discussion moderation guide. This guide was carefully structured to move the conversation from high-level problems to practical advice for young scientists in the audience. We also prepared slides and organized the venue.

TEST

We hosted the panel discussion, which drew an audience of 140 people. This strong turnout reinforced the notion that we had correctly identified a topic of high interest to the student community.

LEARN

The Q&A and subsequent networking session gave us our most crucial insight. We learned that while students are eager to learn, they feel overwhelmed with how to enter the world of scientific translation. The recurring questions weren't about the problems themselves, but about the solutions: "What are the next steps I can take right now?" and "Who can I turn to for support?" This made us realize we could take on a guiding role in our ecosystem, and we began preparing for our next big project.

DESIGN

The panelists encouraged us to take the initiative and help shape the innovation landscape. That was easier said than done. Even for those of us who were well-connected, the idea of influencing our translational ecosystem felt overwhelming. If we felt this way, we realized it was likely that other young scientists and students felt the same. Our goal evolved into a new direction: to better understand Heidelberg's innovation ecosystem, identify its key players, and map the support networks available to help young scientists bridge the translational gap.

BUILD

First, we conducted the necessary research by contacting stakeholders from every relevant part of the ecosystem, including technology transfer offices, startup incubators, and venture capitalist to gather and verify accurate information. Second, with this validated data, we created the guide itself, designing a clear layout and writing concise, actionable content for each section.

TEST

The roadmap will be tested throughout the current academic semester. We will measure the roadmap's success by tracking key metrics:

  1. Quantitative: We will monitor download numbers and see if related innovation workshops are fuller this year compared to previous years.
  2. Qualitative: We will actively collect feedback through a survey.

LEARN

This phase is currently in progress, with the results unfolding over the coming months. Our hypothesis is that by providing a single, comprehensive resource, we will significantly lower the barrier for students to engage with the translational ecosystem. We’ve already received requests from additional institutions to be included in a possible second edition of the guide. The feedback and data we gather will show us whether the roadmap is effective as is, or if a future iteration is needed to improve its content, design, or distribution strategy. The final outcome remains to be seen, and we are eager to learn from our community’s experience.

Shaping Future Innovators

We developed a series of educational formats to make complex synthetic biology concepts accessible to high school students. Beginning with interactive classroom workshops on signaling pathways, we expanded to a Summer School where students gained hands-on laboratory experience. To ensure lasting impact and broader accessibility, we transformed these materials into an interactive online learning platform for students and educators worldwide.

Iteration 1
Iteration 2
Iteration 3

DESIGN

To bring synthetic biology into classrooms, we designed a creative workshop to explain signaling pathways and networks – the basic principle of our own project – to high school students. To make this topic more accessible, we broke it down into three key components: sensing, processing, and responding, giving examples for each. Step by step we explained circuits, endgates and different inputs to make the complexity of such systems easy to grasp.

BUILD

We prepared a presentation on the topics mentioned above, and included a Kahoot, summarizing and reviewing the material. We came up with group work exercises which demanded the students to get creative by designing their own signaling pathways inside of synthetic cells,to solve specific problems. In the process of preparing and creating the learning-materials, we received valuable feedback from a Heidelberg University lecturer and local high school teachers to lay focus on real life applications and the importance of synthetic biology in daily life.

TEST

We hosted our workshop for students of two different advanced biology high school classes. We received very positive feedback from both the students and the teachers, some of which even proposed a long-term collaboration between a local high school in Heidelberg and the iGEM team. During the group work, the students enjoyed thinking and discussing the different opportunities of genetic engineering and protein design, asking us supervisors a lot of questions which underscored the value of giving them an insight into synthetic biology and biotechnology as possible future fields of studies.

LEARN

Experiencing the students’ enthusiasm firsthand showed us the power of interactive teaching formats. It also revealed the need for deeper, hands-on experiences for those who wanted to learn more. That is why we complemented the school workshops with the Summer School where students are able to conduct their own laboratory experiments.

DESIGN

Building on the initiative established by last year’s iGEM team, we continued our collaboration with the DKFZ Life Science Lab (LSL), organizing and supervising a Summer School. The Summer School consisted of two weekend laboratory workshops where students both attended theoretical seminars and gained hands-on experience, carrying out experiments in cell culture and immunocytochemistry.

BUILD

The experiments conducted in the Summer School were derived from our own iGEM experiments and various university courses. In addition, we prepared accompanying seminars to explain the foundational knowledge in molecular biology and the theoretical background of the experiments. We also developed a script to guide students through the laboratory procedures.

TEST

Before the Summer School, we ran and optimized the experiments ourselves. This ensured smooth execution and availability of all necessary materials. We supervised two three-day courses, both of which were very well received, with all spots filling up immediately. The students actively engaged in the seminars, asking insightful and thought-provoking questions about the experiments and the underlying biology, demonstrating both confidence and curiosity.

LEARN

We discovered that Life Science Lab students already had advanced scientific knowledge and laboratory skills, compared to other children their age. Although the Summer School courses received very positive feedback, the spots were confined to eleven students due to the size of the laboratory. Taking these considerations into account, we went on to expand our initiative into an online learning platform, making our educational material accessible to every student and educator. With that, we ensure our efforts have a lasting impact and enlarge our target audience even more.

DESIGN

We decided to digitalize the summer school script and extend the platform with further modules on molecular cloning and basics of molecular biology, originally derived from our own lab protocols. We envisioned it to contain a real experimental workflow with in-depth theory, explanations to each step.

BUILD

To make the platform more appealing, we added a variety of interactive modules, such as calculators and quizzes, allowing the students to test their calculation skills and knowledge. We shared the platform with students from the Life Science Lab and received requests for more visual materials, leading us to integrate the Videos from our Wetlab Series.

TEST

Furthermore, we consulted multiple high school teachers and university educators with our work to get their insights. We received only positive feedback, and some of the high school teachers even plan to integrate parts into their own lesson curricula. Our learning platform is open for students and educators worldwide and provides self-learning material for engaged students. Also, future iGEM teams can contribute to the platform, further expanding it with additional modules.

LEARN

Students responded positively to the learning platform and provided feedback requesting more pictures and illustrations. We incorporated this feedback into the current version of the platform, which is now available on our wiki. Nevertheless, it is important to acknowledge that the learning platform alone will not reach the students effectively. It must be supported by motivated educators who can spark students’ interest in synthetic biology.