A massively parallel reporter assay library to screen short synthetic promoters in mammalian cells

Identification of functional synthetic promoters using a massively parallel reporter assay

Coupling promoter activity to the production of barcoded mRNAs affords the ability to quantify activity in response to stimuli in a sensitive and high-throughput manner via next-generation sequencing (NGS)¹⁵. We developed a barcoded plasmid library (TRE-MPRA) of synthetic promoters composed of TF binding motifs derived from all unique DNA position weight matrices for hundreds of human and mouse TFs identified via HT-SELEX¹⁹ (see Methods). We reasoned that TREs based on DNA sequences bound by TFs ex vivo would produce superior synthetic promoters compared to sequences based on genomic footprints and removed from their native chromatin context. Four copies of a given binding motif were arranged in six configurations (TRE units) and positioned immediately 5’ to one of three minimal promoters to create short, synthetic promoters (hereafter promoters) driving expression of a protein coding transcript (Luc2) with a barcoded 3’ UTR (Fig. 1, Supplementary Fig. 1). We also included hundreds of negative control promoters containing TREs of scrambled sequences in the library. Four independent plasmid library preparations from distinct liquid bacterial cultures were sequenced on separate flow cells and showed nearly identical barcode representation per promoter, as well as highly correlated barcode reads per million (Supplementary Fig. 2A, B). The mean and median barcode representation for promoters in a representative plasmid library preparation were 82 and 65, respectively. Of the 6318 promoters we designed, a total of 6144 (97%) were detected in our plasmid preparations.

a Transcription factor binding motifs (TFBMs) included in the TRE-MPRA library were derived from the HT-SELEX dataset of Jolma et al. Candidate synthetic promoters were designed by combining homotypic TFBMs and one of three minimal promoters in multiple configurations. Commercially available TREs, as well as negative control promoters were also included in the TRE-MPRA library. b Four copies of a given TFBM were oriented on alternating sides of the DNA double helix using spacer sets of random nucleotides and rotated along the helix relative to the minimal promoter (TRE unit). TRE units combined with minimal promoters (‘promoters’) regulate the expression of a Luc2 CDS containing 24 nucleotide barcodes in the 3’ UTR. Barcodes were mapped to associated TRE units using next-generation sequencing (NGS) during library preparation. c Barcoded RNAs were extracted from transfected cells and sequenced via NGS alongside the input TRE-MPRA plasmid libraries. Resulting barcode counts were used to generate estimated transcription rates and analyzed via MPRAnalyze to compare promoter activities between treatments. Created in BioRender. Zahm, A. (2024) https://BioRender.com/i28a348.

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We first benchmarked this library by transfecting the human HEK293 cell line and culturing the cells in serum-free media for 24 h to establish baseline transcriptional activities of each promoter. We quantified barcoded mRNA levels via NGS and then calculated the aggregate ratio of RNA to DNA reads per million as a proxy estimate of promoter transcription rate. Each of two independent experiments, both comprising four independent replicates of transfected cells and sequenced on separate flow cells, showed a range of transcriptional rate estimates greater than 300-fold across all promoters (Supplementary Fig. 2C). Furthermore, rate estimates were highly correlated across the independent experiments (Spearman’s p = 0.960, p < 0.0001) (Supplementary Fig. 2D). Across the population of TRE units, we observed a pronounced effect of the paired minimal promoter on baseline transcription rates, whereas the spacer sequences between TF binding motifs and the distance between the TRE unit and minimal promoter did not globally alter transcription (Supplementary Fig. 3).

Next, we transfected HEK293 cells with the TRE-MPRA library and subsequently treated the cells with fetal bovine serum (FBS) or forskolin for six hours in triplicate. Cellular responses to serum and forskolin are classically associated with the serum response element (SRE) and cAMP response element (CRE), respectively^20,21,22. Differential promoter activities relative to vehicle-treated cells transfected with the library were determined using MPRAnalyze²³. As expected, serum treatment elevated expression from SRE promoters, while forskolin activated CRE promoters (Fig. 2a). Transcriptional activities from promoters containing one of three human thyroid hormone receptor beta (THRB) motifs (THRB-1) were significantly elevated in cells treated with FBS, whereas motifs of highly-similar sequence did not alter transcription in response to FBS (Fig. 2a, b). Notably, each of these sequence-similar but non-responsive promoters lacks a palindromic structure like the responsive THRB-1 motif. We also observed increased activities from promoters containing the murine v-maf musculoaponeurotic fibrosarcoma oncogene family, protein B (Mafb) binding motif following stimulation with forskolin (Fig. 2a). Of note, the THRB-1 motif is highly similar in sequence to the CArG box of SRE bound by serum response factor (SRF) and thus may provide a readout of SRF activity rather than THRB²². Likewise, the Mafb motif (TGCTGACGTAAGCA) in the TRE-MPRA library contains a sequence very similar to the cAMP responsive element (TGACGTCA) and so may be activated by cAMP responsive element binding protein 1 (CREB1) as opposed to MAFB²¹. Importantly, the responses of these promoters were uncorrelated with barcode abundance in the plasmid library (Supplementary Fig. 4A). Both treatment conditions showed differential effects of spacer sets and the position of TRE units in the DNA helix relative to the minimal promoters for specific TF motifs (Supplementary Fig. 4B, C). This result suggests that, while not an important consideration for many TREs, the distance between TRE and paired minimal promoter significantly affects synthetic promoter utilization by certain TFs.

a Promoter responses of HEK293 cells treated with 10% FBS (left) or 20 µM forskolin (right) (n = 3 each) compared to untreated cells (n = 4). Select promoters are colored by TFBM. Dashed lines: 5% FDR threshold. Dark gray data points: negative control promoters. LRT, likelihood ratio test. b Barcode fold changes for promoters containing the THRB-1 motif or similar motifs following 10% FBS treatment. Individual barcode responses of each THRB-1 (c) or Mafb (e) promoter in FBS or forskolin treated cells, respectively, relative to controls. d, f Dose-response curves of THRB-1 (d) and Mafb (e) TRE promoters tested in dual-luciferase assays. Data were scaled to the Fluc/Rluc ratio in untreated cells (N.D. – no drug). Data points and error bars: mean and standard deviation (n = 4 technical replicates) within each experimental replicate (n = 3 independent experiments). Shaded lines indicate TRE-MPRA doses.

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For each barcode, we calculated the median reads per million across biological replicates and then compared barcode fold changes (treatment versus unstimulated) of all THRB-1 and Mafb promoters against the panel of negative control promoters (Fig. 2c, e). Consistent responses across the populations of barcodes suggested the induction of individual promoters following stimulation was highly reproducible. We also noted the degree of induction of THRB-1 and Mafb TRE activity was dependent upon the paired minimal promoter (Supplementary Fig. 4D). To test these findings in an orthogonal assay, we derived dual-luciferase reporter plasmids containing individual promoters controlling the expression of a luc2P CDS, as well as a constitutive SV40-driven Renilla luciferase cassette. The promoters selected for validation reflected the general MPRA responses of all promoters containing these TREs under these treatment conditions. HEK293 cells transfected with reporter plasmids showed dose-dependent increases in relative luc2P activity following stimulation with FBS or forskolin (Fig. 2d, f). Furthermore, minimal promoter-dependent responses were observed, largely in agreement with our TRE-MPRA results (Supplementary Fig. 5A). These results demonstrate that our synthetic promoters can function as dynamic transcriptional readouts of cell signaling.

These orthogonal dual-luciferase experiments also found baseline transcription rates of the THRB-1 and Mafb promoters in untreated cells to be in agreement with the estimated transcription rates in untreated cells (Supplementary Fig. 5B). To further determine if constitutive transcription rate estimates derived from our TRE-MPRA experiment are reliable predictors of expression output in orthogonal assays, we derived and tested dual-luciferase reporter plasmids containing promoters spanning a range of estimated transcription rates from untreated HEK293 cells (Supplementary Fig. 5C). This series of reporters produced luciferase activities in line with the MPRA transcription rate estimates, with the exception of the BHLHB3 motif-containing promoter (Supplementary Fig. 5D). This discordant finding may reflect TF/TRE-specific translation rates observed in previous studies^24,25,26, and emphasizes the necessity to validate individual candidate promoters in orthogonal assays.

Modulating additional synthetic promoters with additional stimuli

With a validated MPRA platform in hand, we next sought to modulate the activities of additional promoters in the library by treating HEK293 cells with eight additional stimuli, including mitogens and inducers of cellular stress (Supplementary Data 1). To increase throughput, we included a single replicate for most treatment conditions, as our preliminary results from FBS and forskolin treated cells showed that individual biological replicates identified the same sets of top responding promoters as multiple replicates, albeit with lower precision (Supplementary Fig. 6). We performed hierarchical clustering to classify common and specific promoter responses (Fig. 3a). For most stimulus types, we observed hundreds of promoters with significantly altered activity, even at a stringent FDR cutoff of 5%, attesting to the statistical power of MPRAs. Across ten stimulus conditions, 1949 promoters (31.7%) showed altered transcriptional output in at least one condition relative to negative controls, while 207 promoters (3.4%) were altered in at least half of the conditions. Several treatments activated promoters with similar or greater effect sizes as was seen for FBS- or forskolin-responsive promoters. For example, dexamethasone treatment caused significant upregulation of TRE units containing motifs for two nuclear receptor superfamily class I (steroid) members: androgen receptor (AR) and glucocorticoid receptor (NR3C1) (Fig. 3b). A dual-luciferase plasmid containing one of our AR promoters showed a dose-dependent response to dexamethasone with a dynamic range of 134-fold (Fig. 3c). In addition, treatment with lithium chloride caused strong activation of TRE units with an NFAT5 or NFATC1 motif (Supplementary Fig. 7A), in line with lithium’s inhibition of glycogen synthase kinase 3 beta, itself an inhibitor of NFAT transcriptional activity^{27,28,29,30,31}.

a Heatmap of fold change responses in HEK293 cells across ten stimulus conditions relative to untreated cells. Treatment conditions were clustered using Euclidean distance with complete linkage. Displayed are the fold change values for all promoters that were significantly altered by treatment in at minimum one comparison. b Volcano plot of promoter responses following treatment of HEK293 cells with 100 nM dexamethasone in comparison to untreated cells. Dashed line indicates an FDR threshold of 5%. Negative control promoters are indicated by dark gray data points. c Dose response curve from HEK293 cells transfected with an AR promoter dual luciferase reporter and treated with dexamethasone (AR, minCMV, rotation 4, spacer set 1). Data were scaled (baseline normalized) to the Fluc/Rluc ratio in untreated cells (N.D. – no drug). The curve was fit to baseline normalized Fluc/Rluc values. Data points and error bars indicate the mean and standard deviation of technical replicates within each of three experimental replicates (n = 3 independent experiments, distinguished via color). The shaded vertical line indicates the dose of dexamethasone used in the TRE-MPRA experiment. d Scatterplot comparing promoter responses between lithium and cadmium treatments. HSF1 units were more responsive to cadmium. Dashed line indicates the identity line (y = x). e Separated biplots of standardized baseline transcription rates in the six mammalian cell lines. Displayed are the untreated cell line (left) and promoter (right) projections across two dimensions. All colored units are paired with the minCMV promoter. Orange and gray projection lines indicate the positive and negative directions of the treatment projection, respectively. f Example cell line-specific promoters responsive to treatment with 10% FBS. Each displayed promoter was significantly induced by FBS treatment in exactly one of six mammalian cell lines (FDR < 5%).

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Our treatment conditions included two heavy metals: one physiologic (zinc) and one xenobiotic (cadmium). We noted that both metal treatments induced similar responses in metal response element (MRE)-containing and Tp53-containing promoters, relative to vehicle-treated controls, despite the apparent toxicity of zinc but not cadmium (Fig. 3d, Supplementary Fig. 7B). The MRE is bound by metal regulatory transcription factor 1 (MTF-1) in response to both zinc and cadmium elevation, as well as oxidative stress^32,33. However, cadmium treatment showed two- to three-fold higher induction of HSF1- and heat shock element (HSE)-containing promoters relative to zinc. Previously, using a modified HEK293 cell line containing an HSE reporter, Steurer et al. observed³⁴ that HSE was roughly 200-fold more sensitive towards cadmium than zinc³⁵. Because HSE is bound by both MTF-1 and HSF1, the observed HSE and HSF1 promoter activation discrepancies between zinc and cadmium treatments are likely a result of HSF1 activity rather than MTF-1³⁶.

Next, we transfected the TRE-MPRA library into additional mammalian cell lines in order to compare baseline transcription rates between cell lines from different species and tissue origins. While HEK293 experimental replicates had highly-correlated baseline transcription rates, correlations between different cell types were much lower (Supplementary Fig. 8A). To identify differentially active promoters between cell types, we generated biplot displays using standardized aggregate RNA to DNA ratios of barcode reads per million³⁷ (Fig. 3e). Several TRE units were highly active in subsets of cell lines, suggesting certain transcription factors have cell-specific basal activities (Supplementary Fig. 8B). Meanwhile, the basal transcription rates from Tp53-3 containing promoters in Neuro-2a and MDA-MB-231 cell lines were comparable to negative control promoters, whereas all other cell lines displayed much higher transcription rates (Supplementary Fig. 8B). Both Neuro-2a and MDA-MB-231 cell lines are known to harbor missense mutations in the DNA-binding region of p53 (V170L and R280K, respectively)^38,39, which may explain the lack of transcription from these promoters, as p53 missense mutations have been shown to hamper utilization of response elements in human p53 target genes⁴⁰.

To determine if these additional cell lines respond to serum treatment by differentially activating specific promoters, we transfected the cell lines with the TRE-MPRA library and treated them with FBS for 6 h. Serum responses were surprisingly discordant between cell lines, regardless of species (Supplementary Fig. 8C). For example, none of the additional cell lines significantly induced SRF units paired with minPromega or minTK minimal promoters, including those units based off of commercial reporters, whereas these promoters were consistently induced in HEK293 cells (Fig. 3f). Indeed, each cell line responded to serum by activating subsets of promoters not activated in other cell lines. Because baseline promoter transcription rates and the responses to serum were discordant between cell lines tested, we recommend performing the TRE-MPRA screen in specific cell models of interest to identify optimal promoters.

Specific synthetic promoters activated by aminergic GPCR agonism

G-protein coupled receptors (GPCRs) are 7 transmembrane proteins that, upon binding extracellular ligands, catalyze the exchange of GDP for GTP in heterotrimeric G-protein complexes to induce cellular signaling activities. GPCRs are present in every cell in the body and are involved in all known biological process from the detection of light in the retina and neurotransmitter relays in the brain to immune cell antigen detection and bone growth. Therefore, the 800 GPCRs of the human genome have been fruitful targets for drug development, with roughly 1/3 of all FDA approved drugs targeting a GPCR. The totality of signal integration from GPCRs remains unresolved and varies among cells and signaling context and there remains an urgent needed to more completely characterize the molecular and cellular consequences of ligand-receptor interactions for GPCR drug development.

After identifying synthetic promoters with large dynamic range responses across multiple chemical and mitogen treatments, we examined whether the TRE-MPRA library possesses the sensitivity necessary to detect transcriptional responses following GPCR activation. A limited number of TREs have long been used as readouts for GPCR signaling events, particularly as part of bioluminescent sensors⁴¹, but these remain insufficient to fully map the input-output relationship between receptor activation and global cellular response. GPCRs can activate over 300 independent G-protein heterotrimers as well as non-canonical effectors, a complexity that cannot be captured through single, or even several, biological readouts^42,43,44.

Here, we employed TRE-MPRA to profile transcriptional changes induced by activation of three well-characterized aminergic GPCRs. HEK293 cells were co-transfected with the TRE-MPRA plasmid library and a plasmid expressing one of three human GPCRs: β2-adrenergic receptor (β2 AR), 5-hydroxytryptamine receptor 2A (5-HT_2A), or dopamine receptor D2 (D₂R). These receptors selectively couple to Gα_s-, Gα_q-, and Gα_i-containing heterotrimeric G protein complexes, respectively. Upon GPCR activation by receptor agonists, these G protein complexes initiate distinct downstream signaling cascades^45,46. After six hours of receptor agonist treatment (β2AR: 1 µM epinephrine; 5-HT_2A: 100 nM 5-HT; D₂R; 1 µM dopamine), we harvested RNA and analyzed differential barcode abundance between receptor alone and receptor with agonist conditions (Fig. 4a). Serotonin treatment in cells expressing 5-HT_2A induced transcription from many promoters, including those containing THRB-1 and SRE units. Epinephrine treatment in cells expressing β2AR triggered increased expression from promoters containing Mafb and CRE motifs, similar to what we observed in forskolin treated cells, as both forskolin and Gα_s signaling stimulate the formation of cyclic AMP. Conversely, dopamine binding to D₂R activates Gα_i signaling, which leads to the inhibition of cyclic AMP production^47,48,49. Surprisingly, no promoters were differentially active upon D₂R agonism. To determine if this result reflects technical issues with dopamine treatment, we performed the TRE-MPRA assay on two additional GPCRs: dopamine D1 receptor (D₁R; 1 uM dopamine), which is also agonized by dopamine but couples to Gα_s, and the mu-opioid receptor (μOR; 100 nM morphine), which couples to Gα_i. Unlike D₂R, agonism of D₁R with dopamine resulted in differential promoter activities resembling those observed for Gα_s-coupled β2AR (Fig. 4b, Supplementary Fig. 9A). The activation of μOR with the agonist morphine resulted in just two promoters with FDR values below 5%, in line with our results for D₁R, suggesting that activation of Gα_i-coupled GPCRs does not regulate cellular transcription in HEK293 cells (Supplementary Fig. 9A).

a Volcano plots of promoter responses following receptor agonism in HEK293 cells co-transfected with the TRE-MPRA library and GPCR expression plasmids. Dashed lines indicate an FDR threshold of 5%. Negative control promoters are indicated by dark gray data points. Created in BioRender. Zahm, A. (2024) https://BioRender.com/f26t609. b Heatmap of promoter fold change responses to GPCR agonism in HEK293 cells. Displayed are the fold change values for all promoters that were significantly altered by agonist treatment in at minimum one comparison. GPCRs were clustered using Euclidean distance with complete linkage. c Transcription rate estimates (aggregate RNA/DNA ratios) for CRE and Mafb units in HEK293 cells following 1 µM epinephrine treatment or ADRB2 overexpression, or both. Each connected set of data points represents a single promoter.

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Having detected transcriptional changes mediated by exogenous, overexpressed GPCR agonism, we next asked whether the TRE-MPRA platform can detect transcriptional changes due to endogenous GPCR agonism, as well as changes resulting from receptor overexpression in the absence of an exogenous ligand. To address this question, we focused on β2AR in HEK293 cells, which are known to express functional β2AR endogenously⁵⁰. We co-transfected cells with the TRE-MPRA library and a control plasmid expressing GFP and then cultured the cells in serum-free media in either the presence or absence of 1 uM epinephrine for six hours. Epinephrine treatment alone resulted in elevated transcription from promoters that had responded to epinephrine treatment in the presence of overexpressed ADRB2, suggesting that this platform is sensitive enough to detect endogenous GPCR signaling following agonism (Supplementary Fig. 9B). Furthermore, the overexpression of ADRB2 in the absence of epinephrine treatment also caused increased transcription from these promoters, suggesting that our platform can detect basal constitutive signaling from plasmid-expressed GPCRs (Supplementary Fig. 9B). Promoters containing CRE or Mafb units were sensitive to endogenous and exogenous ADRB2 signaling to similar degrees across the three minimal promoter combinations (Fig. 4c).

Synthetic promoter activation following agonism of non-aminergic and promiscuous GPCRs

Having profiled synthetic promoter activity following agonist treatment of canonical Gα_s– (β2AR, D₁R), Gα_q– (5-HT_2A), and Gα_i-coupled (D₂R) aminergic GPCRs, as well as μOR, and identified G protein-specific changes following activation, we next utilized the TRE-MPRA platform to profile activation of additional GPCRs. We first assayed two non-aminergic GPCRs: the adhesion class protease-activated receptor-1 (PAR1) and the recently de-orphaned succinate receptor (GPR91/SUCR1)^51,52. Agonist treatment of cells overexpressing either of these GPCRs significantly upregulated many promoters that were also increased by 5-HT_2A agonism, such as THRB-1 and SRE-containing constructs, suggesting that PAR1 and GPR91 induce transcriptional changes predominantly via Gα_q signaling (Supplementary Fig. 9C). Indeed, PAR1 and GPR91 profiles showed higher correlation with 5-HT_2A than with the other assayed aminergic GPCRs (Supplementary Fig. 9D), though not identical, in line with observations that PAR1 and GPR91 couple to Gα_q and additional Gα^53,54,55,56.

Next, we profiled two additional non-aminergic GPCRs that can strongly couple to and activate multiple distinct G proteins in HEK293 cells: MAS related GPR family member X2 (MRGPRX2) and neurotensin receptor 1 (NTSR1)^44,57,58,59. Similar to PAR1 and GPR91, MRGPRX2 activated a set of promoters also activated by 5-HT_2A, suggesting MRGPRX2 also preferentially activates Gα_q in HEK293 cells (Supplementary Fig. 9E). In contrast, NTSR1 agonism led to the activation of promoters also activated by either the Gα_s-coupled aminergic GPCRs (β2AR and D₁R) or 5-HT_2A (Supplementary Fig. 9E). To compare the profiles of all nine GPCRs assayed, we generated biplot displays using the set of promoters that showed a significant response to receptor agonism in at least one of the nine datasets (Fig. 5a). Projections for PAR1, GPR91, and MRGPRX2 conditions were closely related to that of 5-HT_2A, again suggesting these GPCRs activate similar downstream signaling pathways. Furthermore, projections of the Gα_s-coupled β2AR and D₁R were highly similar, while the Gα_i-coupled μOR and D₂R receptors showed minimal projections. In general, NTSR1 agonism resulted in the activation of both Gα_s– and Gα_q-responsive promoters (Fig. 5b), as denoted by a biplot projection located between β2AR and 5-HT_2A and by correlation analysis (Supplementary Fig. 9D).

a Separated biplots for the set of promoters that showed a significant response to receptor agonism in at least one of the nine datasets. Displayed are the GPCR log₂ fold changes (agonist versus untreated) (left) and promoter (right) projections across two dimensions. Responding promoters of interest are highlighted. Orange and gray projection lines indicate the positive and negative directions of the treatment projection, respectively. b Heatmap of selected promoter responses to agonism across GPCR experiment groups. GPCRs were clustered using Euclidean distance with complete linkage. Arrows indicate the AP1 unit/minCMV promoters. A list of promoter (row) labels can be found in Supplementary Data 6. c Volcano plot of promoter responses following neurotensin 8−13 (NT) treatment in HEK293 cells co-transfected with the TRE-MPRA library and an NTSR1 expression plasmid, with or without addition of the Gα_q-specific inhibitor FR900359 (FR). d Scaled transcription rate estimates (aggregate ratios) for NFKB1, THRB-1, and CRE units paired with minCMV in HEK293 cells expressing NTSR1. N.D., no drug; NT, neurotensin 8−13 [100 nM]; NT + FR, neurotensin 8−13 [100 nM] + FR900359 [50 nM]. Each set of connect dots represents a single promoter. e Dual luciferase response curves in HEK293 cells in the presence or absence of 50 nM of the Gα_q-specific inhibitor FR900359 (THRB-1, minCMV, rotation 8, spacer set 1; NFKB1, minCMV, rotation 8, spacer set 1). Data were scaled (baseline normalized) to the Fluc/Rluc ratio in untreated cells (N.D. – no drug). The curve was fit to baseline normalized Fluc/Rluc values across three experimental replicates. Data points and error bars indicate the mean and standard deviation of four technical replicates within each of three experimental replicates (n = 3 independent experiments, distinguished via shape).

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We next determined whether agonism of NTSR1 in the presence of the Gα_q-specific inhibitor FR900359 (hereafter inhibitor) would block the activation of promoters associated with 5-HT_2A biplot projection. As expected, Gα_q-specific promoters such as NFKB1 were no longer activated by neurotensin treatment in cells pretreated with inhibitor (Fig. 5c, d). We noted that 5-HT_2A agonism (Gα_q signaling) significantly induced promoters containing CRE units, albeit to a lower magnitude than by Gα_s-coupled β2AR and D₁R receptor activation. NTRS1 agonism in the presence of inhibitor partially blocked the activation of CRE promoters, again suggesting that CRE activity, a canonical readout of Gα_s-coupled GPCR activation, is also induced by Gα_q signaling (Fig. 5c, d). Surprisingly, inhibitor treatment did not significantly alter the activation of THRB-1 promoters, despite these being associated with the 5-HT_2A projection (Fig. 5a−d, Supplementary Fig. 9F). We hypothesized that NFKB1 and THRB-1 promoters are readouts of distinct signaling pathways downstream of GPCR activity. To test this notion, we performed dual-luciferase reporter assays in HEK293 cells overexpressing 5-HT_2A or NTSR1. Agonism of NTSR1 or 5-HT_2A activated the NFKB1 promoter in a dose-dependent manner, and these responses were abolished in the presence of inhibitor (Fig. 5e). Similarly, the THRB-1 promoter responded to 5-HT_2A agonism in a Gα_q-specific manner. However, as observed in the MPRA experiment, inhibition of Gα_q did not block the response of the THRB-1 promoter to NTSR1 agonism, suggesting alternative signaling cascades activated by NTSR1 can induce THRB-1 promoters.

Finally, we noted that activation of AP1 units by GPCR agonism was strictly dependent on pairing with the minCMV promoter (Fig. 5b, Supplementary Fig. 10A). To validate this finding, we generated dual-luciferase reporters that replicated the sequences of minCMV and minPromega versions of AP1 TRE units of the MPRA library. We also converted a commercially available AP1 luciferase reporter into a dual-luciferase reporter by replacing its hygromycin expression cassette with an SV40/Rluc cassette for direct comparison with our synthetic promoters. We then co-transfected HEK293 cells with a GPR91 expression plasmid and the AP1 reporters and measured firefly and Renilla luciferase activities after six hours of cis-epoxysuccinate treatment. We observed a dose-dependent increase in transcriptional output for the AP1 unit coupled with minCMV, whereas the minPromega coupling and the modified commercial AP1 reporter showed little or no response to cis-epoxysuccinate, in agreement with the results of the TRE-MPRA experiment (Supplementary Fig. 10B).

Distinct from the significant potential of this toolset for use in GPCR applications, we also demonstrated its utility in identifying compact synthetic promoters with high dynamic-range responses to a variety of mitogens and cellular stimuli. From these we created and validated a robust reporter for androgen receptor activity (Fig. 3c) and distinct heavy metal responsive reporters (Fig. 3d). In addition, we demonstrated that individual cell lines produce distinct basal and stimulus-dependent TRE-MPRA signatures, highlighting the utility of this biologically-responsive reporter library for use in cell-type specific applications. Our TRE-MPRA platform can be applied to aid in meeting the current significant demands for compact cell-type specific, stimulus-dependent, and combination reporters for synthetic biology applications in complex systems, as our suite of responsive elements represent some of the smallest, endogenously-coupled functional promoters with the highest transcriptional dynamic range yet generated for these applications^60,61,62,63.

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• Source: https://www.nature.com/articles/s41467-024-54502-9