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Customizable gene sensing and response without altering endogenous coding sequences

Nature Chemical Biology (2024)Cite this article

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Abstract

Synthetic biology aims to modify cellular behaviors by implementing genetic circuits that respond to changes in cell state. Integrating genetic biosensors into endogenous gene coding sequences using clustered regularly interspaced short palindromic repeats and Cas9 enables interrogation of gene expression dynamics in the appropriate chromosomal context. However, embedding a biosensor into a gene coding sequence may unpredictably alter endogenous gene regulation. To address this challenge, we developed an approach to integrate genetic biosensors into endogenous genes without modifying their coding sequence by inserting into their terminator region single-guide RNAs that activate downstream circuits. Sensor dosage responses can be fine-tuned and predicted through a mathematical model. We engineered a cell stress sensor and actuator in CHO-K1 cells that conditionally activates antiapoptotic protein BCL-2 through a downstream circuit, thereby increasing cell survival under stress conditions. Our gene sensor and actuator platform has potential use for a wide range of applications that include biomanufacturing, cell fate control and cell-based therapeutics.

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Fig. 1: Embedding gene sensor modules downstream of target genes creates functional sensors without requiring modifications to coding sequences.
Fig. 2: The dosage response of a gene sensor can be fine-tuned by modifying the number of sgRNA cassettes and by using reshaper modules.
Fig. 3: Bin-dependent logistic model fits the experimental data well and predicts EYFP levels in uncharacterized circuits accurately.
Fig. 4: Chromosomally integrated gene sensor to monitor RPS21 expression.
Fig. 5: Chromosomally integrated gene sensor module to monitor and respond to ER stress in CHO-K1 cells.

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Data availability

The main data supporting the results reported in this study are available within the paper and its Supplementary Information. The experimental data that support this study are publicly available from Zenodo (https://doi.org/10.5281/zenodo.12735076)75.

Code availability

Scripts used to fit the model and make predictions can be obtained from GitHub (https://github.com/wang-junmin/GeneSensorModel). MATLAB scripts to analyze flow data supporting the results presented in Fig. 2 are available from Zenodo (https://doi.org/10.5281/zenodo.12735171)72.

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Acknowledgements

We thank L. Wang, R. Jones and O. Adir for the discussion of circuit design and experimental techniques. We thank G. Alighieri and O. Adir for providing the miRNA generating plasmids and miRNA target site sequence. We thank N. Wauford and B. DiAndreth for providing the plasmids encoding CasE and providing the sequences of CasE-BSs. We would like to acknowledge M. L. Kemp and C. Belta for discussions and D. Key and C. Haase-Pettingell for administrative support. We thank our funding sources Defense Advanced Research Projects Agency (DARPA) W911NF19C0008, NIH HR0011-20-2-0005 and NIH 5-R01-EB030946-04 (to R.W. and F.C), National Science Foundation (NSF) CBET-0939511 and NIH HR0011-20-2-0005 (to E.V.), NIH 5R01HD105947-03 (to S.K.), Wellcome Leap HOPE program (to H.S.), NSF CNS-1446474 NIH 5-R01-EB025256-04 and DARPA W911NF-17-3-003 (to C.N.E.), DARPA W911NF-17-2-0098 and NIH 5-R01-EB025256-04 (to J.T.), NIH 5RC2DK120535 (to J.J.C.) and MIT support (to N.E.).

Author information

Author notes

  1. These authors contributed equally: Fabio Caliendo, Elvira Vitu.

Authors and Affiliations

  1. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Fabio Caliendo, Elvira Vitu, Hayden Sandt, Casper Nørskov Enghuus, Jesse Tordoff, Neslly Estrada, James J. Collins & Ron Weiss

  2. Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA

    Fabio Caliendo, Elvira Vitu, Shuo-Hsiu Kuo, Hayden Sandt, Casper Nørskov Enghuus, Jesse Tordoff & Ron Weiss

  3. Bioinformatics Graduate Program, Boston University, Boston, MA, USA

    Junmin Wang

  4. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Shuo-Hsiu Kuo

  5. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA

    James J. Collins

  6. Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    James J. Collins

  7. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    James J. Collins

  8. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Ron Weiss

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Contributions

F.C., E.V. and R.W. conceptualized the study. F.C. and E.V. designed all experiments. F.C., E.V., S.K., H.S., C.N.E., J.T. and N.E. performed the experiments. J.W. developed the mathematical models. R.W. and F.C. analyzed the polytransfection data. R.W. and J.J.C. supervised the research and experimental design. F.C., J.W. and R.W. wrote the paper with input from all authors.

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Correspondence to Ron Weiss.

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Competing interests

The Massachusetts Institute of Technology has filed a patent application on behalf of the inventors (R.W., J.J.C., E.V., C.N.E. and J. Gam) of the gene sensor design described (US Patent App. 16/875,257, 2020). The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Impact of dCas9 on the expression of the input gene mKate in HEK293FT cells.

To investigate if expression of dCas9 alters expression of the input gene, we compared mKate expression in two scenarios: HEK293FT cells transfected with rtTa and TRE-mKate plasmids, and HEK293FT cells transfected with the circuit outlined in Fig. 1a which also includes dCas9-VPR, both in presence and absence of Doxycycline. In both scenarios EBFP2 was used as the transfection marker. In presence of doxycycline, we observed that expression of the downstream synthetic circuit ( + dCas9-VPR) did not alter expression of mkate when compared to cells transfected with only the plasmids necessary to express mKate (-dCas9-VPR). For scatter plots, dots represent the average geometric mean of two independent replicates, and error bars represent geometric mean values ± SD of three independent biological replicates.

Extended Data Fig. 2 Gene sensor module generates functional miRNAs.

a) Genetic circuit to validate miRNA production from a gene sensor module. A gene sensor module carrying two pri-miRNA-FF4 cassettes was inserted into a constitutively expressed transcriptional unit encoding fluorescent reporter EYFP (input protein) downstream of bGH-PAS. This construct was transfected into HEK293FT together with plasmids encoding output mKate. The 3’UTR of the transcriptional unit encoding mKate was engineered with four repeats of miRNA-FF4 target sequence. EBFP2 was used as transfection marker. (b) The pri-miRNA-FF4 within the gene sensor module inserted downstream of bGH-PAS did not impair upstream EYFP expression. miRNA-FF4 expressed from the gene sensor module regulated mKate expression. (c) Genetic circuit to validate that functional miRNAs are produced from a gene sensor module inserted downstream of an inducible gene. A gene sensor module carrying two pri-miRNA-FF4 cassettes was inserted downstream of bGH-PAS into a Doxycycline (Dox) inducible transcriptional unit encoding fluorescent reporter EYFP. The construct was transfected into HEK293FT together with plasmids encoding rtTa and output mKate. The 3’UTR of the transcriptional unit encoding for mKate output was engineered with four repeasts of a sequence targeted by miRNA-FF4. In the presence of Dox, EYFP mRNA and associated pri-miRNA-FF4 cassettes are co-transcribed. The pri-miRNA-FF4 cassettes are processed into mature miRNA-FF4, which in turn downregulates mKate expression. EBFP2 was used as transfection marker. (d) Insertion of pri-miRNA-FF4 cassettes within the gene sensor module downstream of bGH-PAS did not compromise the ability of rtTa to induce EYFP expression in presence of doxycycline. As above, miRNA-FF4 expressed from the gene sensor module regulated mKate expression. For scatter plots, dots represent the average geometric mean of two independent replicates, and error bars represent geometric mean values ± SD of two independent biological replicates. Circuit schematics created with Biorender.com.

Extended Data Fig. 3 Positional effects of the gene sensor module.

Gene sensor modules were inserted at different distances from the AATAA sequence of bGH PAS (bGA[+/−n]) and rb-Globin PAS (Glb[+/−n]). bGH[END] indicates that gRNA was inserted at the end of the PAS, and bGH[WT] and Glb[WT] are the wild-type sequences. HEK293FT cells were transfected as in Fig. 1e. mKate and EYFP fluorescence intensities were binned according to EBFP2 transfection marker. Data show geometric mean of mKate fluorescence input (a, c) and EYFP fluorescence output (b, d) for each EBFP2 bin. (a) We observed that inserting gene sensor modules in half of the locations within bGH-PAS did not reduce upstream gene expression (c) and insertion of gene sensor modules in rb-Glb PAS did not reduce upstream gene expression for the majority of the locations. EYFP output levels were lower when the gene sensor modules were inserted within the rb-Glb PAS in comparison to bGH PAS. For scatter plots, dots represent the average geometric mean of two independent replicates, and error bars represent geometric mean values ± SD of two independent biological replicates.

Extended Data Fig. 4 Effects of the distance between sgRNA cassettes and AATAAA on upstream gene expression and gene sensor performance.

(a) A small molecule inducible circuit to test sgRNAs produced from gene sensor modules inserted at distal sites downstream of the polyA signal AATAAA of endogenous gene Sox17. A gene sensor module carrying 3 sgRNA cassettes flanked by an upstream hammerhead ribozyme and downstream HDV ribozyme (both self-cleaving ribozymes used to release the gRNA from the RNA transcript) is inserted in different locations within the Sox17 PAS downstream of an abscisic acid (ABA) inducible transcriptional unit encoding fluorescent reporter EYFP. The constructs were co-transfected in HEK293FT together with plasmids encoding the two ABA-responsive transcription factor subunits (NLS-VPR-PYL1 and PhIF-NES-ABI)2, dCas9-VPR, mKate output and EBFP transfection marker. Administration of ABA dimerizes the two transcription factors and activates expression of EYFP from the PlhFO promoter along with downstream mRNA encoding the sgRNA cassettes. sgRNA complexes with dCas9-VPR to activate mKate expression. (b) Data showing EYFP output normalized to EBFP transfection marker indicates that the system is inducible by ABA and that upstream EYFP gene expression is not impaired by the insertion of sgRNA cassettes at various distances. Output mKate expression is also normalized to EBFP transfection marker. While ABA is able to induce mKate expression via expression of sgRNAs, the level of activation diminishes as distances from the AATAAA increase. Violin plots depicting the distribution of sample measurements. The horizontal line represent the median fluorescence intensity top whisker represent the 1.5 interquartile range [*IQR] from top hinge or highest observation, whichever is lower, and the bottom whisker represent the 1.5*IQR from bottom hinge or lowest observation, whichever is higher. Whisker points and median fluorescence intensities can be found at 10.5281/zenodo.12735076. Circuit schematics created with Biorender.com.

Extended Data Fig. 5 Presence of multiple sgRNA cassettes does not alter input gene expression.

Dox inducible TRE-mKate transcriptional unit is equipped with gene sensor modules carrying from 0 to 16 sgRNA cassettes. These constructs are co-transfected in HEK293FT cells together with rtTa, CasE, dCas9-VPR and EYFP (output) encoding plasmids. EBFP2 was used as transfection marker. Trend lines depict moving window averages. (a) Data showing mKate expression for various numbers of sgRNA cassettes in presence or absence of rtTa. (b) Data showing aggregated trend lines from (A) of different mKate/sgRNA constructs. Trendlines represent the mean fluorescence intensity of fluorescent proteins.

Extended Data Fig. 6 Impact of minimal promoters on output expression.

(a) Dox inducible circuit used to test the performance of four minimal promoters where dCas9-VPR/sgRNA drives expression of EYFP. A negative control circuit did not include sgRNA cassette. (b) Experimental data from a transfection experiment in HEK293 cells depicting EYFP output as a function of promoter comparing the circuit from (a) versus the negative control circuit that does not encode any sgRNA cassettes. Data represent EYFP geometric mean for a selected EBFP2 bin. YB_TATA shows the highest fold induction performance among the minimal promoters tested. For bar charts, dots represent individual values, and error bars represent median fluorescent intensity ± SD of two independent biological replicates. Circuit schematics created with Biorender.com.

Extended Data Fig. 7 Impact of Kozak Sequences and uORFs on output expression.

(a) Variants of the full gene sensor and reshaper module. A reshaper module encoding Gal4-VPR regulated by YB_TATA minimal promoter is equipped with different Kozak sequences and upstream open reading frames (uORFs). These constructs are co-transfected in HEK293FT cells together and CasE, dCas9-VPR and EYFP (output) encoding plasmids, and with or without rtTa coding plasmid. EBFP2 was used as transfection marker (b) Kozak 3 sequence reduces leaky expression by the reshaper. Data represent mKate geometric means for a selected EBFP2 bin in the absence or presence of rtTA. (c) EYFP fold change for gene sensor and reshaper circuit variants (equipped with YB_TATA and Kozak 3 sequence) with different sgRNA cassettes and uORFs. For (b) bar charts, dots represent individual values, and error bars represent median fluorescent intensity ± SD of three independent biological replicates. EYFP fold change is calculated as the ratio of the geometric mean of EYFP fluorescence intensity in the presence versus absence of rTta for a selected EBFP2 bin. Circuit schematics created with Biorender.com.

Extended Data Fig. 8 Effect of the reshaper module on the timing of output gene expression.

HEK293FT were transfected with a plasmid encoding TRE-mKate (input gene) fused with a gene sensor module comprising four sgRNA cassettes. Together with this plasmid, we transfected either plasmids encoding the genetic circuit described in Fig. 1b (No reshaper) or plasmids encoding the genetic circuit described in Extended Data Fig. 7a that includes a YB_TATA-1xuORF-K3-Gal4-VPR reshaper module (Reshaper). 48 h after transfection we treated the transfected cells with Dox and evaluated the level of EYFP output at different time points: two, four, six, nine, 12, and 18 hours. An initial small response can be observed by the ‘without reshaper’ circuit at 9 hours, and that both circuits exhibit a more pronounced response at 12 hours. Hence, as expected, the ‘with reshaper’ activation cascade circuit adds a small delay to the response of the system. For scatter plots, dots represent the average geometric mean of two independent replicates, and error bars represent geometric mean values ± SD of two independent biological replicates.

Extended Data Fig. 9 Impact of SynPAS integration in the endogenous RPS21 terminator.

(a) Representation of bGH-SynPAS integration in the terminator region of the RPS21 locus. (b) qPCR experiments demonstrated that SynPAS integration did not alter endogenous RPS21 expression levels. For bar charts, dots represent individual values, and error bars represent median fluorescent intensity ± SD of two independent biological replicates. The P value was calculated using the two-tailed student’s t-test with Welsh’s correction using bGH-HDV140 sample as control group. The 95% confidence interval for the difference in means was calculated to be −0.1868 to 0.002941. Circuit schematics created with Biorender.com.

Extended Data Fig. 10 Candidate UPR genes to monitor ER stress in CHO-K1 cells.

(a) qPCR-RT results showing activation of several UPR genes in response to Thapsigargin treatment. (b) Output level in engineered CHO-K1 cells carrying gene sensor modules within the BiP locus. (c) Output level in engineered CHO-K1 cells carrying a gene sensor module within the ATF4 locus. For (a) bar charts, dots represent individual values, and error bars represent ΔΔCt ± SD of three technical replicates. For (b) and (c) bar charts, dots represent individual values, and error bars represent median fluorescent intensity ± SD of three independent biological replicates.

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Caliendo, F., Vitu, E., Wang, J. et al. Customizable gene sensing and response without altering endogenous coding sequences. Nat Chem Biol (2024). https://doi.org/10.1038/s41589-024-01733-y

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