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Metabolic engineering generates a transgene-free safety switch for cell therapy

Nature Biotechnology volume 38, pages 1441–1450 (2020)Cite this article

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Abstract

Safeguard mechanisms can ameliorate the potential risks associated with cell therapies but currently rely on the introduction of transgenes. This limits their application owing to immunogenicity or transgene silencing. We aimed to create a control mechanism for human cells that is not mediated by a transgene. Using genome editing methods, we disrupt uridine monophosphate synthetase (UMPS) in the pyrimidine de novo synthesis pathway in cell lines, pluripotent cells and primary human T cells. We show that this makes proliferation dependent on external uridine and enables us to control cell growth by modulating the uridine supply, both in vitro and in vivo after transplantation in xenograft models. Additionally, disrupting this pathway creates resistance to 5-fluoroorotic acid, which enables positive selection of UMPS-knockout cells. We envision that this approach will add an additional level of safety to cell therapies and therefore enable the development of approaches with higher risks, especially those that are intended for limited treatment durations.

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Fig. 1: Disruption of UMPS in human cells through genome editing leads to auxotrophic cell growth.
Fig. 2: Biallelic gene targeting creates UMPS-knockout cell lines that are auxotrophic toward uridine and resistant to 5-FOA.
Fig. 3: Uridine auxotrophy and 5-FOA resistance of human T cells and human pluripotent stem cells with UMPS gene disruption.
Fig. 4: Auxotrophy assessment in vivo.

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Data availability

All data generated or analyzed during this study are included in this published article and its extended data. Source data are provided with this paper.

Code availability

The custom script used to analyze next-generation sequencing data indelQuantificationFromFastqPaired-1.0.1.pl can be found at https://github.com/piyuranjan/NucleaseIndelActivityScript/blob/master/indelQuantificationFromFastqPaired-1.0.1.pl.

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Acknowledgements

We thank the Stanford Small Animal Imaging Facility and the FACS Core of the Institute for Stem Cell Biology and Regenerative Medicine at Stanford University for providing access to equipment and training. We thank the Stanford Medicine Veterinary Service Center for excellent animal welfare and husbandry. We thank L. Nguyen (Stanford University) for excellent laboratory management and administration. We thank Synthego for providing modified sgRNAs and IDT for providing early access to high-fidelity Cas9 protein. V.W. gratefully acknowledges receiving research fellowships from the Deutsche Forschungsgemeinschaft (DFG) and the Care-For-Rare Foundation, Germany. We thank the Amon G. Carter Foundation and the Laurie Kraus Lacob Faculty Scholar Award in Pediatric Translational Research for support of this work.

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  1. Ciaran M. Lee

    Present address: APC Microbiome Institute, University College Cork, Cork, Ireland

Authors and Affiliations

  1. Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA

    Volker Wiebking, Renata Martin, Monica K. Chanda, Waracharee Srifa & Matthew H. Porteus

  2. Auxolytic Ltd, London, UK

    James O. Patterson

  3. Department of Bioengineering, Rice University, Houston, TX, USA

    Ciaran M. Lee & Gang Bao

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Contributions

Conceptualization: V.W., J.O.P. and M.H.P.; methodology: V.W., C.M.L. and M.H.P.; validation: V.W. and C.M.L.; formal analysis: V.W.; investigation: V.W., R.M., M.K.C. and C.M.L.; resources: V.W., W.S., M.K.C., C.M.L., G.B. and M.H.P.; writing–original draft: V.W.; writing–review and editing: V.W. and M.H.P.; visualization: V.W.; supervision: G.B. and M.H.P.; project administration: V.W. and M.H.P.; funding acquisition: V.W. and M.H.P.

Corresponding author

Correspondence to Matthew H. Porteus.

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Competing interests

The authors declare the following competing interests: V.W., J.O.P. and M.H.P. are inventors on intellectual property related to this work. V.W., M.H.P. and J.O.P. own shares of and J.O.P. is the director of Auxolytic Ltd, a company that owns intellectual property related to this work. J.O.P. declares that he is bound by confidentiality agreements that prevent him from disclosing additional competing interests in this work.

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Extended data

Extended Data Fig. 1 Predicted specificity for sgRNAs in UMPS exon 1.

a, sgRNAs in the target region of the UMPS gene are shown with their attributed symbol, the genomic target sequence and the specificity score. sgRNAs are ranked by their predicted specificity. b, Numbers of predicted off-target sites as evaluated by COSMID are shown in a stacked bar graph. Grey shades encode the COSMID score as annotated in the legend. Sites with lower scores are predicted to be more relevant (higher chance of endonuclease activity). Y-axis is broken to better illustrate results for sgRNAs with <10 predicted off-target sites.

Extended Data Fig. 2 Proliferation of bulk edited T cell populations and the InDel spectrum after gene editing.

a, Proliferation of bulk T cell populations either mock treated or edited at the CCR5 or UMPS loci and cultured without supplementation of UMP or uridine. Graphs show viable cell counts as measured by trypan blue exclusion. b, Proliferation of a bulk T cell population after electroporation of an RNP targeting UMPS cultured either with high concentrations of uridine or UMP, or without nutrient supplementation. Data points in a, b represent means of 3 biological replicates. Data is from the same experiment shown in Fig. 1f. For statistical analysis on day 5 see Fig. 1f. c, InDel spectrum on day 5 after electroporation of T cells with RNP targeting UMPS, for samples cultured either with or without nutrients as indicated.

Extended Data Fig. 3 Gene targeting approaches to create UMPSKO/KO cells and to knock-in Luciferase-GFP into a safe-harbor locus.

a, Gene targeting approach used to create UMPS-/- Nalm6 cells and UMPS-/- T cells. Dual-allelic gene targeting using constructs carrying tNGFR and tEGFR allow for the purification of the dual-positive population by either fluorescence-activated or magnetic beads-activated cell sorting (FACS or MACS). b, Representative FACS plots of Nalm6 cells that have undergone dual-allelic gene targeting at the UMPS locus and after sorting of the NGFR+/EGFR+ population. Controls are shown that were only mock electroporated or AAV transduced without RNP electroporation. Data from a single experiment. c, Approach used to create cells expressing Luciferase and GFP from a safe harbor. The depicted donor construct was used to target the HBB gene locus considered a safe harbor in non-erythropoietic cells. d, FACS analysis of K562 cells targeted with the approach in c and the relevant controls, before and after sorting of GFP+ cells. The procedure was performed once.

Extended Data Fig. 4 Enrichment of UMPS knockout T cells through 5-FOA.

a, Outline of the experiment used to simulate a mixed population of T cells with intact UMPS or bi-allelic UMPS knockout. Pure cell populations with the respective genotypes were stained with different tracking dyes (eFluor670 or CFSE), mixed and cultured in the presence or absence of 5-FOA during continuous T cell stimulation. b, Representative FACS plots (out of the 3 experiments) showing the mixed T cell populations before and 3 days after culture with 5-FOA. The relative percentages of the populations and the genotype of the cell populations identified by the dyes are annotated. c, Representative plots used for gating of viable T cells (plots 1 and 2) upstream of identification using the tracking dyes (plot 3) are shown. PI, propidium iodide. KO, knockout. WT, wild-type.

Extended Data Fig. 5 Dual-sgRNA editing of UMPS to increase full gene knockout in T cells and analysis strategy for in vivo samples.

a, Illustration of the genomic region with UMPS exon 1. The sgRNA binding sites in exon 1 are indicated, with dashed lines illustrating the cleavage sites. The cut sites of the two sgRNAs UMPS-1 and UMPS-7 are 89 bp apart in order to create a frameshift deletion, as UMPS is an enzyme consisting of 2 separate enzymatic functions and InDels in exon 1 that keep the open reading frame intact will not disrupt the function of ODC, which is encoded by the downstream part of the gene. b, InDel frequencies in human T cells electroporated with RNPs using sgRNA UMPS-7 (blue) or both UMPS-7 and UMPS-1 (red). The graph and error bars represent means and standard deviations. Statistical significance by comparison using two-sided t tests is annotated. Data from n = 4 (UMPS-7) and n = 3 (UMPS-7 + UMPS-1) biological replicates. c, InDel spectrum of T cells edited with one or two RNPs. The relatively low frequency of frameshift-mutations using only 1 sgRNA is due to the high frequency of 6 bp deletions. The increase in frameshift InDels is explained primarily by the high frequency of deletions of the 89-bp fragment between the two cut sites. Shown is 1 representative sample per condition. d, Gating strategy used to detect and quantify human T cells in mouse peripheral blood. Plot 1 shows gating of beads to be used as counting reference. Plot 2 shows all events excluding beads and gates on cells without debris. Plot 3 excludes dead cells. Plot 4 excludes events not expressing CD45. Plots 5 and 6 show the same population (CD45+ viable cells) with different axes combinations. huCD45, human CD45. mCD45, murine CD45. huTCR, human T cell receptor.

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Wiebking, V., Patterson, J.O., Martin, R. et al. Metabolic engineering generates a transgene-free safety switch for cell therapy. Nat Biotechnol 38, 1441–1450 (2020). https://doi.org/10.1038/s41587-020-0580-6

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