Precise tuning of gene expression output levels in mammalian cells

Context:

Introducing new genes and regulating their expression is not only a cornerstone of biology research, but is also an essential component of emerging cell- and gene-based therapies. Researchers, this reader included, typically insert transgenes under control of synthetic promoters that drive very high, although variable gene expression. When needed, Tet-based gene expression systems permit inducible expression or repression in response to doxycycline. However, no molecular biology tool offers the function of a volume knob to dial transgene expression levels at will in mammalian cells. Michaels et al reasoned that they could fulfill just such a function by integrating synthetic, user-designed target sites into any transgene, that would be targeted by the cell’s endogenous microRNAs.

Data:

To make a genetic module for digital control of gene expression, the authors start by using a well known microRNA, miR-17. They then construct a “dictionary” of miR-17 specific miRNA Response Elements (MREs) that bear increasing mismatches to the consensus target sequence. The authors first validate this dictionary in silico and then in cells expressing miR-17 endogenously, using a fluorescence reporter gene. Next, they confirm the system works with a transgene encoding the inhibitory immune receptor PD-1 in Jurkat T-cells (Figure 1). These initial results show that they can select the desired level of gene expression simply by inserting the proper MRE variant downstream of the PD-1 coding sequence. They call this approach microRNA silencing-mediated fine-tuners (miSFITs).

In the rest of the paper the authors set about testing functional applications of the miSFIT strategy. They put their idea to the test in a biological context where miSFIT identity dictates antigen expression in a growing tumor. For this, they generate B16-F10 tumor cell lines expressing different levels of a model antigen derived from Ovalbumin (Ova), using miSFIT elements to control Ova expression. Adaptive immunity drives tumor clearance of Ova-expressing, syngeneic tumor cells. As they reduce Ova expression, the authors observe a drop off in tumor cell killing by cytotoxic T cells in vitro, and reduced survival in tumor-bearing mice.

Implications:

Much research has focused on gene regulation through endogenous microRNAs, while experimentally increasing or decreasing the expression of transgenes has relied on synthetic promoters or codon optimization. The present work brings these together for the first time to this reader’s knowledge, in an elegant system with the ability to control gene expression across a wide dynamic range.

 

Beyond dissecting the sequence parameters of miRNA repression at single nucleotide resolution, the authors chose to explore the effects of incrementally decreasing gene expression using an immunogenic tumor model. This represents a pathological context of immense interest to biomedical research. The study of neoantigens – proteins expressed by tumor cells that bear altered amino acid sequences – has dominated tumor immunology¹. But far less attention has been paid to the cellular context of neoantigen expression, despite clear evidence that expression levels can determine immune responses^2,3. The authors put the miSFIT system to use toward a conceptually simple yet experimentally difficult problem, by tuning expression of Ova on otherwise identical clones of B16 cells.

Looking ahead, the miSFIT system merits close attention and development. With this tool in hand, different Ova-expressing clones of B16 cells could perhaps be mixed in defined ratios to assess heterogeneity of antigen expression. This reader also wonders if the results might not be different should a naturally occurring antigen be used, with miSFITs inserted in its endogenous 3’ UTR. Another possibility worth exploring is to reverse the strategy: would exogenously expressed miRNAs with varying affinities target endogenous genes with a linear relation as observed here? Even if the answer is no, integrating miSFITs into transgenes is an easy addition to cloning protocols. Thus, digital control over gene expression might be a regular feature of protocols and in publications before long.

References

1. Spranger, S. et al. Density of immunogenic antigens does not explain the presence or absence of the T-cell–inflamed tumor microenvironment in melanoma. Proc. Natl. Acad. Sci. 113, E7759–E7768 (2016).
2. Spiotto, M. T. et al. Increasing Tumor Antigen Expression Overcomes “Ignorance” to Solid Tumors via Crosspresentation by Bone Marrow-Derived Stromal Cells. Immunity 17, 737–747 (2002).
3. Kurts, C. et al. CD8 T cell ignorance or tolerance to islet antigens depends on antigen dose. Proc. Natl. Acad. Sci. 96, 12703–12707 (1999).

Tags: gene expression, genomics, immunology, mirna, pd-1

doi: https://doi.org/10.1242/prelights.4133

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