Flow cytometry of v-Abl transformed pre-B cells heterogeneous in ectopic expression levels reveals Ras dose-response

Optimization of oncogene expression through intra-population competition

Although functional roles have been assigned to many genes, e.g. those involved in cell-cycle regulation, growth signaling, or cancer, considerably less is known about the quantitative relationship between gene expression levels and outcome. We devised an intra-population competition to study oncogene dosage. Cell populations were engineered to express a range of H-Ras oncogene levels. Cells with different levels of H-Ras then "competed" for an increased share of the total cell population. Using flow cytometry to track the population composition over time, we determined the relationship between the different H-Ras oncogene expression levels and the net proliferation rate. Under culture conditions in which wild-type Ras activation was suppressed, we found that increased and maximal net proliferation occurred when the H-Ras G12V oncogene was expressed at a level 1.2-fold that of wild-type Ras. As the H-Ras G12V expression levels increased above this optimal level, proliferation rates decreased. Our findings suggest that the tumor evolution process may optimize gene expression levels for maximal cell proliferation. In principle, engineered intra-population competitions can be used to determine proliferation rates associated with the level of any ectopically expressed gene. The approach also may be used to determine proliferation rates associated with different cell species in a heterogeneous population or to improve the proliferation rate of a cell line. We also envision that the tracking of intra-population competitions could be utilized to investigate the evolution of tumors in the body.

Tuning gene expression with synthetic upstream open reading frames

We engineered short ORFs and used them to control the expression level of recombinant proteins. These short ORFs, encoding a two-amino acid peptide, were placed upstream of an ORF encoding a protein of interest. Insertion of these upstream ORFs (uORFs) resulted in suppression of protein expression. By varying the base sequence preceding the uORF, we sought to vary the translation initiation rate of the uORF and subsequently control the degree of this suppression. Using this strategy, we generated a library of RNA sequence elements that can specify protein expression over a broad range of levels. By also using multiple uORFs in series and non-AUG start codons, we were able to generate particularly low expression levels, allowing us to achieve expression levels spanning three orders of magnitude. Modeling supported a mechanism where uORFs shunt the flow of ribosomes away from the downstream protein-coding ORF. With a lower translation initiation rate at the uORF, more ribosomes "leak" past the uORF; consequently, more ribosomes are able to reach and translate the downstream ORF. We report expression control by engineering uORFs and translation initiation to be robust, predictable, and reproducible across all cell types tested. We propose control of translation initiation as a primary method of choice for tuning expression in mammalian systems.