A simplified transposon mutagenesis method to perform phenotypic forward genetic screens in cultured cells

Abstract

Background: The introduction of genome-wide shRNA and CRISPR libraries has facilitated cell-based screens to identify loss-of-function mutations associated with a phenotype of interest. Approaches to perform analogous gain-of-function screens are less common, although some reports have utilized arrayed viral expression libraries or the CRISPR activation system. However, a variety of technical and logistical challenges make these approaches difficult for many labs to execute. In addition, genome-wide shRNA or CRISPR libraries typically contain of hundreds of thousands of individual engineered elements, and the associated complexity creates issues with replication and reproducibility for these methods.

Results: Here we describe a simple, reproducible approach using the SB transposon system to perform phenotypic cell-based genetic screens. This approach employs only three plasmids to perform unbiased, whole-genome transposon mutagenesis. We also describe a ligation-mediated PCR method that can be used in conjunction with the included software tools to map raw sequence data, identify candidate genes associated with phenotypes of interest, and predict the impact of recurrent transposon insertions on candidate gene function. Finally, we demonstrate the high reproducibility of our approach by having three individuals perform independent replicates of a mutagenesis screen to identify drivers of vemurafenib resistance in cultured melanoma cells.

Conclusions: Collectively, our work establishes a facile, adaptable method that can be performed by labs of any size to perform robust, genome-wide screens to identify genes that influence phenotypes of interest.

Fig. 1

Overview of cell-based Sleeping Beauty (SB) mutagenesis screens. (1) Cells are engineered to express the SB100X transposase. This is done using a piggyBac transposon expression system using the hyPBase transposase to stably deliver the SB100X transgene. (2) Once SB100X-expressing cells are selected, cells are transfected with the T2-Onc3 plasmid, or similar mutagenic SB transposon vector, and cells with the desired phenotype are selected from among the population of mutagenized cells. (3) Genomic DNA is collected from each population of selected and control cells, and each DNA sample is subjected to a ligation-mediated PCR approach to isolate the transposon-genome junctions. Individual LM-PCR libraries are then multiplexed and sequenced on the Illumina platform. (4) Raw sequences are trimmed, mapped to the reference genome, and filtered based on user-defined criteria. (5) Finally, filtered sequences are combined and analyzed to identify candidate genes enriched for transposon insertions in selected but not control cells

Fig. 2

Transposon mutagenesis drives vemurafenib resistance in A375 cells. Cells were engineered as described in Fig. 1. Twenty-four hours after mutagenesis was initiated, 10 cm plates were seeded with mutagenized or control cells. After allowing cells to attach, 5 μM vemurafenib was added to the culture medium. Culture media and drug were replaced twice weekly until colonies emerged on the plates containing mutagenized cells. Colonies were stained with Coomassie Blue. Representative plates are shown

Fig. 3

Comparison of transposon insertion sites in a series of vemurafenib-resistant A375 colonies. Eight distinct vemurafenib-resistant colonies were isolated from three independent populations of SB-mutagenized A375 cells. Each colony was expanded and transposon insertion sites were identified (see Fig. 1). Between 10 and 135 insertion events were present in each expanded colony. In general, transposon insertion sites were distributed across the genome, suggesting that transposon mutagenesis is capable of performing genome-wide screens

Fig. 4

Predicting the functional impact of transposon insertion on individual candidate genes. The gCIS2 pipeline employs an algorithm for each gene that has ≥5 independent insertions to predict the impact of transposon insertion on the gene (i.e. over-expression or gene disruption). a The gCIS2 pipeline also determines the skewness and kurtosis values for the distribution of transposon insertions across the gene. These values can be evaluated by the user to further distinguish between different mechanisms of over-expression (i.e. full-length vs. 5’truncation). b Actual skewness and kurtosis values are shown for the candidate drivers of vemurafenib resistance identified in A375 cells. [dashed lines indicate the 1–99% intervals for skewness and kurtosis obtained from the analysis of 20 independent simulated data sets (see Methods)]

Fig. 5

High degree of replication in cell-based SB mutagenesis screens. The vemurafenib resistance screen was replicated by three different individuals spanning a period of several months. The gCIS2 results were obtained for each independent replicate and compared to the results obtained by analyzing the combined data set. Of the nine vemurafenib resistance driver genes identified by analyzing the entire data set, six were identified by analyzing each replicate independently while the remaining three genes (indicated with asterisks) were identified in two of the three replicates