GigaAssay - An adaptable high-throughput saturation mutagenesis assay platform.

High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the "GigaAssay", a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.

RNAi screen for telomerase reverse transcriptase transcriptional regulators identifies HIF1alpha as critical for telomerase function in murine embryonic stem cells.

In various types of stem cells, including embryonic stem (ES) cells and hematopoietic stem cells, telomerase functions to ensure long-term self-renewal capacity via maintenance of telomere reserve. Expression of the catalytic component of telomerase, telomerase reverse transcriptase (Tert), which is essential for telomerase activity, is limiting in many types of cells and therefore plays an important role in establishing telomerase activity levels. However, the mechanisms regulating expression of Tert in cells, including stem cells, are presently poorly understood. In the present study, we sought to identify genes involved in the regulation of Tert expression in stem cells by performing a screen in murine ES (mES) cells using a shRNA expression library targeting murine transcriptional regulators. Of 18 candidate transcriptional regulators of Tert expression identified in this screen, only one candidate, hypoxia inducible factor 1 alpha (Hif1alpha), did not have a significant effect on mES cell morphology, survival, or growth rate. Direct shRNA-mediated knockdown of Hif1alpha expression confirmed that suppression of Hif1alpha levels was accompanied by a reduction in both Tert mRNA and telomerase activity levels. Furthermore, gradual telomere attrition was observed during extensive proliferation of Hif1alpha-targeted mES cells. Switching Hif1alpha-targeted mES cells to a hypoxic environment largely restored Hif1alpha levels, as well as Tert expression, telomerase activity levels, and telomere length. Together, these findings suggest a direct effect of Hif1alpha on telomerase regulation in mES cells, and imply that Hif1alpha may have a physiologically relevant role in maintenance of functional levels of telomerase in stem cells.

Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay.

The data in this article are associated with the research paper "GigaAssay - an adaptable high-throughput saturation mutagenesis assay" [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the "GigaAssay". A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.