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.

XRCC4 and MRE11 Roles and Transcriptional Response to Repair of TALEN-Induced Double-Strand DNA Breaks.

Double-strand breaks (DSB) are one of the most lethal forms of DNA damage that, if left unrepaired, can lead to genomic instability, cellular transformation, and cell death. In this work, we examined how repair of transcription activator-like effector nuclease (TALEN)-induced DNA damage was altered when knocking out, or inhibiting a function of, two DNA repair proteins, XRCC4 and MRE11, respectively. We developed a fluorescent reporter assay that uses TALENs to introduce DSB and detected repair by the presence of GFP fluorescence. We observed repair of TALEN-induced breaks in the XRCC4 knockout cells treated with mirin (a pharmacological inhibitor of MRE11 exonuclease activity), albeit with ~40% reduced efficiency compared to normal cells. Editing in the absence of XRCC4 or MRE11 exonuclease was robust, with little difference between the indel profiles amongst any of the groups. Reviewing the transcriptional profiles of the mirin-treated XRCC4 knockout cells showed 307 uniquely differentially expressed genes, a number far greater than for either of the other cell lines (the HeLa XRCC4 knockout sample had 83 genes, and the mirin-treated HeLa cells had 30 genes uniquely differentially expressed). Pathways unique to the XRCC4 knockout+mirin group included differential expression of p53 downstream pathways, and metabolic pathways indicating cell adaptation for energy regulation and stress response. In conclusion, our study showed that TALEN-induced DSBs are repaired, even when a key DSB repair protein or protein function is not operational, without a change in indel profiles. However, transcriptional profiles indicate the induction of unique cellular responses dependent upon the DNA repair protein(s) hampered.

The Data Error Criteria (DEC) for retrospective studies: development and preliminary application.

Retrospective chart review (RCR) studies rely on the collection and analysis of documented clinical data, a process that can be prone to errors. The aim of this study was to develop a defined set of criteria to evaluate RCR datasets for potential data errors. The Data Error Criteria (DEC) were developed by identifying data coding and data entry errors via literature review and then classifying them based on error types. Three components comprise the DEC: general errors, numerical-specific errors, and categorical variable-specific errors. Two reviewers independently applied these criteria via a manual review process to an existing de-identified database. A total of 10,168 errors were identified out of a total of 28,656 data points. The total number of errors included redundancies as certain errors may be included in multiple categories. These included 2515 general errors, 39 numerical-specific errors, and 7614 categorical variable-specific errors. Input-related categorical variable-specific errors occurred most frequently, followed by errors secondary to blank cells. Inter-rater agreement was near perfect for all categories. Identifying errors outlined in the DEC can be crucial for the data analysis stage as they can lead to inaccurate calculations and delay study timelines. The DEC offers a framework to evaluate datasets while reducing time and efforts needed to create high-quality RCR-related databases.

Evaluating Long-Term Outcomes of a High School-Based Impaired and Distracted Driving Prevention Program.

Motor vehicle crashes are one of the leading causes of death among teenagers. Many of these deaths are due to preventable causes, including impaired and distracted driving. You Drink, You Drive, You Lose (YDYDYL) is a prevention program to educate high school students about the consequences of impaired and distracted driving. YDYDYL was conducted at a public high school in Southern Nevada in March 2020. A secondary data analysis was conducted to compare knowledge and attitudes of previous participants with first-time participants. Independent-samples-t test and χ2 test/Fisher's exact test with post-contingency analysis were used to compare pre-event responses between students who had attended the program one year prior and students who had not. Significance was set at p < 0.05. A total of 349 students participated in the survey and were included for analysis; 177 had attended the program previously (50.7%) and 172 had not (49.3%). The mean age of previous participants and first-time participants was 16.2 (SD ± 1.06 years) and 14.9 (SD ± 0.92 years), respectively. Statistically significant differences in several self-reported baseline behaviors and attitudinal responses were found between the two groups; for example, 47.4% of previous participants compared to 29.4% of first-time participants disagreed that reading text messages only at a stop light was acceptable. Students were also asked how likely they were to intervene if a friend or family member was practicing unsafe driving behaviors; responses were similar between the two groups. The baseline behaviors and attitudes of participants regarding impaired and distracted driving were more protective among previous participants compared to first-time participants, suggesting the program results in long-term positive changes in behaviors and attitudes. The results of this secondary retrospective study may be useful for informing the implementation of future impaired and distracted driving prevention programs.

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.