Measurements

Introduction

The method used to obtain the results and the approach to data analysis are key components of any experiment. The choice of a specific technique and an objective interpretation of the results allow for outcomes that most accurately reflect the real behavior of biological molecules.

Selection of cell lines – analysis of alpha-fetoprotein (AFP) expression

A crucial step in designing our experiment was the evaluation of AFP transcription in different cell lines. We selected HepG2 cells as the positive control (target hepatocellular carcinoma cells expressing AFP). The negative control for our experiment was chosen based on RT-qPCR analysis results for four cell lines: A549, HEK, HeLa, and Wi-38.

Based on these results, we selected the HEK cell line due to its ease of cultivation and its frequent use by other iGEM teams. Moreover, through RT-qPCR analysis, we confirmed the presence of AFP transcripts in the HepG2 cell line.

Flow cytometry analysis

The first step in analyzing the flow cytometry data was to distinguish actual cells from debris and cell aggregates. This was achieved by gating based on cell size (FSC-A) versus granularity (SSC-A), following the methodology described in publication [1] (Figures 2a and 2b). The next gating step was performed to isolate single cells only (Figures 3a and 3b). Using the negative control, we determined the level of autofluorescence for each cell type and defined a gate for GFP-expressing cells accordingly (Figures 4a and 4b).

For the gated cell populations, we compared cell density distributions across different toeholds to preliminarily assess the percentage of fluorescent (GFP-positive) cells and the fluorescence intensity. Subsequently, for all single-cell–gated samples, we determined the median fluorescence intensity, which—unlike the mean—is less sensitive to outliers.

Evaluation of Toehold functionality

The experiment was conducted as described in the Experiments section. Each Toehold was tested in two cell lines (HepG2 and HEK) with three replicates per line. For each replicate, a positive control (transfection with a plasmid expressing GFP under a strong promoter) and two negative controls (transfection with water and untransfected cells) were included. The use of two negative controls allowed us to verify whether the transfection process using lipofectamine—which can induce cellular stress—had any effect on cell autofluorescence.

Statistical Analysis

The final statistical analysis of the experimental results is just as crucial for the reliability of the study as the experiment itself. By selecting appropriate statistical tests for a given dataset, it is possible to obtain results that accurately reflect the true state of the system. The final assessment of statistical significance allows us to determine whether the difference between two analyzed variables is meaningful and reliable.

In our experiment to ensure the true proper handling of the data acquired, we had to ensure the comparability between experiment, and so we had to preprocess the data accordingly. As we were working with 2 different cell lines, which vary in both base fluorescence parameters and transfection effectiveness, we subtracted from the results the mean autofluorescence, according to the cell line from which these were obtained. Then using the positive control, which expression of the reporter gene was not obstructed by the toehold hairpin, we calculated the possible maximal fluorescence rate that a cell could emit. Knowing the difference of maximal expression rates of GFP, we calculated the transfection efficiency, and consistent with our intuition, the transfection for the HEK cells was significantly higher then for HepG2. Using these measurements, we scaled the fluorescence of the cells, and performed a statistical analysis on the results, which may be interpreted as percentage of maximal expression level of the reporter, which these results directly tell us how efficient the toehold is at obstructing the expression. On such data we have performed Student’s t-test, to ensure that the results are significant.

Literature

1. Cossarizza A, Chang HD, Radbruch A, et al. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition). Eur J Immunol. 2021;51(12):2708-3145. doi:10.1002/eji.202170126