Evaluation and validation of reference genes for RT-qPCR gene expression in Naegleria gruberi

Abstract

Naegleria gruberi is a free-living amoeboflagellate commonly found in freshwater and in soils around the world. It is a non-pathogenic relative of Naegleria fowleri, which is the etiologic agent of Primary Amoebic Meningoencephalitis (PAM). PAM occurs world-wide and it is considered a rare disease, but its fatality rate is high (96%) mainly because of delay in initiation of treatment due to misdiagnosis and lack of a specific treatment. The analysis of gene expression by quantitative real-time PCR in N. gruberi could be a highly efficient means to understand the pathogenicity of N. fowleri and also to find drug targets. Accurate RT-qPCR analysis requires correct normalization of gene expression data using reference genes (RG), whose expression should be constant under different experimental conditions. In this study, six genes, representing the most frequently used housekeeping genes, were selected for evaluation as reference genes in N. gruberi. The expression and stability of these genes was evaluated employing four algorithms (geNorm, NormFinder, BestKeeper and RefFinder). This work shows significant variations of the stability of RGs depending on the algorithms employed and on the experimental conditions (i.e. logarithmic, stationary, heat-shock and oxidative stress). The geNorm, NormFinder and RefFinder analysis of all the experimental conditions in combination revealed that ACT and G6PD were the most stable RGs. While BestKeeper analysis showed that 18S and TBP were the most stable RGs. Moreover, normalization of HSP90 gene expression with the most stable RGs resulted in an upregulation whereas when the normalization was done with the unstable RGs, the gene expression was not reliable. Hence, the implications of this study are relevant to gene expression studies in N. gruberi.

Figure 1

Box plot of mean Cq values after efficiency correction (CqE) of the RGs from two experimental conditions. (a) Different growth stage (LOG and STAT). (b) Stressful conditions (HS and OS). The average (horizontal line), upper and lower quartiles (box), and maximum and minimum values (whisker) of each RG are shown.

Figure 2

Expression stability of RGs for the normalization of all conditions in N. gruberi cells calculated by different algorithms. (a) geNorm expression stability M. (b) NormFinder stability values, the line indicates the NormFinder cut-off value of 0.15. (c) BestKeeper coefficient of correlation. (d) RefFinder geomean of ranking values.

Figure 3

Pairwise variation calculated by geNorm software for N. gruberi cultured at different conditions. Vn/Vn + 1 values were used to determine the optimal number of RGs (with threshold value: 0.15). AC: all conditions combined. GP: growth phases: LOG + STAT. SC: stress conditions: HS + OS. LOG: logarithmic phase. STAT: stationary phase. HS: heat shock. OS: oxidative stress.

Figure 4

Relative expression of HSP90 of N. gruberi after 1 h heat-shock was compared with the relative expression of HSP90 of N. gruberi control. Normalization with the two most and the least stable RGs. (a) Based on results of the analysis of all conditions combined (AC) normalized with the two most stable RGs (ACT/G6PD). (b) Based on the analysis of stress conditions (SC) normalized with the two most stable RGs (18S/ACT, G6PD/GAPDH or ACT/G6PD). (c) Based on the analysis of heat-shock conditions (HS) normalized with the two most stable RGs (G6PD/TBP). p-values are marked with asterisks (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).