Selection of the candidate reference genes and their amplification efficiencies.
Ten genes were identified as potential reference genes from Clostridium species based on their previous use in this or other bacterial species. DNA sequences for eight candidatereference genes previously evaluated for C. difficile (adk, gyrA, rho, rpsJ, tpiA, gluD (gdhA in C. perfringens), rpoA, rrs)10 were acquired from NCBI for four Clostridium perfringens strains (ATCC 13124, strain 13, EHE-NE18, and SM101) and aligned in MegAlignPro in order to identify highly (100%) conserved areas suitable for primer design. Two additional genes (ftsZ and recA) were chosen as they have been previously validated as suitable reference genes for other bacteria21. Species-specific primers for these targets were designed using Primer322,23 (Table 1). Primers sets for rpoA and rrs were used as previously described as they had not been previously validated7,24,25.
Primer melting temperatures (Tm) are listed in Table 2 and corresponded to predicted Tms. Amplification specificity was confirmed for all primer pairs by visualizing single PCR amplicons of the correct size on agarose gel electrophoresis (Supplementary Fig. S1). Additionally, single peaks were observed for all 10 primer sets from dissociation curve analysis (Supplementary Fig. S2) indicating to absence of primer-dimers and non-specific amplification products.
Amplicons for each of the ten candidate reference genes were cloned into a cloning vector in order to generate standard curves for the calculation of amplification efficiencies. Amplification efficiencies for these genes ranged from 1.72 (gdhA) to 1.86 (rpsJ) with regression coefficients (R2) of 0.99 (Table 2).
Establishment of experimental conditions.
We chose to evaluate three varied growth conditions to simulate potential environments the bacterial cells could encounter during pathogenesis. The first condition (referred to as ‘incubation period’) assessed expression of the candidate reference genes after 4 hours and 9 hours of growth. These time points were chosen to approximate log phase and stationary phase growth; however, due to logistical constraints, real-time bacterial densities could not be monitored during the trial. For this trial, the density of bacterial growth equaled an OD600 of 0.15, 0.3, and 0.78 respectively for CP-1, CP-2, and CP-4 for the 4-hour time point and an OD600 of 1.2, 1.3, and 1.4 respectively for CP-1, CP-2, and CP-4 for the 9-hour time point.
In the second trial, two additional conditions were assessed. One condition (referred to as ‘oxygen shock’) evaluated expression of the candidate reference genes after a 30-minute exposure to an aerobic environment following 4 hours of growth under normal anaerobic conditions. No measurements of oxygen status were recorded. The other condition (referred to as ‘heat shock’) evaluated expression of the candidate reference genes after a 30-minute exposure to 50°C following 4 hours of growth under normal 37°C growth.
Expression stability of candidate reference genes
The stability of transcription levels of the candidate reference genes under different stress conditions was initially evaluated by geNorm13 within the qbase+ software package, version 3.2 (Biogazelle, Zwijnaarde, Belgium - www.qbaseplus.com). These results were then compared to analyses by additional algorithms─ BestKeeper15, comparative delta Ct26, normFinder14, and RefFinder16.
A geNorm pilot experiment utilizing all 10 candidate reference genes produced M-values ranging from 0.69 (gyrA) to 2.0 (gdhA) when assessing stability only for the incubation period experimental condition (Fig. 1). Genes with medium stability, defined as having average geNorm M-values between 0.5 and 1.0, are often seen when heterogeneous sets of samples, such as our bacterial cultures, are evaluated27. Four genes fall into the category of medium stability when evaluating the incubation period condition (simulating log and stationary phase) - ftsZ, gyrA, recA, and rpoA or heat shock condition- ftsZ, gyrA, rpoA, and rpsJ (Fig. 1). Under our conditions, oxygen shock had the least influence on transcript levels of the candidate reference genes. Six out of the 10 candidate genes were considered stable after being subjected to oxygen shock with ftsZ, gyrA. recA, rho, rpsJ, and rpoA having M-values less than 1.0; gyrA, recA, and rho had M-values less than 0.5. Mean Cq values for an isolate and cycle variation, as indicated by standard deviation of the mean Cq values, across all conditions for a respective isolate are shown in Table 3. Average Cq values for any given gene would often differ by up to 10 Cq values between isolates for different growth/stress parameters indicating sample heterogeneity. The greatest variation is observed from all genes during comparisons during the incubation period trial (standard deviations range from 0.33 for CP-1 rrs to 6.47 for CP-2 rpsJ). The genes gyrA and recA showed the least variation in cycle number (standard deviation less than 1.0) for each isolate when assessing transcript levels during the oxygen shock and heat shock trials.
To compare the stability ranking determined by qbase+ software to other algorithms, Cq data was submitted to the online tool RefFinder (as found at www.heartcure.com.au/reffinder/). RefFinder16 is a comprehensive tool that integrates the output of other computational algorithms by assigning weight to each candidate genes then calculating a final ranking based on the geometric mean of the weighting value for each gene. In this process, the tool provides the output for each of the additional computational programs. Comparisons of the expression stability ranking calculated by RefFinder for geNorm, BestKeeper, NormFinder, and the delta Ct method, as well as the comprehensive RefFinder ranking are shown in Table 4. For most of the algorithms and conditions, the genes ftsZ, recA, and gyrA were consistently within the top four ranks. The BestKeeper15 computational algorithm showed the most different ranking of the 10 genes under the incubation period condition compared to the other analysis platforms with rrs, rho, and gdhA identified as the three most stable genes. Two of these genes (rrs and gdhA) were identified among the least stable genes by the other platforms. RefFinder comprehensive rankings identified ftsZ, recA, and gyrA consistently within the top four ranks when comparing any of the conditions (incubation period, oxygen shock or heat shock, all conditions together) with geometric means of rank values between 1.41 and 3.71 depending on the growth/stress condition being evaluated. Under two conditions (incubation period and all conditions together), RefFinder identified rho as the third most stable gene with a geometric mean of the rank value at 3.36 and 2.51, respectively. Under these same conditions, rpoA was not determined to be within the top four most stable genes (rank 9 for incubation period and rank 5 for all conditions together).
Expression profile over time of the alpha toxin gene (plc)
It has long been recognized that alpha toxin production occurs during active cellular growth17,28–30, so evaluating the expression of plc at various time points during growth should allow us to evaluate the reliability of our selected reference genes for use in normalization of transcript levels. The incubation time points we evaluated were 2.5 hours and 4 hours for simulating early- and mid-log phase, and 6 hours and 22 hours for simulating early- and late-stationary phase. Because of the variability in growth rates between our three C. perfringens isolates, it was difficult to achieve the desired growth phase targets (early-log, mid-log, early-stationary) for all three strains when cells were harvested at our experimental time points. The actual OD600 of the cultures used for RNA harvest are shown in Supplementary Table S1. Expression of the plc gene relative to expression of this gene after 22 hours of growth was assessed following normalization with our previously determined set of reference genes (ftsZ, recA, and gyrA), with these genes individually, with one of the least stable but reliably amplified genes (tpiA), and with rrs as a historically used reference gene (Fig. 2). Our set of reference genes and the same genes individually as reference genes produced similar fold changes in plc expression; however, using the set of reference genes more often produced more consistent results indicated by shorter error bars. When a Student’s t-test was used to assess statistical significance (p≤ 0.05) of the changes in expression at 4 hours in relation to the 22-hour time point, a maximal and significant upregulation of plc transcription was observed when employing ftsZ, gyrA, and recA either as a set or individually. Although the transcript levels decreased by 6 hours, the level of plc expression was still significantly upregulated when normalizing with the reference set genes or ftsZ and gyrA individually, but not recA individually.
When tpiA, one of the less stably expressed candidate reference genes, was used for normalization; the same pattern of expression was observed but to a greatly depressed level. Expression of plc at the 4-hour time point was maximal with 9 times less transcript observed when tpiA was used for normalization as compared to the same expression when normalization was performed using the set of three reference genes (~6-fold increase vs 54-fold increase, respectively). None of the change in plc expression were found to be significant when tpiA was used in the normalization process.
When plc expression was normalized with rrs, the apparent relative expression of plc decreased over time instead of increasing during active growth. As such, normalization with the 16S RNA gene produced a different expression profile for plc than was observed when using our reference set genes (either as a set or individually). Significant upregulation of plc at the 2.5-hour time point was only noted when rrs was utilized for normalization.