The application of qPCR in the evaluation of TNT bioremediation

The effect of bioaugmentation, biostimulation, rhizoremediation and their combinations on TNT removal and on the microbial community involved was assessed in a 28-day laboratory pot experiment. QPCR was used to estimate the abundance of the total bacterial community as well as two functionally important phylogenetic groups (Pseudomonas and Stenotrophomonas) known to possess TNT degradation capacity (Cho et al., 2008; Travis et al., 2008) by targeting 16S rRNA genes with universal, Pseudomonas genus-specific and Stenotrophomonas genus-specific primers. The detailed results and conclu-sions are presented in Paper II.

In brief, all of the applied bioremediation treatments resulted in decreased concentrations of TNT in the soil (Paper II Fig. 1), with rye cultivation combined with biostimulation-bioaugmentation treatment having the most profound effect. Contrary to previous findings (Gong et al., 1999), no inhibi-tory effect of TNT on microbial abundance was recorded (Paper II Table 4).

Instead, the survival and elevation of the introduced Stenotrophomonas and especially Pseudomonas strains was noted in TNT-contaminated samples (Paper II Fig.4 and Table 4), fulfilling an important prerequisite for the su-ccessful application of bioaugmentation (Thompson et al., 2005). This phenomenon can most likely be attributed to the selective pressure of TNT promoting the growth of microbes able to utilize the pollutant. The recorded strong impact of bioaugmentation on the functional pattern and phylogenetic structure of the microbial community (Paper II Fig. 2, 3) further supported this finding. Plants enhanced the overall abundance of the microbial community, but in the case of blue fenugreek, cultivation did not significantly affect the proportions of functional microbial communities in soil or the rate of TNT degradation. Rye cultivation, on the other hand, had a positive effect on TNT removal (Paper II Fig. 1). Contrary to previous findings, where rhizore-mediation had overshadowed bioaugmentation in TNT removal from soil (van Dillewijn et al., 2007), the simultaneous application of biostimulation and bioaugmentation treatments resulted in more profound effects in this study.

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5.3.1. The impact of qPCR data quality control implementation on TNT bioremediation monitoring

The impact of modifications in qPCR amplification quality estimation as well as other alterations in qPCR data analysis on 16S rRNA gene quantifications for TNT bioremediation assessment was estimated through the reanalysis of TNT degradation pot experiment qPCR amplification data.

In the original study (Paper II) the reaction outliers were determined by visual analysis of amplification and melting curves. The implementation of subsequent steps of the quality control procedure resulted in the detection of several more deviating amplification reads from all of the standard curves and environmental amplification related datasets (Appendix Table 1). All deter-mined reaction outliers were omitted from further study. Even though most of the re-analysed qPCR amplification datasets were of relatively good quality (except for the Pseudomonas-specific 16S rRNA standard curve), significant differences between the mean amplification efficiency values of the generated standard curves and the analysed experimental samples were recorded for all primer sets used (Table 5). This result corresponds with findings in Paper I (Paragraph 5.2.1) and Paper III (Paper III Fig. 1) highlighting the difficulty of generating standard curves with comparable amplification efficiency to ana-lysed environmental samples, especially when the targeted sequences are quite variable. Despite the notion that comparable amplification efficiency is a requirement for precise target gene quantification (Töwe et al., 2010) this is evidently not easily achievable in practice. If this possibly bias-creating difference cannot be avoided, it should at least be reported and taken into account when interpreting the target gene quantification results.

In order to estimate the impact of qPCR amplification data quality im-provement on the result of TNT bioremediation monitoring, the targeted 16S rRNA genes were re-quantified (Appendix Table 3) and compared to the original report (Paper II Table 4) using the paired t-test. Quantification results were compared per treatment type as these introduce different compounds into the soil possibly affecting the microbial community, DNA extraction and subsequent qPCR amplification to a varying degree. The results indicated that total community 16S rRNA gene quantification had somewhat overestimated the absolute target gene copy numbers in non-planted as well as in TNT-spiked and biostimulated experiment variants (P<0.05) in the original study.

While a comparison of Pseudomonas-specific 16S rRNA quantifications did not yield any meaningful differences, Stenotrophomonas-specific 16S rRNA genes were found to have been somewhat underestimated in the experimental variants that used rye cultivation (P<0.05). Despite the fact that in this case the conclusions made based on absolute gene quantifications in the original study (Paper II) remained unchanged, these findings accentuate the impact of qPCR amplification data quality on the recorded target gene quantification and there-fore bioremediation monitoring results. The pre-experiments had indicated no inhibition in the qPCR reactions of the samples analysed, and therefore no IAC for inhibition measurement was used in this study.

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It has been stated that the comparison of absolute target gene copy numbers between different studies is not valid due to differences in qPCR workflows applied (Smith and Osborn, 2009). Instead, target gene normalizations reducing the impact of qPCR workflow details are preferable. The normali-zations in the original study (Paper II Fig. 4) were based on calculated absolute target gene copy numbers – the method generally used in environ-mental microbiology research (Cébron et al., 2008). However, the clearly different amplification efficiencies of the amplicon groups (Table 5) under-mine the credibility of such analysis. Therefore, for target gene normalization re-analysis calculation, a formula based on amplicons’ Ct values and amplifi-cation efficiencies was used (Ruijter et al., 2009). A comparison of the relative abundance of targeted phylogenetic groups gauged in the original study (Fig.

4A) and in the re-analysis (Fig. 4B) revealed that the proportion of targeted bacterial groups in the TNT bioremediation experiment had been severely underestimated in the original study. The re-normalizations resulted in a 2.08 to 5.97 times (on average 3.62 times) higher relative abundance of Pseudo-monas group and a 7.21 to 25.98 times (on average 13.43 times) higher relative abundance of the Stenotrophomonas group (Fig. 4, Appendix Table 3) in the analysed samples. While the general occurrence patterns of the Pseudo-monas group in different bioremediation treatments remained unchanged, the occurrence patterns of the Stenotrophomonas group in TNT spiked but not amended soil was subjected to changes (Fig. 4). The general results and conclusions, such as the elevation of targeted phylogenetic groups indicating the survival of the introduced microbial consortium and the selective pressure of TNT recorded in the original study (Paper II; Paragraph 5.3), remained unchanged. However, the variation magnitude recorded in the target gene normalization results generated by the different data analysis methodology applied highlights the impact that varying analysis methods can have on bioremediation monitoring and subsequent decision-making.

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Figure 4. Changes in the relative abundance of Pseudomonas andStenotrophomonas groups recorded by 16S rRNA gene quantifications in different bioremediation treatments designated by (A) – normalisations of calculated target gene copy numbers or (B) – normalisations using the amplification efficiency and Ct values of target gene amplifications. Group mean and standard deviation are shown. Treatment type abbreviations: TNT – TNT spiked soil, I – bioaugmentation, A – biostimulation, O – only planted or nonplanted samples, + indicates combination of different treatments.

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