6. PCR-DGGE Characterization of Bacterial Associations from Soil Microcosms Arrays
6.2 Results and Discussion
6.2.1 Analysis of bacterial community profiles from soil microcosm arrays at two
6.2.1.3 The effects of the redox, pH, and phenol concentration of landfill leachate
Table 6.3 The significance of P-values of the two sample pair-wise t-test for comparing the Species Richness (S), Shannon-Weaver Index (H’), and the Shannon-Weaver Evenness Index (E) for two different hydraulic loading rates (HLR) over time
P-value Factors
Compared Time 1 Time 2 Time 3 Time 4
SH vs SL 0.283 0.002 0.002 <0.001
H’H vs H’L 0.629 0.002 0.013 <0.001
EH vs EL 0.055 0.356 0.926 0.116
6.2.1.3 The effects of the redox, pH, and phenol concentration of landfill leachate on
The selection pressure posed by changing pH over time appears to have less of an impact on S over time when compared to the contributions of the redox environment over both treatments.
Figure 6.11 Three Dimensional (3-D) surface representations of “area under the curve” (AUC) data for Redox*Time (x-axis) and pH*Time (y-axis) plotted against Bacterial measures of diversity (z-axis) as follows: (a) and (b) Species Richness (S), (c) and (d) Shannon-Weaver Index (H), (e) and (f) Shannon-Weaver Evenness Index (E). Treatment HLRh is represented by (a); (c); and (e) while treatment HLRl is represented by (b); (d); and (f), for the respective measures of diversity.
(a) (c)
(b) (d)
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A similar relationship is evident for both leachate treatments when AUC redox*time and AUC pH*time are plotted against average H’ over time (Figures 6.11c and d). However, the pH appears to have more of an effect on average H’ than on average S, as the redox conditions become more anoxic for treatment HLRh (Figure 6.11c). There is a decrease in H’ with increasing pH*time. There is the emergence of a stronger influence of redox*time on H’, as apposed to S, for treatment HLRh specifically since conditions become increasingly anoxic. Therefore, the effects of increasing pH in reduced redox environments manifests by changing the numerical composition (intensity of bands over time) of different Bacterial species (bands) over time. Indeed, Singh (2001) showed that methanogenesis was successfully initiated in conditions of increasing soil pH with the corresponding decreasing Eh. This was evident for both treatments in this investigation, since redox and the corresponding pH were shown to share a strong negative correlation (ρHLRh = −0.919; p < 0.001 and ρHLRl = −0.744; p < 0.001), implying that any change in one characteristic would instigate a significant but reverse change in the remaining characteristic.
With respect to treatment HLRh, there is an initial increase and stabilization in E as the AUC redox*time changes from 8000 to 3000 (Figure 6.11e). Thereafter, there is a noticeable, decline in E from 0.95 to 0.91 (Table 6.2) as conditions become more anoxic.
Comparatively, the change in E for treatment HLRl is less perceptible, only showing non- significant changes (6.2.1.2.3) at the third decimal place, from 0.940 to 0.930 (Figure 6.11f). The relatively steady state of E for treatment HLRl over time can be explained by the lower rate of landfill leaching, making it possible for a greater proportion of the Bacterial species to adapt and survive. In Chapter Four (4.2.2) we discussed the lag of 17 weeks between both leaching treatments before the major sequence of reduction was triggered first with treatment HLRh; this time lag would provide sufficient time to account for differences in E between the two treatments, thereby influencing the numerical composition (intensity of bands) and distribution (presence/absence of bands) of different Bacterial species over time. As with S and H’, AUC pH*time has an inverse relationship with E for both treatments.
6.2.1.3.2 Redox and phenol
The interpolated effects of changing redox and relative phenol consumption on S, H, and E are represented in Figure 6.12. The positive relationship between redox*time and S, H’, and E was reiterated i.e. a general decrease in the redox state in the soil arrays resulted in an initial increase followed by a decrease in the investigated diversity measures for both treatments. In comparison to the AUC redox*time effects, phenol*time effects are less noticeable at the identical points of comparison on the graphs. The effects yield a similar plot pattern to the effects discussed in 6.2.1.3.1 in this Chapter. During the initial stages of leaching when conditions appear to be more oxidized than reduced, there is a definite elevation in S when the relative phenol concentration is low, followed by a decrease in S as the uptake is reduced (Figure 6.12a). This pattern is evident only for treatment HLRh. The lower rate of leaching saw no change in S during the initial stages of redox monitoring, however there was an increase in S (35 – 45 bands) as the redox*time state shifted from an AUC of 2500 to 2000, proceeded by a steep decline to 20 species at a AUC redox*time state of 1500 (Figure 6.12b). Both systems showed stability at different AUC redox*times, with treatment HLRh stabilizing earlier from 2000 and treatment HLRl from 900. The bioavailability of phenol and the prevalent redox environments play a key role in determining S since it is these two factors that will ultimately determine the rate of phenol degradation (Guerin, 1999).
The effects of redox and phenol on H’ are represented in Figure 6.12c and d. They reflect a similar trend as that projected for their effects on S. However, from an AUC redox*time of 2000 H’ continues to decrease for treatment HLRh and at the final sampling time the projected H’ is 2.7 whereas for treatment HLRl the projected H’ is 3.0 having stabilized at an AUC redox*time of 900. One can assume that the major contributor to the differences in diversity is the different rates of leaching with the synthetic leachate.
Treatment HLRh supplies more carbon, nutrients and water to generate more rapid changes in the redox state of the soil arrays, thereby leading to changes in the type and number of Bacterial species. The effects of greater phenol loading are evident in Figure 6.12c, where at the termination of the experiment, there appears to be a more noticeable reduction in H’
as phenol accumulates in the soil arrays. This trend is less noticeable in soil arrays perfused at HLRl (Figure 6.12d).
The effects of redox*time and phenol*time on E follow a similar trajectory to that projected for the effects of redox*time and pH*time on E (Figure 6.12e and f). There is a general decrease in E with an increase in phenol concentration over time. This is highlighted by a comparison of the two treatments, with a greater change in E documented for treatment HLRh (0.95 – 0.91) as apposed to that recorded for HLRl (0.940 – 0.930) over the investigation.
Here again, redox potential and phenol degradation share a relationship that is negatively correlated for both treatments (ρHLRh = −0.811; p < 0.001 and ρHLRl = −0.857;
p < 0.001) (4.2.2 and 4.2.3). The correlation between organic carbon and redox potential in soil environments was shown to be non-linear in nature (Singh, 2001). However, the rates of phenol degradation decrease under aerobic and anaerobic conditions, and can be distinguished further under nitrate-and sulphate reducing and methanogenic conditions (van Schie and Young, 2000). It is true that our knowledge of aerobic phenol degrading bacteria is more advanced than phenol degrading pathways involving anerobic bacteria.
The aerobic phenol degrading bacteria employ metabolic pathways that make use of oxygen dependent enzymes that enable quicker degradation of phenolics. The range of anaerobic bacteria, including methanogenic, sulphate, iron and nitrate reducing bacteria, make use of multiple anaerobic degradation pathways often containing oxygen sensitive carboxylase enzymes (van Schie and Young, 2000).
However with respect to the two cases discussed thus far (6.2.1.3.1 and 6.2.1.3.2), the change in redox state appears to be the dominating factor in determining the response of Bacterial diversity for both treatments.
Figure 6.12 Three Dimensional (3-D) surface representations of “area under the curve” (AUC) data for Redox*Time (x-axis) and Phenol*Time (y-axis) plotted against Bacterial measures of diversity (z-axis) as follows: (a) and (b) Species Richness (S), (c) and (d) Shannon-Weaver Index (H), (e) and (f) Shannon-Weaver Evenness Index (E). Treatment HLRh is represented by (a); (c); and (e) while treatment HLRl is represented by (b); (d); and (f), for the respective measures of diversity.
(a)
(b)
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6.2.1.3.3 pH and phenol
The projected effects of phenol and pH on Bacterial diversity are more visible on the three-dimensional plots that obviate the effects of redox potential on the soil arrays described in Chapter Four (Figure 6.13). With respect to S and H’, a general increase in pH over time results in an increase in diversity up to a threshold, after which any further increase in AUC pH*time forces a decrease in S and H’ for both treatments. The start-to- threshold range of S projected for treatment HLRh and HLRl under the effects of AUC pH*time were 18-37 and 19-44 species, respectively (Figures 6.13a and b). The start-to- threshold range for H’ was 2.75-3.40 and 2.77-3.54, respectively (Figures 6.13c and d).
Regarding the effects of phenol*time, the start-to-threshold ranges projected for S and H’, when pH effects were optimal for the acquisition of maximum diversity, were 34-37 and 39-44 species for treatments HLRh and HLRl, respectively . In terms of H’, these values were 3.25-3.40 (HLRh) (Figures 6.13a and b) and 3.35-3.54 (HLRl) (Figures 6.13c and d).
In Chapter Four, regression analysis of phenol (4.2.3) and pH (4.2.1) revealed significantly different responses between the two leaching treatments which in turn have contributed, accordingly, to significantly different overall S (6.2.1.2.1)and H’ (6.2.1.2.2) between both treatments.
An altogether different trajectory was projected for the effect of pH*time on E for both leaching treatments (Figures 6.13e and f). The trajectory for treatment HLRh implies a constant decrease in Bacterial community evenness as the pH increased over time, punctuated by a temporary plateau measuring between 90 and 120 AUC pH*time (Figure 6.13e). Much the same pattern is evident for treatment HLRl but with two apparent differences; the first being the prominent increase in E evident between 90 and 120 AUC pH*time and the second being the relatively non-significant (F=0.856, Table 6.2) change in E (change projected only over the third decimal place) (Figure 6.13f).
By comparison, the change in E over time for treatment HLRh was deemed non-significant (F=0.067, Table 6.2) so one can conclude that the average change in E over time for treatment HLRh was relatively non-random when compared to the change in average E detected for treatment HLRl.
Phenol concentration and the corresponding pH were shown to share a strong positive correlation (ρHLRh = 0.852; p < 0.001 and ρHLRl = 0.880; p < 0.001), implying that
any change in one characteristic would instigate a significant change, in the same direction, in the remaining characteristic.
Figure 6.13 Three Dimensional (3-D) surface representations of “area under the curve” (AUC) data for Phenol*Time (x-axis) and pH*Time (y-axis) plotted against Bacterial measures of diversity (z-axis) as follows: (a) and (b) Species Richness (S), (c) and (d) Shannon-Weaver Index (H), (e) and (f) Shannon-Weaver Evenness Index (E). Treatment HLRh is represented by (a); (c); and (e) while treatment HLRl is represented by (b); (d); and (f), for the respective measures of diversity.
(a)
(b)
(c)
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(e)
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