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Landfill cover soils play a major role in limiting methane emissions to the atmosphere, predominantly through microbial oxidation of methane. Hence there is a need for a better understanding of the microorganisms involved in methane oxidation in landfill cover soil and of the factors influencing the diversity and activity of these microorganisms. This study identified the active methanotrophs in the Ufton landfill cover soil and also investigated the impact of earthworms on active bacterial

community involved in methane oxidation.

Methanotroph diversity in the landfill cover soil

In this study, we used both DNA- and RNA-SIP to analyze the active bacterial community oxidizing methane in the landfill cover soil. A similar study using both DNA- and RNA-SIP was performed by Luederset al. (2004) to investigate the temporal dynamics of methylotrophs in rice field soil. The authors suggested that RNA-SIP (after 6 days of incubation) revealed the initially active methylotrophs, whereas DNA-SIP (after 42 days incubation) revealed a specific enriched methylotroph. However, recent work by Neufeldet al. (2007d) has

improved DNA-SIP sensitivity by optimizing the amount of substrate incorporation and the length of incubation times. In this study, 11 µmol of13C-CH4g-1soil at 7

days of incubation were sufficient for efficient labelling of both DNA and RNA (as revealed by the quite similar bacterial 16S rRNA gene DGGE profile). However, it should be noted that a comparison between DNA and RNA-SIP at an earlier time point could have provided different results.

pmoAgene based analysis revealed a high methanotroph diversity,

to both Type I and Type II methanotrophs. The presence of a high diversity ofpmoA sequences from Type I and Type II methanotrophs in this landfill cover soil is similar to other landfill cover soils (Wise et al., 1999; Bodrossy et al., 2003; Uz et al., 2003; Crossman et al., 2004; Stralis-Pavese et al., 2004). However, the diversity ofmmoXgene sequences was comparatively lower than that ofpmoA, with more than 80% of the sequences related to themmoXfrom genusMethylocystis. DGGE- based analysis of13C-DNA and RNA identifiedMethylobacter,Methylosarcinaand Methylocystisas the active methanotrophs. These results are congruent with the pmoAhybridization signal pattern with13C-DNA. Previous SIP experiments in different environments such as peat soil (Morris et al., 2002) and Movile cave (Hutchens et al., 2004) identified a broad range of both Type I and Type II

methanotrophs, whereas in some environments such as Russian soda lake sediments, it has been suggested that only Type I methanotrophs are active (Lin et al., 2004). pmoAmicroarray hybridization signals forMethylocaldum(McI408) and Upland soil cluster gamma probes (P_USCG-255 and P_USCG-255b) were obtained only with the12C-DNA and not with the13C-DNA samples, suggesting that although these methanotrophs are present they are not necessarily active.

Previous studies have concluded that 16S rRNA andpmoA-based analysis of methanotroph community structure gave similar results (Costello and Lidstrom, 1999; Horz et al., 2001). The results obtained from this study also confirm this observation. In particular, highly congruent results were obtained with thepmoA clone libraries andpmoAmicroarray hybridization patterns. However, microarray results revealed a more diverse methanotroph community structure than clone library analysis, indicating the sensitivity and suitability of this method for high throughput analysis ofpmoAgene diversity in the environment. The poor representation of

methanotroph diversity inpmoAclone library analysis compared topmoAmicroarray analysis might be due to the low number of clones analyzed in this study. Type I methanotroph-specific 16S rRNA gene DGGE profiles based on12C-DNA and12C- RNA revealed a complex and high diversity of Type I methanotrophs, whereas DGGE profiles based on13C-DNA and RNA revealed only a few distinct bands, suggesting that the dominant members of the community were not necessarily active. However,pmoAmicroarray results suggested that almost all of the methanotrophs detected (with12C-DNA) were active (with13C-DNA). This could be due to the lack of specificity of Type I methanotroph 16S rRNA gene primers when used to target Type I methanotrophs in a DNA or RNA template with complex bacterial

community. In12C-DNA and RNA, the proportion of Type I methanotrophs among total bacteria might be too small to avoid amplification of non-methanotrophic bacteria (Héry et al., 2008).

Effect of earthworms on bacterial community structure

The distinct band present in the 16S rRNA gene DGGE profiles of13C-DNA and RNA of +worms sample corresponded to aBacteroidetes-related bacterium and was the only difference observed between control and +worms samples using 16S rRNA gene based analysis. This is the first time that there is an indication of a possible role ofBacteroidetesin methane oxidation. Previous studies have reported Bacteroidetesin methane-rich environments (Scholten-Koerselman et al., 1986; Reed et al., 2002; Reed et al., 2006); however, there is a lack of evidence for possible methane oxidation capacity ofBacteroidetes. It is also possible that this result might be due to a cross-feeding phenomenon where theBacteroidetes-related bacteria feeding a labelled by-product (such as methanol) produced by

fed on the dead13C-labelled methanotroph biomass due to food-web interactions. So far there is no conclusive evidence for the role ofBacteroidetesin methane oxidation and further investigations are necessary to understand the contribution (if any) of this bacterium to methane oxidation.

pmoAmicroarray analysis are semi-quantitative in nature, allowing us to compare the relative abundance ofpmoAtarget sequences in environmental samples (Bodrossy et al., 2003).pmoAmicroarray hybridization signal patterns with13C- DNA indicated a higher relative abundance of Type Ia methanotrophs in +worms sample than in control sample. This can be suggested since the highest hybridization signals were observed for the generic Type Ia probe, O_Ia193 along with otherpmoA probes targeting several genera of Type Ia methanotrophs such asMethylomicrobium (Mmb303),Methylomonas(P_Mm531) andMethylobacter(P_MbSL#3-300).

Moreover, higher numbers of Type I methanotrophs-related sequences than Type II methanotroph-related sequences were found in thepmoAgene library with +worms sample. These results suggest that earthworms might stimulate the growth or activity of Type I methanotrophs. Previous studies have suggested that Type I methanotrophs might respond quickly to changing environmental conditions compared to Type II methanotrophs, possibly due to a higher growth rate (Grahamet al., 1993; Bodelier et al., 2000; Henckelet al., 2000a). This stimulation of activity could also be correlated with the increased nitrogen and/or nutrient availability directly linked earthworm activity (Needham, 1957; Buse, 1990). In this study, the relative amounts of ammonia and nitrate were influenced by the presence of earthworms. The possible interaction mechanisms between earthworms and methanotrophs are discussed in detail in Chapter 4. The higher nitrate content in the +worms soil compared to control soil might also indicate a possible stimulation of nitrifers. Earthworms

burrow walls (Parkin and Berry, 1999) and casts (Mulongoy and Bedoret, 1989) are known to harbour a higher number of nitrifiers compared to bulk soil. The enzyme ammonia monooxygenase in nitrifiers is evolutionarily related to methane

monooxygenase and could possibly co-oxidize methane. However, the role of nitrifiers in methane cycling is unclear and further investigations will be necessary. In summary, use of SIP allowed us to identify the active methanotrophs in this landfill cover soil. It also showed that the earthworm-mediated increase in soil methane oxidation was only weakly correlated with a shift in the active

methanotroph community structure. Further investigations are needed to understand the effect of earthworms on methanotroph activity and growth and also the possible role of nitrifiers in methane oxidation.

Chapter 4

Spatial and temporal shifts in active