Multivariate statistical analyses of rDNA and rRNA fingerprint data to differentiate microbial communities in swine manure

Seasonal transition of active bacterial and archaeal communities in relation to water management in paddy soils

Paddy soils have an environment in which waterlogging and drainage occur during the rice growing season. Fingerprinting analysis based on soil RNA indicated that active microbial populations changed in response to water management conditions, although the fundamental microbial community was stable as assessed by DNA-based fingerprinting analysis. Comparative clone library analysis based on bacterial and archaeal 16S rRNAs (5,277 and 5,436 clones, respectively) revealed stable and variable members under waterlogged or drained conditions. Clones related to the class Deltaproteobacteria and phylum Euryarchaeota were most frequently obtained from the samples collected under both waterlogged and drained conditions. Clones related to syntrophic hydrogen-producing bacteria, hydrogenotrophic methanogenic archaea, rice cluster III, V, and IV, and uncultured crenarchaeotal group 1.2 appeared in greater proportion in the samples collected under waterlogged conditions than in those collected under drained conditions, while clones belonging to rice cluster VI related to ammonia-oxidizing archaea (AOA) appeared at higher frequency in the samples collected under drained conditions than in those collected under waterlogged conditions. These results suggested that hydrogenotrophic methanogenesis may become active under waterlogged conditions, whereas ammonia oxidation may progress by rice cluster VI becoming active under drained conditions in the paddy field.

Diet-induced alterations in total and metabolically active microbes within the rumen of dairy cows

DNA-based techniques are widely used to study microbial populations; however, this approach is not specific to active microbes, because DNA may originate from inactive and/or dead cells. Using cDNA and DNA, respectively, we aimed to discriminate the active microbes from the total microbial community within the rumen of dairy cows fed diets with increasing proportions of corn silage (CS). Nine multiparous lactating Holstein cows fitted with ruminal cannulas were used in a replicated 3×3 Latin square (32-d period; 21-d adaptation) design to investigate diet-induced shifts in microbial populations by targeting the rDNA gene. Cows were fed a total mixed ration with the forage portion being either barley silage (0% CS), a 50∶50 mixture of barley silage and corn silage (50% CS), or corn silage (100% CS). No differences were found for total microbes analyzed by quantitative PCR, but changes were observed within the active ones. Feeding more CS to dairy cows was accompanied by an increase in Prevotella rRNA transcripts (P = 0.10) and a decrease in the protozoal rRNA transcripts (P<0.05). Although they were distributed differently among diets, 78% of the amplicons detected in DNA- and cDNA-based fingerprints were common to total and active bacterial communities. These may represent a bacterial core of abundant and active cells that drive the fermentation processes. In contrast, 10% of amplicons were specific to total bacteria and may represent inactive or dead cells, whereas 12% were only found within the active bacterial community and may constitute slow-growing bacteria with high metabolic activity. It appears that cDNA-based analysis is more discriminative to identify diet-induced shifts within the microbial community. This approach allows the detection of diet-induced changes in the microbial populations as well as particular bacterial amplicons that remained undetected using DNA-based methods.

Tracking dynamics of plant biomass composting by changes in substrate structure, microbial community, and enzyme activity

BACKGROUND

Understanding the dynamics of the microbial communities that, along with their secreted enzymes, are involved in the natural process of biomass composting may hold the key to breaking the major bottleneck in biomass-to-biofuels conversion technology, which is the still-costly deconstruction of polymeric biomass carbohydrates to fermentable sugars.However, the complexity of both the structure of plant biomass and its counterpart microbial degradation communities makes it difficult to investigate the composting process.

RESULTS

In this study, a composter was set up with a mix of yellow poplar (Liriodendron tulipifera) wood-chips and mown lawn grass clippings (85:15 in dry-weight) and used as a model system. The microbial rDNA abundance data obtained from analyzing weekly-withdrawn composted samples suggested population-shifts from bacteria-dominated to fungus-dominated communities. Further analyses by an array of optical microscopic, transcriptional and enzyme-activity techniques yielded correlated results, suggesting that such population shifts occurred along with early removal of hemicellulose followed by attack on the consequently uncovered cellulose as the composting progressed.

CONCLUSION

The observed shifts in dominance by representative microbial groups, along with the observed different patterns in the gene expression and enzymatic activities between cellulases, hemicellulases, and ligninases during the composting process, provide new perspectives for biomass-derived biotechnology such as consolidated bioprocessing (CBP) and solid-state fermentation for the production of cellulolytic enzymes and biofuels.

A novel fingerprint method to assess the diversity of methanogens in microbial systems

Understanding the ecology of methanogens in natural and engineered environments is a prerequisite to predicting or managing methane emissions. In this study, a novel high-throughput fingerprint method was developed for determining methanogen diversity and relative abundance within environmental samples. The method described here, designated amplicon length heterogeneity PCR of the mcrA gene (LH-mcrA), is based on the natural length variation in the mcrA gene. The mcrA gene encodes the alpha-subunit of the methyl-coenzyme M reductase, which is involved in the terminal step of methane production by methanogens. The methanogenic communities from stored swine and dairy manures were distinct from each other. To validate the method, methanogenic communities in a plug flow-type bioreactor (PFBR) treating swine manure were characterized using LH-mcrA method and correlated to mcrA gene clone libraries. The diversity and relative abundance of the methanogenic groups were assessed. Methanobrevibacter, Methanosarcinaceae, Methanoculleus, Methanogenium, Methanocorpusculum and one unidentified group were assigned to particular LH-mcrA amplicons. Particular phylotypes related to Methanoculleus were predominant in the last compartment of the PFBR where the bulk of methane was produced. LH-mcrA method was found to be a reliable, fast and cost-effective alternative for diversity assessment of methanogenic communities in microbial systems.