Evaluation of stable isotope fingerprinting techniques for the assessment of the predominant methanogenic pathways in anaerobic digesters.

Laboratory biogas reactors were operated under various conditions using maize silage, chicken manure, or distillers grains as substrate. In addition to the standard process parameters, the hydrogen and carbon stable isotopic composition of biogas was analyzed to estimate the predominant methanogenic pathways as a potential process control tool. The isotopic fingerprinting technique was evaluated by parallel analysis of mcrA genes and their transcripts to study the diversity and activity of methanogens. The dominant hydrogenotrophs were Methanomicrobiales, while aceticlastic methanogens were represented by Methanosaeta and Methanosarcina at low and high organic loading rates, respectively. Major changes in the relative abundance of mcrA transcripts were observed compared to the results obtained from DNA level. In agreement with the molecular results, the isotope data suggested the predominance of the hydrogenotrophic pathway in one reactor fed with chicken manure, while both pathways were important in the other reactors. Short-term changes in the isotopic composition were followed, and a significant change in isotope values was observed after feeding a reactor digesting maize silage. This ability of stable isotope fingerprinting to follow short-term activity changes shows potential for indicating process failures and makes it a promising technology for process control.

Molecular assessment of complex microbial communities degrading long chain fatty acids in methanogenic bioreactors.

Microbial diversity of anaerobic sludge after extended contact with long chain fatty acids (LCFA) was studied using molecular approaches. Samples containing high amounts of accumulated LCFA were obtained after continuous loading of two bioreactors with oleate or with palmitate. These sludge samples were then incubated in batch assays to allow degradation of the biomass-associated LCFA. In addition, sludge used as inoculum for the reactors was also characterized. Predominant phylotypes of the different samples were monitored using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified 16S rRNA gene fragments. Fingerprinting analysis showed changes in bacterial and archaeal communities during LCFA accumulation and degradation. Full-length 16S rRNA gene sequences of 22 clones, representing the predominant bacteria and archaea, were determined. Most bacterial clones (80%) clustered within the Clostridiaceae. Two major groups of methanogens were identified: hydrogen- and formate-utilizing organisms, closely related to Methanobacterium, and acetoclastic organisms closely related to Methanosaeta and Methanosarcina. Quantification by FISH and real-time PCR showed that the relative abundance of archaea increased during degradation of biomass-accumulated LCFA. These results provide insight into the importance and dynamics of balanced communities of bacteria and methanogens in LCFA-accumulation/degradation cycles.

The global intrinsic curvature of archaeal and eubacterial genomes is mostly contained in their dinucleotide composition and is probably not an adaptation.

Until now, the genomic DNA of all eubacteria analyzed has been hyper-curved, its global intrinsic curvature being higher than that of a random sequence. In contrast, that rule failed for archaea or eukaryotes, which could be either hypo- or hyper-curved. The existence of the rule suggested that, at least for eubacteria, global intrinsic curvature is adaptive. However, the present results from analyzing 21 eubacterial and six archaeal genomes argue against adaptation. First, there are two eubacterial exceptions to the former rule. More significantly, we found that the dinucleotide composition of the genome alone (which lacks all sequence information) is enough to determine the genome curvature. Additional evidence against adaptation came from showing that the global curvature of bacterial genomes could not have evolved under either of two complementary models of curvature selection: (i) that curvature is selected locally from unbiased variability; (ii) that curvature is established globally through the selection of a curvature-altering mutational bias. We found that the observed relationship between curvature and dinucleotide composition is incompatible with model (i). We also found that, contrary to the predictions of model (ii), the dinucleo-tide compositions of bacterial genomes were not statistically special in their curvature-related properties (when compared to stochastically generated dinucleotide compositions).