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1.  Molecular analysis of meso- and thermophilic microbiota associated with anaerobic biowaste degradation 
BMC Microbiology  2012;12:121.
Microbial anaerobic digestion (AD) is used as a waste treatment process to degrade complex organic compounds into methane. The archaeal and bacterial taxa involved in AD are well known, whereas composition of the fungal community in the process has been less studied. The present study aimed to reveal the composition of archaeal, bacterial and fungal communities in response to increasing organic loading in mesophilic and thermophilic AD processes by applying 454 amplicon sequencing technology. Furthermore, a DNA microarray method was evaluated in order to develop a tool for monitoring the microbiological status of AD.
The 454 sequencing showed that the diversity and number of bacterial taxa decreased with increasing organic load, while archaeal i.e. methanogenic taxa remained more constant. The number and diversity of fungal taxa increased during the process and varied less in composition with process temperature than bacterial and archaeal taxa, even though the fungal diversity increased with temperature as well. Evaluation of the microarray using AD sample DNA showed correlation of signal intensities with sequence read numbers of corresponding target groups. The sensitivity of the test was found to be about 1%.
The fungal community survives in anoxic conditions and grows with increasing organic loading, suggesting that Fungi may contribute to the digestion by metabolising organic nutrients for bacterial and methanogenic groups. The microarray proof of principle tests suggest that the method has the potential for semiquantitative detection of target microbial groups given that comprehensive sequence data is available for probe design.
PMCID: PMC3408363  PMID: 22727142
2.  Molecular profiling of fungal communities in moisture damaged buildings before and after remediation - a comparison of culture-dependent and culture-independent methods 
BMC Microbiology  2011;11:235.
Indoor microbial contamination due to excess moisture is an important contributor to human illness in both residential and occupational settings. However, the census of microorganisms in the indoor environment is limited by the use of selective, culture-based detection techniques. By using clone library sequencing of full-length internal transcribed spacer region combined with quantitative polymerase chain reaction (qPCR) for 69 fungal species or assay groups and cultivation, we have been able to generate a more comprehensive description of the total indoor mycoflora. Using this suite of methods, we assessed the impact of moisture damage on the fungal community composition of settled dust and building material samples (n = 8 and 16, correspondingly). Water-damaged buildings (n = 2) were examined pre- and post- remediation, and compared with undamaged reference buildings (n = 2).
Culture-dependent and independent methods were consistent in the dominant fungal taxa in dust, but sequencing revealed a five to ten times higher diversity at the genus level than culture or qPCR. Previously unknown, verified fungal phylotypes were detected in dust, accounting for 12% of all diversity. Fungal diversity, especially within classes Dothideomycetes and Agaricomycetes tended to be higher in the water damaged buildings. Fungal phylotypes detected in building materials were present in dust samples, but their proportion of total fungi was similar for damaged and reference buildings. The quantitative correlation between clone library phylotype frequencies and qPCR counts was moderate (r = 0.59, p < 0.01).
We examined a small number of target buildings and found indications of elevated fungal diversity associated with water damage. Some of the fungi in dust were attributable to building growth, but more information on the material-associated communities is needed in order to understand the dynamics of microbial communities between building structures and dust. The sequencing-based method proved indispensable for describing the true fungal diversity in indoor environments. However, making conclusions concerning the effect of building conditions on building mycobiota using this methodology was complicated by the wide natural diversity in the dust samples, the incomplete knowledge of material-associated fungi fungi and the semiquantitative nature of sequencing based methods.
PMCID: PMC3206440  PMID: 22017920
3.  Bacterial diversity at different stages of the composting process 
BMC Microbiology  2010;10:94.
Composting is an aerobic microbiological process that is facilitated by bacteria and fungi. Composting is also a method to produce fertilizer or soil conditioner. Tightened EU legislation now requires treatment of the continuously growing quantities of organic municipal waste before final disposal. However, some full-scale composting plants experience difficulties with the efficiency of biowaste degradation and with the emission of noxious odours. In this study we examine the bacterial species richness and community structure of an optimally working pilot-scale compost plant, as well as a full-scale composting plant experiencing typical problems. Bacterial species composition was determined by isolating total DNA followed by amplifying and sequencing the gene encoding the 16S ribosomal RNA.
Over 1500 almost full-length 16S rRNA gene sequences were analysed and of these, over 500 were present only as singletons. Most of the sequences observed in either one or both of the composting processes studied here were similar to the bacterial species reported earlier in composts, including bacteria from the phyla Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Deinococcus-Thermus. In addition, a number of previously undetected bacterial phylotypes were observed. Statistical calculations estimated a total bacterial diversity of over 2000 different phylotypes in the studied composts.
Interestingly, locally enriched or evolved bacterial variants of familiar compost species were observed in both composts. A detailed comparison of the bacterial diversity revealed a large difference in composts at the species and strain level from the different composting plants. However, at the genus level, the difference was much smaller and illustrated a delay of the composting process in the full-scale, sub-optimally performing plants.
PMCID: PMC2907838  PMID: 20350306
4.  Universal ligation-detection-reaction microarray applied for compost microbes 
BMC Microbiology  2008;8:237.
Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones.
Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array.
This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities.
PMCID: PMC2648982  PMID: 19116002

Results 1-4 (4)