Flow cytometric quantification, sorting and sequencing of methanogenic archaea based on F420 autofluorescence

[摘要] BackgroundThe widely established production of CH4 from renewable biomass in industrial scale anaerobic reactors may play a major role in the future energy supply. It relies on methanogenic archaea as key organisms which represent the bottleneck in the process. The quantitative analysis of these organisms can help to maximize process performance, uncover disturbances before failure, and may ultimately lead to community-based process control schemes. Existing qPCR and fluorescence microscopy-based methods are very attractive but can be cost-intensive and laborious.ResultsIn this study we present an autofluorescence-based, flow cytometric method for the fast low-cost quantification of methanogenic archaea in complex microbial communities and crude substrates. The method was applied to a methanogenic enrichment culture (MEC) and digester samples (DS). The methanogenic archaea were quantified using the distinct fluorescence of their cofactor F420 in a range from 3.7 × 108 (± 3.3 × 106) cells mL−1 and 1.8 x 109 (± 1.1 × 108) cells mL−1. We evaluated different fixation methods and tested the sample stability. Stable abundance and fluorescence intensity were recorded up to 26 days during aerobic storage in PBS at 6 °C. The discrimination of the whole microbial community from the ubiquitous particle noise was facilitated by SYBR Green I staining and enabled calculation of relative abundances of methanogenic archaea of up to 9.64 ± 0.23% in the MEC and up to 4.43 ± 0.74% in the DS. The metaprofiling of the mcrA gene reinforced the results.ConclusionsThe presented method allows for fast and reliable quantification of methanogenic archaea in microbial communities under authentic digester conditions and can thus be useful for process monitoring and control in biogas digesters.

[发布日期] 2017-10-30

[关键词] Single cell analytics;F;Autofluorescence;Methanogenic archaea;Anaerobic digestion;Biogas;16S rDNA sequencing;Process monitoring