Quantitative and qualitative transitions of methanogen community structure during the batch anaerobic digestion of cheese-processing wastewater.
Qualitative and quantitative shifts in methanogen community structure, associated with process performance data, were investigated during the batch anaerobic digestion of a cheese-processing wastewater, whey permeate. Denaturing gradient gel electrophoresis (DGGE) and real-time PCR techniques were applied to obtain qualitative and quantitative microbial data sets, respectively, based on methanogen 16S rRNA genes. Throughout the operation, dynamic variations in both qualitative and quantitative community structures were observed, with repeated shifts in dominance between the aceticlastic Methanosarcinaceae (suggested mainly by the detection of a Methanosarcina-like population) and the hydrogenotrophic Methanomicrobiales (suggested mainly by the detection of a Methanofollis-like population). This trend corresponded well to the diauxic utilization of acetate and longer-chain fatty acids (C(3)-C(6)), mainly propionate. Joint-plot non-metric multidimensional scaling (NMS) analysis demonstrated that the qualitative and quantitative community shifts had significant correlations with the composition of residual organic acids and the methane production rate, respectively. This suggests the potential use of microbial community shift analysis as an indicative tool for diagnosing anaerobic digestion processes. The results suggest that more attention should be directed to quantitative, as well as qualitative, approaches for a better understanding of anaerobic digestion, particularly in terms of biogas production efficiency, under dynamic and transitional conditions.
Lee
Changsoo
C
Division of Environmental and Water Resources Engineering, School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
Kim
Jaai
J
Shin
Seung Gu
SG
O'Flaherty
Vincent
V
Hwang
Seokhwan
S
D000085:Acetates / Q000378:metabolism; D000693:Anaerobiosis; D001419:Bacteria / Q000145:classification* / Q000235:genetics / Q000254:growth & development* / Q000378:metabolism; D044822:Biodiversity; D002611:Cheese; D016000:Cluster Analysis; D004269:DNA, Bacterial / Q000737:chemistry / Q000235:genetics; D004275:DNA, Ribosomal / Q000737:chemistry / Q000235:genetics; D004591:Electrophoresis, Polyacrylamide Gel; D005227:Fatty Acids / Q000378:metabolism; D019649:Food Industry; D007220:Industrial Waste; D008697:Methane / Q000378:metabolism*; D008969:Molecular Sequence Data; D009691:Nucleic Acid Denaturation; D010802:Phylogeny; D016133:Polymerase Chain Reaction; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA; D018508:Water Purification / Q000379:methods*
D000085:Acetates; D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D005227:Fatty Acids; D007220:Industrial Waste; D012336:RNA, Ribosomal, 16S; D008697:Methane