A novel high-throughput multi-parameter flow cytometry based method for monitoring and rapid characterization of microbiome dynamics in anaerobic systems

• Published in: Bioresource technology Vol. 220; pp. 566 - 571
• Main Authors: Dhoble, Abhishek S., Bekal, Sadia, Dolatowski, William, Yanz, Connor, Lambert, Kris N., Bhalerao, Kaustubh D.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.11.2016
• Subjects: Anaerobic digestion; Anaerobiosis; Autofluorescence; Automation; Bioreactors - microbiology; Cluster Analysis; Databases as Topic; DNA, Ribosomal Spacer - genetics; Flow cytometry; Flow Cytometry - methods; Labe free monitoring; Microbial community; Microbial Consortia - genetics; Microbial dynamics; Microbiome characterization; Microbiota - genetics; Time Factors; Flow cytometry; Labe free monitoring; Microbiome characterization; Autofluorescence; Microbial dynamics; Anaerobic digestion; Microbial community
• ISSN: 0960-8524; 1873-2976
• DOI: 10.1016/j.biortech.2016.08.076

•Flow cytometry can facilitate rapid characterization of dynamics of complex microbiomes.•Flow cytometry is comparable to traditional culture-independent techniques like ARISA.•Flow cytometry is sensitive to lab scale to industrial scale anaerobic digesters. A novel multidimensional flow cytometry based method has been demonstrated to monitor and rapidly characterize the dynamics of the complex anaerobic microbiome associated with perturbations in external environmental factors. While community fingerprinting provides an estimate of the meta genomic structure, flow cytometry provides a fingerprint of the community morphology including its autofluorescence spectrum in a high-throughput manner. Using anaerobic microbial consortia perturbed with the controlled addition of various carbon sources, it is possible to quantitatively discriminate between divergent microbiome analogous to community fingerprinting techniques using automated ribosomal intergenic spacer analysis (ARISA). The utility of flow cytometry based method has also been demonstrated in a fully functional industry scale anaerobic digester to distinguish between microbiome composition caused by varying hydraulic retention time (HRT). This approach exploits the rich multidimensional information from flow cytometry for rapid characterization of the dynamics of microbial communities.