Assessment of the microbial interplay during anaerobic co-digestion of wastewater sludge using common components analysis

• Published in: PloS one Vol. 15; no. 5; p. e0232324
• Main Authors: Puig-Castellví, Francesc, Cardona, Laëtitia, Jouan-Rimbaud Bouveresse, Delphine, Cordella, Christophe B Y, Mazéas, Laurent, Rutledge, Douglas N, Chapleur, Olivier
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.05.2020; Public Library of Science (PLoS)
• Subjects: Advertising executives; Anaerobic digestion; Anaerobic microorganisms; Analysis; Analytical chemistry; Bacteria; Biogas; Biological activity; Biology and Life Sciences; Biomass energy; Chemical oxygen demand; Chemical Sciences; Composition effects; Computer and Information Sciences; Data analysis; Data processing; Deoxyribonucleic acid; DNA; Engineering and Technology; Environmental Engineering; Environmental Sciences; Gene sequencing; Information management; Mathematics; Medicine and Health Sciences; Microbial activity; Microorganisms; Physical Sciences; Principal components analysis; Ribonucleic acid; RNA; RNA sequencing; Sludge; Sludge digestion; Solid wastes; Statistics; Substrates; Taxonomy; Waste management; Wastes; Wastewater; Water treatment; France
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0232324

Anaerobic digestion (AD) is used to minimize solid waste while producing biogas by the action of microorganisms. To give an insight into the underlying microbial dynamics in anaerobic digesters, we investigated two different AD systems (wastewater sludge mixed with either fish or grass waste). The microbial activity was characterized by 16S RNA sequencing. 16S data is sparse and dispersed, and existent data analysis methods do not take into account this complexity nor the potential microbial interactions. In this line, we proposed a data pre-processing pipeline addressing these issues while not restricting only to the most abundant microorganisms. The data were analyzed by Common Components Analysis (CCA) to decipher the effect of substrate composition on the microorganisms. CCA results hinted the relationships between the microorganisms responding similarly to the AD physicochemical parameters. Thus, in overall, CCA allowed a better understanding of the inter-species interactions within microbial communities.