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Assessment of the microbial interplay during anaerobic co-digestion of wastewater sludge using common components analysis.
Puig-Castellví, Francesc; Cardona, Laëtitia; Jouan-Rimbaud Bouveresse, Delphine; Cordella, Christophe B Y; Mazéas, Laurent; Rutledge, Douglas N; Chapleur, Olivier.
Afiliación
  • Puig-Castellví F; Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, Paris, France.
  • Cardona L; Université Paris-Saclay, INRAE, PRocédés biOtechnologiques au Service de l'Environnement, Antony, France.
  • Jouan-Rimbaud Bouveresse D; Université Paris-Saclay, INRAE, PRocédés biOtechnologiques au Service de l'Environnement, Antony, France.
  • Cordella CBY; Groupe "Chimiométrie pour la Caractérisation de Biomarqueurs-C2B", UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, INRAE, Université Paris-Saclay, Paris, France.
  • Mazéas L; Groupe "Chimiométrie pour la Caractérisation de Biomarqueurs-C2B", UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, INRAE, Université Paris-Saclay, Paris, France.
  • Rutledge DN; Université Paris-Saclay, INRAE, PRocédés biOtechnologiques au Service de l'Environnement, Antony, France.
  • Chapleur O; Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, Paris, France.
PLoS One ; 15(5): e0232324, 2020.
Article en En | MEDLINE | ID: mdl-32357180
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aguas del Alcantarillado / Bacterias / Archaea Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Estados Unidos
Texto completo
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aguas del Alcantarillado / Bacterias / Archaea Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Estados Unidos