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Article Dans Une Revue Journal of Biotechnology Année : 2020

Correlations between microbial population dynamics, bamA gene abundance and performance of anaerobic sequencing batch reactor (ASBR) treating increasing concentrations of phenol

Résumé

The relevant microorganims driving efficiency changes in anaerobic digestion of phenol remains uncertain. In this study correlations were established between microbial population and the process performance in an anaerobic sequencing batch reactor (ASBR) treating increasing concentrations of phenol (from 120 to 1200 mg L −1). Sludge samples were taken at different operational stages and microbial community dynamics was analyzed by 16S rRNA sequencing. In addition, bamA gene was quantified in order to evaluate the dynamics of anaerobic aromatic degraders. The microbial community was dominated by Anaerolineae, Bacteroidia, Clostridia, and Methanobacteria classes. Correlation analysis between bamA gene copy number and phenol concentration were highly significant, suggesting that the increase of aromatic degraders targeted by bamA assay was due to an increase in the amount of phenol degraded over time. The incremental phenol concentration affected hydrogenotrophic archaea triggering a linear decrease of Methanobacterium and the growth of Methanobrevibacter. The best performance in the reactor was at 800 mg L −1 of phenol. At this stage, the highest relative abundances of Syntrophorhabdus, Chloroflexus, Smithella, Methanolinea and Methanosaeta were observed and correlated positively with initial degradation rate, suggesting that these microorganisms are relevant players to maintain a good performance in the ASBR.
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hal-03147119 , version 1 (22-03-2021)

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Paternité - Pas d'utilisation commerciale - Pas de modification

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Oscar Franchi, Léa Cabrol, Rolando Chamy, Francisca Rosenkranz. Correlations between microbial population dynamics, bamA gene abundance and performance of anaerobic sequencing batch reactor (ASBR) treating increasing concentrations of phenol. Journal of Biotechnology, 2020, 310, pp.40-48. ⟨10.1016/j.jbiotec.2020.01.010⟩. ⟨hal-03147119⟩
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