Microbial diversity and metabolic inference of diclofenac removal in optimized batch heterotrophic-denitrifying conditions by means of factorial design

Abstract

Using the Response Surface Methodology (RSM) and Rotational Central Composite Design (RCCD), this study evaluated the removal of DCF under denitrifying conditions, with ethanol as cosubstrate, in batch reactors, being 1 L Erlenmeyer flasks (330 mL of reactional volume) containing Dofing medium and kept under agitation at 130 rpm and incubated at mesophilic temperature (30 °C). It considered the individual and multiple effects of the variables: nitrate (130 - 230 mg NO3 - L-1), DCF (60 - 100 µg DCF L-1) and ethanol (130 - 230 mg EtOH L-1). The highest drug removal efficiency (17.5%) and total nitrate removal were obtained at 176.6 ± 4.3 mg NO3 - L-1, 76.8 ± 3.7 µg DCF L-1, and 180.0 ± 2.5 mg EtOH L-1. Under such conditions, the addition of ethanol and nitrate was significant for the additional removal of diclofenac (p > 0.05). The prevalence of Rhodanobacter, Haliangium and Terrimonas in the inoculum biomass (activated sludge systems) was identified through the 16S rRNA gene sequencing. The potential of these genera to remove nitrate and degrade diclofenac was inferred, and the main enzymes potentially involved in this process were α-methylacyl-CoA racemase, long-chain fatty acid-CoA ligase, catalases and pseudoperoxidases.