Nitrate Bioreduction under Cr(VI) Stress: Crossroads of Denitrification and Dissimilatory Nitrate Reduction to Ammonium

Abstract

This study explored the response of NO3 –-N bioreduction to Cr­(VI) stress, including reduction efficiency and the pathways involved (denitrification and dissimilatory nitrate reduction to ammonium (DNRA)). Different response patterns of NO3 –-N conversion were proposed under Cr­(VI) suppress (0, 0.5, 5, 15, 30, 50, and 80 mg/L) by evaluating Cr­(VI) dose dependence, toxicity accumulation, bioelectron behavior, and microbial community structure. Cr­(VI) concentrations of >30 mg/L rapidly inhibited NO3 –-N removal and immediately induced DNRA. However, denitrification completely dominated the NO3 –-N reduction pathway at Cr­(VI) concentrations of <15 mg/L. Therefore, 30 and 80 mg/L Cr­(VI) (R4 and R6) were selected to explore the selection of the different NO3 –-N removal pathways. The pathway of NO3 –-N reduction at 30 mg/L Cr­(VI) exhibited continuous adaptation, wherein the coexistence of denitrification (51.7%) and DNRA (13.6%) was achieved by regulating the distribution of denitrifiers (37.6%) and DNRA bacteria (32.8%). Comparatively, DNRA gradually replaced denitrification at 80 mg/L Cr­(VI). The intracellular Cr­(III) accumulation in R6 was 6.60-fold greater than in R4, causing more severe oxidant injury and cell death. The activated NO3 –-N reduction pathway depended on the value of nitrite reductase activity/nitrate reductase activity, with 0.84–1.08 associated with DNRA activation and 1.48–1.57 with DNRA predominance. Although Cr­(VI) increased microbial community richness and improved community structure stability, the inhibition or death of nitrogen-reducing microorganisms caused by Cr­(VI) decreased NO3 –-N reduction efficiency.

Microbial Insights into Shale Gas Wastewater from the Sichuan Basin: Diversity, Potential Functions, and Implications

“…This analysis, along with subsequent plotting, was conducted in R (version 4.3.2) . The Functional Annotation of Prokaryotic Taxa (FAPROTAX) was utilized to predict the potential functions of microbial communities. , The iNAP platform was employed to construct molecular ecological networks . This analysis was conducted using stochastic matrix theory-based Spearman’s correlations, utilizing the relative abundance of OTUs for bacteria, archaea, and eukaryotes.…”