Inhibitory effect of cyanide on wastewater nitrification determined using SOUR and RNA-based gene-specific assays.

UNLABELLED

The effect of cyanide (CN(-) ) on nitrification was examined with samples from nitrifying bacterial enrichments using two different approaches: by measuring substrate (ammonia) specific oxygen uptake rates (SOUR), and by using RT-qPCR to quantify the transcripts of functional genes involved in nitrification. The nitrifying bioreactor was operated as a continuous reactor with a 24 h hydraulic retention time. The samples were exposed in batch vessels to cyanide for a period of 12 h. The concentrations of CN(-) used in the batch assays were 0·03, 0·06, 0·1 and 1·0 mg l(-1) . There was considerable decrease in SOUR with increasing dosages of CN(-) . A decrease of more than 50% in nitrification activity was observed at 0·1 mg l(-1) CN(-) . Based on the RT-qPCR data, there was notable reduction in the transcript levels of amoA and hao for increasing CN(-) dosage, which corresponded well with the ammonia oxidation activity measured via SOUR. The inhibitory effect of cyanide may be attributed to the affinity of cyanide to bind ferric haeme proteins, which disrupt protein structure and function. The correspondence between the relative expression of functional genes and SOUR shown in this study demonstrates the efficacy of RNA-based function-specific assays for better understanding of the effect of toxic compounds on nitrification activity in wastewater.

SIGNIFICANCE AND IMPACT OF THE STUDY

The effect of cyanide on nitrifying bacteria was characterized by measuring physiological and transcriptional response. Cyanide was inhibitory to nitrification at concentrations that may be found in industrial waste. The RNA-based function-specific assays represent a mechanistic approach for better understanding the effect of toxic compounds on nitrification activity in wastewater. Moreover, the relative abundance of RNA transcripts can be used to closely track in situ nitrifying bacterial activity which can be used to predict inhibition events, thereby providing a metric to potentially improve performance of wastewater nitrifying systems.