Fluorescein diacetate hydrolytic activity as a sensitive tool to quantify nitrogen/sulfur gene content in urban river sediments in China

Abstract

The relative abundance of functional genes used to quantify the abundance of functional genes in communities is controversial. Quantitative PCR (qPCR) technology offers a powerful tool for quantifying functional gene abundance. However, humic substances can inhibit qPCR in sediment/soil samples. Therefore, finding a convenient and effective quantitative analysis method for sediment/soil samples is necessary. The functional genes and physicochemical properties in sediments with different-level pollutions were analyzed in this study. Correlations between physicochemical properties and the relative abundance of functional genes were used to test whether relative abundance in gene prediction quantifies the abundance of functional genes. The abundance of functional genes could be corrected by multiplying the fluorescein diacetate (FDA) hydrolytic rates by the relative abundance of functional genes since the FDA assay has been widely used as a rapid and sensitive method for quantifying microbial activity in sediments. Redundancy analysis showed significant interrelations between the functional genes and the physicochemical properties of sediments. The relative abundance of functional genes is unreliable for quantifying the abundance of functional genes because of the weak correlation (R < 0.5, P < 0.05) between different pollutants and the relative abundance of functional genes. However, a significant positive correlation between concentrations of different pollutants and the activities of associated enzymes was obtained (R > 0.933, P < 0.05), which revealed that the abundance of functional genes could be reliably quantified by the relative abundance and FDA hydrolytic rate. This study proposed an alternative method besides qPCR to quantify the absolute abundance of functional genes, which overcomes the problem of humic interference in the quantitative analysis of sediment/soil samples.

Keywords: Acidified volatile sulfides; Correlation analysis; Functional gene; High-throughput sequencing; Redundancy analysis; Sediment; Total nitrogen.