Implementation of artificial neural networks (ANNs) to analysis of inter-taxa communities of benthic microorganisms and macroinvertebrates in a polluted stream

This study was performed to gain an understanding of the structural and functional relationships between inter-taxa communities (macroinvertebrates as consumers, and microbes as decomposers or preys for the invertebrates) in a polluted stream using artificial neural networks techniques. Sediment samples, carrying microorganisms (eubacteria) and macroinvertebrates, were seasonally collected from similar habitats in streams with different levels of pollution. Microbial community taxa and densities were determined using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA sequence analysis techniques. The identity and density of macroinvertebrates were concurrently determined. In general, differences were observed on grouping by self-organizing map (SOM) in polluted, clean and recovering sites based on the microbial densities, while the community patterns were partly dependent on the sampling period. A Spearman rank order correlation analysis revealed correlations of several eubacterial species with those of macroinvertebrates: a negative correlation was observed between Acidovorax sp. (from polluted sites) and Gammaridae (mostly from the clean site), while Herbaspirillum sp. and Janthinobacterium sp. appeared to have positive correlations with some macroinvertebrate species. The population dynamics of the tolerant texa, Tubificidae and Chironomidae, appeared to be related with changes in the densities of Acidovorax sp. This study revealed community relationships between macroinvertebrates and microorganisms, reflecting the connectivity between the two communities via the food chain. A further physio-ecological and symbiological study on the invertebrate-microorganism relationships will be required to understand the degradation and utilization of detritus in aquatic ecosystems as well as to elucidate the roles of the inter-taxa in the recovery of polluted aquatic environments.     

Analysis of N-nitrosamines and other nitro(so) compounds in water by high-performance liquid chromatography with post-column UV photolysis/Griess reaction

Despite their potential carcinogenicity and probable formation during water disinfection processes, little is known about the occurrence of other nitro(so) compounds than a few specific N-nitroso compounds such as N-nitrosodimethylamine (NDMA). An analytical method was developed to monitor various nitro(so) compounds including N-nitrosamines based on the Griess colorimetric determination of nitrite generated by UV-254 nm photolysis of nitro(so) compounds after separation by HPLC (HPLC-Post Column UV photolysis/Griess reaction (HPLC-PCUV)). To differentiate N-nitro(so) compounds (i.e. UV-labile) from other nitro(so) and N-containing compounds (i.e. UV-resistant), a pre-treatment was established by photolyzing solid-phase extracted samples at 254 nm (1000 mJ/cm²) and thus removing N-nitro(so) compounds selectively. Considering a 1000-fold concentration factor and extraction efficiencies (57–83%) during solid phase extraction, the method detection limits ranged from 4 to 28 ng/L for dimethylnitramine and eight N-nitrosamines (EPA 8270 nine nitrosamines mixture except for N-nitrosodiphenylamine). For four pool waters, the UV-resistant groups accounted for more than 78% of the estimated total concentration of nitro(so) and other N-containing compounds (6.1–48.6 nM). Only one unknown UV-labile compound was detected in one pool water (2.0–7.9 nM). NDMA was most frequently detected and N-nitrosodipropylamine (NDPA) and N-nitrosodibutylamine (NDBA) were additionally detected in one pool water. Chloramination of a secondary wastewater effluent with NDMA (0.2 nM) and UV-resistant compounds (7.9 nM) from a pilot-scale municipal wastewater treatment plant led to a significant formation of not only unidentified UV-resistant compounds (67.8 nM) and UV-labile compounds (14.6 nM), but also identified nitrosamines such as NDMA (4.3 nM), N-nitrosopiperidine (1.8 nM), NDPA (0.5 nM), and NDBA (0.5 nM). Overall, the novel HPLC-PCUV system is a powerful screening tool for the detection of (un)known N-nitro(so) as well as other nitro(so) and UV-induced nitrite-producing compounds.