Detecting structural and functional differences in activated sludge bacterial communities originating from laboratory treatment of elementally and totally chlorine-free bleaching effluents

Abstract

The ability to differentiate functional and structural diversity of bacterial communities present in activated sludges adapted to elementally (ECF) and totally (TCF) chlorine-free bleaching effluents was evaluated. Community function was evaluated through substrate utilization patterns in BiologGN microplates, and taxonomic structure was evaluated by fluorescent in situ hybridization using probes targeting the Eubacteria; the alpha, beta, and gamma subclasses of the Proteobacteria; and gram-positive bacteria with high GC content. Over 6-week sampling periods, ECF-and TCF-adapted sludge bacterial communities presented reproducible substrate utilization patterns that through principal components (PCs) analysis, separated the ECF samples from the TCF samples. Application of the fluorescent in situ hybridization technique was complicated by the intense autofluorescence of the bleaching effluent sludge samples that interfered with detection of specific hybridization signals. The most notable difference in community structure detected using the chosen set of probes was the relatively greater proportion of cells of the alpha subclass in TCF sludge (27%) than in ECF sludge (6%). Nonspecific hybridization with beta and gamma probes was relatively high, but both sludges appeared to have similar proportions of cells of the beta (20-22%) and gamma (11-12%) subclasses. The two sludges presented relatively few gram-positive cells with high GC content (<0.2% of eubacterial counts). Differences in both metabolic potential and taxonomic structure of the microbial communities in the ECF- and TCF-activated sludges were detected. The kinetics of the development of these differences in treatment plants and their relationships with treatment efficiency and production process conditions should now be evaluated.

Pulp Mill Wastewater: Characteristics and Treatment

“…Additionally, the most remarkable differences between softwood-and hardwood-derived effluents are in the aromatic region. The aromatic lignin-derived structures such as syringyl and guaiacyl units are not important structural elements in HMW effluent materials from ECF bleaching of oxygen delignified hardwood kraft pulps, but are important in softwood HMW effluents [31,32]. Similarly, the results show that all HMW effluents contained carbohydrates.…”

“…Several authors [14,30,31] have worked in determining the molecular weight distribution of the components in the effluents. The importance of determining the molecular weight distribution comes from the fact that significant removal in the biological treatment system is achieved from the low molecular weight (LMW) material.…”

“…The HMW fraction contributed to approximately 40% of the total effluent load of COD both in softwood and hardwood ECF bleached pulps production, and about 30-40% to TCF bleached pulps effluents [30,31]. Additionally, the most remarkable differences between softwood-and hardwood-derived effluents are in the aromatic region.…”

“…Concerning the presence of carboxylic acids, the HMW samples showed high levels of these groups. They were formed due to the oxidation of lignin structures in the bleaching process [30][31][32].…”

Time-resolvable fluorescent conjugates for the detection of pathogens in environmental samples containing autofluorescent material

“…Autofluorescence is frequently encountered with biological samples and is not limited to those environmentally sourced, unwanted fluorescence can be introduced by methods used to prepare samples and formalin treatment of tissue sections has been reported to result in high levels of background autofluorescence 1 . Fluorescent in-situ hybridization (FISH) signals in bacteria can be weak, particularly when applied to the in-situ analysis of microbial communities where autofluorescing background has been reported to be a significant problem in such studies [1][2][3] . A method of overcoming the unpredictable nature of autofluorescence is to use the fluorescence lifetime of the probe as the discriminating parameter.…”