Metagenomic analysis of two enhanced biological phosphorus removal (EBPR) sludge communities

Enhanced biological phosphorus removal (EBPR) is one of the best-studied microbially mediated industrial processes because of its ecological and economic relevance. Despite this, it is not well understood at the metabolic level. Here we present a metagenomic analysis of two lab-scale EBPR sludges dominated by the uncultured bacterium, Candidatus Accumulibacter phosphatis.'' The analysis sheds light on several controversies in EBPR metabolic models and provides hypotheses explaining the dominance of A. phosphatis in this habitat, its lifestyle outside EBPR and probable cultivation requirements. Comparison of the same species from different EBPR sludges highlights recent evolutionary dynamics in the A. phosphatis genome that could be linked to mechanisms for environmental adaptation. In spite of an apparent lack of phylogenetic overlap in the flanking communities of the two sludges studied, common functional themes were found, at least one of them complementary to the inferred metabolism of the dominant organism. The present study provides a much needed blueprint for a systems-level understanding of EBPR and illustrates that metagenomics enables detailed, often novel, insights into even well-studied biological systems.

Development of a decision support system for the integrated control of membrane bioreactors

The work presented in this PhD thesis includes various partial studies aimed at developing a decision support system for membrane bioreactor integrated control. The decision support systems (DSS) have as a main goal to facilitate the operation of complex processes due to the multiple variables that are processed. For this reason, the research used has focused on aspects related to nutrient removal, and on the development of indicators or sensors capable of facilitating, automating and controlling the filtration process in an integrated way with the biological processes that taking place. Work has also been done on the design, development, implementation and validation of tools based on the knowledge made available by the automatic control and the supervision of the MBRs

Microbial quantification in activated sludge: the hits and misses

Since the implementation of the activated sludge process for treating wastewater, there has been a reliance on chemical and physical parameters to monitor the system. However, in biological nutrient removal (BNR) processes, the microorganisms responsible for some of the transformations should be used to monitor the processes with the overall goal to achieve better treatment performance. The development of in situ identification and rapid quantification techniques for key microorganisms involved in BNR are required to achieve this goal. This study explored the quantification of Nitrospira, a key organism in the oxidation of nitrite to nitrate in BNR. Two molecular genetic microbial quantification techniques were evaluated: real-time polymerase chain reaction (PCR) and fluorescence in situ hybridisation (FISH) followed by digital image analysis. A correlation between the Nitrospira quantitative data and the nitrate production rate, determined in batch tests, was attempted. The disadvantages and advantages of both methods will be discussed.

Use of stable-isotope probing, full-cycle rRNA analysis, and fluorescence in situ hybridization-microautoradiography to study a methanol-fed denitrifying microbial community

A denitrifying microbial consortium was enriched in an anoxically operated, methanol-fed sequencing batch reactor (SBR) fed with a mineral salts medium containing methanol as the sole carbon source and nitrate as the electron acceptor. The SBR was inoculated with sludge from a biological nutrient removal activated sludge plant exhibiting good denitrification. The SBR denitrification rate improved from less than 0.02 mg of NO3-.N mg of mixed-liquor volatile suspended solids (MLVSS)(-1) h(-1) to a steady-state value of 0.06 mg of NO3-.N mg of MLVSS-1 h(-1) over a 7-month operational period. At this time, the enriched microbial community was subjected to stable-isotope probing (SIP) with [C-13] methanol to biomark the DNA of the denitrifiers. The extracted [C-13]DNA and [C-12]DNA from the SIP experiment were separately subjected to full-cycle rRNA analysis. The dominant 16S rRNA gene phylotype (group A clones) in the [C-13]DNA clone library was closely related to those of the obligate methylotrophs Methylobacillus and Methylophilus in the order Methylophilales of the Betaproteobacteria (96 to 97% sequence identities), while the most abundant clone groups in the [C-12]DNA clone library mostly belonged to the family Saprospiraceae in the Bacteroidetes phylum. Oligonucleotide probes for use in fluorescence in situ hybridization (FISH) were designed to specifically target the group A clones and Methylophilales (probes DEN67 and MET1216, respectively) and the Saprospiraceae clones (probe SAP553). Application of these probes to the SBR biomass over the enrichment period demonstrated a strong correlation between the level of SBR denitrification and relative abundance of DEN67-targeted bacteria in the SBR community. By contrast, there was no correlation between the denitrification rate and the relative abundances of the well-known denitrifying genera Hyphomicrobium and Paracoccus or the Saprospiraceae clones visualized by FISH in the SBR biomass. FISH combined with microautoradiography independently confirmed that the DEN67-targeted cells were the dominant bacterial group capable of anoxic [C-14] methanol uptake in the enriched biomass. The well-known denitrification lag period in the methanol-fed SBR was shown to coincide with a lag phase in growth of the DEN67-targeted denitrifying population. We conclude that Methylophilales bacteria are the dominant denitrifiers in our SBR system and likely are important denitrifiers in full-scale methanol-fed denitrifying sludges.

Advances in distributed parameter approach to the dynamics and control of activated sludge processes for wastewater treatment

This paper presents a review of modelling and control of biological nutrient removal (BNR)-activated sludge processes for wastewater treatment using distributed parameter models described by partial differential equations (PDE). Numerical methods for solution to the BNR-activated sludge process dynamics are reviewed and these include method of lines, global orthogonal collocation and orthogonal collocation on finite elements. Fundamental techniques and conceptual advances of the distributed parameter approach to the dynamics and control of activated sludge processes are briefly described. A critical analysis on the advantages of the distributed parameter approach over the conventional modelling strategy in this paper shows that the activated sludge process is more adequately described by the former and the method is recommended for application to the wastewater industry (c) 2006 Elsevier Ltd. All rights reserved.