The treatment of wastewater is important for the removal pathogens, the removal of organic carbon, to Increase the aesthetic quality of the water and to eliminate the risk of eutrophication, which refers to the effects caused by the excessive release of nutrients Into the receiving water bodies (eg. Cyanobacterlal blooms, commonly referred to as blue-green algae). The activated sludge process is the biological treatment of wastewater with the objective of removing nutrients and particulate matter prior to discharge. However, many wastewater treatment plants can suffer from unstable performance and unpredictable breakdowns.
Current process prediction models are based on extensive modelling of the phenotypic data from pure-cultured organisms. However, It has been well established that cultured organisms do not always accurately represent the whole nature of the microbial community. Thus, there Is a need to modify the process
models likely leading to more efficient and reliable nutrient removal practices. This can only be achieved by in-depth structural and functional analyses of the microbial community, in the first instance using molecular techniques to determine the numerical abundance of the organisms. It is possible that accurate microbial abundance measurements could be used to predict process performance and monitoring strategies.
This study chose to develop molecular microbial methods for the quantification of Nitrospira-like organisms, as the target organisms, in full-scale activated sludge samples. Nitrospira-like organisms were shown to be the key organisms responsible for nitrite oxidation in the activated sludge process, which is a rate-limiting step in the removal of nitrogen from wastewater. The abundance and specific activity of these organisms Is critical in the design and operation of wastewater treatment plants as they have
a low growth rate, are as-yet uncultured and are highly sensitive to several environmental factors (eg, pH, dissolved oxygen, temperature, substrate concentration and toxic inhibitors). As a consequence the development of a rapid quantification method for use in routine monitoring could provide an early detection system for organism number decline and ultimately improve nutrient removal prediction models. This study also aimed to determine If the developed methods can be used to monitor Nitrospira-like cell numbers in full-scale wastewater treatment plants and to determine If these numbers correlate with specific cell activity. This study concentrated on the development of targeted methods including real-time PCR, quantitative competitive (QC)-PCR and quantitative fluorescence in situ hybridisation (Q-FISH).
Real-time polymerase chain reaction (PCR). Real-time PCR Is the detection and measurement of PCR
products in "real time" during the PCR process. Real-time PCR involves the use of conventional PCR primers, nucleotides and thermostable DNA polymerase for the PCR. In addition there is an oligonucleotide with an attached fluorescent reporter and quencher whose close proximity obviates the capacity of the fluorochrome to emit light if excited. The fluorescently-labelled oligonucleotide hybridises to the target DNA between the PCR primer sites. During the PCR, the exocatalytic activity of the DNA polymerase cleaves the probe from the target sequence, separating the quencher from the fluorochrome, allowing the fluorochrome to be excited and to emit light. This emitted light is then plotted as a function of the number of cycles and then compared to a standard curve to determine the number of templates in the sample.
In this study, a real-time PCR assay was developed for the quantification of Nitrospira-like organisms. Due to
design constraints however, only a subgroup of the group was targeted, known as the Nitrospira-ll sublineage. This assay was shown to be specific, sensitive, reproducible and reasonably accurate but the method fell short in being able to correlate cell numbers with specific activity measures. There are many theories why this occurred including the inaccuracy of the method, different cell activities and discrepancies In the DNA extraction method. The DNA extraction method and the effects the method had on the realtime PCR results was investigated and it was concluded that the Fast DNA® Spin Kit for Soil (BI0IOI, QBIoGene, CA) was the best method available due to the consistently high DNA yield. This method was further investigated and while reducing the sample size increased the amount of DNA extracted/mL of sample. It had little effect on the real-time PCR results. The reproducibility of the method to extract DNA from full-scale samples was investigated.
While the DNA concentration of the extracts was reproducible, the determined Nitrospira-II cell numbers were significantly different. This shows the unreproducible nature of the method to extract DNA from the same organisms each time. Until a reproducible and reliable DNA extraction method can be developed, this study concludes that to analyse samples using the Nitrospira-ll real-time PCR assay, the DNA extracts should be analysed using a replicate dilution analysis, as is performed by other researchers.
Quantitative Competitive PCR. Quantitative competitive PCR (QC-PCR) is an assay based on the competitive co-amplification of a target sequence, or wild-type template (WT) with a known amount of an internal standard (IS) in the one reaction tube. PCR products are analysed after the PCR has finished and the theory is that if the final ratio of WT to IS product concentration is one, then the Initial
template numbers were equivalent. QC-PCR eliminates the bias caused by the thermocycler, reaction mixture differences, tube to tube variations and the presence of inhibitors, i.e. If inhibitors were present in the sample they would affect both the PCR of both the WT and IS.
A QC-PCR assay was developed for the quantification of Nitrospira as an alternative to the real-time PCR assay, as it eliminates the effects of PCR inhibitors. This method proved unsuccessful and showed a lower detection limit of 103 cells. This method is widely used for many different organisms and may prove to be useful In the quantification of activated sludge organisms, however, further evaluation of amplicon detection methods and IS construction is required.
Quantitative Fluorescence in situ Hybridisation. Fluorescence in situ hybridisation (FISH) is a technique
which is used to identify, visually monitor and determine the spatial distribution of microorganisms in their habitats. FISH is frequently used as a quantitative tool. However, many studies focus on manual counting of cells for enumeration. The biovolume measurement allows rapid quantification of a large number of bacteria without the requirement of single cell recognition and reports the relative abundance of an organism with respect to all bacteria present in the sample. In this study, a Q-FISH protocol was developed based on biovolume measurements for the quantification of Nitrospira cells from full-scale activated sludge samples. The results showed that the hybridisation method required no further modification. However maximising the number of cells analysed decreased the variability of the results while not affecting the relative abundance of the organism. The accuracy of the biovolume measurements was addressed by measuring the standard error of the method
and this was found to be 0.99%. These results indicate that the method is reasonably accurate in the determination of the relative abundance of Nitrospira cells in full-scale activated sludge samples. This study showed that the relative abundance of Nitrospira cells determined using the developed Q-FISH procedure proved the most effective method of monitoring the Nitrospira population and correlation of the nitrite oxidation activity.
To increase the stability and efficiency of nutrient removal practices in the activated sludge processes, in-depth structural and functional analyses of the microbial community using molecular techniques are required. The methods developed In this thesis go along way to providing solutions but solutions to the problem will only come with combining both molecular and functional quantification methods, to determine not only the microbial ecology of the treatment system but
the specific activity of many of the organisms implicated as the being responsible for key nutrient transformations.