Development of a novel titration and off-gas analysis (TOGA) sensor for study of biological processes in wastewater treatment systems

The development of the new TOGA (titration and off-gas analysis) sensor for the detailed study of biological processes in wastewater treatment systems is outlined. The main innovation of the sensor is the amalgamation of titrimetric and off-gas measurement techniques. The resulting measured signals are: hydrogen ion production rate (HPR), oxygen transfer rate (OTR), nitrogen transfer rate (NTR), and carbon dioxide transfer rate (CTR). While OTR and NTR are applicable to aerobic and anoxic conditions, respectively, HPR and CTR are useful signals under all of the conditions found in biological wastewater treatment systems, namely, aerobic, anoxic and anaerobic. The sensor is therefore a powerful tool for studying the key biological processes under all these conditions. A major benefit from the integration of the titrimetric and off-gas analysis methods is that the acid/base buffering systems, in particular the bicarbonate system, are properly accounted for. Experimental data resulting from the TOGA sensor in aerobic, anoxic, and anaerobic conditions demonstrates the strength of the new sensor. In the aerobic environment, carbon oxidation (using acetate as an example carbon source) and nitrification are studied. Both the carbon and ammonia removal rates measured by the sensor compare very well with those obtained from off-line chemical analysis. Further, the aerobic acetate removal process is examined at a fundamental level using the metabolic pathway and stoichiometry established in the literature, whereby the rate of formation of storage products is identified. Under anoxic conditions, the denitrification process is monitored and, again, the measured rate of nitrogen gas transfer (NTR) matches well with the removal of the oxidised nitrogen compounds (measured chemically). In the anaerobic environment, the enhanced biological phosphorus process was investigated. In this case, the measured sensor signals (HPR and CTR) resulting from acetate uptake were used to determine the ratio of the rates of carbon dioxide production by competing groups of microorganisms, which consequently is a measure of the activity of these organisms. The sensor involves the use of expensive equipment such as a mass spectrometer and requires special gases to operate, thus incurring significant capital and operational costs. This makes the sensor more an advanced laboratory tool than an on-line sensor. (C) 2003 Wiley Periodicals, Inc.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Robust multivariable control of complex biological processes

This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

Modelling biological processes under anaerobic conditions through integrating titrimetric and off-gas measurements - applied to EBPR systems

An innovative method for modelling biological processes under anaerobic conditions is presented and discussed. The method is based on titrimetric and off-gas measurements. Titrimetric data is recorded as the addition rate of hydroxyl ions or protons that is required to maintain pH in a bioreactor at a constant level. An off-gas analysis arrangement measures, among other things, the transfer rate of carbon dioxide. The integration of these signals results in a continuous signal which is solely related to the biological reactions. When coupled with a mathematical model of the biological reactions, the signal allows a detailed characterisation of these reactions, which would otherwise be difficult to achieve. Two applications of the method to the enhanced biological phosphorus removal processes are presented and discussed to demonstrate the principle and effectiveness of the method.

Combined hydraulic and biological modelling and full-scale validation of SBR process

The biological reactions during the settling and decant periods of Sequencing Batch Reactors (SBRs) are generally ignored as they are not easily measured or described by modelling approaches. However, important processes are taking place, and in particular when the influent is fed into the bottom of the reactor at the same time (one of the main features of the UniFed process), the inclusion of these stages is crucial for accurate process predictions. Due to the vertical stratification of both liquid and solid components, a one-dimensional hydraulic model is combined with a modified ASM2d biological model to allow the prediction of settling velocity, sludge concentration, soluble components and biological processes during the non-mixed periods of the SBR. The model is calibrated on a full-scale UniFed SBR system with tracer breakthrough tests, depth profiles of particulate and soluble compounds and measurements of the key components during the mixed aerobic period. This model is then validated against results from an independent experimental period with considerably different operating parameters. In both cases, the model is able to accurately predict the stratification and most of the biological reactions occurring in the sludge blanket and the supernatant during the non-mixed periods. Together with a correct description of the mixed aerobic period, a good prediction of the overall SBR performance can be achieved.

A dynamic mathematical model for sequential leach bed anaerobic digestion of organic fraction of municipal solid waste

A mathematical model that describes the operation of a sequential leach bed process for anaerobic digestion of organic fraction of municipal solid waste (MSW) is developed and validated. This model assumes that ultimate mineralisation of the organic component of the waste occurs in three steps, namely solubilisation of particulate matter, fermentation to volatile organic acids (modelled as acetic acid) along with liberation of carbon dioxide and hydrogen, and methanogenesis from acetate and hydrogen. The model incorporates the ionic equilibrium equations arising due to dissolution of carbon dioxide, generation of alkalinity from breakdown of solids and dissociation of acetic acid. Rather than a charge balance, a mass balance on the hydronium and hydroxide ions is used to calculate pH. The flow of liquid through the bed is modelled as occurring through two zones-a permeable zone with high flushing rates and the other more stagnant. Some of the kinetic parameters for the biological processes were obtained from batch MSW digestion experiments. The parameters for flow model were obtained from residence time distribution studies conducted using tritium as a tracer. The model was validated using data from leach bed digestion experiments in which a leachate volume equal to 10% of the fresh waste bed volume was sequenced. The model was then tested, without altering any kinetic or flow parameters, by varying volume of leachate that is sequenced between the beds. Simulations for sequencing/recirculating 5 and 30% of the bed volume are presented and compared with experimental results. (C) 2002 Elsevier Science B.V. All rights reserved.

Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

Effect of free ammonia and free nitrous acid concentration on the anabolic and catabolic processes of an enriched Nitrosomonas culture

The effects of free ammonia (FA; NH3) and free nitrous acid (FNA; HNO2) concentrations on the metabolisms of an enriched ammonia oxidizing bacteria (AOB) culture were investigated using a method allowing the decoupling of growth and energy generation processes. A lab-scale sequencing batch reactor (SBR) was operated for the enrichment of an AOB culture. Fluorescent in-situ hybridization (FISH) analysis showed that 82% of the bacterial population in the SBR bound to the NEU probe specifically designed for Nitrosomonas europaea. Batch tests were carried out to measure the oxygen and ammonium consumption rates by the culture at various FA and FNA levels, in the presence or absence of inorganic carbon (CO2, HCO3, and CO32-). It was revealed that FA of up to 16.0 mgNH(3)-N (.) L-1, which was the highest concentration used in this study, did not have any inhibitory effect on either the catabolic or anabolic processes of the Nitrosomonas culture. In contrast, FNA inhibited both the growth and energy production capabilities of the Nitrosomonas culture. The inhibition on growth initiated at approximately 0.10 mgHNO(2)-(NL-1)-L-., and the data suggested that the biosynthesis was completely stopped at an FNA concentration of 0.40 mgHNO(2)-N (.) L-1. The inhibition on energy generation initiated at a slightly lower level but the Nitrosomonas culture was still oxidizing ammonia at half of the maximum rate at an FNA concentration of 0.50-0.63 mgHNO(2)-N (.) L-1. The affinity constant of the Nitrosomonas culture with respect to ammonia was determined to be 0.36 mgNH3-N (.) L-1, independent of the presence or absence of inorganic carbon. (c) 2006 Wiley Periodicals, Inc.

Emotions at multiple levels: An integration

Weiss and Isen have provided many supportive comments about the multi-level perspective, but also found limitations. Isen noted the importance of integrating affect, cognition, and motivation. Weiss commented similarly that the model lacked an integrating “thread.” He suggested that, to be truly multilevel, each level should constrain processes at other levels, and also provide guidance for the development of new concepts. Weiss also noted that the focus on biological processes was a strength of the model. I respond by suggesting that these very biological processes may constitute the “missing” thread. To illustrate this, I discuss some of the recent research on emotions in organizational settings, and argue that biology both constrains and guides theory at each level of the model. Based on this proposition, I revisit each of the five levels in the model, to demonstrate how this integration can be accomplished in this fashion. Finally, I address two additional points: aggregation bias, and the possibility of extending the model to include higher levels of industry and region.

Platyhelminth phylogenetics - a key to understanding parasitism?

The comparative method, the inference of biological processes from phylogenetic patterns, is founded on the reliability of the phylogenetic tree. In attempting to apply the comparative method to the understanding of the evolution of parasitism in the phylum Platyhelminthes, we have highlighted several points we consider to be of value along with many problems. We discuss four of these topics. Firstly, we view the group at a phylum level, in particular discussing the importance of establishing the sister taxon to the obligate parasite group, the Neodermata, for addressing such questions as the monophyly, parasitism or the endo or ectoparasitic nature of the early parasites. The variety of non-congruent phylogenetic trees presented so far, utilising either or both morphological and molecular data, gives rise to the suggestion that any evolutionary scenarios presented at this stage be treated as interesting hypotheses rather than well-supported theories. Our second point of discussion is the conflict between morphological and molecular estimates of monogenean evolution. The Monogenea presents several well-established morphological autapomorphies, such that morphology consistently estimates the group as monophyletic, whereas molecular sequence analyses indicate paraphyly, with different genes giving different topologies. We discuss the problem of reconciling gene and species trees. Thirdly, we use recent phylogenetic results on the tapeworms to interpret the evolution of strobilation, proglottization, segmentation and scolex structure. In relation to the latter, the results presented indicate that the higher cestodes are diphyletic, with one branch difossate and the other tetrafossate. Finally, we use a SSU rDNA phylogenetic tree of the Trematoda as a basis for the discussion of an aspect of the digenean life-cycle, namely the nature of the first intermediate host. Frequent episodes of host-switching, between gastropod and bivalve hosts or even into annelids, are indicated.

Progressive Age-Related Changes Similar to Age-Related Macular Degeneration in a Transgenic Mouse Model

Age-related macular degeneration (AMD) is the major cause of blindness in the developed world. its pathomechanism is unknown and its late onset, complex genetics and strong environmental components have all hampered investigations. Here we demonstrate the development of an animal model for AMD that reproduces features associated with geographic atrophy, a transgenic mouse line (mcd/mcd) expressing a mutated form of cathepsin D that is enzymatically inactive thus impairing processing of phagocytosed photoreceptor outer segments in the retinal pigment epithelial (RPE) cells. Pigmentary changes indicating RPE cell atrophy and a decreased response to flash electroretinograms were observed in 11- to 12-month-old mcd/mcd mice. Histological studies showed RPE cell proliferation, photoreceptor degeneration, shortening of photoreceptor outer segments, and accumulation of immunoreactive photoreceptor breakdown products in the RPE cells. An accelerated photoreceptor cell death was detected in 12-month-old mcd/mcd mice. Transmission electron microscopy demonstrated presence of basal laminar and linear deposits that are considered to be the hallmarks of AMD. Small hard drusen associated with human age-related maculopathy were absent in the mcd/mcd mouse model at the ages analyzed. in summary, this model presents several features of AMD, thus providing a valuable tool for investigating the underlying biological processes and pathomechanism of AMD.

Testing the sediment-trapping paradigm of seagrass: Do seagrasses influence nutrient status and sediment structure in tropical intertidal environments?

Seagrass meadows are considered important for sediment trapping and sediment stabilisation. Deposition of fine sediments and associated adsorbed nutrients is considered an important part of the chemical and biological processes attributed to seagrass communities. This paradigm was based on work in temperate regions on Zostera marina and in tropical regions on Thalassia testudinum, two species that maintain relatively high biomass, stable meadows. The current study investigates this concept for three species of intertidal tropical seagrass meadows in northeastern Australia. Sediment structure and nutrient status did not differ between vegetated and unvegated habitats in intertidal areas within the central region of the Great Barrier Reef World Heritage Area. The 'trapping' functions that have been attributed to seagrasses need to be re-assessed for a variety of locations and species before they can be accepted as dogma. In tropical Australia, intertidal meadows are predominantly ephemeral and comprised of structurally small species of low biomass. Consequently, sediment trapping within these meadows is largely insignificant.

Systematic characterization of the zinc-finger-containing proteins in the mouse transcriptome

Zinc-finger-containing proteins can be classified into evolutionary and functionally divergent protein families that share one or more domains in which a zinc ion is tetrahedrally coordinated by cysteines and histidines. The zinc finger domain defines one of the largest protein superfamilies in mammalian genomes; 46 different conserved zinc finger domains are listed in InterPro (http://www.ebi.ac.uk/InterPro). Zinc finger proteins can bind to DNA, RNA, other proteins, or lipids as a modular domain in combination with other conserved structures. Owing to this combinatorial diversity, different members of zinc finger superfamilies contribute to many distinct cellular processes, including transcriptional regulation, mRNA stability and processing, and protein turnover. Accordingly, mutations of zinc finger genes lead to aberrations in a broad spectrum of biological processes such as development, differentiation, apoptosis, and immunological responses. This study provides the first comprehensive classification of zinc finger proteins in a mammalian transcriptome. Specific detailed analysis of the SP/Kruppel-like factors and the E3 ubiquitin-ligase RING-H2 families illustrates the importance of such an analysis for a more comprehensive functional classification of large protein families. We describe the characterization of a new family of C2H2 zinc-finger-containing proteins and a new conserved domain characteristic of this family, the identification and characterization of Sp8, a new member of the Sp family of transcriptional regulators, and the identification of five new RING-H2 proteins.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.