Maximizing microbial perchlorate degradation using a genetic algorithm: consortia optimization.

Microorganisms in consortia perform many tasks more effectively than individual organisms and in addition grow more rapidly and in greater abundance. In this work, experimental datasets were assembled consisting of all possible selected combinations of perchlorate reducing strains of microorganisms and their perchlorate degradation rates were evaluated. A genetic algorithm (GA) methodology was successfully applied to define sets of microbial strains to achieve maximum rates of perchlorate degradation. Over the course of twenty generations of optimization using a GA, we saw a statistically significant 2.06 and 4.08-fold increase in average perchlorate degradation rates by consortia constructed using solely the perchlorate reducing bacteria (PRB) and by consortia consisting of PRB and accompanying organisms that did not degrade perchlorate, respectively. The comparison of kinetic rates constant in two types of microbial consortia additionally showed marked increases.

Effects of glucose on the performance of enhanced biological phosphorus removal activated sludge enriched with acetate.

The effects of glucose on enhanced biological phosphorus removal (EBPR) activated sludge enriched with acetate was investigated using sequencing batch reactors. A glucose/acetate mixture was serially added to the test reactor in ratios of 25/75%, 50/50%, and 75/25% and the EBPR activity was compared to the control reactor fed with 100% acetate. P removal increased at a statistically significant level to a near-complete in the test reactor when the mixture increased to 50/50%. However, EBPR deteriorated when the glucose/acetate mixture increased to 75/25% in the test reactor and when the control reactor abruptly switched to 100% glucose. These results, in contrast to the EBPR conventional wisdom, suggest that the addition of glucose at moderate levels in wastewaters does not impede and may enhance EBPR, and that glucose waste products should be explored as an economical sustainable alternative when COD enhancement of EBPR is needed.

Maximizing microbial degradation of perchlorate using a genetic algorithm: Media optimization.

Microbial communities are under constant influence of physical and chemical components in ecosystems. Shifts in conditions such as pH, temperature or carbon source concentration can translate into shifts in overall ecosystem functioning. These conditions can be manipulated in a laboratory setup using evolutionary computation methods such as genetic algorithms (GAs). In work described here, a GA methodology was successfully applied to define sets of environmental conditions for microbial enrichments and pure cultures to achieve maximum rates of perchlorate degradation. Over the course of 11 generations of optimization using a GA, we saw a statistically significant 16.45 and 16.76-fold increases in average perchlorate degradation rates by Dechlorosoma sp. strain KJ and Dechloromonas sp. strain Miss R, respectively. For two bacterial consortia, Pl6 and Cw3, 5.79 and 5.75-fold increases in average perchlorate degradation were noted. Comparison of zero-order kinetic rate constants for environmental conditions in GA-determined first and last generations of all bacterial cultures additionally showed marked increases.

Research advances and challenges in the microbiology of enhanced biological phosphorus removal--a critical review.

Enhanced biological phosphorus removal (EBPR) is a well-established technology for removing phosphorus from wastewater. However, the process remains operationally unstable in many systems, primarily because there is a lack of understanding regarding the microbiology of EBPR. This paper presents a review of advances made in the study of EBPR microbiology and focuses on the identification, enrichment, classification, morphology, and metabolic capacity of polyphosphate- and glycogen-accumulating organisms. The paper also highlights knowledge gaps and research challenges in the field of EBPR microbiology. Based on the review, the following recommendations regarding the future direction of EBPR microbial research were developed: (1) shifting from a reductionist approach to a more holistic system-based approach, (2) using a combination of culture-dependent and culture-independent techniques in characterizing microbial composition, (3) integrating ecological principles into system design to enhance stability, and (4) reexamining current theoretical explanations of why and how EBPR occurs.

Simultaneous abiotic reduction-biotic oxidation in a microbial-MnO2-catalyzed Fenton-like system.

The possibility of simultaneous activity of superoxide-mediated transformations and heterotrophic aerobic bacterial metabolism was investigated in catalyzed H(2)O(2) propagations (CHP; i.e., modified Fenton's reagent) systems containing Escherichia coli. Two probe compounds were used: glucose for the detection of heterotrophic metabolism of E. coli, and tetrachloromethane (CCl(4)) for the detection of superoxide generated in a MnO(2)-catalyzed CHP system. In the MnO(2)-catalyzed CHP system without bacteria, only CCl(4) loss was observed; in contrast, only glucose degradation occurred E. coli systems without CHP reagents. In combined microbial-MnO(2) CHP reactions, loss of both probes was observed. Glucose assimilation decreased and CCl(4) transformation increased as a function of H(2)O(2) concentration. Central composite rotatable experimental designs were used to determine that the conditions providing maximum simultaneous abiotic-biotic reactions were a biomass level of 10(9)CFU/mL, 0.5mM H(2)O(2), and 0.5 g MnO(2). These results demonstrate that bacterial metabolism can occur in the presence of superoxide-mediated transformations. Such coexisting reactions may occur when H(2)O(2) is injected into MnO(2)-rich regions of the subsurface as a microbial oxygen source or for in situ oxidation; however, process control of such coexisting transformations may be difficult to achieve in the subsurface due to heterogeneity. Alternatively, hybrid abiotic reduction-biotic oxidation systems could be used for the treatment of industrial effluents or dilute solvent wastes that contain traces of highly halogenated compounds.

A method for assaying perchlorate concentration in microbial cultures using the fluorescent dye resazurin.

Low concentrations (microg/L) of the perchlorate anion, ClO(4)(-), have been measured in surface and ground water supplies in many locations throughout the United States. Perchlorate is known to affect the function of the thyroid gland in mammals and its toxicity primarily results from its inhibition of thyroid hormone output. The major sources of perchlorate contamination in surface and ground waters are defense contractors, military installations, propellant manufacturers and agriculture. The currently accepted method of perchlorate analysis, recommended by the US EPA, is neither fast nor easy to use and requires purchase of an expensive high performance ion chromatograph (IC). The novel method described here uses dye resazurin to measure perchlorate reduction by bacterial cultures and bacterial consortia in a high-throughput, multi-well, culture plate format. The method is based on the observation that perchlorate reduction and the decrease of resazurin fluorescence occur simultaneously in perchlorate degrading cultures. The bioassays were performed in anaerobic serum bottles or 96-well plates with constant shaking, using a minimal ATCC medium with 10 mM acetate as electron donor/carbon source and 200 ppm perchlorate as an electron acceptor. Fluorescence measurements with excitation at 570 nm and emission at 590 nm were taken in 20 min intervals. Changes in perchlorate concentration were confirmed using IC. Based on the experimental data, a simple model showing the correlation between perchlorate concentration in microbial culture and resazurin fluorescence level was proposed. Other dyes including redox indicators, reactive azo dyes and electron shuttle chemicals were also tested for comparison and were found less useful.

Heavy metals removal from mine runoff using compost bioreactors.

Permeable bioreactors have gained both research and management attention as viable methods for treating mine runoff waters. We examined the operation of a field-scale bioreactor (containing mixed compost, straw and gravel) for treatment of runoff from the Mother Load (ML) mine in northern Idaho, U.S. and compared it to an experimental laboratory-scale reactor, containing a similar matrix and treating similar mine runoff water. In general both reactors were efficient in removing most of the metals assayed, Al, As, Cd, Fe, Ni, Pb and Zn, with the exception of Mn. Both systems showed evidence of bacterial-mediated sulphate reduction and concomitant metal sulphide complexes. However, the experimental laboratory bioreactor showed greater proportions of immobile metals reductions than did the ML bioreactor, presumably due to the greater action of sulphate-reducing bacteria. The major metal removal mechanism in the ML bioreactor was surmised to be adsorption. Differences in metal removal mechanisms between the reactors were hypothesized to be due to fluctuating hydraulic residence times at the ML site, in turn, due to unregulated runoff flow.

Development of drinking water standards for perchlorate in the United States.

Perchlorate, an anion that originates as a contaminant in ground and surface waters, is both naturally occurring and manmade. Because of its toxicity, there has been increased interest in setting drinking water safety standards and in health effects when perchlorate is present at low (parts per billion (ppb)) levels. In January 2009, the EPA issued a heath advisory to assist state and local officials in addressing local contamination of perchlorate in drinking water. The interim health advisory level of 15 micrograms per liter (microg/L), or ppb, is based on the reference dose recommended by the National Research Council (NRC) of the National Academy of Sciences (NAS). This paper describes scope and extent of contaminant issues and a legal process of setting standards for perchlorate concentration in drinking water in the United States of America.

Using a genetic algorithm to drive a microbial ecosystem in a desirable direction.

The functioning of natural microbial ecosystems is influenced by various biotic and abiotic conditions. The careful experimental manipulation of environmental conditions can drive microbial ecosystems toward exhibiting desirable types of functionality. Such manipulations can be systematically approached by viewing them as a combinatorial optimization problem, in which the optimal configuration of environmental conditions is sought. Such an effort requires a sound optimization technique. Genetic algorithms are a class of optimization methods that should be suitable for such a task because they can deal with multiple interacting variables and with experimental noise and because they do not require an intricate understanding or modelling of the ecosystem of interest. We propose the use of genetic algorithms to drive undefined microbial ecosystems in desirable directions by combinatorially optimizing sets of environmental conditions. We tested this approach in a model system where the microbial ecosystem of a human saliva sample was manipulated in successive steps to display increasing amounts of azo dye decoloration. The results of our experiments indicated that a genetic algorithm was capable of optimizing ecosystem function by manipulating the presence or absence of a set of 10 chemical supplements. Genetic algorithms hold promise for use as a tool in environmental microbiology for the efficient control of the functioning of natural and undefined microbial ecosystems.

Demonstrating the suitability of genetic algorithms for driving microbial ecosystems in desirable directions.

The functioning of natural microbial ecosystems is determined by biotic interactions, which are in turn influenced by abiotic environmental conditions. Direct experimental manipulation of such conditions can be used to purposefully drive ecosystems toward exhibiting desirable functions. When a set of environmental conditions can be manipulated to be present at a discrete number of levels, finding the right combination of conditions to obtain the optimal desired effect becomes a typical combinatorial optimisation problem. Genetic algorithms are a class of robust and flexible search and optimisation techniques from the field of computer science that may be very suitable for such a task. To verify this idea, datasets containing growth levels of the total microbial community of four different natural microbial ecosystems in response to all possible combinations of a set of five chemical supplements were obtained. Subsequently, the ability of a genetic algorithm to search this parameter space for combinations of supplements driving the microbial communities to high levels of growth was compared to that of a random search, a local search, and a hill-climbing algorithm, three intuitive alternative optimisation approaches. The results indicate that a genetic algorithm is very suitable for driving microbial ecosystems in desirable directions, which opens opportunities for both fundamental ecological research and industrial applications.

A bioremediation approach using natural transformation in pure-culture and mixed-population biofilms.

Bacterial transformation by naked DNA is thought to contribute to gene transfer and microbial evolution within natural environments. In nature many microbial communities exist as complex assemblages known as biofilms where genetic exchange is facilitated. It may be possible to take advantage of natural transformation processes to modify the phenotypes of biofilm communities giving them specific and desirable functions. Work described here shows that biofilms composed of either pure cultures or mixed populations can be transformed with specific catabolic genes such that the communities acquire the ability to degrade a particular xenobiotic compound. Biofilms were transformed by plasmids bearing genes encoding green fluorescent protein (mut2) and/or atrazine chlorohydrolase (atzA). Confocal microscopy was used to quantify the number of transformants expressing mut2 in the biofilms. Degradation of atrazine by expressed atzA was quantified by tandem mass spectrometry. PCR analysis was performed to confirm the presence of atzA in transformed biofilms. These results indicate that it should be possible to use natural transformation to enhance bioremediation processes performed by biofilms.

Use of stochastic models to assess the effect of environmental factors on microbial growth.

We present a novel application of a stochastic ecological model to the study and analysis of microbial growth dynamics as influenced by environmental conditions in an extensive experimental data set. The model proved to be useful in bridging the gap between theoretical ideas in ecology and an applied problem in microbiology. The data consisted of recorded growth curves of Escherichia coli grown in triplicate in a base medium with all 32 possible combinations of five supplements: glucose, NH(4)Cl, HCl, EDTA, and NaCl. The potential complexity of 2(5) experimental treatments and their effects was reduced to 2(2) as just the metal chelator EDTA, the presumed osmotic pressure imposed by NaCl, and the interaction between these two factors were enough to explain the variability seen in the data. The statistical analysis showed that the positive and negative effects of the five chemical supplements and their combinations were directly translated into an increase or decrease in time required to attain stationary phase and the population size at which the stationary phase started. The stochastic ecological model proved to be useful, as it effectively explained and summarized the uncertainty seen in the recorded growth curves. Our findings have broad implications for both basic and applied research and illustrate how stochastic mathematical modeling coupled with rigorous statistical methods can be of great assistance in understanding basic processes in microbial ecology.

Coupled abiotic-biotic mineralization of 2,4,6-trinitrotoluene (TNT) in soil slurry.

The explosive 2,4,6-trinitrotoluene (TNT) is a contaminant of soils and ground waters worldwide. To help alleviate such environmental contamination, we investigated a coupled abiotic-biotic treatment scheme for remediating TNT-contaminated soil in slurry solutions. Two types of soil were used (sandy and silt loam) to simulate different soils that might be found at actual sites. These soils were subsequently contaminated with 5000 mg kg(-1) TNT. Mineralization of TNT was initially optimized for minimum reactant use (Fe(3+) and H(2)O(2)) and maximum soil slurry percentage (percent solids) using modified Fenton reactions conducted in the absence of light followed by the addition of an uncharacterized aerobic biomass. Greater than 97% TNT degradation was observed under optimum reaction conditions for both soils. Using two optimum reactant concentrations for each soil, coupled abiotic-biotic reactions showed an increase in TNT mineralization, from 41 to 73% and 34 to 64% in the sandy soil (10 and 20% slurry, respectively, 1470 mM H(2)O(2)), and increases from 12 to 23% and 13 to 28% in the silt loam soil (5% slurry, 294 and 1470 mM H(2)O(2), respectively). These results show promise in the use of combined abiotic-biotic treatment processes for soils contaminated with high concentrations of TNT.

Studies on nitroaromatic compound degradation in modified Fenton reactions by electrospray ionization tandem mass spectrometry (ESI-MS-MS).

Degradation products resulting from modified Fenton reactions with the nitroaromatic compounds trinitrotoluene (TNT) and trinitrobenzene (TNB) were identified by electrospray ionization tandem mass spectrometry (ESI-MS-MS). Several hydroperoxide adducts were tentatively identified as initial, one-electron reduction products of TNT and tandem mass spectrometry confirmed their structure. A transformation pathway of TNT, resulting from reactions with oxygen radical species generated by the modified Fenton reaction, was proposed.

Coupled abiotic-biotic mineralization of 2,4,6-trinitrotoluene (TNT).

Munitions wastes such as TNT are widespread contaminants in soils and ground waters. We investigated a coupled abiotic-biotic treatment scheme for remediation of aqueous solutions of TNT. Mineralization of aqueous TNT (0.22 mM) was initially optimized with minimum reactant use (Fe3+ and H2O2) in light-assisted and dark, modified Fenton reactions at acidic and neutral pH. Complete TNT degradation occurred under all reaction conditions within 24 h. Using the optimum reactant concentrations, coupled abiotic-biotic reactions showed an increase in TNT mineralization, from 47 to 80%, after biomass addition to the acidic, dark Fenton-like reaction. Comparable increases of TNT mineralization were observed under neutral pH with similar reaction conditions. In light-assisted Fenton-like reactions at neutral pH, no increase in cumulative TNT mineralization (66%) was seen in coupled abiotic-biotic reactions. Abiotic photo-Fenton-like reactions alone, at acidic pH, produced complete TNT mineralization and required no biotic assistance. While light-enhanced Fenton reactions alone can provide high levels of TNT mineralization, the dark abiotic-biotic reaction scheme has perhaps a wider use due to a similar extent of TNT mineralization in the absence of light, leading to possible applications in soil slurry and in situ processes in the subsurface.