986 resultados para Microbial population


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Soil is an unrenewable natural resource under increasing anthropogenic pressure. One of the main threats to soils, compromising their ability to provide us with the goods and ecosystem services we expect, is pollution. Oil hydrocarbons are the most common soil contaminants, and they disturb not just the biota but also the physicochemical properties of soils. Indigenous soil micro-organisms respond rapidly to changes in the soil ecosystem, and are chronically in direct contact with the hydrophobic pollutants on the soil surfaces. Soil microbial variables could thus serve as an intrinsically relevant indicator of soil quality, to be used in the ecological risk assessment of contaminated and remediated soils. Two contrasting studies were designed to investigate soil microbial ecological responses to hydrocarbons, together with parallel changes in soil physicochemical and ecotoxicological properties. The aim was to identify quantitative or qualitative microbiological variables that would be practicable and broadly applicable for the assessment of the quality and restoration of oil-polluted soil. Soil bacteria commonly react on hydrocarbons as a beneficial substrate, which lead to a positive response in the classical microbiological soil quality indicators; negative impacts were accurately reflected only after severe contamination. Hydrocarbon contaminants become less bioavailable due to weathering processes, and their potentially toxic effects decrease faster than the total concentration. Indigenous hydrocarbon degrader bacteria, naturally present in any terrestrial environment, use specific mechanisms to improve access to the hydrocarbon molecules adsorbed on soil surfaces. Thus when contaminants are unavailable even to the specialised degraders, they should pose no hazard to other biota either. Change in the ratio of hydrocarbon degrader numbers to total microbes was detected to predictably indicate pollutant effects and bioavailability. Also bacterial diversity, a qualitative community characteristic, decreased as a response to hydrocarbons. Stabilisation of community evenness, and community structure that reflected clean reference soil, indicated community recovery. If long-term temporal monitoring is difficult and appropriate clean reference soil unavailable, such comparison could possibly be based on DNA-based community analysis, reflecting past+present, and RNA-based community analysis, showing exclusively present conditions. Microbial ecological indicators cannot replace chemical oil analyses, but they are theoretically relevant and operationally practicable additional tools for ecological risk assessment. As such, they can guide ecologically informed and sustainable ecosophisticated management of oil-contaminated lands.

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The presence of cell agglomerates has been found to influence significantly the rates of liquid drainage from static foams. The process of drainage has been modelled by considering the foam to be made of pentagonal dodecahedral bubbles yielding films, nearly horizontal and nearly vertical Plateau borders. The films are assumed to drain into both kinds of Plateau borders equally. The horizontal Plateau borders are assumed to receive liquid from the films and drain into the vertical Plateau borders, which, in turn, form the main flow paths for gravity drainage. The drainage process is assumed to be similar to that for pure liquid until a stage is reached where the size of the cell agglomerates become equivalent to those of films and Plateau borders. Thereafter, a squeezing flow mechanism has been formulated where the aggromerates deform and flow. The model based on the above assumptions has been verified against experimental results and has been found to predict not only drainage data but also the separation of cell agglomerates from broths.

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Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

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Whether HIV-1 evolution in infected individuals is dominated by deterministic or stochastic effects remains unclear because current estimates of the effective population size of HIV-1 in vivo, N-e, are widely varying. Models assuming HIV-1 evolution to be neutral estimate N-e similar to 10(2)-10(4), smaller than the inverse mutation rate of HIV-1 (similar to 10(5)), implying the predominance of stochastic forces. In contrast, a model that includes selection estimates N-e>10(5), suggesting that deterministic forces would hold sway. The consequent uncertainty in the nature of HIV-1 evolution compromises our ability to describe disease progression and outcomes of therapy. We perform detailed bit-string simulations of viral evolution that consider large genome lengths and incorporate the key evolutionary processes underlying the genomic diversification of HIV-1 in infected individuals, namely, mutation, multiple infections of cells, recombination, selection, and epistatic interactions between multiple loci. Our simulations describe quantitatively the evolution of HIV-1 diversity and divergence in patients. From comparisons of our simulations with patient data, we estimate N-e similar to 10(3)-10(4), implying predominantly stochastic evolution. Interestingly, we find that N-e and the viral generation time are correlated with the disease progression time, presenting a route to a priori prediction of disease progression in patients. Further, we show that the previous estimate of N-e>10(5) reduces as the frequencies of multiple infections of cells and recombination assumed increase. Our simulations with N-e similar to 10(3)-10(4) may be employed to estimate markers of disease progression and outcomes of therapy that depend on the evolution of viral diversity and divergence.

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We analyze theoretically the phenomenon of electromagnetically induced transparency (UT) under conditions where the probe laser is not in the usual weak limit. We consider the effects in both three-level and four-level systems, which are either closed or open (due to losses to an external metastable level). We find that the EIT dip almost disappears in a closed three-level system but survives in an open system. In four-level systems, there is a narrow enhanced-absorption peak (EITA) at line center, which has applications as an optical clock. The peak converts to an EIT dip in a closed system, but again survives in an open system. (C) 2010 Elsevier B.V. All rights reserved.

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Glucose-6-phosphate dehydrogenase (G6PD) deficiency is seen at a higher frequency in many national and ethnic groups in areas of current or former malaria endemicity. A screening programme undertaken to evaluate the gene frequencies for this deficiency in the highly inbred South Indian population of Karnataka revealed that of the 5140 neonates screened, 7.8% were G6PD deficient with no correlation between the reported level of inbreeding and enzyme deficiency. An interesting finding was the equal number of male (198) and female (207) individuals, with G6PD activity of less than 3 IU. The possible implications of this finding with regard to the expression of G6PD gene is discussed.

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Glucose-6-phosphate dehydrogenase (G6PD) is coded by a gene on the X-chromosome. Earlier studies have shown that the South Indian population has a high incidence of this enzyme deficiency. The electrophoretic mobility, pH optimum and the K-m values for G6PD from normal and variant individuals were identical. However, the specific activity of the variant enzyme was 8 times less compared to the value of the normal enzyme. Western blot analysis of partially purified G6PD from normal and variant individuals performed using equal amounts of total protein showed that the variant protein was 3 times less in concentration. Similar analysis performed using protein corresponding to equal enzyme activity units in the normal and variant samples showed that the variant enzyme was 2.25 times less efficient compared to the normal enzyme. RNA dot blot analysis using full length G6PD cDNA probe (PGDT5B, a kind gift from Prof. L Luzzatto) revealed that lymphocytes from normal and variant individuals had equal amounts of G6PD specific mRNA.

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Biotransformation of 3 beta-acetoxy-19-hydroxycholest-5-ene (19-HCA, 6 g) by Moraxella sp. was studied. Estrone (712 mg) was the major metabolite formed. Minor metabolites identified were 5 alpha-androst-1-en-19-ol-3,17-dione (33 mg), androst-4-en-19-ol-3,17-dione (58 mg), androst-4-en-9 alpha,19-diol-3,17-dione (12 mg), and androstan-19-ol-3,17-dione (1 mg). Acidic metabolites were not formed. Time course experiments on the fermentation of 19-HCA indicated that androst-4-en-19-ol-3,17-dione was the major metabolite formed during the early stages of incubation. However with continuing fermentation its level dropped, with a concomitant increase in estrone. Fermentation of 19-HCA in the presence of specific inhibitors or performing the fermentation for a shorter period (48 h) did not result in the formation of acidic metabolites. Resting-cell experiments carried out with 19-HCA (200 mg) in the presence of alpha,alpha'-bipyridyl led to the isolation of three additional metabolites, viz., cholestan-19-ol-3-one (2 mg), cholest-4-en-19-ol-3-one (10 mg), and cholest-5-en-3 beta,19-diol (12 mg). Similar results were also obtained when n-propanol was used instead of alpha,alpha'-bipyridyl. Resting cells grown on 19-HCA readily converted both 5 alpha-androst-1-en-19-ol-3,17-dione and androst-4-en-19-ol-3,17-dione into estrone. Partially purified 1,2-dehydrogenase from steroid-induced Moraxella cells transformed androst-4-en-19-ol-3,17-dione into estrone and formaldehyde in the presence of phenazine methosulfate, an artificial electron acceptor. These results suggest that the degradation of the hydrocarbon side chain of 19-HCA does not proceed via C-22 phenolic acid intermediates and complete removal of the C-17 side chain takes place prior to the aromatization of the A ring in estrone. The mode of degradation of the sterol side chain appears to be through the fission of the C-17-C-20 bond. On the basis of these observations, a new pathway for the formation of estrone from 19-HCA in Moraxella sp. has been proposed.

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Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

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Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.

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In this paper, we report an analysis of the protein sequence length distribution for 13 bacteria, four archaea and one eukaryote whose genomes have been completely sequenced, The frequency distribution of protein sequence length for all the 18 organisms are remarkably similar, independent of genome size and can be described in terms of a lognormal probability distribution function. A simple stochastic model based on multiplicative processes has been proposed to explain the sequence length distribution. The stochastic model supports the random-origin hypothesis of protein sequences in genomes. Distributions of large proteins deviate from the overall lognormal behavior. Their cumulative distribution follows a power-law analogous to Pareto's law used to describe the income distribution of the wealthy. The protein sequence length distribution in genomes of organisms has important implications for microbial evolution and applications. (C) 1999 Elsevier Science B.V. All rights reserved.

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In this paper, electroleaching and electrobioleaching of ocean manganese nodules are discussed along with the role of galvanic interactions in bioleaching. Polarization studies using a manganese nodule slurry electrode system indicated that the maximum dissolution of iron and manganese due to electrochemical reduction occurred at negative DC potentials of -600 and -1,400 mV(SCE). Electroleaching and electrobioleaching of ocean manganese nodules in the presence of Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans at the above negative applied DC potentials resulted insignificant dissolution of copper, nickel and cobalt in 1 M H2SO4 and in sulfuric acid solution at pH 0.5 and 2.0. Mechanisms involved in electrobioleaching of ocean manganese nodules are discussed. Galvanic leaching of ocean manganese nodules in the presence of externally added pyrite and pyrolusite for enhancement of dissolution was also studied. Various electrochemical and biochemical parameters were optimized, and the electroleaching and galvanic processes thus developed are shown to yield almost complete dissolution of all metal values. This electrobioleaching process developed in the laboratory may be cost effective, energy efficient and environmentally friendly.