A distinct physiological role of MutY in mutation prevention in mycobacteria

Oxidative damage to DNA results in the occurrence of 7,8-dihydro-B-oxoguanine (8-oxoG) in the genome. In eubacteria, repair of such damage is initiated by two major base-excision repair enzymes, MutM and MutY. We generated a MutY-deficient strain of Mycobacterium smegmatis to investigate the role of this enzyme in DNA repair. The MutY deficiency in M. smegmatis did not result in either a noteworthy susceptibility to oxidative stress or an increase in the mutation rate. However, rifampicin resistant isolates of the MutY-deficient strain showed distinct mutations in the rifampicin-resistance-determining region of rpoB. Besides the expected C to A (or G to T) mutations, an increase in A to C (or T to G) mutations was also observed. Biochemical characterization of mycobacterial MutY (M. smegmatis and M. tuberculosis) revealed an expected excision of A opposite 8-oxoG in DNA. Additionally, excision of G and T opposite 8-oxoG was detected. MutY formed complexes with DNA containing 8-oxoG: A, 8-oxoG: G or 8-oxoG: T but not 8-oxoG : C pairs. Primer extension reactions in cell-free extracts of M. smegmatis suggested error-prone incorporation of nucleotides into the DNA. Based on these observations, we discuss the physiological role of MutY in specific mutation prevention in mycobacteria.

Synergistic effects of UdgB and Ung in mutation prevention and protection against commonly encountered DNA damaging agents in Mycobacterium smegmatis

The incorporation of dUMP during replication or the deamination of cytosine in DNA results in the occurrence of uracils in genomes. To maintain genomic integrity, uracil DNA glycosylases (UDGs) excise uracil from DNA and initiate the base-excision repair pathway. Here, we cloned, purified and biochemically characterized a family 5 UDG, UdgB, from Mycobacterium smegmatis to allow us to use it as a model organism to investigate the physiological significance of the novel enzyme. Studies with knockout strains showed that compared with the wild-type parent, the mutation rate of the udgB(-) strain was approximately twofold higher, whereas the mutation rate of a strain deficient in the family 1 UDG (ung(-)) was found to be similar to 8.4-fold higher. Interestingly, the mutation rate of the double-knockout (ung(-)ludgB(-)) strain was remarkably high, at similar to 19.6-fold. While CG to TA mutations predominated in the ung(-) and ung(-)/udgb(-) strains, AT to GC mutations were enhanced in the udgB(-) strain. The ung(-)/udgB(-) strain was notably more sensitive to acidified nitrite and hydrogen peroxide stresses compared with the single knockouts (ung(-) or udgB(-)). These observations reveal a synergistic effect of UdgB and Ung in DNA repair, and could have implications for the generation of attenuated strains of Mycobacterium tuberculosis.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Taking Multiple Infections of Cells and Recombination into Account Leads to Small Within-Host Effective-Population-Size Estimates of HIV-1

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.

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

The use of mutagenic drugs to drive HIV-1 past its error threshold presents a novel intervention strategy, as suggested by the quasispecies theory, that may be less susceptible to failure via viral mutation-induced emergence of drug resistance than current strategies. The error threshold of HIV-1, mu(c), however, is not known. Application of the quasispecies theory to determine mu(c) poses significant challenges: Whereas the quasispecies theory considers the asexual reproduction of an infinitely large population of haploid individuals, HIV-1 is diploid, undergoes recombination, and is estimated to have a small effective population size in vivo. We performed population genetics-based stochastic simulations of the within-host evolution of HIV-1 and estimated the structure of the HIV-1 quasispecies and mu(c). We found that with small mutation rates, the quasispecies was dominated by genomes with few mutations. Upon increasing the mutation rate, a sharp error catastrophe occurred where the quasispecies became delocalized in sequence space. Using parameter values that quantitatively captured data of viral diversification in HIV-1 patients, we estimated mu(c) to be 7 x 10(-5) -1 x 10(-4) substitutions/site/replication, similar to 2-6 fold higher than the natural mutation rate of HIV-1, suggesting that HIV-1 survives close to its error threshold and may be readily susceptible to mutagenic drugs. The latter estimate was weakly dependent on the within-host effective population size of HIV-1. With large population sizes and in the absence of recombination, our simulations converged to the quasispecies theory, bridging the gap between quasispecies theory and population genetics-based approaches to describing HIV-1 evolution. Further, mu(c) increased with the recombination rate, rendering HIV-1 less susceptible to error catastrophe, thus elucidating an added benefit of recombination to HIV-1. Our estimate of mu(c) may serve as a quantitative guideline for the use of mutagenic drugs against HIV-1.

Scaling law characterizing the dynamics of the transition of HIV-1 to error catastrophe

Increasing the mutation rate, mu, of viruses above a threshold, mu(c), has been predicted to trigger a catastrophic loss of viral genetic information and is being explored as a novel intervention strategy. Here, we examine the dynamics of this transition using stochastic simulations mimicking within-host HIV-1 evolution. We find a scaling law governing the characteristic time of the transition: tau approximate to 0.6/(mu - mu(c)). The law is robust to variations in underlying evolutionary forces and presents guidelines for treatment of HIV-1 infection with mutagens. We estimate that many years of treatment would be required before HIV-1 can suffer an error catastrophe.

The Presence of Multiple Cellular Defects Associated with a Novel G50E Iron-Sulfur Cluster Scaffold Protein ( ISCU) Mutation Leads to Development of Mitochondrial Myopathy

Background: Muscle-specific deficiency of iron-sulfur (Fe-S) cluster scaffold protein (ISCU) leads to myopathy. Results: Cells carrying the myopathy-associated G50E ISCU mutation demonstrate impaired Fe-S cluster biogenesis and mitochondrial dysfunction. Conclusion: Reduced mitochondrial respiration as a result of diminished Fe-S cluster synthesis results in muscle weakness in myopathy patients. Significance: The molecular mechanism behind disease progression should provide invaluable information to combat ISCU myopathy. Iron-sulfur (Fe-S) clusters are versatile cofactors involved in regulating multiple physiological activities, including energy generation through cellular respiration. Initially, the Fe-S clusters are assembled on a conserved scaffold protein, iron-sulfur cluster scaffold protein (ISCU), in coordination with iron and sulfur donor proteins in human mitochondria. Loss of ISCU function leads to myopathy, characterized by muscle wasting and cardiac hypertrophy. In addition to the homozygous ISCU mutation (g.7044GC), compound heterozygous patients with severe myopathy have been identified to carry the c.149GA missense mutation converting the glycine 50 residue to glutamate. However, the physiological defects and molecular mechanism associated with G50E mutation have not been elucidated. In this report, we uncover mechanistic insights concerning how the G50E ISCU mutation in humans leads to the development of severe ISCU myopathy, using a human cell line and yeast as the model systems. The biochemical results highlight that the G50E mutation results in compromised interaction with the sulfur donor NFS1 and the J-protein HSCB, thus impairing the rate of Fe-S cluster synthesis. As a result, electron transport chain complexes show significant reduction in their redox properties, leading to loss of cellular respiration. Furthermore, the G50E mutant mitochondria display enhancement in iron level and reactive oxygen species, thereby causing oxidative stress leading to impairment in the mitochondrial functions. Thus, our findings provide compelling evidence that the respiration defect due to impaired biogenesis of Fe-S clusters in myopathy patients leads to manifestation of complex clinical symptoms.

Free Energy Gap Dependence of the Electron-Transfer Rate from the Inverted to the Normal Region

numerical study of the free energy gap (FEG) dependence of the electron-transfer rate in polar solvents is presented. This study is based on the generalized multidimensional hybrid model, which not only includes the solvent polarization and the molecular vibration modes, but also the biphasic polar response of the solvent. The free energy gap dependence is found to be sensitive to several factors, including the solvent relaxation rate, the electronic coupling between the surfaces, the frequency of the high-frequency quantum vibrational mode, and the magnitude of the solvent reorganization energy. It is shown that in some cases solvent relaxation can play an important role even in the Marcus normal regime. The minimal hybrid model involves a large number of parameters, giving rise to a diverse non-Marcus FEG behavior which is often determined collectively by these parameters. The model gives the linear free energy gap dependence of the logarithmic rate over a substantial range of FEG, spanning from the normal to the inverted regime. However, even for favorable values of the relevant parameters, a linear free energy gap dependence of the rate could be obtained only over a range of 5000-6000 cm(-1) (compared to the experimentally observed range of 10000 cm(-1) reported by Benniston et al.). The present work suggests several extensions/generalizations of the hybrid model which might be necessary to fully understand the observed free energy gap dependence.

Optimal barrier subdivision for Kramers' escape rate

We examine the effect of subdividing the potential barrier along the reaction coordinate on Kramers' escape rate for a model potential. Using the known supersymmetric potential approach, we show the existence of an optimal number of subdivisions that maximizes the rate.

Oxygen transfer and energy dissipation rate in surface aerator

The dissipation rate of turbulent kinetic energy (epsilon) is a key parameter for mixing in surface aerators. In particular, determination epsilon across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix (R) calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system, oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.

Oxygen transfer and energy dissipation rate in surface aerator

The dissipation rate of turbulent kinetic energy(e)is a key parameter for mixing in surface aerators. In particular, determination e across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system,oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.

Synergy between tribo-oxidation and strain rate response on governing the dry sliding wear behavior of titanium.

The present work provides an insight into the dry sliding wear behavior of titanium based on synergy between tribo-oxidation and strain rate response. Pin-on-disc tribometer was used to characterize the friction and wear behavior of titanium pin in sliding contact with polycrystalline alumina disk under ambient and vacuum condition. The sliding speed was varied from 0.01 to 1.4 ms(-1), normal load was varied from 15.3 to 76 N and with a sliding distance of 1500 m. It was seen that dry sliding wear behavior of titanium was governed by combination of tribo-oxidation and strain rate response in near surface region of titanium. Strain rate response of titanium was recorded by conducting uni-axial compression tests at constant true strain rate of 100 s(-1) in the temperature range from 298 to 873 K. Coefficient of friction and wear rate were reduced with increased sliding speed from 0.01 to 1.0 ms(-1). This is attributed to the formation of in situ self lubricating oxide film (TiO) and reduction in the intensity of adiabatic shear band cracking in the near surface region. This trend was confirmed by performing series of dry sliding tests under vacuum condition of 2 x 10(-4) Torr. Characterization tools such as optical microscopy, scanning electron microscopy, and X-ray diffractometer provided evidence of such processes. These experimental findings can be applied to enhance the dry sliding wear behavior of titanium with proper choice of operating conditions such as sliding speed, normal load, and environment.

Influence of clofibrate administration on the rate of synthesis of macromolecules in regenerating rat liver

Administration of the antihypercholesterolaemic drug clofibrate stimulates the rates of synthesis of nucleic acids and proteins in rat liver. The biosynthesis of mitochondrial proteins also is enhanced by the drug. In drug-fed animals, the rates of incorporation in vivo of radioactive precursors into DNA, RNA and proteins are stimulated even when the liver undergoes regeneration following partial hepatectomy. The rate of synthesis of mitochondrial proteins in the regenerative phase is higher in clofibrate-fed animals. These effects are consistent with the hepatomegalic and mitochondria-proliferating property of the drug.