Genetic transformation of Brassica nigra by agrobacterium based vector and direct plasmid uptake

Genetic transformation systems have been established for Brassica nigra (cv. IC 257) by using an Agrobacterium binary vector as well as by direct DNA uptake of a plasmid vector. Both the type of vectors carried nptII gene and gus gene. For Agrobacterium mediated transformation, hypocotyl tissue explants were used, and up to 33% of the explants produced calli on selection medium. All of these expressed B-glucuronidase gene on histochemical staining. Protoplasts isolated from hypocotyl tissues of seedlings could be transformed with a plasmid vector by FEG mediated uptake of vector DNA. A number of fertile kanamycin resistant plants were obtained using both the methods, and their transformed nature was confirmed by Southern blot analysis and histochemical staining for GUS. Backcrossed and selfed progenies of these transformed plants showed the presence of npt and gus genes.

Transformation in heterokaryons of Neurospora crassa is nuclear rather than cellular phenomenon

In Neurospora crassa, multinucleate macroconidia are used for genetic transformation. The barrier for such a transformation can be either at the cell membrane level or at the nuclear membrane level. For assessment of these possibilities, a forced heterokaryon (containing two genetically marked nuclei and auxotrophic for histidine) of Neurospora crassa was transformed with a plasmid containing his-3(+) gene. The transformants, which could grow without histidine supplementation, were then resolved into component homokaryons to determine into which nucleus or nuclei the plasmid had entered. Our results suggest that the barrier for transformation in Neurospora crassa is at the nuclear level, not at the cell membrane level. In a heterokaryon containing two genetically distinct nuclei, plasmid DNA integrated into only one of the nuclear types at any instance, but never into both nuclear types. Thus, in Neurospora crassa, the competent nucleus is essential for the transformation event to take place, and at a given time only one type of nucleus is competent to take up the exogenous DNA. Genomic Southern analysis showed that the transformants harbor both ectopic and homologous integrations of the plasmid DNA. The type and number of integrations were reflected at the post-translational level, since the specific activity of histidinol dehydrogenase (the translation product of his-3+ gene) was variable among several transformants and always less than the level of the wild type.

MULTI-OBJECTIVE GENETIC ALGORITHM FOR EFFICIENT POINT MATCHING IN MULTI-SENSOR SATELLITE IMAGE

This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient.

Micro-shock wave assisted bacterial transformation

A gene is a unit of heredity in a living organism. It normally resides on a stretch of DNA that codes for a type of protein or for an RNA chain that has a function in the organism. All living things depend on genes, as they specify all proteins and functional RNA chains. Genes hold the information to build and maintain an organism’s cells and pass genetic traits to offspring. The gene has to be transferred to bacteria or eukaryotic cells for basic and applied molecular biology studies. Bacteria can uptake exogenous genetic material by three ways: conjugation, transduction and transformation. Genetic material is naturally transferred to bacteria in case of conjugation and transferred through bacteriophage in transduction. Transformation is the acquisition of exogenous genetic material through cell wall. The ability of bacteria of being transformed is called competency and those bacteria which have competency are competent cells. Divalent Calcium ions can make the bacteria competent and a heat shock can cause the bacteria to uptake DNA. But the heat shock method cannot be used for all the bacteria. In electroporation, a brief electric shock with an electric field of 10-20kV/cmmakes pores in the cell wall, facilitates the DNA to enter into the bacteria. Microprecipitates, microinjection, liposomes, and biological vectors are also used to transfer polar molecules like DNA into host cells.

Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

Ordering transformation in icosahedral quasicrystals and related crystalline phases

Arcs of diffuse intensity appear in various shapes and positions in the diffraction patterns from the icosahedral phase, violating the parity rule for simple icosahedral (SI) symmetry. In the process of annealing treatment, the diffuse spots also evolve in the centre of the arcs and become sharp. These extra diffuse spots change the symmetry of the quasilattice from P-type to F-type. The ordered and disordered structures in quasicrystal have been linked to the ordered and disordered structures present in the crystalline alpha (Al-Mn-Si) and alpha (Al-Fe-Si) alloys.

Preparation of lamellar and hexagonal forms of mesoporous silica and zirconiaby the neutral amine route: lamellar-hexagonal transformation in the solid state

The chain length of the surfactant and the solvent composition are two of the factors that determine whether the lamellar or the hexagonal form of mesoporous SiO2 (or ZrO2) is formed by the neutral amine route; a lamellar-hexagonal transformation occurs on removal of the amine from the former.

Study of texture evolution in metastable beta-Ti alloy as a function of strain path and its effect on alpha transformation texture

Texture evolution in a low cost beta titanium alloy was studied for different modes of rolling and heat treatments. The alloy was cold rolled by unidirectional and multi-step cross rolling. The cold rolled material was either aged directly or recrystallized and then aged. The evolution of texture in alpha and beta phases were studied. The rolling texture of beta phase that is characterized by the gamma fiber is stronger for MSCR than UDR; while the trend is reversed on recrystallization. The mode of rolling affects alpha transformation texture on aging with smaller alpha lath size and stronger alpha texture in UDR than in MSCR. The defect structure in beta phase influences the evolution of a texture on aging. A stronger defect structure in beta phase leads to variant selection with the rolled samples showing fewer variants than the recrystallized samples.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

DSC studies on the phase transformation of hydrazonium sulfate

The high temperature phase transformation of hydrazonium sulfate, N2H6SO4 has been studied using DSC. The enthalpy of phase transition is found to be 3.63 ± 0.1 kJ mole−1. The phase transition temperature is found to decrease with the increase of particle size. It appears that the strain energy and not surface energy, is responsible for the phase transformation. The molar volume of the salt increases during the transformation as found by the dilatometric experiment involving percentage of linear thermal expansion. On cooling, the transformation from the high temperature modification to orthorhombic form is incomplete and extends over a wide range of temperature.

Stress-induced martensitic phase transformation in Cu-Zr nanowires

A novel stress-induced martensitic phase transformation in an initial < 100 >/{100} B2-CuZr nanowire is reported for the first time in this letter. Such behavior is observed in a nanowire with cross-sectional dimensions of 19.44 x 19.44 angstrom(2) over a temperature range of 100-400 K and at a strain rate of 1 x 10(9) s(-1) using atomistic simulations. Phase transformation from an initial B2 phase to a BCT (Body-Centered-Tetragonal) phase is observed via nucleation and propagation of {100} twinning plane under high strain rate tensile deformation. (C) 2009 Elsevier B.V. All rights reserved.

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

Structural Basis of Drug Resistance by Genetic Variants of HIV Type 1 Clade C Protease from India

Using computer modeling of three-dimensional structures and structural information available on the crystal structures of HIV-1 protease, we investigated the structural effects of mutations, in treatment-naive and treatment-exposed individuals from India and postulated mechanisms of resistance in clade C variants. A large number of models (14) have been generated by computational mutation of the available crystal structures of drug bound proteases. Localized energy minimization was carried out in and around the sites of mutation in order to optimize the geometry of interactions present. Most of the mutations result in structural differences at the flap that favors the semiopen state of the enzyme. Some of the mutations were also found to confer resistance by affecting the geometry of the active site. The E35D mutation affects the flap structure in clade B strains and E35N and E35K mutation, seen in our modeled strains, have a more profound effect. Common polymorphisms at positions 36 and 63 in clade C also affected flap structure. Apart from a few other residues Gln-58, Asn-83, Asn-88, and Gln-92 and their interactions are important for the transition from the closed to the open state. Development of protease inhibitors by structure-based design requires investigation of mechanisms operative for clade C to improve the efficacy of therapy.

Microbial transformation of a fungicide-derived amine, dimethyl-p-phenylene diamine by Alcaligenes DM4

Abstract Microbial transformation of N, N-dimethyl-p-phenylene diamine (DMPDA), a microbial product formed from the fungicide fenaminosulf (p-dimethylaminobenzenediazo sodium sulfonate) was studied by enriching microbes in soils treated with the amine. Microorganisms isolated from DMPDA-treated soil belonged to the genera of Micrococcus, Alcaligenes, and Corynebacterium. Of the various isolates, Alcaligenes DM4 showed maximal growth on DMPDA utilizing it as sources of carbon and nitrogen. When grown in mineral salts basal medium containing 0.05% DMPDA to serve as carbon and nitrogen sources, Alcaligenes DM4 grew exponentially up to 18 h. Even though the characterization of the complete pathway of microbial degradation of DMPDA could not be carried out due to the auto-oxidation of the compound, the initial transformation product of DMPDA by Alcaligenes DM4 has been identified as a dimer. The dimer is generated into the culture medium presumably by the extra-cellular oxidase of Alcaligenes DM4. It is suggested that the risk-benefit evaluation on the use of fenaminosulf is to be made taking into consideration the microbial transformations of the fungicide.