Radu E. Sestras

Identification of Salt Stress Biomarkers in Romanian Carpathian Populations of Picea abies (L.) Karst.

The Norway spruce (Picea abies), the most important tree species in European forests, is relatively sensitive to salt and does not grow in natural saline environments. Yet many trees are actually exposed to salt stress due to the common practice of de-icing of mountain roads in winter, using large amounts of NaCl. To help develop strategies for an appropriate use of reproductive seed material on reforestation sites, ensuring better chances of seedling survival in salt-affected areas, we have studied the responses of young spruce seedlings to salt treatments. The specific aim of the work was to identify the optimal salt stress biomarkers in Picea abies, using as experimental material seedlings obtained by germination of seeds with origin in seven populations from the Romanian Carpathian Mountains. These responses included general, conserved reactions such as the accumulation of ions and different osmolytes in the seedlings needles, reduction in photosynthetic pigments levels, or activation of antioxidant systems. Although changes in the contents of different compounds involved in these reactions can be associated to the degree of stress affecting the plants, we propose that the (decreasing) levels of total phenolics or total carotenoids and the (increasing) levels of Na+ or K+ ions in Picea abies needles, should be considered as the most reliable and useful biomarkers for salt stress in this species. They all show very high correlation with the intensity of salt stress, independently of the genetic background of the seeds parental population, and relatively easy, quantitative assays are available to determine their concentrations, requiring simple equipment and little amount of plant material.

A Study of Genetic Algorithm Evolution on the Lipophilicity of Polychlorinated Biphenyls

The search for multivariate linear regression (MLR) in quantitative structure–property relationships (QSPR) is a hard problem, due to the dimension of the entire search space. A genetic algorithm (GA) was developed and assessed, to select proper descriptors for predicting the octan‐1‐ol/H2O partition coefficient of polychlorinated biphenyls. The GA was implemented as a Windows based FreePascal application with MySQL connectivity for fetching the data. An outcome study based on 30 runs was done keeping all parameters constant: sample size, 8; number of variables in the MLR, 2; adaptation‐imposed requirements; maximum number of generations, 1000; selection strategy, proportional; probability of mutation, 0.05; number of genes implied in mutation, 2; optimization parameter, r2; optimization score, minimum in sample; and optimization objective, maximum. The results revealed that the number of evolutions followed the Poisson distribution with the sample size as parameter. The average of the determination coefficient is higher than 98% of the determination coefficient obtained through complete search, and follows the Gaussian distribution. The correlation coefficients obtained by the best performing GA‐MLR models proved not to be statistically different from the correlation coefficient of the QSPR model obtained by complete search.

Screening for drought tolerance in cultivars of the ornamental genus Tagetes (Asteraceae)

Drought tolerance was evaluated in twelve cultivars of three ornamental Tagetes species (T. patula, T. tenuifolia and T. erecta). A stress treatment was performed by completely stopping watering of plants maintained in controlled greenhouse conditions. After three weeks, several plant growth parameters (stem length (SL), fresh weight (FW) and water content (WC)), photosynthetic pigments (chlorophylls and carotenoids (Car)), osmolytes (proline (Pro), glycine betaine (GB) and total soluble sugars (TSS)), an oxidative stress maker (malondialdehyde (MDA)) and antioxidants (total phenolic compounds (TPC) and total flavonoids (TF)) were measured. Considerable differences in the evaluated traits were found among the control and drought-stressed plants. Drought stress generally caused a marked reduction in plant growth and carotenoid pigments, and an increase in soluble solutes and oxidative stress. For most cultivars, proline levels in stressed plants increased between 30 and 70-fold compared to the corresponding controls. According to the different measured parameters, on average T. erecta proved to be more tolerant to drought than T. patula and T. tenuifolia. However, a considerable variation in the tolerance to drought was found within each species. The traits with greater association to drought tolerance as well as the most tolerant cultivars could be clearly identified in a principal components analysis (PCA). Overall, our results indicate that drought tolerant cultivars of Tagetes can be identified at early stages using a combination of plant growth and biochemical markers.

Poisson parameters of antimicrobial activity: a quantitative structure-activity approach.

A contingency of observed antimicrobial activities measured for several compounds vs. a series of bacteria was analyzed. A factor analysis revealed the existence of a certain probability distribution function of the antimicrobial activity. A quantitative structure-activity relationship analysis for the overall antimicrobial ability was conducted using the population statistics associated with identified probability distribution function. The antimicrobial activity proved to follow the Poisson distribution if just one factor varies (such as chemical compound or bacteria). The Poisson parameter estimating antimicrobial effect, giving both mean and variance of the antimicrobial activity, was used to develop structure-activity models describing the effect of compounds on bacteria and fungi species. Two approaches were employed to obtain the models, and for every approach, a model was selected, further investigated and found to be statistically significant. The best predictive model for antimicrobial effect on bacteria and fungi species was identified using graphical representation of observed vs. calculated values as well as several predictive power parameters.

Meta-heuristics on quantitative structure-activity relationships: study on polychlorinated biphenyls.

A genetic algorithm was developed and assessed in order to select pairs of proper structural descriptors able to estimate and predict octanol-water partition coefficients of polychlorinated biphenyls (PCBs). The molecular descriptors family was calculated for a sample of 206 PCBs. The problem of searching for the proper descriptors in order to identify structure-activity relationships was translated in genetic terms. The following parameters were imposed in the genetic algorithm (GA) search: sample size − 12, number of variables in multivariate linear regression − 4, imposed adaptation requirements − 3 criteria, maximum number of generations − 50,000, selection strategy − tournament, probability of parent/child mutation − 0.05, number of genes implied in the mutation − 2, optimization parameter - determination coefficient, optimization score - minimum in the sample, and optimization objective - maximum. The highest determination coefficient was obtained in the generation 17,277. Twenty-one evolutions were studied until the optimum solution was obtained. The model identified by the implemented genetic algorithm proved not to be statistically different from the model identified through complete search (ZSteiger = 1.37, p = 0.0861). According to this GA model, the relationship between the structure of PCBs and octanol-water partition coefficients was of geometric and topological nature as previously revealed by the complete search. The genetic algorithm proved its ability to identify two pairs of molecular descriptors able to characterize the relationship between the structure of PCBs and the octanol-water partition coefficient.

Hard Problems in Gene Sequence Analysis: Classical Approaches and Suitability of Genetic Algorithms

ABSTRACT Genetic algorithms are based on observations of natural phenomena as well as on the simulation of the artificial selection of organisms with multiple loci controlling a measurable trait. Genetic algorithms evolved into complex and strong informatics tools able to deal with hard problems of decision, classification, optimization, or/and simulation. We aimed to show how genetic algorithms can be used to solve hard problems on gene sequence analysis.

Quantum mechanics study on a series of steroids relating separation with structure

A small series of steroid hormones and synthetic steroid anabolics, eluted from a sample by using classical methanol-water mobile phase, was designed at molecular level with in vitro geometrical modeling. Structure-based properties of the compounds were extracted for different strategies of geometry optimization and were related with the percent retardation factors observed in the experiment by using classical linear regression approach. The obtained models were assessed and the most accurate model was selected. The obtained relationship between the structure and retardation factor was interpreted in order to express the main factors driving liquid phase mobility of compounds as a function of their structure. The analysis allowed a series of general conclusions regarding the modeled property (percent of retardation factor), modeling strategy (with help of a family of molecular descriptors) as well as about the level of theory in geometrical modeling (Ab-initio 6-31G*, CLHF, core Hamiltonian guess, symmetric orthogonalization).

Transgenic tomato plants expressing the antigen gene PfCP-2.9 of Plasmodium falciparum

The objective of this work was to obtain transgenic tomato plants expressing the PfCP-2.9 protein (a chimera of the antigens MSP1 and AMA1 of Plasmodium falciparum). Cotyledons of seven-day-old tomatoes, cultivar Summers, were transformed via Agrobacterium tumefaciens. Transgenic expression in the T0 plants was verified in the DNA extracted from fruits. PCR analysis was used to test the presence of the gene of interest in the T1 generation. Reverse transcriptase PCR provided evidence of gene expression at the RNA level, and Western blot analysis confirmed the presence of the protein of interest in the T1 plants. This is the first report of successful transformation with the expression of a malaria antigen (PfCP-2.9) in transgenic tomato plants from the T0 and T1 generations.

Modeling the Antioxidant Capacity of Red Wine from Different Production Years and Sources under Censoring

The health benefit of drinking wine, expressed as capacity to defend the human organism from the free radicals action and thus reducing the oxidative stress, has already been demonstrated, and the results had been published in scientific literature. The aim of our study was to develop and assess a model able to estimate the antioxidant capacity (AC) of several samples of Romanian wines and to evaluate the AC dependency on the vintage (defined as the year in which wine was produced) and grape variety under presence of censored data. A contingency of two grape varieties from two different vineyards in Romania and five production years, with some missing experimental data, was used to conduct the analysis. The analysis showed that the antioxidant capacity of the investigated wines is linearly dependent on the vintage. Furthermore, an iterative algorithm was developed and applied to obtain the coefficients of the model and to estimate the missing experimental value. The contribution of wine source to the antioxidant capacity proved equal to 11%.

A simulation study for the distribution law of relative moments of evolution

Nine selection-survival strategies were implemented in a genetic algorithm experiment, and differences in terms of evolution were assessed. The moments of evolution (expressed as generation numbers) were recorded in a contingency of three strategies (i.e., proportional, tournament, and deterministic) for two moments (i.e., selection for crossover and mutation and survival for replacement). The experiment was conducted for the first 20,000 generations in 46 independent runs. The relative moments of evolution (where evolution was defined as a significant increase in the determination coefficient relative to the previous generation) when any selection-survival strategy was used fit a Log-Pearson type III distribution. Moreover, when distributions were compared to one another, functional relationships were identified between the population parameters, revealing a degeneration of the Log-Pearson type III distribution in a one-parametrical distribution that can be assigned to the chosen variable—evolution strategy. The obtained theoretical population distribution allowed comparison of the selection-survival strategies that were used.