Análises da expressão gênica por PCR quantitativo em tempo real (QPCR) de genes candidatos para a tolerância à seca em cafeeiro.

A seca é uma das principais limitações climáticas à produção do cafeeiro. A importância dessa limitação deve aumentar, em função das mudanças reconhecidas no clima global e, também, porque a cafeicultura vem sendo expandida para regiões marginais onde a baixa pluviosidade e temperaturas desfavoráveis se constituem grandes limitações à produção do café. A seca induz diversas respostas fisiológicas e moleculares nas plantas, incluindo alterações da expressão gênica, visando atingir ajuste osmótico, a indução de reparadores de sistemas moleculares e a expressão de diversas proteínas protetoras. Existem diversas formas de se avaliar a expressão gênica em plantas submetidas ao estresse hídrico. Uma técnica amplamente utilizada nos últimos anos, para a análise quantitativa da expressão gênica é a de PCR quantitativo em tempo real (qPCR). O objetivo do presente trabalho foi analisar a expressão de 14 genes candidatos para a tolerância à seca em cafeeiro, pré-selecionados em estudos de macroarranjos de cDNA, utilizando clones de Coffea canephora (Clone 22 ? sensível e clones 14, 73 e 120 ? tolerantes ao estresse hídrico)

Millimeter wave radiation-induced magnetoresistance oscillations in the high quality GaAs/AlGaAs 2D electron system under bichromatic excitation

Millimeter wave radiation-induced magnetoresistance oscillations are examined in the GaAs/AlGaAs 2D electron system under bichromatic excitation in order to study the evolution of the oscillatory diagonal magnetoresistance, R-xx as the millimeter wave intensity is changed systematically for various frequency combinations. The results indicate that at low magnetic fields, the lower frequency millimeter wave excitation sets the observed R-xx response, as the higher frequency millimeter wave component determines the R-xx response at higher magnetic fields. The observations are qualitatively explained in terms of the order of the involved transitions. The results are also modeled using the radiation-driven electron orbit theory

Evaluation of signal peptide prediction algorithms for identification of mycobacterial signal peptides using sequence data from proteomic methods

Secreted proteins play an important part in the pathogenicity of Mycobacterium tuberculosis, and are the primary source of vaccine and diagnostic candidates. A majority of these proteins are exported via the signal peptidase I-dependent pathway, and have a signal peptide that is cleaved off during the secretion process. Sequence similarities within signal peptides have spurred the development of several algorithms for predicting their presence as well as the respective cleavage sites. For proteins exported via this pathway, algorithms exist for eukaryotes, and for Gram-negative and Gram-positive bacteria. However, the unique structure of the mycobacterial membrane raises the question of whether the existing algorithms are suitable for predicting signal peptides within mycobacterial proteins. In this work, we have evaluated the performance of nine signal peptide prediction algorithms on a positive validation set, consisting of 57 proteins with a verified signal peptide and cleavage site, and a negative set, consisting of 61 proteins that have an N-terminal sequence that confirms the annotated translational start site. We found the hidden Markov model of SignalP v3.0 to be the best-performing algorithm for predicting the presence of a signal peptide in mycobacterial proteins. It predicted no false positives or false negatives, and predicted a correct cleavage site for 45 of the 57 proteins in the positive set. Based on these results, we used the hidden Markov model of SignalP v3.0 to analyse the 10 available annotated proteomes of mycobacterial species, including annotations of M. tuberculosis H37Rv from the Wellcome Trust Sanger Institute and the J. Craig Venter Institute (JCVI). When excluding proteins with transmembrane regions among the proteins predicted to harbour a signal peptide, we found between 7.8 and 10.5 % of the proteins in the proteomes to be putative secreted proteins. Interestingly, we observed a consistent difference in the percentage of predicted proteins between the Sanger Institute and JCVI. We have determined the most valuable algorithm for predicting signal peptidase I-processed proteins of M. tuberculosis, and used this algorithm to estimate the number of mycobacterial proteins with the potential to be exported via this pathway

A Combined Perceptual, Physico-Chemical, and Imaging Approach to ‘Odour-Distances’ Suggests a Categorizing Function of the Drosophila Antennal Lobe

How do physico-chemical stimulus features, perception, and physiology relate? Given the multi-layered and parallel architecture of brains, the question specifically is where physiological activity patterns correspond to stimulus features and/or perception. Perceived distances between six odour pairs are defined behaviourally from four independent odour recognition tasks. We find that, in register with the physico-chemical distances of these odours, perceived distances for 3-octanol and n-amylacetate are consistently smallest in all four tasks, while the other five odour pairs are about equally distinct. Optical imaging in the antennal lobe, using a calcium sensor transgenically expressed in only first-order sensory or only second-order olfactory projection neurons, reveals that 3-octanol and n-amylacetate are distinctly represented in sensory neurons, but appear merged in projection neurons. These results may suggest that within-antennal lobe processing funnels sensory signals into behaviourally meaningful categories, in register with the physico-chemical relatedness of the odours