Characterisation of Australian isolates of Fusarium oxysporum f. sp cubense by DNA fingerprinting analysis

Genetic variation among Australian isolates of the fungus Fusarium oxysporum f. sp. cubense (Foc), which causes Fusarium wilt in banana, was examined using DNA amplification fingerprinting (DAF). Ninety-four isolates which represented Races 1, 2, 3, and 4, and vegetative compatibility groups (VCGs) 0120, 0124, 0125, 0128, 0129, 01211, 01213/16, and 01220 were analysed. The genetic relatedness among isolates within each VCG, and between the 8 different VCGs of Foc present in Australia was determined. The DNA fingerprint patterns were VCG-specific, with each VCG representing a unique genotype. The genetic similarity among isolates within each VCG ranged from 97% to 100%. Among the different VCGs of Foc, 3 major clusters were distinguished which corresponded with race. All Race 1 and 2 isolates (VCGs 0124, 0125, 0128, and 01220) were closely related and clustered together, the Race 3 isolates from Heliconia clustered separately, and all Race 4 isolates (VCGs 0120, 0129, 01211, and 01213/16) clustered together. Fifteen isolates from Alstonville, NSW, were characterised because although they were classified as Race 2 based on their recovery from cooking banana cultivars, they belonged in VCG 0124, which had previously contained only Race 1 isolates. The occurrence of more than one race within a VCG means that vegetative compatibility grouping cannot be used to assign pathotype to pathogenic race as previously thought. It was possible to distinguish the Race 1 and Race 2 isolates within VCG 0124 using DNA fingerprinting, as each race produced a unique DNA fingerprint pattern. Among the Australian isolates, DNA fingerprinting analysis identified 9 different VCGs and genotypes of Foc.

Cryptococcus statzelliae sp nov and three novel strains of Cryptococcus victoriae, yeasts isolated from Antarctic soils

A morphological and physiological characterization of yeast strains CBS 8908, CBS 8915, CBS 8920, CBS 8925(T) and CBS 8926, isolated from Antarctic soils, was performed. Phylogenetic analyses of the sequences of the D1/D2 regions and the adjacent internal transcribed spacer (ITS) regions of the large-subunit rDNA of these strains placed them into the Tremellales clade of the Hymenomycetes. The sequence data identified strains CBS 8908, CBS 8915 and CBS 8920 as belonging to the species Cryptococcus victoriae. Strains CBS 8925(T) and CBS 8926 were found to represent an unique clade within the Hymenomycetes, with Dioszegia crocea CBS 6714(T) being their closest phylogenetic relative. Fatty acid composition and proteome fingerprint data for these novel strains were also obtained. No sexual state was observed. A novel basidiomycetous species, Cryptococcus statzelliae, is proposed for strains CBS 8925(T) and CBS 8926.

Anogenital gland secretions of Lemur catta and Propithecus verreauxi coquereli: A preliminary chemical examination

Although prosimians are greatly olfaction-oriented, little is known about the specifics of how they use scent to communicate. In this preliminary study we attempted to delineate intra- and interspecific differences among the anogenital gland secretions of two lemur species (Lemur catta and Propithecus verreauxi coquereli) using gas chromatography-mass spectrometry (GC-MS). The results indicate that the two species are discernible through scent. Furthermore, we were able to identify reproductive status using this technique. The anogenital secretions of the different sexes in L. catta, though perhaps not P. v. coquereli, are chemically distinguishable. Given this information, it appears that at least some lemur species can use scent marks to determine species, sex, and reproductive status. (C) 2004 Wiley-Liss, Inc.

Evaluation of the effects of Candidatus Liberibacter asiaticus on inoculated citrus plants using laser-induced breakdown spectroscopy (LIBS) and chemometrics tools

This study investigated the organic and inorganic constituents of healthy leaves and Candidatus Liberibacter asiaticus (CLas)-inoculated leaves of citrus plants. The bacteria CLas are one of the causal agents of citrus greening (or Huanglongbing) and its effect on citrus leaves was investigated using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics. The information obtained from the LIBS spectra profiles with chemometrics analysis was promising for the construction of predictive models to identify healthy and infected plants. The major, macro- and microconstituents were relevant for differentiation of the sample conditions. The models were then applied to different inoculation times (from 1 to 8 months). The models were effective in the classification of 82-97% of the diseased samples with a 95% significance level. The novelty of this method was in the fingerprinting of healthy and diseased plants based on their organic and inorganic contents. (C) 2010 Elsevier B.V. All rights reserved.

Using MF-PCR to diagnose multiple defects from single cells: implications for PGD

Single cell genetic analysis is generally performed using PCR and FISH. Until recently, FISH has been the method of choice. FISH however is expensive, has significant misdiagnosis rates, can result in interpretation difficulties and is labour intensive making it unsuitable for high throughput processing. Recently fluorescent PCR reliability has increased to levels at or surpassing FISH whilst maintaining low cost. However, PCR accuracy has been a concern due to allelic dropout. Multiplex PCR can now increase accuracy by using multiple markers for each chromosome to firstly provide diagnosis if markers fail and,or secondly confirm diagnosis. We compare a variety of diagnostic methods and demonstrate for the first time a multiplex PCR system providing simultaneous diagnosis and confirmation of the major aneuploidy chromosomes (21, 18, 13) and sex as well as DNA fingerprint in single cells. We also discuss the implications of using PCR for aneuploidy screening in preimplantation genetic diagnosis. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

Identifying the origin of single corneal cells by DNA fingerprinting - Part I - Implications for corneal limbal allografting

Purpose. To demonstrate that the combination of impression cytology and single cell DNA fingerprinting represents a powerful tool that is suitable for detecting transplanted cells after corneal limbal allografting. Methods, Fifty single cells were obtained by corneal impression cytology from 12 patients undergoing cataract surgery. Individual cells were isolated from samples by micromanipulation. Polymerase chain reaction and short tandem repeat profiling was used to obtain forensic standard DNA fingerprints from single cells. Blood samples taken at the time of impression cytology provided control fingerprints. Results, informative DNA fingerprints were obtained from all corneal samples and 66% (33 of 50 cells) of isolated single cells, Of all fingerprints obtained, most (91%, 30 of 33 fingerprints) corneal fingerprints matched corresponding blond sample fingerprints. At least one corneal fingerprint matched the corresponding blood sample fingerprint in 83% (10 of 12 patients) of the patients in the study, Conclusions. This extremely specific single cell DNA fingerprinting system permits accurate identification of individual corneal epithelial cells, allowing very reliable determination of their origin, which will enable host and donor cells to be distinguished from each other after keratolimbal allografting procedures. even if the host and donor are the same sex or siblings. These DNA fingerprinting methods allow assessment of quality and quantity of donor cell survival, as well as survival time. The extreme sensitivity and accuracy of the technique means that should contamination occur, it would be identified, thus ensuring meaningful results.

Sistema de reconhecimento de impressões digitais baseado em FPGA

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

Plasmid composition and virulence-associated factors of Yersinia pestis isolates from a plague outbreak at the Paraíba State, Brazil

Pathogenic Yersinia pestis isolates were collected during a plague outbreak at the Paraiba State in 1986. The Y. pestis isolates were investigated for the presence of virulence-associated factors and plasmid content. All strains analysed were proficient in the expression of the VW and fraction 1 antigens, pigment adsorption and pesticin-fibronolysin-coagulase production. A similar plasmid profile composed by four plasmid with molecular weight of 60, 44, 14.9, and 6.4 Megadaltons (MD) was found in all strains. DNA cleavage with EcoRI restriction enzyme further demonstrated the uniform plasmid content of the Y. pestis isolates. Seven additional Y. pestis strains, previously isolated in the same region but in an endemic state, showed the same plasmid fingerprint. The lack of any detectable difference between epidemic and endemic isolates as well as the value of plasmid fingerprints in epidemiology of Y. pestis is discussed.

Freshwater arsenic detoxification through selenium-enriched food supplements. A proteomic approach

Dissertação apresentada para a obtenção do grau de doutor em Bioquímica pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Penicillium glabrum cork colonising isolates – preliminary analysis of their genomic similari

Cork stopper manufacturing process includes an operation, known as stabilisation, by which humid cork slabs are extensively colonised by fungi. The effects of fungal growth on cork are yet to be completely understood and are considered to be involved in the so called “cork taint” of bottled wine. It is essential to identify environmental constraints which define the appearance of the colonising fungal species and to trace their origin to the forest and/or as residents in the manufacturing space. The present article correlates two sets of data, from consecutive years and the same season, of systematic biologic sampling of two manufacturing units, located in the North and South of Portugal. Chrysonilia sitophila dominance was identified, followed by a high diversity of Penicillium species. Penicillium glabrum, found in all samples, was the most frequent isolated species. P. glabrum intra-species variability was investigated using DNA fingerprinting techniques revealing highly discriminative polymorphic markers in the genome. Cluster analysis of P. glabrum data was discussed in relation to the geographical location of strains, and results suggest that P. glabrum arise from predominantly the manufacturing space, although cork resident fungi can also contrib

Importance of hand germ contamination in health-care workers as possible carriers of nosocomial infections

The importance of hands in the transmission of nosocomial infection has been world wide admitted. However, it is difficult to induce this behavior in health-care workers. The aim of the present work was to point out the importance of hand bacteria colonization, the influence of hand washing and of patient physical examination. One hundred health-care workers were randomly divided in two groups: Group A without hand washing previous to patient physical examination or handling (PPE); group B with hand washing previous to PPE. Direct fingerprint samples in Columbia agar before and after PPE were obtained. The colonies were counted and identified by conventional techniques, and antibiograms according to NCCLS were performed. Before PPE group A participants showed a high number of bacteria regarding group B participants (73.9 Vs 20.7; p < 0.001); 44 out of 50 participants were carriers of potentially pathogen bacteria. No group B participants were carriers of potential pathogen bacteria before PPE. The latter group showed an increase in number of bacteria after PPE (20.7 CFU (before) Vs 115.9 CFU (after); p < 0.001). Sixteen group B participants were contaminated after PPE with potential pathogens such as S. aureus (50% of them meticillin resistant); Escherichia coli, Pseudomonas aeruginosa and Enterococcus faecalis, half of them multiresistant. We can conclude on the importance of these results to implement educational programs and to provide the health-care workers with the proper commodities to fulfill this practice.

Gold nanoparticles for the detection of DNA adducts as biomarkers of exposure to acrylamide

The main objective of this thesis was the development of a gold nanoparticle-based methodology for detection of DNA adducts as biomarkers, to try and overcome existing drawbacks in currently employed techniques. For this objective to be achieved, the experimental work was divided in three components: sample preparation, method of detection and development of a model for exposure to acrylamide. Different techniques were employed and combined for de-complexation and purification of DNA samples (including ultrasonic energy, nuclease digestion and chromatography), resulting in a complete protocol for sample treatment, prior to detection. The detection of alkylated nucleotides using gold nanoparticles was performed by two distinct methodologies: mass spectrometry and colorimetric detection. In mass spectrometry, gold nanoparticles were employed for laser desorption/ionisation instead of the organic matrix. Identification of nucleotides was possible by fingerprint, however no specific mass signals were denoted when using gold nanoparticles to analyse biological samples. An alternate method using the colorimetric properties of gold nanoparticles was employed for detection. This method inspired in the non-cross-linking assay allowed the identification of glycidamide-guanine adducts and DNA adducts generated in vitro. For the development of a model of exposure, two different aquatic organisms were studies: a goldfish and a mussel. Organisms were exposed to waterborne acrylamide, after which mortality was recorded and effect concentrations were estimated. In goldfish, both genotoxicity and metabolic alterations were assessed and revealed dose-effect relationships of acrylamide. Histopathological alterations were verified primarily in pancreatic cells, but also in hepatocytes. Mussels showed higher effect concentrations than goldfish. Biomarkers of oxidative stress, biotransformation and neurotoxicity were analysed after prolonged exposure, showing mild oxidative stress in mussel cells, and induction of enzymes involved in detoxification of oxygen radicals. A qualitative histopathological screening revealed gonadotoxicity in female mussels, which may present some risk to population equilibrium.

Advances in microbial diagnosis: using mass spectrometry for proteomics and genomics applications

Since the last two decades mass spectrometry (MS) has been applied to analyse the chemical cellular components of microorganisms, providing rapid and discriminatory proteomic profiles for their species identification and, in some cases, subtyping. The application of MS for the microbial diagnosis is currently well-established. The remarkable reproducibility and objectivity of this method is based on the measurement of constantly expressed and highly abundant proteins, mainly important conservative ribosomal proteins, which are used as markers to generate a cellular fingerprint. Mass spectrometry based on matrix-assisted laser desorption ionization-time of flight (MALDI- TOF) technique has been an important tool for the microbial diagnostic. However, some technical limitation concerning both MALDI-TOF and its used protocols for sample preparation have fostered the research of new mass spectrometry systems (e.g. LC MS/MS). LC MS/MS is able to generate online mass spectra of specific ions with further online sequencing of these ions, which include both specific proteins and DNA fragments. In this work a set of data for yeasts and filamentous fungi diagnostic obtained through an international collaboration project involving partners from Argentina, Brazil, Chile and Portugal will be presented and discussed.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.