Staphylococcal enterotoxins: molecular aspects and detection methods

Members of the Staphylococcus genus, especially Staphylococcus aureus, are the most common pathogens found in hospitals and in community-acquired infections. Some of their pathogenicity is associated with enzyme and toxin production. Until recently, S. aureus was the most studied species in the genus; however, in last few years, the rise of infections caused by coagulase-negative staphylococci has pointed out the need for further studies on virulence factors that have not yet been completely elucidated so as to better characterize the pathogenic potential of this group of microorganisms. Several staphylococcal species produce enterotoxins, a family of related proteins responsible for many diseases, such as the toxic-shock syndrome, septicemia and food poisoning. To this date, 23 different enterotoxin types have been identified besides toxic-shock syndrome toxin-1 (TSST-1), and they can be divided into five phylogenetic groups. The mechanism of action of these toxins includes superantigen activity and emetic properties, which can lead to biological effects of infection. Various methods can detect genes that encode enterotoxins and their production. Molecular methods are the most frequently used at present. This review article has the objective to describe aspects related to the classification, structure and regulation of enterotoxins and toxic-shock syndrome toxin-1 detection methods.

Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Provisional Biopharmaceutical Classification of Some Common Herbs Used in Western Medicine

The aim of this study was to classify some markers of common herbs used in Western medicine according to the Biopharmaceutical Classification System (BCS). The BCS is a scientific approach to classify drug substances based upon their intestinal permeability and their solubility, at the highest single dose used, within the physiologically relevant pH ranges. Known marker components of twelve herbs were chosen from the USP Dietary Supplement Compendium Monographs. Different BCS parameters such as intestinal permeability (P-eff) and solubility (C-s) were predicted using the ADMET Predictor, which is a software program to estimate biopharmaceutical relevant molecular descriptors. The dose number (D-0) was calculated when information from the literature was available to identify an upper dose for individual markers. In these cases the herbs were classified according to the traditional BCS parameters using Peff and Do. When no upper dose could be determined, then the amount of a marker that is just soluble in 250 mL of water was calculated. This value, M-x, defines when a marker is changing from highly soluble to poorly soluble according to BCS criteria. This biopharmaceutically relevant value can be a useful tool for marker selection. The present study showed that a provisional BCS classification of herbs is possible but some special considerations need to be included into the classification strategy. The BCS classification can be used to choose appropriate quality control tests for products containing these markers. A provisional BCS classification of twelve common herbs and their 35 marker compounds is presented.

A New Subgeneric Classification of Rhipsalis (Cactoideae, Cactaceae)

Most Cactaceae have succulent stems and inhabit dry or arid areas, but some are epiphytes of humid regions. Rhipsalis is the largest genus of epiphytic cacti. Species of Rhipsalis are notoriously difficult to identify, and the subgeneric classification of the genus has remained controversial. Between 1837 and 1995, eight different subgeneric classifications have been proposed for Rhipsalis. The most comprehensive taxonomic treatment of the genus recognized five subgenera, Phyllarthrorhipsalis, Rhipsalis, Epallagogonium, Calamorhipsalis, and Erythrorhipsalis, characterized mainly by stem morphology. Here, molecular phylogenetic information combined with morphological data is used to re-evaluate the former subgeneric classifications proposed for the genus. Three monophyletic subgenera are recognized, Rhipsalis, Calamorhipsalis and Erythrorhipsalis, which are mainly characterized by floral traits. The changes proposed include expanding the circumscription of Rhipsalis by the inclusion of species previously included in Phyllarthrorhipsalis and Epallagogoniwn and recognizing a broader Calamorhipsalis, also including species from subgenus Epallagogonium. The circumscription of Erythrorhipsalis remains unchanged. For each subgenus a list of synonyms, a brief description and a list of species included are presented. A key for the identification of subgenera is also provided.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

Pathophysiology and molecular aspects of diffuse large B-cell lymphoma

Diffuse large B-Cell lymphoma is the most common subtype of non-Hodgkin lymphoma in the West. In Brazil, it is the fifth cause of cancer, with more than 55,000 cases and 26,000 deaths per year. At Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo - HCFMUSP, diffuse large B-Cell lymphoma represents 49.7% of all non-Hodgkin lymphoma cases. Initially, the classification of non-Hodgkin lymphoma was based on morphology, but advances in immunology and molecular medicine allowed the introduction of a biological classification for these diseases. As for other cancers, non-Hodgkin lymphoma involves patterns of multi factorial pathogenesis with environmental factors, as well as genetic, occupational and dietary factors, contributing to its development. Multiple lesions involving molecular pathways of B-cell proliferation and differentiation may result in the activation of oncogenes such as the BCL2, BCL6,and MYC genes and the inactivation of tumor suppressor genes such as p53 and INK4, as well as other important transcription factors such as OCT-1 and OCT-2. A dramatic improvement in survival was seen after the recent introduction of the anti-CD20 monoclonal antibody. The association of this antibody to the cyclophosphamide, hydroxydaunorubicin, oncovin and prednisolone (CHOP) regimen has increased overall survival of diffuse large B-Cell lymphoma and follicular lymphoma patients by 20%. However, 50% of all diffuse large B-Cell lymphoma patients remain incurable, creating a demand for more research with new advances in treatment. Thus, it is important to know and understand the key factors and molecular pathways involved in the pathogenesis of diffuse large B-Cell lymphoma.

Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).

Molecular method for the characterization of Coxiella burnetii from clinical and environmental samples: variability of genotypes in Spain

[EN] Background. Coxiella burnetii is a highly clonal microorganism which is difficult to culture, requiring BSL3 conditions for its propagation. This leads to a scarce availability of isolates worldwide. On the other hand, published methods of characterization have delineated up to 8 different genomic groups and 36 genotypes. However, all these methodologies, with the exception of one that exhibited limited discriminatory power (3 genotypes), rely on performing between 10 and 20 PCR amplifications or sequencing long fragments of DNA, which make their direct application to clinical samples impracticable and leads to a scarce accessibility of data on the circulation of C. burnetii genotypes. Results: To assess the variability of this organism in Spain, we have developed a novel method that consists of a multiplex (8 targets) PCR and hybridization with specific probes that reproduce the previous classification of this organism into 8 genomic groups, and up to 16 genotypes. It allows for a direct characterization from clinical and environmental samples in a single run, which will help in the study of the different genotypes circulating in wild and domestic cycles as well as from sporadic human cases and outbreaks. The method has been validated with reference isolates. A high variability of C. burnetii has been found in Spain among 90 samples tested, detecting 10 different genotypes, being those adaA negative associated with acute Q fever cases presenting as fever of intermediate duration with liver involvement and with chronic cases. Genotypes infecting humans are also found in sheep, goats, rats, wild boar and ticks, and the only genotype found in cattle has never been found among our clinical samples. Conclusions: This newly developed methodology has permitted to demonstrate that C. burnetii is highly variable in Spain. With the data presented here, cattle seem not to participate in the transmission of C. burnetii to humans in the samples studied, while sheep, goats, wild boar, rats and ticks share genotypes with the human population.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Novel isolates of Cydia pomonella granulovirus (CpGV): deciphering the molecular mechanism for overcoming CpGV resistance in codling moth (Cydia pomonella)

During the last twenty years, Cydia pomonolla granulovirus (CpGV, Baculoviridae) has become the most important biological control agent for the codling moth (CM) in organic and integrated apple production. All registered products in Europe are based on the isolate CpGV-M, which was discovered 1964 in Mexico. A serious threat to future application of CpGV is the occurrence of CM field populations resistant to CpGV. Since 2003, populations with up to 10,000-fold reduced susceptibility were reported from orchards in Germany, France, Italy, Switzerland, Austria and the Netherlands. A putative alternative to CpGV-M are novel CpGV isolates which are able to overcome CM resistance. This thesis focuses on the identification and characterisation of resistance overcoming CpGV isolates and the analysis of their molecular difference to CpGV-M.rnSixteen CpGV isolates were tested against CM lab strains in bioassays. Hereby, five isolates were identified which were able to completely overcome resistance. The genomes of these isolates were compared to CpGV-M by restriction fragment length polymorphism (RFLP) analysis. To identify the molecular factor responsible for improved virulence of some CpGV isolates, major genomic differences were sequenced and analysed. A 0.7 kb insertion was found in CpGV-I01, -I12 and -E2, but not in other resistance overcoming isolates. Analysis of the insertions sequence revealed that it might be due to a transposition event, but not involved in overcoming resistance. rnFor unequivocal identification of CpGV isolates, a new method based on molecular analysis was established. Partial sequencing of the conserved polyhedrin/granulin (polh/gran), late expression factor-8 (lef-8) and late expression factor-9 (lef-9) genes revealed single nucleotide polymorphisms (SNPs). SNP analysis correlated with the grouping obtained by RFLP analysis. A phylogenetic classification due to different genome types A-E is proposed. Phylogenetic analysis suggested that CpGV-M was the phylogenetically youngest of the tested CpGV isolates.rnWhole genome sequencing of two resistance overcoming isolates CpGV-I12 (type D genome) and -S (type E genome) and CpGV-M (type A genome) was performed. Comparison of the three genomes revealed a high sequence identity. Several insertions and deletions ranging from 1-700 nucleotides (nt) were found. Comparison on open reading frame (ORF) level revealed that CpGV-I12 and -S shared only one protein alteration when compared to CpGV-M: a stretch of 24 nt present in ORF cp24 was not found in any of the resistance overcoming isolates. Cp24 codes for the early gene pe38. Combined with the results of phylogenetic analysis, it is proposed that these 24 nt are a recent insertion into the CpGV-M genome. The role of pe38 in overcoming resistance was investigated by knocking out pe38 of a CpGV-M based bacmid and swapping of CpGV-I12 pe38 of into the k.o. bacmid. When pe38 of CpGV-I12 was inserted into the k.o. bacmid, the infectivity could not be rescued, suggesting that the genomic portion of pe38 might play a role in its function.rnIt can be concluded that the recently observed CpGV resistance in CM is only related to type A genomes. RFLP and SNP analysis provide tools for identifying and characterising different CpGV isolates reliably, a pre-condition for a future registration of CpGV products based on novel CpGV isolates.rnrnrn

Comprehensive analysis of CpG island methylator phenotype (CIMP)-high, -low, and -negative colorectal cancers based on protein marker expression and molecular features

CpG island methylator phenotype (CIMP) is being investigated for its role in the molecular and prognostic classification of colorectal cancer patients but is also emerging as a factor with the potential to influence clinical decision-making. We report a comprehensive analysis of clinico-pathological and molecular features (KRAS, BRAF and microsatellite instability, MSI) as well as of selected tumour- and host-related protein markers characterizing CIMP-high (CIMP-H), -low, and -negative colorectal cancers. Immunohistochemical analysis for 48 protein markers and molecular analysis of CIMP (CIMP-H: ? 4/5 methylated genes), MSI (MSI-H: ? 2 instable genes), KRAS, and BRAF were performed on 337 colorectal cancers. Simple and multiple regression analysis and receiver operating characteristic (ROC) curve analysis were performed. CIMP-H was found in 24 cases (7.1%) and linked (p < 0.0001) to more proximal tumour location, BRAF mutation, MSI-H, MGMT methylation (p = 0.022), advanced pT classification (p = 0.03), mucinous histology (p = 0.069), and less frequent KRAS mutation (p = 0.067) compared to CIMP-low or -negative cases. Of the 48 protein markers, decreased levels of RKIP (p = 0.0056), EphB2 (p = 0.0045), CK20 (p = 0.002), and Cdx2 (p < 0.0001) and increased numbers of CD8+ intra-epithelial lymphocytes (p < 0.0001) were related to CIMP-H, independently of MSI status. In addition to the expected clinico-pathological and molecular associations, CIMP-H colorectal cancers are characterized by a loss of protein markers associated with differentiation, and metastasis suppression, and have increased CD8+ T-lymphocytes regardless of MSI status. In particular, Cdx2 loss seems to strongly predict CIMP-H in both microsatellite-stable (MSS) and MSI-H colorectal cancers. Cdx2 is proposed as a surrogate marker for CIMP-H.

Molecular definitions of cell death subroutines: recommendations of the Nomenclature Committee on Cell Death 2012

In 2009, the Nomenclature Committee on Cell Death (NCCD) proposed a set of recommendations for the definition of distinct cell death morphologies and for the appropriate use of cell death-related terminology, including 'apoptosis', 'necrosis' and 'mitotic catastrophe'. In view of the substantial progress in the biochemical and genetic exploration of cell death, time has come to switch from morphological to molecular definitions of cell death modalities. Here we propose a functional classification of cell death subroutines that applies to both in vitro and in vivo settings and includes extrinsic apoptosis, caspase-dependent or -independent intrinsic apoptosis, regulated necrosis, autophagic cell death and mitotic catastrophe. Moreover, we discuss the utility of expressions indicating additional cell death modalities. On the basis of the new, revised NCCD classification, cell death subroutines are defined by a series of precise, measurable biochemical features.

Mining for Class-Specific Motifs in Protein Sequence Classification

Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.

Pathogenesis and classification of eosinophil disorders: a review of recent developments in the field

Eosinophils and their products play an essential role in the pathogenesis of various reactive and neoplastic disorders. Depending on the underlying disease, molecular defect and involved cytokines, hypereosinophilia may develop and may lead to organ damage. In other patients, persistent eosinophilia is accompanied by typical clinical findings, but the causative role and impact of eosinophilia remain uncertain. For patients with eosinophil-mediated organ pathology, early therapeutic intervention with agents reducing eosinophil counts can be effective in limiting or preventing irreversible organ damage. Therefore, it is important to approach eosinophil disorders and related syndromes early by using established criteria, to perform all appropriate staging investigations, and to search for molecular targets of therapy. In this article, we review current concepts in the pathogenesis and evolution of eosinophilia and eosinophil-related organ damage in neoplastic and non-neoplastic conditions. In addition, we discuss classifications of eosinophil disorders and related syndromes as well as diagnostic algorithms and standard treatment for various eosinophil-related disorders.

Classification of acute and delayed contrast media-induced reactions: proposal of a three-step system

Physicians and scientists use a broad spectrum of terms to classify contrast media (CM)-induced adverse reactions. In particular, the designation of hypersensitivity reactions is quite varied. Consequently, comparisons of different papers dealing with this subject are difficult or even impossible. Moreover, general descriptions may lead to problems in understanding reactions in patients with a history of adverse CM-reactions, and in efficiently managing these patients. Therefore, the goal of this paper is to suggest an easy system to clearly classify these reactions. The proposed three-step systems (3SS) is built up as follows: step 1 exactly describes the clinical features, including their severity; step 2 categorizes the time point of the onset (immediate or nonimmediate); and step 3 generally classifies the reaction (hypersensitivity or nonhypersensitivity reaction). The 3SS may facilitate better understanding of the clinical manifestations of adverse CM reactions and may support the prevention of these reactions on the basis of personalized medicine approaches.