Intraspecific sequence variation in 16S rRNA gene of Ureaplasma diversum isolates

Ureaplasma diversum infection in bulls may result in seminal vesiculitis, balanoposthitis and alterations in spermatozoids. In cows, it can cause placentitis, fetal alveolitis, abortion and the birth of weak calves. U. diversum ATCC 49782 (serogroups A), ATCC 49783 (serogroup C) and 34 field isolates were used for this study. These microorganisms were submitted to Polymerase Chain Reaction for 16S gene sequence determination using Tact High Fidelity and the products were purified and bi-directionally sequenced. Using the sequence obtained, a fragment containing four hypervariable regions was selected and nucleotide polymorphisms were identified based on their position within the 16S rRNA gene. Forty-four single nucleotide polymorphisms (SNP) were detected. The genotypic variability of the 16S rRNA gene of U. diversum isolates shows that the taxonomy classification of these organisms is likely much more complex than previously described and that 16S rRNA gene sequencing may be used to suggest an epidemiologic pattern of different origin strains. (c) 2011 Elsevier B.V. All rights reserved.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

Multi-objective clustering ensemble for gene expression data analysis

In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a special crossover operator, which uses clustering validation measures as objective functions. The algorithm proposed can deal with data sets presenting different types of clusters, without the need of expertise in cluster analysis. its result is a concise set of partitions representing alternative trade-offs among the objective functions. We compare the results obtained with our algorithm, in the context of gene expression data sets, to those achieved with multi-objective Clustering with automatic K-determination (MOCK). the algorithm most closely related to ours. (C) 2009 Elsevier B.V. All rights reserved.

Interaction of oligonucleotide-based amphiphilic block copolymers with cell membrane models

Oligonucleotides have unique molecular recognition properties, being involved in biological mechanisms such as cell-surface receptor recognition or gene silencing. For their use in human therapy for drug or gene delivery, the cell membrane remains a barrier, but this can be obviated by grafting a hydrophobic tail to the oligonucleotide. Here we demonstrate that two oligonucleotides, one consisting of 12 guanosine units (G(12)), and the other one consisting of five adenosine and seven guanosine (A(5)G(7)) units, when functionalized with poly(butadiene), namely PB-G(12) and PB-A(5)G(7), can be inserted into Langmuir monolayers of dipalmitoyl phosphatidyl choline (DPPC), which served as a cell membrane model. PB-G(12) and PB-A(5)G(7) were found to affect the DPPC monolayer even at high surface pressures. The effects from PB-G(12) were consistently stronger, particularly in reducing the elasticity of the DPPC monolayers, which may have important biological implications. Multilayers of DPPC and nucleotide-based copolymers could be adsorbed onto solid supports, in the form of Y-type LB films, in which the molecular-level interaction led to lower energies in the vibrational spectra of the nucleotide-based copolymers. This successful deposition of solid films opens the way for devices to be produced which exploit the molecular recognition properties of the nucleotides. (C) 2010 Elsevier Inc. All rights reserved.

Ultrasensitive SERS nanoprobes for hazardous metal ions based on trimercaptotriazine-modified gold nanoparticles

Trimercaptotriazine-modified gold nanoparticles exhibit strong SERS effects,(1) yielding vibrational profiles very sensitive to the presence of heavy metal ions. Because of the contrasting response observed for selected vibrational bands in the SERS profiles, they provide useful nanoprobes for Hg2+ and Cd2+ ions, allowing direct quantitative assays by employing relative peak intensity ratios instead of using internal standards.

GENOTYPE CHARACTERIZATION OF THE Haematobia irritans (DIPTERA: MUSCIDAE) FROM BRAZIL, DOMINICAN REPUBLIC AND COLOMBIA BASED ON RANDOMLY AMPLIFIED POLYMORPHIC DNA (RAPD) ANALYSIS

Blood-sucking flies are important parasites in animal production systems, especially regarding confinement conditions. Haematobia irritans, the horn fly, is one of the most troublesome species within bovine production systems, due to the intense stress imposed to the animals. H. irritans is one of the parasites of cattle that cause significant economic losses in many parts of the world, including South America. In the present work, Brazilian, Colombian and Dominican Republic populations of this species were studied by Random Amplified Polymorphic DNA(RAPD) to assess basically genetic variability between populations. Fifteen different decamer random primers were employed in the genomic DNA amplification, yielding 196 fragments in the three H. irritans populations. Among h. irritans samples, that from Colombia produced the smallest numbers of polymorphic hands. This high genetic homogeneity may be ascribed to its geographic origin, which causes high isolation, low gene flow, unlike the other American populations, from Brazil and Dominican Republic. Molecular marker fragments, which its produced exclusive bands, detected in every sample enabled the population origin to be characterized, but they are also potentially useful for further approaches such as the putative origin of Brazilian, Colombian and Dominican Republic populations of horn fly from South America. Similarity indices produced by chemo metric analysis showed the closest relationships between flies from Brazil and Dominican Republic, while flies from Colombia showed the greatest genotypic differentiation relative to the others populations.

Simple telemedicine for developing regions: Camera phones and paper-based microfluidic devices for real-time, off-site diagnosis

This article describes a prototype system for quantifying bioassays and for exchanging the results of the assays digitally with physicians located off-site. The system uses paper-based microfluidic devices for running multiple assays simultaneously, camera phones or portable scanners for digitizing the intensity of color associated with each colorimetric assay, and established communications infrastructure for transferring the digital information from the assay site to an off-site laboratory for analysis by a trained medical professional; the diagnosis then can be returned directly to the healthcare provider in the field. The microfluidic devices were fabricated in paper using photolithography and were functionalized with reagents for colorimetric assays. The results of the assays were quantified by comparing the intensities of the color developed in each assay with those of calibration curves. An example of this system quantified clinically relevant concentrations of glucose and protein in artificial urine. The combination of patterned paper, a portable method for obtaining digital images, and a method for exchanging results of the assays with off-site diagnosticians offers new opportunities for inexpensive monitoring of health, especially in situations that require physicians to travel to patients (e.g., in the developing world, in emergency management, and during field operations by the military) to obtain diagnostic information that might be obtained more effectively by less valuable personnel.

Characterization of AFN1, a Gene Associated with Cereal Grain Germination

The AFN1 gene is transiently expressed in germinating oat grains. As AFN1 is not expressed in dormant oat grains during imbibition, we hypothesize that AFN1 may be involved in stimulating the germination process. Sequence analysis of an AFN1 cDNA clone indicates that the AFN1 polypeptide is similar to a previously identified abscisic acid (ABA) glucosyl transferase. This suggests that AFN1 may be acting to glucosylate ABA, thereby inactivating it. As the hormone ABA is known to inhibit germination, ABA glucosylation/inactivation could lead to germination in grains expressing AFN1. To test this hypothesis, we have constructed an expression plasmid that encodes an MBP::AFN1 (maltose binding protein) fusion protein. E. coli cells carrying the expression plasmid were found to produce the MBP::AFN1 fusion protein as a substantial fraction of total protein. We are currently in the process of purifying the MBP::AFN1 fusion protein by affinity chromatography, so that it can be assayed for ABA glucosyl transferase activity. We also wish to test the effect of AFN1 gene expression during grain imbibition on the germination behavior of the grains. To this end, we have constructed plasmids for the overexpression and RNAi-based suppression of AFN1 in transgenic plants. These plasmids have been introduced into oat cells by particle bombardment and we are in the process of regenerating transgenic plants for study.

The role of TaABF1 in abscisic acid-mediated suppression of -amylase gene expression in cereal grains

The phytohormones gibberellin (GA) and abscisic acid (ABA) regulate important developments events in germinating seeds. Specifically, GA induces the expression of hyrolase genes, like the α-amylase gene Amy32b, which mobilizes starch reserves to be used by the embryo, and ABA suppresses this induction. Recent advancements identified ABA and GA receptors and key components in the signaling pathways, however, the mechanism of crosstalk between the hormones remains largely unknown. To further elucidate the mechanism of ABA suppression of GA-induced genes, we focused on the transcription factor TaABF1, a member of the ABA response element binding factor family. TaABF1 has been shown to physically interact with the SnRK2 kinase PKABA1 and overexpression of TaABF1 or PKABA1 can suppress Amy32b. We carried out particle bombardment experiments to investigate how TaABF1 suppresses Amy32b and how TaABF1 is activated by ABA. The role of TaABF1 in ABA-mediated suppression of Amy32b is more complicated than hypothesized. Unlike PKABA1, overexpression of TaABF1 did not cause a decrease of GAMyb expression and in fact resulted in an increase of GAMyb expression. When TaABF1 and GAMyb were simultaneously overexpressed in aleurone, the GAMyb induction of Amy32b was unaffected, indicating that the target of TaABF1 action must be upstream of GAMyb. Furthermore, TaABF1 and ABA demonstrated an additive effect on the suppression of Amy32b. Based on our findings, we propose a model in which PKABA1 activates two separate targets, one being TaABF1 which then modifies an unknown target upstream of GAMyb and the other being an unknown transcription factor that suppresses GAMyb transcription.