Identification and Characterization of Ixodes scapularis Antigens That Elicit Tick Immunity Using Yeast Surface Display

Repeated exposure of rabbits and other animals to ticks results in acquired resistance or immunity to subsequent tick bites and is partially elicited by antibodies directed against tick antigens. In this study we demonstrate the utility of a yeast surface display approach to identify tick salivary antigens that react with tick-immune serum. We constructed an Ixodes scapularis nymphal salivary gland yeast surface display library and screened the library with nymph-immune rabbit sera and identified five salivary antigens. Four of these proteins, designated P8, P19, P23 and P32, had a predicted signal sequence. We generated recombinant (r) P8, P19 and P23 in a Drosophila expression system for functional and immunization studies. rP8 showed anti-complement activity and rP23 demonstrated anti-coagulant activity. Ixodes scapularis feeding was significantly impaired when nymphs were fed on rabbits immunized with a cocktail of rP8, rP19 and rP23, a hall mark of tick-immunity. These studies also suggest that these antigens may serve as potential vaccine candidates to thwart tick feeding.

Crystallization and preliminary X-ray diffraction analysis of a glutathione S-transferase from Xylella fastidiosa

Glutathione S-transferases (GSTs) form a group of multifunctional isoenzymes that catalyze the glutathione-dependent conjugation and reduction reactions involved in the cellular detoxification of xenobiotic and endobiotic compounds. GST from Xylella fastidiosa (xfGST) was overexpressed in Escherichia coli and purified by conventional affinity chromatography. In this study, the crystallization and preliminary X-ray analysis of xfGST is described. The purified protein was crystallized by the vapour-diffusion method, producing crystals that belonged to the triclinic space group P1. The unit-cell parameters were a = 47.73, b = 87.73, c = 90.74 angstrom, alpha = 63.45, beta = 80.66, gamma = 94.55 degrees. xfGST crystals diffracted to 2.23 angstrom resolution on a rotating-anode X-ray source.

Purification, crystallization and preliminary crystallographic analysis of the catalytic domain of the extracellular cellulase CBHI from Trichoderma harzianum

The filamentous fungus Trichoderma harzianum has a considerable cellulolytic activity that is mediated by a complex of enzymes which are essential for the hydrolysis of microcrystalline cellulose. These enzymes were produced by the induction of T. harzianum with microcrystalline cellulose (Avicel) under submerged fermentation in a bioreactor. The catalytic core domain (CCD) of cellobiohydrolase I (CBHI) was purified from the extracellular extracts and submitted to robotic crystallization. Diffraction-quality CBHI CCD crystals were grown and an X-ray diffraction data set was collected under cryogenic conditions using a synchrotron-radiation source.

Identification of the Schistosoma mansoni TNF-Alpha Receptor Gene and the Effect of Human TNF-Alpha on the Parasite Gene Expression Profile

Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

Crystallization and preliminary X-ray diffraction analysis of human IL-22 bound to its soluble decoy receptor IL-22BP

Interleukin-22 (IL-22) is a pleiotropic cytokine that is involved in inflammatory responses. Human IL-22 was incubated with its soluble decoy receptor IL-22BP (IL-22 binding protein) and the IL-22 -IL-22BP complex was crystallized in hanging drops using the vapour-diffusion method. Suitable crystals were obtained from polyethylene glycol solutions and diffraction data were collected to 2.75 angstrom resolution. The crystal belonged to the tetragonal space group P41, with unit-cell parameters a = b = 67.9, c = 172.5 angstrom, and contained two IL-22-IL- 22BP complexes per asymmetric unit.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Identification of protein-coding and non-coding RNA expression profiles in CD34(+) and in stromal cells in refractory anemia with ringed sideroblasts

Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Identification of Novel Immunoregulatory Molecules in Human Thymic Regulatory CD4(+)CD25(+) T Cells by Phage Display

Thymic CD4(+)CD25(+) cells play an important role in immune regulation and are continuously developed in the thymus as an independent lineage. How these cells are generated, what are their multiple pathways of suppressive activity and which are their specific markers are questions that remain unanswered. To identify molecules involved in the function and development of human CD4(+)CD25(+) T regulatory cells we targeted thymic CD4(+)CD25(+) cells by peptide phage display. A phage library containing random peptides was screened ex vivo for binding to human thymic CD4(+)CD25(+) T cells. After four rounds of selection on CD4(+)CD25(+) enriched populations of thymocytes, we sequenced several phage displayed peptides and selected one with identity to the Vitamin D Receptor (VDR). We confirmed the binding of the VDR phage to active Vitamin D in vitro, as well as the higher expression of VDR in CD4(+)CD25(+) cells. We suggest that differential expression of VDR on natural Tregs may be related to the relevance of Vitamin D in function and ontogeny of these cells.

GPIomics: global analysis of glycosylphosphatidylinositol-anchored molecules of Trypanosoma cruzi

Glycosylphosphatidylinositol (GPI) anchoring is a common, relevant posttranslational modification of eukaryotic surface proteins. Here, we developed a fast, simple, and highly sensitive (high attomole-low femtomole range) method that uses liquid chromatography-tandem mass spectrometry (LC-MS(n)) for the first large-scale analysis of GPI-anchored molecules (i.e., the GPIome) of a eukaryote, Trypanosoma cruzi, the etiologic agent of Chagas disease. Our genome-wise prediction analysis revealed that approximately 12% of T. cruzi genes possibly encode GPI-anchored proteins. By analyzing the GPIome of T. cruzi insect-dwelling epimastigote stage using LC-MS(n), we identified 90 GPI species, of which 79 were novel. Moreover, we determined that mucins coded by the T. cruzi small mucin-like gene (TcSMUG S) family are the major GPI-anchored proteins expressed on the epimastigote cell surface. TcSMUG S mucin mature sequences are short (56-85 amino acids) and highly O-glycosylated, and contain few proteolytic sites, therefore, less likely susceptible to proteases of the midgut of the insect vector. We propose that our approach could be used for the high throughput GPIomic analysis of other lower and higher eukaryotes. Molecular Systems Biology 7 April 2009; doi:10.1038/msb.2009.13

Diversity and identification of methanogenic archaea and sulphate-reducing bacteria in sediments from a pristine tropical mangrove

Mangrove sediments are anaerobic ecosystems rich in organic matter. This environment is optimal for anaerobic microorganisms, such as sulphate-reducing bacteria and methanogenic archaea, which are responsible for nutrient cycling. In this study, the diversity of these two functional guilds was evaluated in a pristine mangrove forest using denaturing gradient gel electrophoresis (DGGE) and clone library sequencing in a 50 cm vertical profile sampled every 5.0 cm. DGGE profiles indicated that both groups presented higher richness in shallow samples (0-30 cm) with a steep decrease in richness beyond that depth. According to redundancy analysis, this alteration significantly correlated with a decrease in the amount of organic matter. Clone library sequencing indicated that depth had a strong effect on the selection of dissimilatory sulphate reductase (dsrB) operational taxonomic units (OTUs), as indicated by the small number of shared OTUs found in shallow (0.0 cm) and deep (40.0 cm) libraries. On the other hand, methyl coenzyme-M reductase (mcrA) libraries indicated that most of the OTUs found in the shallow library were present in the deep library. These results show that these two guilds co-exist in these mangrove sediments and indicate important roles for these organisms in nutrient cycling within this ecosystem.

No-match ORESTES explored as tumor markers

Sequencing technologies and new bioinformatics tools have led to the complete sequencing of various genomes. However, information regarding the human transcriptome and its annotation is yet to be completed. The Human Cancer Genome Project, using ORESTES (open reading frame EST sequences) methodology, contributed to this objective by generating data from about 1.2 million expressed sequence tags. Approximately 30 of these sequences did not align to ESTs in the public databases and were considered no-match ORESTES. On the basis that a set of these ESTs could represent new transcripts, we constructed a cDNA microarray. This platform was used to hybridize against 12 different normal or tumor tissues. We identified 3421 transcribed regions not associated with annotated transcripts, representing 83.3 of the platform. The total number of differentially expressed sequences was 1007. Also, 28 of analyzed sequences could represent noncoding RNAs. Our data reinforces the knowledge of the human genome being pervasively transcribed, and point out molecular marker candidates for different cancers. To reinforce our data, we confirmed, by real-time PCR, the differential expression of three out of eight potentially tumor markers in prostate tissues. Lists of 1007 differentially expressed sequences, and the 291 potentially noncoding tumor markers were provided.

Identification of the biodiesel source using an electronic nose

Biodiesel is an important new alternative fuel. The feedstock used and the process employed determines whether it fulfills the required specifications. In this work, an identification method is proposed using an electronic nose (e-nose). Four samples of biodiesel from different sources and one of petrodiesel were analyzed and well-recognized by the e-nose. Both pure biodiesel and B20 blends were studied. Furthermore, an innovative semiquantitative method is proposed on the basis of the smellprints correlated by a feed-forward artificial neural network. The results have demonstrated that the e-nose can be used to identify the biodiesel source and as a preliminary quantitative assay in place of expensive equipment.

Novel Isolates for Biological Detoxification of Lignocellulosic Hydrolysate

In this paper, two new strians, Issatchenkia occidentalis (Lj-3, CCTCC M 2006097) and Issatchenkia orienalis (S-7, CCTCC M 2006098), isolated from different environments on solid media, were used in the detoxification process of the hemicellulosic hydrolysate of sugarcane bagasse. High-pressure liquid chromatography elution curve of UV-absorption compounds represented by acetic acid, furfural, and guaiacol (toxic compounds found in the hemicellulosic hydrolysate) showed that several chromatographic peaks were evidently diminished for the case of detoxified hydrolysate with isolate strains compared to the high peaks resulted for no detoxified hydrolysate. It was clear that these inhibitors were degraded by the two new isolates during their cultivation process. Fermentation results for the biodetoxified hydrolysate showed an increase in xylitol productivity (Q (p)) by 1.97 and 1.95 times (2.03 and 2.01 g l(-1) h(-1)) and in xylitol yield (Y (p)) by 1.72 and 1.65 times (0.93 and 0.89 g xylitol per gram xylose) for hydrolysate treated with S-7 and Lj-3, respectively, in comparison with no detoxified hydrolysate (1.03 g l(-1) h(-1) and 0.54 g xylitol per gram xylose). This present work demonstrated the importance of Issatchenkia yeast in providing an effective biological detoxification approach to remove inhibitors and improve hydrolysate fermentability, leading to a high xylitol productivity and yield.

Identification and Validation of Brazilian Chronic Pain Descriptors

Appropriate pain assessment is very important for managing chronic pain. Given the cultural differences in verbally expressing pain and in psychosocial problems, specific tools are needed. The goal of this study was to identify and validate Brazilian pain descriptors. A purposive sample of health professionals and chronic pain patients was recruited. Four studies were conducted using direct and indirect psychophysical methods: category estimation, magnitude estimation, and magnitude estimation and tine-length. Results showed the descriptors which best describe chronic pain in Brazilian culture and demonstrated that there is not a significant correlation between patients and health professionals and that the psychophysical scale of judgment of pain descriptors is valid, stable, and consistent. Results reinforced that the translations of word descriptors and research tools into another language may be inappropriate, owing to differences in perception and communication and the inadequacy of exact translations to reflect the intended meaning. Given the complexity of the chronic pain, personal suffering involved, and the need for accurate assessment of chronic pain using descriptors stemming from Brazilian culture and language, it is essential to investigate the most adequate words to describe chronic pain. Although it requires more refinement, the Brazilian chronic pain descriptors can be used further to develop a multidimensional pain assessment tool that is culturally sensitive. (C) 2009 by the American Society for Pain Management Nursing