552 resultados para Phili (Microbiology)


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The aim of this study was to investigate the presence and prevalence of bla(TEM), bla(SHV), and bla(CTX-M) and bla(GES)-like genes, responsible for extended spectrum beta-lactamases (ESBLs) production in clinical isolates of Klebsiella pneumoniae collected from a Brazilian tertiary care hospital. Sixty-five ESBL producing K. pneumoniae isolates, collected between 2005 and 2007, were screened by polymerase chain reaction (PCR). Identification of bla genes was achieved by sequencing. Genotyping of ESBL producing K. pneumoniae was performed by the enterobacterial repetitive intergenic consensus-PCR with cluster analysis by the Dice coefficient. The presence of genes encoding ESBLs was confirmed in 59/65 (90.8%) isolates, comprising 20 bla(CTX-M-2), 14 bla(CTX-M-59), 12 bla(CTX-M-15), 9 bla(SHV-12), 1 bla(SHV-2), 1 bla(SHV-2a), 1 bla(SHV-5), and 1 bla(SHV-31) genes. The ESBL genes bla(SHV-12), bla(SHV-31), and bla(CTX-M-15), and the chromosome-encoded SHV-type beta-lactamase capable of hydrolyzing imipenem were detected in Brazil for the first time. The analysis of the enterobacterial repetitive intergenic consensus-PCR band patterns revealed a high rate of multiclonal bla(CTX-M) carrying K. pneumoniae isolates (70.8%), suggesting that dissemination of encoding plasmids is likely to be the major cause of the high prevalence of these genes among the K. pneumoniae isolates considered in this study.

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Background: Chamydophila pneumoniae (CP) and/or Mycoplasma pneumoniae ( MP) are two bacteria detected in vulnerable atheromas. In this study we aimed to analyze whether CP and/or MP aggravates atherosclerosis induced by cholesterol-enriched diet in C57BL/6 apoE KO male mice. Thirty male apoE KO mice aged eight weeks fed by a diet containing 1% cholesterol until 32 weeks of age were divided into four groups: the first was inoculated with CP (n = 7), the second with MP (n = 12), the third with both CP + MP ( n = 5), and the fourth with saline (sham n = 6). The animals were re-inoculated at 36 weeks of age, and sacrificed at 40 weeks of age. Two ascending aorta and one aortic arch segments were sampled. In the most severely obstructed segment, vessel diameter, plaque height, percentage of luminal obstruction and the degree of adventitial inflammation were analyzed. The plaque area/intimal surface ratio was obtained by measuring all three segments. The adventitial inflammation was semiquantified (0 absent, 1 mild, 2 moderate, and 3 diffuse). Results: The mean and standard deviation of plaque height, % luminal obstruction, external diameter, the plaque area/intimal surface ratio and the adventitial inflammation values are the following for each group: MP (0.20 +/- 12 mm, 69 +/- 26%, 0.38 +/- 0.11 mm, 0.04 +/- 0.04 and 0.22 +/- 0.67), CP (0.23 +/- 0.08 mm, 90 +/- 26%, 0.37 +/- 0.08 mm, 0.04 +/- 0.03, and 0.44 +/- 0.53), MP + CP ( 18 +/- 0.08 mm, 84 +/- 4.0%, 0.35 +/- 0.25 mm, 0.03 +/- 0.03 and 1.33 +/- 0.82) and sham (0.08 +/- 0.09 mm, 42 +/- 46%, 0.30 +/- 0.10 mm, 0.02 +/- 0.03 and 0.71 +/- 0.76). A wider area of plaque/intimal surface was observed in MP + CP inoculated groups (p = 0.07 and 0.06) as well as an increased plaque height in CP (p = 0.01) in comparison with sham group. There was also an increased luminal obstruction (p = 0.047) in CP inoculated group in comparison to sham group. Adventitial inflammation in MP + CP inoculated group was higher than MP, CP and the sham groups (p = 0.02). Conclusion: Inoculation of CP, MP or both agents in C57BL/6 apoE KO male mice caused aggravation of experimental atherosclerosis induced by cholesterol-enriched diet, with distinct characteristics. CP inoculation increased the plaque height with positive vessel remodeling and co-inoculation of MP + CP caused the highest adventitial inflammation measures.

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The murine model of T. cruzi infection has provided compelling evidence that development of host resistance against intracellular protozoans critically depends on the activation of members of the Toll-like receptor (TLR) family via the MyD88 adaptor molecule. However, the possibility that TLR/MyD88 signaling pathways also control the induction of immunoprotective CD8(+) T cell-mediated effector functions has not been investigated to date. We addressed this question by measuring the frequencies of IFN-gamma secreting CD8(+) T cells specific for H-2K(b)-restricted immunodominant peptides as well as the in vivo Ag-specific cytotoxic response in infected animals that are deficient either in TLR2, TLR4, TLR9 or MyD88 signaling pathways. Strikingly, we found that T. cruzi-infected Tlr2(-/-), Tlr4(-/-), Tlr9(-/-) or Myd88(-/-) mice generated both specific cytotoxic responses and IFN-gamma secreting CD8(+) T cells at levels comparable to WT mice, although the frequency of IFN-gamma(+)CD4(+) cells was diminished in infected Myd88(-/-) mice. We also analyzed the efficiency of TLR4-driven immune responses against T. cruzi using TLR4-deficient mice on the C57BL genetic background (B6 and B10). Our studies demonstrated that TLR4 signaling is required for optimal production of IFN-gamma, TNF-alpha and nitric oxide (NO) in the spleen of infected animals and, as a consequence, Tlr4(-/-) mice display higher parasitemia levels. Collectively, our results indicate that TLR4, as well as previously shown for TLR2, TLR9 and MyD88, contributes to the innate immune response and, consequently, resistance in the acute phase of infection, although each of these pathways is not individually essential for the generation of class I-restricted responses against T. cruzi.

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Background: Bovine anaplasmosis, caused by the rickettsial tick-borne pathogen Anaplasma marginale (Rickettsiales: Anaplasmataceae), is vectored by Rhipicephalus (Boophilus) microplus in many tropical and subtropical regions of the world. A. marginale undergoes a complex developmental cycle in ticks which results in infection of salivary glands from where the pathogen is transmitted to cattle. In previous studies, we reported modification of gene expression in Dermacentor variabilis and cultured Ixodes scapularis tick cells in response to infection with A. marginale. In these studies, we extended these findings by use of a functional genomics approach to identify genes differentially expressed in R. microplus male salivary glands in response to A. marginale infection. Additionally, a R. microplus-derived cell line, BME26, was used for the first time to also study tick cell gene expression in response to A. marginale infection. Results: Suppression subtractive hybridization libraries were constructed from infected and uninfected ticks and used to identify genes differentially expressed in male R. microplus salivary glands infected with A. marginale. A total of 279 ESTs were identified as candidate differentially expressed genes. Of these, five genes encoding for putative histamine-binding protein (22Hbp), von Willebrand factor (94Will), flagelliform silk protein (100Silk), Kunitz-like protease inhibitor precursor (108Kunz) and proline-rich protein BstNI subfamily 3 precursor (7BstNI3) were confirmed by real-time RT-PCR to be down-regulated in tick salivary glands infected with A. marginale. The impact of selected tick genes on A. marginale infections in tick salivary glands and BME26 cells was characterized by RNA interference. Silencing of the gene encoding for putative flagelliform silk protein (100Silk) resulted in reduced A. marginale infection in both tick salivary glands and cultured BME26 cells, while silencing of the gene encoding for subolesin (4D8) significantly reduced infection only in cultured BME26 cells. The knockdown of the gene encoding for putative metallothionein (93 Meth), significantly up-regulated in infected cultured BME26 cells, resulted in higher A. marginale infection levels in tick cells. Conclusions: Characterization of differential gene expression in salivary glands of R. microplus in response to A. marginale infection expands our understanding of the molecular mechanisms at the tick-pathogen interface. Functional studies suggested that differentially expressed genes encoding for subolesin, putative von Willebrand factor and flagelliform silk protein could play a role in A. marginale infection and multiplication in ticks. These tick genes found to be functionally relevant for tick-pathogen interactions will likely be candidates for development of vaccines designed for control of both ticks and tick-borne pathogens.

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Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

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The spectrum of the clinical presentation and severity of malaria infections is broad, ranging from uncomplicated febrile illness to severe forms of disease such as cerebral malaria (CM), acute lung injury (ALI), acute respiratory distress syndrome (ARDS), pregnancy-associated malaria (PAM) or severe anemia (SA). Rodent models that mimic human CM, PAM and SA syndromes have been established. Here, we show that DBA/2 mice infected with P. berghei ANKA constitute a new model for malaria-associated ALI. Up to 60% of the mice showed dyspnea, airway obstruction and hypoxemia and died between days 7 and 12 post-infection. The most common pathological findings were pleural effusion, pulmonary hemorrhage and edema, consistent with increased lung vessel permeability, while the blood-brain barrier was intact. Malaria-associated ALI correlated with high levels of circulating VEGF, produced de novo in the spleen, and its blockage led to protection of mice from this syndrome. In addition, either splenectomization or administration of the anti-inflammatory molecule carbon monoxide led to a significant reduction in the levels of sera VEGF and to protection from ALI. The similarities between the physiopathological lesions described here and the ones occurring in humans, as well as the demonstration that VEGF is a critical host factor in the onset of malaria-associated ALI in mice, not only offers important mechanistic insights into the processes underlying the pathology related with malaria but may also pave the way for interventional studies.

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The extracts from the root, bark and seed of Garcinia kola are currently used in traditional medicine in Nigeria. The aim of this study was to evaluate the inhibitory activity of crude extracts of G. kola on Fusobacterium nucleatum isolated from the oral cavity. Methanol and aqueous extracts were prepared from the seed and the minimal inhibitory concentration was evaluated by the agar dilution method, using a Wilkins-Chalgren agar supplemented with horse blood (5%), hemin (5 mu g/ml) and menadione (1 mu g/ml). Antimicrobial activity of plant extracts on microbial biofilms was determined in microtiter plates. The seed of G. kola demonstrated significant inhibitory action on F. nucleatum isolates at a concentration of 1.25 and 12.5 mg/ml for amoxicillin resistant strain. It was able to inhibit the microbial biofilm formed by the association of F. nucleatum with Porphyromonas gingivalis ATCC 33277, Aggregatibacter actinomycetemcomitans ATCC 33384 and Prevotella intermedia ATCC 2564 at a concentration of 25 mg/ml. The in-vitro inhibitory effect of G. kola on F. nucleatum population suggests a potential role for its use in oral hygiene.

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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.

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Background: Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results: The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion: To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.

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Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

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Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

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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.

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Whole cells of hydrocarbon-degrading bacteria, isolated from polluted sediments in the Santos Estuary (Baixada Santista, Sao Paulo, Brazil), were able to catalyse oxidoreduction reactions with various substituted phenylethanols and acetophenones as substrates. A number of substituted phenylethanols were formed with high (>99 %) enantiomeric excess. The results of microbial oxidation of phenylethanols 2, 3, 5-7 by Acinetobacter sp. 6.4T and the reduction of acetophenones 1a-6a by Serratia marcescens 5.4T showed that the bacteria used as biocatalysts in this study present significant potential for exploitation in biotechnological processes. The reduction of prochiral acetophenones by Serratia marcescens 3.5T yielded optically active alcohols with 90-99 % enantiomeric excess, and Acinetobacter sp. 6.4T is a potential biocatalyst for the oxidation of alcohols.

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Background: Citrus canker is a disease that has severe economic impact on the citrus industry worldwide. There are three types of canker, called A, B, and C. The three types have different phenotypes and affect different citrus species. The causative agent for type A is Xanthomonas citri subsp. citri, whose genome sequence was made available in 2002. Xanthomonas fuscans subsp. aurantifolii strain B causes canker B and Xanthomonas fuscans subsp. aurantifolii strain C causes canker C. Results: We have sequenced the genomes of strains B and C to draft status. We have compared their genomic content to X. citri subsp. citri and to other Xanthomonas genomes, with special emphasis on type III secreted effector repertoires. In addition to pthA, already known to be present in all three citrus canker strains, two additional effector genes, xopE3 and xopAI, are also present in all three strains and are both located on the same putative genomic island. These two effector genes, along with one other effector-like gene in the same region, are thus good candidates for being pathogenicity factors on citrus. Numerous gene content differences also exist between the three cankers strains, which can be correlated with their different virulence and host range. Particular attention was placed on the analysis of genes involved in biofilm formation and quorum sensing, type IV secretion, flagellum synthesis and motility, lipopolysacharide synthesis, and on the gene xacPNP, which codes for a natriuretic protein. Conclusion: We have uncovered numerous commonalities and differences in gene content between the genomes of the pathogenic agents causing citrus canker A, B, and C and other Xanthomonas genomes. Molecular genetics can now be employed to determine the role of these genes in plant-microbe interactions. The gained knowledge will be instrumental for improving citrus canker control.

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Background: Exposure of cells to environmental stress conditions can lead to the interruption of several intracellular processes, in particular those performed by macromolecular complexes such as the spliceosome. Results: During nucleotide sequencing of cDNA libraries constructed using RNA isolated from B. emersonii cells submitted to heat shock and cadmium stress, a large number of ESTs with retained introns was observed. Among the 6,350 ESTs obtained through sequencing of stress cDNA libraries, 181 ESTs presented putative introns (2.9%), while sequencing of cDNA libraries from unstressed B. emersonii cells revealed only 0.2% of ESTs containing introns. These data indicate an enrichment of ESTs with introns in B. emersonii stress cDNA libraries. Among the 85 genes corresponding to the ESTs that retained introns, 19 showed more than one intron and three showed three introns, with intron length ranging from 55 to 333 nucleotides. Canonical splicing junctions were observed in most of these introns, junction sequences being very similar to those found in introns from genes previously characterized in B. emersonii, suggesting that inhibition of splicing during stress is apparently a random process. Confirming our observations, analyses of gpx3 and hsp70 mRNAs by Northern blot and S1 protection assays revealed a strong inhibition of intron splicing in cells submitted to cadmium stress. Conclusion: In conclusion, data indicate that environmental stresses, particularly cadmium treatment, inhibit intron processing in B. emersonii, revealing a new adaptive response to cellular exposure to this heavy metal.