High Prevalence of bla(CTX-M) Extended Spectrum Beta-Lactamase Genes in Klebsiella pneumoniae Isolates from a Tertiary Care Hospital: First report of bla(SHV-12), bla(SHV-31), bla(SHV-38), and bla(CTX-M-15) in Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development and validation of a Xanthomonas axonopodis pv. citri DNA microarray platform (XACarray) generated from the shotgun libraries previously used in the sequencing of this bacterial genome

Background. From shotgun libraries used for the genomic sequencing of the phytopathogenic bacterium Xanthomonas axonopodis pv. citri (XAC), clones that were representative of the largest possible number of coding sequences (CDSs) were selected to create a DNA microarray platform on glass slides (XACarray). The creation of the XACarray allowed for the establishment of a tool that is capable of providing data for the analysis of global genome expression in this organism. Findings. The inserts from the selected clones were amplified by PCR with the universal oligonucleotide primers M13R and M13F. The obtained products were purified and fixed in duplicate on glass slides specific for use in DNA microarrays. The number of spots on the microarray totaled 6,144 and included 768 positive controls and 624 negative controls per slide. Validation of the platform was performed through hybridization of total DNA probes from XAC labeled with different fluorophores, Cy3 and Cy5. In this validation assay, 86% of all PCR products fixed on the glass slides were confirmed to present a hybridization signal greater than twice the standard deviation of the deviation of the global median signal-to-noise ration. Conclusions. Our validation of the XACArray platform using DNA-DNA hybridization revealed that it can be used to evaluate the expression of 2,365 individual CDSs from all major functional categories, which corresponds to 52.7% of the annotated CDSs of the XAC genome. As a proof of concept, we used this platform in a previously work to verify the absence of genomic regions that could not be detected by sequencing in related strains of Xanthomonas. © 2010 Moreira et al; licensee BioMed Central Ltd.

Outbreak of fungemia caused by Candida parapsilosis in a neonatal intensive care unit: Molecular investigation through microsatellite analysis

Background: Opportunistic infections are an increasingly common problem in hospitals, and the yeast Candida parapsilosis has emerged as an important nosocomial pathogen, especially in neonatal intensive care units (NICUs) where it has been responsible for outbreak cases. Risk factors for C. parapsilosis infection in neonates include prematurity, very low birth weight, prolonged hospitalization, indwelling central venous catheters, hyperalimentation, intravenous fatty emulsions and broad spectrum antibiotic therapy. Molecular methods are widely used to elucidate these hospital outbreaks, establishing genetic variations among strains of yeast. Aims: The aim of this study was to detect an outbreak of C. parapsilosis in an NICU at the Hospital das Clinicas , Faculty of Medicine of Botucatu, a tertiary hospital located in São Paulo, Brazil, using the molecular genotyping by the microsatellite markers analysis. Methods: A total of 11 cases of fungemia caused by C. parapsilosis were identified during a period of 43 days in the NICU. To confirm the outbreak all strains were molecularly typed using the technique of microsatellites. Results: Out of the 11 yeast samples studied, nine showed the same genotypic profile using the technique of microsatellites. Conclusions: Our study shows that the technique of microsatellites can be useful for these purposes. In conclusion, we detected the presence of an outbreak of C. parapsilosis in the NICU of the hospital analyzed, emphasizing the importance of using molecular tools, for the early detection of hospital outbreaks, and for the introduction of effective preventive measures, especially in NICUs. © 2012 Revista Iberoamericana de Micología.

Estudo das alterações linfocitárias CD4/CD8 e carga viral em pacientes co-infectados HIV/Mycobacterium tuberculosis associadas a frequência de mutações na região Pol do HIV-1

Pós-graduação em Biociências e Biotecnologia Aplicadas à Farmácia - FCFAR

Avaliação do perfi de mutações e resistência aos inibidores de transcriptase reversa e protease em variantes HIV presentes em pacientes coinfectados pleo VHC

Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB

Molecular investigation of zoonotic genotypes of Giardia intestinalis isolates in humans, dogs and cats, sheep, goats and cattle in Araçatuba (Sãoo Paulo State, Brazil) by the analysis of beta-giardin gene fragments

In the period from July 2009 to October 2010, fecal samples from 61 animals and 154 humans from the municipality of Aracatuba (São Paulo State, Brazil) were studied. Fecal samples from animals were collected in the Municipal Animal Shelter and the Veterinary Hospital of the Universidade Estadual Paulista. Human fecal specimens were collected in playschools in the outskirts of the city by the private network of clinical analysis laboratories of the municipal. Diagnosis was done by optical microscopy using the Faust and Hoffmann, Pons and Janer techniques. The genotypes of Giardia intestinalis were characterized by PCR-RFLP and confirmed by sequencing the ß-giardin gene. Human specimens were positive in 25.3% (39/154) of the cases with 26.8% (36/134) of the specimens from children and 15% (3/20) from adults being positive. The frequency of G. intestinalis among the animals was 23.0% (14/61). A total of 32 isolates of G. intestinalis obtained from human feces and six from dogs and cats were characteristic of the A genotype (AI and AII/AIII). The results of this study in respect to frequency of giardiasis are similar to reported in most studies in Brazil. The prevalence observed in animal populations conforms to worldwide infection rates. G. intestinalis genotypes considered zoonotic were detected in both pets and humans from the city of Aractuba, suggesting a possible zoonotic transmission of the parasite in the northwestern region of São Paulo State. The absence of these genotypes in farm animals may imply that they are not involved in the chain of transmission to humans in this region.

Possible Host Adaptation as an Evolution Factor of Cowpea aphid-borne mosaic virus Deduced by Coat Protein Gene Analysis

Cowpea aphid-borne mosaic virus (CABMV) causes major diseases in cowpea and passion flower plants in Brazil and also in other countries. CABMV has also been isolated from leguminous species including, Cassia hoffmannseggii, Canavalia rosea, Crotalaria juncea and Arachis hypogaea in Brazil. The virus seems to be adapted to two distinct families, the Passifloraceae and Fabaceae. Aiming to identify CABMV and elucidate a possible host adaptation of this virus species, isolates from cowpea, passion flower and C.hoffmannseggii collected in the states of Pernambuco and Rio Grande do Norte were analysed by sequencing the complete coat protein genes. A phylogenetic tree was constructed based on the obtained sequences and those available in public databases. Major Brazilian isolates from passion flower, independently of the geographical distances among them, were grouped in three different clusters. The possible host adaptation was also observed in fabaceous-infecting CABMV Brazilian isolates. These host adaptations possibly occurred independently within Brazil, so all these clusters belong to a bigger Brazilian cluster. Nevertheless, African passion flower or cowpea-infecting isolates formed totally different clusters. These results showed that host adaptation could be one factor for CABMV evolution, although geographical isolation is a stronger factor.

The methylation patterns of the IGF2 and IGF2R genes in bovine spermatozoa are not affected by flow-cytometric sex sorting

The objectives of this study were to investigate the effect of sexing by flow cytometry on the methylation patterns of the IGF2 and IGF2R genes. Frozen-thawed, unsorted, and sex-sorted sperm samples from four Nellore bulls were used. Each ejaculate was separated into three fractions: non-sexed (NS), sexed for X-sperm (SX), and sexed for Y-sperm (SY). Sperm were isolated from the extender, cryoprotectant, and other cell types by centrifugation on a 40:70% Percoll gradient, and sperm pellets were used for genomic DNA isolation. DNA was used for analyses of the methylation patterns by bisulfite sequencing. Methylation status of the IGF2 and IGF2R genes were evaluated by sequencing 195 and 147 individual clones, respectively. No global differences in DNA methylation were found between NS, SX, and SY groups for the IGF2 (P=0.09) or IGF2R genes (P=0.38). Very specific methylation patterns were observed in the 25th and 26th CpG sites in the IGF2R gene. representing higher methylation in NS than in the SX and SY groups compared with the other CpG sites. Further, individual variation in methylation patterns was found among bulls. In conclusion, the sex-sorting procedure by flow cytometry did not affect the overall DNA methylation patterns of the IGF2 and IGF2R genes, although individual variation in their methylation patterns among bulls was observed. Mol. Reprod. Dev. 79:7784, 2012. (C) 2011 Wiley Periodicals, Inc.

Reliable identification of mycobacterial species by PCR-restriction enzyme analysis (PRA)-hsp65 in a reference laboratory and elaboration of a sequence-based extended algorithm of PRA-hsp65 patterns

Abstract Background Identification of nontuberculous mycobacteria (NTM) based on phenotypic tests is time-consuming, labor-intensive, expensive and often provides erroneous or inconclusive results. In the molecular method referred to as PRA-hsp65, a fragment of the hsp65 gene is amplified by PCR and then analyzed by restriction digest; this rapid approach offers the promise of accurate, cost-effective species identification. The aim of this study was to determine whether species identification of NTM using PRA-hsp65 is sufficiently reliable to serve as the routine methodology in a reference laboratory. Results A total of 434 NTM isolates were obtained from 5019 cultures submitted to the Institute Adolpho Lutz, Sao Paulo Brazil, between January 2000 and January 2001. Species identification was performed for all isolates using conventional phenotypic methods and PRA-hsp65. For isolates for which these methods gave discordant results, definitive species identification was obtained by sequencing a 441 bp fragment of hsp65. Phenotypic evaluation and PRA-hsp65 were concordant for 321 (74%) isolates. These assignments were presumed to be correct. For the remaining 113 discordant isolates, definitive identification was based on sequencing a 441 bp fragment of hsp65. PRA-hsp65 identified 30 isolates with hsp65 alleles representing 13 previously unreported PRA-hsp65 patterns. Overall, species identification by PRA-hsp65 was significantly more accurate than by phenotype methods (392 (90.3%) vs. 338 (77.9%), respectively; p < .0001, Fisher's test). Among the 333 isolates representing the most common pathogenic species, PRA-hsp65 provided an incorrect result for only 1.2%. Conclusion PRA-hsp65 is a rapid and highly reliable method and deserves consideration by any clinical microbiology laboratory charged with performing species identification of NTM.

Development and validation of a Xanthomonas axonopodis pv. citri DNA microarray platform (XACarray) generated from the shotgun libraries previously used in the sequencing of this bacterial genome

Abstract Background From shotgun libraries used for the genomic sequencing of the phytopathogenic bacterium Xanthomonas axonopodis pv. citri (XAC), clones that were representative of the largest possible number of coding sequences (CDSs) were selected to create a DNA microarray platform on glass slides (XACarray). The creation of the XACarray allowed for the establishment of a tool that is capable of providing data for the analysis of global genome expression in this organism. Findings The inserts from the selected clones were amplified by PCR with the universal oligonucleotide primers M13R and M13F. The obtained products were purified and fixed in duplicate on glass slides specific for use in DNA microarrays. The number of spots on the microarray totaled 6,144 and included 768 positive controls and 624 negative controls per slide. Validation of the platform was performed through hybridization of total DNA probes from XAC labeled with different fluorophores, Cy3 and Cy5. In this validation assay, 86% of all PCR products fixed on the glass slides were confirmed to present a hybridization signal greater than twice the standard deviation of the deviation of the global median signal-to-noise ration. Conclusions Our validation of the XACArray platform using DNA-DNA hybridization revealed that it can be used to evaluate the expression of 2,365 individual CDSs from all major functional categories, which corresponds to 52.7% of the annotated CDSs of the XAC genome. As a proof of concept, we used this platform in a previously work to verify the absence of genomic regions that could not be detected by sequencing in related strains of Xanthomonas.

Caratterizzazione genomica di virus influenzali suini in Italia mediante next generation sequencing

I sottotipi H1N1, H1N2 e H3N2 di influenza A virus sono largamente diffusi nella popolazione suina di tutto il mondo. Nel presente lavoro è stato sviluppato un protocollo di sequenziamento di c.d. nuova generazione, su piattaforma Ion Torrent PGM, idoneo per l’analisi di tutti i virus influenzali suini (SIV). Per valutare l’evoluzione molecolare dei SIV italiani, sono stati sequenziati ed analizzati mediante analisi genomica e filogenetica un totale di sessantadue ceppi di SIV appartenenti ai sottotipi H1N1, H1N2 e H3N2, isolati in Italia dal 1998 al 2014. Sono stati evidenziati in sei campioni due fenomeni di riassortimento: tutti i SIV H1N2 esaminati presentavano una neuraminidasi di derivazione umana, diversa da quella dei SIV H1N2 circolanti in Europa, inoltre l’emoagglutinina (HA) di due isolati H1N2 era originata dal riassortimento con un SIV H1N1 avian-like. L’analisi molecolare dell’HA ha permesso di rivelare un’inserzione di due amminoacidi in quattro SIV H1N1 pandemici e una delezione di due aminoacidi in quattro SIV H1N2, entrambe a livello del sito di legame con il recettore cellulare. E’ stata inoltre evidenziata un’elevata omologia di un SIV H1N1 con ceppi europei isolati negli anni ’80, suggerendo la possibile origine vaccinale di questo virus. E’ stato possibile, in aggiunta, applicare il nuovo protocollo sviluppato per sequenziare un virus influenzale aviare altamente patogeno trasmesso all’uomo, direttamente da campione biologico. La diversità genetica nei SIV esaminati in questo studio conferma l’importanza di un continuo monitoraggio della costellazione genomica dei virus influenzali nella popolazione suina.

Complexity of miR-223 regulation by CEBPA in human AML

microRNA-223 (miR-223) can trigger normal granulopoiesis. miR-223 expression is regulated by two distinct CEBPA (CCAAT/enhancer binding protein-alpha) sites. Here, we report that miR-223 is largely suppressed in cells from acute myeloid leukemia (AML) patients. By sequencing, we found that miR-223 suppression in AML is not caused by DNA sequence alterations, nor is it mediated by promoter hypermethylation. The analysis of the individual contribution of both CEBPA sites to miR-223 regulation identified the site upstream of the miR-223 primary transcript as the predominant regulatory element. Our results suggest that miR-223 suppression in AML is caused by impaired miR-223 upstream factors.

Characterization of Pasteurellaceae-like bacteria isolated from clinically affected psittacine birds

AIMS: The aim of the present investigation was to identify and characterize Pasteurella-like isolates obtained from clinically affected psittacine birds. METHODS AND RESULTS: A total of 37 isolates from psittacine birds tentatively classified with the family Pasteurellaceae were characterized phenotypically. The genetic relationship was investigated by sequencing of partial rpoB and 16S rRNA genes for selected isolates. The results obtained were compared with the data from 16 reference strains. Nine isolates were identified as Gallibacterium spp., 16 as Volucribacter spp. or Volucribacter-like, while 11 isolates were classified as taxon 44 of Bisgaard. A single isolate was identified as Pasteurella multocida. CONCLUSIONS: Characterization of Pasteurellaceae by traditional methods is often inconclusive because of inconsistent reactions and phenotypic diversity. For the same reason, genotyping is essential to allow proper classification as demonstrated in the present study. SIGNIFICANCE AND IMPACT OF THE STUDY: Limited information exists on the isolation and significance of Pasteurellaceae associated with clinically affected psittacine birds showing signs of digestive and/or respiratory disorders. The present investigations demonstrated that these organisms are widely distributed among clinically affected birds, but isolation of these taxa cannot be unambiguously correlated with the symptoms observed.

Diversity of Mycoplasma hyopneumoniae in pig farms revealed by direct molecular typing of clinical material

Mycoplasma hyopneumoniae is the etiological agent of enzootic pneumonia in swine. Various reports indicate that different strains are circulating in the swine population. We investigated the variety of M. hyopneumoniae strains by a newly developed genetic typing method based on the polyserine repeat motif of the LppS homolog P146. PCR amplification using M. hyopneumoniae specific, conserved primers flanking the region encoding the repeat motif, followed by sequencing and cluster analysis was carried out. The study included strains isolated from different geographic regions as well as lysates from lung swabs from a series of pig farms in Switzerland. High diversity of M. hyopneumoniae was observed but farms being in close geographic or operative contact generally seemed to be affected by the same strains. Moreover, analysis of multiple samples from single pig farms indicated that these harbored the same, farm-specific strain. The results indicate that multiple strains of M. hyopneumoniae are found in the swine population but that specific strains or clones are responsible for local outbreaks. The method presented is a highly reproducible epidemiologic tool allowing direct typing of M. hyopneumoniae from clinical material without prior isolation and cultivation of strains.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.