Dominance of multidrug resistant CC271 clones in macrolide-resistant streptococcus pneumoniae in Arizona

<p>Abstract</p> <p>Background</p> <p>Rates of resistance to macrolide antibiotics in <it>Streptococcus pneumoniae </it>are rising around the world due to the spread of mobile genetic elements harboring <it>mef</it>(E) and <it>erm</it>(B) genes and post-vaccine clonal expansion of strains that carry them.</p> <p>Results</p> <p>Characterization of 592 clinical isolates collected in Arizona over a 10 year period shows 23.6% are macrolide resistant. The largest portion of the macrolide-resistant population, 52%, is dual <it>mef</it>(E)/<it>erm</it>(B)-positive. All dual-positive isolates are multidrug-resistant clonal lineages of Taiwan^19F-14, mostly multilocus sequence type 320, carrying the recently described transposon Tn<it>2010</it>. The remainder of the macrolide resistant <it>S. pneumoniae </it>collection includes 31% <it>mef</it>(E)-positive, and 9% <it>erm</it>(B)-positive strains.</p> <p>Conclusions</p> <p>The dual-positive, multidrug-resistant <it>S. pneumoniae </it>clones have likely expanded by switching to non-vaccine serotypes after the heptavalent pneumococcal conjugate vaccine release, and their success limits therapy options. This upsurge could have a considerable clinical impact in Arizona.</p

Nontuberculous Mycobacterium Infection and Tumor Necrosis Factor-α Antagonists

Contains fulltext : 144010.pdf (publisher's version ) (Open Access)1 oktober 200

Emergence of a unique group of necrotizing mycobacterial diseases.

Although most diseases due to pathogenic mycobacteria are caused by Mycobacterium tuberculosis, several other mycobacterial diseases-caused by M. ulcerans (Buruli ulcer), M. marinum, and M. haemophilum-have begun to emerge. We review the emergence of diseases caused by these three pathogens in the United States and around the world in the last decade. We examine the pathophysiologic similarities of the diseases (all three cause necrotizing skin lesions) and common reservoirs of infection (stagnant or slow-flowing water). Examination of the histologic and pathogenic characteristics of these mycobacteria suggests differences in the modes of transmission and pathogenesis, though no singular mechanism for either characteristic has been definitively described for any of these mycobacteria

The Public Health Impact of Coccidioidomycosis in Arizona and California

The numbers of reported cases of coccidioidomycosis in Arizona and California have risen dramatically over the past decade, with a 97.8% and 91.1% increase in incidence rates from 2001 to 2006 in the two states, respectively. Of those cases with reported race/ethnicity information, Black/African Americans in Arizona and Hispanics and African/Americans in California experienced a disproportionately higher frequency of disease compared to other racial/ethnic groups. Lack of early diagnosis continues to be a problem, particularly in suspect community-acquired pneumonia, underscoring the need for more rapid and sensitive tests. Similarly, the inability of currently available therapeutics to reduce the duration and morbidity of this disease underscores the need for improved therapeutics and a preventive vaccine

Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data

International audienceBACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM) of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52%) corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra-species variability

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p

Comparative Genomic Analysis of Human Fungal Pathogens Causing Paracoccidioidomycosis

Paracoccidioides is a fungal pathogen and the cause of paracoccidioidomycosis, a health-threatening human systemic mycosis endemic to Latin America. Infection by Paracoccidioides, a dimorphic fungus in the order Onygenales, is coupled with a thermally regulated transition from a soil-dwelling filamentous form to a yeast-like pathogenic form. To better understand the genetic basis of growth and pathogenicity in Paracoccidioides, we sequenced the genomes of two strains of Paracoccidioides brasiliensis (Pb03 and Pb18) and one strain of Paracoccidioides lutzii (Pb01). These genomes range in size from 29.1 Mb to 32.9 Mb and encode 7,610 to 8,130 genes. To enable genetic studies, we mapped 94% of the P. brasiliensis Pb18 assembly onto five chromosomes. We characterized gene family content across Onygenales and related fungi, and within Paracoccidioides we found expansions of the fungal-specific kinase family FunK1. Additionally, the Onygenales have lost many genes involved in carbohydrate metabolism and fewer genes involved in protein metabolism, resulting in a higher ratio of proteases to carbohydrate active enzymes in the Onygenales than their relatives. To determine if gene content correlated with growth on different substrates, we screened the non-pathogenic onygenale Uncinocarpus reesii, which has orthologs for 91% of Paracoccidioides metabolic genes, for growth on 190 carbon sources. U. reesii showed growth on a limited range of carbohydrates, primarily basic plant sugars and cell wall components; this suggests that Onygenales, including dimorphic fungi, can degrade cellulosic plant material in the soil. In addition, U. reesii grew on gelatin and a wide range of dipeptides and amino acids, indicating a preference for proteinaceous growth substrates over carbohydrates, which may enable these fungi to also degrade animal biomass. These capabilities for degrading plant and animal substrates suggest a duality in lifestyle that could enable pathogenic species of Onygenales to transfer from soil to animal hosts.National Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health. Department of Health and Human Services (contract HHSN266200400001C)National Institutes of Health. Department of Health and Human Services(contract HHSN2722009000018C)Brazil. National Council for Scientific and Technological Developmen

Genotype Prevalence and Risk Factors for Severe Clinical Adenovirus Infection, United States 2004-2006

Recently, epidemiological and clinical data have revealed important changes with regard to clinical adenovirus infection, including alterations in antigenic presentation, geographical distribution, and virulence of the virus