Abstract: Respiratory virus infections are a major health concern and represent the primary cause of testing consultation and hospitalization for young children. We developed and compared two assays that allow the detection of up to 23 different respiratory viruses that frequently infect children. The first method consisted of single TaqMan quantitative real-time PCR assays in a 96-well-plate format. The second consisted of a multiplex PCR followed by primer extension and microarray hybridization in an integrated molecular diagnostic device, the Infiniti analyzer. Both of our assays can detect adenoviruses of groups A, B, C, and E; coronaviruses HKU1, 229E, NL63, and OC43; enteroviruses A, B, C, and D; rhinoviruses of genotypes A and B; influenza viruses A and B; human metapneumoviruses (HMPV) A and B, human respiratory syncytial viruses (HRSV) A and B; and parainfluenza viruses of types 1, 2, and 3. These tests were used to identify viruses in 221 nasopharyngeal aspirates obtained from children hospitalized for respiratory tract infections. Respiratory viruses were detected with at least one of the two methods in 81.4% of the 221 specimens: 10.0% were positive for HRSV A, 38.0% for HRSV B, 13.1% for influenzavirus A, 8.6% for any coronaviruses, 13.1% for rhinoviruses or enteroviruses, 7.2% for adenoviruses, 4.1% for HMPV, and 1.5% for parainfluenzaviruses. Multiple viral infections were found in 13.1% of the specimens. The two methods yielded concordant results for 94.1% of specimens. These tests allowed a thorough etiological assessment of respiratory viruses infecting children in hospital settings and would assist public health interventions.
Abstract: BACKGROUND: Leishmania parasites cause a diverse spectrum of diseases in humans ranging from spontaneously healing skin lesions (e.g., L. major) to life-threatening visceral diseases (e.g., L. infantum). The high conservation in gene content and genome organization between Leishmania major and Leishmania infantum contrasts their distinct pathophysiologies, suggesting that highly regulated hierarchical and temporal changes in gene expression may be involved. RESULTS: We used a multispecies DNA oligonucleotide microarray to compare whole-genome expression patterns of promastigote (sandfly vector) and amastigote (mammalian macrophages) developmental stages between L. major and L. infantum. Seven per cent of the total L. infantum genome and 9.3% of the L. major genome were differentially expressed at the RNA level throughout development. The main variations were found in genes involved in metabolism, cellular organization and biogenesis, transport and genes encoding unknown function. Remarkably, this comparative global interspecies analysis demonstrated that only 10-12% of the differentially expressed genes were common to L. major and L. infantum. Differentially expressed genes are randomly distributed across chromosomes further supporting a posttranscriptional control, which is likely to involve a variety of 3'UTR elements. CONCLUSION: This study highlighted substantial differences in gene expression patterns between L. major and L. infantum. These important species-specific differences in stage-regulated gene expression may contribute to the disease tropism that distinguishes L. major from L. infantum.
Abstract: BACKGROUND: Drug resistance can be complex, and several mutations responsible for it can co-exist in a resistant cell. Transcriptional profiling is ideally suited for studying complex resistance genotypes and has the potential to lead to novel discoveries. We generated full genome 70-mer oligonucleotide microarrays for all protein coding genes of the human protozoan parasites Leishmania major and Leishmania infantum. These arrays were used to monitor gene expression in methotrexate resistant parasites. RESULTS: Leishmania is a eukaryotic organism with minimal control at the level of transcription initiation and few genes were differentially expressed without concomitant changes in DNA copy number. One exception was found in Leishmania major, where the expression of whole chromosomes was down-regulated. The microarrays highlighted several mechanisms by which the copy number of genes involved in resistance was altered; these include gene deletion, formation of extrachromosomal circular or linear amplicons, and the presence of supernumerary chromosomes. In the case of gene deletion or gene amplification, the rearrangements have occurred at the sites of repeated (direct or inverted) sequences. These repeats appear highly conserved in both species to facilitate the amplification of key genes during environmental changes. When direct or inverted repeats are absent in the vicinity of a gene conferring a selective advantage, Leishmania will resort to supernumerary chromosomes to increase the levels of a gene product. CONCLUSION: Aneuploidy has been suggested as an important cause of drug resistance in several organisms and additional studies should reveal the potential importance of this phenomenon in drug resistance in Leishmania.
Abstract: BACKGROUND: Human immunodeficiency virus type 1 (HIV-1) infects cells by means of ligand-receptor interactions. This lentivirus uses the CD4 receptor in conjunction with a chemokine coreceptor, either CXCR4 or CCR5, to enter a target cell. HIV-1 is characterized by high sequence variability. Nonetheless, within this extensive variability, certain features must be conserved to define functions and phenotypes. The determination of coreceptor usage of HIV-1, from its protein envelope sequence, falls into a well-studied machine learning problem known as classification. The support vector machine (SVM), with string kernels, has proven to be very efficient for dealing with a wide class of classification problems ranging from text categorization to protein homology detection. In this paper, we investigate how the SVM can predict HIV-1 coreceptor usage when it is equipped with an appropriate string kernel. RESULTS: Three string kernels were compared. Accuracies of 96.35% (CCR5) 94.80% (CXCR4) and 95.15% (CCR5 and CXCR4) were achieved with the SVM equipped with the distant segments kernel on a test set of 1425 examples with a classifier built on a training set of 1425 examples. Our datasets are built with Los Alamos National Laboratory HIV Databases sequences. A web server is available at http://genome.ulaval.ca/hiv-dskernel. CONCLUSION: We examined string kernels that have been used successfully for protein homology detection and propose a new one that we call the distant segments kernel. We also show how to extract the most relevant features for HIV-1 coreceptor usage. The SVM with the distant segments kernel is currently the best method described.
