28 research outputs found

    Whole-blood transcriptomic signatures induced during immunization by chloroquine prophylaxis and Plasmodium falciparum sporozoites

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    A highly effective vaccine that confers sterile protection to malaria is urgently needed. Immunization under chemoprophylaxis with sporozoites (CPS) consistently confers high levels of protection in the Controlled Human Malaria infection (CHMI) model. To provide a broad, unbiased assessment of the composition and kinetics of direct ex vivo human immune responses to CPS, we profiled whole-blood transcriptomes by RNA-seq before and during CPS immunization and following CHMI challenge. Differential expression of genes enriched in modules related to T cells, NK cells, protein synthesis, and mitochondrial processes were detected in fully protected individuals four weeks after the first immunization. Non-protected individuals demonstrated transcriptomic changes after the third immunization and the day of treatment, with upregulation of interferon and innate inflammatory genes and downregulation of B-cell signatures. Protected individuals demonstrated more significant interactions between blood transcription modules compared to non-protected individuals several weeks after the second and third immunizations. These data provide insight into the molecular and cellular basis of CPS-induced immune protection from P. falciparum infection

    Transcriptomic evidence for modulation of host inflammatory responses during febrile Plasmodium falciparum malaria

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    Identifying molecular predictors and mechanisms of malaria disease is important for understanding how Plasmodium falciparum malaria is controlled. Transcriptomic studies in humans have so far been limited to retrospective analysis of blood samples from clinical cases. In this prospective, proof-of-principle study, we compared whole-blood RNA-seq profiles at pre-and post-infection time points from Malian adults who were either asymptomatic (nā€‰=ā€‰5) or febrile (nā€‰=ā€‰3) during their first seasonal PCR-positive P. falciparum infection with those from malaria-naĆÆve Dutch adults after a single controlled human malaria infection (nā€‰=ā€‰5). Our data show a graded activation of pathways downstream of pro-inflammatory cytokines, with the highest activation in malaria-naĆÆve Dutch individuals and significantly reduced activation in malaria-experienced Malians. Newly febrile and asymptomatic infections in Malians were statistically indistinguishable except for genes activated by pro-inflammatory cytokines. The combined data provide a molecular basis for the development of a pyrogenic threshold as individuals acquire immunity to clinical malaria

    A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChipĀ® whole-genome resequencing platform

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    DNA resequencing arrays enable rapid acquisition of high-quality sequence data. This technology represents a promising platform for rapid high-resolution genotyping of microorganisms. Traditional array-based resequencing methods have relied on the use of specific PCR-amplified fragments from the query samples as hybridization targets. While this specificity in the target DNA population reduces the potential for artifacts caused by cross-hybridization, the subsampling of the query genome limits the sequence coverage that can be obtained and therefore reduces the technique's resolution as a genotyping method. We have developed and validated an Affymetrix Inc. GeneChipĀ® array-based, whole-genome resequencing platform for Francisella tularensis, the causative agent of tularemia. A set of bioinformatic filters that targeted systematic base-calling errors caused by cross-hybridization between the whole-genome sample and the array probes and by deletions in the sample DNA relative to the chip reference sequence were developed. Our approach eliminated 91% of the false-positive single-nucleotide polymorphism calls identified in the SCHU S4 query sample, at the cost of 10.7% of the true positives, yielding a total base-calling accuracy of 99.992%

    Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

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    <p>Abstract</p> <p>Background</p> <p>Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.</p> <p>Results</p> <p>We experimentally annotated the bacterial pathogen <it>Salmonella </it>Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in <it>Salmonella </it>and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in <it>Salmonella </it>pathogenesis. We also characterized post-translational features in the <it>Salmonella </it>genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our <it>in vivo </it>proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.</p> <p>Conclusion</p> <p>This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of <it>Salmonella </it>as a resource for systems analysis.</p
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