A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children.

BACKGROUND: Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. RESULTS: We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). CONCLUSIONS: Our data justify the further exploration of our signature set as biomarkers for potential childhood TB diagnosis. We show that, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts.

SIMAGE: simulation of DNA-microarray gene expression data.

BACKGROUND: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. RESULTS: Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. CONCLUSION: We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation "SIMAGE" which stands for simulation of microarray gene expression data. The software is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/simage.

The adult nasopharyngeal microbiome as a determinant of pneumococcal acquisition.

BACKGROUND: Several cohort studies have indicated associations between S. pneumoniae and other microbes in the nasopharynx. To study causal relationships between the nasopharyngeal microbiome and pneumococcal carriage, we employed an experimental human pneumococcal carriage model. Healthy adult volunteers were assessed for pneumococcal carriage by culture of nasal wash samples (NWS). Those without natural pneumococcal carriage received an intranasal pneumococcal inoculation with serotype 6B or 23F. The composition of the nasopharyngeal microbiome was longitudinally studied by 16S rDNA pyrosequencing on NWS collected before and after challenge. RESULTS: Among 40 selected volunteers, 10 were natural carriers and 30 were experimentally challenged. At baseline, five distinct nasopharyngeal microbiome profiles were identified. The phylogenetic distance between microbiomes of natural pneumococcal carriers was particularly large compared to non-carriers. A more diverse microbiome prior to inoculation was associated with the establishment of pneumococcal carriage. Perturbation of microbiome diversity upon pneumococcal challenge was strain specific. Shifts in microbiome profile occurred after pneumococcal exposure, and those volunteers who acquired carriage more often diverted from their original profile. S. pneumoniae was little prominent in the microbiome of pneumococcal carriers. CONCLUSION: Pneumococcal acquisition in healthy adults is more likely to occur in a diverse microbiome and appears to promote microbial heterogeneity.