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The NIAID TB Portals Program (TBPP) established a unique and growing database repository of socioeconomic, geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis (DR-TB). Currently, there are 2,428 total cases from nine country sites (Azerbaijan, Belarus, Moldova, Georgia, Romania, China, India, Kazakhstan, and South Africa), 1,611 (66%) of which are multidrug- or extensively-drug resistant and 1,185 (49%), 863 (36%), and 952 (39%) of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. We introduce the Data Exploration Portal (TB DEPOT, https://depot.tbportals.niaid.nih.gov) to visualize and analyze these multi-domain data. The TB DEPOT leverages the TBPP integration of clinical, socioeconomic, genomic, and imaging data into standardized formats and enables user-driven, repeatable, and reproducible analyses. It furthers the TBPP goals to provide a web-enabled analytics platform to countries with a high burden of multidrug-resistant TB (MDR-TB) but limited IT resources and inaccessible data, and enables the reusability of data, in conformity with the NIH's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. TB DEPOT provides access to "analysis-ready" data and the ability to generate and test complex clinically-oriented hypotheses instantaneously with minimal statistical background and data processing skills. TB DEPOT is also promising for enhancing medical training and furnishing well annotated, hard to find, MDR-TB patient cases. TB DEPOT, as part of TBPP, further fosters collaborative research efforts to better understand drug-resistant tuberculosis and aid in the development of novel diagnostics and personalized treatment regimens.

There was an error in the author byline. Author Julie C. Dunning Hotopp was inadvertently excluded. The author's affiliation is: 5 J. Craig Venter Institute (JCVI), Rockville, Maryland, United States of America, and the author's current address is: Institute of Genomic Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America. The author's order in the byline is sixth and the author's contributions are: Performed the experiments, analyzed the data, and contributed reagents/materials/analysis tools.

Background Neisseria meningitidis serogroup B has been predominant in Brazil, but no broadly effective vaccine is available to prevent endemic meningococcal disease. To understand genetic diversity among serogroup B strains in Brazil, we selected a nationally representative sample of clinical disease isolates from 2004, and a temporally representative sample for the state of São Paulo (1988–2006) for study (n = 372). Methods We performed multi-locus sequence typing (MLST) and sequence analysis of five outer membrane protein (OMP) genes, including novel vaccine targets fHbp and nadA. Results In 2004, strain B:4:P1.15,19 clonal complex ST-32/ET-5 (cc32) predominated throughout Brazil; regional variation in MLST sequence type (ST), fetA, and porB was significant but diversity was limited for nadA and fHbp. Between 1988 and 1996, the São Paulo isolates shifted from clonal complex ST-41/44/Lineage 3 (cc41/44) to cc32. OMP variation was associated with but not predicted by cc or ST. Overall, fHbp variant 1/subfamily B was present in 80% of isolates and showed little diversity. The majority of nadA were similar to reference allele 1. Conclusions A predominant serogroup B lineage has circulated in Brazil for over a decade with significant regional and temporal diversity in ST, fetA, and porB, but not in nadA and fHbp.

Background: As pathogens that circumvent the host immune response are favoured by selection, so are host alleles that reduce parasite load. Such evolutionary processes leave their signature on the genes involved. Deciphering modes of selection operating on immune genes might reveal the nature of host-pathogen interactions and factors that govern susceptibility in host populations. Such understanding would have important public health implications. Methodology/Findings: We analyzed polymorphisms in four mosquito immune genes (SP14D1, GNBP, defensin, and gambicin) to decipher selection effects, presumably mediated by pathogens. Using samples of Anopheles arabiensis, An. quadriannulatus and four An. gambiae populations, as well as published sequences from other Culicidae, we contrasted patterns of polymorphisms between different functional units of the same gene within and between populations. Our results revealed selection signatures operating on different time scales. At the most recent time scale, within-population diversity revealed purifying selection. Between populations and between species variation revealed reduced differentiation (GNBP and gambicin) at coding vs. noncoding- regions, consistent with balancing selection. McDonald-Kreitman tests between An. quadriannulatus and both sibling species revealed higher fixation rate of synonymous than nonsynonymous substitutions (GNBP) in accordance with frequency dependent balancing selection. At the longest time scale (.100 my), PAML analysis using distant Culicid taxa revealed positive selection at one codon in gambicin. Patterns of genetic variation were independent of exposure to human pathogens. Significance and Conclusions: Purifying selection is the most common form of selection operating on immune genes as it was detected on a contemporary time scale on all genes. Selection for ‘‘hypervariability’’ was not detected, but negative balancing selection, detected at a recent evolutionary time scale between sibling species may be rather common. Detection of positive selection at the deepest evolutionary time scale suggests that it occurs infrequently, possibly in association with speciation events. Our results provided no evidence to support the hypothesis that selection was mediated by pathogens that are transmitted to humans.