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Our understanding of mechanisms underlying progression from Mycobacterium tuberculosis infection to pulmonary tuberculosis disease in humans remains limited. To define such mechanisms, we followed M. tuberculosis-infected adolescents longitudinally. Blood samples from forty-four adolescents who ultimately developed tuberculosis disease (“progressors”) were compared with those from 106 matched controls, who remained healthy during two years of follow up. We performed longitudinal whole blood transcriptomic analyses by RNA sequencing and plasma proteome analyses using multiplexed slow off-rate modified DNA aptamers. Tuberculosis progression was associated with sequential modulation of immunological processes. Type I/II interferon signalling and complement cascade were elevated 18 months before tuberculosis disease diagnosis, while changes in myeloid inflammation, lymphoid, monocyte and neutrophil gene modules occurred more proximally to tuberculosis disease. Analysis of gene expression in purified T cells also revealed early suppression of Th17 responses in progressors, relative to M. tuberculosis-infected controls. This was confirmed in an independent adult cohort who received BCG re-vaccination; transcript expression of interferon response genes in blood prior to BCG administration was associated with suppression of IL-17 expression by BCG-specific CD4 T cells 3 weeks post-vaccination. Our findings provide a timeline to the different immunological stages of disease progression which comprise sequential inflammatory dynamics and immune alterations that precede disease manifestations and diagnosis of tuberculosis disease. These findings have important implications for developing diagnostics, vaccination and host-directed therapies for tuberculosis. Clincialtrials.gov, NCT01119521.

Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. In this prospective cohort study, we followed up healthy, South African adolescents aged 12–18 years from the adolescent cohort study (ACS) who were infected with M tuberculosis for 2 years. We collected blood samples from study participants every 6 months and monitored the adolescents for progression to tuberculosis disease. A prospective signature of risk was derived from whole blood RNA sequencing data by comparing participants who developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex quantitative real-time PCR (qRT-PCR), the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. Participants of the independent cohorts were household contacts of adults with active pulmonary tuberculosis disease. Between July 6, 2005, and April 23, 2007, we enrolled 6363 participants from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in the 12 months preceding tuberculosis. The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. Bill & Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union, and the South African Medical Research Council.

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments. Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays. We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here. Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.

Complete vaccine-mediated immune control of highly pathogenic Mycobacterium tuberculosis is possible if immune effector responses can intercept the infection at its earliest stages. Despite widespread use of the bacille Calmette–Guérin (BCG) vaccine, tuberculosis (TB) remains a leading cause of global mortality from a single infectious agent ( Mycobacterium tuberculosis or Mtb). Here, over two independent Mtb challenge studies, we demonstrate that subcutaneous vaccination of rhesus macaques (RMs) with rhesus cytomegalovirus vectors encoding Mtb antigen inserts (hereafter referred to as RhCMV/TB)—which elicit and maintain highly effector-differentiated, circulating and tissue-resident Mtb-specific CD4 + and CD8 + memory T cell responses—can reduce the overall (pulmonary and extrapulmonary) extent of Mtb infection and disease by 68%, as compared to that in unvaccinated controls, after intrabronchial challenge with the Erdman strain of Mtb at ∼1 year after the first vaccination. Fourteen of 34 RhCMV/TB-vaccinated RMs (41%) across both studies showed no TB disease by computed tomography scans or at necropsy after challenge (as compared to 0 of 17 unvaccinated controls), and ten of these RMs were Mtb-culture-negative for all tissues, an exceptional long-term vaccine effect in the RM challenge model with the Erdman strain of Mtb. These results suggest that complete vaccine-mediated immune control of highly pathogenic Mtb is possible if immune effector responses can intercept Mtb infection at its earliest stages.

The streptavidin–biotin system has provided a unique opportunity to investigate the molecular details of ligand dissociation pathways. An underlying mechanistic question is whether ligand dissociation proceeds with a relatively ordered process of bond breaking and ligand escape. Here we report a joint computational and crystallographic study of the earliest events in biotin dissociation. In molecular dynamics potential of mean force simulations, a water molecule from a defined access channel intercalated into the hydrogen bond between Asp 128 and biotin, bridging them and stabilizing an intermediate state. In forced biotin dissociation simulations, this event led to subsequent bond breaking steps and ligand escape. In equilibrium simulations, the water molecule was sometimes observed to move back to the access channel with re-formation of the biotin hydrogen bond. Analysis of streptavidin crystal structures revealed a close overlap of crystallographically defined and simulated waters in the water access channel. These results suggest that biotin dissociation is initiated by stochastic coupling of water entry with lengthening of a specific biotin hydrogen-bonding interaction.

Transcriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly understood. During infection with HIV-1, human dendritic cells (DCs) can detect the virus through an innate sensing pathway leading to antiviral interferon and DC maturation. Here, we developed an iterative experimental and computational approach to map the innate response circuitry during HIV-1 infection. By integrating genome-wide chromatin accessibility with expression kinetics, we inferred a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observed that an interferon response is required, yet insufficient to drive DC maturation, and identified PRDM1 and RARA as essential regulators of the interferon response and DC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting complexity and cooperativity in the regulatory circuit controlling the DC response to infection.

Alveolar macrophages (AMs) are the first cells to be infected during Mycobacterium tuberculosis (Mtb) infection. Thus the AM response to infection is the first of many steps leading to initiation of the adaptive immune response, which is required for efficient control of infection. A hallmark of Mtb infection is the delay of the adaptive response, yet the mechanisms responsible for this delay are largely unknown. We developed a system to identify, sort and analyze Mtb-infected AMs from the lung within the first 10 days of infection. In contrast to what has been previously described using in vitro systems, we find that Mtb-infected AMs up-regulate a cell-protective antioxidant transcriptional signature that is dependent on the lung environment and not dependent on bacterial virulence. Computational approaches including pathway analysis and transcription factor binding motif enrichment analysis identify Nrf2 as a master regulator of the response of AMs to Mtb infection. Using knock-out mouse models, we demonstrate that Nrf2 drives the expression of the cell protective transcriptional program and impairs the ability of the host to control bacterial growth over the first 10 days of infection. Mtb-infected AMs exhibit a highly delayed pro-inflammatory response, and comparisons with uninfected AMs from the same infected animals demonstrate that inflammatory signals in the lung environment are blocked in the Mtb-infected cells. Thus, we have identified a novel lung-specific transcriptional response to Mtb infection that impedes AMs from responding rapidly to intracellular infection and thereby hinders the overall immune response. Footnotes * Gene name excel conversion errors corrected in supplemental tables.

Prioritizing candidate biomarkers for verification remains a formidable obstacle to the translation of protein diagnostics to clinical applications. Whiteaker et al . assemble a multistage, targeted proteomics pipeline to relieve this bottleneck and use a mouse cancer model to demonstrate its analytical performance. High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.