Delay of phagosome maturation by a mycobacterial lipid is reversed by nitric oxide.

Mycobacterium tuberculosis is a facultative intracellular pathogen that inhibits phagosome maturation in macrophages thereby securing survival and growth. Mycobacteria reside in an early endocytic compartment of near-neutral pH where they upregulate production of complex glycolipids such as trehalose dimycolate. Here, we report that trehalose dimycolate coated onto beads increased the bead retention in early phagosomes, i.e. at a similar stage as viable mycobacteria. Thus, a single mycobacterial lipid sufficed to divert phagosome maturation and likely contributes to mycobacterial survival in macrophages. Previous studies showed that activated macrophages promote maturation of mycobacterial phagosomes and eliminate mycobacteria through bactericidal effectors including nitric oxide generated by inducible nitric-oxide synthase. We show that deceleration of bead phagosome maturation by trehalose dimycolate was abolished in immune-activated wild type, but not in activated nitric-oxide synthase-deficient macrophages, nor when hydroxyl groups of trehalose dimycolate were chemically modified by reactive nitrogen intermediates. Thus, specific host defence effectors of activated macrophages directly target a specific virulence function of mycobacteria

The IFN-inducible Golgi- and endoplasmic reticulum- associated 47-kDa GTPase IIGP is transiently expressed during listeriosis.

Members of the 47-kDa GTPase family are implicated in an IFN-gamma-induced, as yet unclear, mechanism that confers innate resistance against infection with intracellular pathogens. Overt immunological parameters are apparently uncompromised in mice deficient for individual members and the prototype of this family, IGTP, localizes to the endoplasmic reticulum. This suggests that these GTPases are involved in intracellular defense. We analyzed the expression of the 47-kDa GTPase cognate, IIGP, in splenic sections from mice infected with the intracellular pathogen Listeria monocytogenes by immunohistochemistry. An early transient IIGP induction was observed revealing the IFN-gamma responsiveness of cellular subcompartments within the spleen in early listeriosis. Marginal metallophilic macrophages and endothelial cells within the red and white pulp strongly expressed IIGP, while other splenocytes remained negative. In vitro analyses show that both type I and type II IFNs are prime stimuli for IIGP induction in various cells, including L. monocytogenes-infected or LPS-stimulated macrophages, endothelial cells, and activated T cells. Contrary to the subcellular localization of IGTP, IIGP was predominantly associated with the Golgi apparatus and also localizes to the endoplasmic reticulum. We conclude that IIGP exerts a distinct role in IFN-induced intracellular membrane trafficking or processing

IL-4 and T cells are required for the generation of IgG1 isotype antibodies against cardiolipin.

Infection with Mycobacterium tuberculosis induces Abs against a vast array of mycobacterial lipids and glycolipids. One of the most prominent lipid Ags recognized is cardiolipin (CL). The kinetics of the generation of anti-CL Abs during infection reveals that IgM titers to CL increase over time. Interestingly, at day 30 postinfection CL-specific IgG1 appears, an isotype usually dependent on T cell help. Using an immunization schedule with CL/anti-CL Ab complexes, which induces antiphospholipid syndrome in mice, we show that the generation of IgG1 to CL requires IL-4 and that optimal production is T cell dependent. IgG1 production to CL was impaired in nude (nu/nu) mice devoid in conventional T cells, but was not affected in mice deficient for either alphabeta TCR(+), gammadelta TCR(+), CD4(+), CD8(+), or NK1.1(+) T cells. We conclude that IgG1 production to CL depends on T cell help and IL-4, which can be provided by different T cell populations. This is the first report that IL-4 is indispensable for the induction of IgG1 Abs to lipid Ags

Induction of CCL8/MCP-2 by mycobacteria through the activation of TLR2/PI3K/Akt signaling pathway.

Pleural tuberculosis (TB), together with lymphatic TB, constitutes more than half of all extrapulmonary cases. Pleural effusions (PEs) in TB are representative of lymphocytic PEs which are dominated by T cells. However, the mechanism underlying T lymphocytes homing and accumulation in PEs is still incompletely understood. Here we performed a comparative analysis of cytokine abundance in PEs from TB patients and non-TB patients by protein array analysis and observed that MCP-2/CCL8 is highly expressed in the TB-PEs as compared to peripheral blood. Meanwhile, we observed that CCR5, the primary receptor used by MCP-2/CCL8, is mostly expressed on pleural CD4(+) T lymphocytes. Furthermore, we found that infection with either Mycobacterium bovis Bacillus Calmette-Guérin (BCG) or Mycobacterium tuberculosis H37Rv induced production of MCP-2/CCL8 at both transcriptional and protein level in Raw264.7 and THP-1 macrophage cells, mouse peritoneal macrophages as well as human PBMC monocyte-derived macrophages (MDMs). The induction of MCP-2/CCL8 by mycobacteria is dependent on the activation of TLR2/PI3K/Akt and p38 signaling pathway. We conclude that accumulation of MCP-2/CCL8 in TB-PEs may function as a biomarker for TB diagnosis

TRANSVAC workshop on standardisation and harmonisation of analytical platforms for HIV, TB and malaria vaccines: 'how can big data help?'.

High-throughput analyses of RNA and protein expression are increasingly used for better understanding of vaccine-induced immunity and protection against infectious disease. With an increasing number of vaccine candidates in clinical development, it is timely to consider standardisation and harmonisation of sample collection, storage and analysis to ensure results of highest quality from these precious samples. These challenges were discussed by a group of international experts during a workshop organised by TRANSVAC, a European Commission-funded Research Infrastructure project. The main conclusions were: Platforms are rarely standardised for use in preclinical and clinical studies. Coordinated efforts should continue to harmonise the experimental set up of these studies, as well as the establishment of internal standards and controls. This will ensure comparability, efficiency and feasibility of the global analyses performed on preclinical and clinical data sets

Changes in Transcript, Metabolite, and Antibody Reactivity During the Early Protective Immune Response in Humans to Mycobacterium tuberculosis Infection.

BACKGROUND: Strategies to prevent Mycobacterium tuberculosis (Mtb) infection are urgently required. In this study, we aimed to identify correlates of protection against Mtb infection. METHODS: Two groups of Mtb-exposed contacts of tuberculosis (TB) patients were recruited and classified according to their Mtb infection status using the tuberculin skin test (TST; cohort 1) or QuantiFERON (QFT; cohort 2). A negative reading at baseline with a positive reading at follow-up classified TST or QFT converters and a negative reading at both time points classified TST or QFT nonconverters. Ribonucleic acid sequencing, Mtb proteome arrays, and metabolic profiling were performed. RESULTS: Several genes were found to be differentially expressed at baseline between converters and nonconverters. Gene set enrichment analysis revealed a distinct B-cell gene signature in TST nonconverters compared to converters. When infection status was defined by QFT, enrichment of type I interferon was observed. A remarkable area under the curve (AUC) of 1.0 was observed for IgA reactivity to Rv0134 and an AUC of 0.98 for IgA reactivity to both Rv0629c and Rv2188c. IgG reactivity to Rv3223c resulted in an AUC of 0.96 and was markedly higher compared to TST nonconverters. We also identified several differences in metabolite profiles, including changes in biomarkers of inflammation, fatty acid metabolism, and bile acids. Pantothenate (vitamin B5) was significantly increased in TST nonconverters compared to converters at baseline (q = 0.0060). CONCLUSIONS: These data provide new insights into the early protective response to Mtb infection and possible avenues to interfere with Mtb infection, including vitamin B5 supplementation.Analysis of blood from highly exposed household contacts from The Gambia who never develop latent Mycobacterium tuberculosis infection shows distinct transcriptomic, antibody, and metabolomic profiles compared to those who develop latent tuberculosis infection but prior to any signs of infection

Human isotype‐dependent inhibitory antibody responses against Mycobacterium tuberculosis

Accumulating evidence from experimental animal models suggests that antibodies play a protective role against tuberculosis (TB). However, little is known about the antibodies generated upon Mycobacterium tuberculosis (MTB) exposure in humans. Here, we performed a molecular and functional characterization of the human B‐cell response to MTB by generating recombinant monoclonal antibodies from single isolated B cells of untreated adult patients with acute pulmonary TB and from MTB‐exposed healthcare workers. The data suggest that the acute plasmablast response to MTB originates from reactivated memory B cells and indicates a mucosal origin. Through functional analyses, we identified MTB inhibitory antibodies against mycobacterial antigens including virulence factors that play important roles in host cell infection. The inhibitory activity of anti‐MTB antibodies was directly linked to their isotype. Monoclonal as well as purified serum IgA antibodies showed MTB blocking activity independently of Fc alpha receptor expression, whereas IgG antibodies promoted the host cell infection. Together, the data provide molecular insights into the human antibody response to MTB and may thereby facilitate the design of protective vaccination strategies

A blood RNA signature for tuberculosis disease risk: a prospective cohort study.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: Bill & Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union, and the South African Medical Research Council

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

<p>Abstract</p> <p>Background</p> <p>For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or <it>in-silico </it>deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.</p> <p>Results</p> <p>Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach.</p> <p>Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.</p> <p>Conclusions</p> <p>The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.</p