Hugh Salamon

Dynamic antibody responses to the Mycobacterium tuberculosis proteome

Considerable effort has been directed toward controlling tuberculosis, which kills almost two million people yearly. High on the research agenda is the discovery of biomarkers of active tuberculosis (TB) for diagnosis and for monitoring treatment outcome. Rational biomarker discovery requires understanding host–pathogen interactions leading to biomarker expression. Here we report a systems immunology approach integrating clinical data and bacterial metabolic and regulatory information with high-throughput detection in human serum of antibodies to the entire Mycobacterium tuberculosis proteome. Sera from worldwide TB suspects recognized approximately 10% of the bacterial proteome. This result defines the M. tuberculosis immunoproteome, which is rich in membrane-associated and extracellular proteins. Additional analyses revealed that during active tuberculosis (i) antibody responses focused on an approximately 0.5% of the proteome enriched for extracellular proteins, (ii) relative target preference varied among patients, and (iii) responses correlated with bacillary burden. These results indicate that the B cell response tracks the evolution of infection and the pathogen burden and replicative state and suggest functions associated with B cell-rich foci seen in tuberculous lung granulomas. Our integrated proteome-scale approach is applicable to other chronic infections characterized by diverse antibody target recognition.

Cutting Edge: Vitamin D Regulates Lipid Metabolism in Mycobacterium tuberculosis Infection

Vitamin D has long been linked to resistance to tuberculosis, an infectious respiratory disease that is increasingly hard to treat because of multidrug resistance. Previous work established that vitamin D induces macrophage antimicrobial functions against Mycobacterium tuberculosis. In this article, we report a novel, metabolic role for vitamin D in tuberculosis identified through integrated transcriptome and mechanistic studies. Transcriptome analysis revealed an association between vitamin D receptor (VDR) and lipid metabolism in human tuberculosis and infected macrophages. Vitamin D treatment of infected macrophages abrogated infection-induced accumulation of lipid droplets, which are required for intracellular M. tuberculosis growth. Additional transcriptomics results showed that vitamin D downregulates the proadipogenic peroxisome proliferator–activated receptor γ (PPARγ) in infected macrophages. PPARγ agonists reversed the antiadipogenic and the antimicrobial effects of VDR, indicating a link between VDR and PPARγ signaling in regulating both vitamin D functions. These findings suggest the potential for host-based, adjunct antituberculosis therapy targeting lipid metabolism.

IFN-β1b Induces Transient and Variable Gene Expression in Relapsing-Remitting Multiple Sclerosis Patients Independent of Neutralizing Antibodies or Changes in IFN Receptor RNA Expression

Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS). Interferon-beta (IFN-beta) therapy for MS is hypothesized to cause short-term and long-term changes in gene expression that shift the inflammation from Th1 to Th2. In vivo gene induction to define kinetics of response to IFN-beta therapy in a large cohort of MS patients is described. Differential gene expression in peripheral blood mononuclear cells (PBMCs) obtained from relapsing-remitting MS patients (RRMS) was assessed using high content microarrays. Rapid onset of gene expression appeared within 4 h of subcutaneous IFN-beta administration, returning to baseline levels at 42 h in clinically stable RRMS. IFN-beta therapy in vivo rapidly but transiently induced strong upregulation of genes mediating immune modulation, IFN signaling, and antiviral responses. RT-PCR showed significant patient-to-patient variation in the magnitude of expression of multiple genes, especially for IFN-beta-inducible genes, such as MxA, IRF7, and CCL8, a Th1 product. Variation among patients in IFN-beta-induced RNA transcription was not explained by neutralizing antibodies or IFN receptor expression. Surprisingly, genes regulated in vivo by IFN-beta therapy do not support a simple Th1 to Th2 shift. A complex interplay between both proinflammatory and anti-inflammatory immune regulatory genes is likely to act in concert in the treatment of RRMS.

Proteome-Scale Antibody Responses and Outcome of Mycobacterium tuberculosis Infection in Nonhuman Primates and in Tuberculosis Patients

BACKGROUNDnBiomarkers of progression from latent Mycobacterium tuberculosis infection to active tuberculosis are needed. We assessed correlations between infection outcome and antibody responses in macaques and humans by high-throughput, proteome-scale serological studies.nnnMETHODSnMycobacterium tuberculosis proteome microarrays were probed with serial sera from macaques representing various infection outcomes and with single-point human sera from tuberculosis suspects. Fluorescence intensity data were analyzed by calculating Z scores and associated P values. Temporal changes in macaque antibody responses were analyzed by polynomial regression. Correlations between human responses and sputum bacillary burden were assessed by quantile and hurdle regression.nnnRESULTSnMacaque outcome groups exhibited distinct antibody profiles: early, transient responses in latent infection and stable antibody increase in active and reactivation disease. In humans, antibody levels and reactive protein numbers increased with bacillary burden. Responses to a subset of 10 proteins were more tightly associated with disease state than reactivity to the broader reactive proteome.nnnCONCLUSIONSnIntegration of macaque and human data reveals dynamic properties of antibody responses in relation to outcome and leads to actionable findings for translational research. These include the potential of antibody responses to detect acute infection and preclinical tuberculosis and to identify serodiagnostic proteins for the spectrum of bacillary burden in tuberculosis.

Infection with Mycobacterium tuberculosis induces the Warburg effect in mouse lungs.

To elucidate the little-known bioenergetic pathways of host immune cells in tuberculosis, a granulomatous disease caused by the intracellular pathogen Mycobacterium tuberculosis, we characterized infected murine lung tissue by transcriptomic profiling and confocal imaging. Transcriptomic analysis revealed changes of host energy metabolism during the course of infection that are characterized by upregulation of key glycolytic enzymes and transporters for glucose uptake, and downregulation of enzymes participating in the tricarboxylic acid cycle and oxidative phosphorylation. Consistent with elevated glycolysis, we also observed upregulation of a transporter for lactate secretion and a V type H+ -ATPase involved in cytosolic pH homeostasis. Transcription profiling results were corroborated by immunofluorescence microscopy showing increased expression of key glycolytic enzymes in macrophages and T cells in granulomatous lesions. Moreover, we found increased mRNA and protein levels in macrophages and T cells of hypoxia inducible factor 1 alpha (HIF-1α), the regulatory subunit of HIF-1, a master transcriptional regulator. Thus, our findings suggest that immune cells predominantly utilize aerobic glycolysis in response to M. tuberculosis infection. This bioenergetic shift is similar to the Warburg effect, the metabolic signature of cancer cells. Finding immunometabolic changes during M. tuberculosis infection opens the way to new strategies for immunotherapy against tuberculosis.

IFN-β-regulated genes show abnormal expression in therapy-naive relapsing-remitting MS mononuclear cells : Gene expression analysis employing all reported protein-protein interactions

The molecular mechanism by which interferon beta (IFN-beta) is effective in treating multiple sclerosis is not well understood. Mononuclear cells from therapy-naïve MS patients, IFN-beta-1b-treated MS patients, and healthy controls were analyzed to examine mRNA changes that characterize both the disease and its treatment. The scientific literature was comprehensively searched for all protein-protein interactions. In MS patients who had never been treated with IFN-beta, statistical analysis revealed coordinate changes in mRNA expression for proteins reported in the literature as regulated by IFN-beta. As a positive control for this approach, samples from a separate MS patient cohort showed significant change of these same genes during in vivo treatment with IFN-beta-1b.The strength of effect observed for regulation by IFN-beta was greater than for IFN-alpha, IFN-gamma (Th1), or IL-4 (Th2). Of the sets we investigated, the most strongly affected by disease was the subset defined by regulation by both IFN-beta and IFN-alpha. Changes in cells from therapy-naïve MS patients thus anticipated the importance of IFN-beta in therapy. These findings are a significant step towards marrying MS disease etiology and IFN-beta mechanism of action at a molecular level.

Integration of Published Information Into a Resistance-Associated Mutation Database for Mycobacterium tuberculosis

Tuberculosis remains a major global public health challenge. Although incidence is decreasing, the proportion of drug-resistant cases is increasing. Technical and operational complexities prevent Mycobacterium tuberculosis drug susceptibility phenotyping in the vast majority of new and retreatment cases. The advent of molecular technologies provides an opportunity to obtain results rapidly as compared to phenotypic culture. However, correlations between genetic mutations and resistance to multiple drugs have not been systematically evaluated. Molecular testing of M. tuberculosis sampled from a typical patient continues to provide a partial picture of drug resistance. A database of phenotypic and genotypic testing results, especially where prospectively collected, could document statistically significant associations and may reveal new, predictive molecular patterns. We examine the feasibility of integrating existing molecular and phenotypic drug susceptibility data to identify associations observed across multiple studies and demonstrate potential for well-integrated M. tuberculosis mutation data to reveal actionable findings.

Hemoglobin polymerization in sickle cells studied by circular polarized light scattering

We have studied intracellular polymerization of hemoglobin S in suspensions of small populations of sickle cells using circular polarized light scattering. We argue that the preferential scattering of right circular polarized light (as expressed by measurements of the S14 Mueller scattering matrix element) directly reflects the amount of polymer inside cells. This technique has made it possible to investigate the effect of oxygen tension, cell density and osmotic stress on intracellular hemoglobin polymerization. Using S14 to determine hemoglobin polymer, we show that the polymer increases with deoxyhemoglobin concentration, that cells containing higher hemoglobin concentrations show significantly more polymer than cells containing less hemoglobin, and that polymerization occurs in sickle-trait cells in hypertonic solutions as the oxygen tension in the suspension is reduced. We also present kinetic measurements of polymerization, including that induced by osmotic shock. Finally, we demonstrate that the total light scattered (S11 Mueller scattering matrix element) that is routinely measured simultaneously with S14 can be used to estimate the percent of reduced (deoxy) Hb in the sample. These experiments demonstrate the potential of this technique to monitor hemoglobin polymerization simultaneously with oxygen dissociation under a wide variety of physiological conditions.

Differential Gene Expression in Thrombomodulin (TM; CD141)+ and TM− Dendritic Cell Subsets

Previously we have shown in a mouse model of bronchial asthma that thrombomodulin can convert immunogenic conventional dendritic cells into tolerogenic dendritic cells while inducing its own expression on their cell surface. Thrombomodulin+ dendritic cells are tolerogenic while thrombomodulin− dendritic cells are pro-inflammatory and immunogenic. Here we hypothesized that thrombomodulin treatment of dendritic cells would modulate inflammatory gene expression. Murine bone marrow-derived dendritic cells were treated with soluble thrombomodulin and expression of surface markers was determined. Treatment with thrombomodulin reduces the expression of maturation markers and increases the expression of TM on the DC surface. Thrombomodulin treated and control dendritic cells were sorted into thrombomodulin+ and thrombomodulin− dendritic cells before their mRNA was analyzed by microarray. mRNAs encoding pro-inflammatory genes and dendritic cells maturation markers were reduced while expression of cell cycle genes were increased in thrombomodulin-treated and thrombomodulin+ dendritic cells compared to control dendritic cells and thrombomodulin− dendritic cells. Thrombomodulin-treated and thrombomodulin+ dendritic cells had higher expression of 15-lipoxygenase suggesting increased synthesis of lipoxins. Thrombomodulin+ dendritic cells produced more lipoxins than thrombomodulin− dendritic cells, as measured by ELISA, confirming that this pathway was upregulated. There was more phosphorylation of several cell cycle kinases in thrombomodulin+ dendritic cells while phosphorylation of kinases involved with pro-inflammatory cytokine signaling was reduced. Cultures of thrombomodulin+ dendritic cells contained more cells actively dividing than those of thrombomodulin− dendritic cells. Production of IL-10 is increased in thrombomodulin+ dendritic cells. Antagonism of IL-10 with a neutralizing antibody inhibited the effects of thrombomodulin treatment of dendritic cells suggesting a mechanistic role for IL-10. The surface of thrombomodulin+ dendritic cells supported activation of protein C and procarboxypeptidase B2 in a thrombomodulin-dependent manner. Thus thrombomodulin treatment increases the number of thrombomodulin+ dendritic cells, which have significantly altered gene expression compared to thrombomodulin− dendritic cells in key immune function pathways.

On distinguishing unique combinations in biological sequences.

The problem of defining combinations of variants unique to a sequence is efficiently addressed as a set covering computation. The unique-combinations method is introduced, which identifies patterns in biological sequence data that distinguish a sequence from a group of other sequences. This method is further developed to describe features consistently present in one group of sequences but not in a second group. The approach is incorporated into a novel analytical tool, designed for use in studies of polymorphic sequence data, such as mitochondrial, human leukocyte antigen (HLA), or viral pathogen sequences. The unique combinations method is well suited to applications in medical genetics and evolutionary genetics. An example implementation of the unique-combinations method yields greatly improved risk assessment for insulin-dependent diabetes mellitus (IDDM) from amino acid patterns isolated in an analysis of HLA class II DQA1-DQB1 patient and control genotypes.