Pathogenic Fungi Regulate Immunity by Inducing Neutrophilic Myeloid-Derived Suppressor Cells

Peer reviewedPublisher PD

The Dectin-2 family of C-type lectin-like receptors : an update

Peer reviewedPublisher PD

Identifying Biological Network Structure, Predicting Network Behavior, and Classifying Network State With High Dimensional Model Representation (HDMR)

This work presents an adapted Random Sampling - High Dimensional Model Representation (RS-HDMR) algorithm for synergistically addressing three key problems in network biology: (1) identifying the structure of biological networks from multivariate data, (2) predicting network response under previously unsampled conditions, and (3) inferring experimental perturbations based on the observed network state. RS-HDMR is a multivariate regression method that decomposes network interactions into a hierarchy of non-linear component functions. Sensitivity analysis based on these functions provides a clear physical and statistical interpretation of the underlying network structure. The advantages of RS-HDMR include efficient extraction of nonlinear and cooperative network relationships without resorting to discretization, prediction of network behavior without mechanistic modeling, robustness to data noise, and favorable scalability of the sampling requirement with respect to network size. As a proof-of-principle study, RS-HDMR was applied to experimental data measuring the single-cell response of a protein-protein signaling network to various experimental perturbations. A comparison to network structure identified in the literature and through other inference methods, including Bayesian and mutual-information based algorithms, suggests that RS-HDMR can successfully reveal a network structure with a low false positive rate while still capturing non-linear and cooperative interactions. RS-HDMR identified several higher-order network interactions that correspond to known feedback regulations among multiple network species and that were unidentified by other network inference methods. Furthermore, RS-HDMR has a better ability to predict network response under unsampled conditions in this application than the best statistical inference algorithm presented in the recent DREAM3 signaling-prediction competition. RS-HDMR can discern and predict differences in network state that arise from sources ranging from intrinsic cell-cell variability to altered experimental conditions, such as when drug perturbations are introduced. This ability ultimately allows RS-HDMR to accurately classify the experimental conditions of a given sample based on its observed network state

A Prominent Role for DC-SIGN+ Dendritic Cells in Initiation and Dissemination of Measles Virus Infection in Non-Human Primates

Measles virus (MV) is a highly contagious virus that is transmitted by aerosols. During systemic infection, CD150+T and B lymphocytes in blood and lymphoid tissues are the main cells infected by pathogenic MV. However, it is unclear which cell types are the primary targets for MV in the lungs and how the virus reaches the lymphoid tissues. In vitro studies have shown that dendritic cell (DC) C-type lectin DC-SIGN captures MV, leading to infection of DCs as well as transmission to lymphocytes. However, evidence of DC-SIGN-mediated transmission in vivo has not been established. Here we identified DC-SIGNhiDCs as first target cells in vivo and demonstrate that macaque DC-SIGN functions as an attachment receptor for MV. Notably, DC-SIGNhicells from macaque broncho-alveolar lavage and lymph nodes transmit MV to B lymphocytes, providing in vivo support for an important role for DCs in both initiation and dissemination of MV infection

HIV-1 Disease Progression Is Associated with Bile-Salt Stimulated Lipase (BSSL) Gene Polymorphism

Background: DC-SIGN expressed by dendritic cells captures HIV-1 resulting in trans-infection of CD4+ T-lymphocytes. However, BSSL (bile-salt stimulated lipase) binding to DC-SIGN interferes with HIV-1 capture. DC-SIGN binding properties of BSSL associate with the polymorphic repeated motif of BSSL exon 11. Furthermore, BSSL binds to HIV-1 co-receptor CXCR4. We hypothesized that BSSL modulates HIV-1 disease progression and emergence of CXCR4 using HIV-1 (X4) variants. Results: The relation between BSSL genotype and HIV-1 disease progression and emergence of X4 variants was studied using Kaplan Meier and multivariate Cox proportional hazard analysis in a cohort of HIV-1 infected men having sex with men (n = 334, with n = 130 seroconverters). We analyzed the association of BSSL genotype with set-point viral load and CD4 cell count, both pre-infection and post-infection at viral set-point. The number of repeats in BSSL exon 11 were highly variable ranging from 10 to 18 in seropositive individuals and from 5-17 in HRSN with 16 repeats being dominant (>80% carry at least one allele with 16 repeats). We defined 16 to 18 repeats as high (H) and less than 16 repeats as low (L) repeat numbers. Homozygosity for the high (H) repeat number BSSL genotype (HH) correlated with high CD4 cell numbers prior to infection (p = 0.007). In HIV-1 patients, delayed disease progression was linked to the HH BSSL genotype (RH = 0.462 CI = 0.282-0.757, p = 0.002) as was delayed emergence of X4 variants (RH = 0.525, 95% CI = 0.290-0.953, p = 0.034). The LH BSSL genotype, previously found to be associated with enhanced DC-SIGN binding of human milk, was identified to correlate with accelerated disease progression in our cohort of HIV-1 infected MSM (RH = 0.517, 95% CI = 0.328-0.818, p = 0.005). Conclusion: We identify BSSL as a marker for HIV-1 disease progression and emergence of X4 variants. Additionally, we identified a relation between BSSL genotype and CD4 cell counts prior to infectio

Innate immunity against HIV: a priority target for HIV prevention research

This review summarizes recent advances and current gaps in understanding of innate immunity to human immunodeficiency virus (HIV) infection, and identifies key scientific priorities to enable application of this knowledge to the development of novel prevention strategies (vaccines and microbicides). It builds on productive discussion and new data arising out of a workshop on innate immunity against HIV held at the European Commission in Brussels, together with recent observations from the literature

Glycomic analysis of life stages of the human parasite Schistosoma mansoni reveals developmental expression profiles of functional and antigenic glycan motifs

Contains fulltext : 155377.pdf (publisher's version ) (Open Access)Glycans present on glycoproteins and glycolipids of the major human parasite Schistosoma mansoni induce innate as well as adaptive immune responses in the host. To be able to study the molecular characteristics of schistosome infections it is therefore required to determine the expression profiles of glycans and antigenic glycan-motifs during a range of critical stages of the complex schistosome lifecycle. We performed a longitudinal profiling study covering schistosome glycosylation throughout worm- and egg-development using a mass spectrometry-based glycomics approach. Our study revealed that during worm development N-glycans with Galbeta1-4(Fucalpha1-3)GlcNAc (LeX) and core-xylose motifs were rapidly lost after cercariae to schistosomula transformation, whereas GalNAcbeta1-4GlcNAc (LDN)-motifs gradually became abundant and predominated in adult worms. LeX-motifs were present on glycolipids up to 2 weeks of schistosomula development, whereas glycolipids with mono- and multifucosylated LDN-motifs remained present up to the adult worm stage. In contrast, expression of complex O-glycans diminished to undetectable levels within days after transformation. During egg development, a rich diversity of N-glycans with fucosylated motifs was expressed, but with alpha3-core fucose and a high degree of multifucosylated antennae only in mature eggs and miracidia. N-glycan antennae were exclusively LDN-based in miracidia. O-glycans in the mature eggs were also diverse and contained LeX- and multifucosylated LDN, but none of these were associated with miracidia in which we detected only the Galbeta1-3(Galbeta1-6)GalNAc core glycan. Immature eggs also exhibited short O-glycan core structures only, suggesting that complex fucosylated O-glycans of schistosome eggs are derived primarily from glycoproteins produced by the subshell envelope in the developed egg. Lipid glycans with multifucosylated GlcNAc repeats were present throughout egg development, but with the longer highly fucosylated stretches enriched in mature eggs and miracidia. This global analysis of the developing schistosome's glycome provides new insights into how stage-specifically expressed glycans may contribute to different aspects of schistosome-host interactions

Characterisation of Innate Fungal Recognition in the Lung

The innate recognition of fungi by leukocytes is mediated by pattern recognition receptors (PRR), such as Dectin-1, and is thought to occur at the cell surface triggering intracellular signalling cascades which lead to the induction of protective host responses. In the lung, this recognition is aided by surfactant which also serves to maintain the balance between inflammation and pulmonary function, although the underlying mechanisms are unknown. Here we have explored pulmonary innate recognition of a variety of fungal particles, including zymosan, Candida albicans and Aspergillus fumigatus, and demonstrate that opsonisation with surfactant components can limit inflammation by reducing host-cell fungal interactions. However, we found that this opsonisation does not contribute directly to innate fungal recognition and that this process is mediated through non-opsonic PRRs, including Dectin-1. Moreover, we found that pulmonary inflammatory responses to resting Aspergillus conidia were initiated by these PRRs in acidified phagolysosomes, following the uptake of fungal particles by leukocytes. Our data therefore provides crucial new insights into the mechanisms by which surfactant can maintain pulmonary function in the face of microbial challenge, and defines the phagolysosome as a novel intracellular compartment involved in the innate sensing of extracellular pathogens in the lung