The emergence of viral respiratory pathogens with pandemic potential, such as severe acute respiratory syndrome coronavirus (SARS-CoV) and influenza A H5N1, urges the need for deciphering their ...pathogenesis to develop new intervention strategies. SARS-CoV infection causes acute lung injury (ALI) that may develop into life-threatening acute respiratory distress syndrome (ARDS) with advanced age correlating positively with adverse disease outcome. The molecular pathways, however, that cause virus-induced ALI/ARDS in aged individuals are ill-defined. Here, we show that SARS-CoV-infected aged macaques develop more severe pathology than young adult animals, even though viral replication levels are similar. Comprehensive genomic analyses indicate that aged macaques have a stronger host response to virus infection than young adult macaques, with an increase in differential expression of genes associated with inflammation, with NF-kappaB as central player, whereas expression of type I interferon (IFN)-beta is reduced. Therapeutic treatment of SARS-CoV-infected aged macaques with type I IFN reduces pathology and diminishes pro-inflammatory gene expression, including interleukin-8 (IL-8) levels, without affecting virus replication in the lungs. Thus, ALI in SARS-CoV-infected aged macaques developed as a result of an exacerbated innate host response. The anti-inflammatory action of type I IFN reveals a potential intervention strategy for virus-induced ALI.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A major cause of respiratory failure during influenza A virus (IAV) infection is damage to the epithelial-endothelial barrier of the pulmonary alveolus. Damage to this barrier results in flooding of ...the alveolar lumen with proteinaceous oedema fluid, erythrocytes and inflammatory cells. To date, the exact roles of pulmonary epithelial and endothelial cells in this process remain unclear.Here, we used an in vitro co-culture model to understand how IAV damages the pulmonary epithelial-endothelial barrier. Human epithelial cells were seeded on the upper half of a transwell membrane while human endothelial cells were seeded on the lower half. These cells were then grown in co-culture and IAV was added to the upper chamber.We showed that the addition of IAV (H1N1 and H5N1 subtypes) resulted in significant barrier damage. Interestingly, we found that, while endothelial cells mounted a pro-inflammatory/pro-coagulant response to a viral infection in the adjacent epithelial cells, damage to the alveolar epithelial-endothelial barrier occurred independently of endothelial cells. Rather, barrier damage was associated with disruption of tight junctions amongst epithelial cells, and specifically with loss of tight junction protein claudin-4.Taken together, these data suggest that maintaining epithelial cell integrity is key in reducing pulmonary oedema during IAV infection.
High Throughput Sequencing (HTS) has enabled researchers to probe the human T cell receptor (TCR) repertoire, which consists of many rare sequences. Distinguishing between true but rare TCR sequences ...and variants generated by polymerase chain reaction (PCR) and sequencing errors remains a formidable challenge. The conventional approach to handle errors is to remove low quality reads, and/or rare TCR sequences. Such filtering discards a large number of true and often rare TCR sequences. However, accurate identification and quantification of rare TCR sequences is essential for repertoire diversity estimation.
We devised a pipeline, called Recover TCR (RTCR), that accurately recovers TCR sequences, including rare TCR sequences, from HTS data (including barcoded data) even at low coverage. RTCR employs a data-driven statistical model to rectify PCR and sequencing errors in an adaptive manner. Using simulations, we demonstrate that RTCR can easily adapt to the error profiles of different types of sequencers and exhibits consistently high recall and high precision even at low coverages where other pipelines perform poorly. Using published real data, we show that RTCR accurately resolves sequencing errors and outperforms all other pipelines.
The RTCR pipeline is implemented in Python (v2.7) and C and is freely available at http://uubram.github.io/RTCR/along with documentation and examples of typical usage.
b.gerritsen@uu.nl.
Vaccine development involves time-consuming and expensive evaluation of candidate vaccines in animal models. As mediators of both innate and adaptive immune responses dendritic cells (DCs) are ...considered to be highly important for vaccine performance. Here we evaluated how far the response of DCs to a vaccine in vitro is in line with the immune response the vaccine evokes in vivo. To this end, we investigated the response of murine bone marrow-derived DCs to whole inactivated virus (WIV) and subunit (SU) influenza vaccine preparations. These vaccine preparations were chosen because they differ in the immune response they evoke in mice with WIV being superior to SU vaccine through induction of higher virus-neutralizing antibody titers and a more favorable Th1-skewed response phenotype. Stimulation of DCs with WIV, but not SU vaccine, resulted in a cytokine response that was comparable to that of DCs stimulated with live virus. Similarly, the gene expression profiles of DCs treated with WIV or live virus were similar and differed from that of SU vaccine-treated DCs. More specifically, exposure of DCs to WIV resulted in differential expression of genes in known antiviral pathways, whereas SU vaccine did not. The stronger antiviral and more Th1-related response of DCs to WIV as compared to SU vaccine correlates well with the superior immune response found in mice. These results indicate that in vitro stimulation of DCs with novel vaccine candidates combined with the assessment of multiple parameters, including gene signatures, may be a valuable tool for the selection of vaccine candidates.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To identify immunological mechanisms that govern distinct clinical phases of a chronic hepatitis B virus (HBV) infection—immune tolerant (IT), immune active (IA), inactive carrier (IC), and hepatitis ...B e antigen (HBeAg)‐negative (ENEG) hepatitis phases—we performed a systems biology study. Serum samples from untreated chronic HBV patients (n = 71) were used for multiplex cytokine measurements, quantitative hepatitis B surface antigen (HBsAg), HBeAg levels, HBV genotype, and mutant analysis. Leukocytes were phenotyped using multicolor flow cytometry, and whole‐blood transcriptome profiles were generated. The latter were compared with liver biopsy transcriptomes from IA (n = 16) and IT (n = 3) patients. HBV viral load as well as HBeAg and HBsAg levels (P < 0.001), but not leukocyte composition, differed significantly between distinct phases. Serum macrophage chemotactic protein 1, interleukin‐12p40, interferon (IFN)‐gamma‐inducible protein 10, and macrophage inflammatory protein 1 beta levels were different between two or more clinical phases (P < 0.05). Comparison of blood transcriptomes identified 64 differentially expressed genes. The gene signature distinguishing IA from IT and IC patients was predominantly composed of highly up‐regulated immunoglobulin‐encoding genes. Modular repertoire analysis using gene sets clustered according to similar expression patterns corroborated the abundant expression of B‐cell function‐related genes in IA patients and pointed toward increased (ISG) transcript levels in IT patients, compared to subsequent phases. Natural killer cell activities were clustered in clinical phases with biochemical liver damage (IA and ENEG phases), whereas T‐cell activities were higher in all phases, compared to IT patients. B‐cell‐related transcripts proved to be higher in biopsies from IA versus IT patients. Conclusion: HBV clinical phases are characterized by distinct blood gene signatures. Innate IFN and B‐cell responses are highly active during the IT and IA phases, respectively. This suggests that the presumed immune tolerance in chronic HBV infections needs to be redefined. (Hepatology 2015;62:87‐100)
Interspecies transmission of pathogens may result in the emergence of new infectious diseases in humans as well as in domestic and wild animals. Genomics tools such as high-throughput sequencing, ...mRNA expression profiling, and microarray-based analysis of single nucleotide polymorphisms are providing unprecedented ways to analyze the diversity of the genomes of emerging pathogens as well as the molecular basis of the host response to them. By comparing and contrasting the outcomes of an emerging infection with those of closely related pathogens in different but related host species, we can further delineate the various host pathways determining the outcome of zoonotic transmission and adaptation to the newly invaded species. The ultimate challenge is to link pathogen and host genomics data with biological outcomes of zoonotic transmission and to translate the integrated data into novel intervention strategies that eventually will allow the effective control of newly emerging infectious diseases.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To characterize the host response to dendritic cell-based immunotherapy and subsequent combined antiretroviral therapy (cART) interruption in HIV-1-infected individuals at the plasma protein level.
...An autologous dendritic cell (DC) therapeutic vaccine was administered to HIV-infected individuals, stable on cART. The effect of vaccination was evaluated at the plasma protein level during the period preceding cART interruption, during analytical therapy interruption and at viral reactivation. Healthy controls and post-exposure prophylactically treated healthy individuals were included as controls.
Plasma marker ('analyte') levels including cytokines, chemokines, growth factors, and hormones were measured in trial participants and control plasma samples using a multiplex immunoassay. Analyte levels were analysed using principle component analysis, cluster analysis and limma. Blood neutrophil counts were analysed using linear regression.
Plasma analyte levels of HIV-infected individuals are markedly different from those of healthy controls and HIV-negative individuals receiving post-exposure prophylaxis. Viral reactivation following cART interruption also affects multiple analytes, but cART interruption itself only has only a minor effect. We find that Thyroxine-Binding Globulin (TBG) levels and late-stage neutrophil numbers correlate with the time off cART after DC vaccination. Furthermore, analysis shows that cART alters several regulators of blood glucose levels, including C-peptide, chromogranin-A and leptin. HIV reactivation is associated with the upregulation of CXCR3 ligands.
Chronic HIV infection leads to a change in multiple plasma analyte levels, as does virus reactivation after cART interruption. Furthermore, we find evidence for the involvement of TBG and neutrophils in the response to DC-vaccination in the setting of HIV-infection.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study reveals that 1918 H1N1 influenza virus spreads to and induces proinflammatory cytokine responses in extrarespiratory tissues, including the nervous system, liver, and heart. This likely ...contributes to the development of severe disease, including diseases of the nervous system.
Abstract
Background
The 1918 Spanish H1N1 influenza pandemic was the most severe recorded influenza pandemic with an estimated 20–50 million deaths worldwide. Even though it is known that influenza viruses can cause extrarespiratory tract complications—which are often severe or even fatal—the potential contribution of extrarespiratory tissues to the pathogenesis of 1918 H1N1 virus infection has not been studied comprehensively.
Methods
Here, we performed a time-course study in ferrets inoculated intranasally with 1918 H1N1 influenza virus, with special emphasis on the involvement of extrarespiratory tissues. Respiratory and extrarespiratory tissues were collected after inoculation for virological, histological, and immunological analysis.
Results
Infectious virus was detected at high titers in respiratory tissues and, at lower titers in most extrarespiratory tissues. Evidence for active virus replication, as indicated by the detection of nucleoprotein by immunohistochemistry, was observed in the respiratory tract, peripheral and central nervous system, and liver. Proinflammatory cytokines were up-regulated in respiratory tissues, olfactory bulb, spinal cord, liver, heart, and pancreas.
Conclusions
1918 H1N1 virus spread to and induced cytokine responses in tissues outside the respiratory tract, which likely contributed to the severity of infection. Moreover, our data support the suggested link between 1918 H1N1 infection and central nervous system disease.
The RIG-I-like receptor (RLR) pathway is essential for detecting cytosolic viral RNA to trigger the production of type I interferons (IFNα/β) that initiate an innate antiviral response. Through ...systematic assessment of a wide variety of genomics data, we discovered 10 molecular signatures of known RLR pathway components that collectively predict novel members. We demonstrate that RLR pathway genes, among others, tend to evolve rapidly, interact with viral proteins, contain a limited set of protein domains, are regulated by specific transcription factors, and form a tightly connected interaction network. Using a Bayesian approach to integrate these signatures, we propose likely novel RLR regulators. RNAi knockdown experiments revealed a high prediction accuracy, identifying 94 genes among 187 candidates tested (~50%) that affected viral RNA-induced production of IFNβ. The discovered antiviral regulators may participate in a wide range of processes that highlight the complexity of antiviral defense (e.g. MAP3K11, CDK11B, PSMA3, TRIM14, HSPA9B, CDC37, NUP98, G3BP1), and include uncharacterized factors (DDX17, C6orf58, C16orf57, PKN2, SNW1). Our validated RLR pathway list (http://rlr.cmbi.umcn.nl/), obtained using a combination of integrative genomics and experiments, is a new resource for innate antiviral immunity research.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
With the advent of high-throughput proteomics, the type and amount of data pose a significant challenge to statistical approaches used to validate current quantitative analysis. Whereas many ...studies focus on the analysis at the protein level, the analysis of peptide-level data provides insight into changes at the sub-protein level, including splice variants, isoforms and a range of post-translational modifications. Statistical evaluation of liquid chromatography-mass spectrometry/mass spectrometry peptide-based label-free differential data is most commonly performed using a t-test or analysis of variance, often after the application of data imputation to reduce the number of missing values. In high-throughput proteomics, statistical analysis methods and imputation techniques are difficult to evaluate, given the lack of gold standard data sets. Here, we use experimental and resampled data to evaluate the performance of four statistical analysis methods and the added value of imputation, for different numbers of biological replicates. We find that three or four replicates are the minimum requirement for high-throughput data analysis and confident assignment of significant changes. Data imputation does increase sensitivity in some cases, but leads to a much higher actual false discovery rate. Additionally, we find that empirical Bayes method (limma) achieves the highest sensitivity, and we thus recommend its use for performing differential expression analysis at the peptide level.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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