Signature patterns revealed by microarray analyses of mice infected with influenza virus A and Streptococcus pneumoniae

An efficient method for mining cross-timepoint gene regulation sequential patterns from time course gene expression datasets

BACKGROUND

Observation of gene expression changes implying gene regulations using a repetitive experiment in time course has become more and more important. However, there is no effective method which can handle such kind of data. For instance, in a clinical/biological progression like inflammatory response or cancer formation, a great number of differentially expressed genes at different time points could be identified through a large-scale microarray approach. For each repetitive experiment with different samples, converting the microarray datasets into transactional databases with significant singleton genes at each time point would allow sequential patterns implying gene regulations to be identified. Although traditional sequential pattern mining methods have been successfully proposed and widely used in different interesting topics, like mining customer purchasing sequences from a transactional database, to our knowledge, the methods are not suitable for such biological dataset because every transaction in the converted database may contain too many items/genes.

RESULTS

In this paper, we propose a new algorithm called CTGR-Span (Cross-Timepoint Gene Regulation Sequential pattern) to efficiently mine CTGR-SPs (Cross-Timepoint Gene Regulation Sequential Patterns) even on larger datasets where traditional algorithms are infeasible. The CTGR-Span includes several biologically designed parameters based on the characteristics of gene regulation. We perform an optimal parameter tuning process using a GO enrichment analysis to yield CTGR-SPs more meaningful biologically. The proposed method was evaluated with two publicly available human time course microarray datasets and it was shown that it outperformed the traditional methods in terms of execution efficiency. After evaluating with previous literature, the resulting patterns also strongly correlated with the experimental backgrounds of the datasets used in this study.

CONCLUSIONS

We propose an efficient CTGR-Span to mine several biologically meaningful CTGR-SPs. We postulate that the biologist can benefit from our new algorithm since the patterns implying gene regulations could provide further insights into the mechanisms of novel gene regulations during a biological or clinical progression. The Java source code, program tutorial and other related materials used in this program are available at http://websystem.csie.ncku.edu.tw/CTGR-Span.rar.

Microwave and magnetic (M(2) ) proteomics of the experimental autoimmune encephalomyelitis animal model of multiple sclerosis

We hypothesized that quantitative MS/MS-based proteomics at multiple time points, incorporating rapid microwave and magnetic (M(2) ) sample preparation, could enable relative protein expression to be correlated to disease progression in the experimental autoimmune encephalomyelitis (EAE) animal model of multiple sclerosis. To test our hypothesis, microwave-assisted reduction/alkylation/digestion of proteins from brain tissue lysates bound to C8 magnetic beads and microwave-assisted isobaric chemical labeling were performed of released peptides, in 90 s prior to unbiased proteomic analysis. Disease progression in EAE was assessed by scoring clinical EAE disease severity and confirmed by histopathologic evaluation for central nervous system inflammation. Decoding the expression of 283 top-ranked proteins (p <0.05) at each time point relative to their expression at the peak of disease, from a total of 1191 proteins observed in four technical replicates, revealed a strong statistical correlation to EAE disease score, particularly for the following four proteins that closely mirror disease progression: 14-3-3ε (p = 3.4E-6); GPI (p = 2.1E-5); PLP1 (p = 8.0E-4); PRX1 (p = 1.7E-4). These results were confirmed by Western blotting, signaling pathway analysis, and hierarchical clustering of EAE risk groups. While validation in a larger cohort is underway, we conclude that M(2) proteomics is a rapid method to quantify putative prognostic/predictive protein biomarkers and therapeutic targets of disease progression in the EAE animal model of multiple sclerosis.

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

Resequencing microarray method for molecular diagnosis of human arboviral diseases

BACKGROUND

Resequencing DNA microarray (RMA) technology uses probes designed to identify a panel of viral sequences. It can be used for detecting emerging viruses by revealing the nucleotide polymorphisms within the target of interest.

OBJECTIVES/STUDY DESIGN

As a new tool for molecular diagnosis of arbovirus infection, high density PathogenID v2.0 RMA (PID2-RMA) was assessed for the detection and genetic analysis of dengue, West Nile, and Chikungunya viruses in spiked blood samples or sera from individuals infected with dengue virus. Viral RNAs extracted from biological samples were retrotranscribed into cDNA and amplified using the Phi 29 polymerase-based method. This amplified cDNA was used for hybridization on PID2-RMA.

RESULTS

A good specificity of RMA-based detection was demonstrated using a panel of arboviruses including Dengue, West Nile and Chikungunya viruses. This technology was also efficient for the detection and genetic analysis of the different serotypes of dengue virus in sera of infected patients. Furthermore, the mixing of dengue, West Nile and Chikungunya prototype viruses within a single sample of human blood did not interfere with the sensitivity of PID2-RMA.

CONCLUSIONS

Our data show that high density PID2-RMA was suitable for the identification of medically important arboviruses. It appears to be particularly adapted to the genetic analysis of dengue, West Nile, and Chikungunya viruses in urgent clinical situations where the rapid identification and characterization of the pathogen is essential.

Global transcriptome analysis in influenza-infected mouse lungs reveals the kinetics of innate and adaptive host immune responses

An infection represents a highly dynamic process involving complex biological responses of the host at many levels. To describe such processes at a global level, we recorded gene expression changes in mouse lungs after a non-lethal infection with influenza A virus over a period of 60 days. Global analysis of the large data set identified distinct phases of the host response. The increase in interferon genes and up-regulation of a defined NK-specific gene set revealed the initiation of the early innate immune response phase. Subsequently, infiltration and activation of T and B cells could be observed by an augmentation of T and B cell specific signature gene expression. The changes in B cell gene expression and preceding chemokine subsets were associated with the formation of bronchus-associated lymphoid tissue. In addition, we compared the gene expression profiles from wild type mice with Rag2 mutant mice. This analysis readily demonstrated that the deficiency in the T and B cell responses in Rag2 mutants could be detected by changes in the global gene expression patterns of the whole lung. In conclusion, our comprehensive gene expression study describes for the first time the entire host response and its kinetics to an acute influenza A infection at the transcriptome level.

The innate immune response to Streptococcus pneumoniae in the lung depends on serotype and host response

Bacteremic pneumonia with some pneumococcal capsular serotypes, including serotype 3 (ST3), has been associated with a higher risk of death, whereas others, such as ST8, are associated with a lower risk. To provide a molecular basis for understanding such differences, we used oligo cDNA microarrays to analyze and compare the gene expression profiles of the lungs of Balb/c mice infected intranasally with either ST3, strain A66.1, or ST8, strain ATCC 6308 (6308). Compared to uninfected controls, infection with either A66.1 or 6308 led to inoculum-dependent expression of IFN-γ inducible CXC chemokines among other pro-inflammatory genes. To investigate the role that IFN-γ inducible chemokines CXCL9, CXCL10 and CXCL11 play in A66.1- and 6308-induced pneumonia, we examined the effect of the absence of their common receptor, CXCR3, on intranasal infection in CXCR3(-/-) (Balb/c) mice. Compared to wild type (WT) mice, virulence of A66.1 but not 6308 was attenuated in CXCR3(-/-) mice. A66.1-infected CXCR3(-/-) mice had fewer lung neutrophils and more alveolar macrophages 48 h after infection and fewer blood CFU 72 h after infection. Histopathological examination of lung sections revealed less inflammation among A66.1-infected CXCR3(-/-) than WT mice. The reduced virulence of A66.1 in CXCR3(-/-) mice suggests that inhibition of the functional activity of IFN-γ inducible chemokines modulates the host response to A66.1, in turn suggesting a novel approach to improve vaccine-mediated protection against ST3 pneumonia.

Uncovering the global host cell requirements for influenza virus replication via RNAi screening

Influenza virus is reliant on numerous host cell functions during its replication cycle. RNA interference technology, applied on a genome-wide level, has identified human host factors that are necessary for efficient virus replication and provides new insight into how influenza virus interacts with its host at the molecular level.

The Human Lung Microbiome

The human lower respiratory tract is considered sterile in normal healthy individuals (Flanagan et al., 2007; Speert, 2006) despite the fact that every day we breathe in multiple microorganisms present in the air and aspirate thousands of organisms from the mouth and nasopharynx. This apparent sterility is maintained by numerous interrelated components of the lung physical structures such as the mucociliary elevator and components of the innate and adaptive immune systems (discussed below) (reviewed in (Diamond et al., 2000; Gerritsen, 2000)). However, it is possible that the observed sterility might be a result of the laboratory practices applied to study the flora of the lungs. Historically, researchers faced with a set of diseases characterized by a changing and largely cryptic lung microbiome have lacked tools to study lung ecology as a whole and have concentrated on familiar, cultivatable candidate pathogens.

Gene expression signature-based screening identifies new broadly effective influenza a antivirals

Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be used to identify antivirals. Such an approach could accelerate drug discovery and be extended to other pathogens.

Gene expression changes in the host response between resistant and susceptible inbred mouse strains after influenza A infection

Inbred mouse strains exhibit differences in susceptibility to influenza A infections. However, the molecular mechanisms underlying these differences are unknown. Therefore, we infected a highly susceptible mouse strain (DBA/2J) and a resistant strain (C57BL/6J) with influenza A H1N1 (PR8) and performed genome-wide expression analysis. We found genes expressed in lung epithelium that were specifically down-regulated in DBA/2J mice, whereas a cluster of genes on chromosome 3 was only down-regulated in C57BL/6J. In both mouse strains, chemokines, cytokines and interferon-response genes were up-regulated, indicating that the main innate immune defense pathways were activated. However, many immune response genes were up-regulated in DBA/2J much stronger than in C57BL/6J, and several immune response genes were exclusively regulated in DBA/2J. Thus, susceptible DBA/2J mice showed a hyper-inflammatory response. This response is similar to infections with highly pathogenic influenza virus and may serve as a paradigm for a hyper-inflammatory host response to influenza A virus.

HLA class I molecules reflect an altered host proteome after influenza virus infection

Class I HLA sample and display peptides from thousands of endogenous proteins at the cell surface. During infection, the influenza virus modifies the host cell proteome by triggering host antiviral responses, hijacking host processes, and inhibiting host mRNA processing. In turn, the catalog of HLA class I peptides that decorate the surface of an infected cell is positioned to reflect an altered host cell proteome. To understand the host-encoded peptides presented by class I molecules after influenza infection, we compared by mass spectrometry (MS) the peptides eluted from the HLA of naive and infected cells. We identified 20 peptide ligands unique to infected cells and 347 peptides with increased presentation after infection. Infection with different influenza strains demonstrated that proteome changes are predominantly strain-specific, with few individual cellular interactions observed for multiple viral strains. Modeling by pathway analysis, however, revealed that strain specific host peptide changes represent different routes to the same destination; host changes mediated by influenza are found predominantly clustered around HLA-B, ACTB, HSP90AB1, CDK2, and ANXA2. The class I HLA proteome scanning of influenza-infected cells therefore indicates how divergent strains of influenza pursue alternate routes to access the same host cell processes.

Mammalian cell transcriptome in response to meningitis-causing pathogens

Bacterial meningitis continues to be a major cause of mortality and morbidity, despite improved antimicrobial therapy. A key factor that contributes to this situation is the incomplete understanding of its pathogenesis. High-throughput methods (e.g., DNA microarray technology) can provide a holistic picture of the transcriptional events that underlie the host response to bacterial infections, including that during bacterial meningitis. Since 2001, several studies have been reported on the cellular host's responses to infections with Neisseria meningitidis and Streptococcus pneumoniae (the leading causes of bacterial meningitis) using DNA microarrays and have described numerous differentially expressed genes. The present review summarizes the main recent findings with gene expression analyses in the field of bacterial meningitis. Experiments that defined a common host response, as well as pathogen-specific host responses, will be discussed. This review will also outline the contributions of global gene analyses to our understanding of the pathophysiology of bacterial meningitis.

Novel approaches to the identification of Streptococcus pneumoniae as the cause of community-acquired pneumonia

Current diagnostic tests lack sensitivity for the identification of the bacterial etiology of pneumonia. Attempts during the past 2 decades to improve sensitivity of detection of bacterial constituents in blood by use of antibody-antigen complexes and polymerase chain reaction have been disappointing. Recent data using pneumococcal conjugate vaccines as probes suggest that increased levels of both C-reactive protein and procalcitonin may be useful adjuncts to chest radiographs in the selection of patients with presumed bacterial pneumonia for inclusion in clinical trials. Among pneumococcal diagnostics currently under investigation, quantitative real-time polymerase chain reaction of respiratory secretions, as well as urinary antigen detection and pneumococcal surface adhesin A serological analysis for adults, are candidates for use in future clinical trials of antibiotics.

Gene expression analysis of host innate immune responses during Lethal H5N1 infection in ferrets

How viral and host factors contribute to the severe pathogenicity of the H5N1 subtype of avian influenza virus infection in humans is poorly understood. We identified three clusters of differentially expressed innate immune response genes in lungs from H5N1 (A/Vietnam/1203/04) influenza virus-infected ferrets by oligonucleotide microarray analysis. Interferon response genes were more strongly expressed in H5N1-infected ferret lungs than in lungs from ferrets infected with the less pathogenic H3N2 subtype. In particular, robust CXCL10 gene expression in H5N1-infected ferrets led us to test the pathogenic role of signaling via CXCL10's cognate receptor, CXCR3, during H5N1 influenza virus infection. Treatment of H5N1-infected ferrets with the drug AMG487, a CXCR3 antagonist, resulted in a reduction of symptom severity and delayed mortality compared to vehicle treatment. We contend that unregulated host interferon responses are at least partially responsible for the severity of H5N1 infection and provide evidence that attenuating the CXCR3 signaling pathway improves the clinical course of H5N1 infection in ferrets.