Host Gene Expression of Macrophages in Response to Feline Coronavirus Infection

Feline coronavirus is a highly contagious virus potentially resulting in feline infectious peritonitis (FIP), while the pathogenesis of FIP remains not well understood, particularly in the events leading to the disease. A predominant theory is that the pathogenic FIPV arises from a mutation, so that it could replicate not only in enterocytes of the intestines but also in monocytes, subsequently systemically transporting the virus. The immune status and genetics of affected cats certainly play an important role in the pathogenesis. Considering the importance of genetics and host immune responses in viral infections, the goal of this study was to elucidate host gene expression in macrophages using RNA sequencing. Macrophages from healthy male cats infected with FIPV 79-1146 ex vivo displayed a differential host gene expression. Despite the virus uptake, aligned viral reads did not increase from 2 to 17 h. The overlap of host gene expression among macrophages from different cats was limited, even though viral transcripts were detected in the cells. Interestingly, some of the downregulated genes in all macrophages were involved in immune signaling, while some upregulated genes common for all cats were found to be inhibiting immune activation. Our results highlight individual host responses playing an important role, consistent with the fact that few cats develop feline infectious peritonitis despite a common presence of enteric FCoV.

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Robust classification of bacterial and viral infections via integrated host gene expression diagnostics

Science Translational Medicine ◽

10.1126/scitranslmed.aaf7165 ◽

2016 ◽

Vol 8 (346) ◽

pp. 346ra91-346ra91 ◽

Cited By ~ 128

Author(s):

Timothy E. Sweeney ◽

Hector R. Wong ◽

Purvesh Khatri

Keyword(s):

Gene Expression ◽

Viral Infections ◽

Host Gene ◽

Host Gene Expression ◽

Robust Classification

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Reanalysis And Integration Of Public Microarray Datasets Reveals Novel Host Genes Modulated In Leprosy

10.1101/824805 ◽

2019 ◽

Author(s):

Thyago Leal-Calvo ◽

Milton Ozório Moraes

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Host Gene ◽

Host Responses ◽

P Value ◽

Host Gene Expression ◽

Novel Genes ◽

Functional Studies ◽

Novel Host ◽

Microarray Datasets

AbstractBackgroundLeprosy is an insidious disease caused primarily by mycobacteria. The difficulties in culturing this slow-growing bacteria together with the chronic progression of the disease have hampered the development of accurate methods for diagnosis. Host gene expression profiling is an important tool to assess overall tissue activity, whether in health or disease conditions. High-throughput gene expression experiments have become popular over the last decade or so, and public databases have been created to easily store and retrieve these data. This has enabled researchers to reuse and reanalyze existing datasets with the aim of generating novel and or more robust information. In this work, after a systematic search, nine microarray datasets evaluating host gene expression in leprosy were reanalyzed and the information was integrated to strengthen evidence of differential expression for several genes.ResultsReanalysis of individual datasets revealed several differentially expressed genes (DEGs). Then, five integration methods were tested, both at the P-value and effect size level. In the end, random effects model (REM) and ratio association (sdef) were selected as the main methods to pinpoint DEGs. Overall, some classic gene/pathways were found corroborating previous findings and validating this approach for analysis. Also, various original DEGs related to poorly understood processes in leprosy were described. Nevertheless, some of the novel genes have already been associated with leprosy pathogenesis by genetic or functional studies, whilst others are, as yet, unrelated or poorly studied in these contexts.ConclusionsThis study reinforces evidences of differential expression of several genes and presents novel genes and pathways associated with leprosy pathogenesis. Altogether, these data are useful in better understanding host responses to the disease and, at the same time, provide a list of potential host biomarkers that could be useful in complementing leprosy diagnosis based on transcriptional levels.

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1218. Comparing the Diagnostic Accuracy of Clinician Judgement to a Novel Host Response Diagnostic for Acute Respiratory Illness

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1403 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S630-S630

Author(s):

Ian S Jaffe ◽

Anja K Jaehne ◽

Eugenia Quackenbush ◽

Micah T McClain ◽

Geoffrey S Ginsburg ◽

...

Keyword(s):

Gene Expression ◽

Diagnostic Accuracy ◽

Bacterial Infections ◽

Viral Infections ◽

Treatment Plan ◽

Respiratory Illness ◽

Host Gene ◽

Host Gene Expression ◽

Net Benefit ◽

Material Support

Abstract Background Discriminating bacterial and viral infections remains clinically challenging. The resulting antibacterial misuse contributes to antimicrobial resistance. Host gene expression-based tests are a promising strategy to discriminate of bacterial and viral infections, but their potential clinical utility has not yet been evaluated. Methods A host gene expression biosignature was measured using either qRT-PCR or microarray in 683 ED subjects with suspected infection. Based on chart reviews, we recorded clinical diagnosis as defined both by the provider assessment and by the provider treatment plan. The biosignature, diagnosis, treatment plan, and procalcitonin were compared to clinical adjudication as the reference standard. With this as a baseline, we then calculated average weighted accuracy (AWA) and change in overall net benefit (∆NB), weighting bacterial false negatives four times more seriously than false positives. Results Gene expression correctly classified the three possible disease etiologies (bacterial, viral, or non-infectious) 76.1% of the time, outperforming provider diagnosis, provider treatment, and procalcitonin (Table 1). Overall accuracy was higher in subjects with bacterial infections (n=278, 83.8% accurate) compared to those with viral (n=234, 76.5%) and non-infectious (n=171, 63.2%) etiologies. Due to a strong sensitivity bias to treat bacterial infections at the expense of diagnostic accuracy and specificity, the provider diagnosis was overall more accurate than the corresponding treatment plan (71.4% accuracy vs. 68.1%), resulting in inappropriate antibiotic use in 41.0% of cases where antibiotics were prescribed. The gene expression test had significantly higher AWA for the diagnosis of bacterial infection than both procalcitonin and provider treatment (82.4% vs. 70.3% and 74.4%, respectively; p < 0.0001). Consequently, the host gene expression test had greater net benefit than provider treatment (∆NBbact = 9.9%), provider diagnosis (∆NBbact = 4.4%), and procalcitonin (∆NBbact = 27.1%). Table 1: Summary of provider, procalcitonin, and host gene expression test performance in a cohort of 683 subjects. Conclusion Host gene expression-based tests to distinguish bacterial and viral infection can facilitate more appropriate treatment, leading to improved patient outcomes and mitigating the antibiotic resistance crisis. Disclosures Geoffrey S. Ginsburg, MD PhD, Predigen, Inc (Shareholder, Other Financial or Material Support) Ephraim L. Tsalik, MD, MHS, PhD, Predigen (Shareholder, Other Financial or Material Support, Founder)

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Suppression of Proinflammatory Signal Transduction and Gene Expression by the DualNucleic Acid Binding Domains of the Vaccinia Virus E3L Proteins

Journal of Virology ◽

10.1128/jvi.00607-06 ◽

2006 ◽

Vol 80 (20) ◽

pp. 10083-10095 ◽

Cited By ~ 54

Author(s):

Jeffrey O. Langland ◽

John C. Kash ◽

Victoria Carter ◽

Matthew J. Thomas ◽

Michael G. Katze ◽

...

Keyword(s):

Gene Expression ◽

Signal Transduction ◽

Vaccinia Virus ◽

Cellular Response ◽

Viral Infections ◽

Host Gene ◽

Host Gene Expression ◽

Danger Signals ◽

Binding Domains ◽

Z Dna

ABSTRACT Cells have evolved elaborate mechanisms to counteract the onslaught of viral infections. To activate these defenses, the viral threat must be recognized. Danger signals, or pathogen-associated molecular patterns, that are induced by pathogens include double-stranded RNA (dsRNA), viral single-stranded RNA, glycolipids, and CpG DNA. Understanding the signal transduction pathways activated and host gene expression induced by these danger signals is vital to understanding virus-host interactions. The vaccinia virus E3L protein is involved in blocking the host antiviral response and increasing pathogenesis, functions that map to separate C-terminal dsRNA- and N-terminal Z-DNA-binding domains. Viruses containing mutations in these domains allow modeling of the role of dsRNA and Z-form nucleic acid in the host response to virus infection. Deletions in the Z-DNA- or dsRNA-binding domains led to activation of signal transduction cascades and up-regulation of host gene expression, with many genes involved in the inflammatory response. These data suggest that poxviruses actively inhibit cellular recognition of viral danger signals and the subsequent cellular response to the viral threat.

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2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness

Open Forum Infectious Diseases ◽

10.1093/ofid/ofy210.1674 ◽

2018 ◽

Vol 5 (suppl_1) ◽

pp. S588-S588

Author(s):

L Gayani Tillekeratne ◽

Sunil Suchindran ◽

Emily Ko ◽

Elizabeth Petzold ◽

Champica K Bodinayake ◽

...

Keyword(s):

Gene Expression ◽

Viral Infections ◽

Respiratory Illness ◽

Host Gene ◽

Sri Lankan ◽

Host Gene Expression ◽

Febrile Respiratory Illness

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From Gene to Protein—How Bacterial Virulence Factors Manipulate Host Gene Expression During Infection

International Journal of Molecular Sciences ◽

10.3390/ijms21103730 ◽

2020 ◽

Vol 21 (10) ◽

pp. 3730 ◽

Cited By ~ 1

Author(s):

Lea Denzer ◽

Horst Schroten ◽

Christian Schwerk

Keyword(s):

Gene Expression ◽

Host Cell ◽

Host Gene ◽

Host Cells ◽

Host Gene Expression ◽

Protein Activation ◽

Virulence Proteins ◽

Mrna Stabilization ◽

Host Immune Responses ◽

Bacterial Effectors

Bacteria evolved many strategies to survive and persist within host cells. Secretion of bacterial effectors enables bacteria not only to enter the host cell but also to manipulate host gene expression to circumvent clearance by the host immune response. Some effectors were also shown to evade the nucleus to manipulate epigenetic processes as well as transcription and mRNA procession and are therefore classified as nucleomodulins. Others were shown to interfere downstream with gene expression at the level of mRNA stability, favoring either mRNA stabilization or mRNA degradation, translation or protein stability, including mechanisms of protein activation and degradation. Finally, manipulation of innate immune signaling and nutrient supply creates a replicative niche that enables bacterial intracellular persistence and survival. In this review, we want to highlight the divergent strategies applied by intracellular bacteria to evade host immune responses through subversion of host gene expression via bacterial effectors. Since these virulence proteins mimic host cell enzymes or own novel enzymatic functions, characterizing their properties could help to understand the complex interactions between host and pathogen during infections. Additionally, these insights could propose potential targets for medical therapy.

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