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A vector-host system to fingerprint virus tropism.

ABSTRACT: Reporter genes are important tools for assessing vector pharmacology in vivo. Although useful, current systems are limited by (1) the need to generate a new vector for each different reporter, (2) the inability to package reporter genes in small vectors, and (3) variations in reporter gene feedback due to variations in cell-to-cell vector copy number. To circumvent these problems, we have used Cre recombinase as a "cat's paw" to activate reporter genes embedded in transgenic mice. The small Cre gene was introduced into self-complementary adeno-associated viral (scAAV) vectors with limited packaging capacity. Injection of scAAV-Cre vectors into mice with loxP-inactivated luciferase enabled in vivo imaging distributions comparable to the signal observed after AAV-luciferase injection. When injected into mT/mG mice, AAV-Cre converted ubiquitous expression of red fluorescent protein (RFP) to green fluorescent protein (GFP) expression only where the vectors transduced cells. Injection into F(1) hybrid luciferase and mT/mG mice enabled simultaneous three-reporter tracking. This system was able to discriminate cell-specific transduction in all organs tested, with particular usefulness for detecting AAV serotype-specific transduction in the liver, kidney, and muscle. Given that F(1) mice bear exactly one copy of luciferase and one copy of RFP-GFP, each reporter gene is either "on" or "off" in a cell. The Cre system therefore provides a unique quantum method to quantify vector delivery that can be applied when vector capacity is limited.

SUBMITTER: Hillestad ML

PROVIDER: S-EPMC3472556 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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A vector-host system to fingerprint virus tropism.

Hillestad Matthew L ML Guenzel Adam J AJ Nath Karl A KA Barry Michael A MA

Human gene therapy 20121001 10

Reporter genes are important tools for assessing vector pharmacology in vivo. Although useful, current systems are limited by (1) the need to generate a new vector for each different reporter, (2) the inability to package reporter genes in small vectors, and (3) variations in reporter gene feedback due to variations in cell-to-cell vector copy number. To circumvent these problems, we have used Cre recombinase as a "cat's paw" to activate reporter genes embedded in transgenic mice. The small Cre ...[more]

PMID: 22834781

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Project description:BackgroundMajority of influenza A viruses reside and circulate among animal populations, seldom infecting humans due to host range restriction. Yet when some avian strains do acquire the ability to overcome species barrier, they might become adapted to humans, replicating efficiently and causing diseases, leading to potential pandemic. With the huge influenza A virus reservoir in wild birds, it is a cause for concern when a new influenza strain emerges with the ability to cross host species barrier, as shown in light of the recent H7N9 outbreak in China. Several influenza proteins have been shown to be major determinants in host tropism. Further understanding and determining host tropism would be important in identifying zoonotic influenza virus strains capable of crossing species barrier and infecting humans.ResultsIn this study, computational models for 11 influenza proteins have been constructed using the machine learning algorithm random forest for prediction of host tropism. The prediction models were trained on influenza protein sequences isolated from both avian and human samples, which were transformed into amino acid physicochemical properties feature vectors. The results were highly accurate prediction models (ACC>96.57; AUC>0.980; MCC>0.916) capable of determining host tropism of individual influenza proteins. In addition, features from all 11 proteins were used to construct a combined model to predict host tropism of influenza virus strains. This would help assess a novel influenza strain's host range capability.ConclusionsFrom the prediction models constructed, all achieved high prediction performance, indicating clear distinctions in both avian and human proteins. When used together as a host tropism prediction system, zoonotic strains could potentially be identified based on different protein prediction results. Understanding and predicting host tropism of influenza proteins lay an important foundation for future work in constructing computation models capable of directly predicting interspecies transmission of influenza viruses. The models are available for prediction at http://fluleap.bic.nus.edu.sg.

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A vector-host system to fingerprint virus tropism.

Publications

A vector-host system to fingerprint virus tropism.

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