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Identification of potential biomarkers of vaccine inflammation in mice.

ABSTRACT: Systems vaccinology approaches have been used successfully to define early signatures of the vaccine-induced immune response. However, the possibility that transcriptomics can also identify a correlate or surrogate for vaccine inflammation has not been fully explored. We have compared four licensed vaccines with known safety profiles, as well as three agonists of Toll-like receptors (TLRs) with known inflammatory potential, to elucidate the transcriptomic profile of an acceptable response to vaccination versus that of an inflammatory reaction. In mice, we looked at the transcriptomic changes in muscle at the injection site, the lymph node that drained the muscle, and the peripheral blood mononuclear cells (PBMCs)isolated from the circulating blood from 4 hr after injection and over the next week. A detailed examination and comparative analysis of these transcriptomes revealed a set of novel biomarkers that are reflective of inflammation after vaccination. These biomarkers are readily measurable in the peripheral blood, providing useful surrogates of inflammation, and provide a way to select candidates with acceptable safety profiles.

SUBMITTER: McKay PF

PROVIDER: S-EPMC6555592 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Identification of potential biomarkers of vaccine inflammation in mice.

McKay Paul F PF Cizmeci Deniz D Aldon Yoann Y Maertzdorf Jeroen J Weiner January J Kaufmann Stefan He SH Lewis David Jm DJ van den Berg Robert A RA Del Giudice Giuseppe G Shattock Robin J RJ

eLife 20190514

Systems vaccinology approaches have been used successfully to define early signatures of the vaccine-induced immune response. However, the possibility that transcriptomics can also identify a correlate or surrogate for vaccine inflammation has not been fully explored. We have compared four licensed vaccines with known safety profiles, as well as three agonists of Toll-like receptors (TLRs) with known inflammatory potential, to elucidate the transcriptomic profile of an acceptable response to vac ...[more]

PMID: 31084714

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Project description:Leishmania spp. is a protozoan parasite that affects millions of people around the world. At present, there is no effective vaccine to prevent leishmaniases in humans. A major limitation in vaccine development is the lack of precise understanding of the particular immunological mechanisms that allow parasite survival in the host. The parasite-host cell interaction induces dramatic changes in transcriptome patterns in both organisms, therefore, a detailed analysis of gene expression in infected tissues will contribute to the evaluation of drug and vaccine candidates, the identification of potential biomarkers, and the understanding of the immunological pathways that lead to protection or progression of disease. High-throughput real-time quantitative PCR is a highly sensitive, and specific technique that allows analysis of gene expression in multiple genes at the same time. Hence, it is an interesting approach that may bring light to this complex topic. In this large-scale analysis, forty-seven BALB/c mice were divided in two groups: control mice and mice infected with L. infantum promastigotes. After infection animals were sacrificed at different timepoints, RNA was purified from spleens and expression of 112 genes related with immune system was determined by high-throughput qPCR. These extensive gene-expression analyses reveal a selective recruitment of lymphocytes to the spleen and an immunosuppressive response, which favors parasite persistence, in early stages of the infection. In later stages of infection, gene-expression patterns suggest an inflammatory process that should resolve infection. Nevertheless, a detailed analysis reveals that L. infantum infection induces a regulatory process that counteracts the Th1/M1 response. This large pool of data was also used to identify a group of potential biomarkers of infection and parasitic burden in spleen, on the bases of two different statistical models, a logistic regression analysis and a linear regression analysis. Given the results, it seems clear that gene expression signature analysis is a useful tool to identify the mechanisms involved in disease outcome and to establish a rational approach for the identification of potential biomarkers useful for monitoring disease progression, new therapies or vaccine development in Leishmaniases.

Dataset Information

Identification of potential biomarkers of vaccine inflammation in mice.

Publications

Identification of potential biomarkers of vaccine inflammation in mice.

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