Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Sep 7:12:738388.
doi: 10.3389/fimmu.2021.738388. eCollection 2021.

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms

Lorena Leonardelli  1 , Giuseppe Lofano  2 , Gianluca Selvaggio  1 , Silvia Parolo  1 , Stefano Giampiccolo  1 , Danilo Tomasoni  1 , Enrico Domenici  1   3 , Corrado Priami  1   4 , Haifeng Song  2 , Duccio Medini  5 , Luca Marchetti  1   3 , Emilio Siena  6
Affiliations
Review

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms

Lorena Leonardelli et al. Front Immunol. .

Abstract

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid the literature, making it difficult to formulate new hypotheses to be tested in clinical settings and ultimately improve this technology platform. Here, we propose a systems biology approach, based on the combination of literature mining and mechanistic graphical modeling, to consolidate existing knowledge around mRNA vaccines mode of action and enhance the translatability of preclinical hypotheses into clinical evidence. A Natural Language Processing (NLP) pipeline for automated knowledge extraction retrieved key biological evidences that were joined into an interactive mechanistic graphical model representing the chain of immune events induced by mRNA vaccines administration. The achieved mechanistic graphical model will help the design of future experiments, foster the generation of new hypotheses and set the basis for the development of mathematical models capable of simulating and predicting the immune response to mRNA vaccines.

Keywords: graphical modeling; mRNA vaccines; mechanisms of action; natural language processing; scientific literature mining.

PubMed Disclaimer

Conflict of interest statement

GL, HS, DM, and ES were all employees of the GSK group of companies at the time of the study. The “Fondazione The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI)” institute received financial remuneration for conducting the activates described in this study. The authors declare that this study received funding from GlaxoSmithKline Biologicals SA. The funder had the following involvement in the study: study design, interpretation of data, the writing of this article and the decision to submit it for publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
In silico modeling of the immune system. Integrative systems biology approach to properly describe, explain, and predict the behavior of any biological mechanism, which in our specific case study is the immune response to mRNA-based vaccines.
Figure 2
Figure 2
Mechanistic graphical model of the mRNA-based vaccine biological mechanism of action. Lipid nanoparticles encapsulating mRNA molecules are intradermal or intramuscular injected triggering immune signals that reach the draining lymph node, where other immune reactions generate the specific antibodies, eventually transferred into the circulatory system. This figure is proposed in a dynamic view at the link https://www.cosbi.eu/fx/9839203, where each connection (blue arrows) is documented by literature references as well as the involved cells measured in mouse and NHP experiments.
See this image and copyright information in PMC

References

    1. Thess A, Grund S, Mui BL, Hope MJ, Baumhof P, Fotin-Mleczek M, et al. . Sequence-Engineered mRNA Without Chemical Nucleoside Modifications Enables an Effective Protein Therapy in Large Animals. Mol Ther (2015) 23:1456–64. 10.1038/mt.2015.103 - DOI - PMC - PubMed
    1. Karikó K, Muramatsu H, Welsh FA, Ludwig J, Kato H, Akira S, et al. . Incorporation of Pseudouridine Into mRNA Yields Superior Nonimmunogenic Vector With Increased Translational Capacity and Biological Stability. Mol Ther (2008) 16:1833–40. 10.1038/mt.2008.200 - DOI - PMC - PubMed
    1. Kauffman KJ, Webber MJ, Anderson DG. Materials for non-Viral Intracellular Delivery of Messenger RNA Therapeutics. J Control Release (2016) 240:227–34. 10.1016/j.jconrel.2015.12.032 - DOI - PubMed
    1. Pardi N, Hogan MJ, Naradikian MS, Parkhouse K, Cain DW, Jones L, et al. . Nucleoside-Modified mRNA Vaccines Induce Potent T Follicular Helper and Germinal Center B Cell Responses. J Exp Med (2018) 215:1571–88. 10.1084/jem.20171450 - DOI - PMC - PubMed
    1. Guan S, Rosenecker J. Nanotechnologies in Delivery of mRNA Therapeutics Using Nonviral Vector-Based Delivery Systems. Gene Ther (2017) 24:133–43. 10.1038/gt.2017.5 - DOI - PubMed

Publication types

LinkOut - more resources