Vaccine and antibody production in plants : developments and computational tools
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Plants as bioreactors have been widely used to express efficient vaccine antigens against viral, bacterial and protozoan infections. To date, many different plant-based expression systems have been analyzed, with a growing preference for transient expression systems. Antibody expression in diverse plant species for therapeutic applications is well known, and this review provides an overview of various aspects of plant-based biopharmaceutical production. Here, we highlight conventional and gene expression technologies in plants along with some illustrative examples. In addition, the portfolio of products that are being produced and how they relate to the success of this field are discussed. Stable and transient gene expression in plants, agrofiltration and virus infection vectors are also reviewed. Further, the present report draws attention to antibody epitope prediction using computational tools, one of the crucial steps of vaccine design. Finally, regulatory issues, biosafety and public perception of this technology are also discussed.
Dubey , K K , Luke , G A , Knox , C , Kumar , P , Pletschke , B I , Singh , P K & Shukla , P 2018 , ' Vaccine and antibody production in plants : developments and computational tools ' Briefings in Functional Genomics , vol. 17 , no. 5 , pp. 295-307 . https://doi.org/10.1093/bfgp/ely020
Briefings in Functional Genomics
© 2018, Publisher / the Author(s). This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at www.XXXX.xxx / https://doi.org/xxxx
DescriptionK.K.D. and P.S. sincerely acknowledge the support and facility provided by the M.D. University, Rohtak, Haryana. P.S. acknowledges the infrastructural support from Department of Science and Technology, Govt. of India through FIST grant (Grant No. 1196 SR/FST/LS-I/2017/4).
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