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Multifactorial Analysis of Terminator Performance on Heterologous Gene Expression in Physcomitrella

Overview
Journal Plant Cell Rep
Publisher Springer
Date 2024 Jan 21
PMID 38246952
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Abstract

Characterization of Physcomitrella 3'UTRs across different promoters yields endogenous single and double terminators for usage in molecular pharming. The production of recombinant proteins for health applications accounts for a large share of the biopharmaceutical market. While many drugs are produced in microbial and mammalian systems, plants gain more attention as expression hosts to produce eukaryotic proteins. In particular, the good manufacturing practice (GMP)-compliant moss Physcomitrella (Physcomitrium patens) has outstanding features, such as excellent genetic amenability, reproducible bioreactor cultivation, and humanized protein glycosylation patterns. In this study, we selected and characterized novel terminators for their effects on heterologous gene expression. The Physcomitrella genome contains 53,346 unique 3'UTRs (untranslated regions) of which 7964 transcripts contain at least one intron. Over 91% of 3'UTRs exhibit more than one polyadenylation site, indicating the prevalence of alternative polyadenylation in Physcomitrella. Out of all 3'UTRs, 14 terminator candidates were selected and characterized via transient Dual-Luciferase assays, yielding a collection of endogenous terminators performing equally high as established heterologous terminators CaMV35S, AtHSP90, and NOS. High performing candidates were selected for testing as double terminators which impact reporter levels, dependent on terminator identity and positioning. Testing of 3'UTRs among the different promoters NOS, CaMV35S, and PpActin5 showed an increase of more than 1000-fold between promoters PpActin5 and NOS, whereas terminators increased reporter levels by less than tenfold, demonstrating the stronger effect promoters play as compared to terminators. Among selected terminator attributes, the number of polyadenylation sites as well as polyadenylation signals were found to influence terminator performance the most. Our results improve the biotechnology platform Physcomitrella and further our understanding of how terminators influence gene expression in plants in general.

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