Means to optimize protein expression in transgenic plants
Introduction
The potential of transgenic plants to act as alternatives to classical/standard expression systems for protein production has led to an increasing interest in this field of biotechnology. Several studies (reviewed in [1•]) have already highlighted that transgenic plants can produce low-cost biomass and yield high amounts of recombinant proteins. Moreover, they can modify pharmaceutically important proteins in a post-transcriptional manner and some of them can be grown like crops [2]. In 2012 the U.S. Food and Drug Administration (FDA) approved the first plant cell-expressed therapeutic drug in a transgenic carrot cell culture system. The yield of the biotechnologically relevant protein is dependent on the used host system, the transformation method, the targeted cellular compartment, the realized expression level in the host system and by the accumulation status of the protein [1•].
Adjustable parameters for gene engineering can be grouped into inside features (IF; mRNA and protein primary structure and features) and outside features (OF; host system, vector system, culture conditions). IFs and OFs are closely connected and impact each other. For most research projects individual parameter sets are evaluated and improved on a per case basis, therefore a bullet-proof correlation of gene features and their predicted impact on the amount of end-product is still lacking. In the same context it is still under debate exactly which impact the changes in codon usage can have on the final protein abundance. In some cases it apparently does not increase gene expression at all and in other cases up to 1000-fold [1•, 3•, 4, 5]. It is also debated how codon usage effects other features of the underlying transcript like for example RNA folding, that might result in changes of protein expression level [6].
As reviewed in [3•], maximizing heterologous protein expression is a multidimensional optimization problem. To benefit from plant-specific features, one needs to decode the complex nature of multiple factors influencing and controlling the outcome of eukaryotic expression systems. By using new technologies, knowledge gaps are being closed by monitoring the necessary parameters [5]. Recently a study [7] based on a hypothesis about selection constraints and codon bias [8] could link the IF codon bias and OFs like ribosomal dependent translation, tRNA abundance and host evolution in prokaryotes. The question remains whether these findings also apply for eukaryotic expression systems [9].
Next to the already mentioned IF codon bias a diverse set of IF and OF parameters can influence protein expression and should be considered for optimization as highlighted in Figure 1. In this review we give an overview about recent improvements which have been made in optimization, correlation and prediction of these IFs and OFs which altogether influence protein expression in transgenic plants. We will further clarify the importance of experimental design and highlight how new resources and design-rules can be adapted for genetic engineering.
Section snippets
Improving inside features (IFs)
In the process of developing gene engineering, codon bias is an intensively studied parameter influencing protein expression and hence impacts industrial production systems [10]. Next to a dependence on the OF tRNA abundance and the IF codon bias even altering synonymous sites on the mRNA level (maintaining the original protein sequence) can lead to tremendous effects on transcription level. This can be due to changed folding capacities of the mRNA or by introducing or removing miRNA target
Nucleotide frequencies of mRNA (codon usage and GC content)
One important step in introducing a transgene for protein production comprises altering the codon usage to match the host genome (either be the nuclear genome or the genome of the targeted semi-autonomous organelle). Codon usage data for some plants can be found in the ‘codon usage database’ (http://www.kazusa.or.jp/codon/ [12]). There are several metrics that can be applied to measure codon usage. In [13] a whole chapter deals with different classification categories, evaluates selected
Importance of untranslated regions (UTRs)
Recently our knowledge of sequences upstream of the translation start site and correlation of this upstream stretch with translation efficiency in plants was expanded. The 21 bp upstream region, highly conserved in plants, was shown to account for translational variation up to 200 fold in Arabidopsis thaliana, opening new possibilities for improving 5′ UTRs for gene engineering [24]. As reviewed in [25], plant viruses harbor so-called 3′ CAP-independent translational enhancers which can overcome
Improving outside features (OFs)
As recently reviewed [32••], modifying the host system can be the method of choice to overcome endogenous mechanisms like the unfolded protein response, which can influence recombinant protein production in plants. Host modification also helps to conquer other host specific limiting OFs such as altering glycosylation capabilities, reducing the production of proteases and increasing the content of chaperones. The unfolded protein response and its underlying mechanisms are conserved among
Expression cassette repertoire
Expressing a transgene in a host plant requires expression cassettes that produce high amounts of protein. Several systems are used in different host plants and an overview of plant hosts and expression cassettes is provided by [40•].
Different plant viral vector systems are used for transient expression of transgenes; see [41] for a summary of the currently used vector systems. A newer trend is using viral vector systems to also down-regulate host transcripts via virus induced gene silencing
Host features
Akin to mammalian expression systems, plant systems benefit from their ability to perform post-translational modifications. The introduced modifications, for example glycosylation patterns, can have severe effects on the structural and functional properties of the recombinant proteins [3•]. Several plant systems can now be used to produce human-like glycosylation patterns in biopharmaceuticals and may be a good alternative to mammalian expression hosts; however, only a few plant systems have
Culture conditions
The plant status, including time point during development and interaction with the environment, can feedback into the expression status, highlighting the importance of culture conditions as an OF. Individual culture condition factors in plant cell culture or conventional crop systems which directly or indirectly influence protein production are diverse and previous work has covered them comprehensively [69, 70]. A recent review summarizes the existing modeling approaches for plant cultures and
Conclusions
The host spectrum for genetic engineering expands and new species are introduced to offer advantages as compared to the existing expression systems. As an example, seaweed was recently introduced as a novel expression system [74], potentially unlocking vast underwater habitats. However, systematic analysis of new host systems are required for improving recombinant protein production and to cope with the needs of molecular farming in terms of for example eliminating non-human glycosylation
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgement
We thank Linley Jesson for critical reading of the manuscript.
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