Synthetic Biology | Applications of Synthetic Biology
52
control of flowering time, or the hacking of the circadian clock. This may be achieved, for instance, by
designing a synthetic plant signal transduction pathway, which is the starting point to assemble fully synthetic
signalling networks.
Synthetic approaches aiming at engineering C4 photosynthesis (as found in for example maize and sorghum)
into the more diffused C3 background have been suggested by Denton et al. (2013). The obvious advantage of
C4 plants as compared to C3 is higher productivity at elevated temperatures, and higher nitrogen and water
use efficiencies (
i.e. more biomass with less input). Systems and synthetic approaches are used to understand
the trait, aided by the completion of several genome sequences of C4 grasses.
McFadden (2012) describes synthetic biology as “our best hope for a healthy future” – bringing up hopes to
create plants that are able to perform photosynthesis more efficiently by harvesting light from wider regions
of the spectrum or capture nitrogen directly from the air so they will not need nitrogen fertiliser. In addition,
the design of new microbes that digest and degrade toxic pollutants or turn agricultural waste into electricity
are mentioned as applications that will tackle food security and at the same time reduce the negative
environmental impacts of agriculture (McFadden 2012).
Synthetic Biology | Risk assessment and risk management
53
5
Risk assessment and risk management
5.1
Current risk assessment approaches
The current approach for the risk assessment of GM plants in the European Union is set out by different EU
regulations and EFSA guidance documents and dealing with the marketing of food and feed, the use for non-
food and non-feed purposes, and the deliberate release into the environment (EFSA 2011, 2010a, 2009; EC
2001, 2003, 2013). The risk assessment is characterised by the four different steps: hazard identification,
hazard characterisation, exposure assessment and risk characterisation.
In addition, the following elements are part of the current risk assessment procedure:
i)
Risk assessment of GM plants and derived food and feed (EFSA 2011):
-
Characteristics of the donor organisms
and recipient plant
-
Genetic modification and its functional consequences
-
Agronomic and phenotypic characteristics of the GM plant
-
Compositional characteristics of GM plants and derived food and feed
-
Potential toxicity and allergenicity of gene products (proteins, metabolites) and the whole GM plant
and its derived products
-
Dietary intake and potential
for nutritional impact
-
Influence of processing and storage on the characteristics of the derived products
ii)
Environmental risk assessment of GM plants (EFSA 2010a):
-
Persistence and invasiveness including plant-to-plant gene flow
-
Plant to micro-organisms gene transfer
-
Interactions of the GM plant with target organisms
-
Interactions of the GM plant with non-target organisms
-
Impacts of the specific cultivation, management
and harvesting techniques
-
Effects on biogeochemical processes
-
Effects on human and animal health
-
Post-market environmental monitoring
The risk assessment of GM plants not intended for food or feed uses contains similar elements to those
abovementioned (EFSA 2009): molecular characterisation, safety for humans and animals (e.g. compositional
characterisation, toxicology), safety for the environment, monitoring.
With all three EFSA guidance documents, the comparative approach is considered a crucial part of the risk
assessment. Besides the molecular characterisation, it forms the basis for the evaluation of the intended
alterations of
the plant phenotype and, in particular, for the detection of any unintended effect:
"
Unintended effects may be detected through the comparison of the agronomic, phenotypic and
compositional characteristics" (EFSA 2011),
"
The comparative safety assessment is being followed in order to identify differences caused by either
intended or unintended effects" (EFSA 2010a),
"
Compositional analyses have to be carried out […] to identify and quantify possible unintended changes in
the composition of the whole GM plant” (EFSA 2009)
Comparative approaches were introduced as key element of the GMO risk assessment (OECD 1993). They
intend to provide significant information on the substantial equivalence between GM plants and comparators,
which – in case of sexually propagating crops – are defined to be non-GM genotypes with genetic backgrounds
as close as possible to the GM plant (EFSA 2011). The EFSA guidance for GM plants used for non-food and non-
Synthetic Biology | Risk assessment and risk management
54
feed purposes gives detailed comments on "substantially modified" transgenic plants. It is said that
substantially modified transgenic plants cannot be statistically compared with conventional plants making the
risk assessment much more laborious and complex. The reason is that extensive genetic modifications (e.g. the
insertion of multiple genes) can lead to substantial changes in the original metabolism and composition of the
GM plant (EFSA 2009).
For GM plants used for non-food and non-feed purposes, the EFSA GMO Panel still considers that the vast
majority of the basic biology of the GM plant and the non-GM comparator will remain the same. Therefore a
certain level of comparison with a non-GM comparator will always be appropriate.
5.2
Applicability of current approaches on plants created by synthetic
genomics
Per definition, metabolism and also physiology of a synthetic organism will be largely different to any
conventional plant. In addition, plants produced by synthetic genomics are different as regards composition,
and any process of synthetic engineering of a plant can result in unknown physiological and biological
processes. For this reason the application of the concept of substantial equivalence is not possible and not
feasible.
The risk assessment and evaluation of synthetic plants has to be done in a case specific manner and with
respect to potential impact on human and animal health and the environment addressing:
the level of differences with respect to the main biological characteristics of conventionally bred crops in
general,
the technology and concept behind the design of the synthetic plant,
the biogenetic principles and the construction process of the synthetic material and the underlying
biological functions and characteristics of the synthetic organism at the genome and metabolic level,
the intended function and behaviour of a synthetic plant,
the design of field trials required to account for situations where the receiving environment of the
synthetic plant is substantially different to the appropriate comparator,
the different environments that are associated with the intended function and the intended use of the
synthetic plant,
specific biological and genomic properties, e.g. expression of artificial proteins,
newly introduced
regulatory mechanisms,
the selection of the endpoints that need to be tested, possibly based on the new variety studies for crop
plants (DUS), that could provide the basis for establishing a minimum requirement for plants created by
synthetic genomic (UPOV 2011),
the variation in the endpoints tested depending on the biology of the
synthetic organism,
the assessment of the comparative data in relation to the outcome of the molecular characterisation,
the verification of any unanticipated effect by additional experimental data (e.g. field testing, food
safety
studies),
the problem that the products of synthetic plants (e.g. a different nucleic acid) released into the
environment could be highly hazardous, and
the necessity of extensive laboratory testing prior to any release experiment.
It is noteworthy that synthetic genes and, in general, new life forms have no evolutionary history and cannot
be traced back to wild ancestors (Norton 2010). A comparative approach usually will not be applicable due to
the missing evolutionary history and relationship of a synthetic higher plant (a non-existing biological system)
and a conventional crop plant. A comprehensive toxicological and allergological risk assessment can provide
the missing data. Internationally accepted approaches applied for testing chemicals in foods (Renwick et al.
2003; EFSA 2011) form the basis for the testing and quantification of adverse effects caused by artificial