Synthetic Biology | Definition and delimitation
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2.2.1
Systems biology
Systems biology is a discipline that models processes (e.g. regulatory networks), and iteratively tests and
improves these models (Ehrhardt and Frommer 2012). It emerged from molecular biology, when the progress
in automated DNA sequencing and improved computational tools allowed scientists to combine
experimentation and computation to reverse-engineer cellular networks (Cameron et al. 2014). It is an
“interdisciplinary approach that attempts to develop and test holistic models of living systems.” Systems
biology lays the basis for engineering organisms,
i.e. synthetic biology, and includes, inter alia, novel
approaches like nanoreactors, attempts to redesign networks and pathways, and includes the synthesis of
complete chromosomes (Ehrhardt and Frommer 2012). It is based on either a “top-down” systems approach
that “uses quantitative modelling to identify and describe the underlying biosynthetic and regulatory networks
of a system” or a “bottom-up” approach that “attempts to model the systems-wide phenotypes that emerge
from component interactions”.
2.2.2
Metabolic engineering
Metabolic engineering may be defined as the optimisation of genomic and regulatory processes within cells
and tissues with the aim of increased production of desired substances and/or the reduction of unwanted
substances; it can lead to more energy efficient biochemical processes and reduce large-scale production costs
(Ellis and Goodacre 2012).
It is about the design, engineering and optimisation of pathways for the production of a variety of products,
including fuels, materials and chemicals (Stephanopoulos 2012). As maximising the production of a desired
metabolite generally involves quantitative evaluation and adjustment of cellular metabolism (Boyle and Silver
2012), synthetic biology approaches may contribute tremendously to the possible outcomes. Concomitantly,
however, it is difficult to draw clear borders between the two disciplines.
Like synthetic biology, metabolic engineering focusses on the improvement and/or design of cells, following
different strategies like the enhancement of substrate range, production of novel products, increased yield
and productivity, and augmentation of cellular robustness (Nielsen and Keasling 2011). In most cases, the
design and construction of platform cell factories requires both synthetic biology and metabolic engineering;
due to advancements in systems biology it is expected that continuously more efficient cell factories will be
developed.
The design of organisms to produce important metabolites is frequently mentioned as one of the main
applications of synthetic biology (Boyle and Silver 2009). Although the reconfiguration of metabolism is a
challenge due to the complex regulation of the metabolome, synthetic biology advanced in the context of
metabolic pathway optimisation and metabolic engineering (Stephanopoulos 2012). The basic elements of
metabolic engineering within the context of synthetic biology are pathway design, construction, and
optimisation. However, while it may be relatively easy to build a pathway, its improvement to support a
commercial process can be a tedious process.
The major prerequisite to successfully engineer cellular metabolism is to understand metabolic reactions and
regulatory elements that affect metabolic throughput (Boyle and Silver 2012). Two stages may be identified: a
proof of concept stage – novel enzyme combinations to produce a desired product – and an
optimisation stage
– regulatory adjustments to improve product yields. The necessary elements include approaches for
transcriptional and translational pathway control, spatial pathway control (through for example scaffolds,
subcellular compartmentalisation, and synthetic (microbial) consortia), and modelling and measuring the
metabolic network. The emerging engineering design cycle includes both in silico modelling and prediction as
well as directed evolution and screening. Metabolomics (including metabolic profiling,
metabolite flux analysis,
Synthetic Biology | Definition and delimitation
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metabolic fingerprinting, and metabolic footprinting) contributes to the understanding of metabolic networks,
which will greatly assist synthetic biology (Ellis and Goodacre 2012).
Porcar and Pereto (2012) suggested that implementing a complex pathway into a heterologous host that in
addition is constantly adjusted and optimised (the “sophistication of a genetic modification”) renders an
approach “synthetic biology”.
Systems metabolic engineering has developed from metabolic engineering (Yadav et al. 2012). Instead of
deleting or over-expressing endogenous genes and introducing heterologous genes, gene expression and
regulatory networks are manipulated throughout the cell. Thus, metabolic engineering by now involves
knowledge far beyond the control of pathway gene expression (Stephanopoulos 2012).
It furthermore includes
approaches beyond genetic engineering and molecular biology by making use of synthetic genetic constructs
like networks or circuits.
While contemporary metabolic engineering focuses on altering existing pathways, future engineering will
design metabolisms and minimal organisms
de novo (Bilgin and Wagner 2012). Metabolic engineering
applications are expected to increase dramatically, also fostered by market forces, concern about
sustainability and the associated increasing interest in the production of products from renewable resources
(Stephanopoulos 2012). Arpino et al. (2013) and Yadav et al. (2012) conclude that “instead of
becoming a state
of the art discipline, metabolic engineering has remained a collection of elegant demonstrations” – not
surprisingly, synthetic biology has the potential to aid future developments in this field significantly. Synthetic
biology opens the possibility to synthesise and control non-natural pathways, whereas metabolic engineering
provides the basic methods to design analyse and optimise them.
2.2.3
Synthetic metabolic pathways
A driving force for advances in synthetic biology is the idea to streamline pathways in industrial biotechnology,
for improved production of biopharmaceuticals, fine chemicals or biofuels and biodegradation of wastes.
Research endeavours applying the principles of synthetic biology to the improvement of metabolic pathways
are summarised under the keyword of “metabolic engineering” (Comba et al. 2012).
Biotechnology,
i.e. synthesis or energy conversion in living microbial cells is
centuries old, and the employment
of genetically engineered strains has become a routine since decades. Therefore it is difficult to distinguish
between classical genetic engineering and synthetic biology in this context.
Current scientific reviews on metabolic engineering typically refer to pathway modularisation, multiplex-
automated genome modification, metabolic flux analysis and dynamic control using regulatory devices. These
approaches have mostly been exemplified in the construction of heterologous terpenoid biosynthesis
pathways. Terpenoid biosynthesis is of particular interest, since potent plant-pharmaceuticals, such as the
anti-malaria agent artemisinin and the anti-tumour component taxol are derived from terpenoid moieties.
Terpenoids are also building blocks for carotenoid pigments which are suitable for colorimetric high
throughput analysis of experimental success. In metabolic engineering, terpenoid biosynthesis genes from
bacteria, yeasts and various plants are combined for optimised cost-effective production in
Escherichia coli
(Yadav et al. 2012; Xu et al. 2012; Comba et al. 2012). However, the same principles may be applied to any
biotechnological pathway. The project list of the iGEM competition website may provide an idea of the
application potential of metabolic engineering (
http://2013.igem.org/Jamboree/Team_Abstracts
). Genome-
scale metabolic engineering may be attempted by
in vivo editing or
de novo synthesis (Esvelt and Wang 2013).