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as “systems biotechnology.” Thus, biotechnology processes can be
developed in a much more rational and systematic way by following
systems biotechnological strategies rather than traditionally used “trial
and error” type approaches.
In this chapter, high-throughput experimental techniques and in
silico modeling and simulation methods for strain development are
reviewed in the context of systems biotechnology. This is followed by
strategic procedures and relevant case studies addressing how wet
and dry experiments can be interactively combined to achieve the
improvement of microbial strains. Such an integrated strategy based
on systems-level quantitative analysis of cellular phenotypes in con-
junction with real experiments is the main focus of this chapter. Future
perspectives on systems biotechnology are also discussed to suggest
new opportunities and challenges in this field.
HIGH-THROUGHPUT X-OMIC EXPERIMENTS
Biology has evolved rapidly during the last decade, and so has biotech-
nology. This rapid development is being even more accelerated by
the advent of high-throughput experimental techniques, allowing the
generation of various biological data at unprecedentedly high rates.
These revolutionary techniques for the rapid acquisition of genome,
transcriptome, proteome, metabolome, and fluxome data are changing
the traditional paradigm of biological and biotechnological research
[21-23]. These technological advances naturally led to the birth of
“systems biology,” which aims to elucidate biological mechanisms
and phenomena in a quantitative manner at a holistic and genome-scale
level (figure 7.2). Applying this approach to biotechnological develop-
ment leads to “systems biotechnology,” which enables improvement of
organisms and bioprocesses employing them at systems level.
Before describing some successful stories on the use of high-
throughput x-omic experiments to design improved organisms, we
wish to insert a few words of caution. Transcriptome profiling, which
allows measurement of the levels of all transcripts in a cell, provides
a global view on gene expression under particular circumstances.
However, it should be noted that gene expression is a necessary but
not a sufficient condition for the corresponding protein production,
since there exist translational regulation, uncharacterized RNA and
protein stability, and sometimes posttranslational modification. This
is further complicated by the fact that protein abundance does not
necessarily correlate with the high activity of that protein due to
several factors such as varying substrate concentration, cofactor abun-
dance, and feedback inhibition. Therefore, even though proteome
profiling by two-dimensional gel electrophoresis (2DE) reveals a rela-
tive abundance of proteins, we still have limited information on the
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