Klipp E., Herwig R., Kowald A., Wierling C., Lehrach H. Systems Biology in Practice: Concepts, Implementation and Application
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4.2.5
Transgenic Animals
Genetic material can be introduced into single-celled organisms (bacteria, yeast) by
transformation (see Section 4.1.2), and it is then automatically passed down to the
offspring during each cell division. To achieve the same outcome in a multicellular
organism is much more complicated.
The first method applied successfully to mammals was DNA microinjection (Gor-
don and Ruddle 1981). This technique is based upon the observation that in mam-
malian cells linear DNA fragments are rapidly assembled into tandem repeats which
are then integrated into the genomic DNA. This integration occurs at a single ran-
dom location within the genome. A linearized gene construct is therefore injected
into the pronucleus of a fertilized ovum. After introduction into foster mothers, em-
bryos containing the foreign DNA in some cells of the organism develop; this is
known as a chimera. If the construct is also present in germ line cells, some animals
of the daughter generation (F
1
generation) will carry the transgene in all of its body
cells and a transgenic animal has been created. The advantage of DNA microinjec-
tion is that it is applicable to a wide range of species. The disadvantage is that the
integration is a random process and thus the genomic neighborhood of the insert is
unpredictable. This often means that the expression of the recombinant DNA is sup-
pressed by silencers or by an unfavorable chromatin structure. If a mutant form of
an endogenous gene has been introduced, it has to be considered that, generally, the
wild type will also be present, which restricts this approach to the investigation of
dominant mutants.
This problem can be overcome by using the method of embryonic stem cell–
mediated transfer (Gossler et al. 1986). In rare cases (approximately 0.1%), the integra-
tion of a gene variant into the genome does not occur randomly, but actually replaces
the original gene via homologous recombination. This paves the way to modify or inac-
tivate any gene. In the latter case, this results in knockout animals. For this technique
the gene construct is introduced into embryonic stem cells (ES cells), which are omni-
potent and can give rise to any cell type. With the help of PCR or Southern blotting, the
few ES cells that undergo homologous recombination can be identified. Some of these
cells are then injected into an early embryo at the blastocyst stage, which leads to chi-
meric animals that are composed of wild-type cells and cells derived from the manipu-
lated ES cells. As in the case of DNA microinjection, an F
1
generation of animals has to
be bred to obtain genetically homogeneous animals. ES cell–mediated transfer works
particularly well in mice and is the method of choice to generate knockout mice,which
are invaluable in deciphering the function of unknown genes.
The random integration that accompanies DNA microinjection often has negative
effects on the expression of the transgene. To circumvent this obstacle, the method
of retrovirus-mediated gene transfer has been developed. In this case the recombi-
nant DNA is inserted into a vector that originates from a retrovirus before it is in-
jected. Retroviruses have developed methods to express their own genes regardless
of the location in the host genome, and this ability can be hijacked to increase the ex-
pression of the transgene of interest.
130
4 Experimental Techniques in a Nutshell
4.2.6
RNA Interference
We have seen that the generation of transgenic animals and the use of homologous
recombination to produce knockout animals is one way to elucidate the function of a
gene. However, this approach is time-consuming, technically demanding, and ex-
pensive. A new convenient method for transiently downregulating arbitrary genes
makes use of the phenomenon of RNA interference (RNAi). In 1998 it was discov-
ered that the injection of double-stranded RNA (dsRNA) into the nematode Caenor-
habditis elegans led to a sequence-specific downregulation of gene expression (Fire
et al. 1998). It turned out that this effect is part of a natural defense system of eukar-
yotes against viruses and selfish genetic elements that propagate via long, double-
stranded RNA intermediates.
The dsRNA is recognized by a cellular endoribonuclease of the RNase III family,
called DICER. This cuts the dsRNA into short pieces of 21–23 bp in length with a
2-bp, single-stranded overhang at the 3' end. These short fragments are called short
interfering RNAs (siRNAs). After phosphorylation they are assembled (as single
strands) into a riboprotein complex called RISC (RNA-induced silencing complex). If
RISC encounters an mRNA complementary to its siRNA, the mRNA is enzymati-
cally cut at a position that corresponds to the middle of the siRNA (Fig. 4.10). In
mammals, long dsRNA also induces the interferon response, which causes unspeci-
fic degradation of mRNA and a general shutdown of translation. This would severely
hamper the use of RNA interference as research tool, but, luckily, artificial siRNAs
can also be used to activate the RNA interference machinery (Dykxhoorn et al. 2003).
Artificial siRNAs are synthesized chemically and can in principle be targeted
against any mRNA. However, currently there are no clear design rules that would
yield the most effective siRNAs, and positional effects can lead to suppression levels
that vary between 10% and 70% (Holen et al. 2002). Because the transfection of
siRNA is only transient (it lasts only a few days in mammals), there might also be
problems in silencing genes that encode for long-lived proteins, but in general RNAi
is a very versatile technique.
If siRNAs are expressed from plasmids or viral vectors, their effects are more per-
sistent and they can be used as therapeutic agents by downregulating specific dis-
ease genes. Applications to HIV and other targets have been discussed (Dykxhoorn
et al. 2003; Stevenson 2003). They can also be used to study regulatory interactions
among proteins by targeting individual components and then measuring the effects
on global gene expression. By following this approach, is was possible to study the
structure of a signaling pathway involved in the immune response of Drosophila mel-
anogaster (Boutros et al. 2002). Finally, RNA interference would also be very useful
for the model building of metabolic or gene networks. After a network has been for-
mulated by a set of equations, it can be tested by silencing genes individually or in
combination and then measuring the resulting new expression levels. This type of
network perturbation can be used to iteratively improve agreement of the model pre-
dictions with the experimental data.
131
4.2 Advanced Techniques
132
4 Experimental Techniques in a Nutshell
Fig. 4.10 Mechanism of RNA interference
(RNAi). Double-stranded RNA (dsRNA) is
cleaved by the endoribonuclease DICER into
small fragments of 21–23 nucleotides, which are
subsequently phosphorylated at the 5' end. To
become functional, these small interfering RNAs
(siRNAs) form an RNA-induced silencing com-
plex (RISC) with cellular proteins. If the RISC
complex encounters an mRNA that is comple-
mentary to the siRNA, this mRNA is cleaved in
the middle of the complementary sequence,
leading to gene silencing (from Stevenson
2003). Exogenously added siRNAs are also func-
tional in triggering RNAi.
133
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Part II
Standard Models and Approaches in Systems Biology
5
Metabolism
Introduction
Living cells require energy and material for building membranes, storing molecules,
replenishing enzymes, replication and repair of DNA, movement, and many other
processes. Through metabolism cells acquire energy and use it to build new cells.
Metabolism is the means by which cells survive and reproduce. Metabolism is the
general term for two kinds of reactions: (1) catabolic reactions (breakdown of com-
plex compounds to get energy and building blocks) and (2) anabolic reactions (con-
struction of complex compounds used in cellular functioning). Metabolism is a
highly organized process. It involves thousands of reactions that are catalyzed by en-
zymes.
Metabolic networks consist of reactions transforming molecules of one type into
molecules of another type. In modeling terms, the concentrations of the molecules
and their rates of change are of special interest. The basic concepts of reaction net-
works, which are outlined here, may also be applied for other types of cellular reac-
tion networks, e.g., signal transduction pathways. In this chapter metabolism will be
studied on three levels of abstraction:
1. Enzyme kinetics investigates the dynamic properties of the individual reactions in
isolation.
2. The network character of metabolism is studied with stoichiometric analysis con-
sidering the balance of compound production and degradation.
3. Metabolic control analysis quantifies the effect of perturbations in the network
employing the individual dynamics of concentration changes and their integration
in the network.
Note that most modeling approaches for individual biochemical reactions or net-
works of such reactions that are presented in this chapter also apply for other types
of networks, such as signaling cascades or binding of transcription factors to DNA.
Since the modeling of metabolic networks is the most elaborate, it is subsumed
here.
In order to illustrate the theoretical concepts, we will apply a running example
throughout this chapter. This example comprises a subset of reactions of glycolysis
137
in yeast as represented by Hynne and colleagues (2001). You can also find the com-
plete model and many other models in modeling databases (Snoep and Olivier
2002).
Example 1
We will consider the first four reactions from the upper part of glycolysis as well as
reactions balancing the energy currency ATP and ADP as represented in Fig. 5.1.
The ODE system for this reaction system is given by
d
dt
Gluc6P v
1
v
2
v
3
d
dt
Fruc6P v
3
v
4
d
dt
Fruc1,6P
2
v
4
v
5
d
dt
ATP v
1
v
2
v
4
v
6
v
7
v
8
d
dt
ADP v
1
v
2
v
4
v
6
v
7
2 v
8
d
dt
AMP v
8
: (5-1)
Abbreviations are explained in the legend of Fig. 5.1. The individual rate expres-
sions read
138
5 Metabolism
Fig. 5.1 Schematic representation of the
upper part of glycolysis, i.e., the degradation
of glucose in order to yield energy and building
blocks for cellular processes. Abbreviations:
Gluc6P: glucose-6-phosphate; Fruc6P: fruc-
tose-6-phosphate; Fruc1,6P
2
: fructose-1,6-bi-
sphosphate; ATP: adenosine-triphosphate;
ADP: adenosine-diphosphate: AMP: adeno-
sine-monophosphate. Reactions: v
1
: hexoki-
nase; v
2
: consumption of glucose-6-phosphate
in other pathways; v
3
: phosphoglucoisome-
rase; v
4
: phosphofructokinase; v
5
: aldolase; v
6
:
ATP production in lower glycolysis; v7: ATP
consumption in other pathways; v
8
: adenylate
kinase.
v
1
V
max;1
ATP tGlucose
1
ATP t
K
ATP;1
Glucose
K
Glucose;1
ATP t
K
ATP;1
Glucose
K
Glucose;1
or v
1
V
max;1
ATP t
K
ATP;1
ATP t
(5-2)
v
2
k
2
ATP tGluc6Pt (5-3)
v
3
V
f
max;3
K
Gluc6P;3
Gluc6Pt
V
r
max;3
K
Fruc6P;3
Fruc6Pt
1
Gluc6Pt
K
Gluc6P;3
Fruc6Pt
K
Fruc6P;3
(5-4)
v
4
V
max;4
Fruc6Pt
2
K
Fruc6P;4
1 k
ATP t
AMP t
2
!
Fruc6Pt
2
(5-5)
v
5
k
5
Fruc1,6P
2
t (5-6)
v
6
k
6
ADP t (5-7)
v
7
k
7
ATP t
(5-8)
v
8
k
8f
ATP tAMP tk
8r
ADP t
2
; (5-9)
with the following parameters:
Glucose 12:8174mM; V
max;1
1398:00mM min
1
; K
ATP;1
0:10mM;
K
Glucose;1
0:37mM ; V
max;1
50:2747mM min
1
k
2
2:26mM
1
min
1
V
f
max;3
140:282mM min
1
; V
r
max;3
140:282mM min
1
; K
Gluc6P;3
0:80mM;
K
Fruc6P;3
0:15mM
V
max;4
44:7287mM min
1
; K
Fruc6P;4
0:021mM
2
; k 0:15
k
5
6:04662 min
1
k
6
68:48 min
1
k
7
3:21 min
1
k
8f
432:9mM
1
min
1
; k
8r
133:33mM
1
min
1
The temporal evolution of the concentrations starting from arbitrarily given va-
lues is shown in Fig. 5.2.
139
Introduction