Negative Autoregulation Speeds the Response Times
of Transcription Networks
Nitzan Rosenfeld1
, Michael B. Elowitz2
and Uri Alon1
*
1
Department of Molecular Cell
Biology, Department of Physics
of Complex Systems
Weizmann Institute of Science
Rehovot 76100, Israel
2
Rockefeller University, 1230
York Avenue, New York, NY
10021, USA
Cells regulate gene expression using networks of transcription interactions;
it is of interest to discover the principles that govern the dynamical
behavior of such networks. An important characteristic of these systems is
the rise-time: the delay from the initiation of production until half maximal
product concentration is reached. Here we employ synthetic gene circuits in
Escherichia coli to measure the rise-times of non-self-regulated and of negatively
autoregulated transcription units. Non-self-regulated units have a
rise-time of one cell-cycle. We demonstrate experimentally that negative
autoregulation feedback (also termed autogenous control) reduces the risetime
to about one fifth of a cell-cycle. This agrees with an analytical solution
of a mathematical model for negative autoregulation. This may help in
understanding the function of negative autoregulation, which appears in
over 40% of known transcription factors in E. coli.
q 2002 Elsevier Science Ltd. All rights reserved
Keywords: autogenous control; biophysics; design principles; feedback
kinetics; systems-biology*Corresponding author
Introduction
A major current challenge is to understand the
design principles of gene regulation networks. It is
therefore of interest to study the properties of regulatory
structures, or “motifs”, that occur frequently
in the networks. Understanding the function of a
recurring motif is likely to shed light on the design
of numerous systems in which it appears. One
such common motif is negative autoregulation, in
which transcription factors negatively regulate
their own transcription.1
This occurs, for example,
in over 40% of known Escherichia coli transcription
factors (Table 1).2,3
Examples of transcription
factors that negatively regulate their own transcription
include Crp, a global transcription factor that
mediates the catabolite response of several hundred
genes, LexA, the master regulator of the SOS
DNA repair system, and numerous other wellcharacterized
transcription factors involved in
metabolism and stress responses. Negative autoregulation
has been shown to reduce cell-to-cell
fluctuations in the steady-state level of the transcription
factor.4
Here, we explore the effect of
negative autoregulation on the kinetics of
transcription.
The kinetics of simple transcription units are
slow.5
If the protein product is long lived, the typical
time-scale for changes in the concentration is
the cell-cycle. One strategy to achieve faster
kinetics is to shorten the lifetime of the product by
degrading it.6
This incurs the metabolic cost of
constant protein production and turnover. Here,
we consider an alternative strategy, where a transcription
factor represses its own transcription.
Negative autoregulation has been theoretically
suggested to decrease rise-time without need for
high protein turnover rates.1,7,8
To study this
experimentally, we use a synthetic circuit in
E. coli4,9,10
to demonstrate that negative autoregulation
can speed up transcription responses, in
agreement with mathematical models.
Results
Theory
Assume that the design goal is a circuit which
produces a given steady-state protein concentration
when induced. We compare two strategies
of gene regulation: a simple transcription unit and
a negative autoregulatory circuit (Figure 1). The
two circuits can be designed to reach the same
steady-state level of protein concentration, by having
differing values for the maximal production
rate of their promoters. We will show that the
0022-2836/02/$ - see front matter q 2002 Elsevier Science Ltd. All rights reserved
E-mail address of the corresponding author:
urialon@weizmann.ac.il
Abbreviations used: aTc, anhydrotetracycline; GFP,
green fluorescence protein.
doi:10.1016/S0022-2836(02)00994-4 available online at http://www.idealibrary.com on
Bw
J. Mol. Biol. (2002) 323, 785–793
negative autoregulatory circuit approaches its
steady-state value much faster than the non-autoregulatory
circuit.
For both models, the rate of change of the concentration
of the protein product x has been
described5,11
(see Table 2, and for more details see
also math primer†):
dxðtÞ
dt
¼ AðtÞ 2 ax ð1Þ
with a production term A(t ) and a dilution/degradation
term 2ax. For a long lived gene product,
the latter accounts for the dilution of the protein
when the cells grow and divide, with a cell-cycle
time of t, where a ¼ ln(2)/t. In order to study the
kinetics of induction we will examine cases where
the initial protein concentration of zero.
We define the rise-time tr as the time required for
a gene product to reach half of its steady-state
concentration, xðtrÞ ¼ xst
=2:
Kinetics of a simple transcription unit
For a simple transcription unit with a constant
rate of production A1 ¼ b1, the steady-state
concentration is:
xst
1 ¼ b1=a ð2Þ
Table 1. Transcription factors in E. coli that repress their
own transcription (negative autorgulation, also termed
autogenous control)2
Negatively
autoregulating
transcription
factors
Additional
transcription
regulation Function
AraC Crp Arabinose utilization
ArgR Arginine biosynthesis
Crp Catabolite repression, global
regulator
CysB Cysteine biosynthesis
DsdC Regulator of D-serine
dehydratase
EmrRAB Multidrug resistance pump
ExuR Carbon utilization
Fis rRNA and tRNA operons and
DNA replication
Fnr Aerobic, anaerobic respiration,
osmotic balance
Fur Crp Iron transport
GalS GalR Galactose utilization
GcvA Cleavage of glycine
GlnA Crp, RpoN Glutamine synthesis
Hns Global regulator
Ihf Integration host factor, global
regulator
IlvY Isoleucine and valine synthesis
LexA SOS DNA repair
Lrp Leucine response, amino acid
limitation, global regulator
LysR Lysine biosynthesis
MarA Rob Multiple antibiotic resistance
ModE Molybdate transport
MtlADR Mannitol utilization
Nac RpoN Histidine utilization/nitrogen
assimilation
NadR NAD biosynthesis, other roles
NagC Crp Repressor of genes for
catabolic enzymes
OxyR Oxidative stress
PhdR Fis Activator of hca cluster, other
roles
PurR Purine biosynthesis
PutAP Nac Proline synthesis, other roles
RpiR Ribose catabolism
SoxS SoxR Superoxide stress
SrlA-D Glucitol/sorbitol utilization
TrpR Tryptophan biosynthesis
UxuABR ExuR Mannonate utilization
Several of these operons have additional transcription factor
inputs.
Figure 1. Synthetic transcription circuits. (a) Simple
transcription unit (open loop, Dh5a þ pZS12-tetR þ
pZE21-gfp). Cells expressing TetR can be induced, by
adding aTc to the medium, to produce GFP. (b) Negative
autoregulation (Dh5a þ pZSp
21tetR-egfp4
): the tet promoter
controls the production of its repressor, TetR
fused to GFP. The TetR–GFP fusion protein represses its
own promoter.4
Table 2. Variables and parameters used in the models
Description
xðtÞ Protein concentration in cells
AðtÞ Protein production rate
t Cell-cycle time
a Growth rate a ¼ ln(2)/t
b Protein production rate from the fully induced
promoter
b1, x1ðtÞ Subscript 1 indicates the simple transcription unit
b2, x2ðtÞ Subscript 2 indicates the negatively autoregulated
circuit
b/a Steady-state protein concentration from fully
induced promoter
k Dissociation constant of the repressor to its own
promoter
† http://www.weizmann.ac.il/mcb/UriAlon/
786 Negative Autoregulation
and the kinetics of step induction are:5,11
x1ðtÞ
xst
1
¼ 1 2 e2at
ð3Þ
so that the deviation of x from its steady-state
value drops by half each cell-cycle. Thus, a simple
transcription unit has a rise-time of one cell-cycle:
tr ¼ t
Negative autoregulation speeds response times
A genetic autoregulatory circuit is one in which
the rate of production of the gene product depends
on its intracellular concentration. For simplicity we
assume a Michaelis–Menten-like form for the
activity of the promoter:
A2ðtÞ ¼
b2
1 þ
x2ðtÞ
k
ð4Þ
where b2/a is the steady-state product concentration
from an unrepressed promoter and k is
the dissociation constant (¼1/affinity) of the
repressor to its own promoter. The steady-state is:
xst
2 ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
k2 þ 4kb2=a
p
2 k
2
ð5Þ
For strong autorepression (b2/a) q k, the steadystate
approaches:
xst
2 ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffi
kb2=a
p
ð6Þ
and the kinetics approach a simple limiting form:
x2ðtÞ
xst
2
¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 2 e22at
p
; b2=a q k ð7Þ
The rise-time is:
tr ¼ ðlog2ð4=3Þ=2Þt ¼ 0:21t
compared to tr ¼ t for the simple transcription
unit. The parameters of the two designs can be set
to achieve an equal steady-state (x1
st
¼ x2
st
) by
assigning a relatively weak promoter to the
unrepressed circuit and a strong promoter to the
autorepressed circuit. The rise-time of the negatively
autoregulated circuit is about one fifth of
the equivalent circuit (with the same steady-state)
without negative autoregulation.
The rise-time approaches the limiting value of
about one-fifth of a cell-cycle for strong autorepression,
b2/a q k. When autorepression is
weak, b2/a p k, there is effectively no autoregulation
and tr ¼ t. For intermediate value of b2/a, the
rise-time changes continuously between these limiting
values (equations (9) and (10) in Materials
and Methods, and Figure 2, marked with T ¼ 0).
Interestingly, there is a broad region where the
rise-time is about 0.2t, independent of the biochemical
parameters b2/a and k. For example,
using reasonable parameters for bacterial
repressors,7
at an unrepressed level of 4000 proteins
per cell (equivalent to a concentration of
roughly b2/a ¼ 4 mM) and a binding constant of
k ¼ 10 nM, the expected steady state level is 200
molecules per cell and the expected rise-time is
tr ¼ 0.24t.
Effects of cooperativity
Analysis of cooperativity in autorepression
A3 ¼ b3/(1 þ xH
/kH
) (equation (11) in Materials
and Methods), suggests that cooperativity in the
repression of the transcription factor’s own promoter
can further decrease the rise-time. (The lower
limit of tr/t decreases as the cooperativity
increases (tr
H¼1
< 0.21t, tr
H¼2
< 0.06t, tr
H¼3
< 0.02t,
and tr
H¼4
< 0.01t).
Effects of protein degradation
For a gene product with a finite half-life time
tdeg, we substitute everywhere the dilution rate
a ¼ ln(2)/t with a0
¼ ln(2) £ (t21
þ tdeg
21
), so that
for short lived proteins a0
¼ ln(2)/tdeg. All the
above analysis holds for degradable gene products,
replacing a by a0
. The rise-time is faster by the
same factors, replacing t with t0
¼ (t21
þ tdeg
21
)21
.
Thus, for rapidly degradable proteins with lifetime
tdeg, much smaller than t, a simple transcription
unit has a rise-time of tr ¼ tdeg, while a strong negatively
autoregulated circuit has a rise-time of
tr < 0.2tdeg.
Effects of explicitly treating mRNA levels
Note that for simplicity we did not explicitly
include equations for the production and degradation
of mRNA in the equations above. mRNA
concentration is assumed to be at a quasi-steadystate
proportional to A(t ), due to the short mRNA
lifetime compared to that of the proteins. For
example, mRNA lifetime in prokaryotes is usually
on the order of a few minutes, while protein
dilution and degradation rates are generally on
the order of tens of minutes to many hours.12,13
Indeed, numerical solutions of the system of
equations obtained by explicitly calculating the
mRNA levels (equations (12a) and (12b) in
Materials and Methods) yield kinetics that nearly
coincide with the solutions of the equations above.
Effects of delays in the formation of active proteins
Delays on the order of a few minutes are
expected between transcription initiation and the
formation of the active repressor able to negatively
regulate the activity of its own promoter.12,14
Such
delays are due to the cumulative effect of steps
such as elongation, termination, ribosome binding
and peptide elongation, protein folding, formation
of complexes such as dimers, and their diffusion
to the DNA-binding site. A simple way to
Negative Autoregulation 787
represent the effects of the cumulative delay T is:
dx
dt
ðtÞ ¼
b
1 þ
xðt 2 TÞ
k
2 axðtÞ ð8Þ
We find that the delay has a significant effect only
for promoters so strong that the production during
the delay time T is of the order of the steadystate
level of the repressor (equation (6)), that is
bT , sqrt(kb/a). In this case, by the time the first
repressors become active, many repressors are
already in production. Therefore, the feedback is
unable to stop production and a large overshoot
in protein concentration can occur. Figure 2 shows
the rise-times obtained for various values of the
delay time T obtained by numerical solutions of
equation (8). The delay leads to a decrease in the
rise time in comparison to the model with no
delay (equations (9) and (10) in Materials and
Methods), marked by T ¼ 0 in Figure 2. The
bold line shows cases where an overshoot is
obtained. In many cases a large overshoot is
probably undesirable, due to possible toxic
effects15,16
and increased production cost. In
addition, this excess protein takes a long time to
dilute out when the system is turned off. Therefore,
an optimal design may favor intermediate values
of the repression strength (b/a)/k, which have a
rapid rise-time but are far from the overshoot
region.
Experimental kinetics of simple transcription
units and negative autoregulatory circuits
The simple transcription unit (Figure 1(a)) was
represented by cells bearing a plasmid carrying a
green fluorescent protein (gfp ) gene controlled by
the tet promoter, which is repressed by a constitutively
produced repressor TetR. The bacteria were
grown in a multi-well fluorimeter that allows automated
measurements of fluorescence and cell
density at a temporal resolution of minutes.23
Cells
from overnight cultures were diluted into fresh
medium containing the inducer anhydrotetracycline
(aTc), which binds and inactivates the
repressor TetR. After a short lag the fluorescence
Figure 2. Numerical calculation of the rise-time (in cell-cycles) of a non-cooperative negative autoregulatory circuit.
The rise-time is plotted as a function of the repression ratio (b/a)/k. b/a is the steady-state concentration produced
from an unrepressed promoter, and k is the repressor dissociation constant to its own promoter. The rise-times for
various values of the delay T between transcript initiation and active protein formation are shown, for
T ¼ [0.1 0.06 0.035 0.02 0.01 0.006 0.002 0] in units of the cell-cycle. The cross marks the measured parameters (with
errors) of the negative autoregulatory circuit used in this study. From the measured position of the cross, the effective
time delay may be estimated, and is found to be 0.02(^0.01) cell-cycles, or roughly three minutes. The bold black
line marks the regime where large overshoots in protein concentration occur. Note that without production delay
(T ¼ 0), when b2/a q k the rise-time approaches a constant fraction of the cell-cycle, tr
min
¼ 0.21t.
788 Negative Autoregulation
per cell kinetics agrees with equation (3) (Figure 3)
and shows a rise-time of one cell-cycle.
To measure the effect of negative autoregulation
on the rise kinetics, we employed the synthetic circuit
of Becskei & Serrano,4
in which a transcription
factor (TetR–GFP fusion) represses its own production
(Figure 1(b)). To observe the effects of
negative autoregulation on the induction kinetics,
one needs to turn on the production of repressor
from a low initial concentration of active repressor.
To do this, we made use of an extraordinary
property of the tet system: TetR binds to its inducer
molecule aTc with an extremely high affinity
(1012
M21
).17
Because of the high affinity, it is well
established that aTc can be titrated out of the
medium by TetR.18
During growth of the cells, the
amount of TetR–GFP fusion protein increases
until the concentration of TetR–GFP equals that of
aTc. At this point (Figure 4, horizontal lines),
virtually all TetR are bound and inactivated by
aTc. The inducer aTc is titrated out of the medium,
and the new TetR produced are free to repress
their own promoter. From this point on, the
kinetics qualitatively changes due to negative
autoregulation.
We find that the rise-time of the negative autoregulatory
circuit is much smaller than the risetime
of an unregulated unit (tr < 0.2t, Figure 3).
We compare the observed kinetics to the model of
a negative autoregulatory transcription unit
(equation (7)). It is striking that this limiting solution,
which has no free parameters, displays a
timescale similar to the experimentally observed
kinetics (Figure 3). At late times (after 0.2 cellcycles)
the experimental rise is even faster than
the model (possible reasons are discussed in
Materials and Methods). Under conditions where
aTc is not depleted, the tet repressor is fully inactivated,
the feedback loop is cut, and the behavior
of the autoregulated circuit is identical with that
of the non-autoregulated transcription unit, showing
a rise time of one cell-cycle (Figure 3, broken
black line).
To compare the experimental results to the more
detailed theoretical model including delays
between transcription initiation and active
Figure 3. Comparison of the experimentally observed kinetics of a negative autoregulatory circuit and a simple transcription
unit. Fluorescence per cell, normalized by its maximal value, is plotted versus time in cell-cycles. The rise-time
is the time to reach half of the maximal product concentration (thin dashed lines). Bold black line, induction of a
simple transcription unit (open loop). Fine black line, theory (equation (3)). Red, cyan, and purple lines, kinetics of
negative autoregulatory circuit. Blue, analytical solution of the mathematical model of negative autoregulation in the
limit of strong autorepression, b2/a q k (equation (7)). Broken black line, kinetics of the autoregulatory circuit prior
to aTc depletion, where tetR is fully inactivated and the feedback is cut. The simple transcription unit has a rise-time
of one cell-cycle, while the negative autoregulatory circuit has a rise-time of 0.2 cell-cycles.
Negative Autoregulation 789
protein formation, we estimated the repression
ratio (b/a)/k from the measured ratio of the
steady-states at saturating aTc and under negative
autoregulation. We find that (b/a)/k ¼ 100(^20).
Using this value in equation (8), we find that the
kinetics are well described with a delay time of
3(^1) minutes (0.02 cell-cycles). The kinetics
virtually coincides with the analytical solution
without delay (equation (7)). We note that a three
minute delay time agrees with typical delays
between induction and formation of the first active
proteins in E. coli.12,14
Discussion
We demonstrate experimentally that negative
autoregulation can significantly speed up the risetimes
of transcription units. It has long been
known that simple transcription cascades composed
of long-lived transcription factors with no
autoregulation are typically very slow. For
example, the classic experiments on beta-galactosidase
production showed that though the first
enzymes are produced within minutes the risetime
is on the order of a cell-cycle.5
Our findings
suggest that negative autoregulation can reduce
these delays to a fraction of the cell-cycle time.
Consider evolution as an engineer, whose goal is
to design a transcription unit that gives rise to a
given steady-state product concentration. Two
designs are compared: (A) a relatively weak promoter
with no negative autoregulation, and (B) a
strong promoter with negative autoregulation.
Design B will show a faster rise-time to the same
steady-state. The rise-time is expected to decrease
with increased cooperativity in the binding of the
repressor to its own promoter.
The fundamental reason that the negative autoregulatory
circuit has a shorter rise-time is that the
unrepressed promoter creates a fast initial rise,
while at later times the newly produced repressor
shuts off its own production to reach the required
steady-state concentration. Note that a strong nonautoregulated
promoter will reach any given concentration
faster, but will stabilize at a much higher
steady-state. Steady-state concentrations of the product
that are much higher than its functional range
are undesirable due to the metabolic cost of
unneeded production, possible toxic effects and
the long time required for its subsequent dilution
when production is ceased.15,16
An alternative way of speeding the responses is
to introduce degradation of the gene product. The
response time is then determined by the degradation
rate, and so to achieve fast responses at a
given steady-state level requires increased production.
This has the drawback of increased metabolic
cost (“futile cycle”). There are qualitative
differences in the kinetics of systems employing
degradation compared with those using negative
autoregulation: degradation speeds up both the
rise-time and the turn-off time of protein levels
(the time to reach half steady-state levels after transcription
is turned off), while negative autoregulation
speeds up the rise-time, but does not
generally affect the turn-off time. It is interesting
that eukaryotic cells seem to use the degradation
strategy for transcription factors more often than
prokaryotes.6
Even in a system that has degradation,
adding negative autoregulation still speeds
up the response time to a fraction of the degradation
time.
The present results should apply to a broad
variety of gene regulation systems in E. coli and
other organisms (Table 1). For example, the SOS
Figure 4. Fluorescence (continuous
lines) of the negative autoregulatory
circuit (Figure 1(b)) in
response to different concentrations
of aTc shows two distinct regimes,
an exponential increase in fluorescence
followed by a transition to
a slower rate of increase. The fluorescence
at the transition (horizontal
lines) is proportional to the concentration
of aTc, and the final fluorescence
equals the fluorescence at
the transition plus a constant. Inset:
blue stars, final fluorescence data
from two repeated experiments.
Red, fit to a straight line.
790 Negative Autoregulation
DNA repair system genes are transcriptionally
repressed by a negatively autoregulating repressor
LexA.19
Upon DNA damage, the LexA cleavage
rate is increased, its level drops and the SOS repair
genes are expressed.20
After damage is repaired,
the cleavage process stops, and LexA levels build
up to repress the system. Negative autoregulation
can help speed up the recovery of LexA levels.8
Additional examples include transcription factors
that are transcriptionally regulated by other transcription
factors, and negatively regulate their
own production (Table 1). Such is the case of the
negatively autoregulating transcription factor
AraC, which controls the arabinose untilization
genes.21
The transcription of the araC gene is
activated by Crp, a global regulator responsive to
glucose starvation. Upon removal of glucose from
the medium, Crp becomes activated to induce
AraC transcription. The negative autoregulation of
AraC should speed up its production, leading to a
faster utilization of the sugar arabinose in place of
glucose.
This study contributes to the emerging understanding
of genetic regulatory networks. It would
be interesting to characterize the kinetic behavior
of additional regulatory circuit elements. Positive
autoregulation,22
for example, is expected to slow
down the response times of transcription units.1
Artificial gene circuits could be very useful tools
for isolating and analyzing such circuits in detail.
This will be important in approaching a systemslevel
understanding of networks composed of
such recurring regulatory motifs.2
Materials and Methods
Bacterial strains and plasmids
E. coli strain Dh5a, which expresses lacI, was used in
all experiments. Plasmid pair pZS12-tetR þ pZE21-gfp
was used to make the non-autoregulatory network.
The plasmids were based on the modular system of
Lutz & Bujard.16
For pZS12-tetR, tetR was cloned into a
vector containing the low-copy SC101 origin of replication,
ampicillin resistance cassette, and PLlacO1
promoter.16
pZE21-gfp contained a ColE1 origin,
kanamycin resistance cassette, PLtetO1 promoter, and
gfpmut3.23
pZSp
21tetR-egfp (kindly obtained from
Becskei & Serrano4
) was the negative autoregulatory
circuit.
Growth conditions and measurements
Cultures (2 ml) inoculated from single colonies were
grown overnight in defined medium (M9 salts (Bio 101
Inc.) þ 0.05% (w/v) Casamino acids þ 0.1% (v/v)
glycerol þ 2 mM MgSO4 þ 0.1 mM CaCl2 þ 1.5 mM
thiamine þ antibiotics: either kanamycin (50 mg/ml) þ
ampicillin (100 mg/ml) or kanamycin (25 mg/ml)) at
37 8C with shaking at 300 rpm. For the simple transcription
unit, 0.08 mM isopropyl-b-D-thiogalactopyranoside
(IPTG) was added to all media to induce the lac promoter
to produce TetR, the repressor of the tet promoter.
The cultures were diluted 1:100 into the same medium
plus anhydrotetracycline (aTc) (Acros Organics), which
inactivates TetR, as inducer: 500 ng/ml for the simple
transcription unit, and varying amounts of aTc
(0–500 ng/ml, see Figure 4) for the negative autoregulatory
circuit. Growth rate was not affected at the
aTc concentrations used. The dilution was done into
flat-bottom 96 well plates at a final volume of 200 ml
per well. Cultures were grown in a Wallac Victor2 multiwell
fluorimeter with injectors set at 37 8C and
assayed with an automatically repeating protocol of
absorbance (A ) measurements (600 nm filter, 1.0 second,
absorbance through approximately 0.5 cm of fluid),
fluorescence readings (485 nm and 535 nm filters, 0.5
second, CW lamp energy 2482 units), and shaking
(2 mm double-orbital, normal speed, 203 seconds).24
Once every three repeats the shaking was replaced by
automated injection of 7 ml double-distilled water into
each well to counteract evaporation. Time between
repeated measurements was eight minutes. Background
fluorescence of cells bearing a promotorless gfp
vector was subtracted. Relative error between repeated
experiments using the ptet-tetR-gfp construct was less
than 5%.
For the open-loop kinetics (Figure 3, continuous black
line), bacteria were diluted from overnight culture into
medium with inducer (500 ng/ml aTc). After a short lag
phase the bacteria enter exponential growth, with a cellcycle
time of t ¼ 135 minutes, and reach a maximum
fluorescence per A of ,50,000 fl units per A unit. The
strain carrying the negative autoregulatory circuit grew
at a maximum rate of one doubling every t ¼ 72
minutes. For the negative autoregulation kinetics (Figure
3, colored lines), we calculated the amount of repressor
needed to titrate the inducer by a straight line fit (Figure
4 inset). We then calculated the amount of new repressor
molecules produced after the inducer aTc was titrated
out, by the difference between the fluorescence (continuous
lines in Figure 4) and the fluorescence at the
point of titration (horizontal lines in Figure 4). The fluorescence
difference was divided by the absorbance to get
relative fluorescence per A, which was normalized by
its maximum value of ,5600 fl units per A unit. This
was plotted versus the growth of the cells in cell-cycles,
calculated by log2(A(t)/A(t0)). The lines correspond to
the continuous lines in Figure 4 with 3.1, 6.25 and
12.5 ng/well aTc. With saturating aTc (when no qualitative
change in the expression was observed due to
depletion of aTc by TetR and the effects of negative autoregulation)
the negatively autoregulatory circuit reached
a fluorescence level of 55,000(^5000) fl units per A unit.
Roughly 15 hours from the beginning of the experiment
(time , 900 minutes in Figure 4) the cells start to enter
stationary phase and their growth rate drops substantially,
so only a few cell-cycles are measured in Figure 3.
A slight increase in tet promoter activity is observed
under the present conditions, as the cells leave exponential
growth and enter stationary phase, in both open
loop and closed loop circuits.
The unusually high affinity of aTc to TetR allowed us
to calibrate fluorescence in terms of number of GFP
molecules (using the fluorescence at the point where all
TetR–GFP molecules are bound by aTc, Figure 4 and
inset). Assuming that all the aTc is active and binds
TetR molecules, we estimate that one fl unit equals
4.4(^1) fmol GFP molecules per well. Note that if only
a fraction 0 , u , 1 of the aTc molecules are active,18
then correspondingly one fl unit equals
u £ (4.4 ^ 1) fmol GFP molecules per well. One A unit
corresponds to about 108
cells per well.
Negative Autoregulation 791
Simple model of the kinetics of a negative
autoregulatory circuit
Equations (1) and (4) can be integrated, using equation
(5):
tðxÞ 2 tðx0Þ ¼ 2
1
2a
logððx 2 xstÞðx þ k þ xstÞÞ
þ
k
k þ 2xst
log

x 2 xst
x þ k þ xst
!x
x0
ð9Þ
When (b2/a) q k this equation can be approximated by
equation (7), and when k q (b2/a) by equation (3).
From equations (5) and (9), we can calculate the risetime:
tr:
tr ¼ t
xst
2
 
2 tð0Þ ¼ f
b2=a
k
 
ð10Þ
which turns out to be a function only of the dimensionless
ratio, r ¼ (b2/a)/k.
For cooperative autorepression A3 ¼ b3/(1 þ xH
/kH
),
we obtain at the limit b3/a q k3:
x3ðtÞ
xst
3
¼ 1 2 e2ðHþ1Þat
À Á 1
Hþ1 ; x3ðt0 ¼ 0Þ ¼ 0;
b3=a q k
ð11Þ
System of equations obtained by explicitly
calculating mRNA levels
dm
dt
¼
~b
1 þ
xðtÞ
k
2 ammðtÞ ð12aÞ
dx
dt
¼ gmðtÞ 2 axðtÞ ð12bÞ
Biochemical parameters of the tetracycline system
For completeness, we include the values of some of
the known biochemical parameters of the tet system.
TetR occurs as homodimers, with Kd smaller than
1027
M.25
In the absence of inducers (such as tetracycline
or aTc) TetR dimers bind tightly (Kd ¼ 10211
M)26,27
to the
specific DNA operator sequence O2. PLtetO-1 (used in the
construction of the circuits used here) contains the O2
operator twice,16
yet they are not known to have cooperative
effects. Two lac operators in corresponding positions
show that the repression effect of the operator in one
position is 50–70 times stronger than in the other
position,28
indicating that the promoter may be adequately
modeled by a non-cooperative repression
model. aTc inactivates the DNA-binding abilities of TetR
by tightly binding to it (Kd , 10212
M).17
The binding of
the first aTc reduces the affinity of the TetR dimer to
DNA by two to three orders of magnitude and the
second bound aTc reduces the affinity by a further four
to seven orders.26
One may speculate that the positive deviation of the
negative autoregulation kinetics from the model after
about half a cell-cycle (Figure 3) may be due to system
details that were not included in the model, such as
TetR dimerization. For example, consider the following
hypothetical scenario: upon aTc depletion, TetR dimers
are all doubly bound, both TetR monomers being bound
to aTc. As fresh TetR is produced, it can no longer bind
aTc since all aTc is already bound. However, aTc or
dimer dissociation and re-association on a slow timescale
lead to formation of bound/unbound TetR heterodimers,
which are inactive as repressors. Thus, repression
would be less strong than expected in the model,
leading to an overshoot (effectively, depletion is acting
at a delay). Eventually virtually all inactive dimers
would be singly bound, and the newly produced TetR
dimers would be active repressors.
The presently observed agreement between the induction
kinetics of the TetR–GFP fusion prior to aTc
depletion, the kinetics of GFP from a fully induced promoter,
and the model for long-lived proteins (broken,
bold, and light black lines in Figure 3) suggests that the
lifetimes of both GFP and TetR–GFP are much longer
than the cell-cycle.
Acknowledgements
We thank A. Becskei, L. Serrano, R. Lutz and
H. Bujard for plasmids. We thank P. Bashkin for
assistance. We thank N. Barkai for illuminating
discussions and suggestions. We thank M. Surette,
S. Leibler, O. Stock, A. Levine and all members of
our laboratory for discussions. This work was supported
by the Israel Science Foundation, the
Human Frontiers Science Project and the Minerva
foundation. M.E. is supported by the Seaver
institute and the Burroughs-Wellcome Fund. N.R.
dedicates this work to the memory of his father,
Yasha Rosenfeld.
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Edited by M. Yaniv
(Received 9 May 2002; received in revised form 2 September 2002; accepted 7 September 2002)
Negative Autoregulation 793