SUPPLEMENTARY INFORMATION
Molecular crowding shapes gene expression in synthetic
cellular nanosystems
Cheemeng Tan1, Saumya Saurabh2,3, Marcel Bruchez2,3, Russell Schwartz1,4*, and Philip
LeDuc1,5*
SUPPLEMENTARY METHODS
S12 bacterial extract preparation
S12 bacterial extract was prepared following an established protocol
1
with slight
modifications. Specifically, each starter culture of Escherichia coli BL21DE3 cells was
incubated overnight at 37oC (225 rotation per minute (rpm)). Next, the starter culture was diluted
1000x into Luria Broth (LB) supplemented with 100M Isopropyl β-D-1-thiogalactopyranoside
(IPTG) and incubated at 37oC (225rpm) for eight hours. For each BL21pro/pTetRFPT7 culture,
cells were induced at the eighth hour and incubated at 30oC (225rpm) for a total of 24 hours.
Next, cell pellets were harvested by centrifugation at 4000rpm for 10min and resuspended in
10ml phosphate buffered saline (PBS). The cells were spun down again and cell pellets were
resuspended in 1ml buffer A (for each 100ml of cultures). Buffer A contained 10mM tris–acetate
buffer (pH 8.2), 14mM magnesium acetate, 60mM potassium glutamate, and 1mM dithiothreitol
(DTT). The resuspended cells were stored overnight at -80oC. Next, the cells were thawed and
lysed using a sonicator to obtain crude bacterial lysate. Each lysate was centrifuged at 12,000
relative centrifugal force (rcf) for 20min. The supernatant was extracted and incubated at 37oC
for 30min. The resulting S12 bacterial extract was stored at -80oC. Both S12 and S30 extracts
produced the same magnitude of gene expression rates (Supplementary Fig. 1b)1.
1
Supplementary Table 1: Formulation of the S12 supplement
Item
Working
Source
concentration
HEPES
50 mM
Sigma, MO, USA
ATP, Disodium
1.2 mg/ml
Roche, IN, USA
GTP, sodium salt
0.8 mg/ml
Roche, IN, USA
CTP, disodium salt
0.8 mg/ml
Roche, IN, USA
UTP, trisodium salt
0.8 mg/ml
Roche, IN, USA
0.17 mg/ml
Roche, IN, USA
0.035 mM
Sigma, MO, USA
Magnesium acetate
20 mM
Sigma, MO, USA
Potassium glutamate
100 mM
Sigma, MO, USA
Ammonium acetate
80 mM
Sigma, MO, USA
PEG-8000
0.2 g/ml
Sigma, MO, USA
DTT
1.5 mM
Sigma, MO, USA
4 mM
Sigma, MO, USA
80 mM
Roche, IN, USA
Creatine kinase
0.08 mM
Roche, IN, USA
Adenosine 3′,5′-cyclic
0.65 mM
Sigma, MO, USA
tRNA (MRE600)
Folinic acid calcium salt
hydrate
Spermidine
Creatine phosphate
monophosphate (cAMP)
DNA purification
Bacteria carrying plasmids were incubated overnight at 37oC in 3ml LB supplemented
with appropriate antibiotics. Next, plasmids were purified from the bacterial cultures using a
miniprep kit (Qiagen, CA, USA). Next, plasmids were examined for their purity using a
nanodrop (NanoDrop, DE, USA). Each plasmid-prep yields plasmids with a 280/260nm ratio
between 1.8 to 1.9 and a 230/260nm ratio between 2.3-2.4. For all plasmids with a pBR322
replication origin, plasmid concentrations were maintained consistently between 250-300ng/l.
2
Cell-free expression assay
Unless otherwise noted, each cell-free expression system consisted of 20l S12 or S30
extract, 15l S12 supplement, 5l amino acids (Sigma, MO, USA), 2l plasmid DNA, and 58ul
deionized sterile water. For experiments using crowding agents, the water was substituted with
water containing the indicated amount of dextran, ficoll, or polyethylene glycol (PEG) (Sigma,
MO, USA). Each reaction was carried out in a Tecan Safire I platereader (Tecan, CA, USA) at
30oC with intermittent shaking at every 10minutes. Gene expression rates were calculated using
fluorescence intensities at the one hour time-point.
Western blot (Supplementary Fig. 2a & Supplementary Fig. 7c)
Each protein extract was subjected to SDS-PAGE for one hour at 200V and then
transferred to nitrocellulose (Biorad, CA, USA) overnight at 30V and 4oC. Immunoblots were
blocked with 5% skim milk in 1% TBST for one hour. Blots were incubated with either
T7RNAP (1:10,000) or GFP (1:10,000) antibody in 5% skim milk (TBST) for one hour, washed
twice for 30 minutes in TBST and incubated with 1:2000 anti-mouse antibody (Biorad, CA, USA)
for one hour. The GFP antibody has been shown to bind CFP (Abcam, Cambridge, USA). Blots
were washed twice for 30 minutes in TBST. Proteins were visualized using ECL Western
Blotting Detection Reagents (Biorad, CA, USA) in an imager.
Cloning of pTet-TagRFP-T7RNAP, pIVLys, pIVCFP, pIVGFP, and pIVTagRFP
T7 RNAP gene was amplified from BL21DE3 cells and inserted between BamHI and
HindIII digestion sites of a pTetLysGFPlva plasmid (p15a, kanamycin). The TagRFP657 gene
was cloned from a pTagRFP plasmid 2. TagRFP was chosen for its high photostability and far
red emission spectrum. The TagRFP gene was fused to the T7RNAP gene using a linker
sequence obtained from 3 that demonstrated the successful fusion of GAL4 to the N-terminal of
T7RNAP. The TagRFP gene and the linker were cloned into the pTetLysGFPlva plasmid
between the EcoRI and the BamHI digestion sites. All genetic constructs were sequenced and
verified.
3
CFP was amplified from a pET15bL-CFP plasmid 4. GFP was amplified from a pZEmg
plasmid 5. T7 Lys was amplified from a pLysS plasmid (Promega, Madison, USA). T7 Lys, CFP,
GFP, and TagRFP were inserted into a pIV2.3d plasmid (pBR322, Amp) between XbaI and NotI
digestion sites.
The weak T7 promoter was designed based on
6
(Fig. 2b). The promoter was cloned
between XbaI and BglII digestion sites of the pIV2.3d plasmid. The weak RBS (Fig. 2b) was
designed based on 7. The RBS sequence was appended to a PCR sense primer when amplifying
CFP.
Preparation of single molecule chambers (Fig. 1b-e, Supplementary Fig. 3a, and
Supplementary Fig. 4a)
Single molecule experiments were performed using PEG treated glass coverslips that
were prepared as reported in 8. For performing experiments with varying crowding agent
conditions, flow cells were prepared as follows: 3”×1” glass microslides (Corning, NY) were
exposed to a butane torch flame for approximately 10 seconds and two 1.25 mm holes were
drilled into the slides within 1.25 cm of each other. Polyethylene tubes (PE60), about 5cm long
were fixed through these holes using UV-curing optical glue. 100µm thick double-sided tape
(Grace Biolabs, OR) was applied to the microslide such that the holes were centered between the
double sided tape strip. This was followed by sticking the coverslip to the exposed side of the
tape such that the PEG treated face of the coverslip would face the microslide. The chamber was
then mounted on the microscope and solutions were changed using a syringe pump.
To
construct
Cy3-PT7,
we
ordered
a
sense
PCR
primer
(5’-
AGAGGATCGAGATCTCGATCCCGCG-3’) conjugated with a Cy3 molecule at the seventh
nucleotide and an antisense PCR primer (5’-TGTTGCATCACCTTCACCCTCTCCA-3’). Next,
we PCR a 200bp double stranded Cy3-PT7 using a pIVEX2.3d-CFP plasmid as a template. The
sense PCR primer was used as a negative control for single molecule binding experiments.
4
Setup of microscope for single molecule imaging (Fig. 1 & Supplementary Fig 3-5)
Single molecule imaging was performed using an objective-type TIRF on a Nikon Ti
inverted microscope stand (Nikon Instruments, NY, USA) equipped with a 100x 1.45 N.A. oil
immersion TIRF objective. For the imaging of TagRFP, a filter set containing a 630/23 – 532/12
dual band pass excitation filter, 532/638 (ZT) RPC dichroic mirror, and a 685/70 (ET) emission
filter was used (Chroma Technologies, VT, USA). An additional 685/70 (ET) filter (Chroma
Technologies, VT, USA) was used in the emission filter wheel to minimize the stray reflected
light getting to the detector. For imaging Cy3 labeled DNA, a filter cube containing a 535/25
excitation filter, 565 dichroic mirror and 590 long pass emission filter was used (Nikon
Instruments, NY, USA). These filters are slightly tilted to provide optimal blocking of the
reflected light. We used a 532 nm and a 639 nm diode pumped solid-state laser for excitation in
the two channels respectively. The measured power at the back of the objective was 3.6mW for
the 532 nm line and was 3.8mW for the 639nm line. The TIRF angle was optimized for the two
wavelengths using the motorized TIRF mirror attached to the stand. The detector used for all the
measurements was an Evolve 512 electron multiplying charge coupled device (Photometrics, AZ,
USA). Hardware control and image acquisition was performed using Micromanager 9. The cellfree systems of each single molecule experiments were prepared by mixing 20l RFPT7RNAP
lysate, 15l S12 supplement, and 65l dH2O supplemented with the indicated amount of
crowding agents.
Fluorescent recovery after photo bleaching (FRAP) (Fig. 1b-c & Supplementary Fig. 3)
The same microscope setup as above was also used for FRAP measurements, except that
we illuminated the sample through epi-fluorescence. For each FRAP experiment, we used a
sample with a total volume of 250l that contained 20l RFP-T7RNAP extracts and the
indicated percentage mixture of water and crowding agents.
5
Algorithms for the analysis of single molecule results (Fig. 1d-e & Supplementary Fig. 4)
Images were analyzed by modifying a custom program in Matlab
10
. The program first
summed 50 Cy3 images to locate positions of CY3-PT7. Next, the program created a Cy3-PT7
mask for all corresponding RFP images. The program calculated average RFP intensity using
3x3 pixels centered at each CY3-PT7 positions. Through this approach, we obtained time series of
RFP around each pT7-Cy3 molecules (Supplementary Fig. 5a). The RFP intensities were
smoothed using a wavelet-denoise algorithm with a db4 wavelets at the 2nd level. The program
identified positive binding events when RFP intensities were above three standard deviation of
the background level. Each histogram in Fig. 1e was fitted using the “histfit” function in Matlab
using an exponential distribution with 50 bins. Approximately 200 Cy3-PT7 molecules were
analyzed to obtain each curve. The results are consistent across replicated experiments on
different days.
Perturbation of gene expression rates (Fig. 3b & Supplementary Fig. 9)
The gene expression system was perturbed by using 20l of 1M potassium glutamate,
0.5l of 1M magnesium acetate, 2l of 5M ammonium acetate, 0.5l of 0.7M spermidine, or
0.5l of 7mM folinic acid.
Preparation of liposomes (Fig. 4, Supplementary Fig. 11 & 12)
1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleoyl-snglycero-3-phospho-L-serine (POPS) were purchased from Avanti (Alabama, USA). Lipid
mixtures (POPC:POPS:Cholesterol (Sigma, MO) = 25:1:2.5 (weight ratio)) were dried using a
vacuum chamber (Thermo Scientific Nalgene, NY, USA) for eight hours. The dried lipid film
was then rehydrated using deionized water overnight at 37oC. The hydrated lipids were stored as
50l aliquots at -80oC. The aliquots were then subjected to freeze-drying using a lyophilizer
(Labconco, MO, USA) for four hours and then stored at -20oC.
6
Preparation of artificial cells (Fig. 4, Supplementary Fig. 11 & 12)
We constructed artificial cells following an existing method
11
. Freeze-dried liposomes
were rehydrated using 50l of cell-free expression systems that consists of 10l of S12 extract,
15l of S12 supplement, 5l of amino acids, 4l of pIV-GFP plasmids, and 16l deionized water
supplemented with or without 20% Dex-Big. 0.1g/ml RNAse A was added to inhibit reactions
outside artificial cells. For each expression experiment, all reagents were kept on ice before
incubation at 37oC for one hour. For flow cytometry, artificial cells were resuspended in 500l
PBS. For the analysis of flow cytometer results, we omitted data points with intensity of
GFP<200a.u., which was equal to the background GFP level. We calculated GFP intensity
(Fig. 4c) using the equation
GFP DNA  GFP DNA
100% , where GFP+DNA represents mean
GFP DNA
fluorescence intensity of GFP with plasmids and GFP-DNA represents mean fluorescence intensity
of GFP without plasmids.
Mathematical modeling
We modeled gene expression in a cell free system (Fig. 2a) using a simplified ordinary
differential model with two variables.
d [ R]
[ RNAP ]
 k c k p [ R]
 k d [ R]
dt
[ RNAP]  K
[S1]
d [ P]
[ RNAP ]
 k p [ R]
dt
[ RNAP ]  K
[S2]
where R represents limited resources for gene expression such as ATP and amino acids, P
represents a protein, kc represents the consumption rate constant, kp represents gene expression
rates by the RNAP, K represents the half maximal synthesis rate of P, and kd represents
degradation of resource R.
For the negative feedback circuit (Fig. 3c), we modified Eq. S2 to Eq. S3 and added two
additional variables (Eq. S4&5) to model interactions between T7 RNAP and T7 Lysozyme.
7
d [ Lys]
[ RNAP ]
 k p [ R]
 k as [ RNAP ][ Lys]  kbs [ RNAP.Lys]
dt
[ RNAP ]  K
[S3]
d [ RNAP ]
 k as [ RNAP ][ Lys ]  kbs [ RNAP.Lys ]
dt
[S4]
d [ RNAP.Lys ]
 k as [ RNAP ][ Lys ]  k bs [ RNAP.Lys ]
dt
[S5]
where Lys represents the T7 Lysozyme, kas represents the association rate constant between
T7RNAP and T7 Lys, and kbs represents the dissociation rate constant between T7RNAP and T7
Lys.
To model the impact of molecular crowding, we modified binding constant K, kb, ka, kas,
and kbs using Eq. S6-10.
K
kb
ka
[S6]
kb 
kb0
K    nb
[S7]
ka 
k a 0 ( K  1   na1 )
( K  2   na 2 )
[S8]
k bs 
k bs 0
K s   ns
[S9]
k as  k as 0 ( K s   nas )
[S10]
where kb represents the dissociation rate constants between RNA polymerase and the promoter,
ka represents the apparent association rate constants between RNA polymerase and the promoter,
kas represents the apparent association rate constants between RNA polymerase and inhibitor, kbs
represents the dissociation rate constants between RNA polymerase and inhibitor, kb0 represents
the basal dissociation constant between RNA polymerase and the promoter, ka0 represents the
8
basal association constant between RNA polymerase and the promoter, K K Ksand Ks
represent the threshold values,  represents the crowding density, nb, na, nas, and ns represent
the scaling of . We formulated the impact of molecular crowding using polynomial equations to
emulate two aspects of our experiment results: dex-big increased the mean bound time of T7
RNAP and number of binding events more significantly than dex-small (Fig. 1e); both dex-small
and dex-big increased the immobile fractions and decreased the initial recovery rates (Fig. 1c&e).
We note that the qualitative outcomes of our equations (Eqn. S6-10) are similar to that of
established models 12, 13. We note that as long as a model generated the same qualitative
outcomes as our model (Supplementary Fig. 6), our conclusions would remain the same.
Supplementary Table 2: Model parameters
Parameter
Small crowding
Big crowding
Negative feedback
molecule
molecule
circuit
kc (M-1 min-1)
0.01
0.01
1
kp (M-1 min-1)
0.5
0.5
0.01
ka0 (M-1 min-1)
5
[5, 0.05]
2
K
1
8
8
na1
1
4
4
K
10
10
10
na2
2.5
2.5
2.5
kb0 (min-1)
300
[300, 3000]
700
K
1
5
5
nb
0
1
1

10-1 to 101
10-1 to 101
10-1 to 101
kas (M-1 min-1)
N.A.
N.A.
10-5
kbs0 (min-1)
N.A.
N.A.
103
Ks
N.A.
N.A.
10
ns
N.A.
N.A.
1
9
Kas
N.A.
N.A.
10
nas
N.A.
N.A.
4
103
103
103
1
1
[0.5, 1]
[R]0 (M)
[RNAP]0 (M)
Note 1: We have tested additional sets of parameters (by fixing the parameters in Eq. S6-S10),
which did not affect our qualitative conclusions in this manuscript.
Note 2: [RNAP]0, kb0, kc, and kp were estimated using the magnitude of parameters from previous
studies 14, 15. ka0 and [R]0 were fitted using experimental results without crowding agents
(Supplementary Fig. 7a, 0% Dex-Big). All other crowding-related parameters (Eq. S7-S10) were
determined based on our measurement from FRAP and single molecule experiments.
Robustness tests (Fig. 3a)
For each random perturbation, either a parameter or an initial condition was randomly
perturbed by 10fold around a basal parameter set. For a low crowding environment, = 0.001;
for a high crowding environment, = 10. Next, we calculated fold perturbations by comparing
initial expression rates of P using Eq. S11. We subtracted a value of one from fold perturbations
so that a zero value would represent no changes of P.
Fold perturbation – 1 =
Pperturbed
Pbasal
1
[S11]
Stochastic model (Fig. S9a)
We modeled stochastic gene expression using the chemical Langevin equation 16. The
stochastic model was simulated using a forward-Euler scheme.
Rt  Rt 1  (k c k p [ R]
[ RNAP ]
 k d [ R]) dt 
[ RNAP ]  K
 k c k p [ R]
[ RNAP ]
 k d [ R] dt
[ RNAP ]  K
[S12]
10
Pt  Pt 1  (k p [ R]
[ RNAP ]
[ RNAP ]
)dt  k p [ R]
dt
[ RNAP ]  K
[ RNAP ]  K
[S13]
where  represents normal noise N(0,1).
Supplementary Figure Legends
Figure S1: S12-extract production and quality control
a. The schematic of S12-extract production. BL21DE3 cultures were induced to synthesize
T7 RNAP and incubated between 8-16 hours. Next, the cultures were spun down and resuspended using S12 buffer. After freeze-thawing, the cells were sonicated to release
cytoplasmic content. The sonicated cells were centrifuged to separate cellular proteins
from debris. The supernatants were collected and incubated at 37oC to finish all run-off
reactions. The S12 extracts were aliquoted and stored at -80oC. The protocol is based on 1.
See detailed description in SI.
b. Expression rates of bacterial extracts. Both S12 and S30 extracts (Promega, Madison,
USA) gave rise to similar expression rates, suggesting that our S12 extracts have similar
quality as standard extracts. Each error bar represents one SEM of five replicates.
c. Bacterial growth in bacterial extracts. To examine potential contamination of bacteria in
cell extracts, we added the extracts to minimal M9 media and tracked bacterial growth
using optical densities (absorbance @600nm). We did not observe any bacterial growth
in both our S12 and S30 extracts, which suggests that the extracts did not contain live
bacteria. Grey lines represent the media with added bacteria. Red lines represent the
media with S30 extracts. Black lines represent the media with S12 extracts.
Figure S2: RFP-T7 RNAP functional tests
a. Western blots of RFP-T7RNAP using T7 RNAP antibody (EMD Millipore Chemicals,
MA, USA). RFP-T7RNAP fusion proteins were expressed at the correct size ~150kD.
11
b. Expression of CFP by RFP-T7RNAP extracts. RFP-T7RNAP fusion proteins could
transcribe CFP from a PT7 promoter in our cell free systems. The cell-free expression
system contains RFP-T7 RNAP fusion proteins, but not the wild type T7 RNAP proteins.
See SI for detailed protocol.
Figure S3: Fluorescence recovery after photobleaching (FRAP) using RFP-T7RNAP
a. Schematic of the FRAP experimental setup. A glass cover slip was coated with PEGsuccinimidyl carboxymethyl ester (MW = 5000) to prevent protein adhesion 17. Therefore,
RFP-T7 RNAP could freely diffuse in the system. Based on this experimental setup, we
could study the diffusion of RFP-T7 RNAP in a bulk solution.
b. A sample RFP time series in a FRAP experiment. RFP was normalized between zero and
one (black open box). The system was photobleached for 5 minutes, followed by a
recovery period of 5 minutes. Molecular crowding could trap molecules, thereby giving
rise to an immobile fraction18. A fitted curve (grey line) is drawn using an equation f(1exp(-kt), where f represents the immobile fraction plotted in Fig. 1c. An arrow indicates
the initial recovery rate plotted in Fig. 1b.
c. Sample RFP images in a FRAP experiment.
Figure S4: Single-molecule DNA binding experiments
a. Schematic of the single molecule binding experiments. A cover slip was coated with
Biotin-PEG- succinimidyl carboxymethyl ester (MW = 5000). Streptavidin was added
into the system and bound to biotin. After washing away free streptavidin, DNA with
biotin was flowed into the system and bound to streptavidin. Through this approach,
DNA was fixed to the surface and could be tracked for T7 RNAP binding.
b. A fluorescence image of single DNA-Cy3 molecules. Each DNA was tagged with a Cy3
molecule. Our custom algorithm identified and located the centroid of each Cy3
molecules. For each frame of the field, the algorithm would only select between 100-200
DNA molecules that exhibited high Cy3 intensities.
12
c. A sample fluorescence image of Cy3-PT7 molecules. Cy3-DNAs were significantly
brighter than the control without Cy3-DNAs. Both images were normalized using the
same minimum and maximum fluorescence intensities.
d. A sample fluorescence image of RFP-T7RNAP. RFP-T7RNAPs were significantly
brighter than the control without RFP-T7 RNAPs.
Figure S5: Computational analysis of single molecule results
a. Temporal RFP-T7RNAP dynamics at a Cy3-T7 DNA molecule. The top panel shows
time series of RFP intensities at a Cy3-T7 molecule. Black dots represent the background
RFP. Red dots represent the raw RFP data. Blue dots represent the smoothed RFP data.
The bottom panel shows the identified binding events. When RFP intensity at a specific
time increased above three times the standard deviation of the background RFP, the
algorithm would register it as a binding event. A chain of binding events without pauses
was connected as a single event. See SI for a detailed algorithmic description.
b. Histogram of bound time using DNAs without a T7 promoter. The number of binding
events was negligible when compared to the number of binding events using DNA
containing a T7 promoter (Fig. 1e). A grey line indicates the histogram of binding events
without Dex-Big. A black line indicates the histogram of binding events with Dex-Big.
c. Number of binding events per promoter with increasing crowding densities. Dex-Big
significantly increased the average number of detected binding events per promoter at
intermediate crowding densities when compared to Dex-Small. Each error bars indicate
one SEM of at least five replicates.
Figure S6: Model assumptions of rate constants dependence on molecular density
Modeling assumptions of an association rate constant ka and a dissociation rate constant
kb of T7 RNAP with PT7 promoter. kb represents the dissociation rate constant with DexBig. ka represents the association rate constant with Dex-Big.
13
Figure S7: CFP expression levels at different crowding densities
a. Temporal dynamics of CFP with increasing densities of Dex-Big. Increasing densities
(g/vol) of Dex-Big increased CFP expression monotonically.
b. CFP expression rates were quantified using results from (A).
c. Western blots of synthesized CFP using extracts with three different crowding densities.
The results show that the increased CFP fluorescence was indeed due to the increased
concentrations of CFP.
Figure S8: Control of gene expression rates using either alternative crowding molecules or
genetic components
a. Normalized CFP expression rates at increasing densities of three crowding agents.
Alternative crowding agents yielded similar qualitative results as dextran. We tested
Ficoll-400 (400x103g/mol), PEG-100k (100x103g/mol), and PEG-8k (8x103g/mol) as
alternative crowding molecules to confirm that the observed effects were not molecule
specific. Ficoll-400 is approximately the size of Dex-Big and resulted in monotonically
increasing expression rates. In addition, PEG-8k caused biphasic expression rates and
PEG-100k significantly increased gene expression rates when compared to PEG-8000.
CFP expression rates were normalized using the expression rate at the lowest crowding
density. Each error bars indicate one SEM of at least four replicates.
b. CFP expression rates of the three genetic constructs (Fig. 2b). PT7,weak and RBSweak
resulted in lower CFP expression rates when compared to the base module (WT). Each
error bars indicate one SEM of three replicates.
Figure S9: Perturbation of gene expression
a. Simulated results of gene expression using a stochastic model. The highly crowded
environment results in a narrow distribution of fold gene-expression perturbation (red
bars), suggesting that molecular crowding decreases the fluctuation of gene expression
rates due to the perturbation of gene environmental factors. In contrast, the low crowding
14
environment results in significant perturbation of the system (grey bars). Each fold
perturbation was calculated by dividing gene expression rates of the perturbed systems by
the unperturbed systems. See the section “Stochastic model” in SI for detailed model
description.
b. Fold perturbation of CFP expression rates due to perturbation of ammonium acetate.
Increasing densities of Dex-Big increased robustness of gene expression towards the
perturbation. Each error bars indicate one SEM of four replicates.
Figure S10: Perturbation of the negative feedback circuit
a. CFP expression rates with increasing crowding densities. The addition of pT7-RFP
plasmids did not cause biphasic gene expression rates with increasing crowding densities.
The results suggest that both the addition of plasmids and an increased metabolic burden
were not the underlying reasons of the biphasic gene expression rates observed using the
negative feedback circuit.
b. Gene expression rates with increasing crowding densities. With less T7 RNAP, both
modeling (black line) and experiment (black squares) results show that the system
generated biphasic gene expression rates with increasing crowding densities. The peak
CFP expression rate occurred at 8% Dex-Big. Each error bars indicate one SEM of three
replicates.
Figure S11: The construction of artificial cells
a. Schematic of the artificial-cell construction. A phospholipid solution was vacuum-dried
to yield a thin lipid film. Next, the lipid film was hydrated with deionized water. After an
overnight incubation, liposomes were formed. The liposomes were stored at -80oC and
then lyophilized. The lyophilized liposomes were then hydrated with S12 reaction mix to
form artificial cells.
b. A phase image of liposomes before lyophilization.
15
c. A composite fluorescence image of liposomes that were lyophilized and then hydrated
with water containing sulforhodamine 101. The green channel represents the phase image.
The red channel represents the red fluorescence image.
Figure S12: GFP expression levels inside artificial cells
a. GFP expression in cell-free systems with different [RNAse]. 0.1g/ml RNAse
completely inhibited GFP expression.
b. Distributions of Cy5 inside liposomes. Liposomes were hydrated using S12 reaction mix
and Cy5. The Cy5 distribution indicated that Cy5 was indeed encapsulated inside
liposomes (black curve). Cy5 levels were used as surrogates of liposome volumes.
c. Forward-scattered light data (FSC) of liposomes without Cy5 dye. We did not observe a
correlation between FSC and the intensity of Cy5.
d. FSC of liposomes with Cy5 dye. We observed a positive correlation between FSC and
the intensity of Cy5, suggesting that the intensity of Cy5 was an appropriate subrogate of
liposome volume.
e. Histogram of GFP levels inside artificial cells at four increasing Cy5 levels. Each level
corresponds to the respective Cy5 level in Fig. 4c. Each histogram is plotted using at least
50 data-points.
Supplementary Movie 1: A sample movie of a FRAP experiment
Supplementary Movie 2: A sample movie of T7 RNAP - DNA binding dynamics
16
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