4 A U G U S T 2 0 1 6 | V O L 5 3 6 | N A T U R E | 8 1
LETTER doi:10.1038/nature18930
Synchronized cycles of bacterial lysis for in vivo
delivery
M. Omar Din1
*, Tal Danino2
†*, Arthur Prindle1
, Matt Skalak2
, Jangir Selimkhanov1
, Kaitlin Allen2
, Ellixis Julio1
, Eta Atolia2
,
Lev S. Tsimring3
, Sangeeta N. Bhatia2,4,5,6,7,8
§ & Jeff Hasty1,3,9
§
The widespread view of bacteria as strictly pathogenic has given way
to an appreciation of the prevalence of some beneficial microbes
within the human body1–3
. It is perhaps inevitable that some bacteria
would evolve to preferentially grow in environments that harbour
disease and thus provide a natural platform for the development of
engineered therapies4–6
. Such therapies could benefit from bacteria
that are programmed to limit bacterial growth while continually
producing and releasing cytotoxic agents in situ7–10
. Here we
engineer a clinically relevant bacterium to lyse synchronously at
a threshold population density and to release genetically encoded
cargo. Following quorum lysis, a small number of surviving
bacteria reseed the growing population, thus leading to pulsatile
delivery cycles. We used microfluidic devices to characterize the
engineered lysis strain and we demonstrate its potential as a drug
delivery platform via co-culture with human cancer cells in vitro. As
a proof of principle, we tracked the bacterial population dynamics
in ectopic syngeneic colorectal tumours in mice via a luminescent
reporter. The lysis strain exhibits pulsatile population dynamics
in vivo, with mean bacterial luminescence that remained two orders
of magnitude lower than an unmodified strain. Finally, guided by
previous findings that certain bacteria can enhance the efficacy of
standard therapies11
, we orally administered the lysis strain alone
or in combination with a clinical chemotherapeutic to a syngeneic
mouse transplantation model of hepatic colorectal metastases. We
found that the combination of both circuit-engineered bacteria
and chemotherapy leads to a notable reduction of tumour activity
along with a marked survival benefit over either therapy alone.
Our approach establishes a methodology for leveraging the tools
of synthetic biology to exploit the natural propensity for certain
bacteria to colonize disease sites.
In order to control population levels and facilitate drug delivery using
bacteria, we engineered a synchronized lysis circuit (SLC) using coupled
positive and negative feedback loops that have previously been
used to generate robust oscillatory dynamics12,13
. The circuit (Fig. 1a)
consists of a common promoter that drives expression of both its own
activator (positive feedback) and a lysis gene (negative feedback).
Specifically, the luxI promoter regulates production of autoinducer
(AHL), which binds LuxR and enables it to transcriptionally activate
the promoter. Negative feedback arises from cell death that is triggered
by a bacteriophage lysis gene (ϕX174 E) which is also under control of
the luxI promoter13–15
. AHL can diffuse to neighbouring cells and thus
provides an intercellular synchronization mechanism.
The bacterial population dynamics arising from the synchronized
lysis circuit can be conceptualized as a slow build-up of the signalling
molecule (AHL) to a threshold level, followed by a lysis event that
rapidly prunes the population and enables the release of bacterial contents
(Fig. 1b). After lysis, a small number of remaining bacteria begin
to produce AHL anew, allowing the ‘integrate and fire’ process to be
repeated in a cyclical fashion. We used microfluidic devices to observe
growth and lysis with the fluorescent protein superfolder GFP (sfGFP)
as a proxy for circuit dynamics in attenuated Salmonella enterica subsp.
enterica serovar Typhimurium (Supplementary Videos 1 and 2). We
observed periodic lysis events characterized by peaks in the fluorescent
reporter expression that correspond to population lysis (Fig. 1c). The
fraction of lysed cells remains consistent across subsequent cycles, suggesting
that lysis and survival occur in a stochastic manner (Extended
1
Department of Bioengineering, University of California, San Diego, La Jolla, California 92093, USA. 2
Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge,
Massachusetts 02139, USA. 3
BioCircuits Institute, University of California, San Diego, La Jolla, California 92093, USA. 4
Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02139, USA.
5
Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts 02139, USA. 6
Electrical Engineering and Computer Science and David H. Koch Institute for Integrative Cancer
Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 7
Marble Center for Cancer Nanomedicine and Ludwig Center for Molecular Oncology, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, USA. 8
Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA. 9
Molecular Biology Section, Division of Biological Science,
University of California, San Diego, La Jolla, California 92093, USA. †Present address: Department of Biomedical Engineering, Columbia University, New York, New York 10027, USA.
*These authors contributed equally to this work.
§​These authors jointly supervised this work.
c
a b
AHL
LuxR-AHL
Therapeutic
hlyE
X174E
sfGFP
luxI
Reporter
LysisActivator
0 15 20105
0
1,000
2,000
3,000
0
1,000
2,000
3,000
Fluorescence(a.u.)
Bacteria
Time (h)
d
36 37 38 39 40
Period(h)
Temperature (°C)
Velocity (μm s–1)
5
4
3
2
1
80 100 120 140 160 180 200
Growth Quorum threshold Synchronized lysis
10 μm
22 min 94 min60 min
Figure 1 | Construction and characterization of the SLC. a, The circuit
contains an activator13
and lysis plasmid. When the population reaches
the quorum threshold at a critical AHL concentration, the luxI promoter
drives the transcription of gene E for lysis, luxI, and sfGFP or luxCDABE
as the reporter module. The luxI or the tac promoter also drives the
transcription of the therapeutic gene for the stabilized circuit used in vivo.
LuxR in this system is driven by the native luxR promoter. b, The main
stages of each lysis cycle from seeding to quorum ‘firing’. Shown below
the schematic depictions are typical time series images of the circuitharbouring
cells undergoing the three main stages of quorum firing in
a microfluidic growth chamber12
. c, Fluorescence profile of a typical
microfludic experiment. The estimated cell population trajectory
reveals that lysis events correspond to peaks of sfGFP fluorescence.
d, Period as a function of estimated flow velocity in the media channel
of the microfluidic device and environmental temperature. Error bars
indicate ±​ 1 s.d. for 13–50 peaks. These experiments were performed with
strain 1, see Supplementary Information for complete strain information.
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8 2 | N A T U R E | V O L 5 3 6 | 4 A U G U S T 2 0 1 6
LETTERRESEARCH
Data Fig. 1a, b). Given the ultimate goal of implementation in an
in vivo microenvironment characterized by variable growth conditions,
we tested a range of incubation temperatures (36 °C to 40 °C) and perfusion
rates (100 μ​m s−1
to 200 μ​m s−1
), measuring an average period of
3 h across all conditions (Fig. 1d). These findings demonstrate that the
SLC has the capacity to generate robust cycles of bacterial lysis in our
microfluidic devices across a spectrum of environmental fluctuations
that is likely to exist in an in vivo context.
The emergence of bacterial therapies in synthetic biology has accentuated
the need for predictive modelling. This need stems from a bottleneck
created by a difference in the timescales for bacterial cloning
versus animal experiments; the circuits required for candidate therapies
can be created much faster than they can be tested in vivo. Therefore,
in order to quantitatively characterize the SLC concept before ­testing
in animal models, we developed a computational model (Fig. 2a and
Supplementary Information) to define an optimal strategy for subsequent
testing in a lower-throughput animal model setting. We found
that high production and degradation rates of the feedback-­controlling
proteins resulted in a wider domain of oscillatory ­dynamics in the
parameter space (Fig. 2b). This model is consistent with our observations
that oscillations in S. Typhimurium were more robust than
in Escherichia coli, in which rates of protein production and degradation
were previously found to be lower16
(Extended Data Fig. 1c and
Supplementary Video 3). As the ability to manipulate circuit behaviour
enhances the versatility of the system, we explored the tunability of
the lysis period by adding an ssrA degradation tagging sequence on
the LuxI protein. Consistent with model predictions, we observed an
increased period and colony firing amplitude when tracking bacterial
population dynamics (Fig. 2c, d and Extended Data Fig. 1d). The SLC
thus enables tuning of the period and magnitude of delivery, which will
be necessary for eventual application of this platform in the complex
and fluctuating conditions present in vivo.
To incorporate a cytotoxic payload into the SLC strain, we added
expression of Haemolysin E, encoded by hlyE of E. coli, which has been
tested as a pore-forming anti-tumour toxin17
. We initially confirmed
the capability of the circuit to release intracellular contents by visualizing
released sfGFP with a small microfluidic sink located beneath the
growth chamber (Extended Data Fig. 2a–c). Then to visualize bacterial
lysis and killing of cancer cells in vitro via HlyE, we engineered a
microfluidic device so that cancer cells adhere inside a growth channel
that is flanked by smaller bacterial growth chambers, which permits
simultaneous single-cell visualization of bacterial lysis and cancer cell
death (Extended Data Fig. 2d). After co-culturing human cervical
cancer HeLa cells with S. Typhimurium harbouring the SLC circuit,
we observed HeLa cell death upon the onset of bacterial lysis, indicating
efficient toxin release (Fig. 3a, b and Supplementary Videos 4 and 5).
Complete cell death occurred in the growth channel within ∼​111 min
of initial sfGFP fluorescence (Fig. 3c). Thus, the SLC bacteria were
capable of releasing HlyE at levels necessary to kill tumour-derived
cells.
We assessed the toxicity of released SLC or control bacterial contents
in batch culture. As anticipated, we found that HeLa cells exposed to
supernatant from a culture of the SLC bacteria bearing the hlyE module
exhibited almost complete loss of viability (Fig. 3d), whereas the viability
of HeLa cells exposed to supernatants of bacteria bearing the hlyE
module without the SLC and equivalent dose of non-payload bearing
SLC bacteria were only slightly affected (∼​15%). We concluded that
bacterial lysis allowed for efficient HlyE release in vitro and that natural
intracellular bacterial contents do not significantly affect HeLa cell
viability. We further investigated the delivery characteristics of the SLC
bacteria with hlyE by seeding variable amounts of circuit-harbouring
bacteria with HeLa cultures in well plates. We observed that the time to
HeLa cell death following initial seeding increased with lower bacterial
seeding volumes, presumably resulting from the extended time needed
for bacteria to reach the quorum threshold (Fig. 3e and Supplementary
Video 6). Initial seeding with a larger volume of bacteria resulted in
increased firing rates which corresponded to shorter HlyE exposure
times until cell death, consistent with a greater magnitude of lysis and
payload release, although the cumulative toxicity threshold appears to
be similar in all cases (Fig. 3f). On the basis of these observations, the
seeding size of the bacterial population can be adjusted to determine
the initial timing and release characteristics of the circuit.
We used a luciferase reporter to monitor bacterial population
dynamics in grafted syngeneic colorectal tumours in mice. To minimize
the extent of plasmid loss in the absence of antibiotic selection in vivo,
we incorporated previously described stabilizing elements for plasmid
retention and segregation into the SLC strain18–22
. Additionally, we
placed both the payload and luxCDABE genes (the in vivo reporter
module) under the luxI promoter as an indicator of hlyE production
and quorum firing via bacterial luminescence (Fig. 1a). Using a subcutaneous
model of colorectal cancer (MC26 cell line) in immunocompetent
mice, we intratumorally injected a strain of SLC bacteria
(SLC-hly). We observed pulsatile bacterial population dynamics
within the tumour (Fig. 4a–c and Extended Data Fig. 3a, b) using
in vivo imaging technology23
, consistent with the design and in vitro
characterization (Fig. 2). The end luminescence intensity was on
Figure 2 | Computational modelling and
tunability. a, The model consists of intracellular
variables (lysis protein E and LuxI concentrations)
and extracellular variables (colony size and AHL
concentrations). A time series of colony size
(black), colony AHL (blue), intracellular LuxI
(green) and lysis protein concentrations (red) are
shown on the right. b, The region in the model
parameter space for ClpXP-mediated degradation
(see Supplementary Information) and flow where
the model output is oscillatory increases with
higher production and degradation terms.
c, Results from the computational model
showing the ability to tune the oscillatory period
by varying ClpXP mediated degradation of LuxI.
d, Fluorescence profiles showing lysis oscillations
for LuxI ssrA (black, strain 2) and LuxI non-ssrA
(blue, strain 1) tagged versions of the circuit. See
Supplementary Information for complete model
information.
a b
dc
6,000
Fluorescence(a.u.)
Time (h)
4,000
2,000
0
0 5 10 15 20
– ssrA tag
+ ssrA tag
Lysis LuxI
Colony AHL
Period(min)
ClpXP degradation (a.u.)
0 4 8 12 16
50
60
70
80
Time (min)
Fluorescence(a.u.)
0 50 100 150 200
0
5
10
15
Oscillatory
region
1.5×
2.0×
Increasing
production
and degradation
0.1 3010 20
30
20
10
0.1
Flow rate (a.u.)
ClpXPdegradation(a.u.)
Concentration(a.u.)
Time (h)
Extracellular variables
0 4 8 12 16 20
10–1
101
10–1
100
Intracellular variables
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4 A U G U S T 2 0 1 6 | V O L 5 3 6 | N A T U R E | 8 3
LETTER RESEARCH
Figure 3 | In vitro co-culture. a, Schematic of
the microfluidic co-culture with cancer cells and
bacteria. Fluidic resistance was modified in this
chip to achieve stable near-stagnant flow reduction
to allow for cancer cell adherence and for diffusion
of released therapeutic from the trap to the channel
(see Supplementary Information). b, Frames from
the co-culture time series sequentially visualizing
S. Typhimurium (strain 3) firing, lysis and HeLa
cell death. c, Fluorescent profile of the bacteria and
HeLa cell viability fraction (number of live cells /
number of dead cells in image frames) from
b with time. d, Percentage viability of HeLa cells
co-cultured with supernatant from S. Typhimurium
culture harbouring the SLC +​HlyE (strain 4), the
SLC only (strain 5), constitutive hlyE only (strain 6),
or no plasmid (strain 7). Error bars indicate ±​ 1 s.e.
averaged over three measurements. e, Fluorescence
profile of the SLC +​HlyE (strain 4) co-cultured
with HeLa cells at various initial seeding densities.
The x symbols on the graph mark the point of
complete HeLa cell death. f, The toxin exposure
time, measured from the initial presence of
fluorescence to HeLa cell death, as a function of the
sfGFP production rate (see example in e). Although
the time to death depends on seeding, the total
magnitude of exposure remains conserved (inset).
Error bars indicate ±​ 1 s.e. for three measurements.
See Supplementary Information for ELH1301 host
strain information.
20 μm
Media flow
Cancer cell
growth channel
Bacterial growth
chamber
f
a b
c d
e
Time (min)
Fluorescence(a.u.)
4,000
Viabilityfraction
3,000
2,000
1,000
0
0 20 40 60 80 100 120
1
0.75
0.5
0.25
0
Time (min)
Fluorescence(a.u.)
0.5 μl
1 μl
3 μl
6 μl
10 μl
X
XX
X
Firing rate
d(a.u.)/dt
X
Exposure
magnitude
(a.u. min)Exposure time
1,500
1,000
500
0
0 100 200 300 400 500
Firing rate (d(a.u.)/dt)
Bacterial seed (μl)
0 5 10 15 20 25 30
0
5
10
15 (× 104)
Exposure
magnitude
(a.u.min)
Exposuretime(min)
400
300
200
100
0
0 5 10 15 20 25 30
0
min
39
min
183
min
Lysis:
Therapeutic:
+
–+
+
+
–
–
–
Percentageviability
100
80
60
40
20
0
Figure 4 | In vivo bacterial dynamics, effect on tumours and tolerability
in a subcutaneous tumour model. a, In vivo imaging over time of a
mouse bearing two hind flank tumours injected once with the stabilized
SLC-hly strain (strain 8). b, Single tumour density map trajectories of
bacterial luminescence (relative to luminescence at 0 h) for the SLC-hly
strain (strain 8). Data for each axis represents separate experiments.
c, Single tumour density map trajectories of bacterial luminescence for
the genomically integrated constitutively luminescent strain (strain 9).
Intratumoral injection resulted in over 35-fold higher post-injection
luminescence compared to intravenous injection (Extended Data Fig. 3d).
d, Average relative tumour volume over time for subcutaneous tumour
bearing mice injected with SLC-hly (red, strain 10), SLC-cdd (green, strain
14), SLC-ccl21 (blue, strain 15), and all together (SLC-3) (black). Bacteria
were injected intratumorally on days 0, 2, 6, 8, and 10 (black arrows)
(*​*​*​*​P <​ 0.0001, two-way ANOVA with Bonferroni post-test, n =​ 14–17
tumours, error bars show s.e.). e, Average relative tumour volume over
time for mice with subcutaneous tumours injected with the SLC-3 strains
(black, strains 10, 14 and 15) and the no-plasmid control (magenta, strain 7).
Bacteria were injected intratumorally on days 0, 2, 6, and 10 (black arrows)
(*​*​*​*​P <​ 0.0001, two-way ANOVA with Bonferroni post-test, n =​ 18–19
tumours, error bars represent s.e.). f, Average relative body weight over
time for mice with subcutaneous tumours injected with the SLC-3 strains
(black, strain 10, 14, and 15) and the no-plasmid control (magenta,
strain 7). Bacteria were injected intratumorally on days 0, 2, 6, and 10
(black arrows) (n =​ 10 mice for both cases, error bars represent s.e.).
g, Average relative body weight over time for subcutaneous tumourbearing
mice with a single intravenous injection of the SLC +​ constitutive
hlyE (turquoise, n =​ 9 mice, strain 11), a non-SLC strain with constitutive
hlyE (orange, n =​ 5 mice, strain 12), or the no-plasmid control strain
(magenta, n =​ 9 mice, strain 7) (*​*​*​P <​ 0.001, two-way ANOVA with
Bonferroni post-test, error bars represent s.e.).
e
b
d
c
0
200
400
600
800
Time (h)
0 29 77
800 14 19 25 39 43 49 55 64 76
2.5 5 20 24 44 47 53 67
Time (h)
0 3020 669 44 52
f g
0 4 8 12
0.8
0.85
0.9
0.95
1.0
1.05
Time (days)
Relativebodyweight(a.u.)
No plasmid
Const haemolysin (+synch lysis)
Const
haemolysin
(–synch lysis)
***
49 h 55 h 64 hh52 39 h 43 h19 h14 h0 h 76 h
a
Time (days)
Relativetumourvolume(a.u.)
No plasmid
Triple
therapy
0 4 8 12
0
4
8
12
****
0 4 8 12
0
4
8
12
16
Time (days)
Relativetumourvolume(a.u.)
Pro-apoptotic
peptide
Haemolysin
Chemokine
Triple therapy
****
****
0 4 8 12
0.8
0.85
0.9
0.95
1.0
1.05
Time (days)
Relativebodyweight(a.u.)
No plasmid
Triple therapy
Synchronized lysis circuit Non-lysis control
Intratumoural delivery Systemic delivery
Intratumoural delivery Intratumoural delivery
Intratumoural delivery
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8 4 | N A T U R E | V O L 5 3 6 | 4 A U G U S T 2 0 1 6
LETTERRESEARCH
than unmodified bacteria or non-SLC strains producing constitutive
therapy (Fig. 4g). Although further targeted studies are required to
systematically explore the effect of these bacteria on host health, these
preliminary experiments suggest that the SLC design can reduce the
burden of bacterial injections.
To explore a proof-of-principle for the application of our circuit in
the context of in vivo tumours, we examined the efficacy of our system
in an experimental syngeneic transplantation model of colorectal
metastases within the liver. We had previously established that oral
delivery of these bacterial strains led to safe and efficient colonization
of hepatic colorectal metastases (see Methods), and that mice tolerated
repeated dosing without overt adverse effects (Fig. 5a, b)22
. In
the context of bacteria-based therapeutic candidates, previous studies
have shown that anaerobic bacteria can occupy avascular tumour compartments
where chemotherapy is thought to be ineffective due to poor
drug delivery11
. Thus a synergistic effect may arise when bacteria are
used to deliver drugs to the necrotic core of a tumour, while standard
chemotherapy is used for the vascularized regions11,26
. Inspired by this
paradigm, we tested the combination of SLC-3 bacteria with a common
clinical chemotherapy of 5-fluorouracil (5-FU). Tumours exhibited
similar growth trajectories in response to repeated oral delivery
of either the bacterial therapy alone, or two i.v. doses of 5-FU on day 0
and day 21 (Fig. 5c). In contrast, combination of these two applications
led to a marked decrease in tumour activity over a period of
18 days, followed by a return to growth (Fig. 5d). During the initial
18-day period, a large fraction of the tumours was scored as eliciting at
least a 30% reduction in tumour activity (Fig. 5e). The overall response
led to roughly a 50% increase in the mean survival time for animals
harbouring incurable colorectal metastases (Fig. 5f). Improvements
may arise from strategies for long-term circuit stability or the utilization
of additional therapeutic cargo.
The synchronized lysis circuit exemplifies a methodology for
leveraging the tools of synthetic biology to exploit the ability of certain
bacteria to colonize disease sites. In contrast to most drug delivery strategies,
the synchronized lysis paradigm does not require pre-loading
of a drug or the engineering of additional secretion machinery. In
addition, it has the potential to decrease the likelihood of a systemic
average ∼​300-fold lower than the constitutive control strain, indicating
a significant decrease in bacterial population levels within the tumour
(Extended Data Fig. 3c).
Given the ability to engineer bacterial population dynamics in
tumour grafts, we leveraged the versatility of the SLC bacteria as a
delivery system to compare different classes of previously developed
payloads. In addition to the haemolysin strain that was characterized in
microfluidic devices, we created two additional SLC strains expressing
genes to activate a host immune response (via T-cell and dendritic cell
recruitment, using mouse CCL21) or trigger tumour cell apoptosis
(using the cell death domain of Bit1 fused to the tumour-penetrating
peptide iRGD, or CDD-iRGD)24,25
. Upon intratumoral injection, the
immune recruitment strain elicited the strongest effect on tumour
growth when compared to the haemolysis or apoptotic strains (Fig. 4d).
We observed that an equal mixture of the three strains generated a
stronger response than any single strain (Fig. 4d and Extended Data
Fig. 3e–g), and on this basis we elected to pursue the ‘triple-strain’ dose
for further testing in order to minimize animal usage. In a side-by-side
comparison, we observed that the tumour response to SLC triple-strain
(SLC-3) injections was significantly larger than the response to unmodified
bacteria (Fig. 4e). Upon necropsy, histopathological analysis of
remnant tumours was performed for mice treated with the SLC-3
strains, chemotherapy or unmodified bacteria. In mice treated with
SLC-3 and non-circuit bacterial strains, robust staining of bacteria
was observed by anti-Salmonella antibodies, showing localization of
Salmonella within tumours. TUNEL staining indicated higher levels
of apoptosis and cell death in SLC-3 treated tumours (Extended Data
Fig. 4).
As a first step towards monitoring the effect of bacterial injections
on the host, we compared how the triple-strain system affected body
weight when administered intratumorally and intravenously, as the
administration route affects bacterial localization (Extended Data
Fig. 3d). We found that treatment with the SLC strains generated
the same weight change as unmodified bacteria when administered
intratumorally (Fig. 4f). However, intravenous administration of the
SLC conferred a greater health benefit on the basis of observations
that SLC strains producing constitutive therapy were better tolerated
Figure 5 | In vivo testing in an experimental model of colorectal
metastases in the liver via oral delivery of bacteria. a, Schematic of
the experimental syngeneic transplantation model of hepatic colorectal
metastases in a mouse, with the dosing schedule of either engineered
bacteria (SLC-3) or a common cytotoxic chemotherapeutic, the
antimetabolite 5-FU. The SLC-3 strains were delivered orally. 5-FU was
delivered via intraperitoneal injection. b, Relative body weight over time
for the mice with hepatic colorectal metastases fed with the SLC-3 strains
(blue), injected with 5-FU chemotherapy (red), or a combination of the
two (green). Error bars indicate ±​ 1 s.e. for 5–7 mice. c, Median relative
tumour activity, measured via tumour cell luminescence using in vivo
imaging, for the chemotherapy and SLC-3 cases from b. d, Median relative
tumour activity for the combination therapy case from b. Error bars for
c and d indicate the interquartile ranges for 5–7 mice. The dashed line
marks relative tumour activity of 0.70. e, Fraction of mice from the
cases in b which respond with 30% reduction of tumour activity over
time. f, Fraction survival over time for the mice in b (*​*​P <​ 0.01, log rank
test; n =​ 5–7 mice).
a b
Time (days)
Bacteria
5-FU
04030201 050
Combination therapy
e f
c
d
100
102
104
Time (days)
Mediantumour
activity(a.u.)
10–1
100
101
0 10 20 30 40 0 10 20 30 40
0 10 200 10 20 30 40
0 20 40 60
Time (days)
Mediantumouractivity(a.u.)
0.95
1
1.05
1.1
1.15
Time (days)
Relativebodyweight(a.u.)
NS
0
0.2
0.4
0.6
0.8
1
Time (days)
**
Fractionsurvival
Time (days)
0
0.2
0.4
0.6
0.8
1
Responsefraction
Oral delivery of
bacteria
Chemotherapy
injection
Combination therapy
Triple therapy
Chemotherapy
© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
4 A U G U S T 2 0 1 6 | V O L 5 3 6 | N A T U R E | 8 5
LETTER RESEARCH
inflammatory response through population control; as the bacterial
colony is pruned after each oscillatory lysis event, the design could
mitigate an undesirable host response. The circuit may enable new
bacterial drug delivery strategies through modulation of the frequency
and amplitude of the population cycles over time. Given recent insights
into how host metabolism and circadian function are affected by the
population dynamics of the gut micobiota, cyclical population control
may be a prospective strategy to prevent host disturbances resulting
from aberrant oscillations of gut microbes27,28
. Such engineering
strategies may allow for the development of therapeutic communities
within in vivo environments in which population dynamics are driven
by interacting viruses, bacteria and host immune cells29
.
Online Content Methods, along with any additional Extended Data display items and
Source Data, are available in the online version of the paper; references unique to
these sections appear only in the online paper.
Received 24 January; accepted 13 June 2016.
Published online 20 July 2016.
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Supplementary Information is available in the online version of the paper.
Acknowledgements The UCSD team was supported by the National
Institute of General Medical Sciences of the National Institutes of Health
(R01GM069811) and the San Diego Center for Systems Biology (P50
GM085764). The MIT team was supported by a Koch Institute Support Grant
(P30-CA14051) from the National Cancer Institute (Swanson Biotechnology
Center), a Core Center Grant (P30-ES002109) from the National Institute of
Environmental Health Sciences, the Ludwig Center for Molecular Oncology at
MIT and an Amar G. Bose Research Grant. T.D. was supported by the Misrock
Postdoctoral fellowship and the NIH Pathway to Independence Award NIH
(K99 CA197649-01). A.P. was supported by the Department of Defense
National Defense Science and Engineering Graduate Fellowship and holds a
Simons Foundation Fellowship of the Helen Hay Whitney Foundation and a
Career Award at the Scientific Interface from the Burroughs Wellcome Fund.
S.N.B. is an HHMI Investigator. We would like to thank R. Johnson for help
with constructing microfluidic devices, H. Fleming for help with editing the
manuscript, and H. Ding of The Barbara K. Ostrom (1978) Bioinformatics and
Computing Facility in the Swanson Biotechnology Center for help with the
statistical tests carried out in this study. We would also like to thank L. You for
providing the lysis gene used in this study.
Author Contributions M.O.D. and J.H. designed the synchronized lysis circuit.
M.O.D., J.S., L.S.T. and J.H. developed the computational model. M.O.D. and
A.P. built and tested the bacterial circuit in microfluidics and performed the
co-culture experiments. M.O.D. and E.J. collected the viability data, and M.O.D.
and J.H. analysed the bacterial circuit data. T.D., M.S., K.A., and E.A. designed
and performed the in vivo experiments. M.O.D., T.D., A.P., S.N.B., and J.H.
analysed the animal data, and wrote and edited the manuscript.
Author Information Reprints and permissions information is available at
www.nature.com/reprints. The authors declare no competing financial
interests. Readers are welcome to comment on the online version of the
paper. Correspondence and requests for materials should be addressed to
J.H. (jhasty@eng.ucsd.edu).
Reviewer Information Nature thanks R. Solé, B. Vogelstein and the other
anonymous reviewer(s) for their contribution to the peer review of this work.
© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
LETTERRESEARCH
30.	 Soares, K. C. et al. A preclinical murine model of hepatic metastases. JoVE
e51677 (2014).
METHODS
Strains and plasmids. Our circuit strains were cultured in LB media with
50 μ​g ml−1
and 34 μ​g ml−1
of kanamycin and chloramphenicol respectively,
along with 0.2% glucose, in a 37 °C incubator. Mammalian cells (HeLa CCL-2
from ATCC, verified by third-party cell line authentication services using an STR
­multiplex system) were cultured in DMEM media supplemented with 10% fetal
bovine serum and 1% penicillin/streptomycin (CellGro 30-002-CI), placed inside a
tissue culture incubator at 37 °C maintained at 5% CO2. Plasmids were constructed
using the CPEC method of cloning or using standard restriction digest/ligation
cloning. The activator plasmid (Kan, ColE1) was used in previous work from our
group, and the lysis plasmid was constructed by taking the lysis gene, E, from the
ePop plasmid via PCR and cloning it into a vector (Chlor, p15A) under the control
of the luxI promoter13,15
. The hlyE gene was obtained via PCR from the genomic
DNA of MG1655, while mouse CCL21 and CDD-iRGD were synthesized. These
genes were cloned into the lysis plasmid, under the control of either the tac or luxI
promoters (Extended Data Fig. 5). Co-culturing was performed with HeLa cells
and either motile or non-motile S. Typhimurium, SL1344 (Extended Data Table 1).
For full strain and plasmid information, please refer to the Supplementary
Information.
Microfluidics and microscopy. The microfluidic devices and experiment preparation
protocols used in this study are similar to those previously reported from our
group13
. The bacteria growth chambers were 100 ×​ 100 μ​m in area and approximately
1.4 μ​m in height. For co-culture experiments on the chip, we first loaded a
suspended culture of HeLa cells in the device media channels at very low flow rates,
to allow for adherence, and then incubated the device in a tissue culture incubator
for 0.5–2 days to allow for proliferation. On the day of the experiment, the device
was transferred to the microscope and circuit-containing bacteria were loaded in
the growth chambers before imaging. Acquisition of images was performed with
a Nikon TI2 using a Photometrics CoolSnap cooled CCD camera. The scope and
accessories were programmed using the Nikon Elements software.
Co-cultures for well plate experiments were performed in Falcon 96-well tissue
culture plates. HeLa cells were allowed to adhere to the wells before the addition
of bacteria and subsequent imaging under the microscope or measurement in a
TECAN Infinite M200 Pro plate reader. For viability measurements using an MTT
assay, there were two technical replicates per well. For fluorescence measurements
of co-cultures with variable seeding densities of bacteria, there were three technical
replicates per case.
Additional details on microfluidics and microscopy can be found in the
Supplementary Information.
In vivo experiments. All animal work was approved by the committee on animal
care (MIT, protocol 0414-022-17). The protocol requires ­animals to be euthanized
when tumors reach 2 cm3
, or under veterinary staff ­recommendation. The cell line
(MC26-LucF, Tanabe laboratory, Massachusetts General Hospital) was obtained
from, and authenticated by, the Tanabe laboratory, MGH. The cell line was tested
several times to be mycoplasma-free before implantation in mice. Sample sizes for
mice were determined by expected effect size to produce a power of 0.8–0.9. Mice
were blindly randomized into various groups using a random number generator.
Subcutaneous tumour model. Animal experiments were performed on 6-week-old
female BALB/c mice (Taconic Biosciences) with bilateral subcutaneous hind flank
tumours from an implanted mouse colon cancer cell line. The concentration for
implantation of the tumour cells was 108
cells per ml in DMEM (no phenol red).
Cells were then implanted subcutaneously at a volume of 100 μ​l per flank, with
each implant consisting of 107
cells. Tumours were typically grown to an average
of 300 mm3
before experiments.
Experimental liver metastasis model. The experimental metastasis model was
generated by injecting luciferase-producing mouse cancer cells into surgically
externalized spleens of immunocompetent mice. Tumour cells seeded the liver during
90 s, after which the spleen was removed to prevent ectopic tumour growth30
.
The MC26-LucF cell line was used (Tanabe Laboratory, MGH) and injected at
5 ×​ 104
cells per 100 μ​l PBS into the spleens of female BALB/c mice at 6 weeks of
age (Taconic Biosciences.). For the liver metastasis model, tumours were grown
for 5–7 days to an average total tumour burden of 143 mm3
before experiments.
Bacterial growth and administration. Bacterial strains were grown overnight in
LB media containing appropriate antibiotics and 0.2% glucose as for the in vitro
experiments. A 1:100×​dilution in fresh media with antibiotics was started the day
of injection and grown until an OD <​0.1 to prevent bacteria from reaching the
quorum threshold (for SLC specifically). Bacteria were spun down and washed 2
to 3 times with sterile PBS before injection into mice. Intratumoural injections of
bacteria were performed at a concentration of 5 ×​ 107
cells per ml in PBS with a
total volume of 10–20 μ​l injected per tumour, while intravenous injections were
given at a total volume of 100 μ​l. For the SLC-3 strains injection, this final volume
was equally divided between the three strains at the indicated density. For liver
metastasis experiments, bacteria were grown in LB media containing appropriate
antibiotics and 0.2% glucose until they reached an OD of 0.05, after which they
were concentrated to 109
to 5 ×​ 109
bacteria per ml and delivered via oral gavage.
Post-administration monitoring for subcutaneous liver metastasis models.
Luminescent signal was measured with the IVIS spectrum in vivo imaging system
following bacterial injection. Measurements were compared relative to pre-injection
values to follow dynamics. Subcutaneous tumour volume was quantified using calipers
to measure the length, width, and height of each tumour throughout the imaging
course (V =​ L ×​ W ×​ H). Volumes were compared to pre-injection values to follow
physical tumour growth. Survival of mice was measured as the time from the beginning
of the experiment up to the day when mice were moribund and euthanized.
Survival for the experiment in Fig. 4f was measured with two biological replicates.
Statistical analysis. Statistical tests were calculated either in Excel (Student’s
t-test) or GraphPad Prism 5.0 (ANOVA with Bonferroni post-test, log-rank test).
The details of the statistical tests carried out are indicated in the respective figure
legends. Where data were approximately normally distributed, values were compared
using either a Student’s t-test or one-way ANOVA for single variable, or a
two-way ANOVA for two variables. Mice were randomized in different groups
before experiments.
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LETTER RESEARCH
Extended Data Figure 1 | Various properties of the SLC. a, The fraction
and number of bacterial cells cleared per consecutive oscillatory cycle
in the growth chamber for a typical microfluidic experiment for
S. typhimurium, including the effects of lysis and flow of cells outside of
the trap (strain 1). b, Subset of time series images from the experiment in
a showing a portion of the growth chamber where survivors of the initial
lysis event (160 min frame, red outline) produce progeny (250 min frame,
magenta outline) which are lysis sensitive. c, Period as a function of the
environmental temperature for E. coli (strain 13). The circuit does not
oscillate for temperatures above 37 °C in E. coli. Error bars indicate ±​ 1 s.d.
for 12–19 peaks. d, Colony amplitude at quorum firing for increasing
degradation on the LuxI activator protein in the computational model.
These simulation results are supported by batch well-plate experiments
of the LuxI ssrA (black, strain 2) and non-ssrA (blue, strain 1) tagged
versions of the circuit in S. Typhimurium (inset).
© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
LETTERRESEARCH
Extended Data Figure 2 | Investigating lysis-mediated intracellular
release. a, A bacterial growth chamber with a 0.4 μ​m high sink for
sfGFP visualization after release. b, Number of bacteria (red), bacterial
fluorescence (blue), sink fluorescence (pink) for a typical oscillatory
cycle (strain 1). c, Fluorescence time series images of the microfluidic sink
from b. d, General procedure for performing bacterial and cancer cell
co-culture experiments in a microfluidic device (also see Supplementary
Information).
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LETTER RESEARCH
Extended Data Figure 3 | In vivo expression and therapy testing.
a, End-point in vitro luminescence intensity for SLC strains after ∼​20 h
of growth. Host strains A and B are the host bacteria for strains 8 and 10.
They are ELH1301 and ELH 430, respectively. Host A exhibits around
twofold higher luminescence with the same circuit than host B. b, In vivo
imaging over time of a mouse bearing subcutaneous tumours injected with
a genomically integrated constitutively luminescent strain (strain 9).
c, End-point in vivo bacterial luminescence of the SLC-hly strain and the
constitutively luminescent strain from the experiments presented in Fig. 4.
Error bars represent the s.e.m. bacterial luminescence from 9 tumours.
d, Post-injection in vivo bacterial luminescence for the constitutively
luminescent strain administered intravenously (vein) or intratumorally
(tumour). Luminescence was measured ∼​20 h post-injection. Error bars
represent s.e.m. bacterial luminescence from 6 and 9 tumours for the
intravenous and intratumoural cases, respectively. e, Average relative
tumour volume over time for subcutaneous tumour bearing mice injected
with the no-plasmid bacterium (strain 7), 5-FU chemotherapy, the SLC-3
strains, and the combination of SLC-3 with chemotherapy. Bacteria
were injected intratumorally on days 0, 4, and 7 (black arrows), and
chemotherapy was administered on days 2 and 9 (red arrows) (*​P <​ 0.05,
*​*​*​*​P <​ 0.0001, two-way ANOVA with Bonferroni post-test, n =​ 12–16
tumours, error bars represent s.e.). f, Fraction of mice from the cases
in e which respond with 30% reduction of tumour volume over time.
g, Fraction survival over time for mice with hepatic colorectal metastases
fed with either the SLC-3 strains (blue) or the no-plasmid control (black)
(*​P <​ 0.05, log rank test; n =​ 11–12 mice).
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LETTERRESEARCH
Extended Data Figure 4 | Histological analysis of tumour sections.
a, Histology of tumour sections taken from mice with different treatments
3 days post-administration. Haematoxylin and eosin staining for tissue
sections intravenously injected with a combination of therapeutic bacteria
(SLC-3), chemotherapy (5-FU), or a bacteria control with no therapeutic
(strain 7) (i); TUNEL staining (red) in the same sections indicating cell
apoptosis (ii); Salmonella immunohistochemistry (red) in the same
sections confirming presence of bacteria in tumours (iii). Scale bars for
(i–iii) denote 50 μ​m. TUNEL (iv) and Salmonella (v) staining (red) in
the entire tumour sections (examples indicated by arrows). Scale bars
for iv and v denote 100 μ​m. DAPI staining (blue) was used to obtain a
measure of live and dead cells in ii–iv. Histology slices (n =​ 6) from 20×​
images were compared across the groups and mean intensity of TUNEL
staining, normalized by sample area, was demonstrated to be significantly
higher for SLC-3 compared to the other two groups (P <​ 0.0001, one-way
ANOVA), and not significantly different between the chemotherapy and
bacteria-only cases.
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LETTER RESEARCH
Extended Data Figure 5 | The main plasmids used in this study. See Supplementary Information for more details.
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LETTERRESEARCH
Extended Data Table 1 | A list of strains and respective plasmids used in this study
See Supplementary Information for more details.
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