Alexander R French1,1, Alexander L Tesmer1,1, Mathew Tantama1,1,2. 1. Department of Chemistry and Institute for Integrated Neuroscience, Purdue University, West Lafayette, Indiana 47907, United States. 2. Department of Chemistry, Wellesley College, Wellesley, Massachusetts 02481, United States.
Abstract
Genetically encoded fluorescent and luminescent indicators have revolutionized our ability to monitor physiology in real time, but the separate development of new sensors for each of these imaging modalities involves substantial effort and resources. Methods to rapidly engineer multimodal sensors would, therefore, significantly accelerate the diversification of sensors for simultaneous use in different systems and applications. We hypothesized that the enhanced Nano-lanterns could be incorporated into modular ratiometric sensors as an efficient approach to creating dual-mode fluorescent-luminescent sensors. As a proof-of-concept, we engineered an Epac1-based sensor that responds to cyclic adenosine monophosphate binding with a greater than 80% change in both Förster Resonance Energy Transfer and bioluminescent resonance energy transfer (BRET) modes. We also demonstrate that our new sensor reports cellular changes in G-protein-coupled signaling, and that the ratiometric BRET mode is bright enough for subcutaneous measurements in mice.
Genetically encoded fluorescent and luminescent indicators have revolutionized our ability to monitor physiology in real time, but the separate development of new sensors for each of these imaging modalities involves substantial effort and resources. Methods to rapidly engineer multimodal sensors would, therefore, significantly accelerate the diversification of sensors for simultaneous use in different systems and applications. We hypothesized that the enhanced Nano-lanterns could be incorporated into modular ratiometric sensors as an efficient approach to creating dual-mode fluorescent-luminescent sensors. As a proof-of-concept, we engineered an Epac1-based sensor that responds to cyclic adenosine monophosphate binding with a greater than 80% change in both Förster Resonance Energy Transfer and bioluminescent resonance energy transfer (BRET) modes. We also demonstrate that our new sensor reports cellular changes in G-protein-coupled signaling, and that the ratiometric BRET mode is bright enough for subcutaneous measurements in mice.
Genetically encoded
indicators (GEIs) have been engineered to sense
a diverse array of cellular signals by converting a change in the
target molecule concentration to a change in the fluorescent or bioluminescent
properties of the GEI.[1,2] These sensors confer a large spatiotemporal
advantage over previous techniques for interrogating molecular signaling
events since they can read out dynamics in real time in genetically
targeted cell types and subcellular compartments. GEIs, thus, enable
the study of these molecules from specific contexts in vivo to subcellular
signaling microdomains in vitro.[1,2]A common GEI design
strategy is to fuse a pair of resonance energy
transfer (RET)-compatible proteins across the termini of a protein
that naturally binds the molecule of interest.[1,3] Upon
binding the target molecule, the protein undergoes a conformational
change that alters either the distance or orientation of the RET pair
with respect to each other, changing the RET efficiency, and, therefore,
the light output of the RET pair. This approach has the advantage
that the ratio of the donor and acceptor emissions provides a metric
for the target molecule concentration that is independent of the sensor
expression level.Given the significant effort required to engineer
new GEIs, we
sought a method for rapidly improving existing sensors and extending
their use to new systems. For example, fluorescence-based sensors
have found extensive application in examining subcellular signaling
mechanisms in vitro, but in vivo their application is limited to use
in surface tissues due to the requirement for multiphoton excitation.[1,2] Similarly, bioluminescence-based sensors have been successfully
applied toward in vitro drug screening for their low background,[4,5] but their application in vivo is limited by the low light emission
from traditional luciferases.[6] NanoLuc,
a new, exceptionally bright shrimp luciferase, has the potential to
overcome this limitation for luminescent sensors in vivo.[6,7] However, despite having spectral properties similar to other luciferases,
its incorporation into existing sensors is not always straightforward.[8]One advancement that may aid the incorporation
of NanoLuc into
sensors is the recent development of “Enhanced Nano-lanterns”
(eNLs).[9] eNLs are engineered protein fusions
between NanoLuc and one of several fluorescent proteins (FPs) in such
a way that NanoLuc undergoes constitutive bioluminescent RET (BRET)
with the FP.[9] These constructs, therefore,
red-shift NanoLuc emission from the autoluminescence of its substrate,
further reducing the background signal, and several eNLs have a brightness
greater than NanoLuc alone. Since the eNL maintains the fluorescent
capabilities of the original FP, we reasoned that incorporating eNLs
into existing Förster resonance energy transfer (FRET) sensor
designs could be an effective method for rapidly generating dual-mode
sensors capable of FRET- and BRET-based reporting. These sensors would,
therefore, overcome the brightness limitations of in vivo bioluminescence
studies while retaining FRET capabilities for use in subcellular studies
on traditional fluorescence microscopes.As a proof-of-concept,
we chose to engineer an eNL-based FRET–BRET
cyclic adenosine monophosphate (cAMP) sensor because of the central
importance of cAMP as a second messenger of G-protein signaling following
G-protein-coupled receptor (GPCR) activation.[10] The relevance of cAMP dynamics is underscored by previous efforts
to develop fluorescence- and bioluminescence-based sensors for measuring
its dynamics.[11−13] For example, cAMP levels are a preferred metric for
G-protein-dependent signaling in opioid receptors (ORs),[14] and the balance of G-protein dependent to independent
signaling at these receptors has behavioral effects that are guiding
drug development efforts.[15] Thus, creating
a bright dual-mode FRET- and BRET-capable sensor for detecting OR
G-protein signaling that is scalable from in vitro screening to in
vivo mechanism validation could accelerate these efforts.In
this work, we demonstrate that eNLs are capable of modular inclusion
into a previously designed ratiometric cAMP sensor architecture, with
the similar dynamic range as the original sensor. In doing so, we
give a proof-of-concept that eNLs can be used to make dual-mode sensors
capable of operating in either FRET or BRET modes. We show that our
sensor responds to cAMP changes in both modes in intact cells, and
that in the BRET mode, the ratio remains constant even as overall
luminescence decays from the NanoLuc (NL) substrate turnover. Finally,
we show that our sensor is bright enough to ratiometrically report
cAMP through tissue and fur in a mouse.
Results
Design and
Screen for a Ratiometric, Dual-Mode cAMP Sensor
To generate
a dual-mode cAMP sensor, we chose to re-engineer the
FRET-based cAMP sensor, Indicator of cAMP using Epac 3 (ICUE3).[11] ICUE3 is a fusion protein of a fragment of the
cAMP-binding protein, exchange protein activated by cAMP 1 (Epac1),
with CFP and a circularly permuted mVenus at its N- and C-termini,
respectively. Since the FP in each eNL is at its N-terminus, we reasoned
that an efficient approach would be to replace the C-terminal FP in
ICUE3 with an eNL and the N-terminal FP with a RET-compatible red
FP (Figure a). The
molecular “reporting” should, therefore, still primarily
occur from RET between the two FPs on either side of Epac1. Thus,
only one interaction needs to be optimized, whether we supply excitation
energy through the NanoLuc substrate in the BRET mode or we excite
the FP in the eNL directly to operate in the FRET mode. We designed
six constructs (Figure b), testing three alternative bright red fluorescent proteins at
the N-terminus of Epac1 and two RET-compatible eNL variants at its
C-terminus. To directly assess the maximal cAMP response of each construct,
we first measured their cAMP dose–response curves (Figure c,d). Epac1-based
sensors are difficult to purify from bacteria, as they are readily
cleaved in this expression system.[13] Though
Jiang et al.[12] report that purifying their
sensor with a 6xHis tag, we could not replicate their results due
to cleavage at multiple sites between the fluorescent domains, observable
via sodium dodecyl sulfate-polyacrylamide gel electrophoresis gel,
even when using their buffers, protease inhibitors, or a low-temperature
prep. Other groups have successfully measured Epac1-based sensor responses
in the cell lysate and found the resulting EC50 values to be similar
to that of purified protein.[13,16,17] Therefore, we chose to characterize our sensors in the diluted HEK293
cell lysate. We observed that the switch architecture is very robust
to the choice of protein, and nearly every construct responds in at
least one optical detection mode. Interestingly, the maximum percent
change for each construct is not identical for both modes, with many
performing better in the BRET mode than in the FRET mode (Figure e). Since RRvT and
tdTomato are dimers,[18] it may be that the
second FP is able to accept RET in the unbound state in the FRET mode,
but that in the BRET mode, direct RET from NanoLuc to the red FP compensates
for this effect.
Figure 1
Screen for a dual-mode FRET and BRET cAMP sensor. (a)
Diagram showing
how a dual-mode FRET and BRET sensor using eNL could function. Excitation
can be supplied from direct excitation of FP in the eNL to operate
via FRET or through the NanoLuc (NL) bioluminescence in the presence
of furimazine (FZ) to operate via BRET. (b) Constructs screened for
the construction of the sensor. Cyan (CeNL) and green (GeNL) eNLs
incorporate an mTurqoise2 or mNeonGreen, respectively. (c, d) Dose–response
curves of sensors in the HEK cell lysate in FRET (c) and BRET (d)
modes (mean ± σ, n = 3). ‡Measurements at 0 cAMP put at 10–10 M cAMP for
fitting and plotting. (e) Maximum percent change in ratio of each
construct of the fits in (c, d) plotted against each other. The dashed
line is y = x and data is given
as mean ± 95% c.i., n = 3. Construct abbreviations
(see (b) also): S, mScarlet; R, RRvT; T, tdTomato; C, CeNL (mTurquoise2-NL);
G, GeNL (mNeonGreen-NL).[9]
Screen for a dual-mode FRET and BRET cAMP sensor. (a)
Diagram showing
how a dual-mode FRET and BRET sensor using eNL could function. Excitation
can be supplied from direct excitation of FP in the eNL to operate
via FRET or through the NanoLuc (NL) bioluminescence in the presence
of furimazine (FZ) to operate via BRET. (b) Constructs screened for
the construction of the sensor. Cyan (CeNL) and green (GeNL) eNLs
incorporate an mTurqoise2 or mNeonGreen, respectively. (c, d) Dose–response
curves of sensors in the HEK cell lysate in FRET (c) and BRET (d)
modes (mean ± σ, n = 3). ‡Measurements at 0 cAMP put at 10–10 M cAMP for
fitting and plotting. (e) Maximum percent change in ratio of each
construct of the fits in (c, d) plotted against each other. The dashed
line is y = x and data is given
as mean ± 95% c.i., n = 3. Construct abbreviations
(see (b) also): S, mScarlet; R, RRvT; T, tdTomato; C, CeNL (mTurquoise2-NL);
G, GeNL (mNeonGreen-NL).[9]We also observed that although the EC50 values for both modes
are
near the 8.8–12.5 μM published range for Epac1-based
sensors,[12,17] the constructs each had higher EC50 values
in the BRET mode (Supporting Information (SI) Table 1). For example, mScarlet-Epac-GeNL has a mean (95%
c.i.) EC50 of 2.5 (1.64, 3.92) μM in FRET but 19.8 (17.2, 22.8)
μM in BRET (SI Table 1). In the BRET
mode, the NanoLuc must turn over the substrate, setting up a linked
equilibrium with the cAMP-binding reaction that can be affected by
intramolecular interactions within the protein in the cAMP-bound and
-unbound states. The differences in filters and instrumentation between
the measurements may also contribute to the range in EC50 values.
Regardless of these differences, the affinities in either mode are
still well-tuned to detect fluctuations in physiological levels of
cAMP. To evaluate this, we continued the characterization of our highest
performing sensor in cells.Overall, the mScarlet-Epac-GeNL
construct performed best in both
BRET and FRET modes, achieving ∼80% maximum signal change in
each. This is comparable to previous cAMP sensors and is only a 20%
difference from the original ICUE3,[11] confirming
that our approach is an effective method for adding functionality
to FRET-based sensors. Evaluating the fluorescence and bioluminescence
spectra for mScarlet-Epac-GeNL, we observed the expected changes upon
cAMP binding, namely, a decrease in emission from mScarlet at 594
nm and an increase in emission from mNeonGreen at 517 nm (SI, Figure 1). These data together demonstrate that
mScarlet-Epac-GeNL is a dual-mode, ratiometric cAMP sensor.
Live-Cell
Validation of mScarlet-Epac-GeNL
We next
sought to validate the function of both modes of our sensor with live-cell
imaging. In HEK cells stably expressing the κ-opioid receptor
(κOR), the fluorescence emission ratio faithfully increases
in response to forskolin (FSK), a drug that stimulates cAMP production
by directly activating adenylyl cyclase (Figure ). This change is reversed upon addition
of the endogenous κOR agonist dynorphin, which stimulates Gαi
through κOR to inhibit adenylyl cyclase. The maximum change
in cAMP observed using the mScarlet-Epac-GeNL sensor is approximately
44%, comparable to that for ICUE3.[11] This
suggests that inserting the eNL into the ICUE3 architecture largely
preserves the sensor’s FRET capabilities and confirms that
the FP in the eNL is a viable donor for FRET-based reporting of cAMP.
Figure 2
mScarlet-Epac-GeNL
responds to changes in cellular cAMP in the
FRET mode. HEK293 cells stably expressing κ-opioid receptor
(κOR) were transiently transfected with mScarlet-Epac-GeNL and
imaged in the FRET mode. (a) Images of a representative group of cells
showing that cells are healthy and have an even distribution of the
sensor in the cytosol. (b, c) After 5 min, cells were treated with
50 μM forskolin (FSK), which activates adenylyl cyclases and
stimulates cAMP production. After 30 min with FSK, 9 nM dynorphin
(dyn), the endogenous agonist to κOR, was added, leading to
the inhibition of cellular adenylyl cyclase and cellular cAMP returns
to previous levels. (b) Ratio images of HEK293 cells in (a) undergoing
treatment at different time points (scale bar = 10 μm). (c)
Quantification of data (mean ± σ, n =
3) of three independent wells with 20 cells each.
mScarlet-Epac-GeNL
responds to changes in cellular cAMP in the
FRET mode. HEK293 cells stably expressing κ-opioid receptor
(κOR) were transiently transfected with mScarlet-Epac-GeNL and
imaged in the FRET mode. (a) Images of a representative group of cells
showing that cells are healthy and have an even distribution of the
sensor in the cytosol. (b, c) After 5 min, cells were treated with
50 μM forskolin (FSK), which activates adenylyl cyclases and
stimulates cAMP production. After 30 min with FSK, 9 nM dynorphin
(dyn), the endogenous agonist to κOR, was added, leading to
the inhibition of cellular adenylyl cyclase and cellular cAMP returns
to previous levels. (b) Ratio images of HEK293 cells in (a) undergoing
treatment at different time points (scale bar = 10 μm). (c)
Quantification of data (mean ± σ, n =
3) of three independent wells with 20 cells each.We similarly sought to validate the BRET functionality of mScarlet-Epac-GeNL
in living cells. We seeded HEK293A cells in a 96-well plate and imaged
the well population in the presence of the NanoLuc substrate furimazine
using a Spectral Instruments Ami HT animal imager designed for bioluminescence
quantification. We find that the cell population shows a ratiometric
change of approximately 29% in response to adenylyl cyclase stimulation
by FSK (Figure a).
The BRET response is similar to the change seen in the FRET mode (Figure ), validating that
mScarlet-Epac-GeNL can be used as a dual-mode sensor in cells. Importantly,
the ratio of the green-to-red emission holds constant even as the
luminescence signal from both channels decays as furimazine is turned
over by NanoLuc (Figure b). This result underscores the consistency of our ratiometric design
and suggests that this feature will allow for better comparisons between
samples and trials.
Figure 3
mScarlet-Epac-GeNL reports cAMP changes in cells in the
BRET mode.
(a) HEK293A cells seeded into a 96-well plate and transiently transfected
with mScarlet-Epac-GeNL respond to 50 μM forskolin (FSK) addition.
(b) Vehicle (Veh) data in (a) is plotted with the channel intensity
values to show that the ratio remains constant even as intensity drops
dramatically due to consumption of FZ. Traces in both plots normalized
to mean baseline and shaded area for both plots are mean ± σ, n = 3.
mScarlet-Epac-GeNL reports cAMP changes in cells in the
BRET mode.
(a) HEK293A cells seeded into a 96-well plate and transiently transfected
with mScarlet-Epac-GeNL respond to 50 μM forskolin (FSK) addition.
(b) Vehicle (Veh) data in (a) is plotted with the channel intensity
values to show that the ratio remains constant even as intensity drops
dramatically due to consumption of FZ. Traces in both plots normalized
to mean baseline and shaded area for both plots are mean ± σ, n = 3.
Ratiometric cAMP Response
of mScarlet-Epac-GeNL through Mouse
Tissue
After determining that our sensor functions in both
modes in cells, we sought to evaluate the brightness of our sensor
in animal tissues. We injected HEK cell lysate containing mScarlet-Epac-GeNL
corresponding to ∼1200 transfected cells subcutaneously into
the deceased mice (Figure ). We find that the protein exhibits a higher response to
cAMP when injected into animals, an approximate 147% change, compared
to an 83% change in the dose–response curves (compare Figures b to 1c,d). The raw ratio values are lower in the tissue, as expected
from the protein luminescence spectra and the higher scattering and
absorption of 510 nm light over 650 nm light in tissues (SI, Figures 1 and 2). However, the high cAMP ratio
did not scale to the same degree as the 0 cAMP condition, resulting
in the higher observed dynamic range (SI, Figure 2).[19] Although the underlying reason
for this difference is unclear, the increase in the dynamic range
suggests that our sensor will maintain or perhaps exceed the 30% dynamic
range it showed in the cell culture when expressed in vivo. This supports
the application of our sensor to measuring cAMP changes in multiple
systems.
Figure 4
mScarlet-Epac-GeNL is sufficiently bright to report cAMP through
the tissue and fur in a mouse. (a) HEK293 lysate containing mScarlet-Epac-GeNL
corresponding to ∼1200 transfected cells was injected subcutaneously
into a mouse having either 0 mM (left) or 2.5 mM (right) cAMP. Shown
are the images for the 510 and 650 channels (radiance, photons·s–1·cm–2·sr–1) and the computed ratio image for a representative experiment in
a mouse. (b) Quantification of data for three independent experiments
performed as in (a), mean ± σ, n = 3.
mScarlet-Epac-GeNL is sufficiently bright to report cAMP through
the tissue and fur in a mouse. (a) HEK293 lysate containing mScarlet-Epac-GeNL
corresponding to ∼1200 transfected cells was injected subcutaneously
into a mouse having either 0 mM (left) or 2.5 mM (right) cAMP. Shown
are the images for the 510 and 650 channels (radiance, photons·s–1·cm–2·sr–1) and the computed ratio image for a representative experiment in
a mouse. (b) Quantification of data for three independent experiments
performed as in (a), mean ± σ, n = 3.Importantly, the radiance values for both the 510
and 650 nm channels
are 1–2 orders of magnitude greater than the background (Figure a, mean background
is ∼1.5 × 104 photons·s–1·cm–2·sr–1 with an
upper 2σ value of ∼6.4 × 105 photons·s–1·cm–2·sr–1 for either channel), supporting the potential use of mScarlet-Epac-GeNL
in tissue studies even in the unshaved mice.
Discussion
In this study, we established mScarlet-Epac-GeNL as a dual-mode
FRET and BRET sensor. Previous efforts have made single-mode ratiometric
FRET or BRET sensor for cAMP[11,12] and other molecules.[1,2] Using a split NanoLuc approach, intensiometric luminescent sensors
have been developed using Nano-lanterns as a basis, including a sensor
for cAMP. However, these sensors significantly reduce the brightness
of NanoLuc, reducing the benefits of using the eNL.[9,20] In
contrast, our approach demonstrates that eNLs can be incorporated
into existing ratiometric sensors with rapid optimization and no disruption
of the NanoLuc structure, taking full advantage of its brightness
and the ability of eNL to red-shift NanoLuc emission from autoluminescence
caused by background oxidation of the substrate. Thus, the advantages
of the eNL are maximized.The BRET-based approach we built on
here[9] is a part of a wider effort to red-shift
luciferase emission.[2,21,22] NanoLuc, although bright, has
a peak emission at 460 nm, which is highly scattered and absorbed
by tissues.[7,19] Although other efforts have successfully
red-shifted NanoLuc emission through direct mutation or through chemical
modifications to its substrate furimazine,[23−25] our approach
employs the red-shifted eNLs to modularly add bioluminescence capabilities
to existing FRET sensors. It would be interesting if these red-shifted
mutant NanoLuc enzymes could be fused with still longer wavelength-emitting
fluorescent proteins to employ a similar approach to ours to generate
ratiometric sensors that were truly in the “optical window”
for in vivo imaging.We were able to generate a dual-mode FRET
and BRET sensor with
eNL using a screen of only six constructs, suggesting that other dual-mode
ratiometric sensors could be rapidly engineered using our approach.
However, the conformational change in Epac is particularly robust
to the addition of different fluorescent proteins on its termini.[26] Thus, it may not be expected that eNL incorporation
into other sensors would be as facile. Fortunately, our approach aligns
closely with that of Komatsu et al.,[8] who
used the Renilla luciferase-containing Nano-Lanterns
to make hybrid FRET–BRET kinase sensors using AKAR sensors
as a scaffold, and Aper et al., who generated a zinc FRET–BRET
sensor.[27] Our study improves upon their
results by using the brighter eNLs and extends the strategy to the
family of Epac-based cAMP sensors. Together, our results suggest that
this approach may be generalizable to other ratiometric sensors.One significant application of BRET-based cAMP sensors is in cell-based
drug screening assays.[4,28] Ideally, a single sensor could
function in high-throughput screening assays and then be used for
the mechanism of action and animal studies. Our sensor functions well
in cells in vitro in the BRET mode and maintains the FRET mode functionality
for subcellular assessment of the drug function. In mice, mScarlet-Epac-GeNL
from approximately 1200 cells is bright over noise by 1–2 orders
of magnitude and faithfully reports cAMP changes in a ratiometric
manner, with a lower reporter limit <300 cells in our assay (SI, Figures 3 and 4). However, even after accounting
for the equivalent number of cells represented by the amount of injected
protein, direct injection of lysate into a deceased mouse is a crude
method of estimating the signal strength. The overall brightness of
our sensor in the future animal work will depend on the cell number
and protein expression levels in the cell population being examined.
Future extensions of this work into animals will need to optimize
their assay conditions according to their observed brightness, as
is standard with any sensor.[29] Nonetheless,
we have demonstrated that differentials in the tissue scattering of
the 510 vs 650 nm light in the mice did not disrupt the ability of
our sensor to ratiometrically report cAMP differences in deceased
mice. Furthermore, from the signal to noise in the BRET cell-based
assay (Figure ), we
estimate that in an ideal case, our sensor could statistically identify
changes in cAMP leading to a 9% change in the ratio, corresponding
to cAMP deviations of ∼3 μM. This is well within the
sensitivity needed to detect fluctuations commonly seen in neurons
responding to natural and synthetic agonists acting at the membrane
in cultured cells, including neurons.[12,30] Furthermore,
the large signal-to-noise ratio observed through the tissue with the
lysate derived from a small number of cells, together with its apparent
resolution in cells, suggests that mScarlet-Epac-GeNL could, in principle,
be used in vivo for initial drug validation. Furthermore, by applying
our approach to sensors that monitor different aspects of GPCR signaling,[1] a suite of sensors could be developed to screen
and characterize novel drugs from subcellular compartments to in vivo
animals, minimizing time spent on unproductive compounds and mechanism
validation.[31]In conclusion, we have
generated a cross-platform FRET and BRET
cAMP ratiometric sensor that may find applications in monitoring cAMP
dynamics in vitro and in vivo and may contribute to screening for
new therapeutic targets at GPCRs. Our use of GeNL should reduce interference
from shorter wavelength background autoluminescence, and our use of
mScarlet facilitates filter-based imaging because of the large spectral
difference between the donor and acceptor. Furthermore, our method
of adding bright BRET functionality to existing FRET sensors through
replacement of its C-terminal FP with an eNL may be extendable to
other GEIs, promoting rapid diversification of sensors and their applications.
Materials
and Methods
Molecular Biology
ICUE3 (Addgene #61622) was a generous
gift from Zhang.[11] mScarlet-N1 (Addgene #85066) was a generous
gift from Gadella.[32] HisB-RRvT (Addgene
# 87364) was a generous gift from Campbell.[18] tdTomato (Addgene #54856) and mTurquoise2 (Addgene # 54844) were
generous gifts from Davidson.[33,34] mNeonGreen-N1 was a
generous gift from Day.[35] pT7-CalfluxVTN
(Addgene #83926) containing NanoLuc was a generous gift from Johnson.[36]Red fluorescent proteins, hEpac1 (148-881),
mNeonGreen (ΔC10, res. 1-226), mTurqoise2 (ΔC10, res.
1-229), and NanoLuc fragments, were amplified using PCR and ligated
into the pGW1 vector at the XbaI/EcoRI restriction sites in a single
reaction using Gibson cloning (NEB HiFi kit). For GeNL constructs,
a GF linker was inserted between mNeonGreen (ΔC10) and NanoLuc
(ΔN5, res. 6-171); for CeNL constructs, an LH linker was inserted
between mTurquoise2ΔC10 and NanoLuc (ΔN3, res. 4-171).[9] An AGT linker was placed between the RFP and
hEpac1 (148-881), and an EQ linker was used between hEpac1 (148-881)
and GeNL/CeNL, similar to the FRET-based sensor ICUE3.[11]
Cell Culture and Transfection
Transient
transfections
of the sensor constructs in the pGW1 vector were carried out in HEK293A
cells or a stable HEK293 κ-opioid receptor line (HEKKOR), as indicated using the calcium phosphate method from Jordan et
al.[37] Salmon sperm carrier DNA (Invitrogen
15632011) was used to dilute sensor DNA for cell viability according
to the needs of the experiment ranging from 1:1 to 7:1 carrier/sensor
DNA mass ratios. HEK lines were maintained in a 37 °C incubator
at 10% CO2 in Dulbecco’s modified Eagle’s
medium (Fisher #31600034) pH 7.08, with 10% HyClone CCS (Fisher #SH3008703)
and passaged every 3–4 days. Media for HEKKOR cells
were supplemented with 0.35 mg mL–1 of G418 (Sigma
G8168).
Dose–Response Curves and Protein Spectra with HEK Lysate
HEKKOR cells were transfected with sensor constructs
in a six-well plate and allowed to express protein for 36 h before
being lysed with a hypotonic lysis solution (5 mM Tris·HCl, 2
mM ethylenediaminetetraacetic acid, pH = 7.3).[16] Briefly, cells were transferred to imaging media (15 mM N-(2-hydroxyethyl)piperazine-N′-ethanesulfonic
acid, 120 mM NaCl, 3 mM KCl, 3 mM NaHCO3, 1.25 mM NaH2PO4, 10 mM glucose, 2 mM CaCl2, 1 mM
MgCl2) and imaged (see “Determination
of FRET cAMP response in cells”) to evaluate transfection
efficiency. Cells were then rinsed 1× with 1× Dulbecco’s
phosphate-buffered saline (DPBS) (Fisher #14-200-075) and nonenzymatically
dissociated (Fisher #13 150-016) at 37 °C for 8–9
min. Cells were then resuspended in 1 mL of imaging media and pelleted
at 200g for 5 min. Cells were rinsed in 0.5 mL of
ice-cold DPBS and repelleted before being resuspended in 0.44 mL of
ice-cold lysis buffer. Cells were left in the lysis buffer for 10
min on ice and pipetted 5× three times during incubation to ensure
protein escape from membranes. Cell debris was then pelleted at 17 000g for 10 min, and protein-containing supernatant was removed
for analysis.cAMPstocks (25 mM) were made by dissolving cAMP
(Millipore-Sigma, #A6885) in the lysis buffer. Serial dilutions of
this stock were added stepwise to wells containing the sensor lysate.
FRET-based measurements were performed on a Synergy H4 plate reader
(Biotek) at a gain setting of 60 and the following filters/mirrors:
for CeNL constructs, 420/50 ex, 485/20 & 620/15 em; for GeNL constructs,
485/20 ex, 528/20 & 620/15 em; and a 50% 200–850 nm ex/em
dichroic mirror for all channels. To maximize the signal, the protein
was left at a full concentration in the lysate.Protein for
BRET-based dose–response curves was diluted
to a common effective concentration based on the direct fluorescence
of the RFP that was determined to slow furimazine decay while allowing
high signal:noise. The protein was diluted in 100 μL of the
lysis buffer in a 96-well plate and 25 μL of the Nano-Glo substrate
(Promega N2011), prepared with furimazine at 1× concentration
according to the manufacturer’s guidelines, was added just
prior to starting the experiment. The 96-well plate was imaged in
a Spectral Ami animal imager using a group acquisition with 2 ×
2 binning, exposure time 2 s, FOV 20, Fstop 1.2, object height 10
cm for both luminescence channels 510/20 and 650/20. During the 510/20
acquisition, the Ami took a photo using the default settings. Protein
received the same cAMP dosing as when determining the FRET dose–response
curves.For fluorescence and luminescence spectra of mScarlet-Epac-GeNL,
the lysate was prepared as above and quantified in a Synergy H4 plate
reader (Biotek) using a 9 nm bandwidth and read height of 8.0 mm.
For fluorescence spectra, 480/9 excitation was applied and spectra
were read from 500 to 700 nm with a 5 nm step size. For luminescence
spectra, the scanning speed seemed to affect the observed differences
in spectra. After optimizing the protein concentration, the best balance
for signal:noise and speed was to use a 0.1 s integration time and
a 10 nm step size from 450 to 700 nm. An autogain function was used
to determine the optimum gain for each set of curves and was set at
the first read and held constant through the rest of the repetition.For all dose–response curves and spectra, a single experiment/repetition
constitutes the lysate prepped from an independently transfected well
in a 6-well plate. Three background wells containing the lysis buffer
(and the Nano-Glo substrate, where applicable) were included with
each read and received cAMP. The average background was subtracted
from each data point prior to normalization or analysis. The lysate
from untransfected cells did not differ from the lysis buffer alone.
During analysis, dose–response curve repetitions are normalized
to their zero cAMP value prior to averaging. Normalized values were
then fitted tousing the
nonlinear least squares method in
custom MATLAB scripts. Spectra are presented with each repetition
normalized to its own area 100×. Figures were plotted in MATLAB
and arranged in Inkscape.
Determination of FRET cAMP Response in Cells
mScarlet-Epac-GeNL
was transiently transfected into HEKKOR cells and allowed
to express for 36 h. Media were exchanged for imaging media (as above)
and cells were imaged on an Olympus IX83 microscope with an Andor
Zyla4.2 sCMOS camera, Lumencor LED light source, and prior motorized
stage controlled by the Andor iQ3 software. mTurquoise2 fluorescence
and FRET from mTurquoise2 were observed with 438/29x (Chroma), 470/24m
ET (Chroma), and 632/60m ET (Chroma) filters with a 69008bs dichroic
mirror (Chroma). mNeonGreen fluorescence and FRET from mNeonGreen
were observed using 475/34x (Chroma), 525/50m ET (Chroma), and 632/60m
ET (Chroma) filters with a 59 022bs dichroic mirror (Chroma).
A plan Apo VC 20x objective (0.75 NA) was used for capture with exposure
time 100 ms and 2 × 2 binning each channel.For each repetition,
a baseline was acquired for six frames before imaging media was removed
and replaced with media containing the indicated drugs, either 50
μM forskolin (FSK, Tocris #1099) or 50 μM FSK + 9 nM Dynorphin
A (1–17) (dyn, Genscript custom peptide). Frames were collected
at 1 min intervals, and media changes performed between frames. Images
were background-subtracted using the rolling ball algorithm (radius
= 50) in ImageJ prior to computing the ratio image.[38] ROIs of cells were selected based on thresholded images
in either the green or red channel and applied to the ratio image
to get each cell’s average ratio in each frame. For Figure b, a mask was applied
to eliminate noncell pixels from the image. This is because many background
pixels in the ratio image have nonreal or saturated values from dividing
by zero or near-zero values after background subtraction.For
FRET cAMP responses in cells, data from 20 cells imaged in
an independently transfected well were averaged to form a single experimental
repetition/trial. The G/R ratio time course of each cell was normalized
to the average G/R ratio of its own 6 frame baseline prior to averaging.
Images and measurements were processed in ImageJ, data was analyzed,
and plotted in MATLAB, and Figure was arranged in Inkscape.
Demonstration of BRET cAMP
Response in Cells
HEK293A
cells were seeded and transfected in a 96-well plate and imaged 36–48
h later in the Spectral Ami animal imager using the filter setup above.
Cell growth media was changed to Opti-MEM media (Invitrogen #22600-050)
upon removing cells from the incubator. Just prior to imaging, 25
μL of the Nano-Glo substrate having 0.5× furimazine was
added to each well. At the indicated time, 80 μL of the well
solution was drawn out and mixed with FSK or vehicle and then returned
to the well. This was necessary due to the low solubility of FSK and
the desire to not alter the furimazine state in the well. The parameters
used for imaging were 2 s exposure time, FOV = 20, FStop = 1.2, object
height = 10 cm. This imager is not setup to do fast imaging but a
delay of 27 s approximated an imaging time step of 1 min for the 2
s exposure time setting. The plate was taped down to a 10 cm pipette
tip box to reduce well-to-well luminescence bleed through. Thresholded
images in either the 510 or 650 nm channel were used to generate ROIs
for each well, and the ratio of the mean ROI intensities was calculated
for Figure a. Images
were processed using ImageJ, and the data was plotted in MATLAB. An
independently transfected well of cells served as a repetition/trial,
and three independent repetitions were used for each condition.
Animal Work
Fvb mice p111–112 were sacrificed
using CO2 euthanasia. For each repetition/trial, a pool
of lysate was further diluted into conditions with either 0 or 2.5
mM cAMP and the Nano-Glo substrate having 1× furimazine. Each
mixture (25 μL), corresponding to ∼1200 transfected cells,
was injected subcutaneously into the dorsal caudal surface of a mouse,
with 0 cAMP lysate on the left side and 2.5 mM cAMP on the right.
Mice were imaged on Spectral Ami animal imager with exposure time
of 5 s, FOV = 20, Fstop = 1.2, object height 2 cm. No background subtraction
was needed for these images. The raw images were masked with an arbitrary
threshold to eliminate pixels with nonreal values and overlaid with
the photoimage of the mouse using ImageJ. Pixel values were converted
to radiance using the conversion factor calculated from the Spectral
Aura software. Values quantified in Figure b are calculated from the unmasked areas
in the ratio image of each repetition. Data was processed and analyzed
in MATLAB.All animal works were carried out with the approval
of the Purdue Animal Care and Use Committee and performed in accordance
with their guidelines.
Authors: Lily I Jiang; Julie Collins; Richard Davis; Keng-Mean Lin; Dianne DeCamp; Tamara Roach; Robert Hsueh; Robert A Rebres; Elliott M Ross; Ronald Taussig; Iain Fraser; Paul C Sternweis Journal: J Biol Chem Date: 2007-02-05 Impact factor: 5.157
Authors: Matthew D Wiens; Yi Shen; Xi Li; M Alaraby Salem; Nick Smisdom; Wei Zhang; Alex Brown; Robert E Campbell Journal: Chembiochem Date: 2016-11-15 Impact factor: 3.164
Authors: Jonathan D Violin; Lisa M DiPilato; Necmettin Yildirim; Timothy C Elston; Jin Zhang; Robert J Lefkowitz Journal: J Biol Chem Date: 2007-11-28 Impact factor: 5.157
Authors: Brittany R Benlian; Pavel E Z Klier; Kayli N Martinez; Marie K Schwinn; Thomas A Kirkland; Evan W Miller Journal: ACS Sens Date: 2021-03-16 Impact factor: 9.618
Authors: Adam L Valkovic; Martina Kocan; Brad Hoare; Sarah Marshall; Daniel J Scott; Ross A D Bathgate Journal: Int J Mol Sci Date: 2022-02-08 Impact factor: 5.923