The WNT signaling system governs critical processes during embryonic development and tissue homeostasis, and its dysfunction can lead to cancer. Details concerning selectivity and differences in relative binding affinities of 19 mammalian WNTs to the cysteine-rich domain (CRD) of their receptors-the ten mammalian Frizzleds (FZDs)-remain unclear. Here, we used eGFP-tagged mouse WNT-3A for a systematic analysis of WNT interaction with every human FZD paralogue in HEK293A cells. Employing HiBiT-tagged full-length FZDs, we studied eGFP-WNT-3A binding kinetics, saturation binding, and competition binding with commercially available WNTs in live HEK293A cells using a NanoBiT/BRET-based assay. Further, we generated receptor chimeras to dissect the contribution of the transmembrane core to WNT-CRD binding. Our data pinpoint distinct WNT-FZD selectivity and shed light on the complex WNT-FZD binding mechanism. The methodological development described herein reveals yet unappreciated details of the complexity of WNT signaling and WNT-FZD interactions, providing further details with respect to WNT-FZD selectivity.
The WNT signaling system governs critical processes during embryonic development and tissue homeostasis, and its dysfunction can lead to cancer. Details concerning selectivity and differences in relative binding affinities of 19 mammalian WNTs to the cysteine-rich domain (CRD) of their receptors-the ten mammalian Frizzleds (FZDs)-remain unclear. Here, we used eGFP-tagged mouse WNT-3A for a systematic analysis of WNT interaction with every human FZD paralogue in HEK293A cells. Employing HiBiT-tagged full-length FZDs, we studied eGFP-WNT-3A binding kinetics, saturation binding, and competition binding with commercially available WNTs in live HEK293A cells using a NanoBiT/BRET-based assay. Further, we generated receptor chimeras to dissect the contribution of the transmembrane core to WNT-CRD binding. Our data pinpoint distinct WNT-FZD selectivity and shed light on the complex WNT-FZD binding mechanism. The methodological development described herein reveals yet unappreciated details of the complexity of WNT signaling and WNT-FZD interactions, providing further details with respect to WNT-FZD selectivity.
The ten mammalian
Frizzleds
(FZD1–10) are G protein-coupled receptors (GPCRs)
and form—together with Smoothened (SMO)—the class F
of GPCRs.[1,2] The 19 different WNT lipoglycoproteins are
the main macromolecular ligands of FZDs, interacting with the extracellular
cysteine-rich domain (CRD) of the receptor. WNT-FZD signaling orchestrates
multiple processes during embryonic development, stem cell regulation,
and adult tissue homeostasis.[2] Additionally,
aberrant WNT signaling is implicated in tumorigenesis and other pathologies.[3,4] Whereas recent advances have resulted in a better understanding
of the underlying mechanisms controlling WNT-induced FZD activation
and signal initiation, the relative binding affinities and ligand–receptor
selectivity remain largely unknown.[5−13] The quantitative assessment of WNT binding has been limited by the
strong lipophilicity of WNTs, which makes their purification challenging
and necessitates detergents and serum for solubilization and stabilization
of WNTs, respectively.[14,15] Nevertheless, WNT-FZD interactions
were studied using biochemical and biophysical assays as well as through
the use of in silico calculations.[16−22] These studies generally reported WNT-FZD binding affinities in the
range of 1–100 nM, which is reasonable when considering the
known affinities of proteinaceous ligands to other GPCRs.[23,24] Nevertheless, it remains unclear how these values translate into
the physiological reality, since the local concentration of WNTs at
the receptors in vivo remains unknown and is likely
to be highly context-dependent.[25] Until
recently, the assessment of ligand binding was based on WNT binding
to the CRD rather than the full-length FZD, or the reported assays
were not performed in live cells. However, progress has been made
with the use of FRET- and cpGFP-based biosensors to demonstrate WNT-induced
FZD conformational dynamics and receptor activation,[7,12,26] where WNT binding to a full-length
receptor was reflected by an outward movement of the transmembrane
domain TM6. Furthermore, the generation of a functional eGFP-tagged
WNT-3A provided for the first time a biologically relevant FZD ligand
that could be used as a probe in quantitative binding assays in real-time
using living cells.[27,28]Here, using live cell analysis
of transiently transfected HEK293A
cells overexpressing HiBiT-tagged FZDs, we provide a comparative assessment
of binding affinities of eGFP-WNT-3A to all human FZD paralogues using
kinetic and saturation binding formats. Furthermore, using a competition
binding assay, we have assessed binding affinities of unlabeled, commercially
available WNT proteins to FZD4. Finally, we have also explored
the contribution of the FZD transmembrane core for the binding of
WNTs to the primary FZD-CRD binding site.[29] Compared with the previously described BRET-based assay for Nluc-FZD4 and Nluc-FZD6,[28] we
have used a nanoluciferase complementation-based BRET binding approach
here, termed NanoBiT/BRET. In this BRET assay format, the fluorescent
WNT-3A binds FZDs that are N-terminally tagged with the 11-amino-acid
HiBiT peptide. The addition of the complementary LgBiT to the system
allows rapid and high-affinity association to the HiBiT peptide, forming
a stable NanoBiT moiety with a luciferase activity. This setup allows
targeted analysis of cell surface receptors due to the cell impermeability
of LgBiT, thereby providing a system with less intracellular background
luminescence. This method is a modification of a well-established
NanoBRET binding assay to study ligand–receptor association,[30] and has been lately employed to study ligand
binding to Class A GPCRs and receptor tyrosine kinases.[31−34] Our results demonstrate that eGFP-WNT-3A interacts with full-length
human FZDs transiently overexpressed in live HEK293A cells in a paralogue
selective manner. This concept was expanded to unlabeled WNTs in competition
binding experiments suggesting a complex WNT-FZD selectivity profile.
The binding data based on full-length FZDs, FZD-CD86, and FZD-FZD
chimeras underline the complexity of the WNT-FZD interaction and suggest
that the core regions of FZDs may contribute to receptor selectivity.
Results
and Discussion
eGFP-WNT-3A/FZD Binding Kinetics
In order to establish
a nanoluciferase complementation-dependent NanoBiT/BRET binding assay
format to study all human FZD paralogues, we generated constructs
for all 10 receptors carrying an N-terminal HiBiT tag (Figure S1A,B). Upon transient overexpression
in HEK293A cells, all receptor constructs were detected at the cell
surface, albeit with varying cell surface expression levels (Figure S1C). Additionally, HiBiT-tagged FZD1, FZD2, FZD4, FZD5, FZD7, FZD8, and FZD10 mediated WNT-3A-induced
β-catenin-dependent signals as assessed by the TOPFlash reporter
assay performed in HEK293T cells devoid of endogenous FZDs (ΔFZD1–10 HEK293T cells, Figure S1D(25)). In contrast, FZD3, FZD6, and FZD9 could not transduce WNT-3A-induced activation
of this pathway, similar to what has been reported previously, yet
with differing results for FZD9.[28,35−38] Having verified the sequence and functionality of the HiBiT-tagged
FZD constructs, HEK293A cells transiently overexpressing these FZDs
were used in kinetic binding experiments. For these experiments, cells
were first incubated with the complementary LgBiT protein and the
luciferase substrate vivazine, and after 1 h, eGFP-WNT-3A was added
to final concentrations of 2.1, 4.2, or 8.3 nM, and BRET readings
were taken over a 4 h period at 37 °C (Figure A). The concentrations used for eGFP-WNT-3A
were dictated by the maximal concentration that could be obtained
for the eGFP-WNT-3A preparations and the assay format. We detected
a saturable net BRET ratio indicative of eGFP-WNT-3A specific binding
to HiBiT-tagged FZD1, FZD2, FZD4,
FZD5, FZD7, and FZD10, with Kd values varying from 2.3 to 29.9 nM (Figure B, Table ). In line with the TOPFlash
data, no concentration-dependent increase in receptor–ligand
BRET was detected for FZD3 and FZD9. Interestingly,
FZD8, which maintained a strong WNT-3A-induced TOPFlash
activity, and to a lesser extent FZD6, displayed very low
but detectable binding that could be fitted to association curves
over time (Figure S2A).
Figure 1
eGFP-WNT-3A binding kinetics.
A. The scheme depicts the experimental
setup of the NanoBiT/BRET analysis of association kinetics between
the HiBiT-tagged FZD and the eGFP-WNT-3A. Created with BioRender.com. B. Association kinetics
of the eGFP-WNT-3A to human HiBiT-FZDs were determined by the detection
of NanoBiT/BRET in transiently overexpressing living HEK293A cells
over time. BRET was sampled once per 90 s for 240 min. Data points
are presented as means ± SEM from n = 3 individual
experiments, fitting a two or more hot ligand concentrations kinetics
model. Experiments were performed with eGFP-WNT-3A batch 1.
Table 1
Kinetic and Saturation Binding Parameters
of eGFP-WNT-3A Binding to All 10 Human HiBiT-Tagged FZD Paraloguesa
FZD1
FZD2
FZD3
FZD4
FZD5
FZD6
FZD7
FZD8
FZD9
FZD10
Kinetic binding Kd (nM)
± SEM
29.9 ± 1.5
5.4 ± 0.1
n.d.
9.4 ± 0.5
2.3 ± 0.2
10.2 ± 3.7
2.8 ± 0.2
17.8 ± 4.4
n.d.
4.3 ± 0.3
Saturation binding Kd (nM) ± SEM
36.7 ± 12.7
48.6 ± 8.2
n.d.
17.7 ± 7.2
14.9 ± 7.6
6.5 ± 5.7
24.9 ± 9.9
4.9 ± 3.1
n.d.
21.3 ± 9.0
Kd values are based on data from n = 3–4
individual
experiments (shown in Figures B and 2B) and shown as a best-fit value
± SEM; n.d. = not determined.
eGFP-WNT-3A binding kinetics.
A. The scheme depicts the experimental
setup of the NanoBiT/BRET analysis of association kinetics between
the HiBiT-tagged FZD and the eGFP-WNT-3A. Created with BioRender.com. B. Association kinetics
of the eGFP-WNT-3A to human HiBiT-FZDs were determined by the detection
of NanoBiT/BRET in transiently overexpressing living HEK293A cells
over time. BRET was sampled once per 90 s for 240 min. Data points
are presented as means ± SEM from n = 3 individual
experiments, fitting a two or more hot ligand concentrations kinetics
model. Experiments were performed with eGFP-WNT-3A batch 1.Kd values are based on data from n = 3–4
individual
experiments (shown in Figures B and 2B) and shown as a best-fit value
± SEM; n.d. = not determined.
Figure 2
eGFP-WNT-3A saturation binding. A. The
scheme depicts the experimental
setup of NanoBiT/BRET analysis of equilibrium binding between the
HiBiT-tagged FZD and the eGFP-WNT-3A. Created with BioRender.com. B. Saturation binding
of the eGFP-WNT-3A to human HiBiT-FZDs was determined by the detection
of NanoBiT/BRET in transiently overexpressing living HEK293A cells
following 240 min incubation. Data points are presented as means ±
SEM from n = 4 individual experiments, fitting a
one-site specific model models. Experiments were performed with eGFP-WNT-3A
batch 1.
eGFP-WNT-3A/FZD Binding Affinity at Equilibrium
To
define saturation binding affinity of eGFP-WNT-3A, we incubated human
HiBiT-FZDs with a full concentration range (16.7 pM to 16.7 nM) of
eGFP-WNT-3A for 240 min at 37 °C (Figure A). The net BRET ratio representing ligand–receptor
binding increased in a clear, concentration-dependent manner for FZD1, FZD2, FZD4, FZD5, FZD7, and FZD10. Unfortunately, using transient overexpression
of HiBiT-FZDs in HEK293A cells and the eGFP-WNT-3A with a limited
maximal concentration in the conditioned medium, binding curves did
not reach maximal asymptotic values but only came to near-saturable
levels (Figure B).
Again, detection of binding of eGFP-Wnt-3A to FZD6 and
FZD8 was only marginally above background levels, as the
net BRET values were low (Figure S2B).
Similar to the kinetic binding assays, no quantifiable eGFP-WNT-3A
binding was detected for FZD3 or FZD9. The affinities
of eGFP-WNT-3A/FZD interactions were determined from linear regression
curves showing near-saturable binding,[39] and the Kd values are shown in Table . The reported saturation
binding affinity values range from 4.9 to 48.6 nM, and they are in
good agreement with the Kd values determined
with kinetic binding for FZD1, FZD4, and FZD6. The degree of agreement is, however, only fair for FZD5, FZD8, and FZD10 and relatively poor
for FZD2 and FZD7. Taken together, these kinetic
and saturation binding data are in line with our previous results
using fluorescence microscopy analysis, where no eGFP-WNT-3A association
could be observed with C-terminally mCherry-tagged FZD6, and only a very weak association with FZD8 and FZD9 (FZD3 was not used).[28] Although this fluorescence imaging-based method could provide an
estimate of the relative ability of eGFP-WNT-3A to associate with
different FZDs, accurate quantification of the binding affinities
was not possible. Also, in that study, ΔFZD1–10 HEK293GFP-free cells overexpressing FZD8-mCherry (but not FZD6-mCherry), showed very faint binding
of eGFP-WNT-3A, and this is also in agreement with the HiBiT-tagged
system used here, which can detect very low level, but specific, binding
to FZD8 (Figure S2). This is
in agreement with a recent report claiming that ligand–receptor
interaction using the HiBiT-tagged system allows detection of very
weak interactions.[32] Furthermore, in the
case of FZD6, there are differences in reports of its ability
to bind or respond to WNT-3A. Biochemical experiments failed to detect
any association between WNT-3A and FZD6-CRD-IgG,[16] and no eGFP-WNT-3A/Nluc-FZD6 interaction
was detected in our previous NanoBRET study.[28] However, it should be noted that, compared with the HiBiT-tagged
systems, binding analyses with Nluc-tagged receptors can display reduced
sensitivity for detection of weak interactions, as recently discussed.[32] On the other hand, recombinant human WNT-3A
induced a conformational change in FZD6[12] and affected the mobility of the receptor in the cell membrane
as assessed by fluorescence recovery after photobleaching assay.[40] Finally, the findings with respect to FZD8 are particularly intriguing, given the existing structural
information on the WNT-3A-FZD8 CRD complex.[41] It is currently unclear why such discrepancies
exist for these two FZD paralogues.eGFP-WNT-3A saturation binding. A. The
scheme depicts the experimental
setup of NanoBiT/BRET analysis of equilibrium binding between the
HiBiT-tagged FZD and the eGFP-WNT-3A. Created with BioRender.com. B. Saturation binding
of the eGFP-WNT-3A to human HiBiT-FZDs was determined by the detection
of NanoBiT/BRET in transiently overexpressing living HEK293A cells
following 240 min incubation. Data points are presented as means ±
SEM from n = 4 individual experiments, fitting a
one-site specific model models. Experiments were performed with eGFP-WNT-3A
batch 1.Data are based on n = 3–6 individual experiments
presented in Figure B. pKi values are presented as a best-fit
value ± SEM; n.d.
= not determined.
Figure 3
Competition binding between
eGFP-WNT-3A and untagged WNTs at FZD4. A. The scheme depicts
the experimental setup of NanoBiT/BRET
analysis of competition binding between the eGFP-WNT-3A and commercially
available untagged WNT-3A, WNT-5A, WNT-5B, WNT-10B, WNT-11, and WNT-16B.
Created with BioRender.com.
B. FZD4 binding of eGFP-WNT-3A at 0.4 nM in the presence
of increasing concentrations of the untagged WNTs was determined by
the detection of NanoBiT/BRET in transiently overexpressing living
HEK293A cells following 240 min incubation. Data points are presented
as means ± SEM from n = 3–6 individual
experiments, fitting a three- or four-parameter model. Upper dashed
line indicates the BRET ratio of eGFP-WNT-3A-only treated cells; lower
dashed line indicates the BRET ratio of ligand-untreated cells (BRET
donor only). Experiments were performed with eGFP-WNT-3A batch 2.
In order
to directly compare NanoBiT/BRET and NanoBRET binding
assay formats, we used Nluc-FZD4 and HiBiT-FZD4 constructs for saturation binding (Figure S3A–C). NanoBiT/BRET experiments were performed in two different experimental
paradigms, where LgBiT protein was added either directly after (setup
1, used throughout this study Figure S3B and Figure A) or
for 10 min before (setup 2, Figure S3C)
the 4 h incubation with eGFP-WNT-3A. This allowed us to test for any
potential steric hindrance of WNT binding to FZD caused by the presence
or complementation of nanoluciferase. In these comparisons, although
the differences in Kd values were apparent,
they did not reach statistical significance (Nluc-FZD4Kd (nM) ± SEM = 7.6 ± 3.6; HiBiT-FZD4 setup 1 Kd (nM) ± SEM =
11.9 ± 3.6; HiBiT-FZD4 setup 2 Kd ± SEM (nM) = 20.4 ± 7.6). Furthermore, eGFP-WNT-3A
binding to Nluc-FZD4 (Figure S3A) resulted in lower maximal BRET (BRETmax) compared to
either of the two HiBiT-FZD4 binding setups (Figure S3B,C) at similar luminescence levels
(Nluc-FZD4 BRETmax ± SEM = 0.026 ±
0.006 vs HiBiT-FZD4 setup 1 BRETmax ± SEM
= 0.049 ± 0.005, P = 0.0484; vs HiBiT-FZD4 setup 2 BRETmax ± SEM = 0.049 ± 0.004, P = 0.0349). This suggests that intracellular luminescence
originating from receptors that are not accessible for the ligand
reduces the assay’s dynamic range (see Figure S3D for expression analysis). In support of our choice
to change from NanoBRET to the NanoBiT/BRET experimental setup, a
recent study has shown that affinity measurements obtained from NanoBRET
binding assays were generally less consistent in comparison with NanoBiT/BRET
analyses.[32]
eGFP-WNT-3A Competition
Binding with Untagged WNTs at FZD4
With the aim
to understand the competitive nature
of eGFP-WNT-3A binding to FZD, we combined eGFP-WNT-3A with increasing
concentrations of several commercially available and purified untagged
WNT proteins: WNT-3A, WNT-5A, WNT-5B, WNT-10B, WNT-11, and WNT-16B.
Again, we have used HiBiT-FZD4 as our model receptor. In
this assay setup, HEK293A cells transiently overexpressing HiBiT-FZD4 were preincubated with the untagged WNTs for 30 min before
addition of eGPF-WNT-3A to a final concentration of 0.4 nM. Cells
were then incubated for a further 4 h to allow a competitive equilibrium
to be reached before addition of LgBiT and subsequent BRET measurement
(Figure A). The results of these experiments are shown in Figure B and summarized
in the Table , and
show that the untagged WNTs competitively displaced eGFP-WNT-3A from
FZD4 with different affinities and capacities. Interestingly,
WNT-10B and WNT-11 had the highest affinities, but they showed moderate
BRET signal decrease as indicated by remaining residual BRET. Intriguingly,
WNT-3A presented higher binding affinity (lower Kd) but caused a lower reduction of BRET than WNT-5A and
WNT-5B. WNT-16B did not compete with eGFP-WNT-3A in this FZD4-based assay. These results are in fair agreement with the recently
published potencies and efficacies of WNTs in eliciting conformational
changes in FZD4-cpGFP biosensor except for WNT-5B.[12] Nevertheless, a similar rank order of affinities
was obtained for WNT-3A, WNT-5A, and WNT-5B in binding to the isolated
FZD4 CRD.[17] Obviously, the insights
into the mechanism of WNT–WNT competition for the primary binding
site at FZDs remain obscure. We can only speculate that the process
of functional ligand binding is more complex than for small-molecule
ligands and other GPCRs. Along these lines, FZD oligomers associate
or dissociate upon ligand addition,[42−44] adding to the complexity
of ligand binding analysis.[45] Additionally,
FZD coreceptors and various regulators could alter WNT interactions
with FZD in HEK293 cells.[25]
Table 2
Binding Properties
of Various FZD
Ligands in Competition with eGFP-WNT-3A Binding (0.4 nM) to HiBiT-FZD4a
WNT-3A
WNT-5A
WNT-5B
WNT-10B
WNT-11
WNT-16B
Competition binding pKi ± SEM
7.26 ± 0.35
7.08 ± 0.21
6.93 ± 0.25
7.87 ± 0.55
8.90 ± 0.66
n.d.
ΔBRET ± SEM
–0.002 ± 0.001
–0.004 ± 0.0002
–0.004 ± 0.0002
–0.001 ± 0.0003
–0.001 ± 0.0004
n.d.
0.4 nM eGFP- WNT-3A binding
displaced (%)
40.8
78.4
78.3
34.5
58.4
n.d.
Data are based on n = 3–6 individual experiments
presented in Figure B. pKi values are presented as a best-fit
value ± SEM; n.d.
= not determined.
Competition binding between
eGFP-WNT-3A and untagged WNTs at FZD4. A. The scheme depicts
the experimental setup of NanoBiT/BRET
analysis of competition binding between the eGFP-WNT-3A and commercially
available untagged WNT-3A, WNT-5A, WNT-5B, WNT-10B, WNT-11, and WNT-16B.
Created with BioRender.com.
B. FZD4 binding of eGFP-WNT-3A at 0.4 nM in the presence
of increasing concentrations of the untagged WNTs was determined by
the detection of NanoBiT/BRET in transiently overexpressing living
HEK293A cells following 240 min incubation. Data points are presented
as means ± SEM from n = 3–6 individual
experiments, fitting a three- or four-parameter model. Upper dashed
line indicates the BRET ratio of eGFP-WNT-3A-only treated cells; lower
dashed line indicates the BRET ratio of ligand-untreated cells (BRET
donor only). Experiments were performed with eGFP-WNT-3A batch 2.
Binding of eGFP-WNT-3A to FZD Chimeras
WNTs directly
engage the CRD through protein–protein and protein–lipid
interactions.[41,46] However, it remains unclear whether
non-CRD domains of FZDs contribute to WNT-FZD interaction.[20] It has been hypothesized that the CRD simply
serves the purpose of binding WNTs in order to bring them in close
proximity with the receptor for additional binding/activation mechanisms.[47] Indeed, the long and flexible nature of the
linker connecting the CRD of FZDs to TM1 would tend to support such
a hypothesis.[48] The role of the FZD transmembrane
domains in ligand binding, complex formation, receptor conformational
changes, and signal transduction has been a subject of debate.[5,8,9,49−52] Here, we seek to obtain a more mechanistic insight into the contribution
of the transmembrane core to eGFP-WNT-3A binding. To this end, we
generated two chimeric proteins fusing the N-terminal domain (NTD;
CRD + linker) of one FZD with an unrelated CD86 single transmembrane
domain spanning protein (Figure A). Specifically, we generated FZD4-CD86
and FZD8-CD86 chimeric proteins (Figure S4A). In this manner, we aimed to study the effect of a FZD
core on eGFP-WNT-3A binding to the CRD. We validated the chimeras
with regard to proper membrane trafficking upon transient overexpression
in HEK293A cells and detected no difference in surface expression
levels between FZD-CD86 and wild-type (WT) FZDs (Figure B).
Figure 4
eGFP-WNT-3A binding to
FZD-CD86 chimeras. A. The cartoon representations
of the FZD-CD86 fusion proteins used in this study. eGFP-WNT-3A binding
at equilibrium was assessed as depicted in Figure A. Created with BioRender.com. B. Cell surface expression
of HiBiT-tagged FZD-CD86 chimeras as measured by NanoBiT luminescence
(from the experiments summarized in Figure B and parts C–D). Data are presented
as means ± SEM from n = 3–4 individual
experiments. Expression data of FZD4, FZD8,
and pcDNA are also depicted in SI Figure 1C. C. Saturation binding of eGFP-WNT-3A at FZD4-CD86 and
FZD4 (data also present in Figure B) was determined by the detection of NanoBiT/BRET
in transiently overexpressing living HEK293A cells following 240 min
incubation. Data points are presented as means ± SEM from n = 3–4 individual experiments. eGFP-WNT-3A batch
1 was used in these experiments. D. Saturation binding of eGFP-WNT-3A
at FZD8-CD86 and FZD8 (data also present in Figure B) was determined
by the detection of NanoBiT/BRET in transiently overexpressing living
HEK293A cells following 240 min incubation. Data points are presented
as means ± SEM from n = 3–4 individual
experiments. eGFP-WNT-3A batch 1 was used in the experiments. Linear
scale data are fitted to a one-site specific binding model. Logarithmic-scale
data are fitted to a normalized three- or four-parameter model. The
right plot in every panel shows data normalized between 0% (BRETmin) and 100% (BRETmax) for each studied construct.
eGFP-WNT-3A binding to
FZD-CD86 chimeras. A. The cartoon representations
of the FZD-CD86 fusion proteins used in this study. eGFP-WNT-3A binding
at equilibrium was assessed as depicted in Figure A. Created with BioRender.com. B. Cell surface expression
of HiBiT-tagged FZD-CD86 chimeras as measured by NanoBiT luminescence
(from the experiments summarized in Figure B and parts C–D). Data are presented
as means ± SEM from n = 3–4 individual
experiments. Expression data of FZD4, FZD8,
and pcDNA are also depicted in SI Figure 1C. C. Saturation binding of eGFP-WNT-3A at FZD4-CD86 and
FZD4 (data also present in Figure B) was determined by the detection of NanoBiT/BRET
in transiently overexpressing living HEK293A cells following 240 min
incubation. Data points are presented as means ± SEM from n = 3–4 individual experiments. eGFP-WNT-3A batch
1 was used in these experiments. D. Saturation binding of eGFP-WNT-3A
at FZD8-CD86 and FZD8 (data also present in Figure B) was determined
by the detection of NanoBiT/BRET in transiently overexpressing living
HEK293A cells following 240 min incubation. Data points are presented
as means ± SEM from n = 3–4 individual
experiments. eGFP-WNT-3A batch 1 was used in the experiments. Linear
scale data are fitted to a one-site specific binding model. Logarithmic-scale
data are fitted to a normalized three- or four-parameter model. The
right plot in every panel shows data normalized between 0% (BRETmin) and 100% (BRETmax) for each studied construct.In the NanoBiT/BRET binding experiments with the
FZD4-CD86 chimera, we could detect a concentration-dependent
increase
in the BRET signal indicative of eGFP-WNT-3A binding. Interestingly,
eGFP-WNT-3A interacted with FZD4-CD86 with a visibly lower
affinity (higher Kd) and a visibly lower
maximal BRET (at the fixed concentrations used) than for an intact
FZD4 protein (FZD4-CD86 Kd ± SEM (nM) = 141.9 ± 181.5, P =
0.0991; BRETmax ± SEM = 0.019 ± 0.001 vs FZD4 BRETmax ± SEM = 0.030 ± 0.004, P = 0.0622; Figure C). In order to emphasize differences in Kd for the tested receptors, the data were also normalized
and are presented in a semilogarithmic presentation in Figure C (FZD4-CD86 pKd ± SEM = 8.19 ± 0.04 vs FZD4 pKd ± SEM = 8.31 ± 0.05, P = 0.0331). Importantly, differences in BRETmax for FZD4-CD86 and FZD4 cannot arise from differences
in surface expression levels, as both studied receptors are similarly
expressed (P = 0.3324).Next, we performed
a similar analysis for a FZD8-CD86
chimera. eGFP-WNT-3A binding to the chimera FZD8-CD86 compared
to FZD8 at similar levels of receptor surface expressions
(P = 0.8340; Figure B) did not differ in affinity in the analysis of non-normalized
data (FZD8-CD86 Kd ± SEM
(nM) = 22.9 ± 10.6, P = 0.6668; Figure D), but the difference reached
statistical significance when comparing the normalized values (P = 0.0390; Figure D). Furthermore, the NanoBiT/BRET signal increased significantly
when the FZD8 core was replaced by CD86. The NanoBiT/BRET
signal (BRETmax) was in fact comparable to other WNT-3A-binding
competent FZDs (FZD8-CD86 BRETmax ± SEM
= 0.056 ± 0.006 vs FZD8 BRETmax ±
SEM = 0.003 ± 0.0003, P = 0.0002; Figure D and Figure ). Intriguingly, these findings are the opposite
of what we observe for FZD4, where replacing the receptor
core with CD86 visibly reduced maximal BRET (Figure C). The efficiency of resonance energy transfer
depends on both orientation and distance between BRET donor and BRET
acceptor.[53] Thus, in the NanoBiT/BRET binding
setup, the differences in BRETmax can be interpreted as
distinct ligand–receptor conformations. This further suggests
that the cores of FZD4 and FZD8 can differently
contribute to WNT-FZD binding.In addition to the FZD-CD86 chimeras
detailed above, we also generated
FZD-FZD chimeras. Specifically, we constructed FZD4-FZD6, FZD4-FZD8, FZD5-FZD6, FZD5-FZD7, and FZD6-FZD4 chimeric proteins (Figure S4B).
In this manner, we have used at least one FZD paralogue from every
FZD homology cluster. The transmembrane cores of FZD6 and
FZD8 were selected to test whether they negatively affect
eGFP-WNT-3A binding to the CRD of FZD4 and FZD5. On the other hand, the FZD7 core was chosen to assess
if it positively modulates ligand binding to the CRD of FZD5. The rationale for this selection was based on the very weak NanoBiT/BRET
signal seen for eGFP-WNT-3A binding to FZD6 and FZD8, and strong NanoBiT/BRET signal of eGFP-WNT- 3A/FZD7 association in the two assay paradigms described in this study (Figure B and Figure B). Additionally, the FZD6 core was replaced with the FZD4 core to assess
whether eGFP-WNT-3A binding to FZD6 CRD would increase
upon insertion of a core from an eGFP-WNT-3A binding-competent FZD
paralogue (Figure B and Figure B).
We validated the chimeras with regard to their proper membrane trafficking
upon transient overexpression in HEK293A cells and detected that the
FZD-FZD chimera proteins are relatively poorly expressed on the cell
surface compared to WT receptors (Figure S4C). Binding affinities of fluorescent propranolol to HiBiT-tagged
β2-adrenergic receptors vary depending on the protein expression
levels, with higher expression levels generally resulting in slightly
elevated Kd values (lower affinity).[32] Furthermore, binding affinities of DKK1-eGFP
proteins to the WNT coreceptor LRP6-mCherry measured by dual-color
axial line-scanning FCS (axial lsFCS) were higher for lower, more
physiologically relevant receptor expression levels.[54] Our data for transient overexpression of FZD4 in HEK293A cells mostly support these notions, with some exceptions
(Figure S4D). Overall, it needs to be emphasized
that although the Kd is a thermodynamic
parameter that should be constant for various expression levels, differences
in the cellular context may lead to different functionalities of overexpressed
receptors present on the cell surface. This in turn can affect the
comparative analysis and interpretation of real-time ligand binding
data.[54] However, provided the availability
of cell surface expression data in the experimental paradigm of the
NanoBiT/BRET binding assay, we shed light on a potential role of the
receptor core for WNT-CRD binding. Focusing on the FZD4 chimeras, eGFP-WNT-3A bound with a significantly higher affinity
(lower Kd) to the FZD4-FZD6 and the FZD4-FZD8 chimeras compared
to full-length FZD4 (FZD4-FZD6Kd ± SEM (nM) = 3.5 ± 1.8, P = 0.0255; FZD4-FZD8Kd ± SEM (nM) = 2.9 ± 1.3, P = 0.0371; Figure S4E). Interestingly,
BRETmax values were visibly or significantly lower for
both weakly expressed FZD4-FZD chimeras than for the intact
FZD4 (FZD4-FZD6 BRETmax ± SEM = 0.021 ± 0.003, P = 0.0828; FZD4-FZD8 BRETmax ± SEM = 0.010 ±
0.001, P = 0.0192).Additionally, our data
showed that in comparison to WT FZD5, eGFP-WNT-3A binding
to FZD5-FZD6 occurred
with only visibly higher affinity, but this difference did not reach
statistical significance (FZD5-FZD6Kd ± SEM (nM) = 4.4 ± 1.5, P = 0.0638; Figure S4F). Next,
the affinity of eGFP-WNT-3A binding to FZD5-FZD7 was also not significantly different compared with WT FZD5 (FZD5-FZD7Kd ±
SEM (nM) = 5.0 ± 2.4, P = 0.2622; Figure S4F). Moreover, the differences in BRETmax did not reach statistical significance (FZD5-FZD6 BRETmax ± SEM = 0.080 ± 0.014, P = 0.1715; FZD5-FZD7 BRETmax ± SEM = 0.098 ± 0.026, P = 0.2046; FZD5 BRETmax ± SEM = 0.051 ± 0.009).In addition, our data indicated that eGFP-WNT-3A bound to FZD6-FZD4 with the same affinity (FZD6-FZD4Kd ± SEM (nM) = 5.8 ±
3.4, P = 0.9695; Figure S4G) as to FZD6 but with a significant, over 10-fold increase
in the maximal BRET signal (FZD6-FZD4 BRETmax ± SEM = 0.030 ± 0.006 vs FZD6 BRETmax ± SEM = 0.002 ± 0.001, P = 0.056)
arguing that the FZD6CRD can efficiently bind eGFP-WNT-3A
in the context of a different receptor core. As mentioned before,
it needs to be emphasized that receptor expression levels can affect
ligand–receptor interaction. Along these lines, in classical
BRET titration experiments, increasing BRET donor amounts (by increasing
plasmid DNA amounts) with constant BRET acceptor levels (unchanged
plasmid DNA amounts) leads to a decrease in BRETmax signal
for specific donor–acceptor interactions.[55] In contrast, no such relationship was found in our FZD-CD86
and FZD-FZD NanoBiT/BRET binding experiments, further supporting the
notion that the FZD core has a differential role in WNT binding depending
on the FZD paralogue.Here, we have used the NanoBiT/BRET system
to analyze the contribution
of the FZD seven-transmembrane-spanning core to eGFP-WNT-3A binding
to the CRD. We show that swapping the receptor core can have a substantial
effect on the affinity or maximal BRET of eGFP-WNT-3A binding in the
NanoBiT/BRET read-out. Our data, particularly from the FZD-CD86 experiments,
argue that the seven-transmembrane-spanning core contributes to ligand
binding for the tested FZDs, even though the details on the molecular
level remain obscure.This study adds substantial methodological
advance to the pharmacological
toolbox suitable for the study of the class F GPCRs and their coreceptors.[28,54,56] We have demonstrated the vast
potential of employing fluorescent WNTs and the NanoBiT/BRET binding
technique for the pharmacological quantification of WNT-FZD interactions
in live HEK293A cells despite the limitations that come with the low
concentration of the tracer WNT in the conditioned medium preparation.
The broader analysis of the selectivity of ligand–receptor
interactions, WNT binding in the presence or absence of either FZD
coreceptors, FZD-binding intracellular transducer proteins and at
different FZD expression levels, can now be further investigated to
understand the pluridimensionality of WNT-FZD system in a more physiologically
relevant cell system.
Experimental Section
Cell Culture and Ligands
HEK293A cells (ATCC), HEK293F
(Thermo Fisher Scientific, Waltham, MA, USA), HEK293T (DSMZ ACC-635),
and ΔFZD1–10 HEK293T cells[25] were cultured in DMEM supplemented with 10% FBS, 1% penicillin/streptomycin,
and 1% l-glutamine (all from Thermo Fisher Scientific, Waltham,
MA, USA) in a humidified CO2 incubator at 37 °C. All
cell culture plastics were from Sarstedt (Nümbrecht, Germany),
unless otherwise specified. The absence of mycoplasma contamination
was routinely confirmed by PCR using 5′-GGCGAATGGGTGAGTAACACG-3′
and 5′-CGGATAACGCTTGCGACTATG-3′
primers detecting 16 S rRNA of mycoplasma in the media after 2–3
days of cell exposure. Untagged human WNT-3A, human/mouse WNT-5A,
human WNT-5B, human WNT-10B, human WNT-11, and human WNT-16B were
all from RnD Systems/Biotechne (#5036-WN, #645-WN, #7347-WN, #7196-WN,
#6179-WN, and #7790-WN, Minneapolis, MI, USA). WNTs were dissolved
at 100 μg/mL in filter-sterilized 0.1% BSA/PBS and stored at
4 °C. Molecular weights of the WNTs were as per supplier’s
datasheets. Porcupine inhibitor C59 was from Abcam (#ab142216, Cambridge,
UK).[57] C59 was dissolved in DMSO at 5 mM
and stored at −20 °C. The serial dilutions of WNTs were
prepared in the protein-low binding tubes (Eppendorf, Hamburg, Germany).
Preparation of eGFP-WNT-3A CM
HEK293F suspension cells
growing in serum-free Expi293 expression medium (60 mL, 2.5 ×
106 cells/mL) were cotransfected with 10 μg of either pCS2+-WNT-3A or pCS2+-eGFP-WNT- 3A together with 50 μg
of pCMV-His-Afamin plasmid using ScreenFect UP-293
(ScreenFect GmbH, Eggenstein-Leopoldshafen, Germany) according to
the manufacturer’s instructions. The corresponding control
CM was generated from cells transfected with pCS2 plasmid.Cells were first cleared
from the HEK293F CM by centrifugation at 260 g (1200
rpm) for 10 min and then at 2800 g (4000 rpm) for
30 min to remove any remaining cellular debris and insoluble material.
This “raw” CM then was concentrated 5-fold using Vivaspin
turbo 15 centrifugal concentrators (30,000-molecular-weight-cutoff,
Satorius AG, Göttingen, Germany) and exchanged to the desired
cell culture medium using Sephadex G-25 PD10 desalting columns (GE
Healthcare Bio-Science, Freiburg, Germany). The final concentration
and integrity of eGFP-WNT-3A in the CM samples were determined using
ELISA (GFP ELISA kit, #ab171581, Abcam) and SDS-PAGE/Western Blot
analysis, respectively. Two eGFP-WNT-3A batches (eGFP-WNT-3A batch
1 final concentration: 16.7 nM; eGFP-WNT-3A batch 2 final concentration:
16.2 nM) were used in this study. Current WNT purification methods
allow only limited WNT concentration to be obtained from CM.[58] For validation of the eGFP-WNT-3A batches, please
see Figure S5.
Plasmids
Generation
of HiBiT-FZD4, HiBiT-FZD6, and Nluc-FZD4 has been described previously.[28] Gibson cloning was used to generate other HiBiT-tagged
receptor constructs using HiBiT-tagged backbone from HiBiT-FZD4 containing a 5-HT3A signal sequence. To generate
chimeras, the N-terminal domains (NTD; CRD with a linker region) and
the transmembrane cores were defined according to Frizzled structures
predicted on GPCRdb (http://www.gpcrdb.org), and the constructs were generated with Gibson cloning. Nluc-CD86
used to generate FZD-CD86 chimeras was from Martin J. Lohse (Max-Delbrueck
Center for Molecular Medicine, Berlin, Germany). Frizzled and CD86
signal peptides were defined with SignalIP-5.0 Server (http://www.cbs.dtu.dk/services/SignalP/). The constructs were validated by sequencing (Eurofins GATC, Konstanz,
Germany). The details of the constructs used in this study are presented
in Figure S1A,B and Figure S4A.
NanoBiT/BRET Binding
HEK293A cells
were transiently
transfected in suspension using Lipofectamine 2000 (Thermo Fisher
Scientific, Waltham, MA, USA). A total of 4 × 105 cells
were transfected in 1 mL with 1000 ng of HiBiT-tagged FZDs or 10 ng
of Nluc-FZD4 plasmid DNA. The cells (50 μL) were
seeded onto a poly(d-lysine)-coated black 96-well cell culture
plate with a solid flat bottom (Greiner BioOne). Next, 50 μL
of complete DMEM medium was added to each well. Forty-eight hours
post-transfection, the cells were washed once with 200 μL of
Hanks’ balanced salt solution (HBSS; HyClone). In the kinetic
binding experiments, the cells were preincubated with 50 μL
of a mix of Nluc substrate vivazine (1:50 dilution; #N2581, Promega,
Fitchburg, WI, USA) and LgBiT (1:100 dilution; #N2421, Promega, Fitchburg,
WI, USA) in a complete, nonphenol red DMEM (HyClone) supplemented
with 10 mm HEPES for 1 h at 37 °C without CO2. Subsequently,
50 μL of eGFP-WNT-3A conditioned medium or control medium supplemented
with 5% FBS and 10 mm HEPES was added, and the BRET signal was measured
every 90 s for 240 min at 37 °C (161 measurements, no CO2). In the saturation-binding experiments, the cells were incubated
with different concentrations of eGFP-WNT-3A conditioned medium (90
μL) supplemented with 5% FBS and 10 mm HEPES for 240 min at
37 °C with no CO2. In the competition binding experiments,
the cells were preincubated for 30 min at 37 °C with 80 μL
of unlabeled WNT proteins at 37 °C with no CO2. Subsequently,
10 μL of eGFP-WNT-3A at a concentration of 3.6 nM (final concentration
of 0.4 nM) were added, and the cells were incubated for further 240
min at 37 °C with no CO2. Next, for saturation and
competition binding experiments, 10 μL of a mix of furimazine
(1:10 dilution; #N2421, Promega, Fitchburg, WI, USA) and LgBiT (1:20
dilution; #N2421, Promega, Fitchburg, WI, USA) was added. For saturation
binding experiments with Nluc-FZD4 furimazine was used
at 1:1000 final dilution (#N1572, Promega, Fitchburg, WI, USA) and
no LgBiT was added. The cells were incubated for another 10 min at
37 °C with no CO2 before the BRET measurements. The
BRET ratio was determined as the ratio of light emitted by eGFP (energy
acceptor) and light emitted by HiBiT-FZD1–10 or
Nluc-FZD4 (energy donors). The net BRET ratio was calculated
as the difference in BRET ratio
between cells treated with eGFP-WNT-3A, and cells treated with vehicle.
ΔBRET ratio in the competition binding experiment was calculated
as the difference in BRET ratio of cells treated with vehicle (eGFP-WNT-3A
only wells, no ΔBRET) and cells treated with WNTs. The BRET
acceptor (bandpass filter, 535–30 nm) and BRET donor (bandpass
filter, 475–30 nm) emission signals were measured using a CLARIOstar
microplate reader (BMG, Ortenberg, Germany). Cell surface expression
of HiBiT-tagged FZDs and total expression of Nluc-FZD4 was
assessed by measuring luminescence of vehicle-treated wells (no BRET
acceptor) in the NanoBiT/BRET or NanoBRET binding assays, respectively.
eGFP fluorescence was measured prior to reading BRET (excitation,
470–15 nm; emission, 515–20 nm).
TOPFlash Reporter Gene
Assay
ΔFZD1–10 HEK 293T cells were
transfected in suspension (4 × 105 cells were transfected
in 1 mL) with 700 ng of HiBiT-tagged receptor,
250 ng M50 Super 8× TOPFlash (#12456; Addgene, Watertown, MA,
USA), and 50 ng pRL-TK Luc (#E2241, Promega, Fitchurg, WI, USA) and
seeded (50 μL) onto a poly(d-lysine)-coated white 96-well
cell culture plate with a solid flat bottom (Greiner BioOne). Next,
50 μL of complete DMEM medium was added to each well. Twenty-four
hours after transfection, the medium was changed to starvation medium
(DMEM without FBS) containing either 8.0 nM (300 ng/mL) WNT-3A or
vehicle, and 10 nM C59. Twenty-four hours after stimulation, cells
were lysed gently shaking with 20 μL 1× Passive Lysis Buffer
(#E1910; Promega, Fitchurg, WI, USA) for 15 min. Subsequently, 20
μL of LAR II (Promega, E1910) was added to all wells after which
luminescence (580–80 nm) was read, and then 20 μL of
Stop & Glo (Promega, E1910) was added to all wells after which
luminescence (480–80 nm) was read again with a CLARIOstar microplate
reader (BMG, Ortenberg, Germany).
Data Analysis and Statistics
All data were analyzed
in GraphPad Prism 8 (San Diego, CA, USA) using built-in equations.
All data presented in this study come from n individual
experiments (at least three biological replicates) with each individual
experiment performed typically in duplicates (technical replicates)
for each tested concentration/condition. Data points on the binding
curves represent mean ± SEM. Saturation binding curves were fit
using one-site-specific or total and nonspecific saturation nonlinear
regression models (linear scale for eGFP-WNT-3A concentrations) or
normalized three-parameter or normalized four-parameter nonlinear
regression models (logarithmic scale for eGFP-WNT-3A concentrations
with normalized net BRET ratio). The fitting models were selected
based on an extra-sum-of-squares F-test (P < 0.05). Kinetic binding data were analyzed using the
association model with two or more hot ligand concentrations. Binding
affinity values (Kd) are presented as
a best-fit Kd with SEM. Kd values were compared using an extra-sum-of-squares F-test (P < 0.05). Competition binding
curves were analyzed using a three- or four-parameter nonlinear regression
model to obtain equilibrium dissociation constant values pKi with SEM of unlabeled ligands as per the Cheng–Prusoff
equation.[59] Minimal BRET (BRETmin) and maximal BRET (BRETmax) were defined as the lowest
and highest measured net BRET ratios, respectively. BRETmax values were compared using unpaired t-test. TOPFlash
and cell surface expression data are presented as mean ± SEM.
TOPFlash and cell surface expression data were analyzed for differences
with Brown–Forsythe and Welch one-way analysis of variance
(ANOVA); ** P ≤ 0.01, * P ≤ 0.05.
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