The nanoscale spatial organization of transmembrane tumor necrosis factor (TNF) receptors has been implicated in the regulation of cellular fate. Accordingly, molecular tools that can induce specific arrangements of these receptors on cell surfaces would give us an opportunity to study these effects in detail. To achieve this, we introduce DNA origami nanostructures that precisely scaffold the patterning of TNF-related apoptosis-inducing ligand-mimicking peptides at nanoscale level. Stimulating human breast cancer cells with these patterns, we find that around 5 nm is the critical interligand distance of hexagonally patterned peptides to induce death receptor clustering and a resulting apoptosis. We thus offer a strategy to reverse the non-efficacy of current ligand- and antibody-based methods for TNF superfamily activation.
The nanoscale spatial organization of transmembrane tumor necrosis factor (TNF) receptors has been implicated in the regulation of cellular fate. Accordingly, molecular tools that can induce specific arrangements of these receptors on cell surfaces would give us an opportunity to study these effects in detail. To achieve this, we introduce DNA origami nanostructures that precisely scaffold the patterning of TNF-related apoptosis-inducing ligand-mimicking peptides at nanoscale level. Stimulating human breast cancer cells with these patterns, we find that around 5 nm is the critical interligand distance of hexagonally patterned peptides to induce death receptor clustering and a resulting apoptosis. We thus offer a strategy to reverse the non-efficacy of current ligand- and antibody-based methods for TNF superfamily activation.
Entities:
Keywords:
DNA origami; TRAIL-mimicking peptide; apoptosis; death receptor clustering; hexagonal pattern
Because the tumor necrosis
factor (TNF) receptor superfamily (TNFRSF)
plays important roles in cell proliferation, cell death, immune regulation,
and morphogenesis, it has been extensively targeted for disease treatment.[1−5] Although structural information on TNFRSF, corresponding ligands,
and even the receptor–ligand complexes have been quite thoroughly
characterized,[6,7] molecular tools and drugs that
can effectively trigger TNFRSF signaling are still missing.[3,5] Currently available agonists usually fail to work as expected.[8] A typical example is the TNF-related apoptosis-inducing
ligand (TRAIL). TRAIL can recognize and bind to death receptor 4 (DR4)
and death receptor 5 (DR5).[9] Human TRAIL
(Dulanermin) and DR4/5 agonistic monoclonal antibodies (e.g., Mapatumumab and Lexatumumab) have been under clinical trials as
anticancer therapeutics since the mid-1990s.[10,11] Randomized control trials have however recently shown that their
efficiency in terms of survival benefits is lacking.[12,13] Studies of TRAIL–DR5 complexes on cells displaying apoptosis
have revealed that the transmembrane domain of DR5 formed higher-order
structures through clustering.[14] Thus,
one potential reason for the lack of efficacy could be that death
receptor triggering via the natural ligand/antibody–receptor
binding mechanism, might not be strong enough to cause receptor clustering.
To explore this, anti-TRAIL antibodies, which can cross-link TRAIL,
were used together with TRAIL to promote the formation of DR5 clusters.[15,16] This strategy improved the apoptosis of cancer cells. Another strategy
was to covalently multimerize TRAIL or TRAIL-mimicking peptide on
peptide-, dextran-, or graphene-based scaffolds,[17−20] which was also demonstrated to
be efficient. However, using these strategies it is typically not
possible to precisely control the nanoscale spatial presentation of
the proteins or peptides. By conjugating ligands onto surfaces with
prepatterned nanodot arrays, other groups have achieved a nanoscale
arrangement of TNF with spacings between 58 and 290 nm.[21] Cell culture on those surfaces showed a dependence
on interligand distances, revealing the importance of interligand
distance control for efficient death receptor activation. Nevertheless,
the achievable smallest interdot distance was the size of nanodots
themselves, making, for example, sub-10 nm interdot arrangement a
challenge. Also, note that in display experiments where a surface
is covered in ligands, both the number and spatial separation between
them vary at the same time. Consequently, surfaces with differently
spaced ligands would also display different overall ligand amounts
at the surface–cell interface, which could also affect cell
activity, giving potentially confounded interpretations. On top of
this, clinical translations of surface patterning methods are typically
limited as the path from patterning large planar surfaces to patterning
biocompatible nanoparticles is not straightforward.In contrast,
DNA origami nanostructures[22−29] offer both a programmable way to precisely display biomolecule nanopatterns
from monodisperse particles and, through this, a way to display these
to cells from the solution phase. This allows us to vary the separation
of ligands independently from the total dosage or total concentration
of ligands and further allows us to focus solely on the spatial separation
between ligands on the nanoscale. Thanks to its spatial addressability,[30−33] varying nanopatterns of ephrin-A5,[34,35] caspase-9
variant,[36] antigens of human IgGs and IgMs,[37] immunogen eOD-GT8,[38] and Fas ligands[39] on DNA origami nanostructures
have been studied, showing an increasing importance for biomedical
applications.
Results and Discussion
To investigate
the effect of differing ligand pattern sizes on
death receptors, we prepared two versions of DNA origami as templates:
a single-layer wire frame (W) flat sheet (Figure a) and a double-layer square lattice (L)
style flat sheet (Figure b and Supporting Information (SI) Figures S1 and S2). Sharp electrophoresis bands of structures (before
and after purification) on 2% agarose gels (Figure S3) and expected structural characteristics under atomic force
microscopy (AFM) (Figure c,d) indicate successful structure preparations. We produced
a collection of structures displaying protruding 5′ single-stranded
DNA (ssDNA) handles for subsequent hybridization of ssDNA–ligand
conjugates.
Figure 1
Structure design and characterization. (a) Stylized renderings
of the single-layer W-structure (top view), together with a highlight
of its DNA arrangement details. (b) Stylized renderings of the double-layer
L-structure (side view, front view, and top view), together with a
highlight of its DNA arrangement details. The scaffold DNA is colored
in dark blue, and staples are in gray. (c and d) Two types of structures
imaged by atomic force microscopy. Scale bars are 100 nm. (e) Computed
mean structures and RMSF of the W- and L-structures using oxDNA, top
and front views. (f) Schematic illustration of how the TRAIL-mimicking
peptides are attached to the DNA origamis (same scheme in both W and
L). (g) Schematic illustration of how breast cancer cell apoptosis
can be triggered by peptide patterns on DNA origami templates by inducing
clustering of death receptor 5.
Structure design and characterization. (a) Stylized renderings
of the single-layer W-structure (top view), together with a highlight
of its DNA arrangement details. (b) Stylized renderings of the double-layer
L-structure (side view, front view, and top view), together with a
highlight of its DNA arrangement details. The scaffold DNA is colored
in dark blue, and staples are in gray. (c and d) Two types of structures
imaged by atomic force microscopy. Scale bars are 100 nm. (e) Computed
mean structures and RMSF of the W- and L-structures using oxDNA, top
and front views. (f) Schematic illustration of how the TRAIL-mimicking
peptides are attached to the DNA origamis (same scheme in both W and
L). (g) Schematic illustration of how breast cancer cell apoptosis
can be triggered by peptide patterns on DNA origami templates by inducing
clustering of death receptor 5.Because of the different structural design methods for W and L,
they are expected to possess differences in local rigidity and propensity
for thermal fluctuation. The mean structures, which were computed
from oxDNA molecular dynamics simulation[40,41] in 500 mM Na+ (simulation parameter), showed that the
L-type structure tended to stay flatter than the W-types (Figure e). Root mean square
fluctuation (RMSF) values of the Ws are estimated to be around 5 times
higher than those of the Ls (Figure e), further validating its higher local structural
flexibility. These differences are a consequence of the design schemes
that can be attributed to the fact that DNA helices in L (Figure b) are more restrained
through multiple connections to other helices in the structures as
is common in lattice-based 3D origami. This analysis and similar previous
investigations on wire frame structures[42] suggest that the displayed separations on the W-structures are probably
fluctuating more during experiments than the corresponding ones on
the L-structures.Homotrimeric TRAIL is the natural ligand of
DR5, although it is
still not clear if the oligomeric state of the preligand DR5 association
is trimeric (Figure S7a)[43] or dimeric (Figure S7e).[7,14,44] We used a small cyclic peptide
composed of 17 amino acids (Figure S5).
This peptide has shown its ability to compete the binding of homotrimeric
TRAIL to preligand DR5 association and thus mimic TRAIL’s functions.[45,46] The rationale for this was 2-fold: (1) The much smaller spatial
dimension of the peptide, which has its van der Waals radius at ∼1.5
nm (Figure S4a), could allow sub-10 nm
interligand spacing, while the spatial dimension of homotrimeric TRAIL
(PDB ID 1DG6) itself is already around 10 nm (Figure S4b). (2) There is an ease of DNA conjugation: conjugating a protein
such as TRAIL monomer/trimer with ssDNA could potentially result in
multiple modifications per protein or complex. This would in turn
risk having one protein occupy more than one binding site of the DNA
origami, impeding the formation of expected protein patterns. In contrast,
we could easily achieve one ssDNA per peptide conjugation by chemically
targeting one prefunctionalized site of the peptide.We produced
the ssDNA–peptide conjugate via click chemistry
between an azide functionalized lysine residue located
at the C-terminal of the peptide and a dibenzocyclooctyne (DBCO) modification
at the 5-prime end of the ssDNA (Figure S5). On native polyacrylamide gels, the conjugate had a slower electrophoretic
migration than the peptide itself, which was clearly visualized by
fluorescent DNA labeling and peptide staining (Figure S6), verifying the reliability of this conjugation
method. Importantly, we used a strategy where the conjugation site
is on the 5-prime end and binding to a 5-prime end protrusion, thus
constraining the peptide close to the site on the DNA origami where
the protrusion originates (Figure f). Proceeding this way, we avoid a large distance
being introduced by the hybridization.Previous studies on DR5
clusters on apoptotic cells have led to
a hypothesis that a nanoscale hexagonal DR5 network formed through
the dimerization of DR5 trimers (Figure S7b,c) can directly result in apoptosis.[47] More
recent studies have then shown that the signaling driver is more likely
due to the formation of higher-order transmembrane helix (TMH) structures via the trimerization of DR5 dimers (Figure S7f,g). Similar to earlier hypotheses though, the potential
clustering network mediated by DR5 TMH would again be presented by
a hexagonal pattern.[14] This formation,
however, is inhibited by the extracellular domain of DR5 unless the
receptor is externally induced to cluster. Antibody AMG655 can promote
the homotrimeric TRAIL’s efficacies on DR5 clustering and antitumor
activity. Position modeling of the crystallographically decoded TRAIL-DR5-AMG
655 Fab ternary complex further emphasized the importance of the hexagonal
honeycomb DR5 pattern on apoptosis (Figure S7d,h).[15] Following this, we aimed to develop
a method to precisely induce this active hexagonally organized DR5
network in breast cancer cells, irrespective of whether the actual
molecular mechanism to trigger apoptosis is dimerization of DR5 trimers
or trimerization of DR5 dimers (Figure g).We thus decided to investigate patterns of
peptides displayed in
hexagons, where all patterns had sizes less than 50 nm in intrapeptide
spacing. We investigated 5.7 nm (W6), 9.43 nm (W9), 15.8 nm (W16),
18.8 nm (W19), and 25.5 nm (W26) peptide patterns on the W-structures
(Figure S8) and 6.3 nm (L6) and 11.1 nm
(L11) peptide patterns on the square L-structures (Figures S9 and S10). The nominal distances used in the naming
of the structures are taken from the mean distance of the six individual
nucleotide-to-nucleotide distances (corresponding to the 6 edges of
the hexagons) on the DNA origami from oxDNA molecular dynamics simulations
(Figure S11). First, electrophoresis of
these structures on agarose gel shows clean monomeric products (Figures S12 and S13). Peptide attachment does
not appear to affect the gel mobility, which could be expected since
the molecular weight increase (from 5.02 to 5.06 MDa), resulting from
hybridizing the peptide–DNA conjugates to the origamis, is
minute (0.80% increase). Instead, to verify the correct localization
of peptides on structures, we performed a DNA-PAINT experiment: For
this analysis only, we inserted 9 extra nucleotides (NTs) between
the peptide and the origami-hybridizing region close to the 5′
of the DNA in the ssDNA–peptide conjugates (Figure a). These 9 NT regions were
used as docking sites for transient binding of Atto 550-labeled DNA
imager strands. This transient binding process was then imaged using
DNA-PAINT.[48−50] Imaging results showed the expected hexagonal patterns
(Figure b and Figures S14–S23), indicating an overall
correct localization of the peptides on DNA origami. Not all structures
in each sample showed a 6-spot hexagonal pattern, and the distribution
analysis showed individual site occupancy rates of 49–76%,
depending on structure (Figure S24). The
occupancy rate was however estimated to be higher following gel analysis
(see below), and it is likely that the microscopy analysis is underestimating
the incorporation possibly due to the 9nt PAINT-imaging sites getting
sterically blocked from PAINT–probe binding as they lie sandwiched
between the protruding site dsDNA and the peptide itself. The pattern
size distributions calculated from DNA-PAINT data appear smaller,
particularly for the larger patterns, than the sizes in design and
oxDNA simulations (Figure S25). This is
to some degree expected as the wire frame structures have a higher
sensitivity for global deformations (which would primarily impact
the larger patterns) as the structures land on the biotinylated surface
during PAINT imaging. Note that this strategy is not imaging empty
sites, but importantly we are estimating the actual incorporation
of DNA–peptide conjugates by targeting the conjugate strand
itself with the PAINT probes (Figure a).
Figure 2
Peptide pattern imaging and quantification. (a) Schematic
illustration
of how Atto 550-labeled imager
strands transiently bind to the 9 extra nucleotides (NTs) region between
the peptide and the origami-hybridizing region of the DNA in the ssDNA–peptide
conjugate in DNA PAINT experiment. (b) Representative DNA-PAINT images
of the differently sized peptide patterns on DNA origamis. Scale bars
are 50 nm. W37 is a 37 nm peptide pattern on a wire frame structure
used exclusively as a reference during PAINT imaging and analysis.
(c and d) W6-structures decorated with varying numbers of peptides
were treated with DNase I to completely digest the DNA origami template.
The samples were then run on an SDS-PAGE gel, imaged via silver staining. L = protein ladder, P = peptide alone, C = empty
origami control, I–VI = decorated origamis according to panel
c. (e) Dosiometry of the gel images plotted as estimated protrusion
site occupancy by ssDNA–peptide conjugate on W6 (with varying
numbers of protruding ssDNA sites). (f) Similar analysis of all estimated
calculated protrusion site occupancies by ssDNA–peptide conjugate
on the different DNA origamis (with 6 protruding DNA sites) used in
the study.
Peptide pattern imaging and quantification. (a) Schematic
illustration
of how Atto 550-labeled imager
strands transiently bind to the 9 extra nucleotides (NTs) region between
the peptide and the origami-hybridizing region of the DNA in the ssDNA–peptide
conjugate in DNA PAINT experiment. (b) Representative DNA-PAINT images
of the differently sized peptide patterns on DNA origamis. Scale bars
are 50 nm. W37 is a 37 nm peptide pattern on a wire frame structure
used exclusively as a reference during PAINT imaging and analysis.
(c and d) W6-structures decorated with varying numbers of peptides
were treated with DNase I to completely digest the DNA origami template.
The samples were then run on an SDS-PAGE gel, imaged via silver staining. L = protein ladder, P = peptide alone, C = empty
origami control, I–VI = decorated origamis according to panel
c. (e) Dosiometry of the gel images plotted as estimated protrusion
site occupancy by ssDNA–peptide conjugate on W6 (with varying
numbers of protruding ssDNA sites). (f) Similar analysis of all estimated
calculated protrusion site occupancies by ssDNA–peptide conjugate
on the different DNA origamis (with 6 protruding DNA sites) used in
the study.To further verify the stoichiometry
of peptides on each structure,
we performed a protein gel analysis after a DNase treatment. Briefly,
fully assembled and purified test structures including the positioned
peptides, were first incubated with DNase I (Figure c and Figure S26a). Following this, we ran the resulting degradation products on SDS-PAGE
gels and stained for peptides, after which we performed dosimetry
analysis on the lanes to estimate the total peptide content in the
samples. The analysis showed a clear correlation between the number
of protruding DNA sites per structure and the silver staining intensity
of peptide bands (Figure d and Figure S26b), corroborating
a close match between the designed stoichiometry and the experimental
implementation of the structures. On both W- and L-structures, we
estimate that the average protruding DNA site occupancy by ssDNA–peptide
conjugate was decreasing, from around 93% (sample of structure with
1 protrusion site) to around 75% (sample of structure with 6 protrusion
sites), with increasing number of protrusion sites (Figure e and Figure S26c). This could probably be attributed to a combination of
charge- and steric-hindrance effects and is often observed in functionalized
DNA origami with many sites.[34,51,52] In the target hexagonal peptide patterns, the estimated percentage
of site occupancy is between 75 and 80% (Figure f), which is slightly higher than the corresponding
values from the DNA-PAINT assay (Figure S24).Human cancer cells can respond to TRAIL treatment very differently.[53] When it comes to breast cancer cells, the triple-negative
mesenchymal ones, to which MDA-MB-231 cells belong, were found to
be sensitive to TRAIL.[54] However, those
having receptors for estrogen, which include MCF-7 cells, appear to
be largely resistant to TRAIL. Those with Her-2 upregulation, including
the SK-BR-3 cells, also appear to have a low sensitivity to TRAIL
treatment. Although the expression level of death receptors could
partially be linked to this phenomenon,[55] and intracellular negative feedbacks on TRAIL response were revealed
in certain cells,[56] the actual mechanisms
behind this discrepancy are still not well understood. We used MDA-MB-231,
MCF-7, and SK-BR-3 cell lines to cover all of these three types of
human breast cancer.To visualize DR5 clusters, we first established
GFP-DR5-expressing
cells by plasmid transfection (Figure a). We then treated these cells with DNA origami presenting
TRAIL-mimicking peptide patterns, following by imaging cells under
confocal microscopy. On all cell lines, it showed that (Figure b–e) neither did peptide
itself nor did DNA origami structures themselves have observable effects
on DR5 clustering; for peptide patterns, W6 and W9 successfully caused
DR5 clusters, while W16, W19, or W26 did not. This size-dependent
effect indicated that, to trigger the process of DR5 clustering, peptides
need to be patterned closely enough and around 10 nm seemed to be
the critical distance. We also observed significant differences between
cells treated with W6 and cells treated with W9. We then further investigated
this with the stiffer structures—L6 and L11. The results showed
that (Figure b–e),
being more effective than W6, L6 successfully triggered DR5 clustering.
Interestingly, being different from W9, L11 failed to cause DR5 clustering.
The main reason for this is probably the different distances (higher
spatial density of ligands in W9), but it cannot be ruled out that
some of the observed differences could have arisen from the internal
structure differences between W- and L-structures, for example a slightly
higher charge density of L-structures due to their more closely packed
DNA.
Figure 3
Peptide patterns-induced GFP-DR5 clusters. (a) Experimental workflow.
(b) GFP-DR5 (cyan) clusters in breast cancer cells with 4 h treatments
of 2-nM DNA origami structures or 12 nM peptides. Scale bars are 20
μm. The enlarged panels above correspond to the indicated areas
in the panels below. (c–e) GFP-DR5 cluster counting of MCF-7
cells (c), SK-BR-3 cells (d), and MDA-MB-231 cells (e). Each point
stands for the number of GFP-DR5 clusters for one cell (n = 100 cells). PBS stands for phosphate-buffered saline, and PEP
stands for peptide. ***, p < 0.001.
Peptide patterns-induced GFP-DR5 clusters. (a) Experimental workflow.
(b) GFP-DR5 (cyan) clusters in breast cancer cells with 4 h treatments
of 2-nM DNA origami structures or 12 nM peptides. Scale bars are 20
μm. The enlarged panels above correspond to the indicated areas
in the panels below. (c–e) GFP-DR5 cluster counting of MCF-7
cells (c), SK-BR-3 cells (d), and MDA-MB-231 cells (e). Each point
stands for the number of GFP-DR5 clusters for one cell (n = 100 cells). PBS stands for phosphate-buffered saline, and PEP
stands for peptide. ***, p < 0.001.In both W- and L-cases, notably, for all three cell lines,
treated
cells having GFP-DR5 clusters that showed high colocalizations with
Cy5-labeled DNA origami (Figure a–d). It shows that, for W6-, W9-, and L6-treated
cells, the colocalizations of DNA origami to GFP-DR5 clusters are
similarly around 70%. The reasons this is not 100% could be due to
(1) Cy5 loss during the washings, (2) the sensitivity limitation of
the imaging method, and/or (3) the signal filtering threshold setting
during our image analysis. We also found that if we study patterns
of L6 with purposely removed peptides, on MCF-7 cells, the extent
of DR5 clustering decreased with respect to the removal of peptides
(Figure S27), validating the importance
of having full patterns for optimal clustering. With these results
together, we concluded that DR5 clustering is a precisely controlled
cellular process, whose effective triggering needs around 5 nm-spaced
hexagonal ligand patterns.
Figure 4
DNA origamis and GFP-DR5 clusters colocalization.
(a) Localization
of DNA origami (magenta) relative to GFP-DR5 (cyan) clusters. The
cells were treated with 2 nM DNA origami structures or 12 nM peptides
for 4 h. Scale bars are 20 μm. (b–d) Percentage of DNA
origami colocalized with GFP-DR5 clusters (n = 50
fields) from MCF-7 (b), SK-BR-3 (c), and MDA-MB-231 (d) cells. ***, p < 0.001.
DNA origamis and GFP-DR5 clusters colocalization.
(a) Localization
of DNA origami (magenta) relative to GFP-DR5 (cyan) clusters. The
cells were treated with 2 nM DNA origami structures or 12 nM peptides
for 4 h. Scale bars are 20 μm. (b–d) Percentage of DNA
origami colocalized with GFP-DR5 clusters (n = 50
fields) from MCF-7 (b), SK-BR-3 (c), and MDA-MB-231 (d) cells. ***, p < 0.001.On the basis of these
DR5 clustering results, we then measured
the apoptosis in nontransfected cell lines. On all three cell lines
(Figure ), W6 or W9
induced significantly more apoptotic and apoptosis-resulted necrotic
cells than W16, W19, and W26. For cells treated with L6 or L11, however,
only L6 showed a strong apoptosis-inducing capability. Empty DNA origami
or peptide itself showed no effect.
Figure 5
Apoptosis of cells treated with peptide
patterns. (a, c, e) Representative
MCF-7 (a), SK-BR-3 (c), and MDA-MB-231 (e) cell apoptosis induced
by indicated treatments (24 h with 2 nM DNA origami structures or
12 nM peptides). Q1, percentage of cell necrosis; Q2, percentage of
apoptosis-induced necrosis; Q3, percentage of cell apoptosis; Q4,
percentage of alive cells. (b, d, f) Percentages of apoptosis and
apoptosis-induced necrosis (Q2 plus Q3) for MCF-7 (b), SK-BR-3 (d)
and MDA-MB-231 (f) cells. Each point stands for the mean value of
one biological replicate (n = 3). Each biological
replicate includes 6 technical replicates. PBS stands for phosphate-buffered
saline, and PEP stands for peptide alone. *, p <
0.05; ***, p < 0.001.
Apoptosis of cells treated with peptide
patterns. (a, c, e) Representative
MCF-7 (a), SK-BR-3 (c), and MDA-MB-231 (e) cell apoptosis induced
by indicated treatments (24 h with 2 nM DNA origami structures or
12 nM peptides). Q1, percentage of cell necrosis; Q2, percentage of
apoptosis-induced necrosis; Q3, percentage of cell apoptosis; Q4,
percentage of alive cells. (b, d, f) Percentages of apoptosis and
apoptosis-induced necrosis (Q2 plus Q3) for MCF-7 (b), SK-BR-3 (d)
and MDA-MB-231 (f) cells. Each point stands for the mean value of
one biological replicate (n = 3). Each biological
replicate includes 6 technical replicates. PBS stands for phosphate-buffered
saline, and PEP stands for peptide alone. *, p <
0.05; ***, p < 0.001.We also checked a cleaved caspase-8 level, which is the key molecular
indicator of apoptotic cascades,[57] by cell-based
ELISA (Figure a).
The most cleaved caspase-8 was detected in MCF-7 cells treated by
L6, showing a higher extent of apoptosis and apoptosis-induced necrosis
(Figure b and Figure S28). On all cell lines, the viability
of cells treated by L6 was the lowest among different treatments (Figure c–e). This
circumvents the previously revealed TRAIL resistance of MCF-7 cell
line. The half-maximal inhibitory concentrations (IC50)
of the peptide were significantly reduced after being patterned on
DNA origami (W6, W9, and L6) (Table S1).
Combining the data from these measurements and the GFP-DR5 clustering
results showed clear correlations (Figure f–h), verifying that lower cell viabilities
were most likely resulted from an effective DR5 clustering.
Figure 6
Cell viability.
(a) Workflow of cell-based ELISA for cleaved caspase-8
detection. (b) Normalized (to GAPDH) cleaved caspase-8 level after
the treatment (1.5 h with 2 nM DNA origami structures or 12 nM peptides).
(c–e) Cell viability assay with indicated treatments (48 h
with 2 nM DNA origami structures or 12 nM peptides) from MCF-7 (c),
SK-BR-3 (d), and MDA-MB-231 (e) cells. Each point stands for the mean
of 6 technical replicates from 1 biological replicate. There are 3
biological replicates. (f–h) Correlation of viability of MCF-7
(f), SK-BR-3 (g), and MDA-MB-231 (h) cells to the number (per 10 cells)
of GFP-DR5 cluster. For each treatment, 6 groups of independent data
are presented. PBS stands for phosphate-buffered saline, and PEP stands
for peptide. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Cell viability.
(a) Workflow of cell-based ELISA for cleaved caspase-8
detection. (b) Normalized (to GAPDH) cleaved caspase-8 level after
the treatment (1.5 h with 2 nM DNA origami structures or 12 nM peptides).
(c–e) Cell viability assay with indicated treatments (48 h
with 2 nM DNA origami structures or 12 nM peptides) from MCF-7 (c),
SK-BR-3 (d), and MDA-MB-231 (e) cells. Each point stands for the mean
of 6 technical replicates from 1 biological replicate. There are 3
biological replicates. (f–h) Correlation of viability of MCF-7
(f), SK-BR-3 (g), and MDA-MB-231 (h) cells to the number (per 10 cells)
of GFP-DR5 cluster. For each treatment, 6 groups of independent data
are presented. PBS stands for phosphate-buffered saline, and PEP stands
for peptide. *, p < 0.05; **, p < 0.01; ***, p < 0.001.To fully determine whether or not these peptide patterns on DNA
origami (W6, W9, and L6) are more effective on apoptosis induction
than other DR5 agonists, such as cross-linking TRAIL by antibodies[15,16] or pre-cross-linking TRAIL/TRAIL-mimicking peptides by peptides/proteins/polymers,[17−20] comparative studies would be needed. Furthermore, the efficacy and
potential side effects of our peptide patterns for treatment applications
need to be further investigated on animal models.
Conclusions
In conclusion, we demonstrated an effective strategy of using a
DNA origami method to regulate death receptor clustering and following
cell apoptosis. This offers a precise and reliable way to understand
the importance of nanoscale ligand spatial organization and its control
over apoptosis triggering. Notably, this approach does not rely on
surface patterning and the stimulating patterns are displayed from
solution. The fact that monomeric binders, as were used in this study,
are able to trigger apoptosis could indicate that the preligand clustering
state of DR5 is less important than was previously thought and that
the clustering of DR5, whatever the preligand state may be, is enough
to trigger apoptosis. By tuning the size of hexagonal TRAIL-mimicking
peptide pattern, we conclude that the interpeptide distance for effective
apoptosis was sub-10 nm. Surprisingly, this method worked on both
TRAIL-sensitive and breast cancer cells that were previously deemed
to be resistant. Our findings also reveal that precise spatial pattern
screening of drug molecules at the nanoscale could be a potential
way to alleviate some of the non-efficacy problems of currently approved
TNFRSF-targeting drugs.
Experimental Section
Peptide–DNA
Conjugate
We purchased the cyclic
peptide (WDCLDNRIGRRQCVKL), with an azide modification at its C-terminal,
from JPT Peptide Technologies. We purchased oligonucleotide (TAGATGGAGTGTGGTGTG),
with a dibenzocyclooctyne (DBCO) modification at its 5-prime, from
Integrated DNA Technologies. The molar ratio of peptide to oligonucleotide
in the reaction was 10 to 1. We carried out the reaction in PBS pH
7.4, under room temperature, overnight. We used an Amicon 3K filter
tube (Millipore) to purify a small amount (100 μL, 100 nM) of
conjugate. The process was done with centrifugation at 14000g for 30 min and was repeated 3 times. We purified a big
amount of conjugate (above 100 μL and 100 nM) via a proFIRE system (Dynamic Biosensors).
Silver Staining
We performed this using the ProteoSilver
Silver Stain Kit (Sigma-Aldrich) according to its established protocol.
Briefly, we placed gels in 100 mL of fixing buffer (50 mL of ethanol,
40 mL of Milli-Q water, and 10 mL of glacial acetic acid) overnight.
Subsequently, we washed the gels for 10 min in 30% ethanol solution
and then in 200 mL of Milli-Q water for 10 min and sensitized the
gels in 100 mL of sensitization solution (1 mL of ProteoSilver sensitizer
in 99 mL of Milli-Q water). Following this, we washed the gels once
more in Milli-Q water for 10 min, equilibrated the gels in silver
solution (1 mL of ProteoSilver silver solution and 99 mL of Milli-Q
water) for 10 min, followed by two brief washes in Milli-Q water.
The gels were then developed for approximately 5 min in 100 mL of
developer solution (5 mL of ProteoSilver Developer 1, 0.1 mL of ProteoSilver
Developer 2, and 95 mL of Milli-Q water) after which the reaction
was stopped by adding 5 mL of the provided stopping solution for at
least 10 min. Stained gels were imaged using the GE LAS 4000 gel imager.
Peptide-Patterned DNA Origami Production
Step 1: p8064 Scaffold
DNA Production
In a shaker at
37 °C, we cultured Escherichia coli (E. coli) strain JM109 in 250 mL of 2× Yeast extract
Tryptone growth medium (Sigma-Aldrich) with 5 mM MgCl2 (Sigma-Aldrich)
until its optical density at 600 nm reached 0.5. Then we added the
phage containing p8064 scaffold DNA to the bacteria at a multiplicity
of infection of 1, after which the phage was amplified with shaking,
under 37 °C, for 4 h. We collected the culture and then centrifuged
at it 4000g for 30 min to pellet the bacteria. The
supernatant, which contained the phage, was kept, followed by adding
10 g of PEG8000 (VWR International) and 7.5 g of NaCl (VWR). We then
incubated the supernatant with ice for 30 min and centrifuged it at
10000g for 30 min to pellet the phage. We resuspended
the phage in 10 mL of Tris buffer (10 mM, pH 8.5, VWR) and added 10
mL of a solution containing 0.2 M NaOH (VWR) and 1% SDS. Then we denatured
the phage protein coat by adding 7.5 mL of 3 M KOAc (VWR), pH 5.5,
and gently mixing, incubating on ice for 10 min. The sample was next
centrifuged at 16500g for 30 min to pellet the denatured
phage proteins. The supernatant containing p8064 scaffold DNA was
collected, and 50 mL of 99.5% EtOH (Sigma-Aldrich) was added, mixed
gently, and incubated on ice for another 30 min. The sample was centrifuged
at 16500g for 30 min to pellet the p8064 scaffold
DNA. The pellet was then washed with 75% EtOH and air-dried at room
temperature for 15 min, followed by resuspending in 10 mM Tris, pH
8.5. The concentration and quality were characterized by UV–vis
(NanoDrop, Thermo Scientific) and a 2% agarose gel, respectively.
Step 2: DNA Origami Folding and Purification
Staple
oligonucleotides (SI Table S1), with the
concentration of 100 μM in Milli-Q water, were ordered from
Integrated DNA Technologies in 96-well plates. DNA concentrations
used for structure folding were as follows: 20 nM ssDNA scaffold and
100 nM per staple DNA. For Cy5-labeled DNA origami, 6 staple DNA strands
of the structures were replaced by the same sequences but modified
with Cy5 at their 5 primes. All wFS structures were folded in PBS
by rapid heat denaturation (80 °C for 5 min) followed by cooling
from 80 to 60 °C over 20 min, then from 60 to 24 °C over
14 h. By using the same annealing program, all sFS structures were
folded in the buffer containing 13 mM MgCl2 (Sigma-Aldrich),
5 mM TRIS (VWR), and 1 mM EDTA (VWR). Folded structures were purified
and concentrated by using Amicon 100 K filter tube (Millipore). The
process included 6 times washings with the folding buffer at 5000g for 2 min.
Step 3: Peptide Attachment to DNA Origami
The peptide–DNA
conjugates were added with a 10-fold excess to each protruding site
on the DNA origami and incubated in the thermocycler (Bio-Rad) at
37 °C for 1 h, followed by keeping the system under room temperature
overnight.
Step 4: Removal of Excess Conjugate
This was carried
out also by using Amicon 100 K filter tubes (Millipore). The removal
process included 6 times washings with the folding buffer at 5000g for 2 min. The final concentrations of peptide-patterned
DNA origami were measured at UV–vis A260 on Nanodrop (Thermo
Scientific).
Agarose Gels Electrophoresis
2%
agarose (Sigma-Aldrich)
gels were cast in 0.5× TBE buffer (VWR) supplemented with 10
mM MgCl2 and 0.5 mg/mL ethidium bromide (Sigma-Aldrich).
For all samples, gels were run in 0.5× TBE buffer supplemented
with 10 mM MgCl2 at 90 V for 3 h on ice. Gels were imaged
under a GE LAS 4000 imager.
Gel-Based Peptide Quantification of DNA Origami
Step
1: DNA Origami Digestion
Under 37 °C, 10
μL of 20 nM DNA origami structures (with different numbers of
peptide attachment) in PBS were incubated with 0.1 U/μL DNase
I (Invitrogen) and 2 mM MgCl2 for 25 min. The goal of this
process was to completely degrade the DNA origami template, releasing
peptides from the structure.
Step 2: Gel Electrophoresis
and Peptide Staining
The
samples were then run on 4–20% gradient PAGE gel (Bio-Rad)
with 1 L buffer containing 3 g of Tris base (VWR), 14.4 g of glycine
(VWR), and 1 g of SDS (Sigma-Aldrich). After the run, the gel was
stained by the method of silver staining.
Step 3: Peptide Band Intensity
Quantification
In ImageJ,
the band areas (same size for all bands on one gel) were selected,
and the mean pixel intensities of the areas were used to compare the
peptide amount.
Step 4: Peptide Occupancy Rate Calculation
We calculated
the peptide amount of each sample on the basis of their band intensity
on the polyacrylamide gels: peptide amount of each sample = (known
peptide amount of peptide only sample × band intensity of each
sample)/(band intensity of peptide only sample). We then calculated
the protrusion site occupation (by peptide) percentage with the following
equation: occupation percentage = [peptide of each sample/(DNA original
amount of in each sample × number of protrusion sites)] ×
100%.
Atomic Force Microscopy
Samples
of μL each, with
the concentration of 1.5 nM in imaging buffer [10 mM MgCl2 (Sigma-Aldrich), 5 mM TRIS (VWR), and 1 mM EDTA (VWR)] were dropped
to freshly cleaved mica for 30 s incubation. A 4 μL aliquot
of NiSO4 (5 mM, VWR) was added for a further 5 min incubation.
We then washed the sample micasurface by 1 mL of imaging buffer. We
used a cantilever AC40 (Bruker) with a nominal spring constant of
0.09 N/m to carry out the AFM (JPK instruments Nanowizard 3 ultra)
imaging.
DNA-PAINT
Step 1: Sample Preparation for DNA-PAINT
Glass microscope
slides (VWR) and coverslips (1.5H, VWR) were cleaned with acetone
and isopropanol before drying. Double-sided Scotch tape was placed
onto the slides in two parallel stripes approximately 0.8 cm apart,
and the clean coverslips were placed on it to create flow chambers.
The channel was flushed with 1 mg/mL biotinylated-BSA (Sigma-Aldrich)
in buffer A (10 mM Tris-HCl, 100 mM NaCl, and 0.05% Tween-20, pH 7.5)
and incubated for 2 min. The channel was then washed with buffer A.
The channel was then flushed with 0.5 mg/mL streptavidin (Thermo Scientific)
in buffer A and incubated for 2 min. The channel was washed then with
buffer A. After this 80 nm of AuNP solution (Sigma-Aldrich), used
as fiducial markers, resuspended in buffer A was flushed into the
channel and incubated for 2 min followed by a washing step with buffer
A. The channel was then washed with buffer B (5 mM Tris-HCl, 10 mM
MgCl2, 1 mM EDTA, and 0.05% Tween-20, pH 8) before structures carrying
TRAIL peptides with DNA-PAINT docking sites and 6 biotin sites for
immobilization resuspended in buffer B were flushed in at 200 pM concentration
and incubated for 5 min, followed by washing with buffer B. The channel
was then flushed with imaging buffer and sealed with epoxy glue. The
imaging buffer used was based on buffer B and contained oxygen scavengers
2.4 mM PCA (Sigma-Aldrich) and 10 nM PCD (Sigma-Aldrich) and 1 mM
Trolox (Sigma-Aldrich) along with Atto-550-labeled imager strands
(IDT) at the concentration of 10 nM.The samples were imaged
with a microscope with a Nikon Eclipse Ti-E microscope frame with
the Perfect Focus system (Nikon Instruments) and an objective-type
TIRF configuration using an iLAS2 circular TIRF module (Gataca Systems).
For magnification, a 1.49 NA CFI Plan Apo TIRF 100× oil immersion
objective (Nikon Instruments) was used with a 1.5× auxiliary
Optovar magnification resulting in a final pixel size of 87 nm. For
illumination, an OBIS 561 nm LS 150 mW laser (Coherent) was used with
custom iLas input beam expansion optics (Cairn) optimized for reduced
field super-resolution imaging. Before the objective, the laser beam
was passed through a filter cube (89901, Chroma Technology) containing
an excitation quadband filter (ZET405/488/561/640x, Chroma Technology),
a quadband dichroic (ZET405/488/561/640bs, Chroma Technology), and
a quadband emission filter (ZET405/488/561/640m, Chroma Technology).
The collected light was spectrally filtered with an additional emission
filter (ET595/50m, Chroma Technology) before entering the iXon Ultra
888 EMCCD camera (Andor) used for recording. The Micromanager software
was used for acquiring 12000 frames of long time lapses of samples
using frame-transfer mode of the camera, 300 ms exposure time, 10
MHz readout rate, and no EM gain.
Step 2: Preprocessing of
DNA-PAINT Data
Localization
coordinates in the collected time lapses were calculated using the
Picasso Localize program from the Picasso software package using 2000
for the minimum net gradient for localization identification and the
MLE algorithm with 0.001 and 1000 set as convergence criterion and
maximum number of allowed iterations, respectively. The localizations
were then drift-corrected using the RCC algorithm with 200 frame fragment
size in the Picasso Render program and localizations belonging to
the gold nanoparticles used as fiducial markers were selected and
exported using the “export selected localizations” feature
of the program for later filtering. Following this the low precision
localization (localization precision > 0.03 camera pixels), asymmetric
localizations (localization ellipticity < 0.1) and multilocalizations
(photon count > mean photon count + 2 STD) were removed along localization
belonging to the gold nanoparticles using a custom Python script.
Finally, the localizations belonging to single structures were selected
using the “pick similar” feature of the Picasso Render
software (circular pick regions, 1.5 camera pixel diameter, pick similar
range of 2.0 std) starting from 30 manually picked structures and
the localization were undrifted a second time using the software’s
“undrift from picked” feature.
Processing
of DNA-PAINT Images of Peptide-Patterned DNA Origamis
Detection
of DNA Origami Structure in Localization Data
DNA origami
structures were detected using a custom Python script
from the cleaned localization data. The localizations were rendered
into a low-resolution image (20× oversampling), and clusters
of localizations were detected using contour detection and sorted
into origami ROIs centered around the detected clusters. ROIs containing
noise due to unspecific binding of imagers were removed on the basis
of the cluster size and temporal span of localization within the ROI.
Quantification of TRAIL Peptides in Structure ROIs
TRAIL
proteins were detected using a custom Python script in the
localizations sorted into origami ROIs. Localizations in each origami
ROI were rendered into high-resolution images (60×, 60×,
100×, 120×, 120×, and 150× oversampling for the
37, 28, 19, 16, 9, and 5 nm origami structures); the intensity of
images was normalized and a Gaussian smoothing filter was applied
to them. Local maxima in these images were detected, and maxima closer
than ∼0.5× the designed site distance were merged. To
only keep maxima belonging to a single origami structure, a euclidian
distance-based clustering was applied to the maxima and only the most
central clusters with the highest number of maxima were kept. The
coordinates of these maxima were then exported as detected positions
of TRAIL peptides. For quantification, the TRAIL peptide per origami
distribution was calculated from counting the detected TRAIL peptides
in each origami ROI, and for the mean nearest neighbor distance distribution
the distance to the closest neighbor was calculated for each TRAIL
position detected in an origami ROI and the mean was calculated from
that for each origami ROI in each data set.
Cell Culture
Cell lines were purchased from ATCC. All
of them were cultured in Dulbecco’s modified Eagle’s
medium (DMEM, Sigma-Aldrich) with 20% heat-inactivated FBS (Gibco)
and 100 U/mL penicillin-streptomycin (Gibco) in a humidified environment
containing 5% CO2 at 37 °C. To establish GFP-DR5-expressing
cell lines, we used Lipofectamine 3000 reagent (Thermo Fisher Scientific)
to transfect GFP-tagged human tumor necrosis factor receptor superfamily
10b (GFP-TNFRSF10B/GFP-DR5) plasmid (OriGene) into the cell lines.
The GFP sequence is tagged to the C terminus of the sequence of DR5,
and thus it locates inside the cytoplasm. For each well of a 6-well
plate, cells were cultured to be 70–90% confluent for transfection.
Then 2.5 μg of GFP-TNFRSF10B plasmid was mixed with 3.75 μL
of Lipofectamine 3000 reagent and 5 μL of P3000 reagent (reagent
in the kit) for 15 min incubation. Then we added the DNA–lipid
complex to each cell well for 2 days. The transfected cells were then
used immediately for the following treatment experiments.
Confocal Data
Collection and Image Analysis
At 24 h
prior to the transfection of GFP-DR5 plasmid, 1 × 106 cells per well were cultured on a coverslip in each well of a 6-well
plate. After 2 days, cells were washed with fresh DMEM medium containing
20% heat-inactivated FBS and 100 U/mL penicillin-streptomycin. Then
the cells were treated with peptide-patterned DNA origami structures
(Cy5-free or Cy5-labeled), at certain concentrations and for certain
periods (as indicated in corresponding figures or the caption of figures).
Finally, cells were fixed in 4% paraformaldehyde for 15 min, washed,
and stained by Fluoroshield Mounting Medium with DAPI (Abcam). Cells
were imaged on LSM710 (Zeiss). For GFP-DR5 cluster quantification
in ImageJ, images were converted into 8-bit images and filtered for
the next processing. The absolute scale in micrometers per pixel of
the image was set. The clusters were then outlined, counted, and analyzed
in ImageJ using the Analyze Particles plug-in. The GFP-DR5 cluster
size threshold was 0.500 μm2. For colocalization
analysis between Cy5-labeled DNA origami and GFP-DR5 clusters, the
analysis was performed with Colocalization Analysis plug-in in ImageJ.
Flow Cytometry
In a 6-well plate, 1 × 107 cells per well were cultured for 24 h prior to treatments. Cells
were then treated with 2 nM peptide-patterned DNA origami (equals
to 12 nM peptide) for 24 h. All cells (including dead and detached
cells that were present in the medium) were collected (centrifuge
at 3000 rpm for 5 min) and washed with cold PBS for 3 times. Cells
were resuspended and then stained with annexin V-FITC and PI, sequentially,
according to the commercial protocol of the Dead Cell Apoptosis Kit
with Annexin V-FITC and PI (Thermo Fisher Scientific).
Cleaved Caspase-8
Detection
We used the method of cell-based
ELISA with use of a Human Cleaved Caspase-8 (Asp391) Immunoassay kit
(R&D Systems).
Step 1: Culture, Treat, Fix, and Block Cells
In 100
μL of DMEM medium per well, 1.5 × 104 cells
were seeded in a 96-well black polystyrene microplate with clear bottom
(Corning) and cultured overnight. Cells were then treated with 2 nM
peptide-patterned DNA origami (equals 12 nM peptide) for 4 h. Cells
were then fixed by replacing the medium with 100 μL of 4% formaldehyde
in PBS, for 20 min under room temperature. After the fixation, cells
were washed by the Wash Buffer, kept in 100 μL of the Quenching
Buffer for 20 min, again washed by the Wash Buffer, and kept in 100
μL of Blocking Buffer for 1 h.
Step 2: Incubation of Primary
and Secondary Antibodies
After removing the Blocking Buffer
and washing the cells with Wash
Buffer, 100 μL of the primary antibody mixture containing rabbit
anticleaved caspase-8 (Asp391) and mouse antitotal GAPDH was added
for 16 h incubation under 4 °C. The primary antibodies were removed,
and the cells were washed by Wash Buffer. Then 100 μL of the
secondary antibody mixture containing HRP-conjugated antirabbit IgG
and AP-conjugated antimouse IgG was added for 2 h incubation under
room temperature to bind targeting primary antibodies.
Step 3:
Fluorogenic Detection
The secondary antibodies
were removed, and the cells were washed with Wash Buffer. A 75 μL
aliquot of substrate of HRP was added for 30 min incubation at room
temperature, followed by adding 75 μL of substrate of AP for
an additional 30 min incubation. The signals were then read under
a multimode microplate reader (Varioskan LUX): with excitation at
540 nm and emission at 600 nm for Cleaved Caspase-8 (Asp391) detection;
with excitation at 360 nm and emission at 450 nm for total GAPDH detection.
Cell Viability Assay
We used the method of ATP-based
luminescent cell viability assay with the kit named CellTiter-Glo
Luminescent Cell Viability Assays (Promega). In 100 μL of DMEM
medium per well 5 ×104 cells were seeded in a 96-well
opaque white polystyrene microplate (Corning) and cultured for 24
h. Cells were treated with various concentrations of peptide-patterned
DNA origami structures (as indicated in corresponding figures or the
caption of figures). After 48 h incubation, the plate was taken out
from the cell incubator and equilibrated at room temperature for 30
min. A 100 μL aliquot of CellTiter-Glo reagent (Promega) was
added to each well, followed by mixing for 2 min on an orbital shaker
to induce cell lysis. The plate was then incubated at room temperature
for 10 min to stabilize the luminescent signal. Finally, the luminescence
was recorded on a multimode microplate reader (Varioskan LUX). The
results of control wells containing medium without cells were used
as the background luminescence. % viable cells = (luminescencesample – luminescencebackground)/(luminescencePBS – luminescencebackground) × 100.
Statistical Analysis
All experiments were performed
in multiple distinct replicates, as indicated in the text and figure
legends. Statistical analysis was performed using R. Cluster counting data in the microscopy images were analyzed using
Kruskal–Wallis one-way analysis of variance and subsequent
Mann–Whitney U tests for further analysis between conditions.
Other data were analyzed using two-tailed Student’s t tests for 2 groups and one-way ANOVA followed by Tukey
post-tests for multiple groups. Results are expressed as mean ±
SD unless otherwise indicated. For each box-and-whisker plot, the
center line is the median and whiskers represent the minimum and maximum
values.
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