Natalia Feiner-Gracia1,2, R Alis Olea1,3, Robert Fitzner4, Najoua El Boujnouni3, Alexander H van Asbeck3, Roland Brock3, Lorenzo Albertazzi1,2. 1. Nanoscopy for Nanomedicine Group, Institute for Bioengineering of Catalonia (IBEC) , The Barcelona Institute of Science and Technology (BIST) , Carrer Baldiri Reixac 15-21, 08024 Barcelona , Spain. 2. Department of Biomedical Engineering, Institute for Complex Molecular Systems (ICMS) , Eindhoven University of Technology , 5612AZ Eindhoven , The Netherlands. 3. Department of Biochemistry, Radboud Institute for Molecular Life Sciences , Radboud University Medical Center , Nijmegen , The Netherlands. 4. Department of Mathematics and Computer Science , Eindhoven University of Technology , Post Office Box 513, 5600 MD Eindhoven , The Netherlands.
Abstract
The successful application of gene therapy relies on the development of safe and efficient delivery vectors. Cationic polymers such as cell-penetrating peptides (CPPs) can condense genetic material into nanoscale particles, called polyplexes, and induce cellular uptake. With respect to this point, several aspects of the nanoscale structure of polyplexes have remained elusive because of the difficulty in visualizing the molecular arrangement of the two components with nanometer resolution. This limitation has hampered the rational design of polyplexes based on direct structural information. Here, we used super-resolution imaging to study the structure and molecular composition of individual CPP-mRNA polyplexes with nanometer accuracy. We use two-color direct stochastic optical reconstruction microscopy (dSTORM) to unveil the impact of peptide stoichiometry on polyplex structure and composition and to assess their destabilization in blood serum. Our method provides information about the size and composition of individual polyplexes, allowing the study of such properties on a single polyplex basis. Furthermore, the differences in stoichiometry readily explain the differences in cellular uptake behavior. Thus, quantitative dSTORM of polyplexes is complementary to the currently used characterization techniques for understanding the determinants of polyplex activity in vitro and inside cells.
The successful application of gene therapy relies on the development of safe and efficient delivery vectors. Cationic polymers such as cell-penetrating peptides (CPPs) can condense genetic material into nanoscale particles, called polyplexes, and induce cellular uptake. With respect to this point, several aspects of the nanoscale structure of polyplexes have remained elusive because of the difficulty in visualizing the molecular arrangement of the two components with nanometer resolution. This limitation has hampered the rational design of polyplexes based on direct structural information. Here, we used super-resolution imaging to study the structure and molecular composition of individual CPP-mRNA polyplexes with nanometer accuracy. We use two-color direct stochastic optical reconstruction microscopy (dSTORM) to unveil the impact of peptide stoichiometry on polyplex structure and composition and to assess their destabilization in blood serum. Our method provides information about the size and composition of individual polyplexes, allowing the study of such properties on a single polyplex basis. Furthermore, the differences in stoichiometry readily explain the differences in cellular uptake behavior. Thus, quantitative dSTORM of polyplexes is complementary to the currently used characterization techniques for understanding the determinants of polyplex activity in vitro and inside cells.
Cell-penetrating peptides (CPPs),
also known as protein transduction domains, are a very promising class
of vectors for gene delivery[1] because of
their ability to facilitate cell entry of conjugated molecules.[2,3] Moreover, because of their positive charge, CPPs are ideal candidates
for the noncovalent complexation of negatively charged oligonucleotides
into nanosized particles named polyplexes.[4] The potential of polyplexes to deliver different oligonucleotide
cargo such as plasmid DNA or RNA into cells for gene therapy has been
widely explored.[5−7] Recently, mRNA has emerged as another promising option.[8−10] Polyplexes of mRNA only need to penetrate cells and escape from
the endosomes or lysosomes to the cytoplasm, where mRNA gets translated
immediately into proteins. Furthermore, mRNA is only transiently active
without the risk of insertion into the host genome, and it is fully
degraded via physiological mechanisms. Therefore, mRNA-loaded polyplexes
have recently been proposed as efficient carriers for oligonucleotide
therapy.[8−10]Despite the many gene carriers proposed and
studied, the design
of the polyplexes is still very challenging, and activity varies greatly.[11] This may also be attributed to the fact that
the structure space of delivery vectors has been navigated with a
limited understanding of the structural properties and variations
of the fabric of a polyplex. In fact, only a handful of methods for
polyplex characterization are currently available. The average hydrodynamic
size and charge of the polyplexes can be measured using dynamic light
scattering (DLS) and zeta potential or electrophoretic shift assays,
respectively.[7] Also, images from electron
microscopy (EM) and atomic force microscopy (AFM) can indicate the
polyplex size and shape,[12] thus providing
information on morphological changes.[13,14] The efficiency
of complexation is evaluated using gel electrophoresis by detecting
the presence of free pan class="Chemical">oligonucleotides, while the affinity is currently
measured using a dye exclusion assay.[7] Overall,
each of the current methods supplies valuable information; however,
they exhibit two main limitations: (i) they are mostly ensemble techniques
providing average information for the polyplexes and (ii) they are
not able to distinguish between the two components of the polyplex
and therefore miss quantitative and qualitative aspects of the composition
and inner organization of individual polyplexes. Therefore, only very
limited data is available for composing molecular models of the structure
and the composition of polyplexes.[15−17]
Here, we propose
the use of two-color direct stochastic optical
reconstruction microscopy (dSTORM) to unveil the structure and composition
of polyplexes on a single-particle basis. Recently, it has been demonstrated
that dSTORM can be used to image synthetic nanoparticles with different
chemical natures and sizes.[18−20] The nanometric resolution, down
to 20 nm, provided by this technique together with the possibility
to obtain two-color images is very promising for the characterization
of multicomponent nanometric assemblies such as polyplexes. With the
appropriate knowledge of the photophysical properties of the dye such
as the duty cycle and bleaching rate, STORM provides the possibility
to obtain quantitative information about stoichiometries and absolute
molecule numbers. In this framework, membrane receptors,[21−23] DNA origami DNA strands,[24] and accessible
binding sites on endocytic/endosomal vesicles[25] were quantified. Therefore, dSTORM can also contribute to the quantitative
understanding of polyplexes. Despite this potential, to the best of
our knowledge, the use of super-resolution for the study of gene delivery
carriers has not been explored.One of the most important experimental
degrees of freedom in polyplex
generation is the ratio of the cationic moiety and nucleic acids,
which determines the N/P ratio, the ratio of positive over negative
charge carriers. The N/P ratio determines several key properties of
the formed polyplexes such as the net charge, size, and stability.[11,26] We considered the N/P ratio to be an ideal test case to establish
a direct quantitative analysis of polyplex composition using super-resolution
dSTORM microscopy. Gene-delivery carriers consisting of mRNA complexed
with the peptidenona-arginine (R9) were imaged with molecular resolution.
Owing to the ability to simultaneously measure the size and composition
of polyplexes, our results show both qualitative and quantitative
differences in the content of mRNA and CPPs for different N/P ratios.
Moreover, dSTORM imaging can be performed in a complex matrix, which
allowed us to visualize changes in polyplex structure in blood serum.
This is key information becauase one of the reasons for the failure
of gene carriers in vivo is the lack of stability in blood. Finally,
we demonstrate that the information on polyplex stoichiometry obtained
by STORM readily explains quantitative differences in the cellular
uptake of the polyplexes. Our results highlight the potential of super-resolution
microscopy to play a pivotal role in the study of polyplexes, complementing
the existing methodologies and contributing to the rational design
of new structures to enhance cell transfection.For our dSTORM
analysis, we prepared polyplexes formed by the CPPl-nona-arginine
(R9) with a 1929-nucleotide-long mRNA coding
for firefly luciferase. R9 is a well-known cell-penetrating peptide,
and its capacity to complex and induce the cellular uptake of oligonucleotides
has been previously studied.[11,27,28] An overview of our procedure is reported in Figure a. To perform dSTORM imaging, both components
were labeled using the dSTORM-compatible, spectrally well-separated
dyes, AlexaFluor488 and Cyanine 5 for R9 and mRNA, respectively. The
peptide was labeled at the N-terminus. The mRNA was stochastically
labeled with Cy5-UTP with an average labeling ratio of 27 dyes per
molecule, as estimated from UV/vis absorption measurements (as detailed
in Supporting Information). The labeling
ratio (i.e,. the proportion of labeled molecules) was optimized to
obtain an optimal signal density for dSTORM, as described extensively
in the Materials and Methods section. STORM
images of polyplexes with nonlabeled molecules were obtained as a
control, showing almost no localization (Supporting Information Figure S6). After complexation, the polyplexes
were deposited on a glass coverslip for dSTORM imaging. Figure B,C shows representative images
of R9-mRNA polyplexes at an N/P ratio of 5. We had seen before that
well-defined polyplexes were formed for N/P ratios larger than 3.
Figure 1
Imaging
of polyplexes using dSTORM microscopy. (A) Schematic representation
of polyplex formation from mRNA-Cy5 and AlexaFluor488-R9, with imaging
and analysis. (B) Conventional fluorescent image of polyplexes at
N/P 5 (red represents mRNA molecules and green R9 molecules). (C)
dSTORM imaging of polyplexes, with the same field of view as in B.
Scale bar 2 μm. (D) Close-up images of three different areas
showing low-resolution data on the left and high-resolution data on
the right. Scale bar 400 nm.
Imaging
of polyplexes using dSTORM microscopy. (A) Schematic representation
of polyplex formation from mRNA-Cy5 and pan class="Chemical">AlexaFluor488-R9, with imaging
and analysis. (B) Conventional fluorescent image of polyplexes at
N/pan class="Gene">P 5 (red represents mRNA molecules and green R9 molecules). (C)
dSTORM imaging of polyplexes, with the same field of view as in B.
Scale bar 2 μm. (D) Close-up images of three different areas
showing low-resolution data on the left and high-resolution data on
the right. Scale bar 400 nm.
The direct comparison between conventional (B) and dSTORM
(C) microscopy
images shows how the improvement of resolution allows individual polyplexes
to be resolved, while in the conventional image it is impossible to
distinguish a single polyplex from clusters. Images revealed complexes
of 50–75 nm in radius, in agreement with DLS measurements (Supporting Information Figure S7). Interestingly,
a large amount of green signal (which corresponds to the peptide)
was not associated with the polyplexes, indicating that not all of
the peptide used in the complexation procedure was incorporated. This
observation is of special interest as most of the other characterization
methods (e.g., DLS, TEM, AFM, and gel electrophoresis) cannot detect
individual peptides and are strongly biased toward the macromolecular
assemblies. Notably, free cationic moieties may play a role in the
transfection and/or toxicity. As an example, previous studies of Vaidyanathan
et al. proved the enhanced pDNA endosomal escape of polyplexes due
to the addition of free PEI polymer.[29] Moreover,
for acylated TP10 analogs, nonincorporated peptide at higher N/P ratios
showed enhanced toxicity.[30] Therefore,
being able to visualize the noncomplex materials is of crucial importance.In addition, dSTORM imaging allowed the study of the distribution
of the pan class="Chemical">peptide and the mRNA within the polyplexes as magnified in Figure D. The observed overlap
of the two colors indicates that mRNA and R9 molecules are homogeneously
intertwined inside the polyplex, at least within the resolution of
dSTORM. A dSTORM 3D image was acquired to prove these observations
and rule out the effect of the projection, and a middle stack of a
polyplex in Supn>porting Information Figure S8 shows that both molecules are indeed intertwined. This result proves
that mRNA molecules are not exposed on the polyplex surface but are
shielded within the structure. This information is of utmost impn>ortance
when designing effective gene delivery systems because confined mRNA
will be more stable than exposed mRNA.[31]
Having successfully obtained super-resolution images of polyplexes
formed at N/P 5, we further aimed to compare the structure and distribution
of mRNA and R9 molecules for different N/P ratios. For this purpose,
we imaged polyplexes formed at N/P 1, 3, 5, and 7. The mRNA concentration
was maintained at a constant value in order to follow the complexation
of the same amount of oligonucleotides. In Figure A, a representative image of each condition
is shown. At N/P 1, the mRNA-Cy5 signal was not clustered, resulting
in more spread structures compared to the images obtained for N/P
5. Only minimal mRNA signal colocalized with the Alexa488-R9 signal
and mostly free mRNA and free peptides were present, suggesting that
the amount of R9 present at N/P 1 was not sufficient to condense mRNA
into polyplexes. The distribution of mRNA changed dramatically at
N/P 3, for which clear rounded clusters of mRNA-Cy5 were present.
Therefore, we concluded that the R9 concentration present at N/P 3
was sufficient to compact the mRNA into polyplexes. The N/P 5 and
N/P 7 polyplexes clearly contained more R9 than the N/P 3 ones. Both
N/P 5 and N/P 7 were very similar to each other, which indicates that
the charges in the mRNA were already saturated and the extra R9 remained
in solution and was not incorporated into the polyplexes. Overall,
this qualitative evaluation of dSTORM images of polyplexes formed
at different N/P ratios provided important structural information
regarding the mRNA and R9 interplay in the formation of polyplexes.
Figure 2
Structure
and stoichiometry differences of polyplexes. (A) dSTORM
images of polyplexes prepared at N/P ratios of 1, 3, 5, and 7 from
left to right. (B) Frequency histograms of the size of the polyplexes
quantified from the STROM images for each N/P ratio. (C) Box plot
comparing the number of localizations of mRNA and peptide quantified
for each N/P ratio together with the quantification of single molecules
and the number of localizations obtained from the simulations. Statistical
analyses were run (Mann–Whitney test), showing significant
differences between the peptide content in NP3 and NP5 (p < 0.0001) and the mRNA content between NP1 and NP3 (p < 0.0001). Scale bar 200 nm.
Structure
and stoichiometry differences of polyplexes. (A) dSTORM
images of polyplexes prepared at N/P ratios of 1, 3, 5, and 7 from
left to right. (B) Frequency histograms of the size of the polyplexes
quantified from the STROM images for each N/P ratio. (C) Box plot
comparing the number of localizations of mRNA and peptide quantified
for each N/P ratio together with the quantification of single molecules
and the number of localizations obtained from the simulations. Statistical
analyses were run (Mann–Whitney test), showing significant
differences between the peptide content in NP3 and NP5 (p < 0.0001) and the mRNA content between NP1 and NP3 (p < 0.0001). Scale bar 200 nm.In dSTORM, the image reconstruction is based on single-molecule
localizations detected during the imaging.[32] Therefore, dSTORM provides a highly powerful approach to analyzing
the polyplexes not only qualitatively but also quantitatively.[33] Using an adapted version of a previously developed
MatLab script,[34] the localizations in the
mRNA-Cy5 channel were clustered in order to remove the free R9 localizations
on the glass coverslip and to provide an estimation of the localizations
of mRNA and CPP molecules at different complexation ratios. (The procedures
are described in the SI.) In Figure B, the size of the polyplexes
quantified for each N/P ratio is plotted on a frequency histogram.
The radius of the polyplexes was between 60 and 80 nm under all conditions;
however, the polydispersity of N/P 1 was significantly higher compared
to that of the other ratios. N/P 1 polyplexes had a significant population
of polyplexes exceeding 100 nm in size, indicating that under this
condition most of the mRNA molecules were not packaged. For N/P 3
to 7, the formation of polyplexes reduced the size of the structures,
also obtaining more monodisperse populations with no significant differences
between N/P 3 and 7. Notably, for all conditions, the sizes quantified
by dSTORM matched the DLS ensemble measurements (Supporting Information Figure S7).In Figure C, the
median number of localizations per polyplex detected for each N/pan class="Chemical">P
ratio, which is propn>ortional to the number of molecules of the specific
compn>onent, is plotted to unveil the compn>osition of the polyplexes
for the different conditions. More than 15 000 polyplexes were
measured per N/pan class="Chemical">P ratio. The frequency histogram of the number of localizations
is represented in Supporting Information Figures S9–S12.
To better understand the data in Figure C, the median number
of localizations per
polyplex was plotted together with two more conditions: (i) polyplexes
with only one labeled mRNA molecule or only one labeled R9 molecule
and (ii) simulated data obtained from a stochastic blinking model.
(See the Supporting Information for further
details.) The results for polyplexes with only one labeled molecule
are crucial to interpreting the data from the measured polyplexes
because they provide a reference for the estimation of the number
of molecules per polyplex (e.g., they distinguish single uncomplexed
RNA strands from multiple RNAs in a particle). On the other hand,
the simulations can unmask the stochastics of the dSTORM blinking,
one of the main issues of dSTORM quantification, and provide the possibility
to compare the median number of localizations that was detected experimentally
with a theoretical framework. As previously shown,[35] stochastic simulations can predict the expected number
and distribution of localizations of a set number of molecules. Therefore,
comparing the number of localizations per polyplex that were experimentally
detected to simulated data can provide a more accurate estimation
of the composition of individual polyplexes. To obtain the simulated
data presented in Figure C, the following steps were performed: (i) we acquired dSTORM
images of polyplexes with a single labeled R9 molecule from which
we estimated the photophysical parameters of the AlexaFluor488 dye;
(ii) we introduced these parameters together with the known expn>erimental
data such as the number of frames and the number of polyplexes to
be simulated; (iii) we simulated the blinking behavior of a single
R9 molecule and verified that the outpn>ut number of localizations per
cluster corresponded to the expn>erimental one (detailed information
on the simulation can be found in the Supporting Information); and (iv) data reported in Figure C was obtained by simulating the blinking
behavior of a Poissonian population of polyplexes with a specific
number of peptides. The distributions of simulated and experimentally
detected localizations were compared to determine which simulated
peptide number matched the peak of the experimental data (e.g., higher
peptide numbers for high N/P ratios). Notably, for mRNA no simulation
was conducted because of the heterogeneous labeling of the mRNA, which
together with the stochastic nature of the detection could not be
approximated.From the experimental and simulated data presented
in Figure C, comprehensive
information on the polyplex structure and composition can be obtained.
For N/P 1, the number of mRNA localizations was comparable to that
for a single molecule supporting the hypothesis that single mRNA molecules
were present that were not complexed into polyplexes. For N/P 3, the
experimentally determined median number of mRNA localizations significantly
increased to about 2 to 3 times that of the single molecule and remained
stable at N/P ratios of 5 and 7. These results indicate that inside
each polyplex there were only a few mRNA molecules. Interestingly,
from N/P 3 to N/P 5 the box width was enlarged, which indicated a
high polydispersity with respect to the number of encapsulated mRNAs.
In contrast, the density of the peptides followed different behavior
compared to that of the mRNA molecules. At N/P 1, the number of R9
localizations per polyplex was very low and similar to that of a single
peptide. Considering the labeling density (about 1.25% of labeled
peptides were mixed with 98.75% unlabeled ones), this is compatible
with individual mRNA molecules with about 100 peptides attached, an
insufficient number to compact the oligonucleotides into a polyplex.
At N/P 3, the number of R9 localizations slightly increased, but it
was not until N/P 5 that the number abruptly grew and remained stable
for higher ratios. At N/P 5 and N/P 7, the box widths were similar
and again larger than that at N/P 3. The median number of simulated
localizations matched the experimental data, demonstrating the validity
of our model. The number of peptides for which the simulated number
of localizations best matched the experimental data was about 25–30
labeled peptides per polyplexes; considering that 1.25% of the peptides
were labeled, we can estimate approximately 2000–2400 peptides
per polyplex. Still, for N/P 5 and 7 the box plot was broader. The
simulated data always corresponded to the lower range of the plots.
The frequency histograms of the number of localizations in Supporting Information Figures S9–S11 show
the presence of a major population in the experimental sample, which
fits the simulated data, together with a tail of polyplexes with a
larger number of molecules that cannot be fitted to the simulated
data. The fact that the experimental data was always broader demonstrates
heterogeneity in the samples, which the simulation did not recapitulate.
Thus, the measured heterogeneity cannot be simply explained by the
stochastic behavior of the dye; therefore, it can be concluded that
the polyplex formulation does not consist of a single monodisperse
population but rather of a mixture where polyplexes of different sizes
and RNA quantities coexist.To summarize these data in a molecular
picture, R9 binds mRNA at
N/P 1, but only from N/P 3 is this binding sufficient to condense
the mRNA into polyplexes. Polyplexes from N/P 3 to N/P 7 are similar
in size and amount of mRNA but change significantly with respect to
the amount of peptide present in the particles. Moreover, a significant
heterogeneity of the molecular composition is present, especially
at N/P 5 and 7. Notably, the differences between the last three conditions
and the heterogeneity in the samples would have been difficult or
impossible to measure with other methods, showing the potential of
dSTORM to complement existing technique for polyplex characterization.Above, the median number of localizations per component and condition
was analyzed to determine the approximate number of molecules per
polyplex and the polydispersity of the samples. However, dual-color
dSTORM simultaneously provides information regarding the number of
localizations for each component and the size for each individual
polyplex. Figure A,B
shows a correlative analysis of these three variables. The scatter
plots in Figure A
represents the data from over 15 000 polyplexes: every dot
in the chart represents one polyplex that is positioned in the graph
depending on its amount of R9 or mRNA localizations. Moreover, every
point is plotted in a different color depending on the size of the
polyplex. With this representation, we can draw conclusions about
the relationship between the size and amount of the two components
on a single-particle basis and thus with respect to the heterogeneity
of the sample. At N/P 1, the mRNA localization is rather monodisperse
compared to that of other samples, corresponding to the presence of
single mRNA molecules. At N/P 3, the number of mRNA localizations
significantly increased as did the polydispersity of the mRNA content,
indicating the existence of polyplexes with multiple RNA molecules.
Moreover, a correlation between the amounts of R9 and mRNA is present.
This is even more evident for N/P ratios 5 and 7, where the number
of R9 localizations increased overall. In particular, the polyplexes
with higher mRNA localizations are the ones that show a pronounced
increase in the number of R9 localizations. Following this pattern,
at N/P 5 the polyplexes with high mRNA localizations display an increase
in the R9 localizations, and at N/P 7, a similar correlation was observed,
suggesting that the charges were saturated at N/P 5. These results
prove a clear correlation in the number of molecules of each component
inside individual polyplexes.
Figure 3
Correlation between the number of mRNA localizations
and R9 localizations.
(A) Scatter plots of the number of mRNA localizations versus the number
of R9 localizations, together with a color code representing the size
for each polyplex. (B) Number of localizations plotted as a function
of polyplex size.
Correlation between the number of mRNA localizations
and R9 localizations.
(A) Scatter plots of the number of mRNA localizations versus the number
of R9 localizations, together with a color code representing the size
for each polyplex. (B) Number of localizations plotted as a function
of polyplex size.Moreover, the color code
provides information on the interplay
between composition and size. In all of he N/P studied, higher amounts
of mRNA and R9 were found in larger polyplexes (green-blue color).
The plots in Figure B, where the RNA and R9 content are plotted against size, also confirm
this. However, the data also indicate that the density of the packing
inside the polyplexes must be heterogeneous. Within the size category
of a 65–85 nm radius, polyplexes differ in volume by a factor
of maximally 2.2 while the number of localization varies by up to
a factor of 8. Similarly, with increasing N/P more localizations for
both mRNA and peptide are found for polyplexes of the same size.Moreover, we calculated the ratio of R9 localizations per mRNA
localizations and found that it was constant for N/P 1 and 3 but slightly
increased with higher radii at N/P 5 and 7 (Supporting Information Figure S13). These results indicate that the density
of polyplexes prepared at the same N/P is overall similar, although
there is a trend of higher ratios at higher radii.Importantly,
the estimated number of about 2000 peptides per polyplex
is fully consistent with the increase in mRNA localizations by about
a factor of 3 when going from a single mRNA molecule to a polyplex.
Two thousand peptides correspond to 18 000 positive charges,
which, at an N/P ratio of 3, can accommodate 6000 negative charges.
Because the mRNA is 1929 nucleotides in length, about 3 mRNA molecules
carry this charge.Altogether our measurements depict some important
structural aspects
of polyplexes: (i) a significant heterogeneity is present, with polyplexes
varying significantly in size and composition; (ii) a correlation
between the two components is present, with more R9 necessary to pack
a higher copy number of mRNA inside the same polyplexe; and (iii)
higher mRNA content results in larger sizes.Next, we aimed
to assess whether the STORM analyses could lead
to a better understanding of cell biological experiments. For this
purpose, polyplexes were formed with Cy5-mRNA and fluorescein-labeled
R9. We had shown before that fluorescein and Alexa488-labeled R9 yield
equivalent results.[36] In this case, fluorescein-labeled
R9 was mixed with unlabeled peptide in a ratio of 1:10. As confirmed
by DLS, polyplexes with diameters ranging from 70 to 130 nm were formed
for all N/P ratios. HeLa cells were incubated with polyplexes at constant
concentrations of mRNA, resulting in increasing concentrations of
peptide. These concentrations were proved to be noncytotoxic for cells
at any of the N/P ratios (Supporting Information Figure S14). Then, intracellular fluorescence was recorded
by confocal microscopy after 1 h of incubation (Figure A). For N/P 1, corresponding to a concentration
of fluorescein-labeled peptide of 0.05 μM, hardly any cell-associated
fluorescence could be detected. From N/P 3, vesicular fluorescence
was presented that further increased to an N/P ratio of 5 with no
further increase to N/P 7 (Figure A). Quantitative image analysis demonstrated that both
the mean intensity of vesicular fluorescence (Figure B) and the total number of vesicular pixels
per cell as a measure of the number of endosomes increased from N/P
1 to N/P 5 (Figure C). At N/P 1, almost no polyplex was internalized, and at N/P 3,
the amount increased, as it also did at N/P 5 and 7. These data demonstrate
that at N/P 5 the polyplexes had the right composition to be internalized.
Figure 4
Dependence
of cellular nanoparticle uptake on the N/P ratio. HeLa
cells were incubated for 1 h with polyplexes consisting of Cy5-mRNA
and fluorescein-labeled R9 at the indicated N/P ratios, followed by
washing and confocal microscopy of living cells. Labeled peptide was
mixed with unlabeled peptide in a ratio of 1:10. The mRNA concentration
was constant at 4.5 pM for all N/P ratios, corresponding to peptide
concentrations of 0.5, 1.5, 2.5, and 3.5 μM for N/P 1, 3, 5
and 7, respectively. (A) Cellular uptake and intracellular distribution.
To facilitate the discrimination of intensities, a false color look-up
table has been employed. The scale bar corresponds to 20 μm.
(B) Average pixel intensities for vesicular fluorescence. (C) Pixels
per cell as a measure of the number and size of endocytic vesicles.
(D) Average pixel intensity for fluorescence outside cells, recorded
at a higher detector gain. (E) Ratio of peptide over mRNA fluorescence
intensity. Ratios were calculated for the vesicular intensities of
each analysis image and averaged. Error bars correspond to the standard
deviation for normalized data of two independent experiments.
Dependence
of cellular nanoparticle uptake on the N/P ratio. HeLa
cells were incubated for 1 h with polyplexes consisting of Cy5-mRNA
and fluorescein-labeled R9 at the indicated N/P ratios, followed by
washing and confocal microscopy of living cells. Labeled peptide was
mixed with unlabeled peptide in a ratio of 1:10. The mRNA concentration
was constant at 4.5 pM for all N/P ratios, corresponding to peptide
concentrations of 0.5, 1.5, 2.5, and 3.5 μM for N/P 1, 3, 5
and 7, respectively. (A) Cellular uptake and intracellular distribution.
To facilitate the discrimination of intensities, a false color look-up
table has been employed. The scale bar corresponds to 20 μm.
(B) Average pixel intensities for vesicular fluorescence. (C) Pixels
per cell as a measure of the number and size of endocytic vesicles.
(D) Average pixel intensity for fluorescence outside cells, recorded
at a higher detector gain. (E) Ratio of peptide over mRNA fluorescence
intensity. Ratios were calculated for the vesicular intensities of
each analysis image and averaged. Error bars correspond to the standard
deviation for normalized data of two independent experiments.Even though the cells were washed
in order to reduce extracellular
out-of-focus fluorescence, there was still some fluorescence left.
For the peptide, this extracellular fluorescence strongly increased
with increasing N/P ratio, consistent with the STORM results that
had demonstrated the incomplete incorporation of peptide from N/P
ratios larger than 3 (Figure D). Moreover, we divided both mean fluorescence intensities
(peptide vs mRNA) to assess the ratio of peptide per mRNA in the internalized
poyplexes (Figure E). Interestingly, from N/P 3 to 7 this value remained constant.
This observation proves that a specific composition of the polyplexes
is needed to be internalized by the cells. From our STORM data, we
demonstrated that at N/P 3 most of the polyplexes did not have enough
peptide incorporated to pack the mRNA; therefore, we hypothesis that
only a small population of polyplexes at N/P 3 have the right composition,
which corresponds to the lower internalization observed. Finally,
the higher ratio at N/P 1 is consistent with the absence of polyplex
formation so that only free peptide was internalized.Having
established the methodology to measure the polyplex size
and composition, we exploited the ability of dSTORM to perform analyses
in complex media such as blood serum. Polyplexes are designed to be
intravenously injected into the bloodstream, being in contact with
proteins and other biomolecules that can destabilize the complex.
Therefore, it is of major importance to understand the stability of
the polyplexes in serum. Classically, gel retardation assays are used
to assess the release and decomposition of polyplexes.[7] Using dSTORM imaging, we expected to obtain information
on the mechanism of decomplexation because we were able to track the
composition and size of polyplexes. To this end, we incubated polyplexes
at 37 °C with fetal bovine serum (FBS) at concentrations of 1,
20, and 100% for 1 min and 1 h followed by deposition on coverslips.
Then, dSTORM images of the complexes were acquired (Figure and Supporting Information Figure S15). The behavior of the polyplexes was
similar when incubated with 1 or 20% FBS. Under these conditions,
after 1 min the mRNA content in the polyplexes remained stable compared
to the initial composition, indicating that the polyplexes were not
releasing their payload. However, we observed a decrease in the number
of peptide molecules. After 1 min of serum incubation, only half of
the initial peptide localizations were detected. In contrast, after
1 h of FBS incubation both the numbers of mRNA and R9 molecules abruptly
dropped (Figure A–C).
Altogether, these results indicate that the serum proteins interact
with the polyplexes in two stages as schematically represented in Figure D: (i) serum rapidly
removes peptides from the polyplexes without compromising the mRNA
compacted inside the particle (minute timescale) and (ii) proteins
destabilize the complexes causing the release of mRNA molecules (hour
timescale). We envision that the ability of dSTORM to provide additional
information about the mechanism of polyplex disassembly will support
the study and design of gene carriers with improved serum stability.
Figure 5
Stability
of polyplexes in serum. (A) dSTORM image of the N/P 5
polyplexes initially and after being incubated with 20% FBS for 1
min and 1 h. Scale bar 200 nm. (B) Number of mRNA localizations of
N/P 5 polyplexes after being incubated with 20% FBS for 1 min and
1 h. (C) Number of R9 localizations of N/P 5 polyplexes after being
incubated with 20% FBS for 1 min and 1 h. (D) Schematic representation
of the destabilization of the polyplexes in time in the presence of
serum.
Stability
of polyplexes in serum. (A) dSTORM image of the N/P 5
polyplexes initially and after being incubated with 20% FBS for 1
min and 1 h. Scale bar 200 nm. (B) Number of mRNA localizations of
N/P 5 polyplexes after being incubated with 20% FBS for 1 min and
1 h. (C) Number of R9 localizations of N/P 5 polyplexes after being
incubated with 20% FBS for 1 min and 1 h. (D) Schematic representation
of the destabilization of the polyplexes in time in the presence of
serum.We presented an in-depth study
of the structure and composition
of polyplexes containing mRNA and cell-penetrating peptide R9 using
dSTORM imaging. Our results show both qualitative and quantitative
differences in the mRNA and peptide content of individual polyplexes
formed at different N/P ratios. Importantly, a minimum excess of peptide
was required to condense the mRNA into polyplexes because at N/P 1
no distinct clusters could be observed. At N/P 3, the number of peptides
was sufficient to pack the mRNA into compact polyplexes. With an increase
in N/P, the R9 content and peptide to mRNA ratio in the polyplexes
further increased, reaching a plateau at around N/P 5. The possibility
to image individual polyplexes allowed us to dissect the relationship
between the relative content of the two components and the size of
the polyplexes, demonstrating a next-to-positive correlation of both
components with respect to size, some heterogeneity in the packing
density, and an increase in the packing density with increasing N/P
ratio. Our analyses clearly demonstrate that the insights gained through
the STORM analysis of the polyplexes directly translate into a better
understanding of cellular uptake experiments. From N/P 5 to 7, the
characteristics of the polyplexes are the same, which explains why
they have the same cellular uptake efficiency. At N/P 3, sufficient
mRNA encapsulation had been achieved for only a fraction of the polyplexes
as evident from the large heterogeneity of polyplexes at the molecular
level, demonstrated by STORM. Finally, the imaging of the destabilization
of polyplexes in the presence of serum provided mechanistic insights
into the disassembly mechanism, a crucial aspect for the in vivo performance
of gene carriers. Our study highlights the potential of multicolor
super-resolution microscopy to shed new light on the nanoscale structure
and stoichiometry of polyplexes, a key aspect for the understanding
of gene delivery carriers. Future perspectives include a study of
structure–activity relationships for a variety of polymeric,
lipidic, and peptidic carriers and a study of the structure of polyplexes
in cells after internalization. In this framework it has to be considered
that STORM imaging is possible only in fixed cells and therefore optimization
of the fixation procedure to retain the polyplex structure is necessary.
In conclusion, we believe that super-resolution microscopy can nicely
complement the current techniques for polyplex characterization contributing
to the guidance of the design of more effective oligonucleotide therapeutics.
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