Multivalent protein-carbohydrate interactions initiate the first contacts between virus/bacteria and target cells, which ultimately lead to infection. Understanding the structures and binding modes involved is vital to the design of specific, potent multivalent inhibitors. However, the lack of structural information on such flexible, complex, and multimeric cell surface membrane proteins has often hampered such endeavors. Herein, we report that quantum dots (QDs) displayed with a dense array of mono-/disaccharides are powerful probes for multivalent protein-glycan interactions. Using a pair of closely related tetrameric lectins, DC-SIGN and DC-SIGNR, which bind to the HIV and Ebola virus glycoproteins (EBOV-GP) to augment viral entry and infect target cells, we show that such QDs efficiently dissect the different DC-SIGN/R-glycan binding modes (tetra-/di-/monovalent) through a combination of multimodal readouts: Förster resonance energy transfer (FRET), hydrodynamic size measurement, and transmission electron microscopy imaging. We also report a new QD-FRET method for quantifying QD-DC-SIGN/R binding affinity, revealing that DC-SIGN binds to the QD >100-fold tighter than does DC-SIGNR. This result is consistent with DC-SIGN's higher trans-infection efficiency of some HIV strains over DC-SIGNR. Finally, we show that the QDs potently inhibit DC-SIGN-mediated enhancement of EBOV-GP-driven transduction of target cells with IC50 values down to 0.7 nM, matching well to their DC-SIGN binding constant (apparent Kd = 0.6 nM) measured by FRET. These results suggest that the glycan-QDs are powerful multifunctional probes for dissecting multivalent protein-ligand recognition and predicting glyconanoparticle inhibition of virus infection at the cellular level.
Multivalent protein-carbohydrate interactions initiate the first contacts between virus/bacteria and target cells, which ultimately lead to infection. Understanding the structures and binding modes involved is vital to the design of specific, potent multivalent inhibitors. However, the lack of structural information on such flexible, complex, and multimeric cell surface membrane proteins has often hampered such endeavors. Herein, we report that quantum dots (QDs) displayed with a dense array of mono-/disaccharides are powerful probes for multivalent protein-glycan interactions. Using a pair of closely related tetrameric lectins, DC-SIGN and DC-SIGNR, which bind to the HIV and Ebola virus glycoproteins (EBOV-GP) to augment viral entry and infect target cells, we show that such QDs efficiently dissect the different DC-SIGN/R-glycan binding modes (tetra-/di-/monovalent) through a combination of multimodal readouts: Förster resonance energy transfer (FRET), hydrodynamic size measurement, and transmission electron microscopy imaging. We also report a new QD-FRET method for quantifying QD-DC-SIGN/R binding affinity, revealing that DC-SIGN binds to the QD >100-fold tighter than does DC-SIGNR. This result is consistent with DC-SIGN's higher trans-infection efficiency of some HIV strains over DC-SIGNR. Finally, we show that the QDs potently inhibit DC-SIGN-mediated enhancement of EBOV-GP-driven transduction of target cells with IC50 values down to 0.7 nM, matching well to their DC-SIGN binding constant (apparent Kd = 0.6 nM) measured by FRET. These results suggest that the glycan-QDs are powerful multifunctional probes for dissecting multivalent protein-ligand recognition and predicting glyconanoparticle inhibition of virus infection at the cellular level.
Multivalent protein–carbohydrate
interactions are widespread
in biology and play a central role in many important biological events,
including viral and bacterial infection, cell–cell communication,
and host immune response regulation.[1−5] Such interactions initiate the first contact between pathogens (e.g.,
viruses and bacteria) and target cells that ultimately leads to infection.
However, monovalent protein–glycan interactions are intrinsically
weak, and hence biologically inactive. To compensate this limitation,
pathogens display arrays of specific glycans on their surface, allowing
them to bind efficiently to multimeric glycan-binding proteins (lectins)
on target cell surfaces and to exploit multivalency to enhance binding
affinity and gain cell entry, which ultimately leads to infection.[3−6] Therefore, these multivalent interactions are attractive targets
for developing novel antiviral interventions, especially entry inhibitors,
which can minimize virus resistance development.[1−5,7] In this regard, the
spatial- and orientation-match between the viral surface glycans and
carbohydrate recognition domains (CRDs) of cell surface lectins is
key to enhance binding affinity and specificity.[8,9] Therefore,
understanding the structure and spatial arrangement of the multivalent
binding partners is essential for antiviral intervention, which has
been the focus of significant current research.[1−5,7,10]Synthetic glycoconjugates can block pathogen–lectin
interactions
whose inhibitory potency critically depends on the spatial- and orientation-match
between the multivalent binding partners.[3,8−14] However, a major challenge is the lack of structural information
for many cell surface multimeric lectins, due to the problems associated
with solving the structure of such flexible, complex, and multimeric
membrane proteins by X-ray crystallography. For example, despite extensive
research over the past two decades, the complete crystal structures
of two important pathogen receptors, the tetrameric dendritic cell
receptor, DC-SIGN,[15−20] and its closely related endothelial cell receptor DC-SIGNR[21] (collectively abbreviated as DC-SIGN/R hereafter),
remain unknown apart from a structure model built upon the solution
X-ray scattering data.[20] These two receptors
play a key role in promoting HIV/Ebola virus (EBOV) infection by binding
to multiple mannose-containing glycans on the virus surface.[15,18,19,21−23] Interestingly, despite sharing 77% amino acid identity,
an overall tetrameric structure,[24,25] and identical
individual CRD-mannose binding motifs,[17] these two receptors can differentially augment viral infectivity.
For example, DC-SIGN is more effective in augmenting the infectivity
of some HIV strains than DC-SIGNR,[18,23] while only
DC-SIGNR, but not DC-SIGN, can effectively promote West Nile virus
infection.[26] Given their close similarity,
such differences must result from their different multivalent binding
properties, arising presumably from the different spatial and orientation
arrangements of their four CRDs, which have been shown to be flexibly
linked to the neck domain.[27] These observations
make DC-SIGN/R an ideal pair of model multimeric proteins to investigate
how subtle structural differences influence multivalent protein–glycan
interactions. Unfortunately, the widely used biophysical techniques
(e.g., isothermal titration calorimetry (ITC)[28,29] and surface plasmon resonance (SPR)[30]), although powerful in providing quantitative binding affinities,
kinetics, and thermodynamics, cannot reveal the structural information
(e.g., binding mode, binding site distance, and orientation), which
is key to the design of potent multivalent inhibitors.[1,8,9,11] Therefore,
there appears to be a clear capability gap of current methods in dissecting
such multivalent lectin–glycan interactions.Herein,
we propose that this capability gap may be addressed by
developing a polyvalent glycan-quantum dot (QD-glycan)-based multimodal
readout strategy to fully exploit multivalency and QD’s unique
properties. First, the QD’s unique, size-dependent, strong,
and stable fluorescence[31−33] can be harnessed for binding
quantification via a Förster resonance energy transfer (FRET)-based
ratiometric readout.[34−38] As compared to other methods (e.g., SPR and ITC), the QD-FRET readout
has the advantages of rapid, separation-free detection in solution,
high sensitivity, and a ratiometric readout signal with self-calibration
function, making it much less sensitive to instrument noise and signal
fluctuation, allowing for highly robust, accurate detection.[34−37] Indeed, the QD-FRET technique has been widely employed to address
broad biological and biomedical problems, for example, bio/enzymatic-/intracellular-
sensing, immunoassays, cell monitoring, and tracking,[31−46] and more recently to probe multivalent protein–glycan interactions.[47] Second, the solid nanoscale core of the QD can
be decorated with polyvalent specific glycan ligands to enhance binding
affinity by exploiting multivalency. Third, the QD-protein binding
can be directly monitored in solution by dynamic light scattering
via binding-induced hydrodynamic size changes. Finally, the high contrast
of the QD core in scanning transmission electron microscopy (STEM)
can be harnessed to directly visualize binding-induced particle arrangements
so as to probe the exact binding mode. Despite extensive research,
most QD-FRET work reported so far has only utilized the fluorescence
property of the QD; hence the unique multifunctionality of the QD
probe has not been fully exploited. For example, using the QD-FRET
readout strategy, we have recently found that compact polyvalent monomannose-capped
QDs (QD-Man) specifically bind to DC-SIGN, but not to DC-SIGNR. We
have also proposed that the four CRDs face upward in DC-SIGN, but
point sideways in DC-SIGNR, making the latter unable to bind multivalently
(>2) to one QD.[47] However, QD-Man failed
to differentiate binding of DC-SIGNR and monovalent CRD (Figure S1),[47] possibly
due to the fact that the individual CRD-mannose binding is too weak
to measure at low concentrations. Therefore, the overall QD-Man-DC-SIGN/R
binding modes remain unclear. Herein, we solved this problem by increasing
the individual CRD binding affinity of the glycan displayed on the
QD and by developing a novel multimodal readout strategy comprising
FRET, hydrodynamic size measurement, and S/TEM imaging to fully exploit
the unique multifunctionality of the glycan-QD. We further show that
there is a good correlation between the QD’s DC-SIGN/R binding
affinity and their virus inhibition potency.
Results and Discussion
Glycan
Ligand Design and Synthesis
To increase individual
CRD-glycan binding affinity, manno-pyranosyl-α-1,2-manno-pyranose
(DiMan) was coupled to the terminal end of the dihydrolipoic acid-oligo(ethylene
glycol)-based multifunctional ligands[48,49] (abbreviated
as DHLA-EG-DiMan hereafter, where n = 3 or 11 stands for a uniform linker containing 3 or
11 EG units, respectively) using the route described in Scheme . For comparison, their monomannosyl
equivalent ligands (i.e., DHLA-EG-Man, n = 3 or 11) were also synthesized as described previously.[47] Individual DiMan-CRD binding is ∼4 times
as strong as that of Man-CRD (Kd ≈
0.9 versus 3.5 mM),[29] allowing us to investigate
how individual CRD-glycan affinity contributes to the overall QD-glycan-DC-SIGN/R
multivalent binding.
Scheme 1
Synthetic Route to DHLA-EG-DiMan (where n = 3 or 11)
Synthetic Route to DHLA-EG-DiMan (where n = 3 or 11)
Reaction conditions: (i) DCC/DMAP,
DCM; (ii) triphenyl-phosphine, EtOAc/H2O; (iii) DCC/DMAP,
DCM; (iv) BF3·OEt2, DCM, molecular sieves;
(v) NaN3/TBAI, DMF; (vi) NaOMe, MeOH, then Amberlite H+ resin; (vii) EtOH; (viii) TCEP·HCl, CHCl3/EtOH/H2O.Briefly, lipoic acid
(LA) was first coupled to NH2-EG-N3 (n = 3 or
11) to form LA-EG-N3 (step
i). It was then reduced to LA-EG-NH2 by triphenyl-phosphine (step ii), and then coupled to cyclooctyne-COOH
to form LA-EG-cyclooctyne (step iii).
Meanwhile, 3,4,6-tri-O-acetyl-2-O-(2,3,4,6-tetra-O-acetyl-α-d-mannopyranosyl)-α-d-mannopyranosyl-trichloroacetimidate was reacted with 2-[2-(2-chloroethoxy)
ethoxy]ethanol to introduce a EG2 linker (step iv), which
was then treated with NaN3 to convert the linker terminal
chloride group into an azide (step v), and after removal of the acetyl
protection groups, the azide-modified glycan (1-azido-3,6-dioxaoct-8-yl-2-O-α-d-manno-pyranosyl-α-d-mannopyranoside)
was obtained (step vi). After that, the azide-modified glycan was
coupled to LA-EG-cyclooctyne via the
Cu-free “click” chemistry to give LA-EG-glycan (step vii), and reduction by tris(2-carboxyethyl)phosphine
(TCEP) gave the desired final DHLA-EG-glycan ligand. Details of the synthesis procedures and their spectroscopic
data are given in the Supporting Information. Each DHLA-EG-glycan ligand contains
three different functional domains: a DHLA for robust chelative QD
capping;[48,50] a hydrophilic, flexible EG linker for imposing high water-solubility, stability, and
resistance against nonspecific adsorption as well as for tuning the
intersugar spacing; and a terminal glycan for specific protein binding.[47]
Preparation and Characterization of Glycan-QDs
The
DHLA-EG-glycan ligands, after deprotonation
by NaOH, were directly used to initiate cap-exchange with a commercial
hydrophobic CdSe/ZnS QD (λEM ≈ 560 nm) in
a homogeneous solution using our recently developed highly efficient
cap-exchange method.[47] Details of the cap-exchange
procedures were given in the Supporting Information section 3. All of the resulting DHLA-EG-glycan capped QDs (abbreviated as QD-EG-glycan hereafter) formed highly stable dispersions in aqueous
media, and displayed no noticeable changes in appearance or fluorescence
over times >1 month. Moreover, the QDs were compact and uniform
in
size, displaying a small hydrodynamic diameter (Dh) of 8.3 and 9.5 nm for QD-EG3-DiMan and QD-EG11-DiMan, respectively (Figure S2),[51] suggesting the formation of isolated,
aggregation-free QD dispersions.[52−55] Importantly, the QDs were densely
capped with the glycan ligands (glycan valency >220), which would
be difficult to achieve by other methods (e.g., post cap-exchange
chemical coupling). Using the Dh values
and corresponding glycan valencies, the average interglycan distances
(d) of the QD-EG-glycans
were estimated in the range of 0.9–1.3 nm (Table ; see Supporting Information section 6.1 for calculation method). Interestingly,
this distance matches well to the average interglycan sequon distance
(∼1.2 nm) found on the HIV surface heavily glycosylated glycoprotein,
gp120.[56,57] Moreover, the QD surface glycan density
and interglycan distance (d) can be readily tuned
by varying the linker length and diluting the DHLA-EG-glycan ligand using an inert hydrophilic spacer
ligand, DHLA-zwitterion, during the cap-exchange process (see Figure ).
Table 1
Summary of the Chemical and Physical
Parameters of the QD-EG-glycan Conjugates
QD surface ligands
glycan valency
Dh (nm)
interglycan spacing (nm)
glycan footprint
on QD surface (nm2)
DHLA-EG3-Man
330 ± 70
8.9 ± 0.1
0.98 ± 0.11
0.75 ± 0.16
DHLA-EG11-Man
222 ± 62
9.6 ± 0.2
1.29 ± 0.36
1.30 ± 0.36
DHLA-EG3-DiMan
369 ± 38
8.3 ± 0.1
0.86 ± 0.09
0.59 ± 0.06
DHLA-EG11-DiMan
281 ± 25
9.5 ± 0.1
1.13 ± 0.10
1.01 ± 0.09
Figure 1
(A) Schematic showing
our approach to quantify QD-glycan-DC-SIGN/R
multivalent binding by QD-sensitized dye FRET mechanism. (B–D)
Schematic presentation of tuning the QD surface glycan valency and
interglycan distance (d) via EG linker length (n = 3 for B; n = 11 for C) and glycan dilution
with an inert DHLA-zwitterion spacer ligand (D).
(A) Schematic showing
our approach to quantify QD-glycan-DC-SIGN/R
multivalent binding by QD-sensitized dye FRET mechanism. (B–D)
Schematic presentation of tuning the QD surface glycan valency and
interglycan distance (d) via EG linker length (n = 3 for B; n = 11 for C) and glycan dilution
with an inert DHLA-zwitterion spacer ligand (D).
Differentiating QD-DiMan-DC-SIGN/R Binding Modes by FRET
The DC-SIGN/R proteins were expressed and labeled with an Atto-594
dye at a site-specifically introduced cysteine residue on the CRD
(Supporting Information section 4).[47] The chosen mutation residue (Q274 in DC-SIGN
and R287 in DC-SIGNR) is located out with the glycan binding sites,
minimizing any possible interference with CRD glycan binding. The
QD emission has good overlap with the Atto-594 absorption, ensuring
that efficient FRET can occur (Förster radius R0 = ∼4.0 nm, Figure S3), but has minimal overlap of dye emission spectra, allowing for
easy separation of the QD and dye FRET signal without the need of
spectral deconvolution. We first screened the QD-glycan-DC-SIGN/R
binding by titrating different amounts of labeled proteins into a
fixed concentration of the QD-glycan (40 nM) in a binding buffer (20
mM HEPES, 100 mM NaCl, 10 mM CaCl2, pH 7.8). The resulting
fluorescence spectra were shown in Figure (all spectra have been corrected by dye
direct excitation background). Similar to QD-Man, incubation of QD-DiMan
with the labeled DC-SIGN resulted in significant quenching of QD fluorescence
(λEM ≈ 554 nm) and a concurrent enhancement
of the Atto-594 FRET signal (λEM ≈ 626 nm),
consistent with a QD-sensitized Atto-594 FRET mechanism (Figure ). Moreover, the
FRET signal was found to be strongly Ca2+-dependent and
was completely diminished in the absence of Ca2+ (Figure S4). This observation is fully consistent
with the Ca2+-dependency of the DC-SIGN-glycan binding.[17,24] Despite such similarities, three major differences between QD-DiMan
and QD-Man binding to DC-SIGN/R were observed:
Figure 2
Dye-direct excitation
background-corrected fluorescence spectra
of QD-DiMan (100% glycan density) after binding to Atto-594-labeled
proteins at different protein:QD ratios (PQR): QD-EG11-DiMan
+ DC-SIGN (A); QD-EG11-DiMan + DC-SIGNR (B); QD-EG11-DiMan + DC-SIGN CRD (C); QD-EG3-DiMan + DC-SIGN
(E); QD-EG3-DiMan + DC-SIGNR (F); QD-EG3-DiMan
+ DC-SIGN CRD (G); and the resulting I626/I554 ratio versus PQR relationship for
QD-EG11-DiMan (D) and QD-EG3-DiMan (H). DC-SIGNR
binding data are fitted by Hill’s equation, y = Rmax × x/(k + x), where Rmax is the maximum I626/I554 ratio, k is the
PQR value that gives 50% Rmax, and n is the Hill coefficient. The best fit parameters are Rmax = 2.6 ± 0.9, k = 17.2
± 6.1, n = 1.5 ± 0.1, and R2 = 0.9984 for QD-EG11-DiMan and Rmax = 1.7 ± 0.2, k = 9.7 ±
1.5, n = 2.4 ± 0.4, and R2 = 0.9991 for QD-EG3-DiMan.
Dye-direct excitation
background-corrected fluorescence spectra
of QD-DiMan (100% glycan density) after binding to Atto-594-labeled
proteins at different protein:QD ratios (PQR): QD-EG11-DiMan
+ DC-SIGN (A); QD-EG11-DiMan + DC-SIGNR (B); QD-EG11-DiMan + DC-SIGN CRD (C); QD-EG3-DiMan + DC-SIGN
(E); QD-EG3-DiMan + DC-SIGNR (F); QD-EG3-DiMan
+ DC-SIGN CRD (G); and the resulting I626/I554 ratio versus PQR relationship for
QD-EG11-DiMan (D) and QD-EG3-DiMan (H). DC-SIGNR
binding data are fitted by Hill’s equation, y = Rmax × x/(k + x), where Rmax is the maximum I626/I554 ratio, k is the
PQR value that gives 50% Rmax, and n is the Hill coefficient. The best fit parameters are Rmax = 2.6 ± 0.9, k = 17.2
± 6.1, n = 1.5 ± 0.1, and R2 = 0.9984 for QD-EG11-DiMan and Rmax = 1.7 ± 0.2, k = 9.7 ±
1.5, n = 2.4 ± 0.4, and R2 = 0.9991 for QD-EG3-DiMan.(1) Most significantly, binding of DC-SIGNR to QD-DiMan produced
notable FRET signals, which were markedly higher and well-separated
from those of the monovalent CRDs (Figure and Figure S5), a sharp contrast to that of QD-Man where signals obtained from
DC-SIGNR and monovalent CRD binding were equally weak and indistinguishable
from nonspecific adsorption background (Figure S1).[47] Moreover, the apparent FRET
ratios (I626/I554) obtained from the monovalent CRD-QD-DiMan binding were still indistinguishable
from the background, suggesting that monovalent binding is too weak
(Kd ≈ 0.9 mM)[29] to measure with 40 nM QD. Given that the I626/I554 ratio is linearly
correlated to the number of acceptors (proteins) bound to each QD
in the absence of other quenching effect (see Supporting Information section 5.4),[47] this result implies that DC-SIGNR-QD-DiMan binding is multivalent,
and not monovalent; otherwise similar FRET ratios would have been
expected.(2) Binding of DC-SIGN to QD-DiMan still produced
a much stronger
FRET signal than that of DC-SIGNR (Figure ), suggesting that DC-SIGN must display a
higher binding multivalency to one QD than DC-SIGNR. These results
are not unexpected, and, in fact, they are fully consistent with our
proposed QD-DC-SIGN/R binding models.[47] The four side-way facing CRDs in DC-SIGNR may split into two pairs
and bind divalently with two different QDs. This binding mode should
result in positive binding cooperativity. Fitting the DC-SIGNR binding
curves by the Hill’s function: y = Rmax × x/(k + x), where Rmax is the maximum I626/I554 ratio, k is the protein:QD
ratio (PQR) that gives 50% Rmax, and n is the Hill coefficient, indeed revealed that the n values for both QD-EG11-DiMan (1.5 ± 0.1)
and QD-EG3-DiMan (2.4 ± 0.4) were >1, clearly confirming
positive binding cooperatively (Figure D/H). In contrast, the four upwardly facing CRDs in
DC-SIGN may bind tetravalently to a single QD, which should produce
no binding cooperativity (n ≤ 1). Indeed,
a similar Hill’s fit of the DC-SIGN binding curves with QD-DiMan
with 25% glycan density revealed the n to be 0.85
± 0.15 for QD-EG11-DiMan and 1.0 ± 0.3 for QD-EG3-DiMan, confirming no binding cooperativity (Figure ). Here, the QD surface glycan
density used in DC-SIGN binding was diluted to 25% by DHLA-zwitterion
ligand to avoid FRET quenching observed with 100% glycan density QDs
at high PQRs (see Figure D/H and the next section). Therefore, the different binding
multivalency modes of DC-SIGN/R have been successfully differentiated
via polyvalent QD-DiMan binding and a ratiometric FRET readout strategy.
Figure 3
Dye-direct
excitation background-corrected fluorescence spectra
of QD-EG-DiMan (with 25% glycan density
diluted by DHLA-ZW ligands) after binding to Atto-594-labeled proteins
at different PQRs: QD-EG11-DiMan + DC-SIGN (A); QD-EG11-DiMan + DC-SIGNR (B); QD-EG3-DiMan + DC-SIGN
(D); QD-EG3-DiMan + DC-SIGNR (E); and the I626/I554 ratio versus PQR
relationship for QD-EG11-DiMan (C) and QD-EG3-DiMan (F). The DC-SIGN binding data were fitted to Hill’s
equation, giving Rmax = 1.2 ± 0.2, k = 4.9 ± 2.1, n = 0.85 ± 0.15,
and R2 = 0.9918 for QD-EG11-DiMan and Rmax = 5.4 ± 1.6, k = 4.4 ± 3.1, n = 1.0 ± 0.3,
and R2 = 0.9994 for QD-EG3-DiMan.
Dye-direct
excitation background-corrected fluorescence spectra
of QD-EG-DiMan (with 25% glycan density
diluted by DHLA-ZW ligands) after binding to Atto-594-labeled proteins
at different PQRs: QD-EG11-DiMan + DC-SIGN (A); QD-EG11-DiMan + DC-SIGNR (B); QD-EG3-DiMan + DC-SIGN
(D); QD-EG3-DiMan + DC-SIGNR (E); and the I626/I554 ratio versus PQR
relationship for QD-EG11-DiMan (C) and QD-EG3-DiMan (F). The DC-SIGN binding data were fitted to Hill’s
equation, giving Rmax = 1.2 ± 0.2, k = 4.9 ± 2.1, n = 0.85 ± 0.15,
and R2 = 0.9918 for QD-EG11-DiMan and Rmax = 5.4 ± 1.6, k = 4.4 ± 3.1, n = 1.0 ± 0.3,
and R2 = 0.9994 for QD-EG3-DiMan.(3) Interestingly, unlike the
QD-Man-DC-SIGN binding, where the
apparent FRET ratio (I626/I554) followed a typical binding pattern with increasing
PQR before reaching saturation (Figure S1), the QD-DiMan-DC-SIGN interaction exhibited a distinct two-stage
response (Figure D/H).
The I626/I554 ratio initially increased roughly linearly with the PQR at <6
as expected for a single QD-donor in a FRET interaction with N identical receptors model; however, the I626/I554 ratio then decreased
with the increasing PQR at >6. Using the surface areas calculated
from the Dh’s of the QDs and the
DC-SIGN head footprint, the number of DC-SIGN molecules that can be
packed onto the QD surface without crowding was estimated as ∼6/∼8
for QD-EG3-DiMan/QD-EG11-DiMan, respectively
(Figure S6). These numbers approximately
match the critical PQR (the turning point on the FRET response curve),
suggesting that surface crowding is responsible for the observed FRET
decrease. The quenching is likely due to crowding-induced reorganization
of the QD-bound DC-SIGNs via their flexible neck region[27] that brings the dyes in proximity to each other
and causes mutual quenching. This assignment was supported by that
no quenching was observed for the labeled DC-SIGN only under equivalent
concentrations in the absence of QD-DiMan (Figure S7). Consistent with these results, the fluorescence lifetime
of the QD-EG11-DiMan (14.75 ns) was reduced to 7.75 ns
and further to 1.76 ns as PQR increased from 3 to 10. Meanwhile, the
dye lifetime (3.48 ns for protein only) was increased to 8.09 ns at
PQR = 3, but then decreased to 4.00 ns at PQR = 10 (Figure S8).[58] Interestingly, diluting
the QD surface DHLA-EG-glycan density
to 25% with DHLA-ZW removed the two-stage behavior, and the binding
curves returned to their normal shape without FRET quenching at high
PQRs (Figure C/F).
However, it also produced significantly lower (∼4-fold) FRET
ratios at saturation (Figure C/F), suggesting a significantly reduced DC-SIGN binding capacity
for the 25% glycan-QD. This result further supports the proposal of
surface crowding-induced CRD reorganization being responsible for
the FRET quenching observed with the 100% glycan-QDs under high PQRs.Using the FRET efficiency obtained from the QD quenching (e.g., E = 1 – I/I0, where I and I0 are the fluorescence intensities of the QD with and without the
protein, respectively) and a single QD in FRET interaction with N identical acceptor model, E = 1/[1 + (r/R0)6/N],[34] the average QD-dye distance r was calculated to be ∼5.2 and ∼5.7 nm for DC-SIGN
binding to QD-EG3-DiMan and QD-EG11-DiMan, respectively
(Figure S3C and D). Both r values were ∼1 nm longer than the hydrodynamic radii of the
corresponding QD-EG-glycans (e.g., ∼4.2
and ∼4.8 nm). This result is not unreasonable considering the
distance between the dye labeling position and the glycan binding
site, as well as the flexible nature of the EG linker, which may become more extended upon protein binding.
However, the equivalent FRET efficiency versus dye:QD ratio responses
for DC-SIGNR binding to QD-DiMan were S-shaped and could not be fitted
by the single QD in FRET interaction with N identical
acceptor model (Figure S3C/D). The relatively
weak binding between DC-SIGNR and QD-DiMan (>100-fold weaker than
that of DC-SIGN equivalent, see the next section) and positive binding
cooperatively may have led to the S-shape response curve, presumably
because DC-SIGNR added under low PQRs was unable to bind efficiently
to QD-DiMan to produce efficient FRET at the early stages of titration.
Quantifying QD-glycan-DC-SIGN/R Binding Affinity by FRET
The different QD-binding modes and multivalency exhibited by DC-SIGN/R
should result in differing binding affinities (Kd’s). Theoretically, the I626/I554 ratio is linearly correlated to
the numbers of acceptors (proteins) bound to the QD, making it a reliable
signal for quantifying the proportion of the bound QD-protein complexes
in a QD/protein mixture (Supporting Information section 5.4).[47,59] Here, we have developed a new
method by simultaneously changing the QD/protein concentration while
keeping PQR fixed at 1 for DC-SIGN (to avoid the FRET quenching at
high PQRs) or 10 for DC-SIGNR (to compensate the low FRET ratio at
PQR = 1, Figure S9). Under such conditions,
the I626/I554 intensity ratio can provide a true reflection of the fraction of
bound QD-protein complexes within the QD-protein mixture. The experiments
were performed in the binding buffer containing 1 mg/mL of bovineserum albumin (BSA) to minimize the possible nonspecific adsorption
of QD/protein on surfaces, which were non-negligible at low concentrations
(<10 nM).[59] The resulting fluorescence
spectra revealed that both the dye FRET and the QD fluorescence signals
increased with the increasing concentration (Figure S9). However, the former increased faster than the latter,
giving an increased I626/I554 ratio with the increasing concentration. The resulting I626/I554 ratio–concentration
relationships were fitted by the Hill’s equation to derive
the apparent dissociation constants (Kd’s, Figure ). The parameters derived from the best fits were summarized in Table .
Figure 4
Relationship between
the I626/I554 ratio and protein concentration for a fixed
protein:QD molar ratio of 1:1 for DC-SIGN and 10:1 for DC-SIGNR. (A)
DC-SIGN + QD-EG3-Man; (B) DC-SIGN + QD-EG11-Man;
(C) DC-SIGN + QD-EG3-DiMan; (D) DC-SIGN + QD-EG11-DiMan; (E) DC-SIGNR + QD-EG3-DiMan; and (F) DC-SIGNR
+ QD-EG11-DiMan. Data were fitted by Hill’s equation, Y = Rmax × C/[Kd + C], where Rmax, Kd, n, and C are the maximum I626/I554 ratio, apparent Kd, Hill coefficient, and protein concentration,
respectively. The fitting parameters were summarized in Table S1.
Table 2
Key Chemical and Biophysical Parameters
of the QD-EG-glycans and Their Binding
Affinities with DC-SIGN/R Measured by FRET
QD surface ligands
glycan valency (N)
apparent Kd DC-SIGN (nM)
apparent Kd DC-SIGNR (nM)
enhancement factor βa
β/N
DHLA-EG3-Man
330 ± 70
35 ± 7
100 000
∼300
DHLA-EG11-Man
222 ± 62
714 ± 18
4900
∼22
DHLA-EG3-DiMan
369 ± 38
0.61 ± 0.07
62 ± 8
1 480 000
∼4000
DHLA-EG11-DiMan
281 ± 25
2.1 ± 0.5
633 ± 77
430 000
∼1500
DC-SIGN affinity
enhancement factor
is calculated by β = Kd (CRD-Glycan)/Apparent Kd(DC-SIGN-QD), where Kd CRD-Man and Kd CRD-DiMan are 3.5 and 0.9 mM,
respectively.[29]
Relationship between
the I626/I554 ratio and protein concentration for a fixed
protein:QD molar ratio of 1:1 for DC-SIGN and 10:1 for DC-SIGNR. (A)
DC-SIGN + QD-EG3-Man; (B) DC-SIGN + QD-EG11-Man;
(C) DC-SIGN + QD-EG3-DiMan; (D) DC-SIGN + QD-EG11-DiMan; (E) DC-SIGNR + QD-EG3-DiMan; and (F) DC-SIGNR
+ QD-EG11-DiMan. Data were fitted by Hill’s equation, Y = Rmax × C/[Kd + C], where Rmax, Kd, n, and C are the maximum I626/I554 ratio, apparent Kd, Hill coefficient, and protein concentration,
respectively. The fitting parameters were summarized in Table S1.DC-SIGN affinity
enhancement factor
is calculated by β = Kd (CRD-Glycan)/Apparent Kd(DC-SIGN-QD), where Kd CRD-Man and Kd CRD-DiMan are 3.5 and 0.9 mM,
respectively.[29]Four notable findings are revealed by Table . First, a polyvalent display
of DiMan on
the QD greatly enhanced its affinity for DC-SIGN: a remarkably low
apparent Kd of 610 pM was achieved with
QD-EG3-DiMan, translating to a massive ∼1.5 million-fold
affinity enhancement (β) over the monovalent CRD-DiMan binding
(Kd ≈ 0.9 mM),[29] and a normalized per sugar enhancement factor, β/N, of ∼4000. Second, although a polyvalent display
of Man on the QD also enhanced its DC-SIGN affinity, the level of
enhancement was significantly lower than that of the DiMan equivalent
(<1/10 in β/N terms). This difference may be due to the extended
binding surface of the DC-SIGN CRD, which contains both primary and
secondary binding sites.[17,24] For QD-Man, it may
bind mainly to the primary site, whereas QD-DiMan may bind to both
primary and secondary sites, leading to greater affinity enhancement.
Third, the apparent Kd for QD-DiMan binding
to DC-SIGN was found to be >100-fold lower than that to DC-SIGNR,
suggesting that DC-SIGN’s binding affinity is >100-fold
stronger
than that of DC-SIGNR. Given that each HIV surface gp120 trimer spike
is densely coated with mannose containing glycans[57] and is of size (∼12 nm)[60] comparable to a QD-DiMan, this result thus provides a plausible
explanation why DC-SIGN has been found to be more effective in trans-infecting
some HIV strains than DC-SIGNR.[23] Moreover,
this result explains the reason why wild-type DC-SIGNR was unable
to compete off DC-SIGN from binding to QD-DiMan observed in the next
section. Finally, the flexible EG linker also had a significant impact
on the overall binding affinity: increasing the linker length from
3 to 11 EG units led to >3-fold lower affinity. This is presumably
because the longer is the EG linker the more flexible and disordered
the terminal glycans will be, and hence there is a greater entropic
penalty to pay upon DC-SIGN binding. Nevertheless, a suitable EG linker
is essential to impose high QD stability in aqueous media and to minimize
nonspecific interactions with nontarget proteins.
Confirming
QD-DC-SIGN/R Binding Specificity Using Wild-Type
Receptor Competition
A FRET competition experiment using
unlabeled wild-type proteins was further employed to confirm that
the labeled DC-SIGN/R (containing a site-specific cysteine mutation
and Atto-594 labeling, see Supporting Information section 4)-QD binding truly reflected wild-type protein binding
properties. The experiment was performed on the QDs with 25% glycan
density to overcome the FRET quenching problem observed with 100%
glycan-QD (Figure S10A). As the wild-type
protein:labeled DC-SIGN ratio (WLR) increased, the FRET signal reduced
progressively while the QD fluorescence correspondingly recovered
(Figure A), confirming
that wild-type DC-SIGN successfully displaced labeled DC-SIGNs from
binding to the QD. In contrast, wild-type DC-SIGNR caused no apparent
changes to either the QD or the FRET signal (Figure B), suggesting no binding competition occurred.
These results indicate that wild-type and labeled DC-SIGN molecules
must bind to the same sugar sites (same binding mode) on the QD surface,
whereas DC-SIGNR may be too weak to displace the labeled DC-SIGN from
binding to the QD. Their different competition efficiencies were clearer
in the normalized I626/I554 versus WLR plots (Figure C), where DC-SIGNR gave no apparent changes
but DC-SIGN yielded significantly reduced FRET ratios. This result
is not unexpected because DC-SIGNR-QD-DiMan binding is >100-fold
weaker
than that of the equivalent DC-SIGN interaction (see previous section, Table ).
Figure 5
Dye-direct excitation
background corrected fluorescence spectra
of QD-EG3-DiMan(25%)/DHLA-ZW(75%) + Atto-594 labeled DC-SIGN
(PQR = 12.5 to ensure saturate protein binding) after mixing with
different amounts of wild-type DC-SIGN (A) or DC-SIGNR (B). The QD-only
fluorescence spectra in the absence of proteins are also displayed
for comparison (shown in ○). (C) Plots of the corresponding
normalized I626/I554 ratio versus wild-type protein:labeled DC-SIGN molar ratio
(WLR) fitted by a competitive binding model.
Dye-direct excitation
background corrected fluorescence spectra
of QD-EG3-DiMan(25%)/DHLA-ZW(75%) + Atto-594 labeled DC-SIGN
(PQR = 12.5 to ensure saturate protein binding) after mixing with
different amounts of wild-type DC-SIGN (A) or DC-SIGNR (B). The QD-only
fluorescence spectra in the absence of proteins are also displayed
for comparison (shown in ○). (C) Plots of the corresponding
normalized I626/I554 ratio versus wild-type protein:labeled DC-SIGN molar ratio
(WLR) fitted by a competitive binding model.The relative affinity between wild-type and labeled DC-SIGN
for
the QD-DiMan binding was further evaluated by a simple competitive
model, F = IR50/[IR50 + CWT/CLP], where F is the FRET ratio in the presence of wild-type protein
normalized by that without, CWT and CLP are wild-type and labeled protein concentrations,
respectively, and IR50 is the molar ratio of wild type
DC-SIGN:labeled DC-SIGN required to reduce F by 50%.
An IR50 value of 1 indicates that both proteins bind to
the QD with equal affinity, while an IR50 value of <1
indicates that the labeled protein binds more weakly than wild-type
protein. Fitting the data using this model gave an IR50 value of 0.88 and 0.37 for QD-EG11-DiMan and QD-EG3-DiMan, respectively (Figure and Figure S10). Both IR50 values were <1, indicating that the site-specific mutation
and dye-labeling in DC-SIGN weakened its binding affinity with the
QDs. This effect was more pronounced for QD-EG3-DiMan,
presumably because its shorter EG3 linker may limit the
terminal sugar’s ability to reorganize and fit perfectly within
the protein’s binding pockets.
Differentiating QD-Wild-Type
Protein Binding Modes by DLS, TEM,
and Fluorescence Quenching
The hydrodynamic size (Dh) of the QD-protein assemblies provided further
support for the different binding modes of DC-SIGN/R.[51] Binding of wild-type DC-SIGN with QD-EG11-DiMan
(PQR = 12.5) gave only a single, narrowly distributed species with
a Dh of ∼42 nm (Figure B). This value was significantly
bigger than that of isolated QDs (Dh ≈
8.8 nm in binding buffer, Figure A) or wild-type DC-SIGN (Dh ≈ 14 nm, Figure S11), suggesting
that all DC-SIGNs were bound to the QD and formed a uniform QD-protein
assembly. In contrast, binding of wild-type DC-SIGNR gave a bimodal
distribution with Dh’s of ca. 124
and 205 nm (Figure C), respectively. Moreover, almost identical Dh distributions were also observed with its equivalent QD-EG3-DiMan interaction (Figure S2D, Table S2). These Dh values were too large
to be isolated as individual QD-protein assemblies, a strong indication
of QD agglomeration via QD/DC-SIGNR interlinking. This hypothesis
was confirmed by two-dimensional imaging of the QD dispersions via
rapid plunge freezing and subsequent TEM/STEM imaging at low magnification
after analytical confirmation of the QD size and contrast level in
these images[61] (we term this cryo-snapshot
TEM/STEM, SI section 6), where the high
contrast of the QD was employed as the differentiating modality. Figure D shows that the
QDs clustered in the binding buffer, possibly due to weak binding
between Ca2+ ions and QD-surface DiMan ligands because
QD-DiMan appeared as isolated particles in pure water without Ca2+ (Figure S12). However, the QD-DiMan
clusters were completely dispersed upon binding with wild-type DC-SIGN,
revealing only isolated QDs (Figure E), whereas binding of wild-type DC-SIGNR produced
more aggregated QDs (Figure F). The different binding behaviors were further supported
by a nearest neighbor particle distance (NND) analysis of TEM images
(see Supporting Information section 6).[61] A large NND of ∼46 nm was found for DC-SIGN
bound QDs, which was >3 times that of DC-SIGNR bound QDs (∼14
nm) or clustered QDs in binding buffer (∼12 nm, see Figure G/H/I). These results
agree excellently with the DLS results and our proposed DC-SIGN/R
binding modes. The strong tetravalent binding of DC-SIGN with one
QD should produce isolated QDs, preventing them from getting close
to each other and hence a large NND, whereas the bis-divalent binding
of DC-SIGNR with two different QDs should lead to QD interlinking
and a small NND.
Figure 6
Hydrodynamic diameter histograms of QD-EG11-DiMan before
(A) and after binding to wild-type DC-SIGN (B) or DC-SIGNR (C) measured
by dynamic light scattering (DLS). Insets show schematics of the QD
and/or QD-protein assemblies. Cryo-TEM (contrast inverted HAADF STEM)
images of the QD-EG11-DiMan before (D) and after binding
to wild-type DC-SIGN (E) or DC-SIGNR (F). Consistent with the Dh values shown in (A), both isolated and clustered
QDs are found in the corresponding TEM image (D) for QD-EG11-DiMan. Histograms of nearest neighbor distance (NND) distributions
measured from the TEM images of QD-EG11-DiMan before (G)
and after binding to wild-type DC-SIGN (H) or DC-SIGNR (I). The distribution
histograms were fitted by Gaussian function with fitting parameters
shown in each graph. All samples were measured in binding buffer.
Hydrodynamic diameter histograms of QD-EG11-DiMan before
(A) and after binding to wild-type DC-SIGN (B) or DC-SIGNR (C) measured
by dynamic light scattering (DLS). Insets show schematics of the QD
and/or QD-protein assemblies. Cryo-TEM (contrast inverted HAADF STEM)
images of the QD-EG11-DiMan before (D) and after binding
to wild-type DC-SIGN (E) or DC-SIGNR (F). Consistent with the Dh values shown in (A), both isolated and clustered
QDs are found in the corresponding TEM image (D) for QD-EG11-DiMan. Histograms of nearest neighbor distance (NND) distributions
measured from the TEM images of QD-EG11-DiMan before (G)
and after binding to wild-type DC-SIGN (H) or DC-SIGNR (I). The distribution
histograms were fitted by Gaussian function with fitting parameters
shown in each graph. All samples were measured in binding buffer.The postulated DC-SIGN/R-QD binding
modes were further supported
by the different fluorescence quenching behaviors by DHLA-EG3-DiMan coated gold nanoparticles (GNP-EG3-DiMan, Figure S13). GNP was chosen here because its
efficient universal fluorescence quenching can extend beyond the traditional
FRET distance limit of ∼10 nm.[62,63] Here, a 605
nm emitting QD was used to minimize the QD fluorescence reduction
due to absorption of GNP at the excitation wavelength (λEX = 590 nm). Mixing GNP-EG3-DiMan (5 nM) with QD-EG3-DiMan (10 nM) in binding buffer gave almost the same fluorescence
as the QD alone, suggesting minimal QD-GNP cross-linking. Addition
of wild-type DC-SIGNR to the QD-GNP mixture significantly quenched
the QD fluorescence, whereas introduction of wild-type DC-SIGN increased
the QD fluorescence considerably (Figure S14). These results matched well to that expected from the DC-SIGN/R
binding modes: cross-linking by DC-SIGNR should lead to QD/GNP assembly
and QD fluorescence quenching by the proximal GNPs, whereas the strong
tetravalent binding of DC-SIGN to one QD or GNP should not only prevent
any GNP or QD assembly, but also break up any preassembled QD clusters
in binding buffer (see Figure D), resulting in higher fluorescence over the QD-only sample.
Inhibiting DC-SIGN/R-Mediated Augmentation of EBOV-GP-Driven
Viral Entry
The strong DC-SIGN binding affinity afforded
by QD-EG-DiMan suggests that these QDs
could effectively block DC-SIGN-mediated virus infection. To investigate
this potential, a murine leukemia virus (MLV)-based vector bearing
the EBOV-GP was employed to deliver the luciferase gene into humanembryonic kidney cells (293T) previously transfected to express DC-SIGN/R.[47] The virus particles can bind to cell surface
DC-SIGN/R via incorporated EBOV-GPs on their membrane surface to enhance
cell uptake and gene transduction. As expected, DC-SIGN/R expression
in cells greatly increased the efficiency of EBOV-GP-driven gene transduction.
Pretreatment of cells with QD-EG-DiMan
greatly reduced the gene transduction of DC-SIGN-positive cells down
to the low nanomolar range, indicating high inhibition potency (Figure S15). The normalized inhibition data were
fitted by an inhibition model, giving an IC50 of 0.7 ±
0.2 and 1.4 ± 0.1 nM for QD-EG3-DiMan and QD-EG11-DiMan, respectively (Figure ). Such low IC50 values place them among
the most potent glyconanoparticle inhibitors against EBOV-GP-driven
transduction of host cells. In fact, their inhibition potency is comparable
to those of the giant globular multivalent glycofullerenes (IC50 = 0.667 nM)[14] and the virus-like
glycodendri-nanoparticles (IC50 = 0.91 nM).[13]
Figure 7
Normalized luciferase activities of the DC-SIGN- or DC-SIGNR-expressing
293T cells as a function of the pretreatment QD-EG3-DiMan
(A) or QD-EG11-DiMan (B) concentration. The data for particles
bearing the Ebola virus glycoprotein (EBOV-GP) are shown in open circles,
while the results obtained with control particles bearing the vesicular
stomatitis virus glycoprotein (VSV-G) are shown in triangles. The
luciferase activities, after subtraction by their corresponding pcDNA
control background, were normalized by the respective values in the
absence of the QDs (Figure S15). Data were
fitted by a competitive binding model, F = IC50/(IC50 + CQD), where F is the normalized luciferase activity, CQD is the QD concentration, and IC50 is the
concentration that gives 50% inhibition.[47] The gene transduction driven by a control vector bearing VSV-G,
which cannot use DC-SIGN/R to augment cell entry, was unaffected by
the QD treatment, confirming that the specific QD-DC-SIGN/R binding
was responsible for the observed inhibition.
Normalized luciferase activities of the DC-SIGN- or DC-SIGNR-expressing
293T cells as a function of the pretreatment QD-EG3-DiMan
(A) or QD-EG11-DiMan (B) concentration. The data for particles
bearing the Ebola virus glycoprotein (EBOV-GP) are shown in open circles,
while the results obtained with control particles bearing the vesicular
stomatitis virus glycoprotein (VSV-G) are shown in triangles. The
luciferase activities, after subtraction by their corresponding pcDNA
control background, were normalized by the respective values in the
absence of the QDs (Figure S15). Data were
fitted by a competitive binding model, F = IC50/(IC50 + CQD), where F is the normalized luciferase activity, CQD is the QD concentration, and IC50 is the
concentration that gives 50% inhibition.[47] The gene transduction driven by a control vector bearing VSV-G,
which cannot use DC-SIGN/R to augment cell entry, was unaffected by
the QD treatment, confirming that the specific QD-DC-SIGN/R binding
was responsible for the observed inhibition.Interestingly, these IC50 values roughly matched
their
apparent binding Kd’s with DC-SIGN
(i.e., 0.61 and 2.1 nM) measured by QD-FRET (Table ). Moreover, the gene transduction of DC-SIGNR-expressing
cells was reduced only marginally by treatment with 80 nM QD-EG11-DiMan (∼10%), but it was more pronounced with QD-EG3-DiMan (∼50%). The inhibition potencies obtained here
again roughly matched those expected from their respective DC-SIGNR
binding apparent Kd’s (i.e., ∼633
and ∼62 nM) measured by FRET. The good match between the apparent Kd and IC50 values demonstrated that
our FRET-based Kd measurement could serve
as a viable, rapid method for predicting virus inhibition potency
of glyconanoparticles at the cellular level. Although the toxic cadmium
content can prevent the current QD-glycans from being used for treatment
and prevention of EBOV infection, replacing the CdSe/ZnS QD with other
biocompatible, nontoxic nanoparticles (e.g., gold, Cd-free QD) should
overcome this problem, where nanoparticles displayed with similar
polyvalent glycan ligands could be used as potent, specific virus
inhibitors and therapeutic reagents.
Conclusions
We
have demonstrated that compact QDs displaying dense polyvalent
DHLA-EG-DiMan ligands are powerful probes
for dissecting multivalent protein–glycan interactions via
multimodal readout strategies (FRET, particle size analysis, TEM imaging,
and GNP-based fluorescence quenching). Unlike most other glycoconjugates
that were constructed on passive scaffolds, the unique properties
of QD (e.g., fluorescence, size, and inherent TEM contrast) have been
fully exploited for the purpose of multimodal readout for the first
time. Significantly, we have revealed that DC-SIGN binds tetravalently
to a single QD, whereas DC-SIGNR binds divalently to two different
QDs. The different binding modes, arising from the different CRD spatial
arrangements, yield >100-fold tighter QD-DiMan binding affinity
for
DC-SIGN over DC-SIGNR, which also help to explain why DC-SIGN is more
effective in trans-infecting some HIV strains than DC-SIGNR. Moreover,
a new QD-FRET-based ratiometric method has been developed to quantify
the apparent QD-protein binding Kd. An
impressively low Kd (∼610 pM) and
a per glycan affinity enhancement factor (β/N) of ∼4000 have been attained with QD-DiMan. Importantly,
QD-DiMan was found to potently inhibit DC-SIGN-mediated augmentation
of EBOV-GP-driven infection of host cells with an IC50 of
∼0.7 nM, placing it among the most potent inhibitors against
the EBOV-GP driven virus infections.[10,13,14] Moreover, this IC50 value also matches
well to its DC-SIGN binding apparent Kd measured by the ratiometric QD-FRET readout strategy. Together,
these results demonstrate that the QD-FRET-based affinity measurement
developed herein could serve as a robust, rapid, and sensitive method
for predicting glyconanoparticle inhibition potencies against EBOV-GP
driven virus infections at the cellular level.
Experimental
Section
Materials
A CdSe/ZnS core/shell QD (λEM ≈ 560 nm) was purchased from PlasmaChem GmbH (Berlin, Germany).
The QD was supplied as dry powders and capped with mixed ligands of
trioctylphosphine oxide (TOPO), hexadecylamine, and oleic acid. A
CdSe/ZnSe/ZnS core/shell/shell QD capped with mixed ligands of TOPO
and trioctylphospine (λEM ≈ 605 nm) in toluene
was purchased from STREM chemicals UK Ltd. O-(2-Aminoethyl)-O′-(2-azidoethyl)decylethylene glycol (N3-EG11-NH2, >95% oligomer purity) was purchased
from Polypure Plc (Norway). Azido-3,6,9-trioxyundecan-1-amine (N3-EG3-NH2, >90% monomer purity), N,N-dimethyl-1,3-propanediamine (>99%),
1,3-propane-sultone (>99%), lipoic acid (LA, >99%), triphenylphosphine
(>98.5%), dicyclohexyl-carbodiimide (DCC, >99%), dimethylamino-pyridine
(DMAP, >99%), tris(2-carboxyethyl)phosphine hydrochloride (TCEP·HCl,
>98%), and other chemicals were purchased from Sigma-Aldrich UK
Ltd.
(Dorset, UK). Solvents were obtained from Fisher Scientific (Loughborough,
UK). Ultrapure water (resistance >18.2 MΩ cm) purified by
an
ELGA Purelab classic UVF system was used for all experiments and making
buffers.
Preparation of QD-EG-glycan (n = 3 or 11)[47]
One nanomole
of CdSe/ZnS QD in 0.2 mL of toluene was first precipitated by 1 mL
of ethanol followed by centrifugation to remove any free ligands.
The QD pellet was dissolved in CHCl3 (50 μL), then
DHLA-EG-glycan ligand (0.80 μmol
in CHCl3) predeprotonated by NaOH (8.0 μL, 0.10 M
in EtOH) and MeOH were added to make a homogeneous solution (CHCl3:MeOH = 1:1 v/v). The resulting solution was wrapped in aluminum
foil and stirred at room temperature (rt) for 30 min. Hexane was then
added until the solution became cloudy. The mixture was centrifuged
at 10 000g for 5 min, where all of the formed
QD-EG-glycan pelleted. After removal
of the clear supernatant, the pellet was dissolved in 100 μL
of pure H2O and transferred to a 30 kDa MWCO spin column
and washed with H2O (3 × 100 μL) to remove any
unbound free ligands, yielding the QD-EG-glycan stock. The QD concentration was determined by its first exciton
peak absorbance at 546 nm (ε = 1.3 × 105 M–1 cm–1) using the Beer–Lambert
law.[47]
Fluorescence Spectroscopy
All fluorescence spectra
were recorded on a Cary Eclipse fluorometer using a fixed excitation
wavelength, λEX, of 450 nm, corresponding to the
absorption minimum of Atto-594 to minimize the direct excitation background.
The measurements were performed in a binding buffer (20 mM HEPES pH
7.8, 100 mM NaCl, 10 mM CaCl2) containing 10 μg/mL
of a His6-Cys peptide, which we found to improve the QD
stability and reduce nonspecific adsorption.[47,59] The labeled proteins were mixed with the QD at room temperature
for 20 min before fluorescence spectra were recorded. Binding of labeled
monomeric DC-SIGN or DC-SIGNR CRD with the QDs was performed the same
way. For apparent Kd measurement, a series
of samples containing different concentrations of the QD/labeled proteins
(but with a fixed PQR of 1 for DC-SIGN or 10 for DC-SIGNR) were prepared
in the same binding buffer as above but containing 1 mg/mL of BSA
to reduce nonspecific adsorption. The samples were incubated at room
temperature for 20 min before fluorescence spectra were recorded.
Adjustments of the PMT voltages and EX/EM slit widths were used to
compensate the low fluorescence signal at low concentrations. Although
this may affect the absolute fluorescence intensity, the FRET ratio
is not affected due to its ratiometric nature. All fluorescence spectra
were corrected for the dye direct excitation background by subtracting
the corresponding fluorescence spectrum of the same concentration
labeled protein only recorded under identical conditions.
Data Fitting
Direct excitation background corrected
fluorescence peak intensities at 554 nm (QD) and 626 nm (Atto-594
FRET) were used to calculate the apparent FRET ratio, I626/I554. The I626/I554 ratio versus protein
concentration plots were fitted to Hill’s equation to derive
the apparent Kd:where Rmax is
the saturated FRET ratio, Kd is the apparent
dissociation constant, [C] is the
protein concentration, and n is Hill’s coefficient.
Iterative fittings were used to yield the best fit (R2) for Rmax and Kd determination. The relative binding affinity between
wild-type and labeled DC-SIGN for the QD-DiMan was analyzed by a simple
competitive model, F = IR50/[IR50 + CWT/CLP], where F is the apparent FRET ratio in the presence
of wild-type protein normalized by that without, and CWT and CLP are wild-type and
labeled protein concentrations, respectively. Iterative fittings were
used to yield the best fit (R2) for the
IR50 determination.
STEM Imaging
Three
QD samples (QD-EG11-DiMan,
QD-EG11-DiMan + wild-type DC-SIGN, and QD-EG11-DiMan + wild-type DC-SIGNR) were prepared in binding buffer with CQD = 40 nM and Cprotein = 1.5 μM. 3.5 μL of the QD sample was placed onto a
plasma-cleaned TEM grid with a continuous carbon support film, blotted,
and plunge frozen into liquid ethane. The TEM grids were then warmed
to room temperature over several minutes by placing them in the liquid
nitrogen cooled storage container in a rotary pumped vacuum desiccator.
The samples were analyzed using an FEI Titan Cubed Themis 300 G2 S/TEM
equipped with FEI SuperX energy dispersive X-ray (EDX) spectrometers.
The samples were imaged using high angle annular dark field scanning
transmission electron microscopy (HAADF STEM) mode,[61,64] which provides atomic number contrast (≈Z1.7), thereby permitting imaging of the high atomic number
quantum dots (brighter) on the low atomic number background (darker).
A series of images at the same magnification were recorded for each
sample, which were then analyzed in MATLAB to measure the nearest
neighbor distances (NNDs). Histograms of NNDs for each image were
produced. The combined histograms were plotted as a percentage of
the total population and fitted by Gaussian distribution.
Inhibition
of DC-SIGN/R-Mediated Augmentation of EBOV-GP-Driven
Transduction[47]
The experiments
were performed using humanembryonic kidney293T cells. Target 293T
cells seeded in 96-well plates were transfected with plasmids encoding
DC-SIGN or DC-SIGNR or control transfected with empty plasmid (pcDNA).
The cells were washed at 16 h post transfection and further cultivated
at 37 °C, 5% CO2 in Dulbecco’s modified eagle
medium (DMEM) containing 10% fetal bovine serum (FBS). At 48 h post
transfection, the cells were exposed to twice the final concentration
of QD-DiMan inhibitor in DMEM supplemented with 10% FBS for 30 min
in a total volume of 50 μL. Thereafter, the cells were inoculated
with 50 μL of preparations of MLV vector particles encoding
the luciferase gene and bearing either EBOV-GP or the vesicular stomatitis
virus glycoprotein (VSV-G) as control. Binding of QD-DiMan to DC-SIGN/R
on the surface of 293T cells can block the interaction of these lectins
with the EBOV-GP on the particle surface, reducing the cellular uptake
of vector particles and thus reducing transduction efficiency. At
6 h post inoculation, 100 μL of fresh DMEM culture medium was
added, and the cells were incubated for another 72 h. Thereafter,
luciferase activities in cell lysates were determined using a commercially
kit (PJK), following the manufacturer’s instructions, as described
in our previous publication.[47]
Authors: Fadi Aldeek; Dana Hawkins; Valle Palomo; Malak Safi; Goutam Palui; Philip E Dawson; Igor Alabugin; Hedi Mattoussi Journal: J Am Chem Soc Date: 2015-02-11 Impact factor: 15.419
Authors: S Pöhlmann; F Baribaud; B Lee; G J Leslie; M D Sanchez; K Hiebenthal-Millow; J Münch; F Kirchhoff; R W Doms Journal: J Virol Date: 2001-05 Impact factor: 5.103
Authors: S Pöhlmann; E J Soilleux; F Baribaud; G J Leslie; L S Morris; J Trowsdale; B Lee; N Coleman; R W Doms Journal: Proc Natl Acad Sci U S A Date: 2001-02-27 Impact factor: 11.205
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