Fluorescent nanosensor probes have suffered from limited molecular recognition and a dearth of strategies for spatial-temporal operation in cell culture. In this work, we spatially imaged the dynamics of nitric oxide (NO) signaling, important in numerous pathologies and physiological functions, using intracellular near-infrared fluorescent single-walled carbon nanotubes. The observed spatial-temporal NO signaling gradients clarify and refine the existing paradigm of NO signaling based on averaged local concentrations. This work enables the study of transient intracellular phenomena associated with signaling and therapeutics.
Fluorescent nanosensor probes have suffered from limited molecular recognition and a dearth of strategies for spatial-temporal operation in cell culture. In this work, we spatially imaged the dynamics of nitric oxide (NO) signaling, important in numerous pathologies and physiological functions, using intracellular near-infrared fluorescent single-walled carbon nanotubes. The observed spatial-temporal NO signaling gradients clarify and refine the existing paradigm of NO signaling based on averaged local concentrations. This work enables the study of transient intracellular phenomena associated with signaling and therapeutics.
Nitric oxide
(NO) is integral
to the vascular system as a vasodilator, the nervous system as a neurotransmitter
and the immune system as a defensive agent,[1,2] but
it also plays an integral role in pathology, specifically for inflammatory
diseases, vascular diseases, diabetes, and cancer.[3−6] Currently, NO detection in tissues
is limited to assays developed to detect downstream products of NO.
However, these assays fail to elucidate the implications of fluctuating
intracellular NO levels.Many techniques have been developed
to quantify nitric oxide levels
in biological settings. Two common approaches are the use of small-molecule
labeling dyes[7−13] and specially coated electrodes.[14−18] Dyes are usually delivered intracellularly or in
the interstitia where they bind reactive species and indicate species
concentration through either fluorescence or chemiluminescence. However,
dyes such as the widely used 4,5-diaminofluorescein respond to all
species that nitrosate the substrate, including many NO decomposition
products. Such dyes can also react with dehydroascorbic acid and ascorbic
acid to yield emission products with similar emission wavelengths,
interfering with NO detection.[19] These
dyes are also nonreversible, suffer from chemical photobleaching inherent
to small-molecule fluorophores, and generally cannot be resolved at
a sufficient level to measure NO at subcellular spatial resolution.
Electrochemical measurement, however, is capable of detecting absolute
NO levels but it cannot map the subcellular space. Hence, none of
these methods to date have enabled the detection of intracellular
NO dynamics.Molecular sensors based on nanoscale structures
are well suited
to address many of these limitations with examples including sensors
based on quantum dot FRET probes,[20] graphene
oxide probes,[21] aggregating gold nanorods
and nanoparticles,[22] and single-walled
carbon nanotubes (SWCNTs). SWCNTs have been shown to be particularly
well-suited as intracellular nitric oxide sensors. SWCNTs have a very
strong photoluminescence (PL) response, absorbing and emitting in
the visible and near-infrared (nIR) spectra, respectively. Small-molecule
analytes can interrupt the PL emission by providing a site for generated
excitons to recombine destructively. This results in an easily observable
quenching and in the case of NO, single-molecule detection as individual
molecules adsorb to the surface.[23] Various
polymers or DNA corona phases can wrap the outer surface of the SWCNT
to enable selective molecular detection of other analytes by restricting
molecular access to the SWCNT surface. With this method, we have designed
sensors specific for glucose,[24−27] DNA,[28−31] ATP,[23] H2O2,[32,33] and NO.[23,34] Such sensors have also been demonstrated
for whole-animal measurements[35] but have
not been studied for their ability to do spatiotemporal sensing at
the subcell length scale.In this work, we utilize the SWCNT-based
NO sensor and a new methodology
to study NO generation and intracellular signaling for the first time.
Such sensors are readily internalized by A375melanoma cells through
macropinocytosis,[36] exhibit low background
signals and have a high signal-to-noise ratio that allows for real
time detection of intracellular spatiotemporal NO. NO generation and
subsequent intracellular signaling was assayed using the NO releasing
anticancer drug JS-K in the A375melanoma cells. Endogenous NO generation
from vascular endothelial growth factor (VEGF) stimulation of human
umbilical vein endothelial cells (HUVECs) was also measured. We show
that the resulting spatial and temporal fluctuations can only arise
from two or more asynchronous NO sinks within the cell that are spatially
distinct. This finding provides a more in-depth understanding of intracellular
NO and illustrates just one use of these nanosensor probes and their
capability to expand the knowledge of biological molecules and their
intracellular distribution.While it is currently believed that
the local average concentration
of NO governs its pathophysiology, some studies have indicated the
importance of intracellular NO localization.[37] With the novel SWCNT sensor for NO, we demonstrate that NO concentration
is dynamically modulated at an intracellular level, leading to a more
complex picture of NO signaling and biochemistry. It is shown that
spatiotemporal fluctuations can only be a consequence of temporally
varying NO sinks within the cell, and that two or more asynchronous
sinks must be present to model the observations. These results offer
new possibilities to explore and understand NO signaling. For our
future work, the unique PL emissions of different SWCNT chiralities
can be utilized for the simultaneous study of multiple substrates
and their dynamic interactions.
SWCNT Uptake and Colocalization in Melanoma
Cells
d(AT)15-DNA wrapped SWCNTs previously found
to selectively detect
nitric oxide in vitro[23] were prepared and
introduced to cultures of A375melanoma cells (see Supporting Information Methods). The SWCNT concentration was
quantified via absorbance spectroscopy, and a concentration of 2 μg/mL
was diluted into media for cellular uptake. After introduction of
the SWCNTs and a 12 h incubation, the cells were found to have internalized
the SWCNTs. SWCNT PL was observed using a previously described nIR
fluorescence microscope setup[23] (Figure 1A). Briefly, SWCNTs were excited with a 632 nm laser
(CrystaLaser, CL660-100, 100 mW), and fluorescent emission was monitored
in an inverted microscope (Carl Zeiss, Axiovert 200) using a 100x
TIRF objective and a two-dimensional (2D) liquid nitrogen-cooled InGaAs
near-infrared sensor array (Princeton Instruments OMA 2D). nIR images
were saved every 0.2 s over the course of an experiment. The absorbance
spectra for four SWCNT chiralities[38] is
shown in Figure 1E.
Figure 1
Experimental setup for
the detection of intracellular NO. (A) The
fluorescence setup with an A375 melanoma cell of interest located
on a Petri dish, a 632 nm excitation source, and a nIR sensor array.
(B) Co-localization of the SWCNT sensors (yellow) with the cell endosomes
(red) as indicated using LysoTracker Red. (C) A cartoon of a DNA(AT)15-wrapped SWCNT capable of detecting NO. (D) Chemical pathway
for the penetration and decomposition of JS-K, resulting in increased
NO concentrations in the endosome. (E) Absorbance spectra for four
SWCNT chiralities. (F) Chemical pathway for the binding of VEGF-A
to VEGF receptors on HUVEC cells, causing a release of NO from eNOS
bound to the cell membrane.
Experimental setup for
the detection of intracellular NO. (A) The
fluorescence setup with an A375melanoma cell of interest located
on a Petri dish, a 632 nm excitation source, and a nIR sensor array.
(B) Co-localization of the SWCNT sensors (yellow) with the cell endosomes
(red) as indicated using LysoTracker Red. (C) A cartoon of a DNA(AT)15-wrapped SWCNT capable of detecting NO. (D) Chemical pathway
for the penetration and decomposition of JS-K, resulting in increased
NO concentrations in the endosome. (E) Absorbance spectra for four
SWCNT chiralities. (F) Chemical pathway for the binding of VEGF-A
to VEGF receptors on HUVEC cells, causing a release of NO from eNOS
bound to the cell membrane.The intracellular presence and location of the SWCNTs was
confirmed
through optical and fluorescent microscopy. The SWCNT nIR emission
was observed in the perinuclear region, indicative of a late endosome
and lysosome localization. This was further confirmed through incubation
with LysoTracker Red, which colocalized with the nIR image (Figure 1B). SWCNT sensors were shown to respond through
the direct administration of nitric oxide to the cell medium (see Supporting Information), but this method was
not used extensively because of the short diffusion length, roughly
20 μm,[39] and cellular barriers from
large nitric oxide concentration gradients in and near cells. MAHMA
NONOate [(Z-1-N-methyl-N-[6-(N-methylammoniohexyl)amino]diazen-1-ium-1,2-diolate)] was
also attempted for NO introduction (see Supporting
Information) but release occurred outside of the cell, diluting
its effect. Instead, we relied on the production of intracellular
nitric oxide using the nitric oxide pro-drug JS-K.
Nitric Oxide
Signaling Dynamics in Response to the Glutathione
Activated Donor JS-K
The nitric oxide pro-drug JS-K[40] [O2-(2,4-dinitrophenyl)1-[(4-ethoxycarbonyl)piperazin-1yl]diazen-1-ium-1,2-diolate]
was utilized to exogenously generate intracellular NO concentrations
and signaling. JS-K reacts with intracellular glutathione (GSH) to
produce an intermediate (4-carbethoxy-PIPERAZI/NO) that then releases
two parts NO for each JS-K molecule (Figure 1D). This additional nitric oxide can then freely diffuse throughout
the cell and its intracellular location detected with our SWCNT sensors.
This mechanism was verified first by modulating the JS-K concentration
and then modulating the intracellular GSH concentrations to alter
net nitric oxide production.The degree of SWCNT quenching in
A375melanoma cells was found to increase with increasing JS-K concentrations
in the range of 16–28 μM (Figure 2). For a given JS-K concentration, the baseline integrated SWCNT
PL intensity of a target cell was observed for 400 s. JS-K was then
added to the cell medium, and the PL levels of the same cell were
imaged over another 400 s, which was typically sufficient for the
quenching to reach steady state (Figure 2A).
The PL at local maxima (central SWCNT positions) were also found to
decrease in a similar manner (Figure 2B). Data
for each JS-K concentration represent the results of three replicates
unless otherwise stated. Examples of the PL changes over 3 min for
each tested JS-K concentration (16, 20, 25, and 28 μM) are shown
in Figure 2C, and the final quenched intensity
for each concentration is shown in Figure 2D. To ensure the introduced dimethyl sulfoxide (DMSO) solution was
not responsible for the PL changes, a stock DMSO solution was added
instead and no PL change observed (see Supporting
Information Note 3). The protocol for JS-K administration and
NO release was qualitatively confirmed through the administration
of the commercial NO-sensitive fluorescent dye DAF-FM (see Supporting Information Note 6). It is important
to note that in contrast to diaminofloureceins, SWCNT NO sensors react
with NO directly and do not involve reactive oxygen species nor NO
byproducts.
Figure 2
Confirmation of Intracellular NO Detection. (A) nIR intensity profiles
of the endosome region over 3 min after exposure to JS-K, showing
gradual intensity quenching. (B) Intensity of a single point over
time showing rapid quenching followed by a settling to a new steady
state intensity. (C) Quenching profiles for several JS-K concentrations,
and confirmation of the included literature JS-K pathway by promoting
the intermediate reagent GSH with Cisplatin or reducing GSH with buthionine
sulfoximine (BSO). (D) Calibration curves showing the final quenching
response to various JS-K concentrations after incubation with Cisplatin,
BSO, or sodium azide. (E) A similar calibration curve for a HUVEC
cell exposed to vascular endothelial growth factor (VEGF).
Confirmation of Intracellular NO Detection. (A) nIR intensity profiles
of the endosome region over 3 min after exposure to JS-K, showing
gradual intensity quenching. (B) Intensity of a single point over
time showing rapid quenching followed by a settling to a new steady
state intensity. (C) Quenching profiles for several JS-K concentrations,
and confirmation of the included literature JS-K pathway by promoting
the intermediate reagent GSH with Cisplatin or reducing GSH with buthionine
sulfoximine (BSO). (D) Calibration curves showing the final quenching
response to various JS-K concentrations after incubation with Cisplatin,
BSO, or sodium azide. (E) A similar calibration curve for a HUVEC
cell exposed to vascular endothelial growth factor (VEGF).We investigated NO dynamics in the presence of
both elevated and
suppressed GSH. Intracellular GSH levels were measured using a GSH
assay (see Supporting Information Methods)
with a measured concentration of 1.3 ± 0.3 mM inside the A375melanoma cells. Incubating the cells with Cisplatin (see Supporting Information Methods), a chemotherapeutic
agent that cross-links DNA increasing cellular stress and GSH production,[41] resulted in an increased GSH concentration of
3.2 ± 0.4 mM and increased PL quenching for each concentration
of JS-K tested (Figure 2D). Conversely, incubating
the cells with buthionine sulphoximine (BSO), an inhibitor of gamma-glutamylcysteine
synthetase that reduces GSH concentrations,[42] resulted in a decreased GSH concentration of 0.71 ± 0.24 mM
and less PL quenching (Figure 2D). Finally,
administering sodium azide disabled aerobic metabolism in the melanoma
cells and effectively removed their ability to produce GSH. Subsequent
addition of JS-K resulted in no observable quenching of the SWCNT
PL (Figure 2D).
Application to Vascular
Endothelial Growth Factor and HUVEC
Cells
To examine our hypothesis in a different system, vascular
endothelial growth factor (VEGF)-mediated NO production was monitored
in endothelial cells. HUVEC cells were observed to uptake the SWCNT
sensors using the same incubation protocol as the A375melanoma cells.
Introducing VEGF activates endothelial nitric oxide synthase (eNOS)[43] resulting in an increase in intracellular NO
concentration and a detectable quenching of the SWCNT PL, as illustrated
in Figure 1F. PL quenching was tested for VEGF
treatments ranging from 1 ng/mL to 100 ng/mL. Responses were observed
at the widely accepted treatment concentration of 10 ng/mL (Figure 2E). Furthermore, VEGF stimulated NO release occurs
more rapidly with larger intracellular gradients, illustrating the
differences between physiological and pharmacological NO release (see Supporting Information).
Spatiotemporal Mapping
of Intracellular Nitric Oxide
To interpret the resulting
novel data sets, we developed an absorption/scattering
image processing algorithm for allowing spatial and temporal data
to be extracted from movies of cellular quenching during NO signaling,
which we demonstrate for the case of an A375melanoma cell responding
to JS-K. The d(AT)15-DNA wrapped SWCNT sensors allow for
spatiotemporal resolution of nitric oxide concentrations not possible
with previous NO detection mechanisms. Inside the cell, the SWCNTs
are localized to multiple endosomes resulting in multiple effective
sensors within the cell. Each SWCNT bundle within an endosome functions
as a point source of photoluminescent light in the nIR scattering
and absorbing cell, effectively illuminating the surrounding region
(Figure 3A,B). The SWCNT centers and intensities
were reconstructed using a simple nIR scattering/absorption model,
and the resulting intensity traces were analyzed to calculate the
observed nitric oxide signal using known kinetics for SWCNT PL quenching
by NO.
Figure 3
Calculation of intracellular nitric oxide concentration
through
observations of SWCNT fluorescence. (A) Fluorescence intensity of
SWCNT in A375 melanoma cell. (B) Experimental intensity profile. (C)
Reconstructed intensity profile after fitting a small number of point
illumination sources with point spread functions indicated in the
inset. (D) Demonstration that point-source process retains the same
total intensity information from Figure 2.
(E) Intensity for each point source, before and after removal of high
frequency noise with a smoothing spline. (F) Calculated nitric oxide
concentration for each point source using a kinetic model for the
adsorption/desorption of nitric oxide on SWCNT.
Each SWCNT bundle is treated as a point illumination
source. The propagation of nIR light in tissue and cells is effectively
modeled at steady state by solving the Helmholtz equation for a scattering/absorbing
mediumwhere ϕ is the spatially
varying light
intensity, μa, μs, and g are the tissue absorption, scattering, and anisotropy coefficients
at the emission wavelength, approximated with values from in vivo
melanoma tissue,[44] and the source term
for a point illumination source with intensity ϕ0 and location r1 is a delta function
ϕ0δ(r – r1). For point sources in an unbounded medium, the Green’s
function isand the resulting spatiotemporal intensity
for the illumination from all SWCNT point sources is a summation over
the Green’s function for each point sourcewhere ϕ0,(t) and r(t) are the time-dependent intensity and position
of the kth SWCNT bundle. A point source was initially
placed at every local maximum in the first frame of a nIR experimental
movie and the closest sources combined until the minimum point separation
was below a threshold distance of 5 μm (the length scale of
interest). At each time frame T, we minimize the
error between the frame pixels I and the calculated intensity by adjusting the point intensity
and locationsAn
example of the resulting intensity field
ϕ(r,t) is shown in Figure 3C, as well as the point spread function G(r) in the inset. Summation of the intensity
field at each time point (Figure 3D), resulted
in the same integrated information as discussed in Figure 2.Calculation of intracellular nitric oxide concentration
through
observations of SWCNT fluorescence. (A) Fluorescence intensity of
SWCNT in A375melanoma cell. (B) Experimental intensity profile. (C)
Reconstructed intensity profile after fitting a small number of point
illumination sources with point spread functions indicated in the
inset. (D) Demonstration that point-source process retains the same
total intensity information from Figure 2.
(E) Intensity for each point source, before and after removal of high
frequency noise with a smoothing spline. (F) Calculated nitric oxide
concentration for each point source using a kinetic model for the
adsorption/desorption of nitric oxide on SWCNT.The local nitric oxide concentration at each sensor location
can
be calculated by considering the reversible interaction of NO with
an unoccupied site on the SWCNT surface, forming the NO-SWNCT complex
that results in a quenched emission state at that site, as we have
shown previously in the case of single molecule detection[45] of NO. The adsorption and desorption of nitric
oxide can be described by a first order reversible process, leading to the rate expressionwhere kf, kr are the forward
and backward rate constants,
respectively, and calculated from previous in vitro single-SWCNT experiments[23] to be kf = 8.68
× 10–4 (μM s)−1 and k = 3.18 × 10–3 s–1 (see Supporting Information Note 5). The SWCNT PL intensity is proportional to the fraction
of unoccupied sites, [SWCNT], or I/I0 = [SWCNT]/[SWCNT]0. The value of I0 was set to correspond to the minimum initial
NO concentration for the calculated concentrations to be positive,
or I0 = I([1 + (kf/kr)C0], where C0 = 5 μm. The number of sensor sites are conserved
with the conservation relation [SWCNT]0 = [SWCNT] + [NO-SWCNT].
Making this substitution and rearranging, the concentration of NO
can be calculated directly from the local intensity and its time-derivativeThe finite imaging detector frame rate
introduces noise into the
calculation of the intensity derivative, potentially amplifying the
fluctuations in the excitation source. Hence, each intensity trace
is smoothed using a FFT low-pass filter prior to differentiation (Figure 3E). This method yielded similar results as compared
to regularized differentiation[46] at a fraction
of the computation cost. The resulting nitric concentrations are shown
in Figure 3F for each of the SWCNT groupings
in Figure 3C. Full analysis for each of the
experimental conditions is included in Supporting
Information Note 1. These NO concentrations fall within the
same range as those reported in previous studies.[39] Complete analysis of nitric oxide concentration for all
experimental conditions are included in the Supporting
Information.Previous work has shown that DNA-wrapped
SWCNT enter the cell through
macropinocytosis.[36] We found that the majority
of A375melanoma cells displayed fluorescent SWCNTs in multiple endosomes
after a 3 h incubation. These allowed for the measurement of the heterogeneity
of intracellular nitric oxide generation and decay (Figure 4). At each observed time point, the concentration
difference between each pair of SWCNT sensors was calculated and normalized
by their spatial separation. All of the observed differences over
the course of an experiment were used to build a probability density
of concentration differences (Figure 4A). Before
stimulation with JS-K, difference values of approximately 0.1 μM/μm
were observed, corresponding to baseline intracellular NO heterogeneity.
When 28 μM of JS-K was added, NO differences increased to 1
μM/μm. This change is potentially due to a combination
of variations in JS-K diffusion into the cell and intracelluar glutathione
(see Figure 3F). Over time, the observed differences
returned to their values before JS-K addition.
Figure 4
Observed intracellular
NO gradients and a numerical model for the
release of NO by JS-K addition. (A) Typical observed NO concentration
gradients between sensor regions before and after the introduction
of 28 μM JS-K. Baseline concentration differences are approximately
0.1 μM/um. A second peak in the histogram at approximately 1
μM/um occurs at the beginning of the experiment, before the
SWCNT settle to a new equilibrium. (B) Diffusion-reaction model simulation
of intracellular NO formation with 16 μM JS-K addition. Zero
to four sources of intracellular GSH are placed in various locations.
The system is optimized such that NO concentration is approximately
4 μM, and the gradient is studied. (C,D) For each scenario in
B, the gradient is calculated as the concentration difference collected
at random pairs of locations within 3 μm of the nucleus normalized
by distance. A probability density distribution is then plotted. Results
show that at least one source is required to reproduce the concentrations
and gradients.
Observed intracellular
NO gradients and a numerical model for the
release of NO by JS-K addition. (A) Typical observed NO concentration
gradients between sensor regions before and after the introduction
of 28 μM JS-K. Baseline concentration differences are approximately
0.1 μM/um. A second peak in the histogram at approximately 1
μM/um occurs at the beginning of the experiment, before the
SWCNT settle to a new equilibrium. (B) Diffusion-reaction model simulation
of intracellular NO formation with 16 μM JS-K addition. Zero
to four sources of intracellular GSH are placed in various locations.
The system is optimized such that NO concentration is approximately
4 μM, and the gradient is studied. (C,D) For each scenario in
B, the gradient is calculated as the concentration difference collected
at random pairs of locations within 3 μm of the nucleus normalized
by distance. A probability density distribution is then plotted. Results
show that at least one source is required to reproduce the concentrations
and gradients.The diffusion of nitric
oxide has been very well studied. For a
diatomic gas with a diffusion coefficient of 10–7 cm2/s, equilibrium can be achieved on the order of 10
ms. However, our setup detects intracellular concentration differences
persisting over seconds. We demonstrate below that such spatial and
temporal fluctuations can only occur from the asynchronous modulation
of two or more spatially distinct NO sinks within the cell. These
results can be understood with a simple numerical model for JS-K diffusion
and reaction to produce nitric oxide within the cell.
Numerical Model
for the Response of Intracellular SWCNT to an
External JS-K Stimulus
To understand the implications of
the nitric oxide gradients reported by our sensors under a variety
of conditions, we constructed a simple numerical 2D model for the
diffusion of JS-K into the cell and the reaction with GSH to form
NO according to the scheme presented in Figure 1D. We also consider various models for spatially heterogeneous production
and consumption of intracellular NO that have not yet been considered
due to the lack of NO sensors with sufficient spatial resolution.We construct a diffusion and reaction model to simulate intracellular
nitric oxide (NO) concentrations from JS-K treatment (see Supporting Information Table 1 for model parameters
and Supporting Information Note 2 for full
details of the model). The geometry of the system simulates the cytosol
with a 10 μm diameter circle and a nucleus at the center with
a 2 μm diameter impermeable boundary (Figure 4). The outer boundary of the cytosol was permeable to JS-K
and NO but impermeable to GSH. The concentration of JS-K was set outside
the cell to the various levels used in the experiments (16–28
μM). The reaction of JS-K with GSH to form NO was included with
literature rate data.[40] Intracellular NO
production and first-order consumption was modeled both homogeneously
and heterogeneously with sources and sinks as two-dimensional sinusoidal
functions (i.e., proportional to[sin(x/X)sin(y/Y)], where we control the sharpness and position of the function
with a, x, and y). The magnitudes of these functions were adjusted to obtain the
experimental concentrations of NO and the resulting intracellular
spatial differences were compared. COMSOL was used to solve for the
resulting NO concentrations and each simulation was run until equilibrium
was reached, typically 10 s.We performed the simulation for
combinations of four potential
sources placed either proximal or distal to the nucleus (Figure 4B). Random pairs of points were used to calculate
the gradient in the perinuclear region, defined as between 1 and 3
μm to the center of the simulated cell. A kernel density estimation
of the gradient probability density distribution was constructed to
compare with the experimental readings (Figure 4C,D). At least one sink that caused a polarization of the intracellular
NO concentrations was required to result in gradients similar to those
reported by our intracellular sensors. Furthermore, while proximal
sources created higher gradient readings, probability density function
shapes from sources further away from the nucleus more closely resembled
the data. We hypothesize that the sensors are detecting multiple GSH
sources at different intracellular locations during the experiment.
Future work will focus on the identification and characterization
of cellular sources of NO. As SWCNT sensors can be modified to detect
a variety of species, this intracellular detection schema can be used
to understand the distribution and modulation of other biological
molecules.The role of NO in human physiology and pathology
is paradoxical
not only in its contributions to vasodilation, neurotransmission,
and intercellular signaling but also its implications in DNA damage,
lipid oxidation, and cancer progression. One prevailing hypothesis
explaining this paradox attributes the NO associated pathway and outcome
to local concentrations on the tissue or cellular scale. It is important
to note that current detection systems potentially yielding such spatial
information either do not have the required resolution or fail to
measure NO directly. Therefore, the field currently lacks the appropriate
tools to test the above hypothesis.The method we developed
in this work along with our findings call
into question the notion of an average cellular concentration of NO.
We show clear evidence for persistent gradients within the cell. These
gradients are observed with both exogenous (JS-K) and endogenous (VEGF
→ eNOS) NO sources. We believe that these gradients are a result
of sources and sinks nonuniformly distributed within the cell. With
gradients of the magnitude that we observe, regions of the cell will
experience NO concentrations at orders of magnitude higher than others.
This phenomenon and its regulation can be important in NO signaling
and is not reflected in current bulk detection systems. Even more
importantly, we show that this gradient fluctuates in tens of seconds
and that this can only arise from temporal modulations in the source
and sink pathways for NO. As biological signaling is often modulated
via duration and frequency, deciphering intracellular NO dynamics
can prove to be instrumental in studying the mechanism of NO action
for its various biological functions.We use d(AT)15-DNA in this work to demonstrate the intracellular
detection of NO. In comparison with other techniques, the preparation
of SWCNT probes is relatively simple and does not require organic
synthesis. These sensors are stable for prolonged periods of time
and do not photobleach with repeated excitation at high frequency.
Furthermore, nIR imaging allows for minimal signal attenuation in
biological environments that also lends itself to tissue analysis
in addition to in vitro culture. For the first time, we were able
to achieve intracellular spatial and temporal NO resolution. In addition
to concentration, we show that location and frequency of NO signals
can now be detected and may play a major role in intra- and extracellular
communication.Overall, this technology allows for the study
of NO that will further
our understanding of its function in cellular signaling and equilibrium.
It can also be readily expanded for the detection of other species
and multiplexed for multiplex applications. In this case, investigation
of NO dynamics can extend to applications such as the early detection
of endothelial dysfunction and the study of tumor progression and
response to treatment. As a unique tool to query cellular states,
these sensors provide new and valuable information in both the basic
understanding and potential toward novel clinical diagnostics.
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