Sudhir Kumar Sharma1, Sauparnika Vijay2, Sangram Gore2, Timothy M Dore2,3, Ramesh Jagannathan1. 1. Engineering Division, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE. 2. Science Division, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE. 3. Department of Chemistry, University of Georgia, Athens, Georgia 30602, United States.
Abstract
The cellular-level process of ion transport is known to generate a magnetic field. A noninvasive magnetoencephalography (MEG) technique was used to measure the magnetic field emanating from HeLa, HEK293, and H9c2(2-1) rat cardiac cells. The addition of a nonlethal dose of ionomycin to HeLa and capsaicin to TRPV1-expressing HEK293 cells resulted in a sudden change in the magnetic field signal consistent with Ca2+ influx, which was also observed by confocal fluorescence microscopy under the same conditions. In contrast, addition of capsaicin to TRPV1-expressing HEK293 cells containing an optimum amount of a TRPV1 antagonist (ruthenium red), resulted in no detectable magnetic or fluorescent signals. These signals confirmed that the measured MEG signals are due to cellular ion transport through the cell membrane. In general, there is evidence that ion channel/transporter activation and ionic flux are linked to cancer. Therefore, our work suggests that MEG could represent a noninvasive method for detecting cancer.
The cellular-level process of ion transport is known to generate a magnetic field. A noninvasive magnetoencephalography (MEG) technique was used to measure the magnetic field emanating from HeLa, HEK293, and H9c2(2-1) rat cardiac cells. The addition of a nonlethal dose of ionomycin to HeLa and capsaicin to TRPV1-expressing HEK293 cells resulted in a sudden change in the magnetic field signal consistent with Ca2+ influx, which was also observed by confocal fluorescence microscopy under the same conditions. In contrast, addition of capsaicin to TRPV1-expressing HEK293 cells containing an optimum amount of a TRPV1 antagonist (ruthenium red), resulted in no detectable magnetic or fluorescent signals. These signals confirmed that the measured MEG signals are due to cellular ion transport through the cell membrane. In general, there is evidence that ion channel/transporter activation and ionic flux are linked to cancer. Therefore, our work suggests that MEG could represent a noninvasive method for detecting cancer.
At a global level, cancer therapeutics suffer from the lowest success
rate compared to therapeutics for other major diseases. All indications
suggest that cancer will soon be the leading cause of mortality in
developed countries. The future of cancer research depends on the
successful inter-dependencies between therapeutic, diagnostic, and
prognostic technologies.[1,2] The power of early detection
in particular is key to successful therapeutic and prognostic outcomes,
and noninvasive imaging techniques such as CT, MRI, and PET are proving
to be extremely useful.[1,3] A radically different approach
to early-stage detection would focus on the development of noninvasive
techniques to monitor the cellular-level process of ion transport
through membranes and related membrane protein interactions as an
indicator of cell health. The changes to membrane polarizations are
measured by electrophysiology, fluorescent dyes, and proteins that
respond to changes in voltage or specific charged analytes (e.g.,
Ca2+) in the cytoplasm. There is evidence that ion channel
and transporter activation are linked to cancer.[4−6] Dividing cells
like HeLa cells have a lower membrane potential (−48 mV)[7] than that of nondividing ones (e.g., neurons
with −60 to −70 mV).[8] Metastatic
cancer cells are typically more depolarized than normal cells.[9,10] Overexpression of potassium channels has been strongly associated
with a number of cancer cell lines, and the phenomenon is generally
accepted as fundamental to understanding cancer biology.[4,11,12]From basic physics, it
is known that an ion (i.e., a charge carrier)
moving through an electric field will generate a current and a magnetic
field. Naturally, it follows that ion flow through polarized cell
membranes should result in a net magnetic field and magnetic sensors,
in principle, have the potential to quantitatively measure them. Detectors
of magnetic fields have been used to probe nerve impulses and ion
transporters in cell and tissue culture.[13−15] Wijesinghe
described the results of their work with a specially designed neuromagnetic
current probe to measure magnetic fields created by single axons and
bundles.[16] Precise high-resolution measurements
of action potentials from individual neuronal activity have been made
using a technique based on optically probed nitrogen vacancy (NV)
quantum defects in diamond.[17,18] This technique enabled
long-term data collection without any bleaching effects at sub-millisecond
resolution and is label-free. However, it did not have sufficient
detection sensitivity for weak magnetic fields that are generated
through cell membranes in broad classes of different cell types.Magnetoencephalography (MEG) was one of the three early techniques
that clearly established the existence of measurable magnetic fields
due to ionic action currents in biological tissues.[19−21] Due to significant
advances in computational science, MEG has become a useful tool to
study brain function, neuronal activities, and their associated magnetic
fields. In the last several years, significant research activity in
the MEG field has been able to firmly establish the quantitative causal
relationship between magnetic signals and ionic currents in isolated
nerve axons and muscle systems.[13] A MEG
instrument consists of an array of superconducting quantum interference
device (SQUID) detectors.[22,23] They can measure fields
as small as a femtotesla in millisecond timeframes. Modern-day MEG
systems consist of axial gradiometers that only measure a change in
the magnetic field.Taken together, these observations suggest
that SQUID devices arrayed
in a MEG instrument may have the potential to reveal fundamental information
about cancer by noninvasively measuring the magnetic signature of
the tissue.[22,23] In this manuscript, we propose
that the naturally emanating magnetic signals generated by ion flux
in various cell types in culture can be quantitatively measured using
the MEG system.
Results and Discussion
We adapted a MEG system originally designed for a human head and
instead applied it to tissue culture. Data were collected on a 224-channel
(sensors) MEG system (model PQ1128R, Figure a) with a headpiece designed to fit a human
subject’s head (Figure b) containing an array of 208 SQUID sensors (Figure c) and three orthogonally oriented
reference sensors located away from the headpiece. It is important
to note that, at a given time, the MEG system consisting of axial
gradiometers will only measure a change in a contiguous magnetic field
that is perpendicular to the pickup coil. In other words, the MEG
signals describe the temporal characteristic of ion transport through
the channels due to opening and closing of the channels (i.e., the
rise and fall rates) and could provide valuable information regarding
channel-gating dynamics. A zero MEG signal might imply a constant,
steady-state transmembrane ionic flux. Various parameters were examined,
such as the cell type (HeLa, HEK 293, and H9c2(2-1)), number of cells
(n = 1 × 105, 5 × 105, 1 × 106, and 2 × 106), flask sizes,
shapes, and location and orientation within the MEG headpiece, to
determine the best experimental protocol for our experiments. We decided
to use T-25 flasks as a preferred choice and maintained all the geometrical
parameters relative to the MEG headpiece constant. We also took a
more constrained approach to only include signals equal to 750 fT
or greater in magnitude.
Figure 1
Concept diagram of the MEG system used in the
study. (a) Sketch
of the system with the MEG head where the sensor array is located.
(b) Magnified sketch of the MEG head with the cavity where the cell
culture flask is placed. (c) Actual schematic of the sensor array
located within the MEG head.
Concept diagram of the MEG system used in the
study. (a) Sketch
of the system with the MEG head where the sensor array is located.
(b) Magnified sketch of the MEG head with the cavity where the cell
culture flask is placed. (c) Actual schematic of the sensor array
located within the MEG head.
Ionomycin-Induced Ca2+ Flux in
HeLa Cells in Culture
Confocal Fluorescence
Microscopy Studies
Ionomycin is a diacidpolyether antibiotic
that has a high affinity
for Ca2+, which gives it ionophoric properties.[24] Ionomycin stimulates the release of Ca2+ from internal stores and Ca2+ influx from the extracellular
space through ion channels or both.[25,26] The net effect
is an increase in intracellular [Ca2+]. The smallest dose
of ionomycin to give a Ca2+ signal from the Ca2+-sensitive fluorescence dye (Fluo-4) was determined by treating HeLa
cells in culture with increasing ionomycin concentrations and observing
the effects by confocal fluorescence microscopy (Figure a). Below 2 μM, ionomycin
did not result in any noticeable fluorescence signal, but a maximal
signal was observed at 2 μM, indicating Ca2+ influx
into the cytosol. Exposure to high ionomycin concentrations caused
extended cell death. We determined the optimum concentration of ionomycin
and length of exposure to be 1, 2, and 5 μM and 5, 10, and 30
min, respectively. The extent of cell death was measured by trypan
blue assay (Figure b). A 2 μM ionomycin concentration for an exposure of 5 min
resulted in 10% cell death, and longer exposure times and higher concentrations
led to greater cell death (Figure c,d).
Figure 2
Effect of ionomycin addition on cytosolic Ca2+, cell
death, and the MEG data. (a) Normalized fluorescent signal from Fluo-4
upon exposure to 0.5, 1.0, 1.5, and 2.0 μM ionomycin to establish
the minimum ionomycin concentration to observe a response from the
calcium indicator. (b) Percentage of cell death from 5, 10, and 30
min exposure to 1, 2, and 5 μM ionomycin observed in a trypan
blue assay. Error bars represent the standard deviation of the measurement.
(c, d) Confocal images of HeLa cells loaded with Fluo-4 (c) before
and (d) after addition of ionomycin (2 μM). (e) MEG data for
1 × 106 cells detected by channels 121, 127, 131,
137, and 142 when ionomycin (2 μM) is added to the flask as
indicated by the dashed line.
Effect of ionomycin addition on cytosolic Ca2+, cell
death, and the MEG data. (a) Normalized fluorescent signal from Fluo-4
upon exposure to 0.5, 1.0, 1.5, and 2.0 μM ionomycin to establish
the minimum ionomycin concentration to observe a response from the
calcium indicator. (b) Percentage of cell death from 5, 10, and 30
min exposure to 1, 2, and 5 μM ionomycin observed in a trypan
blue assay. Error bars represent the standard deviation of the measurement.
(c, d) Confocal images of HeLa cells loaded with Fluo-4 (c) before
and (d) after addition of ionomycin (2 μM). (e) MEG data for
1 × 106 cells detected by channels 121, 127, 131,
137, and 142 when ionomycin (2 μM) is added to the flask as
indicated by the dashed line.
MEG Studies
We repeated the same
fluorescence microscopy experiment using a MEG instrument to measure
the change in the magnetic field. The addition of 2 μM ionomycin
to 1 × 106 HeLa cells resulted in a change in the
magnetic signal (Figure e and Figure S1). It took approximately
1–2 s to add all the ionomycin solution to the culture flask
and record the time of completion. The red dotted line represents
the end of ionomycin solution addition to the culture flask. Immediately
afterward, a sudden, significant increase in the magnetic signal (
50–75 pT) in several channels was observed over a period of
0.15 s, and the signal rapidly decayed thereafter. It is reasonable
to assume that the processes related to the release of Ca2+ from internal stores and Ca2+ influx from the extracellular
space through ion channels were triggered from the moment we started
to add ionomycin to the culture flask. Since the MEG system only detects
a change in the magnetic field and ionomycin-induced Ca2+ flux is irreversible, the rapid decay of the MEG signal after 0.15
s probably indicated the onset of a steady-state Ca2+ flux.
During the signal oscillations, the intensities of the signals were
attenuated, probably due to saturation of the sensors. Overlaid plots
of the signals measured by channels 121,127, and 142 (Figure S2) show that the temporal response rates
and curve shapes of the signals are identical; this confirms that
the source of the signals is the same. The signal measured by channel
121 does not show any spikes, probably because the orientation of
the spiked response is not perpendicular to the pickup coil of the
sensor or perhaps because the sensor is located further away from
the cells. For the control experiment, we repeated the above experiment
but added the same volume of the culture media without any ionomycin
to the flask. We found no detectable change in the magnetic signal
(Figure S3).
Capsaicin-Induced
Ca2+ Flux in
TRPV1-Expressing HEK293 Cells in Culture
Confocal
Fluorescence Microscopy Studies
A method to induce Ca2+ ion flux is to activate transient
receptor potential cation channel subfamily V member 1 (TRPV1) on
the surface of cells. The TRP family of ion channels is part of well-understood
cellular sensors that regulate the response to temperature, touch,
pain, and other stimuli.[27,28] Activation of TRPV1 by either binding of a ligand such as capsaicin,
a small molecule that is the active component in chili peppers and
imparts a burning sensation by activating nociceptive sensory neurons; N-vanillyl-nonanoylamide (VNA), an equipotent capsaicin
analog; or by exposure to noxious heat (>37 °C) results in
nerve
terminal depolarization and generation of action potentials.[29] The responses observed by engineered and endogenously
expressed TRPV1 channels to both applied capsaicin and exposure to
heat are nearly identical,[30] making activation
of TRPV1 channels a versatile method for studying signal transduction
activity of sensory neurons.Using a confocal fluorescence microscope,
we measured the influx of Ca2+ with the Ca2+ sensitive dye (Fluo-4) before and after the TRPV1-expressing HEK293
cells were exposed to the TRPV1 receptor agonist capsaicin (Figure a). Capsaicin dosage
levels were optimized to achieve a maximum fluorescence signal with
minimal toxicity (Figure S4-1). In these
experiments, activation of TRPV1 channels depends on the diffusion
of capsaicin to the cell receptors. Capsaicin (10 μM final concentration)
was added to these cells, and the influx of Ca2+ was observed
(Figure b and Figure S4-2). The cells responded with a significant
increase in the fluorescence signal after the addition of capsaicin.
The fluorescence signal in some cells decayed back to nearly starting
levels, whereas in other cells, this signal decay was not observed.
This is probably because there is ample capsaicin in the media to
keep the ligand bound to the channels, which holds them open. In another
series of experiments, we investigated the effect of the TRPV1 antagonist
ruthenium red on capsaicin addition to TRPV1-expressing HEK293 cells.
We added ruthenium red (10 μM final concentration) to the flask
containing adherent HEK293 cells prior to the addition of capsaicin
(Figure c). As expected,
subsequent addition of capsaicin (10 μM final concentration)
did not result in any detectable fluorescence signals (Figure d and Figure S4-3).
Figure 3
Effect of capsaicin addition on cytosolic Ca2+ on HEK293
cells stably transfected with TRPV1 with and without the TRPV1 antagonist
ruthenium red using confocal florescence imaging and MEG: (a) images
of HEK293 cells stably transfected with TRPV1 channels loaded with
Fluo-4 before addition of capsaicin. (b) Images of HEK293 cells stably
transfected with TRPV1 channels loaded with Fluo-4 after addition
of capsaicin (10 μM). (c) Images of HEK293 cells stably transfected
with TRPV1 channels containing the TRPV1 antagonist ruthenium red,
(10 μM) loaded with Fluo-4 before addition of capsaicin (10
μM). (d) Images of HEK293 cells stably transfected with TRPV1
channels, containing ruthenium red (10 μM) loaded with Fluo-4
after addition of capsaicin (10 μM). (e) MEG data for 0.05 ×
106 HEK293 cells stably transfected with TRPV1 channels
detected by channels 148, 150, 162, 177, and 181 when capsaicin in
the culture media (10 μM final concentration) was added to the
flask at the time point marked by the dotted line. (f) MEG data for
0.05 × 106 HEK293 cells stably transfected with TRPV1
channels, containing ruthenium red (10 μm), detected by channels
163, 164, 177, 183, and 198 when capsaicin in the culture media (10
μM final concentration) was added to the flask at the time point
marked by the dotted line.
Effect of capsaicin addition on cytosolic Ca2+ on HEK293
cells stably transfected with TRPV1 with and without the TRPV1 antagonist
ruthenium red using confocal florescence imaging and MEG: (a) images
of HEK293 cells stably transfected with TRPV1 channels loaded with
Fluo-4 before addition of capsaicin. (b) Images of HEK293 cells stably
transfected with TRPV1 channels loaded with Fluo-4 after addition
of capsaicin (10 μM). (c) Images of HEK293 cells stably transfected
with TRPV1 channels containing the TRPV1 antagonist ruthenium red,
(10 μM) loaded with Fluo-4 before addition of capsaicin (10
μM). (d) Images of HEK293 cells stably transfected with TRPV1
channels, containing ruthenium red (10 μM) loaded with Fluo-4
after addition of capsaicin (10 μM). (e) MEG data for 0.05 ×
106 HEK293 cells stably transfected with TRPV1 channels
detected by channels 148, 150, 162, 177, and 181 when capsaicin in
the culture media (10 μM final concentration) was added to the
flask at the time point marked by the dotted line. (f) MEG data for
0.05 × 106 HEK293 cells stably transfected with TRPV1
channels, containing ruthenium red (10 μm), detected by channels
163, 164, 177, 183, and 198 when capsaicin in the culture media (10
μM final concentration) was added to the flask at the time point
marked by the dotted line.MEG experiments with
TRPV1-expressing HEK293 cells were carried out in a similar manner
to the fluorescence microscopy experiments. We added capsaicin (10
μM final concentration) to HEK293 cells in culture and observed
a significant spike in the magnetic signal in several channels (Figure e). The black dotted
lines in Figure e
represent the approximate time of completion of the capsaicin solution
addition to the culture flask. The signals decayed to the baseline
in a way similar to the experiments with ionomycin addition. The intensity
of the spike in the magnetic signal due to capsaicin (3–5 pT)
was much less than that observed in the ionomycin experiments (50–75
pT), and the much shorter duration of the spike was probably due to
the magnetic signal strength falling below our threshold of 0.75 pT.
Overlaid plots of these signals (Figure S6) confirmed that the signals measured by these channels originated
from a single source. Plotting the dependence of the measured magnetic
field as a function of [capsaicin] (Figure S7) revealed that increasing [capsaicin] from 0 to 10 μM resulted
in a proportional increase in [Ca2+], which reached a steady-state
value. Overall, it is clear that an increase in [capsaicin] and hence
an increase in [Ca2+] resulted in an increase in the magnetic
field. The effect of the addition of capsaicin to adherent TRPV1-expressing
HEK293 cells detected by an immediate spike in the magnetic signal
has been repeated several times for different concentrations. These
results strongly support our hypothesis that the measured magnetic
signals correspond to cellular ionic flux. In control experiments,
when only the culture media was added to the cells, we detected no
increase in the magnetic signal (Figure S8). We also investigated the effect of TRPV1 antagonist (ruthenium
red) on capsaicin addition to TRPV1-expressing HEK293 cells in culture.
Ruthenium red (10 μM final concentration) was added to the flask
containing the adherent HEK293 cells in culture prior to the addition
of capsaicin. No detectable magnetic signals were observed after capsaicin
(10 μM final concentration) addition (Figure f). The experiment was repeated several times
during the same day and on different days. The results are consistent
with the fluorescence experiments, demonstrating that the magnetic
signals measured by the MEG system are strongly correlated to the
cellular ionic flux. We would like to note that, while we are monitoring
the [Ca2+] activity, a major contributor to the ionic flux
through these channels would be [Na+].
Effect of Multiple Additions of Capsaicin
We further examined the stability
of the adsorbed capsaicin on
the cell membrane by making multiple additions of capsaicin to the
same cells and observing the effect with confocal microscopy (Figure S9). Whereas the first addition of capsaicin
(10 μM final concentration) resulted in a spike in the fluorescence
intensity, the second addition did not result in any detectable response.
This observation likely results from saturation of the TRPV1 receptors
with capsaicin, which has an EC50 of approximately 300
nM.[31]
MEG
Studies
MEG experimental results
were also found to be consistent with fluorescence experiments when
capsaicin was added at 100 and 725 s (Figure S10) to the same cell population. That is, whereas the first addition
of capsaicin (10 μM final concentration) resulted in a spike
in the magnetic signal, the second addition of the same concentration
did not result in any detectable response. Similar observations were
made when the experiments were repeated with different waiting periods
of up to 10 min between the two capsaicin additions.In a second
set of experiments, we examined the effect of replacing the culture
before the second addition by washing the cells with fresh culture
three times (Figure S11). Once again, the
first addition of capsaicin resulted in a magnetic signal, but no
detectable magnetic response was observed after the second addition
(Figure S12), probably because the TRPV1
channels were saturated with the agonist. Any subsequent addition
of capsaicin would therefore have no significant effect on Ca2+ flux through the channels. The results support the hypothesis
in that the measured magnetic signals are due to the cellular ionic
flux.
Magnetic Field Measurements
from Cells in
Culture
HeLa Cells
MEG data from channels
3, 21, 35, 45, and 175 for 1 × 106 HeLa cells in culture
at 80% confluency reveal a cluster of signals, approximately 1–3
pT in intensity (Figure a and Figure S13). Overlaid plots of signals
from three channels (3, 21, and 45) for a period of 0.1 s (Figure S14) indicate that the temporal response
rates and curve shapes of these signals are identical with respect
to each other, implying that all the channel signals originate from
the same source. We therefore hypothesize that these weak signals
are due to the normal transmembrane ionic flux and each signal wavelength
(FWHM) corresponds to the rise and fall rates of ion flux during channel
opening and closing. Fast Fourier transform (FFT) of the data from
channel 175 revealed a high level of periodicity in these signals
with a characteristic frequency of 27.8 Hz (36 × 10–3 s) (Figure S15). If we assume that each
adjacent signal corresponds to an open and closed state, our data
would imply that, at any given time, HeLa ion channels either stay
opened and closed for a duration of 36 × 10–3 s.
Figure 4
MEG detection of magnetic fields from HeLa cells in culture. (a)
Typical data for 1 × 106 cells detected by channels
3, 21, 35, 45, and 175. (b) MEG data from a flask containing only
culture but no cells.
MEG detection of magnetic fields from HeLa cells in culture. (a)
Typical data for 1 × 106 cells detected by channels
3, 21, 35, 45, and 175. (b) MEG data from a flask containing only
culture but no cells.Two series of control
experiments were carried out to establish
the system noise floor. In the first experiment, we measured the magnetic
field from a flask containing only culture but no cells (Figure b and Figure S16). No detectable signals were observed.
In the second experiment, we measured magnetic fields from HeLa cells
dispersed in culture (Figure S17). Once
again, we did not measure any detectable magnetic signals. This is
consistent with our expectation in that, in the case of cell dispersions
in the culture, there would be no net magnetic field due to symmetry
considerations. This control experiment also eliminates any concern
of signal contribution/contamination from any unknown “cell-related
debris” in the culture.
Nondifferentiated
H9c2(2-1) Rat Cardiac
Myoblasts versus Differentiated Myocytes
The morphology of
H9c2(2-1) cells were characterized before and after differentiation[32] (Figure S18). MEG
signals from H9c2(2-1) rat cardiac myoblasts and differentiated myocytes
were measured in a manner similar to that of the HeLa cells (Figure S19). Magnetic signals emanating from
nondifferentiated cells (Figure S19a) were
similar to those of the HeLa cells, whereas differentiated cells exhibited
clusters of signals (Figure S19b,c). FFT
of the data showed a high degree of periodicity for both cell lines
(Figure S19d–f). Nondifferentiated
cell lines had a characteristic magnetic signature of 27.8 Hz, similar
to that of the HeLa cells. In general, the differentiated cell lines
consistently showed a cluster of higher-frequency signals with a characteristic
frequency of around 220 Hz (4.54 × 10–3 s).
If we assume that our earlier hypothesis for the HeLa cells is applicable
to other cell types, then we would conclude that the ion channels
in the nondifferentiated cell lines exhibited similar behavior and
stay opened or closed for the same duration of time of 36 × 10–3 s. The differentiated cell lines, however, stayed
open or closed for a much shorter duration of time, namely, 4.54 ×
10–3 s. The delineation of different frequencies
within the cluster of signals in the differentiated cell lines is
likely due to different specific ion channels.
Conclusions
We report a noninvasive method to measure
the net ionic transport
through an electric field at a polarized membrane using the MEG system.
Addition of a nonlethal dose of ionomycin to HeLa cells or capsaicin
to TRPV1-expressing HEK293 cells resulted in a sudden change in the
magnetic signal, which was consistent with confocal fluorescence experiments.
Our experimental results with the TRPV1 antagonist ruthenium red,
which blocks the TRPV1 ion channels, showed that the magnetic signals
detected by the MEG system are strongly correlated with the cellular
ionic flux. It is interesting to observe that the nondifferentiated
H9c2(2-1) rat cardiac myoblasts and the differentiated myocytes showed
a significant difference in their magnetic signatures. The characteristic
frequency of 27.8 Hz for the myoblasts was found to be identical to
that of HeLa cells, which is a cancer cell line. The differentiated
cell lines showed a cluster of higher characteristic frequencies of
around 220 Hz. It is speculated that each of the three frequencies
in the cluster is attributable to a specific ionic flux. One could
then infer that the ion channel-gating dynamics of nondifferentiated
cell lines are nondistinct, which is a key factor affecting cellular
homeostasis. Detailed investigations are still needed to correlate
the magnetic signals to a flux of specific ions, such as Na+, K+, and Ca2+. This would further enable correlations
to specific biological processes related to the cell state, type,
and differentiation stage. The resulting insights into the cellular
processes at the membranes would potentially lead to a noninvasive
method for early-stage cancer detection.
Experimental
Section
Cell Culture
HeLa cells were cultured
in RPMI 1640 media with 10% FBS and 1% penicillin/streptomycin in
cell-culture flasks at 37 °C and 5% CO2. HEK293 cells
stably expressing TRPV1 were created by transfection with a pCMV6-NEO-TRPV1
plasmid (Origene) using a TrueFect reagent (United BioSystems) and
G418 (600 μg/mL) for selection. The cells were cultured in DMEM
with 10% FBS and 1% PEN-STREP. The antibiotic G418 (300 μg/mL)
was used for maintaining the stable expression of TRPV1. TRPV1 expression
was verified by western blot and immunofluorescence staining using
a TRPV1 antibody[33] (Figure S5). H9c2(2-1) (ATCC CRL1446) cells were cultured in
RPMI 1640 with 10% FBS and 1% penicillin/streptomycin in cell-culture
flasks at 37 °C and 5% CO2 at no greater than 50%
confluence. To initiate differentiation, cells were allowed to grow
to confluency and maintained in 2% FBS supplemented media for four
days.[32]
Calcium
Dye Loading
Calcium dye (50
μg, Fluo-4 AM, Life Technologies) was dissolved in DMSO (50
μL). Both Fluo-4 AM and Pluronic F-127 (Molecular Probes) were
added to HBSS resulting in a 0.002% final concentration of each. The
mixture was sonicated for 5 min, loaded onto cells growing in a 35
mm glass bottom dish, and then de-esterified for 30 min in a humidified
CO2 incubator (37 °C, 5% CO2).
Confocal Microscopy
Live cell imaging
was carried out on an Olympus FluoView FV1000MPE confocal microscope.
Excitation using an argon ion laser was set at 488 nm and emitted
light was reflected through a 500–600 nm filter from a dichroic
mirror. Data capture and extraction was carried out with FluoView
10-ASW version 4.0 (Olympus), Image J-Fiji,[34] and DeltaGraph (Red Rock Software). Stock solutions of ionomycin
and capsaicin were prepared in DMSO, and DMSO accounted for no more
than 0.2% of the final concentration of these reagents. To initiate
the experiments, ionomycin (2 μM final concentration) or capsaicin
(10 μM final concentration) was added to the culture dish from
a pipette.
Evaluation of Ionomycin-Dependent
Cell Death
HeLa cells grown in culture were treated with
ionomycin solutions
(1, 2, and 5 μM final concentrations) for a period of 5, 10,
or 30 min. After the designated time period, the cell suspension was
treated with trypan blue (final concentration of 0.4%) and immediately
loaded into a hemocytometer. Dead cells are stained blue, and live
cells are unstained. The cells were counted manually using a handheld
tally counter.
Evaluation of Capsaicin-Dependent
Cell Death
HEK293 cells stably expressing TRPV1 grown in
culture were treated
with DMSO (0.2%) or capsaicin solutions (1.25, 2.5, 5, and 10 μM
final concentrations) for a period of 30 min. After the designated
time period, the cell suspension was treated with CellTiter Blue (Promega),
and the fluorescence was measured after 1.5 h using 560/590 nm filters
on a BioTek Synergy microplate reader and compared to an untreated
control.
MEG Data Acquisition and Analysis
A T-25 culture flask containing plated HeLa/HEK293, or H9c2(2-1)
cells was placed inside the MEG chamber in a pre-determined position
on the base of the helmet. MEG data was collected in the continuous
mode with a 208-channel axial gradiometer system (Kanazawa Institute
of Technology, Kanazawa, Japan) using MEG 160 software for data collection
and post-processing. This MEG software is produced jointly by Yokogawa
Electric Corp., Eagle Technology Corp., and the Kanazawa Institute
of Technology (KIT). A low pass of 200 Hz, high pass of 0.1 Hz, and
sampling rate of 3000 Hz for data recording were used. Data from the
MEG system was acquired by a DAQ system assembled by Eagle Technology.
For MEG data post-processing, offline noise reduction with a specifically
designed algorithm, that is, the continuously adjusted least-squares
method (CALM), using three reference magnetometers mounted outside
the MEG head was used.[35] The CALM noise
reduction method eliminates any detected covariance between the measured
data in the MEG sensors with respect to the reference sensors. This
technique was specifically designed to eliminate low-frequency (<10
Hz) noise as well as large extramural unintentional magnetic noise
to disrupt MEG sensors. The selected data plotting and analysis was
done using Origin Pro 2016 software.
MEG Experiments
for Remote Addition of Ionomycin
and Capsaicin
The experimental set up was designed such that
we could add the optimum dosage of ionomycin or capsaicin dissolved
in culture to the culture flask remotely. We used a fine plastic tubing,
one end of it being attached to the end cap of the culture flask.
The other end of the tubing located outside the MEG room was attached
to a plastic bulb, which contained the ionomycin or the capsaicin
solution. This arrangement enabled undisturbed measurement of the
baseline signal from the cells in the flask and after the addition
of ionomycin or capsaicin by applying pressure to the liquid inside
the tubing through a plastic bulb attached to the other end located
outside the MEG room. The complete addition of ionomycin or capsaicin
took approximately 1–2 s.
Noise Floor Characterization
During
the first phase of our experiments,
we carried out a detailed study of the noise floor of the MEG system
and the contiguous environment. We worked closely with other active
NYUAD faculty from the neurobiology department who relied on the MEG
system for their core research and the representatives of the company
that built the MEG system. The purpose of these conversations was
to be educated and trained on the capabilities/limits of the MEG system
and adapt the experimental protocols associated with “good”
data acquisition practices, identifying potential sources of noise
that are specific to the MEG system and their characteristic signatures.
Overall, the MEG system was set up such that the noise floor is comparable
to MEG systems in other global research facilities.Our standard experimental procedure
involved the following: all (reference) control experiments for a
specific set of studies and general background noise measurements
were repeated during each experimental session. We measured the noise
floor before and after each experiment and many times between experiments
as well. For (reference) control experiments, we did a minimum of
two repeats and sometimes up to four repeats in each session.As described in the manuscript,
we
only considered signals above a significant threshold that were repeatable within each experimental
session and in other experiments carried out on different days.For each experimental
set, we usually
measured signals from three to four cell cultures per session and
collected two to five sets of data for each cell culture.
Reference Controls
Neat cell
cultures: As described in
the manuscript, the control experiments for the “neat”
adherent cell culture measurements involved the cell-culture flask
prepared in the same manner as with the adherent cells but without
the cells. The data acquisition procedure was identical to that with
the cells.Ionomycin
experiments: For the ionomycin
experiment, the control experiment involved a procedure that was identical
to that of the main experiment in which ionomycin in culture media
(2 μM final concentration) was added to the cells using plastic
tubing and pneumatic pressure, except that no ionomycin was present
in the culture for the control experiment. This was repeated during
the experimental session on the same day, and all the experiments
were repeated again several times on different days.Capsaicin experiments: For the capsaicin
experiment, the control experiment involved a procedure that was identical
to that of the main experiment in which 10 μM capsaicin in culture
media was added to the adherent HEK cells using a plastic tubing and
pneumatic pressure, except that no capsaicin was present in the culture
media for the control experiment. This was repeated during the experimental
session on the same day, and all the experiments were repeated again
several times on different days.Signal processing and statistical
analysis: We did extensive statistical analysis of the data for nondifferentiated
cells. The time domain magnetic signals from select channels were
transformed into the frequency domain using the FFT algorithm in MatLab
and Origin Pro 2016. FFT results obtained from nine individual sensors
per experiment were selected for statistical testing. We calculated
the standard error of the mean (SEM) for an average of five independent
experiments using Prism 6.0 software (GraphPad Software, Inc. La Jolla,
CA, U.S.A.). Statistical significance between or among experiments
was assessed by one-way analysis of variance (ANOVA) followed by Tukey’s
or Dunnett’s post hoc test. A value of p <
0.0001 was considered to be statistically significant in our experiments.Data Availability: All
data generated
or analyzed during this study are included in this published article
and in the Supporting Information.
Authors: Malte Schmick; Nachiket Vartak; Björn Papke; Marija Kovacevic; Dina C Truxius; Lisaweta Rossmannek; Philippe I H Bastiaens Journal: Cell Date: 2014-04-10 Impact factor: 41.582
Authors: Johannes Schindelin; Ignacio Arganda-Carreras; Erwin Frise; Verena Kaynig; Mark Longair; Tobias Pietzsch; Stephan Preibisch; Curtis Rueden; Stephan Saalfeld; Benjamin Schmid; Jean-Yves Tinevez; Daniel James White; Volker Hartenstein; Kevin Eliceiri; Pavel Tomancak; Albert Cardona Journal: Nat Methods Date: 2012-06-28 Impact factor: 28.547
Authors: John F Barry; Matthew J Turner; Jennifer M Schloss; David R Glenn; Yuyu Song; Mikhail D Lukin; Hongkun Park; Ronald L Walsworth Journal: Proc Natl Acad Sci U S A Date: 2016-11-22 Impact factor: 11.205
Authors: Ana F Branco; Susana P Pereira; Susana Gonzalez; Oleg Gusev; Albert A Rizvanov; Paulo J Oliveira Journal: PLoS One Date: 2015-06-29 Impact factor: 3.240