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Wireless electrical-molecular quantum signalling for cancer cell
apoptosis
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  * Open Access
  * Published: 14 September 2023

Wireless electrical-molecular quantum signalling for cancer cell
apoptosis

  * Akhil Jain  ORCID: orcid.org/0000-0003-2019-2030^1,
  * Jonathan Gosling^2,
  * Shaochuang Liu  ORCID: orcid.org/0000-0002-1010-2321^3,
  * Haowei Wang^3,
  * Eloise M. Stone^4,
  * Sajib Chakraborty  ORCID: orcid.org/0000-0002-8900-503X^5,
  * Padma-Sheela Jayaraman^6,
  * Stuart Smith  ORCID: orcid.org/0000-0002-4556-2707^7,8,
  * David B. Amabilino  ORCID: orcid.org/0000-0003-1674-8462^9,10,
  * Mark Fromhold^11,
  * Yi-Tao Long  ORCID: orcid.org/0000-0003-2571-7457^3,
  * Lluisa Perez-Garcia  ORCID: orcid.org/0000-0003-2031-4405^4,12,13
    ,
  * Lyudmila Turyanska  ORCID: orcid.org/0000-0002-9552-6501^2,
  * Ruman Rahman  ORCID: orcid.org/0000-0002-6541-9983^7 &
  * ...
  * Frankie J. Rawson  ORCID: orcid.org/0000-0002-4872-8928^1 

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Nature Nanotechnology (2023)Cite this article

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Subjects

  * Bionanoelectronics
  * Electrochemistry
  * Nanoparticles

Abstract

Quantum biological tunnelling for electron transfer is involved in
controlling essential functions for life such as cellular respiration
and homoeostasis. Understanding and controlling the quantum effects
in biology has the potential to modulate biological functions. Here
we merge wireless nano-electrochemical tools with cancer cells for
control over electron transfer to trigger cancer cell death. Gold
bipolar nanoelectrodes functionalized with redox-active cytochrome c
and a redox mediator zinc porphyrin are developed as
electric-field-stimulating bio-actuators, termed bio-nanoantennae. We
show that a remote electrical input regulates electron transport
between these redox molecules, which results in quantum biological
tunnelling for electron transfer to trigger apoptosis in
patient-derived cancer cells in a selective manner. Transcriptomics
data show that the electric-field-induced bio-nanoantenna targets the
cancer cells in a unique manner, representing electrically induced
control of molecular signalling. The work shows the potential of
quantum-based medical diagnostics and treatments.

Main

We are entering an era where it has been realized that
bioelectricity, defined as the electrical language of cells, programs
cell function^1,2. The cell is increasingly viewed as a mass of
bioelectrical interconnected circuits that use an endogenous current
generated by electron transfer processes to communicate with each
other to maintain homoeostasis^3. These electron transfer processes
in biology, when governed by quantum mechanical effects such as
electron tunnelling, are classified as quantum biological tunnelling
for electron transfer (QBET). For instance, one of the most
well-known electron transfer pathways is photosynthesis, the
mechanism of which was one of the first to be linked to quantum
mechanical effects^4. Cytochrome c (Cyt c) is known for its vital
role in the mitochondrial electron transfer chains that are governed
by the redox activity (Fe^2+ to Fe^3+, and vice versa) of the haem
ring present in its structure^5. These redox processes in Cyt c are
also known to occur via electron tunnelling^6,7,8 and are regulated
by the Warburg effect, which is underpinned by bioelectrical faradaic
currents^9,10. Furthermore, these processes are crucial for the
translocation of Cyt c to the cytosol^11 and for modulating its
binding conformation^12 for interaction with apoptotic protease
activating factor 1 (APAF-1)^13. Although quantum biology is still in
its infancy, we envisage future interdisciplinary developments, which
will be reinforced by the understanding and modulation of these
quantum mechanical processes^14. This highlights the need for
technology to electrically interact with redox molecules such as Cyt
c whose functions are supported by quantum mechanical processes.

Remotely induced electrical-molecular communication (electrical input
causing a redox change in a targeted molecule, inducing an alteration
in cell behaviour) inside cells opens the possibility of creating
disruptive technologies, including the development of quantum
medicines for cancer treatments^15. However, on-demand targeted
electrical-molecular communication within cells has yet to be
realized. This is a result of the lack of technological innovation
that is suitable for interfacing with cells in a medium at a spatial/
temporal level in which native biological interaction occurs. The aim
of this study is to pioneer solutions to these challenges.

Gold nanoparticles (GNPs) and carbon nanotubes can behave as bipolar
nanoelectrodes^16,17 within cells when external electric fields (EFs)
are applied. The bipolar nanoelectrodes become polarized when an EF
is applied, leading to a voltage gradient across the particle^18.
With a sufficiently large potential difference between the poles of
the electrode, the thermodynamic driving force can cause
electrochemically induced redox reactions to occur by virtue of
bipolar electrochemistry (also known as wireless electrochemistry)^19
,20. It was thought that nanoscale wireless electrochemistry was not
possible in the presence of cells even at very high applied voltages^
21,22. Importantly, most recently, bipolar electrodes in series lead
to a dramatic drop in cell impedance^23, which may allow electrical
inputs to be used without inducing cell damage. Redox reactions at
carbon nanotube porins, acting as bipolar nanoelectrodes, can occur
at unprecedentedly low applied voltages in cells without inducing
direct cell death^24. We, therefore, designed an approach that uses
bifunctionalized bipolar nanoelectrodes with attached redox-active
molecules, which we term bio-nanoantennae (they are capable of
receiving a remotely applied external EF input and converting this to
bio-signalling events). Furthermore, alternating current (a.c.) EFs
are reported to notably lower the impedance of the cell membrane at
higher frequencies to penetrate the cytoplasm^25,26, which together
with the enhanced voltage gradient observed at the nanoscale would
facilitate bipolar electrochemistry^27. Therefore, we hypothesized
that these bio-nanoantennae in combination with applied a.c. EFs
could be used to modulate electron transfer, which then could be
converted into molecular actuation via targeting a specific metabolic
pathway (Fig. 1).

Fig. 1: Illustration of wireless electrical-molecular quantum
signalling mediated by a.c.-EF-responsive bio-nanoantennae to induce
cell death.
figure 1

a, Bio-nanoantennae (GNP100@r.Cyt c@Z) were synthesized by covalently
conjugating r.Cyt c and Z to carboxylic GNP100s using N-
(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC)/N
-hydroxysuccinimide (NHS) chemistry. b, Primary patient-derived GBM
cells, namely, GIN (derived from the GBM infiltrative margin) and GCE
(derived from the GBM proliferative core) cells, were incubated with
bio-nanoantennae to enable their uptake. These GBM cells were
electrically stimulated with a.c. EFs of 3 MHz at 0.65 V cm^-1. V,
voltage; ES, electrical stimulation; Ox, oxidized; Red, reduced. c,
These applied a.c. EFs caused the intracellular wireless
electrochemistry to occur at the bio-nanoantennae surface to induce
caspase-3/7-mediated apoptosis of GBM cells. We examined the
electrical-molecular signalling by connecting gene regulation with
the a.c.-EF-mediated cell death in GBM cells. d, The a.c. EFs were
applied to induce wireless electrochemistry at the surface of
bio-nanoantennae to wirelessly switch the redox state of Cyt c
(reduced to oxidized), ex situ, suggesting QBET in the proposed
system. e^-, electron. e, Diagram representing the a.c.-EF-responsive
bio-nanoantennae for electrical-molecular quantum signalling with GBM
cells. Protein Data Bank (PDB) structural entries were used to
represent Cyt c (PDB 1HRC; refs. ^39,40), apoptosome (PDB 3J2T; refs.
^41,42) and caspase 3/7 (PDB 3GJQ; refs. ^43,44). Chemspider
structure no. 19989078 (ref. ^45) was used to represent Z. Structure
illustrations by Leonora Martinez Nunez. a,d, Z from ref. ^45; a,c,d,
Cyt c from refs. ^39^,^40; c, Apoptosome from refs. ^41^,^42; Caspase
3/7 from refs. ^43^,^44.

Full size image

The strategy to fulfil the development of a quantum
electrical-molecular communication tool was multipronged and inspired
by the observation that electron transfer in Cyt c is mediated
through QBET^8. Therefore, we functionalized GNPs with an
electron-donor-reduced Cyt c (r.Cyt c) and a redox mediator, zinc
porphyrin (zinc 5-(4-aminophenyl)-10,15,20-(tri-4-sulfonatophenyl)
porphyrin triammonium; Z). When these particles are exposed to an
electrical input, a voltage gradient is induced at the surface; these
are therefore described as electronic bio-nanoantennae (Fig. 1a). We
show that the electrical input confers specific signalling in cells
via the bio-nanoantennae to induce apoptosis-mediated glioblastoma
(GBM) cell death. The transcriptomic analysis enabled elucidation of
the biochemical signalling when using the electrical-molecular
communication tool (Fig. 1b,c). We show that on the application of a
resonant electrical input (a.c. EF, 3 MHz, 0.65 V cm^-1), wireless
electrochemistry is induced at the bio-nanoantennae surface and
switches the redox state of the Cyt c. We propose that the QBET
phenomenon and resonant electron transfer between the Cyt c and Z
facilitate cellular apoptosis (Fig. 1d). The data suggest
a.c.-EF-induced molecular actuation via bio-nanoantennae in the
treatment of a disease, which is a quantum functional medicine tool
(Fig. 1e). This could lead to exciting opportunities for the
development of quantum nanomedicines and cancer treatments and
provide a state-of-the-art means of modulating cell metabolism.

Design of bio-nanoantennae for actuating cell death

To electrically communicate with cells at a level equivalent to that
underpinning molecular biochemistry, we initially used carboxylic PEG
modified 100 nm spherical GNPs (GNP100s; PEG, polyethylene glycol) as
bipolar nanoelectrodes. These GNP100s can sense an EF applied
extracellularly^16,23. This occurs when they are functionalized with
redox-active biomolecules to yield a bio-nanoantenna that can enable
surface redox reactions (via wireless electrochemistry) to actuate a
cell-specific signalling pathway. Apoptosis is mediated (in part) by
Cyt c bioelectrochemistry in which the oxidized state (Fe^3+)
facilitates apoptosis-mediated cell death^12. Therefore, we
conjugated GNP100 with an electrical donor, that is, r.Cyt c
(inactive, Fe^2+), and a redox mediator Z using carbodiimide coupling
chemistry to form bio-nanoantennae (GNP100@r.Cyt c@Z). On application
of a resonant a.c. EF, the bio-nanoantennae would polarize, providing
the thermodynamic driving force for nanoscale wireless
electrochemistry to occur and switch the redox state of r.Cyt c from
Fe^2+ to Fe^3+ (oxidized Cyt c or o.Cyt c)^28.

The successful bifunctionalization of carboxylic PEG modified GNP100s
(2 kDa PEG) with r.Cyt c and Z is evident from transmission electron
microscopy (TEM) images (Fig. 2a), dynamic light scattering
(Supplementary Fig. 1) and zeta potential (Supplementary Fig. 2) and
UV-visible (Fig. 2b,c and Supplementary Fig. 3a-e) characterizations
of GNP100@r.Cyt c@Z. A quantification of redox molecules bound to
each nanoparticle is presented in Supplementary Tables 1-4. Cyclic
voltammetry was carried out to study the redox behaviour of r.Cyt c
and Z on a bifunctionalized system (Fig. 2d and Supplementary Fig.
4a-c). The heterogeneous electron transfer rate coefficient (k^0) of
Cyt c for GNP100@r.Cyt c was calculated to be 9.6 x 10^-3 cm s^-1
(Supplementary Table 5), while that for GNP100@r.Cyt c@Z was
3.75 x 10^-3 cm s^-1 (Supplementary Fig. 5a-f), suggesting a slight
decrease in the electron transfer rate of Cyt c in a bifunctionalized
system. A detailed discussion is in Supplementary Note 1.

Fig. 2: Physico-chemical and electro-analytical characterization of
bio-nanoantennae and their interaction with patient-derived GBM
cells.
figure 2

a, TEM image of bio-nanoantennae (GNP100@r.Cyt c@Z) prepared by
coupling r.Cyt c and Z to GNP100s. The inset is a high-resolution TEM
image of 100 nm bio-nanoantennae. The TEM analysis was done on three
different samples of bio-nanoantennae that were synthesized over the
course of three individual experiments. b, UV-visible absorption
spectra of bio-nanoantennae dispersed in phosphate buffer saline
(PBS) before ES. c, Zoomed-in UV-visible absorption spectra from 360
to 460 nm showing surface functionalization with r.Cyt c
(GNP100@r.Cyt c), Z (GNP100@Z) and both r.Cyt c and Z (GNP100@r.Cyt c
@Z). d, Cyclic voltammetry scan rate studies to analyze the redox
properties of GNP100@r.Cyt c@Z. Redox potentials were measured using
an ITO working electrode, platinum wire counter electrode and Ag/AgCl
reference electrode with samples (25 ug mL^-1) dispersed in 10 mM
PBS, scanned from +1.2 V to -0.25 V. ITO, indium tin oxide. e, ICP-MS
analysis to determine the association of bio-nanoantennae with
different patient-derived GBM cells and cortical astrocytes; the data
are expressed as the number of GNPs per cell. Results are expressed
as +-s.d. of the mean obtained from a triplicate experiment and
repeated three times. The data were considered significant if *P
 <= 0.05, **P <= 0.01, ***P <= 0.001 and ***P <= 0.0001 versus GNP100,
obtained using two-way analysis of variance (ANOVA) with a Tukey
post-test. NS, not significant.

Source data

Full size image

To explore the potential of bio-nanoantennae on the a.c.-EF-mediated
redox switching of Cyt c, first we investigated the association and
uptake of bio-nanoantennae on four types of preclinical GBM cells,
isolated from two GBM patients, glioma invasive margin (GIN 28 and
GIN 31) and glioma contrast-enhanced core (GCE 28 and GCE 31), which
echo similar characteristics to different regions of GBM tumours^29,
and a commercial GBM cancer cell line, U251. Human-derived cortical
astrocytes were also included as a control for non-tumorigenic cells.
A three-dimensional analysis of z-stack confocal microscopy images
(Supplementary Fig. 6) confirmed that the bio-nanoantennae were
internalized by all types of cells after 8 hours of incubation, and
the number per cell was quantified using inductively coupled plasma
mass spectrometry (ICP-MS; Fig. 2e). PrestoBlue assay data revealed
that the bio-nanoantennae are biocompatible up to a tested range of
100 ug mL^-1 (Supplementary Fig. 7).

EF responsive bio-nanoantennae induce apoptosis in GBM

To examine the electrical input that can be sensed by intracellular
bio-nanoantennae for inducing wireless electrochemistry, we optimized
the voltage and frequency (Supplementary Fig. 8) by assessing the
change in metabolic activity of GIN 31 cells as the preliminary
read-out of Cyt c redox switching. The maximum effect on the
metabolic activity was observed at 3 MHz, at an applied potential of
1 V cm^-1 or 0.65 V cm^-1 (no significant difference between
0.65 V cm^-1 and 1 V cm^-1; P value = 0.23), with significant
differences between the tested controls (GNP100, GNP100@r.Cyt c and
GNP100@Z) and the bifunctionalized bio-nanoantennae (GNP100@r.Cyt c
@Z). Importantly, the observed decrease in metabolic activity of
GNP100@r.Cyt c@Z-treated cells was significantly higher than that
following 24 h application of in vitro tumour-treating fields that
have been approved by the US Food and Drug Administration^30,31. We
ascribe this decrease in metabolic activity to the
electrical-molecular communication via redox switching of r.Cyt c to
o.Cyt c, thus inducing cell stress. To eliminate any potential effect
of the applied 1 V on water electrolysis (1.23 V versus normal
hydrogen electrode), we chose 0.65 V cm^-1 for further studies. The
response of the cells to the treatment with bio-nanoantennae
(GNP100@r.Cyt c@Z) was comparable in different patient-derived GIN
and GCE cells, as well as in the U251 cell line (Fig. 3a,b and
Supplementary Fig. 9), with a reported, ~50% decrease in metabolic
activity achieved after 12 h compared to ~20% decrease after 2 h of
a.c. EF stimulation (Supplementary Fig. 10). This decrease in
metabolic activity was significantly higher compared to all other
experimental controls (P values obtained from the statistical
analysis are listed in Supplementary Table 6). By contrast, a weaker
effect (~20% decrease in metabolic activity) was observed in cortical
astrocytes (Fig. 3c; P value = 0.011), which was found to be
significantly different from the control (no treatment with either
bio-nanoantennae or a.c. EFs). A brief discussion on the response of
other normal cells (liver and cerebellar astrocyte; Supplementary
Fig. 11a,b) to the treatment can be found in Supplementary Note 2.
Thus, based on the obtained data, we conclude that the change in
metabolic activity depends on the duration of treatment and cell
type.

Fig. 3: Wireless electrical-molecular communication mediated by
a.c.-EF-responsive bio-nanoantennae induces caspase-3/7-mediated
apoptosis in preclinical GBM cells.
figure 3

a-c, Metabolic activity of GIN/GCE 31, GIN/GCE 28 and cortical
astrocytes was analyzed using a PrestoBlue HS assay. GIN cells, GCE
cells and human cortical astrocytes were treated with GNP100@r.Cyt c
@Z for 8 h followed by a.c. EF stimulation (3 MHz, 0.65 V cm^-1) for
12 h. The control is no treatment with either bio-nanoantennae or
a.c. EFs. Error bars represent mean +- standard error of mean (s.e.m.)
obtained from triplicate experiments repeated three times.
Statistical analysis was performed by applying a two-way ANOVA with a
Tukey's post-test. d-g, Representative samples from flow cytometric
analysis of cells stained with CellEvent Caspase-3/7 Green to detect
caspase 3/7 apoptotic activity and Zombie NIR fixable dye to detect
the dead cell population. The quadrants in the figure represents the
following: A-D-, no cell death either due to caspase 3/7 apoptosis or
necrosis; A+D-, caspase 3/7 positive apoptotic cells; A+D+,
non-viable/dead cells caused by apoptosis; and A-D+, necrotic cells.
The gating strategy is shown in Supplementary Fig. 14. FITC,
fluorescein isothiocyanate and NIR, near infra-red are filters. h,
High-magnification confocal microscopy images to demonstrate caspase
3/7 activation immediately after the treatment with a.c. EFs (3 MHz,
0.65 V cm^-1) for 12 h in the presence of bio-nanoantennae. Cells
were fixed with paraformaldehyde followed by counterstaining with a
caspase 3/7 detection kit (green), Cytopainter actin phalloidin
(Texas Red 591, in red) and Hoechst nuclear stain (blue). Scale bars,
20 um. To confirm caspase 3/7 activation, at least five confocal
images (each with nearly 30 cells) were taken at x10. High-resolution
(x63) images show both morphology and caspase 3/7 activation (in
green). The -EF and +EF indicate before and after the EF treatment. i
, Confocal microscopy images to demonstrate the cytoplasmic
localization of GNP100@r.Cyt c@Z immediately after the treatment with
a.c. EFs (3 MHz, 0.65 V cm^-1) for 12 h in the presence of
bio-nanoantennae. Cells were stained with late endosome dye (green)
and imaged using a Leica confocal microscope with green fluorescent
protein, GFP (late endosomes) and Alexa 633 (GNP100@r.Cyt c@Z) filter
settings. Scale bars, 100 um. White arrows represent the endosomal
escape and localization of bio-nanoantennae, at least 60 cells were
analysed.

Source data

Full size image

The alteration in metabolic activity in cells treated with
GNP100@r.Cyt c@Z plus a.c. EFs (3 MHz at 0.65 V cm^-1 for 12 hours)
is correlated with increased cell death, as clearly evidenced by the
results of a live-dead assay (Supplementary Figs. 12 and 13). The
mechanism of cell death was probed by flow cytometry (Fig. 3d-g and
Supplementary Figs. 14-16) and confocal microscopy (Fig. 3h and
Supplementary Fig. 17), where the induced caspase 3/7 activity was
observed in GIN/GCE cells treated with GNP100@r.Cyt c@Z followed by
electrical stimulation (ES), indicative of apoptosis. This could be
attributed to the increased affinity of activated Cyt c (Fe^3+) on
bio-nanoantennae with APAF-1 (ref. ^12). Confocal microscopy revealed
that bio-nanoantennae, upon ES, escape the endo/lysosomal degradation
to localize in the cytosol (Fig. 3i and Supplementary Fig. 18).
Further studies are required to investigate the precise mechanism. We
note that no reactive oxygen species and temperature changes were
observed (Supplementary Figs. 19 and 20). Therefore, we successfully
conducted the ES of GBM cells and demonstrated the wireless
electrochemistry-mediated redox switching and activation of Cyt c on
the surface of GNP100@r.Cyt c@Z, leading to the apoptosis of GBM
cells.

To further understand this electrical-molecular signalling, we
performed transcriptomic analysis on a sample of GBM cells and
healthy cortical astrocytes (Fig. 4 and Supplementary Figs. 21 and 22
) to explore the effect of the bioelectronic communication tool on
gene expression and regulation. Hierarchical clustering analysis
showed a differential expression of genes related to apoptosis,
cancer proliferation and angiogenesis, and tumour suppression (Fig. 4
). This change in differentially expressed genes was highest for GIN/
GCE 31 cells treated with GNP100@r.Cyt c@Z and followed by ES
compared to untreated cells and other experimental controls.
Interestingly, we observed minimal changes in the gene regulation for
astrocytes, which suggests that the astrocytic transcriptomic
landscape remains largely unperturbed upon the treatment. By
contrast, an important deviation in the transcriptome has been
monitored for GBM cell lines, implying that the treatment modulates
signalling pathways that are specific only to GBM. To explain this
effect, we conducted gene-set enrichment analysis of gene ontology
biological processes (Extended Data Fig. 1 and Supplementary Figs. 23
and 24). A detailed discussion on transcriptomics data and gene
ontology biological process analysis is in Supplementary Note 3.
Collectively, the data obtained from Figs. 3-4 and Extended Data Fig.
1 imply that GNP100@r.Cyt c@Z treatment followed by ES leads to
reduced proliferation and apoptosis induction in patient-derived GBM
cells. Overall, the in vitro results indicate successful
communication with biology at a molecular scale using electricity.
Importantly, this approach enables selective actuation of cancer cell
behaviour compared to normal healthy cells (astrocytes and liver bile
duct cells).

Fig. 4: Transcriptomic analysis to connect bio-nanoantennae-mediated
wireless electrical -molecular communication with gene expression and
regulation.
figure 4

Heat map demonstrating hierarchical clustering of top 35 genes that
were regulated after the treatment with GNP100@r.Cyt c@Z for 8 h
followed by a.c. EF stimulation (3 MHz, 0.65 V cm^-1) for 2 h. A
variance-stabilized transformation was performed on the raw count
matrix, and 35 genes with the highest variance across samples were
selected for hierarchical clustering. Each row represents one gene,
and each column represents one sample. The colour represents the
difference of the count value to the row mean. GIN 31 and GCE 31,
which showed the maximum response to the treatment with GNP100@r.Cyt
c@Z and a.c. EFs, were chosen. As a control to cancer cells, healthy
cortical astrocytes were used. Immediately after the treatment, cells
were washed and centrifuged to obtain a pellet, which was snap-frozen
in liquid nitrogen and shipped (in dry ice) to Qiagen in Germany for
RNA sequencing. The treatment codes are as follow: EF-, control (no
treatment with either bio-nanoantennae or a.c. EFs); EF+, cells
treated with a.c. EFs; NP1 EF+, cells treated with GNP100@r.Cyt c;
and NP2 EF+, cells treated with GNP100@r.Cyt c@Z; treatment was for
8 h followed by 2 h with the a.c. EF.

Source data

Full size image

Nanoscale wireless electrochemistry and in vitro QBET

The electrical-molecular communication via wireless electrochemistry
induced at bio-nanoantennae was probed by circular dichroism analysis
(Fig. 5a and Supplementary Fig. 25) and UV-visible absorption
spectroscopy (Fig. 5b,c and Supplementary Figs. 26 and 27). There was
no significant change in the hydrodynamic diameter h[d] and zeta
potential z after ES with an a.c. EF (Supplementary Figs. 28 and 29).
A detailed discussion on the data demonstrating that the
bio-nanoantennae act as bipolar electrodes and can modulate the redox
state of the Cyt c under application of the EF is in Supplementary
Note 4.

Fig. 5: Nanoscale wireless electrochemistry and in vitro electron
tunnelling via bio-nanoantennae for inducing cell death in GBM cells.
figure 5

a, The effect of a.c. EFs on the conformation of redox moieties:
circular dichroism spectra in the Soret region to emphasize the
redox-mediated change in haem moieties of free native o.Cyt c, r.Cyt
c and bifunctionalized GNP bio-nanoantennae in 10 mM PBS (pH 7.4).th,
molar ellipticity. All samples with identical concentrations
(25 ug mL^-1) were used for spectrum acquisition. Three spectra of
each sample were collected and averaged. Insulated, coated steel
electrodes were used as a control to demonstrate the occurrence of
wireless electrochemistry at the nanoscale. b,c, UV-visible spectra
of bio-nanoantennae after stimulation with a.c. EFs of 3 MHz,
0.65 V cm^-1 indicating a blueshift in the absorption maxima in
GNP100@r.Cyt c@Z, indicating the redox switching of Cyt c (from r.Cyt
c to o.Cyt c). d-f, Metabolic activity of GIN 31 cells as a function
of different-sized bio-nanoantennae (20 nm, 50 nm and 100 nm;
GNP20@r.Cyt c@Z, GNP50@r.Cyt c@Z and GNP100@r.Cyt c@Z, respectively)
synthesized using various linker lengths (1, 2, 3.5 and 5 kDa). GIN
31 cells were treated with bifunctionalized bio-nanoantennae for 8 h
followed by a.c. EF stimulation (3 MHz, 0.65 V cm^-1) for 12 h. Error
bars represent +-s.e.m. of the mean obtained from triplicate
experiments repeated three times. Statistical analysis was performed
by applying a two-way ANOVA with a Tukey's post-test. Exact P values
are in Supplementary Table 7.

Source data

Full size image

To facilitate the translation of the technology more broadly,
understanding of the electrically induced mode of electron transfer
is needed. The frequency we used for electrical communication was
3 MHz; considering the electron transfer rate constant of 3.75 x 10^
-3 cm s^-1 calculated from Fig. 2d, the maximum distance the electron
could travel at this frequency is 0.01 nm. Thus, theoretically at
this given frequency, the redox event should not occur. We propose
that the observed activity is enabled by QBET induced from the Cyt c,
as was indicated previously^8. However, this process has not been
controlled using ES.

To gather experimental evidence for QBET in our system, we consider
molecular tunnel junctions, where quantum electron tunnelling can
occur^32,33. We altered the tunnel junction energy by using GNPs with
different sizes (20, 50 and 100 nm) and a PEG linker with different
lengths (1, 2, 3.5 and 5 kDa; Supplementary Figs. 30 and 31).
Toxicity studies of different-sized bio-nanoantennae synthesized
using PEG linkers of various lengths without ES at 25 ug mL^-1 showed
no significant changes in the metabolic activity compared to an
untreated control (Supplementary Fig. 32). The metabolic assays (Fig.
5d-f, Supplementary Table 7 and Supplementary Fig. 33) and viability
studies (Supplementary Figs. 34 and 35) on GIN 31 and GCE 31 cells
with ES (3 MHz and 0.65 V cm^-1) indicated a resonant biological
effect with bio-nanoantennae using the 1 and 2 kDa PEG linkers with
50 nm and 100 nm GNPs. Importantly, this effect is seen only for
cells treated with bio-nanoantennae (GNP@r.Cyt c@Z) following 12 h of
ES. ICP-MS analysis revealed no significant difference in the number
of Z or r.Cyt c per cell when treated with GNP20@r.Cyt c@Z,
GNP50@r.Cyt c@Z or GNP100@r.Cyt c@Z (Supplementary Figs. 36 and 37).
We propose that a QBET is occurring in our system, as evidenced by
the resonance at specific conditions, and is indicative of wave-like
behaviour^8,34. Thus, we suggest that the electron transfer in this
system is an example of electrically stimulated QBET in biology and
consequently an example of facilitating electrical-molecular
communication.

To provide further evidence of the mechanism of electron transfer, we
established a mathematical model. The cell metabolic rate (shown in
Fig. 5d-f) was correlated to the rate of charge transfer from Cyt c,
derived as Equation (1) (full details of the derivation are presented
in the Methods). These values were then plotted as a function of the
barrier junction, altered using the PEG ligands with different length
and different-sized nanoparticles (Fig. 6a,b).

$${r}_{{\mathrm{d}}}=-\frac{{\rm{ln}}\left(M\left(t\right)\right)}{t}
$$
(1)

where r[d] is the rate of donor charging and M(t) is the metabolic
activity at time t.

Fig. 6: Mathematical modelling and plasmon resonance energy transfer
analysis for probing quantum tunnelling in bio-nanoantennae system.
figure 6

a,b, Mathematic modelling to determine the rate of donor charging, r
[d], calculated using the metabolic activity, using equation (1),
compared to the PEG linker length, L, for GNP20@r.Cyt c@Z (a) and
GNP100@r.Cyt c@Z (b) in GIN 31 cell samples. The black lines show the
exponential behaviour expected for quantum tunnelling with an inverse
localization radius a and constant of proportionality b, shown in the
figure legends. Error bars represent +-s.d. of the mean. The x-axis
error bar represents the s.d. of the mean PEG linker length, and the
y-axis error bar represents the s.d. of the mean r[d] (rate of Cyt c
charging), which was obtained from equations (5)-(7) in the Methods.
R^2, coefficient of determination. c, Scattering spectra (I,
intensity) and spectra difference (D) for QBET obtained for
GNP100@r.Cyt c@Z bio-nanoantennae. The quantized peaks were obtained
from the difference of scattering spectra between the samples
functionalized with r.Cyt c and Z using a 2 kDa linker and GNP100.
Solid curves are captured scattering spectra (linked to left axis) of
GNP100@r.Cyt c@Z, and dashed curves are quantized peaks, that is, the
corresponding spectra difference (linked to right axis). Blue arrows
indicate a peak shift. LSPR, localized surface plasmon resonance. d,
Quantized peaks of GNP100@r.Cyt c@Z within a 530-550 nm region
(zoomed-in from c) confirming the presence of o.Cyt c in samples
exposed to a.c. EFs.

Source data

Full size image

The results fit well with the exponential dependences expected for
the tunnelling of an electron through a barrier^35, supporting the
hypothesis that the resonant biological effects observed with the
electrical input result in QBET. Further primary experimental
evidence for the quantum tunnelling is provided by plasmon resonance
scattering probing the plasmon resonance energy transfer^36. Without
ES, quantized dips from scattering spectra were obtained by
subtracting the spectra for the unmodified particle and vice versa.
For GNP100@r.Cyt c@Z samples (no ES), the scattering peaks were
observed at ~465 nm (ITO substrate); a broad peak due to r.Cyt c and
Z, at around 568 nm; and a localized surface plasmon resonance peak
(LSPR), shifted to 711 nm (LSPR of GNP100 = 612 nm; Fig. 6c and
Supplementary Fig. 38a). This equates to the frequencies with the
absorption peak of r.Cyt c or Z and subsequently induces the
electronic excitation of the r.Cyt c at the specific wavelength^8.
Importantly, the QBETs captured are cumulative. Under ES, we see a
quantized dip at 536 nm due to the switching of r.Cyt c to o.Cyt c
and thus representing QBET (Fig. 6d). We also see a 20 mV shift in
the surface plasmon resonance peak (heat maps in Extended Data Fig.
2a (no EF) and Extended Data Fig. 2b (EF applied)) indicative of
charge transfer, which we associate with the redox behavor of an
electron relay donor complex^37,38. The appearance of o.Cyt c was not
observed in all other control samples with ES (3 MHz, 0.65 V;
Supplementary Fig. 38b-i). The combined data indicate that resonant
frequency effects resulting in cell death, model exponential decay
based on barrier junction energetics and quantized dips from plasmon
resonance energy transfer all represent electron tunnelling. Linker
length, applied frequency and voltage were found to be critical for
QBET-mediated electrical-molecular communication and inducing cancer
cell apoptosis. A detailed discussion on the role of these parameters
is in Supplementary Note 5. Collectively and to the best of our
knowledge, this is the first successful demonstration of
electrical-molecular quantum signalling technology in biology, which
could be used for the induced apoptosis of cancer cells as a
biomedical exemplar.

Conclusions

Inspired by wireless electrochemistry, we tuned the redox state of
molecules functionalized on the surface of nanoantennae by applying
a.c. EFs. This approach is shown to selectively facilitate
electrical-molecular communication to induce apoptosis in
patient-derived GBM cells by switching the redox state of Cyt c at a
resonant electric field. Based on the obtained data, we infer that
the electron transfer in the bio-nanoantennae occurs through
EF-induced quantum tunnelling and is thus QBET, with the applied
frequency, potential and linker length playing a critical role.
Moreover, transcriptomics shows that electrical-molecular
communication is specifically targeted in cancer cells. This
represents a wireless electrical-molecular communication tool that
facilitates the killing of cancer cells.

Methods

Reagents

The following reagents were used: horse heart Cyt c (C7752,
Sigma-Aldrich), EDC (E6383, Sigma-Aldrich), NHS (130672,
Sigma-Aldrich), 2-(N-morpholino)ethane sulfonic acid hydrate,
4-morpholineethanesulfonic acid (M8250, Sigma-Aldrich), l-ascorbic
acid (A92902, Sigma-Aldrich), m-plate 24-well black ibiTreat surface
(IB-82426, Thistle Scientific), Hoechst 33342 (NucBlue Live
ReadyProbes Reagent, R37605, Thermo Fisher Scientific), actin using
Phalloidin-iFluor 488 conjugate (23115, AAT Bioquest, Stratech),
PrestoBlue HS cell viability reagent (P50200, Invitrogen), calcein AM
(C1430, Thermo Fisher Scientific), propidium iodide (P4170,
Sigma-Aldrich), H2DCFDA (D399, Invitrogen), CellEvent Caspase-3/7
Green Flow Cytometry Assay Kit (C10427, Invitrogen), Zombie NIR
Fixable Viability Kit (423105, BioLegend), CellEvent Caspase-3/7
Green ReadyProbes Reagent (R37111, Invitrogen), CellLight Late
Endosomes-GFP, BacMam 2.0 (C10588, Thermo Fisher Scientific) and
LysoTracker Green DND-26 (L7526, Thermo Fisher Scientific). A
catalogue number is not available for the carboxylic-PEG-coated GNPs
or Z as they were customized and purchased from Nanopartz and
Porphychem, respectively.

Synthesis of bifunctionalized gold bipolar bio-nanoantennae

Spherical GNPs with a diameter (d) of 100 nm and capped with
thiol-carboxylic-PEG (SH-PEG-COOH; molecular weight M = 1 kDa, 2 kDa,
3.5 kDa and 5 kDa) with a PEG density of 1-1.5 nm^2 were purchased
from Nanopartz. The r.Cyt c was obtained by adding 10 mg of the
oxidized form of the horse heart Cyt c (o.Cyt c) into 5 mL l-ascorbic
acid solution (1 mg mL^-1 in PBS) and purifying by dialysis at 4 degC
in dark conditions for 36 h to remove excess ascorbic acid. The r.Cyt
c and Z were covalently conjugated to a carboxylic group on the
capping ligands of GNPs using EDC/NHS carbodiimide coupling
chemistry. Briefly, 20 mL GNP solution (3.6 mg mL^-1 in ultrapure
water) was mixed with 20 mL EDC/NHS solution in 2-(N-morpholino)
ethane sulfonic acid buffer (10 mM, pH 5.5) at a concentration of 30
and 36 mg mL^-1. The solution was mixed for 1 h at room temperature;
then 1 mL of washing buffer (x1 PBS with 0.01% (w/v) Tween 20) was
added, and the solution was centrifuged at 450g for 20 min. The
supernatant was discarded and 20 mL r.Cyt c (1 mg mL^-1) and Z
(0.5 mg mL^-1) were added to the pellet and sonicated using a
Fisherbrand ultrasonic bath (FB11201, 80 KHz, 50% power, 1 min).
Next, the solution was incubated for 4 h at room temperature under
mixing; then 1 mL washing buffer was added, and the solution was
centrifuged at 450g for 20 min. To ensure the complete removal of
unbound r.Cyt c and Z, the washing step was repeated twice. The
obtained pellet consist of GNPs conjugated with r.Cyt c and Z
(GNP100@r.Cyt c@Z) was dispersed in PBS and stored at 4 degC until
further use.

To prepare the control samples of GNPs covalently conjugated with
only one molecule, either r.Cyt c (GNP100@r.Cyt c) or Z (GNP100@Z),
only one of these compounds was introduced during the EDC/NHS step
with concentrations of 0.25 mg mL^-1 or 0.1 mg mL^-1, respectively.
The same protocol was used to synthesize bio-nanoantennae with
different GNP diameters (20 nm, 50 nm and 100 nm) and different PEG
lengths (1 kDa, 2 kDa, 3.5 kDa, 5 kDa). The concentration of Cyt c
and Z during the EDC/NHS step was optimized (0.25, 0.5 and 1 mg mL^
-1) to obtain a similar binding ratio of Cyt c and Z per GNP.

Characterization techniques

Dynamic light scattering and zeta potential measurements

The hydrodynamic diameter (h[d]) and zeta potential (z) of
bio-nanoantennae (in ultrapure water) was measured using a Malvern
Zetasizer Nano-ZS ((Malvern Instruments).

Transmission electron microscopy

A TEM instrument (JEOL 2000 FX TEM) operating at 200 kV accelerating
voltage was used to record TEM images. The samples were prepared by
drop-casting 10 mL of sample onto a carbon-coated copper grid (400
Mesh, Agar Scientific) twice in an interval of 1 h. The sample was
dried for at least 30 min before TEM imaging.

UV-visible absorption spectroscopy

UV-visible absorption spectra of bio-nanoantennae dispersed in PBS
were recorded on a Cary 3500 UV-visible instrument (Agilent
Technologies).

Circular dichroism

Far- and near-UV circular dichroism spectra were recorded at 20 degC on
a Chirascan circular dichroism spectrophotometer (Applied
Photophysics) equipped with a temperature control unit TC125 (Quantum
Northwest). Samples were dispersed in 10 mM PBS at pH 7.4. At least
three spectra were recorded for each sample and averaged. A quartz
cuvette with an optical path length of 1 cm was used for the circular
dichroism measurements.

Cyclic voltammetry

The electrochemical analyses were conducted using a Metrohm Autolab
M204 potentiostat equipped with a three-electrode system consisting
of a platinum wire counter electrode, an Ag/AgCl reference electrode
and an ITO working electrode (Delta Technologies). ITO-coated glass
(10 mm x 20 mm) was washed with acetone and water, dried with argon
and assembled into an electrochemical cell with an exposed working
area of 38.5 mm^2. Bifunctionalized gold bipolar nanoelectrodes were
dispersed in PBS to a final concentration of 25 mg mL^-1 (determined
using UV-visible spectroscopy). Cyclic voltammetry was conducted
between 1.2 V and -0.2 V with varying scan rates between 50 mV s^-1
and 2 V s^-1. Repetitive consecutive cyclic voltammetry measurements
were conducted at a fixed scan rate of 100 mV s^-1. Control cyclic
voltammetry measurements were conducted with carboxylic-PEG-modified
GNPs using PBS as the supporting electrolyte.

The heterogeneous rate constant (k^0) was calculated using the
Nicholson and Shain method^46. The rate transfer coefficient, a, was
calculated from the scan rate study (Supplementary Fig. 5). The slope
of the logarithm of the scan rate versus the difference between the
peak potential and formal potential of the cell is given by equation
(2):

$${\rm{Slope}}=-\frac{2.3\,{RT}}{\alpha {nF}}$$
(2)

where R is the gas constant, T is temperature, n is the number of
electrons transferred in the redox reaction and F is the Faraday
constant.

However, the Nicholson and Shain method for determining ps (ps is a
function of the peak separation) assumes that a = 0.5. But in this
work, the value of a is different (Supplementary Table 5); therefore,
the Lavagnini method^47 is used to calculate ps as the function of the
peak separation DE[p] using equation (3):

$$\psi =2.18{\left(\frac{\alpha }{\uppi }\right)}^{0.5}{{\exp }}\left
[\right.-\left(\frac{{\alpha }^{2}F}{{RT}}\right)n\Delta {E}_{\mathrm
{{p}}}.$$
(3)

Then k^0 for the nanoantennae is calculated using equation (4):

$$\psi ={k}^{0}{\left[\frac{{{\uppi }}{{D}}{nv}{{F}}}{{{RT}}}\right]}
^{-0.5}$$
(4)

where D is the diffusion coefficient.

Cell lines

GIN cells were isolated from the 5-aminolevulinic acid (5-ALA)
fluorescing infiltrative tumour margin, and GCE cells were isolated
from the core central region of the tumour, from GBM patients who
underwent surgery at the Queen's Medical Centre, University of
Nottingham (Nottingham, UK), using a previously described method^29.
Low-passage U251 cell lines (purchased from ATCC) and patient-derived
GIN 28, GIN 31, GCE 28 and GCE 31 cells were cultured in DMEM medium
(Gibco) supplemented with 10% foetal bovine serum (FBS), 1%
penicillin/streptomycin and 1% l-glutamine. Human-derived cortical
astrocytes (HCOA; catalogue no. 1800, batch no. 24490, ScienCell) and
cerebellar astrocytes (HCEA; catalogue no. 1810, ScienCell) were
cultured in astrocyte medium containing 2% FBS, 1% astrocyte growth
supplement and 1% penicillin/streptomycin from ScienCell. The human
intrahepatic biliary epithelial cells (HIBEpiC) isolated from healthy
human liver tissue were acquired from Innoprot (P10654) and cultured
in epithelial basal medium containing 2% FBS, 1% epithelial cell
growth supplement and 1% penicillin/streptomycin. All cells were
maintained at 37 degC in an incubator with a humidified atmosphere,
containing 5% CO[2]. Cells were routinely tested for mycoplasma (once
a month), and they were grown in an antibiotic-free medium for one
week before mycoplasma testing. All cells used were mycoplasma-free.

PrestoBlue HS assay for biocompatibility and metabolic activity
studies

The cells (U251, HCOA, GIN and GCE) were seeded in a 96-well plate at
a density of 5 x 10^3 cells per well and allowed to adhere for 24 h.
The medium was replaced with fresh medium containing GNP conjugates
at different concentrations (25, 50 and 100 mg mL^-1), and the cells
were incubated for 8 h. The medium was removed, and the cells were
washed with PBS and incubated for another 48 h in fresh medium. The
medium was replaced with a complete medium containing 10% PrestoBlue
HS cell viability reagent and incubated for an hour before reading
the fluorescence at 590 nm and 610 nm (excitation and emission) in a
Tecan microplate reader (Infinite M Plex and Spark 10M). Cells grown
in culture media provided only the negative control. Values are
presented relative to the negative control. The data are represented
as an average of a triplicate experiment with three independent
repeats.

Cellular association using ICP-MS and uptake using confocal
microscopy

GIN and GCE cells were seeded into a 24-well plate at a density of
1 x 10^5 cells per well and incubated at 37 degC for 24 h. After 24 h,
the culture medium was replaced with fresh medium containing 25 mg mL
^-1 of GNP100@r.Cyt c@Z and incubated for 8 h. Then the medium was
removed, and the cells were washed with PBS (300 mL, repeated two
times). The cells were trypsinized, and 50 mL of cell suspension was
used for trypan blue cell viability and counting. The remaining cell
suspension was centrifuged at 300g for 5 min. The obtained cell
pellet was digested overnight with 70% nitric acid, diluted with
Milli-Q water to bring the acid concentration to 2% and used for
ICP-MS analysis (iCAPQ, Thermo Fischer).

To confirm the cellular uptake of the bipolar nanoelectrode, after
8 h exposure, the cells were washed with PBS (300 mL, two times),
fixed with 4% paraformaldehyde for 15 min and washed twice with PBS.
The cell nuclei were stained with Hoechst 33342 and actin using
Phalloidin-iFluor 488 conjugate and incubated for 1 h at 37 degC in the
dark. After washing the cells twice and immersing them in PBS, the
fluorescence imaging was performed using a Leica TCS SPE confocal
microscope. The orthogonal sections of z stacks were obtained, and
the images were analysed using ImageJ.

Electrical stimulation studies

U251, HIBEpiC, GIN 28, GIN 31, GCE 28 and GCE 31 cells were seeded in
a 24-well plate (m-plate 24-well black ibiTreat, Thistle Scientific)
at a density of 7.5 x 10^4 cells per well, while HCOA and HCEA were
seeded at a density of 5 x 10^4 cells per well in a poly-l
-lysine-coated 24-well plate. The cells were incubated for 24 h at
37 degC and 5% CO[2], and then the cell culture medium was replaced
with fresh medium containing bio-nanoantennae (25 mg mL^-1) and
incubated for 8 h. The cells were washed twice with PBS. Two steel
electrodes (0.5 mm x 25 mm) were placed at a fixed distance (at
opposite sides of the well and 10 mm from each other) in each well of
a 24-well plate and dipped in cell culture medium. The electrodes
were connected to an arbitrary function generator (AFG-21225, RS PRO)
to deliver the required a.c. sine-wave signals, frequency and
amplitude. The cells were stimulated with a.c. EFs with a frequency
of 3 MHz and a peak voltage amplitude of 0.65 V cm^-1 for a period of
2 h or 12 h. The EF between the electrodes was measured using a
digital oscilloscope (TDS 210, Tektronix), and the temperature was
monitored every 2 h using an infrared laser gun (IR-801, ATP). The
intensity of the EF is expressed in peak voltage amplitude per
centimetre (V cm^-1). The metabolic activity of cells after ES was
analyzed using a PrestoBlue HS assay.

Calcein AM and propidium iodide live-dead assay

Immediately after the ES, the medium was removed and replaced with
fresh medium containing mixed dyes 1 mM calcein AM and 1 mg mL^-1
propidium iodide, and incubated for 30 min at 37 degC and 5% CO[2]. The
cells were washed twice with PBS, and fresh phenol red free medium
was added. The cells were imaged using a Nikon Eclipse Ti fluorescent
microscope with GFP and mCherry filter settings. The populations of
live and dead cells were quantified using ImageJ software.

H[2]DCFDA/DCF reactive oxygen species generation assay

The cells were incubated with non-fluorescent cell-permeant
2',7'-dichlorodihydrofluorescein diacetate (H[2]DCFDA, 5 mM) probe
for 30 min prior to ES. Immediately after the ES, the cells were
washed with PBS. The generated reactive oxygen species converted H[2]
DCFDA into 2',7'-dichlorofluorescein. Green fluorescence of
2',7'-dichlorofluorescein was detected using a Nikon Eclipse Ti with
FITC filter settings.

Caspase 3/7 flow cytometry analysis of cell death

Immediately after the ES, cells were trypsinized and centrifuged (300
g for 5 min) to obtain a cell pellet. After washing with PBS, cells
were incubated with a dye master mix containing CellEvent Caspase-3/7
Green Detection Reagent (1:1,000) and Zombie NIR fixable viability
stain (1:2,500) for 30 min. Then the cells were centrifuged at 300g
for 5 min, washed with PBS and fixed with 4% paraformaldehyde. The
fluorescence signals of the caspase 3/7 dye (excitation and emission,
511 nm and 523 nm) and Zombie NIR dye (excitation and emission,
719 nm and 746 nm), characteristic for apoptotic and necrotic cell
populations, respectively, were detected using a Sony ID7000 spectral
flow cytometer. Kaluza software (v.2.1) was used to analyze the data.

Caspase 3/7 detection using confocal microscope

Immediately after the ES, the medium was removed and the cells were
incubated with 8 uM CellEvent Caspase-3/7 Green ReadyProbes Reagent
in PBS containing 5% FBS for 30 min at 37 degC. Afterwards, the cells
were fixed with 4% paraformaldehyde for 20 min and subsequently
washed twice with PBS. Later the cells were treated with actin stain
Phalloidin-iFluor 594 conjugate for 90 min at 37 degC in the dark and
washed again with PBS, followed by staining with Hoechst 33342 for
10 min. Finally, the cells were washed with PBS (twice) and imaged
using a Leica TCS SPE confocal microscope with a x63 objective using
the filter settings of Alexa Fluor 488 and Texas Red 594 dyes.

Colocalization studies

GIN and GCE cells were seeded at a density of 4 x 10^4 cells per well
in a 24-well plate and incubated at 37 degC for 24 h. After 24 h, the
culture medium was replaced with fresh medium containing CellLight
Late Endosomes-GFP, BacMam 2.0 and incubated overnight at 37 degC and
5% CO[2]. Later, the medium was replaced with fresh medium containing
25 mg mL^-1 of GNP100@r.Cyt c@Z and incubated for 8 h. Immediately
after the ES, the cells were washed with PBS and imaged using a Leica
confocal microscope. For lysosomal staining, immediately after ES,
the cells were incubated with medium containing 100 nM LysoTracker
Green DND-26 for 30 min followed by washing and imaging.

Gene regulation analysis

Differential gene regulation analysis

Immediately after the ES (3 MHz, 0.65 V cm^-1, 2 hours) cells were
washed with PBS, trypsinized and centrifuged to obtain a pellet. The
cell pellets were snap-frozen in liquid nitrogen for 5 min and stored
at -80 degC until shipment (in dry ice) to the Qiagen genomics facility
at Hilden, Germany.

Sample preparation

RNA was isolated from 200,000 cells using the RNeasy Micro (Qiagen)
according to the manufacturer's instructions with an elution volume
of 14 uL.

Library preparation and sequencing

The library preparation was done using the QIAseq UPX 3'
Transcriptome Kit (Qiagen). A total of 10 ng purified RNA was
converted into cDNA Next Generation Sequencing (NGS libraries).
During reverse transcription, each cell is tagged with a unique ID
and each RNA molecule is tagged with a unique molecular index (UMI).
Then the RNA is converted to cDNA (complementary Deoxyribonucleic
acid). The cDNA was amplified, the PCR (polymerase chain reaction)
indices were added and the libraries were purified. Library
preparation was quality controlled using capillary electrophoresis
(Agilent DNA 7500 Chip). Based on the quality of the inserts and the
concentration measurements, the libraries were pooled in equimolar
ratios. The library pool(s) were quantified using qPCR (quantitative
polymerase chain reaction). Each library pool was then sequenced on a
NextSeq (Illumina) sequencing instrument according to the
manufacturer instructions with 100 bp read length for read 1 and
27 bp for read2. Raw data were de-multiplexed, and FASTQ files for
each sample were generated using the bcl2fastq2 software (Illumina).

Read demultiplexing, mapping and quantification of gene expression

The 'Demultiplex QIAseq UPX 3' reads' tool of the CLC Genomics
Workbench v.20.0.4 was used to de-multiplex the raw sequencing reads
according to the sample indices. The 'Quantify QIAseq UPX 3'
workflow' was used to process the de-multiplexed sequencing reads
with default settings. In short, the reads are annotated with their
UMI and are then trimmed for poly(A) and adapter sequences, minimum
reads length (15 nucleotides), read quality and ambiguous nucleotides
(maximum of 2). They are then deduplicated using their UMI. Reads are
grouped into UMI groups when they (1) start at the same position
based on the end of the read to which the UMI is ligated (that is,
Read2 for paired data), (2) are from the same strand and (3) have
identical UMIs. Groups that contain only one read (singletons) are
merged into non-singleton groups if the singleton's UMI can be
converted to a UMI of a non-singleton group by introducing an single
nucleotide polymorphism (the biggest group is chosen). The reads were
then mapped to the human genome hg38 and annotated using the refseq
GRCh38.p13 mRNA (messenger Ribonucelic acid) annotation.

The 'Empirical analysis of DGE' algorithm of the CLC Genomics
Workbench v.21.0.4 was used for differential expression analysis with
default settings. It is an implementation of the 'Exact Test' for
two-group comparisons developed by Robinson and Smyth^48 and
incorporated in the EdgeR Bioconductor Package (Robinson et al.,
2010)^49.

For all unsupervised analysis, only genes were considered with at
least ten counts summed over all samples. A variance stabilizing
transformation was performed on the raw count matrix using the
function vst of the R package DESeq2 v.1.28.1. Some 500 genes with
the highest variance were used for the principal component analysis.
The variance was calculated agnostically to the predefined groups
(blind = TRUE). Some 35 genes with the highest variance across
samples were selected for hierarchical clustering.

Differential gene expression and gene-set enrichment analysis

To identify differentially expressed genes, we used the linear
modelling-based limma algorithm on the transcriptome dataset^50.
Briefly, we compared differential mRNA expression among the different
conditions (treated versus untreated) across the cell lines. The
significantly regulated genes were selected with an adjusted P value
below 0.05 using the Benjamini-Hochberg correction method for
multiple testing. Enrichment analysis of the biological processes was
carried out by a gene-set enrichment analysis algorithm^51. Briefly,
the gene sets were obtained from MSigDB (ref. ^52), and enrichment
analyses were conducted among the different conditions across cell
lines. Normalized enrichment scores, P values and adjusted P values
(calculated with a standard Benjamini-Hochberg procedure) were
retrieved for each of the gene sets. The gene sets with higher
normalized enrichment score values and an adjusted P value < 0.05
were considered as enriched for a specific GBM region.

To identify the cell-line-specific responses to treatment, the top
differentially regulated pathways (P value < 0.05) with high
normalized enrichment scores across the astrocytic and GBM-derived
cell lines were selected.

Mathematical model of metabolic activity, charging rate and quantum
tunnelling

We looked to develop a mathematical model to support the
characteristic exponential decay connected with quantum mechanics:

$$P\propto {\mathrm{{e}}}^{-\alpha r}$$
(5)

where P is the probability of electron tunnelling; a is the inverse
localization length, which scales with the energy barrier that an
electron must tunnel through; and r is the length of the energy
barrier. We define an intrinsic rate of cell death (directly
proportional to the probability of a given cell dying within a given
time frame), r[d], which we assume is proportional to the rate of
cytochrome charging. Then, the number of dead cells (D) at time t is

$$D\left(t\right)={\int }_{\!\!0}^{t}{\rm{d}}{t}^{{\prime} }A\left
({t}^{{\prime} }\right){r}_{\mathrm{{d}}}$$
(6)

where A is the number of alive cells. The metabolic activity is given
by

$$M\left(t\right)=\frac{A(t)}{A(t)+D(t)}=\frac{T-{r}_{\mathrm{{d}}}{\
int }_{\!\!0}^{t}{\rm{d}}{t}^{{\prime} }A\left({t}^{{\prime} }\
right)}{T}$$
(7)

where T = D + A is the total number of cells. Solving the above
equation, we find that \(M\left(t\right)={{\mathrm{e}}}^{-{r}_{{\
mathrm{d}}}t}.\) therefore, the rate of charging at any given time (t
) is given by r[d] [?] -ln[M(t)].

Dark-field microscopy and plasmon resonance scattering spectroscopy

The plasmon resonance scattering measurements were carried out on an
inverted dark-field microscope (eclipse Ti-U, Nikon) using a x40
objective lens (numerical aperture, 0.6) and a dark-field condenser
(0.8 < numerical aperture < 0.95). A halogen lamp (100 W) was used as
a source of white light to generate plasmon resonance scattering
light. The dark-field images were captured by a true-colour digital
camera (Nikon DS-fi). The light scattered from the bifunctionalized
nanoantennae was split by a monochromator (grating density,
300 lines mm^-1; blazed wavelength, 500 nm; Acton SP2300i, Princeton
Instruments). An IsoPlane-320 spectrometer was used, and the split
light was collected by a charge-coupled device (Pixis 100BX,
Princeton Instruments). An a.c. EF of 3 MHz at 0.65 V was applied for
10 min, and scattering spectra were monitored (1,000 frames
recorded). The exposure time was 500 ms. The samples for plasmon
resonance scattering were prepared by immobilizing nanoantennae on
ITO. First, ITO slides were treatment with ethanol, acetone and water
under sonication. Next, 50 ul nanoantennae solution was drop-casted
on the ITO slides for 10 min, followed by a single-step washing and
rinsing with water. Finally, the slides were dried with N[2] gas.

Statistics and reproducibility

All the statistical analyses were performed using GraphPad Prism
v.9.4.1 software (GraphPad Software). All the data are expressed as
mean +- s.e.m., unless specified. For responses that were affected by
two variables, a two-way ANOVA with a Tukey post-test was used. The
value P <= 0.05 was considered significant. The number of technical
replicates and independent repeats is included in the figure legends.

Reporting summary

Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.

Data availability

Source data are provided with this paper. All other data associated
with this manuscript (including the Supplementary Information) can be
found at https://doi.org/10.17639/nott.7303. The complete dataset of
transcriptomics analysis can be found at the Gene Expression Omnibus
(GEO) under accession number GSE233380.

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Download references

Acknowledgements

This work was supported by the Engineering and Physical Sciences
Research Council (grant number EP/R004072/1 to F.J.R.) and Royal
Society of Chemistry Enablement Grant no. E21-1135058786 to F.J.R.
and A.J. A.J. acknowledges the University of Nottingham internal
funding schemes NanoPrime and UNICAS. J.G., M.F. and L.T. acknowledge
the Engineering and Physical Sciences Research Council (grant number
EP/P031684/1). L.P.-G. thanks project PID2020-115663GB-C3, which was
funded by MCIN/AEI/10.13039/501100011033 and AGAUR (Generalitat de
Catalunya), for a grant to consolidated research groups 2021 SGR
01085. We thank B. Xie at Nanjing University, China, for plasmon
resonance scattering and DFM (Dark Field Microscopy) analysis; D.
Onion at the University of Nottingham, Flow Cytometry Unit, for
assistance with flow cytometry analysis; M. Sueca-Comes for providing
HIBEpiC cells; M. Fay for help with TEM; J. Potts for assistance with
particle analysis; and L. Martinez Nunez for the illustration in Fig.
1. We would also like to thank Prof. Nieves Casan-Pastor for her
feedback on the manuscript.

Author information

Authors and Affiliations

 1. Bioelectronics Laboratory, Division of Regenerative Medicine and
    Cellular Therapies, School of Pharmacy, Biodiscovery Institute,
    University of Nottingham, Nottingham, UK

    Akhil Jain & Frankie J. Rawson

 2. Faculty of Engineering, University of Nottingham, Nottingham, UK

    Jonathan Gosling & Lyudmila Turyanska

 3. State Key Laboratory of Analytical Chemistry for Life Science,
    School of Chemistry and Chemical Engineering, Nanjing University,
    Nanjing, China

    Shaochuang Liu, Haowei Wang & Yi-Tao Long

 4. School of Pharmacy, University of Nottingham, Nottingham, UK

    Eloise M. Stone & Lluisa Perez-Garcia

 5. Institute of Medical Bioinformatics and Systems Medicine, Medical
    Center - University of Freiburg Faculty of Medicine, University
    of Freiburg, Freiburg, Germany

    Sajib Chakraborty

 6. School of Medicine, Biodiscovery Institute, University of
    Nottingham, Nottingham, UK

    Padma-Sheela Jayaraman

 7. Children's Brain Tumour Research Centre, School of Medicine,
    Biodiscovery Institute, University of Nottingham, Nottingham, UK

    Stuart Smith & Ruman Rahman

 8. Department of Neurosurgery, Nottingham University Hospitals,
    Nottingham, UK

    Stuart Smith

 9. Institut de Ciencia de Materials de Barcelona (ICMAB-CSIC),
    Campus Universitari de Cerdanyola, Barcelona, Spain

    David B. Amabilino

10. School of Chemistry, University of Nottingham, Nottingham, UK

    David B. Amabilino

11. School of Physics and Astronomy, University of Nottingham,
    Nottingham, UK

    Mark Fromhold

12. Departament de Farmacologia, Toxicologia i Quimica Terapeutica,
    Facultat de Farmacia i Ciencies de l'Alimentacio, Universitat de
    Barcelona, Barcelona, Spain

    Lluisa Perez-Garcia

13. Institut de Nanociencia i Nanotecnologia, Universitat de
    Barcelona (IN2UB), Barcelona, Spain

    Lluisa Perez-Garcia

Authors

 1. Akhil Jain
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 4. Haowei Wang
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Contributions

A.J., L.P.-G., D.B.A., S.S., R.R. and F.J.R. conceptualized the work.
A.J., L.P.-G., D.B.A., R.R., L.T. and F.J.R. designed the experiments
and performed the analysis. A.J. synthesized and characterized the
bio-nanoantennae. A.J. performed all the ES experiments in vitro and
analyzed the data together with L.P.-G., D.B.A., L.T. and F.J.R.;
J.G. and M.F. performed the mathematical modelling. S.L. and H.W.
performed the plasmon resonance scattering. Y.-T.L. supervised S.L.
and H.W.; A.J. and E.M.S. analyzed the cyclic voltammetry data. S.C.
and R.R. performed the gene ontology analysis. S.S. and P.-S.J.
supplied the primary GBM and normal liver bile duct cells,
respectively. F.J.R. supervised A.J.; A.J. and F.J.R. wrote the first
draft of the manuscript. All the authors corrected the manuscript.

Corresponding author

Correspondence to Frankie J. Rawson.

Ethics declarations

Competing interests

The research described in this manuscript has been filed for a UK
patent (application no. 2302102.5) by The University of Nottingham,
UK. Inventors listed are Dr Frankie Rawson, Dr Akhil Jain, Prof David
Amabilino and Prof Luisa Perez-Garcia. All parts of the main paper
have been included in the patent. The authors have no other conflict
of interest to declare. All the authors read the manuscript and
agreed on submission.

Peer review

Peer review information

Nature Nanotechnology thanks Jun-Tao Cao, Binbin Huang and Joao
Pessoa for their contribution to the peer review of this work.

Additional information

Publisher's note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional
affiliations.

Extended data

Extended Data Fig. 1 Gene-set Enrichment analysis (GSEA) of Gene
Ontology Biological Processes (GOBP).

(a) GSEA of GOBP across all cell-lines (Cortical-Astrocytes, GCE-31,
and GIN-31) is represented as a heatmap. The topmost GOBP terms based
on the adjusted p-value are shown. (b) Cortical Astrocyte Response to
Treatment: GSEA of GOBP across all cell-lines (Cortical-Astrocytes,
GCE-31, and GIN-31) is represented as a heatmap. The topmost GOBP
terms that are differentially regulated in cortical astrocytes (based
on the adjusted p-value) compared to GCE-31 and GIN-31 cell-lines are
shown. (c) GCE/GIN 31 Cells Response to Treatment: GSEA of GOBP
across all cell-lines (Cortical-Astrocytes, GCE-31, and GIN-31) is
represented as a heatmap. The topmost GOBP terms that are
differentially regulated in GCE-31 and GIN-31 cell-lines (based on
the adjusted p-value) compared to cortical astrocytes are shown. In
Fig. b-d: the colour code is based on the normalized enrichment score
(NES). The significantly enriched terms (adj p-value < 0.05) are
indicated by (*) symbol. For the GSEA, we used one-tailed Fisher's
exact test with 95% of confidence interval. The p-values were
corrected for multiple comparisons with the Benjamini-Hochberg
method. The exact p values can be found in Supplementary Table 7. The
treatment codes are as follow: Control = no treatment with either
bio-nanoantennae or AC EFs); EF = cells treated with AC EFs; EF_NP1 =
cell treated with GNP100@r.Cyt c, and EF_NP2 = cells treated with
GNP100@r.Cyt c@Z, for 8 h followed by 2-hour a.c. EFs.

Source data

Extended Data Fig. 2 Plasmon resonance scattering spectra and
quantized peaks to demonstrate QBET.

Two-dimensional heat map of scattering spectral changes obtained from
dark field microscopy, (a) in the absence of EF and (b) presence of
EF.

Supplementary information

Supplementary Information

Supplementary Figs. 1-38, Notes 1-5 and Tables 1-7.

Reporting Summary

Source data

Source Data Fig. 2

Source data associated with UV-visible measurements of
bio-nanoantennae before ES (Fig. 2b,c), cyclic voltammetry scan rate
studies (Fig. 2d) and ICP-MS analysis (Fig. 2e).

Source Data Fig. 3

Source data associated with metabolic activity of GIN 31 and GCE 31
cells (Fig. 3a), GIN 28 and GCE 28 cells (Fig. 3b) and cortical
astrocytes (Fig. 3c).

Source Data Fig. 4

Source data associated with the differential gene expression shown in
Fig. 4.

Source Data Fig. 5

Source data associated with circular dichroism (Fig. 5a), UV-visible
measurements of bio-nanoantennae after ES (Fig. 5b,c) and the
metabolic activity of GIN 31 cells as a function of different size
bio-nanoantennae (20 nm, 50 nm and 100 nm; GNP20@r.Cyt c@Z,
GNP50@r.Cyt c@Z and GNP100@r.Cyt c@Z) synthesized using various
linker lengths (1, 2, 3.5 and 5 kDa; Fig. 5d-f).

Source Data Fig. 6

Source data associated with mathematical modelling to determine the
rate of donor charging, r[d], calculated using the metabolic
activity, using equation (1), compared to the PEG linker length, L,
for GNP20@r.Cyt c@Z (Fig. 6a) and GNP100@r.Cyt c@Z (Fig. 6b) in GIN
31 cell samples. Source data for the scattering spectra and spectra
difference (Fig. 6c) and quantized peaks (Fig. 6d) for QBET obtained
for GNP100@r.Cyt c@Z bio-nanoantennae.

Source Data Extended Data Fig. 1

Source data associated with gene-set enrichment analysis of gene
ontology biological processes shown in Extended Data Fig. 1a-c.

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Jain, A., Gosling, J., Liu, S. et al. Wireless electrical-molecular
quantum signalling for cancer cell apoptosis. Nat. Nanotechnol.
(2023). https://doi.org/10.1038/s41565-023-01496-y

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  * Received: 26 March 2023

  * Accepted: 01 August 2023

  * Published: 14 September 2023

  * DOI: https://doi.org/10.1038/s41565-023-01496-y

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