Elisa Lenzi1,2, Dorleta Jimenez de Aberasturi1,2,3, Malou Henriksen-Lacey1,2, Paula Piñeiro1, Ayse J Muniz4, Joerg Lahann4, Luis M Liz-Marzán1,2,3. 1. CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. 2. Centro de Investigación Biomédica en Red de Bioingeniería Biomateriales, y Nanomedicina (CIBER-BBN), 20014 Donostia-San Sebastián, Spain. 3. Ikerbasque, Basque Foundation for Science, 48009 Bilbao, Spain. 4. Biointerfaces Institute, Department of Chemical Engineering, Materials Science and Engineering, Biomedical Engineering Macromolecular Science and Engineering B10-A175 NCRC University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan 48109-2800, United States.
Abstract
With the ever-increasing use of 3D cell models toward studying bio-nano interactions and offering alternatives to traditional 2D in vitro and in vivo experiments, methods to image biological tissue in real time and with high spatial resolution have become a must. A suitable technique therefore is surface-enhanced Raman scattering (SERS)-based microscopy, which additionally features reduced photocytotoxicity and improved light penetration. However, optimization of imaging and postprocessing parameters is still required. Herein we present a method to monitor cell proliferation over time in 3D, using multifunctional 3D-printed scaffolds composed of biologically inert poly(lactic-co-glycolic acid) (PLGA) as the base material, in which fluorescent labels and SERS-active gold nanoparticles (AuNPs) can be embedded. The combination of imaging techniques allows optimization of SERS imaging parameters for cell monitoring. The scaffolds provide anchoring points for cell adhesion, so that cell growth can be observed in a suspended 3D matrix, with multiple reference points for confocal fluorescence and SERS imaging. By prelabeling cells with SERS-encoded AuNPs and fluorophores, cell proliferation and migration can be simultaneously monitored through confocal Raman and fluorescence microscopy. These scaffolds provide a simple method to follow cell dynamics in 4D, with minimal disturbance to the tissue model.
With the ever-increasing use of 3D cell models toward studying bio-nano interactions and offering alternatives to traditional 2D in vitro and in vivo experiments, methods to image biological tissue in real time and with high spatial resolution have become a must. A suitable technique therefore is surface-enhanced Raman scattering (SERS)-based microscopy, which additionally features reduced photocytotoxicity and improved light penetration. However, optimization of imaging and postprocessing parameters is still required. Herein we present a method to monitor cell proliferation over time in 3D, using multifunctional 3D-printed scaffolds composed of biologically inert poly(lactic-co-glycolic acid) (PLGA) as the base material, in which fluorescent labels and SERS-active gold nanoparticles (AuNPs) can be embedded. The combination of imaging techniques allows optimization of SERS imaging parameters for cell monitoring. The scaffolds provide anchoring points for cell adhesion, so that cell growth can be observed in a suspended 3D matrix, with multiple reference points for confocal fluorescence and SERS imaging. By prelabeling cells with SERS-encoded AuNPs and fluorophores, cell proliferation and migration can be simultaneously monitored through confocal Raman and fluorescence microscopy. These scaffolds provide a simple method to follow cell dynamics in 4D, with minimal disturbance to the tissue model.
Entities:
Keywords:
3D bioprinting; SERS imaging; SERS tags; multimodal imaging; scaffolds
The use of 3D-printed
scaffolds for in vitro cell
culture has become an important element in current biomedical research,
in addition to offering an alternative route to in vivo studies.[1,2] By 3D printing the scaffold, both the physical
and biological properties can be tailored, obtaining high degrees
of spatial resolution and reproducibility.[3−5] These 3D-printed
scaffolds can be used in various ways, such as supporting cell growth,[6,7] inducing cell differentiation,[8] acting
as an imaging reference point,[9] or as a
sensing substrate to analyze molecular changes over time.[10] Moreover, 3D printing has become an excellent
fabrication tool for polymeric scaffolds,[11,12] as it provides numerous possibilities to customize the final design
toward reproducible fabrication at a relatively low cost.[13,14] The production of biocompatible scaffolds with micron-scale resolution,
yet combining large footprint areas, has been achieved by means of
3D jet writing of polymer inks.[15−18] This modified electrospinning process can produce,
for example, a honeycomb tessellated structure featuring a highly
organized open structure, which can support the long-term growth of
a wide variety of cell types, including fibroblasts, endothelial cells,
cancer cells, and even mesenchymal stem cells, maintaining the mechanical
integrity and even allowing in vivo implantation.[15,16] Indeed, gold nanoparticles (AuNPs), and/or molecules such as drugs
or fluorophores, can also be included to form multicompartment particles
capable of controlled drug release and multimodal imaging.[19−21]An important condition toward the development of new materials
for sophisticated 3D models is the ability to accurately image and
characterize them in situ, hence providing real-time
information relating to aspects such as cell proliferation, migration,
and differentiation, over time.[22−24] For this purpose, multimodal
imaging techniques that provide complementary information can be explored.
However, the translation of imaging techniques from 2D to 3D cell
models is, in general, not trivial,[25] and
the lack of standardization in emerging characterization techniques[26] is also slowing down the development of new
substrates for 3D culture and their translation into real clinical
protocols.[27]We thus identified a
need to explore alternative methods and optimize
various live cell imaging parameters, toward achieving accurate characterization
of 3D cell models with time. To this aim, we have identified surface-enhanced
Raman scattering (SERS) imaging as a convenient technique for the
interrogation of cells in situ, which furthermore
can be combined with fluorescence imaging.[28,29] SERS imparts both high sensitivity and high selectivity, thus being
an excellent option for imaging live cell-containing 3D structures.[30] For SERS imaging, cells are labeled with SERS
tags comprising AuNPs encoded by adsorbing Raman-active molecules
(Raman reporters) with strong affinity for the AuNP surface and well-defined
Raman fingerprints.[31]The biocompatible
nature and optical stability of purposely designed
SERS tags allows long-term imaging in a noninvasive manner, and the
wide choice of available Raman reporters provides extensive opportunities
for SERS multiplexing, using a single irradiation wavelength.[30,32−34] Compared with fluorescence microscopy, SERS tags
do not suffer from probe photobleaching,[19] and they can be excited by a near-infrared (NIR) laser, resulting
in improved penetration of light through tissue.[35] It should however be recognized that 3D SERS bioimaging
is still in a developmental phase, and not only sophisticated microscopes
but also optimization of measurement parameters and complex data analysis
are required.Herein, we show that the optimization of 3D SERS
live imaging parameters
allowed us to achieve the imaging of SERS-labeled live cells, grown
within 3D-printed scaffolds carrying SERS and fluorescent labels.
We show that the presence of SERS tags in the scaffold or in the cells
does not hinder fluorescence imaging, nor vice versa, and therefore,
both SERS and fluorescence imaging techniques can be combined to achieve
simultaneous multimodal imaging.[36,37] Using the
3D jet writing technique, we fabricated PLGA tessellated scaffolds
containing fluorescent polymers and/or SERS-encoded gold nanostars
(AuNSs). We demonstrate that such hybrid scaffolds offer a suitable
support frame for the long-term growth of human dermal fibroblasts
(HDFs); cells grow in a suspended 3D form which offers sufficient
optical transparency for both fluorescence and SERS imaging. Indeed,
cell–scaffold contact is kept to a minimum, thus promoting
the cell–cell interactions that are found in the natural in vivo microenvironment. The relevant parameters for both
imaging techniques were optimized taking into consideration factors
such as imaging time, resolution, and signal intensity. To achieve
multiplexing, we prelabeled separate HDF populations with SERS tags
of different Raman fingerprints, which can all be excited at the same
laser wavelength.[34] By including fluorescence
and/or SERS tags, the scaffold could be used not only as a support
but also as an imaging reference point to study the migration of different
HDF populations. Our results demonstrate multimodal 3D imaging of
complex living cell systems over long periods of time, with no need
for fixing the cells, thereby opening the way toward 3D live cell
imaging in complex systems, using 3D SERS imaging as a complementary
bioimaging technique.
Results and Discussion
PLGA Scaffolds Labeled
for SERS and Fluorescence Imaging
The preparation of SERS
tags responsive to NIR irradiation was achieved
by first synthesizing AuNSs with a localized surface plasmon resonance
(LSPR) maximum around 800 nm, in resonance with the 785 nm laser wavelength
usually available in Raman microscopes.[31,38] AuNSs are
ideal SERS substrates because of the high electromagnetic field enhancements
at their multiple tips,[39] as well as their
biocompatibility and flexibility regarding the choice of Raman-active
molecular reporters that can be incorporated.[34] AuNSs were synthesized in aqueous solution[40] and transferred to chloroform (CHCl3)[34,41] upon adsorption of biphenyl-4-thiol (BPT), which provides a well-defined
Raman signature and hydrophobicity. The resulting particles (AuNS-BPT)
had an average size of 50 nm, as confirmed by transmission electron
microscopy (TEM), and a main extinction band around 785 nm (Figure S1A).[42] The
SERS spectrum of AuNS-BPT was found to match the characteristic molecular
fingerprint of BPT (Figure S1B).The scaffolds fabricated with the 3D jet writing technique were composed
of PLGA fibers of 10 μm diameter, each of which can also be
divided into different compartments if desired. As such, we fabricated
scaffolds composed of monocompartmental and bicompartmental fibers
including SERS tags and different fluorophores. For their fabrication,
AuNS-BPT ([Au0] = 3 × 10–3 M) SERS
tags, dispersed in chloroform (CHCl3), were subsequently
mixed with the fluorescently labeled polymers (poly[(mphenylenevinylene)-alt-(2,5-dihexyloxy-p-phenylenevinylene]
and poly[tris(2,5-bis(hexyloxy)-1,4-phenylenevinylene)-alt-(1,3-phenylenevinylene)]) and 50–75 kDaA PLGA (30 wt/vol
%), all dissolved in CHCl3. N,N-Dimethylformamide (DMF) was then added to the solution,
resulting in a solvent mixture of CHCl3 and DMF at ca.
93:7 vol/vol %[16] (see details in the Experimental Section). To fabricate the scaffolds,
the different SERS tag PLGA solutions were loaded in individual syringes
and flown in a laminar regime through parallel mounted metallic 20-gauge
needles (Figure A).
Hybrid PLGA scaffolds were printed with either 5 or 10 aligned fibers
of 10 μm in diameter (Figure S2),
resulting in a 10 × 10 mm2 mesh with individual 500
× 500 μm2 squares, as observed by scanning electron
microscopy (SEM) (Figure B). The bicompartmental composition of the fibers allows the
incorporation of either one or two fluorophores (green and blue),
as well as AuNSs-BPT (or other SERS tags). Shown in Figure C and Figure S2C–E are confocal fluorescence microscopy images of
the structure containing different fluorophores and AuNS-BPT, resulting
in strong SERS and fluorescence signals, readily detectable in the
whole scaffold (Figure D).
Figure 1
Characterization of PLGA hybrid scaffolds. (A) Schematic illustration
of the 3D printing system for bicompartmental and monocompartmental
scaffolds. (B) Representative SEM images of the hybrid scaffolds.
(C) Fluorescence confocal microscopy images showing emission from
blue and green labeled compartments. (D) SERS mapping of the signal
from AuNS-BPT SERS tags, distributed throughout the PLGA fibers.
Characterization of PLGA hybrid scaffolds. (A) Schematic illustration
of the 3D printing system for bicompartmental and monocompartmental
scaffolds. (B) Representative SEM images of the hybrid scaffolds.
(C) Fluorescence confocal microscopy images showing emission from
blue and green labeled compartments. (D) SERS mapping of the signal
from AuNS-BPT SERS tags, distributed throughout the PLGA fibers.
SERS Tag Labeling of HDF Cells
Primary
human dermal
fibroblasts (HDF) were selected as a model cell system to test the
ability of hybrid scaffolds to support cell growth in 3D over time.
In their natural setting, HDFs are the main cellular component of
the dermis layer of the skin and play a crucial role in maintaining
the structural integrity of this connective tissue. We have previously
shown that HDF cells avidly uptake positively charged SERS tags and
can retain them for long time periods (ca. 2 weeks).[30] We therefore incubated HDF cells with different SERS tags,
to obtain a mixed group of cells which could be monitored over time.
We chose SERS tags composed of AuNSs labeled with a Raman reporter
(1-naphthalenethiol (1NAT), 2-naphthalenethiol (2NAT), or 4-methylbenzenethiol
(MBT)), and stabilized with dodecylamine-modified polyisobutylene-alt-maleic anhydride (PMA) and further coated with poly-l-arginine hydrochloride (PA) to achieve a positive surface
charge (Figure S3). We denoted these SERS
tags as AuNS-1NAT, AuNS-2NAT, and AuNS-MBT. The choice of 1NAT, 2NAT,
and MBT as the Raman reporter molecules allowed multiplexing through
their spectral features, which could be distinguished using postprocessing
tools such as multiple linear regression analysis (MLRA)[38] or True Component Analysis (Figure A).
Figure 2
Characterization and
imaging of SERS tags for cell labeling. (A)
SERS spectra of AuNS-1NAT, AuNS-2NAT, and AuNS-MBT SERS tags, measured
in water. (B) SERS tag uptake into HDF, as detected via two-photon
confocal microscopy (780 nm excitation, 570–610 nm emission).
Scale bars: 50 μm. (C) Left: brightfield images of cells selected
for SERS imaging (red box); middle: maximum intensity projection SERS
maps showing distribution of signals corresponding to separate SERS
tags; right: 3D volume reconstruction of z-stack SERS maps. SERS imaging
was conducted using 0.02 s integration time with 5 mW laser power
and 1 × 1 × 4 μm step size (XYZ).
Characterization and
imaging of SERS tags for cell labeling. (A)
SERS spectra of AuNS-1NAT, AuNS-2NAT, and AuNS-MBT SERS tags, measured
in water. (B) SERS tag uptake into HDF, as detected via two-photon
confocal microscopy (780 nm excitation, 570–610 nm emission).
Scale bars: 50 μm. (C) Left: brightfield images of cells selected
for SERS imaging (red box); middle: maximum intensity projection SERS
maps showing distribution of signals corresponding to separate SERS
tags; right: 3D volume reconstruction of z-stack SERS maps. SERS imaging
was conducted using 0.02 s integration time with 5 mW laser power
and 1 × 1 × 4 μm step size (XYZ).Indeed, exposure of HDF cells to all three SERS tag formulations
for 24 h resulted in high levels of uptake (ca. 10–30% of added
NP), which was verified via two-photon and SERS confocal microscopy,
showing SERS signals located in peri-nuclear vesicles (Figure B,C). In both cases, SERS tags
were added at a concentration of 0.1 mM (in FBS-containing media)
to previously serum starved cells, thereby promoting endocytosis of
SERS tags by cells, at a similar rate.[43] Previous studies with similar NPs showed no cytotoxicity, thanks
to the protective PMA coating and the inherent biocompatible nature
of gold.[30,34] Verification was performed by analyzing
cell viability via propidium iodide (PI) uptake as a marker of damaged
cell membranes. As shown in Figure S4,
no significant changes in overall cell number, as well as the lack
of PI stained cells in the entire cell population, confirm that SERS
tags are not cytotoxic to HDF, even at relatively high concentrations
(0.1 mM). We thus explored the labeling of HDF cells with SERS for
long-term SERS imaging. First, we studied the Raman signal intensity
over time, using HDF cells prelabeled with AuNS-2NAT as an example
(Figure ). The initial
average signal of the Raman spectra collected between 600 and 1600
cm–1 (4 days in vitro, 4 “DIV”)
showed little change in intensity, while after a further 4 days (8
DIV), the intensity reduced by approximately half. To conduct SERS
imaging, we used a confocal Raman microscope (Alpha300 R, Witec) with
a 20× immersion long working distance objective, and an XYZ step
size of 1 × 1 × 4 μm3. Whereas for initial
cell uptake characterization (Figure C), we used a 0.02 s integration time, working with
5 mW laser power, for interrogation of the cell culture with time,
a longer integration time (0.05 s vs 0.02 s) and higher laser power
(10 mW vs 5 mW) were needed to obtain clear signals. The 1 ×
1 × 4 μm3 step size in XYZ coordinates was sufficient
to spatially resolve the SERS tags in a 2D cell culture over time.
Even higher SERS signal intensities could be achieved by further increasing
the excitation laser power intensity, while avoiding damage to cells
(Figure S5). As a result, cells can be
imaged for longer periods if needed, much in the same way as laser
power and detector gain can be increased in fluorescence imaging.
Figure 3
Monitoring
HDF cells labeled with AuNS-2NAT over time in 3D. (A)
Volume reconstructions from SERS confocal imaging (left) of areas
containing HDF cells, framed by colored boxes in the brightfield optical
images (right). Mapping was performed on day 1 (DIV 1, blue), DIV
4 (orange), and DIV 8 (yellow). (B) Average SERS spectra from DIV
1, DIV 4, and DIV 8, calculated from the entire imaging volume. SERS
imaging was conducted using a 0.05 s integration time with 10 mW laser
power and 1 × 1 × 4 μm step size (XYZ).
Monitoring
HDF cells labeled with AuNS-2NAT over time in 3D. (A)
Volume reconstructions from SERS confocal imaging (left) of areas
containing HDF cells, framed by colored boxes in the brightfield optical
images (right). Mapping was performed on day 1 (DIV 1, blue), DIV
4 (orange), and DIV 8 (yellow). (B) Average SERS spectra from DIV
1, DIV 4, and DIV 8, calculated from the entire imaging volume. SERS
imaging was conducted using a 0.05 s integration time with 10 mW laser
power and 1 × 1 × 4 μm step size (XYZ).
SERS Imaging of Cells within Tessellated Scaffolds
In addition
to the improved signal stability, as compared with fluorescence
confocal microscopy, SERS microscopy offers the ability to image deeper
in a biological sample by using a NIR laser with deeper penetration
length.[30,44] This feature is of special interest in the
characterization of in vitro and in vivo 3D models, which require noninvasive imaging over time and may intrinsically
present high absorption and scattering of visible light. SERS imaging
conditions and parameters were thus optimized to establish both the
limitations and the advantages of SERS for 3D cell model imaging.
We first analyzed the growth kinetics of HDF cells, seeded onto the
hybrid multilabeled scaffolds, using GFP-transfected HDF cells (Figure S6). HDF growth could be clearly observed
to progressively fill the spaces of the scaffold, eventually resulting
in the formation of a continuous HDF film, growing intertwined with
the scaffold fibers (Figures a, S7). Within 14 days of cell
growth, a complete HDF film with a thickness larger than 100 μm
was identified within the printed scaffold. Immunocytochemical staining
revealed the presence of fibronectin in the suspended imaging windows,
colocalizing with the presence of HDF cells. This suggests that, aside
from the fibronectin used initially to coat the scaffolds to aid cell
adherence, HDF cells were producing their own extracellular matrix
to support their growth in 3D (Figure b,c).
Figure 4
HDF cell network formed in 3D jet printed scaffolds, 14
days after
seeding. The scaffold shows blue fluorescence, HDF cells were transfected
to express GFP (green emission), and immunocytochemical staining after
fixing allowed the detection of scaffold associated and HDF secreted
fibronectin (red). (A) Tile image showing the entire scaffold (1 cm2) with HDF cells filling most of the squares. (B) Maximum
intensity projection (MIP) of a Z-stack (ca. 150 μm thick) showing
HDF 3D organization in the scaffold. (C) MIPs of Z-stacks (ca. 150
μm thick) showing individual components and a merged image.
The square in (C, Merge) depicts the area shown at higher magnification
in Figure S7.
HDF cell network formed in 3D jet printed scaffolds, 14
days after
seeding. The scaffold shows blue fluorescence, HDF cells were transfected
to express GFP (green emission), and immunocytochemical staining after
fixing allowed the detection of scaffold associated and HDF secreted
fibronectin (red). (A) Tile image showing the entire scaffold (1 cm2) with HDF cells filling most of the squares. (B) Maximum
intensity projection (MIP) of a Z-stack (ca. 150 μm thick) showing
HDF 3D organization in the scaffold. (C) MIPs of Z-stacks (ca. 150
μm thick) showing individual components and a merged image.
The square in (C, Merge) depicts the area shown at higher magnification
in Figure S7.To study the kinetics of HDF cell growth via SERS, nontransfected
HDF cells prelabeled with the three SERS tags were seeded onto the
scaffold and SERS spectra collected every 3–5 days for a period
of ca. 3 weeks. The scaffold geometry, which supports cell growth
yet with minimum cell–scaffold contact, was ideal for SERS
imaging, as cells were essentially in a suspended state but growing
in a 3D extracellular matrix (Figure ). This provided an imaging “window”
that allowed continued monitoring of cells in a noninvasive manner.
SERS imaging in 2D was conducted, and signals corresponding to the
three SERS tags were plotted and overlaid on a brightfield image of
the same area (Figure , Figure S8). Whereas we did observe changes
in the distribution of the SERS tags within the field of view, the
2D nature of this mapping led to a significant loss of information.
We could confirm the presence of HDF cells in the field of view via
brightfield imaging, but few SERS tag-positive cells were observed
by SERS at a fixed viewing plane. On the basis of the expected dilution
of SERS tags with time, and knowing that HDF cells most likely occupy
the thickness of ca. 100 μm, the 3D distribution of SERS tags
in the scaffold was studied using 30 mW laser power with 0.05 s integration
time (Figure , Figure S9). Indeed, the measurements conducted
at 25 DIV clearly show the presence of many HDF cells labeled with
all three SERS tags, with a homogeneous distribution throughout the
field of view. The z-dimension is also in agreement with that determined
via fluorescence (ca. 100 μm, Figure b).
Figure 5
HDF proliferation and migration. HDF cells prelabeled
with three
different SERS tags were used: AuNS-1NAT (magenta), AuNS-2NAT (green),
and AuNSs-MBT (red). HDFs were allowed to grow in a tessellated scaffold;
SERS mapping of the area framed in yellow was conducted every 3–5
days. Cells containing all three SERS tags are shown in cyan. (A)
Brightfield images with overlaid SERS maps at different time points.
(B) Graph showing the average SERS spectra for all three SERS tags,
as well as the intensity of pixels with positive match for all three
tags, as analyzed by True Component Analysis (Witec). SERS imaging
was conducted using a 0.05 s integration time, 10 mW laser power,
and a 5 × 5 μm2 step size (XY).
Figure 6
3D SERS mapping. HDF cell distribution after 25 DIV, as viewed
with brightfield microscopy (A) and 3D SERS imaging (B). (A) HDF cells
are false-colored in gray blue, the cell-filled imaging window (black
square box) was subsequently mapped by SERS imaging. (B) SERS mapping
of HDF cells, prelabeled with AuNS-1NAT (magenta), AuNS-2NAT (green),
and AuNS-MBT (red). Cells containing all three SERS tags are displayed
in cyan. SERS maps were analyzed using True Component Analysis (Witec).
SERS imaging was conducted using 0.05 s integration, 30 mW laser power,
and 5 × 5 × 5 μm3 step size (XYZ).
HDF proliferation and migration. HDF cells prelabeled
with three
different SERS tags were used: AuNS-1NAT (magenta), AuNS-2NAT (green),
and AuNSs-MBT (red). HDFs were allowed to grow in a tessellated scaffold;
SERS mapping of the area framed in yellow was conducted every 3–5
days. Cells containing all three SERS tags are shown in cyan. (A)
Brightfield images with overlaid SERS maps at different time points.
(B) Graph showing the average SERS spectra for all three SERS tags,
as well as the intensity of pixels with positive match for all three
tags, as analyzed by True Component Analysis (Witec). SERS imaging
was conducted using a 0.05 s integration time, 10 mW laser power,
and a 5 × 5 μm2 step size (XY).3D SERS mapping. HDF cell distribution after 25 DIV, as viewed
with brightfield microscopy (A) and 3D SERS imaging (B). (A) HDF cells
are false-colored in gray blue, the cell-filled imaging window (black
square box) was subsequently mapped by SERS imaging. (B) SERS mapping
of HDF cells, prelabeled with AuNS-1NAT (magenta), AuNS-2NAT (green),
and AuNS-MBT (red). Cells containing all three SERS tags are displayed
in cyan. SERS maps were analyzed using True Component Analysis (Witec).
SERS imaging was conducted using 0.05 s integration, 30 mW laser power,
and 5 × 5 × 5 μm3 step size (XYZ).With regards to the targeted imaging spatial resolution
and time
required to achieve it, it should be noted that 3D cell imaging was
carried out using cubic voxels, measuring 5 μm3 in
XYZ. Therefore, to complete an image measuring 600 × 600 ×
100 μm3 (in XYZ) with this level of imaging resolution
(5 μm3), 12 h were needed. Although, admittedly,
this could be considered as a long time, we rely on the absence of
photoinduced cytotoxicity and probe bleaching during SERS (opposite
to fluorescence) imaging. As an additional evidence, we conducted
a bleaching experiment in which HDF cells, labeled with either SERS
tags or AF488-labeled actin fluorophores, were imaged by SERS and
fluorescence microscopy, respectively. The cells were grown on a scaffold
that was itself labeled with either AuNS-MBT (for SERS imaging) or
poly[(mphenylenevinylene)-alt-(2,5-dihexyloxy-p-phenylenevinylene]
light-emitting polymer (for fluorescence imaging). For the SERS bleaching
test, we conducted a mock imaging experiment in which four sequential
2D images over an area of 250 × 250 μm2, with
5 μm resolution (XY), were conducted using a 785 nm laser–in
resonance with both SERS tags (each of these runs lasted for 1 h).
For the fluorescence bleaching test, an image size of 354 × 354
μm2 was selected, and seven sequential bleaching/imaging
cycles were undertaken using 405 nm laser excitation, in resonance
for the scaffold fluorophore. The pinhole was opened to 24 μm,
and a 60 s bleaching cycle followed by imaging acquisition was used.
Intentionally, only 405 nm irradiation was used to excite the scaffold
fluorophore, so that the green fluorescence from AF488-actin labeled
cells would remain unaffected and provide an internal control. The
results are shown in Figure . No changes were revealed in SERS mapping over time as it
relates to the signal intensity of either BPT (from the scaffold)
or 2NAT (from cells). Oppositely, a significant decrease was recorded
in the fluorescence intensity of the blue channel (scaffold) while
the green fluorescence remained unchanged. These results confirm that,
unlike fluorescence microscopy, SERS can be used for repetitive measurements
without any changes in signal intensity due to photon-induced chemical
changes in the Raman molecules. It should be noted that, in all cases,
the BPT signal was recorded at the well-defined area of the scaffold
and showed negligible fluctuations over time. This result is in agreement
with a high stability of AuNS-BPT SERS tags inside the PLGA scaffold
structure, with no leaching of SERS tags and no Raman molecules leaving
the NP surface, which are essential aspects to be considered when
long irradiation times are required.
Figure 7
Comparison of SERS and fluorescence stability
upon sequential bleaching.
(A) Bleaching test using cell-internalized AuNR-2NAT and AuNS-BPT
NPs inside PLGA scaffolds. For SERS imaging, the selected area (250
× 250 μm2) was repeatedly illuminated for 1
h four times using a 785 nm laser, resonant with all SERS tags used.
For fluorescence imaging, a different area (354 × 354 μm2) was irradiated (in scanning mode) for 60 s seven times using
a 405 nm laser. Images show the first and last illumination SERS maps,
as well as the corresponding average spectra. Zoomed spectra highlight
one of the main representative Raman peaks for each label. A 50×
(NA 0.5) long working distance objective was used. Scale bars: 50
μm. (B) Fluorescence imaging bleaching test. Images in the left
panel show the blue and green channels overlaid with corresponding
optical images, for the first and last illuminations. Scale bars:
50 μm. The graphs to the right show the evolution of fluorescence
intensity for both fluorophores.
Comparison of SERS and fluorescence stability
upon sequential bleaching.
(A) Bleaching test using cell-internalized AuNR-2NAT and AuNS-BPT
NPs inside PLGA scaffolds. For SERS imaging, the selected area (250
× 250 μm2) was repeatedly illuminated for 1
h four times using a 785 nm laser, resonant with all SERS tags used.
For fluorescence imaging, a different area (354 × 354 μm2) was irradiated (in scanning mode) for 60 s seven times using
a 405 nm laser. Images show the first and last illumination SERS maps,
as well as the corresponding average spectra. Zoomed spectra highlight
one of the main representative Raman peaks for each label. A 50×
(NA 0.5) long working distance objective was used. Scale bars: 50
μm. (B) Fluorescence imaging bleaching test. Images in the left
panel show the blue and green channels overlaid with corresponding
optical images, for the first and last illuminations. Scale bars:
50 μm. The graphs to the right show the evolution of fluorescence
intensity for both fluorophores.
Using Other NP Shapes for SERS Imaging
While in this
study we focused on the use of AuNS, it should be noted that AuNPs
with different morphologies can also be used, as long as their LSPR
is in resonance with the Raman excitation wavelength used for imaging.
Gold nanorods (AuNRs) are an obvious example; they feature a longitudinal
LSPR that can be tuned into the NIR during synthesis. We conducted
a supplementary study in which two SERS tags, composed of AuNR-2NAT
and AuNS-MBT both coated with PMA and PA, were used to label HDF cells.
The absorbance spectrum of AuNR, after functionalization with 2NAT
and surface coating with PMA and PA, shows a main peak at 780 nm (Figure S10A). Incubation of HDF cells with AuNR-2NAT
and AuNS-MBT resulted in SERS tag endocytosis, as verified using both
TEM and SERS microscopy (Figure S11). Therefore,
we monitored HDF cell growth with time (Figure S12) and obtained a 3D reconstruction, which confirmed that
two different NP morphologies with two different Raman molecules can
indeed be used for cell imaging in 3D (Figure ). Apart from the additional flexibility
regarding the synthesis of SERS tags using NRs and NSs, the use of
NPs with significantly different morphologies may additionally provide
a method to unmistakably distinguish them in TEM.
Figure 8
(A) Optical image of
the area selected for full 3D SERS mapping.
(B, C) Four different layers from different z-stack measurements,
on which pixels containing AuNS-BPT (blue), AuNR-2NAT (green), and
AuNS-MBT (red) were highlighted. AuNS-BPT corresponds to signal from
the scaffold, whereas AuNR-2NAT and AuNS-MBT corresponds to a signal
from HDF cells. (D) Individual and merged 3D reconstructions of (C).
A 50× (NA 0.5) long working distance objective was used with
a 1s integration time, at 29.55 mW laser power, and a step size of
8 × 8 × 20 μm3 (XYZ). Scale bars: 200 μm.
(A) Optical image of
the area selected for full 3D SERS mapping.
(B, C) Four different layers from different z-stack measurements,
on which pixels containing AuNS-BPT (blue), AuNR-2NAT (green), and
AuNS-MBT (red) were highlighted. AuNS-BPT corresponds to signal from
the scaffold, whereas AuNR-2NAT and AuNS-MBT corresponds to a signal
from HDF cells. (D) Individual and merged 3D reconstructions of (C).
A 50× (NA 0.5) long working distance objective was used with
a 1s integration time, at 29.55 mW laser power, and a step size of
8 × 8 × 20 μm3 (XYZ). Scale bars: 200 μm.
Conclusions
By use
of the complementary confocal imaging techniques SERS and
fluorescence microscopy, we have been able to follow the proliferation
and migration of human fibroblasts in 3D and to determine appropriate
imaging parameters to better characterize such systems in live conditions
(i.e., not chemically fixed). We fabricated hybrid scaffolds, labeled
with SERS tags and/or fluorophores, that allow the proliferation of
fibroblasts in 3D, reaching thicknesses of ca. 100 μm in a suspended
matrix. Fibroblasts were selected because they can be easily labeled
with SERS tags and form an interwoven 3D film whose growth can be
supported by the multimodal labeled scaffold, which in turn provides
a reference framework for imaging. As expected, prelabeling of fibroblasts
with SERS tags allowed us to follow their growth in 2D with relative
ease, achieving a relatively high level of resolution along the XY
dimension. However, distinguishing cells with sufficient resolution
along the Z-axis required optimization of the imaging
system, mainly increasing the laser excitation power and slowing down
the integration time. By using a high-resolution Raman confocal microscope,
we improved the cell imaging resolution along the Z-axis to 5 μm, thereby obtaining a more realistic view of the
true cell density within the scaffold. In addition, our results showed
that continuous irradiation during SERS imaging had little-to-no effect
on the acquired signal, whereas similar experiments using fluorescence
confocal microscopy caused significant photobleaching. This is especially
important if we consider the long irradiation times (in the scale
of many hours for large samples) required to achieve high resolution
3D SERS maps. For the data analysis, we took advantage of the True
Component Analysis tool, a postprocessing function provided in the
Witec Raman microscope software, or MLRA[38] analysis when using our Renishaw Raman microscope. Both methods
are suitable for dealing with large data sets with multiple components,
allowing their separation in a fast and convenient way. This is particularly
important when large 3D areas are to be scanned and when working with
multiple SERS tags. While in this study we only labeled a single cell
type (HDF), but with three SERS tags, the lessons learned are certainly
applicable to imaging of multiple cell types, with even more SERS
tags. We have previously shown that the 2D imaging of up to five different
cell types, labeled with five different SERS tags, was possible, albeit
with poor resolution.[34] We were able to
perform the current work with an upgraded Raman microscope with confocal
imaging capability, thus significantly improving the spatial resolution.
We propose that all these improvements contribute to the characterization
of live cellular 3D structures and will help establish new protocols
to understand cell behavior in real time.
Experimental Section
Chemicals
Tetrachloroauric
acid trihydrate (HAuCl4·3H2O, ≥
99%), citric acid (≥99.5%),
sodium borohydride (NaBH4, 99%), l-ascorbic acid
(≥99%), silver nitrate (AgNO3, ≥ 99%), hexadecyltrimethylammonium
bromide (CTAB, ≥ 99%), O-[2-(3-mercaptopropionylamino)ethyl]-O′-methylpolyethylene glycol (PEG, MW 5000 g mol–1), 2-naphthalenethiol (2NAT, 99%), 4-methylbenzenethiol
(MBT, 98%), biphenyl-4-thiol (BPT, 97%), poly-l-arginine
hydrochloride (PA, Aldrich no. 26982-20-7 > 70 000 Da),
poly(isobutylene-alt-maleic anhydride) (average MW
∼ 6000 g mol–1), dodecylamine (98%),1-decanol,
tetrahydrofuran (THF,
99.85%, extra dry), chloroform (CHCl3, ≥ 99.8%),
and sodium hydroxide (NaOH, > 97%) were purchased from Sigma-Aldrich.
Hydrochloric acid solution (37 wt%) was purchased from Fisher Chemical.
All chemicals were used without further purification. Milli-Q water
(resistivity 18.2 MΩ cm at 25 °C) was used in all experiments.
All glassware was washed with aqua regia, rinsed with Milli-Q water,
and dried prior to use.
AuNP Synthesis
AuNSs were prepared
following a seed-mediated
growth method.[40] The seed solution was
prepared by adding 5 mL of 34 mM citrate solution to 95 mL of boiling
0.5 mM HAuCl4 solution under vigorous stirring. After 15
min of boiling, the solution was cooled down and stored at 4 °C.
For the synthesis of 70 nm AuNSs with LSPR maximum at 780 nm, 2.5
mL of the citrate-stabilized seed solution was added to 50 mL of 0.25
mM HAuCl4 solution (with 50 μL of 1 M HCl) in a 100
mL glass vial at room temperature under moderate stirring. Quickly,
500 μL of 2 mM AgNO3 and 250 μL of 100 mM ascorbic
acid were added simultaneously. The solution rapidly turns from light
red to greenish, indicating AuNSs formation. The resulting solution
was mixed with 410 μL of 0.1 mM PEG-SH and stirred for 15 min,
washed by centrifugation at 1190g, for 25 min, at
10 °C, and redispersed in water. AuNRs with LSPR maximum at 750
nm were prepared by a seeded-growth method. In brief, 1–2 nm
gold seeds were grown in the presence of CTAB to form small anisotropic
seeds (21 nm length, 8 nm width). These seeds provided the base for
the synthesis of larger NRs with LSPR maximum at 750 nm. The exact
protocol has been reported by González-Rubio et al.[45]
AuNP RaR Labeling
Both AuNSs and
AuNRs were labeled
with Raman active molecules following a previously developed method,[34] including wrapping with an amphiphilic polymer
to make them biocompatible and coating with poly-l-arginine
hydrochloride to make them positively charged and thereby enhance
cell uptake, as previously reported.[30]
NP Characterization
TEM images were collected with
a JEOL JEM-1400PLUS transmission electron microscope operating at
120 kV, using carbon-coated 400 square mesh copper grids. UV–vis
optical extinction spectra were recorded using an Agilent 8453 UV–vis
diode array spectrophotometer.
Tessellated Scaffold Fabrication
Using a 50–75
kDaA PLGA (no. 430471 Aldrich) and a solvent 97:3 volume ratio of
CHCl3 and DMF, 10 μm diameter fibers which can be
printed forming 3D scaffolds can be obtained. Briefly, a chloroform
dispersion of AuNS-BPT was subsequently mixed with 50–75 kDaA
PLGA at a 30 wt/vol % solution, also in chloroform. Different fluorescently
labeled polymers dissolved in CHCl3 were also included
in the mixture to allow the fluorescence microscopy of the scaffolds.
Specifically, poly[(mphenylenevinylene)-alt-(2,5-dihexyloxy-p-phenylenevinylene]
with excitation/emission wavelengths at λex: 404
nm/ λem: 451 nm, resulting in blue fluorescence;
or poly[tris(2,5-bis(hexyloxy)-1,4-phenylenevinylene)-alt-(1,3-phenylenevinylene)] with excitation/emission wavelengths at
λex: 448 nm; λem: 518 nm, resulting
in green fluorescence were used. Then the corresponding DMF amount
was added to the solution. The mentioned final solvent mixture correspond
to ca. 93:7 CHCl3:DMF volume ratio.[16] The exact composition mixtures are detailed below:Composition of monocompartmental
scaffolds: 0.15 g of PLGA in 55.45 μL of CHCl3 was mixed
with 54.55 μL of ((poly[(mphenylenevinylene)-alt-(2,5-dihexyloxy-p-phenylenevinylene) blue polymer (1 mg mL–1 diluted in CHCl3) and 350 μL of SERS tag (AuNS-BPT)
([Au0] = 3 × 10–3 M) in CHCl3 and 35 μL of DMF.Composition of bicompartmental scaffolds: In the compartment
(I) 0.15 g of PLGA in 55.45 μL of CHCl3 was mixed
with 54.55 μL of blue polymer (1 mg mL–1 diluted
in CHCl3) and 350 μL of
SERS tag (AuNS-4BPT) ([Au0] = 3 × 10–3 M) in CHCl3 and 35 μL of DMF. Compartment (II)
was prepared by mixing 0.15 g of PLGA in 55.45 μL of CHCl3 with 54.55 μL of green polymer (1 mg mL–1 diluted in CHCl3) and 350 μL of SERS tag (AuNS-4BPT)
([Au0] = 3 × 10–3 M) in CHCl3 and 35 μL of DMF.Then
for the fabrication of the scaffolds, the solution
mixtures with or without AuNS-BPT and the two different fluorophores
(one for each compartment in the case of bicompartmental scaffolds)
were loaded in individual syringes and flown in a laminar regime through
a 20-gauge needle for monocompartmental fiber fabrication or parallel
mounted metallic 20-gauge needles for bicompartmental fiber ones,
at 40 μL h–1, with an applied voltage of 15
kV. As the fluid jet descends to the ground electrode, it passes through
a copper ring at 10 kV. The jetted fibers was collected on the ground
electrode, a stainless-steel plate, which is translated through X–Y
coordinates by computer-controlled motions to stack the depositing
fiber onto itself in a desired pattern.
Confocal Imaging of PLGA
Scaffolds
NP-loaded scaffolds
were sandwiched between two Quartz glass coverslips with the use of
mounting media (Dako). This ensured that the scaffold did not move
or dry out. All confocal images were taken using a Zeiss LSM 880 confocal
laser scanning microscope equipped with 405 nm (blue fluorophore excitation)
and 488 nm (green fluorophore excitation), and Plan-Apochromat 10×
objective (0.45 N.A.) and Plan-Apochromat 20× objective (0.8
N.A.) objectives. A postimaging 3-pixel median filter was generally
applied to remove noise pixels. In the case of 3D characterization
of scaffolds, Z-stacks of approximately 70 μm in thickness were
obtained and postimaging 3-pixel median filter applied prior to 3D
rendering, to obtain images from different angles. Finally, Z-stacks
of higher resolution were obtained by imaging scaffolds composed solely
of blue fluorophore, again with the same 20× objective but with
increased pixel resolution and Z-depth. In this case, we obtained
Z-stacks of approximately 200 μm in thickness with XYZ pixel
resolution of 0.3 × 0.3 × 0.5 μm3.
NP-Incubation
with Cells for Growth on PLGA Scaffolds
Human dermal fibroblasts
(HDF) were purchased from Invitrogen and
grown in DMEM supplemented with 10% fetal bovine serum (FBS) and 1%
penicillin-streptomycin (PS) (herein termed complete DMEM, cDMEM).
To expose cells to NPs for uptake, HDF were seeded in 24 plates (3
× 104 cells per well) and allowed to adhere before
replacing media with a solution of NPs diluted in cDMEM. NPs were
added at a final concentration of 0.1 mM. After 24 h, nonuptaken NPs
were removed by washing the adhered HDF cell monolayer, and the adhered
cells were detached using trypsin. After recounting, cells were added
to the scaffold as described below.
Quantification of SERS
Tag Uptake and Viability
SERS
tag uptake by HDF cells was characterized via ICP-MS and via two-photon
confocal microscopy. For inductively coupled plasma-mass spectrometry
(ICP-MS) measurements, trypsinized HDF cells were digested using aqua
regia and analyzed using standard protocols. For two-photon microscopy
and PI staining, GFP-expressing HDF cells were seeded in optically
transparent 96-well plates (Ibidi) and exposed to SERS tags for 24
h. Samples were washed to remove nonendocytosed NPs and imaged using
two-photon confocal microscopy with a 780 nm laser excitation with
a BP emission filter of 570–610 nm (880 Zeiss Confocal microscope).
A three-pixel mean filter was applied for postprocessing. For PI staining,
cells were stained with 5 μg/mL PI for 20 min, followed by detection
of PI expressing cells (dead) using a Cell Observer Zeiss Microscope.
Scaffold Preparation for In Vitro Studies
A modified previously reported protocol[16] for preparation of NP-loaded scaffolds was used for imaging experiments.
Scaffolds were sandwiched between two metallic windows (0.5 ×
1 cm2) and placed in a 2 mL sterile Eppendorf tube. 50
μL of human fibronectin (50 μg) was placed on top of the
scaffold which lay suspended in the center of the Eppendorf tube.
The fibronectin was allowed to adhere to the scaffold fibers at 37
°C for 30 min. HDF cells, previously incubated with NPs as described
above, were washed, trypsinized, counted, and readjusted to a concentration
of 4–8 × 105 cells mL–1.
A concentrated drop of SERS tag-incubated cells (100 μL) was
then added to the scaffold and allowed to incubate for approximately
30 min before transferring the scaffold to a 24-well plate and adding
cDMEM. Either mixed SERS tag-cell populations or single SERS tag populations
were used. The scaffolds were stored for approximately 2 weeks to
allow cells to form a 3D mesh around the scaffold. cDMEM was carefully
replaced every 2–3 days without disturbing the scaffold.
Multimodal Cell Imaging
For live SERS imaging of the
scaffold, the metal frames were picked up with tweezers, and the whole
component (scaffold and frames) was transferred to a quartz slide
with an adhered in-house 3D printed well,[30] which allowed long-term cell growth and insertion of an immersion
objective without disturbing the cells. The metal holder lays flat
on the base allowing upright and inverted imaging. For live fluorescence
imaging, HDF cells were transfected to express eGFP using a multiplicity
of infection (MOI) of 10 and hygromycin for selection, allowing imaging
using 488 nm excitation. For fixed cell imaging, cell-containing scaffolds
were fixed in situ with the metal holder in the 24-well
plate. To do so, a 4% solution of formaldehyde was used at RT for
20 min, followed by washing with PBS. Immunocytochemical staining
using antifibronectin (F3648 clone) with AF633 labeled antirabbit
secondary antibody was conducted to image fibronectin.
SERS Imaging
For high resolution SERS imaging of AuNS-1NAT,
AuNS-2NAT, and AuNS-MBT NPs incubated with HDF cells, measurements
were performed with a confocal Raman microscope (Alpha300 R –
Confocal Raman Imaging Microscope, Witec) equipped with 1024 ×
512 CCD detectors. A 785 nm laser excitation source (maximum output
79 mW) and a 300 l/mm diffraction grating were used. Measurements
were recorded in static mode (center of scattered wavenumber 1450
cm–1) using a 20× immersion long working distance
objective (numerical aperture, NA = 0.5; Zeiss, Jena, Germany). The
integration time and laser power varied between 0.02–0.05 s
and 5–30 mW, respectively. Exact values are given in the legend
of each figure. SERS data were analyzed using True Component Analysis
provided by the Witec microscope software. This is a nonopen access
script which is described by Witec as “The unique post-processing
function for confocal Raman imaging measurements automatically establishes
the number of components in a sample, locates them in the image, and
differentiates their individual spectra. It delivers meaningful results
in a fast and convenient way.”SERS measurements of HDF
cells incubated with AuNR-2NAT and AuNS-MBT SERS tags were performed
with a confocal Raman microscope (Renishaw inVia) equipped with 1024
× 512 CCD detectors, using a 785 nm laser excitation source (maximum
output 270 mW) and a 1200 l/mm diffraction grating. SERS maps were
recorded in static mode (center of scattered wavenumber 1450 cm–1). For overtime imaging, a 40× immersion objective
(numerical aperture, NA = 0.8; Nikon, Tokyo, Japan) with 0.8s integration
time, at 3.1 mW laser power was used. The map of one selected area
(325 × 225 μm) was acquired with a resolution of 5 μm
in X and Y, and required approximately 1 h and 10 min to be completed.
For 3D imaging, a 50× long distance objective (N.A. = 0.5; Leica
Microsystems, Wetzlar, Germany), with 1s integration time, at 29.55
mW laser power was used. The map of one selected area (584 ×
584 × 60 μm) was acquired with a resolution of 8 μm
in X and Y, and 20 μm in Z, and the total four layers required
approximately 2 h and 30 min to be completed. SERS data were analyzed
using the MLRA method, as described in previous work.SERS reference
spectra were collected from a 5 μL drop of
the SERS tags ([Au]0 = 0.5 mM) on top of a quartz slide.
We used a 50× long working distance objective (NA = 0.5; Leica
Microsystems, Wetzlar, Germany) in expanded scan mode with an integration
time of 10 s, at a laser power of 1.11 mW and five accumulative scans.
SERS data were analyzed using Multiple Linear Regression Analysis
(MLRA) (regress function of Matlab).[38]
SERS Bleaching Test Measurements
Maps of a fixed area–different
from that tested by fluorescence–were acquired four times with
a resolution of 5 μm in X and Y using a 50× long distance
objective (N.A. = 0.5; Leica Microsystems, Wetzlar, Germany), a full-1200
lines mm–1 diffraction grating and a 785 nm HeNe
laser. Each point was exposed to 1.11 mW of laser power for 1s. Each
map has a dimension of 250 × 250 μm and took approximately
1 h to complete. Reference spectra: Raman measurements of colloidal
SERS tags in solution were performed with a 50× long distance
objective (N.A. = 0.5; Leica Microsystems, Wetzlar, Germany), a full-1200
lines mm–1 diffraction grating and a 785 nm HeNe
laser. The volume of the sample was exposed for 10 s in total during
scanning; the PLGA Raman spectrum was obtained by measuring a scaffold
without SERS tags, with a 50× long distance objective (N.A. =
0.5; Leica Microsystems, Wetzlar, Germany), a full-1200 l/mm diffraction
grating and a 785 nm HeNe laser. SERS data were analyzed using the
MLRA method, as described in previous work.[38] The average spectra are represented in Figure .
Fluorescence Scaffold Bleaching Experiments
To determine
the stability of fluorescence signal in the scaffolds after repetitive
confocal imaging, we devised an experimental setup in which the scaffold
and cells were irradiated with a defined laser wavelength and the
mean intensity of scaffold, cellular, and background regions were
analyzed using regions of interest (ROI). Importantly, we did not
change the laser power or pinhole for bleaching and imaging, as we
were interested in seeing the effect that repetitive imaging has on
the fluorescence properties. In detail, HDF cells were grown on scaffolds
containing blue fluorophore, using the method described above to seed
cells. Cells were fixed with formaldehyde and then stained with Actin
488 ReadyProbes fluorophore (Invitrogen). The sample was sandwiched
between two quartz coverslips using mounting media to provide physical
and chemical stability. To conduct the experiment, the sample was
alternatively irradiated with a 405 nm laser for 60 s, and then imaged
using the same 405 nm laser and a 488 nm laser, thereby exciting the
fluorophores in the scaffold and in the cells, respectively. A Plan-Apochromat
20× objective (0.8 N.A.) was used throughout, and the pinhole
was set to 24 μm for both bleaching and imaging. Images were
transferred to ImageJ and, by working with the blue and the green
channels separately, ROIs were drawn to represent the scaffold (blue
channel), the cells (green channel), and their corresponding backgrounds.
In the case of the ROIs representing signal from the blue channel,
they were 10 × 10 μm2. In the case of the ROIs
representing signal from the green channel, they measured 200 ×
100 μm, to capture a greener signal (which comes from the actin
cytoskeleton and is therefore sparser). Using ImageJ, the Raw Integrated
Density of each ROI was calculated (that is, the sum of the pixel
intensities in that ROI), and the average of each area was plotted.
Images for visual understanding were postprocessed with a three-pixel
median filter for clarity.
Authors: Guillermo González-Rubio; Vished Kumar; Pablo Llombart; Pablo Díaz-Núñez; Eva Bladt; Thomas Altantzis; Sara Bals; Ovidio Peña-Rodríguez; Eva G Noya; Luis G MacDowell; Andrés Guerrero-Martínez; Luis M Liz-Marzán Journal: ACS Nano Date: 2019-04-08 Impact factor: 15.881
Authors: Jos L Campbell; Elliott D SoRelle; Ohad Ilovich; Orly Liba; Michelle L James; Zhen Qiu; Valerie Perez; Carmel T Chan; Adam de la Zerda; Cristina Zavaleta Journal: Biomaterials Date: 2017-04-28 Impact factor: 12.479
Authors: Seongjun Moon; Michael S Jones; Eunbyeol Seo; Jaeyu Lee; Lucas Lahann; Jacob H Jordahl; Kyung Jin Lee; Joerg Lahann Journal: Sci Adv Date: 2021-04-14 Impact factor: 14.136
Authors: Ana B Serrano-Montes; Dorleta Jimenez de Aberasturi; Judith Langer; Juan J Giner-Casares; Leonardo Scarabelli; Ada Herrero; Luis M Liz-Marzán Journal: Langmuir Date: 2015-08-14 Impact factor: 3.882
Authors: Gail A Vinnacombe-Willson; Ylli Conti; Steven J Jonas; Paul S Weiss; Agustín Mihi; Leonardo Scarabelli Journal: Adv Mater Date: 2022-08-15 Impact factor: 32.086
Authors: Elisa Lenzi; Malou Henriksen-Lacey; Beatriz Molina; Judith Langer; Carlos D L de Albuquerque; Dorleta Jimenez de Aberasturi; Luis M Liz-Marzán Journal: ACS Sens Date: 2022-06-07 Impact factor: 9.618