A λ/30 Resolution Laser Speckle Pattern Biosensor
for Dynamic Studies on Live Samples
Maria Fernanda Avila1 , Shigeki Yamaguchi2 , Hideho Uchiyama3 , Ruggero Micheletto4
Graduate School of Nanobiosciences, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama 236-0027, JAPAN1

maria-o_o@i.softbank.jp
i080704b@yokohama-cu.ac.jp
3hideho@yokohama-cu.ac.jp
4ruggero@yokohama-cu.ac.jp

2

Abstract—Nowadays there is a big interest in the researchof cell behaviour in different sciences, like biology, physics,and medicine. For this reason, many interdisciplinary research
projects have been developed in many countries. The main goalof the realization of the proposed biosensor is to obtain a superhigh resolution optical detection of nano-scaled movements of livecells. We used a very straightforward principle, the interferenceof laser light with the membrane of the cells under investigation.
The laser light is focused on the target cell, while observing thepicture through an optical microscope. The laser light creates aninterference image (speckle pattern) that is projected on a screenand monitored by a CCD camera. This interference pattern isperturbed by any movement or displacement of the cells, andthis interaction is recorded in real time by the CCD. While thecontrast in standard optical microscopy is very low, the advantageof this approach is that the coherence of laser light produce
constructive or destructive patterns that can be detected withvery high signal-to-noise ratio. The displacement resolution wecan achieve is better than λ/30, that is in the order of 20nm.

We used in previous studies a SNOM system [3], [4] todetect nano-scaled movements of a cell. SNOM is a purelynon-invasive, non-contact method and therefore the natural life
activity of the sample is unperturbed. However this instrument
is very complex, expensive, and difficult to use. This was themain reason we decided to develop this research by designinga new kind of microscope, with similar resolving ability, but
simpler to use and much more economical to realize.

I. I NTRODUCTION
Sub micron studies of cell ultra structure have been performed using scanning and transmission electron microscope(SEM, TEM) or Atomic Force Microscope (AFM). However,live cells cannot be examined using SEM and TEM methods
because these systems require cell fixation and observation
under vacuum, and images of live cells obtained using AFM
systems may be compromised by the direct contact between
the cantilever and sample deforming soft tissues altering thetests [1].
We want to investigate the dynamics of cytoskeleton activities in order to evaluate and estimate the performance ofa speckle pattern analysis. The cytoskeleton of eukaryotic
cells is fundamental to the spatial organization of the cellcomponents. Cytoskeletal systems are dynamic and adaptable, they can change or persist, according to need. Cellularstructures must be assembled, disassembled and reorganized
during the life of the cell; thus the individual macromolecularcomponents that make up these structures are in a constantactivity. Since cells are small and complex, it is hard to detect
their structure and movements, and what we can learn about
cells dynamics depends on the tools available, and on theadoption of different techniques[2].

Fig. 1.
The speckle pattern variation in function of time: two picturesof the screen (device number 7 in figure 3) taken at about one secondinterval. The circled area shows a variation of intensity easily detectable,
corresponding to about 500nm spatial displacement, a value hardly observablewith conventional microscopy.

The system we have constructed uses a low power laser
beam to interfere with the sample and produce an interference
image (speckle pattern, fig. 1) that is recorded and analysed
for dynamical activity. A speckle pattern can be analysedby means of several mathematical and statistical tools andprovide numeric or visual information on its magnitude.
Because the number of scattering centres is very high, thecollective phenomenon is hard to interpret and the individual
contributions to the final result may be difficult to be inferred.
The measurements that are obtained by means of the analysis
tools display the activity level as a sum of the contributionsof phenomena of the scattered light as well as any otherexisting phenomena (time variations of the refractive index
of the sample, etc). A biological sample, for example, that isa material that contains a huge number of mobile scattering
centres, displays refractive index variations in the materials
that compose it with power changes as well as many othereffects, thus increasing the complexity in the identification andisolation of these phenomena. Then, the complete interpretation of the activity of a sample, by means of dynamic speckle,
presents huge challenges[5]A. Cell preparation method and characteristics
To test the characteristics of our Speckle Pattern Biosensor(SPB) we used P19CL6 cells, an embryonal carcinoma (ECcell) derived from C3H mouse [6]. This cell line (Resource
No. RBRC-RCB2318) supplied by Riken Bioresource Center(Tsukuba, Japan).
Cells were cultured at 37 ◦ C in a humidified atmosphereof 95% air and 5% CO2 in 0.1% gelatin-coated 60mm dish(TPP Inc., Switzerland) with 10 mL of culture medium madeup of MEM-alpha supplemented with 10% fetal bovine serum,
100 U/mL penicillin and 100 microgram/mL streptomycin (allfrom GIBCO, Invitrogen Inc.). In passages, cells were washedwith phosphate-buffered saline (PBS), dissociated with 0.25%
Trypsin-EDTA (GIBCO, Invitrogen Inc.), suspended in fresh
medium, split 1:20, and inoculated to a fresh dish with 10mL of fresh medium at 2 days intervals. In differentiation
experiments, 1% (v/v) dimethyl sulfoxide (DMSO, Infinitely
Pure Grade, No.045-24511, Wako Pure Chemical Industries,Osaka, Japan) was added to the culture medium and the cells
were continuously cultured and passaged in this DMSO-added
medium. Usually, 7 to 10 days later several spots of beatingcell clumps of various sizes appeared, and the beating could
last for one to two weeks.

corresponds to a maximum displacement of about 500nm (0.5µm) and this is what we are going to measure to validate theresolving power of our biosensor instrument.
II. T HE INSTRUMENTAL APPARATUS AND CALIBRATIONTESTS

Figure 3 shows a scheme of the experimental apparatus.
A standard optical microscope (Olympus BX51-W1) is fittedwith a solid state Laser (670nm) that focus on the sample.
Cells are placed on a transparent Petri dish, so that the interference pattern is transmitted and reflected on a screen. Any
perturbation of the interference pattern due to displacementsof the cytoskeleton of the cell is recorded in real time by
the CCD camera on a solid state memory. The data are thenanalysed off line and a time profile of the variable domains ofinterference is generated (see figure 4 for an example).

Fig. 3. Layout of the apparatus used. 1. Biosample, 2. Piezoactuator, 3.
Function Generator, 4. Red Laser, 5. Focus Lens, 6. Microscope objective, 7.
White screen, 8. Video camera, 9. Lamp

The instrument was firstly calibrated for sensitivity using
a piezo actuator to give a known displacement to a blanksample and observing the instrument response as speckle
pattern changes. The driving stimulus was a 400Hz signal.
The intensity was changed and the instrument response wasused to determine the average sensitivity (see table I). We
could demonstrate a sensitivity of 0.7 nm/mV, a value of thesame order of magnitude as our previous work with a SNOM
probe[7], [8], but obtained in this case with a much simpler
and low cost instrument.
TABLE IC ALIBRATION DATA S HOW A S ENSITIVITY OF ABOUT 0.7 mV/nm
Fig. 2.
An optical microscope picture of the P19CL6 cells that will
differentiate to cardiomyocytes

P19 cell and its derivatives are embryonal carcinoma cells(EC cells) and they maintain pluripotency, which means thatthey can differentiate into various cell types according to thestimulus they receive. This time the treatment was DMSO,
known to stimulate them to differentiate into cardiomyocytes.
P19CL6 cells have higher differentiation tendencies into cardiomyocytes than the original P19 cells. Adding DMSO at 1%(v/v) to the medium and the cells are continuously cultured inthis medium, the cells will differentiate into cardiomyocytes
in about one week and start beating (see fig. 2). The beating

SignalVoltage [V]8101214161820

Response
Vpp [mV]
2428.8
29.8
33.6
34.0
3232.4SignalVoltage [V]1247891013151720

Response
Vpp [mV]
17.8
17.4
19.6
23.6
22.8
30.2
24.2
28.4
24.6
28.6
33.8

III. R ESULTS ON C ELL’ S BEHAVIOUR
The tests were carried out on samples in condition of strong
and live beatings. Sample was placed on the transparent Petridish and with the aid of the optical microscope an aggregate ofcardiomyocytes is chosen as the target of the investigation (asin fig. 2). The laser is focussed on a single cell of the group.
The corresponding speckle patter is monitored for changes
initially optically. As shown in figure 1 there are domains
in the pattern that show a highly recognizable variation.
These variations are barely visible or not at all noticeable
in the standard optical microscope. This fact motivated us toconstruct a device able to study the speckle pattern and record
all its variations with high sensitivity and in real time.
Initially, with the aid of a single photodetector (a high sensitive photodiode) we recorded the intensity on a confined regionof the interference pattern. If the cell is beating the spatial
displacement associated alters locally the speckle structure andthe beating profile is revealed as a variation of potential in thedetector circuit.

Fig. 4. The luminosity time profile of confined area of the speckle patterndetected by a single photodiode detector. The beating characteristics of cardiomyocytes cells are recorded in high contrast and are clearly recognizable.
Time scale is in frames, 30 frames correspond to about 1 second.

In figure fig. 4 we plot the raw data detected by the photodiode. The plot clearly shows the oscillation of the luminosityof the interference, revealing the rhythmic movements of thecardiomyocytes cells. This beating of the signal, could be due
to many causes, as rearrangement of sub-cellular components.
Our method does not reveal directly the original cause of
the optical variation. However, we can validate this signal as
associated to the cell wall vibration, because of its similarity
in frequency and temporal profile, to well known previous
experiment with cardiomyocytes [3], [4].
To produce an universal system able to investigate a wider
area of the biosample, we replaced the single photodiodedevice with a CCD camera sensor. This device collects simultaneously a much wider area of interference, allowing theresearcher to localize interference pattern of higher contrast.
The device records in this case complete moving pictures in
AVI file format, that can be stored on solid state memories forlater analysis.
The files detected by the CCD camera, are complex data
structures difficult to handle; for this reason we developed abespoke software able to isolate the desired pixel in the fileand plot that pixel intensity against time (frame number).
The data obtained in this way can be investigated pixel by
pixel for a full mathematical analysis. The cardiomyocytes
beating characteristics can be evaluated not only from the pointof view of time profile, but also Fourier analysis, spectrum ofbeating, chaos and any other standard investigation typical in
the study of dynamical systems can be performed off line by
the instrument.
In the lower inset of figure 5 is shown the Fourier spectrumof the cardiomycytes corresponding to the dynamical profile
plotted above. A clearly recognizable peak at about 0.8 seconds is observed. General studies of drug dependence, culture
media composition, temperature, acoustic perturbation, fatigue
and other investigations are possible with this approach.

Fig. 5. In the upper panel the beating of cardiomyocyties is detected by
a CCD device with high contrast and high resolution. The single pixel plot
demonstrates a vertical minimum discrimination of about 20nm, in the orderof λ/30. This value is lower than that obtained with the blank calibration tests,
however well below the diffraction limit of optical microscopy. In the lower
panel is plotted the Fourier spectrum of the same beating profile showing indetail the frequency distribution of the cell beating with a noticeable peak of
about 0.8 Hz (greyed).

IV. C ONCLUSION
In this study we succeeded in detecting tiny mechanicaldisplacements of the cytoskeleton of P19 line stem cells
differentiated as cardiomyocytes. The beating of single cells
was isolated and observed with extremely high resolution
estimated in the order of 20 nm.
We are aware that the optical signal that we recorded, incommon with other optical microscopes, does not contain puremorphological information. Differences in optical coupling
could arise also from other phenomena in the cell body, suchas local modifications in the index of refraction and movement

of inner cellular structures. In the hypothesis that the morphological displacement plays the major role in our measurements,
we can estimate the vertical sensitivity of our recordings.
As we stated above, contractions of cardiac myocytes are
known to extend vertically approximately ∆Z=500 nm. We
could observe the beating by using a noncalibrated opticalsignal ranging between 0 and a maximum of 255 units (8 bitscaled images). The strongest peaks were observed to be about∆S=20 units from the base to the top of the peak. Consideringa minimum discrimination of δm =1 unit, the minimal cell
displacement detectable δo was calculated with the following
relation that resulted to be in the range of 20 nm, about λ/30.
∆Zδm = 20nm∆S
These values are intended to be only estimates, since they
assume linearity between signal and contraction displacement.
This linearity is not guaranteed, because of the complexity ofthe phenomena involved. However, it is a reasonable approximation of the order of magnitude of the vertical sensitivity of
our instrument, lower than that we obtained in the calibration
tests, but well below the diffraction limit of standard optical
microscopy.
The system we constructed uses a CCD camera that records
a wide area of the interference pattern, and a software thatisolates single pixel profiles for data treatment and analysis.
Fourier spectroscopy could demonstrate the beating characteristics of the cell line and observe variations in function of time,
fatigue, culture media composition and other environmental
parameters that condition the cell life activities. This device
will be optimized and we believe it will give a contribution
as a non-invasive biosensor for the dynamical study of nanoscaled movements of cells and in all live biosamples that haveeven tiny dynamical activity in general.
δo =ACKNOWLEDGMENT
We would like to thank prof. Robert Kanaly of Yokohama
City University for his keen suggestions and Alberto La
Barbera of A. Translation services for editing this manuscript.
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