Accepted Manuscript Nanoparticle Analysis of Cancer Cells by Light Transmission Spectroscopy N. Sun, J. Johnson, M.S. Stack, J. Szajko, C. Sander, R. Rebuyon, A. Deatsch, J. Easton, C.E. Tanner, S.T. Ruggiero PII: DOI: Reference:
S0003-2697(15)00240-7 http://dx.doi.org/10.1016/j.ab.2015.05.004 YABIO 12077
To appear in:
Analytical Biochemistry
Received Date: Revised Date: Accepted Date:
30 September 2014 21 April 2015 5 May 2015
Please cite this article as: N. Sun, J. Johnson, M.S. Stack, J. Szajko, C. Sander, R. Rebuyon, A. Deatsch, J. Easton, C.E. Tanner, S.T. Ruggiero, Nanoparticle Analysis of Cancer Cells by Light Transmission Spectroscopy, Analytical Biochemistry (2015), doi: http://dx.doi.org/10.1016/j.ab.2015.05.004
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Nanoparticle Analysis of Cancer Cells by Light Transmission Spectroscopy
N. Sun,1 J. Johnson,2 M. S. Stack,2 J. Szajko,3 C. Sander,1 R. Rebuyon,1 A. Deatsch,1 J. Easton,4 C. E. Tanner,1 and S. T. Ruggiero1 1
Department of Physics, University of Notre Dame, Notre Dame, IN 46556, USA
2
Department of Chemistry and Biochemistry, Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA 3
F Cubed LLC, South Bend, IN, USA 4
Ivy Tech, South Bend, IN, USA
Short Title: Cell analysis by Light Transmission Spectroscopy
Proofs should be mailed to: Prof. Steven T. Ruggiero Department of Physics 225 Nieuwland Hall University of Notre Dame Notre Dame, IN 46556 United States of America
Phone: 303-579-4410 Fax: 574-631-5952 e-mail: [email protected]
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Abstract We have measured the optical properties of cancer and normal whole cells and lysates using light transmission spectroscopy (LTS). LTS provides both the optical extinction coefficient in the wavelength range from 220 to 1100 nm and also (by spectral inversion using a Mie model) the particle distribution density in the size range from 1 to 3000 nm. Our present work involves whole cells and lysates of cultured human oral cells in liquid suspension. We have found systematic differences in the optical extinction between cancer and normal whole cells and lysates, which translate to different particle size distributions (PSDs) for these materials. Specifically, we find that cancer cells have distinctly lower concentrations of nanoparticles with diameters below 100 nm, and higher concentrations of particles with diameters from 100 to 1000 nm—results which hold for both whole cells and lysates. We have also found a power-law dependence of particle density with diameter over several orders of magnitude.
Introduction Optical techniques have contributed greatly to cancer diagnosis. To date, this has for the most part involved characterization at the tissue level. There clearly are significant differences in the optical properties of cancerous and healthy tissues [ 1 , 2 ], and diagnostic optical spectroscopy on the scale of individual organs has proven value for cancer management. Optical cancer diagnosis of the brain, breast, cervix, lung, stomach, colon, prostate, and skin have been employed, especially over the past two decades [3]. Recent use has also been made of multi-modal optical techniques for skin cancer [4].
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Light has also been used to investigate cancer at a finer scale. Most studies have involved
light
scattering,
which
has
been
applied
in
a
number
of
ways
[5,6,7,8,9,10,11,12,13,14] to assess both the degree to which scattering from whole cells can be specifically associated with contributions from sub-cellular structures, and whether there are clear associations with these results and cancer or dysplasia (precancerous growth) [15,16]. Since cancer has been associated with morphological and/or functional changes in sub-cellular structures like organelles and DNA, attention has typically been directed to what specific correspondence there may be between sub-cellular anomalies and specific optical information [17]. Although a variety of techniques have been used to study the optical properties of single cells (such as confocal microscopy [18], and confocal Raman spectroscopy [19], cavity ringdown spectroscopy [20], DVD optics [21], light-interference tomography [22], and dynamic light scattering [23]) these techniques have yet to be specifically applied to systematic cancer cell studies. At the sub-cellular size scale, organelle anomalies have long been recognized as an important diagnostic indicator of cancer [24]. For example, cytopathologists use enlarged nuclei as an indicator of cancer in standard Pap tests. The size of the nucleus [ 25 , 26 ] and mitochondria [27] of cancer cells can be up to twice the size of the same organelles in normal cells. Metabolic changes, morphological anomalies and other defects [28,29,30,31,32] in the mitochondria of cancer cells have been observed, associated with altered optical properties [33], and even inspired new approaches to cancer treatment [34]. Lysosomes have also been singled out as playing a role in the development of cancer, as demonstrated by studies using genetic manipulation to turn off the lysosome system within cells, whereby tumor growth and metastasis could be halted [35]. Lysosomes (200 – 800 nm), mitochondria (1,500 nm) and nuclei (3,000 – 10,000 nm) have generally been noted as being significant contributors to light scattering in this context.
3
Although significant correlations between optical properties and specific biological conditions on both the cellular and tissue level have been identified, clear relationships to physical changes at the sub-cellular scale have not been established to the extent that models can be created wherein specific changes in the size, geometry, or morphology of nano-scale sub-cellular objects can be directly associated with cancer cells. There is nonetheless increasing evidence that nanoparticle analysis can play an important role in the understanding and diagnosis of cancer. For example, with the goal of creating a diagnostic strategy, studies of the size distribution of circulating tumor-derived microvesicles and exosomes using light scattering analysis [36], atomic force microscopy (AFM) [37], and electron microscopy [38] have been performed, showing that a dominant size scale of these objects was in the general range of ~ 50 to 300 nm. In this work we have studied human oral normal and cancer whole cells and lysates and determined that significant differences exist in their optical properties and subcellular particlesize distributions. To obtain detailed information on these materials we have applied a new optical technique for submicron particle analysis developed by our group called light transmission spectroscopy (LTS) [ 39 ]. As opposed to the (typically single-wavelength) measurement of scattered light, LTS employs the high-resolution spectral analysis of transmitted light over a broad optical range (UV to infrared). In this way the size, shape, and absolute number of objects per unit volume in liquid suspension can be determined. LTS is thus well suited to quantitatively examine the nanoparticle populations of whole cells and cell lysates, which for the present study were prepared from cultured human oral normal and cancer cells. We measured the optical properties of both whole cells and lysates derived from these cells, in the latter case as a function of systematic filtration, obtaining both the optical extinction coefficient (the diminution of light intensity) as a function wavelength in the range from 220 to 1100 nm, and the particle size distributions (PSDs) of objects from 1 to 3,000 nm in diameter.
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Based on these results, we observe clear, systematic differences in the PSDs associated with cancer versus normal cells. Materials and methods Cell cultures
Telomerase reverse transcriptase-immortalized normal oral keratinocytes (OKF6/T) [40] and malignant SCC25 [41] (oral squamous cell carcinoma) cells were provided by Dr. J. Rheinwald (Brigham and Women’s Hospital, Harvard Institutes of Medicine, Boston, MA) [42]. OKF6/T cells were maintained in keratinocyte serum-free medium (Life Technologies, Grand Island, NY) supplemented with 100 units/ml penicillin, 100mg/ml streptomycin, 0.2ng/ml epidermal growth factor, 25mg/ml bovine pituitary extract, and 0.62mM CaCl2. SCC25 cells were maintained in DMEM/F12 50/50 w/ l-glutamine (Corning) supplemented with 100 units/ml penicillin, 100mg/ml streptomycin, and 10% fetal bovine serum. Cells were grown at 37oC with 5% CO2 in 150mm culture dishes and harvested at 50% confluence (log phase). Cells were removed by washing with 20ml of phosphate buffer saline (PBS) and then treated with 5ml of 0.25% trypsin/2.21mM EDTA at 37oC for 5min. Trypsinization was stopped with the addition of 10ml media and the cells were collected by centrifugation at 1200rpm (287g) for 2 min. We note that for SCC25 cells in log phase the doubling time is approximately 24 hours. The normal oral keratinocyte (OKF6) doubling rate is approximately 48 hours. Lysate specimens Cultured cancer and normal human oral cells were collected from culture plates and then transferred to 1.5ml microtubes with a 0.1 M PBS solution. Samples were divided in half: one half was used for whole-cell measurements, and the other half was lysed. Cell lysates were prepared at room temperature using a Kontes 2 ml Dounce homogenizer and pestle (abcam
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ab110171). Thirty strokes of the pestle (pestle B), which has a clearance of 0.013–0.064 mm, were used as directed by the kit protocol to homogenize the sample. After being homogenized, cell lysate material was transferred into 1.5 ml microtubes without filtration. For this work normal and cancer lysates were further diluted by factors of 12 and 24, respectively, to create comparable overall light transmission properties. Scanning electron microscopy For scanning electron microscope (SEM) characterization, cells underwent treatment through fixation, dehydration, drying and coating. First, isolated cells were added to the first fixative, a 2% glutaraldehyde buffer solution, for one hour. After three PBS rinses, cell samples were added to the second fixative, a 1% osmium tetroxide buffered solution, for another hour followed by three PBS rinses. Then, fixed cell samples were dehydrated using a graded series of ethanol solutions in DI water: 50%, 70%, 80%, 95%, and 100%, and finally collected on filter paper for critical-point drying using 100% liquid CO2. To enhance surface electrical conductivity, the samples were coated with a 20 nm film of sputtered iridium. Imaging was performed using a Magellan 400 field-emission scanning-electron microscope. Atomic-force microscopy For atomic force microscopy, a 1 in. x 1 in. mica square was cleaved and transferred to a nitrogen-purged case. Prior to use, the mica was washed with methanol for at least 15 sec. and then rinsed with di-ionized (DI) water. A drop of the lysate sample was then pipetted on to the mica to allow particles to adsorb to the surface. The sample was then rewashed with DI water and dried with dry nitrogen. For AFM imaging, a Park Systems XE-70 AFM model was used in non-contact in-air mode, using a non-contact tip. The stated resolution of an unused noncontact tip is 2-3 nm. Light Transmission Spectroscopy
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In order to make more detailed comparisons between cancer and normal PSDs, we have used a new technique developed by our group called light transmission spectroscopy (LTS). The basic operational principle of LTS is that the intensity of a transmitted light beam as a function of wavelength is measured at zero angle with respect to the incoming beam after it passes through a liquid suspension of nanoparticles [39]. By also using a reference channel containing the suspension fluid, the absolute value of the optical extinction due to the particles can be obtained over a broad spectral range (220 to 1100 nm) at high (1 nm) resolution. LTS also uses the measured wavelength-dependent optical extinction to obtain the particle distribution density (number of particles of a given diameter per unit diameter per unit volume, as a function of particle diameter) by performing spectral inversion using a Mie solution to Maxwell’s equations. This provides the number density, the total number of objects of a given diameter per unit volume, as a function of particle diameter, over a range of 1 – 3000 nm. In previous biological applications, LTS has been used to study the “growth” properties of liposomes [43], and is being applied to detect and quantify species-specific environmental DNA [44,45]. Note that some authors use the terms extinction, attenuation, and absorption interchangeably, although they are not always equivalent. Our apparatus measures the reduction in intensity, I , of a transmitted light beam due to both scattering and absorption through a finite length, z, of material. We report our results in terms of an extinction coefficient,
α . These quantities are mathematically related in Eqs. (1) and (2), according to the definition of extinction coefficient as the rate of reduction of the transmitted light [46].
dI = -α I dz
(1)
This expression leads to the well-known exponential decay law for the intensity as a function of distance,
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Iout (z) = Iine− α z
(2)
where Iout and Iin are the output and input light intensities. Our apparatus and data collection scheme is a balanced optical spectrometer, designed to remove the effects of temporal fluctuations in the light source and the attenuation of the light beam due to the suspension fluid. The light intensity transmitted through the sample comprising nanoparticles in a suspension fluid, and separately through a sample of the suspension fluid alone, is simultaneously measured at many wavelengths, here typically from 220 nm to 1000 nm in 1 nm steps. From this information, the transmittance as a function of wavelength due to the nanoparticles alone, T (λ ) , is determined as described in our initial paper [39]. Transmittance is defined in Eq. (3), where
I(λ ) represents light intensity at each wavelength, z is the path length through the sample and reference, and
α (λ ) is the extinction coefficient at each wavelength due to the nanoparticles
present.
T(λ ) =
Iout (λ ) = e−α ( λ )z Iin (λ )
(3)
Iout (λ ) . Iin (λ )
(4)
where the extinction is defined as
α (λ )z = - lnT (λ ) = - ln
The path length in our apparatus is z = 1.0 cm, so the extinction is equal to the extinction coefficient in units of cm-1. As discussed in our original paper, this information is what is required to obtain the particle distribution density using the Mie model for spectral inversion. An additional piece of information is also required, and that is the wavelength-dependent dielectric constant of the material under study. Fortunately, the inversion is not highly sensitive to this and we have found that the dielectric properties of polystyrene (the dielectric constant of which is a
8
monotonic function of wavelength) are a good approximation to those of organic materials [43,44,45]. Actual measurements take place in the following manner. After mechanical processing, lysates were diluted to produce significant light transmission from ~ 220 to 1000 nm. A given lysate sample was pipetted into an optical cuvette and then placed in one optical channel of the LTS spectrometer and the suspension material (PBS in this case) was pipetted into an identical optical cuvette and placed in the second channel. Whole cells were similarly measured except without pre-processing. After a spectrum of both samples was obtained (taking less than one second), the cuvettes were exchanged and a second spectrum was obtained of both samples as described above. In this way any differences in the transmission properties of the optical paths and fluctuations in the light source were removed. In addition, this allows for the elimination of the effect of the optical extinction of the suspension material itself, so we are left with the extinction of the suspended nanoparticles exclusively. Results Whole-cell and lysate characterization by SEM and AFM Shown in Fig. 1 are representative SEM images typical of individual whole human oral normal and cancer cells used in this study. The cancer cells we examined were generally larger in diameter (~ 20 µm) compared to normal cells (~ 10 µm) and had less smooth surfaces. Fig. 2 shows an AFM scan of unfiltered cancer lysates rendered in three dimensions. This shows the relative particle density viewable with AFM and the fact that there are many sub-micron sized particles present. Fig. 3 shows more quantitative AFM scans of cancer and normal lysates in 2D mode. The image-analysis based distributions of the measured particle lengths are also shown, where we find the mean particle sizes for cancer and normal lysates to be 99 ± 40 nm and 108 ± 46 nm, respectively (essentially indistinguishable from this prospective). AFM is able to
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image (only) those particles which have the highest overall number density (and smallest sizes), as will be more evident when we present further information below on particle distributions. Whole-cell and lysate characterization by LTS In this section we discuss the spectroscopic data we obtained with Light Transmission Spectroscopy (LTS) for whole cells and systematically filtered normal and cancer cell lysates. The idea is to establish the basic optical properties of these materials and the size distributions of the nanoparticles of which they are comprised. Unfiltered lysate material in PBS was initially measured and then this material was filtered by a succession of standard syringe filters and measured by LTS at each filtration stage. For these experiments, the absolute densities and growth rates of cancer and normal cells dictated that the normal- and cancer-cell-derived lysates were diluted by factors of 12 and 24, respectively, to achieve comparable optical extinction properties. We grew four distinct sets of cancer and normal cells on separate occasions, referred to as runs A, B, C, and D. Shown in Fig. 4 are the optical extinction (Eq. 4) results for a representative set of normal and cancer cells (run C). The plot shows results for whole cells, unfiltered lysates, and systematically filtered lysate materials. For each run, half of the cells harvested were used for lysis and the remaining cells were measured whole. To quantify differences in the normal and cancer extinction results, we took the value of the extinction at 259 nm and normalized it to the value of the extinction at 300 nm, to obtain the ratio (α 259 / α 300 )C for cancer cells and (α 259 / α 300 )N for normal cells. These quantities are designed to characterize the relative degree of UV extinction, represented by the peak value of the extinction we consistently see at 259 nm. Although the peak itself is likely associated with the presence of DNA it is a convenient standard reference point and generally scales with the more dominant background UV absorption. This is normalized by the “knee” value at 300 nm
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that characterizes the extinction behavior at longer wavelengths. Using this procedure, the overall extinction results for systematic lysate filtration and whole cells are shown in Fig. 5. The individual ratios (α 259 / α 300 )C and (α 259 / α 300 )N can be viewed as indicating the degree to which smaller particles—which scatter more strongly at lower wavelengths—dominate the extinction process (scattering at 259 nm as compared to that at 300 nm) for cancer and normal cells. Thus, based on the results in Fig. 5, this implies that the normal materials have particle distributions with higher quantities of smaller particles than larger particles, as compared with cancer lysates, thus generally making (α 259 / α 300 )C / (α 259 / α 300 )N < 1. This is true for all filtrations except for 0.1 µm (the smallest pore size) where the effect vanishes. This suggests that when there are only particles smaller than 0.1 µm present, there are no longer sufficiently wide particle-size distributions to make the difference in small to large particles observable. Note that this ratio does not depend on the actual number of particles present, only their relative distributions, assuming a linear scaling of extinctions. Importantly, we note that results for whole cells are in good accord with those for unfiltered lysates, suggesting that the lysation process has, for this analysis, no significant effect on either the measured optical properties, or the particle distribution density. Thus, LTS appears to accurately probe the internal PSD of the whole cells. To understand this behavior in a more quantitative way, we have created a simple model based on the existence of two distinct particle populations: small particles that scatter significantly in the UV, and larger particles that do not. Assuming that the extinctions are determined by scattering factors a and b for small and large particles, respectively, times the numbers, ns and nL of small and large particles, respectively, that are present in the suspension, we can say that the extinction depends on these quantities in the following simple way
α = ans + bnL . Thus, for example, at 259 nm
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(5)
α 259 = a259ns + b259nL = a259ns + f259a259nL
(6)
where f ≡ b/a. Thus we can write,
α 259 a259 α 300 C a300 C = α 259 a259 α 300 N a300 N
1+ f259 (nL / ns )C 1+ f (n / n ) 300 s C L 1+ f259 (nL / ns )N 1+ f (n / n ) 300 s N L
(7)
In order to simplify this expression we need to look in more detail at the particle distributions. Shown in Fig. 6 is the particle distribution density (the number of particles per mL per nm) for two representative runs (A and D) of cancer/normal unfiltered lysate and whole-cell samples as determined by LTS. Note that because of the large dynamic range available with LTS we have plotted the results on a log-log scale. This plot was created with the aforementioned Mie inversion procedure using data of the type presented in Fig. 4. Note that these results are consistent with the AFM results in showing a peak in particle density in the vicinity of 100 nm. What is apparent from Fig. 6 is: (1) that there are many more particles with small diameters, especially below ~ 250 nm; (2) that generally materials from normal cells are comprised of a larger number of smaller particles; and (3) that the number of the largest particles is roughly equal for cancer and normal materials. It is appropriate here to discuss overall starting densities. While the inversion process provides an absolute measure of the number of particles of a given diameter per unit volume in the PBS suspension medium for both normal and cancer lysates, the starting number of cells before lysis will differ, as will the volume of the cells and the dilutions of the lysates. It is important to note, however, that this dilution
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process does not affect the quantity defined in Eq. 7, but could affect the absolute comparison of normal to cancer nanoparticle densities. To address this last point above we performed separate optical extinction comparisons of unfiltered normal and cancer lysates and starting whole cells. We also counted cells on the culture plates with an optical microscope prior to harvesting them. Based on this information, we believe that if we used as a reference a given absolute particle count (number of particles of a given diameter per volume) for, say, normal lysates, the corresponding count of the particles for cancer lysates of the same diameter, as scaled to the starting cellular volume, would be correct to within a factor of two (as represented by the extent of the plotted symbols in Fig. 6). Again, owing to the normalization procedure, Eq. 7, that was used to generate the results shown in Fig. 5, our conclusions are unaffected by the absolute densities of the normal and cancer lysates. We will address the issue of estimating the absolute particle count per cell after further discussion. We now return to our mathematical model (Eq. 7) and make the assumption that nL 1. Therefore, we can reduce Eq. 9 to Eq. 10 below, where A is a positive constant and where we have modeled the ratio of the large to small particles with a simple filter function. This parameterizes the step-by-step filtration we performed by the function nL / nS = [1+(B/d)2]-1, where d is the filter pore diameter and B represents a particle-size scale parameter for the system.
α 259 α n 300 C 1 = 1.0 − A L = 1.0 − A 2 α 259 1+ (B / d) ns N α 300 N
(10)
Fitting this expression to our data (Fig. 5) we obtain values of A = 0.3 and B = 0.25 µm. As seen in Fig. 6, this value of 0.25 µm (250 nm) is consistent with the general size demarcation between large populations of small particles (with diameters less than ~ 250 nm), and larger particles. The results shown in Fig. 6 represent the distribution density of the particles, which is the number of particles of a given diameter per nm per mL, as a function of particle diameter. In order to derive the particle density, the number of particles of a given diameter per mL as a function of particle diameter, we simply integrate the area under the peaks of Fig. 6. The results of this are shown in Fig. 7 where the plotted diameter is the maximum value for a given peak in the distribution density. Note that in the process of obtaining size information about particles from numerical inversions of extinction data (see Fig. 4) one issue that arises is what
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the effect of the DNA peak (at 259 nm) may have on the inversion. We have done extensive simulations using both the original extinction curves, and those where the DNA peak was removed and replaced with smooth curves. Based on this analysis, the corresponding uncertainty in the results presented in Fig. 7 is represented by the given size of the plotting symbols. One clear result from Fig. 7 is the power-law dependence of particle density with diameter, here manifest as a linear dependence on this log-log plot. We can characterize this behavior with the simple power-law relation N(D)= kD −γ where N(D) is the number density (number of particles per unit volume) as a function of diameter, D. Since this formulation is scale free, the choice of k affects only the absolute density, whereas the exponent γ can be compared from system to system. The value of γ = 3.64 observed for our cancer and normal whole cells and lysates is in good accord with results for other PSDs for nano-particle suspensions in natural systems. This includes the well-described PSDs of suspended particles in aquatic ecosystems (with particles larger than 1 µm) which exhibit values of γ ranging from 3.03 to 4.33 with an average value of γ = 3.8 [47]. A second relevant study involved the PSDs of extracellular vesicles including exosomes and microvesicles 70 – 600 nm in diameter [48]. Here values of γ ranged from ~ 3.3 to 6.0, with an average value of 4.3. This suggests that the PSD for the internal nano-components of cells is comparable to those found elsewhere in nature. Also evident in this plot is the relative dominance of smaller particles for the normal unfiltered lysates and whole cells in the vicinity of ~ 100 nm and below, and a relative dominance for cancer unfiltered-lysate and whole-cell particles ~ 100 to 1000 nm in diameter. This transition-length scale of ~ 100 nm is consistent with our previous results from the analysis of the results in Fig. 5. To quantify the trends observed in Fig. 7, we have plotted in Fig. 8 the normalized difference between the cancer to normal particle densities (for both whole cells and
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unfiltered lysates) as (NC – NN)/(NC + NN), where NC and NN are particle number densities (number of particles of a given diameter per mL) as plotted in Fig. 7. Fig. 8 clearly demonstrates the trend that was suggested by Fig. 7. We see definitively that (1) for 25 nm < D < 100 nm, there is a relative deficit of particles for cancer unfiltered lysates and whole cells and (2) for 100 < D < 1000 nm the situation is reversed and there is a relative excess of particles for cancer lysates and whole cells, where D is the particle diameter. We note that starting (harvested) samples comprised ~ 106 cells based on cell counting under a microscope. Based on this quantity (and accounting for the dilutions made with normal and cancer cells) we find that for unfiltered lysates there are ~ 104 – 106 particles/cell with diameters in the vicinity of 50 – 100 nm, and ~ 100 particles/cell with diameters in the vicinity of 1,000 – 1,500 nm. This appears to be consistent with the total expected numbers of smaller objects such as exosomes (50 – 100 nm), microvesicles (20 nm and greater), membrane particles (50 – 80 nm) and ribosomes (25 nm) [16, 38], and larger-size particles like organelles, larger membrane particles, and vesicles including lysosomes (250 - 800 nm), peroxisomes (200 – 1000 nm) and cytoplasmic inclusions like secretory granules, lipid granules, and pigment bodies (20 - 500nm). What is not clear is which if any of these well-known classes of nanoparticle systems within the cells is associated with the distinct particle-density imbalances we have observed for cancer as compared to normal cells. Conclusions In conclusion we have investigated the optical properties of cultured human oral cancer and normal whole cells and lysates. Our primary investigative tool was light transmission spectroscopy (LTS) which provides both the light extinction coefficient (from light absorption and scattering) as a function of wavelength from the UV to the infrared, and the particle size distribution (the number of particles of a given diameter as a function of diameter) in the 1 – 3000 nm range. We have found that cancer cells have a systematic defecit of particles in the
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range of 25 – 100 nm and an excess of particles in the range of ~ 100 – 1000 nm compared to normal cells. Significantly, these results hold for measurements of both unfiltered lysates and the whole cells from which they were derived, implying that LTS can accurately probe the internal PSDs of whole cells. We have also found a clear power-law dependence for the overall PSD of our samples with an exponential coefficient of 3.64, which is comperable to results for other naturally-occuring PSDs for particles in liquid suspension. Acknowledgments We are grateful to the University of Notre Dame for support through the Faculty Research Support Program, and for Walter Johnson for theoretical guidance with this work.
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Figure Captions Fig. 1. SEM images of whole normal (left) and cancer (right) cultured human oral cells. Fig. 2. AFM scan of cancer lysates in 3D mode. Fig. 3. AFM images of unfiltered cancer and normal lysates in 2D mode (top left and right images, respectively) and associated particle histograms. Fig. 4. Shown to the left and right are extinction data for normal and cancer, respectively, whole cells and systematically filtered lysates (Run C). Since the optical path length was 1.0 cm, the extinction coefficient,
α (in
units of cm-1), is here numerically equal to the (dimensionless) extinction,
αz .
Individual plots
represent results for a given level of filtration as indicated in the legend. Fig. 5. Optical extinction ratios as a function of inverse filter size (filter pore diameter) for cancer and normal lysates and unfiltered whole cells. Here, triangles, circles, squares, and diamonds correspond to Runs A, B, C and D respectively. Solid symbols represent lysates and open symbols represent whole cells. Also shown is a theoretical model calculation (see Eq. 10). Fig. 6. Shown on the left and right (data from representative runs A and D) are examples of the particle distribution density (number of particles per nm per mL) as a function of particle diameter for cancer and normal materials, shown as red and blue symbols, respectively. Open symbols represent whole cells and solid symbols represent unfiltered lysates. Fig. 7. Shown is the number density of particles (number of particles of a given diameter per mL) as a function of particle diameter for all runs conducted. Here, triangles, circles, squares, and diamonds correspond to Runs A, B, C and D, respectively. Red symbols are for cancer and blue for normal cell data. Solid symbols are for unfiltered lysates, open symbols for whole cells. Shown is a power-law fit and associated exponent (γ = 3.64) for these data. Fig. 8. Normalized relative number densities for nanoparticles in cancer and normal whole cells (open symbols) and for unfiltered lysates (solid symbols), derived from the results shown in Fig. 7. Cancer cells
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show a relative deficit of particles with diameters 100 nm and below, and a relative excess of particles in the ~ 100 to 1000 nm diameter range. Fig. 8. Normalized relative number densities for nanoparticles in cancer and normal whole cells (open symbols) and for unfiltered lysates (solid symbols), derived from the results shown in Fig. 7. Cancer cells show a relative deficit of particles with diameters 100 nm and below, and a relative excess of particles in the ~ 100 to 1000 nm diameter range.
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[22] M. Mir, S.D. Babacan, M. Bednarz, M.N. Do, I. Golding, G. Popescu, Visualizing Escherichia coli subcellular structure using sparse deconvolution spatial light interference tomography, PLoS ONE 7 (2012) 19. [23] G. Farhat, A. Mariampillai, K.K.C. Leec, V.X.D. Yang, G.J. Czarnota, M.C. Kolios, Measuring intracellular motion using dynamic light scattering with optical coherence tomography in a mouse tumor model, Biomedical Applications of Light Scattering, Proc. SPIE 8230 (2012) 1-5. [24] Y.H.M. Chan, W.F. Marshall, Scaling properties of cell and organelle size, Organogenesis 6 (2010) 88-96. [25] S.A. Silchenko, V.I. Loboda, Quantitative assessment of cytologic characteristics of breast-cancer for identification of degree of cell-differentiation, Vopr. Onkol. 37 (1991) 335-40. [26] The Cell Nucleus, Contexo.info, 15 Dec. 2005, http://www.contexo.info/DNA_Basics/Nucleus.htm. [27] The Mitochondria, Contexo.info, 15 Dec. 2005, http://www.contexo.info/DNA_Basics/Mitochondria.htm [28] P.S. Ward, C.B. Thompson, Metabolic reprogramming: a cancer hallmark even Warburg did not anticipate, Cancer Cell 21 (2012) 297-308. [29] J.S. Carew, P. Huang, Mitochondrial defects in cancer, Molecular Cancer 1 (2002) 1-9. [30] V. Gogvadze, S. Orrenius, B. Zhivotovsky, Mitochondria in cancer cells: what is so special about them?, Trends in Cell Biol. 18 (2008) 165-173. [31] D.C. Wallace, Mitochondria and cancer, Nat. Rev. Cancer 12 (2012) 685-698. [32] E. Alirol, J.C. Martinou, Mitochondria and cancer: is there a morphological connection?, Oncogene 25 (2006) 4706–4716. [33] J.D. Wilson, C.E. Bigelow, D.J. Calkins, T.H. Foster, Light scattering from intact cells reports oxidative-stress-induced mitochondrial swelling, Biophys. J. 88 (2005) 2929-2938. [34] W.F. Marshall, Organelle size control systems: From cell geometry to organelle-directed medicine, BioEssays 34 (2012) 721–724. [35] A.M. Cuervo, Autophagy's Top Chef, Science 332 (2011) 1392-1393.
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[36] C. Gercel-Taylor, S. Atay, R.H. Tullis, M. Kesimer, D.D. Taylor, Nanoparticle analysis of circulating cell-derived vesicles in ovarian cancer patients, Anal. Biochem. 428 (2012) 44–53. [37] T. Kanno, T. Yamada, H. Iwabuki, H. Tanaka, S. Kuroda, K. Tanizawa, T. Kawai, Size distribution measurement of vesicles by atomic force microscopy, Anal. Biochem. 309 (2002) 196–199. [38] E. van der Pol, A.N. Boing, P. Harrison, A. Sturk, R. Nieuwland, Classification Functions and Clinical Relevance of Extracelluar Vesicles, Pharmacol. Rev. 64 (2012) 676-705. [39] F. Li, R. Schafer, C.T. Hwang, C.E. Tanner, S.T. Ruggiero, High-precision sizing of nanoparticles by laser transmission spectroscopy, Appl. Optics 49 (2010) 6603-6611. [40] T. Oviir, D. Pagoria, G. Ibarra, W. Geurtsen, Effects of Gray and White Mineral Trioxide Aggregate on the Proliferation of Oral Keratinocytes and Cementoblasts, J. Endodontics 32, (2006) 210–213. [41] B. J. Vermeer, M. C. Wijsman, A. M. Mommaas-Kienhuis and M. Ponec, Binding and Internalization of Low-Density Lipoproteins in SCC25 Cells and SV40 Transformed Keratinocytes. A Morphologic Study, J. Investigative Dermatology 86 (1986) 195–200 [42] Rheinwald, J.G., and Beckett, M.A. Cancer Res. 41 (1981) 1657-1663. [43] J.M. Marr, F. Li, A.R. Petlick, R. Schafer, C.T. Hwang, A. Chabot, S.T. Ruggiero, C.E. Tanner, Z.D. Schultz, The role of lateral tension in calcium-induced DPPS vesicle rupture, Langmuir 28 (2012) 11883−11889. [44] F. Li, A.R. Mahon, M.A. Barnes, J. Feder, D.M. Lodge, C.T. Hwang, R. Schafer, S.T. Ruggiero, C.E. Tanner, Quantitative and rapid DNA detection by laser transmission spectroscopy, PLoS ONE 6 (2011) 16. [45] S.P. Egan, M.A. Barnes, C.T. Hwang, A.R. Mahon, J.L. Feder, S.T. Ruggiero, C.E. Tanner, D.M. Lodge, Rapid invasive species detection by combining environmental DNA with light transmission spectroscopy, Conservation Lett. 6 (2013) 402-409. [46] Extinction Coefficient, Merriam-Webster.com, 2 June 2014, http://www.merriamwebster.com/dictionary/extinction coefficient.
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normal whole cell
cancer whole cell
2.5
Normal
2 1.5
x 2.10
unfiltered 3.1 µm 1.2 µm 0.45 µm 0.25 µm 0.1 µm whole cell
1 0.5 0 200 250 300 350 400 450 500
Wavelength (nm)
Optical Extinction, αz
Optical Extinction, αz
3
3 2.5
Cancer
2 1.5
x 1.21
1 0.5 0 200 250 300 350 400 450 500
Wavelength (nm)
300 N
/α
1.2
0.4
259
300 C
) /(α
0.8
(α
1/0.1
1
/α
259
)
1.4
1/0.5 1/0.25
model
0.6
0.2
0
2
4
6
8
1/Filter Size (1/µm)
10
10
109 108 107 106 105 104 103 10
100
1000
Diameter (nm)
104
Distribution Density (1/nm*mL)
Distribution Density (1/nm*mL)
10
1010 109 108 107 106 10
5
104 103 10
100
1000
Diameter (nm)
104
Number Density (1/mL)
15
10
-3.64
D
13
10
11
10
9
10
7
10
5
10
3
10
1
10
2
10
3
10
Diameter (nm)
4
10
1 0.5
N
0 -0.5
C
C
N
(N - N )/(N + N )
1.5
-1 -1.5 1 10
2
10
3
10
Diameter (nm)
4
10
S0003-2697(15)00240-7 http://dx.doi.org/10.1016/j.ab.2015.05.004 YABIO 12077
To appear in:
Analytical Biochemistry
Received Date: Revised Date: Accepted Date:
30 September 2014 21 April 2015 5 May 2015
Please cite this article as: N. Sun, J. Johnson, M.S. Stack, J. Szajko, C. Sander, R. Rebuyon, A. Deatsch, J. Easton, C.E. Tanner, S.T. Ruggiero, Nanoparticle Analysis of Cancer Cells by Light Transmission Spectroscopy, Analytical Biochemistry (2015), doi: http://dx.doi.org/10.1016/j.ab.2015.05.004
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Nanoparticle Analysis of Cancer Cells by Light Transmission Spectroscopy
N. Sun,1 J. Johnson,2 M. S. Stack,2 J. Szajko,3 C. Sander,1 R. Rebuyon,1 A. Deatsch,1 J. Easton,4 C. E. Tanner,1 and S. T. Ruggiero1 1
Department of Physics, University of Notre Dame, Notre Dame, IN 46556, USA
2
Department of Chemistry and Biochemistry, Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA 3
F Cubed LLC, South Bend, IN, USA 4
Ivy Tech, South Bend, IN, USA
Short Title: Cell analysis by Light Transmission Spectroscopy
Proofs should be mailed to: Prof. Steven T. Ruggiero Department of Physics 225 Nieuwland Hall University of Notre Dame Notre Dame, IN 46556 United States of America
Phone: 303-579-4410 Fax: 574-631-5952 e-mail: [email protected]
1
Abstract We have measured the optical properties of cancer and normal whole cells and lysates using light transmission spectroscopy (LTS). LTS provides both the optical extinction coefficient in the wavelength range from 220 to 1100 nm and also (by spectral inversion using a Mie model) the particle distribution density in the size range from 1 to 3000 nm. Our present work involves whole cells and lysates of cultured human oral cells in liquid suspension. We have found systematic differences in the optical extinction between cancer and normal whole cells and lysates, which translate to different particle size distributions (PSDs) for these materials. Specifically, we find that cancer cells have distinctly lower concentrations of nanoparticles with diameters below 100 nm, and higher concentrations of particles with diameters from 100 to 1000 nm—results which hold for both whole cells and lysates. We have also found a power-law dependence of particle density with diameter over several orders of magnitude.
Introduction Optical techniques have contributed greatly to cancer diagnosis. To date, this has for the most part involved characterization at the tissue level. There clearly are significant differences in the optical properties of cancerous and healthy tissues [ 1 , 2 ], and diagnostic optical spectroscopy on the scale of individual organs has proven value for cancer management. Optical cancer diagnosis of the brain, breast, cervix, lung, stomach, colon, prostate, and skin have been employed, especially over the past two decades [3]. Recent use has also been made of multi-modal optical techniques for skin cancer [4].
2
Light has also been used to investigate cancer at a finer scale. Most studies have involved
light
scattering,
which
has
been
applied
in
a
number
of
ways
[5,6,7,8,9,10,11,12,13,14] to assess both the degree to which scattering from whole cells can be specifically associated with contributions from sub-cellular structures, and whether there are clear associations with these results and cancer or dysplasia (precancerous growth) [15,16]. Since cancer has been associated with morphological and/or functional changes in sub-cellular structures like organelles and DNA, attention has typically been directed to what specific correspondence there may be between sub-cellular anomalies and specific optical information [17]. Although a variety of techniques have been used to study the optical properties of single cells (such as confocal microscopy [18], and confocal Raman spectroscopy [19], cavity ringdown spectroscopy [20], DVD optics [21], light-interference tomography [22], and dynamic light scattering [23]) these techniques have yet to be specifically applied to systematic cancer cell studies. At the sub-cellular size scale, organelle anomalies have long been recognized as an important diagnostic indicator of cancer [24]. For example, cytopathologists use enlarged nuclei as an indicator of cancer in standard Pap tests. The size of the nucleus [ 25 , 26 ] and mitochondria [27] of cancer cells can be up to twice the size of the same organelles in normal cells. Metabolic changes, morphological anomalies and other defects [28,29,30,31,32] in the mitochondria of cancer cells have been observed, associated with altered optical properties [33], and even inspired new approaches to cancer treatment [34]. Lysosomes have also been singled out as playing a role in the development of cancer, as demonstrated by studies using genetic manipulation to turn off the lysosome system within cells, whereby tumor growth and metastasis could be halted [35]. Lysosomes (200 – 800 nm), mitochondria (1,500 nm) and nuclei (3,000 – 10,000 nm) have generally been noted as being significant contributors to light scattering in this context.
3
Although significant correlations between optical properties and specific biological conditions on both the cellular and tissue level have been identified, clear relationships to physical changes at the sub-cellular scale have not been established to the extent that models can be created wherein specific changes in the size, geometry, or morphology of nano-scale sub-cellular objects can be directly associated with cancer cells. There is nonetheless increasing evidence that nanoparticle analysis can play an important role in the understanding and diagnosis of cancer. For example, with the goal of creating a diagnostic strategy, studies of the size distribution of circulating tumor-derived microvesicles and exosomes using light scattering analysis [36], atomic force microscopy (AFM) [37], and electron microscopy [38] have been performed, showing that a dominant size scale of these objects was in the general range of ~ 50 to 300 nm. In this work we have studied human oral normal and cancer whole cells and lysates and determined that significant differences exist in their optical properties and subcellular particlesize distributions. To obtain detailed information on these materials we have applied a new optical technique for submicron particle analysis developed by our group called light transmission spectroscopy (LTS) [ 39 ]. As opposed to the (typically single-wavelength) measurement of scattered light, LTS employs the high-resolution spectral analysis of transmitted light over a broad optical range (UV to infrared). In this way the size, shape, and absolute number of objects per unit volume in liquid suspension can be determined. LTS is thus well suited to quantitatively examine the nanoparticle populations of whole cells and cell lysates, which for the present study were prepared from cultured human oral normal and cancer cells. We measured the optical properties of both whole cells and lysates derived from these cells, in the latter case as a function of systematic filtration, obtaining both the optical extinction coefficient (the diminution of light intensity) as a function wavelength in the range from 220 to 1100 nm, and the particle size distributions (PSDs) of objects from 1 to 3,000 nm in diameter.
4
Based on these results, we observe clear, systematic differences in the PSDs associated with cancer versus normal cells. Materials and methods Cell cultures
Telomerase reverse transcriptase-immortalized normal oral keratinocytes (OKF6/T) [40] and malignant SCC25 [41] (oral squamous cell carcinoma) cells were provided by Dr. J. Rheinwald (Brigham and Women’s Hospital, Harvard Institutes of Medicine, Boston, MA) [42]. OKF6/T cells were maintained in keratinocyte serum-free medium (Life Technologies, Grand Island, NY) supplemented with 100 units/ml penicillin, 100mg/ml streptomycin, 0.2ng/ml epidermal growth factor, 25mg/ml bovine pituitary extract, and 0.62mM CaCl2. SCC25 cells were maintained in DMEM/F12 50/50 w/ l-glutamine (Corning) supplemented with 100 units/ml penicillin, 100mg/ml streptomycin, and 10% fetal bovine serum. Cells were grown at 37oC with 5% CO2 in 150mm culture dishes and harvested at 50% confluence (log phase). Cells were removed by washing with 20ml of phosphate buffer saline (PBS) and then treated with 5ml of 0.25% trypsin/2.21mM EDTA at 37oC for 5min. Trypsinization was stopped with the addition of 10ml media and the cells were collected by centrifugation at 1200rpm (287g) for 2 min. We note that for SCC25 cells in log phase the doubling time is approximately 24 hours. The normal oral keratinocyte (OKF6) doubling rate is approximately 48 hours. Lysate specimens Cultured cancer and normal human oral cells were collected from culture plates and then transferred to 1.5ml microtubes with a 0.1 M PBS solution. Samples were divided in half: one half was used for whole-cell measurements, and the other half was lysed. Cell lysates were prepared at room temperature using a Kontes 2 ml Dounce homogenizer and pestle (abcam
5
ab110171). Thirty strokes of the pestle (pestle B), which has a clearance of 0.013–0.064 mm, were used as directed by the kit protocol to homogenize the sample. After being homogenized, cell lysate material was transferred into 1.5 ml microtubes without filtration. For this work normal and cancer lysates were further diluted by factors of 12 and 24, respectively, to create comparable overall light transmission properties. Scanning electron microscopy For scanning electron microscope (SEM) characterization, cells underwent treatment through fixation, dehydration, drying and coating. First, isolated cells were added to the first fixative, a 2% glutaraldehyde buffer solution, for one hour. After three PBS rinses, cell samples were added to the second fixative, a 1% osmium tetroxide buffered solution, for another hour followed by three PBS rinses. Then, fixed cell samples were dehydrated using a graded series of ethanol solutions in DI water: 50%, 70%, 80%, 95%, and 100%, and finally collected on filter paper for critical-point drying using 100% liquid CO2. To enhance surface electrical conductivity, the samples were coated with a 20 nm film of sputtered iridium. Imaging was performed using a Magellan 400 field-emission scanning-electron microscope. Atomic-force microscopy For atomic force microscopy, a 1 in. x 1 in. mica square was cleaved and transferred to a nitrogen-purged case. Prior to use, the mica was washed with methanol for at least 15 sec. and then rinsed with di-ionized (DI) water. A drop of the lysate sample was then pipetted on to the mica to allow particles to adsorb to the surface. The sample was then rewashed with DI water and dried with dry nitrogen. For AFM imaging, a Park Systems XE-70 AFM model was used in non-contact in-air mode, using a non-contact tip. The stated resolution of an unused noncontact tip is 2-3 nm. Light Transmission Spectroscopy
6
In order to make more detailed comparisons between cancer and normal PSDs, we have used a new technique developed by our group called light transmission spectroscopy (LTS). The basic operational principle of LTS is that the intensity of a transmitted light beam as a function of wavelength is measured at zero angle with respect to the incoming beam after it passes through a liquid suspension of nanoparticles [39]. By also using a reference channel containing the suspension fluid, the absolute value of the optical extinction due to the particles can be obtained over a broad spectral range (220 to 1100 nm) at high (1 nm) resolution. LTS also uses the measured wavelength-dependent optical extinction to obtain the particle distribution density (number of particles of a given diameter per unit diameter per unit volume, as a function of particle diameter) by performing spectral inversion using a Mie solution to Maxwell’s equations. This provides the number density, the total number of objects of a given diameter per unit volume, as a function of particle diameter, over a range of 1 – 3000 nm. In previous biological applications, LTS has been used to study the “growth” properties of liposomes [43], and is being applied to detect and quantify species-specific environmental DNA [44,45]. Note that some authors use the terms extinction, attenuation, and absorption interchangeably, although they are not always equivalent. Our apparatus measures the reduction in intensity, I , of a transmitted light beam due to both scattering and absorption through a finite length, z, of material. We report our results in terms of an extinction coefficient,
α . These quantities are mathematically related in Eqs. (1) and (2), according to the definition of extinction coefficient as the rate of reduction of the transmitted light [46].
dI = -α I dz
(1)
This expression leads to the well-known exponential decay law for the intensity as a function of distance,
7
Iout (z) = Iine− α z
(2)
where Iout and Iin are the output and input light intensities. Our apparatus and data collection scheme is a balanced optical spectrometer, designed to remove the effects of temporal fluctuations in the light source and the attenuation of the light beam due to the suspension fluid. The light intensity transmitted through the sample comprising nanoparticles in a suspension fluid, and separately through a sample of the suspension fluid alone, is simultaneously measured at many wavelengths, here typically from 220 nm to 1000 nm in 1 nm steps. From this information, the transmittance as a function of wavelength due to the nanoparticles alone, T (λ ) , is determined as described in our initial paper [39]. Transmittance is defined in Eq. (3), where
I(λ ) represents light intensity at each wavelength, z is the path length through the sample and reference, and
α (λ ) is the extinction coefficient at each wavelength due to the nanoparticles
present.
T(λ ) =
Iout (λ ) = e−α ( λ )z Iin (λ )
(3)
Iout (λ ) . Iin (λ )
(4)
where the extinction is defined as
α (λ )z = - lnT (λ ) = - ln
The path length in our apparatus is z = 1.0 cm, so the extinction is equal to the extinction coefficient in units of cm-1. As discussed in our original paper, this information is what is required to obtain the particle distribution density using the Mie model for spectral inversion. An additional piece of information is also required, and that is the wavelength-dependent dielectric constant of the material under study. Fortunately, the inversion is not highly sensitive to this and we have found that the dielectric properties of polystyrene (the dielectric constant of which is a
8
monotonic function of wavelength) are a good approximation to those of organic materials [43,44,45]. Actual measurements take place in the following manner. After mechanical processing, lysates were diluted to produce significant light transmission from ~ 220 to 1000 nm. A given lysate sample was pipetted into an optical cuvette and then placed in one optical channel of the LTS spectrometer and the suspension material (PBS in this case) was pipetted into an identical optical cuvette and placed in the second channel. Whole cells were similarly measured except without pre-processing. After a spectrum of both samples was obtained (taking less than one second), the cuvettes were exchanged and a second spectrum was obtained of both samples as described above. In this way any differences in the transmission properties of the optical paths and fluctuations in the light source were removed. In addition, this allows for the elimination of the effect of the optical extinction of the suspension material itself, so we are left with the extinction of the suspended nanoparticles exclusively. Results Whole-cell and lysate characterization by SEM and AFM Shown in Fig. 1 are representative SEM images typical of individual whole human oral normal and cancer cells used in this study. The cancer cells we examined were generally larger in diameter (~ 20 µm) compared to normal cells (~ 10 µm) and had less smooth surfaces. Fig. 2 shows an AFM scan of unfiltered cancer lysates rendered in three dimensions. This shows the relative particle density viewable with AFM and the fact that there are many sub-micron sized particles present. Fig. 3 shows more quantitative AFM scans of cancer and normal lysates in 2D mode. The image-analysis based distributions of the measured particle lengths are also shown, where we find the mean particle sizes for cancer and normal lysates to be 99 ± 40 nm and 108 ± 46 nm, respectively (essentially indistinguishable from this prospective). AFM is able to
9
image (only) those particles which have the highest overall number density (and smallest sizes), as will be more evident when we present further information below on particle distributions. Whole-cell and lysate characterization by LTS In this section we discuss the spectroscopic data we obtained with Light Transmission Spectroscopy (LTS) for whole cells and systematically filtered normal and cancer cell lysates. The idea is to establish the basic optical properties of these materials and the size distributions of the nanoparticles of which they are comprised. Unfiltered lysate material in PBS was initially measured and then this material was filtered by a succession of standard syringe filters and measured by LTS at each filtration stage. For these experiments, the absolute densities and growth rates of cancer and normal cells dictated that the normal- and cancer-cell-derived lysates were diluted by factors of 12 and 24, respectively, to achieve comparable optical extinction properties. We grew four distinct sets of cancer and normal cells on separate occasions, referred to as runs A, B, C, and D. Shown in Fig. 4 are the optical extinction (Eq. 4) results for a representative set of normal and cancer cells (run C). The plot shows results for whole cells, unfiltered lysates, and systematically filtered lysate materials. For each run, half of the cells harvested were used for lysis and the remaining cells were measured whole. To quantify differences in the normal and cancer extinction results, we took the value of the extinction at 259 nm and normalized it to the value of the extinction at 300 nm, to obtain the ratio (α 259 / α 300 )C for cancer cells and (α 259 / α 300 )N for normal cells. These quantities are designed to characterize the relative degree of UV extinction, represented by the peak value of the extinction we consistently see at 259 nm. Although the peak itself is likely associated with the presence of DNA it is a convenient standard reference point and generally scales with the more dominant background UV absorption. This is normalized by the “knee” value at 300 nm
10
that characterizes the extinction behavior at longer wavelengths. Using this procedure, the overall extinction results for systematic lysate filtration and whole cells are shown in Fig. 5. The individual ratios (α 259 / α 300 )C and (α 259 / α 300 )N can be viewed as indicating the degree to which smaller particles—which scatter more strongly at lower wavelengths—dominate the extinction process (scattering at 259 nm as compared to that at 300 nm) for cancer and normal cells. Thus, based on the results in Fig. 5, this implies that the normal materials have particle distributions with higher quantities of smaller particles than larger particles, as compared with cancer lysates, thus generally making (α 259 / α 300 )C / (α 259 / α 300 )N < 1. This is true for all filtrations except for 0.1 µm (the smallest pore size) where the effect vanishes. This suggests that when there are only particles smaller than 0.1 µm present, there are no longer sufficiently wide particle-size distributions to make the difference in small to large particles observable. Note that this ratio does not depend on the actual number of particles present, only their relative distributions, assuming a linear scaling of extinctions. Importantly, we note that results for whole cells are in good accord with those for unfiltered lysates, suggesting that the lysation process has, for this analysis, no significant effect on either the measured optical properties, or the particle distribution density. Thus, LTS appears to accurately probe the internal PSD of the whole cells. To understand this behavior in a more quantitative way, we have created a simple model based on the existence of two distinct particle populations: small particles that scatter significantly in the UV, and larger particles that do not. Assuming that the extinctions are determined by scattering factors a and b for small and large particles, respectively, times the numbers, ns and nL of small and large particles, respectively, that are present in the suspension, we can say that the extinction depends on these quantities in the following simple way
α = ans + bnL . Thus, for example, at 259 nm
11
(5)
α 259 = a259ns + b259nL = a259ns + f259a259nL
(6)
where f ≡ b/a. Thus we can write,
α 259 a259 α 300 C a300 C = α 259 a259 α 300 N a300 N
1+ f259 (nL / ns )C 1+ f (n / n ) 300 s C L 1+ f259 (nL / ns )N 1+ f (n / n ) 300 s N L
(7)
In order to simplify this expression we need to look in more detail at the particle distributions. Shown in Fig. 6 is the particle distribution density (the number of particles per mL per nm) for two representative runs (A and D) of cancer/normal unfiltered lysate and whole-cell samples as determined by LTS. Note that because of the large dynamic range available with LTS we have plotted the results on a log-log scale. This plot was created with the aforementioned Mie inversion procedure using data of the type presented in Fig. 4. Note that these results are consistent with the AFM results in showing a peak in particle density in the vicinity of 100 nm. What is apparent from Fig. 6 is: (1) that there are many more particles with small diameters, especially below ~ 250 nm; (2) that generally materials from normal cells are comprised of a larger number of smaller particles; and (3) that the number of the largest particles is roughly equal for cancer and normal materials. It is appropriate here to discuss overall starting densities. While the inversion process provides an absolute measure of the number of particles of a given diameter per unit volume in the PBS suspension medium for both normal and cancer lysates, the starting number of cells before lysis will differ, as will the volume of the cells and the dilutions of the lysates. It is important to note, however, that this dilution
12
process does not affect the quantity defined in Eq. 7, but could affect the absolute comparison of normal to cancer nanoparticle densities. To address this last point above we performed separate optical extinction comparisons of unfiltered normal and cancer lysates and starting whole cells. We also counted cells on the culture plates with an optical microscope prior to harvesting them. Based on this information, we believe that if we used as a reference a given absolute particle count (number of particles of a given diameter per volume) for, say, normal lysates, the corresponding count of the particles for cancer lysates of the same diameter, as scaled to the starting cellular volume, would be correct to within a factor of two (as represented by the extent of the plotted symbols in Fig. 6). Again, owing to the normalization procedure, Eq. 7, that was used to generate the results shown in Fig. 5, our conclusions are unaffected by the absolute densities of the normal and cancer lysates. We will address the issue of estimating the absolute particle count per cell after further discussion. We now return to our mathematical model (Eq. 7) and make the assumption that nL 1. Therefore, we can reduce Eq. 9 to Eq. 10 below, where A is a positive constant and where we have modeled the ratio of the large to small particles with a simple filter function. This parameterizes the step-by-step filtration we performed by the function nL / nS = [1+(B/d)2]-1, where d is the filter pore diameter and B represents a particle-size scale parameter for the system.
α 259 α n 300 C 1 = 1.0 − A L = 1.0 − A 2 α 259 1+ (B / d) ns N α 300 N
(10)
Fitting this expression to our data (Fig. 5) we obtain values of A = 0.3 and B = 0.25 µm. As seen in Fig. 6, this value of 0.25 µm (250 nm) is consistent with the general size demarcation between large populations of small particles (with diameters less than ~ 250 nm), and larger particles. The results shown in Fig. 6 represent the distribution density of the particles, which is the number of particles of a given diameter per nm per mL, as a function of particle diameter. In order to derive the particle density, the number of particles of a given diameter per mL as a function of particle diameter, we simply integrate the area under the peaks of Fig. 6. The results of this are shown in Fig. 7 where the plotted diameter is the maximum value for a given peak in the distribution density. Note that in the process of obtaining size information about particles from numerical inversions of extinction data (see Fig. 4) one issue that arises is what
14
the effect of the DNA peak (at 259 nm) may have on the inversion. We have done extensive simulations using both the original extinction curves, and those where the DNA peak was removed and replaced with smooth curves. Based on this analysis, the corresponding uncertainty in the results presented in Fig. 7 is represented by the given size of the plotting symbols. One clear result from Fig. 7 is the power-law dependence of particle density with diameter, here manifest as a linear dependence on this log-log plot. We can characterize this behavior with the simple power-law relation N(D)= kD −γ where N(D) is the number density (number of particles per unit volume) as a function of diameter, D. Since this formulation is scale free, the choice of k affects only the absolute density, whereas the exponent γ can be compared from system to system. The value of γ = 3.64 observed for our cancer and normal whole cells and lysates is in good accord with results for other PSDs for nano-particle suspensions in natural systems. This includes the well-described PSDs of suspended particles in aquatic ecosystems (with particles larger than 1 µm) which exhibit values of γ ranging from 3.03 to 4.33 with an average value of γ = 3.8 [47]. A second relevant study involved the PSDs of extracellular vesicles including exosomes and microvesicles 70 – 600 nm in diameter [48]. Here values of γ ranged from ~ 3.3 to 6.0, with an average value of 4.3. This suggests that the PSD for the internal nano-components of cells is comparable to those found elsewhere in nature. Also evident in this plot is the relative dominance of smaller particles for the normal unfiltered lysates and whole cells in the vicinity of ~ 100 nm and below, and a relative dominance for cancer unfiltered-lysate and whole-cell particles ~ 100 to 1000 nm in diameter. This transition-length scale of ~ 100 nm is consistent with our previous results from the analysis of the results in Fig. 5. To quantify the trends observed in Fig. 7, we have plotted in Fig. 8 the normalized difference between the cancer to normal particle densities (for both whole cells and
15
unfiltered lysates) as (NC – NN)/(NC + NN), where NC and NN are particle number densities (number of particles of a given diameter per mL) as plotted in Fig. 7. Fig. 8 clearly demonstrates the trend that was suggested by Fig. 7. We see definitively that (1) for 25 nm < D < 100 nm, there is a relative deficit of particles for cancer unfiltered lysates and whole cells and (2) for 100 < D < 1000 nm the situation is reversed and there is a relative excess of particles for cancer lysates and whole cells, where D is the particle diameter. We note that starting (harvested) samples comprised ~ 106 cells based on cell counting under a microscope. Based on this quantity (and accounting for the dilutions made with normal and cancer cells) we find that for unfiltered lysates there are ~ 104 – 106 particles/cell with diameters in the vicinity of 50 – 100 nm, and ~ 100 particles/cell with diameters in the vicinity of 1,000 – 1,500 nm. This appears to be consistent with the total expected numbers of smaller objects such as exosomes (50 – 100 nm), microvesicles (20 nm and greater), membrane particles (50 – 80 nm) and ribosomes (25 nm) [16, 38], and larger-size particles like organelles, larger membrane particles, and vesicles including lysosomes (250 - 800 nm), peroxisomes (200 – 1000 nm) and cytoplasmic inclusions like secretory granules, lipid granules, and pigment bodies (20 - 500nm). What is not clear is which if any of these well-known classes of nanoparticle systems within the cells is associated with the distinct particle-density imbalances we have observed for cancer as compared to normal cells. Conclusions In conclusion we have investigated the optical properties of cultured human oral cancer and normal whole cells and lysates. Our primary investigative tool was light transmission spectroscopy (LTS) which provides both the light extinction coefficient (from light absorption and scattering) as a function of wavelength from the UV to the infrared, and the particle size distribution (the number of particles of a given diameter as a function of diameter) in the 1 – 3000 nm range. We have found that cancer cells have a systematic defecit of particles in the
16
range of 25 – 100 nm and an excess of particles in the range of ~ 100 – 1000 nm compared to normal cells. Significantly, these results hold for measurements of both unfiltered lysates and the whole cells from which they were derived, implying that LTS can accurately probe the internal PSDs of whole cells. We have also found a clear power-law dependence for the overall PSD of our samples with an exponential coefficient of 3.64, which is comperable to results for other naturally-occuring PSDs for particles in liquid suspension. Acknowledgments We are grateful to the University of Notre Dame for support through the Faculty Research Support Program, and for Walter Johnson for theoretical guidance with this work.
17
Figure Captions Fig. 1. SEM images of whole normal (left) and cancer (right) cultured human oral cells. Fig. 2. AFM scan of cancer lysates in 3D mode. Fig. 3. AFM images of unfiltered cancer and normal lysates in 2D mode (top left and right images, respectively) and associated particle histograms. Fig. 4. Shown to the left and right are extinction data for normal and cancer, respectively, whole cells and systematically filtered lysates (Run C). Since the optical path length was 1.0 cm, the extinction coefficient,
α (in
units of cm-1), is here numerically equal to the (dimensionless) extinction,
αz .
Individual plots
represent results for a given level of filtration as indicated in the legend. Fig. 5. Optical extinction ratios as a function of inverse filter size (filter pore diameter) for cancer and normal lysates and unfiltered whole cells. Here, triangles, circles, squares, and diamonds correspond to Runs A, B, C and D respectively. Solid symbols represent lysates and open symbols represent whole cells. Also shown is a theoretical model calculation (see Eq. 10). Fig. 6. Shown on the left and right (data from representative runs A and D) are examples of the particle distribution density (number of particles per nm per mL) as a function of particle diameter for cancer and normal materials, shown as red and blue symbols, respectively. Open symbols represent whole cells and solid symbols represent unfiltered lysates. Fig. 7. Shown is the number density of particles (number of particles of a given diameter per mL) as a function of particle diameter for all runs conducted. Here, triangles, circles, squares, and diamonds correspond to Runs A, B, C and D, respectively. Red symbols are for cancer and blue for normal cell data. Solid symbols are for unfiltered lysates, open symbols for whole cells. Shown is a power-law fit and associated exponent (γ = 3.64) for these data. Fig. 8. Normalized relative number densities for nanoparticles in cancer and normal whole cells (open symbols) and for unfiltered lysates (solid symbols), derived from the results shown in Fig. 7. Cancer cells
18
show a relative deficit of particles with diameters 100 nm and below, and a relative excess of particles in the ~ 100 to 1000 nm diameter range. Fig. 8. Normalized relative number densities for nanoparticles in cancer and normal whole cells (open symbols) and for unfiltered lysates (solid symbols), derived from the results shown in Fig. 7. Cancer cells show a relative deficit of particles with diameters 100 nm and below, and a relative excess of particles in the ~ 100 to 1000 nm diameter range.
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normal whole cell
cancer whole cell
2.5
Normal
2 1.5
x 2.10
unfiltered 3.1 µm 1.2 µm 0.45 µm 0.25 µm 0.1 µm whole cell
1 0.5 0 200 250 300 350 400 450 500
Wavelength (nm)
Optical Extinction, αz
Optical Extinction, αz
3
3 2.5
Cancer
2 1.5
x 1.21
1 0.5 0 200 250 300 350 400 450 500
Wavelength (nm)
300 N
/α
1.2
0.4
259
300 C
) /(α
0.8
(α
1/0.1
1
/α
259
)
1.4
1/0.5 1/0.25
model
0.6
0.2
0
2
4
6
8
1/Filter Size (1/µm)
10
10
109 108 107 106 105 104 103 10
100
1000
Diameter (nm)
104
Distribution Density (1/nm*mL)
Distribution Density (1/nm*mL)
10
1010 109 108 107 106 10
5
104 103 10
100
1000
Diameter (nm)
104
Number Density (1/mL)
15
10
-3.64
D
13
10
11
10
9
10
7
10
5
10
3
10
1
10
2
10
3
10
Diameter (nm)
4
10
1 0.5
N
0 -0.5
C
C
N
(N - N )/(N + N )
1.5
-1 -1.5 1 10
2
10
3
10
Diameter (nm)
4
10
