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OPTICS LETTERS / Vol. 40, No. 7 / April 1, 2015
Brightness calibrates particle size in single particle fluorescence imaging Zhihe Liu,1 Zezhou Sun,1 Weihua Di,1 Weiping Qin,1 Zhen Yuan,2 and Changfeng Wu1,* 1
State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, Jilin 130012, China 2
Bioimaging Core, Faculty of Health Science, University of Macau, Taipa, Macau SAR, China *Corresponding author: [email protected] Received January 5, 2015; accepted February 17, 2015; posted February 20, 2015 (Doc. ID 231829); published March 19, 2015
This Letter provides a novel approach to quantify the particle sizes of highly bright semiconductor polymer dots (Pdots) for single-particle imaging and photobleaching studies. A quadratic dependence of single-particle brightness on particle size was determined by single-particle fluorescence imaging and intensity statistics. In terms of the same imaging conditions, the particle diameter can be quantified by comparing the individual brightness intensity with associated calibration curve. Based on this sizing method, photobleaching trajectories and overall photon counts emitted by single particles were analyzed. It is found that photobleaching rate constants of different sized Pdots are not strongly dependent on particle diameter except the sparsely occurring fluorescence blinking in certain dim particles and the rapid photobleaching component in some bright particles. The overall photon counts increase with increasing particle diameter. However, those larger than 30 nm deviate away from the increasing tendency. These results reveal the significance of selecting appropriate Pdots (≤30 nm) for single-particle imaging and tracking applications. © 2015 Optical Society of America OCIS codes: (180.2520) Fluorescence microscopy; (160.4236) Nanomaterials; (300.6280) Spectroscopy, fluorescence and luminescence. http://dx.doi.org/10.1364/OL.40.001242
Single-particle fluorescence imaging and tracking are playing a key role in investigating various cellular processes such as molecular transport, membrane dynamics, and the motion of motor proteins [1–5]. Quantification of the centroid of the images of individual fluorescent particles allows localization and tracking via the light microscopes at the accuracy of nanometer scale [6]. To generate high-quality images with high signal-to-noise ratio (SNR), the fluorescent properties of the probes, particularly the brightness and photostability, are extremely important. A variety of fluorescence probes including fluorescent dyes [7], fluorescent proteins [8], and inorganic quantum dots (Qdots) [9,10] have been successfully utilized for imaging and tracking of different biomolecules. In most cases, however, the brightness and photostability of current probes cannot satisfy the requirements of long-term imaging and photon-starved biological applications. Recently, semiconductor polymer dots (Pdots) have attracted considerable attention due to their superior properties in terms of the high brightness and excellent photostability [5,11]. The high brightness of fluorescent Pdots yielded a theoretical particle tracking uncertainty of less than 1 nm, and a lateral tracking uncertainty of 1–2 nm was determined according to the analysis of trajectories of fixed and freely diffusing particles [12]. Size distribution appears to be a ubiquitous phenomenon that significantly affects the optical properties of fluorescent nanoparticles. For example, Qdots exhibit size-dependent emission color, and their per-particle absorption cross-section increases cubically as a function of the particle radius [13]. Further, it is found that the emission color of Pdots is much less sensitive to particle size though the per-particle absorption cross-section is closely related to particle size [5]. However, for the previous work, the size variance is often ignored in 0146-9592/15/071242-04$15.00/0
single-particle studies because of the lack of an appropriate measure. Although commercial instruments from Nanosight can be used to quantify particle sizes of individual nanoparticles, their measurements are based on Brownian motion and not applicable for imaging and tracking of nanoparticle bioconjugates that usually move along certain directions. Here we present a novel approach for quantifying the particle size of highly bright Pdots in single-particle imaging and photobleaching studies. We establish a concrete relationship between single-particle brightness and particle size via single-particle fluorescence imaging and intensity statistics. At given excitation and collection conditions, the particle size of each nanoparticle can be extracted by comparing the individual brightness with the calibration curve. Based on this sizing method, we further investigate the size-dependent photobleaching and overall photon number emitted by single particles. Our results emphasize the importance of selecting appropriate particle size for single-particle imaging and tracking applications. The semiconducting polymer used in this study is poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-benzo-{2,1’,3}thiadiazole)] (PFBT, MW 115,000, polydispersity 3.2), purchased from ADS Dyes, Inc. (Quebec, Canada). The solvent tetrahydrofuran (THF, anhydrous, 99.9%) and the polymer poly(styrene co maleic anhydride) (PSMA, average MW ∼1; 700) were purchased from SigmaAldrich. Pdots were prepared by a two-step nanoprecipitation procedure modified from the previous reports [14,15]. The particle size and morphology of the PFBT Pdots were characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). DLS was performed using a 1-cm disposable polystyrene cuvette at 25°C with a Malvern Nano ZS instrument. Samples for TEM measurements were prepared by drop © 2015 Optical Society of America
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casting the Pdots dispersion onto copper grids. TEM images were obtained using a Hitachi H-600 microscope operated at 120 kV. Single-particle fluorescence imaging was performed by a custom-built total internal reflection fluorescence (TIRF) microscope. A 488-nm Sapphire laser beam (Coherent, USA) was directed into an inverted microscope (Olympus IX71, Japan) using steering optical lenses. The objective used for illumination and light collection was a 1.49-NA UAPON 100× TIRF objective (Olympus, Japan). Laser excitation power was measured at the nosepiece before the objective. Inside the microscope, fluorescence signal was filtered by a 500-nm-long pass filter and imaged on an Andor iXon3 frame transfer EMCCD (Andor Technology, UK). Fluorescence intensity emitted per particle in a given frame was estimated by integrating the CCD counts over the fluorescence spot. PFBT polymer was chosen in this study [Fig. 1(a)], because a number of single-particle imaging and tracking studies were performed on PFBT Pdots that exhibit high quantum yield and excellent photostability [5,12]. The preparation conditions were optimized for PFBT polymer to obtain Pdots of different sizes as the molecular weight and backbone rigidity affect the particles sizes. The polymer was dissolved in THF solution containing different volume fractions of water. We obtained PFBT nanoparticles with an average size of 12 nm using the precursor PFBT polymer in the pure THF solution. Under the same preparation conditions but increasing water fraction in precursor solutions, the resulting particle size increased as well. PFBT Pdots of 21, 37, and 58 nm were obtained when the ratio of water to THF was 5%, 10%, and 15%, respectively. The average particle sizes for these Pdots were measured by a DLS instrument, as
Fig. 1. (a) Chemical structure of semiconductor polymer PFBT and PSMA. The inset shows aqueous dispersions of PFBT nanoparticles under room light and UV light. (b) Dynamic light scattering (DLS) results of the semiconductor Pdots obtained by the two-step nanoprecipitation method. From the top to the bottom shows the DLS data of PFBT12, PFBT21, PFBT37, and PFBT58, respectively. (c) Typical transmission electron microscopy (TEM) image of PFBT37 Pdots.
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shown in Fig. 1(b). According to the average size, these Pdots were named as PFBT12, PFBT21, PFBT37, and PFBT58, respectively. The particle size and morphology were further characterized by transmission electron microscopy (TEM). Figure 1(c) shows a typical TEM image for PFBT37, indicating a spherical morphology. The DLS and TEM image reveals that size distribution is commonly observed for Pdots, although only the average size is usually indicated in most studies. Other sized Pdots also show spherical morphology and certain size distribution, which are consistent with previous reports [5]. Single-particle imaging and intensity statistics were performed to establish the relationship between the perparticle brightness and diameter of the Pdots. As the single-particle brightness increases nonlinearly with the diameter, the dynamic range of the CCD detector is not large enough to compare the four types of Pdots under the same excitation conditions. Correspondingly, we performed the comparative studies in three groups, i.e., PFBT12 versus PFBT21, PFBT21 versus PFBT37, and PFBT37 versus PFBT58, respectively. First, singleparticle fluorescence brightness was measured for PFBT12 and PFBT21 Pdots on the TIRF microscope under identical excitation and detection conditions. Figures 2(a) and 2(c) show single-particle fluorescence images of PFBT12 and PFBT21, respectively. As seen from the images, PFBT12 dots show bright diffractionlimited fluorescence spots, indicating these small dots are excellent candidates for single-particle imaging and tracking studies. PFBT21 exhibited an apparent improvement in signal-to-background ratio as compared to PFBT12 primarily due to the increased diameter. Fluorescence brightness per particle was calculated by integrating the CCD counts over the fluorescence spot. The intensity histograms were shown in Figs. 2(b) and 2(d) for PFBT12 and PFBT21, respectively. The intensity distributions can be well fitted with lognormal functions, which indicate that the average brightness of PFBT21 is 2.48 times higher than that of PFBT12. Imaging experiments were further performed for PFBT21 and PFBT37 by using low excitation power to avoid saturation of the CCD detector. The fluorescence images for the two types of Pdots indicated similar results, and a higher signal-to-background ratio was observed for PFBT37 as compared to PFBT21. The average per-particle brightness of the PFBT37 is 2.65 times higher than that of PFBT21. Likewise, another set of imaging and intensity analysis revealed that PFBT58 is 2.37 times brighter than PFBT37. After the three-group comparisons, the brightness intensities of the four types of Pdots were back-calculated by the respective intensity ratio and scaled up on the basis of the brightness intensity of PFBT12. Because the intensity statistics were done on a few thousands of single particles, it is reliable to correlate the average per-particle brightness with the average diameter measured by dynamic light scattering. Single-particle brightness is determined by the product of the per-particle absorption cross-section and the fluorescence quantum yield. Bulk spectroscopic measurements indicate that four types of PFBT dots have comparable fluorescent quantum yield (∼30%), therefore the per-particle brightness is primarily determined by the
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Fig. 2. Size-dependent single-particle brightness of different sized PFBT Pdots. (a) and (c) show the single-particle fluorescence images of PFBT12 and PFBT21, respectively, obtained under identical excitation and detection conditions. (b) and (d) show the intensity histograms by analyzing single-particle brightness of hundreds of nanoparticles. The black curves were obtained by fitting a lognormal distribution to the histogram, resulting in average intensities of 9515 and 23,627 counts for the PFBT12 and PFBT21, respectively. Scale bar represents 5 μm.
absorption cross-section. Ideally, the number of chromophores in a Pdot is proportional to the particle volume. Thus, the absorption cross-section, together with the per-particle brightness, is expected to follow a cubic dependence on the particle diameter. However, the experimental determined brightness is apparently deviated from the above model. Figure 3(a) shows the brightness intensities (up-scaled CCD counts) as a function of the particle diameter. The solid line represents a linear fitting
Fig. 3. (a) Size-dependent single-particle brightness intensity. The solid rectangles were the experiment data, and the red line shows the linear fitting of the log-log plot of the experimental data. (b), (c), and (d) show typical photobleaching curves of the medium, small, and large PFBT nanoparticles, respectively. The black lines represent the photobleaching trajectories, and the red lines were the fitting curves where single-exponential functions were used for (b) and (c), and a biexponential function for (d), respectively.
to the log-log plot of the data, yielding a slope of 1.95. The results and fitting clearly indicate a quadratic dependence of the per-particle brightness on particle diameter. This relationship is perhaps attributable to the excitation profile of the TIRF setup. Because the TIRF excitation is due to the evanescent field, which decays exponentially as a function of the distance from the coverslip surface, fluorescence of the Pdots likely originates from a thin layer excitation along the lateral direction, resulting in the fact that the brightness is largely dependent on the bottom section of the particle. Importantly, these results establish a concrete size-brightness relationship, providing an approach to evaluate the size variation in a broad range of single-particle imaging and tracking applications. The solid line in Fig. 3(a) serves as a calibration curve for determining the diameter of an unknown particle by comparing the single-particle brightness intensity to those of the standard Pdots under the same imaging conditions. Here, we utilize this approach to explore size-dependent photobleaching kinetics, which are hardly investigated in single-particle studies because of the lack of an approach for measuring the particle diameter in situ. As indicated by DLS in Fig. 1(b), PFBT21 Pdots show size distribution of ∼21 5 nm. We intentionally mixed a small portion of PFBT12 and PFBT37 to expand the size range. Under the same imaging conditions as those for the calibration curve, single-particle photobleaching trajectories were recorded by acquiring a series of consecutive frames. For a given particle, the average intensity in the first three frames was considered as the brightness of the particle because no apparent photobleaching was observed at this time. The particle diameter was then determined by comparing the brightness to the calibration curve. With the particle size determined, we perform further statistics to investigate the photobleaching behavior. Trajectories of hundreds of nanoparticles were plotted and analyzed. The photobleaching processes could be roughly categorized into three types. We noticed the majority of the particles possess medium brightness and exhibit continuous photobleaching behavior with no observable fluorescence blinking, as indicated by a typical trajectory in Fig. 3(b). For those particles, the trajectory can be well fitted by single-exponential decay kinetics, and the photobleaching rate constants were obtained by curve fitting. Meanwhile, some blinking was observed in a small portion of the Pdots that exhibits relatively low brightness (i.e., small size). Figure 3(c) shows a representative photobleaching curve with some sparse blinking behavior. Despite the intermittent fluorescence jump, the portion of the continuous photobleaching curve can still be described by a single-exponential decay. In addition, we noticed some Pdots that possess relatively high brightness (i.e., large size) exhibited a rapid decrease in the first few seconds followed by a relatively slow bleaching process [Fig. 3(d)]. The rapid decrease is likely due to the formation of photo-induced hole polarons or other defects that quench the Pdot fluorescence [16]. The photobleaching kinetics can be reproduced by a bi-exponential decay function, which generally indicates the presence of two or more distinct decaying channels, possibly due to the difference in energetic
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Fig. 4. (a) The scatter plot of the photobleaching rate constants of Pdots versus particle diameter. (b) The overall photon counts of Pdots as a function of particle diameter.
disorder, chain packing morphology, and intraparticle energy transfer from higher energy excitations to lower energy state or defects [16,17]. Because the fraction of emitted photons associated with the rapidly decaying component is small, we use the slow photobleaching rate constant for further analysis. Figure 4(a) shows the scatter plot of the photobleaching rate constant versus particle diameter. As seen from the Figure, the majority of the Pdots exhibit photobleaching rate constants ranging from 10 s to 40 s (circled by the red oval). These results indicate that photobleaching rate constants of small particles (30 nm). The overall photon counts detected for a given particle before irreversible photobleaching can be estimated by integrating the area underneath the respective photobleaching curve. As shown in Fig. 4(b), the overall photon counts exhibit apparent increase with increasing particle diameter. Assuming Pdots of different size possess comparable photobleaching rate constants, the overall photon counts are expected to follow a quadratic dependence on the particle diameter. However, the experimental data are deviated from the relationship, particularly for those particles larger than 30 nm, which generate photons much less than what are estimated by particle size [Fig. 4(b)]. This observation, i.e., the relatively low photon counts in large particles, is consistent with the presence of the initial rapidly decaying component in these particles. These results suggest that it is much better to select Pdots of ∼30 nm diameter or slightly smaller for single-particle imaging and tracking, rather than larger Pdots, because larger Pdots do not generate more photons as expected, and larger particles may also place hydrodynamic drag on biomolecules in tracking experiments. In summary, this study provides an approach for quantifying the particle size of highly bright Pdots in singleparticle fluorescence studies. By single-particle imaging and statistics, the per-particle brightness was determined to follow a quadratic dependence on particle size. Under
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given imaging conditions, the particle diameter can be extracted by comparing the individual brightness intensity with a calibration curve. Based on the sizing information, size-dependent photobleaching and overall photon counts emitted by single particles were analyzed. The photobleaching processes could be roughly categorized into three types. Photobleaching rate constants of small Pdots (30 nm) exhibit a rapid photobleaching component followed by a relatively slow bleaching process. The overall photon counts increase with increasing particle diameter, but those larger than 30 nm do not generate more photons as expected from size increase. This study provides a useful guidance for selecting appropriate Pdots (≤30 nm) for single-particle imaging and tracking applications. Changfeng Wu acknowledges financial support from “Thousand Young Talents Program” and the National Science Foundation of China (Grant Nos. 61222508 and 61335001). This research is also supported by the SRG2013-00035-FHS Grant and the MYRG2014-00093FHS Grant from University of Macau in Macau. References 1. A. Yildiz, J. N. Forkey, S. A. McKinney, T. Ha, Y. E. Goldman, and P. R. Selvin, Science 300, 2061 (2003). 2. G. W. Li and X. S. Xie, Nature 475, 308 (2011). 3. X. S. Xie, P. J. Choi, G. W. Li, N. K. Lee, and G. Lia, Annu. Rev. Biophys. 37, 417 (2008). 4. M. Goulian and S. M. Simon, Biophys. J. 79, 2188 (2000). 5. C. F. Wu, B. Bull, C. Szymanski, K. Christensen, and J. McNeill, ACS Nano 2, 2415 (2008). 6. R. E. Thompson, D. R. Larson, and W. W. Webb, Biophys. J. 82, 2775 (2002). 7. D. Magde, R. Wong, and P. G. Seybold, Photochem. Photobiol. 75, 327 (2002). 8. B. N. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien, Science 312, 217 (2006). 9. R. G. Ute, G. Markus, C. J. Sara, N. Roland, and N. Thomas, Nat. Methods 5, 763 (2008). 10. F. Pinaud, S. Clarke, A. Sittner, and M. Dahan, Nat. Methods 7, 275 (2010). 11. C. F. Wu, C. Szymanski, Z. Cain, and J. McNeill, J. Am. Chem. Soc. 129, 12904 (2007). 12. J. B. Yu, C. F. Wu, S. P. Sahu, L. P. Fernando, C. Szymanski, and J. McNeill, J. Am. Chem. Soc. 131, 18410 (2009). 13. F. Mafune, J. Y. Kohno, Y. Takeda, and T. Kondow, J. Phys. Chem. B 256, 7619 (2002). 14. C. F. Wu, C. Szymanski, and J. McNeill, Langmuir 22, 2956 (2006). 15. K. Sun, H. B. Chen, L. Wang, S. Y. Yin, H. Y. Wang, G. X. Xu, D. N. Chen, X. J. Zhang, C. F. Wu, and W. P. Qin, ACS Appl. Mater. Interfaces 6, 10802 (2014). 16. J. B. Yu, C. F. Wu, Z. Y. Tian, and J. McNeill, Nano Lett. 12, 1300 (2012). 17. C. F. Wu, Y. L. Zheng, C. Szymanski, and J. McNeill, J. Phys. Chem. C 112, 1172 (2008).
OPTICS LETTERS / Vol. 40, No. 7 / April 1, 2015
Brightness calibrates particle size in single particle fluorescence imaging Zhihe Liu,1 Zezhou Sun,1 Weihua Di,1 Weiping Qin,1 Zhen Yuan,2 and Changfeng Wu1,* 1
State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, Jilin 130012, China 2
Bioimaging Core, Faculty of Health Science, University of Macau, Taipa, Macau SAR, China *Corresponding author: [email protected] Received January 5, 2015; accepted February 17, 2015; posted February 20, 2015 (Doc. ID 231829); published March 19, 2015
This Letter provides a novel approach to quantify the particle sizes of highly bright semiconductor polymer dots (Pdots) for single-particle imaging and photobleaching studies. A quadratic dependence of single-particle brightness on particle size was determined by single-particle fluorescence imaging and intensity statistics. In terms of the same imaging conditions, the particle diameter can be quantified by comparing the individual brightness intensity with associated calibration curve. Based on this sizing method, photobleaching trajectories and overall photon counts emitted by single particles were analyzed. It is found that photobleaching rate constants of different sized Pdots are not strongly dependent on particle diameter except the sparsely occurring fluorescence blinking in certain dim particles and the rapid photobleaching component in some bright particles. The overall photon counts increase with increasing particle diameter. However, those larger than 30 nm deviate away from the increasing tendency. These results reveal the significance of selecting appropriate Pdots (≤30 nm) for single-particle imaging and tracking applications. © 2015 Optical Society of America OCIS codes: (180.2520) Fluorescence microscopy; (160.4236) Nanomaterials; (300.6280) Spectroscopy, fluorescence and luminescence. http://dx.doi.org/10.1364/OL.40.001242
Single-particle fluorescence imaging and tracking are playing a key role in investigating various cellular processes such as molecular transport, membrane dynamics, and the motion of motor proteins [1–5]. Quantification of the centroid of the images of individual fluorescent particles allows localization and tracking via the light microscopes at the accuracy of nanometer scale [6]. To generate high-quality images with high signal-to-noise ratio (SNR), the fluorescent properties of the probes, particularly the brightness and photostability, are extremely important. A variety of fluorescence probes including fluorescent dyes [7], fluorescent proteins [8], and inorganic quantum dots (Qdots) [9,10] have been successfully utilized for imaging and tracking of different biomolecules. In most cases, however, the brightness and photostability of current probes cannot satisfy the requirements of long-term imaging and photon-starved biological applications. Recently, semiconductor polymer dots (Pdots) have attracted considerable attention due to their superior properties in terms of the high brightness and excellent photostability [5,11]. The high brightness of fluorescent Pdots yielded a theoretical particle tracking uncertainty of less than 1 nm, and a lateral tracking uncertainty of 1–2 nm was determined according to the analysis of trajectories of fixed and freely diffusing particles [12]. Size distribution appears to be a ubiquitous phenomenon that significantly affects the optical properties of fluorescent nanoparticles. For example, Qdots exhibit size-dependent emission color, and their per-particle absorption cross-section increases cubically as a function of the particle radius [13]. Further, it is found that the emission color of Pdots is much less sensitive to particle size though the per-particle absorption cross-section is closely related to particle size [5]. However, for the previous work, the size variance is often ignored in 0146-9592/15/071242-04$15.00/0
single-particle studies because of the lack of an appropriate measure. Although commercial instruments from Nanosight can be used to quantify particle sizes of individual nanoparticles, their measurements are based on Brownian motion and not applicable for imaging and tracking of nanoparticle bioconjugates that usually move along certain directions. Here we present a novel approach for quantifying the particle size of highly bright Pdots in single-particle imaging and photobleaching studies. We establish a concrete relationship between single-particle brightness and particle size via single-particle fluorescence imaging and intensity statistics. At given excitation and collection conditions, the particle size of each nanoparticle can be extracted by comparing the individual brightness with the calibration curve. Based on this sizing method, we further investigate the size-dependent photobleaching and overall photon number emitted by single particles. Our results emphasize the importance of selecting appropriate particle size for single-particle imaging and tracking applications. The semiconducting polymer used in this study is poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-benzo-{2,1’,3}thiadiazole)] (PFBT, MW 115,000, polydispersity 3.2), purchased from ADS Dyes, Inc. (Quebec, Canada). The solvent tetrahydrofuran (THF, anhydrous, 99.9%) and the polymer poly(styrene co maleic anhydride) (PSMA, average MW ∼1; 700) were purchased from SigmaAldrich. Pdots were prepared by a two-step nanoprecipitation procedure modified from the previous reports [14,15]. The particle size and morphology of the PFBT Pdots were characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). DLS was performed using a 1-cm disposable polystyrene cuvette at 25°C with a Malvern Nano ZS instrument. Samples for TEM measurements were prepared by drop © 2015 Optical Society of America
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casting the Pdots dispersion onto copper grids. TEM images were obtained using a Hitachi H-600 microscope operated at 120 kV. Single-particle fluorescence imaging was performed by a custom-built total internal reflection fluorescence (TIRF) microscope. A 488-nm Sapphire laser beam (Coherent, USA) was directed into an inverted microscope (Olympus IX71, Japan) using steering optical lenses. The objective used for illumination and light collection was a 1.49-NA UAPON 100× TIRF objective (Olympus, Japan). Laser excitation power was measured at the nosepiece before the objective. Inside the microscope, fluorescence signal was filtered by a 500-nm-long pass filter and imaged on an Andor iXon3 frame transfer EMCCD (Andor Technology, UK). Fluorescence intensity emitted per particle in a given frame was estimated by integrating the CCD counts over the fluorescence spot. PFBT polymer was chosen in this study [Fig. 1(a)], because a number of single-particle imaging and tracking studies were performed on PFBT Pdots that exhibit high quantum yield and excellent photostability [5,12]. The preparation conditions were optimized for PFBT polymer to obtain Pdots of different sizes as the molecular weight and backbone rigidity affect the particles sizes. The polymer was dissolved in THF solution containing different volume fractions of water. We obtained PFBT nanoparticles with an average size of 12 nm using the precursor PFBT polymer in the pure THF solution. Under the same preparation conditions but increasing water fraction in precursor solutions, the resulting particle size increased as well. PFBT Pdots of 21, 37, and 58 nm were obtained when the ratio of water to THF was 5%, 10%, and 15%, respectively. The average particle sizes for these Pdots were measured by a DLS instrument, as
Fig. 1. (a) Chemical structure of semiconductor polymer PFBT and PSMA. The inset shows aqueous dispersions of PFBT nanoparticles under room light and UV light. (b) Dynamic light scattering (DLS) results of the semiconductor Pdots obtained by the two-step nanoprecipitation method. From the top to the bottom shows the DLS data of PFBT12, PFBT21, PFBT37, and PFBT58, respectively. (c) Typical transmission electron microscopy (TEM) image of PFBT37 Pdots.
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shown in Fig. 1(b). According to the average size, these Pdots were named as PFBT12, PFBT21, PFBT37, and PFBT58, respectively. The particle size and morphology were further characterized by transmission electron microscopy (TEM). Figure 1(c) shows a typical TEM image for PFBT37, indicating a spherical morphology. The DLS and TEM image reveals that size distribution is commonly observed for Pdots, although only the average size is usually indicated in most studies. Other sized Pdots also show spherical morphology and certain size distribution, which are consistent with previous reports [5]. Single-particle imaging and intensity statistics were performed to establish the relationship between the perparticle brightness and diameter of the Pdots. As the single-particle brightness increases nonlinearly with the diameter, the dynamic range of the CCD detector is not large enough to compare the four types of Pdots under the same excitation conditions. Correspondingly, we performed the comparative studies in three groups, i.e., PFBT12 versus PFBT21, PFBT21 versus PFBT37, and PFBT37 versus PFBT58, respectively. First, singleparticle fluorescence brightness was measured for PFBT12 and PFBT21 Pdots on the TIRF microscope under identical excitation and detection conditions. Figures 2(a) and 2(c) show single-particle fluorescence images of PFBT12 and PFBT21, respectively. As seen from the images, PFBT12 dots show bright diffractionlimited fluorescence spots, indicating these small dots are excellent candidates for single-particle imaging and tracking studies. PFBT21 exhibited an apparent improvement in signal-to-background ratio as compared to PFBT12 primarily due to the increased diameter. Fluorescence brightness per particle was calculated by integrating the CCD counts over the fluorescence spot. The intensity histograms were shown in Figs. 2(b) and 2(d) for PFBT12 and PFBT21, respectively. The intensity distributions can be well fitted with lognormal functions, which indicate that the average brightness of PFBT21 is 2.48 times higher than that of PFBT12. Imaging experiments were further performed for PFBT21 and PFBT37 by using low excitation power to avoid saturation of the CCD detector. The fluorescence images for the two types of Pdots indicated similar results, and a higher signal-to-background ratio was observed for PFBT37 as compared to PFBT21. The average per-particle brightness of the PFBT37 is 2.65 times higher than that of PFBT21. Likewise, another set of imaging and intensity analysis revealed that PFBT58 is 2.37 times brighter than PFBT37. After the three-group comparisons, the brightness intensities of the four types of Pdots were back-calculated by the respective intensity ratio and scaled up on the basis of the brightness intensity of PFBT12. Because the intensity statistics were done on a few thousands of single particles, it is reliable to correlate the average per-particle brightness with the average diameter measured by dynamic light scattering. Single-particle brightness is determined by the product of the per-particle absorption cross-section and the fluorescence quantum yield. Bulk spectroscopic measurements indicate that four types of PFBT dots have comparable fluorescent quantum yield (∼30%), therefore the per-particle brightness is primarily determined by the
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Fig. 2. Size-dependent single-particle brightness of different sized PFBT Pdots. (a) and (c) show the single-particle fluorescence images of PFBT12 and PFBT21, respectively, obtained under identical excitation and detection conditions. (b) and (d) show the intensity histograms by analyzing single-particle brightness of hundreds of nanoparticles. The black curves were obtained by fitting a lognormal distribution to the histogram, resulting in average intensities of 9515 and 23,627 counts for the PFBT12 and PFBT21, respectively. Scale bar represents 5 μm.
absorption cross-section. Ideally, the number of chromophores in a Pdot is proportional to the particle volume. Thus, the absorption cross-section, together with the per-particle brightness, is expected to follow a cubic dependence on the particle diameter. However, the experimental determined brightness is apparently deviated from the above model. Figure 3(a) shows the brightness intensities (up-scaled CCD counts) as a function of the particle diameter. The solid line represents a linear fitting
Fig. 3. (a) Size-dependent single-particle brightness intensity. The solid rectangles were the experiment data, and the red line shows the linear fitting of the log-log plot of the experimental data. (b), (c), and (d) show typical photobleaching curves of the medium, small, and large PFBT nanoparticles, respectively. The black lines represent the photobleaching trajectories, and the red lines were the fitting curves where single-exponential functions were used for (b) and (c), and a biexponential function for (d), respectively.
to the log-log plot of the data, yielding a slope of 1.95. The results and fitting clearly indicate a quadratic dependence of the per-particle brightness on particle diameter. This relationship is perhaps attributable to the excitation profile of the TIRF setup. Because the TIRF excitation is due to the evanescent field, which decays exponentially as a function of the distance from the coverslip surface, fluorescence of the Pdots likely originates from a thin layer excitation along the lateral direction, resulting in the fact that the brightness is largely dependent on the bottom section of the particle. Importantly, these results establish a concrete size-brightness relationship, providing an approach to evaluate the size variation in a broad range of single-particle imaging and tracking applications. The solid line in Fig. 3(a) serves as a calibration curve for determining the diameter of an unknown particle by comparing the single-particle brightness intensity to those of the standard Pdots under the same imaging conditions. Here, we utilize this approach to explore size-dependent photobleaching kinetics, which are hardly investigated in single-particle studies because of the lack of an approach for measuring the particle diameter in situ. As indicated by DLS in Fig. 1(b), PFBT21 Pdots show size distribution of ∼21 5 nm. We intentionally mixed a small portion of PFBT12 and PFBT37 to expand the size range. Under the same imaging conditions as those for the calibration curve, single-particle photobleaching trajectories were recorded by acquiring a series of consecutive frames. For a given particle, the average intensity in the first three frames was considered as the brightness of the particle because no apparent photobleaching was observed at this time. The particle diameter was then determined by comparing the brightness to the calibration curve. With the particle size determined, we perform further statistics to investigate the photobleaching behavior. Trajectories of hundreds of nanoparticles were plotted and analyzed. The photobleaching processes could be roughly categorized into three types. We noticed the majority of the particles possess medium brightness and exhibit continuous photobleaching behavior with no observable fluorescence blinking, as indicated by a typical trajectory in Fig. 3(b). For those particles, the trajectory can be well fitted by single-exponential decay kinetics, and the photobleaching rate constants were obtained by curve fitting. Meanwhile, some blinking was observed in a small portion of the Pdots that exhibits relatively low brightness (i.e., small size). Figure 3(c) shows a representative photobleaching curve with some sparse blinking behavior. Despite the intermittent fluorescence jump, the portion of the continuous photobleaching curve can still be described by a single-exponential decay. In addition, we noticed some Pdots that possess relatively high brightness (i.e., large size) exhibited a rapid decrease in the first few seconds followed by a relatively slow bleaching process [Fig. 3(d)]. The rapid decrease is likely due to the formation of photo-induced hole polarons or other defects that quench the Pdot fluorescence [16]. The photobleaching kinetics can be reproduced by a bi-exponential decay function, which generally indicates the presence of two or more distinct decaying channels, possibly due to the difference in energetic
April 1, 2015 / Vol. 40, No. 7 / OPTICS LETTERS
Fig. 4. (a) The scatter plot of the photobleaching rate constants of Pdots versus particle diameter. (b) The overall photon counts of Pdots as a function of particle diameter.
disorder, chain packing morphology, and intraparticle energy transfer from higher energy excitations to lower energy state or defects [16,17]. Because the fraction of emitted photons associated with the rapidly decaying component is small, we use the slow photobleaching rate constant for further analysis. Figure 4(a) shows the scatter plot of the photobleaching rate constant versus particle diameter. As seen from the Figure, the majority of the Pdots exhibit photobleaching rate constants ranging from 10 s to 40 s (circled by the red oval). These results indicate that photobleaching rate constants of small particles (30 nm). The overall photon counts detected for a given particle before irreversible photobleaching can be estimated by integrating the area underneath the respective photobleaching curve. As shown in Fig. 4(b), the overall photon counts exhibit apparent increase with increasing particle diameter. Assuming Pdots of different size possess comparable photobleaching rate constants, the overall photon counts are expected to follow a quadratic dependence on the particle diameter. However, the experimental data are deviated from the relationship, particularly for those particles larger than 30 nm, which generate photons much less than what are estimated by particle size [Fig. 4(b)]. This observation, i.e., the relatively low photon counts in large particles, is consistent with the presence of the initial rapidly decaying component in these particles. These results suggest that it is much better to select Pdots of ∼30 nm diameter or slightly smaller for single-particle imaging and tracking, rather than larger Pdots, because larger Pdots do not generate more photons as expected, and larger particles may also place hydrodynamic drag on biomolecules in tracking experiments. In summary, this study provides an approach for quantifying the particle size of highly bright Pdots in singleparticle fluorescence studies. By single-particle imaging and statistics, the per-particle brightness was determined to follow a quadratic dependence on particle size. Under
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given imaging conditions, the particle diameter can be extracted by comparing the individual brightness intensity with a calibration curve. Based on the sizing information, size-dependent photobleaching and overall photon counts emitted by single particles were analyzed. The photobleaching processes could be roughly categorized into three types. Photobleaching rate constants of small Pdots (30 nm) exhibit a rapid photobleaching component followed by a relatively slow bleaching process. The overall photon counts increase with increasing particle diameter, but those larger than 30 nm do not generate more photons as expected from size increase. This study provides a useful guidance for selecting appropriate Pdots (≤30 nm) for single-particle imaging and tracking applications. Changfeng Wu acknowledges financial support from “Thousand Young Talents Program” and the National Science Foundation of China (Grant Nos. 61222508 and 61335001). This research is also supported by the SRG2013-00035-FHS Grant and the MYRG2014-00093FHS Grant from University of Macau in Macau. References 1. A. Yildiz, J. N. Forkey, S. A. McKinney, T. Ha, Y. E. Goldman, and P. R. Selvin, Science 300, 2061 (2003). 2. G. W. Li and X. S. Xie, Nature 475, 308 (2011). 3. X. S. Xie, P. J. Choi, G. W. Li, N. K. Lee, and G. Lia, Annu. Rev. Biophys. 37, 417 (2008). 4. M. Goulian and S. M. Simon, Biophys. J. 79, 2188 (2000). 5. C. F. Wu, B. Bull, C. Szymanski, K. Christensen, and J. McNeill, ACS Nano 2, 2415 (2008). 6. R. E. Thompson, D. R. Larson, and W. W. Webb, Biophys. J. 82, 2775 (2002). 7. D. Magde, R. Wong, and P. G. Seybold, Photochem. Photobiol. 75, 327 (2002). 8. B. N. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien, Science 312, 217 (2006). 9. R. G. Ute, G. Markus, C. J. Sara, N. Roland, and N. Thomas, Nat. Methods 5, 763 (2008). 10. F. Pinaud, S. Clarke, A. Sittner, and M. Dahan, Nat. Methods 7, 275 (2010). 11. C. F. Wu, C. Szymanski, Z. Cain, and J. McNeill, J. Am. Chem. Soc. 129, 12904 (2007). 12. J. B. Yu, C. F. Wu, S. P. Sahu, L. P. Fernando, C. Szymanski, and J. McNeill, J. Am. Chem. Soc. 131, 18410 (2009). 13. F. Mafune, J. Y. Kohno, Y. Takeda, and T. Kondow, J. Phys. Chem. B 256, 7619 (2002). 14. C. F. Wu, C. Szymanski, and J. McNeill, Langmuir 22, 2956 (2006). 15. K. Sun, H. B. Chen, L. Wang, S. Y. Yin, H. Y. Wang, G. X. Xu, D. N. Chen, X. J. Zhang, C. F. Wu, and W. P. Qin, ACS Appl. Mater. Interfaces 6, 10802 (2014). 16. J. B. Yu, C. F. Wu, Z. Y. Tian, and J. McNeill, Nano Lett. 12, 1300 (2012). 17. C. F. Wu, Y. L. Zheng, C. Szymanski, and J. McNeill, J. Phys. Chem. C 112, 1172 (2008).
