Telomerase Activity Detection with Amplification-Free Single Molecule

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Telomerase Activity Detection with AmplificationFree Single Molecule Stochastic Binding Assay Xin Su, Zehao Li, Xinzhong Yan, Lei Wang, Xu Zhou, Lin Wei, Lehui Xiao, and Changyuan Yu Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b04883 • Publication Date (Web): 20 Feb 2017 Downloaded from http://pubs.acs.org on February 20, 2017

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Analytical Chemistry

Telomerase Activity Detection with Amplification-Free Single Molecule Stochastic Binding Assay Xin Su,† Zehao Li,† Xinzhong Yan,† Lei Wang,† Xu Zhou,† Lin Wei,‡ Lehui Xiao*,‡,§ and Changyuan Yu*,†

†

College of Life Science and Technology, Beijing University of Chemical Technology, Beijing,

China, 100029. ‡

Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research, Ministry of

Education, Key Laboratory of Phytochemical R&D of Hunan Province, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, 410081, China. §

College of Chemistry, Nankai University, Tianjin, 300071, China.

*

Corresponding author

Email: [email protected], [email protected] Fax: +86-022-23500201

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Abstract Since the elongation of telomeres is associated with tumorigenesis, it is of great interest to develop rapid and high-confidence telomerase activity detection methods for disease diagnosis. Currently, amplification based strategies have been extensively explored for telomerase detection in vitro and in vivo. However, amplification typically associated with poor reproducibility and high background which hamper their further applications particularly for real sample assay. Here, we demonstrated a new amplification-free single molecule imaging method for telomerase activity detection in vitro based on nucleic acid stochastic binding with total internal reflection fluorescence microscopy (TIRFM). The dynamic stochastic binding of short fluorescent DNA probe with genuine target yields a distinct kinetic signature from the background noise, allowing us to identify telomerase reaction products (TRPs) at single molecule level. A limit-of-detection (LOD) as low as 0.5 fM and a dynamic range of 0.5-500 fM for TRPs detection were readily achieved. With this method, telomerase extracted from cancer cells was determined with sensitivity down to 10 cells. Moreover, the length distribution of TRPs was also determined by multiple stochastic probing which would provide deep insight into the mechanistic study of telomerase catalysis.

Keywords Single molecule imaging; Telomerase activity; Nucleic acid probe; Stochastic binding; Enzyme processivity


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Introduction In cancer cells, telomeres can be elongated by telomerase which is a ribonucleoprotein reverse transcriptase that catalyzes the addition of telomeric repeats (TTAGGG)n onto the end of human chromosomes.1 The elongation of telomeres is believed associated with tumorigenesis.2 Telomerase has been a promising target for cancer diagnosis and therapeutics as it is overexpressed in the majority of cancer cells as well as in cancer stem (or stem-like) cells.3 Studying the telomerase activity is therefore of great importance for cancer related basic and clinical research. Much effort has been made to detect telomerase activity, and most of them rely on amplification-based techniques. The most widely used method is telomeric repeat amplification protocol (TRAP).4,5 The apparent limitations of TRAP are long reaction time and false positive readout. A variety of PCR-free methods based on fluorescence or electrochemical signal amplification have been developed.6-11 Although these methods possess high sensitivity, they also suffer from poor reproducibility and high background caused by the signal amplification steps. Moreover, telomerase is known as a processive enzyme.12 These methods only provide telomerase activity measurement and do not study the length of telomerase reaction products (TRPs) which is believed to reflect the ratio of the rate of DNA translocation and DNA dissociation in human telomerase reverse transcriptase (hTERT).13 Multiple evolutionarily conserved domains within hTERT proteins are contributing to promote the telomerase processivity.14,15 Understanding the length distribution of TRPs can offer deep insight into the telomerase catalysis mechanism. In this regard, high-confidence and amplification-free method is therefore urgently needed for telomerase activity detection as well as TRPs length quantification. Single-molecule detection is a powerful tool for biomolecule analysis with high sensitivity.16,17 In vitro detection of target objects at single molecule level can be readily achieved inside a flow channel with total internal reflection fluorescence microscopy (TIRFM). Fang and co-workers designed an interesting experiment to disclose the single molecule dynamics of transforming growth factor receptor on TIRFM, providing mechanistic insight for the activation of TGF-β receptors.18 Zhang and co-workers developed a highly sensitive method for protein kinase detection on TIRFM by taking the advantages of quantum dots and single-molecule fluorescence detection.19 Li et al. developed single-molecule-detection microarray on TIRFM for gene expression analysis.20 Myong and co-workers monitored the activity of telomerase at single



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molecule level on TIRFM.21 These single molecule approaches not only provided high sensitivity but also disclosed biomolecule interaction mechanisms. However, the main limitations of these direct single molecule counting-based approaches are the false positive and negative readouts caused by the nonspecific binding of probe and irreversible photo-bleaching from fluorescent dyes respectively. Short DNA oligonucleotides (diffusing strands) can stochastically bind with complementary “docking” strands immobilized on slides surface.22,23 Fluorescently-labeled diffusing strands in the bound state can be specifically illuminated due to the excitation geometry of TIRFM. Thus, the binding of probe with its target possesses unique kinetic signature, which can be easily discriminated from nonspecific binding events. Distinct from regular single molecule imaging methods, this approach is resistant to photobleaching because those fluorescent probes could be recycled rapidly. Based on this technique, DNA-point accumulation imaging in nanoscale topography (DNA-PAINT) and quantitative-PAINT (qPAINT) have been developed for subcellular super-resolution imaging24 and biomolecules counting inside cells.25 Inspired by DNA-PAINT, we have demonstrated a kinetic fingerprinting approach for the amplification-free detection of nucleic acids, which also allows direct quantification of miRNA biomarker in clinical biofluids.26 In this work, we demonstrated a new single molecule approach for the amplification-free telomerase activity detection by stochastically probing telomeric repeats with TIRFM for the first time. By taking the advantage of stochastic binding assay, TRPs can be identified at single molecule level without additional signal amplification. True targets can be confidently discriminated from background according to the featured kinetic signature of nucleic acid transient hybridization, affording “background-free” telomerase activity detection. With this method, telomerase extracted from cancer cells was accurately detected with sensitivity down to 10 cells within 10 min. Multiple stochastic probing approach was also developed to disclose the length distribution of TRPs, which would provide deep insight into the mechanistic study of telomerase catalysis. In contrast to fluorescent intensity based assay that requires complicated photobleaching steps and is disturbed by the inhomogeneity of excitation source, the quantity and length distribution information of TRPs were investigated by the frequency of stochastic binding. As a consequence, owing to the attractive merits as described above, this approach


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would find broad applications in diverse areas, including cancer diagnosis, drug screening and so on.

Experimental Section Materials. Oligonucleotides were synthesized and purified by HPLC (Sangon, Shanghai, China) and their sequences are listed in Table S1. (3-Aminopropyl)triethoxysilane (APTES), 3,4dihydroxybenzoate (PCA), protocatechuate dioxygenase (PCD) and Trolox were from SigmaAldrich (St. Louis, MO). mPEG-succinimidyl valerate (mPEG-SVA, MW, 5000), biotin-PEGsuccinimidyl valerate (biotin-PEG-SVA, MW, 5000) and sulfo-disuccinimidyl tartarate and (Sulfo-DST) were obtained from SeeBio Co. (Shanghai, China). The CHAPS lysis buffer was purchased from Millipore (Bedford, MA, USA). All chemicals were used as received without additional purification. Hela, MCF-7, LO-2, A549 and A375 cell lines were purchased from ATCC (Manassas, VA). DNase/RNase free deionized water from Tiangen Biotech Co. (Beijing, China) was used in all experiments. Slide preparation and total internal reflection fluorescence microscope setup. Quartz slides were PEGylated by using previously reported method27. Briefly, the slides were treated with aminopropyltriethoxysilane (APTES) in acetone (1/50) for 15 min followed by reacting with 10:1 mixture of mPEG and biotin-PEG for 3 h. Next, remained APTES was quenched by reacting with Sulfo-DST for 0.5 h. Sample cells were constructed by fixing a cut 1-cm length of a yellow pipet tip (Axygen) to a coverslip using epoxy adhesive. Single molecule experiments were performed using an Olympus IX-83 objective-type TIRF microscope equipped with a 60 × oil-immersion objective (APON 60XOTIRFM, 1.49NA), Cell^TIRF and z-drift control modules as well as an EMCCD camera (IXon 897, Andor, EM gain 1000) for all measurements. Cell culture and telomerase extraction. Hela, MCF-7, A549, A375 cancer cell lines, and human normal liver cells (LO-2) were cultivated in DMEM medium supplemented with 1% Penn/Strep, 10% fetal bovine serum and incubated at 37°C in a humidified atmosphere of 5%CO2/95% air. Cells were collected during the exponential phase of growth, rinsed twice with phosphate buffered saline (PBS) solution. Next, the cells were resuspended in 100 µL of CHAPS lysis buffer (10 mM Tris−HCl, pH 7.5, 1 mM MgCl2, 1 mM EGTA, 0.1 mM PMSF, 5 mM mercaptoethanol, 0.5% CHAPS, 10% glycerol) at a concentration of 1×106 cells/mL. The lysate



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was incubated on ice for 30 min and centrifuged at 12000 rpm for 20 min at 4 °C. The supernatant was collected and stored at −80 °C for use. Telomerase substrate (TS) extension. In a typical assay, 50 nM TS and 0.5 mM dNTPs were incubated with different amount of telomerase extract in the telomerase reaction buffer (20 mM Tris-HCl, 1.5 mM MgCl2, 63 mM KCl, 1 mM EGTA, 0.05% Tween-20) for 2 h, then heated to 95 °C for 5 min to inactivate telomerase activity. Next, the reaction solution was diluted 5000fold for single molecule assays. Single molecule telomerase detection. All solutions were prepared in 1.7-ml microcentrifuge tubes, and target oligonucleotides were diluted in the presence of 0.03 mg/mL polyT as a carrier in order to protect the targets from absorbing on the tube. The slide surface was briefly incubated with TE buffer (10 mM Tris-HCl, 1 mm EDTA, pH 8.0) followed by 1 mg/ml streptavidin for 10 min. Then, excess streptavidin was flushed out by the TE buffer. Next, 20 nM of the biotinylated capture probe was added in 1× PBS buffer for 10 min, and the excess was flushed out by 1× PBS for three times. Telomerase reaction products were introduced into the sample cell and incubated for 30 min for target DNA transporting and hybridization. Then, the solution was switched to imaging buffer. The imaging conditions for telomerase activity measurement and product length distribution study were summarized in Table S2. The transient binding of probes to target molecules was monitored under illumination by 532 nm laser light. Image acquisition was performed using the EMCCD camera. Note that for single molecule assays the room temperature was controlled at 25 °C (±1 °C). Analysis of single molecule fluorescence data. Fluorescence time trajectory was extracted from acquired movies by custom MATLAB code. Single fluorescence traces displaying singlestep photobleaching, a signal-to-noise ratio of >3, and a total fluorescence intensity of >1800 (arbitrary units) were selected for kinetic analysis. The trajectories were fitted with Hidden Markov model (HMM) using QuB software to identify the number of transitions and dwell times of the bound (τon) and unbound (τoff) states for individual candidate molecule. Results and Discussion The Principle of Amplification-Free Single Molecule Stochastic Binding Assay.


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The schematic diagram of the strategy for single molecule telomerase activity detection was illustrated in Figure 1A. The biotinylated capture probe (19 nt) that was complementary with a part of the telomerase substrate (TS, 23 nt) was firstly immobilized on the PEGylated slide surface through biotin-streptavidin interaction. TS and TRPs could then be recognized by the capture probes on the surface through the stable DNA hybridization. The short fluorescent probes (9-10 nt) were designed complementary with the junction of the first telomeric repeat and TS. Incubation of these short probes with the pre-hybridized structure enabled a kinetic hybridization process (ssDNA of 8-12-nt), which is highly sensitive to the number of complementary bases.28,29 The details of this sandwich configuration are shown in Figure 1A. In the presence of TRPs, the short fluorescent probe can bind with TRPs stochastically with increased affinity, exhibiting distinct fluorescence intensity signature against the nonspecific binding under TIRFM illumination (Figure 1B, top). In the absence of telomerase, the TS will not be extended and cannot accept short fluorescent probe, which thus only exhibits the signal in a nonspecificbinding manner (Figure 1B, bottom). The differential kinetic signature of genuine target and background allows us to identify TRPs and measure telomerase activity at single molecule level, greatly enhancing the sensitivity and confidence. Under favorable integration time, the majority of the target TRPs on the slides surface could be “lighting up” definitively. As a consequence, this approach displays noticeable advantages over previously reported amplification-free methods, such as single molecule counting. One of the key advantages of this design is that the short fluorescent DNA probes could be regenerated in a thermal dynamic driven manner. Photobleaching was avoided as the probe could be continuously recycled from the bulk solution. To validate this assay, we used the fluorescent probe to detect the synthetic products elongated by telomerase (TS-1R) and TS. As shown in Figure S1, the synthetic oligonucleotides showed similar results as that from TRPs. For the convenience of presentation, the time-averaged raw fluorescent images are shown in Figure 2A and B. The density of fluorescent spots in the assay with telomerase was significantly higher than that without telomerase. To differentiate the target signal from background noise, raw movies were firstly processed to generate single molecule fluorescence time traces that were further analyzed using custom written MATLAB (The Math Works) scripts (see supporting information). Individual fluorescent spots were then analyzed for kinetics of probe binding. Each fluorescent state change was noted as a “transition” (i.e. 51 transitions in top of Figure 1B). 7 ACS Paragon Plus Environment


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To discriminate target and background accurately, we quantified the number of transitions of all observed molecules. The average number of transitions of genuine target observed in a given time window can be described as = 2 /( + ) where and are the rate constant of single molecule DNA association and dissociation, is the concentration of fluorescent probe.26 Due to the rapid exchange rate of bound and unbound state, the number of transitions for genuine target is much higher than that of non-specific binding. The distribution of the number of transitions was described statistically as a Poisson process.26 According to the characteristic of Poisson distribution, the standard deviation of the number of transitions is expected to increase only as the number of transitions, implying that the observation time can be lengthened to achieve arbitrarily high discrimination between target and non-specific binding. Within 10 min, two separated Poisson peaks were found in the assay with telomerase, corresponding to nonspecific and specific binding, respectively (Figure 2E). In this assay, without telomerase, only nonspecific binding peak was found with a boundary value of 12 (Figure 2F). Molecules passing this threshold (i.e., 12) could then be rationally regarded as genuine targets. With this data analyzing method, 497 and 0 candidates were found in the positive and negative assays, respectively. Background-free telomerase detection was thus achieved. Two representative reconstructed single molecule counting images from a subarea of Figure 2A and B are shown in Figure 2C and D respectively where the background spots were completely filtered according to the threshold. Unlike the previously reported single molecule fluorescence assay where the background spots cannot be identified from the fluorescent image confidently,30,31 our method demonstrated here only counted the genuine targets and removed the background noise. Furthermore, compared with the spectroscopy approaches performed in bulk solution, the interference of background was also addressed, potentially enabling high sensitivity and amplification-free detection. Optimization of the Reaction Conditions for the Stochastic Single Molecule Binging Process. In accordance with the Poisson process, the probe binding kinetics or stochastic probing frequency was important for the differentiation of target and background. The binding kinetics of double strand DNA (dsDNA), particularly short strand relies on the number of complementary bases, ionic strength and temperature.32 Thus, the choice of probe length and ionic strength was 8 ACS Paragon Plus Environment

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critical in this study to achieve high sensitivity at room temperature. Moreover, in a typical Poisson process, the signal and background peaks in histograms are progressively better resolved with elongated acquisition time. Thus, the acquisition time was another important issue probably affecting sensitivity. We firstly optimized the assay conditions by varying the length of fluorescent probe and Na+ concentration (SI, Figure S2). 10-nt probe with 200 mM Na+ and 9-nt probe with 600 mM Na+ showed higher sensitivity. The sensitivity was relatively low at high concentration of Na+ probably because the formation of G-quadruplex of telemetric repeats hinders the binding of probes.33 Thus, high concentration of sodium was avoided in this assay. 10-nt probe (FP1) and 200 mM Na+ concentration were chosen for telomerase quantification. In addition, the acquisition time was also optimized. As shown in Figure S3, 10 min was sufficient for target and background separation. It is worth to point out that, even though the total image stack acquisition time is 10 min, the laser power applied was low (5 W/cm2), which maintains enough fluorescent probes in the bulk solution for the diffusion-controlled DNA hybridization process. Telomerase Activity Assay from Cancer Cells. Next, the sensitivity and dynamic range for TRPs assay were determined by using the synthetic TRPs (TS-1R), yielding a limit-of-detection (LOD) as low as 0.5 fM and dynamic range of 0.5-500 fM (Figure S4). To demonstrate the promising capability of this method for real sample assay, we further measured the telomerase activity from cancer cells. The correlation of HeLa cell number and counts of TRPs is plotted in Figure 3A. Due to the merit of “backgroundfree” detection, telomerase extracted from 10 Hela cells can be detected by this method without any complicated enzyme-based amplification steps. Broad dynamic range was also achieved from 10 to 2000 cells (Figure 3B). This method was even more sensitive than those amplification-based approaches.34-36 To demonstrate the broad application capability of this method, besides HeLa cell, telomerase extracts from different cancer cell lines (A549, A357 and MCF-7) were further tested. As shown in Figure 3C, noticeable statistical differences were noted between the results from those tested human cancer cell lines and liver normal cell line (LO-2) or inactivated cancer cell line, further confirming the reliability of this method. In order to demonstrate the high specificity of this method for telomerase assay, different proteins were used as controls (Figure 3D). Comparing with telomerase, other proteins did not 9 ACS Paragon Plus Environment


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show any positive signal. Furthermore, the effect from telomerase inhibitor was also evaluated. As shown in Figure S5A and B, the telomerase activity decreased gradually with the addition of the two inhibitors. These results together demonstrated that this method holds great potential for telomerase based anti-cancer drug screen. Investigating the Length Distribution of Telomerase Reaction Products. In addition to the quantification of TRPs, since the length of TRPs (or the telomerase processivity) also reflects the catalysis mechanism of telomerase, the distribution of TRPs length is therefore another essential parameter to characterize the telomerase reactivity. On this basis, we further extended this method to explore the length distribution of TRPs. As illustrated in Figure 4A, the stochastic binding probe was designed complementary with the junction of two repeats. In this design, two telomeric repeats were able to provide one binding site for the fluorescent probe. The binding sites were then quantified by the frequency of stochastic binding. Instead of relying on the fluorescence intensity, this approach determined the number of probe binding sites through calculating the probe unbound time by taking the advantages of the predictable and programmable binding kinetics as described below. The rate constant of single molecule DNA association ( ) and dissociation ( ) can be described as the following equations × = τ

(1)

= τ

(2)

where τ and τ are the dwell time of bound and unbound state, respectively, was a constant because there were large excess of probes in the solution. Typically, the stochastic binding frequency will ideally increase n times if a single TRP contains n probe binding sites. Thus, we have n = ( × × τ )

(3)

where τ is the probe unbound time in the multiple stochastic binding mode. According to the equation 3, and are constant, thus, n can be calculated as long as the τ is measured accurately. and are also important for the accuracy and precision 10 ACS Paragon Plus Environment

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of the τ measurement. In the previous study by Jungmann et al,25 × = 0.03 can provide high precision and accuracy. By using the stochastic probing mode, we first determined the hybridization kinetics of FP3 for telomerase product with two repeats (SI, Figure S6) where equals to 0.0021 ∙ . By adjusting the probe concentration to 15 nM, × = 0.032 . Figure 4B presents the raw time trajectories of FP3 in the presence of synthetic TRPs with different number of binding sites. Multiple-state hidden markov model (HMM) was used for idealizing the trace. As shown in the histogram, the fraction of unbound state decreased gradually with the number of binding sites. The experimental τ measured by single molecule assay showed good agreement with the theoretical τ calculated by equation 3 in which the unbound time of multiple binding sites was calculated by the experimental unbound time with 1 binding sites (Figure 4C). Next, the distribution of the length of TRPs generated by telomerase from 2000 HeLa cells were studied. The binding sites were calculated by equation 3, and all time trajectories were idealized by two-state HMM where the multiple binding states were not considered. Two-state HMM gave the same τ with multiple-state HMM (SI, Figure S7). By fitting the histogram by Gaussian distribution (Figure 5A), the relative population of different length TRPs could be achieved (Figure 5B). Note that the total counts of TRPs were derived from the single molecule assay by using FP1. As shown in Figure 5B, TRPs with less repeats shows higher frequency than those with more, indicating the relatively low ratio of substrate translocation and dissociation. The fraction of TRPs decreased exponentially from 4-5 repeats to 10-11 repeats. This may explain the low sensitivity of some amplification-based methods that relied on the hybridization of probe with long TRPs. Conclusion In summary, an amplification-free, highly sensitive, and high-confidence method has been developed for telomerase activity assay. Short fluorescent DNA probe was used to stochastically bind with TRPs, yielding distinct kinetic signature from background recorded by TIRFM. A limit-of-detection (LOD) as low as 0.5 fM and a dynamic range of 0.5-500 fM for TRPs detection were readily achieved. With this method, telomerase extracted from cancer cells was



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determined with sensitivity down to 10 cells irrespective of the cellular type. The sensitivity can be further enhanced by coupling with microfluidic devices or other fluorescent materials with better brightness. Furthermore, the length distribution of TRPs was also studied by multiple stochastic probing mode. Short TRPs was found to be the prevalent product, which was not determined by other homogeneous fluorescence approaches. Due to the versatility and high sensitivity of this method, it would find broad applications in the fields of clinical diagnostics and basic research.


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Acknowledgements We thank Dr. Alexander Johnson-Buck at University of Michigan for Matlab coding. This work was supported by the National Natural Science Foundation of China (31600687, 81273631, 31400915, 21405045, 21522502), Fundamental Research Funds for the Central Universities (12060070031, 12060090029 and 12060072011), Program for New Century Excellent Talents in University (China, NCET-13-0789), and Hunan Natural Science Funds for Distinguished Young Scholar (14JJ1017). Supporting Information The Supporting Information is available free of charge on the website. The sequences of oligonucleotides used in this work are listed in table S1. The imaging conditions for quantifying TRPs and study of length distribution of TRPs are listed in table S2. The supporting figures are included.



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(31) Gunnarsson, A.; Jonsson, P.; Marie, R.; Tegenfeldt, J. O.; Hook, F. Nano Lett. 2008, 8, 183188. (32) SantaLucia, J.; Hicks, D. Annu. Rev. Bioph. Biom. 2004, 33, 415-440. (33) An, N.; Fleming, A. M.; Middleton, E. G.; Burrows, C. J. P. Natl. Acad. Sci. USA 2014, 111, 14325-14331. (34) Wang, W. J.; Huang, S.; Li, J. J.; Rui, K.; Zhang, J. R.; Zhu, J. J. Sci. Rep. 2016, 6, 14325. (35) Li, X. Q.; Wang, W.; Chen, Y. Y.; Ding, C. F. Analyst 2016, 141, 2388-2391. (36) Yi, Z.; Wang, H. B.; Chen, K.; Gao, Q.; Tang, H.; Yu, R. Q.; Chu, X. Biosens. Bioelectron. 2014, 53, 310-315.



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FIGURES AND CAPTIONS

Figure 1. Telomerase detection by single molecule stochastic binding of the telomeric repeats. (A) The schematic diagram of single molecule telomerase activity detection with TIRFM. The telomerase reaction products (TRPs) were transferred to the sample cell and captured by capture probe. The short probes were designed complementary with the junction of TS and telomeric repeats. (B) Single molecule characterization of stochastic binding process. Blue line is a typical time trajectory of the stochastic binding of short fluorescent probe with TRPs and black line represents non-target binding (red, idealization from hidden Markov modeling). The positive signal was from the assay of 2000 HeLa cells. The short probe concentration was 25 nM.


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Figure 2. Time-averaged fluorescent image of fluorescent probe for TRPs in the presence (A) and in the absence of telomerase (B). (C-D) Zoom-in of the selected area from A and B (122×122 pixel) where the background spots were completely screened out according to the background threshold as noted in E and F. (E-F) Histograms of the number of candidate molecules showing a given number of state transitions in the presence (E) or absence (F) of telomerase (from 2000 HeLa cells). Candidates showing less than 12 transitions were treated as the background. The probe used was FP1 and its concentration was 25 nM.



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Figure 3. (A) Counts of candidates filtered by threshold versus the number of HeLa cells. (B) Linear plot of the counts of filter candidates and the number of HeLa cells. (C) Detection of telomerase activity of different cell lines (2000 cells). Counts were the number of threshold filtered candidates. (D) Selectivity of the single molecule assay for different proteins (telomerase was from 2000 HeLa cells). Note that counts were the number of threshold filtered molecules.


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Figure 4. Multiple stochastic probing mode. (A) Stochastic probing synthetic TRPs with different number of repeats. The short probe (FP3) was complementary with the junction of two repeats. Binding sites increased by adding two repeats. (B) Single molecule fluorescence time trajectories and intensity histograms of the hybridization between FP3 and the synthetic oligos with different number of telomeric repeats. C) The linear relationship of theoretical and experimental τ . Theoretical τ of 2-4 binding sites was calculated by equation 3 using the experimental τ of 1 binding sites. The experimental τ of 2-4 binding sites was measured by idealizing their time trajectories. For this assay, 500 fM synthetic TRPs was used.



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Figure 5. Study of the length distribution of TRPs. (A) Unbound time distribution of TRPs generated by the telomerase from 2000 HeLa cells by the stochastic probing using FP3 (15 nM). Peak fitting of the histogram was centered at n=1, 2, 3, 4, 5. (B) TRPs population derived from (A). The total number of TRP was determined by using FP1 (25 nM).


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For TOC only


Telomerase Activity Detection with Amplification-Free Single Molecule

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