Stoichiometry and Dispersity of DNA Nanostructures Using

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Stoichiometry and Dispersity of DNA Nanostructures Using Photobleaching Pair Correlation Analysis Amani A. Hariri, Graham D Hamblin, Jack S Hardwick, Robert Godin, JeanFrancois Desjardins, Paul W. Wiseman, Hanadi F. Sleiman, and Gonzalo Cosa Bioconjugate Chem., Just Accepted Manuscript • DOI: 10.1021/acs.bioconjchem.7b00369 • Publication Date (Web): 04 Aug 2017 Downloaded from http://pubs.acs.org on August 8, 2017

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Bioconjugate Chemistry

Stoichiometry and dispersity of DNA nanostructures using photobleaching pair correlation analysis Amani A. Hariri1,2, Graham D. Hamblin1,2, Jack S. Hardwick1,2, Robert Godin1,2, Jean-Francois Desjardins3, Paul W. Wiseman1,3, Hanadi F. Sleiman*1,2, and Gonzalo Cosa*1,2

1

Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, Quebec,

H3A 0B8, Canada, 2Center for Self-Assembled Chemical Structures (CSACS-CRMAA), McGill University, 801 Sherbrooke Street West, Montreal, Quebec, H3A 0B8, Canada, 3Department of Physics, McGill University, 3600 University Street, Montreal, Quebec, H3A 0B8, Canada;

KEYWORDS:

Nanotechnology,

single

molecule

fluorescence,

DNA

nanotubes,

photobleaching, polydispersity, stoichiometry, characterization and analytical techniques.

ABSTRACT: A wide variety of approaches have become available for fabricating nanomaterials with increasing degrees of complexity, precision, and speed while minimizing cost. Their quantitative characterization however remains a challenge. Analytical methods to better inspect and validate the structure/composition of large nanoscale objects are required to optimize their applications in diverse technologies. Here we describe single molecule

1 ACS Paragon Plus Environment


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fluorescence-based strategies relying on photobleaching and multiple color colocalization features toward the characterization of supramolecular structures. By optimizing imaging conditions including surface passivation, excitation power, frame capture rate, fluorophore choice, buffer media, and antifading agents, we have built a robust method to dissect the structure of synthetic nanoscale systems. We showcase the use of our methods by retrieving key structural parameters of four DNA nanotube systems differing in their preparation strategy. Our method rapidly and accurately assesses the outcome of synthetic work building nano-and mesoscale architectures providing a key tool for product studies in nanomaterial synthesis.


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The synthetic power towards building highly complex nano-assemblies that incorporate organic and/or biological building blocks has tremendously advanced in the past decade (1-7). Both top-down and bottom-up approaches have enabled the systematic and rapid fabrication of numerous symmetric or periodic nanostructures with precisely organized features (8-10). The unique self-assembly properties and ease of synthesis of DNA have made of it the building block par excellence to assemble complex, rigid and aperiodic nanoscale objects (11). A number of approaches have thus exploited DNA (12-16). For instance, DNA-origami (10) a technique in which a long single-stranded scaffold (often from the phage M13mp18 (17)) is folded into any desired shape with the help of a multitude of short staple strands, has revolutionized our way of aligning nanoscale components into patterns with nanometer precision (18-20). The size constraint dictated by the length of the M13mp18 strand has stimulated interest in organizing larger-scale origami arrays with multiple units (21, 22). A periodic 2D lattice of DNA origami tiles was thus achieved by Seeman and co-workers (23). This, and related systems, led to larger periodic DNA origami arrays with micrometer dimension (24-26). A DNA-minimal approach developed by some of us (27-29) provides an alternative method to exploit DNA as a building block. Working with a set of few DNA strands, we have shown the generation of extended DNA nanotubes with contour lengths in the hundreds of nanometers. The new structures provide structural scaffolds that can organize arrays of cargo by using a minimal set of starting materials (30-32). Progress in developing larger constructs is however accompanied with many technical challenges, the most significant of which is the increased error rate in assembly which may affect robustness and performance (33, 34). In order to enable the creation of arrays with minimal or no defects and large structural diversity, it is critical to develop tools to characterize the composition



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and patterns of the end-product to rationalize and ultimately guide the assembly and control the quality of the new structures prepared from different building blocks. Improved analytical methods to inspect and validate the structure (35, 36), assembly precision (37) and overall composition(38) of large nanoscale objects in order to facilitate their applications in areas such as photonics (39-41), medicine (42-44) and energy (36, 44-46) are currently needed. While gel electrophoresis (47), atomic force microscopy (48) (AFM) and transmission electron microscopy (49) (TEM) based methods yield useful structural information on a resulting DNA construct, these are either ex situ and/or intrusive techniques, preventing further structural manipulation. Single-molecule fluorescence (SMF) techniques (50-55) enable the continuous observation of individual structures in solution, reporting on structure (56), dynamics (57), and morphology (58) of distinct populations. In particular, SMF methods offer the opportunity to monitor realtime discrete photobleaching steps i.e., discrete intensity jumps associated to depletion of individual –uncoupled- fluorophores located along e.g. a protein or DNA backbone (59). Direct quantification of the number of fluorescently tagged repeat units within a structure is thus possible (60). From this perspective, single molecule fluorescence approaches lend themselves as the method of choice for characterization and manipulation of DNA constructs (61). Several groups have employed one-color single molecule photobleaching to elucidate the stoichiometry in e.g. plasma membrane proteins (62), RNA- and DNA-structures (63) among others (64-66).While the number of repeat units forming different oligomers might range from a few to tens or hundreds, the number of discrete photobleaching steps reported in the literature has rarely extended beyond eleven (unless extended using mathematical extrapolation) (67, 68). A major complexity in analyzing single molecule fluorophore photobleaching data lies in the increasing probability that, with an increasing number of dyes, two or more fluorophores will


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photobleach either simultaneously (within a frame) or within a short period of time/frames, effectively preventing accurate assignment of steps. Such outcome may skew the step size distribution and complicate the estimation of a unitary photobleaching step size. Additionally, the dynamic range of current EMCCD cameras prevents the accurate resolution of photobleaching steps from noise as the number of dyes recorded (and steps expected) is increased beyond 10-11. For this reason, the number of countable photobleaching steps reported in the literature has, to our knowledge, not exceeded 11 steps in size (62, 69). These limitations make the application of photobleaching analysis to larger assemblies significantly challenging. A multiple-color single molecule experiment where two or more differently labelled building blocks can be incorporated into one complex provides a way to circumvent the limitations listed above. Zhang et al. reported a simultaneous dual-color photobleaching of differently labeled pRNA to elucidate their stoichiometry (5 or 6) and assembly mechanism on the phi29 DNA packaging motor (63). More recently, our group conducted two-color single molecule experiments to monitor the assembly and assess the stoichiometry on dually-labeled Cy3/Cy5 DNA nanostructures (70). Although single molecule techniques were employed in both of these studies, the data was analyzed to generate ensemble histograms revealing the distribution of the number of photobleaching steps for the two different colors separately. Here, we describe a single molecule fluorescence method that enables us to assign polydispersity, and stoichiometry for different DNA nanotubes with a large number of repeat units, by correlating the photobleaching steps recorded on two color emission channels, molecule by molecule. We reasoned that by tagging repeat units in supramolecular systems of interest with an increasing number of spectrally distinguishable fluorophores (71), one may proportionally increase the number of units accurately counted. Furthermore, colocalization of the different



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labels may serve as an additional marker to validate the success of the assembly (72, 73). Key to our method is the implementation of a two-color single-molecule photobleaching technique in order to unequivocally count the number of repeat units in each of the structures and increase the maximum number of countable building block units. Working with fluorescence intensity-time trajectories of doubly labeled DNA nanotubes bearing green absorbing Cy3 and red absorbing Cy5 or ATTO647N fluorescent dyes along their backbone, we monitored discrete photobleaching steps of single molecules in the two colors and successfully retrieved key structural parameters of four DNA nanotube systems differing in their preparation method. Photobleaching steps in both channels were assigned to a given nanotube. By analysing large two-color datasets consisting of hundreds of nanotubes monitored in parallel over time, we were able to provide a rapid and systematic way to accurately assess the outcome of synthetic work building supramolecular systems. We postulate that the method described herein, while developed for DNA nanotubes, will be instrumental to research groups synthesizing rationally-designed large supramolecular structures or studying naturally-occurring ones.

RESULTS AND DISCUSSION Single molecule photobleaching In order to acquire fluorescence intensity time trajectories of dually-labelled (green absorbing Cy3 and red absorbing Cy5 or ATTO647N) individual supramolecular structures, we utilized a total internal reflection fluorescence microscope (TIRFM) equipped with an EMCCD camera. Polycarbonate imaging chambers were assembled onto glass coverslips pre-coated with a mixture of polyethylene glycol (PEG) and biotin-tagged PEG to prevent nonspecific adsorption


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(59, 74, 75). Individual dye-labeled DNA nanotubes were next specifically immobilized on the chambers via biotin-streptavidin interactions (Figure 1A, see also Supplementary Information Section 2). Excitation was performed with two evanescent beams exciting first at 641 nm and next at 532 nm. About 200 bright fluorescent spots were observed in any given image, with Cy3 and Cy5/ATTO647N emissions co-localizing in the images, an indication that the two fluorophores resided within the same observation volume and that the imaged DNA nanotubes contained both units. For each single nanotube imaged, the fluorescence intensity-time trajectory was observed to decrease stepwise over time, giving a descending “staircase” photobleaching pattern with a measurable number of discrete intensity levels (Figure 1B).

Figure 1: Photobleaching analysis of DNA nanotubes. A. Cartoon illustrating surface bound DNA nanotubes under different laser excitation (532 nm, top and 641 nm, bottom). B. Fluorescence intensity-time trajectories showing the photobleaching steps of the Cy3 ( 7 steps) and Cy5 (6 steps) labels colocalized in space (grey arrows indicate the manual counting). The observation that steps are seen with each color enables next the experimentalist to count the total number of repeat units regardless their color by conducting two-color experiments. Design and preparation of DNA nanotubes 7 ACS Paragon Plus Environment


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To validate our photobleaching pair correlation analysis method we utilized different DNA structures assembled via synthetic strategies yielding increasing levels of control in structure, stoichiometry and polydispersity. A total of four different synthetic strategies were explored based on previously published protocols (27, 28, 70, 76). By organizing triangular DNA polygons on top of one another using linking strands, we generated a variety of nanotube systems with tunable rigidity and porosity. Common to all of the nanotubes is the DNA rung, a building block constructed from a closed triangular single-stranded DNA scaffold characterized by orthogonal sequences in each of its three sides. The rung was completed after the hybridization of three strands (CS1-2-3), each complementary to a triangle side and presenting an extended non-complementary region at the ends for subsequent functionalization along the vertices (‘sticky ends’). Next, three rigidifying strands were hybridized at the vertices to render the rung sticky ends better oriented in space. Linking pillar strands (LS) were then used to connect the rungs and generate elongated DNA nanotubes (See Supplementary Information Section 1). Outlined in Figure 2 are the different synthetic strategies used herein (see Supplementary Information Section 1, Figures S1 and S2). A solution-based growth approach, which gives little control over length, was adopted for samples A, B, and C. Sample A (KG Random) consisted of randomly mixing Cy3 and Cy5 labelled DNA rungs that would polymerize in the presence of linkers, with no control over the length or sequence pattern of the end-product (Figure 2A) (27). For sample B (KG1:1), the nanotube was designed bearing Cy3 labelled DNA rungs that were randomly polymerized as for sample A; while the addition of Cy5 labelled DNA linkers assured a 1:1 sequence pattern of dyes as shown in Figure 2B. Sample C (RCA1:1) took advantage of rolling circle amplification (RCA), an enzymatic process that produces long and highly polydisperse single-stranded DNA backbones (∼1400−15000 bases long) from a cyclic template


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(76). This gives a long repeating strand that replaces one of the struts (linking strands) and guides the nanotube assembly (77). The backbones are produced with alternating regions binding Cy3 and Cy5 labelled DNA rungs to form templated DNA nanotubes with 1:1 sequence patterns as shown in Figure 2C. Another assembly approach exploited a solid-phase synthesis towards a sequential construction to control the length and patterns on every position of DNA nanotubes (70). We applied this approach to sample D (SP1:1), where we built the tubes step by step on the surface by adding, in an alternating fashion, Cy3 and ATTO674N labelled DNA rungs with DNA linkers in between to generate nanotubes with controlled length and 1:1 sequence pattern (Figure 2D). Importantly, given that the minimum interdye distance is larger than 7nm, neither homoFRET nor heteroFRET are possible within our constructs. Figure 2 below shows the distances between the ATTO647N/Cy5 and the two neighboring Cy3 dyes. In system A-B-D, the dyes are attached to the ridgidifying strands, and the distance in between consecutive dyes is 24.5nm where FRET is impossible. As for system C, given the fact that the Cy3 and ATTO647N/Cy5-tagged overhangs are double-stranded (10 bases), we estimated the distances at the two extreme ends at which the red and orange emitters could possibly be (the closest side to Cy3 and the farthest from it, ends at 180° angle difference) (78). In either of the two cases, the distance is at least 7 nm, which implies that the FRET expected at this proximity is minimal. It is important to note that our methodology is useful in as far as the dyes utilized in labeling repeating elements are not interacting with each other. One may thus tackle architectures whose repeat units are at least a few nanometers in length or larger.



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Figure 2: An Artistic representation of DNA nanotubes systems with different level of control over their polydispersity and stoichiometry: A. DNA nanotubes assembled in solution following a random polymerization of Cy3 and Cy5 labelled-DNA rungs with linkers (random length and stoichiometry). B. DNA nanotubes assembled in solution following a random polymerization of Cy3-labelled DNA rungs and Cy5-labelled DNA linkers (random length but controlled stoichiometry of 1:1 Cy3:Cy5). C. DNA nanotubes assembled by the hybridization of Cy3 and Cy5 labelled DNA rungs on an ABAB enzymatically produced DNA backbone (random length but controlled stoichiometry of 1:1 Cy3:Cy5). D. DNA nanotubes assembled by a stepwise growth synthesis on the surface of Cy3 and ATTO647N labelled DNA rungs, (controlled length and controlled stoichiometry 1:1 Cy3:ATTO647N). The dashed box (bottom) includes two schematics for systems (A, B and D, left) and system (C, right) clarifying the interdye distances in the different constructs.

Data acquisition optimization


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In order to maximize the number of dyes present in a single nanotube a compromise had to be reached between multiple factors. Specifically, detecting a large number of dyes i) without overflowing the dynamic range of the camera thus saturating the detector; ii) whose photobleaching steps may be unequivocally discerned from noise in the intensity-time trajectories; iii) where the rates of photobleaching are large enough to ensure that -given the stochastic nature of the process, the probability for two fluorophores decaying within the same frame is negligible; iv) yet the acquisition is fast enough (minutes) to minimize drifting and enable high throughput studies in the future. The intensity noise, resulting from photon collection noise and the intrinsic EMCCD acquisition noise determined that we set as an upper boundary 11 dyes in a single molecule for their photobleaching steps to be reliably detected within a given emission channel. This boundary is similar to that reported by others (63). Such a choice satisfies that intensity jumps associated to photobleaching are on average larger than the intensity-time trajectory noise when all 11 dyes are emitting (maximum noise attained as the camera noise is constant and the noise in photon collection is in turn proportional to the square root of the intensity). The noise criterion superseded the requirements on dynamic range and photobleaching rates. The latter are interrelated and were next optimized considering factors such as detector saturation, frame capture rate, and time between photobleaching events. At the low excitation powers employed herein, the fluorescence intensity is expected to be linear with excitation power. The excitation power was thus adjusted to take advantage of the full dynamic range of the camera given a selected frame duration (i.e. a higher excitation rate would require a shorter integration time per frame).



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The choice of frame duration next locked the optimal photobleaching rate. We established that a frame acquisition rate equal to or faster than 10 Hz (~100 ms frame duration) would be most appropriate toward ensuring rapid data acquisition. Accordingly, and working at a maximum gain, the laser excitation was optimized to ensure no detector saturation. We next determine the minimum dye lifetime “τ” (in frame unit times) that ensures a negligible probability (chosen as ≤ 0.25%, or 1 chance in 400) that multiple dyes photobleach in a single frame. Such value of τ may be estimated from a binomial distribution. The probability “p” for one dye to photobleach in a frame is given by Equation 1 below. The binomial equation (Equation 2) next calculates the probability “Prob” that given “n” dyes in a single molecule, “k” dyes simultaneously photobleach (where effectively n is the number of trials and k the number of successes). Considering cases where multiple dyes photobleach in a single frame, k ≥ 2, at the maximum value of 11 photoexcited dyes a minimum dye lifetime value of 150 frames satisfies the condition that multiple photobleaching occurs in less than 0.25% of frames. Since our frame duration is 100 ms, this corresponds to a minimum dye lifetime of 15 s, in line with the shortest dye lifetime observed under our optimized experimental conditions. = 1 − ⁄

Equation 1 !

; , = !! 1 −

Equation 2

The choice of the photoprotection media was critical as rapid photobleaching and/or blinking of the dyes may compromise the counting of the steps in a trajectory. We selected Cy3 as an orange emitter as it proved photostable with no photoprotection system. We tested Cy5 and ATTO647N as red emitters, with a number of anti-fading conditions. We favored ATTO647N over Cy5 because of its longer survival time, which results in trajectories with extended intervals of steady intensity between photobleaching steps.


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In order to maximize the number of dyes present in a single nanotube whose photobleaching may be recorded in single molecule intensity-time trajectories we next increased the number of orthogonal emitters (e.g. Cy3 and Cy5/ATTO647N) and accordingly detection channels. This enabled detecting 22 dyes per structure provided the above conditions could be satisfied for each channel (see Supplementary Information, Section 2 and 3 for the conditions employed). While most elements can be dictated through choices in the software acquisition menu, ensuring that both the green and red absorbing dyes exhibit similar photobleaching lifetimes required additional optimization. Prior to image acquisition, a tubing was inserted into the inlet port, connecting the chamber to a syringe placed on a syringe pump. In order to reduce photobleaching and blinking, we first employed the oxygen scavenger/triplet quencher solution (79, 80) consisting of D(+)glucose (3% w/v), glucose oxidase (0.1 mg/mL, 165 units/ml), catalase (0.02 mg/mL) in addition to a triplet quencher ᵦ-mercaptoethanol (BME, 1% v/v) in 1x TAMg buffer for systems A, B and C in which the Cy5 dye was employed (photobleaching lifetime τ 17 s). Because the resulting nanotubes of systems A, B and C had an average size population of 4 rungs (4 steps), and given the long duty cycle of Cy5, minimal blinking was observed in the intensity-time trajectories which could not obstruct the photobleaching step counting process. For system D however, given the larger size population of the nanotubes with 10 rungs on average (10 steps), Cy5 blinking was more prevalent. We therefore switched to a more robust dye ATTO647N which, in the presence of a triplet quencher Trolox (2mM, dissolved in MeOH and filtered to minimize background in the Cy3 channel) presented less blinking and an enhanced photostability (81). Importantly, we noticed that in this case the use of oxygen scavenger solutions prevented observing the complete photobleaching in many of the structures within reasonable timescales. We ultimately established that the combination of



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ATTO647N and Trolox in 1x TAMg buffer yielded the best result in terms of photostability (photobleaching lifetime τ of 55 s), blinking behaviour (minimal) and favorable conditions for the paired green absorbing dye Cy3 (photobleaching lifetime τ of 19 s). The oxygen scavenger/buffer solution was flowed at a rate of 5 µL/min throughout the experiment. Movies (100-200 ms exposure time, 1500 frames) of the region were acquired at this stage. We estimated a reasonable fluorophore photobleaching lifetime τ in the range of 20-50 s (200500 frames) for our experiments performed at an acquisition frame rate of 10Hz. Given the stochastic nature of photobleaching, this τ value ensured that in about 100-250s (5τ, 1000-2500 frames) photobleaching would be complete in >99% of the structures imaged. In order to maximize the information recorded from both emission channels, the imaging and photobleaching of the fluorophore absorbing at a lower frequency was performed first (641 nm) immediately followed by studies on the fluorophore absorbing at higher frequencies (532 nm). Sequential photobleaching studies in this order ensured the red emissive dye was photobleached prior to conducting studies with Cy3, avoiding artifacts in the analysis arising from bleeding of Cy3 emission into the red channel (the red emissive dyes do not bleed into the Cy3 channel). It also prevented premature photobleaching of the red emissive dyes that may absorb upon excitation at 532 nm.

Single molecule photobleaching analysis Utilizing the photobleaching steps recorded in single molecule intensity-time trajectories we initially constructed a histogram of the ratio of green steps to red steps in order to assess the sample stoichiometry (Figure 3, see also Supplementary Information, Section 4). More than 100 single DNA nanotubes were analyzed in this way for each of the four samples. Consistent with a


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1/1 average stoichiometry we recorded mean values close to 1 for the Cy3/Cy5 step ratio (Figure 3, inset). A marked drop in standard deviation (SD) recorded in going from sample KG random to SP1:1 in turn underscored the increasing level of control/precision in the structure stoichiometry.

Figure 3: Dye-quantized photobleaching analysis on four systems of DNA nanotubes assembled using different strategies. A. Histogram displaying the probability distribution of the ratio of green steps to red steps for a control sample with a random combination of red and green dyes, centered at 1.37 and a standard deviation (SD) of 1.24. (B-D) Histograms displaying the probability distribution of the ratio of green steps to red steps for a DNA sample with 1:1 stoichiometry of the red and green absorbing dyes, centered at around 1 (1.16, 1.16, 1.01, respectively) with decreasing SD values (0.78, 0.49, 0.18, respectively). In each case, N is the total number of nanotubes analyzed.

A correlation analysis was next conducted on the number of photobleaching steps recorded for the green versus the red absorbing dye in the four nanotube samples, where we reasoned the particle by particle correlation analysis would provide details on polydispersity and stoichiometry. A surface contour plot was subsequently built to facilitate the data visualization (Figure 4) for the four DNA constructs described in Figure 2. The slope of the linear fit revealed the average stoichiometry of the sample while the corresponding R2 value provides a qualitative evaluation of the deviation from the average stoichiometry. The values of the slope and R2, extracted from the plots (See Table S1), diverged from 1 in going from sample SP1:1 to KG random confirming the decreasing level of precision in the structure stoichiometry, similar to the 15 ACS Paragon Plus Environment


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results obtained with the ratiometric analysis. This may be attributed to the incomplete dyelabelling of DNA strands, to structural defects during the nanotube assembly and to the random nature of rung incorporation (KG random, with poor correlation). The spread along the diagonal line in turn provided a measure of the degree of dispersity in the samples. We quantified this parameter by computing the standard deviation of the distribution along the diagonal (x=y cross section, See Supplementary Information Section 6, Figure S11). Nanotubes built sequentially on the surface with complete control over their length presented the lowest spread value (1.62) while those built using a highly polydisperse backbone RCA1:1, showed the largest dispersity along the diagonal (2.40). We additionally conducted simulations to anticipate the shape of the correlation. A perfectly monodisperse sample of DNA nanotubes composed of 10 green and 10 red rungs per nanotube, with a 100% labelling efficiency of the dye-tagged DNA displayed as expected a single peak whose coordinates are 10:10 (Figure 5A). Deviations from this ideal point would be attributed to various structural characteristics of the nanotubes which we identified by simulating the expected distribution upon varying the 1) dispersity, 2) stoichiometry and 3) labeling efficiency of the sample (See Figure 5A-D and also Supplementary Information Section 5). Clearly, while the interplay of sample dispersity and stoichiometry (Figure S8) may lead to a rather poor correlation of green and red absorbing dyes, adding the effect of inefficient dye labeling to the constitutive DNA strands would result in an intractable data set. However, a narrow dispersity, defined stoichiometry and efficient labeling should approach an ideal situation as that illustrated in Figure 5A.


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Figure 4: Surface contour plot showing a 2-color correlation of the number of photobleaching steps in green versus red absorbing dyes for real DNA nanotube samples: KG-random (A), KG1:1 (B), RCA1:1 (C), and SP1:1 (D). White line along the diagonal represents the x=y line (1:1 ratio).

Figure 5: Surface contour plot showing a 2-color correlation of the number of photobleaching steps in green versus red absorbing dyes for simulated DNA nanotubes built step by step (10 green : 10 red) with A. 100%-100% labelling efficiency-reaction efficiency, B. 100:90% labelling efficiency-reaction efficiency and C. 90:90% labelling efficiency-reaction efficiency. D. 95%-95% labelling efficiency-reaction efficiency with an additional 5% termination yield.

Comparison of the simulations based on labeling efficiency and data in Figure 4D reveals that the pronounced spread along the diagonal observed in the contour plots of the sample SP1:1 may not arise from poor labelling efficiency (< 100%), but rather from the presence of truncated tubes possibly formed either during washing steps throughout the synthesis or as a result of strained structures. An alternative hypothesis involving the synthesis of defective nanotubes which fail to grow in a subsequent step due to e.g. an irreversible structural failure was also considered to account for the distribution observed in the SP1:1 contour plot. Simulations involving nanotubes 17 ACS Paragon Plus Environment


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with 95% reaction yield, 95% labelling efficiency and with 5% termination yield at each step were generated (see Figure 5D and Supplementary Information Section 5.1.4). While adding the termination factor did elongate the distribution along the diagonal, such an outcome would result in a larger population of small structures (more tubes with less dyes) than middle sized structures contrary to the experimental observations. The absence of small tubes in the experimental data could be an indication that the probability of error increases with tube length, or that the operating mechanism is that larger tubes are more prone to errors in the addition. This may arise from larger tubes collapsing on the surface of the coverslip, reducing the availability of the capturing strands.

From single molecule to bulk measurements: PDI values Upon combining single molecule data and by implementing the fundamental characterization parameters commonly encountered in the polymer chemistry literature we were able to next retrieve bulk properties (Table 1). Specifically, using the total number of rungs (Mx= green rungs + red rungs), we calculated the number average molecular weight (Mn), the weight average molecular weight (Mw) and the polydispersity index (PDI), as defined by Equations 3-5 below, respectively, where Nx is the number of nanotubes of weight (size) Mx. We note that the molecular weight, in this case, is proportional to the number of rungs (steps in green + steps in red) in a given tube. =

∑

Equation 3

∑

Equation 4

∑

= ∑

=

!

Equation 5

"


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Upon combining single molecule data, an average length size of 10 rungs and an average PDI value of 1.3 were computed for the three solution-based (KG random, KG1:1 and RCA1:1) constructs, indicative of the predominance of short monodisperse structures in these samples (See supplementary information section 4.1 and Figure S5”). Conversely, for typical step polymerization,

which is the mechanism that may possibly be attributed to the solution-based nanotube elongation, the average PDI value is around 2. The lower PDI observed by the single molecule method would indicate preferential surface binding of the population of shorter nanotubes, whereas larger structures would remain in solution due to the possible unavailability of the biotin molecules (See Supplementary Information Section 7, Table S2). On the other hand, the solidphase constructs (SP1:1) presented an average length of 18 rungs with a PDI value of 1.1, which highlights the advantage of the solid phase approach in producing highly monodisperse samples with a precise length, in comparison with solution-based approaches.

Table 1: Bulk quantities extracted from single molecule data sets #

%$# $% &%

# $% &%'

M

KG random

215

1640

16764

7.62

10.22

1.34

KG 1:1

235

1596

14504

6.79

9.08

1.33

RCA 1:1

231

2155

25865

9.32

12.00

1.28

SP 1:1

278

4402

78628

15.83 17.86

1.13

Sample

n

M

w

PDI

CONCLUSION In this work, we have demonstrated how single molecule fluorescence-based methods can unravel the structure of nanomaterials through a simple protocol centered on the measurement and analysis of fluorophore photobleaching. Increasing the number of orthogonally emitting dyes 19 ACS Paragon Plus Environment


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utilized, with dedicated detection channels, enabled proportionally increasing the number of detectable repeat units, where every new color may enable the accurate detection of approximately 11 singly tagged units upon monitoring the photobleaching steps of their attached fluorophore. Surface contour plots adopted herein to correlate the two color channels allowed for a rigorous comparison of the different samples. Using this approach, samples with differing unit composition were readily distinguishable on the basis of the correlated number of photobleaching steps in the two color analysis. On one hand, the surface contour plots display the slope and deviations of the distribution to evaluate the stoichiometry of the sample, while on the other hand, the spread of the distribution along the diagonal revealed the dispersity of the size of our assembled nanostructures. Our method enabled a consistent and systematic way of assessing the polydispersity and stoichiometry of different structures and designs which, we posit, will be instrumental for sample characterization in the new age of complex assemblies at the nano and mesoscale. We believe that this technique can be extended and generalized to facilitate the characterization of DNA arrays composed of different building blocks and organized in different patterns (e.g. DNA origami) and will assist in the creation of structures with minimal or no imperfections and larger structural diversity.

EXPERIMENTAL METHODS DNA nanotubes synthesis: DNA strands were deprotected and cleaved from the solid support in the presence of concentrated ammonium hydroxide solution (60°C, 16 hours). Polyacrylamide gel electrophoresis (PAGE: 20 cm x 20 cm vertical Hoefer 600 electrophoresis unit) was employed to purify crude products (8-20% polyacrylamide/8M urea at constant current of 30 mA for 2 hours, with 1xTBE as a running buffer). The desired bands were then excised, crushed and


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incubated in 11 mL of autoclaved water at 60°C for at least 12 hours. After drying the samples to 1.5 mL, size exclusion chromatography (Sephadex G-25) was used to desalt the solution. The strands were quantified (OD260) by UV/vis spectroscopy with a NanoDrop Lite Spectrophotometer and using IDT’s extinction coefficient at 260nm. ATTO647N/Cy5/Cy3tagged DNA strands were purchased from IDT and Cy5-Biotin DNA strand was purchased from TriLink Biotechnologies. Gels containing dye-labelled oligonucleotides were visualised (BioRad GelDoc XR+ controlled with the Image Lab software package) using the appropriate excitation wavelength before being stained with GelRed (Biotium). 1xTBE buffer is composed of 90 mM Tris and boric acid, 1.1 mM EDTA, with a pH of ~8.3. 1xTAMg buffer is composed of 45 mM Tris, 7.6 mM MgCl2, with pH adjusted to 8.0 using glacial acetic acid. It is important to note that buffers used in single molecule experiments are prepared with molecular biology grade water (Fisher) and are filtered afterwards. 1xMESMg buffer is composed of 250 mM MES, 20 mM MgCl2, with pH 7.6. DNA sequences and designs utilized in constructing the different samples of DNA nanotubes including rungs and linkers used as repeating units are based on published references (27-28).

ASSOCIATED CONTENT The supporting Information is available free of charge on the ACS Publications website. DNA nanotube synthesis; DNA nanotubes sample preparation; single molecule sample preparation and imaging; coverslip functionalization procedure; TIRF Microscopy; Single molecule analysis using MATLAB-Origin software; intensity-time trajectories extraction and analysis; rejection criteria; sources of errors; analysis of single molecule intensity-time trajectories; dye-count histogram; single molecule correlation analysis; simulations on the expected nanotubes size



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distribution and dye composition; polydisperse DNA nanotubes with a 1:1 dye stoichiometry; monodisperse DNA nanotubes with a random dye stoichiometry; monodisperse DNA nanotubes with incomplete dye labelling efficiency and reaction efficiency; monodisperse DNA nanotubes with incomplete dye labelling efficiency with a probability of irreversible damage (termination, Figure 5D); surface contour plots of DNA nanotube samples, PDI calculations including larger nanotubes. AUTHOR INFORMATION Corresponding Authors E-mail*: [email protected] E-mail*: [email protected]

Author Contributions AAH performed the single molecule photobleaching measurements. AAH and GC carried out the data analysis. AAH and JSH characterized and purified the foundation rung, JSH also assisted AAH with photobleaching experiments. GDH, AAH, and HFS planned the DNA synthesis. GDH, and AAH, carried out the DNA synthesis. RG and GC performed the MATLAB simulations on nanotubes with different labelling efficiencies. JFD and PW contributed to the discussion. AAH, RG, HFS and GC designed experiments and wrote the manuscript. HFS and GC designed and coordinated the study. Notes The authors declare no competing financial interests.

ACKNOWLEDGEMENTS GC and HFS are thankful to the National Science and Engineering Research Council of Canada and the Canada Foundation for Innovation. We are also thankful to FRQNT (GC), the Canada 22 ACS Paragon Plus Environment

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Institute for Health Research (CIHR) (GC, HFS) and the Canada Research Chairs program (HFS). HFS is a Cottrell Scholar of the Research Corporation. We are also thankful to the McGill CIHR drug-development training program (AAH), GRASP and FRQNT (AAH), NSERC (RG) and Vanier Canada (GDH) for Graduate Scholarships.

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Stoichiometry and Dispersity of DNA Nanostructures Using

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