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Single Molecule Profiling of Molecular Recognition at a Model Electrochemical Biosensor Qufei Gu, Warren Nanney, Huan H. Cao, Haiyang Wang, and Tao Ye J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.8b07325 • Publication Date (Web): 06 Oct 2018 Downloaded from http://pubs.acs.org on October 8, 2018
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Journal of the American Chemical Society
Qufei Gu†, Warren Nanney‡, Huan H. Cao‡, Haiyang Wang†, and Tao Ye*,‡ †
School of Engineering and ‡School of Natural Sciences, University of California, Merced, 5200 N Lake Rd., Merced, California, 95343, United States ABSTRACT: The spatial arrangement of target and probe molecules on the biosensor is a key aspect of the biointerface structure that ultimately determines the properties of interfacial molecular recognition and the performance of the biosensor. However, the spatial patterns of single molecules on practical biosensors have been unknown, making it difficult to rationally engineer biosensors. Here we have used high resolution atomic force microscopy to map closely spaced individual probes as well as discrete hybridization events on a functioning electrochemical DNA sensor surface. We also applied spatial statistical methods to characterize the spatial patterns at the single molecule level. We observed the emergence of heterogeneous spatiotemporal patterns of surface hybridization of hairpin probes. The clustering of target capture suggests that hybridization may be enhanced by proximity of probes and targets that are about 10 nm away. The unexpected enhancement was rationalized by the complex interplay between the nanoscale spatial organization of probe molecules, the conformational changes of the probe molecules, and target binding. Such molecular level knowledge may allow one to tailor the spatial patterns of the biosensor surfaces to improve the sensitivity and reproducibility.
Biosensors typically consist of recognition elements immobilized on the surfaces of the transducer materials. For example, the electrochemical DNA biosensors,1-2 which hold significant potential in point-of-care diagnostics due to their abilities in highly selective, label-free, and miniaturized detection of a range of biomarkers in complex biofluids,3 immobilize nucleic acid capture probes onto the electrode surfaces. Molecular recognition is influenced by the interactions between the probe and the biointerface, which consists of neighboring probe molecules and captured biomarkers (target molecules), the passivating layer, the solid substrate (planar3 or nanostructured surfaces4-5), and the solution.6-7 An outstanding challenge is that the influences of the biointerface are complex and difficult to predict, hampering the effort to form biosensors with predictable performance. Extensive studies have explored the effects of probe design,8 probe surface density,9-12 surface chemistry,13-14 and surface morphology.15 However, one aspect that has remained poorly understood is how the nanoscale lateral organization of probe and captured target molecules influences molecular recognition. The spatial organization is a key aspect of the biointerface structure that ultimately determines the complex interactions and the properties of interfacial molecular recognition. The heterogeneous local density of probe molecules was thought to have difficult-to-predict influences on the accessibility of target molecules to the probe molecules (crowding interactions).9, 16-17 Numerous studies provided indirect evidence that the impacts of the poorly controlled, often heterogeneous spatial organization of probe molecules18 may be profound: they may not only limit detection sensitivity4, 16 but also be the root cause of the large device-to-device signal variabilities6, 19-22 of many of these surface-based sensors devices. Immobilization procedures that enhance probe dispersion18 were found to improve reproducibility in target binding.20, 22-23 Moreover, the attachment of probes to nanoscale DNA tetrahedra
increased the target binding rate by orders of magnitude.16, 24-25 It was proposed that the footprint of the tetrahedral structures helps maintain uniform inter-probe separations and facilitate target binding. However, a definitive correlation between nanoscale spatial patterns and interfacial molecular recognition had not been possible as existing techniques cannot resolve single molecules on biosensors.26-27 On a practical biosensor surface with a probe density in the range of 1010-1013/cm2,7, 28 many of the molecules are separated by less than 10 nm, which is beyond the resolving power of existing techniques. Although few techniques, such as fluorescence microscopy,27, 29-30 atomic force microscopy31 and surface plasmon resonance32 have detected single recognition events, single molecule imaging was only achieved on surfaces with extremely dilute coverages. Hence, almost all existing studies relied on the overall surface densities as the key parameter to describe how surface immobilization impacts molecular recognition.9, 26, 33 While such studies have revealed general trends suggesting that surface crowding by probe molecules 9, 16-17 and captured targets34 inhibits target recognition, these ensemble averaging observables are not adequate descriptors of the crowding interactions, especially in light of growing evidence that a realistic biosensor may be highly heterogeneous in probe density.6, 18 In addition, the difficulty is compounded by the complex influences of other surface heterogeneities such as surface morphology,35 surface chemistry, and molecular conformations.6-7 Previously, using surfaces that can switch interactions with DNA on demand,18, 36-37 we have enabled atomic force microscopy (AFM) to spatially resolve single DNA molecules that are tethered to selfassembled monolayers (SAMs) on gold.38 However, the previous work did not shed light on the complex relationship between the surface structure of the DNA probes and the hybridization, because the surface hybridization kinetics was characterized using the overall hybridization yield, which is an ensemble-averaging observable that
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Figure 1. Schematic of a dynamically switchable E-DNA sensor surface. (a) A stem-loop DNA probe is covalently tethered at one end to a singlecrystal Au electrode passivated with a MUDA monolayer and modified with a MB tag (Silver) at the other end. The probe is pinned down to the surface after adding Ni2+ and thus can be imaged by AFM. (b) After imaging, the surface is rinsed with an STAE buffer and a DPV measurement is carried out under a PBS7 buffer. (c) Upon the addition of a complementary target DNA into the PBS7 buffer, the same DPV measurement is repeated. (d) The hybridized surface is imaged following the same procedure as given in step (a) above. AFM images and DPV signals of the sensor surface (e,f) before and (h,g) after the hybridization with the targets. The scale bar is 25 nm.
obscures important details of an intrinsically heterogeneous system. In addition, how the surface structure impacts the electrochemical signals was unknown as the imaging was not carried out on functioning electrochemical sensors. To address the above challenges, we have investigated for the first time how the spatial patterns of single probe molecules impact the molecular recognition of a functioning biosensor. We constructed model surfaces that serve as electrochemical DNA sensors and simultaneously utilized AFM to spatially resolve surface hybridization even when the inter-probe separation is less than 10 nm, allowing us to probe the regime where crowding interactions are important. The surfaces, which consist of electroactive DNA probes tethered to highly ordered SAMs, make it possible to modulate interaction with DNA,36 and provide an ideal platform for investigating how spatial organization of single molecules alters molecular recognition as these surfaces minimize the impact of uncontrolled morphological and compositional heterogeneities. Moreover, by applying spatial statistical tools including Ripley’s K function,39-41 nearest-neighbor distances, local crowding indices to characterize spatial heterogeneities in target binding,18 our study revealed unexpected spatiotemporal patterns of surface hybridization. The hybridization yields of probe molecules were observed to vary substantially with the nearest neighbor-distance. Hybridization of DNA targets with hairpin probes preferentially occurs where the probes are clustered, suggesting that the interactions between molecules separated by ~10 nm may facilitate target binding. The cooperative effect, in contrast with the prevailing view that increasing molecular crowding inhibits target capturing,9, 17, 33 suggests new mechanisms through which the biosensor surface can influence target binding. Our study provided the first direct evidence that the nanoscale spatial distribution of probe molecules exerts a major influence on surface hybridization. As the sensitivity of a biosensor is directly linked to interfacial molecular recognition, our findings have ramifications in biosensor design. The dramatic effect of the nearestneighbor distance on hybridization suggests a new pathway to
improve the sensitivity: we may tailor the spatial patterns to favor inter-probe separations that maximize target binding efficiency. It should also be noted that the nanoscale spatial organization likely has important but undetermined influences on almost all surfacebased biosensors.4, 42-43 In addition to surface hybridization, our approach of combining spatially resolved measurement on model surfaces with single molecule spatial statistical analysis may be applied to other types of molecular recognition, such as aptamer sensors that detect proteins.25, 44-45 How complex intermolecular interactions at the surface/interface influence the pathways of target recognition remain largely unknown. Therefore, probing and analyzing these biointerfaces at the molecular scale will lead to valuable insight that can help improve the performance of these biosensors.
To investigate target recognition by electrochemical DNA sensors at the single molecule level, we assembled a 11mercaptoundecanoic acid (MUDA) SAM on single-crystal Au(111) disk electrodes, then 23-base stem-loop probes (P1) possessing a terminal thiol on the 5’ end and a methylene blue (MB) redox reporter46 on the 3’ end were tethered to the SAM (insertion method, see Methods for details), which generates a relatively uniform probe distribution18 as opposed to the conventional backfilling method (Figure S1).12 Similar negatively charged SAMs have been used for electrochemical DNA sensors in previous studies.13, 47 The probes can be strongly immobilized on the MUDA SAM in the presence of Ni2+ (Figure 1a), appearing as circular protrusions of ~8 nm diameter (Figure 1e).36 Importantly, these immobilized probes can return to their upright state by replacing the Ni2+ buffer with a saline Tris-acetate-EDTA (STAE) buffer to enable both differential pulse voltammetry (DPV) measurement and target hybridization (Figure 1b, c). The sensor surface produces a well-resolved DPV peak, whereas after the addition of target DNAs, the peak signal drops (Figure 1f, g). We employed a target containing a 19-base singlestranded sticky-end, a 2-base spacer, and 19-bp double-stranded
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Journal of the American Chemical Society the molecular features. Hence only a lower limit, 2 1012 probes/cm2 could be estimated. As listed in Table 1 (supporting information), these values cover most of the range of probe surface densities of biosensors and microarrays used in practice, except for the high end, 1012-1013/cm2.7, 10 While single molecule imaging can directly quantify the probe densities, we also utilized the unique ability to characterize the spatial patterns of single molecules, which are inaccessible with existing averaging techniques.33, 49-50 First, we calculated the Ripley’s K function, which can characterize the tendency for the probe molecules to cluster or disperse at different spatial scales. 𝐾(𝑟) = −1 𝐸 = −1 ∑𝑖 ∑𝑗≠𝑖 𝑤(𝑙𝑖 , 𝑙𝑗 )−1
𝐼(𝑑𝑖,𝑗
