Atomic force microscopy is a powerful and widely used imaging technique that can visualize single molecules and follow processes at the single-molecule level both in air and in solution. For maximum usefulness in biological applications, atomic force microscopy needs to be able to identify specific types of molecules in an image, much as fluorescent tags do for optical microscopy. The results presented here demonstrate that the highly specific antibodyantigen interaction can be used to generate single-molecule maps of specific types of molecules in a compositionally complex sample while simultaneously carrying out high-resolution topographic imaging. Because it can identify specific components, the technique can be used to map composition over an image and to detect compositional changes occurring during a process.
The human proteome has millions of protein variants due to alternative RNA splicing and post-translational modifications, and variants that are related to diseases are frequently present in minute concentrations. For DNA and RNA, low concentrations can be amplified using the polymerase chain reaction, but there is no such reaction for proteins. Therefore, the development of single molecule protein sequencing is a critical step in the search for protein biomarkers. Here we show that single amino acids can be identified by trapping the molecules between two electrodes that are coated with a layer of recognition molecules and measuring the electron tunneling current across the junction. A given molecule can bind in more than one way in the junction, and we therefore use a machine-learning algorithm to distinguish between the sets of electronic ‘fingerprints’ associated with each binding motif. With this recognition tunneling technique, we are able to identify D, L enantiomers, a methylated amino acid, isobaric isomers, and short peptides. The results suggest that direct electronic sequencing of single proteins could be possible by sequentially measuring the products of processive exopeptidase digestion, or by using a molecular motor to pull proteins through a tunnel junction integrated with a nanopore.
To cite this article: Yuana Y, Oosterkamp TH, Bahatyrova S, Ashcroft B, Garcia Rodriguez P, Bertina RM, Osanto S. Atomic force microscopy: a novel approach to the detection of nanosized blood microparticles. J Thromb Haemost 2010; 8: 315À23.See also Freyssinet J-M, Toti F. Membrane microparticle determination: at least seeing whatÕs being sized! This issue, pp 311À4.Summary. Background: Microparticles (MPs) are small vesicles released from cells of different origin, bearing surface antigens from parental cells. Elevated numbers of blood MPs have been reported in (cardio)vascular disorders and cancer. Most of these MPs are derived from platelets. Objectives: To investigate whether atomic force microscopy (AFM) can be used to detect platelet-derived MPs and to define their size distribution. Methods: Blood MPs isolated from seven blood donors and three cancer patients were immobilized on a modified mica surface coated with an antibody against CD41 prior to AFM imaging. AFM was performed in liquid-tapping mode to detect CD41-positive MPs. In parallel, numbers of CD41-positive MPs were measured using flow cytometry. Mouse IgG 1 isotype control was used as a negative control. Results: AFM topography measurements of the number of CD41-positive MPs were reproducible (coefficient of variation = 16%). Assuming a spherical shape of unbound MPs, the calculated diameter of CD41-positive MPs (d sph ) ranged from 10 to 475 nm (mean: 67.5 ± 26.5 nm) and from 5 to 204 nm (mean: 51.4 ± 14.9 nm) in blood donors and cancer patients, respectively. Numbers of CD41-positive MPs were 1000-fold higher than those measured by flow cytometry (3À702 · 10 9 L )1 plasma vs.11À626 · 10 6 L )1 plasma). After filtration of isolated MPs through a 0.22-lm filter, CD41-positive MPs were still detectable in the filtrate by AFM (mean d sph : 37.2 ± 11.6 nm), but not by flow cytometry. Conclusions: AFM provides a novel method for the sensitive detection of defined subsets of MPs in the nanosize range, far below the lower limit of what can be measured by conventional flow cytometry.
An aneurysm of the aorta is a common pathology characterized by segmental weakening of the artery. Although it is generally accepted that the vessel-wall weakening is caused by an impaired collagen metabolism, a clear association has been demonstrated only for rare syndromes such as the vascular type Ehlers-Danlos syndrome. Here we show that vessel-wall failure in growing aneurysms of patients who have aortic abdominal aneurysm (AAA) or Marfan syndrome is not related to a collagen defect at the molecular level. On the contrary our findings indicate similar (Marfan) or even higher collagen concentrations (AAA) and increased collagen cross-linking in the aneurysms. Using 3D confocal imaging we show that the two conditions are associated with profound defects in collagen microarchitecture. Reconstructions of normal vessel wall show that adventitial collagen fibers are organized in a loose braiding of collagen ribbons. These ribbons encage the vessel, allowing the vessel to dilate easily but preventing overstretching. AAA and aneurysms in Marfan syndrome show dramatically altered collagen architectures with loss of the collagen knitting. Evaluations of the functional characteristics by atomic force microscopy showed that the wall has lost its ability to stretch easily and revealed a second defect: although vascular collagen in normal aortic wall behaves as a coherent network, in AAA and Marfan tissues it does not. As result, mechanical forces loaded on individual fibers are not distributed over the tissue. These studies demonstrate that the mechanical properties of tissue are strongly influenced by collagen microarchitecture and that perturbations in the collagen networks may lead to mechanical failure.A ortic aneurysms are localized dilatations of the aortic wall that are caused by segmental weakening of the vessel wall. Although aneurysms generally are without clinical symptoms, larger aneurysms may rupture, and bleeding from a ruptured aneurysm is responsible for more than 15,000 annual deaths in the United States alone (1).Aneurysm formation relates to a primary or secondary (acquired) defect in the matrix structures supporting the vessel wall resulting in attenuation and ultimate failure of the vessel wall (2). Although extensive loss of medial elastin traditionally is considered the hallmark of aneurysm formation, it now is acknowledged that aneurysmal growth and ultimate rupture relate to impaired collagen homeostasis (2). Remarkably, although numerous studies have looked for putative quantitative changes in aortic collagen, results reported to date are controversial (3-5). With the exception of rare mutations in the collagen III gene such as the vascular type of Ehlers-Danlos syndrome, no clear association between impaired collagen homeostasis and aneurysm growth and/or rupture has been identified.In search of the collagen defect(s) underlying aneurysm formation, we applied an integrated approach of biochemical analyses, multiple imaging modalities, and functional analysis by atomic force microscopy (AFM) to...
4(5)-(2-mercaptoethyl)-1H-imidazole-2-carboxamide is a molecule that has multiple hydrogen bonding sites and a short flexible linker. When tethered to a pair of electrodes, it traps target molecules in a tunnel junction. Surprisingly large recognition-tunneling signals are generated for all naturally occurring DNA bases A, C, G,T, and 5-methyl-Cytosine. Tunnel current spikes are stochastic and broadly distributed, but characteristic enough so that individual bases can be identified as a tunneling probe is scanned over DNA oligomers. Each base yields a recognizable burst of signal, the duration of which is controlled entirely by the probe speed, down to speeds of 1 nm/s, implying a maximum off-rate of 3 s-1 for the recognition complex. The same measurements yield a lower bound on the on-rate of ~1 M-1s-1. Despite the stochastic nature of the signals, an optimized multi-parameter fit allows base-calling from a single signal peak with an accuracy that can exceed 80% when a single type of nucleotide is present in the junction, meaning that recognition-tunneling is capable of true single-molecule analysis. The accuracy increases to 95% when multiple spikes in a signal cluster are analyzed.
Carbohydrates are one of the four main building blocks of life, and are categorized as monosaccharides (sugars), oligosaccharides and polysaccharides. Each sugar can exist in two alternative anomers (in which a hydroxy group at C-1 takes different orientations) and each pair of sugars can form different epimers (isomers around the stereocentres connecting the sugars). This leads to a vast combinatorial complexity, intractable to mass spectrometry and requiring large amounts of sample for NMR characterization. Combining measurements of collision cross section with mass spectrometry (IM–MS) helps, but many isomers are still difficult to separate. Here, we show that recognition tunnelling (RT) can classify many anomers and epimers via the current fluctuations they produce when captured in a tunnel junction functionalized with recognition molecules. Most importantly, RT is a nanoscale technique utilizing sub-picomole quantities of analyte. If integrated into a nanopore, RT would provide a unique approach to sequencing linear polysaccharides.
Microparticles, also known as microvesicles, found in blood plasma, urine, and most other body fluids, may serve as valuable biomarkers of diseases such as cardiovascular diseases, systemic inflammatory disease, thrombosis, and cancer. Unfortunately, the detection and quantification of microparticles are hampered by the microscopic size of these particles and their relatively low abundance in blood plasma. The use of a combination of microfluidics and atomic force microscopy to detect microparticles in blood plasma circumvents both problems. In this study, capture of a specific subset of microparticles directly from blood plasma on antibody-coated mica surface is demonstrated. The described method excludes isolation and washing steps to prepare microparticles, improves the detection sensitivity, and yields the size distribution of the captured particles. The majority of the captured particles have a size ranging from 30 to 90 nm, which is in good agreement with prior results obtained with microparticles immediately isolated from fresh plasma. Furthermore, the qualitative shape of the size distribution of microparticles is shown not to be affected by high-speed centrifugation or the use of the microfluidic circuit, demonstrating the relative stable nature of microparticles ex vivo.Electronic supplementary materialThe online version of this article (doi:10.1007/s10544-012-9642-y) contains supplementary material, which is available to authorized users.
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