Investigating biomolecular recognition at the cell surface using atomic force microscopy.

Micron 60 (2014) 5–17

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Review

Investigating biomolecular recognition at the cell surface using atomic force microscopy Congzhou Wang, Vamsi K. Yadavalli ∗ Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA

a r t i c l e

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Article history: Received 28 October 2013 Received in revised form 7 January 2014 Accepted 7 January 2014 Available online 17 January 2014 Keywords: Atomic force microscopy Force spectroscopy Biomolecular recognition Cell surface

a b s t r a c t Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. © 2014 Elsevier Ltd. All rights reserved.

Contents 1. 2.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Basic principles of force spectroscopy via AFM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Force spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Experimental strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . AFM-FS of cell surface biomolecules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Membrane receptor proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Vascular endothelial growth factor receptor (VEGFR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Protein tyrosine kinase 7(PTK7) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. Transforming growth factor ␤1 (TGF-␤1) receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4. Invariant natural killer T cell receptor (iNKTCR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.5. Fission yeast pheromone receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.6. Adhesins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.7. Integrins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.8. Vascular endothelial cadherin (VE-cadherin) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.9. Fibrinogen adhesion receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Cell surface glycans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Glycans detected using lectin-probes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Other glycans on bacterial and plant cell surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications of cell-surface AFM-FS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Probing cancer related biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1. Prostate specific membrane antigen (PSMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2. Tenascin-C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author. Tel.: +1 804 828 0587. E-mail address: [email protected] (V.K. Yadavalli). 0968-4328/$ – see front matter © 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.micron.2014.01.002

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5.

4.1.3. P-selectin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4. Glycans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Drug design and detection of action mechanisms at the molecular scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1. Antibiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2. Rituximab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3. Design of a drug delivery system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Evaluating the effects of therapeutic agents at cell surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1. Atorvastatin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2. Effects of cigarette smoke extract (CSE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3. Trastuzumab and Pertuzumab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Challenges and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Biomolecular interactions play important roles in many biological and physiological processes (Hinterdorfer and Dufrene, 2006). Specific recognition processes between macromolecules on cell surfaces are essential for diverse cellular functions including embryonic development, signal transduction, immune response, cell adhesion, and tissue assembly (Bertozzi and Kiessling, 2001; Bustamante et al., 2004; Sheetz, 2001; Vogel and Sheetz, 2006). Recognition events on cell surfaces typically involve complex interactions between molecules such as membrane receptor proteins and ligands, carbohydrates and lectins, antigens and antibodies, and cell adhesion molecules (CAMs) and the extracellular matrix (ECM) (Fig. 1) (Kienberger et al., 2006; Mrksich, 2002; WehrleHaller and Imhof, 2002). For instance, membrane receptor proteins serve as mediators to transmit the biological signals between the cytoplasm and the extracellular environment, as realized via interactions with their specific ligands (Antonova et al., 2001; Jefford and Dubreuil, 2000; Thomas, 1996). Lectins on cell surfaces mediate cell–cell interactions by recognizing specific and complementary carbohydrates on adjacent cells (Brandley and Schnaar, 1986). CAMs such as integrin, cadherins and selectins are the transmembrane glycoproteins that mediate cell–cell and cell–ECM adhesions by the recognition of specific receptors on other cells or ECM (Edelman, 1983; Edelman and Crossin, 1991). Several important, fundamental questions remain in our understanding of these events: How do receptor proteins interact with their ligands and initiate specific transduction pathways? How do lectins bind with their specific carbohydrates and mediate relevant cell–cell recognition and cell–ECM adhesion? How do CAMs interact with ECM

Fig. 1. Typical biomolecular interactions that can be measured on the surface of cells.

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and make cells grow on different types of surfaces? What happens if these interactions are blocked by exogenous substances? All these recognition events on cell surfaces are driven by molecular scale interaction forces. The interaction forces of proteins with their ligands contain fundamental biophysical data that can enable us to quantitatively elucidate the relevant cellular signal transduction processes. Interactions on cell surfaces have fundamental roles for characterizing various normal processes including cellular growth, differentiation, junction formation and polarity (Albelda and Buck, 1990; Aplin et al., 1998) or pathological processes in living organisms, such as cellular adhesion, infection and cancer cell metastasis (Gorelik et al., 2001; Ohyama et al., 1999; Sharon and Lis, 1989). In addition, these interaction forces provide a mean for evaluating the selectivity and specificity of various biological probes that can be useful in developing cell-specific bio-analytical and biomedical devices (Jelinek and Kolusheva, 2004; Turner, 2000; Zheng et al., 2005). Consequently, measuring these forces directly has implications in unraveling the molecular basis of relevant biological and pathological processes on cell surfaces, as well as in developing new tools for disease diagnosis and detection, or drug screening at a molecular level (Kim et al., 2007; Yu et al., 2011). Force spectroscopy as a dynamic analytical technique, allows the measurement of interaction forces at the level of individual molecules, which cannot be obtained from conventional ensemble measurements (Hugel and Seitz, 2001). In this context, “force spectroscopy” is not used in the sense of traditional spectroscopy, which is based on the interaction of radiation with matter (Carvalho and Santos, 2012). Typically, in this process, the pair-wise interaction between (bio)molecules is measured by immobilizing one (bio)molecule on a substrate, while the other attached to another surface or a probe (for example, a magnetic bead or a stiff cantilever). The force is then derived from the deviation of the surface or the probe from its equilibrium position (Israelachvili et al., 2010; Lin et al., 2005; Molloy and Padgett, 2002; Neuman and Nagy, 2008). The technique of force spectroscopy has been used to study the unfolding of single proteins and nucleic acid structures by mechanically stretching the biomolecule across two ends immobilized to surfaces (Hyeon and Thirumalai, 2007; Zhuang and Rief, 2003). To date, several different kinds of force spectroscopy techniques have been employed for determining these forces of interaction. These include optical tweezers, magnetic tweezers and atomic force microscopy (AFM) (Gosse and Croquette, 2002; Krasnoslobodtsev et al., 2007; Leckband et al., 1992; Merkel et al., 1999; Moffitt et al., 2008), all of which operate within specific limits of sensitivity and range of forces. The principles, applications and limitations of these three techniques were recently summarized in an excellent review (Neuman and Nagy, 2008). Among them, AFM has rapidly emerged as a versatile tool widely used over the last couple of decades. The unique advantage of the AFM is the ability not only to image single molecules with nanoscale resolution, but also measure inter- and intra-molecular interaction forces with piconewton


sensitivity (Dufrene and Hinterdorfer, 2008; Florin et al., 1994; Jalili and Laxminarayana, 2004; Li et al., 2002). The unique abilities of working under near physiological environments combined with excellent force and lateral resolution make AFM-based force spectroscopy (henceforth referred to as AFM-FS in this manuscript) a powerful approach to measure the biomolecular interaction forces not only on fixed non-biological substrates (such as glass or silicon), but importantly, on soft cell surfaces. There have been several reviews on the use of AFM in different imaging modalities as well as their use in studying protein structure and function (Engel and Muller, 2000; Fotiadis et al., 2002; Santos and Castanho, 2004; Shao et al., 1996). A number of reviews have also covered the use of AFM-based force spectroscopy to uncover interaction forces as well as unique nanomechanical signatures obtained by the forced mechanical unfolding of proteins and polymers (Borgia et al., 2008; Bujalowski and Oberhauser, 2013; Hoffmann and Dougan, 2012; Puchner and Gaub, 2009). In this review, we specifically focus on the methodology of AFM-FS applied at static and dynamic cell surfaces. Our focus is primarily on biomolecules that are either present at cell surfaces or have a direct impact on cellular behavior and function. Of special interest is the in situ application of AFM-FS on cell surfaces, a relatively recent technique with a great potential to directly probe biomolecules in their milieu. We then discuss the unique challenges that distinguish this form of force spectroscopy and summarize recent progress in the study of biomolecules found at the cell surfaces. Probing the forces that drive biomolecular recognition on cell surfaces will result in increasing our understanding of the fundamental organization, mechanics, interactions and processes at the cell surface.

2. Basic principles of force spectroscopy via AFM 2.1. Force spectroscopy The workings of the AFM have been extensively covered in prior works and will not be reiterated here (Cappella and Dietler, 1999; Dufrene, 2008; Giessibl, 2003; Lee et al., 2007a; Santos and Castanho, 2004). Briefly, an AFM primarily consists of four parts: a soft cantilever with a sharp tip (commonly silicon or silicon nitride), a sample stage on a piezoelectric scanner, a laser diode and a photodetector as the optical detection system. In AFM-FS studies, tips are commonly functionalized with one or a small amount of probe molecules. The cantilever with the modified tip moves vertically (z-axis) toward the surface, contacts the surface, and then retracts. During this process, the interaction forces between the tip and sample cause bending of the cantilever detected by the photodetector. The cantilever deflection (x) as a function of the vertical displacement of the piezoelectric scanner can be recorded. Then the force can be obtained by applying Hooke’s law (F = −kx), where F is the force, k is the spring constant of the cantilever and x is the deflection of the cantilever. The force of rupture between a pair of molecules can therefore be determined (Hugel and Seitz, 2001; Merkel et al., 1999). A typical force curve reflecting the interactions of the cantilever with a typical sample surface is shown in Fig. 2. The measured rupture forces closely depend on the loading rates (spring constant of cantilever multiplied by retraction velocity of tip) that are exerted on the molecular complex. With the increase of loading rates, the forces increase due to their linear relationship with loading rates (Evans and Calderwood, 2007; Friddle et al., 2012; Schwesinger et al., 2000). By collecting a range of data over broad loading rates, dynamic force spectroscopy (DFS) as a subset of AFM-FS has emerged as a valuable technique for the characterization of dissociation kinetics and energy profile of the interacting molecules (Evans, 2001; Hugel and Seitz, 2001; Hyeon and Thirumalai, 2012). In recent years, the process of

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Fig. 2. Probing cell surfaces using AFM based force spectroscopy.

collecting individual force curves has been further expanded with the advent of automated scanning modes that allow us to obtain spatial distributions of adhesion forces. These “adhesion force mapping” methods are based on collecting arrays of force curves on a given size area, and then displaying the unbinding force values of all traces (Fig. 3a–c and f). Owing to the collection of spatial and force information simultaneously, this approach has been particularly useful for mapping recognition sites on the surfaces of live cells (De Pablo et al., 1999; Eaton et al., 2002; Heinz and Hoh, 1999; Kienberger et al., 2006). Another AFM based force mapping method termed “dynamic recognition imaging” is also used to identify the recognition sites on cell surfaces. With a ligand functionalizedAFM tip oscillating on the cell surface, cognate receptors can be detected due to a reduction in the oscillation amplitude when ligand–receptor binding events occur. Although lacking quantitative force values, the force maps generated by this approach tend to have higher spatial and time resolution compared to adhesion force maps (Chtcheglova and Hinterdorfer, 2011; Dupres et al., 2007; Han et al., 1996; Stroh et al., 2004). 2.2. Experimental strategies Biomolecular interactions can be measured by AFM-FS not only on static (often non-biological) substrates, but also directly on the surfaces of living cells (Dupres et al., 2007). In order to measure the pair-wise interaction forces between biomolecules on the tip and on the sample using AFM, the first step is to immobilize them on each surface (Neuman and Nagy, 2008). There are several requirements that need to be fulfilled during this step in order to collect correct or meaningful data: (i) firm immobilization to avoid detachment of the immobilized biomolecules during retraction; (ii) optimal orientation and availability of binding sites of biomolecules for recognition; (iii) preservation of their native states, and, (iv) minimization of nonspecific interactions between the functionalized tip and the substrate (Barattin and Voyer, 2011; Lv et al., 2009; Safenkova et al., 2012). In the case of cells, where the biomolecule being probed is in situ at the cell surface, the challenge is to immobilize the complementary molecule to the cellular target on the tip only. The basic principles still remain the same as nowadays, it is possible to obtain AFM tips with a wide diversity of materials coatings including silicon, silicon nitride, aluminum and gold. Generally, the simplest way to immobilize biomolecules is by physical absorption. However, the intrinsic lack of control over this attachment of molecules via this method makes it difficult to fulfill the requirements discussed above (Barattin and Voyer, 2008; Schon et al., 2007). In contrast, chemical modification combined with functionalized self-assembled monolayers (SAMs) typically shows superior performance due to good reproducibility and flexibility in biomolecular immobilization, especially for proteins (Dammer

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Fig. 3. Examples of AFM-FS studies on biomolecular recognition on cell surfaces. (a–c) Adhesion force maps in real time showing VEGFRs on cell surface concentrating toward cell boundaries and clustering rapidly after the addition of the antibody at: (a) 0, (b) 10, and (c) 45 min. Source: Reprinted from (Almqvist et al., 2004) with the permission of Elsevier. (d) AFM-FS measurements of specific binding forces between HBHA and its receptor HSPG on living host cells (Dupres et al., 2009; Muller et al., 2009). Constant force plateaus at large loading rates on force curves implied that stressed HSPG receptors can potentially detach from the cytoskeleton, leading to extraction of the membrane tethers or nanotube. Source: Reprinted from (Muller et al., 2009) with the permission of Nature Publishing Group. (e, f) Detection of peptidoglycan on surface of living Lactococcus lactis cells using adhesion force mapping. (e) Topographic image of two dividing bacterial cells. (f) Adhesion force map (400 nm × 400 nm) recorded with a LysM modified probe in the square area shown in topographic image. The peptidoglycan molecules were detected (bright pixels) to be arranged as lines running parallel to the short cell axis. Source: Reprinted from (Andre et al., 2010) with the permission of Nature Publishing Group.

et al., 1996; Miyake et al., 2007; Smith et al., 2004). Common systems include alkylthiolation on gold surfaces or silanization on silicon surfaces. The reaction of alkylthiols with gold and silane with silicon form covalent S H bonds and Si O Si bonds respectively. S H and Si O Si bonds have a higher strength, compared with the binding forces of the biomolecules themselves, which is necessary for force spectroscopy. After the formation of SAM, the surfaces are often functionalized with the terminated groups of the alkylthiols and silanes (Love et al., 2005; Miyake et al., 2007). For example, for protein immobilization, the gold tip and substrate can be functionalized with a COOH-terminated SAM (Lv et al., 2010; Wang et al., 2011). Terminated carboxyl groups can then be activated by 1-ethyl-3-(dimethylaminopropyl) carbodiimide hydrochloride (EDC), and N-hydroxysulfosuccinimide (NHS). Finally, proteins are immobilized by the formation of an amide linkage between the activated carboxyl groups and amine groups of lysine on the protein surface. The advantage of force spectroscopy on cell surfaces is that the molecules studied are in the milieu of their cell membranes, which maintains their structural assembly and functional state (Lecuit and Lenne, 2007). This enables forces, dynamics and distributions of specific interactions to be detected in real time (Dufrene and Garcia-Parajo, 2012). However, the extremely complex nature of cell membranes, their relative deformability, fragile nature, and lack of flatness pose additional challenges in their study by AFMFS. For instance, different targets exposed on cell surfaces may produce both specific and nonspecific interactions concurrently, which makes the interpretation of force curves difficult (Muller et al., 2009). Similarly, the soft cell membrane may be penetrated by the stiffer cantilevers with high spring constant during the force collection, which may cause inaccuracies in the force measurement process itself (Kwon et al., 2009). Beside the tip preparation strategies mentioned above, proper cell immobilization methods to maintain the natural state of cells are also necessary for accurate force measurements. Typical

substrates for cell immobilization include glass, mica and silicon. The selection of the substrate depends on the cell type and target molecules studied. For instance, for studying membrane proteins on animal cells, traditional methods including air-drying and glutaraldehyde immobilization may denature the proteins at the surface (Kienberger et al., 2006). A simple method by virtue of their ability to spread and stick to solid substrate has been used by most animal cell studies. Therefore, AFM-FS can be conducted directly in cell culture media in a Petri dish (Almqvist et al., 2004). The advantage of this method lies in the preservation of normal cell morphology and viability in a liquid environment. By pre-coating the substrate with collagen, fibronectin and polylysine, it is possible to enhance the immobilization, and separate the cell from the substrate to avoid denaturation (Carvalho et al., 2010; Henderson et al., 1992). In contrast, for polysaccharides on plant cell wall surfaces, protein denaturation is not a key issue. Such cells can be immobilized directly on glass substrates with epoxy glue and with force measurements performed in a liquid environment (Zhang et al., 2012b). Generally, a fluid cell as a part of the sample stage creates the needed liquid medium for force measurements. For microbial cells such as bacteria and yeast which cannot adhere to substrates easily, immobilization is achieved by mechanically trapping them, into porous polycarbonate membranes for example (Andre et al., 2010). The prerequisite of this method is that the pore size of the membrane should be comparable to the dimensions of the cell (Dufrene, 2002; Heinisch et al., 2012; Touhami et al., 2004). 3. AFM-FS of cell surface biomolecules The cell separates its cytoplasm from the extracellular environment via a cell membrane consisting of a phospholipid bilayer with embedded proteins and carbohydrates located on the extracellular surface of the membrane (Fig. 1). The basic function of cell membrane is protection of cell cytoplasm from its surroundings. Various cellular activities are triggered by the biomolecular recognition at


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Table 1 Some reported examples of biomolecules on cell surfaces studied via AFM-FS.

Membrane receptor proteins

Cell adhesion molecules

Biomolecules on cell surface

Functionalized tip

Vascular endothelial growth factor receptor (VEGFR) (Almqvist et al., 2004; Lee et al., 2007b) Protein tyrosine kinase 7 (PTK7) (O’Donoghue et al., 2012) CD1d-presented lipid antigens (Bozna et al., 2011) Fission yeast pheromone receptor (Sasuga et al., 2012) Transforming growth factor ˇ (TGF-ˇ) receptor (Yu et al., 2007) Chlorinated ovalbumin (OVA) receptor (Zapotoczny et al., 2012)

VEGFR-antibody

Heparin-binding haemagglutinin adhesin (HBHA) (Dupres et al., 2005) Heparan sulfate proteoglycan receptors (Dupres et al., 2009) Integrin ␣2 ␤1 (Attwood et al., 2013)a

Heparin

Integrin lymphocyte function-associated antigen-1 (Rico et al., 2010) ␣llb ␤3 -related integrin (Carvalho et al., 2010) Vascular endothelia cadherin (VE-cadherin) (Chtcheglova et al., 2010) Glycans

Glycans detected by lectins

Soybean agglutinina (Sletmoen et al., 2009) Glycosylated extracellular domain III of the epidermal growth factor receptor (Gunning et al., 2008) Concanavalin A (Zhang and Yadavalli, 2009)a Mannose and Galactose (Francius et al., 2008) d-galactose (Li et al., 2011b)

Glycans on bacterial and plant cell surface

O-antigenic lipopolysaccharides (Handa et al., 2010) Natural crystalline cellulose (Zhang et al., 2012b) Peptidoglycans (Andre et al., 2010)

a

DNA aptamer sgc8c and PTK7-antibody T cell receptor (TCR) Pheromone TGA-ˇ1 Chlorinated OVA

HBHA Collagen containing specific integrin-binding motif Intercellular adhesion molecule-1 Fibrinogen VE-cadherin-antibody Porcine submaxillary mucin Wheat germ agglutinin Mannose Concanavalin A and Pseudomonas aeruginosa lectin Ricinus communis agglutinin-120 Bacteriophage P22 tailspike proteins Carbohydrate-binding module of cellulolytic enzyme Lysine motif

Experiments using biomolecules on static surfaces. All others refer to in situ cell surface experiments.

the cell surface (Andersson et al., 1988; Korn, 1969; Salton, 1967; Yeagle, 1989). More practicably, the force mapping technique that combines AFM-FS with the high spatial resolution of the AFM, offers the opportunity to map cell surface recognition sites or biomarkers that would not be otherwise found by traditional, macroscale techniques. There have been an increasing number of reports applying AFM-FS to characterizing biomolecular interactions that may be found on the cell surfaces, indicated their potential to pry out answers to fundamental questions. In the following sections, we discuss these studies to demonstrate the unique advantages of AFM-based spectroscopy as applied to different kinds of biomolecular systems. Table 1 summarizes some of these reports. 3.1. Membrane receptor proteins Membrane proteins play an important role in a variety of cell functions (Dirienzo et al., 1978; Eisenberg, 1984; Tanford and Reynolds, 1976). In particular, membrane receptor proteins transmit signals between the extracellular and intracellular environments. For example, cell adhesion molecules mediate cell–cell recognition and cell–ECM adhesion. Their functions are largely determined by physical forces acting on and between the biomolecules. A few examples of membrane proteins studied via AFM-FS are presented below: 3.1.1. Vascular endothelial growth factor receptor (VEGFR) VEGFR is a typical transmembrane receptor protein expressed on vascular endothelial cells (Olsson et al., 2006). The recognitions between VEGFR and its ligand are critical to several cellular activities such as focal adhesion turnover, actin cytoskeletal remodeling, and angiogenesis (Izumi et al., 2003; Rakhmilevich et al., 2004). Spatial features such as clustering, distribution of VEGFR on cell surfaces are closely related to endothelial cell growth and

migration (Thomas, 1996). Preliminary studies using AFM-FS have typically involved directly measuring interaction forces between the biomolecular pairs on static substrates prior to their studies in the more complex cellular environments. Almqvist et al. initially employed AFM-FS to measure the adhesion forces between isolated VEGFR adsorbed on the mica substrate and its antibody immobilized on an AFM tip (Almqvist et al., 2004). The unbinding force of 60 ± 10 pN was consistent with previous studies using the antigen–antibody pair (Lee et al., 2007a; Ros et al., 1998). As discussed above, one significant feature of AFM-FS lies in its “adhesion force mapping” method allowing mechanical detection of cell surface recognition sites in real-time and in situ under different physiological conditions. Using this approach, the location, density and distribution of VEGFRs on cell surfaces were imaged. The adhesion force map showed that the VEGFRs tended to concentrate toward the cell boundaries and clustered rapidly after the addition of VEGF or the antibody of VEGFR (Fig. 3a–c). In a later study, a twostep procedure was developed: first locating the VEGFRs followed by force analysis (Lee et al., 2007b). This process used dynamic recognition imaging method to map VEGFRs on vascular endothelial cell surface with antibody-modified AFM tips. Force maps obtained by this approach revealed the non-uniform distribution of VEGFRs with respect to the underlying cytoskeleton. The force maps from dynamic recognition imaging method have a higher spatial and time resolution compared to an adhesion force map, as force curves are not collected point by point. In order to obtain detailed information on the interaction forces, AFM-FS spectroscopy was then conducted on the recognition sites to measure the rupture force and unbinding times. The distribution of these rupture forces with two peaks of 33 and 64 pN implied one or two receptors binding with a single antibody. This study highlighted the use of AFM-FS to assess kinetic parameters of binding process on cell surfaces. From the rupture force and unbinding time acquired, the

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equilibrium dissociation rate koff was determined directly through the Bell model (Bell, 1978), koff = 1.05 ± 0.6 × 10−4 s−1 . The equilibrium association rate kon was obtained from a monovalent binding kinetic model (Lauffenburger and Linderman, 1993) by blocking receptors with soluble antibodies, kon = 5.83 ± 1.48 × 104 s−1 M−1 . Both approaches provided spatial visualization of VEGFRs as well as the forces between ligands and their receptors which could shed light on their functional roles in receptor-mediated cellular behavior. 3.1.2. Protein tyrosine kinase 7(PTK7) PTK7, as a member of the receptor tyrosine kinase family, is an important surface biomarker in cancer research (Lewis et al., 2011). The interactions between PTK7 and its ligand are important in developing specific bio-analytical and biomedical techniques (Zhang et al., 2013a). O’Donoghue et al. focused on the investigation of the binding affinity of a natural antibody and a synthetic DNA aptamer with PTK7. AFM-FS provides a high accuracy tool to measure and compare the rupture forces of PTK7 with its respective DNA aptamer and antibody (anti-PTK7). The rupture force on live cell membranes between the aptamer and protein was measured to be 46 ± 26 pN, while the force with the antibody was 68 ± 33 pN. The measured force values with two ligands are very similar indicating that DNA aptamer has the potential for targeted delivery of chemotherapy to tumors. This study also showed that aptamers are useful bio-probes to detect specific biomarkers on various cell surfaces via functionalization on AFM tips (O’Donoghue et al., 2012). In addition to specific receptors, AFM-FS was recently applied for discovery of unknown receptors on cell surface. One example is probing the specific recognition events between chlorinated ovalbumin (OVA) and macrophages (Zapotoczny et al., 2012). The unique aspect of this research was the data processing, which reported on the use of adhesion frequency (AF) to detect the unknown receptors on cell surface. The AFM tip modified with chlorinated OVA showed 85% AF on macrophage surface, while the native OVA modified tip as control experiment showed a negligible AF value. Blocking of the receptors by the chlorinated OVA significantly decreased the adhesion between chlorinated OVA and the cell surface, which confirmed the specificity of the interactions. The results implied this technique could be useful to detection of undefined recognition sites on cell surfaces. AFM-FS has been further used in conjunction with other techniques to enable efficient data collection and improve experimental validity for different systems: 3.1.3. Transforming growth factor ˇ1 (TGF-ˇ1) receptor TGF-ˇ1 regulates various cellular biological processes including cell motility, recognition, proliferation, differentiation, and apoptosis. The TGF-ˇ1signaling process involves TGF-ˇ1binding to its receptors including type I TGF-ˇ receptor (TˇRI) and type II TGFˇ receptor (TˇRII) (Massague, 1990; Massague and Chen, 2000). Using force spectroscopy, the interactions between TGF-ˇ1and its receptors were investigated in vitro and in vivo. Fluorescence imaging was used to locate fluorescently-tagged TGF-ˇ receptors on cell surface. The AFM results revealed similar unbinding force of TGF-ˇ1with TˇRII on a silicon substrate as well as TˇRII on the cell surface. The co-expression of TˇRI with TˇRII increased the unbinding force of TGF-ˇ1 with its receptors, although the expressed TˇRI alone showed no specific binding affinity with TGF-ˇ1 (Yu et al., 2007). Here AFM-FS provided a better understanding of the molecular mechanism of TGF-ˇ signaling and the fluorescent imaging offered the AFM with an efficient collection of force curves. 3.1.4. Invariant natural killer T cell receptor (iNKTCR) Invariant natural killer T (iNKT) cells play a critical role in the immune system. The functions of iNKT cells are realized by

the recognition between iNKTCR on the iNKT membrane with endogenous and exogenous cluster of differentiation 1d (CD1d) – presented lipid antigens (Joyce, 2001). By using iNKTCR functionalized AFM tips, the unbinding forces with CD1d proteins having different length of the phytosphingosine chain were measured in vitro and in vivo. The results showed that the CD1d–glycolipid complexes immobilized on both mica surfaces and on living cell surfaces had specific interactions with iNKTCR. Higher unbinding forces were required to dissociate the iNKTCR and CD1d with longer phytosphingosine chains. This study also compared the kinetic rate constants of the pairwise molecules obtained from AFM-FS with those obtained using surface plasmon resonance (SPR). The good consistency of the two techniques further confirmed the validity of the results (Bozna et al., 2011). 3.1.5. Fission yeast pheromone receptor The fission yeast pheromone receptor is a kind of G proteincoupled receptor (GPCR), a typical membrane receptor protein on cell surface. These receptors are activated by pheromone binding and then enable cellular signal transduction (Kohl et al., 2001). The interactions between the pheromone and its receptors on yeast cell surfaces were studied by AFM-FS (Sasuga et al., 2012). AFM tips were modified with the pheromone and a pheromone analog (lacking specific binding sites) to measure the interaction forces on cell surfaces. The specific rupture forces between the pheromone and its receptor were recorded to be ∼120 pN at a pulling velocity of 1.74 ␮m/s. As expected, the pheromone analog modified tips do not show a force jump in force curves. A report gene assay was carried out to study their interactions, wherein a green fluorescent protein labeled reporter gene was used to monitor the activation level of signal transduction following the interactions of pheromone and its receptors. Binding of the pheromone to its receptors on cell surface initiated the relevant signaling pathway and increased the fluorescence intensity, while the nonspecific pheromone analog did not show positive results. The results of the report gene assay therefore confirmed the validity of the AFM results, implying that this approach has the potential for signaling and screening studies of receptors and their ligands. In addition, cell adhesion molecules (CAMs), as another type of membrane receptor proteins, are typically transmembrane glycoproteins that mediate binding to extracellular matrix (ECM) molecules or to counter-receptors on other cells. These molecules determine the specificity of cell–cell or cell–ECM interaction (Aplin et al., 1998): 3.1.6. Adhesins Adhesins, as a class of CAMs located on bacterial cell surfaces, facilitate bacterial adhesion to host cell surfaces by the recognition between adhesins and their specific receptors on host cell surfaces (Jacques and Paradis, 1998). Using AFM-FS, biomolecular interactions can be measured both in vitro and in vivo, thereby providing complementary information for the system. For instance, the specific interaction forces between heparin and adhesin (heparinbinding haemagglutinin adhesin, HBHA) were measured and then the HBHA distribution were mapped on the surface of Mycobacterium tuberculosis using adhesion force mapping (Dupres et al., 2005). First, the adhesion forces were measured between HBHA modified tips and a heparin immobilized surface. The adhesion force histogram showed a bimodal distribution with forces of 50 and 117 pN that could be attributed to one and two binding pairs of HBHA and heparin. The adhesion force map obtained on living cell surfaces using heparin-modified tips showed that adhesin tended to cluster on the cell surfaces, instead of being homogeneously distributed. In a later report by the same group, the interactions between HBHA and heparan sulfate proteoglycan (HSPG) receptors on living cell surfaces were investigated. Adhesion forces


measured on the cell surface showed similar force values to the HBHA–heparin pairs. The adhesion force map on living cell surface showed homogeneous distribution of HSPG receptors. Interestingly, force curves with constant force plateaus were observed at higher loading rates, which might be interpreted as the extraction of membrane tethers or nanotubes during the pulling process of AFM tip (Dupres et al., 2009; Muller et al., 2009) (Fig. 3d). This particular phenomenon observed from AFM-FS may open new avenues in pathogenesis research. In addition, the idea of spatially representing force data creates new methods for visualizing biophysical data on the cellular scale. 3.1.7. Integrins Integrins form another class of CAMs that mediate cell–cell adhesion and cell–matrix interactions. The integrins as adhesion receptors on cell surfaces are involved in a number of biological processes, including cellular signal-transduction, embryonic development, inflammation, cancer metastasis and wound healing (Albelda and Buck, 1990). For example, the recognition between platelet transmembrane receptor, integrin ␣2 ␤1 , and collagen is crucial for hemostasis (Knight et al., 2000). Using AFM-FS, the interaction forces between integrin ␣2 ␤1 and a collagen containing specific integrin-binding motif Gly-Phe-Hyp-Gly-Glu-Arg (GFOGER) were measured. Control experiments were conducted by using a collagen containing Gly-Pro-Pro (GPP) which lacks the GFOGER motif. The force curves showed multiple unbinding events for both GFOGER and GPP indicating that the binding sites between ␣2 ␤1 and collagen are not only at the GFOGER motif, but also at other parts of the collagen molecule (Attwood et al., 2013). In another study, the temperature effect on integrin-mediated cell adhesion was investigated using AFM-FS (Rico et al., 2010). The AFM tip was functionalized with intercellular adhesion molecule-1 (ICAM-1) and was used to probe the receptor integrin lymphocyte function-associated antigen-1 (LFA-1) on the cell surface. The results indicated that cell adhesion was suppressed by a decrease of temperature. This implies that a reduction of temperature contributes to controlling swelling and inflammation. 3.1.8. Vascular endothelial cadherin (VE-cadherin) VE-cadherin, a single-pass transmembrane glycoprotein, is the major adhesion molecule of endothelial adherent junctions and known to be primarily responsible for mechanical linkage between endothelial cells. By using a VE-cadherin-Fc -functionalized AFM tip and dynamic force mapping, a recognition map of the distribution of VE-cadherin on microvascular endothelial cells was obtained. The VE-cadherins were observed to not be uniformly distributed, but located mostly along F-actin filaments (Chtcheglova et al., 2010). This study showed that the clustered VE-cadherin molecules are linked through their cytoplasmic domain to the actin-based cytoskeleton, which is important for the understanding of mechanism of VE–VE adhesion from the view of their cell surface architecture. 3.1.9. Fibrinogen adhesion receptors The interactions of fibrinogen and its adhesion receptors on erythrocyte membrane are the primary reason for erythrocyte aggregation, which increases the incidence of cardiovascular and cerebrovascular diseases. The interaction forces between fibrinogen and its receptors on erythrocyte membrane were initially detected using AFM (Maeda et al., 1987). The unbinding force of 97 pN was close to the force between fibrinogen and a platelet. The interactions were inhibited by eptifibatide (an ␣llb ␤3 specific inhibitor), which implied the possibility of ␣llb ␤3 -related integrin as the adhesion receptors on the cell surfaces. Subsequently, force spectroscopy was conducted on cells from a patient with Glanzmann thrombasthenia, a disease caused by ␣llb ␤3 deficiency.

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The decreased unbinding forces further confirmed the presence of ␣llb ␤3 -related integrin on the erythrocyte surfaces (Carvalho et al., 2010). These examples showed the suitability and versatility of AFM-FS for studies on cell–cell adhesion and cell–matrix interactions from a mechanical perspective. Simultaneous imaging of specific binding sites down to the level of a few nanometers was also enabled. Besides the molecular scale studies discussed above, AFM-based single-cell force spectroscopy (SCFS) has been developed as an expanded tool for studying CAMs and the dynamics of regulated adhesion processes in living cells. By attaching a single cell onto an AFM cantilever, a living cell can be converted to a “cell-probe” to detect the adhesion force between whole cells or to CAMs immobilized on substrates (Helenius et al., 2008). The depiction of cell–cell adhesion measurements and typical force–distance curves are shown in Fig. 4a and b. For example, a lectin functionalized surface was used to immobilize Dictyostelium discoideum cells onto an AFM cantilever and substrate so that cell–cell adhesion could be studied (Benoit et al., 2000). Developmental regulation and EDTA resistance indicated that the measured force of 23 pN may be due to unbinding of contact site A (csA) molecules on the cell surfaces. Further genetic manipulation demonstrated that csA is the principal source of the intercellular adhesion. Similarly, the interaction of LFA-1, expressed on Jurkat T cells, with intercellular adhesion molecules (ICAM) were also studied using SCFS (Wojcikiewicz et al., 2006; Zhang et al., 2002). In the latter report, the interaction of LFA-1 with ICAM-1 and ICAM-2 were conducted at varying loading rates (Wojcikiewicz et al., 2006). An AFM cantilever attached with a Jurkat T cell was allowed to interact with the proteincoated substrates. The results indicated that the dissociation of both complexes involved overcoming a steep inner, and a wide outer activation barrier. ICAM-1 exhibited stronger binding to the high-affinity form of LFA-1. Differences in the kinetic profiles and intermolecular potentials of ICAM-1 and ICAM-2 could therefore be attributed to structural differences in their binding site. For integrin and collagen interactions, early steps of ␣2 ␤1 integrin-mediated cell adhesion to a collagen type I matrix were studied using SCFS. Increasing the contact time to a certain extent showed elevated overall cell adhesion, suggesting a change from single to cooperative receptor binding (Taubenberger et al., 2007). This SCFS study provided new insights into temporal and mechanistic aspects of early integrin binding events. 3.2. Cell surface glycans 3.2.1. Glycans detected using lectin-probes Cell-surface glycans have been studied as significant factors in various cellular physiology and diseases, including immune recognition, cell adhesion, cell migration, bacterial infections, inflammation and cancer (Inatani et al., 2003; Ohyama et al., 1999; Pilobello and Mahal, 2007). Lectins are proteins having a specific affinity to glycans. By virtue of their interactions with specific glycans, lectins have evolved as efficient molecular probes to detect specific glycans on cell surfaces, which in turn, are essential to a variety of cell functions and pathological processes (Grandbois et al., 2000; Kim and Varki, 1997). Several works have focused on the interactions between lectins–glycans both in vitro and in vivo by using AFM-FS. For instance, soybean agglutinin (SBA) as a molecular probe showed its unique ability to analyze the structural property of glycoproteins by force curve analysis. The unbinding forces between SBA on a mica surface and mucin on AFM tip were measured (Sletmoen et al., 2009). Force curves with multiple force jumps implied several unbinding events, consistent with the structure of the carbohydrate chains of mucin. Moreover, the unbinding distance shown on force curves was equal to the length of the mucin chain. These results combined with calculated kinetic parameters

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Fig. 4. (a) Schematic of cell based force spectroscopy experiments: During the approach (green arrows), the cell probe is pressed onto the cell on substrate until a set force is reached and held for a specific contact time. The cell is then retracted from the substrate (blue arrows) and the detachment forces between the probe and sample can be measured from the bending of the cantilever. (b) Before detachment, two types of molecular unbinding events can occur. In the first, the receptor remains anchored in the cell cortex and unbinds as the force increases (jumps). The second unbinding event occurs when receptor anchoring is lost and membrane tethers are pulled out of the cell (tethers). Source: Reprinted from (Helenius et al., 2008) with the permission of Company of Biologists Ltd.

were compatible with a binding model in which lectin molecules tend to “bind and jump” from a glycan residue to another along the polypeptide chain of mucin before dissociating. In another report, wheat germ agglutinin (WGA) was used as the probe to detect specific receptors on a cell surface. Gunning et al. measured the interaction forces between a WGA coated tip and a glass surface functionalized with N,N ,N -triacetylchitotriose (a known receptor for WGA) (Gunning et al., 2008). The rupture force between WGA and its receptor (the glycosylated extracellular domain III of the epidermal growth factor receptor) was measured on a Caco-2 human colon carcinoma cell. Adhesive events were subsequently used to map the location of recognition sites on the cell surface revealing heterogeneity in their distribution. Similarly, Ricinus communis agglutinin-120 (RCA120) was used as a probe to directly measure the interaction forces between RCA120 and galactosyl residues on living HeLa cell surfaces (Li et al., 2011b). The unbinding force was observed to be 43 pN at loading rate of 0.4 nN s−1 . The blocking experiment performed in free d-galactose solution confirmed the specificity of the lectin–carbohydrate interactions. Concanavalin A (Con A) is another widely used lectin that binds specifically to ␣-d-mannosyl and ␣-d-glucosyl residues. Zhang et al. used an efficient one-step amination reaction strategy to fabricate carbohydrate arrays based on mixed self-assembled monolayers and then probe the specific Con A-mannose interactions. The results showed the value of the rupture force for a single Con A-mannose bond to be 95 ± 10 pN (Zhang and Yadavalli, 2009). The aggregation state of Con A was regulated by pH, resulting in different dominant rupture forces. Con A was also used as a probe to detect specific carbohydrates on cell surface. Francius et al. used a Con A modified tip to probe mannose immobilized on agarose beads. The corresponding adhesion force histogram displayed a rupture force peak at 57 ± 19 pN (Francius et al., 2008). This and another functionalized tip (Pseudomonas aeruginosa lectin, PA-1 that interacts with galactose) were used to map the surface polysaccharides of the Lactobacillus rhamnosus strain GG (LGG) wild-type and mutant strains using adhesion force mapping. The maps showed the mannose and galactose properties (distribution, adhesion, extension) of the LGG wild-type are markedly different from those of the mutant strains. Similarly, the presence of bacterial glycogen on the surface of Pseudomonas fluorescens was determined by combining infrared spectroscopy, AFM-FS and fluorescence microscopy (Quiles et al., 2012). Con A was used as

the bio-probe in both AFM-FS and fluorescence experiments. The results showed the increase of glycogen production with time. The conformational change of the glycogen with time, revealed through its infrared spectral signature, was further confirmed by analysis of the force curves using a Freely Jointed Chain polymer model, which indicated an increase in glycogen contour length. The combination of these techniques provided the bulk and surface information of chemical composition at both the macroscale and molecular scale. These results demonstrate AFM-FS as a powerful technique to explore the recognition and force of lectin–carbohydrate interaction on both static substrates and cell surfaces in their native environments. 3.2.2. Other glycans on bacterial and plant cell surfaces AFM-FS is also suitable for the study of the specific recognition between proteins and polysaccharides on bacterial cell walls such as lipopolysaccharides (LPS) and peptidoglycans. Generally, the LPS covers the outer membrane of Gram-negative bacteria, while in Gram-positive bacteria, a thick layer of peptidoglycan constitutes the main body of the cell wall. These bacterial polysaccharides play crucial roles in various processes such as adhesion, infection and inflammation via biomolecular recognition (Beveridge and Graham, 1991; Costerto et al., 1974). Handa et al. measured the interactions between bacteriophage P22 tailspike proteins (TSPs) and O-antigenic LPS of the Gram-negative bacteria Salmonella typhimurium. AFM tips were modified with TSPs and an LPS bilayer deposited on a solid substrate by vesicle fusion (Handa et al., 2010). The results showed strong and multivalent binding of immobilized TSPs to supported LPS. A stable unbinding force under varying environmental conditions also demonstrated that phages are less sensitive to pH and temperature fluctuations. This makes them attractive candidates as immunosensors. In another report on Gram-positive bacteria, a Lysine Motif (LysM), a protein module that specifically binds peptidoglycan, was used to modify the AFM tip (Andre et al., 2010). Adhesion forces were then collected on living Lactococcus lactis cells. The force distribution showed a single peak at 71 ± 16pN, which reflected the rupture force of the specific LysM–peptidoglycan complex. The recorded high adhesion areas on adhesion force maps (Fig. 3f) correlated well with the corresponding features on topographic images (Fig. 3e), implying that the peptidoglycans were arranged as lines running parallel to the short cell axis. This study showed the AFM-FS based adhesion force


mapping as a valuable approach for understanding the architecture and assembly of specific biomolecules on cell surfaces. In recent cellulose research, both AFM imaging and force spectroscopy were performed to study the recognition between the carbohydrate-binding module (CBM3a) of a cellulolytic enzyme and the natural crystalline cellulose on the cell wall. First, using AFM non-contact imaging, CBM3a-modified gold nanoparticles were observed to bind with the cellulose on cell surface. In order to confirm the affinity of CBM3a and cellulose, a CBM3a-functionalized tip was used to map the plant cell wall surface using dynamic recognition imaging. CBM3a was observed to bind to the cellulose surface, closely aligning along the cellulose extension. AFM-FS was then used to measure the interaction forces between the cellulose and CBM3a. The unbinding force was measured to be 44.96 ± 18.80 pN at loading rate of 67.2 nN/s. This research provided a better understanding of biomass–enzyme interactions which is valuable for the design of high-efficiency cellulolytic enzymes (Zhang et al., 2012b). 4. Applications of cell-surface AFM-FS As shown above, AFM-FS has been widely applied to characterize diverse biomolecular recognition processes on cell surfaces owing to advantages of high force sensitivity and the ability to operate under different physiological conditions. Knowledge of these forces contribute to a better understanding of the molecular basis of molecular recognition events. Specifically, such data has direct implications in areas such as cancer research and drug screening. We discuss some examples of AFM-FS applications in these areas: 4.1. Probing cancer related biomarkers A significant application of interest is the prospect of probing cell surface biomarkers that relate to cancer etiology and progression. 4.1.1. Prostate specific membrane antigen (PSMA) PSMA is a possible therapeutic target expressed on the surface of prostate cancer cells (Chang et al., 1999; Israeli et al., 1994). Laidler et al. used AFM tips with anti-PSMA antibodies to detect PSMA on different types of prostate cancer cell surfaces. The specific recognition events showed the effect of estradiol and basic fibroblast growth factor in the expression of PSMA. The identical unbinding force values for different cell lines implied the antigenic similarity of the membrane form of PSMA (Laidler et al., 2005). 4.1.2. Tenascin-C The high expression of tenascin-C can be used as a tumor biomarker and target in glioblastoma diagnosis and therapy (Reardon et al., 2007; Yokoyama et al., 2000; Zagzag et al., 1995). Using a tenascin-C DNA aptamer modified AFM tip, the interaction forces between the aptamer and tenascin-C on living cells were measured at different loading rates. Several dynamic parameters acquired including the association rate constant, dissociation rate constant and dissociation constant provide a better understanding of the binding mechanisms of the aptamer to its ligand as well as potential diagnostic and therapeutic targets. The results also showed that the interactions depend on the presence of magnesium ions: The unbinding force did not change apparently while the binding probability increased in the presence of Mg2+ (Li et al., 2013b). 4.1.3. P-selectin P-selectin, which belongs to the family of selectin adhesion molecules, has been studied as a common therapeutic target for cardiovascular disorders, inflammation and tumor metastasis (Ludwig et al., 2007). Platelets protect tumor cells from the immune cells by their adhesion to the tumor cell (Borsig et al.,

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2001). P-selectin expressed on the activate platelets surface mediate tumor cells metastasis by their interactions with the ligands (CD44 variant isoforms, CD44v) on tumor cell surface (Hanley et al., 2006). P-selectin functionalized AFM tips were used to probe the interactions between P-selectin and CD44v incorporated into lipid vesicles. By comparing the interactions between fibrin and CD44v, P-selectin and CD44v showed higher tensile strength, which explains their better binding ability at elevated shear stresses. These studies provided biophysical insight into the shear-dependent receptor–ligand binding involved in cancer metastasis (Raman et al., 2011). 4.1.4. Glycans As discussed above, glycans on cell surfaces play important roles in various biological processes. Alterations in glycans have been demonstrated to be related to many diseases such as bacterial infections, inflammation and tumor metastasis (Dwek, 1996; Sharon and Lis, 2004). For instance, Lekka et al. studied the glycans expression on two human bladder cells (cancer and nonmalignant ones) with AFM-FS by using lectins as probes (Lekka et al., 2006). The results showed differences in glycan expression between cancer cells and the nonmalignant cells. Both the number of given glycan types (characterized by binding probability) and their structure (as characterized by unbinding force) were observed to be different in the two cell types. In particular, for the lectin from Phaseolus vulgaris, a much larger unbinding force indicated a distinct structure of the binding site in cancer cells. These results highlight the applicability of AFM for investigating alteration of the glycans during the cancer transformation. In another report, AFM-FS combined with fluorescence microscopy was utilized to characterize glycans on pathogenic and non-pathogenic yeast cell walls (El-Kirat-Chatel et al., 2013). Specific fluorescent-labeled lectins and antibodies were used to detect glycans on cell surfaces using fluorescence microscopy. Both AFM-FS and fluorescence results showed consistent differences in cell glycan properties including density, distribution, and extensions between pathogenic and nonpathogenic yeasts. 4.2. Drug design and detection of action mechanisms at the molecular scale 4.2.1. Antibiotics Vancomycin is a member of glycopeptide antibiotics in the treatment of methicillin resistant Staphylococcus aureus. It binds to the terminal d-alanyl-d-alanine moieties of peptidoglycan precursors with a high affinity and specificity, thus preventing the synthesis of bacterial cell wall (Nieto and Perkins, 1971; Walsh, 2000; Williams, 1996). The interaction forces between d-alanyl-d-alanine immobilized on mixed self-assembled monolayers and vancomycin modified on AFM tips were measured (Gilbert et al., 2007). The adhesion force histogram displayed a single maximum of 98 pN, which reflected a single rupture pair. A complementary adhesion force map obtained on a cell surface showed that the specific binding sites were mainly detected in the septum region, implying that the newly formed peptidoglycan was inserted in these regions. AFM-FS also provided a new opportunity to study antibiotic resistance by investigating the nanoscale effects of drugs on bacteria. Two kinds of P. aeruginosa, ATCC 27853 as the nondrug resistant strain, and PaR3 as a multi-drug resistant strain, were submitted to the antibiotics ticarcillin, tobramycin and paraguanidinoethylcalix[4]arene (CX1). Lectin-functionalized tips were used to detect specific carbohydrates on cell wall surface. PaR3 showed flat force curves after treatment with ticarcillin and tobramycin, while ATCC 27853 showed specific interactions, which implied the cell wall of PaR3was not disorganized by the two antibiotics and no molecules could be pulled out from the surface.

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Interestingly, both the PaR3 and ATCC 27853 after treatment with CX1 showed long distance pull-off forces, which could imply that CX1 disorganized the bacterial cell such that long glycans (lectin recognition molecules) were pulled off from the cell wall (Formosa et al., 2012). 4.2.2. Rituximab Rituximab is a monoclonal antibody against cluster of differentiation 20 (CD20) on most B cell lymphomas. By recognition with CD20 on a cell surface, rituximab is able to trigger lysis of the dysfunctional B cell, and thus treat the lymphomas (Cartron et al., 2004). Winiarksa et al. first measured the interactions of Rituximab attached on AFM tip and CD20 on Raji cell and lovastatin pre-treated Raji cell surfaces (Winiarska et al., 2008). The decreased unbinding force on the lovastatin pre-treated cell surface implied potential conformational changes of CD-20 induced by statins. Combined with other biochemical methods, this research showed statins could interfere with both the detection of CD20, as well as the anti-lymphoma activity of rituximab, which had significant clinical implications. Subsequently, Li et al. used rituximab modified AFM tips to measure the rupture force between rituximab and CD-20 on mica, obtaining a single pair force value of 121 pN (Li et al., 2011a). Then the forces were measured on Raji cells and lymphoma patient B cells, which showed ruptures of 89 pN and 126 pN respectively. This research provided essential biophysical data on the molecular interactions for the development of a monoclonal antibody drug. In recently reported research from the same group, fluorescence microscopy was used to differentiate cancer cells from normal cells by virtue of ROR1 fluorescence labeling on cancer cells, since ROR1 is a specific biomarker expressed on the cancer cells, but not on normal cells. Interaction forces of rituximab and CD20 on the surfaces of B cell lymphomas could then be measured with the guidance of fluorescence labeling. Here, the application of fluorescence microscopy as a complementary tool improved the efficiency and scope of data collection (Li et al., 2013a). 4.2.3. Design of a drug delivery system One strategy to achieve cancer cell targeting is by integrating a ligand moiety in a drug delivery system, capable of recognizing specific binding sites on the surfaces of cancer cells (Dharap et al., 2005). It had been found that the receptors for luteinizing hormonereleasing hormone (LHRH-R) are over-expressed in breast, ovarian, and prostate cancer cells (Dharap and Minko, 2003). LHRH can therefore be used as a target for drug delivery systems to release the drug to malignant cancer cells and reduce the concentration of toxic drug for normal cells. As a promising anticancer target drug, the LHRH-P. aeruginosa exotoxin 40 (LHRH-PE40) was constructed by the fusion of both LHRH and PE40 genes using genetic engineering in vitro. Via AFM-FS, the recognition force of LHRH-PE40/LHRH-R was compared with that of LHRH/LHRH-R. The results showed that the recombinant protein LHRH-PE40 preserves the LHRH moiety’s ability to bind to LHRH-Rs on a living cell surface, thereby validating its capability as a promising target drug (Zhang et al., 2012a). 4.3. Evaluating the effects of therapeutic agents at cell surfaces As discussed above, the ability of AFM-FS to probe biomolecular interactions in various liquid and cellular media, including the presence of drugs, provides a unique tool to evaluate the effect of therapeutic agents or exogenous substances on biomolecular interactions. A few interesting examples are discussed below: 4.3.1. Atorvastatin Inflammatory responses from vascular endothelial cells which involve monocyte adhesion to the vascular endothelial cells, play

an important role in the pathogenesis of atherosclerosis. Adhesion of monocytes to the endothelial cells occurs by means of the interactions between intercellular cell adhesion molecule-1 (ICAM1) on endothelial cells and integrin CD1b on monocytes (Hentzen et al., 2000; Libby, 2000). Atorvastatin, as a commonly used statin drug for atherosclerosis therapy, has been recently reported for its anti-inflammatory potential (Weitz-Schmidt, 2002). Using CD1b modified tips, the interaction forces of ICAM-1 and CD1b were measured on endothelial cells in the absence and presence of atorvastatin. The results showed atorvastatin did not inhibit binding of ICAM-1 to CD1b. Flow cytometry results indicated that atorvastatin decreased the expression of ICAM-1, which may contribute to its anti-inflammatory effects. The combination of AFM and flow cytometry here provided a new approach to study the mechanisms of drug action (Li et al., 2010). 4.3.2. Effects of cigarette smoke extract (CSE) As a vital anticoagulation cofactor, thrombomodulin (TM) located on the endothelial cell surface regulates intra-vascular coagulation by binding to thrombin. The effects of CSE on TMthrombin recognition were measured using AFM-FS (Wei et al., 2012). First, the unbinding forces of TM and thrombin were measured in vitro in the absence and presence of CSE by AFM-FS. The results showed that the unbinding force values were similar with and without CSE treatment, but CSE tended to reduce the binding probability. Unbinding forces measured on the living-cell surface showed that the CSE could reduce the binding probability of thrombin to its specific receptor TM. These results provided new insight into the understanding of thrombosis induced by smoking, and the potential of AFM-FS as a tool to study the effects of clinically relevant drugs and to screen candidates based on biomolecular recognition at the cell surface. 4.3.3. Trastuzumab and Pertuzumab HER2, as a member of the epidermal growth factor receptor family, is often over-expressed on several human tumor cells, especially breast cancer cells (Slamon et al., 1987). Trastuzumab and Pertuzumab are two monoclonal antibodies targeting different extracellular domains of HER2 for cancer therapy (Ross et al., 2009). By using AFM-FS on living cell surfaces, the effects of these two antibodies on HER2-modulated epidermal growth factor (EGF)epidermal growth factor receptor (EGFR) interactions were studied. The results demonstrated that the binding of EGF and EGFR was more stable on the cells co-expressing EGFR and HER2, and that this binding enhancement in the presence of HER2 was inhibited by either Trastuzumab or Pertuzumab. The research showed AFMFS offers a new approach to study the molecular mechanism of anti-cancer drugs at the cellular level (Zhang et al., 2013b). 5. Challenges and future directions The wide-ranging examples reviewed above show how AFMFS is a label-free, highly sensitive tool for the study of biomolecular recognitions on cell surfaces. We have confined our discussion here to the vitally important and emerging field of investigations on the surface of living cells. The unique capabilities of this modality include not only measuring interaction forces between cellularly relevant biomolecules, but also being able to directly map recognition sites on cell surfaces. Importantly, these measurements can be taken at physiological conditions and on live cells, which are significant for unraveling key biological and pathological questions from the nanoscale perspective of molecular mechanics. Changes in the extracellular environment can be directly probed for their effect on specific cell surface targets. However, there are still several challenges that need to be addressed for the broader application


of AFM-FS for cellular systems. The first is the complicated liquid environments of cell surface. It is often difficult to differentiate the nonspecific binding events from specific interactions owing to the multicomponent and soft cell surface. Several sets of control experiments therefore need to be conducted to confirm the specific interactions and improve the signal to noise ratio. The typical control experiments for instance, involve using different kinds of tips including bare tip and tips modified with non-specific molecules, or by directly adding free blocking agents in the liquid media during force measurement. A higher quality of sample preparation and equilibration of the system is also critical to improve the accuracy of data collection. Data interpretation is a crucial factor that will determine the results of the experiments (Muller and Dufrene, 2011; Muller et al., 2009). The current trend to automate collection and analysis of force-spectroscopy data has the ability to streamline this process. The second challenge lies in balancing requirements of time of data collection vs. spatial resolution, especially for adhesion force mapping. Higher spatial resolutions of force maps imply the collection of more force curves and therefore more time required to conduct the experiments. Given the highly dynamic nature of cells, this is poses an added technical challenge. Many biological processes may occur faster than the time required by AFM to collect force curves. During the long period of time of data collection, particularly in liquid environments, instruments undergo thermal drift, which result in the inaccuracies in the force maps obtained. This implies that both the spatial and time resolution should be taken into account for high quality of force map. The use of softer (lower spring constant) and sharper (lower radius of tips) tips will facilitate to detect smaller interaction forces and smaller recognition sites on cell surface, which cannot probed by conventional AFM tips (Viani et al., 1999). Finally, there is a good potential for combining AFM-FS with other analysis methods, such as fluorescence microscopy, surface plasmon resonance, quartz crystal microbalance and Raman spectroscopy (Wei and Latour, 2010; Yeo et al., 2009; Zhang and Yadavalli, 2011). These multifunctional techniques will provide more biophysical and biochemical information of biomolecular recognitions on cell surfaces. In the future, AFM-FS is expected to be increasingly applied in biomolecular research on cell surfaces, especially for molecular recognition related pathological process and specific biomarker on cancer cells. The quantitative characterization of biophysical information will contributes to the design and screening of drugs-modulating biomolecular recognition processes on cell surface. Overall, this tool is only beginning to scratch the surface of vast potential at and inside complex cellular environments. Acknowledgement The authors would like to thank Dr. Y.R. Sarma for valuable edits and critiques of the manuscript. References Albelda, S.M., Buck, C.A., 1990. Integrins and other cell-adhesion molecules. FASEB J. 4, 2868–2880. Almqvist, N., et al., 2004. Elasticity and adhesion force mapping reveals real-time clustering of growth factor receptors and associated changes in local cellular rheological properties. Biophys. J. 86, 1753–1762. Andersson, S., et al., 1988. Minimal-surfaces and structures – from inorganic and metal crystals to cell-membranes and bio-polymers. Chem. Rev. 88, 221–242. Andre, G., et al., 2010. Imaging the nanoscale organization of peptidoglycan in living Lactococcus lactis cells. Nat. Commun. 1, 1–8. Antonova, I., et al., 2001. Rapid increase in clusters of presynaptic proteins at onset of long-lasting potentiation. Science 294, 1547–1550. Aplin, A.E., et al., 1998. Signal transduction and signal modulation by cell adhesion receptors: the role of integrins, cadherins, immunoglobulin-cell adhesion molecules, and selectins. Pharmacol. Rev. 50, 197–263.

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Investigating cell mechanics with atomic force microscopy.

Filming biomolecular processes by high-speed atomic force microscopy.

Atomic force microscopy in biomaterials surface science.

Atomic species identification at the (101) anatase surface by simultaneous scanning tunnelling and atomic force microscopy.

Imaging and Force Recognition of Single Molecular Behaviors Using Atomic Force Microscopy.

Multiparametric imaging of adhesive nanodomains at the surface of Candida albicans by atomic force microscopy.

Mapping HA-tagged protein at the surface of living cells by atomic force microscopy.

Deep atomic force microscopy.

Hyphenating atomic force microscopy.

Surface microstructure of bitumen characterized by atomic force microscopy.

Uncovering by atomic force microscopy of an original circular structure at the yeast cell surface in response to heat shock.

Atomic force microscopy in microbiology: new structural and functional insights into the microbial cell surface.

An Unroofing Method to Observe the Cytoskeleton Directly at Molecular Resolution Using Atomic Force Microscopy.

Prior Surface Integrity Assessment of Coated and Uncoated Carbide Inserts Using Atomic Force Microscopy.

Noncontact atomic force microscopy III.

Noncontact atomic force microscopy II.

Nanorheology by atomic force microscopy.

Dynamic nano-triboelectrification using torsional resonance mode atomic force microscopy.

Nanoscale probing the kinetics of oriented bacterial cell growth using atomic force microscopy.

Generation of living cell arrays for atomic force microscopy studies.

Fundamental aspects of electric double layer force-distance measurements at liquid-solid interfaces using atomic force microscopy.

Nanoscale monitoring of drug actions on cell membrane using atomic force microscopy.

Atomic force microscopy study of enamel remineralization.

Imaging biological samples with atomic force microscopy.