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. Author manuscript; available in PMC: 2014 Oct 9.
Published in final edited form as: J Lab Autom. 2012 Sep 26;17(6):425–434. doi: 10.1177/2211068212460665

Cellular-Level Surgery Using Nano Robots

Bo Song 1, Ruiguo Yang 1, Ning Xi 1, Kevin Charles Patterson 2, Chengeng Qu 1, King Wai Chiu Lai 1
PMCID: PMC4190063  NIHMSID: NIHMS630627  PMID: 23015517

Abstract

The atomic force microscope (AFM) is a popular instrument for studying the nano world. AFM is naturally suitable for imaging living samples and measuring mechanical properties. In this article, we propose a new concept of an AFM-based nano robot that can be applied for cellular-level surgery on living samples. The nano robot has multiple functions of imaging, manipulation, characterizing mechanical properties, and tracking. In addition, the technique of tip functionalization allows the nano robot the ability for precisely delivering a drug locally. Therefore, the nano robot can be used for conducting complicated nano surgery on living samples, such as cells and bacteria. Moreover, to provide a user-friendly interface, the software in this nano robot provides a “videolized” visual feedback for monitoring the dynamic changes on the sample surface. Both the operation of nano surgery and observation of the surgery results can be simultaneously achieved. This nano robot can be easily integrated with extra modules that have the potential applications of characterizing other properties of samples such as local conductance and capacitance.

Keywords: AFM, nano robot, multifunctions, cellular-level surgery

Introduction

The biomedical world was revolutionized the recent advancement of technology, enabling diagnostics and treatment from the microscopic and even molecular level. Targeted imaging and drug delivery has introduced nanotechnology to medicine. The laboratory-level testing of therapeutic options requires instruments that can provide nanoscale imaging and operation. Being one of the centerpieces in nanotechnology, atomic force microscopy (AFM) is a suitable candidate for such needs as it could scan and manipulate matters at nanoscale, from which comes the term AFM nanorobotics. The nano robot used for cellular-level surgery is a special and useful technological device to sense the nano environment and to conduct local surgery on living samples. This nano surgery robot system is developed based on AFM. Because the AFM tip apex is approximately 20 nm or less and it can manipulate samples in nano scale, the sharp AFM tip could be considered the end effector of the nano robot. The nano robot concept first came with the augmented reality system developed by our lab for AFM-based nano manipulations.1 AFM has the advantages of high-resolution imaging2 and a vacuum-free working environment. In recent years, it played an increasingly important role in biomedical research.3,4 Not only can it provide high-resolution images in liquid,5 but it also can characterize mechanical properties such as Young’s modulus and surface roughness.6-8 Therefore, the AFM-based nano robot has the natural characteristics of nano scale imaging and measuring mechanical properties. In addition, if a functionalized tip is applied to the nano robot, it can stimulate the cell by means of direct molecular interaction and signaling.9,10

Both nano robots and conventional AFM can image and measure, but the significant advantage of the nano robot is that it can also manipulate the samples in nano scale. In the nano robot system, AFM tips have been employed as an end effector to manipulate and modify sample surfaces.11 Conducting surgery on living cells is possible because of the accurate position control of the nano robot. However, in most cases, nano surgery is a complicated process with complex issues arising from the process of surface cutting, local drug delivery, and dynamically monitoring the situation. All of these are significant challenges of AFM-based manipulations. For our nano robot, three main techniques have been applied to solve these challenges.

First, the augmented reality interface for the AFM-based nano robot system has solved the problem of nano robot positioning and motion control. With the help of this interface, it is very convenient for the operator to employ the joystick for controlling the nano robot’s movement during nano surgery. Second, various functionalized tips equip the nano robot with the function of local drug delivery. Finally, to obtain visual feedback of living samples during nano surgery, a real-time online monitoring system has been built for dynamically visualizing the surface changes during surgery. This approach focuses on scanning the surface locally where the nano surgery is simultaneously performed and updating the most recent image instead of either using the first image or reimaging the entire work surface. This is a new step for building a nano surgery system with visual feedback. To further increase the real-time monitoring update rate, two different methodologies were developed: online sensing and compressed scan strategies. The online sensing strategy has a cutting force calculation and detection module that uncovers the relationship between the cutting depth and force acting on the AFM tip. Then, an adaptive local scan approach is applied to obtain the realtime topography of the local cutting area.12 The advantage of this online sensing strategy is that the update frame rate is high enough for visualizing real-time operation. To obtain a high update rate, this technique sacrifices the updated local image quality. For some applications, updated images are very important for detailed information, and the compressed scan strategy is suitable for this condition. In a compressed scan, partial topography information is collected by randomly scanning instead of scanning the entire area.13,14 We developed this technique based on compressive sensing, which is known as an efficient way for signal sampling and reconstruction. Because the compressive sensing brings fewer measurements than conventional sampling, the local image can be updated at a high rate (1 frame per second with a 500 nm scan size).

The integration of these three main techniques endows the nano robot with the ability to conduct local surgery on samples both in air and liquid environments. It has many applications such as understanding the relationship of neighboring cells and the adaptations to stresses, each of which has a significant importance in disease and treatments.

Principles of Operation

In this section, the basic working principle of the nano robot system used for cellular-level surgery will be introduced. This nano robot is developed based on AFM. Besides imaging, the nano robot can also conduct surgery on live samples such as cells, characterize mechanical properties, and deliver drugs using a functionalized tip (as shown in Fig. 1). There are three key techniques that enable this nano robot with multifunctions: an augmented reality system, local drug delivery, and online real-time monitoring (as shown in Fig. 2).

Figure 1.

Figure 1

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Basic functions of the nano robot: manipulations, mechanical properties characterization, imaging, and drug delivery.

Figure 2.

Figure 2

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Multifunctional nano robot. The nano robot is equipped with functions of tip motion control, force feedback, functionalized tip, compressed scan, and properties characterization.

Augmented Reality System

The augmented reality system provides an interface for the operator to use a haptic system (joystick) to manipulate samples. By using the joystick, the user receives threedimensional (3-D) interaction forces. At the same time, the “videolized” AFM image will be refreshed in high frame rate (video rate), which enables the user to obtain the realtime sample surface changes of the nano environment. A model of tip-substrate-object has been developed to display the real-time changes, in which the tip is contacting the substrate surface during nano surgery.

The augmented reality system is designed to provide the user with actual tip position control, real-time videolized visual display, and force feedback during nano surgery. The videolized real-time visual display is a dynamic AFM video (images) of the operating environment, which is updated by online monitoring.

The positioning precision is one of the most critical issues that requires consideration in nano surgery. Two significant factors cause position errors. The first factor that could cause position error is the thermal drift, which is the actuator output drift caused by temperature change. If the manipulation environment is not well controlled, the thermal drift is not stable, and the tip may be several hundred nanometers away from our observation area. The position error caused by thermal drift can be compensated by using a local scan mechanism. The basic idea for the local scan mechanism is that before starting the manipulation, the real position of the object can be obtained by a quick local scan around the object. The position error due to the thermal drift can be fixed by an operation right after the local scan. The detailed information can be found in the work by Liu et al.15 The bending of the cantilever is another factor affecting the positioning precision. It causes a lateral displacement along the length direction of the cantilever. An active cantilever that can control the stiffness of the probe and a position compensation algorithm can be used to minimize this effect.16

Functionalizing the Tip for Local Drug Delivery

Attaching antibody or ligands onto the AFM tip could extensively enhance the capability of AFM for the study of specific molecular interactions, i.e., binding events or molecular recognition. Specifically, the reagents on the AFM tip could be used to study localized effects of these chemicals through the so-called in vitro local drug delivery, where the chemicals on the AFM tip could be directed through the lateral motion to a selected site(s) on the cell and delivered locally. There are varieties of ways to functionalize the AFM tip with chemical species. The easiest method is by dipping the cantilever into the chemical solution. The direct link suffers a low binding affinity and probability. The most common method that has been routinely used by researchers worldwide introduces a spacer or linker molecule in between the AFM tip and the molecule of interest. It will enhance the link capability and provide a higher degree of spatial specificity. The general strategy of spacerbased functionalization is to create a covalent bond between the chemical and the spacer.17 The most common linker is polyethylene glycol (PEG). The PEG linker is first attached to the NH2 group on the AFM group, and the other end will be subsequently linked to the antibody of interest. The protocol could be described in the following steps in detail.

  1. Create the NH2 group on the AFM tip using aminopropyltriethoxysilane (ATPES) modification. (1) The silicon nitride AFM cantilever is placed under ultraviolet (UV) light for 15 min. (2) Purge argon gas into a desiccator for 5 min, place 10 mL of APTES into a petri dish inside the desiccator, put another petri dish into the desiccator with 5 mL of N, N-diisopropylethylamine. (3) Continue to purge the desiccators with argon gas for 5 min, place the UV-cleaned cantilever in, and the seal the desiccators for 2 h. (4) Remove the two chemicals and keep the argon gas to maintain a nonreactive environment for the probe with the NH2 group.

  2. Link the spacer onto the NH2 group. (1) Dilute the NHS-PEG-MAL with approximately 2000 molecular weight in 5 mL of chloroform with 1 mL of triethylamine. (2) Dip the tip end of the NH2-modified AFM cantilever into the linker solution for 2 h.

  3. Modify the antibody with SATP. (1) Wash the PD-10 column with 30 mL of buffer A (100 mM NaCl, 50 mM NaH2PO4, 1 mM of EDTA, pH 7.5). (2) Take 20 μL of antibody solution and dilute it into 180 μL of phosphate-buffered saline (PBS), add the solution (200 μL) into 300 μL buffer A. (3) Filter the solution 9 times. Take 0.3 mL of DMSO into a 1.5 mL vial. Dissolve 0.5 mg of SATP into 0.3 mL DMSO. (4) Take 2 μL of the SATP solution and dilute it into the filtered antibody solution.

  4. Link the SATP antibody onto the cantilever. (1) Lower the probe into (50 μL of SATP-antibody solution + 25 μL of NH2OH [500 mM] + NH2OH. HCl [25 mM] + EDTA, pH 7.4) + 50 μL of buffer A, and incubate in room temperature for 1 h. (2) Rinse the probe with buffer A and PBS.

Online Monitoring for Nano Surgery

As described in the augmented reality system section, videolized nano surgery is necessary for accurate operation. To update each frame in videolized nano surgery, online monitoring is applied to this system. In this section, an example of online monitoring about cells cutting and monitoring is introduced to illuminate the basic idea of online monitoring. Online monitoring includes several steps, as Figure 3 shows. First, a force detection module is used for calculating the force applied by the AFM tip. This module determines whether the tip has cut through the sample surface or not. Once the tip of the nano robot has cut through the sample surface, the tip motion planner starts to work. This is because at the moment the sample surface starts to be modified, the system needs visual feedback to update the online real-time video. In this step, the motion planner calculates the scan trajectory, which is based on the original AFM image. The scan direction and range are also determined by the motion planner. As the default setting, the scan range is a quarter of the original image size (for example, if the original image is 1 × 1 μm2, the scan range for image updating is 0.25 × 0.25 μm2). The scan direction is 0°. In addition, these parameters could be manually adjusted according to the needs of various nano surgeries.

Figure 3.

Figure 3

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Scheme of online monitoring.

Note that although conventional AFM has the imaging function, the imaging speed is too slow to dynamically capture surface change. Typically, conventional AFM needs several minutes to obtain an image, whereas our online sensing strategy can update surface change as fast as one frame per second. This is very helpful for conducting nano surgery with real-time visual feedback.

The topography information is collected by compressed scan, and then the partial topography information will be transferred into the display module, which reconstructs the local image. With this local image, it is easy to observe the nano surgery results. In addition, the motion planner would control where and when the next compressed scan is performed.13 The compressive scan is a fast imaging strategy that uses compressive sensing to sample fewer data and then reconstruct the original image. It would ensure that the dynamic changes occurring during nano surgery are well captured. Finally, the updated images will be displayed as the online monitoring video.

One thing to be noted about the compressed scan is that it is used to scan partially the area where nano surgery operated. The goal of applying the compressed scan is to increase the imaging speed to obtain the video rate imaging. This technique is developed based on compressive sensing. Introducing compressive sensing into the nano robot system is a convenient and efficient way for reducing time spent on scanning. The goal is to decrease the scan trajectory, which samples fewer than conventional measurements. Typically, the imaging speed for a compressed scan is eight times faster than conventional raster scanning. For example, if the scan size is 500 × 500 nm2, the imaging speed of the compressed scan could reach as fast as one frame per second. After the partial information has been collected, the image could be well reconstructed by an image recovery algorithm. We have published some articles to describe the details about how to apply the compressive sensing into AFM-based nano robot imaging.13,14

Nano Robot Instrumentation Description

Hardware

The hardware setup of the nano surgery system is shown in Figure 4. The main platform is an AFM system called Bioscope (Veeco Instruments [now Bruker-nano], Santa Barbara, CA), which is equipped with a scanner possessing a maximum scan range of x-90 μm, y-90 μm, and z-5 μm. There are several peripheral devices, such as an optical microscope, a charge-coupled device (CCD) camera, and a signal access module. The signal access module has the ability to access real-time signals inside the AFM system. The inverted optical microscope and the CCD camera work together to help the user position the tip and coarsely locate areas of interest. A haptic device (joystick; Phantom, Sensable Company, Woburn, MA) is added to the augmented reality interface.

Figure 4.

Figure 4

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Hardware architecture of the nano robot system.

In addition, we also developed a module named signal access control box, and this is used for adding control voltage into the AFM controller as well as for reading out the signal from each sensor inside the scanner. A computer with the Realtime-Linux (RT-Linux) system controls the motion of the nano robot and simultaneously records the topography information from “Height, Phase and Amplitude” channels.

Software

The software of this nano robot consists of four components: the nano robot system and three subsystems—a fast imaging system, a mechanical properties measurement system, and an object tracking system. Each of these four components has its own function but could work together for a complicated nano surgery (as shown in Fig. 5).

Figure 5.

Figure 5

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A simplified view of the components of the nano robot software system.

Robot software

The robot software is the most basic and fundamental piece for all nano robot–based manipulations. This component connects the AFM, RT-Linux, haptic device, and signal access control box together. Therefore, this software can obtain the AFM image from conventional AFM software, obtain the real-time position feedback from the joystick, send tip-moving commands to RT-Linux, and collect all the feedback signals from all sensors. Once this software is prepared, the operator can use it to control the 3-D movement of the nano robot to manipulate the samples with functions such as pushing and cutting; each of these is a basic operation required for nano surgery.

Fast imaging software and mechanical properties characterization system

As mentioned in previous sections, the visual feedback (online monitoring) is very helpful for the operator while the nano surgery is ongoing. The fast imaging software is used for increasing the imaging speed and obtaining the topography information. This software is run on an RT-Linux computer. Once it receives a trigger command from the robot software, the fast imaging software starts to work. The basic working principle of this software is that it first generates a random trajectory for scanning and then samples the topography information along this trajectory. After all the data have been collected, this software automatically calls an image reconstruction function and recovers the local image. Once the image has been fully recovered, it will send the image to the nano robot software. In the user interface of the nano robot software, the real-time monitoring video (images) is updated by the fast imaging software.

As the name implies, the mechanical properties characterization component is a convenient tool for real-time characterization of the sample’s mechanical properties. This is especially useful for studying the mechanical behavior of biomedical samples. In this function, the nano robot will touch the sample surface lightly to measure properties such as stiffness and viscosity. This information will be sent to the robot software user interface after the measurements are completed. The fast imaging software can be integrated with the mechanical properties measurement component, and both of them can work together to simultaneously conduct imaging and measuring.

Object tracking system

Both the end-to-end and arbitrary trajectory tracking functions are provided for advanced applications of the nano robot. The users can either use an object identify function to automatically recognize the outline of samples or use the joystick to draw their own tracking trajectory. The tracking trajectory is recorded by the software, and a nonvector space controller is used to control the movement of the nano robot for tracking the special trajectory or particles. Detailed information about the nonvector space controller can be found in the work of Song et al.18 This software is used for studying the local properties of samples such as the locally sequencing DNA.

Examples for multisoftware collaboration for nano surgery

To elaborate on the process of how these components work on a given project, here is an example for using the nano robot to conduct nano surgery on living cells. First, the AFM scans the entire area of interest, and the nano robot software is used to load this image. The next step is using the joystick to move the nano robot to the area of interest and to begin cutting the surface of a single cell. Then, the fast imaging software starts monitoring the dynamic changes of that area automatically. The real-time monitoring video is updated in the user interface. Once the cutting step is finished, the mechanical properties characterization component starts to measure and collect the data for local mechanical properties. In addition, the functionalized tip could be involved in this nano surgery at any time to locally deliver a drug to the area. The user could both operate the nano robot as well as observe the surface change and mechanical properties indicators dynamically during the surgery. The software flow chart is shown in Figure 6.

Figure 6.

Figure 6

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Software flowchart of multisoftware collaboration for nano surgery.

Applications

EGF Stimulation and Its Effect on A431 Cells

Epidermal growth factor (EGF) is a ligand for the epidermal growth factor receptor, which is a cell surface receptor possessing an intrinsic tyrosine kinase activity.19 Its activation by EGF can trigger a variety of signaling events. The activation process itself is time, dose, and context dependent. Different activation mechanisms can either stimulate or inhibit cell cycle progression, resulting in cell proliferation or cell apoptosis. The A431 human epidermoid carcinoma cell line has been widely used as a model for the study of signaling events after the interaction of EGF with its specific cell surface receptors.20

The EGF-stimulated A431 cells behave differently from normal cells, showing significant rounding, swelling, and stiffening after the loss of focal adhesion.21 This is believed to be the effect of cytoskeleton reconfiguration after EGF-related signaling events.22 The cellular response to the stimulation, either proliferation or apoptosis, can be significantly manifested in cell morphology and cellular mechanics change. Hence, dynamic morphological appearance and mechanical properties have been regarded as biomarkers, sometimes even regulators, of the signaling and physiological processes. To characterize those properties in real time requires special instrumentation and techniques. We previously reported that the nano robot could characterize the fine nanomechanical property changes after the EGF-induced cell structural change.9 The cell will exhibit an increase in stiffness while the energy dissipation measurement by quartz crystal microbalance with dissipation monitoring shows a decrease.

Signal Propagation through Neighboring Cells

Upon EGF stimulation, the local stimulation signal could be propagated to neighboring cells.23 Thus, we sought to deliver the EGF stimulation effect locally to an individual cell. Using an AFM tip functionalized with EGF (protocols described in the previous section), we can target the AFM tip onto individual cells or even a specific cluster of EGF receptors. Once the individual cell is stimulated, the signaling pathway inside the cell will be triggered. Ultimately, the signal will be passed on to the cells that are in close contact with the stimulated cell through the various cell-based junctions: tight junctions, gap junctions, or even adherens junctions. The stimulation signal passed through the physical contacts will therefore be relayed to neighboring cells. Thus, the neighboring cells will similarly experience the structural reorganization as well as mechanical property changes, and these changes can be picked up by the nano robot–based nanomechanical analysis (as shown in Fig. 7).

Figure 7.

Figure 7

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Nano surgery for cell signaling pathway investigation.

Mechanically Cutting the Cellular Connection to Disrupt the Signal Propagation

It is logical to contemplate what would happen if those physical connections were to be interrupted between the individual stimulated cell and its neighbors. With the nano robot-based cellular surgery system, we can test a lot of possible hypotheses raised by biological demands. The EGF molecules will first be delivered to a specific cell, and then the nanodissection is employed to sever the intercellular junctions with different cutting strategies: half the depth, full depth, half the circumference, and the full circumference of the cell. For different surgery strategies, the readout from the nano robot mechanical characterizations of neighboring cells will be compared and analyzed.

For the depth detection, we will use the force-distance curve to penetrate the cells until the tip touches the glass slides where the cell rests; this gives us an idea about the height of the cell. Using this, the dissection depth can be controlled during cell surgery. The lateral size/circumference of the cut can also be controlled precisely with the joystick-based control interface. With these strategies, not only do we learn the pattern of signal propagation through neighboring cells but also which type of junction structure is essential in the communication process. Beyond the application described above, there are more potential applications on nano manipulations as the interdisciplinary research advances (as shown in Table 1). It could also be used to delivery transfection reagents into the cell with property tip selections. It may also direct the dissection of cellular cytoskeleton components to test their property and their effects on the whole cell structure as to mimic disease conditions.

Table 1.

Applications of Nano Robot System

Application Example Potential Users
Cellular-level surgery Signaling pathway identification Labs, hospital
Food safety Escherichia coli and other bacteria detection U.S. Department of Agriculture
Medicinal therapeutic investigation Antibody screening Pharmaceutical manufacturers
Nano fabrications Nano sensors, nano actuator nano processor Labs, industry
Properties characterization Characterizes conductivity
Electric field gradient distribution
Characterizes capacitance
Thermal characterization		 Labs, industry
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Conclusions

In this article, we demonstrated that the nano robot can be applied for cellular-level surgery on living samples. The nano robot is capable of imaging, manipulation, mechanical properties measuring, and tracking. With the use of a functionalization tip, the nano robot can also locally deliver a drug. All of these characteristics give the nano robot the ability to conduct complicated nano surgery on living samples such as cells and bacteria. Moreover, to provide a user-friendly interface, the software in this nano robot provides a videolized visual feedback for monitoring the dynamic changes on the sample surface. The user can conduct nano surgery as well as simultaneous observe the surgery results. This instrumentation would enable biological-oriented studies by providing reliable surgery capabilities at the cellular level. Combined with the in vitro drug delivery utility, the nano robot system can further facilitate the drug screen process at the single-cell level.

Acknowledgments

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research work is partially supported under NSF grant IIS 0713346, ONR grant N00014-07-1-0935, ONR grant N00014-04-1-0799, and NIH grant R43 GM084520.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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