Automated Optical Tweezers Manipulation to Transfer Mitochondria from Fetal to Adult MSCs to Improve Antiaging Gene Expressions

Mitochondrial dysfunction is considered to be an important factor that leads to aging and premature aging diseases. Transferring mitochondria to cells is an emerging and promising technique for the therapy of mitochondrial deoxyribonucleic acid (mtDNA)-related diseases. This paper presents a unique method of controlling the quality and quantity of mitochondria transferred to single cells using an automated optical tweezer-based micromanipulation system. The proposed method can automatically, accurately, and efficiently collect and transport healthy mitochondria to cells, and the recipient cells then take up the mitochondria through endocytosis. The results of the study reveal the possibility of using mitochondria from fetal mesenchymal stem cells (fMSCs) as a potential source to reverse the aging-related phenotype and improve metabolic activities in adult mesenchymal stem cells (aMSCs). The results of the quantitative polymerase chain reaction analysis show that the transfer of isolated mitochondria from fMSCs to a single aMSC can significantly increase the antiaging and metabolic gene expression in the aMSC. The proposed mitochondrial transfer method can greatly promote precision medicine for cell therapy of mtDNA-related diseases.

Automated Embryo Manipulation and Rotation via Robotic nDEP-Tweezers

Embryo manipulation is a fundamental task in assisted reproductive technology (ART). Nevertheless, conventional pick-place techniques often require proper alignment to avoid causing damage to the embryo and further, the tools have limited capability to orient the embryo being handled.

OBJECTIVE

This paper presents a novel and non-invasive technique that can easily manipulate mouse embryos on a polyvinyl chloride (PVC) Petri dish.

METHODS

An inverted microchip with quadrupole electrodes was attached to a micromanipulator to become a robotic dielectrophoresis (DEP) tweezers, and a motorized platform provided additional mobility to the embryos lying on a Petri dish. Vision-based algorithms were developed to evaluate relevant information of the embryos from the image, and to provide feedback signals for precise position and orientation control of the embryo.

RESULTS

A series of experiments was conducted to examine the system performance, and the embryo can be successfully manipulated to a specified location with the desired orientation for subsequent processing.

CONCLUSION

This system offers a non-contact, low cost, and flexible method for rapid cell handling.

SIGNIFICANCE

As the DEP tweezers can grasp the embryo without the need for precise alignment, the overall time required to process a large number of embryos can be shortened.

Path planning in three dimensional live environment with randomly moving obstacles for viscoelastic bio-particle

Significant capabilities of atomic force microscopy (AFM) such as operating in various environments and scales made it a useful device in different operations. According to AFM abilities and applications, in this work, the path through the live environment with fixed and moving obstacles that are distributed all over the space randomly has been provided. The optimized path has been discovered in this article based on the applications mentioned above. Since for biological applications, the tool's accuracy plays an important role in success and reliability of the operation, in this article, the cost function is defined as combination of the tool's error, the maximum applied force on the tool, and the maximum deformation of the particle to be minimized. In this regard, constraints which limit the particle's motion and speed such as critical force and time and the maximum applied force have been considered. While in living environment obstacle existence is possible, fixed and moving obstacles with random profile and distribution will be considered. Routing of viscoelastic particle considering above conditions has been performed and comparison with the previous works proved the correctness of the path. The effects of different constraints have been compared using path optimization in different situations. The time of path planning for critical force and time was about 117.657, for the maximum applied force 118.240, and for all constraints together was 120.540 s which shows that the applied force constraint has been more effective than others and increases path planning time. Path planning in three dimensional live environment of HN5 cells. Consideration of viscoelasticity for biological particles. Consideration of randomly distributed stationary obstacles and moving obstacles with unknown motion profile. Minimization of tool error and particle deformation along with finding the shortest path.

Progress in Nanorobotics for Advancing Biomedicine

Nanorobotics, which has long been a fantasy in the realm of science fiction, is now a reality due to the considerable developments in diverse fields including chemistry, materials, physics, information and nanotechnology in the past decades. Not only different prototypes of nanorobots whose sizes are nanoscale are invented for various biomedical applications, but also robotic nanomanipulators which are able to handle nano-objects obtain substantial achievements for applications in biomedicine. The outstanding achievements in nanorobotics have significantly expanded the field of medical robotics and yielded novel insights into the underlying mechanisms guiding life activities, remarkably showing an emerging and promising way for advancing the diagnosis & treatment level in the coming era of personalized precision medicine. In this review, the recent advances in nanorobotics (nanorobots, nanorobotic manipulations) for biomedical applications are summarized from several facets (including molecular machines, nanomotors, DNA nanorobotics, and robotic nanomanipulators), and the future perspectives are also presented.

Path planning of the viscoelastic micro biological particle to minimize path length and particle's deformation using genetic algorithm

Manipulation of biological particles including pulling, and holding-and-indenting them, using the atomic force microscope (AFM) has attracted enormous interests. High deformability and vulnerability of biological particles, especially cells, make moving toward the target point inside complex biological environments with the least invasion the most critical factor. In this article, the optimal path of the particle movement is determined by considering the mechanical and morphological properties of the biological cell. Furthermore, the shortest path with the least amount of cell deformation is determined by using the equations of 3D manipulation of spherical viscoelastic particles and genetic algorithm (GA). Eventually, the final path is determined considering the mechanical properties of breast cancer cells by applying different constraints such as folding factor and the particle's roughness.Results reveal that increasing the number of constraints raise the needed time to find the optimal path. Additionally, the maximum time belongs to the spherical particle in the presence of folding. As a result, the total path planning times for the smooth, rough, and folded spherical particle are 59.386, 129.578, and 214.404 s, respectively. Various optimal pathfinders are used, to reduce calculations and speed up the process, as well as obtaining the correct answer with high certainty. Comparing the error files founded for three methods including cellular learning Automata, Dijkstra, and GA, the third method has the best performance in the lowest error rate. Using the GA, the error rate can be reduced by 40%, compared to the cellular learning Automata method. Furthermore, comparing the cellular learning Automata method used in previous studies, it can be seen that not only the results are correct, but also less time spent, at the practically identical situation, on finding the optimal path for this algorithm.

Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios

Developing a safe and efficient collision-avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generates its paths with limited observation of other robots’ states and intentions. Prior distributed multi-robot collision-avoidance systems often require frequent inter-robot communication or agent-level features to plan a local collision-free action, which is not robust and computationally prohibitive. In addition, the performance of these methods is not comparable with their centralized counterparts in practice. In this article, we present a decentralized sensor-level collision-avoidance policy for multi-robot systems, which shows promising results in practical applications. In particular, our policy directly maps raw sensor measurements to an agent’s steering commands in terms of the movement velocity. As a first step toward reducing the performance gap between decentralized and centralized methods, we present a multi-scenario multi-stage training framework to learn an optimal policy. The policy is trained over a large number of robots in rich, complex environments simultaneously using a policy-gradient-based reinforcement-learning algorithm. The learning algorithm is also integrated into a hybrid control framework to further improve the policy’s robustness and effectiveness. We validate the learned sensor-level collision-3avoidance policy in a variety of simulated and real-world scenarios with thorough performance evaluations for large-scale multi-robot systems. The generalization of the learned policy is verified in a set of unseen scenarios including the navigation of a group of heterogeneous robots and a large-scale scenario with 100 robots. Although the policy is trained using simulation data only, we have successfully deployed it on physical robots with shapes and dynamics characteristics that are different from the simulated agents, in order to demonstrate the controller’s robustness against the simulation-to-real modeling error. Finally, we show that the collision-avoidance policy learned from multi-robot navigation tasks provides an excellent solution for safe and effective autonomous navigation for a single robot working in a dense real human crowd. Our learned policy enables a robot to make effective progress in a crowd without getting stuck. More importantly, the policy has been successfully deployed on different types of physical robot platforms without tedious parameter tuning. Videos are available at https://sites.google.com/view/hybridmrca .

Translational and rotational manipulation of filamentous cells using optically driven microrobots

Optical cell manipulation has become increasingly valuable in cell-based assays. In this paper, we demonstrate the translational and rotational manipulation of filamentous cells using multiple cooperative microrobots automatically driven by holographic optical tweezers. The photodamage of the cells due to direct irradiation of the laser beam can be effectively avoided. The proposed method will enable fruitful biomedical applications where precise cell manipulation and less photodamage are required.

Modeling and Control of Single-Cell Migration Induced by a Chemoattractant-Loaded Microbead

Cell migration plays an essential role in cancer cell study. Investigation of a novel method for controlling cell migration movement can help develop new therapeutic strategies. In this paper, a chemoattractant-loaded microbead, which is controlled by optical tweezers, is used to stimulate a target cell to accomplish automated migration along a desired path while avoiding obstacles. Models of both tweezers-bead and bead-cell interactions are investigated. A dual closed-loop control strategy is proposed, which includes an inner tweezers-bead control loop and an outer bead-cell control loop. A proportional-integral feedback plus feedforward controller is used to control the inner loop, and an active disturbance rejection controller is used for the outer loop, which can address the cell migration modeling errors and unknown external disturbances. A traffic rule based on interference-clearing mechanism is also proposed to reduce external disturbances on the system by preventing other particles from interfering with the migration process. The effectiveness of the proposed control approach is verified by simulations and experiments on migrating leukemia cancer cells.

Manipulation of Biological Cells Using a Robot-Aided Optical Tweezers System

This article reviews the autonomous manipulation strategies of biological cells utilizing optical tweezers, mainly including optical direct and indirect manipulation strategies. The typical and latest achievements in the optical manipulation of cells are presented, and the existing challenges for autonomous optical manipulation of biological cells are also introduced. Moreover, the integrations of optical tweezers with other manipulation tools are presented, which broadens the applications of optical tweezers in the biomedical manipulation areas and will also foster new developments in cell-based physiology and pathology studies, such as cell migration, single cell surgery, and preimplantation genetic diagnosis (PGD).

Out-of-Plane Rotation Control of Biological Cells With a Robot-Tweezers Manipulation System for Orientation-Based Cell Surgery

In many cell surgery applications, cell must be oriented properly such that the microsurgery tool can access the target components with minimum damage to the cell. In this paper, a scheme for out of image plane orientation control of suspended biological cells using robotic controlled optical tweezers is presented for orientation-based cell surgery. Based on our previous work on planar cell rotation using optical tweezers, the dynamic model of cell out-of-plane orientation control is formulated by using the T-matrix approach. Vision-based algorithms are developed to extract the cell out of image plane orientation angles, based on 2-D image slices obtained under an optical microscope. A robust feedback controller is then proposed to achieve cell out-of-plane rotation. Experiments of automated out of image plane rotational control for cell nucleus extraction surgery are performed to demonstrate the effectiveness of the proposed approach. This approach advances robot-aided single cell manipulation and produces impactful benefits to cell surgery applications such as nucleus transplantation and organelle biopsy in precision medicine.

Remotely controlled fusion of selected vesicles and living cells: a key issue review

Remote control over fusion of single cells and vesicles has a great potential in biological and chemical research allowing both transfer of genetic material between cells and transfer of molecular content between vesicles. Membrane fusion is a critical process in biology that facilitates molecular transport and mixing of cellular cytoplasms with potential formation of hybrid cells. Cells precisely regulate internal membrane fusions with the aid of specialized fusion complexes that physically provide the energy necessary for mediating fusion. Physical factors like membrane curvature, tension and temperature, affect biological membrane fusion by lowering the associated energy barrier. This has inspired the development of physical approaches to harness the fusion process at a single cell level by using remotely controlled electromagnetic fields to trigger membrane fusion. Here, we critically review various approaches, based on lasers or electric pulses, to control fusion between individual cells or between individual lipid vesicles and discuss their potential and limitations for present and future applications within biochemistry, biology and soft matter.

A process engineering approach to increase organoid yield

Temporal manipulation of the in vitro environment and growth factors can direct differentiation of human pluripotent stem cells into organoids - aggregates with multiple tissue-specific cell types and three-dimensional structure mimicking native organs. A mechanistic understanding of early organoid formation is essential for improving the robustness of these methods, which is necessary prior to use in drug development and regenerative medicine. We investigated intestinal organoid emergence, focusing on measurable parameters of hindgut spheroids, the intermediate step between definitive endoderm and mature organoids. We found that 13% of spheroids were pre-organoids that matured into intestinal organoids. Spheroids varied by several structural parameters: cell number, diameter and morphology. Hypothesizing that diameter and the morphological feature of an inner mass were key parameters for spheroid maturation, we sorted spheroids using an automated micropipette aspiration and release system and monitored the cultures for organoid formation. We discovered that populations of spheroids with a diameter greater than 75 μm and an inner mass are enriched 1.5- and 3.8-fold for pre-organoids, respectively, thus providing rational guidelines towards establishing a robust protocol for high quality intestinal organoids.

A dynamic model of chemoattractant-induced cell migration

Cell migration refers to a directional cell movement in response to chemoattractant stimulation. In this work, we developed a cell-migration model by mimicking in vivo migration using optically manipulated chemoattractant-loaded microsources. The model facilitates a quantitative characterization of the relationship among the protrusion force, cell motility, and chemoattractant gradient for the first time (to our knowledge). We verified the correctness of the model using migrating leukemia cancer Jurkat cells. The results show that one can achieve the ideal migrating capacity by choosing the appropriate chemoattractant gradient and concentration at the leading edge of the cell.

Towards Independent Control of Multiple Magnetic Mobile Microrobots

In this paper, we have developed an approach for independent autonomous navigation of multiple microrobots under the influence of magnetic fields and validated it experimentally. We first developed a heuristics based planning algorithm for generating collision-free trajectories for the microrobots that are suitable to be executed by an available magnetic field. Second, we have modeled the dynamics of the microrobots to develop a controller for determining the forces that need to be generated for the navigation of the robots along the trajectories at a suitable control frequency. Next, an optimization routine is developed to determine the input currents to the electromagnetic coils that can generate the required forces for the navigation of the robots at the controller frequency. We then validated our approach by simulating an electromagnetic system that contains an array of sixty-four magnetic microcoils designed for generating local magnetic fields suitable for simultaneous independent actuation of multiple microrobots. Finally, we prototyped an m m -scale version of the system and present experimental results showing the validity of our approach.

Direct measurement of cell protrusion force utilizing a robot-aided cell manipulation system with optical tweezers for cell migration control

Cell migration refers to the directional cell movement in response to a chemoattractant gradient, a key process that occurs in a wide variety of biological phenomena. Cell protrusion force is generated by the actin polymerization of a cell, which drives the cell to move toward the stimulus as induced by the chemoattractant gradient. This paper presents a new methodology for the direct measurement of cell protrusion force utilizing a robot-aided optical tweezer system. The functionalized beads that are robotically trapped and placed near the cell serve as both cell migration stimulators and protrusion force probes. The force generated by the actin polymerization of the cell propels the bead to move away from the trapping center when the cell comes in contact with the bead. Such a deviation can be determined and used to calculate the trapping force, which is equal to the protrusion force at a balanced position. With the quantitative measurement of the protrusion, we find that the protrusion force of a live cell in response to a chemoattractant within the range of hundreds of piconewtons. We further probe the protrusion force distribution at the cell leading edge and find that the highest protrusion force appears at the cell migration direction. These measurements can help us characterize the mechanism of cell migration and lay a solid foundation for further proactive control of cell movement.

Indirect pushing based automated micromanipulation of biological cells using optical tweezers

In this paper, we introduce an indirect pushing based technique for automated micromanipulation of biological cells. In indirect pushing, an optically trapped glass bead pushes a freely diffusing intermediate bead that in turn pushes a freely diffusing target cell towards a desired goal. Some cells can undergo significant changes in their behaviors as a result of direct exposure to a laser beam. Indirect pushing eliminates this problem by minimizing the exposure of the cell to the laser beam. We report an automated feedback planning algorithm that combines three motion maneuvers, namely, push, align, and backup for micromanipulation of cells. We have developed a dynamics based simulation model of indirect pushing dynamics and also identified parameters of measurement noise using physical experiments. We present an optimization-based approach for automated tuning of planner parameters to enhance its robustness. Finally, we have tested the developed planner using our optical tweezers physical setup and carried out a detailed analysis of the experimental results. The developed approach can be utilized in biological experiments for studying collective cell migration by accurately arranging the cells in arrays without exposing them to a laser beam.

Micro-Assembly of a Vascular-Like Micro-Channel with Railed Micro-Robot Team-Coordinated Manipulation

The 3D assembly of cellular structures is important for the fabrication of biological substitutes in tissue engineering. In particular, a micro-channel with a 200 μm diameter is of interest because of its promising ability to construct the vascular network for oxygen and nutrition delivery in thick biological substitutes in the future. In this paper, a novel rail-guided micro-robot-team system is proposed for the micro-assembly of a cellular structure. The cellular two-dimensional (2D) component was fabricated by ultraviolet (UV) illumination of a cross-linkable hydrogel. The modular rail-guided micro-robotic system was set up with multi-micromanipulators as the modules and controlled with hybrid motors to achieve an operation resolution of 30 nm. To realize the bottom-up fabrication of the cellular micro-channel, different micro-assembly strategies with multi-manipulators were developed. The micro-assembly success rate and the efficiency of the different strategies were evaluated based on the assembly of micro-donuts. Through the novel, designed, concentric movement of the multi-manipulators along the rail, arbitrary change of the approaching angle and the coordination posture was achieved to improve the micro-assembly's flexibility. The operation range for every micromanipulator in different coordinated manipulation modes was analysed to avoid the breakdown of the assembled 3D structure. The image processing for the target location and end-effector identification was conducted to improve assembly efficiency in the micro-robot-team system. Finally, the assembly of the cellular vascular-like micro-channel was achieved with coordinated manipulation in the rail-guided micro-robot-team system.

Probing the mechanobiological properties of human embryonic stem cells in cardiac differentiation by optical tweezers

Human embryonic stem cells (hESC) and hESC-derived cardiomyocytes (hESC-CM) hold great promise for the treatment of cardiovascular diseases. However the mechanobiological properties of hESC and hESC-CM remains elusive. In this paper, we examined the dynamic and static micromechanical properties of hESC and hESC-CM, by manipulating via optical tweezers at the single-cell level. Theoretical approaches were developed to model the dynamic and static mechanical responses of cells during optical stretching. Our experiments showed that the mechanical stiffness of differentiated hESC-CM increased after cardiac differentiation. Such stiffening could associate with increasingly organized myofibrillar assembly that underlines the functional characteristics of hESC-CM. In summary, our findings lay the ground work for using hESC-CMs as models to study mechanical and contractile defects in heart diseases.