Micropipette Aspiration of Single Cells for Both Mechanical and Electrical Characterization

An AFM-Based Model-Fitting-Free Viscoelasticity Characterization Method for Accurate Grading of Primary Prostate Tumor

Viscoelasticity is a crucial property of cells, which plays an important role in label-free cell characterization. This paper reports a model-fitting-free viscoelasticity calculation method, correcting the effects of frequency, surface adhesion and liquid resistance on AFM force-distance (FD) curves. As demonstrated by quantifying the viscosity and elastic modulus of PC-3 cells, this method shows high self-consistency and little dependence on experimental parameters such as loading frequency, and loading mode (Force-volume vs. PeakForce Tapping). The rapid calculating speed of less than 1ms per curve without the need for a model fitting process is another advantage. Furthermore, this method was utilized to characterize the viscoelastic properties of primary clinical prostate cells from 38 patients. The results demonstrate that the reported characterization method a comparable performance with the Gleason Score system in grading prostate cancer cells, This method achieves a high average accuracy of 97.6% in distinguishing low-risk prostate tumors (BPH and GS6) from higher-risk (GS7-GS10) prostate tumors and a high average accuracy of 93.3% in distinguishing BPH from prostate cancer.

Viscoelastic Properties of Zona Pellucida of Oocytes Characterized by Transient Electrical Impedance Spectroscopy

The success rate in vitro fertilization is significantly linked to the quality of the oocytes. The oocyte's membrane is encapsulated by a shell of gelatinous extracellular matrix, called zona pellucida, which undergoes dynamic changes throughout the reproduction cycle. During the window of highest fertility, the zona pellucida exhibits a softening phase, while it remains rigid during oocyte maturation and again after fertilization. These variations in mechanical properties facilitate or inhibit sperm penetration. Since successful fertilization considerably depends on the state of the zona pellucida, monitoring of the hardening process of the zona pellucida is vital. In this study, we scrutinized two distinct genetic mouse models, namely, fetuin-B wild-type and fetuin-B/ovastacin double deficient with normal and super-soft zona pellucida, respectively. We evaluated the hardening with the help of a microfluidic aspiration-assisted electrical impedance spectroscopy system. An oocyte was trapped by a microhole connected to a microfluidic channel by applying suction pressure. Transient electrical impedance spectra were taken by microelectrodes surrounding the microhole. The time-depending recovery of zona pellucida deflections to equilibrium was used to calculate the Young's modulus and, for the first time, absolute viscosity values. The values were obtained by fitting the curves with an equivalent mechanical circuit consisting of a network of dashpots and springs. The observer-independent electrical readout in combination with a fitting algorithm for the calculation of the viscoelastic properties demonstrates a step toward a more user-friendly and easy-to-use tool for the characterizing and better understanding of the rheological properties of oocytes.

Mechanical Characterization and Modelling of Subcellular Components of Oocytes

The early steps of embryogenesis are controlled exclusively by the quality of oocyte that linked closely to its mechanical properties. The mechanical properties of an oocyte were commonly characterized by assuming it was homogeneous such that the result deviated significantly from the true fact that it was composed of subcellular components. In this work, we accessed and characterized the subcellular components of the oocytes and developed a layered high-fidelity finite element model for describing the viscoelastic responses of an oocyte under loading. The zona pellucida (ZP) and cytoplasm were isolated from an oocyte using an in-house robotic micromanipulation platform and placed on AFM to separately characterizing their mechanical profiling by analyzing the creep behavior with the force clamping technique. The spring and damping parameters of a Kelvin–Voigt model were derived by fitting the creeping curve to the model, which were used to define the shear relaxation modulus and relaxation time of ZP or cytoplasm in the ZP and cytoplasm model. In the micropipette aspiration experiment, the model was accurate sufficiently to deliver the time-varying aspiration depth of the oocytes under the step negative pressure of a micropipette. In the micropipette microinjection experiment, the model accurately described the intracellular strain introduced by the penetration. The developed oocyte FEM model has implications for further investigating the viscoelastic responses of the oocytes under different loading settings.

Octopus-Inspired Microgripper for Deformation-Controlled Biological Sample Manipulation

Predators in nature grip their prey in different ways, which give innovational ideas of gripping approaches in industrial applications. Octopus performs flexible gripping with the help of vacuum grippers, suction cups, which inspired a new type of microgripper for biological sample micromanipulation. The proposed gripper consists of a glass pipette and a pump driven by a step-motor. The step-motor is controlled with adaptive robust control to adjust the gripping pressure applied on the biological sample. A dynamic model is developed for the biological sample aiming for better deformation control performance. A visual detection algorithm is developed for data processing to identify the parameters in the dynamic model and the detection result of visual algorithm is also used as feedback of adaptive robust control, which diminishes the negative influence of parameter and model uncertainties. Zebrafish larva was used as the testing sample for experiment and the corresponding parameters were identified experimentally. The experimental results correlated well with the model predicted deformation curve and visual detection algorithm provided promising accuracy, which is less than [Formula: see text]. Adaptive robust control provides fast and accuracy response in point-to-point deformation testing, and the average responding time is less than 30 s and the average error is no larger than 1 pixel.

Automated Cell Mechanical Characterization by On-Chip Sequential Squeezing: From Static to Dynamic

The mechanical properties of cells are harmless biomarkers for cell identification and disease diagnosis. Although many systems have been developed to evaluate the static mechanical properties of cells for biomedical research, their robustness, effectiveness, and cost do not meet clinical requirements or the experiments with a large number of cell samples. In this paper, we propose an approach for on-chip cell mechanical characterization by analyzing the dynamic behavior of cells as they pass through multiple constrictions. The proposed serpentine microfluidic channel consisted of 20 constrictions connected in series and divided into five rows for tracking cell dynamic behavior. Assisted by computer vision, the squeezing time of each cell through five rows of constrictions was automatically collected and filtered to evaluate the cell's mechanical deformability. We observed a decreasing passage time and increasing dynamic deformability of the cells as they passed through the multiple constrictions. The deformability increase rate of the HeLa cells was eight times greater than that of MEF cells. Moreover, the weak correlation between the deformability increase rate and the cell size indicated that cell recognition based on measuring the deformability increase rate could hardly be affected by the cell size variation. These findings showed that the deformability increase rate of the cell under on-chip sequential squeezing as a new index has great potential in cancer cell recognition.

Single Cell Mass Spectrometry with a Robotic Micromanipulation System for Cell Metabolite Analysis

ObjectiveThe increasing demand for unraveling cellular heterogeneity has boosted single cell metabolomics studies. However, current analytical methods are usually labor-intensive and hampered by lack of accuracy and efficiency.

METHODS

we developed a first-ever automated single cell mass spectrometry system (named SCMS) that facilitated the metabolic profiling of single cells. In particular, extremely small droplets of sub nano-liter were generated to extract the single cells, and the underlying mechanism was verified theoretically and experimentally. This was crucial to minimize the dilution of the trace cellular contents and enhance the analytical sensitivity. Based on the precise 3D positioning of the pipette tip, we established a visual servoing robotic micromanipulation platform on which single cells were sequentially extracted, aspirated, and ionized, followed by the mass spectrometry analyses.

RESULTS

With the SCMS system, inter-operator variability was eliminated and working efficiency was improved. The performance of the SCMS system was validated by the experiments on bladder cancer cells. MS and MS2 analyses of single cells enable us to identify several cellular metabolites and the underlying inter-cell heterogeneity.

CONCLUSION

In contrast to traditional methods, the SCMS system functions without human intervention and realizes a robust single cell metabolic analysis.

SIGNIFICANCE

the SCMS system upgrades the way how single cell metabolites were analyzed, and has the potential to be a powerful tool for single cell metabolomics studies.

Robust Neurooptimal Control for a Robot via Adaptive Dynamic Programming

We aim at the optimization of the tracking control of a robot to improve the robustness, under the effect of unknown nonlinear perturbations. First, an auxiliary system is introduced, and optimal control of the auxiliary system can be seen as an approximate optimal control of the robot. Then, neural networks (NNs) are employed to approximate the solution of the Hamilton-Jacobi-Isaacs equation under the frame of adaptive dynamic programming. Next, based on the standard gradient attenuation algorithm and adaptive critic design, NNs are trained depending on the designed updating law with relaxing the requirement of initial stabilizing control. In light of the Lyapunov stability theory, all the error signals can be proved to be uniformly ultimately bounded. A series of simulation studies are carried out to show the effectiveness of the proposed control.

Non-invasive acquisition of mechanical properties of cells via passive microfluidic mechanisms: A review

The demand to understand the mechanical properties of cells from biomedical, bioengineering, and clinical diagnostic fields has given rise to a variety of research studies. In this context, how to use lab-on-a-chip devices to achieve accurate, high-throughput, and non-invasive acquisition of the mechanical properties of cells has become the focus of many studies. Accordingly, we present a comprehensive review of the development of the measurement of mechanical properties of cells using passive microfluidic mechanisms, including constriction channel-based, fluid-induced, and micropipette aspiration-based mechanisms. This review discusses how these mechanisms work to determine the mechanical properties of the cell as well as their advantages and disadvantages. A detailed discussion is also presented on a series of typical applications of these three mechanisms to measure the mechanical properties of cells. At the end of this article, the current challenges and future prospects of these mechanisms are demonstrated, which will help guide researchers who are interested to get into this area of research. Our conclusion is that these passive microfluidic mechanisms will offer more preferences for the development of lab-on-a-chip technologies and hold great potential for advancing biomedical and bioengineering research studies.

Robotic Label-Free Precise Oocyte Enucleation for Improving Developmental Competence of Cloned Embryos

OBJECTIVE

The invisibility of domestic oocyte nucleus in bright field currently forces operators to blindly aspirate nucleus out in oocyte enucleation, usually causing large cytoplasm losses and poor developmental competences of cloned embryos. Although fluorescent labeling of nucleus allows for nucleus localization, the involved photobleaching problems and barriers to the execution of enucleation process limit its online-application in oocyte enucleation. This paper reports a novel label-free oocyte enucleation method for precise removal of the nucleus with less cytoplasm loss.

METHODS

The relative positions between the injection pipette and nucleus for complete removal of nucleus with less cytoplasm loss were determined through a finite element modeling of nucleus aspiration. To position injection pipette to the above positions relative to nucleus, the appropriate oocyte orientation and trajectory of injection pipette inside oocyte were derived according to the offline-calibrated 3-D distribution of nucleus and the simulated dynamic drift of nucleus that occurs as injection pipette is maneuvered inside oocyte. Finally, a robotic label-free precise enucleation procedure was established.

RESULTS

The experimental results on more than 1000 porcine oocytes proved that this system is capable of reducing cytoplasm loss by 60% at the same level of enucleation success rate and almost doubling the cleavage rate of clone embryos in comparison to blind aspiration method.

CONCLUSIONS

The results prove that our method significantly improves the developmental competence of cloned embryos in comparison to manual enucleation method.

SIGNIFICANCE

Our method is expected to improve the extremely low success rate of animal cloning in the future.

An AFM-Based Nanomechanical Study of Ovarian Tissues with Pathological Conditions

BACKGROUND

Different diseases affect both mechanical and chemical features of the involved tissue, enhancing the symptoms.

METHODS

In this study, using atomic force microscopy, we mechanically characterized human ovarian tissues with four distinct pathological conditions: mucinous, serous, and mature teratoma tumors, and non-tumorous endometriosis. Mechanical elasticity profiles were quantified and the resultant data were categorized using K-means clustering method, as well as fuzzy C-means, to evaluate elastic moduli of cellular and non-cellular parts of diseased tissues and compare them among four disease conditions. Samples were stained by hematoxylin-eosin staining to further study the content of different locations of tissues.

RESULTS

Pathological state vastly influenced the mechanical properties of the ovarian tissues. Significant alterations among elastic moduli of both cellular and non-cellular parts were observed. Mature teratoma tumors commonly composed of multiple cell types and heterogeneous ECM structure showed the widest range of elasticity profile and the stiffest average elastic modulus of 14 kPa. Samples of serous tumors were the softest tissues with elastic modulus of only 400 Pa for the cellular part and 5 kPa for the ECM. Tissues of other two diseases were closer in mechanical properties as mucinous tumors were insignificantly stiffer than endometriosis in cellular part, 1300 Pa compared to 1000 Pa, with the ECM average elastic modulus of 8 kPa for both.

CONCLUSION

The higher incidence of carcinoma out of teratoma and serous tumors may be related to the intense alteration of mechanical features of the cellular and the ECM, serving as a potential risk factor which necessitates further investigation.

Simultaneously Quantifying Both Young's Modulus and Specific Membrane Capacitance of Bladder Cancer Cells with Different Metastatic Potential

Both Young's modulus and specific membrane capacitance (SMC) are two important physical parameters for characterizing cell status. In this paper, we utilized a thin-neck-micropipette aspiration system to simultaneously quantify Young's modulus and SMC value of six types of cell lines in different progression grades, which include four grades from the lowest metastatic potential G1 to the highest potential G4. We investigated how these two physical properties possess heterogeneities in bladder cancer cells with different grades and what roles they might play in grading bladder cancer. The characterization results of these cells of different cancer grades is linearly correlated with the cancer grades, showing that the Young's modulus is negatively linearly correlated with bladder cancer grades, while SMC shows a positive linear correlation. Furthermore, the combination of these two physical properties on a scatter diagram clearly shows the cell groups with different cancer grades, which means that this combination could be a potential tumor grading marker to identify cancer cells with different metastatic potential.

Robotic Micropipette Aspiration for Multiple Cells

As there are significant variations of cell elasticity among individual cells, measuring the elasticity of batch cells is required for obtaining statistical results of cell elasticity. At present, the micropipette aspiration (MA) technique is the most widely used cell elasticity measurement method. Due to a lack of effective cell storage and delivery methods, the existing manual and robotic MA methods are only capable of measuring a single cell at a time, making the MA of batch cells low efficiency. To address this problem, we developed a robotic MA system capable of storing multiple cells with a feeder micropipette (FM), picking up cells one-by-one to measure their elasticity with a measurement micropipette (MM). This system involved the following key techniques: Maximum permissible tilt angle of MM and FM determination, automated cell adhesion detection and cell adhesion break, and automated cell aspiration. The experimental results demonstrated that our system was able to continuously measure more than 20 cells with a manipulation speed quadrupled in comparison to existing methods. With the batch cell measurement ability, cell elasticity of pig ovum cultured in different environmental conditions was measured to find optimized culturing protocols for oocyte maturation.