Comprehensive Imaging of Sensory-Evoked Activity of Entire Neurons Within the Awake Developing Brain Using Ultrafast AOD-Based Random-Access Two-Photon Microscopy.

Determining how neurons transform synaptic input and encode information in action potential (AP) firing output is required for understanding dendritic integration, neural transforms and encoding. Limitations in the speed of imaging 3D volumes of brain encompassing complex dendritic arbors in vivo using conventional galvanometer mirror-based laser-scanning microscopy has hampered fully capturing fluorescent sensors of activity throughout an individual neuron's entire complement of synaptic inputs and somatic APs. To address this problem, we have developed a two-photon microscope that achieves high-speed scanning by employing inertia-free acousto-optic deflectors (AODs) for laser beam positioning, enabling random-access sampling of hundreds to thousands of points-of-interest restricted to a predetermined neuronal structure, avoiding wasted scanning of surrounding extracellular tissue. This system is capable of comprehensive imaging of the activity of single neurons within the intact and awake vertebrate brain. Here, we demonstrate imaging of tectal neurons within the brains of albino Xenopus laevis tadpoles labeled using single-cell electroporation for expression of a red space-filling fluorophore to determine dendritic arbor morphology, and either the calcium sensor jGCaMP7s or the glutamate sensor iGluSnFR as indicators of neural activity. Using discrete, point-of-interest scanning we achieve sampling rates of 3 Hz for saturation sampling of entire arbors at 2 µm resolution, 6 Hz for sequentially sampling 3 volumes encompassing the dendritic arbor and soma, and 200-250 Hz for scanning individual planes through the dendritic arbor. This system allows investigations of sensory-evoked information input-output relationships of neurons within the intact and awake brain.

RoboSCell: an automated single cell arraying and analysis instrument.

Single cell research has the potential to revolutionize experimental methods in biomedical sciences and contribute to clinical practices. Recent studies suggest analysis of single cells reveals novel features of intracellular processes, cell-to-cell interactions and cell structure. The methods of single cell analysis require mechanical resolution and accuracy that is not possible using conventional techniques. Robotic instruments and novel microdevices can achieve higher throughput and repeatability; however, the development of such instrumentation is a formidable task. A void exists in the state-of-the-art for automated analysis of single cells. With the increase in interest in single cell analyses in stem cell and cancer research the ability to facilitate higher throughput and repeatable procedures is necessary. In this paper, a high-throughput, single cell microarray-based robotic instrument, called the RoboSCell, is described. The proposed instrument employs a partially transparent single cell microarray (SCM) integrated with a robotic biomanipulator for in vitro analyses of live single cells trapped at the array sites. Cells, labeled with immunomagnetic particles, are captured at the array sites by channeling magnetic fields through encapsulated permalloy channels in the SCM. The RoboSCell is capable of systematically scanning the captured cells temporarily immobilized at the array sites and using optical methods to repeatedly measure extracellular and intracellular characteristics over time. The instrument's capabilities are demonstrated by arraying human T lymphocytes and measuring the uptake dynamics of calcein acetoxymethylester--all in a fully automated fashion.

Automating Event-detection of Brain Neuron Synaptic Activity and Action Potential Firing in vivo using a Random-access Multiphoton Laser Scanning Microscope for Real-time Analysis.

Determining how a neuron computes requires an understanding of the complex spatiotemporal relationship between its input (e.g. synaptic input as a result of external stimuli) and action potential output. Recent advances in in vivo, laser-scanning multiphoton technology, known as random-access microscopy (RAM), can capture this relationship by imaging fluorescent light, emitted from calcium-sensitive biosensors responding to synaptic and action potential firing in a neuron's full dendritic arbor and cell body. Ideally, a continuous output of fluorescent intensities from the neuron would be converted to a binary output (`event', 'or no-event'). These binary events can be used to correlate temporal and spatial associations between the input and output. However, neurons contain hundreds-to-thousands of synapses on the dendritic arbors generating an enormous quantity of data composed of physiological signals, which vary greatly in shape and size. Thus, automating data-processing tasks is essential to support high-throughput analysis for real-time/post-processing operations and to improve operators' comprehension of the data used to decipher neuron computations. Here, we describe an automated software algorithm to detect brain neuron events in real-time using an acousto-optic, multiphoton, laser scanning RAM developed in our laboratory. The fluorescent light intensities, from a genetically encoded, calcium biosensor (GCAMP 6m), are measured by our RAM system and are input to our 'event-detector', which converts them to a binary output meant for real-time applications. We evaluate three algorithms for this purpose: exponentially weighted moving average, cumulative sum, and template matching; present each algorithm's performance; and discuss user-feasibility of each. We validated our system in vivo, using the visual circuit of the Xenopus laevis.

Development of a real-time three-dimensional spinal motion measurement system for clinical practice.

This paper presents an inertial based sensing system for real-time three-dimensional measurement of human spinal motion, in a portable and non-invasive manner. Applications of the proposed system range from diagnosis of spine injury to postural monitoring, on-field as well as in the lab setting. The system is comprised of three inertial measurement sensors, respectively attached and calibrated to the head, torso and hips, based on the subject's anatomical planes. Sensor output is transformed into meaningful clinical parameters of rotation (twist), flexion-extension and lateral bending of each body segment, with respect to calibrated global reference space. Modeling the spine as a compound flexible pole model allows dynamic measurement of three-dimensional spine motion, which can be animated and monitored in real-time using our interactive GUI. The accuracy of the proposed sensing system has been verified with subject trials using a VICON optical motion measurement system. Experimental results indicate an error of less than 3.1 degrees in segment orientation tracking.

Localized, macromolecular transport for thin, adherent, single cells via an automated, single cell electroporation biomanipulator.

Single cell electroporation (SCE), via microcapillary, is an effective method for molecular, transmembrane transport used to gain insight on cell processes with minimal preparation. Although possessing great potential, SCE is difficult to execute and the technology spans broad fields within cell biology and engineering. The technical complexities, the focus and expertise demanded during manual operation, and the lack of an automated SCE platform limit the widespread use of this technique, thus the potential of SCE has not been realized. In this study, an automated biomanipulator for SCE is presented. Our system is capable of delivering molecules into the cytoplasm of extremely thin cellular features of adherent cells. The intent of the system is to abstract the technical challenges and exploit the accuracy and repeatability of automated instrumentation, leaving only the focus of the experimental design to the operator. Each sequence of SCE including cell and SCE site localization, tip-membrane contact detection, and SCE has been automated. Positions of low-contrast cells are localized and "SCE sites" for microcapillary tip placement are determined using machine vision. In addition, new milestones within automated cell manipulation have been achieved. The system described herein has the capability of automated SCE of "thin" cell features less than 10 µm in thickness. Finally, SCE events are anticipated using visual feedback, while monitoring fluorescing dye entering the cytoplasm of a cell. The execution is demonstrated by inserting a combination of a fluorescing dye and a reporter gene into NIH/3T3 fibroblast cells.

Machine vision-based localization of nucleic and cytoplasmic injection sites on low-contrast adherent cells.

Automated robotic bio-micromanipulation can improve the throughput and efficiency of single-cell experiments. Adherent cells, such as fibroblasts, include a wide range of mammalian cells and are usually very thin with highly irregular morphologies. Automated micromanipulation of these cells is a beneficial yet challenging task, where the machine vision sub-task is addressed in this article. The necessary but neglected problem of localizing injection sites on the nucleus and the cytoplasm is defined and a novel two-stage model-based algorithm is proposed. In Stage I, the gradient information associated with the nucleic regions is extracted and used in a mathematical morphology clustering framework to roughly localize the nucleus. Next, this preliminary segmentation information is used to estimate an ellipsoidal model for the nucleic region, which is then used as an attention window in a k-means clustering-based iterative search algorithm for fine localization of the nucleus and nucleic injection site (NIS). In Stage II, a geometrical model is built on each localized nucleus and employed in a new texture-based region-growing technique called Growing Circles Algorithm to localize the cytoplasmic injection site (CIS). The proposed algorithm has been tested on 405 images containing more than 1,000 NIH/3T3 fibroblast cells, and yielded the precision rates of 0.918, 0.943, and 0.866 for the NIS, CIS, and combined NIS-CIS localizations, respectively.

Development of an autonomous biological cell manipulator with single-cell electroporation and visual servoing capabilities.

Studies of single cells via microscopy and microinjection are a key component in research on gene functions, cancer, stem cells, and reproductive technology. As biomedical experiments become more complex, there is an urgent need to use robotic systems to improve cell manipulation and microinjection processes. Automation of these tasks using machine vision and visual servoing creates significant benefits for biomedical laboratories, including repeatability of experiments, higher throughput, and improved cell viability. This paper presents the development of a new 5-DOF robotic manipulator, designed for manipulating and microinjecting single cells. This biological cell manipulator (BCM) is capable of autonomous scanning of a cell culture followed by autonomous injection of cells using single-cell electroporation (SCE). SCE does not require piercing the cell membrane, thereby keeping the cell membrane fully intact. The BCM features high-precision 3-DOF translational and 2-DOF rotational motion, and a second z-axis allowing top-down placement of a micropipette tip onto the cell membrane for SCE. As a technical demonstration, the autonomous visual servoing and microinjection capabilities of the single-cell manipulator are experimentally shown using sea urchin eggs.