Archetypal Analysis for neuronal clique detection in low-rate calcium fluorescence imaging.

Archetypal analysis (AA) is a versatile data analysis method to cluster distinct features within a data set. Here, we demonstrate a framework showing the power of AA to spatio-temporally resolve events in calcium imaging, an imaging modality commonly used in neurobiology and neuroscience to capture neuronal communication patterns. After validation of our AA-based approach on synthetic data sets, we were able to characterize neuronal communication patterns in recorded calcium waves. Clinical relevance- Transient calcium events play an essential role in brain cell communication, growth, and network formation, as well as in neurodegeneration. To reliably interpret calcium events from personalized medicine data, where patterns may differ from patient to patient, appropriate image processing and signal analysis methods need to be developed for optimal network characterization.

A kinetic-optimized CoChR variant with enhanced high-frequency spiking fidelity.

Channelrhodopsins are a promising toolset for noninvasive optical manipulation of genetically identifiable neuron populations. Existing channelrhodopsins have generally suffered from a trade-off between two desired properties: fast channel kinetics and large photocurrent. Such a trade-off hinders spatiotemporally precise optogenetic activation during both one-photon and two-photon photostimulation. Furthermore, the simultaneous use of spectrally separated genetically encoded indicators and channelrhodopsins has generally suffered from non-negligible crosstalk in photocurrent or fluorescence. These limitations have hindered crosstalk-free dual-channel experiments needed to establish relationships between multiple neural populations. Recent large-scale transcriptome sequencing revealed one potent optogenetic actuator, the channelrhodopsin from species Chloromonas oogama (CoChR), which possessed high cyan light-driven photocurrent but slow channel kinetics. We rationally designed and engineered a kinetic-optimized CoChR variant that was faster than native CoChR while maintaining large photocurrent amplitude. When expressed in cultured hippocampal pyramidal neurons, our CoChR variant improved high-frequency spiking fidelity under one-photon illumination. Our CoChR variant's blue-shifted excitation spectrum enabled simultaneous cyan photostimulation and red calcium imaging with negligible photocurrent crosstalk.

Engineering rhodopsins' activation spectra using a FRET-based approach.

In the past decade, optogenetics has become a nearly ubiquitous tool in neuroscience because it enables researchers to manipulate neural activity with high temporal resolution and genetic specificity. Rational engineering of optogenetic tools has produced channelrhodopsins with a wide range of kinetics and photocurrent magnitude. Genome mining for previously unidentified species of rhodopsin has uncovered optogenetic tools with diverse spectral sensitivities. However, rational engineering of a rhodopsin has thus far been unable to re-engineer spectral sensitivity while preserving full photocurrent. Here, we developed and characterized ChroME-mTFP, a rhodopsin-fluorescent protein fusion that drives photocurrent through Förster resonance energy transfer (FRET). This FRET-opsin mechanism artificially broadened the activation spectrum of the blue-green-light-activated rhodopsin ChroME by approximately 50 nm, driving higher photocurrent at blue-shifted excitation wavelengths without sacrificing kinetics. The excitation spectra's increase at short wavelengths enabled us to optogenetically excite neurons at lower excitation powers with shorter wavelengths of light. Increasing this rhodopsin's sensitivity to shorter, bluer wavelengths pushes it toward dual-channel, crosstalk-free optogenetic stimulation and imaging with green-light-activated sensors. However, this iteration of FRET-opsin suffers from some imaging-light-induced photocurrent crosstalk from green or yellow light due to maintained, low-efficiency excitation at longer wavelengths.

Genetically Encoded Fluorescent Indicators for Imaging Brain Chemistry.

Genetically encoded fluorescent indicators, combined with optical imaging, enable the detection of physiologically or behaviorally relevant neural activity with high spatiotemporal resolution. Recent developments in protein engineering and screening strategies have improved the dynamic range, kinetics, and spectral properties of genetically encoded fluorescence indicators of brain chemistry. Such indicators have detected neurotransmitter and calcium dynamics with high signal-to-noise ratio at multiple temporal and spatial scales in vitro and in vivo. This review summarizes the current trends in these genetically encoded fluorescent indicators of neurotransmitters and calcium, focusing on their key metrics and in vivo applications.

Multi-curvature micropatterns unveil distinct calcium and mitochondrial dynamics in neuronal networks.

Tangential curvatures are a key geometric feature of tissue folds in the human cerebral cortex. In the brain, these smoother and firmer bends are called gyri and sulci and form distinctive curved tissue patterns imposing a mechanical stimulus on neuronal networks. This stimulus is hypothesized to be essential for proper brain cell function but lacks in most standard neuronal cell assays. A variety of soft lithographic micropatterning techniques can be used to integrate round geometries in cell assays. Most microfabricated patterns, however, focus only on a small set of defined curvatures. In contrast, curvatures in the brain span a wide physical range, leaving it unknown which precise role distinct curvatures may play on neuronal cell signaling. Here we report a hydrogel-based multi-curvature design consisting of over twenty bands of distinct parallel curvature ranges to precisely engineer neuronal networks' growth and signaling under patterns of arcs. Monitoring calcium and mitochondrial dynamics in primary rodent neurons grown over two weeks in the multi-curvature patterns, we found that static calcium signaling was locally attenuated under higher curvatures (k > 0.01 µm-1). In contrast, to randomize growth, transient calcium signaling showed higher synchronicity when neurons formed networks in confined multi-curvature patterns. Additionally, we found that mitochondria showed lower motility under high curvatures (k > 0.01 µm-1) than under lower curvatures (k < 0.01 µm-1). Our results demonstrate how sensitive neuronal cell function may be linked and controlled through specific curved geometric features. Furthermore, the hydrogel-based multi-curvature design possesses high compatibility with various surfaces, allowing a flexible integration of geometric features into next-generation neuro devices, cell assays, tissue engineering, and implants.

Faradaic electrochemical impedance spectroscopy for enhanced analyte detection in diagnostics.

Electrochemical impedance spectroscopy (EIS) is a widely implementable technique that can be applied to many fields, ranging from disease detection to environmental monitoring. EIS as a biosensing tool allows detection of a broad range of target analytes in point-of-care (POC) and continuous applications. The technique is highly suitable for multimarker detection due to its ability to produce specific frequency responses depending on the target analyte and molecular recognition element (MRE) combination. EIS biosensor development has shown promising results for the medical industry in terms of diagnosis and prognosis for various biomarkers. EIS sensors offer a cost-efficient system and rapid detection times using minimal amounts of sample volumes, while simultaneously not disturbing the sample being studied due to low amplitude perturbations. These properties make the technique highly sensitive and specific. This paper presents a review of EIS biosensing advancements and introduces different detection techniques and MREs. Additionally, EIS's underlying theory and potential surface modification techniques are presented to further demonstrate the technique's ability to produce stable, specific, and sensitive biosensors.

A Viral Toolbox of Genetically Encoded Fluorescent Synaptic Tags.

Fibronectin intrabodies generated with mRNA display (FingRs) are a recently developed tool for labeling excitatory or inhibitory synapses, with the benefit of not altering endogenous synaptic protein expression levels or synaptic transmission. Here, we generated a viral vector FingR toolbox that allows for multi-color, neuron-type-specific labeling of excitatory or inhibitory synapses in multiple brain regions. We screened various fluorophores, FingR fusion configurations, and transcriptional control regulations in adeno-associated virus (AAV) and retrovirus vector designs. We report the development of a red FingR variant and demonstrated dual labeling of excitatory and inhibitory synapses in the same cells. Furthermore, we developed cre-inducible FingR AAV variants and demonstrated their utility, finding that the density of inhibitory synapses in aspiny striatal cholinergic interneurons remained unchanged in response to dopamine depletion. Finally, we generated FingR retroviral vectors, which enabled us to track the development of excitatory and inhibitory synapses in hippocampal adult-born granule cells.

Low-cost calcium fluorometry for long-term nanoparticle studies in living cells.

Calcium fluorometry is critical to determine cell homeostasis or to reveal communication patterns in neuronal networks. Recently, characterizing calcium signalling in neurons related to interactions with nanomaterials has become of interest due to its therapeutic potential. However, imaging of neuronal cell activity under stable physiological conditions can be either very expensive or limited in its long-term capability. Here, we present a low-cost, portable imaging system for long-term, fast-scale calcium fluorometry in neurons. Using the imaging system, we revealed temperature-dependent changes in long-term calcium signalling in kidney cells and primary cortical neurons. Furthermore, we introduce fast-scale monitoring of synchronous calcium activity in neuronal cultures in response to nanomaterials. Through graph network analysis, we found that calcium dynamics in neurons are temperature-dependent when exposed to chitosan-coated nanoparticles. These results give new insights into nanomaterial-interaction in living cultures and tissues based on calcium fluorometry and graph network analysis.

A high-speed, bright, red fluorescent voltage sensor to detect neural activity.

Genetically encoded voltage indicators (GEVIs) have emerged as a technology to optically record neural activity with genetic specificity and millisecond-scale temporal resolution using fluorescence microscopy. GEVIs have demonstrated ultra-fast kinetics and high spike detection fidelity in vivo, but existing red-fluorescent voltage indicators fall short of the response and brightness achieved by green fluorescent protein-based sensors. Furthermore, red-fluorescent GEVIs suffer from incomplete spectral separation from green sensors and blue-light-activated optogenetic actuators. We have developed Ace-mScarlet, a red fluorescent GEVI that fuses Ace2N, a voltage-sensitive inhibitory rhodopsin, with mScarlet, a bright red fluorescent protein (FP). Through fluorescence resonance energy transfer (FRET), our sensor detects changes in membrane voltage with high sensitivity and brightness and has kinetics comparable to the fastest green fluorescent sensors. Ace-mScarlet's red-shifted absorption and emission spectra facilitate virtually complete spectral separation when used in combination with green-fluorescent sensors or with blue-light-sensitive sensors and rhodopsins. This spectral separation enables both simultaneous imaging in two separate wavelength channels and high-fidelity voltage recordings during simultaneous optogenetic perturbation.

Enhanced genetically encoded voltage indicators advance their applications in neuroscience.

Genetically encoded voltage indicators report membrane voltage with high spatiotemporal resolution. Extensive recent efforts to improve the GEVIs' brightness, sensitivity, and kinetics have greatly increased the GEVIs' signal-to-noise performance over ten-fold and lowered their response time to the sub-millisecond regime. Such capabilities have broadened the GEVIs' ability to measure membrane voltage of neural populations at cellular resolution in vitro and in vivo, all at high speeds. The GEVIs' high voltage fidelity and fast response have revealed novel physiological phenomena in multiple neuroscientific applications. Such applications portend future targeted studies of voltage activity that take advantage of the GEVIs' ability to report rapid dynamics from genetically-targeted neural populations.

Enhancing Glycemic Control via Detection of Insulin Using Electrochemical Impedance Spectroscopy.

BACKGROUND: Currently, glycemic management for individuals with diabetes mellitus involves monitoring glucose only, which is insufficient as glucose metabolism involves other biomarkers such as insulin. Monitoring additional biomarkers alongside glucose has been proposed to improve glycemic control. In this work, the development of a rapid and label-free insulin biosensor with high sensitivity and accuracy is presented. The insulin sensor prototype also serves as a prior study for a multimarker sensing platform technology that can further improve glycemic control in the future. METHODS: Electrochemical impedance spectroscopy was used to identify an optimal frequency specific to insulin detection on a gold disk electrode with insulin antibody immobilized, which was accomplished by conjugating the primary amines of insulin antibody to the carboxylic bond of the self-assembling monolayer on the gold surface. After blocking with ethanolamine, the insulin physiological concentration gradient was tested. The imaginary impedance was correlated to insulin concentration and the results were compared with standard equivalent circuit analysis and correlation of charge transfer resistance to target concentration. RESULTS: The optimal frequency of insulin is 810.5 Hz, which is characterized by having the highest sensitivity and sufficient specificity. The lower limit of detection was 2.26 [Formula: see text] which is comparable to a standard and better than traditional approaches. CONCLUSION: An insulin biosensor prototype capable of detecting insulin in physiological range without complex data normalization was developed. This prototype will be the ground works of a multimarker platform sensor technology for future all-in-one glycemic management sensors.