Fluorescent Biosensors for Neurotransmission and Neuromodulation: Engineering and Applications

Detecting rhythmic spiking through the power spectra of point process model residuals

Objective. Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ('RP', the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established 'shuffling' procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.Approach. In a novel 'residuals' method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the precedingnrmilliseconds. Finally, we compute the PSD of the model's residuals.Main results. We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey-in which alpha-beta oscillations (8-30 Hz) were anticipated-the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.Significance. These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

Next-Generation Genetically Encoded Fluorescent Biosensors Illuminate Cell Signaling and Metabolism

Genetically encoded fluorescent biosensors have revolutionized the study of cell signaling and metabolism, as they allow for live-cell measurements with high spatiotemporal resolution. This success has spurred the development of tailor-made biosensors that enable the study of dynamic phenomena on different timescales and length scales. In this review, we discuss different approaches to enhancing and developing new biosensors. We summarize the technologies used to gain structural insights into biosensor design and comment on useful screening technologies. Furthermore, we give an overview of different applications where biosensors have led to key advances over recent years. Finally, we give our perspective on where future work is bound to make a large impact.

Simultaneous Dopamine and Serotonin Monitoring in Freely Moving Crayfish Using a Wireless Electrochemical Sensing System

Dopamine (DA) and serotonin (5-HT) are neurotransmitters that regulate a wide range of physiological and behavioral processes. Monitoring of both neurotransmitters with real-time analysis offers important insight into the mechanisms that shape animal behavior. However, bioelectronic tools to simultaneously monitor DA and 5-HT interactive dynamics in freely moving animals are underdeveloped. This is mainly due to the limited sensor sensitivity with miniaturized electronics. Here, we present a semi-implantable electrochemical device achieved by integrating a multi-surface-modified carbon fiber microelectrode with a miniaturized potentiostat module to detect DA and 5-HT in vivo with high sensitivity and selectivity. Specifically, carbon fiber microelectrodes were modified through electrochemical treatment and surface coatings to improve sensitivity, selectivity, and antifouling properties. A customized, lightweight potentiostat module was developed for untethered electrochemical measurements. Integrated with the microelectrode, the microsystem is compact (2.8 × 2.3 × 2.1 cm) to minimize its impacts on animal behavior and achieved simultaneous detection of DA and 5-HT with sensitivities of 48.4 and 133.0 nA/μM, respectively, within submicromolar ranges. The system was attached to the crayfish dorsal carapace, allowing electrode implantation into the heart of a crayfish to monitor DA and 5-HT dynamics, followed by drug injections. The semi-implantable biosensor system displayed a significant increase in oxidation peak currents after DA and 5-HT injections. The device successfully demonstrated the application for in vivo simultaneous monitoring of DA and 5-HT in the hemolymph (i.e., blood) of freely behaving crayfish underwater, yielding a valuable experimental tool to expand our understanding of the comodulation of DA and 5-HT.

Updated Toolbox for Assessing Neuronal Network Reconstruction after Cell Therapy

Cell therapy has proven to be a promising treatment for a range of neurological disorders, including Parkinson Disease, drug-resistant epilepsy, and stroke, by restoring function after brain damage. Nevertheless, evaluating the true effectiveness of these therapeutic interventions requires a deep understanding of the functional integration of grafted cells into existing neural networks. This review explores a powerful arsenal of molecular techniques revolutionizing our ability to unveil functional integration of grafted cells within the host brain. From precise manipulation of neuronal activity to pinpoint the functional contribution of transplanted cells by using opto- and chemo-genetics, to real-time monitoring of neuronal dynamics shedding light on functional connectivity within the reconstructed circuits by using genetically encoded (calcium) indicators in vivo. Finally, structural reconstruction and mapping communication pathways between grafted and host neurons can be achieved by monosynaptic tracing with viral vectors. The cutting-edge toolbox presented here holds immense promise for elucidating the impact of cell therapy on neural circuitry and guiding the development of more effective treatments for neurological disorders.

Spatiotemporal Organization of Prefrontal Norepinephrine Influences Neuronal Activity

Norepinephrine (NE), a neuromodulator released by locus ceruleus (LC) neurons throughout the cortex, influences arousal and learning through extrasynaptic vesicle exocytosis. While NE within cortical regions has been viewed as a homogenous field, recent studies have demonstrated heterogeneous axonal dynamics and advances in GPCR-based fluorescent sensors permit direct observation of the local dynamics of NE at cellular scale. To investigate how the spatiotemporal dynamics of NE release in the prefrontal cortex (PFC) affect neuronal firing, we employed in vivo two-photon imaging of layer 2/3 of the PFC in order to observe fine-scale neuronal calcium and NE dynamics concurrently. In this proof of principle study, we found that local and global NE fields can decouple from one another, providing a substrate for local NE spatiotemporal activity patterns. Optic flow analysis revealed putative release and reuptake events which can occur at the same location, albeit at different times, indicating the potential to create a heterogeneous NE field. Utilizing generalized linear models, we demonstrated that cellular Ca2+ fluctuations are influenced by both the local and global NE field. However, during periods of local/global NE field decoupling, the local field drives cell firing dynamics rather than the global field. These findings underscore the significance of localized, phasic NE fluctuations for structuring cell firing, which may provide local neuromodulatory control of cortical activity.

Functional principles of genetically encoded fluorescent biosensors for metabolism and their quantitative use

Genetically encoded fluorescent biosensors provide an attractive means of measuring chemical changes in single cells on fast timescales (milliseconds to seconds). While their most prominent application has been in tracking neural activity and neurotransmitter release, there has been growing interest in developing and deploying new versions of these tools to study brain metabolism. However, the careful use of these tools and the interpretation of the data they provide remain challenging. Many biosensors are subject to interferences that can alter sensor responses within a single cell or between cells, producing ambiguous results. This presents a challenge for quantitation and for our ability to accurately interpret sensor responses. This review describes current methods of sensor quantitation, with a focus on cellular interferences that commonly affect sensor performance, ways to avoid false inferences, and recent advances in sensor optimization to make them more robust.

Detecting rhythmic spiking through the power spectra of point process model residuals

Objective

Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ("RP", the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established "shuffling" procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.

Approach

In a novel "residuals" method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the preceding nr milliseconds. Finally, we compute the PSD of the model's residuals.

Main results

We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey -- in which alpha-beta oscillations (8-30 Hz) were anticipated -- the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.

Significance

These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

A genetically-encoded fluorescent biosensor for visualization of acetyl-CoA in live cells

Acetyl-coenzyme A is a central metabolite that participates in many cellular pathways. Evidence suggests that acetyl-CoA production and consumption are highly compartmentalized in mammalian cells. Yet methods to measure acetyl-CoA in living cells are lacking. In this work, we engineer an acetyl-CoA biosensor from the bacterial protein PanZ and circularly permuted green fluorescent protein (cpGFP). We biochemically characterize the sensor and demonstrate its selectivity for acetyl-CoA over other CoA species. We then deploy the biosensor in E. coli and HeLa cells to demonstrate its utility in living cells. In E. coli, we show that the biosensor enables detection of rapid changes in acetyl-CoA levels. In human cells, we show that the biosensor enables subcellular detection and reveals the compartmentalization of acetyl-CoA metabolism.

A perspective on computer vision in biosensing

Computer vision has become a powerful tool in the field of biosensing, aiding in the development of innovative and precise systems for the analysis and interpretation of biological data. This interdisciplinary approach harnesses the capabilities of computer vision algorithms and techniques to extract valuable information from various biosensing applications, including medical diagnostics, environmental monitoring, and food health. Despite years of development, there is still significant room for improvement in this area. In this perspective, we outline how computer vision is applied to raw sensor data in biosensors and its advantages to biosensing applications. We then discuss ongoing research and developments in the field and subsequently explore the challenges and opportunities that computer vision faces in biosensor applications. We also suggest directions for future work, ultimately underscoring the significant impact of computer vision on advancing biosensing technologies and their applications.

Neural mechanisms of dopamine function in learning and memory in Caenorhabditis elegans

Research into learning and memory over the past decades has revealed key neurotransmitters that regulate these processes, many of which are evolutionarily conserved across diverse species. The monoamine neurotransmitter dopamine is one example of this, with countless studies demonstrating its importance in regulating behavioural plasticity. However, dopaminergic neural networks in the mammalian brain consist of hundreds or thousands of neurons, and thus cannot be studied at the level of single neurons acting within defined neural circuits. The nematode Caenorhabditis elegans (C. elegans) has an experimentally tractable nervous system with a completely characterized synaptic connectome. This makes it an advantageous system to undertake mechanistic studies into how dopamine encodes lasting yet flexible behavioural plasticity in the nervous system. In this review, we synthesize the research to date exploring the importance of dopaminergic signalling in learning, memory formation, and forgetting, focusing on research in C. elegans. We also explore the potential for dopamine-specific fluorescent biosensors in C. elegans to visualize dopaminergic neural circuits during learning and memory formation in real-time. We propose that the use of these sensors in C. elegans, in combination with optogenetic and other light-based approaches, will further illuminate the detailed spatiotemporal requirements for encoding behavioural plasticity in an accessible experimental system. Understanding the key molecules and circuit mechanisms that regulate learning and forgetting in more compact invertebrate nervous systems may reveal new druggable targets for enhancing memory storage and delaying memory loss in bigger brains.

Activity-dependent constraints on catecholamine signaling

Catecholamine signaling is thought to modulate cognition in an inverted-U relationship, but the mechanisms are unclear. We measured norepinephrine and dopamine release, postsynaptic calcium responses, and interactions between tonic and phasic firing modes under various stimuli and conditions. High tonic activity in vivo depleted catecholamine stores, desensitized postsynaptic responses, and decreased phasic transmission. Together, these findings provide a more complete understanding of the inverted-U relationship, offering insights into psychiatric disorders and neurodegenerative diseases with impaired catecholamine signaling.

Fluorescent-Based Neurotransmitter Sensors: Present and Future Perspectives

Neurotransmitters (NTs) are endogenous low-molecular-weight chemical compounds that transmit synaptic signals in the central nervous system. These NTs play a crucial role in facilitating signal communication, motor control, and processes related to memory and learning. Abnormalities in the levels of NTs lead to chronic mental health disorders and heart diseases. Therefore, detecting imbalances in the levels of NTs is important for diagnosing early stages of diseases associated with NTs. Sensing technologies detect NTs rapidly, specifically, and selectively, overcoming the limitations of conventional diagnostic methods. In this review, we focus on the fluorescence-based biosensors that use nanomaterials such as metal clusters, carbon dots, and quantum dots. Additionally, we review biomaterial-based, including aptamer- and enzyme-based, and genetically encoded biosensors. Furthermore, we elaborate on the fluorescence mechanisms, including fluorescence resonance energy transfer, photon-induced electron transfer, intramolecular charge transfer, and excited-state intramolecular proton transfer, in the context of their applications for the detection of NTs. We also discuss the significance of NTs in human physiological functions, address the current challenges in designing fluorescence-based biosensors for the detection of NTs, and explore their future development.

Laser-Induced Graphitization of Polydopamine on Titania Nanotubes

Since the discovery of laser-induced graphite/graphene, there has been a notable surge of scientific interest in advancing diverse methodologies for their synthesis and applications. This study focuses on the utilization of a pulsed Nd:YAG laser to achieve graphitization of polydopamine (PDA) deposited on the surface of titania nanotubes. The partial graphitization is corroborated through Raman and XPS spectroscopies and supported by water contact angle, nanomechanical, and electrochemical measurements. Reactive molecular dynamics simulations confirm the possibility of graphitization in the nanosecond time scale with the evolution of NH3, H2O, and CO2 gases. A thorough exploration of the lasing parameter space (wavelength, pulse energy, and number of pulses) was conducted with the aim of improving either electrochemical activity or photocurrent generation. Whereas the 532 nm laser pulses interacted mostly with the PDA coating, the 365 nm pulses were absorbed by both PDA and the substrate nanotubes, leading to a higher graphitization degree. The majority of the photocurrent and quantum efficiency enhancement is observed in the visible light between 400 and 550 nm. The proposed composite is applied as a photoelectrochemical (PEC) sensor of serotonin in nanomolar concentrations. Because of the suppressed recombination and facilitated charge transfer caused by the laser graphitization, the proposed composite exhibits significantly enhanced PEC performance. In the sensing application, it showed superior sensitivity and a limit of detection competitive with nonprecious metal materials.

An Updated Review on Electrochemical Nanobiosensors for Neurotransmitter Detection

Neurotransmitters are chemical compounds released by nerve cells, including neurons, astrocytes, and oligodendrocytes, that play an essential role in the transmission of signals in living organisms, particularly in the central nervous system, and they also perform roles in realizing the function and maintaining the state of each organ in the body. The dysregulation of neurotransmitters can cause neurological disorders. This highlights the significance of precise neurotransmitter monitoring to allow early diagnosis and treatment. This review provides a complete multidisciplinary examination of electrochemical biosensors integrating nanomaterials and nanotechnologies in order to achieve the accurate detection and monitoring of neurotransmitters. We introduce extensively researched neurotransmitters and their respective functions in biological beings. Subsequently, electrochemical biosensors are classified based on methodologies employed for direct detection, encompassing the recently documented cell-based electrochemical monitoring systems. These methods involve the detection of neurotransmitters in neuronal cells in vitro, the identification of neurotransmitters emitted by stem cells, and the in vivo monitoring of neurotransmitters. The incorporation of nanomaterials and nanotechnologies into electrochemical biosensors has the potential to assist in the timely detection and management of neurological disorders. This study provides significant insights for researchers and clinicians regarding precise neurotransmitter monitoring and its implications regarding numerous biological applications.

From Enzymatic Dopamine Biosensors to OECT Biosensors of Dopamine

Neurotransmitters are an important category of substances used inside the nervous system, whose detection with biosensors has been seriously addressed in the last decades. Dopamine, a neurotransmitter from the catecholamine family, was recently discovered to have implications for cardiac arrest or muscle contractions. In addition to having many other neuro-psychiatric implications, dopamine can be detected in blood, urine, and sweat. This review highlights the importance of biosensors as influential tools for dopamine recognition. The first part of this article is related to an introduction to biosensors for neurotransmitters, with a focus on dopamine. The regular methods in their detection are expensive and require high expertise personnel. A major direction of evolution of these biosensors has expanded with the integration of active biological materials suitable for molecular recognition near electronic devices. Secondly, for dopamine in particular, the miniaturized biosensors offer excellent sensitivity and specificity and offer cheaper detection than conventional spectrometry, while their linear detection ranges from the last years fall exactly on the clinical intervals. Thirdly, the applications of novel nanomaterials and biomaterials to these biosensors are discussed. Older generations, metabolism-based or enzymatic biosensors, could not detect concentrations below the micro-molar range. But new generations of biosensors combine aptamer receptors and organic electrochemical transistors, OECTs, as transducers. They have pushed the detection limit to the pico-molar and even femto-molar ranges, which fully correspond to the usual ranges of clinical detection of human dopamine in body humors that cover 0.1 ÷ 10 nM. In addition, if ten years ago the use of natural dopamine receptors on cell membranes seemed impossible for biosensors, the actual technology allows co-integrate transistors and vesicles with natural receptors of dopamine, like G protein-coupled receptors. The technology is still complicated, but the uni-molecular detection selectivity is promising.

A STIM dependent dopamine-neuropeptide axis maintains the larval drive to feed and grow in Drosophila

Appropriate nutritional intake is essential for organismal survival. In holometabolous insects such as Drosophila melanogaster, the quality and quantity of food ingested as larvae determines adult size and fecundity. Here we have identified a subset of dopaminergic neurons (THD') that maintain the larval motivation to feed. Dopamine release from these neurons requires the ER Ca2+ sensor STIM. Larvae with loss of STIM stop feeding and growing, whereas expression of STIM in THD' neurons rescues feeding, growth and viability of STIM null mutants to a significant extent. Moreover STIM is essential for maintaining excitability and release of dopamine from THD' neurons. Optogenetic stimulation of THD' neurons activated neuropeptidergic cells, including median neuro secretory cells that secrete insulin-like peptides. Loss of STIM in THD' cells alters the developmental profile of specific insulin-like peptides including ilp3. Loss of ilp3 partially rescues STIM null mutants and inappropriate expression of ilp3 in larvae affects development and growth. In summary we have identified a novel STIM-dependent function of dopamine neurons that modulates developmental changes in larval feeding behaviour and growth.

High-throughput deep tissue two-photon microscopy at kilohertz frame rates

High-speed laser scanning microscopes are essential for monitoring fast biological phenomena. However, existing strategies that achieve millisecond time resolution with two-photon microscopes (2PMs) are generally technically challenging and suffer from compromises among imaging field of view, excitation efficiency, and depth penetration in thick tissue. Here, we present a versatile solution that enables a conventional video-rate 2PM to perform 2D scanning at kilohertz frame rates over large fields of view. Our system is based on implementation of a scan multiplier unit that provides inertia-free multiplication of the scanning speed while preserving all the benefits of standard 2PM. We demonstrate kilohertz subcellular-resolution 2PM imaging with an order of magnitude higher imaging throughput than previously achievable and penetration depths exceeding 500 μm, which we apply to the study of neurovascular coupling dynamics in the mouse brain.

Activity-dependent constraints on catecholamine signaling

Catecholamine signaling is thought to modulate cognition in an inverted-U relationship, but the mechanisms are unclear. We measured norepinephrine and dopamine release, postsynaptic calcium responses, and interactions between tonic and phasic firing modes under various stimuli and conditions. High tonic activity in vivo depleted catecholamine stores, desensitized postsynaptic responses, and decreased phasic transmission. Together this provides a clearer understanding of the inverted-U relationship, offering insights into psychiatric disorders and neurodegenerative diseases with impaired catecholamine signaling.

Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo

The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.

Automating the High-Throughput Screening of Protein-Based Optical Indicators and Actuators

Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.

Seeing Neurodegeneration in a New Light Using Genetically Encoded Fluorescent Biosensors and iPSCs

Neurodegenerative diseases present a progressive loss of neuronal structure and function, leading to cell death and irrecoverable brain atrophy. Most have disease-modifying therapies, in part because the mechanisms of neurodegeneration are yet to be defined, preventing the development of targeted therapies. To overcome this, there is a need for tools that enable a quantitative assessment of how cellular mechanisms and diverse environmental conditions contribute to disease. One such tool is genetically encodable fluorescent biosensors (GEFBs), engineered constructs encoding proteins with novel functions capable of sensing spatiotemporal changes in specific pathways, enzyme functions, or metabolite levels. GEFB technology therefore presents a plethora of unique sensing capabilities that, when coupled with induced pluripotent stem cells (iPSCs), present a powerful tool for exploring disease mechanisms and identifying novel therapeutics. In this review, we discuss different GEFBs relevant to neurodegenerative disease and how they can be used with iPSCs to illuminate unresolved questions about causes and risks for neurodegenerative disease.

Cranial Window for Acute and Chronic Optical Access to Record Neuronal Network Dynamics in the Olfactory Bulb

Cranial window implant is the preparation of choice for acute and chronic optical access to a given brain area. The cranial window provides a stable preparation, which can last for months. This window allows to follow the activity of distinct population of neurons expressing genetically encoded fluorescent reporters of activity in awake, behaving, head-fixed animals. The optical access can also be exploited for acute imaging, in anesthetized animals. Here we provide a detailed protocol for acute and chronic cranial window implantations in the olfactory bulb. We also provide the procedure to perform injections of adeno-associated viruses expressing genetically encoded fluorescent sensors in the same area.

The Evolving Role of Animal Models in the Discovery and Development of Novel Treatments for Psychiatric Disorders

Historically, animal models have been routinely used in the characterization of novel chemical entities (NCEs) for various psychiatric disorders. Animal models have been essential in the in vivo validation of novel drug targets, establishment of lead compound pharmacokinetic to pharmacodynamic relationships, optimization of lead compounds through preclinical candidate selection, and development of translational measures of target occupancy and functional target engagement. Yet, with decades of multiple NCE failures in Phase II and III efficacy trials for different psychiatric disorders, the utility and value of animal models in the drug discovery process have come under intense scrutiny along with the widespread withdrawal of the pharmaceutical industry from psychiatric drug discovery. More recently, the development and utilization of animal models for the discovery of psychiatric NCEs has undergone a dynamic evolution with the application of the Research Domain Criteria (RDoC) framework for better design of preclinical to clinical translational studies combined with innovative genetic, neural circuitry-based, and automated testing technologies. In this chapter, the authors will discuss this evolving role of animal models for improving the different stages of the discovery and development in the identification of next generation treatments for psychiatric disorders.

Dopamine, Immunity, and Disease

The neurotransmitter dopamine is a key factor in central nervous system (CNS) function, regulating many processes including reward, movement, and cognition. Dopamine also regulates critical functions in peripheral organs, such as blood pressure, renal activity, and intestinal motility. Beyond these functions, a growing body of evidence indicates that dopamine is an important immunoregulatory factor. Most types of immune cells express dopamine receptors and other dopaminergic proteins, and many immune cells take up, produce, store, and/or release dopamine, suggesting that dopaminergic immunomodulation is important for immune function. Targeting these pathways could be a promising avenue for the treatment of inflammation and disease, but despite increasing research in this area, data on the specific effects of dopamine on many immune cells and disease processes remain inconsistent and poorly understood. Therefore, this review integrates the current knowledge of the role of dopamine in immune cell function and inflammatory signaling across systems. We also discuss the current understanding of dopaminergic regulation of immune signaling in the CNS and peripheral tissues, highlighting the role of dopaminergic immunomodulation in diseases such as Parkinson's disease, several neuropsychiatric conditions, neurologic human immunodeficiency virus, inflammatory bowel disease, rheumatoid arthritis, and others. Careful consideration is given to the influence of experimental design on results, and we note a number of areas in need of further research. Overall, this review integrates our knowledge of dopaminergic immunology at the cellular, tissue, and disease level and prompts the development of therapeutics and strategies targeted toward ameliorating disease through dopaminergic regulation of immunity. SIGNIFICANCE STATEMENT: Canonically, dopamine is recognized as a neurotransmitter involved in the regulation of movement, cognition, and reward. However, dopamine also acts as an immune modulator in the central nervous system and periphery. This review comprehensively assesses the current knowledge of dopaminergic immunomodulation and the role of dopamine in disease pathogenesis at the cellular and tissue level. This will provide broad access to this information across fields, identify areas in need of further investigation, and drive the development of dopaminergic therapeutic strategies.

In vivo protein-based biosensors: seeing metabolism in real time

Biological homeostasis is a dynamic and elastic equilibrium of countless interlinked biochemical reactions. A key goal of life sciences is to understand these dynamics; bioengineers seek to reconfigure such networks. Both goals require the ability to monitor the concentration of individual intracellular metabolites with sufficient spatiotemporal resolution. To achieve this, a range of protein or protein/DNA signalling circuits with optical readouts have been constructed. Protein biosensors can provide quantitative information at subsecond temporal and suborganelle spatial resolution. However, their construction is fraught with difficulties related to integrating the affinity- and selectivity-endowing components with the signal reporters. We argue that development of efficient approaches for construction of chemically induced dimerisation systems and reporter domains with large dynamic ranges will solve these problems.

Biosensors: Electrochemical Devices-General Concepts and Performance

This review provides a general overview of different biosensors, mostly concentrating on electrochemical analytical devices, while briefly explaining general approaches to various kinds of biosensors, their construction and performance. A discussion on how all required components of biosensors are brought together to perform analytical work is offered. Different signal-transducing mechanisms are discussed, particularly addressing the immobilization of biomolecular components in the vicinity of a transducer interface and their functional integration with electronic devices. The review is mostly addressing general concepts of the biosensing processes rather than specific modern achievements in the area.

Neuronal Activity Reporters as Drug Screening Platforms

Understanding how neuronal activity changes and detecting such changes in both normal and disease conditions is of fundamental importance to the field of neuroscience. Neuronal activity plays important roles in the formation and function of both synapses and circuits, and dysregulation of these processes has been linked to a number of debilitating diseases such as autism, schizophrenia, and epilepsy. Despite advances in our understanding of synapse biology and in how it is altered in disease, the development of therapeutics for these diseases has not advanced apace. Many neuronal activity assays have been developed over the years using a variety of platforms and approaches, but major limitations persist. Current assays, such as fluorescence indicators are not designed to monitor neuronal activity over a long time, they are typically low-throughput or lack sensitivity. These are major barriers to the development of new therapies, as drug screening needs to be both high-throughput to screen through libraries of compounds, and longitudinal to detect any effects that may emerge after continued application of the drug. This review will cover existing assays for measuring neuronal activity and highlight a live-cell assay recently developed. This assay can be performed with easily accessible lab equipment, is both scalable and longitudinal, and can be combined with most other established methods.

Tailoring Diffusional Fields in Zwitterion/Dopamine Copolymer Electropolymerized at Carbon Nanowalls for Sensitive Recognition of Neurotransmitters

The importance of neurotransmitter sensing in the diagnosis and treatment of many psychological illnesses and neurodegenerative diseases is non-negotiable. For electrochemical sensors to become widespread and accurate, a long journey must be undertaken for each device, from understanding the materials at the molecular level to real applications in biological fluids. We report a modification of diamondized boron-doped carbon nanowalls (BCNWs) with an electropolymerized polydopamine/polyzwitterion (PDA|PZ) coating revealing tunable mechanical and electrochemical properties. Zwitterions are codeposited with PDA and noncovalently incorporated into a structure. This approach causes a specific separation of the diffusion fields generated by each nanowall during electrochemical reactions, thus increasing the contribution of the steady-state currents in the amperometric response. This phenomenon has a profound effect on the sensing properties, leading to a 4-fold enhancement of the sensitivity (3.1 to 14.3 μA cm^-2 μM^-1) and a 5-fold decrease of the limit of detection (505 to 89 nM) in comparison to the pristine BCNWs. Moreover, as a result of the antifouling capabilities of the incorporated zwitterions, this enhancement is preserved in bovine serum albumin (BSA) with a high protein concentration. The presence of zwitterion facilitates the transport of dopamine in the direction of the electrode by intermolecular interactions such as cation-π and hydrogen bonds. On the other hand, polydopamine units attached to the surface form molecular pockets driven by hydrogen bonds and π-π interactions. As a result, the intermediate state of dopamine-analyte oxidation is stabilized, leading to the enhancement of the sensing properties.

Optogenetics for light control of biological systems

Optogenetic techniques have been developed to allow control over the activity of selected cells within a highly heterogeneous tissue, using a combination of genetic engineering and light. Optogenetics employs natural and engineered photoreceptors, mostly of microbial origin, to be genetically introduced into the cells of interest. As a result, cells that are naturally light-insensitive can be made photosensitive and addressable by illumination and precisely controllable in time and space. The selectivity of expression and subcellular targeting in the host is enabled by applying control elements such as promoters, enhancers and specific targeting sequences to the employed photoreceptor-encoding DNA. This powerful approach allows precise characterization and manipulation of cellular functions and has motivated the development of advanced optical methods for patterned photostimulation. Optogenetics has revolutionized neuroscience during the past 15 years and is primed to have a similar impact in other fields, including cardiology, cell biology and plant sciences. In this Primer, we describe the principles of optogenetics, review the most commonly used optogenetic tools, illumination approaches and scientific applications and discuss the possibilities and limitations associated with optogenetic manipulations across a wide variety of optical techniques, cells, circuits and organisms.

Multiplexed Monitoring of Neurochemicals via Electrografting-Enabled Site-Selective Functionalization of Aptamers on Field-Effect Transistors

Neurochemical corelease has received much attention in understanding brain activity and cognition. Despite many attempts, the multiplexed monitoring of coreleased neurochemicals with spatiotemporal precision and minimal crosstalk using existing methods remains challenging. Here, we report a soft neural probe for multiplexed neurochemical monitoring via the electrografting-assisted site-selective functionalization of aptamers on graphene field-effect transistors (G-FETs). The neural probes possess excellent flexibility, ultralight mass (28 mg), and a nearly cellular-scale dimension of 50 μm × 50 μm for each G-FET. As a demonstration, we show that G-FETs with electrochemically grafted molecular linkers (-COOH or -NH₂) and specific aptamers can be used to monitor serotonin and dopamine with high sensitivity (limit of detection: 10 pM) and selectivity (dopamine sensor >22-fold over norepinephrine; serotonin sensor >17-fold over dopamine). In addition, we demonstrate the feasibility of the simultaneous monitoring of dopamine and serotonin in a single neural probe with minimal crosstalk and interferences in phosphate-buffered saline, artificial cerebrospinal fluid, and harvested mouse brain tissues. The stability studies show that multiplexed neural probes maintain the capability for simultaneously monitoring dopamine and serotonin with minimal crosstalk after incubating in rat cerebrospinal fluid for 96 h, although a reduced sensor response at high concentrations is observed. Ex vivo studies in harvested mice brains suggest potential applications in monitoring the evoked release of dopamine and serotonin. The developed multiplexed detection methodology can also be adapted for monitoring other neurochemicals, such as metabolites and neuropeptides, by simply replacing the aptamers functionalized on the G-FETs.

Optogenetic Methods to Investigate Brain Alterations in Preclinical Models

Investigating the neuronal dynamics supporting brain functions and understanding how the alterations in these mechanisms result in pathological conditions represents a fundamental challenge. Preclinical research on model organisms allows for a multiscale and multiparametric analysis in vivo of the neuronal mechanisms and holds the potential for better linking the symptoms of a neurological disorder to the underlying cellular and circuit alterations, eventually leading to the identification of therapeutic/rescue strategies. In recent years, brain research in model organisms has taken advantage, along with other techniques, of the development and continuous refinement of methods that use light and optical approaches to reconstruct the activity of brain circuits at the cellular and system levels, and to probe the impact of the different neuronal components in the observed dynamics. These tools, combining low-invasiveness of optical approaches with the power of genetic engineering, are currently revolutionizing the way, the scale and the perspective of investigating brain diseases. The aim of this review is to describe how brain functions can be investigated with optical approaches currently available and to illustrate how these techniques have been adopted to study pathological alterations of brain physiology.

Technologies for large-scale mapping of functional neural circuits active during a user-defined time window

The mapping of neural circuits activated during behavior down to individual neurons is crucial for decoding how the brain processes information. Technologies allowing activity-dependent labeling of neurons during user-defined restricted time windows are rapidly developing. Precise marking of the time window with light, in addition to chemicals, is now possible. In these technologies, genetically encoded molecules integrate molecular events resulting from neuronal activity with light/drug-dependent events. The outputs are either changes in fluorescence or activation of gene expression. Molecular reporters allow labeling of activated neurons for visualization and cell-type identification. The transcriptional readout also allows further control of activated neuronal populations using optogenetic tools as reporters. Here we review the design of these technologies and discuss their demonstrated applications to reveal previously unknown connections in the mammalian brain. We also consider the strengths and weaknesses of the current approaches and provide a perspective for the future.

Semi-Implantable Bioelectronics

Developing techniques to effectively and real-time monitor and regulate the interior environment of biological objects is significantly important for many biomedical engineering and scientific applications, including drug delivery, electrophysiological recording and regulation of intracellular activities. Semi-implantable bioelectronics is currently a hot spot in biomedical engineering research area, because it not only meets the increasing technical demands for precise detection or regulation of biological activities, but also provides a desirable platform for externally incorporating complex functionalities and electronic integration. Although there is less definition and summary to distinguish it from the well-reviewed non-invasive bioelectronics and fully implantable bioelectronics, semi-implantable bioelectronics have emerged as highly unique technology to boost the development of biochips and smart wearable device. Here, we reviewed the recent progress in this field and raised the concept of "Semi-implantable bioelectronics", summarizing the principle and strategies of semi-implantable device for cell applications and in vivo applications, discussing the typical methodologies to access to intracellular environment or in vivo environment, biosafety aspects and typical applications. This review is meaningful for understanding in-depth the design principles, materials fabrication techniques, device integration processes, cell/tissue penetration methodologies, biosafety aspects, and applications strategies that are essential to the development of future minimally invasive bioelectronics.

Transgenic mice encoding modern imaging probes: Properties and applications

Modern biology is increasingly reliant on optical technologies, including visualization and longitudinal monitoring of cellular processes. The major limitation here is the availability of animal models to track the molecules and cells in their natural environment in vivo. Owing to the integrity of the studied tissue and the high stability of transgene expression throughout life, transgenic mice encoding fluorescent proteins and biosensors represent unique tools for in vivo studies in norm and pathology. We review the strategies for targeting probe expression in specific tissues, cell subtypes, or cellular compartments. We describe the application of transgenic mice expressing fluorescent proteins for tracking protein expression patterns, apoptotic events, tissue differentiation and regeneration, neurogenesis, tumorigenesis, and cell fate mapping. We overview the possibilities of functional imaging of secondary messengers, neurotransmitters, and ion fluxes. Finally, we provide the rationale and perspectives for the use of transgenic imaging probes in translational research and drug discovery.

Applying a Fast-Scan Cyclic Voltammetry to Explore Dopamine Dynamics in Animal Models of Neuropsychiatric Disorders

Progress in the development of technologies for the real-time monitoring of neurotransmitter dynamics has provided researchers with effective tools for the exploration of etiology and molecular mechanisms of neuropsychiatric disorders. One of these powerful tools is fast-scan cyclic voltammetry (FSCV), a technique which has progressively been used in animal models of diverse pathological conditions associated with alterations in dopamine transmission. Indeed, for several decades FSCV studies have provided substantial insights into our understanding of the role of abnormal dopaminergic transmission in pathogenetic mechanisms of drug and alcohol addiction, Parkinson’s disease, schizophrenia, etc. Here we review the applications of FSCV to research neuropsychiatric disorders with particular attention to recent technological advances.

Pushing the frontiers: tools for monitoring neurotransmitters and neuromodulators

Neurotransmitters and neuromodulators have a wide range of key roles throughout the nervous system. However, their dynamics in both health and disease have been challenging to assess, owing to the lack of in vivo tools to track them with high spatiotemporal resolution. Thus, developing a platform that enables minimally invasive, large-scale and long-term monitoring of neurotransmitters and neuromodulators with high sensitivity, high molecular specificity and high spatiotemporal resolution has been essential. Here, we review the methods available for monitoring the dynamics of neurotransmitters and neuromodulators. Following a brief summary of non-genetically encoded methods, we focus on recent developments in genetically encoded fluorescent indicators, highlighting how these novel indicators have facilitated advances in our understanding of the functional roles of neurotransmitters and neuromodulators in the nervous system. These studies present a promising outlook for the future development and use of tools to monitor neurotransmitters and neuromodulators.

Chemical Targeting of Rhodol Voltage-Sensitive Dyes to Dopaminergic Neurons

Optical imaging of changes in the membrane potential of living cells can be achieved by means of fluorescent voltage-sensitive dyes (VSDs). A particularly challenging task is to efficiently deliver these highly lipophilic probes to specific neuronal subpopulations in brain tissue. We have tackled this task by designing a solubilizing, hydrophilic polymer platform that carries a high-affinity ligand for a membrane protein marker of interest and a fluorescent VSD. Here, we disclose an improved design of polymer-supported probes for chemical, nongenetic targeting of voltage sensors to axons natively expressing the dopamine transporter in ex vivo mouse brain tissue. We first show that for negatively charged rhodol VSDs functioning on the photoinduced electron transfer principle, poly(ethylene glycol) as a carrier enables targeting with higher selectivity than the polysaccharide dextran in HEK cell culture. In the same experimental setting, we also demonstrate that incorporation of an azetidine ring into the rhodol chromophore substantially increases the brightness and voltage sensitivity of the respective VSD. We show that the superior properties of the optimized sensor are transferable to recording of electrically evoked activity from dopaminergic axons in mouse striatal slices after averaging of multiple trials. Finally, we suggest the next milestones for the field to achieve single-scan recordings with nongenetically targeted VSDs in native brain tissue.

Z-scan analysis and theoretical studies of dopamine under physiological conditions

Dopamine (DA) is a widely researched catecholamine best known for its role in motor, motivation, addiction, and reward. Disruption in dopamine homeostasis and signaling within the central nervous system (CNS) can lead to disorders such as attention deficit hyperactivity disorder (ADHD), schizophrenia, Parkinson's disease, and obsessive-compulsive disorder. In the periphery, circulating DA is stored in blood platelets, and its disruption correlates with pathological conditions such as head and neck paragangliomas, Huntington's chorea, and schizophrenia. Various methods to sensitively and selectively detect dopamine have been reported, but sparse attempts have been made to exploit its intrinsic properties. Previously, we have harnessed dopamine's natural mid-ultraviolet auto-fluorescence to carry out its label-free imaging in live brain tissues. Recently, we used the closed-aperture (CA) Z-scan method to provide the first line of evidence on the existence of dopamine nonlinearity. Here, we utilized this simple, sensitive, and straightforward CA Z-scan technique and coupled this with theoretical simulations to further investigate the nonlinear photophysical properties of DA under physiological conditions. Our combined approach revealed that the nonlinear property of dopamine is governed by the thermo-optical effects, and the CA Z-scan profiles can be modulated by parameters such as phase-shift, orders of absorption, and time dependency. Simple and physiologically relevant systems, such as the platelets, are amenable to Z-scan analysis, thereby empowering us to scrutinize in the future if nonlinearity and its alterations, if any, have a direct bearing on DA homeostasis and associated diseases.

Ultrafast Collective Excited-State Dynamics of a Virus-Supported Fluorophore Antenna

Radiation brightening was recently observed in a multifluorophore-conjugated brome mosaic virus (BMV) particle at room temperature under pulsed excitation. On the basis of its nonlinear dependence on the number of chromophores, the origins of the phenomenon were attributed to a collective relaxation. However, the mechanism remains unknown. We present ultrafast transient absorption and fluorescence spectroscopic studies which shed new light on the collective nature of the relaxation dynamics in such radiation-brightened, multifluorophore particles. Our findings indicate that the emission dynamics is consistent with a superradiance mechanism. The ratio between the rates of competing radiative and nonradiative relaxation pathways depends on the number of chromophores per virus. The findings suggest that small icosahedral virus shells provide a unique biological scaffold for developing nonclassical, deep subwavelength light sources and may open new avenues for the development of photonic probes for medical imaging applications.

A Model of Discovery: The Role of Imaging Established and Emerging Non-mammalian Models in Neuroscience

Rodents have been the dominant animal models in neurobiology and neurological disease research over the past 60 years. The prevalent use of rats and mice in neuroscience research has been driven by several key attributes including their organ physiology being more similar to humans, the availability of a broad variety of behavioral tests and genetic tools, and widely accessible reagents. However, despite the many advances in understanding neurobiology that have been achieved using rodent models, there remain key limitations in the questions that can be addressed in these and other mammalian models. In particular, in vivo imaging in mammals at the cell-resolution level remains technically difficult and demands large investments in time and cost. The simpler nervous systems of many non-mammalian models allow for precise mapping of circuits and even the whole brain with impressive subcellular resolution. The types of non-mammalian neuroscience models available spans vertebrates and non-vertebrates, so that an appropriate model for most cell biological questions in neurodegenerative disease likely exists. A push to diversify the models used in neuroscience research could help address current gaps in knowledge, complement existing rodent-based bodies of work, and bring new insight into our understanding of human disease. Moreover, there are inherent aspects of many non-mammalian models such as lifespan and tissue transparency that can make them specifically advantageous for neuroscience studies. Crispr/Cas9 gene editing and decreased cost of genome sequencing combined with advances in optical microscopy enhances the utility of new animal models to address specific questions. This review seeks to synthesize current knowledge of established and emerging non-mammalian model organisms with advances in cellular-resolution in vivo imaging techniques to suggest new approaches to understand neurodegeneration and neurobiological processes. We will summarize current tools and in vivo imaging approaches at the single cell scale that could help lead to increased consideration of non-mammalian models in neuroscience research.

Structural validation and assessment of AlphaFold2 predictions for centrosomal and centriolar proteins and their complexes

Obtaining the high-resolution structures of proteins and their complexes is a crucial aspect of understanding the mechanisms of life. Experimental structure determination methods are time-consuming, expensive and cannot keep pace with the growing number of protein sequences available through genomic DNA sequencing. Thus, the ability to accurately predict the structure of proteins from their sequence is a holy grail of structural and computational biology that would remove a bottleneck in our efforts to understand as well as rationally engineer living systems. Recent advances in protein structure prediction, in particular the breakthrough with the AI-based tool AlphaFold2 (AF2), hold promise for achieving this goal, but the practical utility of AF2 remains to be explored. Focusing on proteins with essential roles in centrosome and centriole biogenesis, we demonstrate the quality and usability of the AF2 prediction models and we show that they can provide important insights into the modular organization of two key players in this process, CEP192 and CEP44. Furthermore, we used the AF2 algorithm to elucidate and then experimentally validate previously unknown prime features in the structure of TTBK2 bound to CEP164, as well as the Chibby1-FAM92A complex for which no structural information was available to date. These findings have important implications in understanding the regulation and function of these complexes. Finally, we also discuss some practical limitations of AF2 and anticipate the implications for future research approaches in the centriole/centrosome field.

Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience

Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Orthogonalization of far-field detection in tapered optical fibers for depth-selective fiber photometry in brain tissue

The field of implantable optical neural interfaces has recently enabled the interrogation of neural circuitry with both cell-type specificity and spatial resolution in sub-cortical structures of the mouse brain. This generated the need to integrate multiple optical channels within the same implantable device, motivating the requirement of multiplexing and demultiplexing techniques. In this article, we present an orthogonalization method of the far-field space to introduce mode-division demultiplexing for collecting fluorescence from the implantable tapered optical fibers. This is achieved by exploiting the correlation between the transversal wavevector k t of the guided light and the position of the fluorescent sources along the implant, an intrinsic property of the taper waveguide. On these bases, we define a basis of orthogonal vectors in the Fourier space, each of which is associated with a depth along the taper, to simultaneously detect and demultiplex the collected signal when the probe is implanted in fixed mouse brain tissue. Our approach complements the existing multiplexing techniques used in silicon-based photonics probes with the advantage of a significant simplification of the probe itself.

From Synapses to Circuits, Astrocytes Regulate Behavior

Astrocytes are non-neuronal cells that regulate synapses, neuronal circuits, and behavior. Astrocytes ensheath neuronal synapses to form the tripartite synapse where astrocytes influence synapse formation, function, and plasticity. Beyond the synapse, recent research has revealed that astrocyte influences on the nervous system extend to the modulation of neuronal circuitry and behavior. Here we review recent findings on the active role of astrocytes in behavioral modulation with a focus on in vivo studies, primarily in mice. Using tools to acutely manipulate astrocytes, such as optogenetics or chemogenetics, studies reviewed here have demonstrated a causal role for astrocytes in sleep, memory, sensorimotor behaviors, feeding, fear, anxiety, and cognitive processes like attention and behavioral flexibility. Current tools and future directions for astrocyte-specific manipulation, including methods for probing astrocyte heterogeneity, are discussed. Understanding the contribution of astrocytes to neuronal circuit activity and organismal behavior will be critical toward understanding how nervous system function gives rise to behavior.

Application of optogenetics and in vivo imaging approaches for elucidating the neurobiology of addiction

The neurobiology of addiction has been an intense topic of investigation for more than 50 years. Over this time, technological innovation in methods for studying brain function rapidly progressed, leading to increasingly sophisticated experimental approaches. To understand how specific brain regions, cell types, and circuits are affected by drugs of abuse and drive behaviors characteristic of addiction, it is necessary both to observe and manipulate neural activity in addiction-related behavioral paradigms. In pursuit of this goal, there have been several key technological advancements in in vivo imaging and neural circuit modulation in recent years, which have shed light on the cellular and circuit mechanisms of addiction. Here we discuss some of these key technologies, including circuit modulation with optogenetics, in vivo imaging with miniaturized single-photon microscopy (miniscope) and fiber photometry, and how the application of these technologies has garnered novel insights into the neurobiology of addiction.

A novel red fluorescence dopamine biosensor selectively detects dopamine in the presence of norepinephrine in vitro

Dopamine (DA) and norepinephrine (NE) are pivotal neuromodulators that regulate a broad range of brain functions, often in concert. Despite their physiological importance, untangling the relationship between DA and NE in the fine control of output function is currently challenging, primarily due to a lack of techniques to allow the observation of spatiotemporal dynamics with sufficiently high selectivity. Although genetically encoded fluorescent biosensors have been developed to detect DA, their poor selectivity prevents distinguishing DA from NE. Here, we report the development of a red fluorescent genetically encoded GPCR (G protein-coupled receptor)-activation reporter for DA termed 'R-GenGAR-DA'. More specifically, a circular permutated red fluorescent protein (cpmApple) was replaced by the third intracellular loop of human DA receptor D1 (DRD1) followed by the screening of mutants within the linkers between DRD1 and cpmApple. We developed two variants: R-GenGAR-DA1.1, which brightened following DA stimulation, and R-GenGAR-DA1.2, which dimmed. R-GenGAR-DA1.2 demonstrated a reasonable dynamic range (ΔF/F0 = - 43%), DA affinity (EC50 = 0.92 µM) and high selectivity for DA over NE (66-fold) in HeLa cells. Taking advantage of the high selectivity of R-GenGAR-DA1.2, we monitored DA in presence of NE using dual-color fluorescence live imaging, combined with the green-NE biosensor GRABNE1m, which has high selectivity for NE over DA (> 350-fold) in HeLa cells and hippocampal neurons grown from primary culture. Thus, this is a first step toward the multiplex imaging of these neurotransmitters in, for example, freely moving animals, which will provide new opportunities to advance our understanding of the high spatiotemporal dynamics of DA and NE in normal and abnormal brain function.

Dopaminergic and Cholinergic Modulation of Large Scale Networks in silico Using Snudda

Neuromodulation is present throughout the nervous system and serves a critical role for circuit function and dynamics. The computational investigations of neuromodulation in large scale networks require supportive software platforms. Snudda is a software for the creation and simulation of large scale networks of detailed microcircuits consisting of multicompartmental neuron models. We have developed an extension to Snudda to incorporate neuromodulation in large scale simulations. The extended Snudda framework implements neuromodulation at the level of single cells incorporated into large-scale microcircuits. We also developed Neuromodcell, a software for optimizing neuromodulation in detailed multicompartmental neuron models. The software adds parameters within the models modulating the conductances of ion channels and ionotropic receptors. Bath application of neuromodulators is simulated and models which reproduce the experimentally measured effects are selected. In Snudda, we developed an extension to accommodate large scale simulations of neuromodulation. The simulator has two modes of simulation – denoted replay and adaptive. In the replay mode, transient levels of neuromodulators can be defined as a time-varying function which modulates the receptors and ion channels within the network in a cell-type specific manner. In the adaptive mode, spiking neuromodulatory neurons are connected via integrative modulating mechanisms to ion channels and receptors. Both modes of simulating neuromodulation allow for simultaneous modulation by several neuromodulators that can interact dynamically with each other. Here, we used the Neuromodcell software to simulate dopaminergic and muscarinic modulation of neurons from the striatum. We also demonstrate how to simulate different neuromodulatory states with dopamine and acetylcholine using Snudda. All software is freely available on Github, including tutorials on Neuromodcell and Snudda-neuromodulation.