Rationally Designed MicroRNA-Based Genetic Classifiers Target Specific Neurons in the Brain

Viral-based animal models in polyglutamine disorders

Polyglutamine disorders are a complex group of incurable neurodegenerative disorders caused by an abnormal expansion in the trinucleotide cytosine-adenine-guanine tract of the affected gene. To better understand these disorders, our dependence on animal models persists, primarily relying on transgenic models. In an effort to complement and deepen our knowledge, researchers have also developed animal models of polyglutamine disorders employing viral vectors. Viral vectors have been extensively used to deliver genes to the brain, not only for therapeutic purposes but also for the development of animal models, given their remarkable flexibility. In a time- and cost-effective manner, it is possible to use different transgenes, at varying doses, in diverse targeted tissues, at different ages, and in different species, to recreate polyglutamine pathology. This paper aims to showcase the utility of viral vectors in disease modelling, share essential considerations for developing animal models with viral vectors, and provide a comprehensive review of existing viral-based animal models for polyglutamine disorders.

Enhancer-AAVs allow genetic access to oligodendrocytes and diverse populations of astrocytes across species

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and our astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.

Overview of the role and action mechanism of microRNA-128 in viral infections

Recently in vivo and in vitro studies have provided evidence establishing the significance of microRNAs (miRNAs) in both physiological and pathological conditions. In this regard, the role of miRNA-128 (miR-128) in health and diseases has been found, and its critical regulatory role in the context of some viral diseases has been recently identified. For instance, it has been found that miR-128 can serve as an antiviral mediator and significantly limit the replication and dissemination of human immunodeficiency virus type 1 (HIV-1). Besides, it has been noted that poliovirus receptor-related 4 (PVRL4) is post-transcriptionally regulated by miR-128, representing possible miRNA targets that can modulate measles virus infection. Of note, the downregulation of seminal exosomes eca-miR-128 is associated with the long-term persistence of Equine arteritis virus (EAV) in the reproductive tract, and this particular miRNA is a putative regulator of chemokine ligand 16 (C-X-C motif) as determined by target prediction analysis. In this review, the latest information on the role and action mechanism of miR-128 in viral infections will be summarized and discussed in detail.

Characterizing microRNA-mediated modulation of gene expression noise and its effect on synthetic gene circuits

MicroRNAs (miRNAs) have been shown to modulate gene expression noise, but less is known about how miRNAs with different properties may regulate noise differently. Here, we investigate the role of competing RNAs and the composition of miRNA response elements (MREs) in modulating noise. We find that weak competing RNAs could introduce lower noise than strong competing RNAs. In comparison with a single MRE, both repetitive and composite MREs can reduce the noise at low expression, but repetitive MREs can elevate the noise remarkably at high expression. We further observed the behavior of a synthetic cell-type classifier with miRNAs as inputs and find that miRNAs and MREs that could introduce higher noise tend to enhance cell state transition. These results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and the utilization of miRNAs to modulate the behavior of synthetic gene circuits.

Enhancer viruses for combinatorial cell-subclass-specific labeling

Rapid cell type identification by new genomic single-cell analysis methods has not been met with efficient experimental access to these cell types. To facilitate access to specific neural populations in mouse cortex, we collected chromatin accessibility data from individual cells and identified enhancers specific for cell subclasses and types. When cloned into recombinant adeno-associated viruses (AAVs) and delivered to the brain, these enhancers drive transgene expression in specific cortical cell subclasses. We extensively characterized several enhancer AAVs to show that they label different projection neuron subclasses as well as a homologous neuron subclass in human cortical slices. We also show how coupling enhancer viruses expressing recombinases to a newly generated transgenic mouse, Ai213, enables strong labeling of three different neuronal classes/subclasses in the brain of a single transgenic animal. This approach combines unprecedented flexibility with specificity for investigation of cell types in the mouse brain and beyond.

Revisiting gene delivery to the brain: silencing and editing

Neurodegenerative disorders, ischemic brain diseases, and brain tumors are debilitating diseases that severely impact a person's life and could possibly lead to their demise if left untreated. Many of these diseases do not respond to small molecule therapeutics and have no effective long-term therapy. Gene therapy offers the promise of treatment or even a cure for both genetic and acquired brain diseases, mediated by either silencing or editing disease-specific genes. Indeed, in the last 5 years, significant progress has been made in the delivery of non-coding RNAs as well as gene-editing formulations to the brain. Unfortunately, the delivery is a major limiting factor for the success of gene therapies. Both viral and non-viral vectors have been used to deliver genetic information into a target cell, but they have limitations. Viral vectors provide excellent transduction efficiency but are associated with toxic effects and have limited packaging capacity; however, non-viral vectors are less toxic and show a high packaging capacity at the price of low transfection efficiency. Herein, we review the progress made in the field of brain gene therapy, particularly in the design of non-toxic and trackable non-viral vectors, capable of controlled release of genes in response to internal/external triggers, and in the delivery of formulations for gene editing. The application of these systems in the context of various brain diseases in pre-clinical and clinical tests will be discussed. Such promising approaches could potentially pave the way for clinical realization of brain gene therapies.

CaMKIIα-Positive Interneurons Identified via a microRNA-Based Viral Gene Targeting Strategy

Single-cell analysis is revealing increasing diversity in gene expression profiles among brain cells. Traditional promotor-based viral gene expression techniques, however, cannot capture the growing variety among single cells. We demonstrate a novel viral gene expression strategy to target cells with specific miRNA expression using miRNA-guided neuron tags (mAGNET). We designed mAGNET viral vectors containing a CaMKIIα promoter and microRNA-128 (miR-128) binding sites, and labeled CaMKIIα⁺ cells with naturally low expression of miR-128 (Lm128C cells) in male and female mice. Although CaMKIIα has traditionally been considered as an excitatory neuron marker, our single-cell sequencing results reveal that Lm128C cells are CaMKIIα⁺ inhibitory neurons of parvalbumin or somatostatin subtypes. Further evaluation of the physiological properties of Lm128C cell in brain slices showed that Lm128C cells exhibit elevated membrane excitability, with biophysical properties closely resembling those of fast-spiking interneurons, consistent with previous transcriptomic findings of miR-128 in regulating gene networks that govern membrane excitability. To further demonstrate the utility of this new viral expression strategy, we expressed GCaMP6f in Lm128C cells in the superficial layers of the motor cortex and performed in vivo calcium imaging in mice during locomotion. We found that Lm128C cells exhibit elevated calcium event rates and greater intrapopulation correlation than the overall CaMKIIα⁺ cells during movement. In summary, the miRNA-based viral gene targeting strategy described here allows us to label a sparse population of CaMKIIα⁺ interneurons for functional studies, providing new capabilities to investigate the relationship between gene expression and physiological properties in the brain.SIGNIFICANCE STATEMENT We report the discovery of a class of CaMKIIα⁺ cortical interneurons, labeled via a novel miRNA-based viral gene targeting strategy, combinatorial to traditional promoter-based strategies. The fact that we found a small, yet distinct, population of cortical inhibitory neurons that express CaMKIIα demonstrates that CaMKIIα is not as specific for excitatory neurons as commonly believed. As single-cell sequencing tools are providing increasing insights into the gene expression diversity of neurons, including miRNA profile data, we expect that the miRNA-based gene targeting strategy presented here can help delineate many neuron populations whose physiological properties can be readily related to the miRNA gene regulatory networks.

Molecular and DNA Artificial Neural Networks via Fractional Coding

This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using fractional coding, a simple molecular perceptron that computes sigmoid of scaled weighted sum of the inputs was presented where the inputs and the weights lie between [-1,1]. Even for computing the perceptron, the prior approach suffers from two major limitations. First, it cannot compute the sigmoid of the weighted sum, but only the sigmoid of the scaled weighted sum. Second, many machine learning applications require the coefficients to be arbitrarily positive and negative numbers that are not bounded between [-1,1]; such numbers cannot be handled by the prior perceptron using fractional coding. This paper makes four contributions. First molecular perceptrons that can handle arbitrary weights and can compute sigmoid of the weighted sums are presented. Thus, these molecular perceptrons are ideal for regression applications and multi-layer ANNs. A new molecular divider is introduced and is used to compute sigmoid(ax) where . Second, based on fractional coding, a molecular artificial neural network (ANN) with one hidden layer is presented. Third, a trained ANN classifier with one hidden layer from seizure prediction application from electroencephalogram is mapped to molecular reactions and DNA and their performances are presented. Fourth, molecular activation functions for rectified linear unit (ReLU) and softmax are also presented.

Viral vectors for neuronal cell type-specific visualization and manipulations

Characterizing neuronal cell types demands efficient strategies for specific labeling and manipulation of individual subtypes to dissect their connectivity and functions. Recombinant viral technology offers a powerful toolbox for targeted transgene expression in specific neuronal populations. In order to achieve cell type-specific targeting, exciting progress has been made to: alter viral tropisms, design rational delivery strategies, and drive selective expression patterns with engineered DNA sequences in viral genomes. For the latter case, emerging single-cell genomic analyses provide rich databases. In this review, we will summarize current status, and point out challenges, of using viral vectors for neuronal cell type-specific visualization and manipulations. With concerted efforts, progress will continue to be made toward developing viral vectors for the vast array of neuronal subtypes in the mammalian nervous system.

A MicroRNA-Based Gene-Targeting Tool for Virally Labeling Interneurons in the Rodent Cortex

More specific and broadly applicable viral gene-targeting tools for labeling neuron subtypes are needed to advance neuroscience research, especially in rodent transgenic disease models and genetically intractable species. Here, we develop a viral vector that restricts transgene expression to GABAergic interneurons in the rodent neocortex by exploiting endogenous microRNA regulation. Our interneuron-targeting, microRNA-guided neuron tag, "GABA mAGNET," achieves >95% interneuron selective labeling in the mouse cortex, including in a murine model of autism and also some preferential labeling of interneurons in the rat brain. We demonstrate an application of our GABA mAGNET by performing simultaneous, in vivo optogenetic control of two distinct neuron subtypes. This interneuron labeling tool highlights the potential of microRNA-based viral gene targeting to specific neuron subtypes.

A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity

MicroRNAs (miRNAs) regulate a majority of protein-coding genes, affecting nearly all biological pathways. However, the quantitative dimensions of miRNA-based regulation are not fully understood. In particular, the implications of miRNA target site location, composition rules for multiple target sites, and cooperativity limits for genes regulated by many miRNAs have not been quantitatively characterized. We explore these aspects of miRNA biology at a quantitative single-cell level using a library of 620 miRNA sensors and reporters that are regulated by many miRNA target sites at different positions. Interestingly, we find that miRNA target site sets within the same untranslated region exhibit combined miRNA activity described by an antagonistic relationship while those in separate untranslated regions show synergy. The resulting antagonistic/synergistic computational model enables the high-fidelity prediction of miRNA sensor activity for sensors containing many miRNA targets. These findings may help to accelerate the development of sophisticated sensors for clinical and research applications.

MicroRNA-Regulated Gene Delivery Systems for Research and Therapeutic Purposes

Targeted gene delivery relies on the ability to limit the expression of a transgene within a defined cell/tissue population. MicroRNAs represent a class of highly powerful and effective regulators of gene expression that act by binding to a specific sequence present in the corresponding messenger RNA. Involved in almost every aspect of cellular function, many miRNAs have been discovered with expression patterns specific to developmental stage, lineage, cell-type, or disease stage. Exploiting the binding sites of these miRNAs allows for construction of targeted gene delivery platforms with a diverse range of applications. Here, we summarize studies that have utilized miRNA-regulated systems to achieve targeted gene delivery for both research and therapeutic purposes. Additionally, we identify criteria that are important for the effectiveness of a particular miRNA for such applications and we also discuss factors that have to be taken into consideration when designing miRNA-regulated expression cassettes.

Computing Mathematical Functions using DNA via Fractional Coding

This paper discusses the implementation of mathematical functions such as exponentials, trigonometric functions, the sigmoid function and the perceptron function with molecular reactions in general, and DNA strand displacement reactions in particular. The molecular constructs for these functions are predicated on a novel representation for input and output values: a fractional encoding, in which values are represented by the relative concentrations of two molecular types, denoted as type-1 and type-0. This representation is inspired by a technique from digital electronic design, termed stochastic logic, in which values are represented by the probability of 1's in a stream of randomly generated 0's and 1's. Research in the electronic realm has shown that a variety of complex functions can be computed with remarkably simple circuitry with this stochastic approach. This paper demonstrates how stochastic electronic designs can be translated to molecular circuits. It presents molecular implementations of mathematical functions that are considerably more complex than any shown to date. All designs are validated using mass-action simulations of the chemical kinetics of DNA strand displacement reactions.

Exploring the Potential Application of Short Non-Coding RNA-Based Genetic Circuits in Chinese Hamster Ovary Cells

The majority of cell engineering for recombinant protein production to date has relied on traditional genetic engineering strategies, such as gene overexpression and gene knock-outs, to substantially improve the production capabilities of Chinese Hamster Ovary (CHO) cells. However, further improvements in cellular productivity or control over product quality is likely to require more sophisticated rational approaches to coordinate and balance cellular pathways. For these strategies to be implemented, novel molecular tools need to be developed to facilitate more refined control of gene expression. Multiple gene control strategies are developed over the last decades in the field of synthetic biology, including DNA and RNA-based systems, which allows tight and timely control over gene expression. microRNAs has received a lot of attention over the last decade in the CHO field and are used to engineer and improve CHO cells. In this review we focus on microRNA-based gene control systems and discuss their potential use as tools rather than targets in order to gain better control over gene expression.

Model-guided combinatorial optimization of complex synthetic gene networks

Constructing gene circuits that satisfy quantitative performance criteria has been a long-standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three-gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high-throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model-guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.

Cell-Specific Targeting of Genetically Encoded Tools for Neuroscience

Genetically encoded tools for visualizing and manipulating neurons in vivo have led to significant advances in neuroscience, in large part because of the ability to target expression to specific cell populations of interest. Current methods enable targeting based on marker gene expression, development, anatomical projection pattern, synaptic connectivity, and recent activity as well as combinations of these factors. Here, we review these methods, focusing on issues of practical implementation as well as areas for future improvement.

MicroRNA-regulated viral vectors for gene therapy

Safe and effective gene therapy approaches require targeted tissue-specific transfer of a therapeutic transgene. Besides traditional approaches, such as transcriptional and transductional targeting, microRNA-dependent post-transcriptional suppression of transgene expression has been emerging as powerful new technology to increase the specificity of vector-mediated transgene expression. MicroRNAs are small non-coding RNAs and often expressed in a tissue-, lineage-, activation- or differentiation-specific pattern. They typically regulate gene expression by binding to imperfectly complementary sequences in the 3' untranslated region (UTR) of the mRNA. To control exogenous transgene expression, tandem repeats of artificial microRNA target sites are usually incorporated into the 3' UTR of the transgene expression cassette, leading to subsequent degradation of transgene mRNA in cells expressing the corresponding microRNA. This targeting strategy, first shown for lentiviral vectors in antigen presenting cells, has now been used for tissue-specific expression of vector-encoded therapeutic transgenes, to reduce immune response against the transgene, to control virus tropism for oncolytic virotherapy, to increase safety of live attenuated virus vaccines and to identify and select cell subsets for pluripotent stem cell therapies, respectively. This review provides an introduction into the technical mechanism underlying microRNA-regulation, highlights new developments in this field and gives an overview of applications of microRNA-regulated viral vectors for cardiac, suicide gene cancer and hematopoietic stem cell therapy, as well as for treatment of neurological and eye diseases.

Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing

Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.

Strategies for targeting primate neural circuits with viral vectors

Understanding how the brain works requires understanding how different types of neurons contribute to circuit function and organism behavior. Progress on this front has been accelerated by optogenetics and chemogenetics, which provide an unprecedented level of control over distinct neuronal types in small animals. In primates, however, targeting specific types of neurons with these tools remains challenging. In this review, we discuss existing and emerging strategies for directing genetic manipulations to targeted neurons in the adult primate central nervous system. We review the literature on viral vectors for gene delivery to neurons, focusing on adeno-associated viral vectors and lentiviral vectors, their tropism for different cell types, and prospects for new variants with improved efficacy and selectivity. We discuss two projection targeting approaches for probing neural circuits: anterograde projection targeting and retrograde transport of viral vectors. We conclude with an analysis of cell type-specific promoters and other nucleotide sequences that can be used in viral vectors to target neuronal types at the transcriptional level.

An integrative approach for analyzing hundreds of neurons in task performing mice using wide-field calcium imaging

Advances in neurotechnology have been integral to the investigation of neural circuit function in systems neuroscience. Recent improvements in high performance fluorescent sensors and scientific CMOS cameras enables optical imaging of neural networks at a much larger scale. While exciting technical advances demonstrate the potential of this technique, further improvement in data acquisition and analysis, especially those that allow effective processing of increasingly larger datasets, would greatly promote the application of optical imaging in systems neuroscience. Here we demonstrate the ability of wide-field imaging to capture the concurrent dynamic activity from hundreds to thousands of neurons over millimeters of brain tissue in behaving mice. This system allows the visualization of morphological details at a higher spatial resolution than has been previously achieved using similar functional imaging modalities. To analyze the expansive data sets, we developed software to facilitate rapid downstream data processing. Using this system, we show that a large fraction of anatomically distinct hippocampal neurons respond to discrete environmental stimuli associated with classical conditioning, and that the observed temporal dynamics of transient calcium signals are sufficient for exploring certain spatiotemporal features of large neural networks.