Sparse Labeling and Neural Tracing in Brain Circuits by STARS Strategy: Revealing Morphological Development of Type II Spiral Ganglion Neurons

Evaluation of a library of loxP variants with a wide range of recombination efficiencies by Cre

Sparse labeling of individual cells is an important approach in neuroscience and many other fields of research. Various methods have been developed to sparsely label only a small population of cells; however, there is no simple and reproducible strategy for managing the probability of sparse labeling at desired levels. Here, we aimed to develop a novel methodology based on the Cre-lox system to regulate sparseness at desired levels, and we purely analyzed cleavage efficiencies of loxP mutants by Cre. We hypothesized that mutations in the loxP sequence reduce the recognition efficiency by Cre, which enables the regulation of the sparseness level of gene expression. In this research, we mutagenized the loxP sequence and analyzed a library of loxP variants. We evaluated more than 1000 mutant loxP sequences, including mutants with reduced excision efficiencies by Cre ranging from 0.51% to 59%. This result suggests that these mutant loxP sequences can be useful in regulating the sparseness of genetic labeling at desired levels.

Smart imaging to empower brain-wide neuroscience at single-cell levels

A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.

Experience-dependent myelination following stress is mediated by the neuropeptide dynorphin

Emerging evidence implicates experience-dependent myelination in learning and memory. However, the specific signals underlying this process remain unresolved. We demonstrate that the neuropeptide dynorphin, which is released from neurons upon high levels of activity, promotes experience-dependent myelination. Following forced swim stress, an experience that induces striatal dynorphin release, we observe increased striatal oligodendrocyte precursor cell (OPC) differentiation and myelination, which is abolished by deleting dynorphin or blocking its endogenous receptor, kappa opioid receptor (KOR). We find that dynorphin also promotes developmental OPC differentiation and myelination and demonstrate that this effect requires KOR expression specifically in OPCs. We characterize dynorphin-expressing neurons and use genetic sparse labeling to trace their axonal projections. Surprisingly, we find that they are unmyelinated normally and following forced swim stress. We propose a new model whereby experience-dependent and developmental myelination is mediated by unmyelinated, neuropeptide-expressing neurons that promote OPC differentiation for the myelination of neighboring axons.

Brainwide Genetic Sparse Cell Labeling to Illuminate the Morphology of Neurons and Glia with Cre-Dependent MORF Mice

Cajal recognized that the elaborate shape of neurons is fundamental to their function in the brain. However, there are no simple and generalizable genetic methods to study neuronal or glial cell morphology in the mammalian brain. Here, we describe four mouse lines conferring Cre-dependent sparse cell labeling based on mononucleotide repeat frameshift (MORF) as a stochastic translational switch. Notably, the optimized MORF3 mice, with a membrane-bound multivalent immunoreporter, confer Cre-dependent sparse and bright labeling of thousands of neurons, astrocytes, or microglia in each brain, revealing their intricate morphologies. MORF3 mice are compatible with imaging in tissue-cleared thick brain sections and with immuno-EM. An analysis of 151 MORF3-labeled developing retinal horizontal cells reveals novel morphological cell clusters and axonal maturation patterns. Our study demonstrates a conceptually novel, simple, generalizable, and scalable mouse genetic solution to sparsely label and illuminate the morphology of genetically defined neurons and glia in the mammalian brain.