Transcriptome analysis in primary neural stem cells using a tag cDNA amplification method

BACKGROUND: Neural stem cells (NSCs) can be isolated from the adult mammalian brain and expanded in culture, in the form of cellular aggregates called neurospheres. Neurospheres provide an in vitro model for studying NSC behaviour and give information on the factors and mechanisms that govern their proliferation and differentiation. They are also a promising source for cell replacement therapies of the central nervous system. Neurospheres are complex structures consisting of several cell types of varying degrees of differentiation. One way of characterising neurospheres is to analyse their gene expression profiles. The value of such studies is however uncertain since they are heterogeneous structures and different populations of neurospheres may vary significantly in their gene expression. RESULTS: To address this issue, we have used cDNA microarrays and a recently reported tag cDNA amplification method to analyse the gene expression profiles of neurospheres originating from separate isolations of the lateral ventricle wall of adult mice and passaged to varying degrees. Separate isolations as well as consecutive passages yield a high variability in gene expression while parallel cultures yield the lowest variability. CONCLUSIONS: We demonstrate a low technical amplification variability using the employed amplification strategy and conclude that neurospheres from the same isolation and passage are sufficiently similar to be used for comparative gene expression analysis

Dixdc1 Is a Critical Regulator of DISC1 and Embryonic Cortical Development

The psychiatric illness risk gene Disrupted in Schizophrenia-1 (DISC1) plays an important role in brain development; however, it is unclear how DISC1 is regulated during cortical development. Here, we report that DISC1 is regulated during embryonic neural progenitor proliferation and neuronal migration through an interaction with DIX domain containing-1 (Dixdc1), the third mammalian gene discovered to contain a Disheveled-Axin (DIX) domain. We determined that Dixdc1 functionally interacts with DISC1 to regulate neural progenitor proliferation by co-modulating Wnt-GSK3β/β-catenin signaling. However, DISC1 and Dixdc1 do not regulate migration via this pathway. During neuronal migration, we discovered that phosphorylation of Dixdc1 by cyclin-dependent kinase 5 (Cdk5) facilitates its interaction with the DISC1-binding partner Ndel1. Furthermore, Dixdc1 phosphorylation and its interaction with DISC1/Ndel1 in vivo is required for neuronal migration. Together, these data reveal that Dixdc1 integrates DISC1 into Wnt-GSK3β/β-catenin-dependent and -independent signaling pathways during cortical development and further delineate how DISC1 contributes to neuropsychiatric disorders.Human Frontier Science Program (Strasbourg, France) (Long-Term Fellowship)Natural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship)National Alliance for Research on Schizophrenia and Depression (U.S.) (Young Investigator Award)National Institutes of Health (U.S.) (Grant NS37007

A Whole-Brain Atlas of Inputs to Serotonergic Neurons of the Dorsal and Median Raphe Nuclei

SummaryThe serotonin system is proposed to regulate physiology and behavior and to underlie mood disorders; nevertheless, the circuitry controlling serotonergic neurons remains uncharacterized. We therefore generated a comprehensive whole-brain atlas defining the monosynaptic inputs onto forebrain-projecting serotonergic neurons of dorsal versus median raphe based on a genetically restricted transsynaptic retrograde tracing strategy. We identified discrete inputs onto serotonergic neurons from forebrain and brainstem neurons, with specific inputs from hypothalamus, cortex, basal ganglia, and midbrain, displaying a greater than anticipated complexity and diversity in cell-type-specific connectivity. We identified and functionally confirmed monosynaptic glutamatergic inputs from prefrontal cortex and lateral habenula onto serotonergic neurons as well as a direct GABAergic input from striatal projection neurons. In summary, our findings emphasize the role of hyperdirect inputs to serotonergic neurons. Cell-type-specific classification of connectivity patterns will allow for further functional analysis of the diverse but specific inputs that control serotonergic neurons during behavior

Targeted optogenetic stimulation and recording of neurons in vivo using cell-type-specific expression of Channelrhodopsin-2

A major long-term goal of systems neuroscience is to identify the different roles of neural subtypes in brain circuit function. The ability to causally manipulate selective cell types is critical to meeting this goal. This protocol describes techniques for optically stimulating specific populations of excitatory neurons and inhibitory interneurons in vivo in combination with electrophysiology. Cell type selectivity is obtained using Cre-dependent expression of the light-activated channel Channelrhodopsin-2. We also describe approaches for minimizing optical interference with simultaneous extracellular and intracellular recording. These optogenetic techniques provide a spatially and temporally precise means of studying neural activity in the intact brain and allow a detailed examination of the effect of evoked activity on the surrounding local neural network. Injection of viral vectors requires 30–45 min, and in vivo electrophysiology with optogenetic stimulation requires 1–4 h.National Institutes of Health (U.S.)National Science Foundation (U.S.)Simons FoundationNational Institutes of Health (U.S.). Pioneer AwardNational Eye Institue (K99 Award)Knut and Alice Wallenberg Foundation (Postdoctoral Fellowship)Brain & Behavior Research Foundation. Young Investigator AwardThomas F. Peterse

Replicability of spatial gene expression atlas data from the adult mouse brain

Background Spatial gene expression is particularly interesting in the mammalian brain, with the potential to serve as a link between many data types. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain sub-divisions, between the Allen Institute’s in situ hybridization data from the adult mouse brain (ABA) and a similar dataset collected using Spatial Transcriptomics (ST). With the advent of tractable spatial techniques, for the first time we are able to benchmark the Allen Institute’s whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. Results We use LASSO, linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen reference atlas labels are classifiable using transcription, but that performance is higher in the ABA than ST. Further, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bi-directionally. Finally, while an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. Conclusions In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability

Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain.

High-throughput, spatially resolved gene expression techniques are poised to be transformative across biology by overcoming a central limitation in single-cell biology: the lack of information on relationships that organize the cells into the functional groupings characteristic of tissues in complex multicellular organisms. Spatial expression is particularly interesting in the mammalian brain, which has a highly defined structure, strong spatial constraint in its organization, and detailed multimodal phenotypes for cells and ensembles of cells that can be linked to mesoscale properties such as projection patterns, and from there, to circuits generating behavior. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain subdivisions, between the Allen Institute's in situ hybridization data from the adult mouse brain (Allen Brain Atlas (ABA)) and a similar dataset collected using spatial transcriptomics (ST). With the advent of tractable spatial techniques, for the first time, we are able to benchmark the Allen Institute's whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. We use regularized linear regression (LASSO), linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen Reference Atlas labels are classifiable using transcription in both data sets, but that performance is higher in the ABA than in ST. Furthermore, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bidirectionally. While an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability ultimately providing a valuable reference set for understanding the cell biology of the brain

Adult trkB signaling in parvalbumin interneurons is essential to prefrontal network dynamics

Inhibitory interneurons expressing parvalbumin (PV) are central to cortical network dynamics, generation of c oscillations, and cognition. Dysfunction of PV interneurons disrupts cortical information processing and cognitive behavior. Brain-derived neurotrophic factor (BDNF)/tyrosine receptor kinase B (trkB) signaling regulates the maturation of cortical PV interneurons but is also implicated in their adult multidimensional functions. Using a novel viral strategy for cell-type-specific and spatially restricted expression of a dominant-negative trkB (trkB.DN), we show that BDNF/trkB signaling is essential to the integrity and maintenance of prefrontal PV interneurons in adult male and female mice. Reduced BDNF/trkB signaling in PV interneurons in the medial prefrontal cortex (mPFC) resulted in deficient PV inhibition and increased baseline local field potential (LFP) activity in a broad frequency band. The altered network activity was particularly pronounced during increased activation of the prefrontal network and was associated with changed dynamics of local excitatory neurons, as well as decreased modulation of the LFP, abnormalities that appeared to generalize across stimuli and brain states. In addition, our findings link reduced BDNF/trkB signaling in prefrontal PV interneurons to increased aggression. Together our investigations demonstrate that BDNF/trkB signaling in PV interneurons in the adult mPFC is essential to local network dynamics and cognitive behavior. Our data provide direct support for the suggested association between decreased trkB signaling, deficient PV inhibition, and altered prefrontal circuitry.ERCSwedish Research CouncilCAPES-STINT Program GrantKarolinska InstitutetKnut and Alice Wallenberg FoundationSTINT Program Joint Brazilian-Swedish Research Collaboration GrantPublishe

Driving fast-spiking cells induces gamma rhythm and controls sensory responses,”

Cortical gamma oscillations (20280 Hz) predict increases in focused attention, and failure in gamma regulation is a hallmark of neurological and psychiatric disease. Current theory predicts that gamma oscillations are generated by synchronous activity of fast-spiking inhibitory interneurons, with the resulting rhythmic inhibition producing neural ensemble synchrony by generating a narrow window for effective excitation. We causally tested these hypotheses in barrel cortex in vivo by targeting optogenetic manipulation selectively to fast-spiking interneurons. Here we show that light-driven activation of fast-spiking interneurons at varied frequencies (82200 Hz) selectively amplifies gamma oscillations. In contrast, pyramidal neuron activation amplifies only lower frequency oscillations, a cell-type-specific double dissociation. We found that the timing of a sensory input relative to a gamma cycle determined the amplitude and precision of evoked responses. Our data directly support the fast-spiking-gamma hypothesis and provide the first causal evidence that distinct network activity states can be induced in vivo by cell-type-specific activation. Brain states characterized by rhythmic electrophysiological activity have been studied intensively for more than 80 years Cell-type-specific expression of channelrhodopsin-2 To test directly the hypothesis that FS interneuron activity in an in vivo cortical circuit is sufficient to induce gamma oscillations, we used the light-sensitive bacteriorhodopsin Chlamydomonas reinhardtii channelrhodopsin-2 (ChR2), a cation channel activated by ,470 nm blue ligh

Spinal Cord Injury Reveals Multilineage Differentiation of Ependymal Cells

Spinal cord injury often results in permanent functional impairment. Neural stem cells present in the adult spinal cord can be expanded in vitro and improve recovery when transplanted to the injured spinal cord, demonstrating the presence of cells that can promote regeneration but that normally fail to do so efficiently. Using genetic fate mapping, we show that close to all in vitro neural stem cell potential in the adult spinal cord resides within the population of ependymal cells lining the central canal. These cells are recruited by spinal cord injury and produce not only scar-forming glial cells, but also, to a lesser degree, oligodendrocytes. Modulating the fate of ependymal progeny after spinal cord injury may offer an alternative to cell transplantation for cell replacement therapies in spinal cord injury