A high-density narrow-field inhibitory retinal interneuron with direct coupling to Müller glia.

Amacrine cells are interneurons composing the most diverse cell class in the mammalian retina. They help encode visual features such as edges or directed motion by mediating excitatory and inhibitory interactions between input (i.e. bipolar) and output (i.e. ganglion) neurons in the inner plexiform layer (IPL). Like other brain regions, the retina also contains glial cells that contribute to neurotransmitter uptake, metabolic regulation and neurovascular control. Here, we report that in mouse retina (of either sex), an abundant, though previously unstudied inhibitory amacrine cell is coupled directly to Müller glia. Electron microscopic reconstructions of this amacrine type revealed chemical synapses with known retinal cell types and extensive associations with Müller glia, the processes of which often completely ensheathe the neurites of this amacrine cell. Microinjecting small tracer molecules into the somas of these amacrine cells led to selective labelling of nearby Müller glia, leading us to suggest the name "Müller glia-coupled amacrine cell," or MAC. Our data also indicate that MACs release glycine at conventional chemical synapses, and viral retrograde transsynaptic tracing from the dorsal lateral geniculate nucleus (dLGN) showed selective connections between MACs and a subpopulation of RGC types. Visually-evoked responses revealed a strong preference for light increments; these "ON" responses were primarily mediated by excitatory chemical synaptic input and direct electrical coupling with other cells. This initial characterization of the MAC provides the first evidence for neuron-glia coupling in the mammalian retina and identifies the MAC as a potential link between inhibitory processing and glial function.Significance Statement:Gap junctions between pairs of neurons or glial cells are commonly found throughout the nervous system and play multiple roles, including electrical coupling and metabolic exchange. In contrast, gap junctions between neurons and glia cells have rarely been reported and are poorly understood. Here we report the first evidence for neuron-glia coupling in the mammalian retina, specifically between an abundant (but previously unstudied) inhibitory interneuron and Müller glia. Moreover, viral tracing, optogenetics and serial electron microscopy provide new information about the neuron's synaptic partners and physiological responses.

Cis-regulatory dissection of cone development reveals a broad role for Otx2 and Oc transcription factors.

The vertebrate retina is generated by retinal progenitor cells (RPCs), which produce >100 cell types. Although some RPCs produce many cell types, other RPCs produce restricted types of daughter cells, such as a cone photoreceptor and a horizontal cell (HC). We used genome-wide assays of chromatin structure to compare the profiles of a restricted cone/HC RPC and those of other RPCs in chicks. These data nominated regions of regulatory activity, which were tested in tissue, leading to the identification of many cis-regulatory modules (CRMs) active in cone/HC RPCs and developing cones. Two transcription factors, Otx2 and Oc1, were found to bind to many of these CRMs, including those near genes important for cone development and function, and their binding sites were required for activity. We also found that Otx2 has a predicted autoregulatory CRM. These results suggest that Otx2, Oc1 and possibly other Onecut proteins have a broad role in coordinating cone development and function. The many newly discovered CRMs for cones are potentially useful reagents for gene therapy of cone diseases.

High-throughput dense reconstruction of cell lineages.

The first meeting exclusively dedicated to the 'High-throughput dense reconstruction of cell lineages' took place at Janelia Research Campus (Howard Hughes Medical Institute) from 14 to 18 April 2019. Organized by Tzumin Lee, Connie Cepko, Jorge Garcia-Marques and Isabel Espinosa-Medina, this meeting echoed the recent eruption of new tools that allow the reconstruction of lineages based on the phylogenetic analysis of DNA mutations induced during development. Combined with single-cell RNA sequencing, these tools promise to solve the lineage of complex model organisms at single-cell resolution. Here, we compile the conference consensus on the technological and computational challenges emerging from the use of the new strategies, as well as potential solutions.

Adeno-Associated Virus Technologies and Methods for Targeted Neuronal Manipulation.

Cell-type-specific expression of molecular tools and sensors is critical to construct circuit diagrams and to investigate the activity and function of neurons within the nervous system. Strategies for targeted manipulation include combinations of classical genetic tools such as Cre/loxP and Flp/FRT, use of cis-regulatory elements, targeted knock-in transgenic mice, and gene delivery by AAV and other viral vectors. The combination of these complex technologies with the goal of precise neuronal targeting is a challenge in the lab. This report will discuss the theoretical and practical aspects of combining current technologies and establish best practices for achieving targeted manipulation of specific cell types. Novel applications and tools, as well as areas for development, will be envisioned and discussed.

Epigenomics of Retinal Development in Mice and Humans.

In this issue of Neuron, Aldiri et al. (2017) present an analysis of epigenetic changes during retinal development, and use these data to probe reprogramming of retinal iPSC cells, as well as the origin of retinoblastoma cells.

The origin and evolution of cell types.

Cell types are the basic building blocks of multicellular organisms and are extensively diversified in animals. Despite recent advances in characterizing cell types, classification schemes remain ambiguous. We propose an evolutionary definition of a cell type that allows cell types to be delineated and compared within and between species. Key to cell type identity are evolutionary changes in the 'core regulatory complex' (CoRC) of transcription factors, that make emergent sister cell types distinct, enable their independent evolution and regulate cell type-specific traits termed apomeres. We discuss the distinction between developmental and evolutionary lineages, and present a roadmap for future research.

Lassa-vesicular stomatitis chimeric virus safely destroys brain tumors.

UNLABELLED: High-grade tumors in the brain are among the deadliest of cancers. Here, we took a promising oncolytic virus, vesicular stomatitis virus (VSV), and tested the hypothesis that the neurotoxicity associated with the virus could be eliminated without blocking its oncolytic potential in the brain by replacing the neurotropic VSV glycoprotein with the glycoprotein from one of five different viruses, including Ebola virus, Marburg virus, lymphocytic choriomeningitis virus (LCMV), rabies virus, and Lassa virus. Based on in vitro infections of normal and tumor cells, we selected two viruses to test in vivo. Wild-type VSV was lethal when injected directly into the brain. In contrast, a novel chimeric virus (VSV-LASV-GPC) containing genes from both the Lassa virus glycoprotein precursor (GPC) and VSV showed no adverse actions within or outside the brain and targeted and completely destroyed brain cancer, including high-grade glioblastoma and melanoma, even in metastatic cancer models. When mice had two brain tumors, intratumoral VSV-LASV-GPC injection in one tumor (glioma or melanoma) led to complete tumor destruction; importantly, the virus moved contralaterally within the brain to selectively infect the second noninjected tumor. A chimeric virus combining VSV genes with the gene coding for the Ebola virus glycoprotein was safe in the brain and also selectively targeted brain tumors but was substantially less effective in destroying brain tumors and prolonging survival of tumor-bearing mice. A tropism for multiple cancer types combined with an exquisite tumor specificity opens a new door to widespread application of VSV-LASV-GPC as a safe and efficacious oncolytic chimeric virus within the brain. IMPORTANCE: Many viruses have been tested for their ability to target and kill cancer cells. Vesicular stomatitis virus (VSV) has shown substantial promise, but a key problem is that if it enters the brain, it can generate adverse neurologic consequences, including death. We tested a series of chimeric viruses containing genes coding for VSV, together with a gene coding for the glycoprotein from other viruses, including Ebola virus, Lassa virus, LCMV, rabies virus, and Marburg virus, which was substituted for the VSV glycoprotein gene. Ebola and Lassa chimeric viruses were safe in the brain and targeted brain tumors. Lassa-VSV was particularly effective, showed no adverse side effects even when injected directly into the brain, and targeted and destroyed two different types of deadly brain cancer, including glioblastoma and melanoma.

Intrinsically different retinal progenitor cells produce specific types of progeny.

Lineage studies conducted in the retina more than 25 years ago demonstrated the multipotency of retinal progenitor cells (RPCs). The number and types of cells produced by individual RPCs, even from a single time point in development, were found to be highly variable. This raised the question of whether this variability was due to intrinsic differences among RPCs or to extrinsic and/or stochastic effects on equivalent RPCs or their progeny. Newer lineage studies that have made use of molecular markers of RPCs, retrovirus-mediated lineage analyses of specific RPCs and live imaging have begun to provide answers to this question. RPCs that produce two postmitotic daughter cells - that is, terminally dividing RPCs - have been the most well characterized RPCs to date, and have been shown to produce specific types of daughter cells. In addition, recent studies have begun to shed light on the mechanisms that drive the temporal order in which retinal cells are born.

Validation of oligoarrays for quantitative exploration of the transcriptome.

BACKGROUND: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5.105. Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE. RESULTS: A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8.105 (oligoarrays), 1.1.105 (MPSS) and 7.6.104 (SAGE), whereas the corresponding sum for all detected transcripts was 1.1.106 (oligoarrays), 2.8.105 (MPSS) and 3.8.105 (SAGE). CONCLUSION: The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5.105 suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands.

Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates.

BACKGROUND: High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). RESULTS: The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. CONCLUSION: Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies.

Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms.

Clustering analysis of SAGE data using a Poisson approach.

Serial analysis of gene expression (SAGE) data have been poorly exploited by clustering analysis owing to the lack of appropriate statistical methods that consider their specific properties. We modeled SAGE data by Poisson statistics and developed two Poisson-based distances. Their application to simulated and experimental mouse retina data show that the Poisson-based distances are more appropriate and reliable for analyzing SAGE data compared to other commonly used distances or similarity measures such as Pearson correlation or Euclidean distance.