Combinatorial and Chemotopic Odorant Coding in the Zebrafish Olfactory Bulb Visualized by Optical Imaging

AbstractOdors are thought to be represented by a distributed code across the glomerular modules in the olfactory bulb (OB). Here, we optically imaged presynaptic activity in glomerular modules of the zebrafish OB induced by a class of natural odorants (amino acids [AAs]) after labeling of primary afferents with a calcium-sensitive dye. AAs induce complex combinatorial patterns of active glomerular modules that are unique for different stimuli and concentrations. Quantitative analysis shows that defined molecular features of stimuli are correlated with activity in spatially confined groups of glomerular modules. These results provide direct evidence that identity and concentration of odorants are encoded by glomerular activity patterns and reveal a coarse chemotopic organization of the array of glomerular modules

Circuit Neuroscience in Zebrafish

A central goal of modern neuroscience is to obtain a mechanistic understanding of higher brain functions under healthy and diseased conditions. Addressing this challenge requires rigorous experimental and theoretical analysis of neuronal circuits. Recent advances in optogenetics, high-resolution in vivo imaging, and reconstructions of synaptic wiring diagrams have created new opportunities to achieve this goal. To fully harness these methods, model organisms should allow for a combination of genetic and neurophysiological approaches in vivo. Moreover, the brain should be small in terms of neuron numbers and physical size. A promising vertebrate organism is the zebrafish because it is small, it is transparent at larval stages and it offers a wide range of genetic tools and advantages for neurophysiological approaches. Recent studies have highlighted the potential of zebrafish for exhaustive measurements of neuronal activity patterns, for manipulations of defined cell types in vivo and for studies of causal relationships between circuit function and behavior. In this article, we summarize background information on the zebrafish as a model in modern systems neuroscience and discuss recent results

Topological Reorganization of Odor Representations in the Olfactory Bulb

Odors are initially represented in the olfactory bulb (OB) by patterns of sensory input across the array of glomeruli. Although activated glomeruli are often widely distributed, glomeruli responding to stimuli sharing molecular features tend to be loosely clustered and thus establish a fractured chemotopic map. Neuronal circuits in the OB transform glomerular patterns of sensory input into spatiotemporal patterns of output activity and thereby extract information about a stimulus. It is, however, unknown whether the chemotopic spatial organization of glomerular inputs is maintained during these computations. To explore this issue, we measured spatiotemporal patterns of odor-evoked activity across thousands of individual neurons in the zebrafish OB by temporally deconvolved two-photon Ca2+ imaging. Mitral cells and interneurons were distinguished by transgenic markers and exhibited different response selectivities. Shortly after response onset, activity patterns exhibited foci of activity associated with certain chemical features throughout all layers. During the subsequent few hundred milliseconds, however, MC activity was locally sparsened within the initial foci in an odor-specific manner. As a consequence, chemotopic maps disappeared and activity patterns became more informative about precise odor identity. Hence, chemotopic maps of glomerular input activity are initially transmitted to OB outputs, but not maintained during pattern processing. Nevertheless, transient chemotopic maps may support neuronal computations by establishing important synaptic interactions within the circuit. These results provide insights into the functional topology of neural activity patterns and its potential role in circuit function

Fast Homogeneous En Bloc Staining of Large Tissue Samples for Volume Electron Microscopy

Fixation and staining of large tissue samples are critical for the acquisition of volumetric electron microscopic image datasets and the subsequent reconstruction of neuronal circuits. Efficient protocols exist for the staining of small samples, but uniform contrast is often difficult to achieve when the sample diameter exceeds a few hundred micrometers. Recently, a protocol (BROPA, brain-wide reduced-osmium staining with pyrogallol-mediated amplification) was developed that achieves homogeneous staining of the entire mouse brain but requires very long sample preparation times. By exploring modifications of this protocol we developed a substantially faster procedure, fBROPA, that allows for reliable high-quality staining of tissue blocks on the millimeter scale. Modifications of the original BROPA protocol include drastically reduced incubation times and a lead aspartate incubation to increase sample conductivity. Using this procedure, whole brains from adult zebrafish were stained within 4 days. Homogenous high-contrast staining was achieved throughout the brain. High-quality image stacks with voxel sizes of 10 × 10 × 25 nm3 were obtained by serial block-face imaging using an electron dose of ~15 e−/nm2. No obvious reduction in staining quality was observed in comparison to smaller samples stained by other state-of-the-art procedures. Furthermore, high-quality images with minimal charging artifacts were obtained from non-neural tissues with low membrane density. fBROPA is therefore likely to be a versatile and efficient sample preparation protocol for a wide range of applications in volume electron microscopy

Multiplexing using synchrony in the zebrafish olfactory bulb

In the olfactory bulb (OB) of zebrafish and other species, odors evoke fast oscillatory population activity and specific firing rate patterns across mitral cells (MCs). This activity evolves over a few hundred milliseconds from the onset of the odor stimulus. Action potentials of odor-specific MC subsets phase-lock to the oscillation, defining small and distributed ensembles within the MC population output. We found that oscillatory field potentials in the zebrafish OB propagate across the OB in waves. Phase-locked MC action potentials, however, were synchronized without a time lag. Firing rate patterns across MCs analyzed with low temporal resolution were informative about odor identity. When the sensitivity for phase-locked spiking was increased, activity patterns became progressively more informative about odor category. Hence, information about complementary stimulus features is conveyed simultaneously by the same population of neurons and can be retrieved selectively by biologically plausible mechanisms, indicating that seemingly alternative coding strategies operating on different time scales may coexist

Practical IR extinction coefficients for water in commercial glasses determined by nuclear reaction analysis

For a number of commercial glasses with different chemical compositions the water contents were determined by nuclear reaction analysis (NRA) measurements. These results were used to deduce practical extinction coefficients by comparison with the measured IR absorbance values at 2.8 μm. For aluminosilicate and television glasses the practical molar extinction coefficients are given for the first time. Practical extinction coefficients are dependent upon glass composition. With increasing basicity of the glasses studied they decrease from 182 to 24 l/(mol cm)

Illuminating Vertebrate Olfactory Processing

The olfactory system encodes information about molecules by spatiotemporal patterns of activity across distributed populations of neurons and extracts information from these patterns to control specific behaviors. Recent studies used in vivo recordings, optogenetics, and other methods to analyze the mechanisms by which odor information is encoded and processed in the olfactory system, the functional connectivity within and between olfactory brain areas, and the impact of spatiotemporal patterning of neuronal activity on higher-order neurons and behavioral outputs. The results give rise to a faceted picture of olfactory processing and provide insights into fundamental mechanisms underlying neuronal computations. This review focuses on some of this work presented in a Mini-Symposium at the Annual Meeting of the Society for Neuroscience in 2012.Molecular and Cellular Biolog

Immunophenotyping and Transcriptomic Outcomes in PDX-Derived TNBC Tissue

Cancer tissue functions as an ecosystem of a diverse set of cells that interact in a complex tumor microenvironment (TME). Genomic tools applied to biopsies in bulk fail to account for this tumor heterogeneity while single cell imaging methods limit the number of cells which can be assessed or are very resource intensive. The current study presents methods based on flow cytometric analysis and cell sorting using known cell surface markers (eg, CD184, CD24, CD90) to identify and interrogate distinct groups of cells in triple-negative breast cancer (TNBC) clinical biopsy specimens from patient-derived xenograft (PDX) models. The results demonstrate that flow cytometric analysis allows a relevant subgrouping of cancer tissue and that sorting of these subgroups provides insights on cancer cell populations with unique, reproducible and functionally divergent gene expression profiles. The discovery of a drug resistance signature implies that uncovering the functional interaction between these populations will lead to deeper understanding of cancer progression and drug response. Implications: PDX-derived human breast cancer tissue was investigated at the single cell level and cell subpopulations defined by surface markers were identified which suggest specific roles for distinct cellular compartments within a solid tumor

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging

Inference of action potentials (‘spikes’) from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals (‘ground truth’). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation