We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multi-neuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data.

The endoplasmic reticulum (ER) is a structurally complex, membrane-enclosed compartment that stretches from the nuclear envelope to the extreme periphery of eukaryotic cells. The organelle is crucial for numerous distinct cellular processes, but how these processes are spatially regulated within the structure is unclear. Traditional imaging-based approaches to understanding protein dynamics within the organelle are limited by the convoluted structure and rapid movement of molecular components. Here, we introduce a combinatorial imaging and machine learning-assisted image analysis approach to track the motion of photoactivated proteins within the ER of live cells. We find that simultaneous knowledge of the underlying ER structure is required to accurately analyze fluorescently-tagged protein redistribution, and after appropriate structural calibration we see all proteins assayed show signatures of Brownian diffusion-dominated motion over micron spatial scales. Remarkably, we find that in some cells the ER structure can be explored in a highly asymmetric manner, likely as a result of uneven connectivity within the organelle. This remains true independently of the size, topology, or folding state of the fluorescently-tagged molecules, suggesting a potential role for ER connectivity in driving spatially regulated biology in eukaryotes.

MOTIVATION: Automatic recognition of cell identities is critical for quantitative measurement, targeting, and manipulation of cells of model animals at single-cell resolution. It has been shown to be a powerful tool for studying gene expression and regulation, cell lineages, and cell fates. Existing methods first segment cells, before applying a recognition algorithm in the second step. As a result, the segmentation errors in the first step directly affect and complicate the subsequent cell recognition step. Moreover, in new experimental settings, some of the image features that have been previously relied upon to recognize cells may not be easy to reproduce, due to limitations on the number of color channels available for fluorescent imaging or to the cost of building transgenic animals. An approach that is more accurate and relies on only a single signal channel is clearly desirable. RESULTS: We have developed a new method, called SRS (for Simultaneous Recognition and Segmentation of cells), and applied it to 3D image stacks of the model organism C. elegans. Given a 3D image stack of the animal and a 3D atlas of target cells, SRS is effectively an atlas-guided voxel classification process: cell recognition is realized by smoothly deforming the atlas to best fit the image, where the segmentation is obtained naturally via classification of all image voxels. The method achieved a 97.7% overall recognition accuracy in recognizing a key class of marker cells, the body wall muscle (BWM) cells, on a data set of 175 C. elegans image stacks containing 14,118 manually curated BWM cells providing the "ground-truth" for accuracy. This result was achieved without any additional fiducial image features. SRS also automatically identified 14 of the image stacks as involving ±90-degree rotations. With these stacks excluded from the data set, the recognition accuracy rose to 99.1%. We also show SRS is generally applicable to other cell-types, e.g. intestinal cells. AVAILABILITY: The supplementary movies can be downloaded from our website http://penglab.janelia.org/proj/celegans_seganno. The method has been implemented as a plug-in program within the V3D system (http://penglab.janelia.org/proj/v3d) and will be released in the V3D plugin source code repository.

CA1 pyramidal neurons are a major output of the hippocampus and encode features of experience that constitute episodic memories. Feature-selective firing of these neurons results from the dendritic integration of inputs from multiple brain regions. While it is known that synchronous activation of spatially clustered inputs can contribute to firing through the generation of dendritic spikes, there is no established mechanism for spatiotemporal synaptic clustering. Here we show that single presynaptic axons form multiple, spatially clustered inputs onto the distal, but not proximal, dendrites of CA1 pyramidal neurons. These compound connections exhibit ultrastructural features indicative of strong synapses and occur much more commonly in entorhinal than in thalamic afferents. Computational simulations revealed that compound connections depolarize dendrites in a biophysically efficient manner, owing to their inherent spatiotemporal clustering. Our results suggest that distinct afferent projections use different connectivity motifs that differentially contribute to dendritic integration.

Human immunodeficiency virus type 1 (HIV-1) assembly occurs on the inner leaflet of the host cell plasma membrane, incorporating the essential viral envelope glycoprotein (Env) within a budding lattice of HIV-1 Gag structural proteins. The mechanism by which Env incorporates into viral particles remains poorly understood. To determine the mechanism of recruitment of Env to assembly sites, we interrogate the subviral angular distribution of Env on cell-associated virus using multicolor, three-dimensional (3D) superresolution microscopy. We demonstrate that, in a manner dependent on cell type and on the long cytoplasmic tail of Env, the distribution of Env is biased toward the necks of cell-associated particles. We postulate that this neck-biased distribution is regulated by vesicular retention and steric complementarity of Env during independent Gag lattice formation.

Transcription factors (TFs) are DNA binding proteins that control the expression of genes. The regulation of transcription is a complex process that involves binding of TFs to specific sequences, recruitment of cofactors and chromatin remodelers, assembly of the pre-initiation complex and ultimately the recruitment of RNA polymerase II. Increasing evidence suggests that TFs are highly dynamic and interact only transiently with DNA. Single molecule microscopy techniques are powerful approaches for visualizing and tracking individual TF molecules as they diffuse in the nucleus and interact with DNA. In this work, we employ multifocus microscopy and highly inclined and laminated optical sheet microscopy to track TF dynamics in response to perturbations in labile zinc inside cells. We sought to define whether zinc-dependent TFs sense changes in the labile zinc pool by determining whether their dynamics and DNA binding can be modulated by zinc. While it is widely appreciated that TFs need zinc to bind DNA, whether zinc occupancy and hence TF function are sensitive to changes in cellular zinc remain open questions. We utilized fluorescently tagged versions of the glucocorticoid receptor (GR), with two C4 zinc finger domains, and CCCTC-binding factor (CTCF), with eleven C2H2 zinc finger domains. We found that the biophysical dynamics of both TFs are susceptible to changes in zinc, but in subtly different ways. These results indicate that at least some transcription factors are sensitive to zinc dynamics, revealing a potential new layer of transcriptional regulation.

The regulation of transcription is a complex process that involves binding of transcription factors (TFs) to specific sequences, recruitment of cofactors and chromatin remodelers, assembly of the pre-initiation complex and recruitment of RNA polymerase II. Increasing evidence suggests that TFs are highly dynamic and interact only transiently with DNA. Single molecule microscopy techniques are powerful approaches for tracking individual TF molecules as they diffuse in the nucleus and interact with DNA. Here we employ multifocus microscopy and highly inclined laminated optical sheet microscopy to track TF dynamics in response to perturbations in labile zinc inside cells. We sought to define whether zinc-dependent TFs sense changes in the labile zinc pool by determining whether their dynamics and DNA binding can be modulated by zinc. We used fluorescently tagged versions of the glucocorticoid receptor (GR), with two C4 zinc finger domains, and CCCTC-binding factor (CTCF), with eleven C2H2 zinc finger domains. We found that GR was largely insensitive to perturbations of zinc, whereas CTCF was significantly affected by zinc depletion and its dwell time was affected by zinc elevation. These results indicate that at least some transcription factors are sensitive to zinc dynamics, revealing a potential new layer of transcriptional regulation.

The resolution of a microscope is determined by the diffraction limit in classical microscopy, whereby objects that are separated by half a wavelength can no longer be visually separated. To go below the diffraction limit required several tricks and discoveries. In his Nobel Lecture, E. Betzig describes the developments that have led to modern super high-resolution microscopy.

Unraveling the structural organization of neurons can provide fundamental insights into brain function. However, visualizing neurite morphology in vivo remains difficult due to the high density and complexity of neural packing in the nervous system. Detailed analysis of neural morphology requires distinction of closely neighboring, highly intricate cellular structures such as neurites with high contrast. Green-to-red photoconvertible fluorescent proteins have become powerful tools to optically highlight molecular and cellular structures for developmental and cell biological studies. Yet, selective labeling of single cells of interest in vivo has been precluded due to inefficient photoconversion when using high intensity, pulsed, near-infrared laser sources that are commonly applied for achieving axially confined two-photon (2P) fluorescence excitation. Here we describe a novel optical mechanism, "confined primed conversion," which employs continuous dual-wave illumination to achieve confined green-to-red photoconversion of single cells in live zebrafish embryos. Confined primed conversion exhibits wide applicability and this chapter specifically elaborates on employing this imaging modality to analyze neural morphology of optically targeted single neurons in the developing zebrafish brain.