Building retinal connectomes

Retinal Pathoconnectomics: A Window into Neurodegeneration

Over the past decade, the field of retinal connectomics has made huge strides in describing the precise topologies underlying retinal visual processing. The same techniques that allowed these advancements are also applicable to understanding the progression of rewiring in retinal remodeling: retinal pathoconnectomics. Pathoconnectomics is unique in its unbiased approach to understanding the impacts of deafferentation on the remaining network components and identifying aberrant connectivities leading to visual processing defects. Pathoconnectomics also paves the way for identifying underlying rules of rewiring that may be recapitulated throughout the nervous system in other neurodegenerative diseases.

Peptide-based immunotherapy against oxidized elastin ameliorates pathology in mouse model of smoke-induced ocular injury

PURPOSE

Age-related macular degeneration (AMD), the leading cause of blindness in western populations, is associated with an overactive complement system, and an increase in circulating antibodies against certain epitopes, including elastin. As loss of the elastin layer of Bruch's membrane (BrM) has been reported in aging and AMD, we previously showed that immunization with elastin peptide oxidatively modified by cigarette smoke (ox-elastin), exacerbated ocular pathology in the smoke-induced ocular pathology (SIOP) model. Here we asked whether ox-elastin peptide-based immunotherapy (PIT) ameliorates damage.

METHODS

C57BL/6J mice were injected with ox-elastin peptide at two doses via weekly subcutaneous administration, while exposed to cigarette smoke for 6 months. FcγR-/- and uninjected C57BL/6J mice served as controls. Retinal morphology was assessed by electron microscopy, and complement activation, antibody deposition and mechanisms of immunological tolerance were assessed by Western blotting and ELISA.

RESULTS

Elimination of Fcγ receptors, preventing antigen/antibody-dependent cytotoxicity, protected against SIOP. Mice receiving PIT with low dose ox-elastin (LD-PIT) exhibited reduced humoral immunity, reduced complement activation and IgG/IgM deposition in the RPE/choroid, and largely a preserved BrM. While there is no direct evidence of ox-elastin pathogenicity, LD-PIT reduced IFNγ and increased IL-4 within RPE/choroid. High dose PIT was not protective.

CONCLUSIONS

These data further support ox-elastin role in ocular damage in part via elastin-specific antibodies, and support the corollary that PIT with ox-elastin attenuates ocular pathology. Overall, damage is associated with complement activation, antibody-dependent cell-mediated cytotoxicity, and altered cytokine signature.

Connectomic mapping of brain-spinal cord neural networks: future directions in assessing spinal cord injury at rest

Following spinal cord injury (SCI), the central nervous system undergoes significant reconstruction. The dynamic change in the interaction of the brain-spinal cord axis as well as in structure-function relations plays a vital role in the determination of neurological functions, which might have important clinical implications for the treatment and its efficacy evaluation of patients with SCI. Brain connectomes based on neuroimaging data is a relatively new field of research that maps the brain's large-scale structural and functional networks at rest. Importantly, increasing evidence shows that such resting-state signals can also be seen in the spinal cord. In the present review, we focus on the reconstruction of multi-level neural circuits after SCI. We also describe how the connectome concept could further our understanding of neuroplasticity after SCI. We propose that mapping the cortical-subcortical-spinal cord networks can provide novel insights into the pathologies of SCI.

A pathoconnectome of early neurodegeneration: Network changes in retinal degeneration

Connectomics has demonstrated that synaptic networks and their topologies are precise and directly correlate with physiology and behavior. The next extension of connectomics is pathoconnectomics: to map neural network synaptology and circuit topologies corrupted by neurological disease in order to identify robust targets for therapeutics. In this report, we characterize a pathoconnectome of early retinal degeneration. This pathoconnectome was generated using serial section transmission electron microscopy to achieve an ultrastructural connectome with 2.18nm/px resolution for accurate identification of all chemical and gap junctional synapses. We observe aberrant connectivity in the rod-network pathway and novel synaptic connections deriving from neurite sprouting. These observations reveal principles of neuron responses to the loss of network components and can be extended to other neurodegenerative diseases.

Dynamic Computational Model of the Human Spinal Cord Connectome

Connectomes abound, but few for the human spinal cord. Using anatomical data in the literature, we constructed a draft connectivity map of the human spinal cord connectome, providing a template for the many calibrations of specialized behavior to be overlaid on it and the basis for an initial computational model. A thorough literature review gleaned cell types, connectivity, and connection strength indications. Where human data were not available, we selected species that have been studied. Cadaveric spinal cord measurements, cross-sectional histology images, and cytoarchitectural data regarding cell size and density served as the starting point for estimating numbers of neurons. Simulations were run using neural circuitry simulation software. The model contains the neural circuitry in all ten Rexed laminae with intralaminar, interlaminar, and intersegmental connections, as well as ascending and descending brain connections and estimated neuron counts for various cell types in every lamina of all 31 segments. We noted the presence of highly interconnected complex networks exhibiting several orders of recurrence. The model was used to perform a detailed study of spinal cord stimulation for analgesia. This model is a starting point for workers to develop and test hypotheses across an array of biomedical applications focused on the spinal cord. Each such model requires additional calibrations to constrain its output to verifiable predictions. Future work will include simulating additional segments and expanding the research uses of the model.

Fractional integral-like processing in retinal cones reduces noise and improves adaptation

In the human retina, rod and cone cells detect incoming light with a molecule called rhodopsin. After rhodopsin molecules are activated (by photon impact), these molecules activate the rest of the signalling process for a brief period of time until they are deactivated by a multistage process. First, active rhodopsin is phosphorylated multiple times. Following this, they are further inhibited by the binding of molecules called arrestins. Finally, they decay into opsins. The time required for each of these stages becomes progressively longer, and each stage further reduces the activity of rhodopsin. However, while this deactivation process itself is well researched, the roles of the above stages in signal (and image) processing are poorly understood. In this paper, we will show that the activity of rhodopsin molecules during the deactivation process can be described as the fractional integration of an incoming signal. Furthermore, we show how this affects an image; specifically, the effect of fractional integration in video and signal processing and how it reduces noise and the improves adaptability under different lighting conditions. Our experimental results provide a better understanding of vertebrate and human vision, and why the rods and cones of the retina differ from the light detectors in cameras.

Rod-cone crossover connectome of mammalian bipolar cells

The basis of cross-suppression between rod and cone channels has long been an enigma. Using rabbit retinal connectome RC1, we show that all cone bipolar cell (BC) classes inhibit rod BCs via amacrine cell (AC) motifs (C1-6); that all cone BC classes are themselves inhibited by AC motifs (R1-5, R25) driven by rod BCs. A sparse symmetric AC motif (CR) is presynaptic and postsynaptic to both rod and cone BCs. ON cone BCs of all classes drive inhibition of rod BCs via motif C1 wide-field GABAergic ACs (γACs) and motif C2 narrow field glycinergic ON ACs (GACs). Each rod BC receives ≈10 crossover AC synapses and each ON cone BC can target ≈10 or more rod BCs via separate AC processes. OFF cone BCs mediate monosynaptic inhibition of rod BCs via motif C3 driven by OFF γACs and GACs and disynaptic inhibition via motifs C4 and C5 driven by OFF wide-field γACs and narrow-field GACs, respectively. Motifs C4 and C5 form halos of 60-100 inhibitory synapses on proximal dendrites of AI γACs. Rod BCs inhibit surrounding arrays of cone BCs through AII GAC networks that access ON and OFF cone BC patches via motifs R1, R2, R4, R5 and a unique ON AC motif R3 that collects rod BC inputs and targets ON cone BCs. Crossover synapses for motifs C1, C4, C5, and R3 are 3-4× larger than typical feedback synapses, which may be a signature for synaptic winner-take-all switches. J. Comp. Neurol. 527:87-116, 2019. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Synaptic Mechanisms Generating Orientation Selectivity in the ON Pathway of the Rabbit Retina

Neurons that signal the orientation of edges within the visual field have been widely studied in primary visual cortex. Much less is known about the mechanisms of orientation selectivity that arise earlier in the visual stream. Here we examine the synaptic and morphological properties of a subtype of orientation-selective ganglion cell in the rabbit retina. The receptive field has an excitatory ON center, flanked by excitatory OFF regions, a structure similar to simple cell receptive fields in primary visual cortex. Examination of the light-evoked postsynaptic currents in these ON-type orientation-selective ganglion cells (ON-OSGCs) reveals that synaptic input is mediated almost exclusively through the ON pathway. Orientation selectivity is generated by larger excitation for preferred relative to orthogonal stimuli, and conversely larger inhibition for orthogonal relative to preferred stimuli. Excitatory orientation selectivity arises in part from the morphology of the dendritic arbors. Blocking GABAA receptors reduces orientation selectivity of the inhibitory synaptic inputs and the spiking responses. Negative contrast stimuli in the flanking regions produce orientation-selective excitation in part by disinhibition of a tonic NMDA receptor-mediated input arising from ON bipolar cells. Comparison with earlier studies of OFF-type OSGCs indicates that diverse synaptic circuits have evolved in the retina to detect the orientation of edges in the visual input.

SIGNIFICANCE STATEMENT

A core goal for visual neuroscientists is to understand how neural circuits at each stage of the visual system extract and encode features from the visual scene. This study documents a novel type of orientation-selective ganglion cell in the retina and shows that the receptive field structure is remarkably similar to that of simple cells in primary visual cortex. However, the data indicate that, unlike in the cortex, orientation selectivity in the retina depends on the activity of inhibitory interneurons. The results further reveal the physiological basis for feature detection in the visual system, elucidate the synaptic mechanisms that generate orientation selectivity at an early stage of visual processing, and illustrate a novel role for NMDA receptors in retinal processing.

Retinal remodeling in human retinitis pigmentosa

Retinitis Pigmentosa (RP) in the human is a progressive, currently irreversible neural degenerative disease usually caused by gene defects that disrupt the function or architecture of the photoreceptors. While RP can initially be a disease of photoreceptors, there is increasing evidence that the inner retina becomes progressively disorganized as the outer retina degenerates. These alterations have been extensively described in animal models, but remodeling in humans has not been as well characterized. This study, using computational molecular phenotyping (CMP) seeks to advance our understanding of the retinal remodeling process in humans. We describe cone mediated preservation of overall topology, retinal reprogramming in the earliest stages of the disease in retinal bipolar cells, and alterations in both small molecule and protein signatures of neurons and glia. Furthermore, while Müller glia appear to be some of the last cells left in the degenerate retina, they are also one of the first cell classes in the neural retina to respond to stress which may reveal mechanisms related to remodeling and cell death in other retinal cell classes. Also fundamentally important is the finding that retinal network topologies are altered. Our results suggest interventions that presume substantial preservation of the neural retina will likely fail in late stages of the disease. Even early intervention offers no guarantee that the interventions will be immune to progressive remodeling. Fundamental work in the biology and mechanisms of disease progression are needed to support vision rescue strategies.

A resource from 3D electron microscopy of hippocampal neuropil for user training and tool development

Resurgent interest in synaptic circuitry and plasticity has emphasized the importance of 3D reconstruction from serial section electron microscopy (3DEM). Three volumes of hippocampal CA1 neuropil from adult rat were imaged at X-Y resolution of ~2 nm on serial sections of ~50-60 nm thickness. These are the first densely reconstructed hippocampal volumes. All axons, dendrites, glia, and synapses were reconstructed in a cube (~10 μm(3)) surrounding a large dendritic spine, a cylinder (~43 μm(3)) surrounding an oblique dendritic segment (3.4 μm long), and a parallelepiped (~178 μm(3)) surrounding an apical dendritic segment (4.9 μm long). The data provide standards for identifying ultrastructural objects in 3DEM, realistic reconstructions for modeling biophysical properties of synaptic transmission, and a test bed for enhancing reconstruction tools. Representative synapses are quantified from varying section planes, and microtubules, polyribosomes, smooth endoplasmic reticulum, and endosomes are identified and reconstructed in a subset of dendrites. The original images, traces, and Reconstruct software and files are freely available and visualized at the Open Connectome Project (Data Citation 1).

Input clustering and the microscale structure of local circuits

The recent development of powerful tools for high-throughput mapping of synaptic networks promises major advances in understanding brain function. One open question is how circuits integrate and store information. Competing models based on random vs. structured connectivity make distinct predictions regarding the dendritic addressing of synaptic inputs. In this article we review recent experimental tests of one of these models, the input clustering hypothesis. Across circuits, brain regions and species, there is growing evidence of a link between synaptic co-activation and dendritic location, although this finding is not universal. The functional implications of input clustering and future challenges are discussed.

Genetics of gene expression in CNS

Transcriptome studies have revealed a surprisingly high level of variation among individuals in expression of key genes in the CNS under both normal and experimental conditions. Ten-fold variation is common, yet the specific causes and consequences of this variation are largely unknown. By combining classic gene mapping methods-family linkage studies and genomewide association-with high-throughput genomics, it is now possible to define quantitative trait loci (QTLs), single-gene variants, and even single SNPs and indels that control gene expression in different brain regions and cells. This review considers some of the major technical and conceptual challenges in analyzing variation in expression in the CNS with a focus on mRNAs, rather than noncoding RNAs or proteins. At one level of analysis, this work has been highly successful, and we finally have techniques that can be used to track down small numbers of loci that control expression in the CNS. But at a higher level of analysis, we still do not understand the genetic architecture of gene expression in brain, the consequences of expression QTLs on protein levels or on cell function, or the combined impact of expression differences on behavior and disease risk. These important gaps are likely to be bridged over the next several decades using (1) much larger sample sizes, (2) more powerful RNA sequencing and proteomic methods, and (3) novel statistical and computational models to predict genome-to-phenome relations.

Retinal connectomics: towards complete, accurate networks

Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 10(12)-10(15) byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies of complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication.

ON cone bipolar cell axonal synapses in the OFF inner plexiform layer of the rabbit retina

Analysis of the rabbit retinal connectome RC1 reveals that the division between the ON and the OFF inner plexiform layer (IPL) is not structurally absolute. ON cone bipolar cells make noncanonical axonal synapses onto specific targets and receive amacrine cell synapses in the nominal OFF layer, creating novel motifs, including inhibitory crossover networks. Automated transmission electron microscopic imaging, molecular tagging, tracing, and rendering of ~400 bipolar cells reveals axonal ribbons in 36% of ON cone bipolar cells, throughout the OFF IPL. The targets include γ-aminobutyrate (GABA)-positive amacrine cells (γACs), glycine-positive amacrine cells (GACs), and ganglion cells. Most ON cone bipolar cell axonal contacts target GACs driven by OFF cone bipolar cells, forming new architectures for generating ON-OFF amacrine cells. Many of these ON-OFF GACs target ON cone bipolar cell axons, ON γACs, and/or ON-OFF ganglion cells, representing widespread mechanisms for OFF to ON crossover inhibition. Other targets include OFF γACs presynaptic to OFF bipolar cells, forming γAC-mediated crossover motifs. ON cone bipolar cell axonal ribbons drive bistratified ON-OFF ganglion cells in the OFF layer and provide ON drive to polarity-appropriate targets such as bistratified diving ganglion cells (bsdGCs). The targeting precision of ON cone bipolar cell axonal synapses shows that this drive incidence is necessarily a joint distribution of cone bipolar cell axonal frequency and target cell trajectories through a given volume of the OFF layer. Such joint distribution sampling is likely common when targets are sparser than sources and when sources are coupled, as are ON cone bipolar cells.

Automated transmission-mode scanning electron microscopy (tSEM) for large volume analysis at nanoscale resolution

Transmission-mode scanning electron microscopy (tSEM) on a field emission SEM platform was developed for efficient and cost-effective imaging of circuit-scale volumes from brain at nanoscale resolution. Image area was maximized while optimizing the resolution and dynamic range necessary for discriminating key subcellular structures, such as small axonal, dendritic and glial processes, synapses, smooth endoplasmic reticulum, vesicles, microtubules, polyribosomes, and endosomes which are critical for neuronal function. Individual image fields from the tSEM system were up to 4,295 µm² (65.54 µm per side) at 2 nm pixel size, contrasting with image fields from a modern transmission electron microscope (TEM) system, which were only 66.59 µm² (8.160 µm per side) at the same pixel size. The tSEM produced outstanding images and had reduced distortion and drift relative to TEM. Automated stage and scan control in tSEM easily provided unattended serial section imaging and montaging. Lens and scan properties on both TEM and SEM platforms revealed no significant nonlinear distortions within a central field of ∼100 µm² and produced near-perfect image registration across serial sections using the computational elastic alignment tool in Fiji/TrakEM2 software, and reliable geometric measurements from RECONSTRUCT™ or Fiji/TrakEM2 software. Axial resolution limits the analysis of small structures contained within a section (∼45 nm). Since this new tSEM is non-destructive, objects within a section can be explored at finer axial resolution in TEM tomography with current methods. Future development of tSEM tomography promises thinner axial resolution producing nearly isotropic voxels and should provide within-section analyses of structures without changing platforms. Brain was the test system given our interest in synaptic connectivity and plasticity; however, the new tSEM system is readily applicable to other biological systems.