Membrane Voltage Is a Direct Feedback Signal That Influences Correlated Ion Channel Expression in Neurons

Santin, Joseph M.; Schulz, David J.

doi:10.1016/j.cub.2019.04.008

Cited by 37 publications

(49 citation statements)

References 31 publications

(55 reference statements)

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“…Taken at face value, models suggest that conductance densities drift throughout the life of an animal as a result of homeostatic processes (LeMasson et al, 1993;Liu et al, 1998;Golowasch et al, 1999b;O'Leary et al, 2014). Conductance densities can also change in an activity dependent manner as a result of perturbations (Turrigiano et al, 1994;Golowasch et al, 1999a;Santin and Schulz, 2019;Golowasch, 2019). Understanding how temperature compensation can be compatible with homeostatic and adaptation mechanisms remains an open theoretical and experimental question.…”

Section: Discussionmentioning

confidence: 99%

Temperature compensation in a small rhythmic circuit

Alonso

Marder

2019

Preprint

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Temperature a↵ects the conductances and kinetics of the ionic channels that underlie neuronal activity. Each membrane conductance has a di↵erent characteristic temperature sensitivity, which raises the question of how neurons and neuronal circuits can operate robustly over wide temperature ranges. To address this, we employed computational models of the pyloric network of crabs and lobsters. We produced multiple di↵erent models that exhibit a triphasic pyloric rhythm over a range of temperatures and explored the dynamics of their currents and how they change with temperature. We found that temperature changes the relative contributions of the currents to neuronal activity so that rhythmic activity smoothly slides through changes in mechanisms. Moreover, the responses of the models to extreme perturbations-such as gradually decreasing a current type-are often qualitatively di↵erent at di↵erent temperatures.Here we explore these issues using computational models of the pyloric network-a subnetwork within the stomatogastric ganglion (STG) of crustaceans (Marder and Bucher, 2007;Maynard, 1972). The pyloric rhythm is a triphasic motor pattern that consists of bursts of action potentials in a specific sequence. This behavior is robust and stable, and the cells and their connections are This manuscript has not been peer-reviewed L.M. Alonso and E. Marder

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Section: Discussionmentioning

confidence: 99%

Temperature compensation in a small rhythmic circuit

Alonso

Marder

2019

Preprint

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“…A very recent study found that three classes of neuronal effector genes - ion channels, receptors and cell adhesion molecules - have the greatest ability to distinguish among morphologically distinct mouse cortical cell populations (51). Our previous work also suggests that differential expression of ion channel mRNAs in STG cells may give rise to their distinct firing properties (52–54). We therefore examined our scRNA-seq data for expression of ion channel mRNAs.…”

Section: Resultsmentioning

confidence: 82%

Molecular Profiling to Infer Neuronal Cell Identity: Lessons from small ganglia of the Crab Cancer borealis

Northcutt

Kick

Otopalik

et al. 2019

Preprint

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54Understanding circuit organization depends on identification of cell types. Recent advances in 55 transcriptional profiling methods have enabled classification of cell types by their gene 56 expression. While exceptionally powerful and high throughput, the ground-truth validation of 57 these methods is difficult: if cell type is unknown, how does one assess whether a given 58 analysis accurately captures neuronal identity? To shed light on the capabilities and limitations 59 of solely using transcriptional profiling for cell type classification, we performed two forms of 60 transcriptional profiling -RNA-seq and quantitative RT-PCR, in single, unambiguously identified 61 neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then 62 combined our knowledge of cell type with unbiased clustering analyses and supervised machine 63 learning to determine how accurately functionally-defined neuron types can be classified by 64 expression profile alone. Our results demonstrate that expression profile is able to capture 65 neuronal identity most accurately when combined with multimodal information that allows for 66 post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised 67 clustering can lead to misidentification and an inability to distinguish between two or more cell 68 types. Therefore, our study supports the general utility of cell identification by transcriptional 69 profiling, but adds a caution: it is difficult or impossible to know under what conditions 70 transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple 71 modalities of information such as physiology, morphology or innervation target can neuronal 72 identity be unambiguously determined. 73 74 3 SIGNIFICANCE STATEMENT 75Single cell transcriptional profiling has become a widespread tool in cell identification, 76 particularly in the nervous system, based on the notion that genomic information determines cell 77 identity. However, many cell type classification studies are unconstrained by other cellular 78 attributes (e.g., morphology, physiology). Here, we systematically test how accurately 79 transcriptional profiling can assign cell identity to well-studied anatomically-and functionally-80 identified neurons in two small neuronal networks. While these neurons clearly possess distinct 81 patterns of gene expression across cell types, their expression profiles are not sufficient to 82 unambiguously confirm their identity. We suggest that true cell identity can only be determined 83 by combining gene expression data with other cellular attributes such as innervation pattern, 84 morphology, or physiology. 85 86 87 88 89Unambiguous classification of neuronal cell types is a long-standing goal in 90 neuroscience with the aim to understand the functional components of the nervous system that 91give rise to circuits and, ultimately, behavior (1-6). Beyond that, agreement upon neuronal cell 92 types provides the opportunity to greatly increase reproduci...

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“…These signaling processes were predicted to then initiate a feedback loop to alter ion channel expression to bring activity back to the set point. Several experimental and theoretical studies directly support this hypothesis (e.g., Bucher, Prinz, & Marder, ; Daur, Bryan, Garcia, & Bucher, ; O'Leary, Rossum, & Wyllie, ; O'Leary, Williams, Caplan, & Marder, ; O'Leary, Williams, Franci, & Marder, ; Ransdell, Nair, & Schulz, ; Santin & Schulz, ; Temporal, Lett, & Schulz, ; Turrigiano, Abbott, & Marder, ; Turrigiano et al, ), and it is now widely accepted that many neural systems continuously tweak their properties in a homeostatic or compensatory manner to ensure stable function over time. However, one challenge in testing this hypothesis has been that compensatory mechanisms are difficult to observe until some regulated variable (e.g., mean firing frequency) changes to a large enough degree to trigger the plasticity.…”

Section: Compensation and Homeostasis Of Nervous System Function: Gapmentioning

confidence: 92%

“…The premise of homeostasis and compensation is that neural systems constantly sense some aspect of their activity to regulate output around a set point (LeMasson et al, ; O'Leary et al, ). Motor neurons that maintain constant activity patterns throughout life seem to have this capacity (Santin & Schulz, ). However, many motor systems across the animal kingdom must produce reliable patterns of output after variable periods of use and disuse.…”

Section: Open Questions and The Use Of Hibernating Animals As Models mentioning

confidence: 99%

Motor inactivity in hibernating frogs: Linking plasticity that stabilizes neuronal function to behavior in the natural environment

Santin

2019

Developmental Neurobiology

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All animals must generate reliable neuronal activity to produce adaptive behaviors in an ever-changing environment. Neural systems are thought to achieve this goal, in part, through cellular and synaptic plasticity mechanisms that stabilize electrophysiological functions. Despite strong evidence for a role in regulating neuronal properties, these plasticity mechanisms have been difficult to link to natural behaviors in animals. In this review, I discuss how animals that inhabit extreme environments can address this challenge. As an example, I highlight recent work from frogs that stop breathing for several months during hibernation and, in response, use classic mechanisms of stabilizing plasticity to support respiratory motor output shortly after emergence. Furthermore, I describe problems for neuronal stability that may benefit from the study of hibernators: how circuits with variable modes of output control stabilizing mechanisms over long time scales and why some neural systems mount robust compensatory responses and others do not. By continuing to appreciate how diverse animal groups overcome challenges in the natural environment, we will broaden our view of the role that plasticity mechanisms play in stabilizing the nervous system. K E Y W O R D SAMPA receptor, control of breathing, hibernation, homeostatic plasticity, motor systems

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Membrane Voltage Is a Direct Feedback Signal That Influences Correlated Ion Channel Expression in Neurons

Cited by 37 publications

References 31 publications

Temperature compensation in a small rhythmic circuit

Temperature compensation in a small rhythmic circuit

Molecular Profiling to Infer Neuronal Cell Identity: Lessons from small ganglia of the Crab Cancer borealis

Motor inactivity in hibernating frogs: Linking plasticity that stabilizes neuronal function to behavior in the natural environment

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