Identification and characterization of site‐specific N‐glycosylation in the potassium channel Kv3.1b

Vicente, Paul Christian; Kim, Jin Young; Ha, Jeong-Ju; Song, Min-Young; Lee, Hyun-Kyung; Kim, Dong-Hyun; Choi, Jin-Sung; Park, Kang-Sik

doi:10.1002/jcp.25915

“…For Man1c1 , the interaction model does not reveal a new relationship, but instead highlights the fact that this gene-property relationship, if real, is potentially more complicated than would be assumed based on the class-conditional model alone. Man1c1 is an enzyme involved in the maturation of N-linked oligosaccharides [24], and is thus a plausible regulator of AHP amplitude, since N-linked glycosylation of voltage-gated potassium channels or their auxiliary subunits is known to regulate both surface trafficking and channel function [25,26]. The apparent class-specificity of this relationship could result from class-specific co-expression of certain potassium channels or other enzymes involved in glycan synthesis or maturation.…”

Section: Resultsmentioning

confidence: 99%

Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes

Bomkamp

¹

,

Tripathy

²

,

Gonzales

³

et al. 2019

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In order to further our understanding of how gene expression contributes to key functional properties of neurons, we combined publicly accessible gene expression, electrophysiology, and morphology measurements to identify cross-cell type correlations between these data modalities. Building on our previous work using a similar approach, we distinguished between correlations which were “class-driven,” meaning those that could be explained by differences between excitatory and inhibitory cell classes, and those that reflected graded phenotypic differences within classes. Taking cell class identity into account increased the degree to which our results replicated in an independent dataset as well as their correspondence with known modes of ion channel function based on the literature. We also found a smaller set of genes whose relationships to electrophysiological or morphological properties appear to be specific to either excitatory or inhibitory cell types. Next, using data from PatchSeq experiments, allowing simultaneous single-cell characterization of gene expression and electrophysiology, we found that some of the gene-property correlations observed across cell types were further predictive of within-cell type heterogeneity. In summary, we have identified a number of relationships between gene expression, electrophysiology, and morphology that provide testable hypotheses for future studies.

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“…A recent study reports that N-glycans of Kv3.1b regulate cell surface expression since the cell surface expression is reduced 10-fold for the unglycosylated Kv3.1b protein compared to its glycosylated counterpart [ 44 ]. However, current density measurements of Kv3.1b expressing Sf9 insect [ 15 ], NB [ 17 ], NB_1, and NB_1 (-Mgat2) cell lines did not detect significant differences in cell surface expression between the glycosylated and unglycosylated Kv3.1b channels.…”

Section: Discussionmentioning

confidence: 99%

Membrane Distribution and Activity of a Neuronal Voltage-Gated K+ Channel is Modified by Replacement of Complex Type N-Glycans with Hybrid Type

Hall¹,

Weidner²,

Dayal³

et al. 2017

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Abnormal modifications in N-glycosylation processing are commonly associated with neurological disorders, although the impact of specific N-glycans on neuronal excitability is unknown. By replacement of complex types of N-glycans with hybrid types in neuroblastoma cells, we provide the first study that addresses how distinct N-glycan types impact neuronal excitability. Using CRISPR/Cas9 technology, NB_1, a clonal cell line derived from rat neuroblastoma cells (NB), was modified to create an N-glycosylation mutant cell line, NB_1 (-Mgat2), which expresses predominantly hybrid type N-glycans. Western and lectin blotting, flow cytometry, TIRF and DIC microscopy, and patch clamp studies were conducted. Lectin binding revealed the predominant type of N-glycans expressed in NB_1 (-Mgat2) is hybrid while those of NB and NB_1 are complex. Kv3.1 b-expressing cells with complex N-glycans localized more glycosylated Kv3.1b to the neurites than cells with hybrid N-glycans. Further the absence of N-glycan attachment to Kv3.1b was critical for sub-plasma distribution of Kv3.1b to neurites in primary adult mammalian neurons, along with NB cells. Replacement of complex type N-glycans with hybrid type hindered the opening and closing rates of outward ionic currents of Kv3.1 b-expressing NB cells. The lacks of N-glycan attachment hindered the rates even more but were not significantly different between the NB cell lines. Taken together, our evidence supports N-glycosylation impacts the sub-plasma membrane localization and activity of Kv3.1 b-containing channels. We propose that N-glycosylation processing of Kv3.1 b-containing channels contributes to neuronal excitability, and abnormal modifications in N-glycosylation processing of Kv3.1b could contribute to neurological diseases.

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“…Man1c1 is an enzyme involved in the maturation of N-linked oligosaccharides (18), and is thus a plausible regulator of AHP amplitude, since N-linked glycosylation of voltage-gated potassium channels or their auxiliary subunits is known to regulate both surface trafficking and channel function (19,20).…”

Section: Divergent Gene-property Relationships In Inhibitory Versus Ementioning

confidence: 99%

Transcriptomic correlates of electrophysiological and morphological diversity within and across neuron types

Bomkamp

¹

,

Tripathy

²

,

Gonzales

³

et al. 2019

Preprint

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In order to further our understanding of how gene expression contributes to key functional properties of neurons, we combined publicly accessible gene expression, electrophysiology, and morphology measurements to identify cross-cell type correlations between these data modalities. Building on our previous work using a similar approach, we distinguished between correlations which were "class-We reason that gene-property relationships that are non-class-driven would be more likely to be potential causal regulators of the associated property. Although some class-driven correlations likely do reflect true relationships between genes and properties which distinguish excitatory from inhibitory cells, separating these relationships from instances where one cell class has a higher value of a property and coincidentally higher or lower expression of a gene without additional sources of data is not possible. Effectively, such situations are analogous to attempting to draw conclusions about correlations with only two data points.Due to limitations in available data, we were unable to address the effect of cell class in our previous work (11). Since then, the RNA-seq and electrophysiology datasets from the Allen Institute for Brain Science (AIBS) (which we originally used as validation data) have expanded greatly, with more cells and more transgenic lines represented. This increase in size, together with the fact that the AIBS data were collected using standardized protocols, suggests that this dataset might prove valuable for discovering genes correlated with electrophysiological and morphological properties. In addition, the growing use of the Patch-seq methodology (17), allowing transcriptomic, electrophysiological, and morphological characterization of the same single cell, also affords an opportunity to test gene-property correlations.Leveraging the larger size of the new AIBS dataset, we were able to address limitations of our previous study related to excitatory versus inhibitory cell class by employing statistical methods to help mitigate the effects of cell class. These methods, together with the larger number of cell types represented in the new dataset, allowed us to identify novel electrophysiological and morphological property-related gene sets which are potentially more likely to represent meaningful biological relationships.showing class-driven relationships (such as Fig 1B) but might miss some instances of non-class-driven relationships (such as Fig 1C).Another possible gene-property relationship is one where there is an interaction between gene and class, meaning that the gene-property relationship is different in excitatory and inhibitory cell types. An interaction could indicate either that excitatory and inhibitory cell types both show a correlation between the gene and property, but the slopes are in opposite directions (as in the example in Fig 1D), or that the gene is correlated with the property only in one cell class. To detect such situations, we introduced a third model, the interaction model, whic...

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Identification and characterization of site‐specific N‐glycosylation in the potassium channel Kv3.1b

Cited by 8 publications

References 39 publications

Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes

Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes

Membrane Distribution and Activity of a Neuronal Voltage-Gated K+ Channel is Modified by Replacement of Complex Type N-Glycans with Hybrid Type

Transcriptomic correlates of electrophysiological and morphological diversity within and across neuron types

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