Localization, proteomics, and metabolite profiling reveal a putative vesicular transporter for UDP-glucose
Abstract
Vesicular neurotransmitter transporters (VNTs) mediate the selective uptake and enrichment of small molecule neurotransmitters into synaptic vesicles (SVs) and are therefore a major determinant of the synaptic output of specific neurons. To identify novel VNTs expressed on SVs (thus identifying new neurotransmitters and/or neuromodulators), we conducted localization profiling of 361 solute carrier (SLC) transporters tagging with a fluorescent protein in neurons, which revealed 40 possible candidates through comparison with a known SV marker. We parallelly performed proteomics analysis of immunoisolated SVs and identified 7 transporters in overlap. Ultrastructural analysis confirmed one of the transporters, SLC35D3, localized to SVs. Finally, by combining metabolite profiling with a radiolabeled substrate transport assay, we identified UDP-glucose as the principal substrate for SLC35D3. These results provide new insights into the functional role of SLC transporters in neurotransmission and improve our understanding of the molecular diversity of chemical transmitters.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
Beijing Municipal Science & Technology Commission (Z181100001318002)
- Yulong Li
Peking-Tsinghua Center for Life Sciences
- Yulong Li
State Key Laboratory of Membrane Biology
- Yulong Li
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Rebecca Seal, University of Pittsburgh School of Medicine, United States
Ethics
Animal experimentation: All animal procedures were performed using protocols approved by the Institutional Animal Care and Use Committee at Peking University. ( LSC LiYL 1 )
Version history
- Received: December 3, 2020
- Accepted: July 15, 2021
- Accepted Manuscript published: July 16, 2021 (version 1)
- Version of Record published: August 18, 2021 (version 2)
Copyright
© 2021, Qian et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Neuroscience
Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or ‘iconic’ memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.
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- Neuroscience
Our ability to recall details from a remembered image depends on a single mechanism that is engaged from the very moment the image disappears from view.