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Synaptic vesicles that store monoamines and glutamate differ in protein composition

ABSTRACT: Neuromodulators such as monoamines assure essential brain functions but relatively little is known about their mechanism of release. While recent work has advanced our knowledge of active zone architecture in dopamine axons, release machinery within the synaptic vesicle (SV) remains poorly understood. Here, we address differences between the release of monoamines and classical synaptic transmitters by comparing the composition of SVs that contain the vesicular monoamine transporter 2 (VMAT2) versus vesicular glutamate transporter 2 (VGLUT2). Previous work revealed that these SV populations differ in frequency dependence, recycling kinetics and biogenesis. We now find differences in the abundance and isoform expression of many SV protein families. These findings provide new insights into the molecular diversity of SVs and mechanisms of dopamine release.

INSTRUMENT(S):

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Brain

SUBMITTER: Juan Oses-Prieto

LAB HEAD: Kätlin Silm

PROVIDER: PXD073685 | Pride | 2026-06-08

REPOSITORIES: Pride

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			Action	DRS
	S20201026-21.raw	Raw
	S20201026-21_search_proteinlist1percentFDR.xlsx	Xlsx
	S20201026-23.raw	Raw
	S20201026-23_search_proteinlist1percentFDR.xlsx	Xlsx
	Y20220502-23-search_proteinlist1percentFDR.xlsx	Xlsx

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Project description:Previous systems-based proteomic approaches have characterized alterations in protein co-expression networks of unfractionated asymptomatic (AsymAD) and symptomatic Alzheimer’s disease (AD) brains. However, it remains unclear how sample fractionation and sub-proteomic analysis influences the organization of these protein networks and their relationship to clinicopathological traits of disease. In this proof-of-concept study, we performed a systems-based sub-proteomic analysis of membrane-enriched post-mortem brain samples from pathology-free control, AsymAD, and AD brains (n=6 per group). Label-free mass spectrometry based on peptide ion intensity was used to quantify the 18 membrane-enriched fractions. Differential expression and weighted protein co-expression network analysis (WPCNA) were then used to identify and characterize modules of co-expressed proteins most significantly altered between the groups. We identified a total of 27 modules of co-expressed membrane-associated proteins. In contrast to the unfractionated proteome, these networks did not map strongly to cell-type specific markers. Instead, these modules were principally organized by their associations with a wide variety of membrane-bound compartments and organelles. Of these, the mitochondrion was associated with the greatest number of modules, followed by modules linked to the cell surface compartment. In addition, we resolved networks with strong associations to the endoplasmic reticulum, Golgi apparatus, nucleus, and other membrane-bound organelles. Fourteen of the 27 modules demonstrated significant correlations with clinical and pathological AD phenotypes. These results revealed that the proteins within individual compartments feature a heterogeneous array of AD-associated expression patterns, particularly during preclinical stages of disease. In conclusion, this systems-based analysis of the membrane-associated AsymAD brain proteome yielded a unique network organization highly linked to cellular compartmentalization. Further study of this membrane-associated proteome may reveal novel insight into the complex pathways governing the earliest stages of disease.

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Synaptic vesicles that store monoamines and glutamate differ in protein composition

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