Cargando…

Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease

BACKGROUND: Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation. However, microglial proteomics studies have been limited by low cellular yield and contamination by non-microglial proteins using existing en...

Descripción completa

Detalles Bibliográficos
Autores principales: Rayaprolu, Sruti, Gao, Tianwen, Xiao, Hailian, Ramesha, Supriya, Weinstock, Laura D., Shah, Jheel, Duong, Duc M., Dammer, Eric B., Webster, James A., Lah, James J., Wood, Levi B., Betarbet, Ranjita, Levey, Allan I., Seyfried, Nicholas T., Rangaraju, Srikant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206797/
https://www.ncbi.nlm.nih.gov/pubmed/32381088
http://dx.doi.org/10.1186/s13024-020-00377-5
_version_ 1783530483882131456
author Rayaprolu, Sruti
Gao, Tianwen
Xiao, Hailian
Ramesha, Supriya
Weinstock, Laura D.
Shah, Jheel
Duong, Duc M.
Dammer, Eric B.
Webster, James A.
Lah, James J.
Wood, Levi B.
Betarbet, Ranjita
Levey, Allan I.
Seyfried, Nicholas T.
Rangaraju, Srikant
author_facet Rayaprolu, Sruti
Gao, Tianwen
Xiao, Hailian
Ramesha, Supriya
Weinstock, Laura D.
Shah, Jheel
Duong, Duc M.
Dammer, Eric B.
Webster, James A.
Lah, James J.
Wood, Levi B.
Betarbet, Ranjita
Levey, Allan I.
Seyfried, Nicholas T.
Rangaraju, Srikant
author_sort Rayaprolu, Sruti
collection PubMed
description BACKGROUND: Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation. However, microglial proteomics studies have been limited by low cellular yield and contamination by non-microglial proteins using existing enrichment strategies. METHODS: We coupled magnetic-activated cell sorting (MACS) and fluorescence activated cell sorting (FACS) of microglia with tandem mass tag-mass spectrometry (TMT-MS) to obtain a highly-pure microglial proteome and identified a core set of highly-abundant microglial proteins in adult mouse brain. We interrogated existing human proteomic data for Alzheimer’s disease (AD) relevance of highly-abundant microglial proteins and performed immuno-histochemical and in-vitro validation studies. RESULTS: Quantitative multiplexed proteomics by TMT-MS of CD11b + MACS-enriched (N = 5 mice) and FACS-isolated (N = 5 mice), from adult wild-type mice, identified 1791 proteins. A total of 203 proteins were highly abundant in both datasets, representing a core-set of highly abundant microglial proteins. In addition, we found 953 differentially enriched proteins comparing MACS and FACS-based approaches, indicating significant differences between both strategies. The FACS-isolated microglia proteome was enriched with cytosolic, endoplasmic reticulum, and ribosomal proteins involved in protein metabolism and immune system functions, as well as an abundance of canonical microglial proteins. Conversely, the MACS-enriched microglia proteome was enriched with mitochondrial and synaptic proteins and higher abundance of neuronal, oligodendrocytic and astrocytic proteins. From the 203 consensus microglial proteins with high abundance in both datasets, we confirmed microglial expression of moesin (Msn) in wild-type and 5xFAD mouse brains as well as in human AD brains. Msn expression is nearly exclusively found in microglia that surround Aβ plaques in 5xFAD brains. In in-vitro primary microglial studies, Msn silencing by siRNA decreased Aβ phagocytosis and increased lipopolysaccharide-induced production of the pro-inflammatory cytokine, tumor necrosis factor (TNF). In network analysis of human brain proteomic data, Msn was a hub protein of an inflammatory co-expression module positively associated with AD neuropathological features and cognitive dysfunction. CONCLUSIONS: Using FACS coupled with TMT-MS as the method of choice for microglial proteomics, we define a core set of highly-abundant adult microglial proteins. Among these, we validate Msn as highly-abundant in plaque-associated microglia with relevance to human AD.
format Online
Article
Text
id pubmed-7206797
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-72067972020-05-14 Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease Rayaprolu, Sruti Gao, Tianwen Xiao, Hailian Ramesha, Supriya Weinstock, Laura D. Shah, Jheel Duong, Duc M. Dammer, Eric B. Webster, James A. Lah, James J. Wood, Levi B. Betarbet, Ranjita Levey, Allan I. Seyfried, Nicholas T. Rangaraju, Srikant Mol Neurodegener Research Article BACKGROUND: Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation. However, microglial proteomics studies have been limited by low cellular yield and contamination by non-microglial proteins using existing enrichment strategies. METHODS: We coupled magnetic-activated cell sorting (MACS) and fluorescence activated cell sorting (FACS) of microglia with tandem mass tag-mass spectrometry (TMT-MS) to obtain a highly-pure microglial proteome and identified a core set of highly-abundant microglial proteins in adult mouse brain. We interrogated existing human proteomic data for Alzheimer’s disease (AD) relevance of highly-abundant microglial proteins and performed immuno-histochemical and in-vitro validation studies. RESULTS: Quantitative multiplexed proteomics by TMT-MS of CD11b + MACS-enriched (N = 5 mice) and FACS-isolated (N = 5 mice), from adult wild-type mice, identified 1791 proteins. A total of 203 proteins were highly abundant in both datasets, representing a core-set of highly abundant microglial proteins. In addition, we found 953 differentially enriched proteins comparing MACS and FACS-based approaches, indicating significant differences between both strategies. The FACS-isolated microglia proteome was enriched with cytosolic, endoplasmic reticulum, and ribosomal proteins involved in protein metabolism and immune system functions, as well as an abundance of canonical microglial proteins. Conversely, the MACS-enriched microglia proteome was enriched with mitochondrial and synaptic proteins and higher abundance of neuronal, oligodendrocytic and astrocytic proteins. From the 203 consensus microglial proteins with high abundance in both datasets, we confirmed microglial expression of moesin (Msn) in wild-type and 5xFAD mouse brains as well as in human AD brains. Msn expression is nearly exclusively found in microglia that surround Aβ plaques in 5xFAD brains. In in-vitro primary microglial studies, Msn silencing by siRNA decreased Aβ phagocytosis and increased lipopolysaccharide-induced production of the pro-inflammatory cytokine, tumor necrosis factor (TNF). In network analysis of human brain proteomic data, Msn was a hub protein of an inflammatory co-expression module positively associated with AD neuropathological features and cognitive dysfunction. CONCLUSIONS: Using FACS coupled with TMT-MS as the method of choice for microglial proteomics, we define a core set of highly-abundant adult microglial proteins. Among these, we validate Msn as highly-abundant in plaque-associated microglia with relevance to human AD. BioMed Central 2020-05-07 /pmc/articles/PMC7206797/ /pubmed/32381088 http://dx.doi.org/10.1186/s13024-020-00377-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Rayaprolu, Sruti
Gao, Tianwen
Xiao, Hailian
Ramesha, Supriya
Weinstock, Laura D.
Shah, Jheel
Duong, Duc M.
Dammer, Eric B.
Webster, James A.
Lah, James J.
Wood, Levi B.
Betarbet, Ranjita
Levey, Allan I.
Seyfried, Nicholas T.
Rangaraju, Srikant
Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title_full Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title_fullStr Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title_full_unstemmed Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title_short Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer’s disease
title_sort flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to alzheimer’s disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206797/
https://www.ncbi.nlm.nih.gov/pubmed/32381088
http://dx.doi.org/10.1186/s13024-020-00377-5
work_keys_str_mv AT rayaprolusruti flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT gaotianwen flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT xiaohailian flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT rameshasupriya flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT weinstocklaurad flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT shahjheel flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT duongducm flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT dammerericb flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT websterjamesa flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT lahjamesj flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT woodlevib flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT betarbetranjita flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT leveyallani flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT seyfriednicholast flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease
AT rangarajusrikant flowcytometricmicroglialsortingcoupledwithquantitativeproteomicsidentifiesmoesinasahighlyabundantmicroglialproteinwithrelevancetoalzheimersdisease