Flow-cytometric microglial sorting coupled with quantitative proteomics identifies moesin as a highly-abundant microglial protein with relevance to Alzheimer's disease
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 str...
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Published in: | Molecular neurodegeneration Vol. 15; no. 1; p. 28 |
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Abstract | 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.
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.
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.
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. |
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AbstractList | 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 A[beta] plaques in 5xFAD brains. In in-vitro primary microglial studies, Msn silencing by siRNA decreased A[beta] 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. Keywords: Microglia, Proteomics, Mass spectrometry, FACS, MACS, Alzheimer's disease 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. 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. 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. 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. 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. 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. 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 A[beta] plaques in 5xFAD brains. In in-vitro primary microglial studies, Msn silencing by siRNA decreased A[beta] 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. 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. 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. Abstract 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. BACKGROUNDProteomic 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.METHODSWe 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.RESULTSQuantitative 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.CONCLUSIONSUsing 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. |
ArticleNumber | 28 |
Audience | Academic |
Author | Seyfried, Nicholas T Lah, James J Wood, Levi B Rayaprolu, Sruti Duong, Duc M Gao, Tianwen Shah, Jheel Rangaraju, Srikant Ramesha, Supriya Weinstock, Laura D Dammer, Eric B Webster, Jr, James A Xiao, Hailian Levey, Allan I Betarbet, Ranjita |
Author_xml | – sequence: 1 givenname: Sruti surname: Rayaprolu fullname: Rayaprolu, Sruti organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 2 givenname: Tianwen surname: Gao fullname: Gao, Tianwen organization: Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China – sequence: 3 givenname: Hailian surname: Xiao fullname: Xiao, Hailian organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 4 givenname: Supriya surname: Ramesha fullname: Ramesha, Supriya organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 5 givenname: Laura D surname: Weinstock fullname: Weinstock, Laura D organization: Parker H. Petit Institute for Bioengineering and Bioscience, Wallace H. Coulter Department of Biomedical Engineering, and Georgia W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA – sequence: 6 givenname: Jheel surname: Shah fullname: Shah, Jheel organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 7 givenname: Duc M surname: Duong fullname: Duong, Duc M organization: Department of Biochemistry, Emory University, Atlanta, GA, 30322, USA – sequence: 8 givenname: Eric B surname: Dammer fullname: Dammer, Eric B organization: School of Medicine, Emory University, Atlanta, GA, 30322, USA – sequence: 9 givenname: James A surname: Webster, Jr fullname: Webster, Jr, James A organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 10 givenname: James J surname: Lah fullname: Lah, James J organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 11 givenname: Levi B surname: Wood fullname: Wood, Levi B organization: Parker H. Petit Institute for Bioengineering and Bioscience, Wallace H. Coulter Department of Biomedical Engineering, and Georgia W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA – sequence: 12 givenname: Ranjita surname: Betarbet fullname: Betarbet, Ranjita organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 13 givenname: Allan I surname: Levey fullname: Levey, Allan I organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA – sequence: 14 givenname: Nicholas T surname: Seyfried fullname: Seyfried, Nicholas T email: nseyfri@emory.edu, nseyfri@emory.edu organization: Department of Biochemistry, Emory University, Atlanta, GA, 30322, USA. nseyfri@emory.edu – sequence: 15 givenname: Srikant orcidid: 0000-0003-2765-1500 surname: Rangaraju fullname: Rangaraju, Srikant email: srikant.rangaraju@emory.edu organization: Department of Neurology, Emory University School of Medicine, Whitehead Biomedical Research Building, 615 Michael Street, Atlanta, GA, 30322, USA. srikant.rangaraju@emory.edu |
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Cites_doi | 10.1038/s41467-019-11674-z 10.2174/1567205014666170117141330 10.1182/blood-2018-06-856831 10.1080/13854046.2015.1119312 10.1021/ac502040v 10.1002/pmic.201800469 10.1016/j.jalz.2011.10.007 10.1523/JNEUROSCI.1860-14.2014 10.1016/j.celrep.2017.09.039 10.1042/BJ20090856 10.1016/j.febslet.2009.10.036 10.1016/j.celrep.2017.12.066 10.1038/nrm882 10.1172/JCI90606 10.1016/j.celrep.2013.06.018 10.1038/sdata.2018.36 10.1186/s12974-017-0840-7 10.1038/ng.2802 10.1016/S1474-4422(15)70016-5 10.1038/nmeth.2019 10.1021/ac0262560 10.1101/719930 10.1016/j.cell.2017.05.018 10.1073/pnas.86.19.7611 10.2353/ajpath.2008.080528 10.1007/s11481-011-9287-2 10.1242/jcs.105.4.1025 10.1016/S0014-5793(98)01674-3 10.1172/jci.insight.121109 10.1038/nrg3185 10.1146/annurev-immunol-051116-052358 10.1126/science.aal3222 10.1186/s13024-018-0266-4 10.1016/j.neuron.2019.12.015 10.1016/j.jneumeth.2008.08.016 10.1002/glia.22298 10.1186/s12974-017-0906-6 10.1021/pr400246t 10.1007/s00401-006-0127-z 10.3389/fimmu.2018.00405 10.1016/S0006-8993(98)00489-2 10.1016/j.immuni.2018.11.004 10.1016/j.cell.2013.03.030 10.1038/s41591-020-0815-6 10.1038/s41593-018-0290-2 10.1016/j.cels.2016.11.006 10.1186/s13024-017-0234-4 10.1073/pnas.86.16.6348 10.1038/nn.4160 10.1016/j.jneumeth.2010.11.001 10.1038/ni1039 10.1016/S0022-510X(01)00508-1 10.1371/journal.pone.0085090 10.1101/798215 10.1007/s11745-007-3136-3 10.1186/s13024-018-0254-8 10.1016/0304-3940(90)90748-X 10.1073/pnas.1525528113 10.1002/glia.23678 10.1007/s00401-017-1691-0 10.1016/j.celrep.2018.06.113 10.1186/s13024-017-0184-x 10.1016/j.jneuroim.2020.577185 10.1073/pnas.88.19.8297 10.1038/s41586-019-0924-x 10.15252/emmm.201708202 10.1038/nmeth.1714 10.3389/fnmol.2018.00454 10.1038/nmeth1113 10.1073/pnas.0900345106 10.1016/j.jamda.2013.05.009 |
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References | L Ping (377_CR28) 2018; 5 A Thompson (377_CR62) 2003; 75 A Hashemiaghdam (377_CR73) 2020; 341 JC Lambert (377_CR3) 2013; 45 M Berryman (377_CR50) 1993; 105 377_CR39 R Gordon (377_CR36) 2011; 194 BA Durafourt (377_CR9) 2012; 60 LS Perlmutter (377_CR6) 1990; 119 J Schindelin (377_CR35) 2012; 9 377_CR40 BT Hyman (377_CR55) 2012; 8 J Esser (377_CR46) 2009; 425 BA Friedman (377_CR14) 2018; 22 R Marek (377_CR37) 2008; 175 A Shcherbina (377_CR51) 1999; 443 K Sharma (377_CR22) 2015; 18 ME Umoh (377_CR31) 2018; 10 T Maier (377_CR21) 2009; 583 MT Heneka (377_CR1) 2015; 14 S Rangaraju (377_CR18) 2018; 13 AR de Sousa (377_CR19) 2009; 5 MC Janelsins (377_CR69) 2008; 173 J Guergues (377_CR24) 2019; 19 S Faure (377_CR52) 2004; 5 H Keren-Shaul (377_CR13) 2017; 169 AG Efthymiou (377_CR4) 2017; 12 E Drummond (377_CR42) 2017; 133 L Ting (377_CR60) 2011; 8 B Zhang (377_CR41) 2013; 153 EM Reiman (377_CR56) 2009; 106 T Gao (377_CR27) 2019; 67 GC McAlister (377_CR61) 2014; 86 ML Bennett (377_CR10) 2016; 113 377_CR57 T Masuda (377_CR58) 2019; 566 B Decourt (377_CR68) 2017; 14 TR Sairanen (377_CR72) 2001; 186 EB Dammer (377_CR63) 2013; 12 WS Griffin (377_CR5) 1989; 86 IM Chiu (377_CR16) 2013; 4 E Spangenberg (377_CR8) 2019; 10 TR Hammond (377_CR17) 2019; 50 C Vogel (377_CR20) 2012; 13 L Kall (377_CR29) 2007; 4 H Braak (377_CR54) 2006; 112 N Oosterhof (377_CR7) 2018; 24 AP Lieberman (377_CR70) 1989; 86 C Liao (377_CR34) 2018; 132 NT Seyfried (377_CR30) 2017; 4 J Kim (377_CR47) 2014; 9 M Colonna (377_CR45) 2017; 35 S Balsis (377_CR53) 2015; 29 Y Zhang (377_CR11) 2014; 34 B Bai (377_CR44) 2020; 105 H Sarlus (377_CR2) 2017; 127 TG Brock (377_CR48) 2008; 43 A Bretscher (377_CR49) 2002; 3 A Flowers (377_CR23) 2017; 14 C Bottcher (377_CR59) 2019; 22 M Michaud (377_CR67) 2013; 14 S Rangaraju (377_CR38) 2017; 14 WT Lankes (377_CR65) 1991; 88 D Gosselin (377_CR12) 2017; 356 SL Montgomery (377_CR66) 2012; 7 DK Kim (377_CR43) 2018; 13 C Gong (377_CR71) 1998; 801 DR Littman (377_CR33) 2013 J Dai (377_CR32) 2018; 11 H Mathys (377_CR15) 2017; 21 S Rangaraju (377_CR25) 2018; 13 S Rangaraju (377_CR26) 2018; 9 DB Swartzlander (377_CR64) 2018; 3 |
References_xml | – volume: 10 start-page: 3758 year: 2019 ident: 377_CR8 publication-title: Nat Commun doi: 10.1038/s41467-019-11674-z contributor: fullname: E Spangenberg – volume: 14 start-page: 412 year: 2017 ident: 377_CR68 publication-title: Curr Alzheimer Res doi: 10.2174/1567205014666170117141330 contributor: fullname: B Decourt – volume: 132 start-page: 2580 year: 2018 ident: 377_CR34 publication-title: Blood doi: 10.1182/blood-2018-06-856831 contributor: fullname: C Liao – volume: 29 start-page: 1002 year: 2015 ident: 377_CR53 publication-title: Clin Neuropsychol doi: 10.1080/13854046.2015.1119312 contributor: fullname: S Balsis – volume: 86 start-page: 7150 year: 2014 ident: 377_CR61 publication-title: Anal Chem doi: 10.1021/ac502040v contributor: fullname: GC McAlister – volume: 19 start-page: e1800469 year: 2019 ident: 377_CR24 publication-title: Proteomics doi: 10.1002/pmic.201800469 contributor: fullname: J Guergues – volume: 8 start-page: 1 year: 2012 ident: 377_CR55 publication-title: Alzheimers Dement doi: 10.1016/j.jalz.2011.10.007 contributor: fullname: BT Hyman – volume: 34 start-page: 11929 year: 2014 ident: 377_CR11 publication-title: J Neurosci doi: 10.1523/JNEUROSCI.1860-14.2014 contributor: fullname: Y Zhang – volume: 21 start-page: 366 year: 2017 ident: 377_CR15 publication-title: Cell Rep doi: 10.1016/j.celrep.2017.09.039 contributor: fullname: H Mathys – volume: 425 start-page: 265 year: 2009 ident: 377_CR46 publication-title: Biochem J doi: 10.1042/BJ20090856 contributor: fullname: J Esser – volume-title: An inducible cre recombinase driven by Cx3cr1. 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Snippet | Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation. However,... Background Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation.... BACKGROUNDProteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation.... Abstract Background Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of... |
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SubjectTerms | Advertising executives Alzheimer Disease - metabolism Alzheimer's disease Analysis Animals Brain Brain - metabolism CD11b antigen Cognitive ability Cognitive Dysfunction - pathology Contamination Disease Models, Animal Endoplasmic reticulum Endoplasmic Reticulum - metabolism FACS Flow cytometry Flow Cytometry - methods Fluorescence Genetic aspects Humans Immune system Inflammation Laboratory animals Lipopolysaccharides Macrophages - metabolism MACS Mass spectrometry Mass spectroscopy Mice Microfilament Proteins - metabolism Microglia Microglia - metabolism Mitochondria Mitogens Moesin Molecular modelling Neurodegenerative diseases Neurons Pathogenesis Pathology Peptides Phagocytosis Phosphatase Physiological aspects Protein turnover Proteins Proteomes Proteomics Proteomics - methods Ribosomal proteins Senile plaques siRNA Tumor necrosis factor |
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