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APP Is a Context-Sensitive Regulator of the Hippocampal Presynaptic Active Zone.

Laßek M, Weingarten J, Wegner M, Mueller BF, Rohmer M, Baeumlisberger D, Arrey TN, Hick M, Ackermann J, Acker-Palmer A, Koch I, Müller U, Karas M, Volknandt W - PLoS Comput. Biol. (2016)

Bottom Line: Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry.The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis.The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.

View Article: PubMed Central - PubMed

Affiliation: Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.

ABSTRACT
The hallmarks of Alzheimer's disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Aβ-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.

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Overview of the experimental design.A Workflow of subcellular fractionation and immunopurification of the native hippocampal PAZ. B Experimental outline of isobaric labeling of peptides with TMT6 and MS analysis by nano-high-pressure liquid chromatography (nHPLC-ESI). C Example of peptide signals (m/z) for the six reporter groups. D Differences in protein abundance of hippocampal PAZ constituents between APP-mutant and control. E Pie chart diagram of proteins attributed to the PAZ. F Scheme of a PPI network illustrating proteins (exemplarily designated as A-K) as nodes and edge betweeness. The thickness of the connections represents the importance of the respective edges for information flow within the network (edge betweenness). Change in abundance of more than ±10% is reflected by increasing sizes of nodes. The color code corresponds to the degree of up- (magenta) and downregulation (green). Nodes in yellow represent proteins with changes in abundance of less than ±10%. UF, upper fractions; LF, lower fractions; IP, immunopurification, MB, magnetic bead; PM, plasma membrane; SV, synaptic vesicle, SC, signaling cascade; CS, cytoskeleton; ME, metabolic enzymes; MI, mitochondria; O, others.
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pcbi.1004832.g001: Overview of the experimental design.A Workflow of subcellular fractionation and immunopurification of the native hippocampal PAZ. B Experimental outline of isobaric labeling of peptides with TMT6 and MS analysis by nano-high-pressure liquid chromatography (nHPLC-ESI). C Example of peptide signals (m/z) for the six reporter groups. D Differences in protein abundance of hippocampal PAZ constituents between APP-mutant and control. E Pie chart diagram of proteins attributed to the PAZ. F Scheme of a PPI network illustrating proteins (exemplarily designated as A-K) as nodes and edge betweeness. The thickness of the connections represents the importance of the respective edges for information flow within the network (edge betweenness). Change in abundance of more than ±10% is reflected by increasing sizes of nodes. The color code corresponds to the degree of up- (magenta) and downregulation (green). Nodes in yellow represent proteins with changes in abundance of less than ±10%. UF, upper fractions; LF, lower fractions; IP, immunopurification, MB, magnetic bead; PM, plasma membrane; SV, synaptic vesicle, SC, signaling cascade; CS, cytoskeleton; ME, metabolic enzymes; MI, mitochondria; O, others.

Mentions: The native hippocampal PAZ from age-matched individual mice was subjected to subcellular fractionation and immunopurification (Fig 1A) [14]. Importantly, the synaptic vesicle protein SV2, the target protein applied for immunopurification, revealed no change in abundance in either APP-mutant (S1 Table; APP-mutant/control 0.997). For the setup of the PPI-network, we analyzed the experimental data derived from APP single KO mice and conditional APP/APLP2 double knockout mice (NexCre-cDKO) as compared to the respective controls. To identify changes in protein abundance between two or more biological conditions, we employed an isobaric labeling approach (tandem mass tag, TMT6) combined with high-resolution mass spectrometry (Fig 1B). The abundance of reporter tags reflects the ratio of peptides in biological triplicates and was used for quantification (Fig 1C). Significantly identified proteins were plotted in an ascending order according to their changes in protein abundance (mutant/control) (Fig 1D). A common core proteome (~1100 proteins) was defined, including only those proteins being identified in all animals (n = 12) and in all experiments (Fig 1E and S1 Table). Furthermore, these core proteins were categorized into different groups within the hippocampal PAZ and were assigned as follows: integral and associated presynaptic plasma membrane proteins (PM), integral and associated synaptic vesicle proteins (SV), signaling cascade (SC), cytoskeleton (CS), metabolic enzymes (ME), mitochondria (M) and yet uncharacterized proteins named others (O) (Fig 1E). The percentage composition of the different categories is depicted in the pie chart (Fig 1E). All proteins within the pie chart were further filtered and visualized according to their subcellular localization and their functional allocation (clustering) by creating a PPI network (scheme Fig 1F; additional information about PPI networks is provided in S1 Text), excluding all non-physical and non-validated interactions.


APP Is a Context-Sensitive Regulator of the Hippocampal Presynaptic Active Zone.

Laßek M, Weingarten J, Wegner M, Mueller BF, Rohmer M, Baeumlisberger D, Arrey TN, Hick M, Ackermann J, Acker-Palmer A, Koch I, Müller U, Karas M, Volknandt W - PLoS Comput. Biol. (2016)

Overview of the experimental design.A Workflow of subcellular fractionation and immunopurification of the native hippocampal PAZ. B Experimental outline of isobaric labeling of peptides with TMT6 and MS analysis by nano-high-pressure liquid chromatography (nHPLC-ESI). C Example of peptide signals (m/z) for the six reporter groups. D Differences in protein abundance of hippocampal PAZ constituents between APP-mutant and control. E Pie chart diagram of proteins attributed to the PAZ. F Scheme of a PPI network illustrating proteins (exemplarily designated as A-K) as nodes and edge betweeness. The thickness of the connections represents the importance of the respective edges for information flow within the network (edge betweenness). Change in abundance of more than ±10% is reflected by increasing sizes of nodes. The color code corresponds to the degree of up- (magenta) and downregulation (green). Nodes in yellow represent proteins with changes in abundance of less than ±10%. UF, upper fractions; LF, lower fractions; IP, immunopurification, MB, magnetic bead; PM, plasma membrane; SV, synaptic vesicle, SC, signaling cascade; CS, cytoskeleton; ME, metabolic enzymes; MI, mitochondria; O, others.
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pcbi.1004832.g001: Overview of the experimental design.A Workflow of subcellular fractionation and immunopurification of the native hippocampal PAZ. B Experimental outline of isobaric labeling of peptides with TMT6 and MS analysis by nano-high-pressure liquid chromatography (nHPLC-ESI). C Example of peptide signals (m/z) for the six reporter groups. D Differences in protein abundance of hippocampal PAZ constituents between APP-mutant and control. E Pie chart diagram of proteins attributed to the PAZ. F Scheme of a PPI network illustrating proteins (exemplarily designated as A-K) as nodes and edge betweeness. The thickness of the connections represents the importance of the respective edges for information flow within the network (edge betweenness). Change in abundance of more than ±10% is reflected by increasing sizes of nodes. The color code corresponds to the degree of up- (magenta) and downregulation (green). Nodes in yellow represent proteins with changes in abundance of less than ±10%. UF, upper fractions; LF, lower fractions; IP, immunopurification, MB, magnetic bead; PM, plasma membrane; SV, synaptic vesicle, SC, signaling cascade; CS, cytoskeleton; ME, metabolic enzymes; MI, mitochondria; O, others.
Mentions: The native hippocampal PAZ from age-matched individual mice was subjected to subcellular fractionation and immunopurification (Fig 1A) [14]. Importantly, the synaptic vesicle protein SV2, the target protein applied for immunopurification, revealed no change in abundance in either APP-mutant (S1 Table; APP-mutant/control 0.997). For the setup of the PPI-network, we analyzed the experimental data derived from APP single KO mice and conditional APP/APLP2 double knockout mice (NexCre-cDKO) as compared to the respective controls. To identify changes in protein abundance between two or more biological conditions, we employed an isobaric labeling approach (tandem mass tag, TMT6) combined with high-resolution mass spectrometry (Fig 1B). The abundance of reporter tags reflects the ratio of peptides in biological triplicates and was used for quantification (Fig 1C). Significantly identified proteins were plotted in an ascending order according to their changes in protein abundance (mutant/control) (Fig 1D). A common core proteome (~1100 proteins) was defined, including only those proteins being identified in all animals (n = 12) and in all experiments (Fig 1E and S1 Table). Furthermore, these core proteins were categorized into different groups within the hippocampal PAZ and were assigned as follows: integral and associated presynaptic plasma membrane proteins (PM), integral and associated synaptic vesicle proteins (SV), signaling cascade (SC), cytoskeleton (CS), metabolic enzymes (ME), mitochondria (M) and yet uncharacterized proteins named others (O) (Fig 1E). The percentage composition of the different categories is depicted in the pie chart (Fig 1E). All proteins within the pie chart were further filtered and visualized according to their subcellular localization and their functional allocation (clustering) by creating a PPI network (scheme Fig 1F; additional information about PPI networks is provided in S1 Text), excluding all non-physical and non-validated interactions.

Bottom Line: Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry.The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis.The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.

View Article: PubMed Central - PubMed

Affiliation: Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.

ABSTRACT
The hallmarks of Alzheimer's disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Aβ-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.

Show MeSH
Related in: MedlinePlus