Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of app processing

Luiz Miguel Camargo; Xiaohua Douglas Zhang; Patrick Loerch; Ramon Miguel Caceres; Shane D. Marine; Paolo Uva; Marc Ferrer; Emanuele De Rinaldis; David J. Stone; John Majercak; William J. Ray; Yi An Chen; Mark S. Shearman; Kenji Mizuguchi

doi:10.1371/journal.pone.0115369

Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of app processing

Luiz Miguel Camargo, Xiaohua Douglas Zhang, Patrick Loerch, Ramon Miguel Caceres, Shane D. Marine, Paolo Uva, Marc Ferrer, Emanuele De Rinaldis, David J. Stone, John Majercak, William J. Ray, Yi An Chen, Mark S. Shearman, Kenji Mizuguchi

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPP α. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

Original language	English
Article number	e0115369
Journal	PLoS ONE
Volume	10
Issue number	2
DOIs	https://doi.org/10.1371/journal.pone.0115369
State	Published - Feb 27 2015

Bibliographical note

Funding Information:
The authors have the following interests. This study was funded by Merck & Co. All authors, with the exception of Kenji Mizuguchi (KM) and Chen Yi-An (CYA), were employed by Merck & Co during the time the research was conducted. Luiz Miguel Camargo (LMC) is currently employed by Novartis Institutes for Biomedical Research. Co-authors Patrick Loerch (PL), Mike Caceres (MC), Xiaohua Douglas Zhang (XDZ), Shane D. Marine (SDM), and David J. Stone (DJS) are currently employed by Merck & Co. Co-author Mark, S, Shearman is currently employed by Merck Serono. Co-author John Majercak is currently employed by Boehringer Ingelheim. Co-author Willian J. Ray is currently employed by Takeda Pharmaceuticals. Co-authors PU, MF, and EDR are currently employed by academic institutions. Co-author Marc Ferrer is currently employed by the National Institutes of Health. Co-author Paolo Uva is currently employed by CRS4 Bioinformatica. Co-author EDR is currently employed by Kings College London. KM and CY are both employed by NIBIO. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Publisher Copyright:
© 2015 Camargo et al.

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (all)
Agricultural and Biological Sciences (all)
General

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1371/journal.pone.0115369

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Camargo, L. M., Zhang, X. D., Loerch, P., Caceres, R. M., Marine, S. D., Uva, P., Ferrer, M., De Rinaldis, E., Stone, D. J., Majercak, J., Ray, W. J., Chen, Y. A., Shearman, M. S., & Mizuguchi, K. (2015). Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of app processing. PLoS ONE, 10(2), [e0115369]. https://doi.org/10.1371/journal.pone.0115369

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title = "Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of app processing",

abstract = "The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPP α. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the {"}regulatory landscape{"} of APP.",

author = "Camargo, {Luiz Miguel} and Zhang, {Xiaohua Douglas} and Patrick Loerch and Caceres, {Ramon Miguel} and Marine, {Shane D.} and Paolo Uva and Marc Ferrer and {De Rinaldis}, Emanuele and Stone, {David J.} and John Majercak and Ray, {William J.} and Chen, {Yi An} and Shearman, {Mark S.} and Kenji Mizuguchi",

note = "Funding Information: The authors have the following interests. This study was funded by Merck & Co. All authors, with the exception of Kenji Mizuguchi (KM) and Chen Yi-An (CYA), were employed by Merck & Co during the time the research was conducted. Luiz Miguel Camargo (LMC) is currently employed by Novartis Institutes for Biomedical Research. Co-authors Patrick Loerch (PL), Mike Caceres (MC), Xiaohua Douglas Zhang (XDZ), Shane D. Marine (SDM), and David J. Stone (DJS) are currently employed by Merck & Co. Co-author Mark, S, Shearman is currently employed by Merck Serono. Co-author John Majercak is currently employed by Boehringer Ingelheim. Co-author Willian J. Ray is currently employed by Takeda Pharmaceuticals. Co-authors PU, MF, and EDR are currently employed by academic institutions. Co-author Marc Ferrer is currently employed by the National Institutes of Health. Co-author Paolo Uva is currently employed by CRS4 Bioinformatica. Co-author EDR is currently employed by Kings College London. KM and CY are both employed by NIBIO. There are no patents, products in development or marketed products to declare. This does not alter the authors{\textquoteright} adherence to all the PLOS ONE policies on sharing data and materials. Publisher Copyright: {\textcopyright} 2015 Camargo et al.",

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AU - Camargo, Luiz Miguel

AU - Zhang, Xiaohua Douglas

AU - Loerch, Patrick

AU - Caceres, Ramon Miguel

AU - Marine, Shane D.

AU - Uva, Paolo

AU - Ferrer, Marc

AU - De Rinaldis, Emanuele

AU - Stone, David J.

AU - Majercak, John

AU - Ray, William J.

AU - Chen, Yi An

AU - Shearman, Mark S.

AU - Mizuguchi, Kenji

N1 - Funding Information: The authors have the following interests. This study was funded by Merck & Co. All authors, with the exception of Kenji Mizuguchi (KM) and Chen Yi-An (CYA), were employed by Merck & Co during the time the research was conducted. Luiz Miguel Camargo (LMC) is currently employed by Novartis Institutes for Biomedical Research. Co-authors Patrick Loerch (PL), Mike Caceres (MC), Xiaohua Douglas Zhang (XDZ), Shane D. Marine (SDM), and David J. Stone (DJS) are currently employed by Merck & Co. Co-author Mark, S, Shearman is currently employed by Merck Serono. Co-author John Majercak is currently employed by Boehringer Ingelheim. Co-author Willian J. Ray is currently employed by Takeda Pharmaceuticals. Co-authors PU, MF, and EDR are currently employed by academic institutions. Co-author Marc Ferrer is currently employed by the National Institutes of Health. Co-author Paolo Uva is currently employed by CRS4 Bioinformatica. Co-author EDR is currently employed by Kings College London. KM and CY are both employed by NIBIO. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. Publisher Copyright: © 2015 Camargo et al.

PY - 2015/2/27

Y1 - 2015/2/27

N2 - The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPP α. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

AB - The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPP α. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

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Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of app processing

Abstract

Bibliographical note

ASJC Scopus subject areas

UN SDGs

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