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Accepted Manuscript
Paradoxical effects of mutant ubiquitin on Aβ plaque formation in an Alzheimer mouse
model
B.M. Verheijen, J.A.A. Stevens, R.J.G. Gentier, C.D. van ‘t Hekke, D.L.A. van den
Hove, D.J.H.P. Hermes, H.W.M. Steinbusch, J.M. Ruijter, M.O.W. Grimm, V.J.
Haupenthal, W. Annaert, T. Hartmann, F.W. van Leeuwen
PII:
S0197-4580(18)30294-X
DOI:
10.1016/j.neurobiolaging.2018.08.011
Reference:
NBA 10347
To appear in:
Neurobiology of Aging
Received Date: 11 April 2018
Revised Date:
3 July 2018
Accepted Date: 10 August 2018
Please cite this article as: Verheijen, B.M., Stevens, J.A.A., Gentier, R.J.G., van ‘t Hekke, C.D., van
den Hove, D.L.A., Hermes, D.J.H.P., Steinbusch, H.W.M., Ruijter, J.M., Grimm, M.O.W., Haupenthal,
V.J., Annaert, W., Hartmann, T., van Leeuwen, F.W., Paradoxical effects of mutant ubiquitin on
Aβ plaque formation in an Alzheimer mouse model, Neurobiology of Aging (2018), doi: 10.1016/
j.neurobiolaging.2018.08.011.
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ACCEPTED MANUSCRIPT
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Paradoxical effects of mutant ubiquitin on Aβ plaque formation in
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an Alzheimer mouse model
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B.M. Verheijen1,‡, J.A.A. Stevens1,‡, R.J.G. Gentier1,‡, C.D. van ‘t Hekke1, D.L.A. van den
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Hove1,2, D.J.H.P. Hermes1, H.W.M. Steinbusch1, J.M. Ruijter3, M.O.W. Grimm4, V.J.
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Haupenthal4, W. Annaert5, T. Hartmann4 and F.W. van Leeuwen1,*
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Sciences, Maastricht University, Maastricht, The Netherlands
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Department of Psychiatry and Neuropsychology, Faculty of Health Medicine and Life
Department of Psychiatry, Psychosomatics and Psychotherapy, University of Würzburg,
Würzburg, Germany
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Department of Medical Biology, Academic Medical Center, Amsterdam, The Netherlands
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Deutsches Institut für DemenzPrävention, University of Saarland, Experimental Neurology,
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Homburg, Germany
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Belgium
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VIB Center for Brain and Disease Research and KU Leuven, Gasthuisberg, O&N4, B-3000,
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Joint first-authors
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Keywords: mutant ubiquitin, ubiquitin-proteasome system, γ-secretase, amyloid-β, behavior,
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Alzheimer’s disease
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*Corresponding author: f.vanleeuwen@maastrichtuniversity.nl
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Acknowledgements
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F.W. van Leeuwen was supported by ISAO (#06502 and 09514) and Hersenstichting
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Nederland (2008.17 and 15F07.48). Prof. D.A. Hopkins (Dalhousie University, Halifax, NS,
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Canada) is acknowledged for critical evaluation of an early version of the manuscript and was
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supported by an ISAO Visiting Professorship and by the Department of Neuroscience of
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Maastricht University. We thank V. Baert for help with the immunoblotting experiments. J.J.
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Cheng is acknowledged for performing behavioral assays. We are grateful to Prof. D.R.
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Borchelt (Center for Translational Research in Neurodegenerative Disease, Department of
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Neuroscience, Gainesville, FL, USA) for providing the original APPSwe/PS1∆E9 mouse line
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(line 85). W.A. is supported by VIB, KU Leuven (C16/15/073), the federal government (IAP
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P7/16), the FWO (S006617N, G078117N and G056017N) and SAO (S#16018).
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Abstract
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Amyloid-β (Aβ) plaques are a prominent pathological hallmark of Alzheimer’s disease (AD).
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They consist of aggregated Aβ peptides, which are generated through sequential proteolytic
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processing of the transmembrane protein amyloid precursor protein (APP), and several Aβ-
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associated factors. Efficient clearance of Aβ from the brain is thought to be important to
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prevent the development and progression of AD. The ubiquitin-proteasome system (UPS) is
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one of the major pathways for protein breakdown in cells and it has been suggested that
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impaired UPS-mediated removal of protein aggregates could play an important role in the
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pathogenesis of AD. To study the effects of an impaired UPS on Aβ pathology in vivo,
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transgenic APPSwe/PS1∆E9 mice (APPPS1) were crossed with transgenic mice expressing
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mutant ubiquitin (UBB+1), a protein-based inhibitor of the UPS. Surprisingly, the
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APPPS1/UBB+1 crossbreed showed a remarkable decrease in Aβ plaque load during aging.
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Further analysis showed that UBB+1 expression transiently restored PS1-NTF expression and
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γ-secretase activity in APPPS1 mice. Concurrently, UBB+1 decreased levels of β-APP-CTF,
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which is a γ-secretase substrate. Although UBB+1 reduced Aβ pathology in APPPS1 mice, it
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did not improve the behavioral deficits in these animals.
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Highlights
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Mutant ubiquitin partially restores γ-secretase activity and reduces β-APP-CTF levels and
Aβ plaque load in APPPS1/UBB+1 mice
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Mutant ubiquitin transiently increases PS1-NTF levels in APPPS1/UBB+1 mice
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Mutant ubiquitin does not rescue the impaired behavioral phenotype of APPPS1 mice
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Introduction
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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common
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cause of dementia. AD is clinically characterized by progressive memory loss and
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impairments in multiple cognitive domains (Scheltens et al., 2016). Currently, there is no
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cure: immunization and γ-secretase inhibitor trials in AD patients have not been effective in
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terms of reduction of dementia (e.g., (De Strooper, 2014; Hardy and De Strooper, 2017)).
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Little is known on the extent to which pathogenic factors drive the development of AD at
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different stages. To better understand AD, biochemical processes that are thought to underlie
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the disease should be scrutinized in the context of the cellular phase of AD (De Strooper and
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Karran, 2016).
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One of the neuropathological hallmarks of AD is the presence of extracellular plaques
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containing aggregated amyloid-β (Aβ) (Goedert and Spillantini, 2006; Gouras et al., 2005;
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Pensalfini et al., 2014). Aβ peptides are generated via β- and γ-secretase-mediated cleavage of
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amyloid precursor protein (APP), a type-1 transmembrane glycoprotein of poorly understood
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function (De Strooper et al., 2010; Müller et al., 2017). Abnormal processing of APP and AD
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are causally linked, as shown by genetic analysis of (early-onset) familial forms of AD and
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Down syndrome, stressing the importance of this process. According to the “amyloid cascade
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hypothesis” of AD, Aβ peptides (especially soluble Aβ oligomers), or aggregates thereof in
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plaques, are the direct cause of the progressive neurodegeneration in AD (Hardy and Selkoe,
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2002; Selkoe and Hardy, 2016). Therefore, lowering Aβ levels is a major therapeutic goal in
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AD. This might be achieved by modulating the production, the aggregation, or the
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degradation of Aβ.
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A growing body of evidence implicates impairment of the ubiquitin–proteasome system
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(UPS), the main intracellular proteolytic pathway in eukaryotes, in AD pathogenesis
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(Ciechanover and Brundin, 2003; Dennissen et al., 2012). A potential role for the UPS in AD
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is supported by recent genome-wide association studies (GWAS), including pathway analysis,
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and comparative proteomics experiments (International Genomics of Alzheimer's Disease
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Consortium (IGAP), 2015; Manavalan et al., 2013). Additionally, proteasome activity has
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been shown to be decreased in AD brains (Keller et al., 2001; López Salon et al., 2000).
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Interestingly, a frameshift mutant form of ubiquitin (UBB+1) has been found to accumulate in
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the neuropathological hallmarks of AD patients (Gentier and van Leeuwen, 2015; van
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Leeuwen et al., 1998). UBB+1 is a dose-dependent inhibitor of the UPS (van Tijn et al., 2007),
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and previous work has demonstrated that UBB+1 can induce neurological abnormalities
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(Fischer et al., 2009; Irmler et al., 2012).
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Although there is some evidence for a role of the UPS in APP processing leading to Aβ, and
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in the clearance of Aβ from cells, the exact contribution of the UPS to Aβ pathology remains
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poorly understood (L. Hong et al., 2014; Tseng et al., 2008). A mouse model for Aβ
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pathology (line 85, carrying familial AD (FAD)-linked APP (APPSwedish) and presenilin 1
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(PS1∆E9), hereafter referred to as APPPS1 (Jankowsky et al., 2004; 2001)), was previously
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crossbred with a mouse line that expresses UBB+1 (line 3413) to investigate the effects of
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long-term UPS inhibition on plaque formation (van Tijn et al., 2012). Unexpectedly, the
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resulting APPPS1/UBB+1 triple transgenic mice showed a decrease in Aβ plaque formation
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during aging. The mechanisms underlying this phenomenon remain unknown (van Tijn et al.,
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2012).
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In the present study, we show that the paradoxical effect of UBB+1 on Aβ load depends on the
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alteration of γ-secretase activity by UBB+1. γ-secretase activity is reduced in APPPS1 mice,
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apparently due to PS1∆E9-induced “poisoning” of the γ-secretase complex (De Strooper,
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2007; Woodruff et al., 2013). UBB+1 causes a transient increase in PS1-NTF in APPPS1 mice
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and partially restores γ-secretase activity, lowering the Aβ burden. Although UBB+1 reduces
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Aβ pathology in APPPS1 mice, it does not reduce the behavioral deficits in these animals.
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Materials and methods
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Animals
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Mouse lines were described previously (van Tijn et al., 2012). Line 3413 expresses human
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UBB+1 under control of the murine CamKIIa promoter on a pure C57BL/6 background
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(Fischer et al., 2009). Distribution of UBB+1 is widespread and specific in the brains of these
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animals (Fischer et al., 2009; Gentier et al., 2015; Verheijen et al., 2017). Transgenic line
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APPPS1 (line 85, APPSwe/PS1∆E9), previously described by (Jankowsky et al., 2004), carries
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a co-integrate of (1) chimeric mouse/human APP695 carrying the Swedish mutation
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(K594M/N595L) and (2) human PS1 with deletion of exon 9 (Jankowsky et al., 2001), each
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under control of a mouse prion protein promoter. UBB+1-expressing transgenic mice were
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crossed with APPPS1 mice to generate APPPS1/UBB+1 triple transgenic mice (van Tijn et al.,
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2012). Transgenic lines were maintained on their respective genetic background by breeding
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homozygous mice to wild-type (WT) mice for more than 20 generations (Couch et al., 2013).
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Genotyping was performed by PCR analysis of tail DNA. WT littermates were used as
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controls. Mice were kept in group housing on a 12/12 h light–dark cycle with food and water
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ad libitum in specific pathogen free conditions. Details on animal numbers and tissue
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collection can be found in the supplementary material. All experimental animal research was
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executed according to protocols approved by the local Animal Ethical Committee of
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Maastricht University and met governmental guidelines.
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Immunohistochemistry and image analysis
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Immunohistochemistry and image analysis were performed as described previously (van Tijn
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et al., 2012). In brief, mouse brains were bisected along the midline and sectioned into 50 µm
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thick sections on a vibratome (Leica VT1000S). To detect and quantify Aβ plaque load,
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sections were pre-treated with formic acid solution (30 min) and incubated with mouse
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monoclonal anti-Aβ antibody 6E10 (1:16000; Signet 9300-02) overnight. Sections were
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further processed using the peroxidase-anti-peroxidase method and Ni-3,3’-diaminobenzidine
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color reaction.
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For analysis of Aβ plaque load and UBB+1 levels, photographs were made using a Zeiss
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Axioskop microscope with Neofluor 2.5x and 5x objectives and a 558.5 nm bandpass filter
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(type DMZ-12, ITOS), connected to a Sony XC-77CE CCD black and white camera. Three
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coronal sections per hemisphere were captured, corresponding to anterior-posterior -1.22, -
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1.82 and -2.30/2.46 relative to bregma (Paxinos and Watson, 2001). In each section, the entire
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cerebral cortex, hippocampus and dentate gyrus were outlined by hand according to Paxinos
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et al. (Paxinos and Watson, 2001) and analyzed. Structure volume (mm3) and Aβ plaque
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density (volume percentage) were measured with a custom-made analysis program in Image-
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Pro Plus software (version 5.1, MediaCybernetics) and Cavalieri’s principle of volume
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estimation (Gundersen and Jensen, 1987). UBB+1 levels were determined by measuring the
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integrated optical density (IOD) of UBB+1 staining per outlined brain area. The experimenter
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was blind to the genotype of the mice.
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Aβ plaque density differences between age groups (3, 6, 9 and 11 months) and genotypes
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(APPPS1 and APPPS1/UBB+1) were compared using two-way analysis of variance
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(ANOVA) for each of the delineated brain structures (cortex, hippocampus and gyrus
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dentatus) using SPSS for Windows (IBM, version 23.0.0.3). Statistical significance was
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accepted at p<0.05.
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Secretase measurements
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Secretase measurements were performed as described previously, with some modifications
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(Grimm et al., 2016; 2013). Mouse brain tissue (hemispheres) was homogenized using 1.4
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mm ceramic beads in a Precellys Minilys (Peqlab, Erlangen, Germany) for 30 s at maximum
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speed in sucrose buffer (10 mM Tris-HCl pH 7.4, 1 mM EDTA, 200 mM sucrose) (without
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chelator in case of α-secretase measurement). Samples were adjusted to a concentration of 4
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mg/ml of total protein using BCA-assay (Smith et al., 1985).
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Post-nuclear fractions were prepared by centrifuging samples at 900 g for 10 min at 4°C.
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Fractions enriched in membranes were prepared by centrifugation at 55000 rpm for 75 min at
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4°C in an Optima MAX Ultracentrifuge with a TLA-55 rotor (Beckmann Coulter, Krefeld,
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Germany). The pellet was solubilized using 0.5 mm glass beads in a Precellys Minilys
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(Peqlab, Erlangen, Germany) for 10 s at minimum speed in sucrose buffer (10 mM Tris-HCl
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pH 7.4, 1 mM EDTA, 200 mM sucrose). For determination of α-secretase activity, samples
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were supplemented with 5 µM ZnCl2 and 5 µM MgCl2.
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α-, β- or γ-secretase activities were measured at 37 °C in a black 96-well plate (BD, Franklin
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Lakes, NJ, USA) by detection of the cleavage of a specific substrate in a Safire2 Fluorometer
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(Tecan, Germany) for β-secretase activity or in an Infinite M1000 Pro (Tecan, Germany) for
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α-secretase and γ-secretase activity.
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For the determination of γ-secretase activity, 500 µg of protein per 100 µl was used. Kinetics
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were started by adding 10 µM γ-secretase substrate (#565764, Calbiochem, Darmstadt,
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Germany). γ-secretase activity was measured with an excitation wavelength of 355 nm
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(bandwidth 10nm) and an emission wavelength of 440 nm (bandwidth 10 nm). Kinetic was
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carried out for 50 cycles with intervals of 180 s.
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For α-secretase the substrate #II-565767 was used, while for β-secretase, #IV-565758 was
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used (both from Calbiochem, Darmstadt, Germany). For measurement of β-secretase activity,
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samples were diluted 1:1 in PBS, pH 4.5 and 100 µl of this dilution, corresponding to 250 µg
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of total protein, was used. Then, 20 µM of β-secretase substrate IV (Calbiochem, Darmstadt,
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Germany) was added. β-secretase activity was measured with an excitation wavelength of
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345nm (bandwidth 5 nm) and an emission wavelength of 500 nm (bandwidth 5 nm). Kinetic
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was carried out for 75 cycles with intervals of 80 s.
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For determination of α-secretase activity, 100 µl sample, corresponding to 100 µg total
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protein, was measured. The α-secretase substrate II was used (Calbiochem, Darmstadt,
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Germany) in a final concentration of 3 µM. Measurement parameters were adjusted to an
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excitation wavelength of 340 nm (bandwidth 10 nm) and an emission wavelength of 490 nm
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(bandwidth 10nm). Kinetic was carried out for 70 cycles with intervals of 120 s.
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Specificity of the assays was monitored by using the following secretase inhibitors: α-
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secretase: 100 µM GM6001 (Calbiochem, Darmstadt), β-secretase: 2 µM Inhibitor IV
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(Calbiochem, Darmstadt) and γ-secretase: 20 µM Inhibitor X (Calbiochem, Darmstadt).
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Statistical analyses were performed using GraphPad Prism 6 Software (Grappa, San Diego,
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CA, USA) by one-way ANOVA, followed by Bonferroni’s multiple comparisons test. Values
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are presented as mean±SEM. Differences between groups were considered significant when
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p≤0.05.
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Western blotting
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Brain hemispheres were homogenized in lysis buffer consisting of STE buffer (250 mM
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sucrose, 5 mM Tris-HCl, and 1 mM EGTA, pH 7.4) with 1% Triton X-100 and a mix of
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protease inhibitors (Roche cOmplete™ Protease Inhibitor Cocktail, cat. no. 11697498001) and
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phosphatase inhibitors (2.5 mM sodium pyrophosphate and 1 mM β-glycerol phosphate
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disodium salt) on ice for 20 min. Lysates were centrifuged at 13000 rpm for 15 min at 4°C.
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Total protein amounts of supernatants were quantified using a standard Bradford assay
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(Pierce). Absorbance (A: 595 nm; 0.1 s/well) was measured with a Victor3 plate reader
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(Perkin Elmer) and lysates were diluted in water (Baxter). Samples (final protein
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concentration: 2 µg/µl) were prepared with sample buffer (4x LDS and 4% 2-
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mercaptoethanol) and lysis buffer followed by incubation in a heater for 10 min at 70°C.
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From each sample, 20 µg of protein was separated using electrophoreses (40 min at 200 V /
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400 mA) in 1x MES running buffer (Invitrogen) on 4-12% bis-tris pre-casted gels (Invitrogen)
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along with SeeBlue Plus2 marker (Invitrogen). Proteins were blotted (100 V / 350 mA
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overnight at 4°C) onto nitrocellulose membranes (Invitrogen) using 1x transfer buffer
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(NuPAGE). Membranes were blocked using blocking buffer (5% milk powder, TBS, 0.1%
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Tween-20) for 1 h at room temperature (RT).
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Primary antibodies (3h at RT) were diluted in blocking buffer (supplementary material).
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Primary antibodies were recognized by horseradish peroxidase-conjugated secondary
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antibodies (goat anti-mouse (GAMPO; Alexa 700, red) or goat anti-rabbit (GARPO; Alexa
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800, green); 1:10000; 1h at RT). Blots were developed using enhanced chemiluminescence
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(ECL) Western Blotting kit (Perkin Elmer) and measured with a Fuji LAS3000. Protein bands
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were quantified by measuring pixel intensity using AIDA Image Analyzer v4.27 software
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(Raytest) and normalized for GAPDH.
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Statistical analyses were performed using Mann-Whitney U-test. Values are presented as
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mean±SEM. Differences between groups were considered significant when p≤0.05.
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Behavior testing
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Nest building
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Mice were housed for 1 week in single cages containing sawdust. On the day before testing, a
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piece of cotton (the so-called Nestlet, 5 x 5 cm; Ancare, Bellmore) was introduced in the
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home cage to permit nesting. The following morning the nests were assessed, according to a
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five-point scale ranging from 1 to 5: 1 = Nestlet not noticeably touched, 2 = Nestlet partially
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torn up, 3 = mostly shredded but often with no identifiable nest site, 4 = an identifiable, but
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flat nest, and 5 = a (near) perfect nest (Deacon, 2006; Deacon et al., 2008).
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Spontaneous alternation Y-maze test
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Performance in the spontaneous alternation Y-Maze was used as to assess spatial working
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memory. The maze was build out of 3 acrylic arms of 40 cm length arranged at a 120° angle.
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A mouse was placed in the end of one arm of the Y-maze and was allowed to explore freely
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during a 6 min session. The maze was thoroughly cleaned with 70% ethanol between tests.
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The sequence and total number of arms entered were recorded. The percentage of alternations
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was calculated as the total number of triads divided by the maximum possible of triads (total
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number of arm entries minus 2), with a triad defined as a consecutive visit through all three
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arms.
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Morris water maze
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The Morris water maze (MWM) used was a white circular pool (80 cm in diameter) divided
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into four equal imaginary quadrants for data analysis. The water was made opaque by addition
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of white non-toxic latex paint, water temperature was maintained at 24±2 C°. A white circular
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platform (6 cm in diameter) was placed beneath the surface of the water. The swimming
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patterns of the mice were recorded with a video camera mounted above the center of the pool
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and analyzed with the EthoVision video-tracking system. The water maze was located in a
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room with several visual stimuli hanging on the walls to provide spatial cues. The acquisition
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phase was carried out during four to five consecutive days. On each training day/session, the
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mice received 3 consecutive training trials with the hidden platform kept in a fixed position. A
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different starting location was used for each trial. Mice that were not able to find the platform
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within 60 s were guided to the platform by the experimenter. To assess spatial retention, a 60
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s probe trial with the platform removed from the pool was given one day after the last hidden
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platform trial. The time spent swimming in the quadrants was recorded, and the percentages
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of time spent in the target quadrant (where the platform was located during hidden platform
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training) were analyzed.
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Contextual and cued fear conditioning
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Contextual and cued fear conditioning (FC) was used to assess hippocampal and fear
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memory. Mice were conditioned in a transparent acrylic chamber (40x40 cm) with a metal
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grid floor. A sound generator attached to the side of the chamber provided a 70 dB tone (cued
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conditioned stimulus (CS)) for 20 s. Mice were first allowed to explore the chamber for 2 min
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after which 4 trials of paired stimuli were presented, spaced 1 min apart. During the last 2 s of
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the CS, a foot shock of 0.75 mA was given (unconditioned stimulus (US)). 24 h after
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conditioning, contextual freezing behavior was assessed by measuring freezing during 2 min
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in the same cage. One day later, cued recall was tested by placing the mice in a modified
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chamber (triangular chamber in which the grid was covered by a textured white floorboard),
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and freezing was analyzed during the presentation of the tone (4 times). Freezing was
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analyzed using Ethovision XT.
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Statistics
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Comparisons between groups for the behavioral measures were done by a two-way ANOVA,
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except for the MWM, which was analyzed with repeated measures tests using the different
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trials as repeated measure. Age and genotype were used as factors. For interaction analysis,
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one-way ANOVAs on genotype were performed. Fear conditioning data was analyzed with a
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two-way ANCOVA model, using baseline freezing as a covariate. LSD correction was
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applied to post-hoc analysis. Statistical analysis was performed using SPSS 23 (IBM).
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Results
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UBB+1 reduces Aβ plaque load in APPPS1 mice
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Immunohistochemistry was performed on mouse brain slices (WT, UBB+1, APPPS1 and
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APPPS1/UBB+1) and Aβ plaque load in cerebral cortex and hippocampus was quantified. This
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analysis revealed an unexpected age-dependent decrease of Aβ plaque load in the AD model
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expressing UBB+1 (Fig. 1). For each of the brain structures, two-way ANOVA showed
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significant effects of age and genotype on Aβ plaque density, but no significant interaction
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between age and genotype for APPPS1 and APPPS1/UBB+1. The absence of a significant
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interaction effect indicates that the genotype effect is independent of the age group and thus
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that the phenotype effect is present at every age. The same test was performed on Aβ plaque
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density for the genotypes WT and UBB+1. This test showed no significant effects of age or
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genotype. These findings corroborate previous findings on a modulating effect of UBB+1 on
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Aβ pathology in mice (van Tijn et al., 2012), showing a decrease in plaque load over a
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prolonged period of time. No changes in Aβ plaque micro-environment were observed (i.e.,
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reactive gliosis (van Tijn et al., 2012) and not shown). Aβ accumulation did not induce
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additional accumulation of UBB+1 (van Tijn et al., 2012).
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UBB+1 partially restores γ-secretase activity in APPPS1 mice
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To evaluate the effects of AD mutations and UBB+1 on flux through the amyloidogenic
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pathway, measurements of α-, β- and γ-secretase activities were carried out on mouse brain
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tissue. Hemispheres from different mouse lines (WT, UBB+1, APPPS1 and APPPPS1/UBB+1)
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of different ages (3M, 6M and 9M) were lysed and subjected to enzymatic assays (Fig. 2). α-
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and β- secretase activities were unaltered in all mouse lines. γ-secretase was significantly and
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specifically decreased in APPPS1 mice at all ages. In APPPS1 mice, a slight increase in γ-
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secretase activity was observed at 9M, as compared to APPPS1 mice at earlier ages. However,
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these differences were not statistically significant (6M vs. 9M: p = 0.15). In the
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APPPPS1/UBB+1 line, a partial but significant restoration of γ-secretase activity was observed
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at 6M. γ-secretase activity in APPPPS1/UBB+1 mice was comparable at all ages tested. These
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results show that γ-secretase activity is decreased in APPPS1 mice and that UBB+1 partially
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rescues this activity at 6M.
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UBB+1 transiently increases PS1-NTF levels and reduces APP-CTFs in APPPS1 mice
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Immunoblots for different components of the γ-secretase complex were performed to explore
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a link between UBB+1 expression and partial increase in γ-secretase activity. Only PS1-NTF
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levels, the processed form of PS1 that is present as a PS1-NTF.CTF heterodimer complex
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(Edbauer et al., 2003; Thinakaran et al., 1996), was found to be significantly increased in
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APPPPS1/UBB+1 mice at 6M (Fig. 3). Additionally, APP-CTF (C99) was significantly
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downregulated in APPPPS1/UBB+1 mice, consistent with increased γ-secretase activity (Fig.
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3). A complete overview of immunoblotting experiments can be found in the supplementary
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material.
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UBB+1 does not improve behavioral outcome in APPPS1 mice
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Mice were subjected to a variety of behavioral tests to assess memory and other behavioral
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parameters in the 4 strains at different ages (Fig. 4). Differences in performance might
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indicate a modifying effect of Aβ load on functional outcomes.
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First, nest building behavior was assessed (Fig. 4A-B). Nest building activity is a spontaneous
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behavior and represents mouse wellbeing. APPPS1 and APPPS1/UBB+1 triple transgenic mice
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showed significantly impaired nest building behavior in comparison with WT and UBB+1
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mice (p<0.05 in all cases, Fig. 4B). There were no differences in nest building activities
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between WT and UBB+1 mice or between APPPS1 and APPPS1/UBB+1 mice. Differences in
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nest building activity remained present as animals aged.
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Next, working memory was assessed in the alternating Y-maze. No significant differences
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were present in any of the strains in the percentage of alternations (Fig. 4C). A trend showing
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more entries for APPPS1 and APPPS1/UBB+1 mice as compared to WT controls was
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observed (data not shown).
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Additionally, the Morris Water Maze (MWM) test was used as a test of spatial memory
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performance. While there was no difference in acquisition time between the strains, APPPS1
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and APPPS1/UBB+1 mice spent significantly less time in the target quadrant during the probe
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trial in comparison to WT animals (p<0.05), but not compared to UBB+1 animals. There was
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no difference between ages (Fig. 4D-E).
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The contextual fear conditioning (FC) is mostly hippocampus-dependent whereas the cued FC
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test mainly indicates integrity of amygdala and cerebellum (Buccafusco, 2009). The
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contextual FC tests showed no impairment of memory between any of the strains at any of the
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tested ages (Fig. 4F). However, all 9-months-old animals performed significantly worse than
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young animals (p<0.001). UBB+1 mice had impaired cued FC memory compared to WT and
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APPPS1 mice (p<0.01), but performed similarly to APPPS1/UBB+1 mice at 3 months of age
401
(Fig. 4G). At 6 months of age, UBB+1, APPPS1 and APPPS1/UBB+1 mice all performed
402
worse than WT mice (p<0.001). APPPS1 mice had the most severe memory problems,
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scoring significantly lower than UBB+1 mice (p<0.001), but interestingly APPPS1/UBB+1
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performed better that APPPS1 mice (p<0.05), matching the altered Aβ load. At 9 months of
405
age, no significant differences between groups could be detected, although there was a trend
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for APPPS1/UBB+1 mice to perform worse than WT mice (p=0.054). This lack of difference
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could be due to the poor performance of the older mice in general, with 9-month-old mice
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scoring significantly lower than young mice (p<0.001).
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Discussion
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UBB+1 was found to decrease Aβ burden in APPPS1 mice (van Tijn et al., 2012), a mouse
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line in which the development and progression of (Aβ) pathology has been described in detail
418
(Garcia-Alloza et al., 2006; Janus et al., 2015; Volianskis et al., 2010). In the present study,
419
we showed that this UBB+1-mediated effect depends, at least in part, on partial restoration of
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γ-secretase activity in APPPS1 mice (Fig. 5). Preserved γ-secretase activity resulted in
421
reduced levels of β-APP-CTF and decreased Aβ42 levels (van Tijn et al., 2012).
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Specifically, γ-secretase activity in APPPPS1/UBB+1 mice was temporarily increased
423
compared to APPPS1 mice at 6 months of age, a critical period of plaque formation (Tucker
424
et al., 2008). Understanding the precise mechanisms underlying these UBB+1-induced changes
425
will be important to explain the rather unexpected effect of UBB+1 on Aβ pathology.
426
Immunoblotting revealed that PS1-NTF levels were also increased in triple transgenic mice at
427
the 6M timepoint. PS1∆E9 that is present in APPPS1 mice cannot be endoproteolytically
428
processed by “presenilinase” activity. Presenilinase has been described as an unknown
429
protease that is required for the normal function of PS1 in the γ-secretase complex (Podlisny
430
et al., 1997), but is has become clear that autoproteolysis probably cleaves PS1 (Fukumori et
431
al., 2010; Wolfe et al., 1999). Therefore, UBB+1 increased levels of WT PS1-NTF in APPPS1
432
mice. UBB+1 might regulate PS1-NTF protein expression through several mechanisms: i)
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UBB+1 may increase WT PS1 protein expression, because WT PS1 holoprotein has been
434
previously shown to be degraded by the UPS (Fraser et al., 1998). However, levels of full-
435
length PS1 were found to be unaltered in APPPPS1/UBB+1 mice in preliminary experiments
436
(supplementary material); ii) UBB+1 might regulate PS1 processing (i.e., affect presenilinase
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activity), and iii) UBB+1 may regulate stability of PS1-NTF(/CTF) fragments (Steiner et al.,
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1998). We cannot exclude a role for other factors in regulating PS1-NTF levels and γ-
439
secretase activity that are affected by UBB+1. In APPPS1 mice, an age-related trend toward
440
increased γ-secretase activity was observed, although this was not statistically significant.
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Perhaps sustained γ-secretase inhibition results in a subtle compensatory rebound, e.g., by
442
altering PS1 turnover.
443
To fully appreciate the complexity of the effects of UBB+1 on APP metabolism and Aβ
444
pathology, it should be noted that UBB+1–mediated effects might be due to interference with
445
other pathways, independent of proteasome inhibition. For example, UBB+1 can signal via
446
K63-linkage (e.g., regulating neuroinflammation) (Ohtake et al., 2016; van Tijn et al., 2012),
447
acts as an inhibitor of specific deubiquitinating enzymes (DUBs) (Krutauz et al., 2014),
448
affects mitochondrial functioning (Braun et al., 2015; Tan et al., 2007), and potentially
449
impacts neuronal activity and synaptic function / long-term synaptic potentiation.
450
We propose that a combination of UBB+1-dependent changes is most likely to explain the
451
ameliorating effect of UBB+1 on Aβ load in vivo. Perhaps most interestingly, UBB+1 induces
452
chaperone expression (heat shock proteins, 14-3-3ζ) in cells, potentially conferring
453
cytoprotective effects (Hope et al., 2003; Irmler et al., 2012). Modulation of protein quality
454
control mechanisms beyond the proteasome would provide an attractive model to explain
455
diminished Aβ load in an environment of chronic UBB+1 expression. This is supported by
456
studies pointing out a role for intracellular trafficking and the endosomal-lysosomal pathway
457
in APP processing, as well as in Aβ degradation, secretion and propagation (Almeida et al.,
458
2006; Nixon, 2017; Otero et al., 2018; Small et al., 2017). Specificity of intramembrane
459
proteolysis probably depends on differential localization of distinct γ-secretase complexes and
460
substrates at the cell surface and at endosomes (Sannerud et al., 2016). The respective roles of
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different APP degradation pathways are poorly understood. With respect to APP-CTF
462
degradation, we suggest that, under physiological conditions, β-APP-CTFs are mostly cleaved
463
by γ-secretase to produce shorter Aβ peptides. Remaining APP-CTFs are cleared via the
464
endo-lysosomal pathway or by alternate proteasome-dependent pathways, like endoplasmic
465
reticulum-associated degradation. By interfering with secretase processivity in AD, the role of
466
these non-secretase-dependent degradation pathways changes, because more intraneuronal
467
APP-CTFs need to be turned over via these mechanisms. UBB+1 could play a crucial role in
468
this re-routing and in the cross-talk between different protein degradation systems.
469
In summary, the mechanism we propose for the paradoxical decrease in Aβ burden by UBB+1
470
expression in mouse brain is manifold and depends on: i) a partial rescue of γ-secretase
471
activity and APP processing, through transiently restoring PS1 levels, presumably by
472
regulating (UPS-mediated) PS1 turnover (this study), ii) induction of molecular chaperones,
473
which decrease Aβ aggregation and improve the clearance of Aβ from brains, and iii) changes
474
in intracellular transport, localization and the endo-lysosomal pathway (to be investigated).
475
Notably, UBB+1 did not improve the overall behavioral phenotype in APPPS1 mice. This may
476
be due to several factors. First, the decrease in Aβ burden in APPPPS1/UBB+1 mice is
477
relatively mild. After the onset of Aβ pathology, irreversible damage may have already
478
occurred, e.g., through neuroinflammation. Also, pre-existing Aβ burden appeared hard to
479
remove in mice (Tucker et al., 2008). There might be a role for residual Aβ oligomers
480
affecting the behavior. In addition, UBB+1 can induce behavioral defects itself (Fischer et al.,
481
2009; Irmler et al., 2012), which could counteract the beneficial effect of reducing the Aβ
482
load. Additionally, γ-secretase has many other substrates besides APP and interfering with its
483
activity could affect other processes at an early stage (De Strooper et al., 2012; Jurisch-Yaksi
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et al., 2013; Kopan and Ilagan, 2004). Lack of statistical power may also explain the absence
485
of improved behavioral phenotypes. Initially, more mice were included in the experimental
486
groups, but several mice had to be excluded due to the occurrence of seizures in these animals
487
(confirmed by neuropeptide Y immunostainings, unpublished). Aβ is known to elicit
488
epileptiform activity (Minkeviciene et al., 2009; Palop and Mucke, 2010). More detailed
489
behavioral analyses, including larger group sizes, will provide better insights into these
490
phenotypes.
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The present findings may have important translational implications. It has previously been
493
suggested to use γ-secretase activity inhibition as a therapeutic approach in AD. However,
494
some studies have indicated that maintaining healthy γ-secretase activity, rather than
495
inhibiting it, should be considered as a therapeutic strategy in AD (Barnwell et al., 2014;
496
Woodruff et al., 2013). Inhibiting γ-secretase activity in patients has actually been associated
497
with adverse events, such as skin cancers and infections (Doody et al., 2013). Our present data
498
add another level of complexity to targeting γ-secretase function in AD.
499
Importantly, most presenilin FAD mutations give rise to overall lower Aβ levels, but rather
500
shift the Aβ profile (so, a quantitative (lower) as well as qualitative (longer Aβ) effect).
501
Silencing expression of mutant alleles and pathological factors, e.g., using antisense therapies
502
or by targeting protein-protein interactions, could prove beneficial to patients. Modulators and
503
stabilizers of γ-secretase that lower Aβ without inhibiting general γ-secretase activity, e.g., by
504
restoring the carboxypeptidase-like trimming function disrupted by mutant PS1, are also of
505
considerable interest (Chávez-Gutiérrez et al., 2012; Szaruga et al., 2017; Voytyuk et al.,
506
2018). Future studies should explore the pathogenic mechanisms that drive AD in more detail:
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by restrictively modifying the expression of AD-associated factors, e.g., those implied in the
508
amyloidogenic pathway and the UPS, one should be able to accurately pinpoint key targets
509
that modify disease phenotypes. These studies should also incorporate other aspects of AD
510
pathology, like tau pathology and synaptic function, and should address the contribution of
511
additional processes and cell types (De Strooper and Karran, 2016; S. Hong et al., 2016; Lin
512
et al., 2018; Sosna et al., 2018; Venegas et al., 2017). Ultimately, it will be possible to
513
establish in vivo dose-response curves and determine critical periods in AD pathology (e.g.,
514
using other UBB+1-expressing transgenic mouse lines (van Tijn et al., 2010)), providing
515
crucial insights for therapeutic approaches.
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Conclusion
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UBB+1 decreases Aβ plaque load in APPPS1 mice through modulating γ-secretase activity
519
and reducing production of long Aβ species (i.e., APP-CTFs, long Aβ oligomers) (Fig. 5).
520
Preserving physiological γ-secretase activity at an early stage, rather than inhibiting it, should
521
be explored as a therapeutic option in AD. The effects of UBB+1 on cells are more complex
522
than previously appreciated and should be investigated in more detail in future studies.
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Figure 1. UBB+1 decreases Aβ plaque load in APPPS1 mice. Quantitative
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immunohistochemical representation by integrated optical densities of Aβ plaque load (e-f) in
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4 different mouse lines (a-d). A clear decrease in Aβ plaque load could be observed in the
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APPPS1/UBB+1 line (vs. APPPS1 mice). Values are presented as mean±SD. *p≤0.05. Bar: 1
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mm.
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Figure 2. UBB+1 partially restores γ-secretase activity in APPPS1 mice. Secretase activity
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measurements in 4 mouse lines reveal that α- and β-secretase activities do not significantly
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differ between mice. In the APPPS1 and APPPS1/UBB+1 triple tg mice, γ-secretase activity
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was significantly decreased at 3, 6 and 9 months of age as compared to WT and UBB+1 mice.
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However, in APPPS1/UBB+1 mice, the γ-secretase activity was partially restored at the age of
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6 months (vs. APPPS1 mice). *p≤0.05; **p≤0.01; ***p≤0.001.
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Figure 3. UBB+1 temporarily increases PS1-NTF levels and lowers levels of APP-CTF in
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APPPS1 mice. Protein expression levels of the PS1-NTF and β-APP-CTF were measured in
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immunoblotting experiments. APP-CTF expression was normalized against APP-FL
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expression and all expression values were normalized against GAPDH. Significantly
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increased (*p≤0.01) PS1-NTF levels (A) and significantly decreased (*p≤0.01) APP-CTF
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levels (B) were found to be present in APPPS1/UBB+1 mice as compared to APPPS1 mice at
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6 months of age. Representative blots are shown.
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Figure 4. UBB+1 does not improve behavioral phenotypes in APPPS1 mice. Mouse strains
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of different ages were tested using several behavioral assays, including nest building (A-B),
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Y-maze (C), Morris Water Maze (D-E), and fear conditioning paradigms (F-G). Values are
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presented as mean±SD (SEM in E). Combined groups (B, E) include animals of different
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genotypes, regardless of age. *p≤0.05; **p≤0.01; ***p≤0.001. No overall improvements in
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behavioral phenotypes were observed in APPPS1/UBB+1 mice (vs. APPPS1 mice).
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Figure 5. Effects of UBB+1 on APP processing in APPPS1 mice. Schematic illustration of
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changes in APPPS1 mice and in APPPS1 mice co-expressing UBB+1. In APPPS1 mice,
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PS1dE9 competes with wild-type PS1, antagonizing γ-secretase activity. Reduced γ-secretase
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activity results in less efficient processing of β-secretase-derived C99 fragments (β-APP-
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CTFs) in the amyloidogenic pathway, resulting in intraneuronally retained long hydrophobic
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APP metabolites and formation of plaques. UBB+1 induces a transient increase of PS1-NTF in
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APPPS1 mice, resulting in partial restoration of γ-secretase activity and increased processing
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of APP.
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UBB
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APPPS1
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0
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*
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2
1
Morris Water Maze combined
40
UBB
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APPPS1
30
APPPS1/UBB
20
+1
10
3
6
9
60
*
UBB+1
APPPS1
APPPS1/UBB+1
20
0
Cued Fear Conditioning
Contextual Fear Conditioning
UBB+1
60
APPPS1
40
APPPS1/UBB
20
0
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+1
60
6
Age (Months)
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***
**
**
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UBB+1
**
APPPS1
*
40
APPPS1/UBB+1
20
0
3
*
*
% Freezing
% Freezing
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% Time in target quadrant
% Time in target quadrant
Morris Water Maze
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APPPS1
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D
100
WT
4
0
9
Alterations Y-Maze
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**
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C
Nest Building combined
% Alterations
B
Nest Building
Nest buiding score
Nest buiding score (1-5)
A
3
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