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1 Institute for Neurodegenerative Diseases, University of California, San Francisco, CA, USA
2 Department of Neurology, University of California, San Francisco, CA, USA
3 Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
4 INSERM, U602, and Université Paris 11, Villejuif, France
5 Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, USA
6 Muscular and Neurodegenerative Disease Unit, University of Genova and G. Gaslini Pediatric Institute, Genova, Italy
6 Department of Cancer Biology, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
7 Department of Biochemistry and Oxford Glycobiology Institute, University of Oxford, Oxford, UK
8 Department of Pharmacology and Toxicology, University of Kansas, Lawrence, KS, USA
9 Institute for Human Genetics and Department of Pediatrics, University of California, San Francisco, CA, USA
10 Department of Pathology and Laboratory Medicine, University of North Carolina Medical Center, Chapel Hill, NC, USA
11 Biotechnology Research and Innovation Center, Faculty of Health Sciences, University of Copenhagen, Denmark
12 Departments of Neurology, Neuroscience and Graduate Program in Neuroscience, University of Minnesota, and Geriatric Research, Education and Clinical Center, Minneapolis Veterans Affairs Medical Center, Minneapolis, MN, USA
13 McLaughlin Research Institute, Great Falls, MT, USA
14 Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
15 Geriatric Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
16 Neuroscience Graduate Program, University of California, San Francisco, CA, USA
17 Gladstone Institute of Neurological Disease, University of California, San Francisco, CA, USA
18 Cardiovascular Research Institute and Departments of Medicine and Pathology, University of California, San Francisco, CA, USA
19 Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA
Correspondence
Stanley B. Prusiner
stanley{at}ind.ucsf.edu
| ABSTRACT |
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Present address: Pappas Ventures, Montreal, QC H3A 1X6, Canada. ![]()
Present address: Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA. ![]()
Present address: Institute for Neuropathology, Heinrich Heine University Düsseldorf, 40001 Düsseldorf, Germany. ![]()
||Present address: Department of Genetics and Genomics, Roslin Institute, Roslin, Midlothian EH25 9PS, Scotland, UK. ![]()
¶Present address: Department of Biochemistry, Neurobiochemistry, Ludwig Maximilians University, Munich, Germany. ![]()
#Present address: University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA. ![]()

Present address: Dublin-Oxford Glycobiology Laboratory, University College, Belfield, Dublin 4, Ireland. ![]()

Present address: Departments of Forensic Science and Biology, Virginia Commonwealth University, Richmond, VA 23284-3079, USA. ![]()

Present address: PDL BioPharma, Inc., Redwood City, CA 94063, USA. ![]()
||||Present address: Center for Human Genetics, K.U. Leuven, Department of Molecular and Developmental Genetics, 3000 Leuven, Belgium. ![]()
Supplementary material is available with the online version of this paper.
| INTRODUCTION |
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Based on these studies, any gene product involved in the formation of PrPSc should affect the onset of prion disease if knocked out, inactivated or overexpressed as demonstrated for PrP itself (Prusiner et al., 1993
, 1990
). Many genes have been suggested to contribute to prion replication, of which we tested 20 (Table 1
). Mice in which the candidate gene product was inactivated, ablated or overexpressed were inoculated and incubation times relative to control mice were recorded (Tables 2
–5
). To determine whether differences in incubation period were significant, we developed a novel statistical method accounting for interexperiment variability. While most of the tested genes did not play a role in prion disease, we show here that mice deficient for the amyloid beta (A4) precursor protein (App) or interleukin-1 receptor, type I (Il1r1) genes had prolonged incubation times by 13 and 16 %, respectively. Similarly, overexpression of human superoxide dismutase 1 (SOD1) extended disease-onset times by 19 %.
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| METHODS |
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3 or the
4 allele of human apolipoprotein E (APOE) driven by the neuron-specific enolase (NSE) promoter on a C57BL/6J-Apoe–/– (C57BL/6J-Apoetm1Unc) background (Raber et al., 1998
k)+/–xTg(tTA)+/– Prnp+/– mice neuronally express a transdominant-negative kinase-deficient mutant of TGF-β receptor II (TβRII
k) and are deficient in TGF-β signalling (Tesseur et al., 2006
promoter on a C57BL/6 background (line N8) (Kojima et al., 1997
) (Petrone et al., 2003The following mice were obtained from the Jackson Laboratory: Apoe–/– mice on a C57BL/6J background (C57BL/6J-Apoetm1Unc); interleukin-10 (IL-10)-knockout mice on a C57BL/6J background, denoted B6-IL-10–/– mice (B6.129P2-Il10tm1Cgn/J); IL-10-knockout mice on a 129S6 background, denoted 129-IL-10–/– mice (129-Il10tm1Cgn/J); tumour necrosis factor (TNF)-deficient mice, denoted Tnf–/– mice (B6.129S6-Tnftm1Gkl/J); mice lacking Tnf receptor superfamily, members 1a (TNF-R1) and 1b (TNF-R2), denoted Tnfrsf1a–/– Tnfrsf1b–/– mice (B6;129S-Tnfrsf1atm1Imx Tnfrsf1btm1Imx/J); and IL-1 receptor, type I-knockout mice, denoted Il1r1–/– mice (B6;129S1-Il1r1tm1Roml/J). C57BL/6J, 129S1/SvImJ, B6129SF2/J and FVB/N mice were obtained as controls. Crossing Tnfrsf1a+/+ Tnfrsf1b+/+ mice with B6129SF2/J mice gave Tnfrsf1a+/– Tnfrsf1b+/– mice. Crossing Il1r1+/+ mice with B6129SF2/J mice yielded Il1r1+/– mice. The genetic status of the progeny was determined using protocols from the Jackson Laboratory.
Prion isolates and transmission.
CD1 mouse-adapted RML, Me7 and 301V prions were used as inocula. RML and Me7 were originally derived from sheep with scrapie and have been serially passaged in mice for many generations; 301V was derived from a cow with BSE and passaged into VM mice (Bruce et al., 1994
; Chandler, 1961
; Dickinson & Meikle, 1969
). Brain homogenates (10 % w/v) in PBS (pH 7.4) were obtained by 10 repeated extrusions through syringe needles of successively smaller sizes, from 18 to 22 gauge, or alternatively by three 30 s strokes of a PowerGen homogenizer (Fisher Scientific). A final 1 % (w/v) brain homogenate for inoculation was obtained by further diluting brain homogenates in 5 % (w/v) bovine albumin Fraction V (ICN) and PBS. Using a 27-gauge syringe, 30 µl of 1 % brain homogenate was inoculated into the right parietal lobe, or 200 µl into the peritoneal cavity of mice. Animals were monitored daily for their clinical status, while the neurological status was assessed three times per week. Mice with progressive neurological dysfunction were euthanized (Carlson et al., 1986
).
| RESULTS |
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Modelling disease onset times
To determine the genotype-independent variation in incubation time, we intracerebrally (i.c.) inoculated over 400 wt FVB/N mice, which were divided into 39 groups at six different time points over a 5 year period, with RML prions (Supplementary Table S1 available in JGV Online, Fig. 1
). Median incubation times were calculated for all 39 groups using the Kaplan–Meier function and mice with intercurrent illness were censored at the time of euthanasia (Kaplan & Meier, 1958
). Although these mice were genetically identical, we observed appreciable variation in median incubation times among different groups of mice ranging between 103 and 137 days for individual groups. This variation was not restricted to wt FVB/N mice and was also evident in C57BL/6J and CD1 mice (data not shown). Since the commonly used logrank test does not take into account this type of experiment-to-experiment variation among genotypically identical mice, we developed a method to compare better the survival curves of prion-diseased mice. Based on our observations, disease-onset times fitted well to a Weibull regression model with the effects of genotypes following an accelerated failure time model (Tables 2
–5
) (Cox & Oakes, 1984
). This model accommodates for the fact that, in a group of prion-infected mice with the same genotype, all the animals become sick within a very close time interval once single animals start to show symptoms. To account for experiment-to-experiment variation, we included a gamma-distributed random effect term in the Weibull model that was weighted by the interexperimental variation observed in RML-inoculated FVB/N mice (Supplementary Table S1, Fig. 1
) (Glidden & Vittinghoff, 2004
; Nielsen et al., 1992
). This improved the accuracy of our statistical evaluation and led to p-values (pWG) that were generally higher than those obtained with the logrank test (pL) (Tables 2
–5
). Effects of experiments in mice expressing neither, one, or both alleles of Il1r1, Tnfrsf1a and Tnfrsf1b, Cd9 and Prnd were also tested for trend (Vittinghoff et al., 2005
). For a given gene, the trend test delivers increased significance, when incubation times are increasingly prolonged or shortened based on the number of alleles present. The relative time for each genotype shown in Tables 2
–5
was calculated from the accelerated failure time model, which takes into account both medians and interpercentile ranges of disease-onset times from genetically modified mice and control mice. All calculations were performed with Intercooled Stata 9.2 (StataCorp).
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and IL-1β and showed 16 % longer incubation times compared with control mice (Fig. 2b
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None of the other four inflammation-associated genes affected incubation times (Supplementary Fig. S3a–f available in JGV Online). In two mouse models, inhibited TNF-
signalling resulted in incubation times similar to controls (Supplementary Fig. S3a and b). We also found that TGF-β1 signalling had no effect on prion incubation times, using three different mouse models: Tg(Tgfb1) mice overexpressing TGF-β1, heterozygous Tg(Tgfb1+/–) mice and double-transgenic Tg(TβRII
k)+/–xTg(tTA)+/– Prnp+/– mice expressing a transdominant-negative mutant of TGF-β receptor II that disrupts TGF-β signalling (Supplementary Fig. S3c and d). Deficiency of CCR2 or CCR5 also did not influence prion incubation times (Supplementary Fig. S3e and f).
Proteins associated with protein maintenance do not influence prion incubation times
We tested the influence of four genes relevant to protein expression and maintenance on prion incubation times (Table 4
). The methionine sulfoxide reductase (Msr) system consisting of MsrA and MsrB reverts methionine sulfoxide to methionine and thereby protects from oxidative stress (Moskovitz & Stadtman, 2003
). We tested the effect of oxidative stress on prion replication in MsrA-knockout mice on a regular or on a selenium-depleted diet that further disables the Msr system by inactivating MsrB, which as a selenoprotein requires selenium to be fully active. MsrA-deficient mice that were kept on a regular or selenium-depleted diet did not show incubation times significantly different from those of control mice (Supplementary Fig. S4a available in JGV Online). Incubation times in Tg(SOD1)3Cje mice that overexpress human superoxide dismutase 1 (SOD1) were significantly extended (pWG=0.016) by 19 % after infection with RML prions (Fig. 2e
), compared with wt littermates. However, this prolongation was not observed when Tg(SOD1)3Cje mice were infected with the 301V prion strain. Tg(HSP70) mice, which overexpress human Hsp70, did not show significantly altered incubation times compared to wt littermates (Supplementary Fig. S4b available in JGV Online). Finally, we addressed whether post-translational modifications impact on PrP conversion in mice lacking mannoside-b1,4-N-acetylglucosaminyltransferase III (Mgat3/GlcNAcT-III). In comparison to PrPC, PrPSc contains decreased levels of N-glycans with a bisecting GlcNAc residue and increased levels of tri- and tetra-antennary complex N-glycans, which may result from a decrease in Mgat3/GlcNAcT-III activity (Rudd et al., 1999
). Incubation times in Mgat3–/– mice did not differ significantly from wt littermates, even when mice were inoculated with three different prion strains: RML, ME7 and 301V (Supplementary Fig. S4b).
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also did not have significantly altered incubation times (Supplementary Fig. S5d). As part of this work, we created Prnd–/– mice that lack expression of the PrP paralogue doppel (Dpl), which did not show any morphological or behavioural defects except for male infertility, as reported earlier (Behrens et al., 2002| DISCUSSION |
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We show that knockout of App protracts the onset of prion disease by 13 %. While the underlying mechanism is unclear, its elucidation is likely to promote our understanding of the neurodegenerative processes in prion disease as well as in AD, both of which share many common features (DeArmond, 1993
). In AD, cleavage of APP gives rise to pathogenic Aβ peptides that are rich in β-sheet conformation and that can form amyloid plaques in the central nervous system (CNS), similar to PrPSc.
Cytokines and their receptors are key mediators of inflammatory as well as anti-inflammatory responses and are often found to be upregulated in a multitude of neurodegenerative conditions, including trauma, stroke, AD and prion disease. Of six candidate genes that had previously been reported to be upregulated during prion disease, only interruption of IL-1 signalling mildly but significantly prolonged disease-onset times by 16 %. Our results agree with a study reporting prolonged incubation times in Il1r1-knockout mice after i.c. infection with at least approximately 15-fold lower concentrations of mouse-adapted 138A scrapie prions (Schultz et al., 2004
). The prolonged incubation time probably occurs by delaying astrocytic gliosis, as IL-1R1 is mainly expressed on astrocytes and oligodendrocytes in the CNS and Il1r1–/– mice show reduced inflammatory responses (Brogi et al., 1997
; Labow et al., 1997
; Tomozawa et al., 1995
).
Consistent with other studies, abrogated TNF-
or TGF-β signalling did not affect prion pathogenesis after i.c. inoculation (Klein et al., 1997
; Mabbott et al., 2000
). In Il10–/– mice, we observed a 19 % reduction in the incubation time on a C57BL/6J background, but no change on a 129S1/SvImJ background. Differences in the genetic background of these two inbred mouse strains are likely to explain the different incubation times we observed. While all Il10–/– mice are anaemic, growth retarded and develop chronic enterocolitis to intestinal antigens (Kuhn et al., 1993
), Il10–/– mice on a C56BL/6J background have less inflammation and fewer adenocarcinomas than mice on a 129Sv background (Berg et al., 1996
). Our results make it difficult to draw a firm conclusion about the role of IL-10 in prion pathogenesis, but they contrast severely with an earlier report in which a >50 % reduction in incubation time was reported for Il10–/– mice on a 129S1/SvImJ background (Thackray et al., 2004
).
Prion disease is accompanied by activation and recruitment of microglia to sites of prion replication (Guiroy et al., 1994
). CCR2 and CCR5 are expressed on microglia and functional in their activation and recruitment through interaction with chemokine (C-C motif) ligand 2 (CCL2) and CCL5 (Albright et al., 1999
; El Khoury et al., 2007
). Although survival times of Ccl2–/– mice infected with ME7 prions were reported to be prolonged (Felton et al., 2005
), we failed to detect an effect on survival in Ccr2–/– and Ccr5–/– mice infected with RML prions. How ablation of Ccl2 but not Ccr2 can affect survival times in prion disease is unclear, since CCR2 is the only established high-affinity receptor for CCL2 (Charo et al., 1994
). This disparity may be attributed to infection with different prion strains of different titres or to problematic statistical analysis of survival times in Ccl2–/– mice. It remains to be determined if either CCR2 or CCR5 can compensate for the other's activity in microglial activation and if incubation times would be prolonged in Ccr2–Ccr5 double-knockout mice.
Our studies also clearly show that the formation of methionine oxides does not play a critical role in prion pathogenesis. Because certain methionine residues in PrPC can be oxidized, it was suggested that PrPC may protect from oxidative stress (Wong et al., 1999
). Disabling the Msr system, which reverts methionine sulfoxide to methionine, increases sensitivity to oxidative stress, resulting in reduced life span, elevated levels of hippocampal neurodegeneration, Aβ deposition and tau phosphorylation (Pal et al., 2007
). MsrA-knockout mice without a functional Msr system (Moskovitz & Stadtman, 2003
) showed incubation times similar to those in controls.
Furthermore, our studies show that the production of free radicals may affect the progression of disease in a strain-dependent fashion. PrPC has been controversially discussed to have SOD activity and that loss of this putative function by its conversion to PrPSc may contribute to prion disease (Hutter et al., 2003
; Wong et al., 1999
). While disabling the Msr system did not affect prion pathogenesis, Tg(SOD)3Cje mice overexpressing human SOD1 showed prolonged incubation times when inoculated with RML prions, but not when injected with 301V prions. In contrast to RML prions, the 301V strain replicates very slowly in mice expressing mouse PrP-A, and PrPSc deposits accumulate only relatively late during pathogenesis. This may cause less immediate inflammation and thus less free radical production (Farquhar et al., 1996
). A protective effect of increased SOD activity may be visible only with a fast-replicating strain, such as RML prions in which PrPSc deposits, inflammation and free-radical production appear relatively early after infection.
While CD9 ablation did not affect incubation times, we cannot exclude that CD81, which shares approximately 65 % sequence similarity with CD9, can compensate for the PrP-related functions in Cd9–/– mice. In this case, a Cd9–Cd81 double-knockout mouse might provide some insight into the role of CD9 and/or CD81 during PrP conversion. While tetraspanins such as CD9 are known for their exceptional ability to associate with other surface proteins, no association of CD9 with PrP could be observed (E. Rubinstein, unpublished data).
In conclusion, our studies underscore the importance of screening genes that may contribute to prion pathogenesis in in vivo models to establish their function in PrP conversion and pathogenesis. While all candidate genes tested here were implicated to have a role in prion pathogenesis in previous studies, only three were shown to affect disease-onset times. We note that many factors influence these findings, such as the genetic background of the animal model, the prion strain, inoculum titres, the route of infection and, importantly, the statistical analysis of incubation times. By using appropriate controls and a rigorous statistical analysis that takes interexperimental variation into account, we were able to rule out many candidate genes, which otherwise would have scored as significant based on the logrank test alone. Clearly, the conversion of PrPC to PrPSc involves a complex pathway, the elucidation of which would benefit treatment of these devastating diseases.
| ACKNOWLEDGEMENTS |
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Received 11 February 2008;
accepted 13 March 2008.
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