Kvantitativ 3D<em> I Silico</em> Modeling (q3DISM) af cerebral amyloid-beta Fagocytose i gnavermodeller af Alzheimers sygdom
Summary
Vi udviklede en metode til kvantitativ 3D in silico modellering (q3DISM) af cerebral amyloid-β (Ap) fagocytose af mononukleære fagocytter i gnavermodeller for Alzheimers sygdom. Denne metode kan generaliseres til kvantificering af næsten enhver fagocytisk begivenhed in vivo.
Abstract
Neuroinflammation er nu anerkendt som en vigtig ætiologisk faktor i neurodegenerativ sygdom. Mononukleære fagocytter er medfødte immunceller er ansvarlige for fagocytose og clearance af snavs og efterladenskaber. Disse celler omfatter CNS-residente makrofager kendt som mikroglia og mononukleære fagocytter infiltrerer fra periferien. Lysmikroskopi har generelt været brugt til at visualisere fagocytose i gnavere eller menneskelige hjerne prøver. Imidlertid har kvalitative metoder ikke givet endegyldige bevis for in vivo fagocytose. Her beskriver vi kvantitativ 3D i silico modellering (q3DISM), en robust metode giver mulighed for ægte 3D kvantificering af amyloid-β (Ap) fagocytose af mononukleære fagocytter i gnavere Alzheimers sygdom (AD) modeller. Fremgangsmåden involverer fluorescerende visualisering Ap indkapslet i phagolysosomes i gnaver hjernesektioner. Store z-dimensionelle konfokale datasæt derefter 3D rekonstrueres til kvantificering af A &# 946; rumligt colocalized inden fagolysosomet. Vi viser den vellykkede anvendelse af q3DISM til muse- og rottehjerner, men denne metode kan udvides til stort set alle fagocytisk begivenhed i helst væv.
Introduction
Alzheimers sygdom (AD), den mest almindelige aldersrelateret demens 1, er karakteriseret ved cerebral amyloid-β (Ap) akkumulering som "senile" p-amyloid plaques, kronisk lavt niveau neuroinflammation, tauopati, neurontab og kognitive forstyrrelser 2 . I AD patient hjerner, er neuroinflammation øremærket af reaktiv astrocytter og mononukleære fagocytter (benævnt mikroglia, selv om deres centrale vs. perifer oprindelse er fortsat uklart) omgiver Ap indskud 3. Da de medfødte immunforsvar vagtposter i CNS, er mikroglia centralt placeret for at rydde hjernen Ap. Imidlertid er mikroglial rekruttering til Ap plaques ledsaget af meget lidt, om nogen, Ap fagocytose 4,5. En hypotese er, at mikroglia er oprindeligt neurobeskyttende ved fagocyterende små forsamlinger Ap. Men i sidste ende disse celler bliver neurotoksisk som overvældende Ap-byrde og / eller aldersrelaterede funktionelle decline, provokerer mikroglia i en dysfunktionel proinflammatorisk fænotype, der bidrager til neurotoksicitet og kognitiv tilbagegang 6.
Nylige genom-dækkende Association Studies (GWAS) har identificeret en klynge af AD risikofaktorer alleler tilhører centrale medfødte immun veje 7, som modulerer fagocytose 8-11. Derfor har immunresponset på cerebral amyloid aflejring blevet en vigtig område af interesse, både med hensyn til forståelsen af AD ætiologi og for at udvikle nye terapeutiske tilgange 12-14. Men der er et vitalt behov for metode til at vurdere Ap fagocytose in vivo. For at løse dette uopfyldt behov, har vi udviklet kvantitativ 3D i silico modellering (q3DISM) for at muliggøre ægte 3D kvantificering af cerebral Ap fagocytose med mononukleære fagocytter i gnavermodeller for Alzheimer-lignende sygdom.
Kun begrænset af det omfang, hvori de rekapitulere sygdom, dyremodeller harvist sig uvurderlig for forståelsen AD pathoetiology og for at vurdere eksperimentelle lægemidler. På grund af det faktum, at mutationer i Presenilin (PS) og amyloidprecursorprotein (APP) gener uafhængigt forårsage autosomal dominant AD, er disse mutante transgener blevet grundigt anvendt til at generere transgene gnavermodeller. Transgene APP / PS1-mus samtidigt at co-udtrykke "svenske" mutant human APP (APP SWE) og Δ exon 9 mutant human presenilin 1 (PS1ΔE9) til stede med accelereret cerebral amyloidosis og neuroinflammation 15,16. Endvidere har vi skabt bi-transgene rotter coinjiceret med APP swe og PS1ΔE9 konstruktioner (line TgF344-AD, på en Fischer 344 baggrund). I modsætning til transgene musemodeller af cerebral amyloidose, TgF344-AD rotter udvikler cerebral amyloid, der går forud tauopati, apoptotiske tab af neuroner, og adfærdsmæssig svækkelse 17.
I denne rapport beskriver vi en protokol for immunostaining mikroglia, phagolysosomes og Ap indskud i hjernen sektioner fra APP / PS1 mus og TgF344-AD rotter og erhvervelse af store z-dimensionelle konfokale billeder. Vi detaljer i silico generation og analyse af ægte 3D-rekonstruktioner fra konfokale datasæt tillader kvantificering af Ap optagelse i microgliale phagolysosomes. Mere bredt kan den metode, we detaljer her anvendes til at kvantificere stort set enhver form for fagocytose in vivo.
Protocol
Representative Results
Discussion
Den protokol, som vi beskriver i denne rapport for ægte 3D kvantificering af Ap fagocytose in vivo ved mononukleære fagocytter afhængig særlig mærkning af cellulære og subcellulære rum samt Ap indskud. Specifikt anvender vi Iba1 (ioniseret-calciumbindende Adaptor molekyle 1), et protein, der er involveret i membranen ruffling og fagocytose ved celleaktivering 18, 19, til at farve cerebrale mononukleære fagocytter. Mens Iba1 + celler generelt betragtes som hjer…
Declarações
The authors have nothing to disclose.
Acknowledgements
M-V.G-S. is supported by a BrightFocus Foundation Alzheimer’s Disease Research Fellowship Award (A2015309F) and an Alzheimer’s Association, California Southland Chapter Young Investigator Award. T.M.W. is supported by an ARCS Foundation and John Douglas French Alzheimer’s Foundation Maggie McKnight Russell-JDFAF Memorial Postdoctoral Fellowship. This work was supported by the National Institute on Neurologic Disorders and Stroke (1R01NS076794-01, to T.T.), an Alzheimer’s Association Zenith Fellows Award (ZEN-10-174633, to T.T.), and an American Federation of Aging Research/Ellison Medical Foundation Julie Martin Mid-Career Award in Aging Research (M11472, to T.T.). We are grateful for startup funds from the Zilkha Neurogenetic Institute, which helped to make this work possible.
Materials
| Isoflurane | Abbott | NDC 0044-5260-05 | |
| Dissecting scissors | VWR | 82027-582 | |
| Dissecting scissors Blunt tip | VWR | 82027-588 | |
| Tweezers | VWR | 94024-408 | |
| 23G needle | VWR | BD305145 | |
| peristaltic pump FH10 | Thermo Scientific | 72-310-010 | |
| PBS 10X | Bioland Scientific | PBS01-02 | Working concentration 1X |
| Adult Mouse Brain Matrix, Coronal slices, Stainless Steel 1mm | Kent Scientific | RBMS-200C | |
| Adult Rat Brain Matrix, Coronal slices, Stainless Steel 1mm | Kent Scientific | RBMS-305C | |
| 32% Paraformaldehyde aqueous solution | EMS | 15714-S | Caution: Toxic. Working concentration 4% in PBS |
| Ethanol | VWR | 89125-188 | Various concentrations, see protocol |
| Tissue-Tek Uni-cassettes Sakura | VWR | 25608-774 | |
| Embedding and Infiltration Paraffin | VWR | 15147-839 | |
| Microtome Leica RM2125 | Leica Biosystems | ||
| Disposable Microtome Blades | VWR | 25608-964 | |
| Water bath Leica HI 1210 | Leica Biosystems | ||
| Micro slide Superfrost plus | VWR | 48311-703 | |
| Xylene | Sigma-Aldrich | 534056-4X4L | Caution: Toxic |
| Target Retrieval Solution 10X | DAKO | S1699 | Working concentration 1X |
| KimWipes | VWR | 21905-026 | |
| Hydrophobic PAP pen | VWR | 95025-252 | |
| Triton X-100 | VWR | 97062-208 | |
| Normal Donkey Serum | Jackson Immuno | 017-000-121 | |
| Coverslips | VWR | 48393081 | |
| Prolong Gold antifade reagent with DAPI | Life Technologies | P36935 | |
| Glass Slide Rack | VWR | 100492-942 | |
| Iba1 antibody (polyclonal, rabbit) | Wako | 019-19741 | Working concentration 1:200 |
| Iba1 antibody (polyclonal, goat) | LifeSpan Bioscience | LS-B2645 | Working concentration 1:200 |
| rat CD68 [KP1] antibody (monoclonal, mouse) | Abcam | ab955 | Working concentration 1:200 |
| mouse CD68 [FA-11] antibody (monoclonal, rat) | Abcam | ab53444 | Working concentration 1:200 |
| mouse CD107a (LAMP1) antibody (monoclonal, rat) | Affymetrix | 14-1071 | Working concentration 1:100 |
| Beta-Amyloid, 17-24 (4G8) antibody (monoclonal, mouse) | Covance | SIG-39220 | Working concentration 1:200 |
| Beta-Amyloid, 1-16 (6E10) antibody (monoclonal, mouse) | Covance | SIG-39320 | Working concentration 1:200 |
| OC antibody (polyclonal, rabbit) | Gifted by D. H. Cribbs and C. G. Glabe (UC Irvine) | Working concentration 1:200 | |
| Alexa Fluor 488 mouse secondary antibody | Invitrogen | A-11001 | Working concentration 1:1000 |
| Alexa Fluor 488 rat secondary antibody | Invitrogen | A-11006 | Working concentration 1:1000 |
| Alexa Fluor 594 rabbit secondary antibody | Invitrogen | A-11037 | Working concentration 1:1000 |
| Alexa Fluor 594 goat secondary antibody | Invitrogen | A-11080 | Working concentration 1:1000 |
| Alexa Fluor 647 mouse secondary antibody | Invitrogen | A-21235 | Working concentration 1:1000 |
| Alexa Fluor 647 rabbit secondary antibody | Invitrogen | A-21443 | Working concentration 1:1000 |
| Immersion oil | Nikon | ||
| A1 Confocal microscope | Nikon | ||
| NIS Elements Advanced Research software | Nikon | ||
| Imaris:Bitplane software version 7.6 | Bitplane | "coloc" and "supass" modules are used. Alternatively, the open-source freeware ImageJ can be used for colocalization analysis of confocal z-stacks datasets. | |
Referências
- Brookmeyer, R., et al. National estimates of the prevalence of Alzheimer’s disease in the United States. Alzheimers Dement. 7 (1), 61-73 (2011).
- Selkoe, D. J. Alzheimer’s disease. Cold Spring Harb Perspect Biol. 3 (7), (2011).
- Heneka, M. T., Golenbock, D. T., Latz, E. Innate immunity in Alzheimer’s disease. Nat Immunol. 16 (3), 229-236 (2015).
- Mawuenyega, , et al. Decreased clearance of CNS beta-amyloid in Alzheimer’s disease. Science. 330 (6012), 1774 (2010).
- Hickman, S. E., Allison, E. K., El Khoury, J. Microglial dysfunction and defective beta-amyloid clearance pathways in aging Alzheimer’s disease mice. J Neurosci. 28 (33), 8354-8360 (2008).
- Johnston, H., Boutin, H., Allan, S. M. Assessing the contribution of inflammation in models of Alzheimer’s disease. Biochem Soc Trans. 39 (4), 886-890 (2011).
- Gjoneska, E., et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature. 518 (7539), 365-369 (2015).
- Reitz, C., Mayeux, R. Alzheimer disease: epidemiology, diagnostic criteria, risk factors and biomarkers. Biochem Pharmacol. 88 (4), 640-651 (2014).
- Hazrati, L. -. N., et al. Genetic association of CR1 with Alzheimer’s disease: a tentative disease mechanism. Neurobiol Aging. 33 (12), 2949 (2012).
- Griciuc, A., et al. Alzheimer’s Disease Risk Gene CD33 Inhibits Microglial Uptake of Amyloid Beta. Neuron. , 1-13 (2013).
- Li, X., Long, J., He, T., Belshaw, R., Scott, J. Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimer’s disease. Scientific reports. 5, 12393 (2015).
- Weitz, T. M., Town, T. Microglia in Alzheimers Disease: “Its All About Context”. Int J Alzheimers Dis. , 314185 (2012).
- Guillot-Sestier, M. -. V., Doty, K. R., Town, T. Innate Immunity Fights Alzheimer’s Disease. Trends Neurosci. 38 (11), 674-681 (2015).
- Guillot-Sestier, M. -. V., Town, T. Innate immunity in Alzheimer’s disease: a complex affair. CNS Neurol Disord Drug Targets. 12 (5), 593-607 (2013).
- Jankowsky, J. L., Slunt, H. H., Ratovitski, T., Jenkins, N. A., Copeland, N. G., Borchelt, D. R. Co-expression of multiple transgenes in mouse CNS: a comparison of strategies. Biomol Eng. 17 (6), 157-165 (2001).
- Guillot-Sestier, M. -. V., et al. Il10 deficiency rebalances innate immunity to mitigate Alzheimer-like pathology. Neuron. 85 (3), 534-548 (2015).
- Cohen, R. M., et al. A transgenic Alzheimer rat with plaques, tau pathology, behavioral impairment, oligomeric aβ, and frank neuronal loss. J Neurosci. 33 (15), 6245-6256 (2013).
- Imai, Y., Ibata, I., Ito, D., Ohsawa, K., Kohsaka, S. A novel gene iba1 in the major histocompatibility complex class III region encoding an EF hand protein expressed in a monocytic lineage. Biochem. Biophys. Res. Commun. 224 (3), 855-862 (1996).
- Ohsawa, K., Imai, Y., Sasaki, Y., Kohsaka, S. Microglia/macrophage-specific protein Iba1 binds to fimbrin and enhances its actin-bundling activity. J Neurochem. 88 (4), 844-856 (2004).
- Bandyopadhyay, U., Nagy, M., Fenton, W. A., Horwich, A. L. Absence of lipofuscin in motor neurons of SOD1-linked ALS mice. Proc Natl Acad Sci U S A. 111 (30), 11055-11060 (2014).
- Holness, C. L., Simmons, D. L. Molecular cloning of CD68, a human macrophage marker related to lysosomal glycoproteins. Blood. 81 (6), 1607-1613 (1993).
- Connor, T., et al. Phosphorylation of the translation initiation factor eIF2alpha increases BACE1 levels and promotes amyloidogenesis. Neuron. 60 (6), 988-1009 (2008).
- Cai, D., et al. Phospholipase D1 corrects impaired betaAPP trafficking and neurite outgrowth in familial Alzheimer’s disease-linked presenilin-1 mutant neurons. Proc Natl Acad Sci U S A. 103 (6), 1936-1940 (2006).
- Marsh, S. E., et al. The adaptive immune system restrains Alzheimer’s disease pathogenesis by modulating microglial function. Proc Natl Acad Sci U S A. 113 (9), 1316-1325 (2016).
- Lefterov, I., et al. Apolipoprotein A-I deficiency increases cerebral amyloid angiopathy and cognitive deficits in APP/PS1DeltaE9 mice. J Biol. Chem. 285 (47), 36945-36957 (2010).
- Blurton-Jones, M., et al. Neural stem cells improve cognition via BDNF in a transgenic model of Alzheimer disease. Proc Natl Acad Sci U S A. 106 (32), 13594-13599 (2009).
- Stalder, M., Deller, T., Staufenbiel, M., Jucker, M. 3D-Reconstruction of microglia and amyloid in APP23 transgenic mice: no evidence of intracellular amyloid. Neurobiol Aging. 22 (3), 427-434 (2001).
- Leinenga, G., Götz, J. Scanning ultrasound removes amyloid-β and restores memory in an Alzheimer’s disease mouse model. Sci Transl Med. 7 (278), 33 (2015).
- Liarski, V. M., et al. Cell distance mapping identifies functional T follicular helper cells in inflamed human renal tissue. Sci Transl Med. 6 (230), 46 (2014).
- Nichols, L., Pike, V. W., Cai, L., Innis, R. B. Imaging and in vivo quantitation of beta-amyloid: an exemplary biomarker for Alzheimer’s disease. Biol Psychiatry. 59 (10), 940-947 (2006).
- Skovronsky, D. M., Zhang, B., Kung, M. P., Kung, H. F., Trojanowski, J. Q., Lee, V. M. In vivo detection of amyloid plaques in a mouse model of Alzheimer’s disease. Proc Natl Acad Sci U S A. 97 (13), 7609-7614 (2000).
- Lian, H., Litvinchuk, A., Chiang, A. C. -. A., Aithmitti, N., Jankowsky, J. L., Zheng, H. Astrocyte-Microglia Cross Talk through Complement Activation Modulates Amyloid Pathology in Mouse Models of Alzheimer’s Disease. J Neurosci. 36 (2), 577-589 (2016).
- Novotny, R., et al. Conversion of Synthetic Aβ to In Vivo Active Seeds and Amyloid Plaque Formation in a Hippocampal Slice Culture Model. J Neurosci. 36 (18), 5084-5093 (2016).
- Tartaro, K., et al. Development of a fluorescence-based in vivo phagocytosis assay to measure mononuclear phagocyte system function in the rat. J Immunotoxicol. 12 (3), 239-246 (2015).
