1. S. Cerevisiae Kulturen und Protein-Expression
Hinweis: Aβ-Varianten weisen unterschiedliche relative Aggregation Neigungen aufgrund einer Mutation in einem einzigen Rückstand an Position 19 (Phe19) des Aβ42 Peptid (Abbildung 1A). Diese Peptid-Varianten sind mit grün fluoreszierenden Proteins (GFP), fungiert als eine Aggregation Reporter (Abbildung 1)29versehen.
<ol><li>Plasmide, die Codierung für 20 Aβ42-GFP-Varianten in Hefezellen mit einem BY4741 elterlichen Hintergrund (MATa seine3Δ1 Leu2Δ0 traf15Δ0 ura3Δ0)30zu verwandeln. Jedes Plasmid kodiert für ein Aβ42 Mutant mit GFP durch einen GSSGSSG Linker verschmolzen. Plasmide sind pESC(-URA) und beinhalten die auswählbare Markierung URA329.<ol>
<li>Bereiten Sie das synthetische komplette Medium ohne Uracil (SC-URA) mit den folgenden Komponenten: 1,9 g/L Hefe Stickstoff base Uracil, 5 g/L Ammoniumsulfat und 900 mL DdH2O kombiniert mit 100 mL Glukose 20 % (w/V).</li>
		<li>Eine Kolonie der transformierten Hefezellen in 20 mL des Mediums SC-URA, enthält 2 % Glukose und wachsen Sie die Kulturen über Nacht bei 30 ° C unter Schütteln bei 210 u/min.</li>
	</ol>
</li>
	<li>Wachsen Sie am nächsten Tag neue Hefekulturen Zellen durch Impfkeimen 100 µL der Übernacht-Kultur in 5 mL frisches SC-URA-Medium.</li>
	<li>Bei einer OD590 von 0,5 die Kulturen bei 3.000 x g für 4 min zentrifugieren, überstand verwerfen und Aufschwemmen der Zellen in die gleiche Menge an frischer SC-URA-Speichermedium mit 2 % Raffinose.</li>
	<li>Bei 30 ° C unter Agitation bei 210 u/min für 30 min inkubieren. Dann die Zellen bei 3.000 x g für 4 min zentrifugieren und den überstand verwerfen. Aufzuwirbeln Sie die Zellen in frischen SC-URA-Speichermedium mit 2 % Galaktose induzieren die rekombinante Proteinexpression.</li>
	<li>Nach 16 h zur Induktion der Proteinexpression in SC-URA 2 % Galaktose-haltigem Medium Ernte 1 mL der induzierten Zellen in sterilen Mikrozentrifugenröhrchen durch Zentrifugation bei 3.000 x g für 4 Minuten. Hinweis: Die wichtigsten Unterschiede auftreten, nachdem eine Einarbeitungszeit von 16 h. induzierte Hefezellen mit dem Ausdruck Aβ42-GFP-Varianten durch Fluoreszenz-Mikroskopie zur Bestimmung der rekombinanten PROTEINVERTEILUNG innerhalb der Zellen (Abb. 2 b) sichtbar gemacht werden kann.</li>
</ol>(2) Zelle färben
Hinweis: Frischzellen-induzierte sind als Negativkontrolle herstellen eine fluoreszierende Schwelle während einer FC-Analyse erforderlich.
<ol><li>Die 16 h-induzierte Hefezellen übernehmen und bestimmen ihre optische Dichte bei 590 nm (OD590). Verdünnen sie in eine sterile Phosphat gepufferte Kochsalzlösung (PBS) ein OD590 von 0,1.<ol>
<li>1 x Phosphat gepufferte Kochsalzlösung wie folgt vorbereiten: 8 g NaCl, KCl, 1,44 g Na2HPO4, 0,2 g und 0,24 g KH2PO4 bis 800 mL DdH2O. füllen Sie die Lösung bis zu 1 L DdH2O nach Einstellen des pH-Werts auf 7,4 mit HCl. Filter des Puffers durch einen 0,2 µm-Filter.</li>
	</ol>
</li>
	<li>Transfer mit dem Ausdruck ihrer Zellsuspensionen entsprechend gekennzeichneten Rohre (12 × 75 mm Rundboden Polystyrol) und vor Licht zu schützen. Stellen Sie sicher, dass sie bereit sind, auf das Durchflusszytometer für Analyse, zusammen mit nicht-induzierte und nicht-gefärbten Zellen geladen werden.</li>
	<li>Jede Probe auf eine Endkonzentration von 5 µM die oxidativen Stress-Sonde (z. B. CellROX tiefrot) hinzu und inkubieren Sie die Zellen bei 30 ° C für 30 Minuten im Dunkeln.</li>
	<li>Waschen Sie nach der Inkubation der Zellen 3 Mal mit 1 X PBS und Aufschwemmen sie in das gleiche Volumen des Puffers vor ihrer Analyse von FC.</li>
</ol>(3) Flow Cytometry Analysis
Hinweis: Verwenden Sie eine FC-Setup mit geeigneten Laser und Filter zur Erkennung von GFP und oxidativem Stress Sonde Fluoreszenzsignal. Ein Durchflusszytometer ausgestattet mit 488 nm blaue Laser für den Nachweis der GLP und einem 635 nm rot-Laser für den Nachweis von oxidativem Stress Sonde Fluoreszenz kann verwendet werden. Erwerb der Fluoreszenz Emission von GFP und oxidativem Stress Sonde erfolgt mit einem 530/30 nm BP und ein 660/20 BP Filter, bzw. (Tabelle 1).
<ol><li>Klicken Sie auf Neues Arbeitsblatt Öffnungsklappe und erstellen Sie die folgenden Erwerb Punkt plottet.<ol>
<li>Wählen Sie aus der Symbolleiste das Scatter Plot-Tool und erstellen Sie ein Grundstück mit den Variablen Side Scatter-Area (SSC-A) auf der y-Achse vs. Forward Scatter-Bereich (FSC-A) in einer linearen Skala auf der x-Achse.</li>
		<li>Klicken Sie auf das Scatter Plot-Werkzeug aus der Werkzeugleiste und erstellen Sie ein Grundstück mit der Variablen FL1-Bereich (FITC) auf der x-Achse Vs. FL3-Bereich (APC) in einer logarithmischen Skala auf der y-Achse.</li>
	</ol>
</li>
	<li>Klicken Sie auf das Symbol " Instrumenten-Einstellungen ". Klicken Sie auf die Registerkarte " Entschädigung " und legen Sie alle Vergütungsstufen. Klicken Sie auf die Registerkarte " Erwerb " und wählen Sie eine Gesamtanzahl von 20.000 Ereignisse aufgezeichnet werden.</li>
	<li>Klicken Sie auf Durchfluss , um den Durchfluss zu niedrigzu wechseln.</li>
	<li>Klicken Sie auf die Registerkarte " Acquire " anfangen zu laufen-induzierte, ungefärbten Zellen, und passen Sie die Spannung in den Geräteeinstellungen des Forward und Side Scatter, bis die Bevölkerung in der Mitte-Links-Quadranten verteilt ist.<ol>
<li>Klicken Sie auf das Polygon -Symbol, um eine Region R1 um die Zellpopulation ausgenommen zellenrückstand gesetzt, und verwenden Sie diese geschlossene Population P1 = R1 für alle fluoreszierenden Punkt plottet und Histogramm Darstellungen (Abbildung 3).</li>
	</ol>
</li>
	<li>Um die PMT-Spannung des Fluoreszenzsignals anzupassen, führen Sie die ungefärbten Zellen im FL1-FL3 Dot Plot, den Gewinn in der Registerkarte " Geräteeinstellung " tuning, bis die Zellen im unteren linken Quadranten verteilt sind.</li>
	<li>Ändern der Probenmaterials auf die induzierte Zellen GFP Fluoreszenz zu messen. Stellen Sie im Register Geräteeinstellung Gain in der FSC-A vs. FL1 (FITC) Wenn die Bevölkerung im rechten unteren Quadranten verteilt wird. Definieren Sie die positiven Zellpopulation mit einem Tor (Tor P2).</li>
	<li>Veränderung der Probe, die nicht induzierten gefärbten Zellen oxidativen Stress durch die Fluoreszenz auf ein FSC-A vs. FL3 (APC) Dot-Plot angezeigt. Tunen Sie die Verstärkung, bis die Zellpopulation im linken oberen Quadranten verteilt wird. Tor der positiven Zellpopulation im P3.</li>
	<li>Machen Sie zwei Histogramm-Grundstücke mit dem Histogramm -Symbol um die Fluoreszenz der Zelle darzustellen. Der Fluoreszenzintensität darzustellen, stellen Sie sicher FL1 (FITC) repräsentieren die GFP Fluoreszenz ist auf der x-Achse und FL3 (APC) repräsentieren die Fluoreszenz in der y-Achse P2 und P3 Populationen bzw. auf einer logarithmischen Skala anwenden. Hinweis: Histogramm Overlays sind eine gute Möglichkeit, Unterschiede zwischen den Fluoreszenz-Profilen von Zellen mit dem Ausdruck Aβ-Varianten zu verdeutlichen.</li>
</ol>(4) rekombinante Protein Immunodetection
<ol><li>Um proteingehalte Ausdruck zu ermitteln, Ernten Sie die Hefekulturen für 16 h durch Zentrifugation bei 4.000 x g für 6 min induziert, und speichern Sie die Zelle Pellets bei-80 ° C.<ol>
<li>Aufschwemmen der gesammelten Zellen rekombinantes Protein für 16 h mit PBS-Puffer zum Ausdruck zu bringen. 200 µL Zellsuspensionen jedes Aβ42-GFP mutierte zu einem OD-590 20 vorzubereiten.</li>
	</ol>
</li>
	<li>Für die Gesamt-Protein Bruchteil Analyse, Ernte 100 µL jeder Mutant durch Zentrifugation bei 14.000 x g für 20 min und Aufschwemmen der Zelle-Pellets in die gleiche Menge an Hefe Lyse Puffer Y-pro (50 mM Tris-HCl pH 8.0, 1 % DMSO, 200 mM NaCl, 1 mM EDTA enthalten 10 mg/mL SB3-14 (Myr Istyl Sulfobetaine) ergänzt mit 1 mM Phenylmethylsulfonyl Fluorid (PMSF)).<ol>
<li>Inkubieren Sie die Proben für 20 min bei Raumtemperatur unter milden Agitation.</li>
	</ol>
</li>
	<li>Bestimmen Sie die Proteinkonzentration Extrakt mithilfe des Bradford-Tests. Laden Sie bis zu 5 µg Proteinextrakt jeder Probe auf eine 15 % Acrylamid SDS-PAGE-Elektrophorese Gel und Blot auf eine Polyvinylidene Difluoride (PVDF) Membran bei 100 V 60 Minuten.<ol>
<li>Bereiten Sie ein Bradford Reagenz mit 100 mg Coomassie Brilliant Blue G-250 in 50 mL 95 % Ethanol gelöst und 100 mL Phosphorsäure 85 % (w/V). Dann, wenn der Farbstoff vollständig aufgelöst ist, verdünnen Sie die Mischung mit DdH2O, 1 L und Filtern sie durch Zellulose Filterpapier kurz vor Gebrauch. Hinweis: Die Bradford-Reagenz sollte sein hellbraun.</li>
		<li>Bereiten Sie einen Standard von Rinderserumalbumin (BSA) von 5-100 µg Protein in 1.000 µL des Bradford-Reagenz.</li>
		<li>Fügen Sie 1 bis 10 µL des Proteins zu 1 mL der Bradford-Reagenz zu extrahieren und die Mischung bei Raumtemperatur für 5 min inkubieren.</li>
		<li>Messung der Extinktion des Standards und die Proteinproben Extrakt bei OD595.</li>
		<li>Machen Sie für die Analyse ein Grundstück mit der Extinktion-Werte, die für die Normen Vs. µg Protein. Anhand der Standardkurve, bestimmen Sie die Konzentrationen an die original-Samples aus der Menge an Protein, wenn man bedenkt, das Volumen und die Verdünnung, falls vorhanden.</li>
	</ol>
</li>
	<li>Spülen Sie die Membran mit 1 x Tris gepufferte Kochsalzlösung (TBS), 0,1 % Tween 20 (TTB), und es mit 5 % (w/V) fettfreie Trockenmilch in 1 X TTBS zu blockieren.<ol>
<li>Um 1 L 10 X TBS vorzubereiten, lösen Sie 24 g Tris-base und 88 g NaCl in 900 mL H2ODd auf und passen Sie den pH-Wert auf 7,6. Fügen Sie DdH2O zu einem Endvolumen von 1 L. Mischen Sie für eine Lösung 1 X 1 Teil 10 X Lager mit 9 Teile des DdH2O.</li>
	</ol>
</li>
	<li>Die Membran für 1 h mit einem β-Amyloid Primärantikörper 6E10 verdünnt 1:1,000 brüten und für 1 h bei Raumtemperatur mit einer Sekundärantikörper Ziege Anti-Maus IgG-HRP Konjugat verdünnt 01:10, 000.</li>
	<li>Entwickeln Sie Membranen mit 1 mL Luminata fluoreszierende Reagenz zu und quantifizieren Sie Bänder durch densitometrische Analysen zu, wie im Schritt 5.2 beschrieben.</li>
</ol>(5) Datenanalyse
<ol><li>Um die Daten, die von FC zu analysieren, erstellen Sie eine Tabelle zeigt die mittlere fluoreszente Intensität (MFI) und mittlere Fluoreszenz mit den entsprechenden Standard-Fehler und/oder der Koeffizient der Varianz (CV) für GFP Fluoreszenz und oxidativen Stress.<ol>
<li>Klicken Sie auf die Registerkarte " Inspektor " und die Statistik -Symbol, um die statistischen Daten anpassen, die für jeden Kanal erforderlich sind. Hinweis: Beim Vergleich von Protein-Varianten konvertieren Sie Fluoreszenz Werte Daten zu einer Falte-Over Hintergrund oder Auflösung Metrik (RD): <img alt="Equation 1" src="/files/ftp_upload/57470/57470eq1.jpg"> In dieser Metrik die mittlere Probe ist die mittlere Fluoreszenz Problem Proben, das mittlere Steuerelement ist die mittlere Fluoreszenz von Zellen als Steuerelement verwendet und die SD ist die Standardabweichung der mittleren Fluoreszenz. RD-Faktor ist ein genauer Index als MFI-Wert, da es nicht nur den Unterschied zwischen Proben, sondern auch Konten für die Verbreitung der Daten berechnet. Diese Berechnung ist besonders relevant, wenn Daten aus verschiedenen Experimenten vergleichen im Laufe der Zeit durchgeführt. Einmal das RDs berechnet wurden, empfiehlt die Verwendung eines statistischen Tests bestätigen die Bedeutung der beobachteten Unterschiede zwischen Protein-Varianten.</li>
	</ol>
</li>
	<li>Quantifizieren Sie für Protein Immunodetection das rekombinante Protein-Ebene durch Western-Blot mit ImageJ-Software.<ol>
<li>Vor der Analyse Densitometrie wandeln Sie die ursprünglichen raw-Bilder der entwickelten Membran in JPEG-Datei-Format und Graustufen-Modus.</li>
		<li>Stellen Sie Abschnitt Gesetzt Messungen des Menüs " Analyze " zu Grau Mittelwert.</li>
		<li>Klicken Sie auf das Rechteck -Werkzeug von ImageJ und definieren Sie eine Region of Interest (ROI) mit einer einheitlichen Größe für die Band Densitometrie Analyse zu. Zentrieren Sie jedes Band auf der Membran Bild innerhalb des erstellten rechteckigen Rahmens und notieren Sie die Messung eins nach dem anderen mit STRG + M (Maßbefehl).</li>
		<li>Den lokalen Hintergrund neben jedes Band, Anwendung der gleichen Gegend ROI zu messen. Subtrahieren Sie nach der Messung den entsprechenden lokalen Hintergrund aus jedem einzelnen Band.</li>
	</ol>
</li>
</ol>

<ol>
	<li>Frydman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Folding+of+newly+translated+proteins+in+vivo:+the+role+of+molecular+chaperones.">Folding of newly translated proteins in vivo: the role of molecular chaperones.</a> Annual Review of Biochemistry. 70, 603-647 (2001).</li><li>Hartl, F. U., Bracher, A., Hayer-Hartl, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+chaperones+in+protein+folding+and+proteostasis.">Molecular chaperones in protein folding and proteostasis.</a> Nature. 475, 324-332 (2011).</li><li>Wong, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+determinants+of+selective+clearance+of+protein+inclusions+by+autophagy.">Molecular determinants of selective clearance of protein inclusions by autophagy.</a> Nature Communications. 3, (2012).</li><li>Winkler, J., Tyedmers, J., Bukau, B., Mogk, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chaperone+networks+in+protein+disaggregation+and+prion+propagation.">Chaperone networks in protein disaggregation and prion propagation.</a> Journal of Structural Biology. 179, 152-160 (2012).</li><li>Glickman, M. H., Ciechanover, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ubiquitin-proteasome+proteolytic+pathway:+destruction+for+the+sake+of+construction.">The ubiquitin-proteasome proteolytic pathway: destruction for the sake of construction.</a> Physiological Reviews. 82, 373-428 (2002).</li><li>Dobson, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Getting+out+of+shape.">Getting out of shape.</a> Nature. 418, 729-730 (2002).</li><li>Chiti, F., Dobson, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+misfolding,+functional+amyloid,+and+human+disease.">Protein misfolding, functional amyloid, and human disease.</a> Annual Review of Biochemistry. 75, 333-366 (2006).</li><li>Aguzzi, A., O'Connor, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+diseases:+pathogenicity+and+therapeutic+perspectives.">Protein aggregation diseases: pathogenicity and therapeutic perspectives.</a> Nature Reviews Drug Discovery. 9, 237-248 (2010).</li><li>Rapezzi, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transthyretin-related+amyloidoses+and+the+heart:+a+clinical+overview.">Transthyretin-related amyloidoses and the heart: a clinical overview.</a> Nature Reviews Cardiology. 7, 398-408 (2010).</li><li>Deas, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alpha-synuclein+oligomers+interact+with+metal+ions+to+induce+oxidative+stress+and+neuronal+death+in+Parkinson's+disease.">Alpha-synuclein oligomers interact with metal ions to induce oxidative stress and neuronal death in Parkinson's disease.</a> Antioxidants &amp; Redox Signaling. 24, 376-391 (2016).</li><li>Brundin, P., Melki, R., Kopito, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prion-like+transmission+of+protein+aggregates+in+neurodegenerative+diseases.">Prion-like transmission of protein aggregates in neurodegenerative diseases.</a> Nature Reviews Molecular Cell Biology. 11, 301-307 (2010).</li><li>Frost, B., Diamond, M. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prion-like+mechanisms+in+neurodegenerative+diseases.">Prion-like mechanisms in neurodegenerative diseases.</a> Nature Reviews Neuroscience. 11, 155-159 (2009).</li><li>Arrasate, M., Mitra, S., Schweitzer, E. S., Segal, M. R., Finkbeiner, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inclusion+body+formation+reduces+levels+of+mutant+huntingtin+and+the+risk+of+neuronal+death.">Inclusion body formation reduces levels of mutant huntingtin and the risk of neuronal death.</a> Nature. 431, 805-810 (2004).</li><li>Ross, C. A., Poirier, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Opinion:+what+is+the+role+of+protein+aggregation+in+neurodegeneration?.">Opinion: what is the role of protein aggregation in neurodegeneration?.</a> Nature Reviews Molecular Cell Biology. 6, 891-898 (2005).</li><li>Mishra, R., Sj&#246;lander, D., Hammarstr&#246;m, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spectroscopic+characterization+of+diverse+amyloid+fibrils+in+vitro+by+the+fluorescent+dye+Nile+red.">Spectroscopic characterization of diverse amyloid fibrils in vitro by the fluorescent dye Nile red.</a> Molecular BioSystems. 7, 1232-1240 (2011).</li><li>Klunk, W. E., Jacob, R. F., Mason, R. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+amyloid+by+congo+red+spectral+shift+assay.">Quantifying amyloid by congo red spectral shift assay.</a> Methods in Enzymology. 309, 285-305 (1999).</li><li>Khurana, V., Lindquist, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modelling+neurodegeneration+in+Saccharomyces+cerevisiae:+why+cook+with+baker's+yeast?.">Modelling neurodegeneration in Saccharomyces cerevisiae: why cook with baker's yeast?.</a> Nature Reviews Neuroscience. 11, 436-449 (2010).</li><li>Tenreiro, S., Outeiro, T. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simple+is+good:+yeast+models+of+neurodegeneration.">Simple is good: yeast models of neurodegeneration.</a> FEMS Yeast Research. 10, 970-979 (2010).</li><li>Moosavi, B., Mousavi, B., Macreadie, I. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Yeast+model+of+amyloid-&#946;+and+Tau+aggregation+in+Alzheimer's+disease.">Yeast model of amyloid-&#946; and Tau aggregation in Alzheimer's disease.</a> Journal of Alzheimer's Disease. 47, 9-16 (2015).</li><li>Tenreiro, S., Munder, M. C., Alberti, S., Outeiro, T. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Harnessing+the+power+of+yeast+to+unravel+the+molecular+basis+of+neurodegeneration.">Harnessing the power of yeast to unravel the molecular basis of neurodegeneration.</a> Journal of Neurochemistry. 127, 438-452 (2013).</li><li>Yang, J., Hao, X., Cao, X., Liu, B., Nystr&#246;m, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+sequestration+and+detoxification+of+huntingtin+by+the+ribosome+quality+control+complex.">Spatial sequestration and detoxification of huntingtin by the ribosome quality control complex.</a> eLife. 5, (2016).</li><li>Braun, R. J., B&#252;ttner, S., Ring, J., Kroemer, G., Madeo, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nervous+yeast:+modeling+neurotoxic+cell+death.">Nervous yeast: modeling neurotoxic cell death.</a> Trends in Biochemical Sciences. 35, 135-144 (2010).</li><li>Figley, M. D., Gitler, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Yeast+genetic+screen+reveals+novel+therapeutic+strategy+for+ALS.">Yeast genetic screen reveals novel therapeutic strategy for ALS.</a> Rare Diseases. 1, e24420 (2013).</li><li>Cooper, A. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alpha-synuclein+blocks+ER-Golgi+traffic+and+Rab1+rescues+neuron+loss+in+Parkinson's+models.">Alpha-synuclein blocks ER-Golgi traffic and Rab1 rescues neuron loss in Parkinson's models.</a> Science. 313, 324-328 (2006).</li><li>Johnson, B. S., McCaffery, J. M., Lindquist, S., Gitler, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+yeast+TDP-43+proteinopathy+model:+exploring+the+molecular+determinants+of+TDP-43+aggregation+and+cellular+toxicity.">A yeast TDP-43 proteinopathy model: exploring the molecular determinants of TDP-43 aggregation and cellular toxicity.</a> Proceedings of the National Academy of Sciences of the United States of America. 105, 6439-6444 (2008).</li><li>Bharathi, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+ade1+and+ade2+mutations+for+development+of+a+versatile+red/white+color+assay+of+amyloid-induced+oxidative+stress+in+saccharomyces+cerevisiae.">Use of ade1 and ade2 mutations for development of a versatile red/white color assay of amyloid-induced oxidative stress in saccharomyces cerevisiae.</a> Yeast. 33, 607-620 (2016).</li><li>Pallar&#232;s, I., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+prediction+of+protein+aggregation+propensity.">Advances in the prediction of protein aggregation propensity.</a> Current Medicinal Chemistry. , (2017).</li><li>Villar-Piqu&#233;, A., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+propensity+is+a+crucial+determinant+of+intracellular+inclusion+formation+and+quality+control+degradation.">Protein aggregation propensity is a crucial determinant of intracellular inclusion formation and quality control degradation.</a> Biochimica et Biophysica Acta. 1833, 2714-2724 (2013).</li><li>Navarro, S., Villar-Piqu&#233;, A., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selection+against+toxic+aggregation-prone+protein+sequences+in+bacteria.">Selection against toxic aggregation-prone protein sequences in bacteria.</a> Biochimica et Biophysica Acta. 1843, 866-874 (2014).</li><li>Morell, M., de Groot, N. S., Vendrell, J., Avil&#233;s, F. X., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Linking+amyloid+protein+aggregation+and+yeast+survival.">Linking amyloid protein aggregation and yeast survival.</a> Molecular BioSystems. 7, 1121-1128 (2011).</li><li>Conchillo-Sol&#233;, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=AGGRESCAN:+a+server+for+the+prediction+and+evaluation+of+&amp;#34;hot+spots&amp;#34;+of+aggregation+in+polypeptides.">AGGRESCAN: a server for the prediction and evaluation of &amp;#34;hot spots&amp;#34; of aggregation in polypeptides.</a> BMC Bioinformatics. 8, 65 (2007).</li><li>Fernandez-Escamilla, A. M., Rousseau, F., Schymkowitz, J., Serrano, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+sequence-dependent+and+mutational+effects+on+the+aggregation+of+peptides+and+proteins.">Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins.</a> Nature Biotechnology. 22, 1302-1306 (2004).</li><li>Renner, M., Melki, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+and+prionopathies.">Protein aggregation and prionopathies.</a> Pathologie Biologie.(Paris). 62, 162-168 (2014).</li><li>Carija, A., Navarro, S., de Groot, N. S., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+into+insoluble+deposits+protects+from+oxidative+stress.">Protein aggregation into insoluble deposits protects from oxidative stress.</a> Redox Biology. 12, 699-711 (2017).</li></ol>

Eine Vielzahl von Krankheiten ist die Anhäufung von fehlgefaltete Proteine in zellulären Einlagen6,7,8,33verbunden. Wurden viele Anstrengungen unternommen, um die molekularen Mechanismen zu entwirren, die das Auftreten dieser Krankheiten mit rechnerische Ansätze, die nicht ins Konto proteinkonzentrationen nehmen, auslösen oder in-vitro- Ansätze, in denen die Proteinkonzentration w...

Proteostase ist eine wesentliche Determinante des Zellprozesse Fitness und Alterung. In den Zellen bleibt Protein Homöostase durch anspruchsvolle Protein-Qualitätskontrolle, die Netzwerke zielte darauf ab, sicherzustellen, das richtige umfaltung fehlgefaltete Protein Konformere durch Chaperone und/oder ihre gezielten Proteolyse mit mehreren gut erhaltenen Mechanismen1 ,2,3,4,5. Eine große Anzahl von Studien unterstützen die Verbindung zwischen der Entstehung und Progression von ein breites Spektrum von Erkrankungen des Menschen und das Scheitern der proteostase, führt zu Protein misfolding und Aggregation. Zum Beispiel gilt das Vorhandensein von Proteinablagerungen eine pathologische Gütesiegel von vielen neurodegenerativen Erkrankungen wie Alzheimer, Parkinson und Huntington Krankheiten6,7,8, Prionogenic Krankheiten, und nicht-degenerativen Amyloidosen9. Es wurde vermutet, dass frühe Oligomere und Protofibrillar Baugruppen in der Aggregation Reaktion die wichtigsten spüren der Zytotoxizität sind, aberrante Interaktionen mit anderen Proteinen in den überfüllten zellulären Milieu10Aufbau. Darüber hinaus können Protein Einschlüsse (PI) zwischen den Zellen, verbreiten ihre toxische Wirkung11,12übertragen werden. Daher könnte es sein, dass die Bildung von PI in der Tat einen entgiftenden Mechanismus, der das Vorhandensein von gefährlichen aggregierten Arten zu bestimmten Stellen in der Zelle beschränkt darstellen, wo sie verarbeitet oder angesammelt ohne große Nebenwirkungen 13 , 14.
Standard in-vitro- biochemische Ansätze lieferten wichtige Einblicke in die verschiedenen Arten, die Aggregation Reaktionen und ihre Eigenschaften15,16bevölkern. Jedoch Bedingungen verwendet in diesen Tests unterscheiden sich deutlich von denen, die innerhalb der Zelle und ihre physiologische Bedeutung daher in Frage zu stellen. Aufgrund der bemerkenswerten Erhaltung zelluläre Signalwege wie Protein-Qualitätskontrolle, Autophagie oder die Regulierung der zellulären Redox Zustand17,18 unter Eukaryoten19,20,21 ,22,23, die angehende Hefe Saccharomyces Cerevisiae (S. Cerevisiae) entstanden als privilegierte einfaches zellulären Modell, die molekulare Determinanten der Proteinaggregation zu studieren und seiner zugehörigen zytotoxische Wirkung auf biologisch relevante Umgebungen24,25,26.
Protein Aggregation Neigung ist eine Funktion, die von Natur aus in der primären Sequenz codiert. So kann die Bildung der Amyloid-ähnliche Strukturen vorhergesagt werden, basierend auf die Identifikation und Bewertung der Potenz der Aggregation-Förderung Regionen in Polypeptide27. Trotz des Erfolgs der bioinformatische Algorithmen, die in-vitro- Aggregation-Eigenschaften von Proteinsequenzen vorherzusagen, sind sie jedoch noch lange nicht vorhersagen, wie diese Neigungen in in Vivo zytotoxische Wirkung zu übersetzen. Studien, die die Verbindung zwischen den aggregierten Zustand eines gegebenen Proteins und seiner damit verbundenen Zellschädigung in systematischer Weise ansprechen können helfen, um diese rechnerische Einschränkung zu umgehen. Diese Verbindung ist in der vorliegenden Studie, unter Ausnutzung von einer großen Anzahl von Varianten des β-Amyloid Peptids Aβ42 unterscheiden sich nur in einer einzigen Rückstand, aber Anzeige einen fortlaufenden Bereich von Aggregation Neigungen in Vivo28gerichtet. Insbesondere bezeichnet man ein FC-Ansatz für die Konformationsänderungen Arten entfallen die oxidativen Schäden hervorgerufen durch Aggregation neigen Proteine in Hefezellen zu identifizieren. Die Methode bietet viele Vorteile wie Einfachheit, Hochdurchsatz-Fähigkeit und genaue quantitative Messung. Dieser Ansatz ermöglichte es, dass PI eine schützende Rolle gegen oxidativen Stress spielen zu bestätigen.

<table><tbody><tr><td>Yeast cells BY4741&amp;nbsp;</td><td>ATCC</td><td>201388</td><td>Genotype: MATa his3&amp;Delta;1 leu2&amp;Delta;0 met15&amp;Delta;0 ura3&amp;Delta;0</td></tr><tr><td>pESC(-Ura) plasmid&amp;nbsp;</td><td>Agilent Genomics</td><td>217454</td><td>Yeast expression plasmid with a Gal promotor. Selectable marker URA3</td></tr><tr><td>Yeast Synthetic Drop-out Medium Supplements</td><td>Sigma</td><td>Y1501</td><td>Powder</td></tr><tr><td>Yeast Nitrogen Base Without Amino Acids</td><td>Sigma</td><td>Y0626</td><td>Powder</td></tr><tr><td>Raffinose</td><td>Sigma</td><td>R7630</td><td>Powder</td></tr><tr><td>Glucose</td><td>Sigma</td><td>G7021</td><td>Powder</td></tr><tr><td>Galactose</td><td>Sigma</td><td>G0750</td><td>Powder</td></tr><tr><td>Phosphate Buffered Saline (PBS)</td><td>Fisher Scientific</td><td>BP3991&amp;nbsp;</td><td>Solution 10X</td></tr><tr><td>CellROX Deep Red Reagent&amp;nbsp;</td><td>Life Technologies</td><td>C10422</td><td>Free radical cell-permeant fluorescent sensor, non-fluorescent while in a reduced state, and exhibits bright fluorescence upon oxidation by reactive oxygen species (ROS), with absorption/emission maxima at 644/665 nm.&amp;nbsp;</td></tr><tr><td>Y-PER protein extraction reagent&amp;nbsp;</td><td>Thermo Scientific</td><td>78990</td><td>Liquid cell lysis buffer</td></tr><tr><td>Acrylamide/Bis-acrylamide</td><td>Sigma</td><td>A6050</td><td>Solution</td></tr><tr><td>Bradford dye reagent</td><td>Bio-Rad&amp;nbsp;</td><td>5000205</td><td>Dye reagent for one-step determination of protein concentration</td></tr><tr><td>&amp;beta;-amyloid antibody 6E10&amp;nbsp;</td><td>BioLegend</td><td>803001</td><td>Mouse IgG1. The epitope lies within amino acids 3-8 of beta amyloid (EFRHDS).</td></tr><tr><td>Goat anti-mouse IgG-HRP conjugate&amp;nbsp;</td><td>Bio-Rad</td><td>1721011</td><td></td></tr><tr><td>Membrane Immobilon-P, PVDF</td><td>Millipore</td><td>IPVH00010</td><td></td></tr><tr><td>Luminata forte</td><td>Merk</td><td>WBLUF0100</td><td>Premixed, ready to use chemiluminescent HRP detection reagent</td></tr><tr><td>Phenylmethanesulfonyl fluoride solution (PMSF)</td><td>Sigma</td><td>93482</td><td>Protease inhibitor. Dissolved at 0.1 M in ethanol</td></tr><tr><td>FACSCanto flow cytometer&amp;nbsp;</td><td>BD Biosciences</td><td>657338</td><td>Equipped with a 488&amp;nbsp;nm blue laser for the detection of GFP, and 635&amp;nbsp;nm red laser / 530/30 nm BP filter and 660/20 BP filter</td></tr><tr><td>Mini Trans-Blot Electrophoresis Transfer cell</td><td>Bio-Rad</td><td>1703930</td><td>Protein transference system</td></tr><tr><td>Mini-PROTEAN Tetra Handcast Systems</td><td>Bio-Rad</td><td>1658000FC</td><td>Electrophoresis system</td></tr></tbody></table>

evaluation of the impact of protein aggregation on cellular oxidative stress in yeast

Protein misfolding und Aggregation in Amyloid Konformationen haben an der Entstehung und Progression von mehreren neurodegenerativen Erkrankungen in Zusammenhang gebracht. Allerdings gibt es noch wenig Informationen über wie unlöslichen Protein Aggregate ihre toxische Wirkung in Vivoausüben. Einfaches Modell der prokaryotischen und eukaryotischen Organismen, wie Bakterien und Hefen, trugen wesentlich zur unsere gegenwärtigen Verständnis der Mechanismen hinter der intrazellulären Amyloid Bildung, Aggregate Ausbreitung und Toxizität. In diesem Protokoll bezeichnet man die Verwendung von Hefe als ein Modell, um die Beziehung zwischen der Entstehung von Protein-Aggregate und ihre Auswirkungen auf die zellulären oxidativen Stress zu sezieren. Die Methode verbindet die Erkennung der intrazellulären löslich/aggregiert Bundesstaat ein Amyloidogenic Protein mit der Quantifizierung der zellulären oxidativen Schäden, die aus ihren Ausdruck mit Durchflusszytometrie (FC). Dieser Ansatz ist einfach, schnell und quantitative. Die Studie zeigt die Technik durch Korrelation der zellulären oxidativen Stress, verursacht durch eine große Anzahl von Amyloid-β-Peptid-Varianten mit ihren jeweiligen inneren Aggregation Neigungen.

Dieses Protokoll beschreibt, wie eine Sammlung von 20 Varianten des Peptids Aβ42 zu beschäftigen, wo Phe19 auf alle natürliche proteinogene Aminosäuren28mutiert worden ist. Die theoretische Aggregation Neigungen dieser Proteine können mit zwei verschiedenen bioinformatische Algorithmen (AGGRESCAN und TANGO31,32) analysiert werden. In beiden Fällen macht diese Analyse eine progressive Abstufung der Agg...

Watch this Scientific Journal Video about Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast at JoVE.com

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

Bewertung der Auswirkungen der Proteinaggregation auf zellulären oxidativen Stress in der Hefe

Proteinaggregation entlockt zellulären oxidativen Stress. Dieses Protokoll beschreibt eine Methode zur Überwachung der intrazellulären Staaten von Amyloidogenic Proteinen und den oxidativen Stress zugeordnet werden, mit Hilfe der Durchflusszytometrie. Der Ansatz dient zur Untersuchung des Verhaltens von löslichen und Aggregation neigende Varianten des β-Amyloid Peptids.

Protein misfolding and aggregation into amyloid conformations have been related to the onset and progression of several neurodegenerative diseases. ...

evaluation-impact-protein-aggregation-on-cellular-oxidative-stress

Research

JoVE Journal

Biochemistry

7.2K Aufrufe.  Universitat Autònoma de Barcelona. Proteinaggregation entlockt zellulären oxidativen Stress. Dieses Protokoll beschreibt eine Methode zur Überwachung der intrazellulären Staaten von Amyloidogenic Proteinen und den oxidativen Stress zugeordnet werden, mit Hilfe der Durchflusszytometrie. Der Ansatz dient zur Untersuchung des Verhaltens von löslichen und Aggregation neigende Varianten des β-Amyloid Peptids.

Serie: Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

Defining Hsp33's Redox-regulated Chaperone Activity and Mapping Conformational Changes on Hsp33 Using Hydrogen-deuterium Exchange Mass Spectrometry

Living organisms regularly need to cope with fluctuating environments during their life cycle, including changes in temperature, pH, the accumulation of reactive oxygen species, and more. These fluctuations can lead to a widespread protein unfolding, aggregation, and cell death. Therefore, cells have evolved a dynamic and stress-specific network of molecular chaperones, which maintain a "healthy" proteome during stress conditions. ATP-independent chaperones constitute one major class of molecular chaperones, which serve as first-line defense molecules, protecting against protein aggregation in a stress-dependent manner. One feature these chaperones have in common is their ability to utilize structural plasticity for their stress-specific activation, recognition, and release of the misfolded client. 
In this paper, we focus on the functional and structural analysis of one such intrinsically disordered chaperone, the bacterial redox-regulated Hsp33, which protects proteins against aggregation during oxidative stress. Here, we present a toolbox of diverse techniques for studying redox-regulated chaperone activity, as well as for mapping conformational changes of the chaperone, underlying its activity. Specifically, we describe a workflow which includes the preparation of fully reduced and fully oxidized proteins, followed by an analysis of the chaperone anti-aggregation activity in vitro using light-scattering, focusing on the degree of the anti-aggregation activity and its kinetics. To overcome frequent outliers accumulated during aggregation assays, we describe the usage of Kfits, a novel graphical tool which allows easy processing of kinetic measurements. This tool can be easily applied to other types of kinetic measurements for removing outliers and fitting kinetic parameters. To correlate the function with the protein structure, we describe the setup and workflow of a structural mass spectrometry technique, hydrogen-deuterium exchange mass spectrometry, that allows the mapping of conformational changes on the chaperone and substrate during different stages of Hsp33 activity. The same methodology can be applied to other protein-protein and protein-ligand interactions.

One of the most challenging stress conditions that organisms encounter during their lifetime involves the accumulation of oxidants. During oxidative stress, cells heavily rely on molecular chaperones. Here, we present methods used to investigate the redox-regulated anti-aggregation activity, as well as to monitor structural changes governing the chaperone function using HDX-MS.

Hsp33 des Redox-regulierten Chaperon Aktivität definieren und Mapping Konformationsänderungen auf Hsp33 mit Wasserstoff-Deuterium Austausch Massenspektrometrie

Living organisms regularly need to cope with fluctuating environments during their life cycle, including changes in temperature, pH, the accumulation of ...

Forschung

Biochemie

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein aggregation. The accumulation of protein aggregates in bacterial cells can lead to significant alterations in the cellular phenotypic behavior, including a reduction in growth rates, stress resistance, and virulence. Several experimental procedures exist for the examination of these stressor-mediated phenotypes. This paper describes an optimized assay for the extraction and visualization of aggregated and soluble proteins from different Escherichia coli strains after treatment with a silver-ruthenium-containing antimicrobial. This compound is known to generate reactive oxygen species and causes widespread protein aggregation. 
The method combines a centrifugation-based separation of protein aggregates and soluble proteins from treated and untreated cells with subsequent separation and visualization by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Coomassie staining. This approach is simple, fast, and allows a qualitative comparison of protein aggregate formation in different E. coli strains. The methodology has a wide range of applications, including the possibility to investigate the impact of other proteotoxic antimicrobials on in vivo protein aggregation in a wide range of bacteria. Moreover, the protocol can be used to identify genes that contribute to increased resistance to proteotoxic substances. Gel bands can be used for the subsequent identification of proteins that are particularly prone to aggregation.

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

This protocol describes the extraction and visualization of aggregated and soluble proteins from Escherichia coli after treatment with a proteotoxic antimicrobial. Following this procedure allows a qualitative comparison of protein aggregate formation in vivo in different bacterial strains and/or between treatments.

Extraktion und Visualisierung von Proteinaggregaten nach Behandlung von Escherichia coli mit einem proteotoxischen Stressor

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein ...

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent. In the experiment, yeast is grown for 48 hours in 1/2X YPD broth containing 3X glucose. The culture is split into a control and treated group. The experiment culture is treated with 0.5 mM H2O2 in Hanks Buffered Saline (HBSS) for 1 hour. The control culture is treated with HBSS only. Total RNA is extracted from both cultures and is converted to a biotin-labeled cRNA product through a multistep process. The final synthesis product is taken back to the UVM Microarray Core Facility and hybridized to the Affymetrix yeast GeneChips. The resulting gene expression data are uploaded into bioinformatics data analysis software.

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent.

Microarray-Analyse für Saccharomyces cerevisiae</em

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen ...

Biologie

Growth Assays to Assess Polyglutamine Toxicity in Yeast

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's disease, and Huntington's disease 1. Huntington's disease (HD) is caused by the abnormal expansion of a polyglutamine (polyQ) region within the protein huntingtin. The polyQ-expanded huntingtin protein attains an aberrant conformation (i.e. it misfolds) and causes cellular toxicity 2. At least eight further neurodegenerative diseases are caused by polyQ-expansions, including the Spinocerebellar Ataxias and Kennedy&#x2019;s disease 3.
The model organism yeast has facilitated significant insights into the cellular and molecular basis of polyQ-toxicity, including the impact of intra- and inter-molecular factors of polyQ-toxicity, and the identification of cellular pathways that are impaired in cells expressing polyQ-expansion proteins 3-8. Importantly, many aspects of polyQ-toxicity that were found in yeast were reproduced in other experimental systems and to some extent in samples from HD patients, thus demonstrating the significance of the yeast model for the discovery of basic mechanisms underpinning polyQ-toxicity. 
A direct and relatively simple way to determine polyQ-toxicity in yeast is to measure growth defects of yeast cells expressing polyQ-expansion proteins. This manuscript describes three complementary experimental approaches to determine polyQ-toxicity in yeast by measuring the growth of yeast cells expressing polyQ-expansion proteins. The first two experimental approaches monitor yeast growth on plates, the third approach monitors the growth of liquid yeast cultures using the BioscreenC instrument. 
Furthermore, this manuscript describes experimental difficulties that can occur when handling yeast polyQ models and outlines strategies that will help to avoid or minimize these difficulties. The protocols described here can be used to identify and to characterize genetic pathways and small molecules that modulate polyQ-toxicity. Moreover, the described assays may serve as templates for accurate analyses of the toxicity caused by other disease-associated misfolded proteins in yeast models.

This manuscript describes three complementary protocols for assessing the toxicity of polyglutamine (polyQ)-expansion proteins in the yeast Saccharomyces cerevisiae. These protocols can easily be modified to monitor the toxicity of other misfolded proteins in yeast.

Wachstums-Assays zur Beurteilung Polyglutamin Toxizität in Hefe

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's ...

4D Imaging of Protein Aggregation in Live Cells

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental conditions and an intracellular environment that is tightly packed, sticky, and hazardous to protein stability1. The ability to dynamically balance protein production, folding and degradation demands highly-specialized quality control machinery, whose absolute necessity is observed best when it malfunctions. Diseases such as ALS, Alzheimer's, Parkinson's, and certain forms of Cystic Fibrosis have a direct link to protein folding quality control components2, and therefore future therapeutic development requires a basic understanding of underlying processes. Our experimental challenge is to understand how cells integrate damage signals and mount responses that are tailored to diverse circumstances.
The primary reason why protein misfolding represents an existential threat to the cell is the propensity of incorrectly folded proteins to aggregate, thus causing a global perturbation of the crowded and delicate intracellular folding environment1. The folding health, or "proteostasis," of the cellular proteome is maintained, even under the duress of aging, stress and oxidative damage, by the coordinated action of different mechanistic units in an elaborate quality control system3,4. A specialized machinery of molecular chaperones can bind non-native polypeptides and promote their folding into the native state1, target them for degradation by the ubiquitin-proteasome system5, or direct them to protective aggregation inclusions6-9.
In eukaryotes, the cytosolic aggregation quality control load is partitioned between two compartments8-10: the juxtanuclear quality control compartment (JUNQ) and the insoluble protein deposit (IPOD) (Figure 1 - model). Proteins that are ubiquitinated by the protein folding quality control machinery are delivered to the JUNQ, where they are processed for degradation by the proteasome. Misfolded proteins that are not ubiquitinated are diverted to the IPOD, where they are actively aggregated in a protective compartment.
Up until this point, the methodological paradigm of live-cell fluorescence microscopy has largely been to label proteins and track their locations in the cell at specific time-points and usually in two dimensions. As new technologies have begun to grant experimenters unprecedented access to the submicron scale in living cells, the dynamic architecture of the cytosol has come into view as a challenging new frontier for experimental characterization. We present a method for rapidly monitoring the 3D spatial distributions of multiple fluorescently labeled proteins in the yeast cytosol over time. 3D timelapse (4D imaging) is not merely a technical challenge; rather, it also facilitates a dramatic shift in the conceptual framework used to analyze cellular structure.
We utilize a cytosolic folding sensor protein in live yeast to visualize distinct fates for misfolded proteins in cellular aggregation quality control, using rapid 4D fluorescent imaging. The temperature sensitive mutant of the Ubc9 protein10-12 (Ubc9ts) is extremely effective both as a sensor of cellular proteostasis, and a physiological model for tracking aggregation quality control. As with most ts proteins, Ubc9ts is fully folded and functional at permissive temperatures due to active cellular chaperones. Above 30 &deg;C, or when the cell faces misfolding stress, Ubc9ts misfolds and follows the fate of a native globular protein that has been misfolded due to mutation, heat denaturation, or oxidative damage. By fusing it to GFP or other fluorophores, it can be tracked in 3D as it forms Stress Foci, or is directed to JUNQ or IPOD.

Cellular viability depends on timely and efficient management of protein misfolding. Here we describe a method for visualizing the different potential fates of a misfolded protein: refolding, degradation, or sequestration in inclusions. We demonstrate the use of a folding sensor, Ubc9ts, for monitoring proteostasis and aggregation quality control in live cells using 4D microscopy.

4D-Bildgebung von Protein Aggregation in lebenden Zellen

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental ...

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must be maintained to avoid deleterious consequences 1. External or internal factors that disrupt this balance can lead to protein aggregation, toxicity and cell death. In humans this is a major contributing factor to the symptoms associated with neurodegenerative disorders such as Huntington's, Parkinson's, and Alzheimer's diseases 10. It is therefore essential that the proteins involved in maintenance of proteostasis be identified in order to develop treatments for these debilitating diseases. This article describes techniques for monitoring in vivo protein folding at near-real time resolution using the model protein firefly luciferase fused to green fluorescent protein (FFL-GFP). FFL-GFP is a unique model chimeric protein as the FFL moiety is extremely sensitive to stress-induced misfolding and aggregation, which inactivates the enzyme 12. Luciferase activity is monitored using an enzymatic assay, and the GFP moiety provides a method of visualizing soluble or aggregated FFL using automated microscopy. These coupled methods incorporate two parallel and technically independent approaches to analyze both refolding and functional reactivation of an enzyme after stress. Activity recovery can be directly correlated with kinetics of disaggregation and re-solubilization to better understand how protein quality control factors such as protein chaperones collaborate to perform these functions. In addition, gene deletions or mutations can be used to test contributions of specific proteins or protein subunits to this process. In this article we examine the contributions of the protein disaggregase Hsp104 13, known to partner with the Hsp40/70/nucleotide exchange factor (NEF) refolding system 5, to protein refolding to validate this approach.

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

This article describes the use of a firefly luciferase-GFP fusion protein to investigate in vivo protein folding in Saccharomyces cerevisiae. Using this reagent, refolding of a model heat-denatured protein can be monitored simultaneously by fluorescence microscopy and an enzymatic assay to probe the roles of proteostasis network components in protein quality control.

Gekoppelt Assays zur Überwachung Proteinrückfaltung in<em&gt; Saccharomyces cerevisiae</em

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must ...

Isolating Potentiated Hsp104 Variants Using Yeast Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic lateral sclerosis, and &#945;-synuclein, implicated in Parkinson&#8217;s disease, are toxic and form cytoplasmic aggregates in yeast. These features recapitulate protein pathologies observed in patients with these disorders. Thus, yeast are an ideal platform for isolating toxicity suppressors from libraries of protein variants. We are interested in applying protein disaggregases to eliminate misfolded toxic protein conformers. Specifically, we are engineering Hsp104, a hexameric AAA+ protein from yeast that is uniquely capable of solubilizing both disordered aggregates and amyloid and returning the proteins to their native conformations. While Hsp104 is highly conserved in eukaryotes and eubacteria, it has no known metazoan homologue. Hsp104 has only limited ability to eliminate disordered aggregates and amyloid fibers implicated in human disease. Thus, we aim to engineer Hsp104 variants to reverse the protein misfolding implicated in neurodegenerative disorders. We have developed methods to screen large libraries of Hsp104 variants for suppression of proteotoxicity in yeast. As yeast are prone to spontaneous nonspecific suppression of toxicity, a two-step screening process has been developed to eliminate false positives. Using these methods, we have identified a series of potentiated Hsp104 variants that potently suppress the toxicity and aggregation of TDP-43, FUS, and &#945;-synuclein. Here, we describe this optimized protocol, which could be adapted to screen libraries constructed using any protein backbone for suppression of toxicity of any protein that is toxic in yeast.

Yeast proteinopathy models are valuable tools to assess the toxicity and aggregation of proteins implicated in disease. Here, we present methods for screening Hsp104 variant libraries for toxicity suppressors. This protocol could be adapted to screen any protein library for toxicity suppressors of any protein that is toxic in yeast.

Isolieren Potenzierte Hsp104 Varianten unter Verwendung von Hefe Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic ...

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein synthesis and protein degradation. Many assays reporting on protein abundance (e.g., single-time point western blotting, flow cytometry, fluorescence microscopy, or growth-based reporter assays) do not allow discrimination of the relative effects of translation and proteolysis on protein levels. This article describes the use of cycloheximide chase followed by western blotting to specifically analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast). In this procedure, yeast cells are incubated in the presence of the translational inhibitor cycloheximide. Aliquots of cells are collected immediately after and at specific time points following addition of cycloheximide. Cells are lysed, and the lysates are separated by polyacrylamide gel electrophoresis for western blot analysis of protein abundance at each time point. The cycloheximide chase procedure permits visualization of the degradation kinetics of the steady state population of a variety of cellular proteins. The procedure may be used to investigate the genetic requirements for and environmental influences on protein degradation.

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Protein abundance reflects the rates of both protein synthesis and protein degradation. This article describes the use of cycloheximide chase followed by western blotting to analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast).

Cycloheximid Chase-Analyse von Proteinabbau in<em&gt; Saccharomyces cerevisiae</em

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein ...

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

In the last decades, the prevalence of neurodegenerative disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD), has grown. These age-associated disorders are characterized by the appearance of protein aggregates with fibrillary structure in the brains of these patients. Exactly why normally soluble proteins undergo an aggregation process remains poorly understood. The discovery that protein aggregation is not limited to disease processes and instead part of the normal aging process enables the study of the molecular and cellular mechanisms that regulate protein aggregation, without using ectopically expressed human disease-associated proteins. Here we describe methodologies to examine inherent protein aggregation in Caenorhabditis elegans through complementary approaches. First, we examine how to grow large numbers of age-synchronized C. elegans to obtain aged animals and we present the biochemical procedures to isolate highly-insoluble-large aggregates. In combination with a targeted genetic knockdown, it is possible to dissect the role of a gene of interest in promoting or preventing age-dependent protein aggregation by using either a comprehensive analysis with quantitative mass spectrometry or a candidate-based analysis with antibodies. These findings are then confirmed by in vivo analysis with transgenic animals expressing fluorescent-tagged aggregation-prone proteins. These methods should help clarify why certain proteins are prone to aggregate with age and ultimately how to keep these proteins fully functional.

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

The goal of the method presented here is to explore protein aggregation during normal aging in the model organism C. elegans. The protocol represents a powerful tool to study the highly insoluble large aggregates that form with age and to determine how changes in proteostasis impact protein aggregation.

Methoden zur Untersuchung Veränderungen inhärenten Proteinaggregation mit dem Alter in Caenorhabditis elegans

In the last decades, the prevalence of neurodegenerative disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD), has grown. These ...

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble proteins over 40% of the time results in an extension of the lifespan in C. elegans, suggesting that many of these proteins are key determinants of the aging process. Isolation and quantitative identification of these insoluble proteins are crucial to understand key biological processes that occur during aging. Here, we present a modified and improved protocol that details how to extract and isolate the SDS-insoluble proteins (insolublome) from C. elegans more efficiently to streamline mass spectrometric workflows via a novel label-free quantitative proteomics analysis. This improved protocol utilizes a highly efficient sonicator for worm lysis that greatly increases efficiency for protein extraction and allows us to use significantly less starting material (approximately 3,000 worms) than in previous protocols (typically using at least 40,000 worms). Subsequent quantitative proteomic analysis of the insolublome was performed using data-dependent acquisition (DDA) for protein discovery and identification and data-independent acquisition (DIA) for comprehensive and more accurate protein quantification. Bioinformatic analysis of quantified proteins provides potential candidates that can be easily followed up with other molecular methods in C. elegans. With this workflow, we routinely identify more than 1000 proteins and quantify more than 500 proteins. This new protocol enables efficient compound screening with C. elegans. Here, we validated and applied this improved protocol to wild-type C. elegans N2-Bristol strain and confirmed that aged day-10 N2 worms showed greater accumulation of the insolublome than day-2 young worms.

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

This novel workflow efficiently extracts and isolates SDS-insoluble proteins (insolublome) from Caenorhabditis elegans with minimal starting material for quantitative differential proteomic analysis. The protocol uses a comprehensive data-independent acquisition mass spectrometry analysis to quantify the insolublome and bioinformatic analysis to gain biological insights into aging mechanisms and pathologies.

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble ...

Bewertung der Auswirkungen der Proteinaggregation auf zellulären oxidativen Stress in der Hefe

Zusammenfassung

Weitere Videos entdecken

Kapitel in diesem Video

Hsp33 des Redox-regulierten Chaperon Aktivität definieren und Mapping Konformationsänderungen auf Hsp33 mit Wasserstoff-Deuterium Austausch Massenspektrometrie

Extraktion und Visualisierung von Proteinaggregaten nach Behandlung von Escherichia coli mit einem proteotoxischen Stressor

Microarray-Analyse für Saccharomyces cerevisiae

Wachstums-Assays zur Beurteilung Polyglutamin Toxizität in Hefe

4D-Bildgebung von Protein Aggregation in lebenden Zellen

Gekoppelt Assays zur Überwachung Proteinrückfaltung in

Isolieren Potenzierte Hsp104 Varianten unter Verwendung von Hefe Proteinopathy Models

Cycloheximid Chase-Analyse von Proteinabbau in

Methoden zur Untersuchung Veränderungen inhärenten Proteinaggregation mit dem Alter in Caenorhabditis elegans

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow