1. culturas de S. cerevisiae e expressão da proteína
Nota: Variantes Aβ apresentam propensões de agregação relativa diferente devido a uma mutação em um único resíduo na posição 19 (Phe19) do peptídeo Aβ42 (figura 1A). Essas variantes do peptide são marcados com a proteína fluorescente verde (GFP), que actua como uma agregação de repórter (Figura 1)29.
<ol><li>Transforme os plasmídeos codificação para 20 variantes de Aβ42-GFP em células de levedura com um BY4741 fundo parental (MATa seu3Δ1 leu2Δ0 conheceu15Δ0 ura3Δ0)30. Cada plasmídeo codifica para um mutante de Aβ42 fundido a GFP por um vinculador GSSGSSG. Os plasmídeos são pESC(-URA) e incluem o marcador selecionável URA329.<ol>
<li>Prepare o suporte completo sintético sem uracil (SC-URA) com os seguintes componentes: 1,9 g/L nitrogênio levedura base sem uracil, 5g/L sulfato de amónio e 900 mL de DDQ2O combinado com 100 mL de glicose de 20% (p/v).</li>
		<li>Colocar uma colônia das células de fermento transformado em 20 mL do meio de SC-URA contendo 2% de glicose e crescem as culturas durante a noite a 30 ° C, sob agitação a 210 rpm.</li>
	</ol>
</li>
	<li>No dia seguinte, cresce novas culturas de células de levedura por inoculando 100 µ l de cultura durante a noite em 5 mL de meio fresco SC-URA.</li>
	<li>Em uma OD590 de 0.5, Centrifugar as culturas a 3.000 x g durante 4 min, desprezar o sobrenadante e ressuspender as células no mesmo volume de meio de SC-URA fresco contendo 2% rafinose.</li>
	<li>Incube a 30 ° C, sob agitação a 210 rpm por 30 min. Em seguida, Centrifugar as células a 3.000 x g, durante 4 min e descartar o sobrenadante. Ressuspender as células em meio de SC-URA fresco contendo 2% de galactose para induzir a expressão da proteína recombinante.</li>
	<li>Após 16 h de induzir a expressão de proteínas em meio de SC-URA contendo 2% de galactose, colha 1 mL de células induzidas em tubos estéreis microcentrifuga por centrifugação a 3.000 x g, durante 4 min. Nota: As diferenças mais relevantes ocorrem após um período de indução de células de levedura induzida de 16 h. expressando variantes de Aβ42-GFP pode ser visualizado por microscopia de fluorescência para determinar a distribuição de proteína recombinante no interior das células (Figura 2B).</li>
</ol>2. coloracao celular
Nota: As pilhas novas não induzida são necessárias como um controle negativo para estabelecer um limiar fluorescente durante uma análise FC.
<ol><li>Levar as células de levedura induzida por h 16 e determinar sua densidade óptica, a 590 nm (OD590). Diluí-los em uma solução salina estéril tamponada de fosfato (PBS) para um OD590 de 0.1.<ol>
<li>Preparar 1 x solução salina tamponada fosfato como segue: adicionar 8 g de NaCl, 0,2 g de KCl, 1,44 g de Na2HPO4, e 0,24 g de KH2PO4 a 800 mL de DDQ2O. Preencha a solução até 1 L de DDQ2O depois de ajustar o pH para 7,4 com HCl. Filtre o buffer com um filtro de 0,2 µm.</li>
	</ol>
</li>
	<li>Transferir as suspensões celulares expressando para tubos apropriadamente rotulados (12 × 75 de poliestireno de hum fundo redondo) e protegê-los de luz. Certifique-se de que estão prontos para ser carregado no citômetro de fluxo para análise, juntamente com células não-induzido e não manchada.</li>
	<li>Adicionar a sonda de estresse oxidativo (por exemplo, CellROX vermelha) para cada amostra em uma concentração final de 5 µM e incube as celulas a 30 ° C por 30 min no escuro.</li>
	<li>Após a incubação, lavar as células 3 vezes com 1X PBS e ressuspendê-los no mesmo volume da reserva antes da sua análise pela FC.</li>
</ol>3. fluxo Cytometry Analysis
Nota: Use uma configuração FC com lasers apropriados e filtros para detectar GFP e sinal de fluorescência de sonda de estresse oxidativo. Um citômetro de fluxo, equipado com um 488 nm azul do laser para a detecção de GFP e laser 635 nm vermelho para a detecção de fluorescência de sonda de stress oxidativo pode ser usado. Aquisição da fluorescência de emissão de GFP e sonda de estresse oxidativo é executada com um filtro de nm BP 530/30 e um filtro de BP 660/20, respectivamente (tabela 1).
<ol><li>Clique em Abrir novo painel de planilha e crie os seguintes lotes do ponto de aquisição.<ol>
<li>Selecione a Ferramenta de plotagem Scatter na barra de ferramentas e criar um enredo com as variáveis Scatter-área lateral (SSC-A) sobre o eixo y vs Forward Scatter-área (FSC-A) em uma escala linear no eixo x.</li>
		<li>Clique na Ferramenta de plotagem Scatter na barra de ferramentas e criar um enredo com as variáveis FL1-área (FITC) sobre o eixo x vs. FL3-área (APC) em uma escala logarítmica no eixo y.</li>
	</ol>
</li>
	<li>Clique no ícone Configurações de instrumentos . Clique na guia de compensação e definir todos os níveis de compensação. Clique na guia de aquisição e selecione um número total de 20.000 eventos para ser gravado.</li>
	<li>Clique no ícone de Caudal para mudar a taxa de fluxo para baixo.</li>
	<li>Clique na guia de adquirir para começar a correr as células não-induzida, imaculadas e ajustar a tensão nas Configurações do instrumento do RCS e dispersão de lado até que a população é distribuída no quadrante médio esquerdo.<ol>
<li>Clique no ícone do polígono para definir uma região R1, em torno de população celular excluindo os restos da célula e usar esta população gated P1 = R1 para todos os lotes do ponto fluorescente e representações de histograma (Figura 3).</li>
	</ol>
</li>
	<li>Para ajustar a tensão de PGTO do sinal de fluorescência, execute as células imaculadas na trama ponto FL1-FL3, ajuste o ganho na guia Configuração do instrumento , até que as células são distribuídas no quadrante inferior esquerdo.</li>
	<li>Altere a amostra para as células induzidas para medir a fluorescência de GFP. Na guia Configuração do instrumento , defina o ganho no FSC-A vs FL1 (FITC) quando a população é distribuída no quadrante inferior direito. Defina a população de células positivas com um portão (portão P2).</li>
	<li>Mudança da amostra para o não-induzida manchado células para exibir o estresse oxidativo por fluorescência em um terreno de ponto FSC-A vs FL3 (APC). Ajuste o ganho até a população celular é distribuída no quadrante esquerdo superior. A população de células positivas em P3 de portão.</li>
	<li>Fazer duas parcelas de histograma com o ícone de histograma para representar a fluorescência da célula. Para representar a intensidade da fluorescência, certifique-se de FL1 (FITC) representando a fluorescência de GFP é no eixo x e FL3 (APC) representando a fluorescência é no eixo y, aplicando as populações P2 e P3 em uma escala logarítmica, respectivamente. Nota: As sobreposições de histograma são uma boa maneira de ilustrar as diferenças entre os perfis de fluorescência das células expressando diferentes variantes Aβ.</li>
</ol>4. recombinação da proteína Immunodetection
<ol><li>Para determinar os níveis de expressão da proteína, colher as culturas de leveduras induzidas por 16 h por centrifugação a 4.000 x g durante 6 min e armazenar as pelotas de célula a-80 ° C.<ol>
<li>Ressuspender as células coletadas, expressando a proteína recombinante para 16 h em PBS. Prepare suspensões da pilha de 200 µ l de cada mutante de Aβ42-GFP para uma OD590 de 20.</li>
	</ol>
</li>
	<li>Para análise de fração de proteínas totais, colheita de 100 µ l de cada mutante por centrifugação a 14.000 x g por 20 min e ressuspender as pelotas de célula no mesmo volume de tampão de lise de leveduras Y-PER (50 mM Tris-HCl pH 8,0, 1% DMSO, 200 mM de NaCl, 1 mM EDTA, contendo 10 mg/mL (myr SB3-14 istyl sulfobetaine) suplementado com fluoreto de phenylmethylsulfonyl de 1 mM (PMSF)).<ol>
<li>Incube as amostras por 20 min em temperatura ambiente sob leve agitação.</li>
	</ol>
</li>
	<li>Determine a concentração de extrato de proteínas usando o ensaio de Bradford. Carrega até 5 µ g de extrato de proteína de cada amostra em um gel de electroforese de SDS-PAGE 15% acrilamida e borrão em uma membrana de difluoreto (PVDF) de polivinilideno a 100 V por 60 min.<ol>
<li>Prepare um Bradford reagente com 100 mg de azul de Coomassie brilhante G-250 dissolvido em 50 mL de etanol a 95% e adicionar 100 mL de ácido fosfórico 85% (p/v). Então, quando o corante é completamente dissolvido, diluir a mistura com o ddH2O de 1L e filtrar por papel de filtro de celulose imediatamente antes da utilização. Nota: O reagente de Bradford deve ser marrom claro.</li>
		<li>Prepare um padrão de albumina de soro bovino (BSA) variando de 5-100 µ g de proteína em 1.000 µ l de reagente de Bradford.</li>
		<li>Adicione 1-10 µ l de proteína extrair a 1 mL de reagente de Bradford e incubar a mistura à temperatura ambiente por 5 min.</li>
		<li>Medir a absorvância das normas e a proteína extrair amostras em OD595.</li>
		<li>Para a análise, fazer um gráfico com os valores de absorvância obtidos para os padrões vs. µ g de proteína. Com base na curva padrão, determine as concentrações das amostras originais da quantidade de proteína, considerando o volume e a diluição, se for o caso.</li>
	</ol>
</li>
	<li>Lavar a membrana com 1 x salino Tris (TBS), 0.1% Tween 20 (TTBS) e bloqueá-lo usando leite seco desnatado 5% (p/v) em 1 x TTBS.<ol>
<li>Para preparar 1 L de 10 x TBS, dissolver 24 g de Tris base e 88 g de NaCl em 900 mL de H2Odd e ajustar o pH 7,6. Adicionar O ddH2até um volume final de 1 L. Para uma solução de 1 x, misturar 1 parte de estoque de x 10 com 9 peças de DDQ2O.</li>
	</ol>
</li>
	<li>Incubar a membrana para 1 h com um anticorpo primário de β-amiloide 6E10 diluído 1:1,000 e por 1h à temperatura ambiente com uma cabra de anticorpo secundário conjugado de anti-mouse IgG HRP diluído 01:10, 000.</li>
	<li>Desenvolver membranas usando 1 mL do reagente fluorescente Luminata e quantificar bandas por análise densitométricos, conforme descrito na etapa 5.2.</li>
</ol>5. análise de dados
<ol><li>Para analisar os dados obtidos pelo FC, criar uma tabela que exibe a média intensidade fluorescente (IFM) e fluorescência mediana com seu correspondente desvio-padrão e/ou o coeficiente de variação (CV) para os níveis de estresse oxidativo e fluorescência de GFP.<ol>
<li>Clique na guia de Inspetor e o ícone de estatísticas para personalizar os dados estatísticos que são necessários para cada canal. Nota: Quando se comparam as variantes da proteína, converta dados valores de fluorescência para um fundo dobrável ou resolução métrica (RD): <img alt="Equation 1" src="/files/ftp_upload/57470/57470eq1.jpg"> Nesta métrica, a amostra média é a média fluorescência das amostras do problema, o controle médio é a média fluorescência das células usado como um controle e o SD é o desvio-padrão da média fluorescência. Fator de RD é um índice mais exato do que o valor de IFM como ele não só calcula a diferença entre as amostras, mas também as contas para a divulgação dos dados. Este cálculo é especificamente relevante quando comparar dados provenientes de diferentes experiências realizadas ao longo do tempo. Uma vez que o RDs foram calculado, o uso de um teste estatístico é aconselhável confirmar a significância das diferenças observadas entre as variantes da proteína.</li>
	</ol>
</li>
	<li>Para a proteína immunodetection, quantificar os níveis de proteína recombinante por Western blot utilizando software ImageJ.<ol>
<li>Antes da análise de densitometria, converta as imagens raw originais da membrana desenvolvida em modo JPEG arquivo formato e escala de cinza.</li>
		<li>Ajuste a seção Definir medições do menu Analyze para Dizer o valor de cinza.</li>
		<li>Clique na ferramenta retângulo do ImageJ e definir uma região de interesse (ROI) com um tamanho consistente para a análise de densitometria de banda. Centro de cada banda na imagem dentro da moldura retangular criada de membrana e registrar a medição de um por um, usando Ctrl + M (o comando de medição).</li>
		<li>Meça o fundo local adjacente à cada banda, aplicando a mesma área ROI. Após a medição, subtrai o fundo local correspondente de cada banda individual.</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>

Uma ampla gama de doenças está ligada ao acúmulo de misfolded proteínas em depósitos celulares6,7,8,33. Muitos esforços foram feitos para desvendar os mecanismos moleculares que desencadeiam o aparecimento destas doenças usando abordagens computacionais, que não levam em concentrações de proteína de conta, ou em vitro se aproxima, em que a concentração de proteína mantém...

Proteostasis é um determinante fundamental dos processos de adequação e envelhecimento celular. Nas células, homeostase de proteína é mantida pelo controle de qualidade de proteína sofisticadas redes visa garantir a correta dobrar de conformistas de misfolded proteínas por acompanhantes e/ou sua proteólise alvejado com vários mecanismos bem conservados1 ,2,3,4,5. Um grande número de estudos oferece suporte à ligação entre o início e a progressão de uma ampla gama de doenças humanas e o fracasso de proteostasis, levando ao enrolamento de proteínas e agregação. Por exemplo, a presença de depósitos de proteína é considerada uma característica patológica de muitas doenças neurodegenerativas, como Alzheimer, Parkinson e Huntington doenças6,7,8, doenças prionogenic e amyloidoses não-degenerativas9. Tem sido sugerido que cedo assemblies oligoméricos e protofibrillar na reação de agregação são os principais elicitores de citotoxicidade, estabelecendo interações aberrantes com outras proteínas no meio lotado de celular10. Além disso, inclusões de proteína (PI) podem ser transmitidos entre as células, seus efeitos tóxicos11,12de propagação. Portanto, pode ser que a formação de PI de fato pode constituir um mecanismo desintoxicante que restringe a presença de espécies perigosas agregados para locais específicos na célula, onde eles podem ser processados ou acumulados sem grandes efeitos colaterais 13 , 14.
Padrão em vitro abordagens bioquímicas forneceram importantes insights sobre as diferentes espécies que povoam as reações de agregação e suas propriedades de15,16. No entanto, as condições usadas nestes ensaios são claramente diferentes das que ocorrem dentro da célula e, portanto, questionar sua relevância fisiológica. Por causa de conservação notável dos caminhos celulares tais como controle de qualidade de proteína, autofagia ou o Regulamento do estado redox celular17,18 entre eucariotas19,20,21 ,22,23, a brotamento de levedura Saccharomyces cerevisiae (S. cerevisiae) surgiu como um modelo de celular simples privilegiado para estudar os determinantes moleculares de agregação da proteína e seu impacto associado citotóxico em ambientes biologicamente relevantes24,25,26.
Propensão de agregação de proteínas é uma característica inerentemente codificada na sequência principal. Assim, a formação de estruturas semelhantes a amiloide pode ser prevista com base na identificação e avaliação da potência de agregação-promover regiões em polipeptídeos27. No entanto, apesar do sucesso de bioinformatic algoritmos para prever as propriedades de agregação em vitro de sequências de proteínas, eles estão ainda longe de previsão como essas propensões traduzem na vivo citotóxicos impacto. Estudos que abordam a relação entre o estado agregado de uma determinada proteína e seu dano celular associado de forma sistemática podem ajudar a contornar essa limitação computacional. Esta conexão é abordada no presente estudo, aproveitando-se de um conjunto grande de variantes do peptídeo β-amiloide Aβ42 diferindo apenas em um único resíduo, mas indicando uma escala contínua de agregação propensões na vivo28. Em particular, uma abordagem baseada em FC para identificar a espécie conformacional representando o dano oxidativo eliciado propensas a agregação de proteínas nas células de levedura é descrita. A metodologia oferece muitas vantagens como simplicidade, capacidade de alta produtividade e precisão das medições quantitativo. Esta abordagem, foi possível confirmar essa jogada de PI um papel protetor contra o estresse oxidativo.

<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

Enrolamento de proteínas e de agregação em conformações amiloides têm sido relacionados ao aparecimento e progressão de várias doenças neurodegenerativas. No entanto, ainda há pouca informação sobre proteína insolúvel como agregados exercem seus efeitos tóxicos em vivo. Organismos-modelo simples de procariotas e eucariotas, tais como bactérias e leveduras, têm contribuído significativamente para nossa compreensão atual dos mecanismos por trás da formação de amiloide intracelular, propagação de agregados e toxicidade. Neste protocolo, o uso de levedura é descrito como um modelo para dissecar a relação entre a formação de agregados de proteínas e seu impacto sobre o estresse oxidativo celular. O método combina a detecção de estado solúvel/agregados intracelular de uma proteína amiloidogénicos com a quantificação dos danos oxidativos celulares resultantes de sua expressão usando citometria de fluxo (FC). Essa abordagem é simples, rápido e quantitativo. O estudo ilustra a técnica correlacionando o estresse oxidativo celular, causado por um conjunto grande de variantes de peptídeo β-amiloide com suas propensões respectiva agregação intrínseca.

Este protocolo descreve como empregar uma coleção de 20 variantes do peptide Aβ42 onde Phe19 alterou a todos os naturais proteinogenic aminoácidos28. A propensão de agregação teórica destas proteínas pode ser analisado usando dois algoritmos diferentes bioinformatic (AGGRESCAN e TANGO31,32). Em ambos os casos, esta análise processa uma gradação progressiva das tendências de agregação, atribui...

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

Avaliação do impacto da agregação da proteína no estresse oxidativo celular na levedura

Agregação da proteína provoca estresse oxidativo celular. Este protocolo descreve um método para monitorar os Estados intracelulares de proteínas amiloidogénicos e o stress oxidativo associado a eles, usando citometria de fluxo. A abordagem é usada para estudar o comportamento de variantes do peptídeo β-amiloide solúveis e propensas a agregação.

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 visualizações.  Universitat Autònoma de Barcelona. Agregação da proteína provoca estresse oxidativo celular. Este protocolo descreve um método para monitorar os Estados intracelulares de proteínas amiloidogénicos e o stress oxidativo associado a eles, usando citometria de fluxo. A abordagem é usada para estudar o comportamento de variantes do peptídeo β-amiloide solúveis e propensas a agregação.

Vídeo: 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.

Definição da atividade de chaperona regulada por redox de Hsp33 e mapeamento de alterações conformacionais em Hsp33 usando espectrometria de massa de troca de hidrogênio-deutério

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

Bioquímica

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.

Extração e Visualização de Agregados proteicos após tratamento de Escherichia coli com um Estressor Proteotóxico

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 Analysis for 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 ...

Biologia

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.

Ensaios de crescimento para avaliar a toxicidade poliglutamina em Levedura

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.

Formação de imagens 4D de agregação de proteínas em células vivas

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.

Ensaios para Monitoramento juntamente redobramento de proteínas em<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.

Isolando potencializado Hsp104 variantes usando levedura 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).

Cicloheximida Análise perseguição de degradação da proteína em<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.

Métodos de estudo mudanças na agregação de proteínas inerente com a idade em 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 ...

Avaliação do impacto da agregação da proteína no estresse oxidativo celular na levedura

Resumo

Explore mais vídeos

Capítulos neste vídeo

Definição da atividade de chaperona regulada por redox de Hsp33 e mapeamento de alterações conformacionais em Hsp33 usando espectrometria de massa de troca de hidrogênio-deutério

Extração e Visualização de Agregados proteicos após tratamento de Escherichia coli com um Estressor Proteotóxico

Microarray Analysis for Saccharomyces cerevisiae

Ensaios de crescimento para avaliar a toxicidade poliglutamina em Levedura

Formação de imagens 4D de agregação de proteínas em células vivas

Ensaios para Monitoramento juntamente redobramento de proteínas em

Isolando potencializado Hsp104 variantes usando levedura Proteinopathy Models

Cicloheximida Análise perseguição de degradação da proteína em

Métodos de estudo mudanças na agregação de proteínas inerente com a idade em Caenorhabditis elegans

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