1.酵母培养和蛋白质表达
注: Aβ变种表现出不同的相对聚集倾向, 由于突变在一个单一的残留在位置 19 (Phe19) 的 Aβ42肽 (图 1A)。这些肽变体被标记为绿色荧光蛋白 (GFP), 它充当聚合报告员 (图 1)29。
<ol><li>将 20 Aβ42-GFP 变种的质粒编码转化成酵母细胞, 具有 BY4741 的父母背景 (他的 3Δ1列伊2Δ0满足15Δ0 ura3 Δ0)30. 每个质粒编码的 Aβ42突变体融合到 GFP 由一个 GSSGSSG 链接器。质粒为收支处 (市建局), 包括可选标记 URA329。<ol>
<li>制备无尿 (SC-市建局) 的合成完全培养基, 其成分为: 1.9 克/升酵母氮基, 无尿, 5 克/升硫酸铵, 900 毫升 ddH2O 结合100毫升 (瓦特/v) 葡萄糖。</li>
		<li>将转化后的酵母细胞的一个菌落放入20毫升的 SC-市建局培养基中, 含2% 葡萄糖, 并在30摄氏度一夜之间以 210 rpm 的搅动生长文化。</li>
	</ol>
</li>
	<li>第二天, 培养新的酵母细胞培养, 通过接种100µL 的隔夜文化成5毫升新鲜的 SC-市建局培养基。</li>
	<li>在 OD590的 0.5, 离心的文化在 3000 x g 4 分钟, 丢弃上清, 并并用重悬细胞在相同数量的新鲜 SC-市建局培养基中含有2% 糖。</li>
	<li>孵育在30°c 下搅动在210转每分钟30分钟。然后, 离心细胞在 3000 x g 4 分钟, 并丢弃上清。并用重悬新鲜的 SC-市建局培养基中含有2% 半乳糖的细胞, 诱导重组蛋白表达。</li>
	<li>16 h 诱导蛋白在 SC-市建局培养基中含有2% 半乳糖后, 在无菌离心管中获得1毫升的诱导细胞, 离心在 3000 x g 处, 4 分钟。 注: 最相关的差异发生在诱导期为16小时的诱导酵母细胞表达 Aβ42-GFP 变种可以通过荧光显微镜可视化, 以确定重组蛋白在细胞内分布 (图 2B)。</li>
</ol>2. 细胞染色
注意: 在 FC 分析期间, 新鲜非诱导细胞作为阴性控制需要建立荧光阈值。
<ol><li>取 16 h 诱导的酵母细胞, 并确定其光学密度在 590 nm (OD590).将其稀释在无菌磷酸盐缓冲盐水 (PBS) 到 OD590的0.1。<ol>
<li>准备1x 磷酸盐缓冲盐水如下: 添加8克氯化钠, 0.2 克氯化钾, 1.44克 Na2HPO4, 和0.24 克的 ddH 2 毫升4至800 mL 2 o 在调整 pH 值到1后, 填充解决方案多达2升 ddH7.4用 HCl 过滤缓冲区通过0.2 µm 过滤器。</li>
	</ol>
</li>
	<li>将表示细胞悬浮液转移到适当标记的管 (12 x 75 毫米圆底聚苯乙烯), 并保护它们不受光照。确保他们已经准备好被装载在流式细胞仪进行分析, 连同非诱导和非染色的电池。</li>
	<li>将氧化应激探针 (例如, CellROX 深红色) 添加到每个样品中, 最终浓度为5µM, 在黑暗中孵化细胞在30摄氏度30分钟。</li>
	<li>孵化后, 用 1x PBS 冲洗细胞3次, 在 FC 分析前将它们并用重悬在相同的缓冲容积内。</li>
</ol>3. 流式细胞仪分析
注: 使用 FC 设置与适当的激光和过滤器, 以检测 GFP 和氧化应激探针荧光信号。一个流式细胞仪配备了 488 nm 蓝激光检测 GFP 和 635 nm 红色激光检测氧化应激探针荧光可以使用。采用 530/30 nm bp 滤波器和 660/20 bp 滤波器分别对 GFP 和氧化应激探针的发射荧光进行了采集 (表 1)。
<ol><li>单击 "打开新工作表" 面板并创建以下购置点图。<ol>
<li>从工具栏中选择散点图工具, 然后在 x 轴上的线性刻度上, 在 y 轴与正向散射区域 ( FSC a) 上创建一个带有变量侧散射区域 (SSC a) 的图。</li>
		<li>单击工具栏上的 "散点图" 工具, 并在 x 轴与 FL1-Area (FITC) 的变量之间创建一个图形。FL3-Area (APC) 在 y 轴上的对数刻度。</li>
	</ol>
</li>
	<li>单击 "仪器设置" 图标。单击 "补偿" 选项卡并设置所有补偿级别。单击 "购置" 选项卡, 然后选择要记录的2万个事件的总数量。</li>
	<li>单击 "流速" 图标可将流量切换到较低的速率。</li>
	<li>单击 "获取" 选项卡, 开始运行非诱导的、无瑕的单元格, 并调整正向和侧向散射的仪器设置中的电压, 直到将人口分布到左中象限。<ol>
<li>点击多边形图标, 设置一个区域 R1 周围的细胞人口, 不包括细胞碎片, 并使用这个门控人口 P1 = R1 所有荧光点图和直方图表示 (图 3)。</li>
	</ol>
</li>
	<li>要调整荧光信号的 PMT 电压, 请在 FL1-FL3 点图中运行无瑕单元格, 调整仪表设置选项卡中的增益, 直到单元格在左下象限中分布。</li>
	<li>将样品改成诱导细胞, 以测定 GFP 荧光。在 "仪器设置" 选项卡中, 在 FL1 (FITC) 中, 当人口分布在右下象限时, 设置在 FSC 中的增益。用门 (门 P2) 定义阳性细胞群。</li>
	<li>将样品改为非诱导的染色细胞, 在 FSC-FL3 (APC) 点图上通过荧光显示氧化应激。调整增益, 直到细胞数量分布在左上象限。P3 阳性细胞群的门。</li>
	<li>用直方图图标绘制两个直方图, 表示细胞荧光。为了表示荧光强度, 请确保代表 GFP 荧光的 FL1 (FITC) 在 x 轴中, 代表荧光的 FL3 (APC) 在 y 轴中, 分别应用 P2 和 P3 种群。 注意: 直方图叠加是一种很好的方法来说明不同 Aβ变种的细胞的荧光剖面之间的差异。</li>
</ol>4. 重组蛋白 Immunodetection
<ol><li>为了确定蛋白质的表达水平, 通过离心 4000 x g 为6分钟, 收获16小时诱导的酵母培养, 并将细胞颗粒贮存在-80 摄氏度。<ol>
<li>并用重悬在 PBS 中表达重组蛋白16小时的收集细胞。将每个 Aβ42-GFP 突变体的200µL 细胞悬浮物准备成590 20。</li>
	</ol>
</li>
	<li>总蛋白分数分析, 以 1.4万 x g 为20分钟, 用离心法收获100µL, 并用重悬在同一体积酵母裂解缓冲液中的细胞颗粒 (50 毫米三盐酸 pH 8.0, 1% 亚砜, 200 毫米氯化钠, 1 毫米 EDTA, 含10毫克/毫升 SB3-14 (马币istyl sulfobetaine) 补充1毫米 phenylmethylsulfonyl 氟 (PMSF))。<ol>
<li>在轻度搅拌的室温下, 将样品孵化20分钟。</li>
	</ol>
</li>
	<li>用布拉德福德测定法测定蛋白质的提取浓度。在15% 丙烯酰胺 SDS 页电泳凝胶上, 将每个样品的蛋白质提取物载入5µg, 并将其涂抹到聚偏聚氟 (PVDF) 膜上100伏60分钟。<ol>
<li>准备一个布拉德福德试剂与100毫克的考马斯灿烂的蓝色 G-250 溶解在50毫升95% 乙醇和添加100毫升 85% (w/v) 磷酸。然后, 当染料完全溶解, 稀释的混合物与 ddH2O 到1升和过滤它通过纤维素过滤纸刚刚使用。 注: 布拉德福德试剂应为浅褐色。</li>
		<li>制备标准的牛血清白蛋白 (BSA) 范围从 5-100 µg 的蛋白质在1000µL 的布拉德福德试剂。</li>
		<li>将 1-10 µL 蛋白提取物添加到布拉德福德试剂1毫升中, 在室温下孵化混合物5分钟。</li>
		<li>测量标准和蛋白质提取样品在 OD595的吸光度。</li>
		<li>对于分析, 用所得到的标准与所获得的吸光度值作一个图。蛋白质的µg。根据标准曲线, 确定原始样品的浓度, 从蛋白质的数量, 考虑到体积和稀释, 如果有的话。</li>
	</ol>
</li>
	<li>用1x 的三缓冲盐水 (tb), 0.1% 吐温 20 (TTBS) 冲洗膜, 并用 5% (w/v) 脱脂干牛奶在 1x TTBS 中阻断。<ol>
<li>准备1升 10x tb, 溶解24克的三基和88克氯化钠在900毫升的 H2Odd和调整 pH 值为7.6。增加 ddH2O 到最后容量 1 L。对于1x 解决方案, 混合1部分10x 库存与 9 ddH2O 的一部分。</li>
	</ol>
</li>
	<li>在室温下孵育1小时的膜, 其主要β淀粉样变性抗体6E10 稀释 1:1, 000 和 1 h 常温下与二级抗体山羊抗鼠 IgG-HRP 共轭稀释1:10,000。</li>
	<li>用1毫升的 Luminata 荧光试剂和密度分析的方法来发展膜, 如步骤5.2 所述。</li>
</ol>5. 数据分析
<ol><li>为了分析 FC 获得的数据, 创建一个表, 显示平均荧光强度和中值荧光及其相应的标准误差和/或 GFP 荧光和氧化应激水平的方差系数 (CV)。<ol>
<li>单击 "检查器" 选项卡和 "统计" 图标可自定义每个通道所需的统计数据。 注意: 在比较蛋白质变体时, 将荧光值数据转换为折叠背景或分辨率度量 (RD): <img alt="Equation 1" src="/files/ftp_upload/57470/57470eq1.jpg"> 在这个度量中, 平均样本是问题样本的均值荧光, 均值控制是作为控制的细胞的均值荧光, SD 是平均荧光的标准偏差。RD 因子是一个比多边基金会价值更准确的指数, 因为它不仅计算样本之间的差异, 而且也说明数据的传播。当比较来自不同实验的数据时, 这个计算是特别相关的。一旦 RDs 被计算出来, 使用统计测试是可取的, 以确认的意义, 观察差异的蛋白质变异。</li>
	</ol>
</li>
	<li>对于蛋白质 immunodetection, 用 ImageJ 软件量化了西方印迹的重组蛋白水平。<ol>
<li>在密度分析之前, 将所开发膜的原始原始图像转换为 JPEG 文件格式和灰度模式。</li>
		<li>将 "分析" 菜单的 "设置测量" 部分调整为灰色值。</li>
		<li>点击矩形工具从 ImageJ 和定义一个感兴趣的区域 (ROI) 与一致的大小为波段密度分析。在所创建的矩形框架内, 将薄膜图像上的每个波段居中, 并使用 Ctrl + M (测量命令) 逐个记录测量结果。</li>
		<li>测量每个波段相邻的本地背景, 并应用相同的 ROI 区域。测量后, 从每个波段减去相应的局部背景。</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>

广泛的疾病与错误折叠蛋白质的积累联系在一起6,7,8,33的细胞沉积。已作出许多努力, 以解开分子机制, 触发这些疾病的开始使用计算方法, 不考虑蛋白质浓度, 或在体外的方法, 其中蛋白质浓度在反应过程中保持恒定。然而, 在细胞内, 蛋白质在拥挤和非均匀的环境中不断地合成和降解。这解释了...

Proteostasis 是细胞适应和衰老过程的基本决定因素。在细胞中, 蛋白质的稳态是由复杂的蛋白质质量控制网络维持的, 目的是通过伴侣和/或他们的靶向蛋白质错误折叠, 以确保正确的复性蛋白构象1 ,2,3,4,5。大量的研究为人类疾病的发生和发展与 proteostasis 的失败之间的联系提供了支持, 导致蛋白质错误折叠和聚集。例如, 蛋白质矿床的存在被认为是许多神经退行性疾病的病理特征, 如阿尔茨海默氏症、帕金森氏病、亨廷顿疾病6、7、8、prionogenic 疾病, 非退行性 amyloidoses9。有人建议, 早期寡聚和 protofibrillar 聚集反应是细胞毒性的主要诱导, 与其他蛋白质在拥挤的细胞环境中建立异常的相互作用10。此外, 蛋白质包裹体 (PI) 可以在细胞间传播, 传播其毒性效应11,12。因此, 可以说, PI 的形成实际上可能构成一种解毒机制, 它将危险的聚集物种的存在限制在细胞中的特定位置, 在那里它们可以被加工或积累而不会产生重大的副作用。13,14。
标准的体外生化方法为不同物种的聚集反应及其性质15,16提供了重要的见解。然而, 这些化验所使用的条件明显不同于细胞内发生的情况, 因此, 质疑它们的生理相关性。由于细胞通路的显著保护, 如蛋白质质量控制, 自噬, 或调节细胞氧化还原状态17,18之间的真核生物19,20,21 ,22,23, 萌芽酵母酿酒酵母 (酵母) 已成为一个特权简单的细胞模型研究蛋白质聚集的分子决定因素及其相关的细胞毒性影响在生物相关的环境24,25,26。
蛋白质聚集倾向是在主序列中固有编码的特征。因此, 可以根据对多肽27中聚集促进区域的效力的鉴定和评价, 预测淀粉样结构的形成。然而, 尽管生物信息学算法成功地预测蛋白质序列的体外聚集特性, 但它们仍远未预测这些倾向如何转化为体内的细胞毒性影响。以系统的方式解决给定蛋白质的聚合状态与其相关的细胞损伤之间的联系的研究可能有助于规避这一计算限制。这个连接在本研究中被处理, 利用一大组变异的淀粉样β肽 Aβ42不同只在单一的残余, 但显示连续的范围的聚集倾向在体内28。特别是, 本文介绍了一种基于 FC 的方法, 用于识别酵母细胞中聚集易感蛋白引起的氧化损伤的构象物种。该方法提供了许多优点, 如简单性、高通量能力和精确的定量测量。这种方法使人们有可能确认 PI 对氧化应激起着保护作用。

<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

蛋白质错误折叠和聚集到淀粉样蛋白构象已经与一些神经退行性疾病的发病和进展有关。然而, 对于不溶性蛋白聚合体在体内如何发挥其毒性作用, 仍有很少的信息。简单的原核和真核模型有机体, 如细菌和酵母, 已大大有助于我们目前对细胞内淀粉样形成的机制, 聚集繁殖和毒性的理解。在本议定书中, 酵母的使用被描述为一个模型来解剖蛋白质团聚体的形成和它们对细胞氧化应激的影响之间的关系。该方法将 amyloidogenic 蛋白的胞内可溶性/聚集态检测与流式细胞术 (FC) 表达的细胞氧化损伤的量化相结合。这种方法简单、快速、定量。本研究通过将一大组淀粉样β肽变异体所引起的细胞氧化应激与它们各自的内在聚集倾向进行关联来说明该技术。

该协议描述如何使用 Aβ42肽的20变种的集合, 其中 Phe19 已经变异为所有自然 proteinogenic 氨基酸28。这些蛋白质的理论聚集倾向可以用两种不同的生物信息学算法 (AGGRESCAN 和探戈31,32) 来分析。在这两种情况下, 这种分析呈现出聚合倾向的渐进级化, 作为一般规则, 将最高值归结为疏水性残留物和最低的电荷和极性 (<...

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

蛋白质聚集对酵母细胞氧化应激的影响评价

蛋白质聚集诱发细胞氧化应激。本协议描述了一种通过流式细胞仪监测 amyloidogenic 蛋白的细胞内状态和与之相关的氧化应激的方法。该方法用于研究淀粉样β肽的可溶性和聚集易变性的行为。

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 次观看.  Universitat Autònoma de Barcelona. 蛋白质聚集诱发细胞氧化应激。本协议描述了一种通过流式细胞仪监测 amyloidogenic 蛋白的细胞内状态和与之相关的氧化应激的方法。该方法用于研究淀粉样β肽的可溶性和聚集易变性的行为。

视频: 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.

用氢-氘交换质谱法定义 Hsp33's 氧化还原调节陪护活动和 Hsp33 映射构象变化

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

科研

生物化学

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.

用蛋白毒性应激器治疗大 肠杆菌 后蛋白质聚合物的提取和可视化

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.

微阵列分析FOR酿酒酵母</em

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

生物学

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.

生长实验，以评估在酵母中的多聚谷氨酰胺毒性

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.

在活细胞中蛋白质聚集的4D成像

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.

耦合检测监控蛋白复性<em&gt;酿酒酵母（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.

隔离增效变种的Hsp104利用酵母Proteinopathy模型

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).

蛋白质降解的放线菌酮大通分析<em&gt;酿酒酵母</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.

方法研究线虫线虫中固有的蛋白质聚集与年龄的变化

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 ...

蛋白质聚集对酵母细胞氧化应激的影响评价

摘要

探索更多视频

此视频中的章节

用氢-氘交换质谱法定义 Hsp33's 氧化还原调节陪护活动和 Hsp33 映射构象变化

用蛋白毒性应激器治疗大肠杆菌后蛋白质聚合物的提取和可视化

微阵列分析FOR酿酒酵母

生长实验，以评估在酵母中的多聚谷氨酰胺毒性

在活细胞中蛋白质聚集的4D成像

耦合检测监控蛋白复性

隔离增效变种的Hsp104利用酵母Proteinopathy模型

蛋白质降解的放线菌酮大通分析

方法研究线虫线虫中固有的蛋白质聚集与年龄的变化

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

蛋白质聚集对酵母细胞氧化应激的影响评价

摘要

探索更多视频

此视频中的章节

用氢-氘交换质谱法定义 Hsp33's 氧化还原调节陪护活动和 Hsp33 映射构象变化

用蛋白毒性应激器治疗大 肠杆菌 后蛋白质聚合物的提取和可视化

微阵列分析FOR酿酒酵母

生长实验，以评估在酵母中的多聚谷氨酰胺毒性

在活细胞中蛋白质聚集的4D成像

耦合检测监控蛋白复性

隔离增效变种的Hsp104利用酵母Proteinopathy模型

蛋白质降解的放线菌酮大通分析

方法研究线虫线虫中固有的蛋白质聚集与年龄的变化

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

用蛋白毒性应激器治疗大肠杆菌后蛋白质聚合物的提取和可视化