Name: measuring mrna levels over time during the yeast s. cerevisiae hypoxic response
Uploaded: 2017-08-10T15:00:00.000+00:00
Duration: 9 min 45 s
Description: Watch this Scientific Journal Video about Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response at JoVE.com

我们感谢刘易斯-杰瑞·斯格勒研究所的综合基因组测序核心设施在普林斯顿大学为技术咨询和 RNA 图书馆的准备和测序。这项工作得到了罗恩大学和 NIH 研究院 R15GM113187 对 M.J.H. 的资助。

1. 诱导缺氧
<ol><li>前一天或更早的缺氧时间课程: 准备孵化器, 细胞过滤系统, 真空, 气罐, 烧瓶, 塞子, 玻璃管, 和油管, 如在材料表。</li>
	<li>将 N 个2容器、孵化器、真空和过滤系统放在接近的位置, 以便能够快速处理电池。</li>
	<li>通过将玻璃瓶和灭菌中的成分混合, 制备无菌液体 YPD 培养基 (1% 酵母提取物, 2% 蛋白胨, 2% 葡萄糖)。</li>
	<li>规划孵化器的烧瓶布局。 注: 从 N2罐, 第一个烧瓶将是一个水陷阱, 第二个烧瓶将是最后的时间点, 第三个烧瓶将是第二的时间点等, 直到最后一个烧瓶是最后的水陷阱。图 1显示了烧瓶之间的顺序和连接。</li>
	<li>在时间的前一天, 接种一个酵母菌落到5毫升液体 YPD 在一个无菌试管内的文化。具体地说, 用无菌涂抹棒从盘子里拿出一个完整的菌落。把棍子放入液体 YPD, 摇动棍子直到大部分的细胞悬浮。</li>
	<li>旋转管在30° c 过夜 (〜16小时)。 注:16 小时后, 野生细胞将达到饱和 (〜 2 x 108细胞/毫升), 由一个非常多云的文化表示。其他菌株可能需要更长的时间达到饱和, 并应通过测量细胞浓度的分光光度计, 如步骤1.9.4 所示。</li>
	<li>在时间路线的天, 在 16 h 以后孵育, 稀释饱和的文化1:50 通过使用5毫升吸管安置4毫升隔夜文化入196毫升液体 YPD 在无菌500毫升烧瓶之内。在30° c 的4小时在 200 rpm 的震动下成长。 注意: 4 小时后, 野生的区域性将达到 mid-log 1-2 x 107单元/mL 的浓度。</li>
	<li>在4小时孵化, 标签的烧瓶 (缺氧和水陷阱) 和50毫升收集管。如果以上步骤1.7 中的孵化器不用于低氧时间课程, 则打开其他孵化器并设置为30° c。</li>
	<li>
就在细胞缺氧之前:
	<ol>
<li>添加〜50毫升水到两个无菌250毫升烧瓶, 将作为水的陷阱。</li>
		<li>填充带有液氮的冰桶的1/3 , 并淹没聚苯乙烯泡沫机架以容纳50毫升离心管。</li>
		<li>设置用于收集单元格的筛选系统。使用无菌镊子, 在过滤系统的底部单元上添加无菌滤片, 小心只触及过滤盘的边缘。将过滤器顶部的单位放到过滤器底部, 并与系统提供的夹具一起安全。确保底部和顶部的单位是对齐, 以便有一个紧密的密封和没有泄漏。</li>
		<li>用分光光度计测量细胞浓度。稀释细胞, 使它们可以在分光光度计的线性范围内进行测量--OD600介于 0.2-0.6 之间, 这取决于光谱仪。 注: 一个 OD600单位是〜 3 x 107细胞/毫升, 根据细胞形态学和分光光度计。所需浓度为 ~ 1-2 x 107单元/mL, 对应于 ~ 0.33-0.66 的 OD600 。</li>
		<li>
快速获取时间0样本。
		<ol>
<li>通过真空管和1000毫升的烧瓶陷阱将过滤系统连接到一个强 (约10毫巴) 真空。打开真空。将养殖 (通常为20毫升) 倒入顶部, 等待液体通过过滤器 (〜十年代, 取决于真空强度)。</li>
			<li>小心地用干净的镊子将滤片取出, 放入50毫升离心管。立即将离心管放入液体氮气的机架中。重要的是, 在插入过滤器之前不要 pre-chill 管, 因为管子会爆炸。</li>
			<li>三十年代 > 之后, 将管子放入一个-80 ° c 的冰箱中, 以备以后的 RNA 提取。每次过滤后, 清洗并重新组装过滤系统。冲洗系统, 通过拉水通过十年代没有一个过滤器光盘。最后, 用纸巾擦干系统。</li>
		</ol>
</li>
		<li>将 4 h 培养液稀释为不同的时间点, 使每个烧瓶达到 mid-log 浓度 (〜 1-2 x 107细胞/毫升) 在指定的时间点缺氧。 注: 表1显示了用于野生类型 S288C HAP1+单倍体菌株的稀释。建议对这些缺氧培养条件下的每株菌株进行测试, 并相应调整稀释。</li>
		<li>一旦细胞和培养基被添加到烧瓶中, 用装有两个玻璃管的塞子取代覆盖烧瓶开口的铝箔。</li>
		<li>将烧瓶放在孵化器中, 并将其放置在先前确定的布局中。</li>
		<li>安全地连接油管, 如图 1所示。</li>
		<li>检查所有的塞子都被紧紧地推入烧瓶开口。</li>
	</ol>
</li>
	<li>0时, 打开调节阀。然后将流量计设置为3升/分。 注: 气泡将在两个水瓶中观察到, 表明适当的气体流动。如果不是这样的话, 检查所有的塞子都是紧密的, 油管是正确的连接。</li>
	<li>关闭孵化器和设置震动速度〜 200 rpm。启动计时器。</li>
	<li>在每个时间点之前, 按照上面的步骤1.9.3 设置过滤系统。</li>
	<li>
在每个时间点 (例如, 5 分钟, 10 min,等) 中, 有两个人快速处理这些单元格, 如下所示:
	<ol>
<li>第一人: 从持有人身上取出适当的烧瓶, 取出塞子 (附玻璃管)。 注意: 这不会将 N2的流分解为任何剩余的区域性烧瓶, 但会暂时中断流向最后一个水阱的流。</li>
		<li>第二人称: 吸管1毫升的文化, 并免除试管。重新连接现在位于生产线末端的养殖烧瓶中的油管, 将其与最后一个水阱 (一个管和一个塞子将在过程中删除)。然后, 测量试管中的细胞浓度, 如上面的步骤1.9.4 所述。</li>
		<li>第一人称: 将养殖的其余部分倒入真空过滤系统, 然后按照上述步骤1.9.5 进行过滤和冻结。</li>
	</ol>
</li>
	<li>完成所有时间点后, 关闭 N2气体。首先关闭稳压器, 等待压力释放, 然后关闭流量计。最后, 拆卸系统, 用清水清洗所有材料, 然后70% 乙醇。</li>
</ol>2. RNA 提取
<ol><li>为 RNA 列纯化准备 RLT 缓冲区, 如材料表中所述。</li>
	<li>通过将 dnasei 库存解决方案的10µL 添加到每个示例的70µL 缓冲区 RDD, 准备一个 dnasei 的工作解决方案 (请参见材料表)。</li>
	<li>从-80 ° c 的冰箱中取出含有过滤器和电池的50毫升管子, 并在冰上放上解冻 (约15分钟)。用冰上的管子执行以下步骤。</li>
	<li>标签2毫升螺丝帽管, 并把它们放在冰, 一个管为每个样品。加入〜0.6 毫升酸洗珠每管, 使用1.5 毫升离心管舀和测量的珠子。</li>
	<li>在50毫升的管子上加入0.6 毫升的冷 RLT 缓冲器。</li>
	<li>吸管向上和向下移除过滤器中的单元格并将其挂起到解决方案中。避免让过滤器留在解决方案中, 因为过滤器会吸收解决方案。通过使用吸管尖端将过滤器挤压到管壁上, 将所有吸收到过滤器中的溶液移除。</li>
	<li>将所有的液体从50毫升的管子转移到含有珠子的螺钉盖管。</li>
	<li>将螺钉盖管放入一个珠磨均质机中, 并运行一分钟。 立即把管子放在冰上三分钟。再次, 将管放入均质机, 并运行一分钟。</li>
	<li>从均质机上取出管子, 在冰上放置5分钟。珠子会沉淀到管子的底部。</li>
	<li>在室温下执行其余步骤。</li>
	<li>与吸管, 转移只有裂解 (〜350µL), 避免珠子, 一个新的1.5 毫升离心管。</li>
	<li>离心为2分钟的最大速度, 然后转移上清到一个新的1.5 毫升离心管。</li>
	<li>添加1量的70% 乙醇 (由200证明分子生物学级乙醇)。混合移。</li>
	<li>将溶液和任何沉淀转移到已放置在2毫升收集管内的 RNA 柱上。</li>
	<li>离心机为十五年代在≥12,000 x g并且摒弃流动通过 (液体在管子)。</li>
	<li>向列中添加350µL 的缓冲区 RW1。离心机十五年代在≥12,000 x g 和放弃流动通过。</li>
	<li>添加80µL dnasei I 孵化混合到柱状膜 (不得到两侧的管), 并允许坐15分钟。</li>
	<li>向列中添加350µL 的缓冲区 RW1。离心十五年代在≥12,000 x g , 并丢弃流通过。</li>
	<li>添加500µL 的缓冲 RPE 到该列。离心十五年代在≥12,000 x g并丢弃流。</li>
	<li>添加500µL 的缓冲 RPE 到该列。离心为2分钟, 在≥12,000 x g。</li>
	<li>小心地删除的列和放置到一个新的2毫升收集管。离心的速度为1分钟 (完全干燥的膜)。</li>
	<li>丢弃收集管, 并将该列放入1.5 毫升离心管中。在柱膜上加入30µL 的无核糖核酸水。</li>
	<li>洗在≥12,000 x g的 microcentrifuging 中, 从该列中提取 RNA 1 分钟。当把柱子装入离心时, 要确保收集管的盖子朝向离心机旋转的方向, 以防止盖子折断。</li>
	<li>在柱状膜上加入另30µL 的无核糖核酸水, 同时保持柱在同一离心管中。</li>
	<li>离心为1分钟, 在≥12,000 x g, 使最终洗卷为60µL。</li>
	<li>在-80 ° c 的冷冻库中储存每1.5 毫升含有60µL 的 RNA 的管子。</li>
</ol>3. 测定 RNA 浓度和质量
<ol><li>测量 rna 和 dna 在每个 rna 样品中的浓度, 使用 (a) 荧光, (b) dna 和 rna 特异荧光染料和 (c) 化验管, 如在材料表中所列。按照荧光和染料的指示进行操作。</li>
	<li>另外, 用紫外分光光度计测量核酸浓度 260 nm。 注: A260读数为 1.0, 相当于 ~ 40 µg/毫升单 RNA。</li>
	<li>通过在商业核酸分析仪上运行 rna 来测试 rna 质量 (参见材料表) 或标准甲醛/琼脂糖凝胶26。</li>
</ol>4. RNA-seq 分析
<ol><li>从总 rna 的股票, 构成了21µL 100 ng/µL RNA 在核糖核酸自由水。使用1µL 这21µL 测试 RNA 浓度如上所述。将剩余的20µL (2 µg) 总 RNA 提交到外部测序中心, 用于 mRNA 富集, 特定于链路的库准备 (八或更多的条形码用于复用) 和排序 (请参见材料表)。或者, 在本地执行 mRNA 浓缩和库准备, 然后提交库进行排序。</li>
	<li>池八或更多的多路复用样本和序列在一个通道的下一代排序器。</li>
	<li>下载包含所有序列读取和相应索引读取的 FASTQ 文件。另外, 下载包含多重条码的文本文件。 注意: 索引读取可能存在于单独的 FASTQ 文件中。将所有这些文件放在一个目录中。</li>
	<li>将 shell 脚本放在这里, "fastq_pipeline", 在同一目录中。根据实验和计算机目录编辑此脚本。 注意: 此脚本包含解释步骤的大量注释。简而言之, 脚本质量修剪读取, 将读取映射到基因组, 并生成一个制表符分隔的文件, 其中包含每个样本的每个基因的读取次数。</li>
	<li>在发布27之前, 将 FASTQ 文件和原始读取计数数据存入 NCBI 的基因表达式综合中。按照 "向 GEO 提交高通量序列数据" 的说明: https://www.ncbi.nlm.nih.gov/geo/info/seq.html。</li>
	<li>将读取计数数据导入 r 统计环境, 并使用此处提供的 r 脚本进行统计分析, "time_course_script。R "。根据实验和计算机目录编辑此脚本。 注意: 此脚本包含解释步骤的大量注释。简而言之, 该脚本导入读取数据, 规范化读取, 识别在时间过程中显著变化的基因, 执行 PCA 分析, 并对选定基因的表达进行图表。</li>
</ol>

<ol>
	<li>Semenza, G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oxygen+sensing,+homeostasis,+and+disease.">Oxygen sensing, homeostasis, and disease.</a> New Eng. J Med. 365 (6), 537-547 (2011).</li><li>Butler, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hypoxia+and+gene+expression+in+eukaryotic+microbes.">Hypoxia and gene expression in eukaryotic microbes.</a> Annu. Rev. Micro. 67, 291-312 (2013).</li><li>Ratcliffe, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oxygen+sensing+and+hypoxia+signalling+pathways+in+animals:+the+implications+of+physiology+for+cancer.">Oxygen sensing and hypoxia signalling pathways in animals: the implications of physiology for cancer.</a> J. Physiol. 591 (Pt 8), 2027-2042 (2013).</li><li>Rosenfeld, E., Beauvoit, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+the+non-respiratory+pathways+in+the+utilization+of+molecular+oxygen+bySaccharomyces+cerevisiae.">Role of the non-respiratory pathways in the utilization of molecular oxygen bySaccharomyces cerevisiae.</a> Yeast. 20 (13), 1115-1144 (2003).</li><li>Ter Linde, J. J., 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=Genome-wide+transcriptional+analysis+of+aerobic+and+anaerobic+chemostat+cultures+of+Saccharomyces+cerevisiae.">Genome-wide transcriptional analysis of aerobic and anaerobic chemostat cultures of Saccharomyces cerevisiae.</a> J. Bacteriol. 181 (24), 7409-7413 (1999).</li><li>Ter Linde, J. J., Steensma, H. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+microarray-assisted+screen+for+potential+Hap1+and+Rox1+target+genes+in+Saccharomyces+cerevisiae.">A microarray-assisted screen for potential Hap1 and Rox1 target genes in Saccharomyces cerevisiae.</a> Yeast. 19 (10), 825-840 (2002).</li><li>Kwast, K. 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=Genomic+analyses+of+anaerobically+induced+genes+in+Saccharomyces+cerevisiae:+functional+roles+of+Rox1+and+other+factors+in+mediating+the+anoxic+response.">Genomic analyses of anaerobically induced genes in Saccharomyces cerevisiae: functional roles of Rox1 and other factors in mediating the anoxic response.</a> J. Bacteriol. 184 (1), 250-265 (2002).</li><li>Becerra, M., 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=The+yeast+transcriptome+in+aerobic+and+hypoxic+conditions:+effects+of+hap1,+rox1,+rox3+and+srb10+deletions.">The yeast transcriptome in aerobic and hypoxic conditions: effects of hap1, rox1, rox3 and srb10 deletions.</a> Mol. Microbiol. 43 (3), 545-555 (2002).</li><li>Lai, L. -. C., Kosorukoff, A. L., Burke, P. V., Kwast, K. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamical+remodeling+of+the+transcriptome+during+short-term+anaerobiosis+in+Saccharomyces+cerevisiae:+differential+response+and+role+of+Msn2+and/or+Msn4+and+other+factors+in+galactose+and+glucose+media.">Dynamical remodeling of the transcriptome during short-term anaerobiosis in Saccharomyces cerevisiae: differential response and role of Msn2 and/or Msn4 and other factors in galactose and glucose media.</a> Mol. Cell. Biol. 25 (10), 4075-4091 (2005).</li><li>Lai, L. C., Kosorukoff, A. L., Burke, P. V., Kwast, K. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic-State-Dependent+Remodeling+of+the+Transcriptome+in+Response+to+Anoxia+and+Subsequent+Reoxygenation+in+Saccharomyces+cerevisiae.">Metabolic-State-Dependent Remodeling of the Transcriptome in Response to Anoxia and Subsequent Reoxygenation in Saccharomyces cerevisiae.</a> Euk. Cell. 5 (9), 1468-1489 (2006).</li><li>Hickman, M. J., Winston, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heme+levels+switch+the+function+of+Hap1+of+Saccharomyces+cerevisiae+between+transcriptional+activator+and+transcriptional+repressor.">Heme levels switch the function of Hap1 of Saccharomyces cerevisiae between transcriptional activator and transcriptional repressor.</a> Mol. Cell. Biol. 27 (21), 7414-7424 (2007).</li><li>Hickman, M. J., Spatt, D., Winston, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Hog1+mitogen-activated+protein+kinase+mediates+a+hypoxic+response+in+Saccharomyces+cerevisiae.">The Hog1 mitogen-activated protein kinase mediates a hypoxic response in Saccharomyces cerevisiae.</a> Genetics. 188 (2), 325-338 (2011).</li><li>Bendjilali, N., 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=Time-Course+Analysis+of+Gene+Expression+During+the+Saccharomyces+cerevisiae+Hypoxic+Response.">Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response.</a> G3. 7 (1), 221-231 (2017).</li><li>Chellappa, R., 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=The+membrane+proteins,+Spt23p+and+Mga2p,+play+distinct+roles+in+the+activation+of+Saccharomyces+cerevisiae+OLE1+gene+expression.+Fatty+acid-mediated+regulation+of+Mga2p+activity+is+independent+of+its+proteolytic+processing+into+a+soluble+transcription+activator.">The membrane proteins, Spt23p and Mga2p, play distinct roles in the activation of Saccharomyces cerevisiae OLE1 gene expression. Fatty acid-mediated regulation of Mga2p activity is independent of its proteolytic processing into a soluble transcription activator.</a> J. Biol. Chem. 276 (47), 43548-43556 (2001).</li><li>Abramova, N. 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=Regulatory+mechanisms+controlling+expression+of+the+DAN/TIR+mannoprotein+genes+during+anaerobic+remodeling+of+the+cell+wall+in+Saccharomyces+cerevisiae.">Regulatory mechanisms controlling expression of the DAN/TIR mannoprotein genes during anaerobic remodeling of the cell wall in Saccharomyces cerevisiae.</a> Genetics. 157 (3), 1169-1177 (2001).</li><li>Hughes, A. L., Todd, B. L., Espenshade, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SREBP+Pathway+Responds+to+Sterols+and+Functions+as+an+Oxygen+Sensor+in+Fission+Yeast.">SREBP Pathway Responds to Sterols and Functions as an Oxygen Sensor in Fission Yeast.</a> Cell. 120 (6), 831-842 (2005).</li><li>Gaisne, M., B&#233;cam, A. M., Verdi&#232;re, J., Herbert, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+&amp;#34;natural&amp;#34;+mutation+in+Saccharomyces+cerevisiae+strains+derived+from+S288c+affects+the+complex+regulatory+gene+HAP1+(CYP1).">A &amp;#34;natural&amp;#34; mutation in Saccharomyces cerevisiae strains derived from S288c affects the complex regulatory gene HAP1 (CYP1).</a> Curr. Gen. 36 (4), 195-200 (1999).</li><li>Wang, Z., Gerstein, M., Snyder, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-Seq:+a+revolutionary+tool+for+transcriptomics.">RNA-Seq: a revolutionary tool for transcriptomics.</a> Nat. Rev. Gen. 10 (1), 57-63 (2009).</li><li>Anders, S., Huber, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+expression+analysis+for+sequence+count+data.">Differential expression analysis for sequence count data.</a> Genome Biol. 11 (10), R106 (2010).</li><li>Conesa, 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=A+survey+of+best+practices+for+RNA-seq+data+analysis.">A survey of best practices for RNA-seq data analysis.</a> Genome Biol. 17 (1), 13 (2016).</li><li>Bolger, A. M., Lohse, M., Usadel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trimmomatic:+a+flexible+trimmer+for+Illumina+sequence+data.">Trimmomatic: a flexible trimmer for Illumina sequence data.</a> Bioinf. 30 (15), 2114-2120 (2014).</li><li>Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TopHat2:+accurate+alignment+of+transcriptomes+in+the+presence+of+insertions,+deletions+and+gene+fusions.">TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions.</a> Genome Biol. 14 (4), R36 (2013).</li><li>Anders, S., Pyl, P. T., Huber, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HTSeq--A+Python+framework+to+work+with+high-throughput+sequencing+data.">HTSeq--A Python framework to work with high-throughput sequencing data.</a> Bioinf. 31 (2), 166-169 (2015).</li><li>. R: A Language and Environment for Statistical Computing Available from: <a target="_blank" href="https://www.R-project.org">https://www.R-project.org</a> (2015)</li><li>Love, M. I., Huber, W., Anders, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Moderated+estimation+of+fold+change+and+dispersion+for+RNA-seq+data+with+DESeq2.">Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.</a> Genome Biol. 15 (12), 550 (2014).</li><li>Brown, T., Mackey, K., Du, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+RNA+by+Northern+and+Slot+Blot+Hybridization.">Analysis of RNA by Northern and Slot Blot Hybridization.</a> Curr. Prot. Mol. Biol. 74, 4.9.1-4.9.19 (2004).</li><li>Edgar, R., Domrachev, M., Lash, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+Expression+Omnibus:+NCBI+gene+expression+and+hybridization+array+data+repository.">Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.</a> Nuc. Acids Res. 30 (1), 207-210 (2002).</li><li>Cherry, J. M., 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=Saccharomyces+Genome+Database:+the+genomics+resource+of+budding+yeast.">Saccharomyces Genome Database: the genomics resource of budding yeast.</a> Nuc. Acids Res. 40, D700-D705 (2012).</li><li>Hothorn, T., Everitt, B. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> A Handbook of Statistical Analyses using R. , (2014).</li><li>Saldanha, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Java+Treeview--extensible+visualization+of+microarray+data.">Java Treeview--extensible visualization of microarray data.</a> Bioinformatics. 20 (17), 3246-3248 (2004).</li><li>Eisen, M. B., Spellman, P. T., Brown, P. O., Botstein, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cluster+analysis+and+display+of+genome-wide+expression+patterns.">Cluster analysis and display of genome-wide expression patterns.</a> Proc. Nat. Acad. Sci. 95 (25), 14863-14868 (1998).</li><li>Davies, B. S. J., Rine, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Role+for+Sterol+Levels+in+Oxygen+Sensing+in+Saccharomyces+cerevisiae.">A Role for Sterol Levels in Oxygen Sensing in Saccharomyces cerevisiae.</a> Genetics. 174 (1), 191-201 (2006).</li><li>Meena, R. C., Kumar, N., Nath, S., Chakrabarti, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Homologous+Recombination+is+Activated+at+Early+Time+Points+Following+Exposure+to+Cobalt+Chloride+Induced+Hypoxic+Conditions+in+Saccharomyces+cerevisiae.">Homologous Recombination is Activated at Early Time Points Following Exposure to Cobalt Chloride Induced Hypoxic Conditions in Saccharomyces cerevisiae.</a> Ind. J. Microb. 52 (2), 209-214 (2012).</li><li>Snoek, I. S. I., Tai, S. L., Pronk, J. T., Yde Steensma, H., Daran, J. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Involvement+of+Snf7p+and+Rim101p+in+the+transcriptional+regulation+of+TIR1+and+other+anaerobically+upregulated+genes+in+Saccharomyces+cerevisiae.">Involvement of Snf7p and Rim101p in the transcriptional regulation of TIR1 and other anaerobically upregulated genes in Saccharomyces cerevisiae.</a> FEMS Yeast Res. 10 (4), 367-384 (2010).</li><li>Ellahi, A., Thurtle, D. M., Rine, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Chromatin+and+Transcriptional+Landscape+of+Native+Saccharomyces+cerevisiae+Telomeres+and+Subtelomeric+Domains.">The Chromatin and Transcriptional Landscape of Native Saccharomyces cerevisiae Telomeres and Subtelomeric Domains.</a> Genetics. 200 (2), 505-521 (2015).</li><li>Collart, M. A., Oliviero, S., 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=Preparation+of+yeast+RNA.">Preparation of yeast RNA.</a> Curr. Prot. Mol. Biol. , (2001).</li><li>Blankenberg, D., 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=Manipulation+of+FASTQ+data+with+Galaxy.">Manipulation of FASTQ data with Galaxy.</a> Bioinf. 24 (14), 1783-1785 (2010).</li><li>Martini, P., 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=timeClip:+pathway+analysis+for+time+course+data+without+replicates.">timeClip: pathway analysis for time course data without replicates.</a> BMC Bioinf. 15, (2014).</li><li>Oh, S., Song, S., Grabowski, G., Zhao, H., Noonan, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time+series+expression+analyses+using+RNA-seq:+a+statistical+approach.">Time series expression analyses using RNA-seq: a statistical approach.</a> BioMed Res. Int. 2013, 1-16 (2013).</li></ol>

作者没有什么可透露的。

在本研究中, 对所有基因的 mRNA 水平进行了测试, 在低氧的酵母S酵母。目的是分析全球基因表达在受控近缺氧环境中的生长变化。采取了若干步骤, 以确保此处所述的方法是经过严格控制和重现的。首先, 细胞暴露在一个精确定义的缺氧环境中: 富媒体 (YPD) 中的 99.999% N2 。其他缺氧的研究已经关闭了烧瓶或管空气32, 使用缺氧模拟氯化钴33, 或雇用缺...

许多生物体反应缺氧, 或低 O2, 通过改变基因表达式1,2,3。这种反应可以帮助细胞应对缺乏对有氧呼吸和一些生物合成反应至关重要的基质, 而且还能改变氧化还原状态4。在S. 酿酒酵母中进行的几个微阵列研究表明, 数百个基因的 mRNA 水平因缺氧而发生变化5、6、7、8、9,10,11,12. 最近, RNA seq 被用来表征在缺氧时的基因表达变化13。在此, 对实验细节进行了介绍和讨论。
缺氧可以以各种方式实现, 每种方法都产生不同级别的 O2。在这里, 缺氧是建立在连续流动超高纯度 N2成烧瓶, 这降低 [O2] 立即溶解与可再生动力学10。这是可能的, 有一些 O2分子存在, 有助于新陈代谢和基因表达, 但这种环境被认为非常接近厌氧。在没有 O2的情况下, 酵母细胞不能合成血红素、麦角甾醇和不饱和脂肪酸4、12、14。因此, 以往的研究包括这些代谢物时, 生长酵母没有氧气5,10,15。然而, 许多缺氧反应是介导的这些代谢物的损耗, 从而补充他们逆转缺氧基因表达反应12,16。为了模拟自然缺氧, 这些代谢物没有添加到媒体。在短时间内, 细胞暴露在缺氧状态, 没有这些必需的代谢物, 没有明显增加细胞死亡 (数据没有显示), 也没有长期的压力响应13。
反应也取决于菌株及其基因型。特别重要的是已知的低氧反应调节器的等位基因2。S288C 应变背景是高度理想的, 以便结果可以与其他基因组研究与此菌株进行比较。然而, S288C 包含了一个部分功能等位基因的HAP1吉恩17, 转录调节器对缺氧反应至关重要。此等位基因在 S288C 中修复, 使用Σ1278b 应变背景下的野生拷贝11。
基因表达高度依赖于细胞环境。因此, 在进行全基因组的 mRNA 分析时, 保持一个恒定的环境是很重要的, 同时改变另一个参数, 例如时间、刺激或基因型。为了获得高度重现性的结果, 请考虑这三项研究的实践及其所有的生物或技术复制。首先, 同样的实验者应该进行这项研究, 因为技术实践可能在实验者中有所不同。第二, 在培养基中应使用相同批次的配料, 因为每个批次都有一个稍有不同的成分, 可以影响基因表达。第三, 为了最小化细胞周期效应, 每个时间点应该由生长 mid-log 阶段的异步细胞组成 (1-2 x 107细胞/mL)。
当表征一个复杂的反应, 如基因表达反应的缺氧, 一个时间的过程是有利的, 以确定动力学的各种事件。应选择特定的时间点来捕获响应的主要变化。在这项研究中, 观察到0和 4 h 之间的时间点, 因为过去的实验揭示了在这一期间的基因表达的广泛变化13。
为了测量全球基因表达, RNA seq 使用了18,19。这个方法使用下一代测序来确定每个基因转录的相对丰度。与 DNA 微阵列分析相比, RNA 序列表现出更高的灵敏度 (以检测更少的抄本), 更大的动态范围 (测量更大的褶皱变化) 和优异的重现性 (准确地跟随基因表达随着时间的推移)。通常, 大多数细胞 rna 是核糖体 rna, 因此许多方法已经开发, 以丰富的特定 RNA 种类20。在这里, 聚 T 珠被用来纯化多含 A 的 mrna 转录, 虽然各种商业可用的 rRNA 耗竭套件也可以有效的 mrna 丰富。
在这里, 对缺氧的S 酿酒酵母基因表达反应进行了表征。细胞暴露在缺氧, 然后取样在八时间点 (0, 5, 10, 30, 60, 120, 180 和240分钟)。为了确认重复性和识别统计变化的成绩单, 三进行了生物复制。rna 是由机械破坏和柱纯化提取, 然后处理 rna 序列分析。描述了 post-sequencing 管道, 并提供了允许精确复制所执行的分析的编程脚本。具体来说, Trimmomatic 21、TopHat2 22、HTseq 23、R 统计环境24和 DESeq2 包25用于处理 RNA 序列数据, 并识别607基因在缺氧.主成分分析 (PCA) 和基因表达的复制表明该技术的重现性。聚类和 heatmaps 揭示了 wide-ranging 表达动力学, 而基因本体 (GO) 分析表明, 许多细胞过程, 如有氧呼吸, 是丰富的一套氧调节基因。

<table><tbody><tr><td>Enclosed dry incubator</td><td>Thermo Scientific</td><td>MaxQ 4000</td><td>Set at 30 &amp;deg;C. Modify the door to allow entry of one Tygon tube. Alternatively, use the New Brunswick G25 incubator, which contains a tube port. Do not use an open-air water shaker, as condensation will collect in the tubes between flasks, possibly cross-contaminating cultures.</td></tr><tr><td>Micro-analysis Filter Holder</td><td>Millipore</td><td>XX1002530</td><td>25mm diameter, stainless steel support, no. 5 perforated silicone stopper mounts in standard 125 mL filtering flask</td></tr><tr><td>Strong vacuum</td><td>Edwards</td><td>E-LAB 2</td><td>The &amp;ldquo;house&amp;rdquo; vacuum may be too weak. Alternatively, use an electric-power portable vacuum pump like the one listed here.</td></tr><tr><td>1,000 mL flask</td><td></td><td></td><td>To act as vacuum trap.</td></tr><tr><td>~2 foot lengths of Heavy Wall Vacuum Tubing, inner diameter 3/8 in, outer diameter 7/8 in</td><td>Tygon</td><td>38TT</td><td>Two pieces: the first connects vacuum to trap, and the second connects trap to filter system.</td></tr><tr><td>High-pressure N&lt;sub&gt;2&lt;/sub&gt; gas tank</td><td></td><td></td><td>99.999% purity, &gt;1,000 psi, with a regulator and gas flow controller</td></tr><tr><td>Autoclaved 500 mL flask</td><td></td><td></td><td>Opening covered with aluminum foil. One for each yeast strain.</td></tr><tr><td>Autoclaved 250 mL flasks</td><td></td><td></td><td>Openings covered with aluminum foil. One for each time point plus two for water traps.</td></tr><tr><td>Flask stoppers (size 6, two holes with 5 mm diameter)</td><td></td><td></td><td>Sterilized with 70% ethanol. One for each flask.</td></tr><tr><td>Glass tubing, length 9 cm or 17 cm, inner diameter 2 mm, outer diameter 5 mm</td><td></td><td></td><td>Sterilized with 70% ethanol. Two tubes for each flask. Place into the holes of each stopper. See Figure 1 for placement of 9- vs 17- cm tubes.</td></tr><tr><td>~25 cm lengths of plastic tubing, inner diameter 5 mm</td><td>Tygon</td><td>E-3603</td><td>One piece for each flask. Sterilized with 70% ethanol.</td></tr><tr><td>Sterile filter discs</td><td>Millipore</td><td>HAWP02500</td><td>25 mm diameter, 0.45 &amp;micro;m pore size, one for each time point</td></tr><tr><td>Sterile dH&lt;sub&gt;2&lt;/sub&gt;O (~100 mL)</td><td></td><td></td><td></td></tr><tr><td>1 mL cuvettes</td><td></td><td></td><td>For measuring OD600 (i.e., cell concentration)</td></tr><tr><td>50 mL sterile centrifuge tubes</td><td></td><td></td><td>One for each time point</td></tr><tr><td>Clean and sterile tweezers</td><td></td><td></td><td></td></tr><tr><td>liquid nitrogen</td><td></td><td></td><td>For freezing cells</td></tr><tr><td>acid-washed beads</td><td>Sigma</td><td>G8772</td><td>Keep at 4 &amp;deg;C for lysing cells</td></tr><tr><td>Qiagen RNeasy Mini Kit</td><td>Qiagen</td><td>74104</td><td>For RNA column purification</td></tr><tr><td>Qiagen RLT buffer</td><td></td><td></td><td>Prepare by adding 10 &amp;micro;L of &amp;beta;-Mercaptoethanol per 1 mL of RLT buffer, keep at 4 &amp;deg;C.</td></tr><tr><td>2 mL collection tubes</td><td>Qiagen</td><td></td><td>included in the Qiagen Rneasy Mini Kit</td></tr><tr><td>Buffer RPE</td><td>Qiagen</td><td></td><td>included in the Qiagen Rneasy Mini Kit</td></tr><tr><td>Buffer RW1</td><td>Qiagen</td><td></td><td>included in the Qiagen Rneasy Mini Kit</td></tr><tr><td>DNase I stock and working solutions</td><td>Qiagen</td><td>79254</td><td>The DNase I enzyme comes as lyophilized powder in a glass vial. Using a sterile needle and syringe, inject 550 &amp;micro;L of RNase-free water (provided in Qiagen kit) into the vial. Mix by gently inverting the bottle. To avoid denaturing the enzyme, do not vortex. Using a pipet, remove this stock solution from the vial and store in freezer (-20 &amp;deg;C) in single-use aliquots (80 &amp;micro;L each). The stock solution should not be thawed and refrozen.</td></tr><tr><td>Buffer RDD</td><td>Qiagen</td><td></td><td>included in the Qiagen DNase Kit</td></tr><tr><td>Ice cold 2 mL screw-cap tubes</td><td></td><td></td><td>For lysing cells during RNA extraction</td></tr><tr><td>bead mill homogenizer</td><td>Biospec Mini-Beadbeater-24</td><td>112011</td><td>Keep in cold room</td></tr><tr><td>Bacto Peptone</td><td>BD</td><td>DF0118</td><td>for liquid YPD media</td></tr><tr><td>Bacto Yeast Extract</td><td>BD</td><td>DF0886</td><td>for liquid YPD media</td></tr><tr><td>glucose</td><td>Fisher</td><td>D16</td><td>for liquid YPD media</td></tr><tr><td>Qubit assay tubes</td><td>Thermo Fisher</td><td>Q32856</td><td>for measuring nucleic acid concentration</td></tr><tr><td>Quant-iTTM dsDNA BR Assay Kit</td><td>Thermo Fisher</td><td>Q32853</td><td>for measuring nucleic acid concentration</td></tr><tr><td>Quant-iTTM RNA Assay Kit</td><td>Thermo Fisher</td><td>Q32855</td><td>for measuring nucleic acid concentration</td></tr><tr><td>Qubit Fluorometer</td><td>Thermo Fisher</td><td>Q33216</td><td>for measuring nucleic acid concentration</td></tr><tr><td>Commercial electrophoresis system</td><td>Agilent</td><td>Bioanalyzer 2100</td><td>for measuring nucleic acid quality</td></tr><tr><td>Next-generation sequencer</td><td>Illumina</td><td>HiSeq 2500</td><td>for sequencing libraries</td></tr><tr><td>automated liquid handling system</td><td>Wafergen</td><td>Apollo 324</td><td>for creating sequencing libraries</td></tr><tr><td>PrepX PolyA mRNA Isolation Kit</td><td>Wafergen</td><td>400047</td><td>for isolating mRNA from total RNA</td></tr><tr><td>PrepX RNA SEQ for Illumina Library Kit</td><td>Wafergen</td><td>400039</td><td>for creating strand-specific sequencing libraries from total RNA</td></tr><tr><td>Barcode Splitter</td><td></td><td></td><td>https://toolshed.g2.bx.psu.edu/repository?repository_id=7119c4f7a89efa57&amp;amp;changeset_revision=e7b7cdc1834d</td></tr><tr><td>Samtools, which includes the gzip command</td><td></td><td></td><td>http://www.htslib.org/download/</td></tr><tr><td>Trimmomatic</td><td></td><td></td><td>http://www.usadellab.org/cms/?page=trimmomatic</td></tr><tr><td>Bowtie2 (installed before TopHat)</td><td></td><td></td><td>http://bowtie-bio.sourceforge.net/bowtie2/index.shtml</td></tr><tr><td>TopHat</td><td></td><td></td><td>https://ccb.jhu.edu/software/tophat/index.shtml</td></tr><tr><td>HTSeq</td><td></td><td></td><td>http://www-huber.embl.de/HTSeq/doc/overview.html</td></tr><tr><td>R (installed before R Studio)</td><td></td><td></td><td>https://cran.rstudio.com</td></tr><tr><td>R Studio (free version)</td><td></td><td></td><td>https://www.rstudio.com/products/rstudio/download/</td></tr></tbody></table>

measuring mrna levels over time during the yeast s. cerevisiae hypoxic response

基因表达的复杂变化通常会调节细胞反应的很大一部分。每个基因都可能改变表达与独特的动力学, 因为该基因是由特定的时间, 其中一个许多刺激, 信号通路或次要的影响调节。为了在酵母S.酵母中捕获对缺氧的整个基因表达反应, 使用 RNA 序列分析在接触缺氧后的特定时间内监测所有基因的 mRNA 水平。缺氧是由生长在 100% N2气体中的细胞建立的。重要的是, 不像其他的缺氧研究, 麦角固醇和不饱和脂肪酸不添加到媒体, 因为这些代谢物影响基因表达。时间点选择在 0-4 小时的范围内缺氧, 因为该时期捕获的主要变化的基因表达。在每个时间点, mid-log 缺氧细胞迅速过滤和冻结, 限制暴露于 O2和伴随变化的基因表达。总 RNA 从细胞被提取并且用于丰富为 mRNA, 然后被转换成 cDNA。从这个 cDNA 中, 创建了多个复合库, 并在下一代排序器的一个泳道中测序了八或更多的样本。描述了 post-sequencing 管道, 包括质量基础修剪、读取映射和确定每个基因的读取数。DESeq2 在 R 统计环境中被用来识别在任何一个缺氧时间点发生显著变化的基因。对三生物复制的分析显示, 高重现性, 不同动力学的基因和大量预期 O2调控基因。这些方法可用于研究各种生物体的细胞如何随着时间的推移对缺氧反应, 并适应在其他细胞反应过程中研究基因表达。

三次独立进行缺氧时间过程和 RNA 序列分析。为了检验三复制的重现性, 利用主成分分析 (PCA) 对所有基因的基因表达数据进行了分析。图 2显示了示例在前两个主要组件上的变化情况, 它们一起表示58.9% 的可变性。这一分析表明, 每一次课程都有类似的变化 (如每条曲线的相似形状所示)。另外, 最后两个复制比第一个复制更相似。这与最后两次复制是由...

Watch this Scientific Journal Video about Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response at JoVE.com

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

在这里, 我们提出了一个协议使用 RNA 序列监测 mRNA 水平随着时间的推移在缺氧反应的S. 酿酒酵母细胞。这种方法可以适应于分析基因表达在任何细胞反应。

在酵母S.酵母缺氧反应期间, 测量一段时间内的 mRNA 水平

Complex changes in gene expression typically mediate a large portion of a cellular response. Each gene may change expression with unique kinetics as the ...

measuring-mrna-levels-over-time-during-yeast-s-cerevisiae-hypoxic

Universidad San Sebastian

Research

JoVE Journal

Genetics

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

8.2K 次观看.  Rowan School of Osteopathic Medicine. 在这里, 我们提出了一个协议使用 RNA 序列监测 mRNA 水平随着时间的推移在缺氧反应的S. 酿酒酵母细胞。这种方法可以适应于分析基因表达在任何细胞反应。

视频: Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Genome-wide Quantification of Translation in Budding Yeast by Ribosome Profiling

Translation of mRNA into proteins is a complex process involving several layers of regulation. It is often assumed that changes in mRNA transcription reflect changes in protein synthesis, but many exceptions have been observed. Recently, a technique called ribosome profiling (or Ribo-Seq) has emerged as a powerful method that allows identification, with high accuracy, which regions of mRNA are translated into proteins and quantification of translation at the genome-wide level. Here, we present a generalized protocol for genome-wide quantification of translation using Ribo-Seq in budding yeast. In addition, combining Ribo-Seq data with mRNA abundance measurements allows us to simultaneously quantify translation efficiency of thousands of mRNA transcripts in the same sample and compare changes in these parameters in response to experimental manipulations or in different physiological states. We describe a detailed protocol for generation of ribosome footprints using nuclease digestion, isolation of intact ribosome-footprint complexes via sucrose gradient fractionation, and preparation of DNA libraries for deep sequencing along with appropriate quality controls necessary to ensure accurate analysis of in vivo translation.

Translational regulation plays an important role in the control of protein abundance. Here, we describe a high-throughput method for quantitative analysis of translation in the budding yeast Saccharomyces cerevisiae.

核糖体剖面对芽殖酵母中翻译的全基因组定量

Translation of mRNA into proteins is a complex process involving several layers of regulation. It is often assumed that changes in mRNA transcription ...

科研

生物化学

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in mRNA synthesis has been shown to be compensated by a simultaneous decrease in mRNA degradation to restore normal steady-state levels. Hence, the genome-wide quantification of mRNA synthesis, independently from mRNA decay, is the best direct reflection of RNA polymerase II transcriptional activity. Here, we discuss a method using non-perturbing metabolic labeling of nascent RNAs in Saccharomyces cerevisiae (S. cerevisiae). Specifically, the cells are cultured for 6 min with a uracil analog, 4-thiouracil, and the labeled newly transcribed RNAs are purified and quantified to determine the synthesis rates of all individual mRNA. Moreover, using labeled Schizosaccharomyces pombe cells as internal standard allows comparing mRNA synthesis in different S. cerevisiae strains. Using this protocol and fitting the data with a dynamic kinetic model, the corresponding mRNA decay rates can be determined.

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

The protocol described here is based on the genome-wide quantification of newly synthesized mRNA purified from yeast cells labeled with 4-thiouracil. This method allows to measure mRNA synthesis uncoupled from mRNA decay and, thus, provides an accurate measurement of RNA polymerase II transcription.

酿酒酵母4-硫尿嘧啶代谢标记及新合成 mRNA 作为 RNA 聚合酶 II. 活性的一种代理

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in ...

遗传学

Labelling and Visualization of Mitochondrial Genome Expression Products in Baker's Yeast Saccharomyces cerevisiae

Mitochondria are essential organelles of eukaryotic cells capable of aerobic respiration. They contain circular genome and gene expression apparatus. A mitochondrial genome of baker&#8217;s yeast encodes eight proteins: three subunits of the cytochrome c oxidase (Cox1p, Cox2p, and Cox3p), three subunits of the ATP synthase (Atp6p, Atp8p, and Atp9p), a subunit of the ubiquinol-cytochrome c oxidoreductase enzyme, cytochrome b (Cytb), and mitochondrial ribosomal protein Var1p. The purpose of the method described here is to specifically label these proteins with 35S methionine, separate them by electrophoresis and visualize the signals as discrete bands on the screen. The procedure involves several steps. First, yeast cells are cultured in a galactose-containing medium until they reach the late logarithmic growth stage. Next, cycloheximide treatment blocks cytoplasmic translation and allows 35S methionine incorporation only in mitochondrial translation products. Then, all proteins are extracted from yeast cells and separated by polyacrylamide gel electrophoresis. Finally, the gel is dried and incubated with the storage phosphor screen. The screen is scanned on a phosphorimager revealing the bands. The method can be applied to compare the biosynthesis rate of a single polypeptide in the mitochondria of a mutant yeast strain versus the wild type, which is useful for studying mitochondrial gene expression defects. This protocol gives valuable information about the translation rate of all yeast mitochondrial mRNAs. However, it requires several controls and additional experiments to make proper conclusions.

Labelling and Visualization of Mitochondrial Genome Expression Products in Baker's Yeast Saccharomyces cerevisiae

Baker&#8217;s yeast mitochondrial genome encodes eight polypeptides. The goal of the current protocol is to label all of them and subsequently visualize them as separate bands.

贝克酵母糖精中线粒体基因组表达产品的标记和可视化

Mitochondria are essential organelles of eukaryotic cells capable of aerobic respiration. They contain circular genome and gene expression apparatus. A ...

In Vivo Monitoring of Transcriptional Activity During Metabolic Transition Using a Bioluminescent Reporter in Yeast

Sequential sugar consumption, from a preferred sugar source to a less preferred one, represents a critical metabolic adaptation in yeast, which is particularly relevant for survival in fluctuating environments such as those found in beer fermentation. However, sugar transitions are an environmental variable that is challenging to predict and detect, impacting the outcome of beer fermentations. This protocol describes an in vivo system to monitor transcriptional activation associated with the glucose-to-maltose metabolic shift in Saccharomyces eubayanus that applies to different wild Saccharomyces yeast strains. 
The system employs an episomal bioluminescent transcriptional reporter for maltose metabolism, focusing on MAL32, since it provides a good readout for metabolic shifts, as studied in S. cerevisiae. For this, yeast strains were transformed with plasmids containing the MAL32 regulatory region from S. eubayanus, controlling the expression of a gene encoding for a destabilized version of firefly luciferase1, and a hygromycin resistance gene used exclusively during transformation to ensure plasmid acquisition. Following selection, transformed yeast cells can be cultured under non-selective conditions, as the episomal plasmid remains stable in culture conditions for up to 7 days. 
This system was validated under a complex sugar environment in microfermentation assays, confirming the effectiveness of the luciferase reporter in informing metabolic transitions. Samples were collected regularly and analyzed with a luminometer, providing continuous insights into yeast responses. While broadly applicable, this protocol is particularly valuable for assessing yeast performance under fermentation conditions, where metabolic changes pose a significant challenge. Additionally, this methodology can be adapted by selecting alternative promoters to explore a broader range of responses to environmental changes, allowing characterization as well as optimization of wild yeast strains for diverse industrial applications.

This protocol employs a bioluminescent reporter, allowing measurements of transcriptional activity in Saccharomyces eubayanus to monitor the glucose-to-maltose transition, enabling real-time analysis of metabolic adaptations and supporting strain optimization for industrial fermentation under diverse conditions.

体内研究 使用酵母中的生物发光报告基因监测代谢转变过程中的转录活性

Sequential sugar consumption, from a preferred sugar source to a less preferred one, represents a critical metabolic adaptation in yeast, which is ...

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

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for using FISH to quantify the number of mRNAs in single yeast cells. Cells can be grown in any condition of interest and then fixed and made permeable. Subsequently, multiple single-stranded deoxyoligonucleotides conjugated to fluorescent dyes are used to label and visualize mRNAs. Diffraction-limited fluorescence from single mRNA molecules is quantified using a spot-detection algorithm to identify and count the number of mRNAs per cell. While the more standard quantification methods of northern blots, RT-PCR and gene expression microarrays provide information on average mRNAs in the bulk population, FISH facilitates both the counting and localization of these mRNAs in single cells at single-molecule resolution.

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

This protocol describes an experimental procedure for performing Fluorescence in situ Hybridization (FISH) for counting mRNAs in single cells at single-molecule resolution.

可视化和分析的mRNA分子，使用荧光<em&gt;在原位</em&gt;杂交<em&gt;酿酒酵母（Saccharomyces cerevisiae）</em

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for ...

Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies depicting the temporal dependence of gene expression provide insight into the dynamics of its regulation; however, there are many technical challenges to obtaining and analyzing fluorescence movies of single cells. We describe here a simple protocol using a commercially available microfluidic culture device to generate such data, and a MATLAB-based, graphical user interface (GUI) -based software package to quantify the fluorescence images. The software segments and tracks cells, enables the user to visually curate errors in the data, and automatically assigns lineage and division times. The GUI further analyzes the time series to produce whole cell traces as well as their first and second time derivatives. While the software was designed for S. cerevisiae, its modularity and versatility should allow it to serve as a platform for studying other cell types with few modifications.

We present a simple protocol to obtain fluorescence microscopy movies of growing yeast cells, and a GUI-based software package to extract single-cell time series data. The analysis includes automated lineage and division time assignment integrated with visual inspection and manual curation of tracked data.

获取荧光时间推移电影的芽殖酵母和分析单细胞动力学移植物

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies ...

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

在单酵母细胞MAPK诱导表达的时空定量

The quantification of gene expression at the  single cell level uncovers novel regulatory mechanisms obscured in measurements  performed at the population ...

Measurement of mRNA Decay Rates in Saccharomyces cerevisiae Using rpb1-1 Strains

mRNA steady state levels vary depending on environmental conditions. Regulation of the steady state accumulation levels of an mRNA ensures that the correct amount of protein is synthesized for the cell&#8217;s specific growth conditions. One approach for measuring mRNA decay rates is inhibiting transcription and subsequently monitoring the disappearance of the already present mRNA. The rate of mRNA decay can then be quantified, and an accurate half-life can be determined utilizing several techniques. In S. cerevisiae, protocols that measure mRNA half-lives have been developed and include inhibiting transcription of mRNA using strains that harbor a temperature sensitive allele of RNA polymerase II, rpb1-1. Other techniques for measuring mRNA half-lives include inhibiting transcription with transcriptional inhibitors such as thiolutin or 1,10-phenanthroline, or alternatively, by utilizing mRNAs that are under the control of a regulatable promoter such as the galactose inducible promoter and the TET-off system. Here, we describe measurement of S. cerevisiae mRNA decay rates using the temperature sensitive allele of RNA polymerase II. This technique can be used to measure mRNA decay rates of individual mRNAs or genome-wide.

Measurement of mRNA Decay Rates in Saccharomyces cerevisiae Using rpb1-1 Strains

The steady state level of specific mRNAs is determined by the rate of synthesis and decay of the mRNA. Genome-wide mRNA degradation rates or the decay rates of specific mRNAs can be measured by determining mRNA half-lives. This protocol focuses on measurement of mRNA decay rates in Saccharomyces cerevisiae.

mRNA的衰变率的测量<em&gt;酿酒酵母</em&gt;使用<em&gt; rpb1-1</em&gt;株

mRNA steady state levels vary depending on environmental conditions. Regulation of the steady state accumulation levels of an mRNA ensures that the ...

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, log-phase, and stationary-phase. Each growth phase can reveal different aspects of fitness that are related to various environmental and genetic conditions. High-resolution and quantitative measurements of all 3 phases of growth are generally difficult to obtain. Here we present a detailed method to characterize all 3 growth phases on solid media using an assay called One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). ODELAY quantifies growth phenotypes of individual cells growing into colonies on solid media using time-lapse microscopy. This method can directly observe population heterogeneity with each growth parameter in genetically identical cells growing into colonies. This population heterogeneity offers a unique perspective for understanding genetic and epigenetic regulation, and responses to genetic and environmental perturbations. While the ODELAY method is demonstrated using yeast, it can be utilized on any colony forming microorganism that is visible by bright field microscopy.

We present a method for quantifying growth phenotypes of individual yeast cells as they grow into colonies on solid media using time-lapse microscopy termed, One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). Population heterogeneity of genetically identical cells growing into colonies can be directly observed and quantified.

ODELAY:用于酵母生长多参数定量的大规模方法

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, ...

在酵母S.酵母缺氧反应期间, 测量一段时间内的 mRNA 水平

摘要

探索更多视频

此视频中的章节

核糖体剖面对芽殖酵母中翻译的全基因组定量

酿酒酵母4-硫尿嘧啶代谢标记及新合成 mRNA 作为 RNA 聚合酶 II. 活性的一种代理

贝克酵母糖精中线粒体基因组表达产品的标记和可视化

体内研究使用酵母中的生物发光报告基因监测代谢转变过程中的转录活性

微阵列分析FOR酿酒酵母

可视化和分析的mRNA分子，使用荧光

获取荧光时间推移电影的芽殖酵母和分析单细胞动力学移植物

在单酵母细胞MAPK诱导表达的时空定量

mRNA的衰变率的测量

ODELAY:用于酵母生长多参数定量的大规模方法

在酵母S.酵母缺氧反应期间, 测量一段时间内的 mRNA 水平

摘要

探索更多视频

此视频中的章节

核糖体剖面对芽殖酵母中翻译的全基因组定量

酿酒酵母4-硫尿嘧啶代谢标记及新合成 mRNA 作为 RNA 聚合酶 II. 活性的一种代理

贝克酵母糖精中线粒体基因组表达产品的标记和可视化

体内研究 使用酵母中的生物发光报告基因监测代谢转变过程中的转录活性

微阵列分析FOR酿酒酵母

可视化和分析的mRNA分子，使用荧光

获取荧光时间推移电影的芽殖酵母和分析单细胞动力学移植物

在单酵母细胞MAPK诱导表达的时空定量

mRNA的衰变率的测量

ODELAY:用于酵母生长多参数定量的大规模方法

体内研究使用酵母中的生物发光报告基因监测代谢转变过程中的转录活性