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>

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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, 或雇用缺氧诱导厌氧室或袋34。每种方法都可能导致不同程度的缺氧或其他意外的环境变化。这将是有用的研究基因表达, 而系统地改变气体混合物 (例如, 90% N2和 10% O2), 因为在野外的酵母可能会遇到不太严重的缺氧情况。第二, 麦角固醇和不饱和脂肪酸 (例如, 吐温 80) 没有添加到培养基中, 因为它们影响基因表达, 如导言中所讨论的那样。第三, 为了尽量减少由不同生长阶段引起的基因表达变化, 进行经验确定的稀释, 以便当一个文化到达一个时间点, 它是在 mid-log 阶段的增长 (〜 1-2 x 107细胞/毫升)。第四, 快速过滤和冷冻 (〜十五年代) 的细胞已经从缺氧是至关重要的, 因为基因表达的变化可能发生在 < 5 分钟的暴露于 O2, 如发生在细胞是由离心收集 (数据没有显示)。通过在缺氧罩或室中进行细胞的生长和采集, 可以减少细胞暴露于 O2的时间。第五, 选择合适的菌株进行研究;为了与其他基因组研究相一致, 采用了常见的 S288C 实验室应变背景。然而, S288C 菌株包含一个突变的hap1等位基因, 因此被修复11。这使得对通过 Hap1 转录因子11响应 O2级别的CYC1等基因的研究成为了问题。
选择时间点是因为他们在以前的缺氧实验中表现出很大的基因表达变化。在这里显示的结果可以通知未来的实验。例如, 在显示大的变化 (例如, 0 到 30 min 缺氧) 的时间间隔内使用更高的分辨率来更精细地捕捉不同的动力学, 这将是很有帮助的。另外, 以后时间点, 在这里被检测的时间段之外 (即, 4 h 缺氧) 可能显露进一步表达变化。
RNA seq 被用来测量 mRNA 的水平, 因为它的重现性和宽动态范围允许测量大折叠的变化18,35。RNA 是由机械破坏的细胞使用强烈动摇的珠子和纯化的一列。其他 RNA 纯化方法可以使用, 如热苯酚36。理想情况下, rna 浓度将在 200 ng/µL-1000 ng/µL 的范围内, 因为 rna 浓度将被稀释到 100 ng/µL 用于反转转录和图书馆准备。rna 浓度应以荧光和 rna 特异染料来测定;紫外线分光光度计是有限的, 因为它测量的总浓度的核酸, 包括 RNA 和 DNA。用凝胶电泳法测定 RNA 的质量;核糖体 rna 带应该是明确的凝胶和涂抹表明 rna 退化。在这里, mRNA 转录被丰富, 但有不同的方法, 以隔离各种 RNA 类型20 , 这也可能是重要的反应。
为了节省资源, 在8和12样本之间的多路复用和测序一起在一条车道, 结果平均至少693读每个基因为每个样品, 足够性确定每个基因的读的数量。事实上, 超过12样本可以在一条车道上复用, 这可能导致对大多数基因进行充分取样。为了计算每个基因的平均读数, 映射到基因 (在 HTSeq 输出文件中) 的总读取数除以提供给 HTSeq 的基因数量 (在本研究中, 7140)。当估计在一条车道上可以多路复用的样本的最大数量时, 请考虑显示最低表达式的兴趣基因 (即, 最低规范化计数), 并使用此和其他 RNA seq 研究的数据。如果一个基因的规范化读取计数在不同的复制中有很大的差异, 那么读取的次数可能太低, 这意味着每个测序车道应该多复用一些样本。
下一代排序将生成包含读取和其他信息的 FASTQ 文件。如果执行了多路传输, 则可能会生成一个条码文件和一个附加的 FASTQ 文件。可以下载这些文件进行本地分析, 如本协议所示。另外, 对于那些不熟悉 command-line 函数或 R 的人, 还有几个在线的下一代序列分析工具。在这方面, 我们建议 Galaxy (https://usegalaxy.org/) 37和 GenomeSpace (http://www.genomespace.org/)。在本协议中, 作者编写的两个脚本用于 FASTQ 处理和表达式分析。脚本是 well-annotated, 可以编辑不同的实验设计和计算机设置。另外, 两个脚本和 "材料" 表提供了用于下载这些脚本中所用工具的网站。第一个脚本 "fastq_pipeline" 是一个在 UNIX/Linux 终端的命令行运行的 shell 脚本。此脚本 de-multiplexes 原始 FASTQ 文件, 其中包含从排序器的一条车道获得的所有读取, 从而为该泳道中的每个样本生成一个 FASTQ 文件。接下来, 每个 FASTQ 文件中的读取都是使用带有默认设置21的 Trimmomatic 进行的质量修剪。然后, 将裁剪后的读取映射到S. 酵母S288C 参考基因组 (SGD R64-1-1_20110203), 并使用默认设置22进行 TopHat2。该脚本最终使用 HTSeq 来确定映射到每个带注释特征19的读取数。
第二个剧本 "time_course_script。r ", 也由作者编写, 并在 r 统计环境中运行24。最初导入到的脚本是由 HTSeq 生成的读取计数数据。每个样本被假定为一个时间点, 因此是相对于其他时间点组织的。原始的读计数然后被进口入 R 包裹, DESeq2 25, 为了辨认基因是差异表达在任何时间点相对于第一 (即, 好氧, 时间 0)。由于其灵活性, DESeq2 可用于执行其他统计测试, 如表达式是否更改为时间13的函数。另外, 使用参数和非参数统计数据进行 RNA seq 读取计数的其他工具也可用于20。然后, 该脚本对读取计数进行规范化, 以控制每个样本的排序程度, 并 log2 转换计数。这些经过处理的读取用于执行 PCA 分析, 以确定每个基因的最大折叠变化, 并在图 4中创建表达式关系图。
一个重要的问题是如何最好地使用统计数据来识别对缺氧有显著反应的基因。至少有三的时间过程的生物复制是必要的, 以计算每一个基因的自然变异性, 从而确定的基因, 对缺氧的反应比预期的机会更显着。另外, 也可以成功地识别随着时间的推移而响应的基因, 没有生物复制13,25,38,39。这些方法的主要缺点是它们没有考虑到每个基因的生物变异性。但是, 如果不执行 RNA-seq 复制, 则可以通过执行多个生物复制13来验证单个基因表达的变化 qPCR。
评估响应的多个时间点有两个主要好处。首先, 如前所述 (特别是在图 2) 中, 时间过程确定了显示较大表达式变化的间隔, 并告知是否需要额外的时间点来改进动力学的分辨率或观察以后的事件响应.第二, 时间课程允许每个基因的表达动力学分化。这有助于识别独特的信号通路, 在响应过程中, 在特定的时间行动, 并提供了洞察时间的启动和终止信号。具体来说, 通过在这里进行的表达模式聚集的基因产生了一系列的共同基因。基因组的启动子可以共享转录因子结合位点, 这表明转录因子在基因改变表达时变得活跃。
在研究细胞的反应时, 观察到的变异是理想的, 因为刺激 (例如, 缺氧), 而不是其他的实验变量。但是, 如图 2所示, 单个研究员和/或媒体组件的批次对基因表达的变异性做出了重大贡献。因此, 这些参数应考虑, 以达到高重现性和最小的实验变异性。尽可能少的时间应该分离每个复制, 因为实验变量更有可能随着时间的推移而改变。
总之, 这一方法可以用来准确地监测在低氧时间过程中基因组范围内的 mRNA 水平 (或其他事件, 如蛋白修饰或蛋白质水平) 的变化。该方法可适用于其他生物体, 特别是可在液体培养中生长的微生物种类。这种全基因组的时效分析将补充细胞形态学、蛋白质活性和新陈代谢的研究。在一起, 这些数据将导致对蜂窝响应的更丰富的理解。

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 border="0" cellpadding="0" cellspacing="0" width="973">
	<tbody>
		<tr height="126">
			<td height="126" style="height:126px;width:292px;">Enclosed dry incubator</td>
			<td style="width:183px;">Thermo Scientific</td>
			<td style="width:119px;">MaxQ 4000</td>
			<td style="width:380px;">Set at 30&#176;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 height="63">
			<td height="63" style="height:63px;width:292px;">Micro-analysis Filter Holder</td>
			<td style="width:183px;">Millipore</td>
			<td style="width:119px;">XX1002530</td>
			<td style="width:380px;">25mm diameter, stainless steel support, no. 5 perforated silicone stopper mounts in standard 125mL filtering flask</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:292px;">Strong vacuum</td>
			<td style="width:183px;">Edwards</td>
			<td style="width:119px;">E-LAB 2</td>
			<td style="width:380px;">The &#8220;house&#8221; vacuum may be too weak. Alternatively, use an electric-power portable vacuum pump like the one listed here.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">1000-mL flask</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">To act as vacuum trap.</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:292px;">~2-foot lengths of Heavy Wall Vacuum Tubing, inner diameter 3/8 in, outer diameter 7/8 in</td>
			<td style="width:183px;">Tygon</td>
			<td style="width:119px;">38TT</td>
			<td style="width:380px;">Two pieces: the first connects vacuum to trap, and the second connects trap to filter system.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">High-pressure N2 gas tank</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">99.999% purity, &#62;1000psi, with a regulator and gas flow controller</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Autoclaved 500mL flask</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">Opening covered with aluminum foil. One for each yeast strain.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Autoclaved 250mL flasks</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">Openings covered with aluminum foil. One for each time point plus two for water traps.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Flask stoppers (size 6, two holes with 5mm diameter)</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">Sterilized with 70% ethanol. One for each flask.</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:292px;">Glass tubing, length 9 cm or 17 cm, inner diameter 2 mm, outer diameter 5 mm</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">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 height="42">
			<td height="42" style="height:42px;width:292px;">~25-cm lengths of plastic tubing, inner diameter 5 mm</td>
			<td style="width:183px;">Tygon</td>
			<td style="width:119px;">E-3603</td>
			<td style="width:380px;">One piece for each flask. Sterilized with 70% ethanol.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Sterile filter discs</td>
			<td style="width:183px;">Millipore</td>
			<td style="width:119px;">HAWP02500</td>
			<td style="width:380px;">25mm diameter, 0.45 &#181;m pore size, one for each time point</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:292px;">Sterile dH2O (~100mL)</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">1-mL cuvettes</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">For measuring OD600 (i.e., cell concentration)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">50-mL sterile centrifuge tubes</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">One for each time point</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Clean and sterile tweezers</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">liquid nitrogen</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">For freezing cells</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">acid-washed beads</td>
			<td style="width:183px;">Sigma</td>
			<td style="width:119px;">G8772</td>
			<td style="width:380px;">Keep at 4&#176;C for lysing cells</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Qiagen RNeasy Mini Kit</td>
			<td style="width:183px;">Qiagen</td>
			<td align="right" style="width:119px;">74104</td>
			<td style="width:380px;">For RNA column purification</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Qiagen RLT buffer</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">Prepare by adding 10&#181;L of &#946;-Mercaptoethanol per 1mL of RLT buffer, keep at 4C.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2-mL collection tubes</td>
			<td style="width:183px;">Qiagen</td>
			<td style="width:119px;"></td>
			<td style="width:380px;">included in the Qiagen Rneasy Mini Kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Buffer RPE</td>
			<td style="width:183px;">Qiagen</td>
			<td style="width:119px;"></td>
			<td style="width:380px;">included in the Qiagen Rneasy Mini Kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Buffer RW1</td>
			<td style="width:183px;">Qiagen</td>
			<td style="width:119px;"></td>
			<td style="width:380px;">included in the Qiagen Rneasy Mini Kit</td>
		</tr>
		<tr height="168">
			<td height="168" style="height:168px;width:292px;">DNase I stock and working solutions</td>
			<td style="width:183px;">Qiagen</td>
			<td align="right" style="width:119px;">79254</td>
			<td style="width:380px;">The DNase I enzyme comes as lyophilized powder in a glass vial. Using a sterile needle and syringe, inject 550&#181;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&#176;C) in single-use aliquots (80&#181;L each). The stock solution should not be thawed and refrozen.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Buffer RDD</td>
			<td style="width:183px;">Qiagen</td>
			<td style="width:119px;"></td>
			<td style="width:380px;">included in the Qiagen DNase Kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Ice cold 2-mL screw-cap tubes</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">For lysing cells during RNA extraction</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">bead mill homogenizer</td>
			<td style="width:183px;">Biospec Mini-Beadbeater-24</td>
			<td align="right" style="width:119px;">112011</td>
			<td style="width:380px;">Keep in cold room</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Bacto Peptone</td>
			<td style="width:183px;">BD</td>
			<td style="width:119px;">DF0118</td>
			<td style="width:380px;">for liquid YPD media</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Bacto Yeast Extract</td>
			<td style="width:183px;">BD</td>
			<td style="width:119px;">DF0886</td>
			<td style="width:380px;">for liquid YPD media</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">glucose</td>
			<td style="width:183px;">Fisher</td>
			<td style="width:119px;">D16</td>
			<td style="width:380px;">for liquid YPD media</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Qubit assay tubes</td>
			<td style="width:183px;">Thermo Fisher</td>
			<td style="width:119px;">Q32856</td>
			<td style="width:380px;">for measuring nucleic acid concentration</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Quant-iTTM dsDNA BR Assay Kit</td>
			<td style="width:183px;">Thermo Fisher</td>
			<td style="width:119px;">Q32853</td>
			<td style="width:380px;">for measuring nucleic acid concentration</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Quant-iTTM RNA Assay Kit</td>
			<td style="width:183px;">Thermo Fisher</td>
			<td style="width:119px;">Q32855</td>
			<td style="width:380px;">for measuring nucleic acid concentration</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Qubit Fluorometer</td>
			<td style="width:183px;">Thermo Fisher</td>
			<td style="width:119px;">Q33216</td>
			<td style="width:380px;">for measuring nucleic acid concentration</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Commercial electrophoresis system</td>
			<td style="width:183px;">Agilent</td>
			<td>Bioanalyzer 2100</td>
			<td style="width:380px;">for measuring nucleic acid quality</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Next-generation sequencer</td>
			<td style="width:183px;">Illumina</td>
			<td style="width:119px;">HiSeq 2500</td>
			<td style="width:380px;">for sequencing libraries</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">automated liquid handling system</td>
			<td style="width:183px;">Wafergen</td>
			<td style="width:119px;">Apollo 324</td>
			<td style="width:380px;">for creating sequencing libraries</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">PrepX PolyA mRNA Isolation Kit</td>
			<td style="width:183px;">Wafergen</td>
			<td align="right" style="width:119px;">400047</td>
			<td style="width:380px;">for isolating mRNA from total RNA</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">PrepX RNA SEQ for Illumina Library Kit</td>
			<td style="width:183px;">Wafergen</td>
			<td align="right" style="width:119px;">400039</td>
			<td style="width:380px;">for creating strand-specific sequencing libraries from total RNA</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:292px;">Barcode Splitter</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">https://toolshed.g2.bx.psu.edu/repository?repository_id=7119c4f7a89efa57&#38;changeset_revision=e7b7cdc1834d</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Samtools, which includes the gzip command</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">http://www.htslib.org/download/</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">Trimmomatic</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">http://www.usadellab.org/cms/?page=trimmomatic</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:292px;">Bowtie2 (installed before TopHat)</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">http://bowtie-bio.sourceforge.net/bowtie2/index.shtml</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">TopHat</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">https://ccb.jhu.edu/software/tophat/index.shtml</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">HTSeq</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">http://www-huber.embl.de/HTSeq/doc/overview.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">R (installed before R Studio)</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">https://cran.rstudio.com</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:292px;">R Studio (free version)</td>
			<td style="width:183px;"></td>
			<td style="width:119px;"></td>
			<td style="width:380px;">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同一个人使用相同批次的媒体组件进行的, 而第一次复制是由不同的人员和批次执行的。这一发现突显了这样一个事实, 即技术和化学品的一致性是获得高重复性的一个重要因素。最后, PCA 分析有助于评估所选择的时间点是否捕获在时间过程中发生的主要变化。集中在一个复制曲线, 有更大的距离在早先样品之间, 表明大变动在基因表示, 并且更小的距离在以后样品之间, 表明更小的变动和可能结尾的开关从有氧到缺氧基因表达。
接下来, 使用 R25中的 DESeq2 包来确定与时间 0 (补充表 1中的 p 值) 相比, 显示显著变化的基因。在这些重要基因中, 607 改变了4倍以上 (折叠在补充表 1)。这些基因的表达模式是聚集在一起的, 以便将类似调控的基因组合在一起, 然后以图 (图 3) 显示。此图显示了在复制中表达式更改具有高度可重复性。同时, 基因表现出不同的动力学, 在表达上都有增加和减少。许多基因表现出峰值增加或减少30分钟, 可能是由于瞬态应力响应13。
图 4描述了以前发现为 O2调节的两个 downregulated 和两个上调基因的表达。基因改变表达性, 与相似的曲线在生物复制之间。复制之间的差异最小的基因是DAN1, 具有重叠曲线。最易变性的基因是CYC1, 也许是因为这个基因的表达是自然变化的。这个数字还说明了大的褶皱变化 (多达1024倍) 被检测到。
为了确定在 607 O2调控基因组中富集的细胞过程, 进行了长期浓缩 (补充表 2)。正如所料, 许多 O2调控的基因在细胞呼吸、新陈代谢的其他方面和核糖体过程中扮演了一个角色13。
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody>
<tr>
<td>示例#</td>
			<td colspan="2">缺氧时间</td>
			<td colspan="2">ml 文化 + YPD</td>
		</tr>
<tr>
<td>2</td>
			<td colspan="2">5分钟</td>
			<td colspan="2">20毫升 + 0 毫升</td>
		</tr>
<tr>
<td>3</td>
			<td colspan="2">10分钟</td>
			<td colspan="2">20毫升 + 0 毫升</td>
		</tr>
<tr>
<td>4</td>
			<td colspan="2">30分钟</td>
			<td colspan="2">20毫升 + 0 毫升</td>
		</tr>
<tr>
<td>5</td>
			<td colspan="2">60分钟</td>
			<td colspan="2">10毫升 + 10 毫升</td>
		</tr>
<tr>
<td>6</td>
			<td colspan="2">120分钟</td>
			<td colspan="2">10毫升 + 10 毫升</td>
		</tr>
<tr>
<td>7</td>
			<td colspan="2">180分钟</td>
			<td colspan="2">5毫升 + 15 毫升</td>
		</tr>
<tr>
<td>8</td>
			<td colspan="2">240分钟</td>
			<td colspan="2">4毫升 + 16 毫升</td>
		</tr>
</tbody></table>表1。单元格稀释执行时间为0。 这些稀释在 N2中的指定时间后被实验确定为导致 mid-log 浓度 (1-2 x 107单元/mL)。
补充表1。所有基因的表达和统计数据。 该表包含系统名称, 七 DESeq2 测试的调整 p 值 (即, 5 min vs 0 分钟, 10 min 与 0 min,等), 最小调整的 p 值, 以及 log2 最大折变。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/Supp_Table1.xlsx">请单击此处下载此文件.</a>
补充表2。去期限充实结果。 这张表显示去过程, 他们的表示法在 607 O2被调控的基因和他们的表示法在基因组。然后, chi-square 测试被用来确定在607基因组中明显或不足的 GO 术语。go 富集分析是在 SGD 28上使用 go 瘦映射器执行的。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/Supp_Table2.xlsx">请单击此处下载此文件.</a>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56226/56226fig1.jpg"> 图1。缺氧设置, 以采取时间点不中断气体流向后的时间点。 如协议所述, 所有连接都保持安全是很重要的。注意短 (9 厘米) 和长 (17 厘米) 玻璃管的位置。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/56226fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56226/56226fig2.jpg"> 图2。主成分分析 (PCA) 显示了三生物复制的关系。 每条曲线有0分钟到240分钟的样品顺序。在 PCA 中使用了所有基因的 log2 归一化基因表达。PC1 占总方差的 34.7%, PC2 占24.2%。黑线是第一次复制, 红线是第二个, 蓝线是第三个。请注意, 箭头是用来指出240分钟时点在不同的样本。主成分分析 (PCA) 是在 R 中使用prcomp函数 (Q 模式或奇异值分解) 对包含列中的基因的 log2-transformed 矩阵和行中的时间点29进行的。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/56226fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56226/56226fig3.jpg"> 图3。图显示607基因的表达, 被确定为 O2调控。 这些基因在至少一个 DESeq2 试验中是显著的, 并且改变了超过4倍的表达。显示为日志2(相对表达式)。红色 = 增加表达式。绿色 = 减少表达式。颜色的强度与变化的程度成正比。在 TreeView 30中创建图之前, 基因表达式在群集 3.0 31中是用 k 表示群集的 k=10。图下面的键显示了刻度。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/56226fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56226/56226fig4.jpg"> 图4。四基因的相对 mRNA 水平随着时间的推移在三复制。 黑线是第一次复制, 红线是第二个, 蓝线是第三个。常见/系统基因名称为CYC1/YJR048W、 ERG5/YMR015C、 DAN1/YJR150C和NCE103/YNL036W。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/56226fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
补充文件1。fastq_pipeline <a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/fastq_pipeline.sh" target="_blank">请单击此处下载此文件。</a>
补充文件2。time_course_script研发 <a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56226/time_course_script.R" target="_blank">请单击此处下载此文件。</a>

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

Nanyang Technological University

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

Determination of the Optimal Chromosomal Location(s) for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In bacteria, the impact of the genetic context on the function of a genetic element can be difficult to assess. Several mechanisms, including topological effects, transcriptional interference from neighboring genes, and/or replication-associated gene dosage, may affect the function of a given genetic element. Here, we describe a method that permits the random integration of a DNA element into the chromosome of Escherichia coli and select the most favorable locations using a simple growth competition experiment. The method takes advantage of a well-described transposon-based system of random insertion, coupled with a selection of the fittest clone(s) by growth advantage, a procedure that is easily adjustable to experimental needs. The nature of the fittest clone(s) can be determined by whole-genome sequencing on a complex multi-clonal population or by easy gene walking for the rapid identification of selected clones. Here, the non-coding DNA region DARS2, which controls the initiation of chromosome replication in E. coli, was used as an example. The function of DARS2 is known to be affected by replication-associated gene dosage; the closer DARS2 gets to the origin of DNA replication, the more active it becomes. DARS2 was randomly inserted into the chromosome of a DARS2-deleted strain. The resultant clones containing individual insertions were pooled and competed against one another for hundreds of generations. Finally, the fittest clones were characterized and found to contain DARS2 inserted in close proximity to the original DARS2 location.

Determination of the Optimal Chromosomal Locations for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

Here, the power of a transposon-mediated random insertion of a non-coding DNA element was used to resolve its optimal chromosomal position.

用新的转介导法测定大肠杆菌中 DNA 元素的最佳染色体位置 (s)

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In ...

科研

遗传学

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Sensory systems allow animals to detect, process, and respond to their environment. Food abundance is an environmental cue that has profound effects on animal physiology and behavior. Recently, we showed that modulation of longevity in the nematode Caenorhabditis elegans by food abundance is more complex than previously recognized. The responsiveness of the lifespan to changes in food level is determined by specific genes that act by controlling information processing within a neural circuit. Our framework combines genetic analysis, high-throughput quantitative imaging and information theory. Here, we describe how these techniques can be used to characterize any gene that has a physiological relevance to broad-range dietary restriction. Specifically, this workflow is designed to reveal how a gene of interest regulates lifespan under broad-range dietary restriction; then to establish how the expression of the gene varies with food level; and finally, to provide an unbiased quantification of the amount of information conveyed by gene expression about food abundance in the environment. When several genes are examined simultaneously under the context of a neural circuit, this workflow can uncover the coding strategy employed by the circuit.

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Here, we present a framework to relate broad-range dietary restriction to gene expression and lifespan. We describe protocols for broad-range dietary restriction and for quantitative imaging of gene expression under this paradigm. We further outline computational analyses to reveal underlying information processing features of the genetic circuits involved in food-sensing.

量化的信息编码的基因表达水平在寿命调制下线虫的宽范围饮食限制

Sensory systems allow animals to detect, process, and respond to their environment. Food abundance is an environmental cue that has profound effects on ...

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

The aleurone layer of barley grains is an important model system for hormone-regulated gene expression in plants. In aleurone cells, genes required for germination or early seedling development are activated by gibberellin (GA), while genes associated with stress responses are activated by abscisic acid (ABA). The mechanisms of GA and ABA signaling can be interrogated by introducing reporter gene constructs into aleurone cells via particle bombardment, with the resulting transient expression measured using enzyme assays. An improved protocol is reported that partially automates and streamlines the grain homogenization step and the enzyme assays, allowing significantly more throughput than existing methods. Homogenization of the grain samples is carried out using an automated tissue homogenizer, and GUS (&#946;-glucuronidase) assays are carried out using a 96-well plate system. Representative results using the protocol suggest that phospholipase D activity may play an important role in the activation of HVA1 gene expression by ABA, through the transcription factor TaABF1.

An improved protocol is presented for the measurement of transient gene expression from reporter constructs in barley aleurone cells after particle bombardment. The combination of automated grain grinding with 96-well plate enzyme assays provides high throughput for the procedure.

提高吞吐量的轰击大麦糊粉层层中基因表达的测定

The aleurone layer of barley grains is an important model system for hormone-regulated gene expression in plants. In aleurone cells, genes required for ...

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

转录因子结合、转录、翻译和营业额的实时分析在细胞激活过程中显示全球事件

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

Measuring Exercise Levels in Drosophila melanogaster Using the Rotating Exercise Quantification System (REQS)

Drosophila melanogaster is a new model organism for studies in exercise biology. To date, two main exercise systems, the Power Tower and the Treadwheel have been described. However, a method to measure the amount of additional animal activity induced through the exercise treatment has been lacking. The Rotating Exercise Quantification System (REQS) fills this need, providing a measure of animal activity for animals experiencing rotational exercise. This protocol details how to use the REQS to assess animal activity during rotational exercise and illustrates the type of data that can be generated. Here, we demonstrate how the REQS is used to measure sex- and strain-specific differences in exercise induced activity. The REQS can also be used to evaluate the impact of various other experimental parameters such as age, diet, or population size on exercise induced activity. In addition, it can be used to compare the efficacy of different exercise training protocols. Importantly, it provides an opportunity to standardize exercise treatments between strains, allowing the researcher to achieve equal amounts of activity between groups if needed. Thus, the REQS is a notable new resource for exercise biologists working with the Drosophila model system and complements existing exercise systems.

Measuring Exercise Levels in Drosophila melanogaster Using the Rotating Exercise Quantification System REQS

The Rotating Exercise Quantification System (REQS) can induce exercise in Drosophila melanogaster through rotation while simultaneously measuring the amount of activity performed by the animals. Here, we present a point-by-point protocol detailing how to measure activity levels of animals experiencing rotational exercise treatments using the REQS.

使用旋转运动量化系统测量果蝇中的运动水平 (满足要求)

Drosophila melanogaster is a new model organism for studies in exercise biology. To date, two main exercise systems, the Power Tower and the Treadwheel ...

Mating-based Overexpression Library Screening in Yeast

Budding yeast has been widely used as a model in studying proteins associated with human diseases. Genome-wide genetic screening is a powerful tool commonly used in yeast studies. The expression of a number of neurodegenerative disease-associated proteins in yeast causes cytotoxicity and aggregate formation, recapitulating findings seen in patients with these disorders. Here, we describe a method for screening a yeast model of the Amyotrophic Lateral Sclerosis-associated protein FUS for modifiers of its toxicity. Instead of using transformation, this new screening platform relies on the mating of yeast to introduce an arrayed library of plasmids into the yeast model. The mating method has two clear advantages: first, it is highly efficient; second, the pre-transformed arrayed library of plasmids can be stored for long-term as a glycerol stock, and quickly applied to other screens without the labor-intensive step of transformation into the yeast model each time. We demonstrate how this method can successfully be used to screen for genes that modify the toxicity of FUS.

This article presents a mating-based method to facilitate overexpression screening in budding yeast using an arrayed plasmid library.

基于交配的酵母超表达文库筛选

Budding yeast has been widely used as a model in studying proteins associated with human diseases. Genome-wide genetic screening is a powerful tool ...

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 ...

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences is desired. We herein provide a detailed in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) protocol to study the RNA structural change in the presence of an experimental drug for spinal muscular atrophy (SMA), survival of motor neuron (SMN)-C2, and in exon 7 of the pre-mRNA of the SMN2 gene. In in vitro SHAPE, an RNA sequence of 140 nucleotides containing SMN2 exon 7 is transcribed by T7 RNA polymerase, folded in the presence of SMN-C2, and subsequently modified by a mild 2&#39;-OH acylation reagent, 2-methylnicotinic acid imidazolide (NAI). This 2&#39;-OH-NAI adduct is further probed by a 32P-labeled primer extension and resolved by polyacrylamide gel electrophoresis (PAGE). Conversely, 2&#39;-OH acylation in in-cell SHAPE takes place in situ with SMN-C2 bound cellular RNA in living cells. The pre-mRNA sequence of exon 7 in the SMN2 gene, along with SHAPE-induced mutations in the primer extension, was then amplified by PCR and subject to next-generation sequencing. Comparing the two methodologies, in vitro SHAPE is a more cost-effective method and does not require computational power to visualize results. However, the in vitro SHAPE-derived RNA model sometimes deviates from the secondary structure in a cellular context, likely due to the loss of all interactions with RNA-binding proteins. In-cell SHAPE does not need a radioactive material workplace and yields a more accurate RNA secondary structure in the cellular context. Furthermore, in-cell SHAPE is usually applicable for a larger range of RNA sequences (~1,000 nucleotides) by utilizing next-generation sequencing, compared to in vitro SHAPE (~200 nucleotides) that usually relies on PAGE analysis. In case of exon 7 in SMN2 pre-mRNA, the in vitro and in-cell SHAPE derived RNA models are similar to each other.

Detailed protocols for both in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) experiments to determine the secondary structure of pre-mRNA sequences of interest in the presence of an RNA-targeting small molecule are presented in this article.

利用体外和细胞内形状研究小分子诱导的预 mrna 结构变化

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences ...

Characterizing Histone Post-translational Modification Alterations in Yeast Neurodegenerative Proteinopathy Models

Neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and Parkinson&#39;s disease (PD), cause the loss of hundreds of thousands of lives each year. Effective treatment options able to halt disease progression are lacking. Despite the extensive sequencing efforts in large patient populations, the majority of ALS and PD cases remain unexplained by genetic mutations alone. Epigenetics mechanisms, such as the post-translational modification of histone proteins, may be involved in neurodegenerative disease etiology and progression and lead to new targets for pharmaceutical intervention. Mammalian in vivo and in vitro models of ALS and PD are costly and often require prolonged and laborious experimental protocols. Here, we outline a practical, fast, and cost-effective approach to determining genome-wide alterations in histone modification levels using Saccharomyces cerevisiae as a model system. This protocol allows for comprehensive investigations into epigenetic changes connected to neurodegenerative proteinopathies that corroborate previous findings in different model systems while significantly expanding our knowledge of the neurodegenerative disease epigenome.

This protocol outlines experimental procedures to characterize genome-wide changes in the levels of histone post-translational modifications (PTM) occurring in connection with the overexpression of proteins associated with ALS and Parkinson&#39;s disease in Saccharomyces cerevisiae models. After SDS-PAGE separation, individual histone PTM levels are detected with modification-specific antibodies via Western blotting.

酵母神经退行性蛋白病模型中组蛋白后转化修饰改变的表征

Neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and Parkinson&#39;s disease (PD), cause the loss of hundreds of thousands of lives ...

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely related biochemical pathways. Previous methods such as the Synthetic Genetic Array (SGA) analysis, and random mutagenesis techniques using ultraviolet (UV) or chemicals like ethyl methanesulfonate (EMS) or N-ethyl-N- nitrosourea (ENU), have been widely used but are often costly and laborious. Also, these mutagen-based screening methods are frequently associated with severe side effects on the organism, inducing multiple mutations that add to the complexity of isolating the suppressors. Here, we present a simple and effective protocol to identify suppressor mutations in mutants which confer a growth defect in Schizosaccharomyces pombe. The fitness of cells with a growth deficiency in standard rich liquid media or synthetic liquid media can be monitored for recovery using an automated 96-well plate reader over an extended period. Once a cell acquires a suppressor mutation in the culture, its descendants outcompete those of the parental cells. The recovered cells that have a competitive growth advantage over the parental cells can then be isolated and backcrossed with the parental cells. The suppressor mutations are then identified using whole-genome sequencing. Using this approach, we have successfully isolated multiple suppressors that alleviate the severe growth defects caused by loss of Elf1, an AAA+ family ATPase that is important in nuclear mRNA transport and maintenance of genomic stability. There are currently over 400 genes in S. pombe with mutants conferring a growth defect. As many of these genes are uncharacterized, we propose that our method will hasten the identification of novel functional interactions with this user-friendly, high-throughput approach.

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

We present a simple suppressor screen protocol in fission yeast. This method is efficient, mutagen-free, and&#160; selective&#160; for&#160; mutations that&#160; often&#160; occur at&#160; &#160;a&#160; single&#160; genomic&#160; locus.&#160; The protocol is suitable for isolating suppressors that alleviate growth defects in liquid culture that are caused by a mutation or a drug.

一种在裂变酵母中的深度固序辅助自发抑制屏

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely ...