作者感谢格雷松巴特勒和玛格丽特-巴雷特帮助进行实验, 朱迪石头的建议谷物均匀化, 和林恩汉努姆征求意见的荧光。这项工作得到了国家科学基金会 (IOB 0443676) 的支持, 由国立卫生研究院国立医学研究院颁发的机构发展奖 (P20GM0103423), 以及赠款来自科尔比学院自然科学分部。

1. 效应器和报告基因构造的制备
<ol><li>构建使用本构启动子 (如玉米泛素, UBI) 的效应器构造, 以从所需的开放阅读框架中驱动表达式。例如, 构造一个包含UBI::TaABF1的质粒, 以驱动 TaABF15的强本构表达式。</li>
	<li>生成包括要测量其活动的启动器的报告器结构, 放置在打开的阅读框架的上游, 如GUS。例如, 构造一个包含HVA1::GUS的质粒, 用于测量从HVA1启动子2,5的表达式。</li>
	<li>生成内部控件构造 (例如UBI::荧光素酶)。</li>
	<li>使用硅胶绑定列协议 (参见材料表), 为每个必需的基因构造准备高质量的质粒。使用紫外光谱 (参见材料表), 仔细测量每种质粒制备的浓度。</li>
</ol>2. 为轰炸准备大麦谷物
<ol><li>设置电子表格 (请参见图 1 ), 指出将被轰炸的质粒、适当的激素治疗以及将作为实验一部分的每种治疗的其他相关信息。</li>
	<li>使用切割板和无菌剃刀刀片, 从喜马拉雅大麦的谷物中切下胚胎 (试验中包括的每种治疗 40)。排除变色或大大小于平均值的谷物。</li>
	<li>将所有的 embryoless 颗粒放入50毫升管中。加入40毫升的水和岩石10分钟。</li>
	<li>仔细倒入水 (以避免失去谷物), 并添加40毫升10% 漂白剂。摇滚20分钟。</li>
	<li>倒出漂白剂, 加入40毫升的无菌水。摇滚5分钟。重复这种无菌水洗四次。</li>
	<li>添加40毫升的饮用溶液 (20 毫米琥珀酸钠, 20 毫米氯化钙, pH 5.0) 和 40 ul 的氯霉素库存溶液 (10 毫克/毫升)。</li>
	<li>将大部分的饮用溶液 (与氯霉素) 从管子转移到蛭石板 (参见材料表)。然后将谷物转移到蛭石板上湿滤纸的表面。均匀地分散谷物。倒入足够的饮用溶液, 使谷物部分 (但不完全) 淹没。把盖子放在蛭石板的顶部。</li>
	<li>用萤光灯孵化24摄氏度的 embryoless 颗粒, 大约48小时。必要时添加其他饮用解决方案。</li>
	<li>打开一个90毫米塑料培养皿和倒入20毫升的饮用溶液到盘子本身和20毫升进入倒盖。添加 20 ul 的氯霉素 (10 毫克/毫升)。用酒精浸泡两对细点钳。</li>
	<li>将一些 embryoless 谷物放入培养皿的盖子中。使用镊子, 轻轻地去除每粒谷物 (透明) 的种子大衣。从谷物的平滑面除去种子外衣时, 不要损害底层 (糊粉层) 细胞。将去皮的谷物转移到含有饮用溶液的培养皿中。</li>
	<li>剥去所有谷物的种子后, 把它们放回蛭石板上。将去皮的 embryoless 颗粒孵化24摄氏度, 16-20 小时。</li>
	<li>就在使用谷物进行轰炸之前, 通过在培养皿中的滤纸之间摇动来去除表面水分。</li>
</ol>3. 用于轰击的质粒 DNA 的制备
<ol><li>标记一个1.5 毫升管为每个治疗, 将包括在轰炸实验。对每个管添加2.5 µg 的UBI::荧光素酶内部控制质粒, 2.5 µg GUS报告质粒, 以及所需的量 (通常0.025 µg 到2.5 µg) 的效应质粒。加水, 使总容积达5µL。</li>
	<li>在发布的协议6之后, 准备1.6 µm 金载体 (参见材料目录)。</li>
	<li>对于每种治疗, 添加50µL 的悬浮载体到1.5 毫升管含有质粒 DNA。根据制造商的协议6, 将载体与质粒 DNA 一起涂上。</li>
	<li>在最后一步, 当质粒涂层的载体悬浮在48µL 100% 乙醇, 吸管 8 ul 悬浮载体到每五 macrocarriers 和允许他们空气干燥。</li>
</ol>4. Embryoless 大麦颗粒的微粒轰击
<ol><li>设置粒子轰击装置 (请参阅材料表)6。</li>
	<li>将 1550 psi 破裂盘放入固定帽, 并将其安装在仪器上。</li>
	<li>将含有所需质粒组合 (连同停止屏幕) 的 macrocarrier 放入载体发射组件中。将组件插入到轰击室的顶槽中。设置在标准距离 (6 毫米) 处的破裂盘护盖与 macrocarrier 盖盖之间的距离, 并将停止屏幕支持置于 (标准) 中间位置, 允许 macrocarrier 旅行距离为 11 mm (图 2A)。</li>
	<li>将 8 embryoless 颗粒排列在一个紧的径向模式下 (用较薄的一端指向内侧) 在滤纸圈上, 将其固定在一个 90 mm 培养皿的盖子上 (参见图 2B)。</li>
	<li>放置菜与五谷入炮击房间, 在距离从停止的屏幕 6 cm。</li>
	<li>将轰炸室疏散至95帕, 然后轰击样品。</li>
	<li>释放真空后, 将被轰击的谷物转移到一个标记为60毫米的培养皿中, 含有4毫升的饮用溶液, 含有氯霉素的1毫克/毫升。</li>
	<li>重复, 直到所有的轰炸已经完成。孵育 (在一个震动平台在 100 rpm) 在24°c 24 小时。</li>
</ol>5. 从轰击颗粒中提取可溶性蛋白质
<ol><li>使用镊子, 从60毫米的培养皿中取出8个被轰击的谷物, 并将它们涂抹在纸巾上晾干。将谷物分成两个标记为2.0 毫升的管子 (每管4粒), 每个含800个 ul 研磨缓冲器 (100 毫米 Na 磷酸盐 pH 值 7.2, 5 毫米, µg/毫升 leupeptin, 10 甘油) 和20% 毫米不锈钢珠。对所有被轰击的谷物重复这个过程。</li>
	<li>将 (最多 48) 2.0 毫升管放入珠均质机的两个机架上 (请参阅材料表)。将机架安装在均质机上。</li>
	<li>在30赫兹处摇动样品3分钟。</li>
	<li>从均质机卸下均质机架, 并将其放在冰上 (5 分钟) 以重新冷却样品。</li>
	<li>将机架重新安装在均质上-在相反的方向上。再次摇动样品在30赫兹3分钟。</li>
	<li>冷却在冰上的架子, 然后重复步骤5.3 到5.5。这将增加总共12分钟的震动。</li>
	<li>离心机的谷物提取物在 1.6万 x g 在4°c 10 分钟。</li>
	<li>
立即离心后, 醒酒清除上清液成第二组离心管。给每个管子一个快速的漩涡。把管子储存在冰上。</li>
	<li>转移上清液后, 从小球中回收钢珠, 以便清洗和再利用。</li>
</ol>6. 从谷物提取物中测定荧光素酶活性
<ol><li>要测定每个谷物提取管, 准备一个12毫米 x 75 毫米玻璃试管, 其中含有 200 ul 的荧光素酶检测混合物 (45 毫米三硫酸酯 pH 值 7.7, 15 毫米氯化镁2, 20 毫米, 1.5 毫米 EDTA, 1 毫米荧光素, 1 毫米 ATP)。</li>
	<li>将第一粒提取物的 100 ul 添加到第一检测管中。涡旋迅速搅拌良好。立即将管置于紫外线的管架中, 并关闭门。当测量完成后, 从紫外线中取下管子--让门打开, 以便放置下一管。</li>
	<li>重复此过程, 直到测量完所有样品。</li>
</ol>7. 谷物提取物中 GUS 活性的测定
<ol><li>添加 200 ul 的 GUS 化验缓冲器 (50 毫米 Na 磷酸盐 pH 7.2, 2.5 毫米 4-甲基伞形酮-葡糖苷酸, 10 毫米, 2 毫米 EDTA, 10 µg/毫升 leupeptin, 20% 甲醇, 0.02% 钠氮) 的每一个井的96个井板。</li>
	<li>将每个谷物提取物的 50 ul 放置到相应的井中。添加后与提示混合。用密封膜密封顶部。</li>
	<li>在37摄氏度在黑暗中孵化96井板20小时。</li>
	<li>离心机96井板在 4000 x g 在4°c 10 分钟并且安置它在冰。</li>
	<li>添加 250 ul 0.2 M Na2CO3到每个井的黑色96井板。</li>
	<li>将每离心 GUS 检测混合物的 6.25 ul 添加到相应的井中 (包含0.2 米 Na2CO3) 的黑色96井板。添加后与提示混合。包括水井与 6.25 ul 10 微米, 40 微米, 100 微米 4-甲基伞形酮作为标准。</li>
	<li>把黑盘子放进盘子荧光计, 读甲基伞形酮的荧光。以 360 nm 的激发波长和 460 nm 的发射波长进行读数。设置仪器的增益, 使含有 6.25 ul 的40微米 4-甲基伞形酮和 250 ul 的 0.2 MNa2CO 3 的油井读数为1000年荧光单位。</li>
</ol>8. 数据分析
<ol><li>在电子表格中输入荧光素酶和 GUS 化验的值。排除从考虑任何样本与荧光素酶读数低于2万相对发光单位 s-1, 因为这表明, 基因构造没有成功地传递到糊粉层细胞。</li>
	<li>对于每个成功轰击的谷物萃取物 (代表一组四 embryoless 谷物), 从原始 gus 和荧光素酶数据中计算规范化的 gus 表达式如下: 规范化 gus = [(gus 表达式 gus 空白) x (200万)]/(荧光素酶表达-荧光素酶空白)。 注意: 这将 GUS 活动的数量正常化为在一次轰炸中观察到的东西, 使荧光素酶读数为200万。</li>
	<li>报告一个特定的记者结构的相对水平在存在的效应构造或激素治疗正在测试通过比较的表现水平, 在没有效应或荷尔蒙。</li>
</ol>

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作者没有什么可透露的。

通过粒子轰击引入效应基因构造, 其次是记者构造的瞬态表达, 是解剖特定行为者在 GA/ABA 信号中的作用以及由此产生的激素调控基因的宝贵策略。表达. 然而, 在大麦糊粉层单元格中进行此类实验的现有 协议2, 3, 4, 5, 6 是非常劳力密集.每组被轰击的颗粒必须在砂浆和杵中手...

大麦糊粉层层是植物激素调控基因表达研究的一个成熟的模型系统1。特别是, 一些需要发芽或早期幼苗发育的基因由赤霉素 (GA) 激活, 而与应激反应相关的基因则由脱落酸 (ABA) 激活。ga 和 aba 信号通路是交织在一起的, 因为一些 ga 激活基因的表达被 ABA 抑制, 反之亦然1。
了解特定行为者在 GA/ABA 信号中的作用的一个有价值的策略是通过粒子轰击引入效应基因构造, 接着是记者构造的瞬态表达, 从而使结果影响下游基因表达的确定。使用报告基因, 如GUS (β-glucuronidase) 或荧光素酶允许对基因表达式的敏感和定量测量, 特别是在接收到效应器结构的细胞内。例如, 引入了一个对转录因子 TaABF15,6编码的效应器构造, 它建立了 ABA 诱导的基因, 如HVA1是由 TaABF1 诱导的, 而 GA 诱导的基因, 如Amy32b被压抑。粒子轰击作为一种实验策略已被多个实验室用来研究遗传/ABA 信号的不同方面。这项工作已导致识别启动子元素重要的激活两个 GA 诱导的2和 ABA 诱导的基因3, 并发现蛋白激酶4和转录因子5 , 调节这些基因的表达。
现有协议2,3,4,5,6为粒子轰击和随后的瞬态基因表达测量是相当劳动密集型的, 因为每套轰炸在砂浆和杵中, 几乎没有谷物是均匀的, 酶的测定是单独进行的。这篇手稿报告了一个改进的协议, 部分自动化和优化均匀化步骤和 GUS 化验, 以允许大量的吞吐量, 允许更多的治疗在同一实验中测试, 和/或包含更多的复制, 每种治疗获得更有统计学意义的结果。代表的结果显示为HVA1和Amy32b报告器构造的表达式, 由转录因子 TaABF1 以及 GA、ABA 和其他调控分子调控。

<table><tbody><tr><td>GeneElute HP plasmid Maxiprep kit</td><td>Sigma</td><td>NA0310-1KT</td><td></td></tr><tr><td>UV-vis spectrophotometer</td><td>Nanodrop</td><td>ND-1000</td><td></td></tr><tr><td>Himalaya barley grains</td><td>/</td><td>/</td><td>A variety of hulless barley (store in the dark at 4&amp;deg; C)</td></tr><tr><td>sodium succinate</td><td>Sigma</td><td>S2378</td><td>Reagent for Imbibing Solution</td></tr><tr><td>calcium chloride (dihydrate)</td><td>Fisher</td><td>C79-500</td><td>Reagent for Imbibing Solution</td></tr><tr><td>Imbibing Solution</td><td>home made</td><td>/</td><td>20 mM sodium succinate, 20 mM calcium chloride, pH 5.0. Sterilize by autoclaving before use.</td></tr><tr><td>chloramphenicol</td><td>Sigma</td><td>C0378</td><td>Prepare a 10 mg/mL stock solution in 70% ethanol.</td></tr><tr><td>vermiculite</td><td>Fisher</td><td>NC0430369</td><td>Used for vermiculite plates.</td></tr><tr><td>filter paper circles (90 mm)</td><td>Whatman</td><td>1001 090</td><td>Used for vermiculite and for pre-bombardment grain preparation</td></tr><tr><td>Vermiculite Plates</td><td>home made</td><td>/</td><td>Add 50 mL of vermiculite to a glass petri dish. Place a 90 mm paper circle on top of the vermiculite. Autoclave.</td></tr><tr><td>forceps (fine pointed)</td><td>Fisher</td><td>13-812-42</td><td>Used for removing seed coat from barley grains.</td></tr><tr><td>forceps (ultra fine point)</td><td>Fisher</td><td>12-000-122</td><td>Used for removing seed coat from barley grains.</td></tr><tr><td>gold microcarriers (1.6 &amp;mu;m)</td><td>BioRad</td><td>1652264</td><td></td></tr><tr><td>macrocarriers</td><td>BioRad</td><td>1652335</td><td></td></tr><tr><td>calcium chloride (dihydrate)</td><td>Fisher</td><td>C79-500</td><td>Prepare a 2.5 M stock solution and store 1 mL aliquots at -20&amp;deg; C.</td></tr><tr><td>spermidine</td><td>Sigma</td><td>S0266</td><td>Prepare a 100 mM stock solution and store 500 &amp;mu;L aliquots at -20&amp;deg; C (use within 2 months).</td></tr><tr><td>rupture discs (1550 psi)</td><td>BioRad</td><td>1652331</td><td></td></tr><tr><td>stopping screens</td><td>BioRad</td><td>1652336</td><td></td></tr><tr><td>macrocarrier holders</td><td>BioRad</td><td>1652322</td><td></td></tr><tr><td>Biolistic particle delivery system</td><td>BioRad</td><td>PDS-1000/He</td><td></td></tr><tr><td>sodium phosphate monobasic monohydrate</td><td>Sigma</td><td>S9638</td><td>Reagent for 1M sodium phosphate pH 7.2</td></tr><tr><td>sodium phosphate dibasic</td><td>Sigma</td><td>S9763</td><td>Reagent for 1M sodium phosphate pH 7.2</td></tr><tr><td>1M sodium phosphate pH 7.2</td><td>home made</td><td>/</td><td>Combine 6.9 g of sodium phosphate monobasic monohydrate with 7.1 g of sodium phosphate dibasic. Add water to 100 mL. Add NaOH to get pH 7.2.</td></tr><tr><td>dithiothrietol (DTT)</td><td>Sigma</td><td>43819</td><td>Dissolve in water to 1 M. Store at -20&amp;deg; in 1 mL aliquots.</td></tr><tr><td>leupeptin</td><td>Sigma</td><td>L2884</td><td>Dissolve in water to 10 mg/mL. Store at -20&amp;deg; C.</td></tr><tr><td>glycerol</td><td>Sigma</td><td>G5516</td><td>Prepare a 50% solution in water.</td></tr><tr><td>Grinding Buffer</td><td>home made</td><td>/</td><td>Combine 10 mL of 1 M sodium phosphate pH 7.2, 500 &amp;mu;L of 1 M DTT, 100 &amp;mu;L of 10 mg/mL leupeptin, and 40 mL of 50% glycerol. Add water to 100 mL.</td></tr><tr><td>stainlesss steel beads (5 mm)</td><td>Qiagen</td><td>69989</td><td></td></tr><tr><td>2.0 mL tubes</td><td>Eppendorf</td><td>22363352</td><td>This specific model of tube is recommended for use with the homogenizer.</td></tr><tr><td>bead homogenizer (TissueLyser)</td><td>Qiagen</td><td>85210</td><td></td></tr><tr><td>12mm x 75 mm glass test tubes</td><td>Fisher</td><td></td><td></td></tr><tr><td>luciferin</td><td>Goldbio</td><td>LUCK-100</td><td>Prepare a 25 mM stock solution and store 1 mL aliquots at -20&amp;deg; C.</td></tr><tr><td>ATP</td><td>Sigma</td><td>A7699</td><td>Prepare a 100 mM stock solution and store 250 &amp;mu;L aliquots at -20&amp;deg;&amp;nbsp;C.</td></tr><tr><td>Tris base</td><td>Sigma</td><td>T1503</td><td>Reagent for 1M Tris sulfate pH 7.7.</td></tr><tr><td>sulfuric acid</td><td>Sigma</td><td>258105</td><td>Reagent for 1M Tris sulfate pH 7.7.</td></tr><tr><td>1M Tris sulfate pH 7.7</td><td>home made</td><td>/</td><td>Dissolve 12.1 g Tris base in 100 mL of water. Adjust pH to 7.7 with sulfuric acid.</td></tr><tr><td>magnesium chloride</td><td>Sigma</td><td>M9397</td><td>Dissolve in water to 2 M.</td></tr><tr><td>Luciferase Assay Buffer (LAB)</td><td>home made</td><td>/</td><td>Combine 3 mL of 1 M Tris sulfate pH 7.7, 500 &amp;mu;L of 2 M magnesium chloride, 1 mL of 1 M DTT, and 200 &amp;mu;L of 0.5 M EDTA. Add water to 50&amp;nbsp;mL.</td></tr><tr><td>Luciferase Assay Mixture</td><td>home made</td><td>/</td><td>Combine 15 mL of LAB, 800 &amp;mu;L of 25 mM luciferin, 200 &amp;mu;L of 100 mM ATP, and 4 mL of water. This makes enough assay mixture (20&amp;nbsp;mL) for 100 luciferase assays.</td></tr><tr><td>luminometer (Sirius)</td><td>Berthold</td><td>/</td><td></td></tr><tr><td>4-methylumbelliferyl-&amp;beta;-D-glucuronide (MUG)</td><td>Goldbio</td><td>MUG1</td><td>Dissolve in DMSO to 100 mM.</td></tr><tr><td>sodium azide</td><td>Sigma</td><td>S8032</td><td>Prepare a 2% stock solution in water and store 1 mL aliquots at -20&amp;deg; C.</td></tr><tr><td>96 well plates (standard)</td><td>Fisher</td><td>12565501</td><td></td></tr><tr><td>GUS assay buffer</td><td>home made</td><td>/</td><td>Combine 2.5 mL of MUG, 5 mL of 1 M sodium phosphate pH 7.2, 400 &amp;mu;L of 0.5 M EDTA, 1 mL of 1 M DTT, 100 &amp;mu;L of 10 mg/ml leupeptin, 20 mL of methanol, and 1 mL of 2% sodium azide. Add water to 100 mL.</td></tr><tr><td>TempPlate sealing film</td><td>USA Scientific</td><td>2921-1000</td><td></td></tr><tr><td>96 well plates (black)</td><td>Costar</td><td>3916</td><td></td></tr><tr><td>sodium carbonate</td><td>Sigma</td><td>S7795</td><td>Prepare a 200 mM solution in water.</td></tr><tr><td>4-methylumbelliferone</td><td>Sigma</td><td>M1381</td><td>Prepare a 100 &amp;mu;M solution in water. Freeze 1 mL aliquots at -20&amp;deg;&amp;nbsp;C.</td></tr><tr><td>microplate fluouresence reader</td><td>Bio-Tek</td><td>FLX-800</td><td></td></tr></tbody></table>

measuring gene expression in bombarded barley aleurone layers with increased throughput

大麦籽粒糊粉层层是植物激素调控基因表达的重要模型体系。在糊粉层细胞中, 萌发或早期幼苗发育所需的基因由赤霉素 (GA) 激活, 而与应激反应相关的基因则由脱落酸 (ABA) 激活。通过粒子轰击引入糊粉层细胞的基因构造, 可以对 GA 和 ABA 信号的机制进行审问, 并利用酶法测定结果的瞬态表达。报告了一种改进的协议, 部分自动化和简化了谷物均匀化步骤和酶的测定, 使吞吐量大大超过现有方法。采用全自动组织均质器进行谷物样品的均匀化, 用96井板系统进行 GUS (β glucuronidase) 测定。使用该协议的代表性结果表明, 磷脂酶 D 活性可以发挥重要作用, 激活HVA1基因表达的 ABA, 通过转录因子 TaABF1。

本文所描述的技术可用于将任何试验基因结构引入大麦籽粒的糊粉层细胞中。然后可以方便地测量测试基因的表达水平 (图 2)。这里描述的高吞吐量协议大大提高了种子研磨和酶测定步骤的效率。该方法已用于评估转录因子 TaABF15、6的能力, 以激活 ABA 诱导的基因HVA17的表达。在这里...

Watch this Scientific Journal Video about Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput at JoVE.com

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

提出了一种改进的协议, 用于测量粒子轰击后大麦糊粉层细胞中的瞬时基因表达。采用全自动谷物研磨与96井板酶检测相结合, 为该过程提供了较高的吞吐量。

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 ...

measuring-gene-expression-bombarded-barley-aleurone-layers-with

Universidad de Cartagena UDEC

Research

JoVE Journal

Genetics

6.4K 次观看.  Colby College. 提出了一种改进的协议, 用于测量粒子轰击后大麦糊粉层细胞中的瞬时基因表达。采用全自动谷物研磨与96井板酶检测相结合, 为该过程提供了较高的吞吐量。

视频: Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

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

Complex changes in gene expression typically mediate a large portion of a cellular response. Each gene may change expression with unique kinetics as the gene is regulated by the particular timing of one of many stimuli, signaling pathways or secondary effects. In order to capture the entire gene expression response to hypoxia in the yeast S. cerevisiae, RNA-seq analysis was used to monitor the mRNA levels of all genes at specific times after exposure to hypoxia. Hypoxia was established by growing cells in ~100% N2 gas. Importantly, unlike other hypoxic studies, ergosterol and unsaturated fatty acids were not added to the media because these metabolites affect gene expression. Time points were chosen in the range of 0 - 4 h after hypoxia because that period captures the major changes in gene expression. At each time point, mid-log hypoxic cells were quickly filtered and frozen, limiting exposure to O2 and concomitant changes in gene expression. Total RNA was extracted from cells and used to enrich for mRNA, which was then converted to cDNA. From this cDNA, multiplex libraries were created and eight or more samples were sequenced in one lane of a next-generation sequencer. A post-sequencing pipeline is described, which includes quality base trimming, read mapping and determining the number of reads per gene. DESeq2 within the R statistical environment was used to identify genes that change significantly at any one of the hypoxic time points. Analysis of three biological replicates revealed high reproducibility, genes of differing kinetics and a large number of expected O2-regulated genes. These methods can be used to study how the cells of various organisms respond to hypoxia over time and adapted to study gene expression during other cellular responses.

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

Here, we present a protocol using RNA-seq to monitor mRNA levels over time during the hypoxic response of S. cerevisiae cells. This method can be adapted to analyze gene expression during any cellular response.

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 ...

科研

遗传学

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 ...

Isolation of High Purity Tissues from Developing Barley Seeds

Understanding the mechanisms regulating the development of cereal seeds is essential for plant breeding and increasing yield. However, the analysis of cereal seeds is challenging owing to the minute size, the liquid character of some tissues, and the tight inter-tissue connections. Here, we demonstrate a detailed protocol for dissection of the embryo, endosperm, and seed maternal tissues at early, middle, and late stages of barley seed development. The protocol is based on a manual tissue dissection using fine-pointed tools and a binocular microscope, followed by ploidy analysis-based purity control. Seed maternal tissues and embryos are diploid, while the endosperm is triploid tissue. This allows the monitoring of sample purity using flow cytometry. Additional measurements revealed the high quality of RNA isolated from such samples and their usability for high-sensitivity analysis. In conclusion, this protocol describes how to practically dissect pure tissues from developing grains of cultivated barley and potentially also other cereals.

Here we present a protocol for high purity manual isolation and quality control of embryo, endosperm and seed maternal tissues during entire barley seed development.

Understanding the mechanisms regulating the development of cereal seeds is essential for plant breeding and increasing yield. However, the analysis of ...

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

The characterization of gene expression is dependent on RNA quality. In germinating, developing and mature cereal seeds, the extraction of high-quality RNA is often hindered by high starch and sugar content. These compounds can reduce both the yield and the quality of the extracted total RNA. The deterioration in quantity and quality of total RNA can subsequently have a significant impact on the downstream transcriptomic analyses, which may not accurately reflect the spatial and/or temporal variation in the gene expression profile of the samples being tested. In this protocol, we describe an optimized method for extraction of total RNA with sufficient quantity and quality to be used for whole transcriptome analysis of cereal grains. The described method is suitable for several downstream applications used for transcriptomic profiling of developing, germinating, and mature cereal seeds. The method of transcriptome profiling using a microarray platform is shown. This method is specifically designed for gene expression profiling of cereals with described genome sequences. The detailed procedure from microarray handling to final quality control is described. This includes cDNA synthesis, cRNA labelling, microarray hybridization, slide scanning, feature extraction, and data quality validation. The data generated by this method can be used to characterize the transcriptome of cereals during germination, in various stages of grain development, or at different biotic or abiotic stress conditions. The results presented here exemplify high-quality transcriptome data amenable for downstream bioinformatics analyses, such as the determination of differentially expressed genes (DEGs), characterisation of gene regulatory networks, and conducting transcriptome-wide association study (TWAS).

A method for transcriptome profiling of cereals is presented. The microarray-based gene expression profiling starts with the isolation of high-quality total RNA from cereal grains and continues with the generation of cDNA. After cRNA labelling and microarray hybridization, recommendations are given for signal detection and quality control.

通过基因表达分析的改良方法从谷物种子获取高质量的转录数据

The characterization of gene expression is dependent on RNA quality. In germinating, developing and mature cereal seeds, the extraction of high-quality ...

生物化学

Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections.

We report a method for introduction, tracking and quantitative analysis of GFP expression in plant cells. This method utilizes a custom-designed robotics system for semi-continuous image collection from large numbers of samples, over time. We also demonstrate the use of ImageJ and ImageReady for analysis of image series.

机器人技术和植物组织的基因表达研究的动态图像分析

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods ...

生物学

A Cell-to-cell Macromolecular Transport Assay in Planta Utilizing Biolistic Bombardment

Here, we present a simple and rapid protocol to detect and assess the extent of cell-to-cell macromolecular transport in planta. In this protocol, a fluorescently tagged-protein of interest is transiently expressed in plant tissue following biolistic delivery of its encoding DNA construct. The intra- and intercellular distribution of the tagged protein is then analyzed by confocal microscopy. We describe this technology in detail, providing step-by-step protocols to assay and evaluate the extent of symplastic protein transport in three plant species, Arabidopsis thaliana, Nicotiana benthamiana and N. tabacum (tobacco).

A Cell-to-cell Macromolecular Transport Assay in Planta Utilizing Biolistic Bombardment

Macromolecular trafficking between plant cells can be assessed by transiently expressing a fluorescently-tagged protein of interest and analyzing its intra- and intercellular distribution by confocal microscopy.

细胞的细胞大分子运输检测在植物利用基因枪法

Here, we present a simple and rapid protocol to detect and assess the extent of cell-to-cell macromolecular transport in planta. In this protocol, a ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

条形码酵母图书馆竞争力的基因屏幕

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing

The powerful tools available to edit yeast genomes have made this microbe a valuable platform for engineering. While it is now possible to construct libraries of millions of genetically distinct strains, screening for a desired phenotype remains a significant obstacle. With existing screening techniques, there is a tradeoff between information output and throughput, with high-throughput screening typically being performed on one product of interest. Therefore, we present an approach to accelerate strain screening by adapting single cell RNA sequencing to isogenic picoliter colonies of genetically engineered yeast strains. To address the unique challenges of performing RNA sequencing on yeast cells, we culture isogenic yeast colonies within hydrogels and spheroplast prior to performing RNA sequencing. The RNA sequencing data can be used to infer yeast phenotypes and sort out engineered pathways. The scalability of our method addresses a critical obstruction in microbial engineering.

A bottleneck in the &#8216;design-build-test&#8217; cycle of microbial engineering is the speed at which we can perform functional screens of strains. We describe a high-throughput method for strain screening applied to hundreds to thousands of yeast cells per experiment that utilizes droplet-based RNA sequencing.

高通量酵母菌株，带基于滴滴的RNA测序

The powerful tools available to edit yeast genomes have made this microbe a valuable platform for engineering. While it is now possible to construct ...

生物工程

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 ...

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

The development of a complex multicellular organism is governed by distinct cell types that have different transcriptional profiles. To identify transcriptional regulatory networks that govern developmental processes it is necessary to measure the spatial and temporal gene expression profiles of these individual cell types. Therefore, insight into the spatio-temporal control of gene expression is essential to gain understanding of how biological and developmental processes are regulated. Here, we describe a laser-capture microdissection (LCM) method to isolate small number of cells from three barley embryo organs over a time-course during germination followed by transcript profiling. The method consists of tissue fixation, tissue processing, paraffin embedding, sectioning, LCM and RNA extraction followed by real-time PCR or RNA-seq. This method has enabled us to obtain spatial and temporal profiles of seed organ transcriptomes from varying numbers of cells (tens to hundreds), providing much greater tissue-specificity than typical bulk-tissue analyses. From these data we were able to define and compare transcriptional regulatory networks as well as predict candidate regulatory transcription factors for individual tissues. The method should be applicable to other plant tissues with minimal optimization.

Presented here is a protocol for laser-capture microdissection (LCM) of plant tissues. LCM is a microscopic technique for isolating areas of tissue in a contamination-free manner. The procedure includes tissue fixation, paraffin embedding, sectioning, LCM and RNA extraction. RNA is used in the downstream tissue-specific, temporally resolved analysis of transcriptomes.