Name: quantifying plant soluble protein and digestible carbohydrate content, using corn (zea mays) as an exemplar
Uploaded: 2018-08-06T14:30:00.000+00:00
Duration: 7 min 19 s
Description: Watch this Scientific Journal Video about Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar at JoVE.com

多亏了我们所有的合作伙伴, 他们帮助了甜玉米领域的收集, 包括多米尼克 Reisig 和丹莫特在北卡罗来纳州立大学, 和帕特波特在得克萨斯州拉伯克 & M 大学德克萨斯州。多亏菲奥娜 Clissold 帮助优化了协议, 并为这篇手稿提供了编辑。这项工作的一部分是由德州 A & M c Everette Salyer 奖学金 (昆虫学系) 和生物技术风险评估赠款项目2015-33522-24099 来自美国农业部的竞争性赠款 (授予天然气和机顶盒)。

1. 工厂的收集和加工
<ol><li>收集和处理工厂样品<ol>
<li>采集植物样品后, 用镊子将植物材料浸入液氮中, 并贮存在-80 摄氏度。如果收集的植物样品太大, 不能闪光冷冻, 快速冷却样品使用干冰和转移到一个-80 °c 冷藏库尽快。植物材料的营养素含量在组织分离后会发生变化, 在采集后应尽快冷冻植物标本。 警告:液氮在接触皮肤时会引起严重冻伤。请务必在批准的容器中运输液氮, 并在搬运过程中佩戴适当的 PPE, 包括冷冻手套、眼谷歌、面罩、围裙和实验室大衣。</li>
		<li>Lyophilize 植物材料使用冷冻干燥器, 以确保组织在新陈代谢不活跃, 而水被删除。干燥, 直到样品的质量稳定, 以确保所有的水已被删除。</li>
		<li>样品干燥后, 用研磨机或磨粒研磨成细粉。将样品储存在干燥柜中, 直到分析。</li>
	</ol>
</li>
</ol>2. 可溶性蛋白测定法
<ol><li>样品准备<ol>
<li>每个组织的复制样品, 大约20毫克每个, 成1.5 毫升聚苯乙烯离心管和标签管。这些样品随后将被称为未知样品。记录每个样本的确切质量, 因为这些信息将需要计算每个未知样本中的%soluble 蛋白。使用离心管与锁定盖子, 因为非锁定盖可能会打开在随后的加热步骤, 导致样品解决方案的损失。</li>
	</ol></li>
	<li>溶解和分离未知样本蛋白<ol>
<li>使用微 pipettor, 在每管中添加500µL 0.1 米氢氧化钠。关闭盖子严密和油脂实验30分钟。预热热水浴90°c。 警告:氢氧化钠是一种很强的碱基, 在接触皮肤时会引起烧伤。虽然0.1 米氢氧化钠代表低浓度, 佩戴防护手套, 以避免皮肤发炎。</li>
		<li>把管子放在热水浴的架子上15分钟。</li>
		<li>离心管在 1.5万 x g 10 分钟。将上清液注入新标记的离心管, 使用新的吸管尖端为每个样品。将300µL 0.1 米的氢氧化钠添加到含有颗粒和离心机的管中, 再以 1.5万 x g 为10分钟。再次, 收集上清液, 并将其与其他上清液相结合, 从相同的样品。这是一个潜在的停止点, 样品可以存储在4°c 隔夜, 如果需要的话。</li>
	</ol></li>
	<li>沉淀植物蛋白<ol>
<li>加入11µL 5.8 米盐酸盐, 中和上清液的 ph 值. 通过将试金石浸在每个样品溶液中, 确认 ph 为7。 警告:盐酸是一种强腐蚀性酸, 在接触皮肤 (皮肤应用或吸入) 时会引起烧伤。在处理 HCl 时, 请戴上手套防止皮肤发炎。</li>
		<li>添加90µL 100% 乙酸酸 (TCA) 到每管和孵化管在冰上30分钟。蛋白质的沉淀会使溶液从清澈变为不透明。如果30分钟后不发生这种情况, 请将管子冷藏1小时。这是一个潜在的停止点, 样品可以存储在4°c 隔夜, 如果需要的话。 警告:乙酸酸具有腐蚀性。在处理时请戴上手套, 防止皮肤接触, 避免吸入。</li>
		<li>离心机样品在 1.3万 x g 10 分钟在4摄氏度。小心地删除 TCA 上清, 用真空线连接到一个精细的玻璃微提示 (相同的提示可以在样品中使用)。不要干扰蛋白颗粒, 避免重吸力和保持适当的距离之间的吸管尖端和颗粒.
</li>
		<li>用100µL-20 摄氏度丙酮快速清洗颗粒。此步骤从颗粒中除去任何残留的 TCA, 这可能会干扰随后的布拉德福德化验;然而, 丙酮会开始溶解蛋白颗粒如果在接触太长, 所以丙酮应该添加然后迅速提取从颗粒在5秒内。</li>
		<li>通过将管子放在通风罩或冰箱中, 使丙酮蒸发。然后, 在每管中加入1毫升0.1 米氢氧化钠, 溶解蛋白颗粒。充分溶解颗粒可能需要在热水浴, 涡流和 sonicating 几轮加热。 注意: 管子放在油烟机或冰箱里的时间越长, 颗粒的干燥越多, 重新溶解的难度就越大。建议将颗粒干燥30分钟, 然后每10-15 分钟检查一次丙酮的存在, 直到发现丙酮已经蒸发 (没有丙酮烟雾是可检测的)。</li>
	</ol></li>
	<li>混合标准溶液, 稀释未知样本解决方案, 并使用布拉德福德化验定量分析未知样品的总蛋白质含量。<ol>
<li>根据表 1中列出的浓度, 制备牛免疫球蛋白 G (igg) 标准溶液 (冻干或 IgG 溶液可与去离子水混合以达到每浓度)。商店标准在4°c。在96井板中, 在 A1 位置 (0 µg/µL A1、A2、A3 位置、0.0125 µg/µL、B1、B2 位置等) 中, 添加每个 IgG 标准溶液的160µL。</li>
		<li>将50µL 0.1 米氢氧化钠加入950µL 蒸馏水中, 制备稀释的氢氧化钠溶液。作为一个空白的负控制, 添加60µL 的这个解决方案的油井板块 (G1, G2, G3 位置)。</li>
		<li>在新的1.5 毫升离心管中加入50µL, 将每个样品溶液中的950µL 蒸馏水稀释, 制备未知样品。然后, 从 H1 位置开始, 将每个稀释样品的60µL 加成三份。96井板应允许分析6标准, 1 空白, 25 未知样本时, 三个三读。每个井板分析应包含自己的 IgG 标准和空白样品。</li>
		<li>将100µL 的蒸馏水添加到所有空白和未知的样品井中。现在每个井都应该包含160µL. 采用多通道吸管 (8 通道), 将考马斯亮蓝 G-250 蛋白染料的40µL 添加到井板第一柱的每一个井中。将染料与样品混合, 多次暴跌。重复所有其他列, 更换吸管提示, 以避免污染。 警告:考马斯灿烂的蓝色 G-250 是一个刺激性和接触皮肤, 眼睛, 或肺部应避免。请戴上手套防止皮肤接触。如果接触皮肤发生, 此产品将染色。</li>
		<li>使用针来弹出在水井中的任何气泡, 因为它们可能会干扰微板块分光光度计阅读。清洁针头以避免水井之间的污染。让微板块在室温下孵化5分钟。</li>
		<li>使用微板块分光光度计, 记录每个井的吸光度值为 595 nm。</li>
		<li>记录三个空白井的平均吸光度, 并从每个标准和未知样本读数中减去这个值。然后, 记录每个标准和未知样本的平均吸光度。 注意: 要用标准曲线计算每个未知样本中的蛋白质含量, 最容易的方法是将每个标准的平均吸光度与每种标准中的蛋白质微克进行回归, 但你可以绘制蛋白质浓度 (µµL) 每个标准如果可取的。但是, 下面的计算是指基于微克的标准曲线, 而不是浓度 (µg/µL)。</li>
		<li>根据每个标准井中的蛋白质总量, 绘制每个标准的平均吸收量 (表 1)。适合于这些数据的线性回归线, 并根据平均吸收量 (图 1a) 计算每个未知样本中蛋白质 (µg) 的数量。 注: 此线的相关系数 (r值) 应大于 0.98, 通常接近0.99。标准回归将特定于每个板块, 因此每个板块中的未知样本井必须分开分析。</li>
		<li>一旦每个未知样本的平均蛋白质量被计算好, 使用下面的等式来计算每个原始样品中蛋白质 (µg) 的总数量: Mp = ((Wp/60) x 1000)/50) * 1000 Mp = 原样品中蛋白质的µg µg在未知样品井中的蛋白质含量<ol>
<li>然后, 使用以下等式确定每个样本中蛋白质的百分比: pp = ((mp/1000)/Mi) * 100 pp =%protein 在样品中 Mi = 样品的初始质量 (毫克) 注: 在某些情况下, 样品可能超过上吸光度阈值。如果是这样, 样品解决方案可能需要在步骤2.4.3 进一步稀释。 在随后的计算中, 必须对附加的稀释进行核算。一些微板块的读者品牌还提供计算机软件, 将根据标准曲线数据自动计算每个未知样本的平均蛋白质浓度。</li>
		</ol>
</li>
	</ol></li>
</ol>3. 消化碳水化合物的测定
<ol><li>样品准备<ol>
<li>称每个组织的复制样品, 大约20毫克每, 成玻璃15毫升管与橡胶衬里的螺丝盖帽 (100 毫米长度)。这些样本随后将被称为未知样本。标签管与防水标志或标签胶带的盖子和记录的确切质量每个样本, 因为这一信息将需要计算%carbohydrates 在每个未知的样品。</li>
	</ol>
</li>
	<li>从每个未知样品中提取易消化的碳水化合物。<ol>
<li>添加1毫升0.1 米2, 所以4到每个管和螺丝帽上管紧密。在沸腾的水浴中放置1小时。 警告:硫酸是非常腐蚀性的。在处理 H2至4时, 请戴上手套、眼谷歌和围裙, 并在通风罩上执行此步骤。</li>
		<li>在温水浴中冷却管。将管的内容倒入标记为1.5 毫升的离心管 (如果某些植物材料留在玻璃管中, 不要担心)。</li>
		<li>离心管在 1.5万 x g 10 分钟。用微 pipettor 去除上清液, 放入新标记的1.5 毫升离心管。在这一点上, 管子可以冷藏一夜。如果继续化验, 请参阅步骤3.3.2。</li>
	</ol>
</li>
	<li>混合标准溶液并量化未知样品的总易消化碳水化合物含量。<ol>
<li>用表 2中列出的浓度制备 D (+) 葡萄糖标准溶液。准备六玻璃试管与每标准溶液的400µL。</li>
		<li>将每个未知样品的吸管15µL 到其自己的试管中, 并在每个试管中添加385µL 的蒸馏水, 每一个总容积为400µL。在油烟机中, 在每个标准和未知样品试管中加入400µL 5% 苯酚, 然后迅速将2毫升浓缩的 H2如此4注入每管。不要接触试管的内容与吸管尖端, 只是添加到解决方案表面 (一个中继吸管的工作最好的)。</li>
		<li>让管子孵化10分钟, 然后仔细地涡旋管子以混合内容。再孵化30分钟。 警告:苯酚和硫酸是腐蚀性刺激性物质。为了防止暴露于皮肤, 眼睛和吸入, 这一步骤应在化学油烟机使用适当的 PPE, 其中包括: 面罩或护目镜, 橡胶手套, 实验室围裙, 和靴子。苯酚与硫酸混合也会产生放热反应, 这将导致管子变热。</li>
		<li>吸管800µL 样品从每管入每3聚苯乙烯1.5 毫升半微小试管 (每样品3技术复制)。将分光光度计设置为 490 nm。在阅读标准或未知样品之前, 校准到含有蒸馏水的空白试管, 并间歇性地贯穿样品读数。通过分光光度计运行每个试管并记录吸光度。每个未知示例的跨技术复制的平均值。 注: 在某些情况下, 样品可能超过上吸光度阈值。如有, 应在步骤3.2.3 中稀释样品。稀释还必须在随后的计算中加以核算。</li>
		<li>计算每个标准的平均吸光度。 注: 要计算每一个未知样品中的总可消化碳水化合物的含量, 使用标准曲线, 最容易的是将每种标准的平均吸光度从每个标准中的 D (+) 葡萄糖的微克中退去, 但也可以如果需要, 绘制每个标准的 D (+) 葡萄糖浓度 (µg/µL)。但是, 下面的计算是指基于微克的标准曲线, 而不是浓度 (µg/µL)。</li>
		<li>通过绘制每个标准溶液中 D (+) 葡萄糖 (µg) 总量的平均吸光度计算标准曲线。将线性回归线与这些数据匹配, 然后使用以下公式计算每个未知样本中的碳水化合物总量 (µg): Mc = ((Ax -b)/米)/(15)) * 1000 样品中碳水化合物的µg x = 未知样本的平均吸光度 b = y 截距 (标准回归线) m = 斜率 (标准回归线) 该线的相关系数应大于 0.98, 通常接近0.99。然后, 使用以下等式确定每个样本中碳水化合物的百分比: Pc = ((mc/1000)/(mi)) * 100 Pc =%carbohydrates Mi = 样品的初始质量 (毫克)</li>
	</ol>
</li>
</ol>

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W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Food carbohydrates: Chemistry, physical properties, and applications. , (2005).</li><li>Chow, P. S., Landh&#228;usser, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+routine+measurements+of+total+sugar+and+starch+content+in+woody+plant+tissues.">A method for routine measurements of total sugar and starch content in woody plant tissues.</a> Tree Physiology. 24 (10), 1129-1136 (2004).</li><li>Masuko, T., Minami, A., Iwasaki, N., Majima, T., Nishimura, S. I., Lee, Y. 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F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Investigating+a+physical+basis+for+spectroscopic+estimates+of+leaf+nitrogen+concentration.">Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration.</a> Remote Sensing of Environment. 75 (2), 153-161 (2001).</li><li>Schulz, H., Baranska, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+and+quantification+of+valuable+plant+substances+by+IR+and+Raman+spectroscopy.">Identification and quantification of valuable plant substances by IR and Raman spectroscopy.</a> Vibrational Spectroscopy. 43 (1), 13-25 (2007).</li><li>Cozzolino, D., Mor&#243;n, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+potential+of+near-infrared+reflectance+spectroscopy+to+analyse+soil+chemical+and+physical+characteristics.">The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics.</a> The Journal of Agricultural Science. 140, 65-71 (2003).</li><li>Simpson, S. J., Sword, G. A., Lorch, P. D., Couzin, I. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cannibal+crickets+on+a+forced+march+for+protein+and+salt.">Cannibal crickets on a forced march for protein and salt.</a> Proceedings of the National Academy of Sciences of the United States of America. 103 (11), 4152-4156 (2006).</li><li>Lihoreau, M., Buhl, J., Sword, G. A., Raubenheimer, D., Simpson, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nutritional+ecology+beyond+the+individual:+a+conceptual+framework+for+integrating+nutrition+and+social+interactions.">Nutritional ecology beyond the individual: a conceptual framework for integrating nutrition and social interactions.</a> Ecology Letters. 18 (3), 273-286 (2015).</li><li>Deans, C. A., Behmer, S. T., Tessnow, A., Tamez-Guerra, P., Pusztai-Carey, M., Sword, G. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nutrition+affects+insect+susceptibility+to+Bt.">Nutrition affects insect susceptibility to Bt.</a> Scientific Reports. 7, 39705 (2017).</li></ol>

作者没有什么可透露的。

通过将已建立的色度测定方法与有效的植物特异萃取协议相结合, 本文所展示的化验结果为测定植物可溶性蛋白和可消化碳水化合物含量提供了一种合理、准确的检测手段。我们用玉米作为范例的结果说明了这些协议是如何被用来在不同生物相关的空间尺度上获得精确测量的。例如, 我们能够发现植物可溶性蛋白和可消化的碳水化合物含量在地理区域, 品种 (或基因型), 组织类型, 甚至空间隔离组织...

植物生物量构成了几乎所有陆地食物网的基础。植物通过根系获得土壤中的营养成分, 并利用其叶面组织中的阳光合成生物分子。特别是, 碳和氮被用来制造碳水化合物, 蛋白质 (由氨基酸组成), 以及构建植物生物量所需的脂质 (应该指出, 在植物生理学中, "营养素" 一词通常指土壤元素, 如 N,但是, 在整个本文中, 这一术语将提到生物分子, 如蛋白质、碳水化合物和脂质。当草食动物消耗植物材料时, 植物组织中的营养素被分解成它们的组成部分, 然后用来驱动消费者的生理过程。这样, 植物营养素对消费者的生理有很大的影响, 同时对高阶生态交互作用和食物网络动力学也有重要影响。
在动物王国中, 可溶性蛋白质和可消化碳水化合物是与生存、繁殖和性能1密切相关的营养素。此外, 大多数动物积极调节其摄入这两个营养素, 以满足其生理需求1,2。这对于检测植物组织中糖和氨基酸浓度的昆虫草食动物尤其如此, 这反过来又指导饲养行为。因此, 植物可溶性蛋白和可消化碳水化合物含量在植物-昆虫相互作用的演化过程中起着很强的作用。
虽然有关植物可溶性蛋白和可消化碳水化合物含量的数据相对少见 (但见6、7、8、9、10、11), 但有一个优势可提供植物元素含量 (碳、氮、磷) 的数据。这主要是因为元素在植物矿物营养3,4,5起主要作用。在测量元素时, 相互关系被用来推断可溶性蛋白质和可消化碳水化合物的数量, 但准确的计算往往很难获得。例如, 由于碳在所有有机化合物中无所不在存在, 因此不可能使用碳作为植物可消化碳水化合物含量的指示器。元素氮与植物可溶性蛋白质含量之间存在较强的关系, 常采用广义氮-蛋白质转化因子。然而, 有确凿的证据表明, 氮-蛋白质转化是高度物种特定的12,13,14,15, 使得使用广义转换可能错误。因此, 氮-蛋白质转化因子往往缺乏精确度, 特别是对草食动物营养研究所需的程度。此外, 含有氮的植物化感物质, 如生物碱和芥子油苷, 通常对食草动物有毒, 可以混淆这些转换。
在这里, 我们提供了两种化学化验方法来测定植物组织中可溶性蛋白质和可消化碳水化合物的浓度。这些化验结果分别提出, 但建议它们同时用于分析相同的植物样本, 以实现更全面的分析植物营养素。两者都采用类似的方法, 包括提取步骤, 然后通过吸光度量化。对于这两种协议, 植物样品的准备也是相同的, 这使得两种分析的串联都很容易运行。这些化验的效用并不源于他们的新奇, 因为它们依赖于旧的, (布拉德福德, 琼斯,, 和) 建立的比色测定16,17,18, 但在这里我们组织了一个明确的和易于遵循的将这些方法与更模糊的植物特异萃取技术17、19结合在一起的协议, 以便使这些化验的应用更便于植物相关领域的研究。
对于这两种化验, 植物营养素首先通过冷冻, 冻干和研磨的植物材料的物理提取。对于可溶性蛋白质测定, 在氢氧化钠溶液中通过几轮涡流和加热样品, 进一步进行化学萃取17、19 。众所周知的布拉德福德化验, 利用考马斯灿烂的蓝色 G-250, 然后用于量化可溶性蛋白质和多肽之间的 3,000-5, 000 道尔顿16,17。这一检测范围在1-20 µg 总蛋白每微板块井或 < 25 µg/毫升, 但不测量游离氨基酸。消化性碳水化合物的提取步骤是基于 Smith 的稀酸法. 20 , 并允许分离可溶性糖, 淀粉和果聚糖-但不结构碳水化合物。采用苯酚-硫酸定量方法. 18和测量所有单, 寡糖, 和多糖 (以及甲基衍生物)。这种化验可以量化特定的糖, 但在这里, 我们用它作为一个指标, 总可消化碳水化合物的内容 (见史密斯等。20进行更详细的分析)。这些化验结果表明, 这两种营养素与植物生态生理学和草食动物的表现密切相关, 提供了陆地食物网基地资源质量的重要数据。提出这些协议促进了植物营养素数据集的生成, 以获得对植物生理学、草食动物营养生态学和植物食草动物相互作用的更透彻的理解。

<table><tbody><tr><td>microplate reader (spectrophotometer)</td><td>Bio-Rad</td><td>Model 680 XR</td><td></td></tr><tr><td>Bio-Rad Protein Assay Dye Reagent concentrate</td><td>Bio-Rad</td><td>#5000006</td><td>450mL</td></tr></tbody></table>

quantifying plant soluble protein and digestible carbohydrate content, using corn (zea mays) as an exemplar

元素数据通常用于推断植物的质量作为草食动物的资源。然而, 生物分子中的碳无处不在, 含氮植物防御化合物的存在, 以及氮与植物蛋白质含量之间的物种特异相关性的变化, 都限制了这些推断的准确性。此外, 针对植物和/或草食动物生理学的研究需要一种不使用广义相关的准确水平。这里提出的方法为研究人员提供了一个明确而快速的协议, 直接测量植物可溶性蛋白和可消化碳水化合物, 这两种植物营养素与动物的生理性能密切相关。这些协议结合了良好的特性比色测定和优化植物特定的消化步骤, 以提供准确和可重现的结果。我们对不同的甜玉米组织的分析表明, 这些化验对检测植物可溶性蛋白和可消化的碳水化合物含量的变化具有敏感性。这包括不同生长区域和植物种类或品种之间的植物差异, 以及在组织类型上的植物差异, 甚至在同一组织内的位置差异。将可溶性蛋白质和可消化碳水化合物含量与元素数据结合起来, 也有可能为植物生物学提供新的机会, 将植物矿质营养与植物生理过程联系起来。这些分析还有助于生成研究营养生态学、植物食草动物相互作用和食物网络动力学所需的可溶性蛋白质和可消化碳水化合物的数据, 这将反过来促进生理学和生态研究。

为了说明这些方法的实用性, 我们分析了四种不同的田间和甜玉米组织的可溶性蛋白和可消化碳水化合物含量, 为草食性昆虫提供了独特的潜在营养资源。我们收集了来自美国 (明尼苏达州, 北卡罗来纳州, 德克萨斯州) 三个农业地区的玉米穗, 其中包括五种不同品种的甜玉米 (即基因型) 和一个外群的田间玉米品种。表 3显示了这些玉米样品的摘要和收集的...

Watch this Scientific Journal Video about Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar at JoVE.com

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar

以玉米 (玉蜀黍) 为例量化植物可溶性蛋白和可消化碳水化合物含量

本文所描述的协议提供了一种清晰和平易近人的方法来测量植物组织中可溶性蛋白质和可消化 (非结构) 碳水化合物的含量。量化这两种植物营养素的能力对促进植物生理学、营养生态学、植物食草动物相互作用和食物网络生态学等领域具有重要的意义。

Elemental data are commonly used to infer plant quality as a resource to herbivores. However, the ubiquity of carbon in biomolecules, the presence of ...

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Research

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Environment

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn (Zea mays) As an Exemplar

19.7K 次观看.  Texas A&M University. 本文所描述的协议提供了一种清晰和平易近人的方法来测量植物组织中可溶性蛋白质和可消化 (非结构) 碳水化合物的含量。量化这两种植物营养素的能力对促进植物生理学、营养生态学、植物食草动物相互作用和食物网络生态学等领域具有重要的意义。

视频: Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (Zea mays L.)

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole grain composition and processing characteristics vary among maize hybrids and can impact the quality of the final processed product. Therefore, in order to produce healthier processed food products from maize, it is necessary to know how to optimize processing parameters for particular sets of germplasm to account for these differences in grain composition and processing characteristics. This includes a better understanding of how current processing techniques impact the nutritional quality of the final processed food product. Here, we describe a microscale protocol that both simulates the processing pipeline to produce cornflakes from large flaking grits and allows for the processing of multiple grain samples simultaneously. The flaking grits, the intermediate processed products, or final processed product, as well as the corn grain itself, can be analyzed for nutritional content as part of a high-throughput analytical pipeline. This procedure was developed specifically for incorporation into a maize breeding research program, and it can be modified for other grain crops. We provide an example of the analysis of insoluble-bound ferulic acid and p-coumaric acid content in maize. Samples were taken at five different processing stages. We demonstrate that sampling can take place at multiple stages during microscale processing, that the processing technique can be utilized in the context of a specialized maize breeding program, and that, in our example, most of the nutritional content was lost during food product processing.

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Here, we present a microscale protocol for processing grain samples and for incorporating this microscale approach into a high-throughput analytical pipeline. This is a higher throughput adaptation of currently available protocols.

玉米加工参数和营养品质分析的高通量、微尺度协议 (玉蜀黍)

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole ...

科研

环境科学

Lignin Down-regulation of Zea mays via dsRNAi and Klason Lignin Analysis

To facilitate the use of lignocellulosic biomass as an alternative bioenergy resource, during biological conversion processes, a pretreatment step is needed to open up the structure of the plant cell wall, increasing the accessibility of the cell wall carbohydrates. Lignin, a polyphenolic material present in many cell wall types, is known to be a significant hindrance to enzyme access. Reduction in lignin content to a level that does not interfere with the structural integrity and defense system of the plant might be a valuable step to reduce the costs of bioethanol production. In this study, we have genetically down-regulated one of the lignin biosynthesis-related genes, cinnamoyl-CoA reductase (ZmCCR1) via a double stranded RNA interference technique. The ZmCCR1_RNAi construct was integrated into the maize genome using the particle bombardment method. Transgenic maize plants grew normally as compared to the wild-type control plants without interfering with biomass growth or defense mechanisms, with the exception of displaying of brown-coloration in transgenic plants leaf mid-ribs, husks, and stems. The microscopic analyses, in conjunction with the histological assay, revealed that the leaf sclerenchyma fibers were thinned but the structure and size of other major vascular system components was not altered. The lignin content in the transgenic maize was reduced by 7-8.7%, the crystalline cellulose content was increased in response to lignin reduction, and hemicelluloses remained unchanged. The analyses may indicate that carbon flow might have been shifted from lignin biosynthesis to cellulose biosynthesis. This article delineates the procedures used to down-regulate the lignin content in maize via RNAi technology, and the cell wall compositional analyses used to verify the effect of the modifications on the cell wall structure.

Lignin Down-regulation of Zea mays via dsRNAi and Klason Lignin Analysis

A double stranded RNA interference (dsRNAi) technique is employed to down-regulate the maize cinnamoyl coenzyme A reductase (ZmCCR1) gene to lower plant lignin content. Lignin down-regulation from the cell wall is visualized by microscopic analyses and quantified by the Klason method. Compositional changes in hemicellulose and crystalline cellulose are analyzed.

木质素下调<em&gt;玉米</em&gt;通过dsRNAi和Klason木质素分析

To facilitate the use of lignocellulosic biomass as an alternative bioenergy resource, during biological conversion processes, a pretreatment step is ...

生物工程

Estimation of Crystalline Cellulose Content of Plant Biomass using the Updegraff Method

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a significant role in plant growth and development by providing strength, rigidity, rate and direction of cell growth, cell shape maintenance, and protection from biotic and abiotic stressors. The cell wall is primarily composed of cellulose, lignin, hemicellulose and pectin. Recently plant cell walls have been targeted for the second-generation biofuel and bioenergy production. Specifically, the cellulose component of the plant cell wall is used for the production of cellulosic ethanol. Estimation of cellulose content of biomass is critical for fundamental and applied cell wall research. The Updegraff method is simple, robust, and the most widely used method for the estimation of crystalline cellulose content of plant biomass. The alcohol insoluble crude cell wall fraction upon treatment with Updegraff reagent eliminates the hemicellulose and lignin fractions. Later, the Updegraff reagent resistant cellulose fraction is subjected to sulfuric acid treatment to hydrolyze the cellulose homopolymer into monomeric glucose units. A regression line is developed using various concentrations of glucose and used to estimate the amount of the glucose released upon cellulose hydrolysis in the experimental samples. Finally, the cellulose content is estimated based on the amount of glucose monomers by colorimetric anthrone assay.

The Updegraff method is the most widely used method for the cellulose estimation. The main purpose of this demonstration is to provide a detailed Updegraff protocol for estimation of cellulose content in plant biomass samples.

使用上格拉夫方法估计植物生物质的晶体纤维素含量

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a ...

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

Extraction and Quantification of Soluble, Radiolabeled Inositol Polyphosphates from Different Plant Species using SAX-HPLC

The phosphate esters of myo-inositol, also termed inositol phosphates (InsPs), are a class of cellular regulators playing important roles in plant physiology. Due to their negative charge, low abundance and susceptibility to hydrolytic activities, the detection and quantification of these molecules is challenging. This is particularly the case for highly phosphorylated forms containing &#8216;high-energy&#8217; diphospho bonds, also termed inositol pyrophosphates (PP-InsPs). Due to its high sensitivity, strong anion exchange high-performance liquid chromatography (SAX-HPLC) of plants labeled with [3H]-myo-inositol is currently the method of choice to analyze these molecules. By using [3H]-myo-inositol to radiolabel plant seedlings, various InsP species including several non-enantiomeric isomers can be detected and discriminated with high sensitivity. Here, the setup of a suitable SAX-HPLC system is described, as well as the complete workflow from plant cultivation, radiolabeling and InsP extraction to the SAX-HPLC run and subsequent data analysis. The protocol presented here allows the discrimination and quantification of various InsP species, including several non-enantiomeric isomers and of the PP-InsPs, InsP7 and InsP8, and can be easily adapted to other plant species. As examples, SAX-HPLC analyses of Arabidopsis thaliana and Lotus japonicus seedlings are performed and complete InsP profiles are presented and discussed. The method described here represents a promising tool to better understand the biological roles of InsPs in plants.

Here we describe strong anion exchange high-performance liquid chromatography of [3H]-myo-inositol-labeled seedlings which is a highly sensitive method to detect and quantify inositol polyphosphates in plants.

使用SAX-HPLC从不同植物物种中提取和定量可溶性、放射性标记肌醇多磷酸盐

The phosphate esters of myo-inositol, also termed inositol phosphates (InsPs), are a class of cellular regulators playing important roles in plant ...

Comprehensive Compositional Analysis of Plant Cell Walls (Lignocellulosic biomass) Part II: Carbohydrates

The need for renewable, carbon neutral, and sustainable raw materials for industry and society has become one of the most pressing issues for the 21st century. This has rekindled interest in the use of plant products as industrial raw materials for the production of liquid fuels for transportation2 and other products such as biocomposite materials6. Plant biomass remains one of the greatest untapped reserves on the planet4. It is mostly comprised of cell walls that are composed of energy rich polymers including cellulose, various hemicelluloses, and the polyphenol lignin5 and thus sometimes termed lignocellulosics. However, plant cell walls have evolved to be recalcitrant to degradation as walls contribute extensively to the strength and structural integrity of the entire plant. Despite its necessary rigidity, the cell wall is a highly dynamic entity that is metabolically active and plays crucial roles in numerous cell activities such as plant growth and differentiation5. Due to the various functions of walls, there is an immense structural diversity within the walls of different plant species and cell types within a single plant4. Hence, depending of what crop species, crop variety, or plant tissue is used for a biorefinery, the processing steps for depolymerisation by chemical/enzymatic processes and subsequent fermentation of the various sugars to liquid biofuels need to be adjusted and optimized. This fact underpins the need for a thorough characterization of plant biomass feedstocks. Here we describe a comprehensive analytical methodology that enables the determination of the composition of lignocellulosics and is amenable to a medium to high-throughput analysis (Figure 1). The method starts of with preparing destarched cell wall material. The resulting lignocellulosics are then split up to determine its monosaccharide composition of the hemicelluloses and other matrix polysaccharides1, and its content of crystalline cellulose7. The protocol for analyzing the lignin components in lignocellulosic biomass is discussed in Part I3.

Comprehensive Compositional Analysis of Plant Cell Walls Lignocellulosic biomass Part II: Carbohydrates

Plant biomass is a major carbon-neutral renewable resource that could be used for the production of biofuels. Plant biomass consists mainly of cell walls, a structurally complex composite material termed lignocellulosics. Here we describe a protocol for a comprehensive analysis of the content and composition of wall derived carbohydrates.

综合植物细胞壁成分分析（木质纤维素生物质）第二部分：碳水化合物

The need for renewable, carbon neutral, and sustainable raw materials for industry and society has become one of the most pressing issues for the 21st ...

生物学

High-throughput Saccharification Assay for Lignocellulosic Materials

Polysaccharides that make up plant lignocellulosic biomass can be broken down to produce a range of sugars that subsequently can be 
used in establishing a biorefinery. These raw materials would constitute a new industrial platform, which is both sustainable and carbon neutral, to replace 
the current dependency on fossil fuel. The recalcitrance to deconstruction observed in lignocellulosic materials is produced by several intrinsic properties 
of plant cell walls. Crystalline cellulose is embedded in matrix polysaccharides such as xylans and arabinoxylans, and the whole structure is encased by the 
phenolic polymer lignin, that is also difficult to digest 1. In order to improve the digestibility of plant materials we need to discover the main bottlenecks 
for the saccharification of cell walls and also screen mutant and breeding populations to evaluate the variability in saccharification 2. These tasks require 
a high throughput approach and here we present an analytical platform that can perform saccharification analysis in a 96-well plate format. This platform has 
been developed to allow the screening of lignocellulose digestibility of large populations from varied plant species. We have scaled down the reaction volumes 
for gentle pretreatment, partial enzymatic hydrolysis and sugar determination, to allow large numbers to be assessed rapidly in an automated system.
This automated platform works with milligram amounts of biomass, performing ball milling under controlled conditions to reduce the plant 
materials to a standardised particle size in a reproducible manner. Once the samples are ground, the automated formatting robot dispenses specified and recorded 
amounts of material into the corresponding wells of 96 deep well plate (Figure 1). Normally, we dispense the same material into 4 wells to have 4 replicates for 
analysis. Once the plates are filled with the plant material in the desired layout, they are manually moved to a liquid handling station (Figure 2). In this 
station the samples are subjected to a mild pretreatment with either dilute acid or alkaline and incubated at temperatures of up to 90&deg;C. The pretreatment solution 
is subsequently removed and the samples are rinsed with buffer to return them to a suitable pH for hydrolysis. The samples are then incubated with an enzyme
mixture for a variable length of time at 50&deg;C. An aliquot is taken from the hydrolyzate and the reducing sugars are automatically determined by the MBTH 
colorimetric method.

A simple, rapid method for determining the saccharification potential of large numbers of plant biomass samples is described. The automated platform for this analysis involves the preparation of the plant biomass for analysis in 96 well plates and the subsequent performance of pretreatment, hydrolysis and quantification of the sugars released.

木质纤维素材料的高通量检测糖化

Polysaccharides that make up plant lignocellulosic biomass can be broken down to produce a range of sugars that subsequently can be 
used in establishing ...

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Measuring quantitative plant phenotypes, or traits, is essential for understanding plant responses to environmental factors, including biotic and abiotic stresses. However, traditional methods of measuring plants can be time-consuming, inaccurate, and destructive, particularly when assessing traits such as biomass and height on an individual basis. Image-based analysis offers an opportunity to reduce labor, improve accuracy and precision, and enable repeated measurements of the same plant over multiple time points. While high-throughput phenotyping facilities provide a solution, they are often prohibitively expensive and limited in availability worldwide. A method is described for capturing plant images using low-cost single-board computers and digital cameras within a photo studio setup, accompanied by an image analysis pipeline based on the free and open-source package PlantCV. This method offers a fast and accurate protocol for image capture, labeling, and transfer, along with best practices for ensuring high-quality image acquisition. Through image analysis, more than 10 phenotypes were quantified for all images in the experiment simultaneously, including traits such as plant size, height, and color. These methods were used to characterize the response of the Zea mays (maize) inbred variety B73 to heat, drought, and combined heat and drought abiotic stress conditions.

A method is presented for low-cost imaging of plants to measure phenotypes, along with best practices for image capture and an image analysis pipeline for quantifying plant traits. These methods were applied to measure maize (Zea mays) phenotypes under heat, drought, and combined abiotic stress conditions.

定量玉米 （Zea mays） 非生物胁迫表型的成像和分析

Measuring quantitative plant phenotypes, or traits, is essential for understanding plant responses to environmental factors, including biotic and abiotic ...

Soluble Protein Assay to Quantify Soluble Protein Content in Plant Tissues

Source: Deans, C. A. et al. <a href="https://app.jove.com/v/58164">Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn (Zea mays) As an Exemplar.</a> J. Vis. Exp. (2018)
This video describes a colorimetric method to quantify the soluble protein content in plant tissues. The method uses Coomassie Brilliant Blue G-250 dye, which interacts with the soluble protein to form a blue-colored stable protein-dye complex, proportional to the soluble protein content in the tissue.

可溶性蛋白测定法定量植物组织中的可溶性蛋白含量

Source: Deans, C. A. et al. Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn (Zea mays) As an Exemplar. J. Vis. Exp. ...

JoVE Encyclopedia of Experiments

Biological Techniques

Assay Techniques

Biochemical assays

Colorimetric Assay for the Quantification of Non-Structural Carbohydrates in Plant Tissues

Source: Deans, C. A. et al. <a href="https://app.jove.com/v/58164">Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn (Zea mays) As an Exemplar.</a> J. Vis. Exp. (2018).
This video describes the method to quantify the digestible carbohydrates present in plant tissues. This helps to collect data from various plant tissues to study nutritional ecology, plant-herbivore interactions, and food-web dynamics.

以玉米 (玉蜀黍) 为例量化植物可溶性蛋白和可消化碳水化合物含量

摘要

探索更多视频

此视频中的章节

玉米加工参数和营养品质分析的高通量、微尺度协议 (玉蜀黍)

木质素下调

使用上格拉夫方法估计植物生物质的晶体纤维素含量

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

使用SAX-HPLC从不同植物物种中提取和定量可溶性、放射性标记肌醇多磷酸盐

综合植物细胞壁成分分析（木质纤维素生物质）第二部分：碳水化合物

木质纤维素材料的高通量检测糖化

定量玉米（Zea mays）非生物胁迫表型的成像和分析

可溶性蛋白测定法定量植物组织中的可溶性蛋白含量

用于定量植物组织中非结构性碳水化合物的比色测定

以玉米 (玉蜀黍) 为例量化植物可溶性蛋白和可消化碳水化合物含量

摘要

探索更多视频

此视频中的章节

玉米加工参数和营养品质分析的高通量、微尺度协议 (玉蜀黍)

木质素下调

使用上格拉夫方法估计植物生物质的晶体纤维素含量

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

使用SAX-HPLC从不同植物物种中提取和定量可溶性、放射性标记肌醇多磷酸盐

综合植物细胞壁成分分析（木质纤维素生物质）第二部分：碳水化合物

木质纤维素材料的高通量检测糖化

定量玉米 （Zea mays） 非生物胁迫表型的成像和分析

可溶性蛋白测定法定量植物组织中的可溶性蛋白含量

用于定量植物组织中非结构性碳水化合物的比色测定

定量玉米（Zea mays）非生物胁迫表型的成像和分析