这篇手稿的发展得到了国家科学基金会 EPSCoR Rhizobiome 创新奖 OIA-1557417 中心的支持。数据收集得到了内布拉斯加大学-林肯分校、农业研究和发展基金以及美国农业部提供的孵化补助金的资助。我们也承认美国农业部提供的支持, 农业和食品研究倡议2011-68005-30411 号竞争性赠款来自美国农业部粮食和农业研究所, 以建立和管理这些领域。

1. 现场介绍
<ol><li>在收集期间描述实验现场站点。使用 GPS 确定域 (纬度、经度和高度) 的位置。</li>
	<li>描述取样深度、取样时间和土壤质地。</li>
	<li>环境因素对微生物群落的形成起着重要的作用。记录气候信息, 如年平均气温、年降水量、往年作物轮作、耕作做法、施肥方法和现场历史。自动气象站或其他设备是有用的记录每天的降雨量和气温在一个生长季节。</li>
</ol>2. 土壤、根际和根场样品的收集和处理
<ol><li>植物的挖掘。<ol>
<li>将洗涤盘和水桶贴上标签, 其中包含有关要取样的植物材料的信息。包括绘图号、植物基因型和植物种类等信息。将标签桶带到绘图区, 并将洗涤盘放在现场的固定工作站后面。</li>
		<li>用铲子刺穿土壤, 深度为30厘米, 以切割在土壤中保持植物的任何侧根。近似体积为18厘米3。随机选择和收集两个植物每个情节从不同的区域内的情节。</li>
		<li>利用铲子挖掘植物根系, 将根球放在标记的桶中。把被挖掘的根球带上标记的水桶回到现场的工作站。切断和丢弃地上植物的生物量。</li>
	</ol>
</li>
	<li>从根部清除土壤和收集大块土。<ol>
<li>摇动根部, 手动移除土壤或使用铁锹或手持的分蘖从根部去除土壤。摇动根部足以去除非常沙土中的土壤。在加工站附近戴上手套并放置根部。</li>
		<li>摇根后, 土壤的大部分将在洗涤锅里。在洗涤盘中混合土壤, 用手持的分蘖分解任何泥土。将不含碎片的泥土样本放置在标签的 17.7 x 19.5 厘米拉链储存袋中, 放置在阴凉处或冰上。</li>
	</ol>
</li>
	<li>根和根际的汇集。<ol>
<li>使用修剪剪刀消毒在70% 乙醇, 消费的各种根, 大约4到6根每株植物和每个根约 9-12 厘米长度。将切除根 (切割所需的) 放置在含有35毫升蒸压的标签50毫升管中, 磷酸盐缓冲器 (6.33 克/升 NaH2PO4, 8.5 克/升 Na2HPO4无水, pH = 6.5, 200 µl/升表面活性剂)。 注: 表面活性剂 (见材料表) 在热处理磷酸盐缓冲液后添加。根球的体积和根长度的变化取决于植物的年龄和植物种类。</li>
		<li>摇管2分钟, 从根部表面释放根际。用镊子在70% 乙醇消毒, 去除根从管, 在纸巾上涂抹, 并放置在一个新的, 标记为50毫升管。把包含根际的管和含有根的管子放在冰上。</li>
	</ol>
</li>
</ol>3. 实验室现场样品的处理
<ol><li>田间采集后根部的表面灭菌。 注: 从现场返回后, 应尽快进行表面杀菌。如果不可能在同一天表面消毒根, 贮存根在4摄氏度, 直到处理。<ol>
<li>添加大约35毫升50% 漂白剂 + 0.01% 吐温20到50毫升根管收集在该领域。摇动50毫升管30到60秒。倒入50% 漂白剂, 加入35毫升70% 乙醇。再摇30到60秒。</li>
		<li>倒入70% 乙醇, 加入35毫升无菌、超纯水。摇1分钟。重复水洗两次。 注: 为了确保我们的表面灭菌处理是足够的, 我们镀样品的水从上次冲洗和观察没有增长的细菌 (p. 王, 未发表的数据, 2014)。其他调查人员使用类似方法9、10测试了根杀菌效率。</li>
		<li>在干净的纸巾上涂抹根干。对每个样品使用干净的纸巾。 注: 纸巾在使用前可以消毒。我们不消毒纸巾。然而, 我们使用1纸巾每样品和保持毛巾包装, 直到使用。</li>
		<li>使用无菌钳和修剪剪刀, 把根切成大约5毫米, 并将切割根部放在一个干净的, 标记为15毫升圆锥管。将样品贮存在摄氏-80 摄氏度, 直至进一步加工。</li>
	</ol>
</li>
	<li>加工根际样品。<ol>
<li>摇动50毫升管, 包含根际样品从田间并用重悬整个样品。使用无菌, 100 µm 网状细胞过滤器 (见材料表), 过滤悬浮样品到一个新的50毫升管。</li>
		<li>在室温下离心管在 3000 x g 处5分钟。立即倒掉并丢弃上清。</li>
		<li>将根际颗粒放在50毫升的冰管中。加入1.5 毫升无菌磷酸盐缓冲液 (不含表面活性剂) 到根际颗粒和涡旋悬浮。</li>
		<li>将悬浮液吸管到一个干净的, 标记的, 2 毫升的离心管。在室温下, 旋转管在 15871 x g 处为2分钟。立即倒入上清, 并将管子排在干净的纸巾上。</li>
		<li>将小球储存在-20 摄氏度, 直到进一步加工。 注: 步骤 3.2.2-3.2.4, 以减少样品管大小的存储。与50毫升管相比, 存储较小的2毫升管的空间效率更高。</li>
	</ol>
</li>
	<li>处理土壤样品进行 DNA 提取和土壤分析。<ol>
<li>使用无菌金属铲, 填充一个干净, 标记2毫升管约3克的土壤 DNA 提取。避免任何小的根碎片和碎片。将土壤样品贮存在摄氏-20 摄氏度。在每个样品之间冲洗70% 乙醇金属刮刀。</li>
		<li>在一个干净的洗涤锅里, 把泥土袋空成堆积的筛子 (见材料表), 在较小的筛子上方筛上较大的筛子, 并通过两个筛子手工筛选土壤。用刷子仔细清洗样品之间的筛子。</li>
		<li>在 17.7 x 19.5 厘米的拉链袋中预留100到125克的被筛土壤, 用于未来土壤理化和纹理分析。将土壤袋放置在4摄氏度, 用于短期贮存。</li>
	</ol>
</li>
	<li>土壤水分的土壤样品处理。<ol>
<li>将一个标有褐色的纸袋包装在秤上。测量40到 45 g 被筛的土壤入褐色纸袋子。将棕色纸袋和土壤的重量记录在数据表上, 并将袋子放在烘干烤箱中, 设置为 55-60 摄氏度。</li>
		<li>72小时后, 从烘干烤箱中取出袋子。让土壤袋冷却至少30分钟, 然后权衡。</li>
		<li>要记录重量, 请将刻度减至零, 并将棕色纸袋放在刻度上。使用公式计算每个样品的土壤含水量百分比: <img alt="Equation" src="/files/ftp_upload/57932/57932eq1v2.jpg"> 注: 土壤水分法是从凯洛格生物站长期生态研究 (LTER)。知识库 LTER 为其网站上的研究人员提供了广泛的既定协议 (https://Lter.kbs.msu.edu/)。</li>
	</ol>
</li>
</ol>4. 制备用于 DNA 提取的加工根样。
<ol><li>研磨冷冻根材料, 使样品均匀。<ol>
<li>将液氮倒入塑料烧杯中, 用干净的铲子, 在干净的砂浆和杵中, 使样品在整个研磨过程中冻结。</li>
		<li>将冷冻组织放入砂浆中, 用杵研磨成细粉。不断地在研磨过程中添加液氮以保持样品冷冻。</li>
		<li>用刮刀将地面组织放置在一个干净的, 标记为2毫升的管。存储在-80 摄氏度。</li>
	</ol>
</li>
</ol>5. 96 井格式提取土壤和根际样品中的 DNA
<ol><li>将土壤样品装入96井板中。<ol>
<li>用70% 乙醇和1% 漂白剂擦拭工作区域。在这些步骤中佩戴实验室手套。从-20 摄氏度的储藏中取出土壤样品, 并允许在冰桶中解冻。</li>
		<li>从带有 DNA 提取试剂盒的96井萃取板上取下密封垫盖。将密封垫盖在2纸巾之间, 在不使用时保持清洁。为避免污染, 使用8井胶粘剂的 PCR 条覆盖96井萃取板12柱。</li>
		<li>将一个不育的重量漏斗 (大小 SM) 在一个刻度上, 并将200到250毫克的土壤称量出来。 注: 这些无菌漏斗在一侧扁平, 因此漏斗在鳞片上平整。漏斗被泥土填满, 直接放进井里。这种技术避免了样品的丢失, 减少了溢出, 防止了交叉污染。</li>
		<li>要揭开萃取板的第一井, 小心地提起胶条, 将填充的称重漏斗的颈部放在适当的井中, 轻轻地将土壤样品引导到适当的井中。更换胶条盖好。</li>
		<li>重复这个过程的每一个良好的板块, 使用一个新的, 不育漏斗为每个样品, 直到该板块填充。保留一个井空作为提取空白控件。 注: 每个萃取板上都留有一个井, 作为负 (空白) 控制。对试剂盒试剂11中可能存在的污染物的控制。</li>
		<li>在萃取板上更换密封垫盖, 并将该板材贮存在-20 摄氏度, 直到准备好进行 DNA 提取。</li>
	</ol>
</li>
	<li>将根际样品装入96井板中。<ol>
<li>从-20 摄氏度的储藏中去除根际样品, 并允许在冰桶中解冻。</li>
		<li>按照以上步骤5.1.2 准备 DNA 提取板。</li>
		<li>将干净的纸擦在秤上, 然后将无菌金属铲抹在秤上。用刮刀小心地从样品管中挖出一些根际颗粒。把刮刀退回到鳞片上, 并在根际样品的200和250毫克之间称量。</li>
		<li>小心地提起胶条, 揭开萃取板的第一井, 将填充的铲入井中, 用无菌牙签将根际物质刮入适当的井中。</li>
		<li>在水中冲洗金属铲, 然后在样品间乙醇70%。对板块的每一个井重复这个过程, 直到盘子填满, 留下一个井空作为提取空白控制。</li>
	</ol>
</li>
	<li>96井格式提取根际和土壤样品中的 DNA。<ol>
<li>利用为土壤优选的试剂盒提取土壤和根际 DNA (见材料表), 遵循制造商的协议。 注意: 我们使用这个特定的试剂盒来隔离土壤和根际 DNA, 因为专有试剂能够去除土壤中的腐植酸和其他功能强大的 PCR 抑制剂。</li>
	</ol>
</li>
	<li>DNA 量化。<ol>
<li>根据制造商的协议, 量化92样品和4浓度标准 (见材料表; 标准包括在内)。</li>
		<li>根据制造商的协议, 将剩余的4个样品从盘子中取出, 以容纳四标准的水井 (见材料表)。</li>
	</ol>
</li>
</ol>6. 从根样品中提取96井格式的 DNA。
<ol><li>将根样品装入96井板中。<ol>
<li>用70% 乙醇和1% 漂白剂擦拭工作区域。在这些步骤中戴上手套。</li>
		<li>把样品放在桶里, 放在干冰里, 保持地面根部的样品冻结。</li>
		<li>用液氮填充塑料烧杯, 在塑料烧杯中放置抗静电 microspatulas 和无菌称重漏斗 (尺寸 XSM) 降温。</li>
		<li>从带套件的96井萃取珠板上取下密封垫盖, 并将其放在2纸巾之间, 在不使用时保持清洁。 注意: 此套件的更新版本, 在我们进行这些 DNA 提取的时间之后发布, 要求用户提供提取珠板。在材料表中, 我们列出了订购这些物料所需的供应商目录信息。</li>
		<li>为避免污染, 使用8井胶粘剂的 PCR 条覆盖96井萃取板12柱。</li>
		<li>将萃取珠板放在干冰上, 将样品保存在井中冷冻。</li>
		<li>小心地提起胶条, 揭开萃取板的第一井, 将填充的称重漏斗的颈部放入适当的井中, 再加入3勺地根组织。更换胶条盖好。 注: 在称重之前, 土壤和根际在冰上解冻, 而植物材料则被重冷冻。冷冻植物组织, 尤其是少量的, 很难在不解冻的情况下进行秤重。在基层组织进行了重量测试, 以确定有多少铲勺是足够的。请注意, 该套件的制造商不需要确切数量的组织, 但建议约50毫克. 不同的植物样本类型将有所不同, 用户将需要确定适当的数量。</li>
		<li>对板块的每一个井重复这个过程, 直到盘子填满。</li>
		<li>储存板在-20 °c, 直到准备 DNA 提取。</li>
	</ol>
</li>
	<li>根组织的 DNA 提取。<ol>
<li>根据制造商的协议, 用为植物优化的套件 (见材料表) 提取 DNA。 注意: 我们使用这个套件专门为植物组织, 以达到最大产量从根样品。与土壤和根际不同的是, 腐植酸和其他污染物对根系组织的问题较小。</li>
	</ol>
</li>
	<li>将 DNA 量化为步骤5.4。</li>
</ol>7. 放大和测序分离的 DNA。
<ol><li>用证明阅读聚合酶 (见材料表) 放大16S 基因的 V4 区域, 如 Gohl等。12条码样品与不同的索引底漆和池排序前。序列使用 Gohl et al12描述的方法使用两步 PCR 过程与 V4 引物 (补充文件 1)。 注意: 这些步骤的一些方法在其他12、13、14中详细描述, 因此不会在此描述。对于根样本, 添加肽拮抗剂, 以减少质 DNA 的数量从植物组织, 这已经被充分描述15。在测序中使用了两个控制, 一个负控制, 其中包括萃取板空白控制 (参见步骤5.1.5 后的注意事项), 以及已知细菌 DNA 种群的模拟社区 (见材料表), 作为一个积极的控制。 注意: 在大多数情况下, MiSeq 试剂盒 v3 用于 2 X 300 基配对端模式。对于本手稿中的样品, Illumina HiSeq 2500 用于快速模式与250配对端 (2 x 250) 模式。所有样品都在同一条车道上测序。</li>
	<li>通过管道进行微生物群落分析 (USEARCH v9.2.64、QIIME v1.9.1 和 RStudio v3.4.3 16) 处理测序数据。<ol>
<li>使用 USEARCH17准备排序数据。 注: USEARCH 可在线提供完整的说明 (https://www.drive5.com/usearch/)。</li>
		<li>使用索引读取或条形码解排序数据, 以将 Illumina 读取分配给示例。</li>
		<li>合并配对端读取以获得一致的序列。使用命令: usearch-fastq_mergepairs * R1 * fastq 重新标记备选 @ fastq_maxdiffs 10-fastq_minmergelen 230-fastq_maxmergelen 320-fastq_pctid 80-fastqout 合并。 注意: 参数是通过引用 USEARCH 指令手册来设置的。</li>
		<li>从测序数据中除去引物, 以避免在底漆序列中进行替代, 这可能是由 PCR 反应引起的。使用命令: usearch-fastx_truncate 合并. stripleft 19-stripright 20-fastqout 剥离。</li>
		<li>过滤测序数据以去除低质量的读数并保持高质量的操作分类单元 (OTU) 序列。使用命令: usearch-fastq_filter 剥离. fastq_maxee 1.0-fastaout 过滤。</li>
	</ol>
</li>
	<li>在 USEARCH 中生成 OTUs。<ol>
<li>执行 dereplication 以标识唯一的 OTU 序列集。使用命令: usearch fastx_uniques 筛选 fastaout 独有 sizeout 重新标记备选。</li>
		<li>群集 OTUs 与 97-100% 序列相似性, 以指定唯一的 OTUs。使用命令: usearch-cluster_otus 独有 minsize 2-otus otus 重新标记备选。 注意: 此步骤还包括从群集 OTUs 中移除单克隆, 并将合体从排序数据中移除。</li>
		<li>在 USEARCH 中创建一个 OTU 表。使用命令: usearch-usearch_global 被剥去. otus. 发线 + id 0.97-otutabout otutable.txt。 注意: 此命令生成一个表, 其中每个示例的所有 OTUs 的读取次数 (计数) 数。OTU 表用于下游步骤, 包括差异丰度分析和微生物多样性分析。OTU 表的示例显示在补充图2中。</li>
		<li>在 QIIME v1.9.1 18进行稀疏分析。 注: 稀疏曲线是用 OTU 表计算的, 以确定测序的深度是否正确地取样了微生物群落。稀疏曲线的示例显示在补充图 3中。</li>
		<li>进行阿尔法多样性分析18。在 QIIME v1.9.1 中使用 alpha_rarefaction 来计算每个样本中微生物群落的多样性。 注意: 此分析计算多样性指数, 如香农19、辛普森20和 Chao121。</li>
		<li>进行 beta 多样性分析18,22。使用 Python 脚本: beta_diversity_through_plots QIIME v1.9.1 Bray–Curtis 相异矩阵。 注: 本分析比较了样品间的微生物群落组成。</li>
		<li>对各组进行统计分析。使用 PERMONOVA 计算的距离矩阵, 使用阿尼斯和方差分析功能在纯素包装23 v2.4.5 在 RStudio16。使用纯素包装中的 capscale 函数对主坐标 (CAP) 分析进行规范化分析。在 RStudio 中使用 ggplot2 包24 v2.2.1 可视化数据。</li>
	</ol>
</li>
</ol>

<ol>
	<li>Philippot, L., Raaijmakers, J. M., Lemanceau, P., vander Putten, W. 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作者没有什么可透露的。

本手稿中描述的方法应能使科学家容易进入土壤和植物 metagenomics 的领域。多年来, 我们已经改进了我们的方法, 因为进行了这篇手稿中描述的实验。一个改变是, 我们现在预先标签的管, 然后走出去的领域样本。我们的实验室使用条形码系统和标签打印机。标签打印机不仅节省了标签管的时间, 而且使所有的东西更容易跟踪和正确识别样本, 而不反复无常的人类手写。另一个关键点是, 我们试图处理的材料后, 尽快从外地回来。我们的目的是冻结用于 DNA 分析的土壤, 对根部进行消毒和冷冻, 并在从田间返回后12小时内过滤和冻结根际。dna 提取程序是漫长的许多步骤, 特别是对土壤和根际, 所以我们购买了机器人 (翠鸟 Flex, ThermoFisher), 最大限度地减少手的 dna 提取协议, 减少人类的错误, 可能会引入,并改善了不同批次的土壤、根或根际处理方式的一致性。在使用植物材料时, 确定要研究的根类型或采取各种根类型来获得 "代表性样本" 是很重要的。在进行 dna 提取时, 保持根和叶子处于冰冻状态是很重要的, 因为在填充96井 dna 萃取板时, 样品之间没有交叉污染。另一个需要考虑的重要因素是在设计野外试验时使用的复制次数, 并在可能的情况下使用完整的随机设计26。由于高场变异性, 可能需要大量的复制来检测小的差异。最后, 根据我们的经验, 在挖掘树根时确保土壤不太湿是必不可少的。如果土壤是饱和的水, 它不仅是混乱的工作, 但它也很难定义的根际和清除土壤从根。
在开发这些方法的早期进行的一项修改是, 而不是用手工摇动管子来释放我们升级到 vortexers 的根际, 以使该领域的工作更容易, 并在更标准化的方面每管被搅动的时间和方式。扩增子测序方法的一个局限性是, 结果的分类解析通常是有限的, 许多 OTUs 是未知的, 或者只在家庭或属的水平上知道。这一研究领域正在迅速发展, 因此必须认识到新的和发展的方法, 特别是数据分析, 这可能会提高结果的分辨率。
这些协议只用于研究细菌和古菌, 而不是真菌。使用不同的引物进行扩增将允许研究真菌群落使用相同的 DNA 样本27,28。这些方法不需要购买大量的设备, 因为这些方法可以简化。我们在这里描述的方法主要是确定 "谁在那里", 但该领域正在迅速演变为问有关功能的重要问题, 这可能是通过使用猎枪排序方法, 隔离和测试功能微生物, 或测序整个微生物基因组。
代表的结果突出了微生物群落的差异, 可以用所描述的方法来识别。在数据分析22中使用 beta-多样性方法, 在样本类型之间显示了成分差异。在 endosphere、根际和土壤中含有独特的微生物群落3的大多数其他研究中都清楚地看到了这些差异。计算了香农多样性指数, 确定了 endosphere、根际和土壤中各植物种类中微生物种类的丰度和均匀性。如本研究所示, 在许多其他方面, 阿尔法多样性在土壤中最高, 在根际略有下降, 然后在 endosphere3,5,29显著减少。这些结果表明, 本文所描述的方法适用于识别 endosphere、根际和土壤中的成分变化。
Proteobacteria的优势是 endosphere 和土壤30、31、32研究中的一个常见发现。Endosphere 的微生物种类普遍较低, Proteobacteria的相对丰度较高。这再次突显出, 这里的结果代表了文献中的其他发现。这项研究的治疗效果没有显著差异, 这两个主要原因可能是, 治疗所施加的差异不够大, 无法产生足够的变异来检测, 而且这种取样是在生长季节, 当田地可能有充足的时间把氮气绘制到类似的水平, 这是在本赛季结束时测量的。在另一项研究中, 使用相同的施肥率在较长的时间内, 只有相对较小的变化, 微生物的组成被测量33。其他研究表明, 由于氮肥34,35, 真菌和细菌群落的变化。
已知植物种类在确定其微生物3、32、36时发挥作用, 甚至在不同植物基因型之间的微生物群落变异之间存在微小差异。单一物种37。在本研究中, 植物物种间的微生物群落组成存在显著差异。在所有的样本类型中, 柳枝稷具有最明显的微生物组成, 但在 endosphere 中, 物种间的差异仅有统计学意义。如果有更多的复制可供分析, 根际群落组成可能变得很重要。
这里描述的联合野外、实验室和分析协议为研究不同因素对土壤、根际和 endosphere36的微生物群落组成的影响提供了有力的方法。在研究微生物方面, 特别是在农业领域, 还有大量工作要做。关于土壤微生物量如何改变产量的重要问题尚未得到充分阐明。甚至关于作物轮作如何影响土壤微生物的最基本问题, 时间如何改变微生物群, 非生物胁迫如何改变微生物群, 土壤类型如何与这些因素相互作用来改变微生物, 以及是否有美国某些农作物或地区的普遍微生物都是开放的问题。这些方法也将有助于流行病学研究, 以确定致病和有益细菌的存在和持续。这些方法的另一个未来地平线将是开始整合这里描述的 DNA 方法与植物和微生物 RNA 和代谢物数据。对更多的变量进行进一步的改进和测试对于进一步优化这些协议将是非常重要的。

微生物研究对于理解和操纵生态系统过程, 如养分循环、有机质周转和土壤病原体的发育或抑制有重要意义1、2。这一研究领域也为了解土壤微生物对自然植物群落和农田生产力的影响提供了巨大的潜力。尽管有许多研究集中在自然生态系统中的土壤微生物群中, 但在农田3中, 对植物根际和 endosphere 微生物的关注较少。在内布拉斯加州, 农业主导着整个州大部分地区的景观, 对这些土壤进行研究, 农业上重要的农作物成为研究的重要课题。本方法的目的是为研究人员提供一组标准的协议来描述农田中的微生物, 以确定植物根系如何改变根际和 endosphere 的微生物群落, 并最终了解这些微生物在土壤健康和植物生产力中发挥的作用。
此处提出的方法与其他4、5中使用的方法略有不同, 因为本文旨在了解哪些微生物完全位于根内, 以及它们与直接在根外的微生物有何不同。根 际。本研究中使用的扩增子测序确定了 DNA 样本中发现的微生物分类, 并允许调查人员根据样本类型或治疗来确定群落的变化。此协议与 Lundberg 所使用的非常相似的协议之间的关键区别之一 。6是, 这个协议使用表面杀菌与漂白剂和乙醇去除根际根的超声波。其他还使用了有效的表面杀菌7,8,9,10。这些方法比其他方法更有利, 但略有不同。这些方法特别适合于大型野外试验, 因为有足够的人每天可以处理超过150场地块, 在划分成 endosphere、根际和土壤时增加约450个样本。本手稿详细描述了用于实地取样的方法, 处理实验室中的材料, 提取和序列 DNA, 并简要概述了分析结果测序数据的步骤。

<table>
	<tbody>
		<tr>
			<td>Dneasy PowerSoil HTP 96 Kit</td>
			<td>Qiagen/MoBio</td>
			<td>12955-4</td>
			<td>Extraction kit for soil and rhizosphere</td>
		</tr>
		<tr>
			<td>Dneasy PowerPlant HTP 96 Kit</td>
			<td>Qiagen/MoBio</td>
			<td>13496-4</td>
			<td>Extraction kit for roots</td>
		</tr>
		<tr>
			<td>D-Handle Digging shovel, 101 cm L</td>
			<td>Fiskars</td>
			<td>9669</td>
			<td></td>
		</tr>
		<tr>
			<td>Rapid Tiller, 40 cm L</td>
			<td>Truper</td>
			<td>34316</td>
			<td></td>
		</tr>
		<tr>
			<td>Ziploc Bags, 17.7 cm x 19.5 cm</td>
			<td>Ziploc</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Cooler</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Wash pan</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Plastic bucket</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Gloves (work and lab)</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>20 cm diameter Soil sieve #8, 2360 &#956;m mesh size</td>
			<td>Dual Manufacturing Co., Chicago IL</td>
			<td>US8-8FS</td>
			<td></td>
		</tr>
		<tr>
			<td>20 cm diameter Soil Sieve #4, 4750 &#956;m mesh size</td>
			<td>Dual Manufacturing Co., Chicago IL</td>
			<td>US8-4FS</td>
			<td></td>
		</tr>
		<tr>
			<td>portable generator</td>
			<td>Honda brand works well</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile cell strainers 100 &#956;m mesh size</td>
			<td>Fisher Scientific</td>
			<td>22-363-549</td>
			<td></td>
		</tr>
		<tr>
			<td>NaH2PO4&#183;H2O</td>
			<td>VWR</td>
			<td>0823</td>
			<td></td>
		</tr>
		<tr>
			<td>Na2HPO4</td>
			<td>VWR</td>
			<td>0404</td>
			<td></td>
		</tr>
		<tr>
			<td>Silwet L-77</td>
			<td>Lehman Seeds</td>
			<td>VIS-30</td>
			<td>Surfactant</td>
		</tr>
		<tr>
			<td>Autoclaves</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Drying Oven</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Scale</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Bleach</td>
			<td>CLOROX - household strength</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Tween 20</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Liquid Nitrogen</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Dry Ice pellets</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>11 cm precision fine point tweezers</td>
			<td>Fisher</td>
			<td>17456209</td>
			<td></td>
		</tr>
		<tr>
			<td>18 cm Straight point specimen forceps</td>
			<td>VWR</td>
			<td>82027-436</td>
			<td></td>
		</tr>
		<tr>
			<td>13.5 cm Pruning Scissors</td>
			<td>Fiskars</td>
			<td>9921</td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL tube</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL PP conical tube</td>
			<td>MIDSCI</td>
			<td>C15B</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL PP conical tube</td>
			<td>MIDSCI</td>
			<td>C50B</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrapure water</td>
			<td>Millipore-sigma</td>
			<td>Milli-Q Integral, Q-POD</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit 2.0 fluorometer</td>
			<td>Invitrogen</td>
			<td>Q32866</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit dsDNA HS Assay Kit</td>
			<td>Invitrogen</td>
			<td>Q32854</td>
			<td>For DNA quantification of removed samples</td>
		</tr>
		<tr>
			<td>QuantiFluor dsDNA System</td>
			<td>Promega</td>
			<td>E2670</td>
			<td>For DNA quantification</td>
		</tr>
		<tr>
			<td>96-Well Black with Clear Flat Bottom Plates</td>
			<td>Corning</td>
			<td>3631</td>
			<td></td>
		</tr>
		<tr>
			<td>pPNA PCR Blocker</td>
			<td>PNA Bio</td>
			<td>PP01-50</td>
			<td></td>
		</tr>
		<tr>
			<td>mPNA PCR Blocker</td>
			<td>PNA Bio</td>
			<td>MP01-50</td>
			<td></td>
		</tr>
		<tr>
			<td>Genomic DNA from Microbial Mock Community B (Even Low Concentration) v5.1L, for 16s rRNA Gene sequencing</td>
			<td>BEI Resources</td>
			<td>HM782D</td>
			<td></td>
		</tr>
		<tr>
			<td>Adhesive 8 well-strips for plates</td>
			<td>VWR</td>
			<td>89134-434</td>
			<td></td>
		</tr>
		<tr>
			<td>Stainless steel beads, 3.2 mm dia</td>
			<td>Next Advance</td>
			<td>SSB32</td>
			<td></td>
		</tr>
		<tr>
			<td>1 ml Assay block (DNA extraction plate for the Qiagen/MoBio Dneasy PowerPlant HTP Kit)</td>
			<td>CoStar</td>
			<td>3959</td>
			<td></td>
		</tr>
		<tr>
			<td>antistatic PP weighing funnel, size small for soil/rhizosphere</td>
			<td>TWD Tradewinds, INC</td>
			<td>ASWF1SPK</td>
			<td></td>
		</tr>
		<tr>
			<td>antistatic PP weighing funnel, size x-small for root/leaf</td>
			<td>TWD Tradewinds, INC</td>
			<td>ASWFXSCS</td>
			<td></td>
		</tr>
		<tr>
			<td>Genie 2 Digital Vortex</td>
			<td>Scientific Industries</td>
			<td>SI-0236</td>
			<td></td>
		</tr>
		<tr>
			<td>Vortex adapter for 50 mL tubes</td>
			<td>Scientific Industries</td>
			<td>SI-H506</td>
			<td></td>
		</tr>
		<tr>
			<td>Mortar (100 mL) and pestle</td>
			<td>Any</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Metal micro-spatula</td>
			<td>VWR</td>
			<td>80071-672</td>
			<td></td>
		</tr>
		<tr>
			<td>Disposable antistatic microspatulas</td>
			<td>VWR</td>
			<td>231-0106</td>
			<td></td>
		</tr>
		<tr>
			<td>Brown Paper bag 2# (10.95 cm x 6.19 cm x 20 cm)</td>
			<td>Duro</td>
			<td>18402</td>
			<td></td>
		</tr>
		<tr>
			<td>5424 Centrifuge for 2 mL tube</td>
			<td>Eppendorf</td>
			<td>22620461</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge for 96-well plate</td>
			<td>Sigma4-16S</td>
			<td>81510</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge rotor for 50 mL tubes</td>
			<td>Sigma4-16S</td>
			<td>12269 - Biosafe</td>
			<td></td>
		</tr>
		<tr>
			<td>KAPA HiFi DNA polymerase</td>
			<td>Kapa Biosystems</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

isolation and analysis of microbial communities in soil, rhizosphere, and roots in perennial grass experiments

植物和土壤微生物学研究对了解微生物在农业生产力中的作用越来越重要。本手稿的目的是提供详细说明如何快速取样土壤, 根际和 endosphere 的复制田间试验和分析可能发生的变化, 在微生物群落由于样本类型, 治疗和植物基因型。用于演示这些方法的实验包括包含两个纯、暖季草 (柳枝柳枝稷和须芒草 gerardii)和低多样性草混合物 (gerardii、Sorghastrum) 的复制场地块。垂穗和Bouteloua curtipendula)。简单地, 植物被挖掘出来, 各种根被切开并放置在磷酸盐缓冲物中, 然后摇动以收集根际。根被带到实验室的冰和表面消毒漂白和乙醇 (乙醇)。用离心法过滤和浓缩根际。从根球周围挖出的泥土被放进塑料袋里, 带到实验室里, 那里有少量的泥土用于 DNA 提取。DNA 从根、土壤和根际提取, 然后用引物放大 16S rRNA 基因的 V4 区。Amplicons 的顺序, 然后分析与开放的访问生物信息学工具。这些方法使研究人员能够测试微生物群落的多样性和组成因样本类型、治疗和植物基因型而异。利用这些方法和统计模型, 表明根系、根际和土壤微生物群落存在显著差异。这里提供了一套完整的步骤来收集野外样本, 分离, 提取, 量化, 放大, 序列 DNA, 并分析微生物群落多样性和组成的复制田间试验。

这份手稿中的代表性成果来自于2012年在内布拉斯加州-林肯农业研究分部农场附近建立的一个实地网站, 在米德, NE. 在实验之前, 该网站已被管理为玉米-大豆轮作.该研究地点位于三种不同类型的土壤上, 但分析的数据是, 如果测量土壤性质的所有变化是由于所实施的处理。
现场网站包含两个, 纯, 柳枝稷 (P. 柳枝稷cv 自由) 和大白羊草 (A. gerardii) 以及一个低多样性的草混合物含有大白羊草, indiangrass (垂穗), 和' 山丘 ' sideoats 格兰玛 (B. curtipendula)。三暖季草地块是在随机完整的块设计, 复制了三次。嵌套在三不同的草地块是二氮气 (N) 受精处理, 是 56 (N1) 和 112 (N2) 公斤 N ha-1的应用的尿素。在生长季节结束时, 微生物取样时, 土壤中含有8.0 到 1.1 (平均的) ppm 硝酸盐在被受精的地块112公斤 n 公顷-1和 6.8 @ 0.7 (平均 + SD) ppm 硝酸盐在被施肥的地块与56公斤 n 公顷-1。这些地块每年受精一次。暖季草地块被指定为主要地块 (8000 米2) 和 N 处理是分裂地块 (4000 米2)。大白羊草被播种为50:50 混合的 ' 金矿 ' 和 ' 金矿 ' 和 Indiangrass 被播种了作为50:50 混合的 ' 侦察员 ' 和 ' 勇士 '。这些地块是在2012年种植的, 第一个 N 应用发生在2013年春季。
土壤和根系取样是在2014年9月15日进行的。下面所述的工作是在一个被设置为三复制的分块随机设计的领域进行的 (图 1)。endosphere 所有样品的平均测序深度如下: 4871 5711 (平均 * SD), 根际: 40726 @ 14684, 土壤: 38184 @ 9043。使用所描述的方法, 这些实验中最大的变异来源之一是在样本类型之间发现的微生物群落的差异 (图 2)。在这个代表性的数据集, 根际和土壤似乎比 endosphere 更相似的组合 (图 2A)。然而, 根际和土壤微生物群落组成也有很大的差异 (p = 0.001) (图 2B)。以样本类型分析的实验结果表明, 总变异率为26%。
阿尔法多样性分析表明, 与土壤和根际相比, endosphere 中微生物群落的样本多样性较低 (图 3)。白羊草和柳枝稷的 endosphere 样品之间, 任何隔间的草种之间的多样性唯一显著差异 (图 3)。相对丰度分析 (图 4) 突出了Proteobacteria在所有样本类型中跟随放线菌的优势。土壤和根际也以Acidobacteria和Chloroflexi为主, 而 endosphere 的Bacteriodetes相对丰度较大。
在本实验中, 植物生长了两种不同的氮肥, 因此我们分析了数据, 以确定是否有治疗效果。治疗效果占总变异的 12%, 但没有显著差异, 虽然在协调两种治疗看起来不同 (图 5)。这突出了统计分析对这些数据集的重要性, 而不是视觉检验或定性判断。
利用约束的协调方法, 对植物组织和土壤微生物群中植物影响的差异进行了可视化研究。统计差异是通过 PERMANOVA 分析确定的特定变量, 如物种, 导致明显不同的微生物群落组成之间的样本。在对所有样本类型进行分析的同时, 由于植物种类的不同, 在微生物群落组成上发现了显著差异 (图 6)。在本实验中, 植物种类的变异量为6.7%。最后, 对每个样本类型分别进行分析, 以确定哪种样本类型可能会推动植物物种的显著效应。只有在 endosphere 有一个高度显著的差异 (p = 0.001) 之间的微生物群落组成的不同植物种类 (图 7)。在其他样本类型中, 个别分析时, 物种效应并不显著。在 endosphere 中, 由于物种的变异率为 27%, 而在根际 (18%) 和土壤 (15%) 中的百分比则较低。这进一步强调了单独分析每个组织类型的重要性。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57932/57932fig1.jpg"> 图 1: 实验场设计的示例.试验场设计, 说明了在内布拉斯加州-林肯东部内布拉斯加大学研究和推广中心附近的一三个实地网站的一个随机完整块设计, NE。有关完整站点说明, 请参阅 "结果" 部分。N1 是低 (56 公斤 n 公顷-1尿素) 和 N2 (112 公斤 n 公顷-1尿素) 是更高的氮气率被应用。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig1large.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/57932/57932fig2.jpg"> 图 2: 在 2014年, 从多年生牧草取样的不同样品类型中, 包括 endosphere、根际和土壤中的微生物组成进行了β分集分析比较.用 QIIME1.9.1 中的 Python 脚本进行了分析, 生成了布雷-柯蒂斯相异矩阵。在 RStudio 中, PCoA 了基于布雷-柯蒂斯相异矩阵的主坐标分析方法。PCoA1 和 PCoA2 表示 PCoA 分析解释的第一和第二最大方差。PERMANOVA 统计分析, 以确定样本类型之间的意义, p值显示在右上角。图中的每个符号代表了每个样本的整个微生物群落。(A) Endosphere、根际和土壤样本类型一起分析。所有87样品都是稀薄到486序列每样品。(B)共同分析了根际和土壤样本。所有59个样品都是稀薄的8231序列。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig2large.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/57932/57932fig3.jpg"> 图 3: 用香农指数对 endosphere、根际和土壤中的每种物种进行阿尔法多样性分析.分析是使用 QIIME1.9.1 中的 Python 脚本进行的。对 endosphere、根际和土壤样本类型分别进行了稀疏处理, 每个样品的486、17154和8231个序列。框表示第二十五和第七十五百分点 (第一和第三分位数)。方框内的水平线表示中值, 红色加号表示平均值。胡须显示的数据范围, 排除异常 (显示为黑点), 下跌超过1.5 倍的四分位范围 (n = 6 为每个样本, 除了 sideoats 格兰玛混合, 其中n = 5)。endosphere 五种的香农指数均低于根际和土壤。用非参数魏氏秩和试验确定物种间的意义, 并在盒顶部显示出物种间的显著差异。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig3large.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/57932/57932fig4.jpg"> 图 4: endosphere、根际和土壤中的相对丰度.对样品进行了分析, 比较了不同样品类型的微生物门的丰度 (每种样品的n = 29)。分析是使用 QIIME1.9.1 中的 Python 脚本从 OTU 表中进行的。饼图中的不同颜色表示门。该百分比表示每个样本类型中每个语系的相对丰度。使用核糖体数据库项目分类器 (RDP)25对该语系信息进行了注释。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57932/57932fig5.jpg"> 图 5: 在所有样本类型之间使用处理作为约束因子的分析.对主坐标 (CAP) 分析进行了规范化分析, 以确定治疗中微生物群落组成是否存在差异。为每 n 治疗, n = 42 为 N1 (56 公斤 n 公顷-1) 和N = 45 为 N2 (112 公斤 n ha-1)。在 QIIME1.9.1 中使用 python 脚本生成了布雷-柯蒂斯相异矩阵。以 RStudio 的因子为基础, 采用基于布雷-柯蒂斯不同矩阵的 CAP 分析方法对其进行了约束。PERMANOVA 分析, 以确定治疗差异是否显著, p值显示在右上角。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57932/57932fig6.jpg"> 图 6: 在所有样本类型之间使用植物种类作为约束因子的分析.进行了分析, 以确定是否有不同的微生物群落组成的植物物种之间的所有样本类型。对所有样本类型 (endosphere、根际和土壤) 进行了主坐标排序和上限分析, 采用了布雷-柯蒂斯不同矩阵。在 QIIME1.9.1 中使用 Python 脚本生成了布雷-柯蒂斯相异矩阵。在 RStudio 的基础上, 通过对植物物种的约束, 建立了基于布雷-柯蒂斯相异矩阵的 CAP 分析方法。PERMANOVA 统计分析, 以确定植物物种之间的意义, P 值显示在右上角。图中的每个符号代表了该样本的整个微生物群落。n = 18 为每个种类在所有样品类型除了n = 15 为 sideoats 格兰玛混合物。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig6large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/57932/57932fig7.jpg"> 图 7: 使用物种作为每个样本类型的约束因子的 CAP 分析示例.用布雷-柯蒂斯不同矩阵对每个样本类型 (endosphere、根际和土壤) 进行主坐标排序和上限分析。每样样品在 endosphere、根际和土壤中分别为486、17154和8231。物种被用作制约协调的因素。PERMANOVA 统计分析, 以确定各样本类型植物种类之间的意义, p值显示在右上角。图中的每个符号代表每个样本的整个微生物群落。样品大小是n = 29 为每个样品类型, n = 6 为每个样品类型的植物种类除了 sideoats 格兰玛混合物 (n = 5)。<a href="https://www.jove.com/files/ftp_upload/57932/57932fig7large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments at JoVE.com

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

详细描述了植物根系从田间开挖以及样品加工到 endosphere、根际和土壤的情况, 包括 DNA 提取和数据分析方法。本文旨在使其他实验室能够利用这些技术来研究土壤、endosphere 和根际微生物。

多年生草试验中土壤、根际和根系微生物群落的分离与分析

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The ...

isolation-analysis-microbial-communities-soil-rhizosphere-roots

Research

JoVE Journal

Environment

54.4K 次观看.  University of Nebraska-Lincoln. 详细描述了植物根系从田间开挖以及样品加工到 endosphere、根际和土壤的情况, 包括 DNA 提取和数据分析方法。本文旨在使其他实验室能够利用这些技术来研究土壤、endosphere 和根际微生物。

视频: Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Technique for Studying Arthropod and Microbial Communities within Tree Tissues

Phloem tissues of pine are habitats for many thousands of organisms. Arthropods and microbes use phloem and cambium tissues to seek mates, lay eggs, rear young, feed, or hide from natural enemies or harsh environmental conditions outside of the tree. Organisms that persist within the phloem habitat are difficult to observe given their location under bark. We provide a technique to preserve intact phloem and prepare it for experimentation with invertebrates and microorganisms. The apparatus is called a &#8216;phloem sandwich&#8217; and allows for the introduction and observation of arthropods, microbes, and other organisms. This technique has resulted in a better understanding of the feeding behaviors, life-history traits, reproduction, development, and interactions of organisms within tree phloem. The strengths of this technique include the use of inexpensive materials, variability in sandwich size, flexibility to re-open the sandwich or introduce multiple organisms through drilled holes, and the preservation and maintenance of phloem integrity. The phloem sandwich is an excellent educational tool for scientific discovery in both K-12 science courses and university research laboratories.

We provide a technique to preserve intact tree phloem and prepare it for observation. We create an apparatus called a phloem sandwich that allows for the introduction and observation of arthropods, microbes, and other organisms that inhabit phloem tissues.

技术树内组织学习节肢动物和微生物群落

Phloem tissues of pine are habitats for many thousands of organisms.  Arthropods and microbes use phloem and cambium tissues to seek mates, lay eggs, rear ...

科研

环境科学

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes and soil organic matter formation to small-scale stable-isotope biomarker probing. Coupling multiple stable isotopes such as 13C with 15N, 18O or&#160;2H has the potential to reveal even more information about complex stoichiometric relationships during biogeochemical transformations. Isotope labeled plant material has been used in various studies of litter decomposition and soil organic matter formation1-4. From these and other studies, however, it has become apparent that structural components of plant material behave differently than metabolic components (i.e. leachable low molecular weight compounds) in terms of microbial utilization and long-term carbon storage5-7. The ability to study structural and metabolic components separately provides a powerful new tool for advancing the forefront of ecosystem biogeochemical studies. Here we describe a method for producing 13C and 15N labeled plant material that is either uniformly labeled throughout the plant or differentially labeled in structural and metabolic plant components.
Here, we present the construction and operation of a continuous 13C and 15N labeling chamber that can be modified to meet various research needs. Uniformly labeled plant material is produced by continuous labeling from seedling to harvest, while differential labeling is achieved by removing the growing plants from the chamber weeks prior to harvest. Representative results from growing Andropogon gerardii Kaw demonstrate the system&#39;s ability to efficiently label plant material at the targeted levels. Through this method we have produced plant material with a 4.4 atom%13C and 6.7 atom%15N uniform plant label, or material that is differentially labeled by up to 1.29 atom%13C and 0.56 atom%15N in its metabolic and structural components (hot water extractable and hot water residual components, respectively). Challenges lie in maintaining proper temperature, humidity, CO2 concentration,&#160;and light levels in an airtight 13C-CO2 atmosphere for successful plant production. This chamber description represents a useful research tool to effectively produce uniformly or differentially multi-isotope labeled plant material for use in experiments on ecosystem biogeochemical cycling.

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

This method explains how to build and operate a continuous 13C and 15N isotope labeling chamber for uniform or differential plant tissue labeling. Representative results from metabolic and structural labeling of Andropogon gerardii are discussed.

设计一个连续和操作<sup&gt; 13</sup&gt; C和<sup&gt; 15</sup&gt;Ñ贴标商会统一或差分，代谢和结构，植物同位素标记

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes ...

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals is often not well understood. Here we demonstrate an integrated field lysimetry and porewater sampling method for evaluating the mobility of chemicals applied to soils and established vegetation. Lysimeters, open columns made of metal or plastic, are driven into bareground or vegetated soils. Porewater samplers, which are commercially available and use vacuum to collect percolating soil water, are installed at predetermined depths within the lysimeters. At prearranged times following chemical application to experimental plots, porewater is collected, and lysimeters, containing soil and vegetation, are exhumed. By analyzing chemical concentrations in the lysimeter soil, vegetation, and porewater, downward leaching rates, soil retention capacities, and plant uptake for the chemical of interest may be quantified. Because field lysimetry and porewater sampling are conducted under natural environmental conditions and with minimal soil disturbance, derived results project real-case scenarios and provide valuable information for chemical management. As chemicals are increasingly applied to land worldwide, the described techniques may be utilized to determine whether applied chemicals pose adverse effects to human health or the environment.

Field lysimetry and porewater sampling allow researchers to evaluate the fate of chemicals applied to soils and established vegetation. The goal of this protocol is to demonstrate how to install required instrumentation and collect samples for chemical analysis during integrated field lysimetry and porewater sampling experiments.

综合外地Lysimetry和孔隙水采样的化学活动性土壤的评价和植被成立

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals ...

Soil Sampling and Isolation of Entomopathogenic Nematodes (Steinernematidae, Heterorhabditidae)

Entomopathogenic nematodes (a.k.a. EPN) represent a group of soil-inhabiting nematodes that parasitize a wide range of insects. These nematodes belong to two families: Steinernematidae and Heterorhabditidae. Until now, more than 70 species have been described in the Steinernematidae and there are about 20 species in the Heterorhabditidae. The nematodes have a mutualistic partnership with Enterobacteriaceae bacteria and together they act as a potent insecticidal complex that kills a wide range of insect species.
Herein, we focus on the most common techniques considered for collecting EPN from soil. The second part of this presentation focuses on the insect-baiting technique, a widely used approach for the isolation of EPN from soil samples, and the modified White trap technique which is used for the recovery of these nematodes from infected insects. These methods and techniques are key steps for the successful establishment of EPN cultures in the laboratory and also form the basis for other bioassays that consider these nematodes as model organisms for research in other biological disciplines. The techniques shown in this presentation correspond to those performed and/or designed by members of S. P. Stock laboratory as well as those described by various authors.

Soil Sampling and Isolation of Entomopathogenic Nematodes Steinernematidae, Heterorhabditidae

Entomopathogenic nematodes are soil-inhabiting roundworms that parasitize a wide range of insects. We demonstrate sampling methods used for the isolation of these nematodes from the soil using two techniques: the insect baiting and the modified White trap, for the recovery of nematodes from soil samples and infected insect cadavers, respectively.

土壤采样及昆虫病原线虫的分离（Steine​​rnematidae，异小）

Entomopathogenic nematodes (a.k.a. EPN) represent a group of soil-inhabiting nematodes that parasitize a wide range of insects. These nematodes belong to ...

Extraction and Analysis of Microbial Phospholipid Fatty Acids in Soils

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about the overall structure of terrestrial microbial communities. PLFA profiling has been extensively used in a range of ecosystems as a biological index of overall soil quality, and as a quantitative indicator of soil response to land management and other environmental stressors.
The standard method presented here outlines four key steps: 1. lipid extraction from soil samples with a single-phase chloroform mixture, 2. fractionation using solid phase extraction columns to isolate phospholipids from other extracted lipids, 3. methanolysis of phospholipids to produce fatty acid methyl esters (FAMEs), and 4. FAME analysis by capillary gas chromatography using a flame ionization detector (GC-FID). Two standards are used, including 1,2-dinonadecanoyl-sn-glycero-3-phosphocholine (PC(19:0/19:0)) to assess the overall recovery of the extraction method, and methyl decanoate (MeC10:0) as an internal standard (ISTD) for the GC analysis.

Phospholipid fatty acids provide information about the structure of soil microbial communities. We present methods for extraction from soil samples with a single-phase chloroform mixture, fractionation of extracted lipids using solid phase extraction columns, and methanolysis to produce fatty acid methyl esters, which are analyzed by capillary gas chromatography.

提取及土壤微生物磷脂脂肪酸分析

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about ...

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial communities, a relatively precise but effort-intensive technique to assay microbial community composition is phospholipid fatty acid (PLFA) analysis. PLFA was developed to analyze phospholipid biomarkers, which can be used as indicators of microbial biomass and the composition of broad functional groups of fungi and bacteria. It has commonly been used to compare soils under alternative plant communities, ecology, and management regimes. The PLFA method has been shown to be sensitive to detecting shifts in microbial community composition.
An alternative method, fatty acid methyl ester extraction and analysis (MIDI-FA) was developed for rapid extraction of total lipids, without separation of the phospholipid fraction, from pure cultures as a microbial identification technique. This method is rapid but is less suited for soil samples because it lacks an initial step separating soil particles and begins instead with a saponification reaction that likely produces artifacts from the background organic matter in the soil. 
This article describes a method that increases throughput while balancing effort and accuracy for extraction of lipids from the cell membranes of microorganisms for use in characterizing both total lipids and the relative abundance of indicator lipids to determine soil microbial community structure in studies with many samples. The method combines the accuracy achieved through PLFA profiling by extracting and concentrating soil lipids as a first step, and a reduction in effort by saponifying the organic material extracted and processing with the MIDI-FA method as a second step.

The article describes a method that increases throughput while balancing effort and accuracy for extraction of lipids from the cell membranes of microorganisms for use in characterizing both total lipids and the relative abundance of indicator lipids to determine soil microbial community structure in studies with many samples.

用于表征土壤微生物的脂质提取和分析方法在许多样品的实验中

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial ...

Nanopore DNA Sequencing for Metagenomic Soil Analysis

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA sequences identified using computer software. Nanopore DNA sequencing is a flexible technique that allows for rapid microbial genome sequencing to identify bacterial and viral species, to characterize bacterial strains, and to detect genetic mutations that confer resistance to antibiotics. The advantages of nanopore sequencing (NS) for life sciences include its low complexity, reduced cost, and rapid real-time sequencing of purified genomic DNA, PCR amplicons, cDNA samples, or RNA. NS is an example of "strand sequencing" which involves sequencing DNA by guiding a single stranded DNA molecule through a nanopore that is inserted into a synthetic polymer membrane. The membrane has an electrical current applied across it, so as the individual bases pass through the nanopore the electrical current is disrupted to varying degrees by the four nucleotide bases. The identification of each nucleotide occurs by detecting the characteristic modulation of the electrical current by the different bases as they pass through the nanopore. The NS system consists of a handheld, USB powered portable device and a disposable flow cell that contains a nanopore array. The portable device plugs into a standard laptop computer that reads and records the DNA sequence using computer software.

Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.

基因土壤分析的纳米 DNA 测序

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA ...

High-throughput Siderophore Screening from Environmental Samples: Plant Tissues, Bulk Soils, and Rhizosphere Soils

Siderophores (low-molecular weight metal chelating compounds) are important in various ecological phenomenon ranging from iron (Fe) biogeochemical cycling in soils, to pathogen competition, plant growth promotion, and cross-kingdom signaling. Furthermore, siderophores are also of commercial interest in bioleaching and bioweathering of metal-bearing minerals and ores. A rapid, cost effective, and robust means of quantitatively assessing siderophore production in complex samples is key to identifying important aspects of the ecological ramifications of siderophore activity, including, novel siderophore producing microbes. The method presented here was developed to assess siderophore activity of in-tact microbiome communities, in environmental samples, such as soil or plant tissues. The samples were homogenized and diluted in a modified M9 medium (without Fe), and enrichment cultures were incubated for 3 days. Siderophore production was assessed in samples at 24, 48, and 72 hours (h) using a novel 96-well microplate CAS (Chrome azurol sulphonate)-Fe agar assay, an adaptation of the traditionally tedious and time-consuming colorimetric method of assessing siderophore activity, performed on individual cultivated microbial isolates. We applied our method to 4 different genotypes/Lines of wheat (Triticum aestivum L.), including Lewjain, Madsen, and PI561725, and PI561727 commonly grown in the inland Pacific Northwest. Siderophore production was clearly impacted by the genotype of wheat, and in the specific types of plant tissues observed. We successfully used our method to rapidly screen for the influence of plant genotype on siderophore production, a key function in terrestrial and aquatic ecosystems. We produced many technical replicates, yielding very reliable statistical differences in soils and within plant tissues. Importantly, the results show the proposed method can be used to rapidly examine siderophore production in complex samples with a high degree of reliability, in a manner that allows communities to be preserved for later work to identify taxa and functional genes.

We present a protocol for rapid screening of environmental samples for siderophore potential contributing to micronutrient bioavailability and turnover in terrestrial systems.

从环境样品中筛选高通量的安德森菌: 植物组织、散装土壤和根际土壤

Siderophores (low-molecular weight metal chelating compounds) are important in various ecological phenomenon ranging from iron (Fe) biogeochemical cycling ...

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis

Many&#160;nitrogen fertilizer studies evaluate the overall effect of a treatment on end-of-season measurements such as grain yield or cumulative N losses. A stable isotope approach is necessary to follow and quantify the fate of fertilizer derived N (FDN) through the soil-crop system. The purpose of this paper is to describe a small-plot research&#160;design utilizing non-confined 15N enriched microplots for multiple soil and plant sampling events over two growing seasons and provide sample collection, handling, and processing protocols for total 15N analysis. The methods were demonstrated using a replicated study from south-central Minnesota planted to corn (Zea mays L.). Each treatment consisted of six corn rows (76 cm row-spacing) 15.2 m long with a microplot (2.4 m by 3.8 m) embedded at one end. Fertilizer-grade urea was applied at 135 kg N&#8729;ha-1 at planting, while the microplot received urea enriched to 5 atom % 15N. Soil and plant samples were taken several times throughout the growing season, taking care to minimize cross-contamination by using separate tools and physically separating unenriched and enriched samples during all procedures. Soil and plant samples were dried, ground to pass through a 2 mm screen, and then ground to a flour-like consistency using a roller jar mill. Tracer studies require additional planning, sample processing time and manual labor, and incur higher costs for 15N enriched materials and sample analysis than traditional N studies. However, using the mass balance approach, tracer studies with multiple in-season sampling events allow the researcher to estimate FDN distribution through the soil-crop system and estimate unaccounted-for FDN from the system.

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis

A microplot design for 15N tracer research is described to accommodate multiple in-season plant and soil sampling events. Soil and plant sample collection and processing procedures, including grinding and weighing protocols, for 15N analysis are put forth.

微图设计及植物和土壤样品制备，进行15次氮气分析

Many&#160;nitrogen fertilizer studies evaluate the overall effect of a treatment on end-of-season measurements such as grain yield or cumulative N losses. ...

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

We describe a method for two-dimensional (2D) visualization and quantification of the distribution of labile (i.e., reversibly adsorbed) inorganic nutrient (e.g., P, Fe, Mn) and contaminant (e.g., As, Cd, Pb) solute species in the soil adjacent to plant roots (the &#8216;rhizosphere&#8217;) at sub-millimeter (~100 &#181;m) spatial resolution. The method combines sink-based solute sampling by the diffusive gradients in thin films (DGT) technique with spatially resolved chemical analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The DGT technique is based on thin hydrogels with homogeneously distributed analyte-selective binding phases. The variety of available binding phases allows for the preparation of different DGT gel types following simple gel fabrication procedures. For DGT gel deployment in the rhizosphere, plants are grown in flat, transparent growth containers (rhizotrons), which enable minimal invasive access to a soil-grown root system. After a pre-growth period, DGT gels are applied to selected regions of interest for in situ solute sampling in the rhizosphere. Afterwards, DGT gels are retrieved and prepared for subsequent chemical analysis of the bound solutes using LA-ICP-MS line-scan imaging. Application of internal normalization using 13C and external calibration using matrix-matched gel standards further allows for the quantification of the 2D solute fluxes. This method is unique in its capability to generate quantitative, sub-mm scale 2D images of multi-element solute fluxes in soil-plant environments, exceeding the achievable spatial resolution of other methods for measuring solute gradients in the rhizosphere substantially. We present the application and evaluation of the method for imaging multiple cationic and anionic solute species in the rhizosphere of terrestrial plants and highlight the possibility of combining this method with complementary solute imaging techniques.

This protocol presents a workflow for sub-mm 2D visualization of multiple labile inorganic nutrient and contaminant solute species using diffusive gradients in thin films (DGT) combined with mass spectrometry imaging. Solute sampling and high-resolution chemical analysis are described in detail for quantitative mapping of solutes in the rhizosphere of terrestrial plants.

多年生草试验中土壤、根际和根系微生物群落的分离与分析

摘要

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此视频中的章节

技术树内组织学习节肢动物和微生物群落

设计一个连续和操作

综合外地Lysimetry和孔隙水采样的化学活动性土壤的评价和植被成立

土壤采样及昆虫病原线虫的分离（Steinernematidae，异小）

提取及土壤微生物磷脂脂肪酸分析

用于表征土壤微生物的脂质提取和分析方法在许多样品的实验中

基因土壤分析的纳米 DNA 测序

从环境样品中筛选高通量的安德森菌: 植物组织、散装土壤和根际土壤

微图设计及植物和土壤样品制备，^进行15次氮气分析

土壤中实验室、无机植物养分和污染物的二维可视化和量化

多年生草试验中土壤、根际和根系微生物群落的分离与分析

摘要

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此视频中的章节

技术树内组织学习节肢动物和微生物群落

设计一个连续和操作

综合外地Lysimetry和孔隙水采样的化学活动性土壤的评价和植被成立

土壤采样及昆虫病原线虫的分离（Steine​​rnematidae，异小）

提取及土壤微生物磷脂脂肪酸分析

用于表征土壤微生物的脂质提取和分析方法在许多样品的实验中

基因土壤分析的纳米 DNA 测序

从环境样品中筛选高通量的安德森菌: 植物组织、散装土壤和根际土壤

微图设计及植物和土壤样品制备，进行15次氮气分析

土壤中实验室、无机植物养分和污染物的二维可视化和量化

土壤采样及昆虫病原线虫的分离（Steinernematidae，异小）

微图设计及植物和土壤样品制备，^进行15次氮气分析