Name: a lipid extraction and analysis method for characterizing soil microbes in experiments with many samples
Uploaded: 2017-07-16T13:00:00.000+00:00
Duration: 17 min 39 s
Description: Watch this Scientific Journal Video about A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples at JoVE.com

这项工作部分由美国能源部大湖生物能源研究中心（DOE BER科学研究DE-FC02-07ER64494）和DOE OBP能源效率和可再生能源办公室（DE-AC05-76RL01830）资助。作者衷心感谢安德斯·古尔达对录像和编辑的耐心和巧妙的贡献。

注意:在整个程序中始终佩戴适当的个人防护装备（PPE）。为了避免潜在的样品污染，请勿用双手触摸玻璃器皿。运行需要处理氯仿的方案步骤时，戴上适当的手套。 准备（约40天样品2天） <ol><li>将土壤收集到无菌袋中，并从包含冰的冷藏箱从野外运输。如果不能立即筛分新鲜土壤并冷冻干燥，将样品储存在-80°C冷冻箱中，直至开始分析。 </li><li>通过均质制备土壤。通过粗筛（ 如 2毫米）去除根部和石块并破碎土块。 </li><li>通过按照冷冻干燥器手册的说明将子样品放入适当的容器中进行冷冻干燥，并尽快冷冻干燥。一旦将土壤冷冻干燥，将其存放在带有干燥剂的密封容器中，直至抽出。最好的在-20°C，但最好在-80°C下冻干土壤。 </li><li>在准备提取时，从储存和研磨中除去冷冻干燥的土壤至面粉样稠度。研磨方法包括球磨机，球磨机，砂浆和研杵。研磨土后，储存在冷藏室（见1.3）。 注:用于提取的样品量取决于其有机物含量。一般的指导方针是使用0.5至1g的碳重量为12至18％的土壤，以及3至5g的重量为1至3％的土壤。 </li><li>用己烷预先冲洗30 mL离心管。向管中加入约2至3mL的己烷并涡旋5秒。将己烷倒入另一管，并涡旋。己烷（2至3 mL）可用于连续冲洗6根管。将己烷冲洗的管子放置在通风橱中倒置，并将废己烷处理在合适的废物容器中。 </li><li>将玻璃器皿包裹在2到3层铝箔中，放在马弗炉中。烤（马弗）玻璃器皿在450℃4.5小时。 </li><li> 准备试剂 <ol><li>对于所用的土壤量，添加磷酸盐缓冲液（P缓冲液）:CHCl 3 :MeOH的0.8:1:2体积比的化学物质。 </li><li>制备P缓冲溶液:磷酸盐缓冲液:0.1M，pH 7.0。 <ol><li>加入61 mL 1M K 2 HPO 4储存液，无菌（化学品应为ACS认证等级或更好）。加入39 mL 1 M KH 2 PO 4储存液，无菌（化学品应为ACS认证等级或更好）。用1型水填充至1000 mL。用NaOH或HCl调节pH至7.0。将未使用的溶液在环境温度下储存7天，或在冰箱中储存30天。 </li><li>或者，称重10.62克K 2 HPO 4和5.31克KH 2 PO 4 ;用1型水稀释至1升。检查pH值，必要时进行调整。 </li></ol></li><li>准备试剂1，皂化试剂。 <ol><li>分配300 mL 1型水。加入300 mL CH 3 OH（HPLC级或更高级）。加入90.00克NaOH（认证的ACS或更好）。在搅拌下将NaOH颗粒加入到溶液中。搅拌直至颗粒溶解。建议将该溶液储存不超过30天。 </li></ol></li><li>准备试剂2，甲基化试剂。 <ol><li>分配275 mL CH 3 OH（HPLC等级或更高）。加入325 mL认证的6.00 N HCl，同时搅拌。建议将该溶液储存不超过30天。 </li></ol></li><li>准备试剂3，提取试剂:50％C 6 H 14 （己烷），50％C 5 H 12 O（MTBE）。 <ol><li>在通风橱中，将200mL C 6 H 14 （HPLC级或更高级）和200mL C 5 H 12 O（HPLC级或更高级）混合。混合好盖紧。存放在易燃柜或通风柜中不超过1年。 </li></ol></li><li>准备试剂4，底洗剂。 <ol><li>分配900mL 1型水至烧杯。在搅拌下加入10.80g NaOH（认证ACS或更好）。搅拌直至颗粒溶解。建议将该溶液储存不超过30天。 </li></ol></li><li>准备内部库存解决方案。 <ol><li>称量100毫克19:0 EE标准。加入50mL己烷冲洗的容量瓶中。向烧瓶中加入〜15 mL己烷 - MTBE溶液（试剂3），旋转溶解。用己烷-MTBE溶液（试剂3）将其升至50mL。盖和漩涡混合。转移到带有PTFE衬里帽的己烷冲洗玻璃管上，并储存在-20°C。 </li></ol></li></ol></li></ol> 2.第1天 - 从土壤中提取脂肪酸（〜40个样品4〜5 h） <ol><li>为P缓冲液，氯仿和甲醇制备三个5至10 mL的分液移液器。 注意:已经提出氯仿的危害性较小的替代品作为萃取剂。这些可能导致等效脂质回收率16 </s， 17 ，但不在本协议中进行评估。 </li><li>将冷冻干燥的土壤称重到30 mL离心管中，记录土壤质量。 </li><li>制作两个空白并包括检查标准（以前已经提取的土壤）。 </li><li>在通风柜中，按照以下顺序将试剂加入离心管中的土壤:P缓冲液，CHCl 3和MeOH（表1）。在添加P-buffer之前，让土壤时间变湿，然后再加入CHCl 3 。将离心管紧紧盖住并盖住以防止光照。 </li><li>将它们放在摇床上，确保它们牢固。速度设置为280 rpm，摇动1小时18 。 </li><li>为每个样品准备两个16 mm x 150 mm玻璃管，如下所示:标记管，并加入相同体积的CHCl 3和等体积的P缓冲液。 </li><li>从振动筛中取出离心管，并在1,430离心10分钟xg和25℃。相分离应在玻璃管中可见。 </li><li>在通风柜中，将上清液从离心管中倒入步骤2.6中制备的管中。重复步骤2.4至2.5，并将上清液倒入第二个管中。 </li><li>安全地盖住所有16毫米×150毫米玻璃管与PTFE衬里的盖子和反转10 x混合。 </li><li> 让样品一夜之间不受干扰，完成两相分离。为了做到这一点，将样品放在黑暗的橱柜/空间中或室温下覆盖在铝箔上。允许提取物在周末分开。 <ol><li>或者，如果希望直接移动到下一步骤，或者如果第二天样品受到干扰，则以1,000 xg和25°C离心样品10分钟。 注意:将对照组中的所有样品标记为相同的相分离静置时间。 </li></ol></li></ol>三天2 - 脂质的分离（〜40个样品3〜4 h） <ol><li>打开蒸发装置和溶剂阱。将蒸发装置置于33°C并预热。 </li><li>在发动机罩中设置真空吸气器:连接到真空泵的侧臂式烧瓶，一段高纯度管道和玻璃吸管。 </li><li>吸出两层玻璃管的顶层和界面（约2/3下方），保留水层。对每个样品使用干净的移液管重复该过程。 </li><li>通过小心倾析将来自第二管的提取物的水层与第一管中的提取物的水层合并。确保倾析管没有划痕或裂缝。 </li><li>一旦CHCl 3萃取物合并，检查液体 - 应该清楚。如果不加甲醇，直到清除。 </li><li>使用真空蒸发装置干燥所有样品。温度设定为33°C，涡流速度为26％，压力为400 mbar。 </li><li> P将样品花在蒸发系统中，10分钟后将压力降低至350毫巴。 </li><li>监控进度，管内液面达到加热块的水平时，将压力降至300毫巴。 </li><li>继续监测剩余液体的高度，当深度约为1厘米时，将压力降至200毫巴。 </li><li>样品干燥后，取出样品并运行泵10分钟以清除蒸气。 </li><li>将管子密封并将脂质储存在-80℃的冷冻箱中。 </li><li>按照适用的化学品安全规定处理抽吸液体。 </li></ol> 4.第3天 - 皂化和甲基化（〜40个样品6〜7小时） <ol><li>打开水浴。将浴1至95℃，浴2至80℃。 </li><li>设置移液器分配器，并确保它们分配正确的体积。 试剂每样品1:1 mL 试剂2:每个样品2 mL 试剂3:每个样品1.25 mL 试剂4:每样品3 mL 注意:加热过程将在管内产生压力。不要使用划痕，破裂或切屑的管。 </li><li>使用移液管分配器将1.0 mL试剂1加入干燥的脂质中。盖紧，旋转5秒，放在架子上。 </li><li>样品管架放入95°C水浴5min。从浴缸中取出管子架，并检查管子是否有泄漏，由管中气泡上升。重新拧紧或更换泄漏管的盖子，并再次检查是否有裂纹或碎屑。继续在水浴中加热管子另外10分钟。 </li><li>从浴1中取出样品并置于浴2（80℃）中，继续孵育15分钟。 </li><li>取出管子并将样品放入一锅自来水中进行冷却。 </li><li>向每个样品加入2 mL试剂2。盖紧并旋转5至10秒。 </l我&gt; <li>将机架放入80°C水浴中孵育10分钟。 </li><li>从水浴中取出管子架，放入一锅自来水中进行冷却。搅动管架加速冷却过程。 注意:不要超过时间和温度。太多的加热会降低FAMEs。 </li><li>使用移液器给每个样品管加入1.25 mL试剂3，以提取脂肪酸甲酯。盖紧并将管放在振动器上10分钟。 </li><li>振荡后，让管架放置10分钟使相分离。使用玻璃移液管将有机相（顶层）转移到16 mm x 100 mm玻璃试管中。 </li><li>重复提取，再次加入试剂3，摇匀，允许相分离，并转移顶部相。 注意不要转移任何底部相。在管中留下少量的顶相是好的。 </li><li>使用移液器分配器，加入3 mL试剂4e 16 mm x 100 mm管。 </li><li>将试管塞紧并旋转20-30秒。 </li><li>涡旋后，以1,000×g离心3分钟。 </li><li>使用干净的玻璃移液管吸出顶部有机相并转移至4 mL琥珀色小瓶。 </li><li>打开蒸发装置和溶剂阱。将蒸发装置置于30℃，涡流速度至26％，真空至200毫巴，并按预热。 </li><li>监视进度。样品干燥后，取出样品并运行泵10分钟以清除蒸气。 </li><li>从试剂瓶1和4中取出移液管，并通过一些稀酸（ 如 1％HCl）泵送，然后用去离子水。用DI水冲洗用于试剂2的移液管。在机罩中，将用于试剂3的移液管的溶剂从合适的容器中排出，并将其保存在发动机罩中，直到溶剂残留物蒸发。 </li><li>存放移液管倒置，将柱塞移开以防止粘连g止回阀。 </li><li>使用玻璃移液器一次，然后放在适当的容器中。 </li><li>在罩中，允许玻璃器皿上的溶剂残留物蒸发。 </li><li>用干净的水和洗涤剂溶液冲洗玻璃器皿。 </li></ol> 5.第4天 - 制备工作溶液并将FAME转移到GC样品瓶（约40小时2-3小时） <ol><li>收集材料:4 mL带有干燥样品的琥珀色小瓶;琥珀色2 mL GC小瓶; 400μL平底玻璃插件和盖子; 500μL玻璃注射器; 50mL容量瓶;储存溶液 - 50/50己烷/ MTBE（试剂3）中的十九烷酸乙酯（19:0 EE内标）。 </li><li>使用玻璃注射器，向50 mL容量瓶中加入500μL十九烷酸乙酯（19:0 EE）储液。 </li><li>用试剂3填充烧瓶至体积分数。 </li><li>将瓶盖倒入5x混合。 </li><li>将3 mL转移到干净的4 mL小瓶中，用于工作溶液储存器。 </li><li>使用the玻璃注射器，向含有干燥的脂肪酸甲酯和帽的4mL小瓶中加入300μL的工作溶液。 </li><li>将样品涡旋15秒，放在一边放置15分钟。 </li><li>使用玻璃巴斯德吸管，小心地将悬浮的脂肪酸甲酯转移到含有400μL插入物的2 mL GC小瓶中。 </li><li>将密封的GC小瓶在分析前储存在-20°C的冷冻箱中。 </li><li>提交样品进行GC分析。 注意:分析必须使用补充文件S1中描述的特定GC色谱柱和条件进行。 GC分析最好在甲基化后2周内完成。 </li></ol>

作者没有什么可以披露的。

为了从具有许多重复和/或实验单位的实验中检查多个样品，研究人员可能发现磷脂脂肪酸分析（PLFA）在时间和材料方面是禁止的25 。使用PLFA方法，使用改良的Bligh和Dyer 26两相含水有机萃取提取，纯化和鉴定细胞膜磷脂。随后进行固相硅胶色谱分离，通过极性分离脂质，并将磷脂脂肪酸碱性甲基化成脂肪酸甲酯。在PLFA中，脂质产率可能很低，但纯度非常高。微生物ID引入了一种替代方法，即脂肪酸甲酯法（MIDI-FA）。在MIDI-FA方法中，所有的脂质直接从纯培养物或土壤/沉积物样品11提取，12，27通过皂化。该方法具有较低的脂质损失并且快速，因为它没有PLFA方法的浓缩或纯化步骤。然而，虽然MIDI-FA方法快速而便宜，因为它最初设计用于识别纯培养物中的生物体，但没有初步的提取或纯化步骤。因此，它可以包括脂质类化合物共萃取从扭曲社区签名27，28，29土壤有机质。因为这种夹杂物也可能扭曲生物量测量，所以MIDI-FA通常仅用于粗略定性描述土壤脂质13 。 我们在此描述的方法结合了两种独立提取方法中的最佳方法:1）使用改良的Bligh和Dyer 26方法提取和浓缩脂质，以及2）脂肪酸甲酯sa商业化开发的成型，甲基化，提取和碱洗方法。开发这种方法以实现这两种协议的优点，同时最大限度地减少缺点15 。通过在执行MIDI-FA之前执行初始提取和分离有机溶解组分（ 例如脂质），并通过纯化步骤完成，该方案提供了速度和精度之间的平衡。虽然当需要高纯度时（ 即 13 C PLFA分析）或分析磷脂和中性脂质时，这种方法可能不合适，但在许多情况下，它可以检测微生物群落对环境条件的反应，具有比基于DNA的更高的灵敏度方法30，31，32，33。细胞死亡后膜脂质分解迅速，反映采样5,7时活微生物群落中，与其中的大部分信息来自死的或不活动的生物体34的环境DNA的对比度。鉴于土壤中的微生物35中观察到的休眠率高，活生物质的表征可以用于以相对精细的时间尺度来了解颞植物-微生物相互作用和脂质的生物标志物可用于测定微生物群落7的生理状况。已经表明，需要高通量的方法来评估大场设置中的微生物反应25 ，而我们在此提出的方法不能复制PLFA生物标志物分析的准确性，它可以提高吞吐量，同时最小化使用MIDI-FA实现的可变性程序。该方法已经被证明是一种有效的解决方法有关微生物群落动力学上的宽范围的大型的农业和生态系统研究36，37，38，42，43，44，45，46，47，48，49，50污垢的问题。 脂质类别相结合，与该方法和可能存在的包含在那些独立的类22，39中的信息的损失，但结合脂质类可以加强电力来检测16的丛枝菌根真菌来源:从两个磷酸1ω5c - 和中性脂质40 。另外，当t未知的脂肪酸（可以来自非生物有机物质）的数量可能会更高，这显示低于MIDI-FA，并且允许对来自具有许多样品的样品的脂质谱进行比较吞吐能力是一个关注15 。中性级分通常被认为主要来自真菌产生的储存脂质，尽管土壤动物群41的贡献也可能较小。鉴于此，本文描述的方法可以产生显示真菌脂质18:2ω6,9c和18:1ω9c比PLFA更大贡献的结果。倾向于出现在中性馏分中的其他脂质包括一些饱和脂肪酸， 例如 16:0,18:0,20:0。 有不同的方式可以表达和分析脂质数据。最常见的表现是丰度（nmol g -1土壤），痣分数n（nmol个体脂质nmol -1总脂质）和摩尔百分比（摩尔分数* 100）。通过样品中的总脂质归一化，摩尔分数和摩尔百分数是给定脂质的相对丰度的量度。经过适当的转换， 例如 ，反正弦平方根，摩尔分数适用于通过主成分分析或冗余分析排序。丰度是每克土壤提取的给定脂质的绝对量。因为每个细胞的脂质量是相当稳定的，脂质提取是高效和全面的，总丰度是总脂质的一个很好的估计，关键指标的丰度反映了其代表的生态群体的生物量17 。最后，探讨微生物群落组成的一个好方法是使用多变量分析方法16 ， 例如 ，诸如非度量多维尺度（NMDS-不需要数据转换）或主成分分析（PCA），可用于比较所有脂质生物标志物的相对丰度。

<html>鉴于微生物在营养循环中的关键作用1 ，植物群落组成的改变2 ，植物生产力调节3 ，有机物分解4 ，了解土壤微生物群落对于了解陆地生态系统至关重要。 由于它们相对高丰富的土壤，它们的化学签名，脂质生物标记物可用于特征包括:土壤微生物群落5优势的生态群。通过量化不同微生物群体特征的脂质生物标志物，我们可以估算总脂质，然后将这些脂质分成生态相关的组，如革兰氏阳性（Gm +）和革兰氏阴性（Gm-）细菌，丛枝菌根（AM）和隐性营养真菌和放线菌5 ，<html> SS = "外部参照"&gt; 6，7，8。 有许多方法来表征微生物群落的方面。 PLFA方法是一种常用于了解基本微生物群落结构的方法。它是评估微生物群体相对丰度以及总微生物生物量的有效途径。由于快速周转的脂质，磷脂脂肪酸分析还允许在土壤中微生物群落的变化相对快速的检测，并给出其允许生态系统功能，例如，真菌的比较信息:细菌比例来评估养分循环1，9，10的速率。然而，虽然PLFA提取方法得到时间的尊重和尊重，但对于需要大量样本的生态系统规模研究来说，也是耗时的，并且不适合实地规模的复制F"&gt; 11,12。 相比之下，脂肪酸甲酯提取法（MIDI-FA）具有允许快速通过的潜力。在该方法中，将样品皂化，转化为FAME，提取，然后分析。 MIDI-FA方法比PLFA快，但差别不大，它将脂质萃取与不同脂质类别13 （磷脂，中性脂质和糖脂）的分离相结合。 在本协议中，我们描述了一种结合PLFA和MIDI-FA脂质分析的元素的方法。它采用改良的Bligh和Dyer方法的初始氯仿提取步骤，然后皂化并转化成FAME，使用脂质提取。这提供了一种可靠的方法来检测，同时排除大部分的背景噪声的从非微生物材料5,14微生物群落结构</suP&gt;。这种方法是为了在PLFA和MIDI-FA协议之间实现平衡，即保留大部分精度，同时提高吞吐量，使其在物理和经济上可行，从许多样品的大规模研究中分析脂质15 。通过在执行MIDI-FA之前执行初始提取和分离有机溶解组分（ 例如脂质），并通过纯化步骤完成，协议提供了速度和精度之间的平衡。

<table><tbody><tr><td>RapidVap</td><td>Labconco</td><td>7900000</td><td>Evaporative system</td></tr><tr><td>RapidVap</td><td>Labconco</td><td>7491400</td><td>Sample block</td></tr><tr><td>Chem-resistant vacuum pump</td><td>Labconco</td><td>7584000</td><td>Vacuum pump</td></tr><tr><td>Chemical trap cannister</td><td>Labconco</td><td>7815300</td><td>Trap cannister</td></tr><tr><td>Solvent insert</td><td>Labconco</td><td>7515200</td><td>Solvent trap insert</td></tr><tr><td>Diaphragm pump</td><td>Welch</td><td>7398000</td><td>DryFast vacuum pump</td></tr><tr><td>Water bath</td><td>Fisher</td><td>15-462-15Q</td><td>2 well water bath</td></tr><tr><td>Gas chromatograph</td><td>Various</td><td>N/A</td><td>For sample analysis</td></tr><tr><td>Centrifuge</td><td>Various</td><td>N/A</td><td>For sample separation</td></tr><tr><td>Freeze Dryer</td><td>Various</td><td>N/A</td><td>For sample lyophilization</td></tr><tr><td>Repipet (6)</td><td>BrandTech</td><td>4720440</td><td>For dispensing reagents</td></tr><tr><td>Vortex</td><td>Fisher</td><td>02-215-365</td><td>Analog vortex mixer</td></tr><tr><td>Teflon centrifuge tubes</td><td>Thermo/Nalgene</td><td>3114-0030</td><td>Teflon sample tubes</td></tr><tr><td>Caps</td><td>Thermo/Nalgene</td><td>DS3131-0020</td><td>Caps for teflon tubes</td></tr><tr><td>Test tube</td><td>Corning</td><td>9825-16</td><td>16x100mm tubes</td></tr><tr><td>Test tube</td><td>Corning</td><td>9825-16xx</td><td>16x150mm tubes</td></tr><tr><td>Caps</td><td>Corning</td><td>9998-15</td><td>15-415 thread black phenolic caps w/PTFE liner</td></tr><tr><td>Pasteur pipets</td><td>Fisher</td><td>13-678-20B</td><td>14.6cm</td></tr><tr><td>500 uL glass syringe</td><td>Fisher</td><td>13684106LC</td><td>Hamilton 81217</td></tr><tr><td>Amber vials</td><td>Agilent</td><td>5182-0716</td><td>4mL Amber vials</td></tr><tr><td>Caps</td><td>Agilent</td><td>5182-0717</td><td>Blue screw caps</td></tr><tr><td>Inserts</td><td>Agilent</td><td>5181-3377</td><td>400uL flat bottom glass inserts</td></tr><tr><td>&lt;strong&gt;Standards&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>19:0 ethyl nonadecanoate (Ethyl nonadecanoate)</td><td>VWR</td><td>TCN0459-5G</td><td>Analytical standard</td></tr><tr><td>&lt;strong&gt;Chemicals&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Dipotassium phosphate (K2HPO4 - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Phosphate-Buffer</td></tr><tr><td>Potassium phosphate monobasic (KH2PO4 - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Phosphate-Buffer</td></tr><tr><td>Methanol (CH3OH - HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagents 1 &amp;amp; 2</td></tr><tr><td>Sodium hydroxide (NaOH - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagents 1 &amp;amp; 4</td></tr><tr><td>Hydrochloric acid (6N HCL)</td><td>Various</td><td>N/A</td><td>For making Reagent 2</td></tr><tr><td>Hexane (HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagent 3</td></tr><tr><td>MTBE (Methyl tert-butyl ether - HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagent 3</td></tr></tbody></table>

a lipid extraction and analysis method for characterizing soil microbes in experiments with many samples

微生物群落是生态系统过程的重要动力和监管者。为了了解生态系统的管理如何影响微生物群落，分析微生物群落组成的相对精确而又费力的技术是磷脂脂肪酸（PLFA）分析。 PLFA被开发用于分析磷脂生物标志物，其可以用作微生物生物量的指标和真菌和细菌的广泛官能团的组成。它通常用于比较替代植物群落，生态学和管理制度下的土壤。已经显示PLFA方法对于检测微生物群落组成的变化是敏感的。 开发了一种替代方法，脂肪酸甲酯提取和分析（MIDI-FA），用于快速提取总脂质，而不分离磷脂级分，作为微生物鉴定技术从纯培养物中分离出来。这个方法是快速但不太适合土壤样品，因为它缺乏分离土壤颗粒的初步步骤，而是开始可能产生可能从土壤中背景有机物质产生人造物的皂化反应。 本文介绍了一种增加产量，同时平衡从微生物细胞膜提取脂质的努力和准确性的方法，用于表征总脂质和指示脂质的相对丰度，以确定具有许多样品的研究中的土壤微生物群落结构。该方法结合了通过提取和浓缩土壤脂质作为第一步通过PLFA分析实现的准确度，并且通过使用MIDI-FA方法皂化有机材料和处理来减少工作量作为第二步。

报表中的数据表可以整理成电子表格或数据库。在调整响应因子（对不同链长的响应进行归一化的校正因子）后，峰面积可以与外标或内标的峰面积进行比较，以达到提取物中的浓度。通过分解提取的土壤质量，数据可以表示为每克土壤的FAME质量，或者通过使用每个FAME的分子量，每克土壤更常见的报告的nmol。微生物FAME的总和指示总微生物生物量，并且可以在处理之间进行比较（ 图1 ）。某些脂肪酸甲酯也可以与特定的微生物群体，如革兰氏阳性或革兰氏阴性菌，放线菌，丛枝菌根真菌和真菌saprotrophic 19，20相关联， <s向上类= "外部参照"&gt; 21，22，23，24。特定生物标志物的比例可以反映这些组的相对丰度（ 图2 ）。总体FAME丰度模式创建社区级指纹，允许通过多变量技术（ 如图3 ）比较微生物群落的不相似性。与大多数基于DNA的方法相比，社区级脂质数据可以作为相对或绝对丰度进行分析。如果样品中总生物量差异很大，这两种方法将产生非常不同的结果;实验的生态学问题应该决定哪种方法被使用。 <img alt="图1" class="xfigimg" src="/files/ftp_upload/55310/55310fig1.jpg" /> F<html>图1 :总FAME生物量。比较来自连续玉米，受精草原和未受精草原的总FAME生物标志物生物量（nmol g -1土壤）。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55310/55310fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图2" class="xfigimg" src="/files/ftp_upload/55310/55310fig2.jpg" /> 图2 :细菌和真菌的FAME生物量。来自连续玉米，受精草原和未受精的草原的细菌和真菌FAME生物标志物生物量（nmol g -1土壤）的处理比较。绝对丰度的真菌和细菌群体。平均（和f /和b）。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55310/55310fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> ve_content"fo:keep-together.within-page ="1"&gt; <img alt="图3" class="xfigimg" src="/files/ftp_upload/55310/55310fig3.jpg" /> 图3 :FAME脂质生物标志物的非度量尺度缩放。使用所有微生物FAME脂质生物标志物的绝对丰度曲线比较整个微生物群落。在这个例子中，连续的玉米和未受精的草原社区分开，距离相当遥远，而一些受精草原样品具有类似于玉米的微生物群落，其他类似于未受精的草原。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55310/55310fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="表格1" src="/files/ftp_upload/55310/55310table1.jpg" /> 表1:TħÈ 所以升 VEN 吨 型， 在 S 数比例 添加 Ti 克 -1 土壤中，D（T）ħEIR 奥德 R 0 添加 F ITI O 4 N。这对于有机和水相的适当萃取和分离是重要的。

Watch this Scientific Journal Video about A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples at JoVE.com

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

该文章描述了一种增加产量，同时平衡从微生物细胞膜提取脂质的努力和准确性，用于表征总脂质和指示性脂质的相对丰度，以确定具有许多样品的研究中的土壤微生物群落结构。

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 ...

a-lipid-extraction-analysis-method-for-characterizing-soil-microbes

Universidad San Sebastian

Research

JoVE Journal

Environment

19.7K 次观看.  University of Wisconsin - Madison. 该文章描述了一种增加产量，同时平衡从微生物细胞膜提取脂质的努力和准确性，用于表征总脂质和指示性脂质的相对丰度，以确定具有许多样品的研究中的土壤微生物群落结构。 

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

Analysis of Fatty Acid Content and Composition in Microalgae

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of microalgal biomass. These fatty acids can be present in different acyl-lipid classes. Especially the fatty acids present in triacylglycerol (TAG) are of commercial interest, because they can be used for production of transportation fuels, bulk chemicals, nutraceuticals (&omega;-3 fatty acids), and food commodities. To develop commercial applications, reliable analytical methods for quantification of fatty acid content and composition are needed. Microalgae are single cells surrounded by a rigid cell wall. A fatty acid analysis method should provide sufficient cell disruption to liberate all acyl lipids and the extraction procedure used should be able to extract all acyl lipid classes.
With the method presented here all fatty acids present in microalgae can be accurately and reproducibly identified and quantified using small amounts of sample (5 mg) independent of their chain length, degree of unsaturation, or the lipid class they are part of.
This method does not provide information about the relative abundance of different lipid classes, but can be extended to separate lipid classes from each other.
The method is based on a sequence of mechanical cell disruption, solvent based lipid extraction, transesterification of fatty acids to fatty acid methyl esters (FAMEs), and quantification and identification of FAMEs using gas chromatography (GC-FID). A TAG internal standard (tripentadecanoin) is added prior to the analytical procedure to correct for losses during extraction and incomplete transesterification.

A method for the determination of fatty acid content and composition in microalgae based on mechanical cell disruption, solvent based lipid extraction, transesterification, and quantification and identification of fatty acids using gas chromatography is described. A tripentadecanoin internal standard is used to compensate for the possible losses during extraction and incomplete transesterification.

脂肪酸组分和含量微藻分析

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of ...

科研

环境科学

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

一种简单的分级提取方法，用于从单个样品中综合分析代谢物，脂质和蛋白质

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually ...

生物化学

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 ...

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled Earth-system processes. Such knowledge is imperative in improving predictions of hydro-biogeochemical cycles, especially under climate change scenarios. We present an experimental method, designed to capture sub-surface heterogeneity of an initially homogeneous soil system. This method is based on destructive sampling of a soil lysimeter designed to simulate a small-scale hillslope. A weighing lysimeter of one cubic meter capacity was divided into sections (voxels) and was excavated layer-by-layer, with sub samples being collected from each voxel. The excavation procedure was aimed at detecting the incipient heterogeneity of the system by focusing on the spatial assessment of hydrological, geochemical, and microbiological properties of the soil. Representative results of a few physicochemical variables tested show the development of heterogeneity. Additional work to test interactions between hydrological, geochemical, and microbiological signatures is planned to interpret the observed patterns. Our study also demonstrates the possibility of carrying out similar excavations in order to observe and quantify different aspects of soil-development under varying environmental conditions and scale.

This study presents an excavation method for investigating subsurface hydrological, geochemical, and microbiological heterogeneity of a soil lysimeter. The lysimeter simulates an artificial hillslope which was initially under homogeneous condition and had been subjected to approximately 5,000 mm of water over eight cycles of irrigation in an 18-month period.

土壤蒸渗仪开挖加之水文，地球化学和微生物调查

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled ...

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

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The purpose of this manuscript is to provide detail on how to rapidly sample soil, rhizosphere, and endosphere of replicated field trials and analyze changes that may occur in the microbial communities due to sample type, treatment, and plant genotype. The experiment used to demonstrate these methods consists of replicated field plots containing two, pure, warm-season grasses (Panicum virgatum and Andropogon gerardii) and a low-diversity grass mixture (A. gerardii, Sorghastrum nutans, and Bouteloua curtipendula). Briefly, plants are excavated, a variety of roots are cut and placed in phosphate buffer, and then shaken to collect the rhizosphere. Roots are brought to the laboratory on ice and surface sterilized with bleach and ethanol (EtOH). The rhizosphere is filtered and concentrated by centrifugation. Excavated soil from around the root ball is placed into plastic bags and brought to the lab where a small amount of soil is taken for DNA extractions. DNA is extracted from roots, soil, and rhizosphere and then amplified with primers for the V4 region of the 16S rRNA gene. Amplicons are sequenced, then analyzed with open access bioinformatics tools. These methods allow researchers to test how the microbial community diversity and composition varies due to sample type, treatment, and plant genotype. Using these methods along with statistical models, the representative results demonstrate there are significant differences in microbial communities of roots, rhizosphere, and soil. Methods presented here provide a complete set of steps for how to collect field samples, isolate, extract, quantify, amplify, and sequence DNA, and analyze microbial community diversity and composition in replicated field trials.

Excavation of plant roots from the field as well as processing of samples into endosphere, rhizosphere, and soil are described in detail, including DNA extraction and data analysis methods. This paper is designed to enable other laboratories to use these techniques for the study of soil, endosphere, and rhizosphere microbiomes.

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 ...

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

用于表征复杂天然有机物混合物的单吞吐量互补高分辨率分析技术

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

A protocol is presented for simultaneously extracting metabolites, proteins, and lipids from a single soil sample, allowing reduced sample preparation times and enabling multi-omic mass spectrometry analyses of samples with limited quantities.

土壤样品多涨价可能分析的 MPLEx 协议

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and ...

化学

Determination of Total Lipid and Lipid Classes in Marine Samples

Lipids are largely composed of carbon and hydrogen and, therefore, provide a greater specific energy than other organic macromolecules in the sea. Being carbon- and hydrogen-rich they are also hydrophobic and can act as a solvent and absorption carrier for organic contaminants and thus can be drivers of pollutant bioaccumulation in marine ecosystems. Their hydrophobic nature facilitates their isolation from seawater or biological specimens: marine lipid analysis begins with sampling and then extraction in non-polar organic solvents, providing a convenient method for their separation from other substances in an aquatic matrix.
If seawater has been sampled, the first step usually involves separation into operationally defined &#39;dissolved&#39; and &#39;particulate&#39; factions by filtration. Samples are collected and lipids isolated from the sample matrix typically with chloroform for truly dissolved matter and colloids, and with mixtures of chloroform and methanol for solids and biological specimens. Such extracts may contain several classes from biogenic and anthropogenic sources. At this time, total lipids and lipid classes may be determined. Total lipid can be measured by summing individually determined lipid classes which customarily have been chromatographically separated. Thin-layer chromatography (TLC) with flame ionization detection (FID) is regularly used for the quantitative analysis of lipids from marine samples. TLC-FID furnishes synoptic lipid class information and, by summing classes, a total lipid measurement.
Lipid class information is especially useful when combined with measurements of individual components e.g., fatty acids and/or sterols, after their release from lipid extracts. The wide variety of lipid structures and functions means they are used broadly in ecological and biogeochemical research assessing ecosystem health and the degree of influence by anthropogenic impacts. They have been employed to measure substances of dietary value to marine fauna (e.g., aquafeeds and/or prey), and as an indicator of water quality (e.g., hydrocarbons).

This protocol is for the determination of lipids in seawater and biological specimens. Lipids in filtrates are extracted with chloroform or mixtures of chloroform and methanol in the case of solids. Lipid classes are measured by rod thin-layer chromatography with flame ionization detection and their sum gives the total lipid content.

海洋样品中总脂质和脂质类别的测定

Lipids are largely composed of carbon and hydrogen and, therefore, provide a greater specific energy than other organic macromolecules in the sea. Being ...

Extraction of High Molecular Weight Genomic DNA from Soils and Sediments

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with nutrient and energy flow within terrestrial ecosystems. Cultivation-independent environmental genomic, also known as metagenomic, approaches promise unprecedented access to this genetic information with respect to pathway reconstruction and functional screening for high value therapeutic and biomass conversion processes. However, the soil microbiome still remains a challenge largely due to the difficulty in obtaining high molecular weight DNA of sufficient quality for large insert library production. Here we introduce a protocol for extracting high molecular weight, microbial community genomic DNA from soils and sediments. The quality of isolated genomic DNA is ideal for constructing large insert environmental genomic libraries for downstream sequencing and screening applications. 
The procedure starts with cell lysis. Cell walls and membranes of microbes are lysed by both mechanical (grinding) and chemical forces (&beta;-mercaptoethanol). Genomic DNA is then isolated using extraction buffer, chloroform-isoamyl alcohol and isopropyl alcohol. The buffers employed for the lysis and extraction steps include guanidine isothiocyanate and hexadecyltrimethylammonium bromide (CTAB) to preserve the integrity of the high molecular weight genomic DNA. Depending on your downstream application, the isolated genomic DNA can be further purified using cesium chloride (CsCl) gradient ultracentrifugation, which reduces impurities including humic acids. The first procedure, extraction, takes approximately 8 hours, excluding DNA quantification step. The CsCl gradient ultracentrifugation, is a two days process. During the entire procedure, genomic DNA should be treated gently to prevent shearing, avoid severe vortexing, and repetitive harsh pipetting.

A methodology to isolate high molecular weight and high quality genomic DNA from soil microbial community is described.

超高分子量基因组DNA的提取土壤和沉积物

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with ...

生物学

Sonication Extraction of Lipid Biomarkers from Sediment

Source: Laboratory of Jeff Salacup&#160;- University of Massachusetts Amherst
The material comprising the living &#34;organic&#34; share of any ecosystem (leaves, fungi, bark, tissue; Figure 1) differs fundamentally from the material of the non-living &#34;inorganic&#34; share (rocks and their constituent minerals, oxygen, water, metals). Organic material contains carbon linked to a series of other carbon and hydrogen molecules (Figure 2), which distinguishes it from inorganic material. Carbon&#39;s wide valency range (-4 to +4) allows it to form up to four separate covalent bonds with neighboring atoms, usually C, H, O, N, S, and P. It can also share up to three covalent bonds with a single other atom, such as the triple bond in the often-poisonous cyanide, or nitrile, group. Over the past 4.6 billion years, this flexibility has led to an amazing array of chemical structures, which vary in size, complexity, polarity, shape, and function. The scientific field of organic geochemistry is concerned with the identification and characterization of the whole range of detectable organic compounds, called biomarkers, produced by life on this planet, as well as others, through geologic time.
<img alt="Figure 1" src="/files/ftp_upload/10055/10055fig1.jpg" /> 
Figure 1. Organic material, such as trees, leaves, and moss, are chemically and visually distinct from inorganic material, such as pavement.

超声提取沉积物的脂类生物标志物

Source: Laboratory of Jeff Salacup&#160;- University of Massachusetts Amherst
The material comprising the living &#34;organic&#34; share of any ecosystem ...