The authors would like to acknowledge Marcos Di Falco for his expertise and advice with the preparation of the samples for nano-LC MS/MS as well as Dr. Zoran Minic from the University of Regina for the LC MS/MS analysis. This work was supported by NSERC (DG402214-2011) and CRC (950-221184) funding. D.C. was supported by Concordia Institute for Water, Energy, and Sustainable Systems and FQRNT.

1.准备试剂<ol><li>制备的SDS-萃取溶液：0.1M的Tris-HCl pH为7.5，5％甘油，10mM EDTA的和1％SDS。过滤消毒使用0.22微米的过滤器，并储存在4℃。 </li><li>备所需的聚丙烯酰胺凝胶的库存试剂。 <ol><li>准备1.5米的Tris-HCl pH值8.8。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li><li>的0.5M的Tris-HCl pH 6.8的。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li><li>准备10％SDS。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li></ol></li><li>需要准备在凝胶胰蛋白酶消化和肽的提取解决方案。 <ol><li>制备100mM碳酸氢铵。过滤消毒使用0.22微米的过滤器，并储存在4℃。 </li><li>准备1 M DTT股票。在-80℃下悬浮于100mM碳酸氢铵和存储。 </li><li>准备550毫米碘乙酰胺的股票。悬浮在100mM碳酸氢铵和储存在-80℃。 </li><li>准备100毫微克/微升胰蛋白酶的股票。分装60微升到的1.5 ml离心管中，并储存在-80℃。 </li><li>制备提取溶液：1％甲酸，2％乙腈。 </li><li>制备悬浮液：5％乙腈和0.1％甲酸。 </li></ol></li></ol> 2.执行细胞裂解插装过滤单元与单元格保存在RNA稳定的解决方案<ol><li>排出从盒滤波器单元（1.5毫升）并进入使用60毫升注射器附接在过滤器的路厄氏锁端2ml微量离心管中的RNA的稳定溶液。 </li><li>离心2 ml离心管10分钟，在17000×g离心以沉淀任何细胞碎片。这样做是使得在步骤2.3的过滤器不堵塞。 </li><li>转移上清液至10 K时超离心过滤器单元以捕获任何蛋白质从细胞中始发，从冻结/ THA已经裂解W精品样品。不要弃沉淀。它将在步骤2.5中使用。在3270×g离心30分钟，或直到体积进行超离心过滤装置的离心分离降低至约600微升。 </li><li>熔化P10尖端的尖端和与尖端的开口端阻塞筒式过滤器单元的非鲁尔锁边。这将确保没有提取缓冲液和生物质在步骤2.5-2.7逸出。 </li><li>暂停沉淀在1毫升SDS-提取解决方案，并吸取其插入原装墨盒过滤装置。以吸管进筒式过滤器单元的最简单方法是叠加P200的尖端到P1000的提示，并用这双尖移液。 </li><li>加入1毫升的SDS提取溶液的筒式过滤器单元，以便总体积是约2ml孵育在室温下10分钟，同时在一个杂交炉旋转。放置3皱实验室湿巾在50ml锥形管的底部。封口膜筒式过滤器单元的封闭两端并把滤芯过滤单元进50毫升管。盖上盖子，把试管放入杂交炉。 </li><li> 10分钟后，代替STERIVEX筛选泡沫浮子和用5毫升注射器的鲁尔锁端将其固定在适当位置。 Float和孵育在95℃水浴15分钟。 </li><li>让暗盒滤波器单元凉爽并旋转在室温下进行1小时（如在步骤2.6）。 </li><li>驱逐SDS提取溶液/细胞裂解物从过滤器与一个60毫升注射器到相同的超离心过滤器单元如前（步骤2.3）。加入1毫升新鲜SDS提取溶液到盒过滤器单元，并用手混合30秒钟，然后使用60毫升注射器的驱逐进入超离心过滤器单元。这是为了冲洗筒式过滤器单元，以确保所有的蛋白质已被除去。 </li><li>该超离心过滤单元上，在3270×g离心，或直到在过滤器单元中的体积进行离心45分钟，小于600微升。 </li><li>弃流过加满油的超离心过滤装置用新鲜的SDS萃取液。 </li><li>离心过滤器单元，用于在3270×g下另外45分钟。 </li><li>重复步骤2.11和2.12两次。确保在超离心过滤单元中的最终体积为至多600微升在最后的旋转的末端。 </li><li>在这一点上，一分为二的浓缩物。一小部分将被用于DNA沉淀，另一个用于蛋白质沉淀。 注意：分馏量取决于生物质的过滤的量和产品的预定用途。在我们的例子中，我们拆分精矿对DNA沉淀10％，对蛋白质沉淀的90％。 </li></ol> 3.蛋白沉淀<ol><li>添加4体积的甲醇：丙酮（50:50），以浓缩物和涡流一体积为10秒。孵育过夜，在-20℃下。 </li><li>降速在17000 XG 30分钟。倒出上清液并让沉淀（可以是不可见的）的干燥在speedvac中1小时（或直到干）。 注意：不要过度干燥沉淀，因为这可能使其难以悬浮。 </li><li>暂停在25微升的SDS-萃取溶液沉淀。让我们坐1小时，然后通过上下吹打重悬。 </li><li>使用蛋白质检测试剂盒和制造商的说明定量蛋白质。 </li></ol> 4. DNA沉淀<ol><li>加入SDS-提取液到浓缩馏分可以用于DNA沉淀，直至500微升标记。这个步骤是简单地增加溶液的体积，使之更易于使用。 </li><li>添加0.583体积的蛋白质沉淀试剂（如MPC的蛋白质沉淀试剂），涡旋10秒。你应该会看到一个白色的沉淀物的形式。 注意：我们也使用苯酚：氯仿提取DNA的方法，但它更困难的，由于低的卷。我们利用获得更好的DNA产量MPC蛋白沉淀试剂。 </li><li>离心机在17000×g离心4℃10分钟。 </li><li>上清转移到另一个的1.5 ml离心管中，加入0.95倍体积的异丙醇。倒置30-40倍。 </li><li>离心机在4℃下10分钟，在最大速度。 </li><li>小心倒出并弃去上清液。 </li><li>用750微升的70％乙醇冲洗两次。 </li><li>除去尽可能多的乙醇可以通过吸液，然后让空气干燥。 注意：不要过度干燥的DNA，因为这可能使其难以悬浮。 </li><li>重悬在25微升的TE低缓冲液，pH 8中（10mM的Tris-HCl，0.1mM的EDTA）中的。 </li><li>量化使用双链DNA测定试剂盒和制造商的说明将DNA。上3微升的DNA进行琼脂糖凝胶（1％）电泳以检查其质量。 </li></ol>蛋白质5. SDS-PAGE凝胶<ol><li>制备样品缓冲液（950微升Laemmli样品缓冲液和50微升β巯基乙醇）。&lt;/ LI&gt; <li>添加了15微克蛋白的相应量，或20微升max与样品缓冲液等体积​​和煮沸4分钟。样品现在可以储存在-80℃直至SDS-PAGE上可以执行。 </li><li>准备用5％丙烯酰胺积层凝胶10％丙烯酰胺分辨凝胶。 </li><li>加载样品和4微升的蛋白质梯的凝胶。运行在恒定的120 V的凝胶，直到250 kDa的阶梯标志刚刚达成的解决凝胶。 </li><li>染色使用根据制造商的说明书基于污渍考马斯凝胶。 </li></ol> 6.在凝胶胰蛋白酶消化和肽提取注：在生物安全柜中进行所有从这里步骤，直到6.10，以减少污染。 <ol><li>在10 kDa的阶梯大关每个车道切掉多余的凝胶。每个线将会在MS / MS分别进行分析。切割每个泳道成1mm×1mm的正方形以增加表面面积，并放置所有SQUA水库从车道进入低结合微离心管中。重复此为所有车道。 （1％乙酸可以用来防止凝胶干涸，成为难以切割）。 注意：最小化污染是非常关键的，在这个阶段，所以凝胶切片在上用于制造凝胶的玻璃SDS-PAGE凝胶铸型生物安全柜内进行。 </li><li>去色斑<ol><li>分配50微升100mM碳酸氢铵成每个低结合管，靠近帽孵育在37℃下进行10分钟。 </li><li>免除50微升的乙腈，接近上限，37℃下5分钟。 </li><li>吸并丢弃150微升。 </li><li>重复步骤6.2.1和6.2.2。 </li><li>吸并丢弃95微升。 </li></ol></li><li>脱水<ol><li>免除50微升乙腈，接近上限，并等待5分钟。吸并丢弃45微升，并等待10分钟。 </li></ol></li><li>减少<ol><li>免除加入50μlDTT（10mM的，稀释在100mM AMM鎓碳酸氢盐），关闭盖子，等待30分钟，在37℃。 </li></ol></li><li>烷基化<ol><li>分配50μl的碘乙酰胺（55毫，稀释在100mM碳酸氢铵），靠近帽和等待20分钟，在37℃。 </li><li>免除100微升乙腈，靠近帽和孵化5分钟，在37℃。吸并丢弃195微升。 </li></ol></li><li>洗刷<ol><li>分配50μl的碳酸氢铵，靠近帽并孵育10分钟，在37℃。 </li><li>免除50微升的乙腈，接近上限，37℃下5分钟。吸并丢弃120微升。 </li></ol></li><li>脱水<ol><li>免除50微升乙腈，接近上限，并等待5分钟。吸并丢弃45微升。 </li><li>免除50微升乙腈，等待5分钟。 </li><li>吸并丢弃75微升，并等待5分钟。 </li></ol></li><li>消化<ol><li>免除微升6月25日至三十○号纳克/μL胰蛋白酶（UNTIL所有凝胶碎片覆盖）。关闭帽并等待30分钟，在室温下进行。 </li><li>孵育过夜（4.5小时最小值），在37℃。 </li><li>让在室温下坐30分钟。 </li></ol></li><li>提取和肽转移<ol><li>免除30微升的提取液，盖上盖子，在冰上30分钟。 </li><li>吸取30微升，并分配一个新的标记低结合管吸气量。 </li><li>分配12微升提取液和12微升乙腈成原管（凝胶）。关闭盖子，并培育在冰上30分钟。 </li><li>吸取15微升并存入新的管。 </li><li>重复步骤（6.9.3和6.9.4）。 </li></ol></li><li>将新管在Speed​​Vac中待干。 </li><li>重悬在50μl再悬浮溶液。涡流的培养基上10分钟以悬浮。 </li><li>吸管肽溶液进入任一纳米/ LC小瓶或96孔板适于纳米/ LCMS / MS的工作。 </li></ol>

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	<li>Madsen, E. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microorganisms+and+their+roles+in+fundamental+biogeochemical+cycles.">Microorganisms and their roles in fundamental biogeochemical cycles.</a> Current opinion in biotechnology. 22 (3), 456-464 (2011).</li><li>El-Swais, H., Dunn, K. A., Bielawski, J. P., Li, W. K. W., Walsh, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seasonal+assemblages+and+short-lived+blooms+in+coastal+northwest+Atlantic+Ocean+bacterioplankton.">Seasonal assemblages and short-lived blooms in coastal northwest Atlantic Ocean bacterioplankton.</a> Environmental microbiology. , (2014).</li><li>Galand, P. E., Potvin, M., Casamayor, E. O., Lovejoy, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hydrography+shapes+bacterial+biogeography+of+the+deep+Arctic+Ocean.">Hydrography shapes bacterial biogeography of the deep Arctic Ocean.</a> The ISME journal. 4 (4), 564-576 (2010).</li><li>Lane, D. J., Pace, B., Olsen, G. J., Stahlt, D. A., Sogint, M. L., Pace, N. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+determination+of+16S+ribosomal+RNA+sequences+for+phylogenetic+analyses.">Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses.</a> Proceedings of the National Academy of Sciences of the United States of America. 83, 4972 (1986).</li><li>Williams, T. J., Long, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+metaproteomic+assessment+of+winter+and+summer+bacterioplankton+from+Antarctic+Peninsula+coastal+surface+waters.">A metaproteomic assessment of winter and summer bacterioplankton from Antarctic Peninsula coastal surface waters.</a> The ISME journal. 6 (10), (2012).</li><li>Sheik, C. S., Jain, S., Dick, G. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic+flexibility+of+enigmatic+SAR324+revealed+through+metagenomics+and+metatranscriptomics.">Metabolic flexibility of enigmatic SAR324 revealed through metagenomics and metatranscriptomics.</a> Environmental microbiology. 16 (1), 304-317 (2014).</li><li>Venter, J. C., Remington, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Environmental+genome+shotgun+sequencing+of+the+Sargasso+Sea.">Environmental genome shotgun sequencing of the Sargasso Sea.</a> Science (New York, N.Y.). 304, 66-74 (2004).</li><li>Tyson, G. W., Chapman, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Community+structure+and+metabolism+through+reconstruction+of+microbial+genomes+from+the+environment.">Community structure and metabolism through reconstruction of microbial genomes from the environment.</a> Nature. 428, 37-43 (2004).</li><li>Schneider, T., Riedel, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Environmental+proteomics:+analysis+of+structure+and+function+of+microbial+communities.">Environmental proteomics: analysis of structure and function of microbial communities.</a> Proteomics. 10 (4), 785-798 (2010).</li><li>Vogel, C., Marcotte, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insights+into+the+regulation+of+protein+abundance+from+proteomic+and+transcriptomic+analyses.">Insights into the regulation of protein abundance from proteomic and transcriptomic analyses.</a> Nature reviews. Genetics. 13 (4), 227-232 (2012).</li><li>Hettich, R. L., Pan, C., Chourey, K., Giannone, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metaproteomics:+harnessing+the+power+of+high+performance+mass+spectrometry+to+identify+the+suite+of+proteins+that+control+metabolic+activities+in+microbial+communities.">Metaproteomics: harnessing the power of high performance mass spectrometry to identify the suite of proteins that control metabolic activities in microbial communities.</a> Analytical chemistry. 85 (9), 4203-4214 (2013).</li><li>Von Bergen, M., Jehmlich, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insights+from+quantitative+metaproteomics+and+protein-stable+isotope+probing+into+microbial+ecology.">Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology.</a> The ISME journal. 7 (10), 1877-1885 (2013).</li><li>Giovannoni, S. J., Bibbs, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteorhodopsin+in+the+ubiquitous+marine+bacterium+SAR11.">Proteorhodopsin in the ubiquitous marine bacterium SAR11.</a> Nature. 438 (7064), 82-85 (2005).</li><li>Georges, A. A., El-Swais, H., Craig, S. E., Li, W. K., Walsh, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metaproteomic+analysis+of+a+winter+to+spring+succession+in+coastal+northwest+Atlantic+Ocean+microbial+plankton.">Metaproteomic analysis of a winter to spring succession in coastal northwest Atlantic Ocean microbial plankton.</a> The ISME journal. , 1-13 (2014).</li><li>Morris, R. M., Nunn, B. L., Frazar, C., Goodlett, D. R., Ting, Y. S., Rocap, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+metaproteomics+reveals+ocean-scale+shifts+in+microbial+nutrient+utilization+and+energy+transduction.">Comparative metaproteomics reveals ocean-scale shifts in microbial nutrient utilization and energy transduction.</a> The ISME journal. 4 (5), 673-685 (2010).</li><li>Williams, T. J., Cavicchioli, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Marine+metaproteomics:+deciphering+the+microbial+metabolic+food+web.">Marine metaproteomics: deciphering the microbial metabolic food web.</a> Trends in microbiology. 22 (5), 248-260 (2014).</li><li>Saito, M. a., McIlvin, M. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+nutrient+stresses+at+intersecting+Pacific+Ocean+biomes+detected+by+protein+biomarkers.">Multiple nutrient stresses at intersecting Pacific Ocean biomes detected by protein biomarkers.</a> Science. 345 (6201), 1173-1177 (2014).</li><li>Bertrand, E., Moran, D., McIlvin, M., Hoffman, J., Allen, A., Saito, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methionine+synthase+interreplacement+in+diatom+cultures+and+communities:+Implications+for+the+persistence+of+B12+use+by+eukaryotic+phytoplankton.">Methionine synthase interreplacement in diatom cultures and communities: Implications for the persistence of B12 use by eukaryotic phytoplankton.</a> Limnology and Oceanography. 58 (4), 1431-1450 (2013).</li><li>Hawley, A. K., Kheirandish, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+tools+for+investigating+microbial+community+structure+and+function+in+oxygen-deficient+marine+waters.">Molecular tools for investigating microbial community structure and function in oxygen-deficient marine waters.</a> Methods in enzymology. 531, 305-329 (2013).</li><li>Da Walsh, ., Zaikova, E., Hallam, 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=Small+volume+(1-3L)+filtration+of+coastal+seawater+samples.">Small volume (1-3L) filtration of coastal seawater samples.</a> Journal of visualized experiments: JoVE. (28), 1-2 (2009).</li><li>Thompson, M., Chourey, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+approach+for+deep+proteome+measurements+from+small-scale+microbial+biomass+samples.">Experimental approach for deep proteome measurements from small-scale microbial biomass samples.</a> Analytical. 80 (24), 9517-9525 (2008).</li><li>Lu, X., Digestion Zhu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Tube-Gel. , 1948-1958 (2005).</li><li>Sharma, R., Dill, B. D., Chourey, K., Shah, M., VerBerkmoes, N. C., Hettich, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coupling+a+detergent+lysis/cleanup+methodology+with+intact+protein+fractionation+for+enhanced+proteome+characterization.">Coupling a detergent lysis/cleanup methodology with intact protein fractionation for enhanced proteome characterization.</a> Journal of proteome research. 11 (12), 6008-6018 (2012).</li><li>Santoro, A. E., Dupont, C. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genomic+and+proteomic+characterization+of+"Candidatus+Nitrosopelagicus+brevis":+An+ammonia-oxidizing+archaeon+from+the+open+ocean.">Genomic and proteomic characterization of "Candidatus Nitrosopelagicus brevis": An ammonia-oxidizing archaeon from the open ocean.</a> Proceedings of the National Academy of Sciences. 112 (4), 1173-1178 (2015).</li><li>Rusch, D. B., Halpern, A. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Sorcerer+II+Global+Ocean+Sampling+expedition:+northwest+Atlantic+through+eastern+tropical+Pacific.">The Sorcerer II Global Ocean Sampling expedition: northwest Atlantic through eastern tropical Pacific.</a> PLoS biology. 5 (3), e77 (2007).</li><li>Swan, B. K., Martinez-Garcia, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Potential+for+chemolithoautotrophy+among+ubiquitous+bacteria+lineages+in+the+dark+ocean.">Potential for chemolithoautotrophy among ubiquitous bacteria lineages in the dark ocean.</a> Science (New York, N.Y.). 333 (6047), 1296-1300 (2011).</li><li>Rinke, C., Schwientek, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insights+into+the+phylogeny+and+coding+potential+of+microbial+dark+matter.">Insights into the phylogeny and coding potential of microbial dark matter.</a> Nature. 499 (7459), 431-437 (2013).</li><li>Saito, M. A., Bulygin, V. V., Moran, D. M., Taylor, C., Scholin, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Examination+of+microbial+proteome+preservation+techniques+applicable+to+autonomous+environmental+sample+collection.">Examination of microbial proteome preservation techniques applicable to autonomous environmental sample collection.</a> Frontiers in microbiology. 2, 215 (2011).</li><li>Shevchenko, A., Tomas, J. H., Olsen, J., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-gel+digestion+for+mass+spectrometric+characterization+of+proteins+and+proteomes.">In-gel digestion for mass spectrometric characterization of proteins and proteomes.</a> Nature protocols. 1 (6), 2856-2860 (2007).</li><li>Thomas, T., Gilbert, J., Meyer, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metagenomics+-+a+guide+from+sampling+to+data+analysis.">Metagenomics - a guide from sampling to data analysis.</a> Microbial Informatics and Experimentation. 2 (1), 3 (2012).</li><li>Huson, D. H., Auch, A. F., Qi, J., Schuster, S. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MEGAN+analysis+of+metagenomic+data.">MEGAN analysis of metagenomic data.</a> Genome research. 17 (3), 377-3786 (2007).</li><li>Huson, D. H., Mitra, S., Ruscheweyh, H. -. J., Weber, N., Schuster, S. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrative+analysis+of+environmental+sequences+using+MEGAN4.">Integrative analysis of environmental sequences using MEGAN4.</a> Genome research. 21 (9), 1552-1560 (2011).</li><li>Ea Ottesen, ., Marin, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metatranscriptomic+analysis+of+autonomously+collected+and+preserved+marine+bacterioplankton.">Metatranscriptomic analysis of autonomously collected and preserved marine bacterioplankton.</a> The ISME journal. 5 (12), 1881-1895 (2011).</li><li>Feike, J., J&#252;rgens, K., Hollibaugh, J. T., Kr&#252;ger, S., Jost, G., Labrenz, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+unbiased+metatranscriptomics+in+suboxic+waters+of+the+central+Baltic+Sea+using+a+new+in+situ+fixation+system.">Measuring unbiased metatranscriptomics in suboxic waters of the central Baltic Sea using a new in situ fixation system.</a> The ISME journal. 6 (2), 461-470 (2012).</li></ol>

The authors have nothing to disclose.

样品保存的关键是metaproteomic研究和以往的研究显示一种RNA稳定的解决方案是之前的蛋白质提取28存储单元一个有用的存储缓冲器。理想情况下，样品将在原地保留处理33,34中否定蛋白表达变化。事实上，原位采样和固定技术已经发展，其允许自主收集和保存的样品的由船部署仪器。但是，获得这些技术并不总是可行的。在于它是不常见的情况下，样品应尽快采集后保?...

微生物是无处不在，发挥在地球的生物地球化学循环1重要作用。目前，可用于表征微生物群落结构和功能众多的分子生物学方法。最常见的是16S rRNA基因的序列分析PCR扩增从环境的DNA 2 - 4。的16S rRNA基因分析的缺点在于，它仅提供了有关系统发育特征和社区结构信息，具有信息很少代谢功能。与此相反，方法，如宏基因组学，metatranscriptomics和metaproteomics提供群落结构和新陈代谢的信息。宏基因组学，或生物体的集合体的基因含量的分析，提供了有关社区5的结构和功能的潜在的信息- 8。虽然功能强大，该功能的潜在可能与代谢生物体的活动。一个生物体的基因型是由它的基因，其每一个可以被转录为RNA和进一步翻译为蛋白质，从而导致表型来表示。因此，为了在微生物的功能活性的理解有助于在一个环境，后基因组分析应进行9。因为它揭示了哪些基因被转录，在任何给定的环境Metatranscriptomics，或RNA转录物的分析是有用的。然而，mRNA水平并不总是与它们相应的蛋白质水平由于翻译调控，核糖核酸半衰期，并且可以为每10 mRNA的生成的多个蛋白副本的事实。 由于这些原因metaproteomics现已被公认为对环境微生物学的重要工具。常见metaproteomic分析用散弹枪蛋白质组学的方法，其中的蛋白质在复杂样品的近满装被纯化，并同时进行分析，通常是通过连接zymatic消化成肽和分析质谱仪。随后的串联质谱（MS / MS）“肽指纹识别”用于确定肽序列和原籍潜在蛋白由蛋白质数据库中搜索（综述见11）。蛋白质组的工作已经走过了漫长的道路，在过去25年由于增加的基因组数据的可用性和增加灵敏度和质谱仪，可用于高通量蛋白质鉴定和定量11,12的准确性。因为蛋白质是基因表达的终产物，metaproteomic数据可以帮助确定哪些生物体是活性，在任何给定的环境，什么蛋白他们表达。试图确定一组特定的环境变量会影响生物或社区的表型时，这是有利的。在早期，在海洋中的MS / MS基于metaproteomic研究中使用，以确定在目标特异性蛋白微生物谱系，与第一项研究聚焦在光驱动质子泵遗传工程中SAR11海洋细菌13。最近，比较metaproteomic分析已经阐明复杂的群体之间的差异蛋白质表达谱。例子包括代谢时间的变化在沿海西北大西洋14或南极半岛5的识别 。其他的研究已经在蛋白表达模式描述的变化跨越空间尺度，例如，沿一个地理断面从一个低营养海洋环流到高生产力的沿海上升流系统 15。对于metaproteomics进一步审查建议施奈德等人（2010）9和威廉姆斯等人 （2014）16。目标蛋白质组也已应用在近几年来量化在环境17,18特定的代谢途径的表达。 疗法e为在metaproteomic分析三个主要阶段。第一阶段是样品制备，其包括样品收集，细胞裂解和蛋白的浓度。海洋微生物学样品收集往往造成工作海水的过滤通过一个预过滤器，以去除较大的真核细胞，颗粒和微粒相关的细菌，然后进行过滤的游离活的微生物细胞的捕获，一般与使用0.22μm的盒的过滤单元19,20。这些过滤器incased在一个塑料缸和细胞裂解和蛋白提取协议，可以在过滤器单元内执行将是有价值的工具。一旦获得生物量，将细胞必须被裂解，以允许蛋白质提取。几种方法可以采用，包括盐酸胍裂解21和十二烷基硫酸钠（SDS）基裂解的方法。尽管像SDS洗涤剂非常有效地破坏细胞膜和溶解许多蛋白质​​种类，concentratiONS低至0.1％，可与下游的蛋白质的消化和质谱分析22干扰。主要关注的是SDS对胰蛋白酶消化效率的负面影响，解决的反相液相色谱法和离子抑制或堆积在离子源23中的电力。 第二阶段是分馏和分析，其中将蛋白进行酶消化，随后通过LC MS / MS分析，结果，可用于确定初始胰蛋白酶肽的一级氨基酸序列上午/ Z裂解谱。各种消化方法可根据所用洗涤剂的类型，以及下游质谱工作流来执行。在我们的协议，1-D PAGE电泳随后从凝胶去除SDS的被利用，以除去任何污染的洗涤剂。蛋白质，是难以溶解，如膜蛋白的分析，需要使用高concen的SDS或其他洗涤剂trations。这导致带SDS-凝胶电泳兼容性问题。如果研究的目标需要的这些坚硬的溶解以溶解的蛋白质，管-凝胶系统可以用来22,24。管 - 凝胶法结合了凝胶基质内的蛋白质，而无需使用电泳的。随后用于溶解任何洗涤剂蛋白质消化之前被除去。 第三个阶段是生物信息学分析。在这个阶段，MS / MS的肽数据被搜索对翻译的核苷酸序列的数据库，以确定哪些肽和蛋白质都存在于样品中。肽的识别取决于其搜索对数据库。海洋metaproteomic数据针对由参考基因组，宏基因组的数据，如全球海洋采样数据集25，以及从未开垦利单细胞扩增的基因组数据库搜索的结果通常neages 26,27。蛋白质鉴定也可以从同一个样品增加通过包含宏基因组序列作为metaproteomic数据推导5。 在这里，我们提供了一个协议，用于通过过滤收集并存储在一个稳定的RNA溶液的肽适用于MS / MS为基础的分析从微生物生物质的产生。这里所描述的协议允许DNA和蛋白质也可以从相同的样品，使所有的步骤导致到蛋白质和DNA沉淀是相同的分离。从实践的角度，需要更少的过滤，因为只有一个过滤器所需的蛋白质和DNA提取。我们还要承认，该协议是通过两个先前公布的协议相结合，改编和修改创建。细胞溶解步骤适于从齐藤等人 （2011）28和在凝胶胰蛋白酶消化成分适于从ShevcheNKO等。 （2007年）29。

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Sterivex -GP 0.22 &#956;m filter unit</td>
			<td>Millipore</td>
			<td>SVGP01050</td>
			<td>Sampling</td>
		</tr>
		<tr>
			<td>RNAlater Stabilization Solution</td>
			<td>Ambion</td>
			<td>AM7021</td>
			<td>Sampling</td>
		</tr>
		<tr>
			<td>Tris&#160;</td>
			<td>Bio Basic</td>
			<td>77-86-1 or TB0196-500G</td>
			<td>Protein Extraction/ SDS PAGE gel</td>
		</tr>
		<tr>
			<td>DTT</td>
			<td>Sigma-Aldrich</td>
			<td>D0632-1G</td>
			<td>Protein Extraction</td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>Bio Basic</td>
			<td>15-21-3</td>
			<td>Protein Extraction/ SDS PAGE gel</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>Bio Basic</td>
			<td>6381-92-6</td>
			<td>Protein Extraction</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>Fisher Scientific</td>
			<td>56-81-5</td>
			<td>Protein Extraction</td>
		</tr>
		<tr>
			<td>10K Amicon Filter</td>
			<td>Millipore</td>
			<td>UFC801024</td>
			<td>Protein Extraction</td>
		</tr>
		<tr>
			<td>Methanol</td>
			<td>Sigma-Aldrich</td>
			<td>179337-4L</td>
			<td>Protein Precipitation</td>
		</tr>
		<tr>
			<td>Acetone</td>
			<td>Fisher Scientific</td>
			<td>67-64-1</td>
			<td>Protein Precipitation</td>
		</tr>
		<tr>
			<td>MPC Protein Precipitation reagent</td>
			<td>Epicenter</td>
			<td>mmP03750</td>
			<td>DNA Precipitation</td>
		</tr>
		<tr>
			<td>2-Propanol</td>
			<td>Fisher Scientific</td>
			<td>67-63-0</td>
			<td>DNA Precipitation</td>
		</tr>
		<tr>
			<td>Qubit dsDNA BR Assay kit</td>
			<td>Life Technologies</td>
			<td>Q32850</td>
			<td>DNA Quantification</td>
		</tr>
		<tr>
			<td>Qubit Protein Assay kit</td>
			<td>Life Technologies</td>
			<td>Q33211</td>
			<td>Protein Quantification</td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>Bio Basic</td>
			<td>57-50-1</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>TEMED</td>
			<td>Bio Rad</td>
			<td>161-0800</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>APS</td>
			<td>Bio Rad</td>
			<td>161-0700</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>30% Acrylamide</td>
			<td>Bio Rad</td>
			<td>161-0158</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>SimplyBlue SafeStain</td>
			<td>Invitrogen</td>
			<td>LC6060</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>Bio Rad</td>
			<td>161-0718</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>B-mercaptoethanol</td>
			<td>Bio Basic</td>
			<td>60-24-2</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>Laemmli Sample Buffer</td>
			<td>Bio Rad</td>
			<td>161-0737</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>Precision Plus Protein Kaleidoscope Ladder</td>
			<td>Bio Rad</td>
			<td>161-0375EDU</td>
			<td>SDS PAGE gel</td>
		</tr>
		<tr>
			<td>Acetonitrile</td>
			<td>VWR</td>
			<td>CABDH6044-4</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>NH4HCO3</td>
			<td>Bio Basic</td>
			<td>1066-33-7</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>DTT</td>
			<td>Sigma-Aldrich</td>
			<td>D0632-1G</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>Formic Acid</td>
			<td>Sigma-Aldrich</td>
			<td>F0507-500ML</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>HPLC grade H2O</td>
			<td>Sigma-Aldrich</td>
			<td>270733-4L</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>Iodoacetamide</td>
			<td>Bio Basic</td>
			<td>144-48-9</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>Trypsin</td>
			<td>Promega</td>
			<td>V5111</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>Protein LoBind Tube 1.5ml</td>
			<td>Eppendorf</td>
			<td>22431081</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>2mL ROBO vial 9mm</td>
			<td>Candian Life Science</td>
			<td>VT009/C395SB</td>
			<td>In-gel Trypsin digest</td>
		</tr>
		<tr>
			<td>PP BM insert, No spring</td>
			<td>Candian Life Science</td>
			<td>4025P-631</td>
			<td>In-gel Trypsin digest</td>
		</tr>
	</tbody>
</table>

an aquatic microbial metaproteomics workflow: from cells to tryptic peptides suitable for tandem mass spectrometry-based analysis

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and metabolism. Although powerful, metagenomics alone can only elucidate functional potential. On the other hand, metaproteomics enables the description of the expressed in situ metabolism and function of a community. Here we describe a protocol for cell lysis, protein and DNA isolation, as well as peptide digestion and extraction from marine microbial cells collected on a cartridge filter unit (such as the Sterivex filter unit) and preserved in an RNA stabilization solution (like RNAlater). In mass spectrometry-based proteomics studies, the identification of peptides and proteins is performed by comparing peptide tandem mass spectra to a database of translated nucleotide sequences. Including the metagenome of a sample in the search database increases the number of peptides and proteins that can be identified from the mass spectra. Hence, in this protocol DNA is isolated from the same filter, which can be used subsequently for metagenomic analysis.

作为示范，我们进行从表面和叶绿素最大的近海在加拿大北部收集2海水样品的协议。在海上，6-7大号海水通过一个3微米的GF / D预滤器被传递，然后下面的沃尔什等人 20的协议的微生物细胞被收集到0.22微米的筒式过滤器单元。细胞立即储存在RNA稳定溶液直至进一步处理。在返回到实验室，我们执行的协议，因为它是这里提出。将浓缩的细胞裂解物分成;蛋白从90％的体积的沉淀，而DN...

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An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis

This protocol is for the extraction and concentration of protein and DNA from microbial biomass collected from seawater, followed by the generation of tryptic peptides suitable for tandem mass spectrometry-based proteomic analysis.

水生微生物Metaproteomics工作流程：从细胞对胰蛋白酶肽适合串联质谱为基础的分析

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and ...

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Research

JoVE Journal

Environment

8.7K 次观看.  Concordia University. This protocol is for the extraction and concentration of protein and DNA from microbial biomass collected from seawater, followed by the generation of tryptic peptides suitable for tandem mass spectrometry-based proteomic analysis.

视频: An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis

Characterization and Application of Passive Samplers for Monitoring of Pesticides in Water

Five different water passive samplers were calibrated under laboratory conditions for measurement of 124 legacy and current used pesticides. This study provides a protocol for the passive sampler preparation, calibration, extraction method and instrumental analysis. Sampling rates (RS) and passive sampler-water partition coefficients (KPW) were calculated for silicone rubber, polar organic chemical integrative sampler POCIS-A, POCIS-B, SDB-RPS and C18 disk. The uptake of the selected compounds depended on their physicochemical properties, i.e., silicone rubber showed a better uptake for more hydrophobic compounds (log octanol-water partition coefficient (KOW) &#62; 5.3), whereas POCIS-A, POCIS-B and SDB-RPS disk were more suitable for hydrophilic compounds (log KOW &#60; 0.70).

A protocol about the characterization and application of five different passive sampling devices is presented.

表征和被动采样的应用在农药水监测

Five different water passive samplers were calibrated under laboratory conditions for measurement of 124 legacy and current used pesticides. This study ...

科研

环境科学

Alternative Method of Removing Otoliths from Sturgeon

Extracting the otoliths (ear bones) from fish that have very thick skulls can be difficult and very time consuming. The common practice of making a transverse vertical incision on the top of the skull with a hand or electrical saw may damage the otolith if not performed correctly. Sturgeons (Acipenseridae) are one family in particular that have a very large and thick skull. A new laboratory method entering the brain cavity from the ventral side of the fish to expose the otoliths was easier than other otolith extraction methods found in the literature. Methods reviewed in the literature are designed for the field and are more efficient at processing large quantities of fish quickly. However, this new technique was designed to be more suited for a laboratory setting when time is not pressing and successful extraction from each specimen is critical. The success of finding and removing otoliths using this technique is very high and does not compromise the structure in any manner. This alternative technique is applicable to other similar fish species for extracting the otoliths.

The goal of the protocol is to show an effective method to extract the otoliths from sturgeon carcasses.

从鲟鱼去除耳石替代方法

Extracting the otoliths (ear bones) from fish that have very thick skulls can be difficult and very time consuming. The common practice of making a ...

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 ...

Characterization of Aquatic Biofilms with Flow Cytometry

Biofilms are dynamic consortia of microorganism that play a key role in freshwater ecosystems. By changing their community structure, biofilms respond quickly to environmental changes and can be thus used as indicators of water quality. Currently, biofilm assessment is mostly based on integrative and functional endpoints, such as photosynthetic or respiratory activity, which do not provide information on the biofilm community structure. Flow cytometry and computational visualization offer an alternative, sensitive, and easy-to-use method for assessment of the community composition, particularly of the photoautotrophic part of freshwater biofilms. It requires only basic sample preparation, after which the entire sample is run through the flow cytometer. The single-cell optical and fluorescent information is used for computational visualization and biological interpretation. Its main advantages over other methods are the speed of analysis and the high-information-content nature. Flow cytometry provides information on several cellular and biofilm traits in a single measurement: particle size, density, pigment content, abiotic content in the biofilm, and coarse taxonomic information. However, it does not provide information on biofilm composition on the species level. We see high potential in the use of the method for environmental monitoring of aquatic ecosystems and as an initial biofilm evaluation step that informs downstream detailed investigations by complementary and more detailed methods.

Flow cytometry in combination with visual clustering offers an easy-to-use and fast method for studying aquatic biofilms. It can be used for biofilm characterization, detection of changes in biofilm community structure, and detection of abiotic particles embedded in the biofilm.

流式细胞仪对水生生物膜的表征

Biofilms are dynamic consortia of microorganism that play a key role in freshwater ecosystems. By changing their community structure, biofilms respond ...

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 ...

Experimental Protocol for Examining Behavioral Response Profiles in Larval Fish: Application to the Neuro-stimulant Caffeine

Fish models and behaviors are increasingly used in the biomedical sciences; however, fish have long been the subject of ecological, physiological and toxicological studies. Using automated digital tracking platforms, recent efforts in neuropharmacology are leveraging larval fish locomotor behaviors to identify potential therapeutic targets for novel small molecules. Similar to these efforts, research in the environmental sciences and comparative pharmacology and toxicology is examining various behaviors of fish models as diagnostic tools in tiered evaluation of contaminants and real-time monitoring of surface waters for contaminant threats. Whereas the zebrafish is a popular larval fish model in the biomedical sciences, the fathead minnow is a common larval fish model in ecotoxicology. Unfortunately, fathead minnow larvae have received considerably less attention in behavioral studies. Here, we develop and demonstrate a behavioral profile protocol using caffeine as a model neurostimulant. Though photomotor responses of fathead minnows were occasionally affected by caffeine, zebrafish&#160;were markedly more sensitive for photomotor and locomotor endpoints, which responded at environmentally relevant levels. Future studies are needed to understand comparative behavioral sensitivity differences among fish with age and time of day, and to determine whether similar behavioral effects would occur in nature and be indicative of adverse outcomes at the individual or population levels of biological organization.

Here, we present a protocol to examine larval zebrafish and fathead minnow locomotor activities and photomotor responses (PMR) using an automated tracking software. When incorporated in common toxicology bioassays, analyses of these behaviors provide a diagnostic tool to examine chemical bioactivity. This protocol is described using caffeine, a model neurostimulant.

检测幼虫行为反应剖面的实验协议: 在神经刺激咖啡因中的应用

Fish models and behaviors are increasingly used in the biomedical sciences; however, fish have long been the subject of ecological, physiological and ...

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions

Variable microorganisms in particulate matter (PM) under different environmental conditions may have significant impacts on human health. In this study, we described a protocol for multiple analyses of the biological compositions in environmental PM. Five experiments are presented: (1) PM number monitoring by using a laser particle counter; (2) PM collection by using a cyclonic aerosol sampler; (3) PM collection by using a high-volume air sampler with filters; (4) culturable microbes collection by the Andersen six-stage sampler; and (5) detection of biological composition of environmental PM by bacterial 16SrDNA and fungal ITS region sequencing. We selected hazy days and a livestock farm as two typical examples of the application in this protocol. In this study, these two sampling methods, cyclonic aerosol sampler and filter sampler, showed different sampling efficiency. The cyclonic aerosol sampler performed much better in terms of collecting bacteria, while these two methods showed the same efficiency in collecting fungi. Filter samplers can work under low temperature conditions while cyclonic aerosol samplers have a sampling limitation for temperature. A solid impacting sampler, such as an Andersen six-stage sampler, can be used to sample bioaerosols directly into the culture medium, which increases the survival rate of culturable microorganisms. However, this method mainly relies on culture while more than 99% of microbes cannot be cultured. DNA extracted from the culturable bacteria collected by the Andersen six-stage sampler and samples collected by cyclonic aerosol sampler and filter sampler were detected by bacterial 16S rDNA and fungal ITS region sequencing.All the methods above may have wide application in many fields of study, such as environmental monitoring and airborne pathogen detection. From these results, we can conclude that these methods can be used under different conditions and may help other researchers further explore the health impacts of environmental bioaerosols.

Understanding the biological composition of environmental particulate matter is important for the study of its significant impacts on human health and disease spread. Here, we used three types of bioaerosol sampling methods and a biological analysis of airborne microbes to better explore airborne microbial communities under different environmental conditions.

不同环境条件下生物气溶胶的组成及分布分析

Variable microorganisms in particulate matter (PM) under different environmental conditions may have significant impacts on human health. In this study, ...

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

Here, we present a protocol for the sequential targeted quantification and non-targeted analysis of fluorinated compounds in water by mass spectrometry. This methodology provides quantitative levels of known fluorochemical compounds and identifies unknown chemicals in related samples with semi-quantitative estimates of their abundance.

利用目标筛选和非靶向筛选高分辨率质谱相结合的工作流程识别跨氟和多氟化学物种

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the ...

Fluorescently Labeled Bacteria as a Tracer to Reveal Novel Pathways of Organic Carbon Flow in Aquatic Ecosystems

Elucidating trophic interactions, such as predation and its effects, is a frequent task for many researchers in ecology. The study of microbial communities has many limitations, and determining a predator, prey, and predatory rates is often difficult. Presented here is an optimized method based on the addition of fluorescently labelled prey as a tracer, which allows for reliable quantitation of the grazing rates in aquatic predatory eukaryotes and estimation of nutrient transfer to higher trophic levels.

Presented here is a protocol for a single-cell, epifluorescence microscopy-based technique to quantify grazing rates in aquatic predatory eukaryotes with high precision and taxonomic resolution.

荧光标记细菌作为追踪器揭示水生生态系统中有机碳流动的新途径

Elucidating trophic interactions, such as predation and its effects, is a frequent task for many researchers in ecology. The study of microbial ...

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

An experimental setup capable of generating a periodic concentration input perturbation of oxygen was used to perform concentration-alternating frequency response analysis (cFRA) on proton-exchange membrane (PEM) fuel cells. During cFRA experiments, the modulated concentration feed was sent to the cathode of the cell at different frequencies. The electric response, which can be cell potential or current depending on the control applied on the cell, was registered in order to formulate a frequency response transfer function. Unlike traditional electrochemical impedance spectroscopy (EIS), the novel cFRA methodology makes it possible to separate the contribution of different mass transport phenomena from the kinetic charge transfer processes in the frequency response spectra of the cell. Moreover, cFRA is able to differentiate between varying humidification states of the cathode. In this protocol, the focus is on the detailed description of the procedure to perform cFRA experiments. The most critical steps of the measurements and future improvements to the technique are discussed.

We present a protocol for concentration alternating frequency response analysis of fuel cells, a promising new method of studying fuel cell dynamics.

燃料电池浓度交替频率响应分析指南

An experimental setup capable of generating a periodic concentration input perturbation of oxygen was used to perform concentration-alternating frequency ...