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. Prepare Reagents
<ol>
	<li>Prepare SDS-extraction solution: 0.1 M Tris-HCl pH 7.5, 5 % glycerol, 10 mM EDTA and 1 % SDS. Filter-sterilize using a 0.22 &#181;m filter and store at 4 &#176;C.</li>
	<li>Prepare stock reagents needed for the polyacrylamide gel.
	<ol>
		<li>Prepare 1.5 M Tris-HCL pH 8.8. Filter-sterilize using a 0.22 &#181;m filter and store at room temperature.</li>
		<li>0.5 M Tris-HCL pH 6.8. Filter-sterilize using a 0.22 &#181;m filter and store at room temperature.</li>
		<li>Prepare 10 % SDS. Filte...

<ol>
	<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>

Sample preservation is key to metaproteomic studies and previous work demonstrated that an RNA stabilization solution is a useful storage buffer for storing cells prior to protein extraction 28. Ideally, samples would be preserved in situ to negate shifts in protein expression during handling 33,34. In fact, in situ sampling and fixation technologies have been developed, which allow for the autonomous collection and preservation of samples by ship-deployed instruments. However, acc...

Microorganisms are ubiquitous and play essential roles in Earth&#8217;s biogeochemical cycles 1. Currently, there are numerous molecular approaches available for characterizing microbial community structure and function. Most common is the analysis of 16S rRNA gene sequences PCR-amplified from environmental DNA 2&#8211;4. A disadvantage of 16S rRNA gene analysis is that it only provides information on phylogenetic identity and community structure, with little information on metabolic function. In contrast, approaches such as metagenomics, metatranscriptomics and metaproteomics provide information on community structure and metabolism. Metagenomics, or the analysis of the gene content of an assemblage of organisms, provides information about the structure and functional potential of the community 5&#8211;8. Although powerful, this functional potential may not correspond to the metabolic activities of the organisms. An organism&#8217;s genotype is represented by its genes, each of which can be transcribed to RNA and further translated to protein, resulting in a phenotype. Thus, to aid in the understanding of microbial functional activity in an environment, post-genomic analysis should be performed 9. Metatranscriptomics, or the analysis of RNA transcripts is useful because it reveals which genes are transcribed in any given environment. However, mRNA levels do not always match their corresponding protein levels due to translational regulation, RNA half-life, and the fact that multiple protein copies can be generated for every mRNA 10.
For these reasons metaproteomics is now recognized as an important tool for environmental microbiology. Common metaproteomic analyses use a shotgun proteomic approach where the near full complement of proteins in a complex sample are purified and analyzed simultaneously, usually through enzymatic digestion into peptides and analysis on a mass spectrometer. Subsequent tandem mass spectrometry (MS/MS) &#8220;peptide fingerprinting&#8221; is used to determine the peptide sequence and potential protein of origin by protein database searching (for a review see 11). Proteomic work has come a long way in the past 25 years thanks to the increase in genomic data availability and the increase in the sensitivity and accuracy of mass spectrometers allowing for high-throughput protein identification and quantification 11,12. Since proteins are the final product of gene expression, metaproteomic data can help determine which organisms are active in any given environment and what proteins they are expressing. This is advantageous when trying to determine how a particular set of environmental variables will affect the phenotype of an organism or community. Early on, MS/MS-based metaproteomic studies in the ocean were used to identify specific proteins in targeted microbial lineages, with the first study focusing on the light driven proton pump proteorhodopsin in SAR11 marine bacteria 13. More recently, comparative metaproteomic analyses have elucidated differential protein expression patterns between complex communities. Examples include the identification of temporal shifts in metabolism in the coastal Northwest Atlantic Ocean 14 or the Antarctic Peninsula 5. Other studies have described variations in protein expression patterns across spatial scales, for instance, along a geographical transect from a low-nutrient ocean gyre to a highly productive coastal upwelling system 15. For further reviews of metaproteomics we recommend Schneider et al. (2010) 9 and Williams et al. (2014) 16. Targeted proteomics has also been employed in recent years to quantify expression of specific metabolic pathways in the environment 17,18.
There are three main phases in metaproteomic analysis. The first phase is sample preparation, which includes sample collection, cell lysis and concentration of protein. Sample collection in marine microbiology often entails the filtration of seawater through a pre-filter to remove larger eukaryotic cells, particles and particle-associated bacteria, followed by filtration for the capture of free living microbial cells, commonly with the use of a 0.22 &#181;m cartridge filter unit 19,20. These filters are incased in a plastic cylinder and a cell lysis and protein extraction protocol that can be performed within the filter unit would be a valuable tool. Once biomass is obtained, the cells must be lysed to allow for protein extraction. Several methods can be employed, including guanidine-HCl lysis 21 and sodium dodecyl sulfate (SDS)-based lysis methods. Although detergents like SDS are very efficient at disrupting membranes and solubilizing many protein types, concentrations as low as 0.1% can interfere with downstream protein digestion and MS analysis 22. Of major concern is the negative effects of SDS on trypsin digestion efficiency, resolving power of reverse phase liquid chromatography and ion suppression or accumulation inside the ion source 23.
The second phase is fractionation and analysis, where proteins are subjected to enzymatic digestion followed by LC MS/MS analysis, resulting in a m/z fragmentation pattern that can be used to ascertain the primary amino acid sequence of the initial tryptic peptide. Various digestion methods can be performed depending on the types of detergents used, as well as the downstream mass spectrometry workflow. In our protocol, 1-D PAGE electrophoresis followed by removal of SDS from the gel is utilized in order to remove any detergent contamination. The analysis of proteins that are difficult to solubilize, such as membrane proteins, requires the use of high concentrations of SDS or other detergents. This leads to compatibility issues with SDS-gel electrophoresis. If the objective of a study requires the solubilization of these hard to solubilize proteins, the tube-gel system can be used 22,24. The tube-gel method incorporates proteins within the gel matrix without the use of electrophoresis. Subsequently any detergents used for solubilization are removed before protein digestion.
The third phase is the bioinformatic analysis. In this phase the MS/MS peptide data are searched against a database of translated nucleotide sequences to determine which peptides and proteins are present in the sample. The identification of peptides is dependent on the database it is searched against. Marine metaproteomic data are commonly searched against databases comprised of reference genomes, metagenomic data such as the Global Ocean Sampling dataset 25, as well as single cell amplified genomes from uncultivated lineages 26,27. Protein identification can also be increased by the inclusion of metagenomic sequences from the same sample as the metaproteomic data was derived 5.
Here we provide a protocol for the generation of peptides suitable for MS/MS-based analysis from microbial biomass collected by filtration and stored in an RNA stabilization solution. The protocol described here allows for DNA and protein to be isolated from the same sample so that all steps leading up to the protein and DNA precipitations are identical. From a practical perspective, less filtration is required since only one filter is required for both protein and DNA extraction. We would also like to acknowledge that this protocol was created through the combination, adaptation and modification of two previously published protocols. The cell lysis steps are adapted from Saito et al. (2011) 28 and the in-gel trypsin digest component is adapted from Shevchenko et al. (2007) 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.

As a demonstration, we performed the protocol on two seawater samples collected from the surface and the chlorophyll maximum of the coastal ocean in Northern Canada. While at sea, 6-7 L of seawater was passed through a 3 &#181;m GF/D prefilter, then microbial cells were collected onto a 0.22 &#181;m cartridge filter unit following the protocol of Walsh et al. 20. Cells were immediately stored in an RNA stabilization solution until further processing. Upon returning to the lab, we performed the protoco...

Watch this Scientific Journal Video about An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis at JoVE.com

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.

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

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8.7K ビュー.  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.

ビデオ: 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.

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

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.

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.

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

Basic Research in Plasma Medicine - A Throughput Approach from Liquids to Cells

In plasma medicine, ionized gases with temperatures close to that of vertebrate systems are applied to cells and tissues. Cold plasmas generate reactive species known to redox regulate biological processes in health and disease. Pre-clinical and clinical evidence points to beneficial effects of plasma treatment in the healing of chronic ulcer of the skin. Other emerging topics, such as plasma cancer treatment, are receiving increasing attention. Plasma medical research requires interdisciplinary expertise in physics, chemistry, and biomedicine. One goal of plasma research is to characterize plasma-treated cells in a variety of specific applications. This includes, for example, cell count and viability, cellular oxidation, mitochondrial activity, cytotoxicity and mode of cell death, cell cycle analysis, cell surface marker expression, and cytokine release. This study describes the essential equipment and workflows required for such research in plasma biomedicine. It describes the proper operation of an atmospheric pressure argon plasma jet, specifically monitoring its basic emission spectra and feed gas settings to modulate reactive species output. Using a high-precision xyz-table and computer software, the jet is hovered in millisecond-precision over the cavities of 96-well plates in micrometer-precision for maximal reproducibility. Downstream assays for liquid analysis of redox-active molecules are shown, and target cells are plasma-treated. Specifically, melanoma cells are analyzed in an efficient sequence of different consecutive assays but using the same cells: measurement of metabolic activity, total cell area, and surface marker expression of calreticulin, a molecule important for the immunogenic cell death of cancer cells. These assays retrieve content-rich biological information about plasma effects from a single plate. Altogether, this study describes the essential steps and protocols for plasma medical research.

A high-throughput cold physical plasma treatment protocol of liquids and cells is shown. It involves setting up different feed gas compositions for plasma ignition, measuring the plasma&#39;s emission spectra, and the subsequent analysis of liquids and cellular activity after plasma treatment.

In plasma medicine, ionized gases with temperatures close to that of vertebrate systems are applied to cells and tissues. Cold plasmas generate reactive ...

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.

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.

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.

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

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.

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.

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.

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