A.N.K. acknowledges support from NIH R33 CA225458 and R35 GM119455. We thank the Kettenbach and Gerber labs for their helpful discussion.

<ol>
	<li>Nilsson, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+phosphatases+in+the+regulation+of+mitosis.">Protein phosphatases in the regulation of mitosis.</a> Journal of Cell Biology. 218 (2), 395-409 (2019).</li><li>Brautigan, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+Ser/Thr+phosphatases--the+ugly+ducklings+of+cell+signalling.">Protein Ser/Thr phosphatases--the ugly ducklings of cell signalling.</a> The FEBS Journal. 280 (2), 324-345 (2013).</li><li>Brautigan, D. L., Shenolikar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+serine/threonine+phosphatases:+keys+to+unlocking+regulators+and+substrates.">Protein serine/threonine phosphatases: keys to unlocking regulators and substrates.</a> Annual Review of Biochemistry. 87, 921-964 (2018).</li><li>Janssens, V., Goris, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+phosphatase+2A:+A+highly+regulated+family+of+serine/threonine+phosphatases+implicated+in+cell+growth+and+signalling.">Protein phosphatase 2A: A highly regulated family of serine/threonine phosphatases implicated in cell growth and signalling.</a> Biochemical Journal. 353, 417-439 (2001).</li><li>Virshup, D. M., Shenolikar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+promiscuity+to+precision:+protein+phosphatases+get+a+makeover.">From promiscuity to precision: protein phosphatases get a makeover.</a> Molecular Cell. 33 (5), 537-545 (2009).</li><li>Bollen, M., Peti, W., Ragusa, M. J., Beullens, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+extended+PP1+toolkit:+designed+to+create+specificity.">The extended PP1 toolkit: designed to create specificity.</a> Trends in Biochemical Sciences. 35 (8), 450-458 (2010).</li><li>Qian, J., Winkler, C., Bollen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=4D-networking+by+mitotic+phosphatases.">4D-networking by mitotic phosphatases.</a> Current Opinion in Cell Biology. 25 (6), 697-703 (2013).</li><li>Heroes, 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=The+PP1+binding+code:+a+molecular-lego+strategy+that+governs+specificity.">The PP1 binding code: a molecular-lego strategy that governs specificity.</a> The FEBS Journal. 280 (2), 584-595 (2013).</li><li>Eichhorn, P. J., Creyghton, M. P., Bernards, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+phosphatase+2A+regulatory+subunits+and+cancer.">Protein phosphatase 2A regulatory subunits and cancer.</a> Biochimica et Biophysica Acta. 1795 (1), 1-15 (2009).</li><li>Bantscheff, 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=Quantitative+chemical+proteomics+reveals+mechanisms+of+action+of+clinical+ABL+kinase+inhibitors.">Quantitative chemical proteomics reveals mechanisms of action of clinical ABL kinase inhibitors.</a> Nature Biotechnology. 25 (9), 1035-1044 (2007).</li><li>Klaeger, 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=Chemical+proteomics+reveals+ferrochelatase+as+a+common+off-target+of+kinase+inhibitors.">Chemical proteomics reveals ferrochelatase as a common off-target of kinase inhibitors.</a> ACS Chemical Biology. 11 (5), 1245-1254 (2016).</li><li>Duncan, J. 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=Dynamic+reprogramming+of+the+kinome+in+response+to+targeted+MEK+inhibition+in+triple-negative+breast+cancer.">Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer.</a> Cell. 149 (2), 307-321 (2012).</li><li>Cooper, M. 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=Application+of+multiplexed+kinase+inhibitor+beads+to+study+kinome+adaptations+in+drug-resistant+leukemia.">Application of multiplexed kinase inhibitor beads to study kinome adaptations in drug-resistant leukemia.</a> PLoS ONE. 8 (6), 66755 (2013).</li><li>Lyons, S. 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=A+quantitative+chemical+proteomic+strategy+for+profiling+phosphoprotein+phosphatases+from+yeast+to+humans.">A quantitative chemical proteomic strategy for profiling phosphoprotein phosphatases from yeast to humans.</a> Molecular and Cellular Proteomics. 17 (12), 2448-2461 (2018).</li><li>Nasa, I., 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=Quantitative+kinase+and+phosphatase+profiling+reveal+that+CDK1+phosphorylates+PP2Ac+to+promote+mitotic+entry.">Quantitative kinase and phosphatase profiling reveal that CDK1 phosphorylates PP2Ac to promote mitotic entry.</a> Science Signaling. 13 (648), (2020).</li><li>Swingle, M., Ni, L., Honkanen, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Small-molecule+inhibitors+of+ser/thr+protein+phosphatases:+specificity,+use+and+common+forms+of+abuse.">Small-molecule inhibitors of ser/thr protein phosphatases: specificity, use and common forms of abuse.</a> Methods in Molecular Biology. 365, 23-38 (2007).</li><li>Moorhead, G. B. G., Haystead, T. A. J., MacKintosh, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synthesis+and+use+of+the+protein+phosphatase+affinity+matrices+microcystin-sepharose+and+microcystin-biotin-sepharose.">Synthesis and use of the protein phosphatase affinity matrices microcystin-sepharose and microcystin-biotin-sepharose.</a> Methods in Molecular Biology. 365, 39-45 (2007).</li><li>Brauer, B. L., Wiredu, K., Mitchell, S., Moorhead, G. B., Gerber, S. A., Kettenbach, A. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Affinity-based+profiling+of+endogenous+phosphoprotein+phosphatases+by+mass+spectrometry.">Affinity-based profiling of endogenous phosphoprotein phosphatases by mass spectrometry.</a> Nature Protocols. 16 (10), 4919-4943 (2021).</li><li>Hughes, C. S., Moggridge, S., M&#252;ller, T., Sorensen, P. H., Morin, G. B., Krijgsveld, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-pot,+solid-phase-enhanced+sample+preparation+for+proteomics+experiments.">Single-pot, solid-phase-enhanced sample preparation for proteomics experiments.</a> Nature Protocols. 14 (1), 68-85 (2019).</li><li>Rappsilber, J., Mann, M., Ishihama, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protocol+for+micro-purification,+enrichment,+pre-fractionation+and+storage+of+peptides+for+proteomics+using+StageTips.">Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.</a> Nature Protocols. 2 (8), 1896-1906 (2007).</li><li>Zecha, 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=TMT+labeling+for+the+masses:+A+robust+and+cost-efficient,+in-solution+labeling+approach.">TMT labeling for the masses: A robust and cost-efficient, in-solution labeling approach.</a> Molecular and Cellular Proteomics. 18 (7), 1468-1478 (2019).</li><li>Elias, J. E., Gygi, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Target-decoy+search+strategy+for+increased+confidence+in+large-scale+protein+identifications+by+mass+spectrometry.">Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.</a> Nature Methods. 4 (3), 207-214 (2007).</li><li>Eng, J. K., Jahan, T. A., Hoopmann, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comet:+an+open-source+MS/MS+sequence+database+search+tool.">Comet: an open-source MS/MS sequence database search tool.</a> Proteomics. 13 (1), 22-24 (2013).</li><li>Tyanova, 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=The+Perseus+computational+platform+for+comprehensive+analysis+of+(prote)omics+data.">The Perseus computational platform for comprehensive analysis of (prote)omics data.</a> Nature Methods. 13 (9), 731-740 (2016).</li><li>Yu, S. H., Ferretti, D., Schessner, J. P., Rudolph, J. D., Borner, G. H. H., Cox, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expanding+the+Perseus+software+for+omics+data+analysis+With+custom+plugins.">Expanding the Perseus software for omics data analysis With custom plugins.</a> Current Protocols in Bioinformatics. 71 (1), 1-29 (2020).</li></ol>

The authors have nothing to disclose and no conflicts of interest.

PIB-MS is a chemical proteomics approach used to quantitatively profile the PPPome from various sample sources in a single analysis. Much work has been done using kinase inhibitor beads to study the kinome and how it changes in cancer and other disease states10,11,12,13. Yet, the study of the PPPome lags behind. We anticipate that this approach is able to fill this gap and shed light on the regulation of cellular dephosphorylation. Here, we show that, using PIBs, we can enrich catalytic and noncatalytic components of PP1, PP2A, PP4, PP5, and PP6. We are also able to identify new candidate PPP interactors in a variety of cell lines, tissue types, and organisms.
There are several critical steps in the PIB-MS protocol that should not be overlooked. These include the incorporation of appropriate controls and replicates, the input of equal amounts of protein across all samples, the maintenance of non-denaturing conditions during sample preparation, the incubation of the sample with PIBs, and the washing of the PIBs. With respect to controls and replicates, it is important that half of each sample is treated with a PPP inhibitor if the goal is to identify novel PPP subunits and interactors. This is required to differentiate between specific and non-specific PIB interactors. If seeking to identify how known PPP subunit or PPP interactor expression changes across cell or tissue types and cell cycle phases, or upon various drug treatments, it is critical to curate a list of known PPP subunits and interactors for comparison. Furthermore, these experiments are typically done in biological triplicate to ensure statistical confidence. Equal protein input per sample is essential for data reproducibility across samples; it also ensures that differences in PPP subunit or interactor abundance are not simply due to differences in protein input. A protein assay such as a BCA must be used to determine protein concentration in each sample. Lastly, non-denaturing conditions in sample preparation, PIB enrichment, and PIB washing is critical to ensure that the proteins remain in their native state. This preserves PPP subunit interactions.
PIB-MS is a powerful tool for interrogating the PPPome, yet it comes with several limitations. PIBs can enrich for the catalytic and noncatalytic components of PP1, PP2A, PP4, PP5, and PP6, but not PP2B or PP7, since MCLR does not inhibit these phosphatases at nanomolar concentrations. It is important to note that this tool is suited for ease of identification and quantification of endogenous, MCLR-sensitive PPP holoenzymes, such as those noted. PIB-MS is unable to detect PPP holoenzymes that are inhibited by endogenous PPP inhibitors that block the PPP active site, such as &#945;4 and SET14. This technique does not require the exogenous expression of tagged PPP subunits or the use of PPP-specific antibodies. Like other affinity enrichment strategies using sepharose-based matrices, PIB-MS is prone to the binding of non-specific proteins. However, the addition of free MCLR as a negative control allows for distinguishing specific from non-specific interactors, enabling the identification of new PPP subunits and interacting proteins. Furthermore, non-specific interactors can be reduced via additional washes and the careful use of the appropriate amount of PIBs.
We have employed PIB-MS to compare the PPP expression patterns of various cancer cell lines, including breast cancer and glioblastoma14. We found that these cancer types have unique PPP expression patterns indicative of their origin14. PPPs are among the most conserved enzymes2,3. We were able to demonstrate that PIB-MS is effective in analyzing the PPPome in yeast and mouse tissues14. PIB-MS can also be used to identify differences in PPP expression patterns under various conditions, such as interphase versus mitotic samples15. Thus, PIB-MS provides insights into phosphoprotein phosphatase networks and expands our understanding of PPP regulation across multiple cell lines and disease states, as well as upon drug treatments.

Protein phosphorylation controls most cellular processes, including but not limited to the response to DNA damage, growth factor signaling, and the passage through mitosis1,2,3. In mammalian cells, the majority of proteins are phosphorylated at one or more serine, threonine, or tyrosine residues at some point in time, with phosphoserines and phosphothreonines comprising approximately 98% of all phosphorylation sites2,3. While kinases have been extensively studied in cellular signaling, the role of PPPs in the regulation of dynamic cellular processes is still emerging.
Phosphorylation dynamics are controlled by the dynamic interplay between kinases and phosphatases. In mammalian cells, there are more than 400 protein kinases that catalyze serine/threonine phosphorylation. Over 90% of these sites are dephosphorylated by phosphoprotein phosphatases (PPPs), a small family of enzymes that consists of PP1, PP2A, PP2B, PP4-7, PPT, and PPZ2,3. PP1 and PP2A are responsible for the majority of phosphoserine and phosphothreonine dephosphorylation within a cell2,3,4. The notable difference in number between kinases and phosphatases and the lack of specificity of PPP catalytic subunits in vitro led to the belief that kinases are the main determinant of phosphorylation2,3. However, multiple studies have shown phosphatases to establish substrate specificity through the formation of multimeric holoenzymes5,6,7,8,9. For example, PP1 is a heterodimer that consists of a catalytic subunit and, at a given time, one out of the more than 150 regulatory subunits6,7,8. Conversely, PP2A is a heterotrimer that is formed of a scaffolding (A), a regulatory (B), and a catalytic (C) subunit2,3,9. There are four distinct families of PP2A regulatory subunits (B55, B56, PR72, and striatin), each with multiple genes, splice variants, and localization patterns2,3,9. The multimeric nature of PPPs fills the gap in the number of kinases and PPP catalytic subunits. However, it creates analytical challenges for studying PPP signaling. To comprehensively analyze PPP signaling, it is critical to investigate the various holoenzymes within a cell or tissue. Great advances have been made in studying the human kinome through the use of kinase inhibitor beads, termed multiplex inhibitor beads or kinobeads, a chemical proteomic strategy where kinase inhibitors are immobilized on beads and mass spectrometry is used to identify enriched kinases and their interactors10,11,12,13.
We have established a similar approach to study PPP biology. This technique involves affinity capture of PPP catalytic subunits using beads with an immobilized, non-selective PPP inhibitor called microcystin-LR (MCLR) termed phosphatase inhibitor beads (PIBs)14,15. Unlike other methods that require the endogenous tagging or expression of exogenous PPP subunits that could alter protein activity or localization, PIB-MS allows for the enrichment of endogenous PPP catalytic subunits, their associated regulatory and scaffolding subunits, and interacting proteins (termed the PPPome) from cells and tissues at a given time point or under specific treatment conditions. MCLR inhibits PP1, PP2A, PP4-6, PPT, and PPZ at nanomolar concentrations, making PIBs highly effective at enriching for the PPPome16. This method can be scaled for use on any starting material from cells to clinical samples. Here, we describe in detail the use of PIBs and mass spectrometry (PIB-MS) to efficiently capture, identify, and quantify the endogenous PPPome and its modification states.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63805/63805fig1v2.jpg" /> 
Figure 1: Visual summary of the PIB-MS protocol. In a PIB-MS experiment, samples can be obtained in various forms, from cells to tumors. The sample is collected, lysed, and homogenized prior to PPP enrichment. To enrich for PPPs, the lysate is incubated with PIBs with or without a PPP-inhibitor, such as MCLR. The PIBs are then washed, and PPPs are eluted in denaturing conditions. The samples are prepared for mass spectrometry analysis by the removal of detergents through SP3 protein enrichment, tryptic digestion, and desalting. Samples can then be optionally TMT-labeled prior to mass spectrometry analysis. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63805/63805fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
PIB-MS involves lysis and clarification of cells or tissues, incubation of the lysate with PIBs, elution, and analysis of the eluate via western blotting or mass spectrometry-based approaches (Figure 1). The addition of free MCLR can be used as a control to distinguish specific PIB binders from non-specific interactors. For most applications, a label-free approach can be used to directly identify proteins in eluates. In cases where greater precision in quantification or the identification of low-abundance species is needed, further processing with tandem mass-tag (TMT) labeling can be used to increase coverage and decrease input.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Acetonitrile (ACN)</td>
			<td>Honeywell</td>
			<td>AH015-4</td>
			<td>CAUTION: ACN is flammable and toxic; wear gloves, and work in a chemical fume hood.</td>
		</tr>
		<tr>
			<td>Anhydrous Acetonitrile</td>
			<td>Sigma-Aldrich</td>
			<td>271004-100ML</td>
			<td>CAUTION: ACN is flammable and toxic; wear gloves, and work in a chemical fume hood.</td>
		</tr>
		<tr>
			<td>Benchtop centrifuge</td>
			<td>Eppendorf</td>
			<td>model no. 5424</td>
			<td></td>
		</tr>
		<tr>
			<td>Beta-glycerophosphoric acid, disodium salt pentahydrate</td>
			<td>Acros Organics</td>
			<td>410991000</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Eppendorf</td>
			<td>model no. 5810 R 15 amp version</td>
			<td></td>
		</tr>
		<tr>
			<td>Distilled water</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>Fisher Scientific</td>
			<td>BP231-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Dounce tissue grinder</td>
			<td>Fisherbrand Pellet Pestles</td>
			<td>12-141-363</td>
			<td></td>
		</tr>
		<tr>
			<td>Empore solid phase extraction disk, C18</td>
			<td>CDS Analytical</td>
			<td>76333-132</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf tubes, 1.5 mL</td>
			<td>Eppendorf</td>
			<td>22363204</td>
			<td>CRITICAL: Other tubes may leach polymer into sample, contaminating the analysis.</td>
		</tr>
		<tr>
			<td>Eppendorf tubes, 2 mL</td>
			<td>Eppendorf</td>
			<td>22363352</td>
			<td>CRITICAL: Other tubes may leach polymer into sample, contaminating the analysis.</td>
		</tr>
		<tr>
			<td>Extraction plate manifold</td>
			<td>Waters</td>
			<td>WAT097944</td>
			<td></td>
		</tr>
		<tr>
			<td>Falcon tubes, 50 mL</td>
			<td>VWR</td>
			<td>21008</td>
			<td></td>
		</tr>
		<tr>
			<td>Generic blunt end needle and plunger</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Generic magnetic separation rack</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma-Aldrich</td>
			<td>H3375</td>
			<td></td>
		</tr>
		<tr>
			<td>Hydrogen chloride (HCl)</td>
			<td>VWR Chemicals BDH</td>
			<td>BDH3028</td>
			<td>CAUTION: HCl is corrosive; wear gloves and work in a chemical fume hood.</td>
		</tr>
		<tr>
			<td>Hydroxylamine solution 50% (wt/vol)</td>
			<td>Sigma-Aldrich</td>
			<td>467804</td>
			<td></td>
		</tr>
		<tr>
			<td>Incubator, 65 &#176;C</td>
			<td>VWR</td>
			<td>model no. 1380FM</td>
			<td></td>
		</tr>
		<tr>
			<td>Koptec Pure Ethanol, 200 Proof</td>
			<td>Decon Labs</td>
			<td>V1001</td>
			<td></td>
		</tr>
		<tr>
			<td>Methanol for HPLC (MeOH)</td>
			<td>Sigma-Aldrich</td>
			<td>34860-4L-R</td>
			<td>CAUTION: MeOH is flammable and toxic; wear gloves, and work in a chemical fume hood.</td>
		</tr>
		<tr>
			<td>Microcystin LR (MCLR)</td>
			<td>Cayman Chemical</td>
			<td>10007188</td>
			<td>CAUTION: MCLR is toxic; wear gloves when handling and avoid skin contact.</td>
		</tr>
		<tr>
			<td>PBS, 1&#215; without calcium and magnesium, pH 7.4 &#177; 0.1</td>
			<td>Corning</td>
			<td>&#160;21-040-CV</td>
			<td></td>
		</tr>
		<tr>
			<td>pH test strips, such as MilliporeSigma MColorpHast pH test strips and indicator papers</td>
			<td>Fisher Scientific</td>
			<td>M1095310001</td>
			<td></td>
		</tr>
		<tr>
			<td>PIBs</td>
			<td></td>
			<td></td>
			<td>For protocol for the generation of PIBs, see Moorhead et al., 2007.</td>
		</tr>
		<tr>
			<td>Pierce BCA Protein Assay Kit</td>
			<td>Thermo Scientific</td>
			<td>23225</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips, 10 &#956;L</td>
			<td>Eppendorf</td>
			<td>22491504</td>
			<td>CRITICAL: Other tips may leach polymer into samples, contaminating the analysis.</td>
		</tr>
		<tr>
			<td>Pipette tips, 1000 &#956;L</td>
			<td>Eppendorf</td>
			<td>22491555</td>
			<td>CRITICAL: Other tips may leach polymer into samples, contaminating the analysis.</td>
		</tr>
		<tr>
			<td>Pipette tips, 200 &#956;L</td>
			<td>Eppendorf</td>
			<td>22491539</td>
			<td>CRITICAL: Other tips may leach polymer into samples, contaminating the analysis.</td>
		</tr>
		<tr>
			<td>plastic syringe, 10 mL</td>
			<td>BD</td>
			<td>309604</td>
			<td></td>
		</tr>
		<tr>
			<td>Protease inhibitor cocktail III</td>
			<td>Research Products International</td>
			<td>P50700-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Q Exactive Plus Hybrid Quadrupole-Orbitrap Mass Spectrometer, Oribtrap Fusion, Orbitrap Fusion Lumos, or Orbitrap Eclipse Tribrid Mass Spectrometer&#160;</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Refrigerated benchtop centrifuge</td>
			<td>Eppendorf</td>
			<td>model no. 5424 R</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotator (Labquake Shaker Rotisserie)</td>
			<td>Thermo Scientific</td>
			<td>13-687-12Q</td>
			<td>8 rpm rotation</td>
		</tr>
		<tr>
			<td>Sample collection plate, 96- well, 1 mL</td>
			<td>Waters</td>
			<td>WAT058957</td>
			<td></td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>Fisher Scientific</td>
			<td>BP1311-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing grade modified trypsin</td>
			<td>Promega</td>
			<td>V511C</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium azide</td>
			<td>EMD Chemicals</td>
			<td>SX0299-1</td>
			<td>CAUTION: Sodium azide is explosive and toxic; wear gloves, work in a chemical fume hood and avoid contact with metals.</td>
		</tr>
		<tr>
			<td>Sodium chloride (NaCl)</td>
			<td>Fisher Chemical</td>
			<td>S27110</td>
			<td></td>
		</tr>
		<tr>
			<td>Sonicator (Branson digital sonifier)</td>
			<td></td>
			<td>model no. SFX 250</td>
			<td></td>
		</tr>
		<tr>
			<td>SPE C18 desalting plate</td>
			<td>Waters</td>
			<td>186001828BA</td>
			<td></td>
		</tr>
		<tr>
			<td>SpeedBeads magnetic carboxylate modified particles (SP3 beads)</td>
			<td>Cytiva</td>
			<td>6.51521E+13</td>
			<td></td>
		</tr>
		<tr>
			<td>Thermomixer</td>
			<td>Eppendorf</td>
			<td>model no. 5350</td>
			<td></td>
		</tr>
		<tr>
			<td>TMT10plex Isobaric Label Reagent Set plus TMT11-131C Label Reagent, 3 &#215; 0.8 mg per tag</td>
			<td>ThermoFisher</td>
			<td>A37725</td>
			<td></td>
		</tr>
		<tr>
			<td>Trifluoroacetic acid (TFA)</td>
			<td>Honeywell</td>
			<td>T6508-25ML</td>
			<td>CAUTION: TFA is corrosive and will irritate skin on contact. Wear gloves and eye protection, and work in a chemical fume hood.</td>
		</tr>
		<tr>
			<td>Tris Base</td>
			<td>Research Products International</td>
			<td>T60040</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>Sigma-Aldrich</td>
			<td>T9284</td>
			<td></td>
		</tr>
		<tr>
			<td>Vacuum centrifuge and vapor trap</td>
			<td>Thermo Scientific</td>
			<td>model nos. SpeedVac SPD120 and RVT5105</td>
			<td></td>
		</tr>
		<tr>
			<td>Vortexer (Vortex-Genie 2)</td>
			<td>Scientific Industries</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Water LC-MS</td>
			<td>Honeywell</td>
			<td>LC365-4</td>
			<td></td>
		</tr>
	</tbody>
</table>

a mass spectrometry-based approach to identify phosphoprotein phosphatases and their interactors

Most cellular processes are regulated by dynamic protein phosphorylation. More than three-quarters of proteins are phosphorylated, and phosphoprotein phosphatases (PPPs) coordinate over 90% of all cellular serine/threonine dephosphorylation. Deregulation of protein phosphorylation has been implicated in the pathophysiology of various diseases, including cancer and neurodegeneration. Despite their widespread activity, the molecular mechanisms controlling PPPs and those controlled by PPPs are poorly characterized. Here, a proteomic approach termed phosphatase inhibitor beads and mass spectrometry (PIB-MS) is described to identify and quantify PPPs, their posttranslational modifications, and their interactors in as little as 12 h using any cell line or tissue. PIB-MS utilizes a non-selective PPP inhibitor, microcystin-LR (MCLR), immobilized on sepharose beads to capture and enrich endogenous PPPs and their associated proteins (termed the PPPome). This method does not require the exogenous expression of tagged versions of PPPs or the use of specific antibodies. PIB-MS offers an innovative way to study the evolutionarily conserved PPPs and expand our current understanding of dephosphorylation signaling.

<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63805/63805fig02.jpg" /> 
Figure 2: Identification of specific PIBs binders. (A) A variety of tissue types or cells can be analyzed via PIB-MS. HeLa cells in biological triplicate were either treated with DMSO or the PPP-inhibitor MCLR, incubated with PIBs, and analyzed via LC-MS/MS. (B) Volcano plot of PIB-MS analysis in DMSO and MCLR-treated HeLa cell lysates, with specific PIB binders shown in red. PPP catalytic subunits are labeled and shown in blue. New candidate PPP subunits or interacting proteins are shown in black. Non-specific binders are shown in grey. (C) Scatter plot of log2 area of two biological replicates from HeLa cell lysates treated with DMSO to demonstrate the reproducibility of the enrichment. Specific binders to PIBs are shown in red. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63805/63805fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63805/63805fig03.jpg" /> 
Figure 3: Network analysis of all PPP subunits and PPP-interacting proteins identified in HeLa cells. These proteins were found to be specific PIB interactors in the HeLa PIB pulldown with and without MCLR. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63805/63805fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To demonstrate the performance of the PIBs, we performed a PIB pulldown experiment in HeLa cells to identify PPPs and their interactors (Figure 2A). HeLa cells were grown in biological triplicate and lysed. Each triplicate lysate was split in half, where half was treated with MCLR for 15 min to prevent the binding of PPP catalytic subunits or DMSO before PIB enrichment was performed. Following PIB enrichment, a label-free comparison of the abundance of proteins quantified in the DMSO-treated and MCLR-treated samples was performed to distinguish specific from non-specific interactors (Figure 2B). In the analysis, we detected all MCLR-sensitive PPP catalytic subunits PP1ca, PP1cb, PP1cc, PP2Aca, PP2Acb, PP4c, PP5c, and PP6c. In the DMSO-treated samples, the abundances (log2 areas of protein quantification) were highly correlated, indicating reproducibility (Figure 2C), yet upon treatment with MCLR, the PPP catalytic subunit or PPP interacting protein abundance in PIB pulldowns was greatly reduced (Figure 2B). In this analysis, we identified 92 PPP subunits and specific PPP interactors (see Supplementary Table 1), which is comparable to a previous PIB-MS analysis in HeLa cells14 (Figure 3).
Supplementary Table 1: MS data of representative PIB-MS analysis. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63805/Supp Table 1 final.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors at JoVE.com

A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors

Here, we present a protocol for the enrichment of endogenous phosphoprotein phosphatases and their interacting proteins from cells and tissues and their identification and quantification by mass spectrometry-based proteomics.

Most cellular processes are regulated by dynamic protein phosphorylation. More than three-quarters of proteins are phosphorylated, and phosphoprotein ...

a-mass-spectrometry-based-approach-to-identify-phosphoprotein

Nanyang Technological University

Research

Education

JoVE Core

JoVE Journal

Analytical Chemistry

Biochemistry

Unit 1

Principles of Mass Spectrometry

SCIENTISTS IN ACTION

2.3K 조회수.  Geisel School of Medicine at Dartmouth. Here, we present a protocol for the enrichment of endogenous phosphoprotein phosphatases and their interacting proteins from cells and tissues and their identification and quantification by mass spectrometry-based proteomics. 

비디오: A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

시간 해결 전기 분무 이온화 수소 - 중수소 교환 질량 분석 단백질 구조와 역학 연구를위한

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. ...

연구

생화학

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.

Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.

블루 기본 페이지와 단백질 상관 관계 프로파일 링에 의한 선호도 정제 단백질 복합체 해결

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological ...

A Tandem Liquid Chromatography&#8211;Mass Spectrometry-based Approach for Metabolite Analysis of Staphylococcus aureus

In an effort to thwart bacterial pathogens, hosts often limit the availability of nutrients at the site of infection. This limitation can alter the abundances of key metabolites to which regulatory factors respond, adjusting cellular metabolism. In recent years, a number of proteins and RNA have emerged as important regulators of virulence gene expression. For example, the CodY protein responds to levels of branched-chain amino acids and GTP and is widely conserved in low G+C Gram-positive bacteria. As a global regulator in Staphylococcus aureus, CodY controls the expression of dozens of virulence and metabolic genes. We hypothesize that S. aureus uses CodY, in part, to alter its metabolic state in an effort to adapt to nutrient-limiting conditions potentially encountered in the host environment. This manuscript describes a method for extracting and analyzing metabolites from S. aureus using liquid chromatography coupled with mass spectrometry, a protocol that was developed to test this hypothesis. The method also highlights best practices that will ensure rigor and reproducibility, such as maintaining biological steady state and constant aeration without the use of continuous chemostat cultures. Relative to the USA200 methicillin-susceptible S. aureus isolate UAMS-1 parental strain, the isogenic codY mutant exhibited significant increases in amino acids derived from aspartate (e.g., threonine and isoleucine) and decreases in their precursors (e.g., aspartate and O-acetylhomoserine). These findings correlate well with transcriptional data obtained with RNA-seq analysis: genes in these pathways were up-regulated between 10- and 800-fold in the codY null mutant. Coupling global analyses of the transcriptome and the metabolome can reveal how bacteria alter their metabolism when faced with environmental or nutritional stress, providing potential insight into the physiological changes associated with nutrient depletion experienced during infection. Such discoveries may pave the way for the development of novel anti-infectives and therapeutics.

Here we describe a protocol for the extraction of metabolites from Staphylococcus aureus and their subsequent analysis via liquid chromatography and mass spectrometry.

의 대사 산물 분석을위한 탠덤 액체 크로마토 그래피 - 질량 분석 기반 접근<em&gt; 포도상 구균</em

In an effort to thwart bacterial pathogens, hosts often limit the availability of nutrients at the site of infection. This limitation can alter the ...

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most cases, the action of noncoding RNAs is mediated by proteins whose functions are in turn regulated by these interactions with noncoding RNAs. Consistent with this, a growing number of proteins involved in nuclear functions have been reported to bind RNA and in a few cases the RNA-binding regions of these proteins have been mapped, often through laborious, candidate-based methods.
Here, we report a detailed protocol to perform a high-throughput, proteome-wide unbiased identification of RNA-binding proteins and their RNA-binding regions. The methodology relies on the incorporation of a photoreactive uridine analog in the cellular RNA, followed by UV-mediated protein-RNA crosslinking, and mass spectrometry analyses to reveal RNA-crosslinked peptides within the proteome. Although we describe the procedure for mouse embryonic stem cells, the protocol should be easily adapted to a variety of cultured cells.

We describe a protocol to identify RNA-binding proteins and map their RNA-binding regions in live cells using UV-mediated photocrosslinking and mass spectrometry.

질량 분석 기반 식별 RNA 바인딩 영역에 대 한 샘플 준비

Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most ...

A Rat Methyl-Seq Platform to Identify Epigenetic Changes Associated with Stress Exposure

As genomes of a wider variety of animals become available, there is an increasing need for tools that can capture dynamic epigenetic changes in these animal models. The rat is one particular model animal where an epigenetic tool can complement many pharmacological and behavioral studies to provide insightful mechanistic information. To this end, we adapted the SureSelect Target Capture System (referred to as Methyl-Seq) for the rat, which can assess DNA methylation levels across the rat genome. The rat design targeted promoters, CpG islands, island shores, and GC-rich regions from all RefSeq genes. 
To implement the platform on a rat experiment, male Sprague Dawley rats were exposed to chronic variable stress for 3 weeks, after which blood samples were collected for genomic DNA extraction. Methyl-Seq libraries were constructed from the rat DNA samples by shearing, adapter ligation, target enrichment, bisulfite conversion, and multiplexing. Libraries were sequenced on a next-generation sequencing platform and the sequenced reads were analyzed to identify DMRs between DNA of stressed and unstressed rats. Top candidate DMRs were independently validated by bisulfite pyrosequencing to confirm the robustness of the platform.
Results demonstrate that the rat Methyl-Seq platform is a useful epigenetic tool that can capture methylation changes induced by exposure to stress.

Here, we describe the protocol and implementation of Methyl-Seq, an epigenomic platform, using a rat model to identify epigenetic changes associated with chronic stress exposure. Results demonstrate that the rat Methyl-Seq platform is capable of detecting methylation differences that arise from stress exposure in rats.

쥐 메 틸-Seq 플랫폼 관련 스트레스에 노출 된 후 변경 내용을 확인 하

As genomes of a wider variety of animals become available, there is an increasing need for tools that can capture dynamic epigenetic changes in these ...

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry

The posttranslational modification of proteins by the small protein ubiquitin is involved in many cellular events. After tryptic digestion of ubiquitinated proteins, peptides with a diglycine remnant conjugated to the epsilon amino group of lysine (&#39;K-&#949;-diglycine&#39; or simply &#39;diGly&#39;) can be used to track back the original modification site. Efficient immunopurification of diGly peptides combined with sensitive detection by mass spectrometry has resulted in a huge increase in the number of ubiquitination sites identified up to date. We have made several improvements to this workflow, including offline high pH reverse-phase fractionation of peptides prior to the enrichment procedure, and the inclusion of more advanced peptide fragmentation settings in the ion routing multipole. Also, more efficient cleanup of the sample using a filter-based plug in order to retain the antibody beads results in a greater specificity for diGly peptides. These improvements result in the routine detection of more than 23,000 diGly peptides from human cervical cancer cells (HeLa) cell lysates upon proteasome inhibition in the cell. We show the efficacy of this strategy for in-depth analysis of the ubiquitinome profiles of several different cell types and of in vivo samples, such as brain tissue. This study presents an original addition to the toolbox for protein ubiquitination analysis to uncover the deep cellular ubiquitinome.

We present a method for the purification, detection, and identification of diGly peptides that originate from ubiquitinated proteins from complex biological samples. The presented method is reproducible, robust, and outperforms published methods with respect to the level of depth of the ubiquitinome analysis.

펩타이드 농축 및 질량 분광법에 의한 단백질 유비퀴틴화 부위 검출

The posttranslational modification of proteins by the small protein ubiquitin is involved in many cellular events. After tryptic digestion of ...

Studying RNA Interactors of Protein Kinase RNA-Activated during the Mammalian Cell Cycle

Protein kinase RNA-activated (PKR) is a member of the innate immune response proteins and recognizes the double-stranded secondary structure of viral RNAs. When bound to viral double-stranded RNAs (dsRNAs), PKR undergoes dimerization and subsequent autophosphorylation. Phosphorylated PKR (pPKR) becomes active and induces phosphorylation of the alpha subunit of eukaryotic initiation factor 2 (eIF2&#945;) to suppress global translation. Increasing evidence suggests that PKR can be activated under physiological conditions such as during the cell cycle or under various stress conditions without infection. However, our understanding of the RNA activators of PKR is limited due to the lack of a standardized experimental method to capture and analyze PKR-interacting dsRNAs. Here, we present an experimental protocol to specifically enrich and analyze PKR bound RNAs during the cell cycle using HeLa cells. We utilize the efficient crosslinking activity of formaldehyde to fix PKR-RNA complexes and isolate them via immunoprecipitation. PKR co-immunoprecipitated RNAs can then be further processed to generate a high-throughput sequencing library. One major class of PKR-interacting cellular dsRNAs is mitochondrial RNAs (mtRNAs), which can exist as intermolecular dsRNAs through complementary interaction between the heavy-strand and the light-strand RNAs. To study the strandedness of these duplex mtRNAs, we also present a protocol for strand-specific qRT-PCR. Our protocol is optimized for the analysis of PKR-bound RNAs, but it can be easily modified to study cellular dsRNAs or RNA-interactors of other dsRNA binding proteins.

We present experimental approaches for studying RNA-interactors of double-stranded RNA binding protein kinase RNA-activated (PKR) during the mammalian cell cycle using HeLa cells. This method utilizes formaldehyde to crosslink RNA-PKR complexes and immunoprecipitation to enrich PKR-bound RNAs. These RNAs can be further analyzed through high-throughput sequencing or qRT-PCR.

공부 하는 단백질 키 니 아 제 RNA 포유류 세포 주기 동안 활성의 RNA 인터

Protein kinase RNA-activated (PKR) is a member of the innate immune response proteins and recognizes the double-stranded secondary structure of viral ...

A Strategy to Identify Compounds that Affect Cell Growth and Survival in Cultured Mammalian Cells at Low-to-Moderate Throughput

Cytotoxicity is a critical parameter that needs to be quantified when studying drugs that may have therapeutic benefits. Because of this, many drug screening assays utilize cytotoxicity as one of the critical characteristics to be profiled for individual compounds. Cells in culture are a useful model to assess cytotoxicity before proceeding to follow up on promising lead compounds in more costly and labor-intensive animal models. We describe a strategy to identify compounds that affect cell growth in a tdTomato expressing human neural stem cells (NSC) line. The strategy uses two complementary assays to assess cell number. One assay works via the reduction of 3-(4,5-dimethylthizol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) to formazan as a proxy for cell number and the other directly counts the tdTomato expressing NSCs. The two assays can be performed simultaneously in a single experiment and are not labor intensive, rapid, and inexpensive. The strategy described in this demonstration tested 57 compounds in an exploratory primary screen for toxicity in a 96-well plate format. Three of the hits were characterized further in a six-point dose response using the same assay set-up as the primary screen. In addition to providing excellent corroboration for toxicity, comparison of results from the two assays may be effective in identifying compounds affecting other aspects of cell growth.

It is often necessary to assess the potential cytotoxicity of a set of compounds on cultured cells. Here, we describe a strategy to reliably screen for toxic compounds in a 96-well format.

낮은 중간 처리량에서 배양 포유류 세포에서 세포 성장 및 생존에 영향을 미치는 화합물을 식별하는 전략

Cytotoxicity is a critical parameter that needs to be quantified when studying drugs that may have therapeutic benefits. Because of this, many drug ...

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Understanding the interactions between genes, the environment and management in agricultural practice could allow more accurate prediction and management of product yield and quality. Metabolomics data provides a read-out of these interactions at a given moment in time and is informative of an organism&#39;s biochemical status. Further, individual metabolites or panels of metabolites can be used as precise biomarkers for yield and quality prediction and management. The plant metabolome is predicted to contain thousands of small molecules with varied physicochemical properties that provide an opportunity for a biochemical insight into physiological traits and biomarker discovery. To exploit this, a key aim for metabolomics researchers is to capture as much of the physicochemical diversity as possible within a single analysis. Here we present a liquid chromatography-mass spectrometry-based untargeted metabolomics method for the analysis of field-grown wheat grain. The method uses the liquid chromatograph quaternary solvent manager to introduce a third mobile phase and combines a traditional reversed-phase gradient with a lipid-amenable gradient. Grain preparation, metabolite extraction, instrumental analysis and data processing workflows are described in detail. Good mass accuracy and signal reproducibility were observed, and the method yielded approximately 500 biologically relevant features per ionization mode. Further, significantly different metabolite and lipid feature signals between wheat varieties were determined.

A method for the untargeted analysis of wheat grain metabolites and lipids is presented. The protocol includes an acetonitrile metabolite extraction method and reversed phase liquid chromatography-mass spectrometry methodology, with acquisition in positive and negative electrospray ionization modes.

밀 곡물의 비표적 액체 크로마토그래피 질량 분광계 기반 대사체학 분석

Understanding the interactions between genes, the environment and management in agricultural practice could allow more accurate prediction and management ...

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Peptidoglycan is an important component of bacterial cell walls and a common cellular target for antimicrobials. Although aspects of peptidoglycan structure are fairly conserved across all bacteria, there is also considerable variation between Gram-positives/negatives and between species. In addition, there are numerous known variations, modifications, or adaptations to the peptidoglycan that can occur within a bacterial species in response to growth phase and/or environmental stimuli. These variations produce a highly dynamic structure that is known to participate in many cellular functions, including growth/division, antibiotic resistance, and host defense avoidance. To understand the variation within peptidoglycan, the overall structure must be broken down into its constitutive parts (known as muropeptides) and assessed for overall cellular composition. Peptidoglycomics uses advanced mass spectrometry combined with high-powered bioinformatic data analysis to examine peptidoglycan composition in fine detail. The following protocol describes the purification of peptidoglycan from bacterial cultures, the acquisition of muropeptide intensity data through a liquid chromatograph&#8212;mass spectrometer, and the differential analysis of peptidoglycan composition using bioinformatics.

This protocol covers a detailed analysis of peptidoglycan composition using liquid chromatography mass spectrometry coupled with advanced feature extraction and bioinformatic analysis software.