Name: semi-quantitative analysis of peptidoglycan by liquid chromatography mass spectrometry and bioinformatics
Uploaded: 2020-10-13T15:00:00
Description: Watch this Scientific Journal Video about Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics at JoVE.com

The authors would like to thank Dr. Jennifer Geddes-McAlister and Dr. Anthony Clarke for their contributions in refining this protocol. This work was supported by operating grants from CIHR awarded to C.M.K (PJT 156111) and a NSERC Alexander Graham Bell CGS D awarded to E.M.A. Figures were created on BioRender.com.

1. Peptidoglycan sample preparation
<ol>
	<li>Growth of bacterial cultures 
	NOTE: The growth of the bacterial cultures will vary depending on the bacterial species and the growth conditions being examined. The experimental parameters to be tested will define the growth conditions.
	<ol>
		<li>Grow bacterial cultures under growth conditions required for the bacterial strain and experimental design. Grow bacteria as triplicate cultures (biological replicates) i.e., three separate colonies per strai...

<ol>
	<li>Vollmer, W., Blanot, D., de Pedro, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidoglycan+structure+and+architecture.">Peptidoglycan structure and architecture.</a> FEMS Microbiology Reviews. 32, 149-167 (2007).</li><li>Pazos, M., Peters, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidoglycan.">Peptidoglycan.</a> Sub-cellular Biochemistry. 92, 127-168 (2019).</li><li>Typas, A., Banzhaf, M., Gross, C. A., Vollmer, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+the+regulation+of+peptidoglycan+synthesis+to+bacterial+growth+and+morphology.">From the regulation of peptidoglycan synthesis to bacterial growth and morphology.</a> Nature Reviews. Microbiology. 10 (2), 123-136 (2011).</li><li>Yadav, A. K., Espaillat, A., Cava, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+strategies+to+preserve+cell+wall+integrity+against+environmental+threats.">Bacterial strategies to preserve cell wall integrity against environmental threats.</a> Frontiers in Microbiology. 9, 2064 (2018).</li><li>Bera, A., Herbert, S., Jakob, A., Vollmer, W., G&#246;tz, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Why+are+pathogenic+staphylococci+so+lysozyme+resistant?+The+peptidoglycan+O-acetyltransferase+OatA+is+the+major+determinant+for+lysozyme+resistance+of+Staphylococcus+aureus.">Why are pathogenic staphylococci so lysozyme resistant? The peptidoglycan O-acetyltransferase OatA is the major determinant for lysozyme resistance of Staphylococcus aureus.</a> Molecular Microbiology. 55 (3), 778-787 (2005).</li><li>Brott, A. S., Clarke, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidoglycan+O-acetylation+as+a+virulence+factor:+its+effect+on+lysozyme+in+the+innate+immune+system.">Peptidoglycan O-acetylation as a virulence factor: its effect on lysozyme in the innate immune system.</a> Antibiotics. 8 (3), 94 (2019).</li><li>Putty, S., Vemula, H., Bobba, S., Gutheil, W. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+liquid+chromatography-tandem+mass+spectrometry+assay+for+D-Ala-D-Lac:+A+key+intermediate+for+vancomycin+resistance+in+vancomycin-resistant+Enterococci.">A liquid chromatography-tandem mass spectrometry assay for D-Ala-D-Lac: A key intermediate for vancomycin resistance in vancomycin-resistant Enterococci.</a> Analytical Biochemistry. 442 (2), 166-171 (2013).</li><li>Arthur, 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=Evidence+for+in+vivo+incorporation+of+D-lactate+into+peptidoglycan+precursors+of+vancomycin-resistant+Enterococci.">Evidence for in vivo incorporation of D-lactate into peptidoglycan precursors of vancomycin-resistant Enterococci.</a> Antimicrobial Agents and Chemotherapy. 36 (4), 867-869 (1992).</li><li>Mardarowicz, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolierung+und+Charakterisierung+des+Murein-Sacculus+von+Brucella.">Isolierung und Charakterisierung des Murein-Sacculus von Brucella.</a> Z. Naturforsdig. 21, 1006-1007 (1966).</li><li>Glauner, B., H&#246;ltje, J. V., Schwarz, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+composition+of+the+murein+of+Escherichia+coli.">The composition of the murein of Escherichia coli.</a> The Journal of Biological Chemistry. 263 (21), 10088-10095 (1988).</li><li>Glauner, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Separation+and+quantification+of+muropeptides+with+high-performance+liquid+chromatography.">Separation and quantification of muropeptides with high-performance liquid chromatography.</a> Analytical Biochemistry. 172, 451-464 (1988).</li><li>Anderson, E. 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=Peptidoglycomics+reveals+compositional+changes+in+peptidoglycan+between+biofilm-+and+planktonic-derived+Pseudomonas+aeruginosa.">Peptidoglycomics reveals compositional changes in peptidoglycan between biofilm- and planktonic-derived Pseudomonas aeruginosa.</a> The Journal of Biological Chemistry. 295 (2), 504-516 (2020).</li><li>van der Aart, L. T., 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=High-resolution+analysis+of+the+peptidoglycan+composition+in+Streptomyces+coelicolor.">High-resolution analysis of the peptidoglycan composition in Streptomyces coelicolor.</a> Journal of Bacteriology. 200 (20), 00290 (2018).</li><li>Bern, M., Beniston, R., Mesnage, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Towards+an+automated+analysis+of+bacterial+peptidoglycan+structure.">Towards an automated analysis of bacterial peptidoglycan structure.</a> Analytical and Bioanalytical Chemistry. 409, 551-560 (2017).</li><li>Brott, A. S., Sychantha, D., Clarke, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assays+for+the+enzymes+catalyzing+the+O-acetylation+of+bacterial+cell+wall+polysaccharides.">Assays for the enzymes catalyzing the O-acetylation of bacterial cell wall polysaccharides.</a> Methods in Molecular Biology. 1954, 115-136 (2019).</li><li>Clarke, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compositional+analysis+of+peptidoglycan+by+high-performance+anion-exchange+chromatography.">Compositional analysis of peptidoglycan by high-performance anion-exchange chromatography.</a> Analytical Biochemistry. 212 (2), 344-350 (1993).</li><li>Rusconi, F., Douard Valton, &. #. 2. 0. 1. ;., Nguyen, R., Dufourc, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+sodium+dodecyl+sulfate+in+microliter-volume+biochemical+samples+by+visible+light+spectroscopy.">Quantification of sodium dodecyl sulfate in microliter-volume biochemical samples by visible light spectroscopy.</a> Analytical Biochemistry. 295, 31-37 (2001).</li><li>Verwer, R. W. H., Beachey, E. H., Keck, W., Stoub, A. M., Poldermans, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oriented+fragmentation+of+Escherichia+coli+sacculi+by+sonication.">Oriented fragmentation of Escherichia coli sacculi by sonication.</a> Journal of Bacteriology. 141 (1), 327-332 (1980).</li><li>Benjamini, Y., Hochberg, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlling+the+false+discovery+rate:+A+practical+and+powerful+approach+to+multiple+testing.">Controlling the false discovery rate: A practical and powerful approach to multiple testing.</a> Journal of the Royal Statistical Society: Series B (Methodological). 57 (1), 289-300 (1995).</li><li>Article, R., Alonso, A., Marsal, S., Juli&#224;, A., James Carroll, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analytical+methods+in+untargeted+metabolomics:+state+of+the+art+in+2015.">Analytical methods in untargeted metabolomics: state of the art in 2015.</a> Frontiers in Bioengineering and Biotechnology. 3, 23 (2015).</li><li>Xi, B., Gu, H., Baniasadi, H., Raftery, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistical+analysis+and+modeling+of+mass+spectrometry-based+metabolomics+data.">Statistical analysis and modeling of mass spectrometry-based metabolomics data.</a> Methods in Molecular Biology. 1198, 333-353 (2014).</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>Cox, 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=1D+and+2D+annotation+enrichment:+a+statistical+method+integrating+quantitative+proteomics+with+complementary+high-throughput+data.">1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data.</a> BMC Bioinformatics. 13, 12 (2012).</li><li>Chang, J. D., Foster, E. E., Thadani, A. N., Ramirez, A. J., Kim, 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=Inhibition+of+Staphylococcus+aureus+cell+wall+biosynthesis+by+desleucyl-oritavancin:+A+quantitative+peptidoglycan+composition+analysis+by+mass+spectrometry.">Inhibition of Staphylococcus aureus cell wall biosynthesis by desleucyl-oritavancin: A quantitative peptidoglycan composition analysis by mass spectrometry.</a> Journal of Bacteriology. 199 (15), 00278 (2017).</li><li>Glauner, B., H&#246;ltje, J. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+pattern+of+the+murein+sacculus+of+Escherichia+coli.">Growth pattern of the murein sacculus of Escherichia coli.</a> The Journal of Biological Chemistry. 265 (31), 18988-18996 (1990).</li><li>Espaillat, A., 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=Chemometric+analysis+of+bacterial+peptidoglycan+reveals+atypical+modifications+that+empower+the+cell+wall+against+predatory+enzymes+and+fly+innate+immunity.">Chemometric analysis of bacterial peptidoglycan reveals atypical modifications that empower the cell wall against predatory enzymes and fly innate immunity.</a> Journal of the American Chemical Society. 138 (29), 9193-9204 (2016).</li><li>Quintela, J. C., Caparros, M., de Pedro, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Variability+of+peptidoglycan+structural+parameters+in+Gram-negative+bacteria.">Variability of peptidoglycan structural parameters in Gram-negative bacteria.</a> FEMS Microbiology Letters. 125, 95-100 (1995).</li><li>Quintela, J. C., Zollner, P., Portillo, F. G., Allmaier, G., de Pedro, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+wall+structural+divergence+among+Thermus+spp.">Cell wall structural divergence among Thermus spp.</a> FEMS Microbiology Letters. 172, 223-229 (1999).</li><li>Torrens, G., 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=Comparative+analysis+of+peptidoglycans+from+Pseudomonas+aeruginosa+isolates+recovered+from+chronic+and+acute+infections.">Comparative analysis of peptidoglycans from Pseudomonas aeruginosa isolates recovered from chronic and acute infections.</a> Frontiers in Microbiology. 10, 0868 (2019).</li><li>Antignac, A., 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=Detailed+structural+analysis+of+the+peptidoglycan+of+the+human+pathogen+Neisseria+meningitidis.">Detailed structural analysis of the peptidoglycan of the human pathogen Neisseria meningitidis.</a> The Journal of Biological Chemistry. 278 (34), 31521-31528 (2003).</li><li>De Jonges, B. L. M., Changi, Y. S., Gage, D., Tomaszs, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidoglycan+composition+of+a+highly+methicillin-resistant+Staphylococcus+aureus+strain.+The+role+of+penicillin+binding+protein+2A.">Peptidoglycan composition of a highly methicillin-resistant Staphylococcus aureus strain. The role of penicillin binding protein 2A.</a> The Journal of Biological Chemistry. 267 (16), 11248-11264 (1992).</li><li>Lee, 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=Muropeptides+in+Pseudomonas+aeruginosa+and+their+role+as+elicitors+of+&#946;-lactam-antibiotic+resistance.">Muropeptides in Pseudomonas aeruginosa and their role as elicitors of &#946;-lactam-antibiotic resistance.</a> Angewandte Chemie - International Edition. 55, 6882-6886 (2016).</li><li>Schumann, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidoglycan+Structure.">Peptidoglycan Structure.</a> Methods in Microbiology. 38, 101-129 (2011).</li><li>Wientjes, F. B., Woldringh, C. L., Nanninga, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Amount+of+peptidoglycan+in+cell+walls+of+Gram-negative+bacteria.">Amount of peptidoglycan in cell walls of Gram-negative bacteria.</a> Journal of Bacteriology. 173 (23), 7684-7691 (1991).</li></ol>

This protocol describes a method to purify peptidoglycan from bacterial cultures, process for LC-MS detection and analyze composition using bioinformatic techniques. Here, we focus on Gram-negative bacteria and some slight modification will be required to enable analysis of Gram-positive bacteria.
The preparation of muropeptides has remained virtually the same since it was first produced in the 1960s9,11,15...

Peptidoglycan (PG) is a defining characteristic of bacteria that serves to maintain cell morphology, while providing structural support for proteins and other cellular components1,2. The backbone of PG is composed of alternating &#946;-1,4-linked N-acetyl muramic acid (MurNAc) and N-acetyl glucosamine (GlcNAc)1,2. Each MurNAc possesses a short peptide bound at the &#7429;-lactyl residue that can be crosslinked to adjacent disaccharide-linked peptides (Figure 1A,B). This crosslinking produces a mesh-like structure that encompasses the entire cell and is often referred to as a sacculus (Figure 1C). During PG synthesis, precursors are generated in the cytoplasm, and transported across the cytoplasmic membrane by flippases. Precursors are subsequently incorporated into the mature PG by transglycosylase and transpeptidase enzymes, which produce the glycosidic and peptide bonds, respectively3. However, once assembled, there are numerous enzymes produced by the bacteria that modify and/or degrade the PG to carry out a number of cellular processes, including growth and division. In addition, various modifications of the PG have been shown to confer adaptations specific to the strain, growth conditions, and environmental stress, which have been implicated in cell signalling, antimicrobial resistance, and host immune evasion4. As examples, a common modification is the addition of a C6 acetyl group on the MurNAc that confers resistance by limiting access to the glycan &#946;-1,4 linkages to host-produced lysozyme enzymes which degrade PG4,5,6. In Enterococci, substitution of the terminal &#7429;-Ala of the peptide sidechain with &#7429;-Lac confers a greater resistance to the antimicrobial, vancomycin7,8.
The general procedure for PG isolation and purification has remained relatively unchanged since it was described in the 1960s9. Bacterial membranes are dissolved through heat treatment with SDS, followed by enzymatic removal of bound proteins, glycolipids, and remaining DNA. The purified intact sacculus can be subsequently digested into the individual components by hydrolysis of the &#946;-1,4 linkage between GlcNAc and MurNAc. This digestion produces GlcNAc-MurNAc disaccharides with any structural modifications and/or crosslinks intact and are called muropeptides (Figure 1B).
Compositional analysis of PG was initially conducted through high pressure liquid chromatographic separation (HPLC) to purify each muropeptide followed by manual identification of muropeptides10,11. This has since been superseded by liquid chromatography tandem mass spectrometry (LC-MS), which increases detection sensitivity and decreases the manual workload of purifying each individual muropeptide. However, the time consuming and complex nature of the manual identification of muropeptides has remained a limiting factor, reducing the number of studies conducted. In recent years with the emergence of &#8220;omic&#8221; technologies, automated LC-MS feature extraction has become a powerful tool, allowing for rapid detection and identification of individual compounds in complex samples from very large datasets. Once the features are identified, bioinformatic software statistically compares the variation between samples using differential analysis isolating even minimal differences among the complex dataset and displaying them graphically to the user. The application of feature extraction software for the analysis of PG composition has only just begun to be explored12,13,14 and coupled to bioinformatic analysis12. Unlike proteomic analysis which benefits from the readily available protein databases that predict peptide fragmentation allowing for fully automated identification, no fragmentation library currently exists for peptidoglycomics. However, feature extraction can be coupled with known and predicted structural databases to predict muropeptide identification12. Here we present a detailed protocol for the use of LC-MS-based feature extraction combined with a muropeptide library for automated identification and bioinformatic differential analysis of PG composition (Figure 2).

<table>
	<tbody>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>C18 reverse phase column - AdvanceBio Peptide column (100 mm x 2.1 mm 2.7 &#181;m)</td>
			<td>Agilent</td>
			<td></td>
			<td>LC-MS data acquisition</td>
		</tr>
		<tr>
			<td>Heating mantle controller, Optichem</td>
			<td>Fisher</td>
			<td>50-401-788</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>Heating Mantle, 1000mL Hemispherical</td>
			<td>Fisher</td>
			<td>CG1000008</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>Incubator, 37&#176;C</td>
			<td></td>
			<td></td>
			<td>for sacculi purification and MS sample prep</td>
		</tr>
		<tr>
			<td>Leibig condenser, 300MM 24/40,</td>
			<td>Fisher</td>
			<td>CG121805</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>Lyophilizer</td>
			<td>Labconco</td>
			<td></td>
			<td>for lyophilization of sacculi</td>
		</tr>
		<tr>
			<td>Magentic stirrer</td>
			<td>Fisher</td>
			<td>90-691-18</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>mass spectrometer Q-Tof model UHD 6530</td>
			<td>Aglient</td>
			<td></td>
			<td>LC-MS data acquisition</td>
		</tr>
		<tr>
			<td>microcentrifuge filters, Nanosep MF 0.2 &#181;m</td>
			<td>Fisher</td>
			<td>50-197-9573</td>
			<td>cleanup of sample before MS injection</td>
		</tr>
		<tr>
			<td>Retort stand</td>
			<td>Fisher</td>
			<td>12-000-102</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>Retort clamp</td>
			<td>Fisher</td>
			<td>S02629</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>round bottom flask - 1 liter pyrex</td>
			<td>Fisher</td>
			<td>07-250-084</td>
			<td>for 4% SDS boil</td>
		</tr>
		<tr>
			<td>Sonicator model 120</td>
			<td>Fisher</td>
			<td>FB120</td>
			<td>for sacculi purification</td>
		</tr>
		<tr>
			<td>Sonicator - micro tip</td>
			<td>Fisher</td>
			<td>FB4422</td>
			<td>for sacculi purification</td>
		</tr>
		<tr>
			<td>Ultracentrifuge</td>
			<td>Beckman</td>
			<td></td>
			<td>sacculi wash steps</td>
		</tr>
		<tr>
			<td>Ultracentrifuge bottles, Ti45</td>
			<td>Fisher</td>
			<td>NC9691797</td>
			<td>sacculi wash steps</td>
		</tr>
		<tr>
			<td>Water supply</td>
			<td>City</td>
			<td></td>
			<td>for water cooled condenser</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Chemdraw</td>
			<td>Cambridgesoft</td>
			<td></td>
			<td>molecular editor for muropeptide fragmentation prediction</td>
		</tr>
		<tr>
			<td>Excel</td>
			<td>Microsoft</td>
			<td></td>
			<td>viewing lists of annotated muropeptides, abundance, isotopic patterns, etc.</td>
		</tr>
		<tr>
			<td>MassHunter Acquisition</td>
			<td>Aglient</td>
			<td></td>
			<td>running QTOF instrument</td>
		</tr>
		<tr>
			<td>MassHunter Mass Profiler Professional</td>
			<td>Aglient</td>
			<td></td>
			<td>bioinformatic differential analysis</td>
		</tr>
		<tr>
			<td>MassHunter Personal Compound Database and Library Manager</td>
			<td>Aglient</td>
			<td></td>
			<td>muropeptide m/z MS database</td>
		</tr>
		<tr>
			<td>MassHunter Profinder</td>
			<td>Aglient</td>
			<td></td>
			<td>recursive feature extraction</td>
		</tr>
		<tr>
			<td>MassHunter Qualitative analysis</td>
			<td>Aglient</td>
			<td></td>
			<td>viewing MS and MS/MS chromatograms</td>
		</tr>
		<tr>
			<td>Prism</td>
			<td>Graphpad</td>
			<td></td>
			<td>Graphing software</td>
		</tr>
		<tr>
			<td>Perseus</td>
			<td>Max Plank Institute of Biochemistry</td>
			<td></td>
			<td>1D annotation</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Material</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile</td>
			<td>Fisher</td>
			<td>A998-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Ammonium acetate</td>
			<td>Fisher</td>
			<td>A637</td>
			<td></td>
		</tr>
		<tr>
			<td>Amylase</td>
			<td>Sigma-Aldrich</td>
			<td>A6380</td>
			<td></td>
		</tr>
		<tr>
			<td>Boric acid</td>
			<td>Fisher</td>
			<td>BP168-1</td>
			<td></td>
		</tr>
		<tr>
			<td>DNase</td>
			<td>Fisher</td>
			<td>EN0521</td>
			<td></td>
		</tr>
		<tr>
			<td>Formic acid</td>
			<td>Sigma-Aldrich</td>
			<td>27001-500ML-R</td>
			<td></td>
		</tr>
		<tr>
			<td>LC-MS tuning mix - HP0321</td>
			<td>Agilent</td>
			<td>G1969-85000</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium chloride</td>
			<td>Sigma-Aldrich</td>
			<td>M8266</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium sulfate</td>
			<td>Sigma-Aldrich</td>
			<td>M7506</td>
			<td></td>
		</tr>
		<tr>
			<td>Mutanolysin from Streptomyces globisporus ATCC 21553</td>
			<td>Sigma-Aldrich</td>
			<td>M9901</td>
			<td></td>
		</tr>
		<tr>
			<td>Nitrogen gas (&#62;99% purity)</td>
			<td>Praxair</td>
			<td>NI 5.0UH-T</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphoric acid</td>
			<td>Fisher</td>
			<td>A242</td>
			<td></td>
		</tr>
		<tr>
			<td>Pronase E from Streptomyces griseus</td>
			<td>Sigma-Aldrich</td>
			<td>P5147</td>
			<td></td>
		</tr>
		<tr>
			<td>RNase</td>
			<td>Fisher</td>
			<td>EN0531</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium azide</td>
			<td>Fisher</td>
			<td>S0489</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium borohydride</td>
			<td>Sigma-Aldrich</td>
			<td>452890</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium dodecyl sulfate (SDS)</td>
			<td>Fisher</td>
			<td>BP166</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hydroxide</td>
			<td>Fisher</td>
			<td>S318</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Phosphate (dibasic)</td>
			<td>Fisher</td>
			<td>S373</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Phosphate (monobasic)</td>
			<td>Fisher</td>
			<td>S369</td>
			<td></td>
		</tr>
		<tr>
			<td>Stains-all</td>
			<td>Sigma-Aldrich</td>
			<td>E9379</td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

Increased detection sensitivity of MS machinery coupled with high-powered peak recognition software has improved the ability to isolate, monitor, and analyze substance compositions of complex samples in very minute detail. Using these technological advancements, recent studies on peptidoglycan composition have begun to use automated LC-MS feature extraction techniques12,13,14,24 over older HPLC...

Watch this Scientific Journal Video about Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics at JoVE.com

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

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

Peptidoglycan is an important component of bacterial cell walls and a common cellular target for antimicrobials. Although aspects of peptidoglycan ...

Peptoglycomics uses advanced mass spectrometry combined with high-powered bioinformatic data analysis to examine peptidoglycan composition in fine detail. Using bioinformatic algorithms enables the analysis, extraction, and comparison of mass spec data across a collection of data files simultaneously, decreasing the workload and increasing the accuracy. Understanding the diverse variations and modifications of peptidoglycan has implications in understanding cellular processes, including growth and division, host immune evasion, and antimicrobial resistance.We recommend preparing and analyzing a small subset of samples first to become familiar with the protocol and to act as a pilot project to assess the experimental parameters. As mass spectrometry data analysis software often varies in the definitions that are used when describing features and functions, visual demonstration will aid users in applying this protocol across platforms. For peptidoglycan sacculi extraction, resuspend frozen cell pellets at approximately one to 10 of the original culture volume in 20 millimolar sodium phosphate at four degrees Celsius before adding the cell suspension dropwise to boiling 8%SDS in 20 millimolar sodium phosphate to a final one-to-one volume.Maintain a gentle boil for 30 minutes to three hours with stirring to ensure complete membrane dissociation. The resulting mixture should be completely clear with no remaining cell clumps or viscosity. When the solution has cooled to room temperature, collect the sacculi by ultra centrifugation, followed by five to seven washes in approximately 50 milliliters of room temperature 20 millimolar sodium phosphate per wash until the wash buffer has an SDS concentration of approximately 0.001%as determined by colorimetric dye.After the last wash, resuspend the sacculi in 5 to 10 milliliters of room temperature 20 millimolar sodium phosphate and supplement the sample with 50 micrograms per milliliter of amylase, DNase, and RNase in 10 millimolar magnesium sulfate for a one-hour incubation with agitation or nutation at 37 degrees Celsius. At the end of the incubation, digest the reaction overnight with 100 micrograms per milliliter of pronase at 37 degrees Celsius. The next morning after ultra centrifugation, boil the sample for one hour in 25 milliliters of 2%SDS and 20 millimolar sodium phosphate in a steamer.At the end of the incubation, wash the sample five to seven times with 50 milliliters of room temperature double distilled water as demonstrated. When the SDS concentration reaches approximately 0.001%resuspend the pellet in a sufficient quantity of double distilled water to obtain a sacculi suspension and wash the container. After overnight storage at minus 80 degrees Celsius, lyophilize the frozen sample before diluting the sacculi to a 10 milligrams of peptidoglycan per milliliter of double distilled water concentration.For LC-MS analysis, start a new project in the instrument software and assign the appropriate LC-MS QTOF data files to the experimental condition of interest. Run the data processing wizard batch recursive feature extraction and set the data processing filters to match the parameters of the LC-MS conditions and instrumentation to accurately identify group and verify mass-to-charge peaks representing individual muropeptides. Review the results at the end of the feature extraction.If a significant number of features failed to align in a group, adjust the recursive filtering parameters to broaden or restrict the detection window as necessary. Then export the data as a compound exchange file. For differential spectral feature analysis, start a new project in the system software and follow the instructions for data import.During the data analysis, select the significance and fold change for differential analysis and set the baseline data to the median intensity across all of the data files. Once the analysis is complete, examine the resulting graphical and statistical analyses to identify muropeptides that demonstrate a significant abundance change between the tested experimental conditions. Under the project navigator, right-click on the various analyses and select an export option to save the feature details as a tsv file.Ensure to save multiple analyses to obtain all the relevant data. Within the differential analysis software, under results interpretation, select ID browser, add a library of expected muropeptide structures, and select similar parameters as demonstrated for the feature extraction to produce a predicted muropeptide annotation for each identified feature. To manually confirm the predicted muropeptide annotation, compare the mass-to-charge ratio peaks of the tandem mass spectrometry chromatogram to the predicted mass-to-charge ratio of all of the possible fragmentations of a known muropeptide structure.Use a molecular editor to draw the predicted muropeptide structure using the mass fragmentation tool to show the mass-to-charge ratio of the mass spectrometry fragments when each bond is broken either individually or in combination, then compare all of the possible fragmentations of the muropeptide structure to the tandem mass spectrometry chromatogram. To confirm the muropeptide annotation, the mass-to-charge ratio peaks of multiple fragments should be found in the tandem mass spectrometry chromatogram with a very minimal mass-to-charge ratio alignment window. To assess the global changes in muropeptide modifications, edit the tsv file of the statistically significant high-fold change muropeptides to include a single column for each muropeptide modification.Populate this column with a designation for each muropeptide annotated and upload the modified tsv file into Perseus. Under annotate rows, click categorically annotate rows and add data files to each experimental parameter. Then under test, click on two sample tests to perform a student's T test and click 1D to perform 1D annotation.An increased detection sensitivity of mass spectrometry machinery coupled with high-powered peak recognition software has improved the ability to isolate, monitor, and analyze substance compositions of complex samples in very minute detail. Associating each mass-to-charge peak extracted from the mass spectrometry data with a particular muropeptide is facilitated by cross-referencing with a database of known and predicted muropeptide structures. The fragmentation tandem mass spectrometry chromatogram for each extracted feature can be compared to the fragmentation profile of the muropeptide proposed using the database.Volcano plots can be used to highlight muropeptides that demonstrate a statistically significant high magnitude of abundance change between the tested conditions. When examined together, multiple muropeptides possessing the same modification can be examined for a trend toward one experimental condition and the entire group can be assessed for significance. Tracking a muropeptide modification in this way can identify a particular enzymatic activity that is affected by the experimental parameter.In addition, outliers from this trend may reveal enzymatic activities with a particular specificity or biological function. This procedure examines biochemical changes and biological variations in polymers, thereby providing insight into the enzymatic activity working on PG in vivo. Examining PG composition in verifying detail will aid in the understanding of complex cellular structures which has implications for many critical physiological processes.

semi-quantitative-analysis-peptidoglycan-liquid-chromatography-mass

Research

JoVE Journal

Biochemistry

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.

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

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.

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.

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

Lipid Droplet Isolation for Quantitative Mass Spectrometry Analysis

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of virion morphogenesis. Quantitative lipid droplet proteome analysis can be used to identify proteins that localize to or are displaced from lipid droplets under conditions such as virus infections. Here, we describe a protocol that has been successfully used to characterize the changes in the lipid droplet proteome following infection with HCV. We use Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) and thus label the complete proteome of one population of cells with &#34;heavy&#34; amino acids to quantitate the proteins by mass spectrometry. For lipid droplet isolation, the two cell populations (i.e.&#160;HCV-infected/&#34;light&#34; amino acids and uninfected control/&#34;heavy&#34; amino acids) are mixed 1:1 and lysed mechanically in hypotonic buffer. After removing the nuclei and cell debris by low speed centrifugation, lipid droplet-associated proteins are enriched by two subsequent ultracentrifugation steps followed by three washing steps in isotonic buffer. The purity of the lipid droplet fractions is analyzed by western blotting with antibodies recognizing different subcellular compartments. Lipid droplet-associated proteins are then separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) followed by Coomassie staining. After tryptic digest, the peptides are quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Using this method, we identified proteins recruited to lipid droplets upon HCV infection that might represent pro- or antiviral host factors. Our method can be applied to a variety of different cells and culture conditions, such as infection with pathogens, environmental stress, or drug treatment.

Lipid droplets are important organelles for the replication of several pathogens, including the Hepatitis C Virus (HCV). We describe a method to isolate lipid droplets for quantitative mass spectrometry of associated proteins; it can be used under a variety of conditions, such as virus infection, environmental stress, or drug treatment.

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of ...

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

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.

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

Nitropeptide Profiling and Identification Illustrated by Angiotensin II

Protein nitration is one of the most important post-translational modifications (PTM) on tyrosine residues and it can be induced by chemical actions of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in eukaryotic cells. Precise identification of nitration sites on proteins is crucial for understanding the physiological and pathological processes related to protein nitration, such as inflammation, aging, and cancer. Since the nitrated proteins are of low abundance in cells even under induced conditions, no universal and efficient methods have been developed for the profiling and identification of protein nitration sites. Here we describe a protocol for nitropeptide enrichment by using a chemical reduction reaction and biotin labeling, followed by high resolution mass spectrometry. In our method, nitropeptide derivatives can be identified with high accuracy. Our method exhibits two advantages compared to the previously reported methods. First, dimethyl labeling is used to block the primary amine on nitropeptides, which can be used to generate quantitative results. Second, a disulfide bond containing NHS-biotin reagent is used for the enrichment, which can be further reduced and alkylated to enhance the detection signal on a mass spectrometer. This protocol has been successfully applied to the model peptide Angiotensin II in the current paper.

Proteomic profiling of tyrosine-nitrated proteins has been a challenging technique due to the low abundance of the 3-nitrotyrosine modification. Here we describe a novel approach for nitropeptide enrichment and profiling by using Angiotensin II as the model. This method can be extended for other in vitro or in vivo systems.

Protein nitration is one of the most important post-translational modifications (PTM) on tyrosine residues and it can be induced by chemical actions of ...

Identification of Inositol Phosphate or Phosphoinositide Interacting Proteins by Affinity Chromatography Coupled to Western Blot or Mass Spectrometry

Inositol phosphates and phosphoinositides regulate several cellular processes in eukaryotes, including gene expression, vesicle trafficking, signal transduction, metabolism, and development. These metabolites perform this regulatory activity by binding to proteins, thereby changing protein conformation, catalytic activity, and/or interactions. The method described here uses affinity chromatography coupled to mass spectrometry or Western blotting to identify proteins that interact with inositol phosphates or phosphoinositides. Inositol phosphates or phosphoinositides are chemically tagged with biotin, which is then captured via streptavidin conjugated to agarose or magnetic beads. Proteins are isolated by their affinity of binding to the metabolite, then eluted and identified by mass spectrometry or Western blotting. The method has a simple workflow that is sensitive, non-radioactive, liposome-free, and customizable, supporting the analysis of protein and metabolite interaction with precision. This approach can be used in label-free or in amino acid-labelled quantitative mass spectrometry methods to identify protein-metabolite interactions in complex biological samples or using purified proteins. This protocol is optimized for the analysis of proteins from Trypanosoma brucei, but it can be adapted to related protozoan parasites, yeast or mammalian cells.

This protocol focuses on the identification of proteins that bind to inositol phosphates or phosphoinositides. It uses affinity chromatography with biotinylated inositol phosphates or phosphoinositides that are immobilized via streptavidin to agarose or magnetic beads. Inositol phosphate or phosphoinositide binding proteins are identified by Western blotting or mass spectrometry.

Inositol phosphates and phosphoinositides regulate several cellular processes in eukaryotes, including gene expression, vesicle trafficking, signal ...

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry

Cell-free protein synthesis (CFPS) is an emerging technology in systems and synthetic biology for the in vitro production of proteins. However, if CFPS is going to move beyond the laboratory and become a widespread and standard just in time manufacturing technology, we must understand the performance limits of these systems. Toward this question, we developed a robust protocol to quantify 40 compounds involved in glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, energy metabolism and cofactor regeneration in CFPS reactions. The method uses internal standards tagged with 13C-aniline, while compounds in the sample are derivatized with 12C-aniline. The internal standards and sample were mixed and analyzed by reversed-phase liquid chromatography-mass spectrometry (LC/MS). The co-elution of compounds eliminated ion suppression, allowing the accurate quantification of metabolite concentrations over 2-3 orders of magnitude where the average correlation coefficient was 0.988. Five of the forty compounds were untagged with aniline, however, they were still detected in the CFPS sample and quantified with a standard curve method. The chromatographic run takes approximately 10 min to complete. Taken together, we developed a fast, robust method to separate and accurately quantify 40 compounds involved in CFPS in a single LC/MS run. The method is a comprehensive and accurate approach to characterize cell-free metabolism, so that ultimately, we can understand and improve the yield, productivity and energy efficiency of cell-free systems.

Here, we present a robust protocol to quantify 40 compounds involved in central carbon and energy metabolism in cell-free protein synthesis reactions. The cell-free synthesis mixture is derivatized with aniline for effective separation using reversed-phase liquid chromatography and then quantified by mass spectrometry using isotopically labelled internal standards.

Cell-free protein synthesis (CFPS) is an emerging technology in systems and synthetic biology for the in vitro production of proteins. However, if CFPS is ...

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of biological membranes, energy storage and production, cellular signaling, vesicular transport of proteins, organelle biogenesis, and regulated cell death. Because the budding yeast Saccharomyces cerevisiae is a unicellular eukaryote amenable to thorough molecular analyses, its use as a model organism helped uncover mechanisms linking lipid metabolism and intracellular transport to complex biological processes within eukaryotic cells. The availability of a versatile analytical method for the robust, sensitive, and accurate quantitative assessment of major classes of lipids within a yeast cell is crucial for getting deep insights into these mechanisms. Here we present a protocol to use liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of major cellular lipids of S. cerevisiae. The LC-MS/MS method described is versatile and robust. It enables the identification and quantification of numerous species (including different isobaric or isomeric forms) within each of the 10 lipid classes. This method is sensitive and allows identification and quantitation of some lipid species at concentrations as low as 0.2 pmol/&#181;L. The method has been successfully applied to assessing lipidomes of whole yeast cells and their purified organelles. The use of alternative mobile phase additives for electrospray ionization mass spectrometry in this method can increase the efficiency of ionization for some lipid species and can be therefore used to improve their identification and quantitation.

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol using liquid chromatography coupled with tandem mass spectrometry to identify and quantify major cellular lipids in Saccharomyces cerevisiae. The described method for a quantitative assessment of major lipid classes within a yeast cell is versatile, robust, and sensitive.

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of ...