Service and Prices

Mass Spectrometry and Biomarker Discovery Core provides a wide range of mass spectrometry services as follows:

  • Identification of protein bands
  • Identification of interacting proteins (interactomes)
  • Global quantitative proteomic comparison of different samples
  • Multiplexed (up to 11plex) quantitative proteomics
  • Metabolomic analysis
  • Lipidomic analysis
  • Highly sensitive quantification of target proteins
  • High-throughput (>100 samples/day) targeted protein quantification
  • Global quantitative phosphoproteomics
  • Global quantitative palmitoyl-proteomics
  • Global quantitative proteomic analysis of other post-translational modifications
  • Characterization of post-translational modifications on target proteins
  • Ultra-deep proteome sequencing
  • Characterization of endogenous (natural) peptides
  • Characterization of synthetic compounds
  • Cholesterol quantification
  • Androgen quantification

For more details, please see below. The listed prices are for internal Cedars-Sinai users only. External users please contact Wei Yang, PhD, at wei.yang@cshs.org or Bo Zhou, PhD, at bo.zhou@cshs.org for quotations. For any other mass spectrometry-related services, please feel free to contact us.


Identification of Protein Bands ($100/band)

Mass spectrometry is an ideal technology for the identification of unknown proteins from single gel bands. With the ultra-high sensitivity of Fusion Lumos, any Coomassie blue-visible protein bands of interest can be identified by liquid chromatography tandem mass spectrometry (LC-MS/MS). Most silver staining-visible protein bands can also be identified, as long as a mass spectrometry-compatible silver staining method (e.g., using the Pierce Silver Staining for Mass Spectrometry Kit, Thermo #24600) instead of a conventional silver staining method is used.

Figure 1. A common workflow for the identification of protein bands by LC-MS/MS. A gel band is excised from an SDS-PAGE gel and further cut into small gel particles. Following gel destaining, proteins are reduced by dithiothreitol, alkylated by iodoacetamide and digested by trypsin in gel. Tryptic peptides are extracted, concentrated and analyzed by LC-MS/MS. The acquired MS data are analyzed by Proteome Discoverer to identify proteins with a false discovery rate of ≤1%. Please refer to (Di Vizio et al. 2009) for gel band identification.


Identification of Interacting Proteins (Interactomes) ($100/sample)

A protein rarely functions alone. Instead, it interacts with other proteins to execute its functions. Likewise, proteins may bind to DNAs or RNAs to change their fate or function. Therefore, it is important to identify proteins interacting with a target protein, RNA or DNA molecule. Immunoprecipitation or affinity purification is typically used to pull down such complexes. Nevertheless, one particular challenge is how to distinguish authentic binding partners from co-enriched contaminating proteins that nonspecifically bind to beads and/or IgGs. By label-free quantitative proteomic comparison of proteins enriched from the experimental verses control conditions, binding partners can be effectively distinguished from contaminating proteins, because the former is significantly enriched in the experimental conditions, whereas the latter is present at similar levels at both experimental and control conditions.

Figure 2. Application of label-free quantitative proteomics to distinguish interacting proteins from co-enriched contaminating (background) proteins. Enriched complexes (≥ 3 replicates) are run into an SDS-PAGE gel for a short range until all proteins enter the separating gel. As such, mass spectrometry-incompatible detergents and/or salts in the samples can be easily washed away from proteins trapped in gel. Gel areas containing proteins are excised and further cut into small gel particles. Proteins are reduced by dithiothreitol, alkylated by iodoacetamide, and digested by trypsin in gel. Tryptic peptides are extracted, concentrated and analyzed by LC-MS/MS. The acquired MS data are analyzed by MaxQuant to identify proteins with a false discovery rate of ≤1% and to quantify proteins. To distinguish interacting proteins from background proteins, a statistical analysis needs to be conducted. Please refer to (Morley et al. 2015) and/or (Han et al. 2018) for protein interactome analysis as well as (Xie et al. 2018) for RNA-interacting protein identification.

Global Quantitative Proteomic Comparison of Different Samples ($250/sample)

In many functional or biomarker discovery studies, researchers are interested in the differences between proteomes under different conditions, for example, disease verses healthy, before treatment verses after treatment and gene overexpression/knockdown/knockout verses control. Label-free quantitative proteomics is a convenient and widely used method to compare different samples in order to identify differentially expressed proteins and thus deregulated pathways and biological processes.

Figure 3. A common workflow for label-free quantitative proteomic comparison of different samples. Proteins are extracted and digested into peptides. Different samples are sequentially analyzed by LC-MS/MS to profile protein contents in an unbiased fashion. The resulting mass spectrometry data are analyzed by MaxQuant or Proteome Discoverer to identify and quantify thousands of proteins across different conditions.

Multiplexed (up to 11plex) Quantitative Proteomics Using Tandem Mass Tags (TMT) (≥$300/sample)

Using either the data-dependent acquisition or the data-independent acquisition mode, label-free proteomic analysis allows relatively simple and scalable profiling of proteomes. Nevertheless, label-free proteomic analysis lacks multiplexing capability and thus only provides a relatively low throughput (typically 6–12 samples per day). In comparison, isobaric labeling-based technologies such as the 11plex tandem mass tags (TMT11plex) enable simultaneous analysis of up to 11 samples in a single run. Consequently, the cost of total instrument time is dramatically decreased. Moreover, TMT-based quantitative proteomics generally provides significantly higher quantification accuracy than label-free quantitative proteomics.

Figure 4. A schematic of TMT-based multiplexed quantitative proteomics. Following protein extraction, same amount of proteins from up to 11 samples are digested into tryptic peptides by filter-aided sample preparation (FASP), and the resulting peptides are differentially labeled with 11 chemically identical but isotopically different TMT reagents (shown in the left box) in parallel. Differentially TMT-labeled peptides are combined, desalted, and analyzed by liquid chromatography-synchronous precursor selection-MS/MS/MS (LC-SPS-MS3) for global protein identification and accurate quantification. Notably, the SPS-MS3 technology eliminates precursor ion interference and thus provides highly accurate quantification results (McAlister et al. 2014).


Metabolomic Analysis (≥$200/sample)

Metabolomics—the study of small-molecule metabolite profiles—is the systematic study of the unique chemical fingerprints that specific cellular processes leave behind. Thus, metabolomic studies improve our understanding of the influences of genes, microbiome, diet, lifestyle and drug treatment.

Figure 5. A typical workflow for untargeted metabolomic analysis. Metabolites can be extracted from cells, tissues, biofluids and extracellular vesicles (EVs). Hydrophilic metabolites are extracted by methanol and the metabolite-containing upper layer is dried down and reconstituted with a suitable buffer, prior to hydrophilic interaction chromatography-tandem mass spectrometry analysis with a positive or negative ion-scanning mode. Hydrophobic metabolites are extracted by chloroform/methanol and the metabolite-containing lower layer is dried down and reconstituted with a suitable buffer, prior to reversed-phase LC-MS/MS with a positive or negative ion-scanning mode. The acquired data are analyzed by Compound Discoverer for metabolite identification and quantification.


Lipidomic Analysis (≥$200/sample)

Lipids play important functions such as being the structural and functional component of membranes, a key form of energy storage within lipid droplets, as well as critical intracellular and extracellular signaling molecules. Lipidomics aim to map and quantify lipid species within a cell or tissue to identify biomarkers and to elucidate metabolism at the cellular level.

Figure 6. A typical workflow for untargeted lipidomic analysis. Lipids are extracted from cells, tissues or EVs by methyl-tert-butyl ether, dried down and reconstituted in isopropanol/methanol mixture for LC-MS/MS analysis using a positive-negative ion switching method (Breitkopf et al. 2017). The acquired mass spectrometry data are analyzed by LipidSearch to identify and quantify about 1,000–1,500 lipid species.


Highly Sensitive Targeted Protein Quantification Using Internal Standard Triggered-Parallel Reaction Monitoring (IS-PRM) (project-based, please request for price quotation)

Researchers often rely on Western blotting to compare the expression and/or modification levels of proteins across different samples. However, Western blotting is only semi-quantitative and relies on high-quality antibodies that are not always available. Internal standard triggered-parallel reaction monitoring is a recently developed antibody-independent targeted mass spectrometry method that enables highly sensitive quantification of target proteins or peptides (Gallien et al. 2015). Compared with the traditional selected reaction monitoring (SRM) method, which is also known as multiple reaction monitoring (MRM), IS-PRM is easier to set up and offers higher or similar sensitivity.

Figure 7. Internal standard-triggered parallel reaction monitoring allows highly sensitive quantification of target proteins or peptides. (A) A typical workflow for IS-RPM assays. Proteins are extracted and digested into peptides using FASP. Appropriate amounts of synthetic stable isotope-labeled peptide standards are spiked into each sample. These internal standards are used to trigger PRM analysis of endogenous peptides of interest, which are surrogates of target proteins. The resulting IS-PRM data are analyzed by PinPoint to compute the relative abundance of each target peptide across different samples. (B) IS-PRM provides higher sensitivity than SRM/MRM and parallel reaction monitoring (PRM). In an example provided in (Gallien et al. 2015), most of the SRM transitions were heavily interfered by background signals, resulting in an undistinguishable elution profile. The regular PRM analysis showed limited ion statistics and inconsistent relative intensities. In comparison, the IS-PRM analysis provided higher signal to noise ratios and consistent relative ion intensities.


High-Throughput (>100 samples/day) Targeted Protein Quantification Using TOMAHAQ (≥$250/sample)

Targeted protein quantification by SRM/MRM or PRM suffers from some limitations including relatively low throughput, because samples need to be analyzed one by one. In comparison, a novel technology named Triggered by Offset, Multiplexed, Accurate mass, High-resolution, Absolute Quantification (TOMAHAQ) enables the quantification of target peptides (including post-translationally modified peptides) in up to 11 sample conditions simultaneously (Erickson et al. 2017). Because it allows accurate quantification of tens of proteins across over 100 samples per day, TOMAHAQ is an ideal method for the quantification of target proteins (e.g., candidate protein biomarkers) across hundreds to thousands of samples with days of instrument time.

Figure 8. A schematic of TOMAHAQ-enabled high-throughput (>100 samples/day) quantification of target proteins. Following protein extraction, same amount of proteins from up to 11 samples are digested into tryptic peptides, which are then differentially labeled with 11 chemically identical but isotopically different TMT reagents in parallel. Differentially TMT-labeled peptides are combined, followed by the addition of appropriate amounts of TMT0-labeled synthetic peptide standards. These peptide standards are used to trigger Synchronous Precursor Selection-MS/MS/MS (SPS-MS3) analyses of TMT11plex-labeled endogenous target peptides, leading to accurate quantification of tens of target proteins across 11 samples within a single 2 h analysis. Consequently, over 100 samples can be analyzed by TOMAHAQ within a single day.


Global Quantitative Phosphoproteomics (≥$300/sample)

Protein phosphorylation plays a crucial role in cell signaling and its deregulation causes many human diseases. Mass spectrometry-based quantitative phosphoproteomics is a powerful tool for determining global changes of protein phosphorylation at the amino-acid-residue resolution and identifying aberrantly activated kinases.

Figure 9. A typical workflow for quantitative phosphoproteomic analysis. Proteins are extracted and digested into peptides, followed by the specific enrichment of phosphopeptides using titanium dioxide beads. The enriched phosphopeptides are analyzed by LC-MS/MS for phosphopeptide identification and label-free quantification. Differentially phosphorylated sites can be determined after statistical analysis and deregulated kinases can be predicted by kinase-substrate enrichment analysis.

Global Quantitative Palmitoyl-Proteomics (≥$300/sample)

Protein palmitoylation is the only reversible lipid modification and plays a critical role in regulating the localization, activity, stability and complex formation of >2,000 human proteins. Well-known palmitoyl-proteins include Ras family proteins, small G proteins, and Src family tyrosine kinases. Global quantitative palmitoyl-proteomics allows the detection of aberrantly palmitoylated proteins in an unbiased fashion.

Figure 10. A schematic of palmitoyl-proteomic analysis by Palmitoyl-protein Identification and Site Characterization (PalmPISC). In PalmPISC (Yang et al. 2010) (Dowal et al. 2011), non-palmitoylated cysteines are blocked by N-ethylmaleimide. Subsequently, palmitoyl groups are specifically removed by neutral hydroxylamine (NH2OH) and the newly formed thiol groups are conjugated by biotin-HPDP. The in vitro biotinylated (formerly palmitoylated) proteins are enriched by streptavidin affinity purification, eluted by a reducing agent TCEP, digested by trypsin, and analyzed by LC-MS/MS for palmitoyl-protein identification. Alternatively, the in vitro biotinylated (formerly palmitoylated) proteins are digested into peptides, followed by streptavidin affinity purification to enrich biotinylated (formerly palmitoylated) peptides and LC-MS/MS analysis to characterize palmitoylation sites.


Global Quantitative Proteomic Analysis of Other Post-Translational Modifications (≥$300/sample)

In addition to protein phosphorylation and palmitoylation, many other post-translational modifications (PTMs) also play key roles in various biological processes. These PTMs such as oxidation, ubiquitination, acetylation, methylation and glycosylation can be enriched by antibodies or chemical approaches, followed by LC-MS/MS analysis to identify site-specific modifications in an unbiased fashion. For quantitative redox proteomics please refer to Waldron et al. 2018.

Figure 11. Global proteomic analysis of PTMs such as ubiquitination, acetylation and methylation. In general, proteins are extracted and digested into peptides. Modified peptides are highly enriched using PTM-specific antibodies and sequenced by LC-MS/MS for site-specific identification and quantification.


Characterization of PTMs on Target Proteins ($300/protein)

Post-translational modifications play critical roles in regulating protein activity, localization, stability and complex formation. Mass spectrometry is a powerful tool to characterize PTMs at the amino-acid-residue resolution on a purified target protein.

Figure 12. A typical workflow for identifying site-specific PTMs on a target protein. Purified target proteins are separated from residual contaminating proteins by SDS-PAGE. Target protein bands are excised, pooled, and further cut into small gel particles. Proteins are reduced by dithiothreitol, alkylated by iodoacetamide, and digested by trypsin in gel. Tryptic peptides are extracted, concentrated, and analyzed by LC-MS/MS using the collision induced dissociation (CID), higher energy collisional dissociation (HCD), and electron transfer dissociation (ETD) fragmentation methods. The acquired MS data are analyzed by Proteome Discoverer software using the error-tolerant search mode to identify PTMs at the site-specific level.


Ultra-Deep Proteome Sequencing (please request for price quotation)

In the post-genomic era, it is important to profile the entire set of proteins expressed by a genome—the proteome, because proteins are the major functional molecules and drug targets. By integrating whole genome, transcriptome and proteome sequencing datasets, researchers can collect information of different layers and thus obtain a more comprehensive overview of molecular events involved in disease pathogenesis and progression.

Figure 13. A schematic of whole proteome sequencing. Proteins are extracted from cells, tissues, biofluids or EVs and digested into peptides using FASP. Peptides are fractionated into 12 to 24 fractions by high-pH, ultra-performance liquid chromatography (UPLC). These peptide fractions are sequentially analyzed by regular low-pH LC-MS/MS. The resulting 12–24 mass spectrometry files are analyzed by MaxQuant or Proteome Discoverer to identify expressed proteins, including those derived from genetic aberrations such as fusion genes and alterative splicing events.


Characterization of Endogenous (Natural) Peptides (≥$150/sample)

Rather than simply being protein degradation products, many endogenous peptides are bioactive and act as hormones, neurotransmitters and antimicrobial agents in vivo. Liquid chromatography tandem mass spectrometry has been proven to be a powerful tool in detailed characterization of purified peptides as well as in global analysis of the peptidome—all the peptides in a cell, tissue or organism.

Figure 14. Characterization of endogenous (natural) peptides such as neuropeptides and major histocompatibility complex-bound peptides by LC-MS/MS. Peptide samples are cleaned up to remove mass spectrometry-incompatible detergents and salts, followed by LC-MS/MS characterization using different fragmentation methods such as CID, HCD and ETD to provide detailed structural information.


Characterization of Synthetic Compound (≥$30/sample)

To determine the successful synthesis of chemical compounds, mass spectrometry can be used to measure the molecular weight of each purified compound and estimate its purity.

Figure 15. A representative mass spectrum of a synthetic compound. The Fusion Lumos mass spectrometer provides very high mass accuracy (<0.5 mDa). For detailed structural characterization, MSn can be conducted on each compound.


Cholesterol Quantification (≥$150/sample)

Cholesterol and its derivatives are important constituents of cell membranes and precursors of other steroid compounds. Their deregulation is associated with increased risk of coronary heart disease and cancer. The expression levels of cholesterol and its derivates like 27-hydroxycholesterol in cells, tissues and serum can be determined by liquid chromatography-parallel reaction monitoring (LC-PRM).

Figure 16. A schematic of LC-PRM quantification of cholesterol (and its derivatives like 27-hydroxycholesterol). Appropriate amounts of stable isotope-labeled cholesterol standards are spiked into samples. Following sterol extraction, endogenous and stable isotope-labeled cholesterols are labeled with 4-(dimethylamino)phenyl isocyanate (DMAPI) to boost assay sensitivity (Ayciriex et al. 2012). The DMAPI-derivatized cholesterols are extracted and analyzed by LC-PRM to determine the absolute amount of endogenous cholesterol (and its derivatives).


Androgen Quantification (≥$150/sample)

Androgens such as testosterone (T) and dihydrotestosterone (DHT) are steroid hormones that regulate the development and maintenance of male characteristics. Sensitive and specific quantification of T and DHT in body fluids or tissues are useful for the diagnosis and treatment of diseases caused by aberrant production of T and/or DHT.

Figure 17. A schematic of LC-PRM quantification of testosterone and dihydrotestosterone. Appropriate amounts of stable isotope-labeled T and DHT standards (i.e., heavy T and DHT, abbreviated as hT and hDHT, respectively) are spiked into samples. Following androgen extraction, endogenous and stable isotope-labeled T and DHT are labeled with 2-hydrazino-4-(trifluoromethyl)-pyrimidine (HTP) to boost assay sensitivity (Weng et al. 2010). The HTP-derivatized T and DHT are extracted and analyzed by LC-PRM to determine the absolute amount of endogenous T and DHT.



References

Ayciriex S, Regazzetti A, Gaudin M, Prost E, Dargére D, Massicot F, Auzeil N, Laprévote O. Development of a novel method for quantification of sterols and oxysterols by UPLC-ESI-HRMS: Application to a neuroinflammation rat model. Anal Bioanal Chem. 2012 Dec;404(10):3049-3059. https://link.springer.com/article/10.1007%2Fs00216-012-6396-6.

Breitkopf SB, Ricoult SJH, Yuan M, Xu Y, Peake DA, Manning BD, Asara JM. A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source. Metabolomics. 2017 Mar;13(3). pii:30. https://link.springer.com/article/10.1007%2Fs11306-016-1157-8.

Dowal L, Yang W, Freeman MR, Steen H, Flaumenhaft R. Proteomic analysis of palmitoylated platelet proteins. Blood. 2011 Sep 29;118(13):e62-73. http://www.bloodjournal.org/content/118/13/e62?sso-checked=true.

Erickson BK, Rose CM, Braun CR, Erickson AR, Knott J, McAlister GC, Wühr M, Paulo JA, Everley RA, Gygi SP. A strategy to combine sample multiplexing with targeted proteomics assays for high-throughput protein signature characterization. Mol Cell. 2017 Jan 19:65(2):361-370. https://www.cell.com/molecular-cell/fulltext/S1097-2765(16)30818-8.

Gallien S, Kim SY, Domon B. Large-scale targeted proteomics using internal standard triggered-parallel reaction monitoring (IS-PRM). Mol Cell Proteomics. 2015 Jun;14(6):1630-1644. http://www.mcponline.org/content/14/6/1630.

Han B, Zhou B, Qu Y, Gao B, Xu Y, Chung S, Tanaka H, Yang W, Giuliano AE, Cui X. FOXC1-induced non-canonical WNT5A-MMP7 signaling regulates invasiveness in triple-negative breast cancer. Oncogene. 2018 Mar;37(10):1399-1408. http://www.nature.com/articles/s41388-017-0021-2.

McAlister GC, Nusinow DP, Jedrychowski MP, Wühr M, Huttlin EL, Erickson BK, Rad R, Haas W, Gygi SP. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Chem. 2014 Jul 15;86(14):7150-7158. https://pubs.acs.org/doi/10.1021/ac502040v.

Morley S, You S, Pollan S, Choi J, Zhou B, Hager MH, Steadman K, Spinelli C, Rajendran K Gertych A, et al. Regulation of microtubule dynamics by DIAPH3 influences amoeboid tumor cell mechanics and sensitivity to taxanes. Sci Rep. 2015 Jul 16;5:12136. http://www.nature.com/articles/srep12136.

Di Vizio D, Kim J, Hager MH, Morello M, Yang W, Lafargue CJ, True LD, Rubin MA, Adam RM, Beroukhim R, et al. Oncosome formation in prostate cancer: association with a region of frequent chromosomal deletion in metastatic disease. Cancer Res. 2009 Jul 1;69(13):5601-5609. http://cancerres.aacrjournals.org/content/69/13/5601.

Waldron RT, Su HY, Piplani H, Capri J, Cohn W, Whitelegge JP, Faull KF, Sakkiah S, Abrol R, Yang W, et al. Ethanol induced disordering of pancreatic acinar cell endoplasmic reticulum: an ER stress/defective unfolded protein response model. Cell Mol Gastroenterol Hepatol. 2018;5(4):479-497. https://www.sciencedirect.com/science/article/pii/S2352345X18300018.

Weng Y, Xie F, Xu L, Zagorevski D, Spink DC, Dink X. Analysis of testosterone and dihydrotestosterone in mouse tissues by liquid chromatography-electrospray ionization-tandem mass spectrometry. Anal Biochem. 2010 Jul 15;402(2);121-128. https://www.sciencedirect.com/science/article/pii/S0003269710002022.

Xie JJ, Jiang YY, Jiang Y, Li CQ, Chee LM, An O, Mayakonda A, Ding LW, Long L, Sun C, et al. Increased expression of the long non-coding RNA LINC01503, regulated by TP63, in squamous cell carcinoma and effects on oncogenic activities of cancer cell lines. Gastroenterology. 2018 Feb 15. pii: S0016-5085(18)30213-0. https://www.gastrojournal.org/article/S0016-5085(18)30213-0/fulltext.

Yang W, Di Vizio D, Kirchner M, Steen H, Freeman MR. Proteome scale characterization of human S-acylated proteins in lipid raft-enriched and non-raft membranes. Mol Cell Proteomics. 2010 Jan;9(1):54–70. http://www.mcponline.org/content/9/1/54.