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Metabolomics and Lipidomics

A cost estimate based on the complexity of the sample preparation, sample number, mass spectrometry analysis time, and data analysis time will be calculated using instrument time and scientist time pricing and will be provided to the investigator. Examples of commonly used methods include:

  • Global profiling of known metabolites including, but not limited to amino acids, biogenic amines, glycolytic intermediates, and organic acids.
  • Untargeted metabolomics using differential analysis software to statistically determine significant features based on data sets containing known IDs, putative IDs, and unknowns.
  • Stable isotope tracing in cell culture or in vivo.
  • Targeted and global profiling of specific lipid classes.
  • Untargeted lipidomics using differential analysis software to determine statistically significant lipid species that are identified based on MS2 product ion spectra.

Metabolomics and lipidomics fee for service is stratified into instrument time and scientist time. Instrument time (samples/hour) is variable depending on the methods required to obtain the requested data. These fees take into account instrument reagents including solvents and columns, solvents for extraction, and consumables. Scientist time includes sample preparation and data analysis. Data analysis time depends on the complexity of the study, sample number, and depth of the analysis. Specialized standards and internal standards are sometimes required and the cost will be charged to the user.

  • Instrument time $75/hr 
  • Scientist time $125/hr

We request that samples are submitted as homogenized tissue or cells in approved buffers/detergents with total protein concentrations measured prior to sample submission by standard assays (e.g. BCA or Bradford). If this is not possible and we are required to perform the protein extraction, an additional charge will be applied. Common types of analyses include:

  • Protein identification 
  • Label free quantitation
  • TMT Multiplexing
  • Post-translational modification (PTM) identification and quantitation (e.g., phosphorylation, acetylation, ubiquitination)
  • Targeted proteomics—absolute quantification of peptides using stable isotope labeled peptides
  • Gel band identification

Proteomics fee for service is billed as cost per sample depending on the requested analysis. The cost per sample takes into account sample preparation costs, instrument time and basic data analysis for quantified protein samples given to the MSC by the investigator. Protein extraction and quantitation performed by the MSC will cost an additional $100/sample. Request for extended gradients will be billed as additional instrument time. Additional levels of data analysis are described below.

  • Protein quantification via label free or TMT assay $350/sample
  • PTM for phosphorylation $400/sample 
  • PTM for ubiquitin and acetylation $650/sample
  • Other PTM—please inquire
  • Targeted quantitative proteomics—please inquire
  • Gel band identification $250/sample 
Proteomics Data Analysis Tiers

Included in standard sample analysis:

  1. Peptide and Protein identification and quantification:
    Peptides are identified and quantified in either MSFragger/IonQuant, MaxQuant, or Proteome Discoverer. Peptides and proteins are reported with an identification confidence score. Proteins are reported as the total intensity of all non-redundant peptides mapped to each protein. Both peptide and protein levels are provided in the final data set.
  2. Peptide and/or Protein level normalization and case-control statistics:
    Peptides are identified and quantified in either MSFragger/IonQuant, MaxQuant, or Proteome Discoverer. Match between runs is utilized to reduce missingness, and data are normalized, and assessed for technical biases. Representative high confidence and co-regulated peptides are identified and used to estimate protein levels. Protein levels are compared between groups and findings adjusted for multiple hypothesis testing.

Analyses available at an additional fee (please enquire for pricing):

  1. Gene ontology analysis.
    Gene ontology enrichment analysis is used to characterize significantly up- and downregulated proteins.
  2. Weighted protein co-expression network analysis.
    WGCNA is used to reduce the dimensionality of large proteomics datasets and identify co-regulated groups of proteins. These protein groups or “modules” are characterized by gene ontology enrichment analysis using WebGestalt.
  3. Kinase enrichment and phosphonetwork analysis. 
    Identification of kinases that are potential drivers of altered protein phosphorylation are modeled using Kinase Enrichment Analysis. Phosphorylation Networks for Mass Spectrometry (PHONEMeS) models up- and downstream signaling networks that may be dysregulated in experimental conditions.