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Organisms are complex. Proteomics is one facet of a systems biology approach to understanding biological function. With two high resolution Orbitrap 480s and Proteome Discoverer software using the SequestHT search tool, METRIC is well-equipped to interrogate your sample proteomes.

An example of a data visualization output from a proteomics study conducted by METRIC. This visualization shows (A) a Venn diagram representing the overall number of proteins identified per condition (n = 3). (B) Volcano plot representing in the x-axis the Log2 ratio for the identified proteins according to the label-free quantification analysis and the y-axis the −Log10 P-value according to the statistical analysis considering a false discovery rate of 0.01. The red shadow area corresponds to the statistically significant area for less abundant proteins identified (i.e., Log2 ratio <1 and P-value <0.01). The blue area corresponds to the statistically significant area for the identified proteins with higher abundance (i.e., Log2 ratio >1 and P-value >0.01). (C) Heatmaps showing the abundance ratio as fold change between automated mH-ECM and manual sH-ECM for collagens, proteoglycans, glycoproteins, and other ECM-related proteins.

From Andreea Badileanu, Camilo Mora-Navarro, Ana M. Gracioso Martins, Mario E. Garcia, Daphne Sze, Emily W. Ozpinar, Lewis Gaffney, Jeffrey R. Enders, Ryan C. Branski, and Donald O. Freytes, Fast Automated Approach for the Derivation of Acellular Extracellular Matrix Scaffolds from Porcine Soft Tissues, ACS Biomaterials Science & Engineering  2020 6 (7), 4200-4213 DOI: 10.1021/acsbiomaterials.0c00265.

Your study is unique. Your hypothesis calls for MS-based proteomics. Talk to us about experimental design so together we can build an effective workflow that targets the hypothesis.

Do you need a detailed picture of your sample proteome? If so, we can assist with the entire discovery proteomics experiment, from study design to data interrogation. Here is what we can learn from label-free discovery data:

  • unambiguous protein identification
  • protein fold-change information (label-free quantification or LFQ)
  • cellular pathways
  • protein biological function
  • cellular compartmentalization
  • protein-protein interactions

We can help with protein extraction. Just bring your biological specimen to us.

  • Diverse organisms (yeast, insects, plants, mammals, wood, bacteria, fungi, viruses)
  • Diverse specimen formats (tendon, soft tissue, cell pellets, cell media)
  • … and more!

You may wish to undertake the protein extraction and purification in your laboratories. Just provide us the protein, either as a gel-separated band, in solution or as a lyophilized powder. We are happy to work with whole cell lysates (WCL), immunoprecipitated (IP) protein or other fractionated protein samples.

Perhaps you wish to dig a little deeper and look at post-translational modifications (PTMs), such as

  • glycosylation
  • phosphorylation
  • ubiquitination
  • acetylation
  • methylation
  • … and more!

We can also help you verify synthetic protein modifications in your samples. Just let us know the chemical structure of your modification and we will take a look.

Interested in protein crosslinking studies? If so, we have the tools and expertise available.

Perhaps you wish better understanding of protein fold change. We can talk to you about designing a labeled discovery proteomics workflow, such as tandem mass tag (TMT), Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) or Isobaric Tags for Relative and Absolute Quantification (iTRAQ).

Perhaps you look through your discovery data and observe some very interesting proteins that you need to quantify accurately. We can help you design a targeted workflow to better interrogate those proteins. Talk to us about protein cleavage isotope dilution mass spectrometry (PC-IDMS). Using this approach, we can quantify nanogram or picogram amounts using stable isotope analogs of unique peptides from target proteins. We can acquire custom internal standards to build accurate and robust quantification methods.

There are many ways to develop a targeted proteomics workflow. If you find a method in the literature that may suit your needs, let us have a conversation about it.

At METRIC, we exclusively use Proteome Discoverer (Thermo Scientific) and Skyline (MacCoss Lab, University of Washington) for all our proteomics projects.

  • Proteome Discoverer (PD)
    • This comprehensive software package allows both targeted and discovery proteomics data processing.
    • Databases in FASTA format containing single letter amino acid sequences of proteins from a target organism are used in proteomics data interrogation. We use proteome databases found in SwissProt and NCBI. We can help you customize a database for the specific needs of your project.
    • PD supports quantitative analysis of samples when using SILAC, TMT, iTRAQ, 18O labelling, as well as label-free quantification (LFQ).
    • Data can be displayed in a variety of ways, such as Venn diagrams, PCA plots, heat maps and volcano plots.
    • For data sets containing biological and/or technical replicates, PD can calculate statistical significance of fold-change between data files in an LFQ experiment.
  • Skyline
    • We use Skyline for absolute quantification and targeted analysis.
    • Skyline offers unique data visualization tools for sample interrogation and can provide useful figures for manuscripts.