Sample preparation is a critical aspect of study design that ultimately determines whether a mass spectrometry experiment will be successful. Independent of the mass spectrometer used, sample preparation directly affects how "quantitative" an experiment can be, what types of molecular characterizations will be possible, and what inferences can be made from the data. Due to complexity and sheer number of possibilities in modern mass spectrometry, MS Center researchers work with investigators to develop an appropriate study design to provide the type and quality of data that addresses a particular biological question.
In the Center, we utilize automated sample preparation platforms whenever possible, to minimize technical variability and maximize sample quality, reproducibility, and throughput. We are continually incorporating new sample preparation methods as the emerge and are accepted into the mass spectrometry community to ensure that MCW investigators can take full advantage of available technologies.
Depending on the project, MS Center staff can start with a crude sample and prepare it for the investigator, or provide detailed protocols for investigators to prepare samples. In all cases, we work with investigators to ensure that mass spectrometry-incompatible reagents and common contaminants are avoided.
Which data analysis platforms are available in the Center?
Data analysis platforms typically include one or more search engines coupled to post-search validation tools for protein inference, grouping, and false-discovery rate estimations. We have several different platforms available to meet the need for a wide variety of workflows, including:
- Proteome Discoverer 2.1, including Sequest HT, MS Amanda, Mascot – Proteomics
- ProSightPD – Top-Down proteomics
- SimGlycan – Glycans, glycopeptides
- Byonic – Glycoproteomics, glycomics, proteomics
- Skyline – Quantitative proteomics
- Trans-Proteomic Pipeline – Proteomics
- Supernovo – Sequencing monoclonal antibodies