Imagine proteins as millions of tiny messengers in the body constantly exchanging information. This exchange is the conversation of the body. The best way to hear it is to measure those proteins—a seemingly impossible process that API has solved.
Biotechnology has been revolutionized over the past few decades by technologies that allow the analysis of many members of an analyte class at one time from the same sample − "omics." This highly parallelized form of data acquisition and discovery has led to hypothesis-generating experimental designs in which many or all possibilities are tested and the selection of the important component or result is data-driven. This contrasts with historical approaches in which a given analyte, selected based on prior experimental results, is evaluated in a hypothesis-testing design. Omics approaches have become highly valued because, as our understanding of the complexity of human biology increases, we have realized that, simply put, we don't know what we don't know.
Proteomics is the study of many proteins at once in a biological system using a given technical approach. The enormous diversity of proteins can be appreciated by considering that tens of thousands of genes give rise to hundreds of thousands of mRNAs which in turn give rise to potentially a million or more forms of proteins including post-translational modifications; a typical biological sample may contain tens of thousands of different protein forms. Proteins are a very valuable source of potential biomarkers: protein presence is driven by combined genetic and environmental factors, and thus proteins provide a measure of actual biological and disease status, not just risk or disposition. In addition, proteins are easily accessible in body fluids and tissues that collect from many of the body's systems. Applied Proteomics uses a mass-spectrometry-based approach, primarily tandem LCMS, to examine all of these potential biomarkers in a rapid and efficient process.
One important key to understanding complex data is pulling together information from different sources into a unified view where comparisons can be easily made. Building visualization tools to accomplish this task is a core strength at Applied Proteomics. The above video clip starts with a high level MS1 view of a proteomic sample. The red markers that appear represent individual MS2 events triggered during data collection, and their overlay on MS1 space provides an important view of the data not available when the MS2 data is considered in isolation. The video clip then zooms into an individual peptide feature, and additional information about the MS2 is shown, including the m/z target location in MS1 space, the associated MS2 spectrum, and fragment ion matches to the spectrum for the top scoring peptide sequence match. The ability to easily navigate between these different sources of information helps to generate new insights into the underlying data.