Emma Chowdhury ’18: Bruker Internship Journal
This summer, I am interning at Bruker Daltonics, a company that sells mass spectrometers and their accompanying devices. I’ve spent every day of the past week learning about MALDI mass spectrometry (matrix assisted laser desorption/ionization), and, to be completely honest, I’m still pretty confused! It’s an entire field of graduate school-level analytical chemistry that I’m attempting to jump into, and if not for the tireless, endless support of my managers there, I would be hopelessly lost.
The general theory behind mass spectrometry is to ionize a given sample (a protein or peptide) by applying voltage to it, allowing the ions to fly through a chamber, and then recording the time it took each ion to move through the chamber. The computer program records this and then relates this time to the ion’s mass to charge ratio (m/z) by using a predetermined equation. Because a given sample releases many ions, the computer constructs a graph, with peaks that indicate separate ions. There are many uses of these graphs, but the general purpose of them is to be able to identify different samples by their molecular weight (given by m/z).
Along with my manager, Linny, my goal for the summer is to do the imaging of a tissue sample. There are two workflows involved in this — peptide identification through LC-MALDI and peptide localization through MALDI-Imaging. The MALDI-MS is incapable of separating a sample such as a tissue, with hundreds (possibly thousands) of proteins inside of it, so that’s where the LC (liquid chromatography) comes in. Through its use of a hydrophobic column, the molecules in the protein are forced to separate themselves by means of polarity. Once LC is completed, the separated proteins are moved into the MALDI MS, where the normal process is completed on each separated protein. This allows for the identification of peptides (by using the m/z), which completes the first work flow. MALDI-Imaging works in tandem with LC-MALDI. It analyzes the tissue and digitally pixelates it. In each pixel, the computer determines how prevalent each specific molecular weight is. Because each peptide has a specific m/z format, identified from MALDI-MS, we are able to figure out the location of different peptides.
It’s definitely a complicated concept, but it’s really fascinating to me. It has so many applications, like biomarking, which can help identify and diagnose diseases/illnesses. It’s also just pretty cool to know that I’m learning how to digitally image a tissue sample in such detail, so I’m excited for the rest of the summer!
