Our goal is analysis of singly-charged intact proteins and complexes with part-per-million mass accuracy up to one MDa. We have recently created an inlet and large-radius frequency-adjusted linear quadrupole ion trap that is capable of capturing large quantities (>100 million ions) of massive (1-1000 kDa) singly-charged ions injected from the atmosphere into vacuum and holding them for on-demand injection into an awaiting mass analyzer. Trapping the ions before mass analysis removes the expansion-induced kinetic energy that causes the deterioration of mass accuracy, resolution and sensitivity as a function of increasing mass. Coupling our inlet and trapping system to an orthogonal time-of-flight mass spectrometer (with reflectron) will permit accurate mass analysis of intact proteins without loss of sensitivity and resolution at high mass. The following measures of performance will be determined for our instrument: 1. We will demonstrate that the sensitivity does not change significantly with increasing mass by measuring working curves (signal intensity versus concentration) for known proteins and peptides spanning the 1-200 kDa molecular weight range;2. We will demonstrate part per million mass accuracy over the 20 to 1000 kDa range with know proteins, multimers of known proteins and immoglobulins;and 3. We will define the resolution over the entire range with known analytes. Resolution of 100,000 or better is expected for mass-to-charge ratios over 100 kDa. We will also design, implement and demonstrate a singly-charged ion source that may be coupled to chromatographic column output. We will then demonstrate that complex protein distributions can be measured by coupling our instrument to a chromatographic separation. Success in this endeavor will be defined by assigning accurate masses to the majority of expressed proteins in a bacterial lysate.
Sensitive, accurate, and resolved mass analysis of singly charged intact proteins and complexes is not currently feasible above roughly 20 kDa. There is also no easy method to comprehensively measure protein distributions and compare them. Yet it is the protein distributions that define the state or health of the organism. These distributions can be used for clinical diagnosis and directly studying the affects of treatment. This project will demonstrate the feasibility of these goals.
