Proteomics mass spectrometry is finally sensitive and specific enough for robust translational medicine (at least in capable hands), and holds tremendous promise to revolutionize biology and medicine. For some, it holds the key to incredible research power for decades to come.
However, there is a chasm that continues to grow between the productive and unproductive labs, because too many proteomics practitioners focus too early on low-level issues (i.e. cost, automation, ease-of-use) without first resolving high-level ones (i.e. sensitivity in presence of noise, quality of results, algorithmic suitability).
For many researchers experimenting with a new high-resolution instrument, the most common scenario is to select a workflow based on running a simple protein solution, usually a purified BSA solution or a commercial protein mixture.
Since different workflows will give basically identical protein IDs results for these simple test cases, they may conclude that all search engines are equivalent. While true when there is almost no signal noise, it is largely irrelevant in translational research. In fact, the exact same test will likely show that low-resolution and high-resolution mass specs are equivalent, the lowest quality reagents will suffice, or maybe you don’t have to clean your glassware as often. These are also true when there is little or no signal noise, but again, that is irrelevant for real-world research.
Seeing that there is little difference in protein IDs, some focus on using protein coverage as the sole metric for evaluating search engines. However, this is actually the opposite of what is needed for sensitive discovery proteomics. For example, if you are hunting for new protein biomarkers (especially a “one-hit wonder”), you do not want the protein inference engine tuned to assigning any ambiguous peptides to already found proteins, thereby hiding them from further study.
Not surprisingly, a workflow selected based on low-noise experiments and focused on protein coverage will excel for simple mixtures, but is not sensitive enough to analyze complex mixtures with wide dynamic range, such as in translational research. Scientists will be able to see the abundant peptides and proteins, but probably little else. That is roughly what most proteomics researchers find today, nothing meaningful, but enough of the obvious to not change their methodologies.
The result is that most labs are not getting the value commensurate with their investments in proteomics mass spectrometry. Under the current economic environment, this is both wasteful and dangerous.
Within the academic world, while many proteomics researchers have trouble getting any interest, a select few are swamped and have to turn away collaborators. Within drug discovery firms, while many are staring at their mostly idle mass spectrometers, a select few are running multiple mass spectrometers 24/7 sieving productively through millions of peptides.
So why are the majority of the proteomics research not producing high-value results?
With our access into the world’s top academic and drug discovery proteomics labs, we have a unique bird’s eye view into the answer. (However, like attorneys, we never give out client-specific information.)
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