Fingerprint Mass Spectrometry: A New Chapter in Proteome Analysis
Researchers at Caltech have designed a novel fingerprint mass spectrometry technique by integrating nanoscale devices with machine learning that is now capable of analysing whole proteomes with unprecedented accuracy.
It’s actually a nanoscale sensor that detects individual particles and molecules with substantial resolution based on a new machine learning method. Fields of protein identification are widely expanding because it has opened doors to map the entire proteome, something which scientists wanted to achieve for ages. Importance of proteome comes from the fact that it contains critical information about health, disease, and treatments.
Understanding the Proteome Puzzle
Proteins are the working engines of life, playing a crucial role in many biological functions. Knowing which proteins are there, in what quantities, and where they are expressed gives a great deal of useful information about biological systems. Current methods to characterize the complete proteome remain incomplete, since current techniques cannot offer a full, real-time picture of protein structures without changing or damaging them. Enter fingerprint mass spectrometry, the newest technique to measure proteins without degradation, unlike the traditional mass spectrometry methods.
This new method allows the scientists to inspect proteins in their native form rather than breaking down proteins into fragments. As per Michael Roukes, a key figure behind this study, this new method permits one to perform experiments at the molecular level that determine individual proteins. This is specially relevant for large protein complexes that cannot be analyzed correctly by standard techniques and often return some partially fragmented results.
Machine Learning Meets Nanoscale Devices
This innovation centers on embedding nanoelectromechanical systems with machine learning algorithms. Ionization could distort or otherwise affect biological molecules in the performance of traditional mass spectrometry. The method of Nanoelectromechanical Systems (NEMS) itself completely avoids this problem, allowing for real-time and nonionized measurements of particles, even to the level of the individual protein.
An important drawback of former NEMS devices was that it was extremely difficult to estimate how the ultrasmall structures used for mass sensing vibrated. At these infinitesimal scales, even minor defects of the devices usually led to false or misleading measurements. By utilizing machine learning, the researchers were able to create a technique for “fingerprint nanoelectromechanical mass spectrometry,” which utilizes data-driven algorithms to calculate mass in a correct manner without depending on the knowledge of the exact vibrational modes of the used nanoscale structure.
Every time that particle is put on the NEMS device, its vibrational frequencies are measured, creating a unique vector or “fingerprint.” The researchers can then correctly identify unknown particles by comparison with the database, even if they don’t know where the particle came to rest on the device.
Fingerprint approach for NEMS mass spectrometry
Importance of GroEL Proteins
To demonstrate their new approach, the authors applied it to GroEL, a 14-subunit chaperone protein complex critical for folding proteins within cells. Current mass spectrometry techniques fail on complexes this size due to insufficient measurements to unambiguously assign a single species; rather they rely on breaking the protein into smaller pieces for fragmentation and subsequent analysis. The fingerprint method circumvents all of these issues by avoiding the need for any fragmentation, allowing a higher resolution description of the single molecule.
This marks a significant step forward in proteomics, because the possibility of measuring proteins in their entirety provides much greater precision of structure, function, and behavior of proteins in cells. In big protein complexes or membrane proteins like GroEL, this kind of technique could introduce new knowledge that has been unreachable before.
Although it is still a fairly new technique, the potential for the fingerprint mass spectrometry method is enormous. It is a powerful tool that will empower scientists to map an entire proteome without destroying it in the process. It could be a game-changer for everything that we know about the mechanism of diseases and quicker identification of disease biomarkers as well as more precise targeting of drugs.
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