Two-Dimensional Partial-Covariance Mass Spectrometry of Large Molecules Based on Fragment Correlations

Abstract

Covariance mapping [L. J. Frasinski, K. Codling, and P. A. Hatherly, Science 246, 1029 (1989)] is a well-established technique used for the study of mechanisms of laser-induced molecular ionization and decomposition. It measures statistical correlations between fluctuating signals of pairs of detected species (ions, fragments, electrons). A positive correlation identifies pairs of products originating from the same dissociation or ionization event. A major challenge for covariance-mapping spectroscopy is accessing decompositions of large polyatomic molecules, where true physical correlations are overwhelmed by spurious signals of no physical significance induced by fluctuations in experimental parameters. As a result, successful applications of covariance mapping have so far been restricted to low-mass systems, e.g., organic molecules of around 50 daltons (Da). Partial-covariance mapping was suggested to tackle the problem of spurious correlations by taking into account the independently measured fluctuations in the experimental conditions. However, its potential has never been realized for the decomposition of large molecules, because in these complex situations, determining and continuously monitoring multiple experimental parameters affecting all the measured signals simultaneously becomes unfeasible. We introduce, through deriving theoretically and confirming experimentally, a conceptually new type of partial-covariance mapping—self-correcting partial-covariance spectroscopy—based on a parameter extracted from the measured spectrum itself. We use the readily available total ion count as the self-correcting partial-covariance parameter, thus eliminating the challenge of determining experimental parameter fluctuations in covariance measurements of large complex systems. The introduced self-correcting partial covariance enables us to successfully resolve correlations of molecules as large as103–104Da, 2 orders of magnitude above the state of the art. This opens new opportunities for mechanistic studies of large molecule decompositions through revealing their fragment-fragment correlations. Moreover, we demonstrate that self-correcting partial covariance is applicable to solving the inverse problem: reconstruction of a molecular structure from its fragment spectrum, within two-dimensional partial-covariance mass spectrometry.

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Plain Language Summary

Large molecules interacting with particles or radiation can fragment into electrons and ions that hold the key to unraveling the physical mechanisms of the decomposition or to reconstructing the structure of the original molecule. But such data are often notoriously difficult to interpret. As we show here, 2D partial-covariance spectroscopy holds promise. This technique identifies particles formed in the same and related decomposition processes by looking at their fluctuating signal intensities. Prior to this work, it could not be realized for large molecules, because it requires identification and continuous measurement of experimental parameters affecting all the signals simultaneously. We derive theoretically and demonstrate experimentally a new type of partial-covariance spectroscopy, which does not require additional measurements and successfully resolves complex biomolecular fragmentations.

Our method uses the readily available total ion count of the measured spectra in order to suppress spurious correlations between unrelated fragments. While previously, covariance spectroscopy had been able to tackle only molecules with masses of about 50 daltons (where one dalton is about the mass of one proton), we have extended this technique to peptides, proteins, and oligonucleotides with masses above10000daltons. Moreover, we show that the 2D partial-covariance spectra of fragmenting biomolecules represent a much more specific fingerprint of their structure in comparison to what 1D mass spectrometry can ever deliver, even in the limit of an infinitely precise measurement of the ionic mass-to-charge ratios.

Our work opens the door for using the new type of partial-covariance spectroscopy for solving challenging structural problems in analytical mass spectrometry such as those encountered in proteomics and genomics.