CysNet: Theorem constrained inference of cysteine redox proteoform states from bottom-up mass spectrometry data

Cobley, J. N.; Jiang, H.; Platani, M.; Lamond, A. I.

doi:10.64898/2026.07.06.736853

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bioRxiv · 10.64898/2026.07.06.736853

CysNet: Theorem constrained inference of cysteine redox proteoform states from bottom-up mass spectrometry data

Cobley, J. N.·Jiang, H.·Platani, M.·Lamond, A. I.

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Abstract

Here, we present CysNet, a theorem-constrained method designed to infer cysteine redox proteoforms, i.e.,oxiforms, from bottom-up, mass spectrometry (MS)-based proteomic data. This overcomes limitations with previous MS redox proteomic approaches, which can quantify residue-resolved cysteine redox states, but leave distinct oxiforms unresolved. CysNet treats each residue-resolved oxidation value as a binary redox-coordinate marginal, enabling theorem-constrained inference of the oxiforms that are necessary, impossible or bounded within the compatible protein-group ensemble. This collapses the vast theoretically possible set of oxiform states to a finite set of allowed values by extracting existence and exclusion constraints from the data, despite the incomplete proteome coverage typical for bottom-up MS datasets. Using CysNet to analyse human induced pluripotent stem cell lines (~6,300 cysteine-containing protein groups, ~22% cysteine coverage), resolved 519 exact oxiforms, inferring 7,000 oxiforms per line. Quantitatively, CysNet bounded the oxiform content to 6.36-8.24 x 1012 protein copies, corresponding to 14-19% of the measured cysteine proteome. These data define the deepest oxiform survey recorded. CysNet revealed a latent structural layer in redox variation between the cell lines, distinguishing changes in oxiform identity (composition) from changes in oxiform weighting (intensity). Hence, CysNet moves bottom-up redox proteomics beyond isolated site-level cataloguing by reconstructing copy-number-weighted oxiform maps, providing a scalable route to deep oxiform information from peptide-level data.

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Cobley, J. N., Jiang, H., Platani, M., Lamond, A. I.. 2026-07-07. CysNet: Theorem constrained inference of cysteine redox proteoform states from bottom-up mass spectrometry data. https://doi.org/10.64898/2026.07.06.736853

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