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Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (Method optimization)

ABSTRACT: Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a variety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent ac-quisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 vg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 pro-teins across three cell lines following short-term treatment with the proteasome inhibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubility of 1,723 pro-teins and the abundance of 374, and ML-792 impacted 1,294 and 288, respectively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal widespread, drug-induced remodeling of the pro-tein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly ap-plicable platform for uncovering protein state transitions and cellular responses to perturbation.

INSTRUMENT(S): Orbitrap Astral

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Phil Lorenzi

PROVIDER: MSV000099789 | MassIVE | Fri Nov 07 09:40:00 GMT 2025

SECONDARY ACCESSION(S): PXD070463

REPOSITORIES: MassIVE

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Project description:Background: The combination of Proteasome inhibitor with Glucocorticoid is one of the most promising antileukemic treatments. Both agents act through pluripotent signal mediators. The two types of agents inhibit key signals that are considered crucial to their effects on malignant cells. Methodology/Principal Findings: Combined use of the two reagents on the lymphoblastic leukemia cell line CCRF-CEM has a range of effects on the viability that depend on the dose and the time used. Even though both reagents are capable of enhancing cell death on the CEM cell line, no combinatorial increase in cell death is detectable, until after the first 120 hours of treatment. In contrast, there are a number of combinatorial effects on the cell cycle phase distribution of treated cells, which indicates a potential for mutual signal disruption between glucocorticoid and proteasome inhibitor at multiple levels. Microarray analysis indicates that Prednisolone and MG132 elicit highly divergent, early-response molecular signatures on this cell line. We assayed levels of the antiapoptotic protein Mcl-1 as a potential model of late, downstream target regulation by both glucocorticoid and proteasome. Synchronized use of Prednisolone with MG132 results in temporary stabilization of Mcl-1 in CEM cells. Stabilization is not the result of a common mechanism of action on the genome, as Prednisolone and MG132 elicit nonreduntant molecular signatures, and it occurs also when the cells are treated at different timepoints with either agent. Conclusions/Significance: Our results show that this glucocorticoid-resistant ALL lymphoblast line is highly sensitive to proteasome inhibitor, and suggest that the proteasome inhibitor and the glucocorticoid regulate different direct target genes. This difference in immediate targets, when the two agents are applied in combination, may lead to negative or positive interference with mechanisms regulating viability of the leukemic lymphoblast. Signal interference between glucocorticoid Prednisolone and the proteasome inhibitor MG132 is expected to occur at more than one level, resulting in complex effects on intracellular signal transduction pathways. The net result depends on the development of individual downstream effects and interactions between key signal mediators. Elucidation of the conditions of interference between glucocorticoid and proteasome targets on leukemic cell fate is expected to improve effects of applied treatment combinations. Experimental setups consisted of the three following samples obtained after 4 h treatment: control, 10nM prednisolone, 1uM prednisolone, 10uM prednisolone, 100M-NM-<M prednisolone, 700M-NM-<M prednisolone, 200nM MG132, 2M-NM-<M MG132 and 20M-NM-<M MG132. Untreated cells were used as reference.

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Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (Method optimization)

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