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DOE OSTI · 3375676

Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics

VonKaenel, Erik D. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000289337413)·Rozum, Jordan C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000243569809)·Zhang, Tong [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000325402017)·Stratton, Kelly G. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000217219688)·Bramer, Lisa M. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000283841926)·Wiley, Henry Steven [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000302326867)·Qian, Wei-Jun [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000253932827)·Sims, Amy C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)]·Melchior, John T. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000337812566)·Feng, Song [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000339839009)
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Abstract

Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation (“roll-up”), to enhance data reliability and interpretability. While roll-up is effective for protein-centered analyses, it may be suboptimal for applications focused on post-translational modifications (PTMs) or protein structural changes, such as limited proteolysis–mass spectrometry (LiP-MS). Here, we investigate how different roll-up strategies influence site-level quantification in PTM differential analysis. Moreover, we introduce a novel site-centric roll-up approach tailored for LiP-MS, which quantifies proteolytic fragments rather than solely tryptic peptides. We benchmark these methods through simulation studies, comparing their sensitivity and specificity in detecting structural and PTM-driven changes. We found that the median and mean roll-up methods outperform the sum method in both PTM and LiP proteomics, and site-level quantification in LiP outperforms peptide-level quantification. Our findings offer the first systematic, data-driven guidance for selecting roll-up techniques in site-level proteomic analyses, with implications for both PTM-focused and structural proteomics studies.

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aggregationbottom-up proteomicslimited proteolysis mass spectrometry (LiP-MS)modificationpeptides and proteinspost-translational modifications (PTMs)protein structureproteomicsproteomics quantification

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VonKaenel, Erik D. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000289337413), Rozum, Jordan C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000243569809), Zhang, Tong [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000325402017), Stratton, Kelly G. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000217219688), Bramer, Lisa M. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000283841926), Wiley, Henry Steven [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000302326867), Qian, Wei-Jun [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000253932827), Sims, Amy C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Melchior, John T. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000337812566), Feng, Song [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000339839009). 2026-05-15. Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics. https://doi.org/10.1021/acs.jproteome.5c00782

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DOE OSTI2025

Coarse-grained molecular dynamics simulation of solvent-dependent cellulose nanofiber interactions

Associations between cellulose are important both in biofuel production and in the use of cellulose for biomaterials. Cellulose nanofibers (CNFs) are sustainable, strong, light-weight alternatives to traditional materials in manufacturing, but are challenging to obtain due to irreversible aggregation in solution during preparative fibrillation. Therefore, it is imperative to understand the underlying factors driving aggregation with a view to designing solvents that can effectively compete with interfiber interactions, hence reducing aggregation. Molecular dynamics (MD) simulation at atomic detail can provide useful information on local interactions. However, the length and timescales accessible are too short to fully capture association processes. Here, we provide a method for accessing the longer length and timescales required using coarse-grained (CG) MD simulations with a MARTINI force field to calculate the interaction behavior of CNFs in three selected solvents: NaOH-urea-water, acetone, and neat water. The CG results are consistent with our prior all-atom MD and with previous experimental results. While acetone is found not to be an effective solvent, urea and ionic moieties in NaOH-urea-water not only solvate the fibrils but also improve the confinement of water molecules around them as shown by the solvent residence times and mean-square displacements. Overall, the presence of urea and ions reduces the likelihood of aggregation in multi-CNF systems relative to neat water irrespective of whether the hydrophobic or hydrophilic CNF surfaces are interacting. In conclusion, the CG method shows clear promise for selecting potential high-performance solvents for experimental prioritization in bioenergy and biomaterials research in a relatively fast manner as well as for understanding the aggregation and rheological behavior of CNF-solvent systems.

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