Neuropeptide Characterization Workflow from Sampling to Data-Independent Acquisition Mass Spectrometry

Endogenous neuropeptides are key modulators of brain function, playing critical roles in behavior, stress, pain, and homeostatic regulation, yet their analysis remains difficult. Biologically, they are low in abundance, rapidly degraded, and processed variably from precursor proteins, with expression limited to small, localized cell populations. Technically, their detection is complicated by a wide dynamic range, diverse post-translational modifications, and sparse signals in mass spectrometry datasets. This protocol outlines a comprehensive workflow for neuropeptide analysis in Rattus norvegicus brain tissue using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry (MS) on a timsTOF platform. Following optimized brain sample preparation, including dissection, peptide extraction and clean-up, nano liquid chromatography (LC)-MS is performed with ion mobility gas-phase fractionation to improve detection sensitivity and accuracy. The DDA-generated spectral library supports DIA-based quantification in Skyline, enabling high-confidence MS2-level measurements. This integrated workflow increases neuropeptide coverage and enhances quantitative reproducibility, providing a robust platform for studying neuropeptides in complex brain tissue.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2025-08-08
DOI
https://doi.org/10.3791/68741
Primary Topic
Mass Spectrometry Techniques and Applications
Type
article
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article

Neuropeptide Characterization Workflow from Sampling to Data-Independent Acquisition Mass Spectrometry

Jonathan V. Sweedler, Yanqi Tan, Samuel Okyem, Elena A. Romanova
Journal of Visualized Experiments
Mass Spectrometry Techniques and Applications
article

Neuropeptide Characterization Workflow from Sampling to Data-Independent Acquisition Mass Spectrometry

Jonathan V. Sweedler, Yanqi Tan, Samuel Okyem, Elena A. Romanova
article en

Abstract

Endogenous neuropeptides are key modulators of brain function, playing critical roles in behavior, stress, pain, and homeostatic regulation, yet their analysis remains difficult. Biologically, they are low in abundance, rapidly degraded, and processed variably from precursor proteins, with expression limited to small, localized cell populations. Technically, their detection is complicated by a wide dynamic range, diverse post-translational modifications, and sparse signals in mass spectrometry datasets. This protocol outlines a comprehensive workflow for neuropeptide analysis in Rattus norvegicus brain tissue using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry (MS) on a timsTOF platform. Following optimized brain sample preparation, including dissection, peptide extraction and clean-up, nano liquid chromatography (LC)-MS is performed with ion mobility gas-phase fractionation to improve detection sensitivity and accuracy. The DDA-generated spectral library supports DIA-based quantification in Skyline, enabling high-confidence MS2-level measurements. This integrated workflow increases neuropeptide coverage and enhances quantitative reproducibility, providing a robust platform for studying neuropeptides in complex brain tissue.

Journal of Visualized Experiments(222)
University of Illinois Urbana-Champaign (US)
Openalex Percentile: Top 82%
Mass Spectrometry Techniques and Applications
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Neuropeptide Characterization Workflow from Sampling to Data-Independent Acquisition Mass Spectrometry — Jonathan V. Sweedler, Yanqi Tan, et al. · Journal of Visualized Experiments (2025) | TGRS Research Map | TGRS