Work

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

Year: 2025

Type: article

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.

Source: Journal of Visualized Experiments

DOI: 10.3791/68741

Authors: Samuel Okyem, Yanqi Tan, Elena Romanova, Jonathan V. Sweedler

Institution: University of Illinois Urbana-Champaign

Language: English

Topic: Advanced Proteomics Techniques and Applications

Subfield: Spectroscopy

Field: Chemistry

Domain: Physical Sciences

Open Access status: green

Funder: National Institute on Drug Abuse

Award: G600732768