Neuropeptides are critical endogenous signaling molecules involved in a wide range of biological processes, including neurotransmission, hormonal regulation, immune responses, and stress management. Despite their importance, the field of neuropeptide research has been historically hampered by significant technical challenges. These include their low abundance in biological systems, diverse and complex post-translational modifications, dynamic expression patterns, and susceptibility to degradation. As such, traditional proteomics approaches often fall short of accurately characterizing neuropeptides, underscoring the need for specialized methodologies to unlock their biological and translational potential. This review evaluates state-of-the-art quantitative mass spectrometry (MS)-based peptidomics, emphasizing their impact on neuropeptide analysis. We highlight how strategies in label-free and label-based quantitation, tandem MS acquisition, and mass spectrometry imaging provide unprecedented sensitivity and throughput for capturing the landscape of neuropeptides and their modifications. Importantly, the review bridges technological innovation with practical applications, highlighting how these approaches have been utilized to uncover novel neuropeptides and elucidate their roles in systems biology and disease pathways.
Neuropeptides are essential regulators for numerous cellular and physiological processes, acting as key neurotransmitters and neuromodulators. They are synthesized in neurons primarily through mRNA translation on ribosomes and undergo extensive post-translational processing, including proteolytic cleavage from larger precursor proteins. These bioactive peptides, typically composed of 3 to 50 amino acids, range in molecular weight from 200 Da to 10 kDa. Their amino acid sequence and composition largely determine their function, while post-translational modifications (PTMs) further refine their physicochemical properties, influencing their solubility, receptor binding, and stability. This enables neuropeptides to participate in diverse neuromodulatory functions beyond being mere byproducts of protein degradation. Neuropeptides play critical roles in synaptic transmission, neuroinflammation, brain development, stress responses, pain perception, appetite regulation, and psychiatric behavior. Some also exhibit antimicrobial properties, contributing to neuroimmune interactions that help regulate inflammation and host defense mechanisms. The regulation of neuropeptide biosynthesis, processing, and secretion is critical for maintaining neuronal homeostasis, as dysregulation can lead to neuropsychiatric disorders, neurodegenerative diseases, and other pathological conditions.
The interdependent functions of many neuropeptides collectively regulate diverse physiological and neural processes, making studies that focus on a single neuropeptide inadequate for capturing their full scope of influence. Neuropeptide co-transmission, along with classical neurotransmitters, further complicates the isolation of their specific contributions to neuronal signaling, while their rapid degradation, low in vivo concentrations, and diffusion in the extracellular space present additional challenges for detection and analysis. Neuropeptide analysis by mass spectrometry (MS)-based techniques, termed neuropeptidomics, has supplanted classical methods such as radioimmunoassays and Edman degradation due to its ability to handle complex samples while providing detailed chemical information. Therefore, MS-based techniques have become the premier method for neuropeptide analysis by providing invaluable information on peptide sequence, relative abundance, PTM characterization, and spatially resolved localization.
Neuropeptidomics involves the direct analysis of endogenous peptides without relying on enzymatic digestion and does not require prior knowledge of peptides present in a sample. These peptidomic methods stem from a branch of proteomics that similarly aims to characterize protein compositions. So-called “bottom-up” proteomics is based on the controlled proteolysis of proteins into sets of cleaved peptide fragments followed by liquid chromatography-tandem mass spectrometry analysis (LC-MS/MS). However, several neuropeptides are endogenously produced fragments derived from larger prohormones with more variable peptide lengths than tryptic fragments. Since trypsin digestion produces a highly complex mixture of peptides, these may mask observations of some other low-abundance short peptides. By forgoing the use of enzymatic proteolysis, native peptide sequences are preserved, allowing for the identification of physiological cleavage patterns without introducing artificial peptide fragments. This enables the detection of low-abundance short neuropeptides in their naturally processed, cleaved form.
Electrospray ionization (ESI) is a soft ionization technique that facilitates the transition into the gas phase with minimal degradation and is readily coupled to online reversed-phase LC separation, enabling high sensitivity and quantitative capabilities in peptide analysis. Peptides partially elute according to their size and hydrophobicity and the analyte is continuously sprayed into and measured by the mass analyzer. MS first measures the mass-to-charge ratios (m/z) of intact peptide “parent” ions in the gas phase (MS 1). These precursor ions are then selected for further fragmentation (MS 2 or MS/MS) to reveal characteristic peptide fragmentation patterns, allowing for peptide characterization and PTM differentiation.
In MS-based peptide analysis, fragment ions are categorized as a/x-, b/y-, and c/z-type, depending on which peptide backbone bond is broken, and peptide sequences are then determined from the MS 2 fragment ion series following an initial MS 1 selection. Commonly employed fragmentation strategies, such as high-energy collision-induced dissociation (HCD) and electron transfer dissociation (ETD) methods, produce MS 2 spectra that contain critical fragment ion information for identifying peptides. In proteomics, these spectra are often searched against an in silico-generated library of theoretical spectra obtained from predicted proteins with predictable cleavage sites from enzymatic proteolysis. Tryptic peptide fragments thus serve as proxies for the protein they originated from, and quantification is performed by aggregating peptides into a single value at the protein level. Whereas bottom-up proteomics attempts to piece together tryptic peptide fragments to inform protein compositions and their isoforms, peptidomics forgoes the use of proteolytic enzymes to directly measure naturally occurring endogenous peptides. Specifically, quantitative peptidomics refers to the systematic characterization and quantification of endogenous peptides present in a biological sample through label-based and label-free methods for relative and absolute quantification.
There is no one-size-fits-all approach for endogenous peptide quantitation by MS-based methods. Label-based quantitative techniques provide increased accuracy and reproducibility with high multiplexing capabilities. In contrast, label-free quantitation can accommodate large sample sets due to straightforward, cost-effective sample preparation and LC-MS/MS analysis. These approaches vary depending on whether the study is discovery-based (untargeted) or if specific peptides (targeted) are being explor
