Unlocking the Neuropeptidome using a Novel Endogenous Peptidomics Framework

Area of Science:

• Biochemistry
• Analytical Chemistry
• Neuroscience

Background:

• Endogenous peptides, especially neuropeptides, are crucial but difficult to study due to low concentrations and high variability.
• Existing data-independent acquisition (DIA) mass spectrometry (MS) tools are often unsuitable for endogenous peptides because they lack defined enzymatic cleavage sites.

Purpose of the Study:

• To develop a novel analytical framework for high-confidence neuropeptide identification using DIA-MS.
• To create the largest crustacean neuropeptide spectral library to date.
• To significantly increase the number of identified neuropeptides in Cancer borealis.

Main Methods:

• Utilized the novel EndoGenius platform combined with DIA-NN software for DIA-MS analysis.
• Employed orthogonal offline fractionation and ion mobility instrumentation.
• Developed an optimized database searching algorithm and an updated spectral library specifically for neuropeptides.
• Cross-validated findings with transcriptomics data.

Main Results:

• Constructed the largest crustacean neuropeptide spectral library.
• Achieved a 100-fold increase in identified neuropeptides across all Cancer borealis tissues analyzed.
• Enhanced identification confidence through transcriptomics data validation.

Conclusions:

• The EndoGenius platform and DIA-NN provide a robust analytical framework for DIA peptidomics.
• This approach significantly advances the study of neuropeptides and other endogenous peptides.
• The developed spectral library and workflow enable more comprehensive neuropeptidome analysis.