A Data-Dependent Acquisition Ladder for Ultrasensitive (Neuro)Proteomics

Abstract

Measurement of broad types of proteins from a small number of cells to single cells would help to better understand the nervous system but requires significant leaps in high-resolution mass spectrometry (HRMS) sensitivity. Microanalytical capillary electrophoresis electrospray ionization (CE-ESI) offers a path to ultrasensitive proteomics by integrating scalability with sensitivity. We report here a data acquisition strategy that expands the detectable and quantifiable proteome in trace amounts of digests using CE-ESI-HRMS. Data-dependent acquisition (DDA) was programmed to progressively exclude high-intensity peptide signals during repeated measurements. These nested experiments formed rungs of our "DDA ladder." The method was tested for replicates analyzing ~500 pg of protein digest from cultured hippocampal (primary) neurons (mouse), which estimates to the total amount of protein from a single neuron. Analysis of net amounts approximating to ~10 neurons identified 428 nonredundant proteins (415 quantified), an ~35% increase over traditional DDA. The identified proteins were enriched in neuronal marker genes and molecular pathways of neurobiological importance. The DDA ladder deepens the detectable proteome from trace amounts of proteins, expanding the analytical toolbox of neuroscience.