Classification of Large Cellular Populations and Discovery of Rare Cells Using Single Cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Cell-to-cell
variability and functional heterogeneity are integral
features of multicellular organisms. Chemical classification of cells
into cell type is important for understanding cellular specialization
as well as organismal function and organization. Assays to elucidate
these chemical variations are best performed with single cell samples
because tissue homogenates average the biochemical composition of
many different cells and oftentimes include extracellular components.
Several single cell microanalysis techniques have been developed but
tend to be low throughput or require preselection of molecular probes
that limit the information obtained. Mass spectrometry (MS) is an
untargeted, multiplexed, and sensitive analytical method that is well-suited
for studying chemically complex individual cells that have low analyte
content. In this work, populations of cells from the rat pituitary,
the rat pancreatic islets of Langerhans, and from the Aplysia californica nervous system, are classified
using matrix-assisted laser desorption/ionization time-of-flight mass
spectrometry (MALDI) MS by their peptide content. Cells were dispersed
onto a microscope slide to generate a sample where hundreds to thousands
of cells were separately located. Optical imaging was used to determine
the cell coordinates on the slide, and these locations were used to
automate the MS measurements to targeted cells. Principal component
analysis was used to classify cellular subpopulations. The method
was modified to focus on the signals described by the lower principal
components to explore rare cells having a unique peptide content.
This approach efficiently uncovers and classifies cellular subtypes
as well as discovers rare cells from large cellular populations.