Characterizing neuropeptide profiles from tens of thousands of cells

The posttranslational enzymatic cleavage of prohormones into bioactive peptides results in the formation of the crucial class of cell-to-cell communication molecules known as neuropeptides. These signaling peptides, once produced, have a role in the development and control of a variety of homoeostatic processes and behaviours, such as mating, eating, olfaction, pain, circadian rhythm, and addiction. Different secondary messenger systems and variation in neuropeptide PTMs, both essential for brain plasticity, are part of neuropeptides’ chemical and functional heterogeneity. Understanding the peptide composition of a single cell is essential for comprehending both normal and pathological neurobiology since neuropeptide expression, colocalization, and activity variability is observed even in nearby cells. Single cell peptide discovery is so hard that biologically active peptides are still be discovered. Mass spectrometry (MS)-based peptidomic measurements, which allow for global characterization of the peptides in a sample, have evolved peptide characterization from targeted investigations to global peptidomics measurements and now are being adapted to single cell measurements.

Although it is no surprise that neuropeptides to differ from one cell to another, it is still not clear exactly how neuropeptide expression significantly differs between neurons. Because of this, it can help to use simpler well-defined animal models when addressing this question. University of Illinois scientists: Dr. Peter Andersen, Assistant Research Professor Elena Romanova, Associate Research Professor Stanislav Rubakhin, and Professor Jonathan Sweedler developed a new high-throughput single cell profiling approach that uses microscopy-guided MS for neuropeptide screening and combined this with the marine mollusc Aplysia californica as the model organism. The research group of Professor Jonathan Sweedler is internationally recognized in analytical neurochemistry research and in developing new innovative measurement methodologies that advanced our understanding of brain physiology and pathology. The goal was to quantify the vast neuropeptide complexity of the brain. The experimental model used, Aplysia is a species of sea slug that has been used extensively in the field of neuroscience to explore molecular mechanisms of processes such as learning and memory; they have a simpler nervous system consisting of about 20,000 and still use a complex suite of neuropeptides and hormones. Here they successfully collected and categorized 26,797 Aplysia single neurons based on their neuropeptide content. The new study is now published in The Journal of Biological Chemistry.

To look at the neuropeptide heterogeneity of individual neurons within the CNS of the neurobiological model Aplysia californica, the research team developed a microscopy-guided, high-throughput single-cell matrix-assisted laser desorption/ionization mass spectrometry method. They successfully mass-matched 866 peptides from 66 prohormones against an in silico peptide library created from known Aplysia prohormones in existing databases. The authors assigned the different neuropeptides to more than 26,000 neurons in 18 animals. Individual neurons’ mass spectra were then subjected to statistical clustering, which identified 40 separate neuronal populations, or clusters, each with its own unique neuropeptide profile. Prohormones and associated peptides were typically detected in isolated ganglia cells, supporting previously reported ganglion localizations. A number of clusters also showed the cellular colocalization of behaviorally associated prohormones, including a cluster with the hormones achatin and neuropeptide Y and another cluster with the distinct hormones such as urotensin II and small cardiac peptide that are active in the feeding network or found in the feeding musculature.

Profiling the gene expression activity in cells is considered as one of the most authentic approaches to probe cell identity, state, function and response. Huge technological breakthroughs have been made in the single-cell transcriptomics during the last decade. With single-cell RNA sequencing, it is now possible to analyze the transcriptome at single-cell level for over millions of cells in a single study. Professor Jonathan Sweedler and his colleagues findings epand on the knowledge acquired from these single cell transcriptomics studies, manual single cell isolation MS analysis, and tissue-level peptidomics. Although the researchers used Aplysia to demonstrate their single-cell methods, the workflow proposed is well suited to research utilizing other animals that may not have the same degree of preexisting biochemical and functional data. The anticipated results will direct future active and behavioural investigations of specific neuropeptides, contribute to our understanding of how neuropeptides and neural networks work, and provides general picture of how neuropeptides and hormones interact in various animal models.

The continuous development of the newly developed technique will broaden its applications in clinical and personalized medicine. The new technique has vast potential in advancing our understanding of biology of the brain and neurodegenerative diseases. Moreover, in the future the new technique can be adapted to a variety of tissues and applied across a breadth of medically important and competitive areas, including cell-based models, cell therapies, regenerative medicine and target discovery.