To the proteome and beyond: advances in single-cell omics profiling for plant systems

Abstract

Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.

Figure 1

An example of single-cell proteomics sample preparation using multiplexing with an isobaric carrier. Single cells are collected using technology such as FACS and deposited into a 96- or 384-well plate for high-throughput sample preparation. During sample preparation, individual cells are lysed either manually or using automated protocols. Individual cells are then labeled using TMT isobaric labels. A reference sample of 5–10 cells and a carrier sample of 100–200 cells are run alongside the single cells to normalize total protein abundance between runs and increase throughput.

Figure 2

Protoplast isolation from plant tissue and FACS to isolate single plant cells. Plant tissue, such as root or leaf, is digested in an enzymatic solution to remove the cell walls. Protoplasts are then filtered through a cell strainer and collected for downstream analysis. During FACS, cells can be separated based on different features such as the presence of a fluorophore, cell size, cell shape, and/or charge. These parameters can be tuned to ensure that only live, individual cells are collected, removing contaminants such as clumps of cells or dead cells.

Figure 3

Analysis and applications of single-cell omics in plants. Single-cell transcriptomics and proteomics must be mapped to the reference genome (or proteome) and normalized before downstream analysis. Initial analysis of single-cell omics data includes selection of HVGs and cell-type assignment. Further applications of single-cell omics data include, but are not limited to, correlation analyses, predictive network inference, and multiscale mathematical modeling such as ABMs.