Enabling technologies for Plant Biology

Current: Ao Liu, Andrea Mair, Steven Huang

Collaborators: Lily Cheung, Shouling Xu

Alumni: Diego Wengier, Yan Gong, Kimmy Ho, Laura Lee, Camila Lopez-Anido

In our pursuit of understanding behaviors of genes and cells in the context of a developing organ we have needed new transcriptomic, proteomic and computation tools. Whenever possible, we try to make these tools generalizable and available to the broader research community. Return to Main Research

scRNA seq for flexible cell fate decisions

Cellular fate specification and differentiation are core features of developmental programs in multicellular organisms. Molecular genetics established the classical view of cell fate commitments as discrete and sequential stages, but more recent work incorporating single-cell RNA sequencing (scRNAseq) revealed that the paths toward cell fates are not always as straightforward and decisive as we thought. We were among the first wave of plant researchers to use scRNAseq to track development in plant leaves. In one set of experiments, we captured cells from all tissue layers, thereby providing an atlas of leaf development that serves as a hypothesis generating and testing resource. Our major focus, however, is the question of developmental flexibility. By including scRNAseq data from pre-sorted stomatal lineage cells, we could define flexible cell states in the epidermal landscape.

Proximity-labeling for sensitive protein-interaction and cell-type specific proteomes

Defining specific protein interactions and spatially or temporally restricted local proteomes improves our understanding of virtually all cellular processes. Obtaining such data is challenging, especially for rare proteins, cell-types or events. In recent years, development of proximity labeling techniques (like TurboID) has enabled discovery of protein neighborhoods that define functional complexes and/or catalog subcellular protein compositions. We were particularly interested in the promise of TurboID to let us find the in vivo partners of key regulatory proteins expressed at low levels in a small number of cells and to identify the entire nuclear proteome of a rare cell-type. Our test cases for these general questions were the transcription factor FAMA and the stomatal guard cell. Analysis of proteins labeled by FAMA-TurboID fusions revealed known interactors of this late stomatal lineage-specific transcription factor, as well as proteins we had not known were partners, and whose activities could facilitate FAMA’s function as an activator and repressor in different contexts. By targeting TurboID to the nucleus of young stomatal guard cells, we were further able to purify proteins specific for this subcellular compartment and cell type.

We also created and tested a suite of TurboID and miniTurboID constructs in Arabidopsis and N. benthamiana to enable customization of the system for other users. These vectors are deposited at Addgene and provide a toolkit to enable their wide use by the research community.

Some recent papers on this theme:

Single-cell resolution of lineage trajectories in the Arabidopsis stomatal lineage and developing leaf (2021) Camila Lopez-Anido, lead author [link to PDF]

Quantitative and dynamic cell polarity tracking in plant cells (2021) Yan Gong, lead author [link to PDF]

Proximity labeling of protein complexes and cell-type-specific organellar proteomes in Arabidopsis enabled by TurboID (2019) Andrea Mair, lead author [link to PDF]

Cell-type--specific transcriptome and histone modification dynamics during cellular reprogramming in the Arabidopsis stomatal lineage (2019) Laura Lee, lead author [link to PDF]