The EMBO JournalNeurosciencePeer-reviewed journal article
A call for a unified and multimodal definition of cellular identity in the enteric nervous system
Homa MajdiD, Andrius CesiulisiD, Ryan M. SamueliD, Mikayla N RichteriD, Nicholas H. ElderiD, Kwun Wah WeniD, Richard A. GuyeriD, Marlene M. HaoiD, Lincon A. StampiD, Allan M. GoldsteiniD, Faranak FattahiiD
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Abstract
The enteric nervous system (ENS) is a tantalizing frontier in neuroscience. With the recent emergence of single cell transcriptomic technologies, this rare and poorly understood tissue has begun to be better characterized in recent years. A precise functional mapping of enteric neuron diversity is critical for understanding ENS biology and enteric neuropathies. Nonetheless, this pursuit has faced considerable technical challenges. By leveraging different methods to compare available primary mouse and human ENS datasets, we underscore the urgent need for careful identity annotation, achieved through the harmonization and advancements of wet lab and computational techniques. We took different approaches including differential gene expression, module scoring, co-expression and correlation analysis, unbiased biological function hierarchical clustering, data integration and label transfer to compare and contrast functional annotations of several independently reported ENS datasets. These analyses highlight substantial discrepancies stemming from an overreliance on transcriptomics data without adequate validation in tissues. To achieve a comprehensive understanding of enteric neuron identity and their functional context, it is imperative to expand tissue sources and incorporate innovative technologies such as multiplexed imaging, electrophysiology, spatial transcriptomics, as well as comprehensive profiling of epigenome, proteome, and metabolome. Harnessing human pluripotent stem cell (hPSC) models provides unique opportunities for delineating lineage trees of the human ENS, and offers unparalleled advantages, including their scalability and compatibility with genetic manipulation and unbiased screens. We encourage a paradigm shift in our comprehension of cellular complexity and function in the ENS by calling for large-scale collaborative efforts and research investments.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- assay: proteomics
- assay: metabolomics
- research focus: cell type annotation
- research focus: clustering
- research focus: database / resource
- approach: statistical model
- approach: machine learning (classical)
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