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Biology subjects

Hoang, G.

Publications and source records attributed to Hoang, G..

2 recordsLinked to original sources

Enabling subcellular DESI-MSI for broad adoption: Acquisition, analysis, and application

Subcellular mass spectrometry imaging (MSI) has required specialized instrumentation and approaches. Additionally, data analysis has required expensive proprietary software, or code-based open-source tools. These barriers render spatial metabolomics less accessible than peer spatial omics techniques (transcriptomics, proteomics). Here we demonstrate subcellular MSI on standard commercial hardware, analyzed using code-free, open-source software. An inexpensive, fully reversible modification of a stock DESI source takes the platform past its typical 5-10 m pixels to routine 2x2 m pixels, and 1x1 m in proof-of-principle experiments. At a tissue-glass boundary imaged at 2x2 m, tissue-specific ions showed no measurable spillover onto the adjacent glass within the {+/-}4.4 m uncertainty of the edge position. To make these data interpretable, we extend MSI.EAGLE, an open-source, vendor-agnostic application with two new methods: i) Spatial UMAP preserves tissue architecture alongside subcellular detail, where conventional clustering breaks apart at high resolution; ii) Histology Fit performs landmark-free co-registration, and recovers synthetic misalignments of up to 8 m to within one pixel of a reference registration. Together, these enable previously high-burden spatial metabolomics experiments. In mouse brain tissue, we demonstrate genuine subcellular signal by resolving mitochondrial cardiolipin into perinuclear puncta, quantifying cytoplasmic enrichment across 6,073 cells. Cell identities are assigned to MSI pixels using histology-predicted transcriptomics, linking cell provenance to metabolism in 2D space directly. Finally, we recover cell-type-specific metabolomes consistent with the transcriptomic identities. This workflow allows cellular and subcellular spatial metabolomics linked to cell provenance, with only stock MSI hardware, open-source GUI-based software, and common histology techniques, putting it within reach of many researchers and laboratories.

molecular biology↗

The Zinc Finger protein SlZFP2 is essential for tomato fruit locular tissue morphogenesis

In tomato (Solanum lycopersicum L.) fruit, the locular tissue (LT) is a unique jelly-like tissue that differentiates from the central axis of the fruit after ovule fertilization. LT is essential for seed development and dispersal by preventing early germination and initiating fruit ripening. In this work, we studied a "gel-less" mutant and identified the underlying mutation in the coding sequence of the C2H2 zinc finger transcription factor (TF) SlZFP2. Histological, cytological and molecular characterization from knockout-CRISPR/Cas9 lines for this gene revealed the strong and early impact of zfp2 mutation on cell cycle and endocycle in LT. Additionally, model-based analysis of cellular data revealed that cell cycle was the main altered process, explaining the zfp2 mutant phenotype. Further laser capture microdissection coupled with RNA-Seq analysis of young LT highlighted global expression changes between WT and zfp2 mutant and led to a preliminary list of potential direct targets of the SlZFP2 TF. This multifaceted approach not only uncovered a new role for SlZFP2 TF as an essential regulator of LT morphogenesis, but also provides a foundation for future works aimed at deciphering the intricate regulatory networks governing fruit tissue development in tomato. One sentence summaryAlteration of cell division and endoreduplication in a gel-less mutant reveals the role of the transcription factor SlZFP2 in tomato locular tissue morphogenesis

plant biology↗