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PubMed2026

Four-dimensional molecular mapping from a spatial snapshot reveals the dynamics of hair follicle organogenesis.

Understanding organ formation requires capturing molecular information simultaneously in three-dimensional (3D) space and across developmental time. To this end, we developed 3D DNase-Enhanced Expression Profiling (3DEEP), a tissue-clearing approach that removes genomic DNA to extend spatial transcriptomic profiling hundreds of microns into intact tissues. We applied 3DEEP to neonatal mouse skin, capturing hundreds of developing hair follicles across their organogenesis trajectory. Ordering follicles by molecularly inferred developmental age transformed this single spatial snapshot into a four-dimensional (3D + time) molecular map of organogenesis. This map revealed developmental dynamics spanning stem cell compartment stratification, emergence of new cell subtypes within the follicle, and cascading structural transformations leading to hair canal formation. Comparative analysis of Foxn1-deficient nude mice, a hairlessness model, revealed organ-wide changes in developmental dynamics, including delayed molecular progression, reduced coordination, and increased developmental instability, preceding overt structural defects. This work demonstrates how deep-tissue spatial transcriptomics can uncover hidden dynamics of organ formation.

Animals↗

PubMed2026

Decoding spatiotemporal fibrotic and cellular immunosuppression of therapeutic T cells in live pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDA) is profoundly immunosuppressive. To help define this behavior, we present integrated experimental and computational frameworks to elucidate therapeutic T cell dynamics. Through the development of TME-CARTographer (TME-CART), a computational pipeline integrating high-dimensional data, graph theory, behavior analysis, and deep learning (DL), we present quantitative insights on 4D T cell-TME interactions in live PDA tumors. Mapping physical immunosuppression demonstrates that collagen fiber architectures direct migration while concomitantly limiting off-axis movement, creating immune exclusion zones. Expanding these findings, we establish that the collagen matrix harbors and spatially organizes immunosuppressive myeloid cells to serve as cooperative co-modulators of T cell behaviors, including migration, sampling, repulsion, and sequestration. Consistent with these findings, DL defines both linear and nonlinear collagen matrix and cellular neighborhood interactions as drivers of T cell behavior. The TME-CART DL framework also accurately predicts shifts in immunosuppression following depletion of myeloid cells. Overall, we identify synergistic barriers impeding anti-tumor T cell behaviors and present TME-CART as a discovery platform for interpreting complex 4D data to enhance the understanding and design of immunotherapies.

Journal Article↗

PubMed2025

Landscape and m6A post-transcriptional regulation of soybean proteome.

The soybean is a critical source of vegetable protein, but its proteome remains undercharacterized. Here, we quantify 12,855 proteins across 14 soybean organs using 4D data-independent acquisition mass spectrometry (4D-DIA-MS), creating the most extensive soybean proteome dataset to date. Organ-specific protein expression and co-expression analyses highlight functional specificity with significant differences in protein-transcript abundance across organs. We also map N6-methyladenosine (m6A) modifications, identifying their key role in post-transcriptional protein regulation. Integrative analysis of the proteome and m6A methylome identifies a novel regulator in m6A methylation. This comprehensive proteomic and m6A landscape advances our understanding of soybean biology and provides a valuable resource for crop improvement.

Glycine max↗

PubMed2026

Integrated LiP-MS and quantitative proteomics reveal coordinated alterations in protein conformation and expression across tumor and peritumoral regions in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) exhibits substantial molecular heterogeneity, yet protein-level alterations beyond abundance remain insufficiently characterized. Here, we integrated limited proteolysis mass spectrometry (Lip-MS) with 4D label-free quantitative proteomics to investigate conformational accessibility and protein abundance across tumor, peritumoral-near, and peritumoral-far tissues from HCC patients. Differential LiP peptides identified by both DDA and DIA corresponded to 725, 674, and 33 differentially conformed proteins in the Tumor vs. Peritumor-far, Tumor vs. Peritumor-near, and Peritumor-near vs. Peritumor-far comparisons, respectively. Quantitative proteomics identified 405, 365, and 4 differentially expressed proteins in the corresponding comparisons. Integrated analysis identified 488 and 469 conformation-specific altered proteins (CSAPs), which showed altered conformational accessibility without significant abundance changes, and 237 and 205 conformation-expression coupled proteins (CECPs) in the two tumor-involved comparisons. LiP peptide and protein abundance changes were positively correlated, with Spearman coefficients of 0.69-0.72, and more than 99% of CECPs showed concordant directions. Among them, 169 region-conserved CECPs (rcCECPs) were predominantly associated with metabolic and redox-related pathways. Protein-protein interaction analysis identified 30 hub rcCECPs. ACLY, ALDH18A1, GMPS, and DHX9 showed increased representative LiP peptide signals and protein abundance, elevated transcript expression in HCC, and associations with poorer overall survival. Peptide mapping further localized their differential LiP signals to specific sequence regions and annotated domains. Collectively, these findings provide an integrated view of regional conformational accessibility and protein abundance alterations in HCC and identify candidate proteins for further structural and functional investigation.

Humans↗