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Exploring cell mechanics with single-cell omics approaches

The mechanical properties of cells are known to be associated with physiological states in various biological contexts, such as cell differentiation, cancer, and aging. However, the underlying molecular cascade remains largely elusive. We have developed novel methods capable of integrating cell mechanics profiling with unbiased transcriptomics for thousands of single cells to elucidate the intricate molecular mechanisms governing cellular behavior in diverse biological processes. Find out more in our recent paper (Shiomi et al. Nat Commun 2024).

Linking phenotypic response to perturbation and transcriptome

For decades, it has been acknowledged that even genetically identical cells can exhibit diverse phenotypic responses to stimuli such as drugs. These variations in phenotypic responses ultimately lead to distinct cell fates, as exemplified by the emergence of drug-resistant populations in cancer cells. A widely accepted hypothesis is that the variation in gene expression is a key factor in the emergence of cell-to-cell variations. However, the molecular cascade of how this variation in gene expression gives rise to different phenotypic responses has remained a mystery, largely owing to the challenges of simultaneously profiling phenotypic responses and the transcriptome. To unravel this mystery, we have introduced an approach combining optical indices from cells and hydrogel beads to link cellular phenotypic response to drugs with single-cell RNA sequencing (Tsuchida et al. (LabChip 2024)).  To further refine our understanding in the temporal direction, we are broadening our approach for linking the transcriptome to the dynamic behaviors of cells, including proliferation and cell cycle progression.

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Hunt for aiding and abetting cells in metastatic niches with secretory GFP reconstitution

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During metastasis, cancer cells interact with neighboring tissue-resident cells and form metastatic niches to gain benefits for their growth. However, the underlying molecular mechanisms promoting metastatic growth are yet to be fully elucidated owing to the lack of methodologies for comprehensive analysis of cell-cell interactions in the metastatic niches.

Here, we developed sGRAPHIC for fluorescent labeling of tissue-resident cells that are close to and interact with cancer cells in deep tissues. The sGRAPHIC enables to isolate metastatic constituting cells for their characterization with single-cell RNA sequencing technology. In the liver metastatic niches, we identified that hepatocytes interacting with cancer cells express Lgals3, encoding galectin-3, as a potential pro-metastatic factor and accelerate metastatic growth and invasion.

(See Minegishi et al. (Nat Commun 2023). This work was done in collaboration with Dr. Kuchimaru group.)

Resolving the regulation of mRNA expression at the subcellular resolution

Protein coding transcripts are synthesized and processed in the nucleus before being exported to the cytoplasm for translation. Long noncoding RNAs (lncRNAs) are enriched and function in the nucleus. However, our understanding of nucleocytoplasmic isoform usage, nuclear export, and transcript degradation is limited at the population level, and their effects on cellular heterogeneity at the single-cell level remain largely unexplored.

To investigate isoform diversity in the cytoplasm and nuclei of single cells, we developed a method called single-cell integrated nuclear and cytoplasmic RNA sequencing (SINC-seq). This technique utilizes the physical separation of the cytoplasm and nucleus through microfluidic electrokinetics. For more details, refer to Abdelmoez et al. (Genome Biol 2018) and Oguchi et al. (Sci Adv 2021).

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