Biology subjects

Cheah, K.

Publications and source records attributed to Cheah, K..

3 recordsLinked to original sources

bioRxiv2025

A blastocyst-derived in vitro model of the human chorion

The placenta supports the foetus by mediating nutrient and gas exchange, hormone production, and immune protection. Yet, human placental biology remains poorly understood due to limited in vitro models. The foetal part of the placenta, the chorion, consists of a trophoblast-derived layer and a mesenchymal zone containing extraembryonic mesoderm cells. Here, we show that human blastocysts can give rise to both trophoblast organoids and extraembryonic mesoderm cells under the same culture conditions. Trophoblast organoids originate from both outer trophoblast cells and inner cells of the blastocyst, while extraembryonic mesoderm cells derive exclusively from inner cells. These organoids recapitulate the cellular composition, morphology, and function of the in vivo trophoblast. Moreover, given the high rate of aneuploidy at the blastocyst stage, aneuploid trophoblast organoids can be readily generated. These models reflect the trophoblasts unique ability to tolerate aneuploidy and offer a valuable platform to study human placental development and pathophysiology.

developmental biology↗

bioRxiv2021

Hypertrophic Chondrocytes Serve as a Reservoir for Unique Marrow Associated Skeletal Stem and Progenitor Cells, Osteoblasts, and Adipocytes During Skeletal Development

Hypertrophic chondrocytes give rise to osteoblasts during skeletal development; however, the process by which these non-mitotic cells make this transition is not well understood. Prior studies have also suggested that skeletal stem and progenitor cells (SSPCs) localize to the surrounding periosteum and serve as a major source of marrow associated SSPCs, osteoblasts, osteocytes, and adipocytes during skeletal development. To further understand the cell transition process by which hypertrophic chondrocytes contribute to osteoblasts or other marrow associated cells, we utilized inducible and constitutive hypertrophic chondrocyte lineage tracing and reporter mouse models (Col10a1CreERT2; R26-tdTomatof/+ and Col10a1Cre; R26-tdTomatof/+) in combination with a PDGFRa-H2B-GFP transgenic line, single cell RNA-sequencing, bulk RNA-sequencing, immunofluorescence staining, and cell transplantation assays. Our data demonstrate that hypertrophic chondrocytes undergo a process of dedifferentiation to generate marrow associated SSPCs that serve as a primary source of osteoblasts during skeletal development. These hypertrophic chondrocyte derived SSPCs commit to a CXCL12-abundant reticular (CAR) cell phenotype during skeletal development and demonstrate unique abilities to recruit vasculature and promote bone marrow establishment, while also contributing to the adipogenic lineage.

developmental biology↗

bioRxiv2019

Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells - hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.

bioengineering↗