Biology subjects

Ng, L. G.

Publications and source records attributed to Ng, L. G..

7 recordsLinked to original sources

bioRxiv2026

A Genetic Tool for Specific Tracking of Mature Neutrophils

Tracking mature neutrophils remains challenging due to the lack of reliable cell surface markers. Although CD101 is a promising candidate for mature neutrophils, its stability under pathological conditions is unclear. Using a CD101-tdTomato reporter mouse model, we confirmed that the reporting system does not alter CD101 expression, and tdTomato fluorescence is predominantly expressed in mature neutrophils across peripheral tissues. Further analysis revealed that CD101+ and tdTomato+ neutrophils display identical characteristics of mature neutrophil, including poly-segmented nuclei, cell size, and key functions under homeostasis. By comparing tdTomato fluorescence with CD101 protein levels, we demonstrate that reduced CD101 expression under pathological states was not attributed to shedding or degradation. Our finding enhances CD101 as a robust and reliable marker of neutrophil maturity, providing a foundation for future applications in spatial transcriptomics and lineage tracing studies to dissect neutrophil heterogeneity and function. Highlights of the studyO_LIIn CD101-tdTomato homozygous mice, tdTomato is predominantly expressed in neutrophils and labels nearly 100% of mature neutrophils, aligning with the phenotype of CD101+ mature neutrophils; C_LIO_LIThe CD101-tdTomato reporting system does not interrupt CD101 expression or neutrophil functions; C_LIO_LICD101 remains a stable and reliable cell surface marker for labeling mature neutrophils, even under pathological conditions. C_LI

immunology↗

bioRxiv2025

STEAP4+ neutrophils: a promising circulating biomarker for lung metastasis

As the leading contributor to cancer-related mortality, metastasis often evades detection until advanced stages, underscoring the critical need for early predictive biomarkers. Neutrophils are naturally circulating sentinels that have been implicated in pioneering pre-metastatic niche formation in distant organs. Nevertheless, their heterogeneity within evolving metastatic microenvironments remains poorly characterized. Here, through dynamically delineating neutrophil subsets via single-cell transcriptomics, we identified a conserved feature of lung metastasis in breast cancer and other cancer models. Among the core genes, a cell surface marker, STEAP4, was selected and validated to indicate lung metastases at both RNA and protein levels. In both humans and mice, these STEAP4+ neutrophils were detectable not only in lung metastatases but also in the circulation. Clinically, the abundance of circulating STEAP4+ neutrophils robustly discriminates patients with lung metastasis from those with localized primary tumor. Our findings uncover STEAP4+ neutrophils as a promising biomarker and lay the groundwork for a non-invasive, blood-based diagnostic strategy for metastatic disease.

cancer biology↗

bioRxiv2023

Integrated analysis of spatial multi-omics with SpatialGlue

Integration of multiple data modalities in a spatially informed manner remains an unmet need for exploiting spatial multi-omics data. We introduce SpatialGlue, a graph neural network with dual-attention mechanism, to learn each modalitys significance at cross-omics and intra-omics integration. We demonstrate that SpatialGlue can accurately aggregate cell types into spatial domains at a higher resolution on different tissue types and technology platforms, as well as gain insights into cross-modality spatial correlations.

bioinformatics↗

bioRxiv2021

WDR82-binding long non-coding RNA lncEry controls mouse erythroid differentiation and maturation

Hematopoietic differentiation is controlled by both genetic and epigenetic regulators. Long non-coding RNAs (lncRNAs) have been demonstrated to be important for normal hematopoiesis, but their function in erythropoiesis needs to be further explored. We profiled the transcriptomes of 16 murine hematopoietic cell populations by deep RNA-sequencing and identified a novel lncRNA, Gm15915, that was highly expressed in erythroid-related progenitors and erythrocytes. For this reason, we named it lncEry. We also identified a novel lncEry isoform, which was also the principal transcript that has not been reported before. LncEry depletion impaired erythropoiesis, indicating the important role of the lncRNA in regulating erythroid differentiation and maturation. Mechanistically, we found that lncEry interacted with WD repeat-containing protein 82 (WDR82) to promote the transcription of Klf1 and globin genes and thus control the early and late stages of erythropoiesis, respectively. These findings identified lncEry as an important player in the transcriptional regulation of erythropoiesis.

cell biology↗

bioRxiv2020

Whole blood immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early prognostic marker for severe COVID-19

SARS-CoV-2 is the novel coronavirus responsible for the current COVID-19 pandemic. Severe complications are observed only in a small proportion of infected patients but the cellular mechanisms underlying this progression are still unknown. Comprehensive flow cytometry of whole blood samples from 54 COVID-19 patients revealed a dramatic increase in the number of immature neutrophils. This increase strongly correlated with disease severity and was associated with elevated IL-6 and IP-10 levels, two key players in the cytokine storm. The most pronounced decrease in cell counts was observed for CD8 T-cells and VD2 {gamma}{delta} T-cells, which both exhibited increased differentiation and activation. ROC analysis revealed that the count ratio of immature neutrophils to CD8 or VD2 T-cells predicts pneumonia onset (0.9071) as well as hypoxia onset (0.8908) with high sensitivity and specificity. It would thus be a useful prognostic marker for preventive patient management and improved healthcare resource management.

immunology↗

bioRxiv2018

Evaluation of UMAP as an alternative to t-SNE for single-cell data

Uniform Manifold Approximation and Projection (UMAP) is a recently-published non-linear dimensionality reduction technique. Another such algorithm, t-SNE, has been the default method for such task in the past years. Herein we comment on the usefulness of UMAP high-dimensional cytometry and single-cell RNA sequencing, notably highlighting faster runtime and consistency, meaningful organization of cell clusters and preservation of continuums in UMAP compared to t-SNE.

bioinformatics↗

bioRxiv2018

Reverse-engineering flow-cytometry gating strategies for phenotypic labelling and high-performance cell sorting

MotivationRecent flow and mass cytometers generate 1,000,000 single cell datasets of dimensions 20 to 40. Many tools facilitate the discovery of new cell populations associated with diseases or physiology. These discoveries require the identification of new gating strategies, but gating strategies become exponentially harder to optimize when dimensionality increases. To facilitate this step we developed Hypergate, an algorithm which given a cell population of interest identifies a gating strategy optimized for high yield and purity.\n\nResultsHypergate achieves higher yield and purity than human experts, Support Vector Machines and Random-Forests on public datasets. We use it to revisit some established gating strategies for the identification of Innate lymphoid cells, which identifies concise and efficient strategies that allow gating these cells with fewer parameters but higher yield and purity than the current standards. For phenotypic description, Hypergates outputs are consistent with fields knowledge and sparser than those from a competing method.\n\nAvailability and ImplementationHypergate is implemented in R and available at http://github.com/ebecht/hypergate under an Open Source Initiative-compliant licence.

bioinformatics↗