Modeling human nutrition using human embryonic stem cells

Distribution-Agnostic Deep Learning Enables Accurate Single-Cell Data Recovery and Transcriptional Regulation Interpretation

Single-cell RNA sequencing (scRNA-seq) is a robust method for studying gene expression at the single-cell level, but accurately quantifying genetic material is often hindered by limited mRNA capture, resulting in many missing expression values. Existing imputation methods rely on strict data assumptions, limiting their broader application, and lack reliable supervision, leading to biased signal recovery. To address these challenges, authors developed Bis, a distribution-agnostic deep learning model for accurately recovering missing sing-cell gene expression from multiple platforms. Bis is an optimal transport-based autoencoder model that can capture the intricate distribution of scRNA-seq data while addressing the characteristic sparsity by regularizing the cellular embedding space. Additionally, they propose a module using bulk RNA-seq data to guide reconstruction and ensure expression consistency. Experimental results show Bis outperforms other models across simulated and real datasets, showcasing superiority in various downstream analyses including batch effect removal, clustering, differential expression analysis, and trajectory inference. Moreover, Bis successfully restores gene expression levels in rare cell subsets in a tumor-matched peripheral blood dataset, revealing developmental characteristics of cytokine-induced natural killer cells within a head and neck squamous cell carcinoma microenvironment.

Links between Nutrition, Infectious Diseases, and Microbiota: Emerging Technologies and Opportunities for Human-Focused Research

The interaction between nutrition and human infectious diseases has always been recognized. With the emergence of molecular tools and post-genomics, high-resolution sequencing technologies, the gut microbiota has been emerging as a key moderator in the complex interplay between nutrients, human body, and infections. Much of the host-microbial and nutrition research is currently based on animals or simplistic in vitro models. Although traditional in vivo and in vitro models have helped to develop mechanistic hypotheses and assess the causality of the host-microbiota interactions, they often fail to faithfully recapitulate the complexity of the human nutrient-microbiome axis in gastrointestinal homeostasis and infections. Over the last decade, remarkable progress in tissue engineering, stem cell biology, microfluidics, sequencing technologies, and computing power has taken place, which has produced a new generation of human-focused, relevant, and predictive tools. These tools, which include patient-derived organoids, organs-on-a-chip, computational analyses, and models, together with multi-omics readouts, represent novel and exciting equipment to advance the research into microbiota, infectious diseases, and nutrition from a human-biology-based perspective. After considering some limitations of the conventional in vivo and in vitro approaches, in this review, we present the main novel available and emerging tools that are suitable for designing human-oriented research.

Roles of H3K27me2 and H3K27me3 Examined during Fate Specification of Embryonic Stem Cells

The polycomb repressive complex 2 (PRC2) methylates lysine 27 of histone H3 (H3K27) through its catalytic subunit Ezh2. PRC2-mediated di- and tri-methylation (H3K27me2/H3K27me3) have been interchangeably associated with gene repression. However, it remains unclear whether these two degrees of H3K27 methylation have different functions. In this study, we have generated isogenic mouse embryonic stem cells (ESCs) with a modified H3K27me2/H3K27me3 ratio. Our findings document dynamic developmental control in the genomic distribution of H3K27me2 and H3K27me3 at regulatory regions in ESCs. They also reveal that modifying the ratio of H3K27me2 and H3K27me3 is sufficient for the acquisition and repression of defined cell lineage transcriptional programs and phenotypes and influences induction of the ESC ground state.

Genome engineering of stem cell organoids for disease modeling

Precision medicine emerges as a new approach that takes into account individual variability. Successful realization of precision medicine requires disease models that are able to incorporate personalized disease information and recapitulate disease development processes at the molecular, cellular and organ levels. With recent development in stem cell field, a variety of tissue organoids can be derived from patient specific pluripotent stem cells and adult stem cells. In combination with the state-of-the-art genome editing tools, organoids can be further engineered to mimic disease-relevant genetic and epigenetic status of a patient. This has therefore enabled a rapid expansion of sophisticated in vitro disease models, offering a unique system for fundamental and biomedical research as well as the development of personalized medicine. Here we summarize some of the latest advances and future perspectives in engineering stem cell organoids for human disease modeling.

Distinct Metabolic States Can Support Self-Renewal and Lipogenesis in Human Pluripotent Stem Cells under Different Culture Conditions

Recent studies have suggested that human pluripotent stem cells (hPSCs) depend primarily on glycolysis and only increase oxidative metabolism during differentiation. Here, we demonstrate that both glycolytic and oxidative metabolism can support hPSC growth and that the metabolic phenotype of hPSCs is largely driven by nutrient availability. We comprehensively characterized hPSC metabolism by using (13)C/(2)H stable isotope tracing and flux analysis to define the metabolic pathways supporting hPSC bioenergetics and biosynthesis. Although glycolytic flux consistently supported hPSC growth, chemically defined media strongly influenced the state of mitochondrial respiration and fatty acid metabolism. Lipid deficiency dramatically reprogramed pathways associated with fatty acid biosynthesis and NADPH regeneration, altering the mitochondrial function of cells and driving flux through the oxidative pentose phosphate pathway. Lipid supplementation mitigates this metabolic reprogramming and increases oxidative metabolism. These results demonstrate that self-renewing hPSCs can present distinct metabolic states and highlight the importance of medium nutrients on mitochondrial function and development.