SON-dependent nuclear speckle rehabilitation alleviates proteinopathies.

Current treatments targeting individual protein quality control pathways have limited efficacy in alleviating proteinopathies, highlighting the prerequisite for a common druggable target capable of global proteostasis modulation. Building upon our prior research establishing nuclear speckles as pivotal membrane-less organelles for transcriptional control of proteostasis, we aim to alleviate proteinopathies through nuclear speckle rehabilitation. We identify pyrvinium pamoate as a nuclear speckle rehabilitator that enhances protein quality control gene expression and suppresses YAP1 transcriptional activity via decreasing the surface/interfacial tension of nuclear speckle condensates through interaction with the intrinsically disordered region of nuclear speckle scaffold protein SON.

CellLENS enables cross-domain information fusion for enhanced cell population delineation in single-cell spatial omics data.

Delineating cell populations is crucial for understanding immune function in health and disease. Spatial omics technologies offer insights by capturing three complementary domains: single-cell molecular biomarker expression, cellular spatial relationships and tissue architecture. However, current computational methods often fail to fully integrate these multidimensional data, particularly for immune cell populations and intrinsic functional states.

Quantitative characterization of tissue states using multiomics and ecological spatial analysis.

The spatial organization of cells in tissues underlies biological function, and recent advances in spatial profiling technologies have enhanced our ability to analyze such arrangements to study biological processes and disease progression. We propose MESA (multiomics and ecological spatial analysis), a framework drawing inspiration from ecological concepts to delineate functional and spatial shifts across tissue states. MESA introduces metrics to systematically quantify spatial diversity and identify hot spots, linking spatial patterns to phenotypic outcomes, including disease progression.

A multi-omics spatial framework for host-microbiome dissection within the intestinal tissue microenvironment.

The intricate interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host and microbiome across multiple spatial modalities.

Same-Slide Spatial Multi-Omics Integration Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment.

The advent of spatial transcriptomics and spatial proteomics have enabled profound insights into tissue organization to provide systems-level understanding of diseases. Both technologies currently remain largely independent, and emerging same slide spatial multi-omics approaches are generally limited in plex, spatial resolution, and analytical approaches. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined and resource-effective approach compatible with various spatial platforms.

Basic research and opportunities for translational advancement in the field of mammalian ∼12-hour ultradian chronobiology.

Repetitive variations, such as oscillation, are ubiquitous in biology. In this mini review, we present a general summary of the ∼24 h circadian clock and provide a fundamental overview of another biological timekeeper that maintains ∼12 h oscillations. This ∼12 h oscillator is proposed to function independently of the circadian clock to regulate ultradian biological rhythms relevant to both protein homeostasis and liver health.

The SET1/COMPASS subunit RBBP5 orchestrates epigenetic control of global proteostasis and the 12h oscillator to safeguard metabolic and cellular homeostasis.

Proteostasis is vital for cellular health, with disruptions leading to aging, neurodegeneration and metabolic disorders. Traditionally, proteotoxic stress responses were studied as acute reactions to various noxious factors; however, recent evidence reveals that many proteostasis genes exhibit ~12h ultradian rhythms under physiological conditions in mammals, driven by an XBP1s-dependent 12h oscillator. By examining the chromatin landscape of this oscillator, we identified RBBP5 as an essential epigenetic regulator of global proteostasis dynamics.

Evidence for ~12-h ultradian gene programs in humans.

Mice and many marine organisms exhibit ~12-h ultradian rhythms, however, direct evidence of ~12-h ultradian rhythms in humans is lacking. Here, we performed prospective, temporal transcriptome profiling of peripheral white blood cells from three healthy humans. All three participants independently exhibited robust ~12-h transcriptional rhythms in molecular programs involved in RNA and protein metabolism, with strong homology to circatidal gene programs previously identified in Cnidarian marine species.

Activation of Peroxisome Proliferator-Activated Receptor-β/δ (PPARβ/δ) in Keratinocytes by Endogenous Fatty Acids.

Nuclear hormone receptors exist in dynamic equilibrium between transcriptionally active and inactive complexes dependent on interactions with ligands, proteins, and chromatin. The present studies examined the hypothesis that endogenous ligands activate peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) in keratinocytes. The phorbol ester treatment or HRAS infection of primary keratinocytes increased fatty acids that were associated with enhanced PPARβ/δ activity.

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data.

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice.

Methionine as a regulator of bone remodeling with fasting.

Caloric restriction improves metabolic health but is often complicated by bone loss. We studied bone parameters in humans during a 10-day fast and identified candidate metabolic regulators of bone turnover. Pro-collagen 1 intact N-terminal pro-peptide (P1NP), a bone formation marker, decreased within 3 days of fasting.

Epigenetically active chromatin in neonatal iWAT reveals GABPα as a potential regulator of beige adipogenesis.

Background: Thermogenic beige adipocytes, which dissipate energy as heat, are found in neonates and adults. Recent studies show that neonatal beige adipocytes are highly plastic and contribute to >50% of beige adipocytes in adults. Neonatal beige adipocytes are distinct from recruited beige adipocytes in that they develop independently of temperature and sympathetic innervation through poorly defined mechanisms.

A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section.

SON-dependent nuclear speckle rehabilitation alleviates proteinopathies.

Current treatments targeting individual protein quality control pathways have limited efficacy in alleviating proteinopathies, highlighting the prerequisite for a common druggable target capable of global proteostasis modulation. Building upon our prior research establishing nuclear speckles as pivotal membrane-less organelles for transcriptional control of proteostasis, we aim to alleviate proteinopathies through nuclear speckle rehabilitation. We identified pyrvinium pamoate as a nuclear speckle rehabilitator that enhances protein quality control gene expression and suppresses YAP1 transcriptional activity via decreasing the surface/interfacial tension of nuclear speckle condensates through interaction with the intrinsically disordered region of nuclear speckle scaffold protein SON.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment.

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous probing of host features and its microbiome across multiple spatial modalities.

MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data.

T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response.

Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8 T cells.

LEF1 isoforms regulate cellular senescence and aging.

The study of aging and its mechanisms, such as cellular senescence, has provided valuable insights into age-related pathologies, thus contributing to their prevention and treatment. The current abundance of high-throughput data combined with the surge of robust analysis algorithms has facilitated novel ways of identifying underlying pathways that may drive these pathologies. For the purpose of identifying key regulators of lung aging, we performed comparative analyses of transcriptional profiles of aged versus young human subjects and mice, focusing on the common age-related changes in the transcriptional regulation in lung macrophages, T cells, and B immune cells.

Integration of spatial and single-cell data across modalities with weakly linked features.

Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked.

LEF1 isoforms regulate cellular senescence and aging.

Background: The study of aging and its mechanisms, such as cellular senescence, has provided valuable insights into age-related pathologies, thus contributing to their prevention and treatment. The current abundance of high throughput data combined with the surge of robust analysis algorithms has facilitated novel ways of identifying underlying pathways that may drive these pathologies.

Methods: With the focus on identifying key regulators of lung aging, we performed comparative analyses of transcriptional profiles of aged versus young human subjects and mice, focusing on the common age-related changes in the transcriptional regulation in lung macrophages, T cells, and B immune cells.

Organization of the human intestine at single-cell resolution.

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health. The intesting has a length of over nine metres, along which there are differences in structure and function. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function.

MAPS: Pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data.