Decoding maize meristems maintenance and differentiation: integrating single-cell and spatial omics

Journal of genetics and genomics/Journal of Genetics and Genomics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Sequencing-based Spatial Transcriptomics with scRNA-seq Sensitivity

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

The advent of spatial transcriptomics has dramatically expanded our ability to study the vast network cell-cell interactions at molecular level in tissue. Among current methods, sequencing-based approaches have great potential discovering because its unbiased capture. In last couple years, resolution for capture addresses been significantly improved from 100 μm <1 μm, well below size a mammalian cell. However, efficiency always pain point, ~one order magnitude lower than that single cell RNA sequencing (scRNA-seq). low limits depth and breadth applications complex biological systems diseases. Here, we introduce Salus Spatial transcriptomic system (Salus-STS), which provides ~1 higher other methods. Analysis with sub-cellular becomes practical transcriptomics.

Language: Английский

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Disruption and adaptation: infant gut microbiota’s dynamic response to SARS-CoV-2 infection

Microbiome, Journal Year: 2025, Volume and Issue: 13(1)

Published: March 11, 2025

The responses of the infant gut microbiota to infection significantly disrupt natural intrahost evolutionary processes microbiome. Here, we collected a 16-month longitudinal cohort microbiomes affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Then, developed multicriteria approach identify core interaction network driving community dynamics under environmental disturbances, which termed Conserved Variated Interaction Group (CVIgroup). CVIgroup showed significant advantages on pinpointing sparse set associated with as validated both our own and publicly available datasets. Leveraging Oxford Nanopore Technology, found this group facilitates ecosystem's adaptation disruptions enhancing mobility mobile genetic elements, including reinforcement twin-arginine translocation pathway in response increased virulence factors. Furthermore, serves an effective indicator ecosystem health. timescale for microbiota's extends beyond 10 months. Members CVIgroup, such Bacteroides thetaiotaomicron Faecalibacterium, exhibit varying degrees genomic structural variants, contribute guiding toward new stable state rather than returning its original configuration. Collectively, offers snapshot adaptive disturbances. disruption subsequent infants after COVID-19 underscores necessity re-evaluating reference standards context post-pandemic era.

Language: Английский

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High-throughput untargeted metabolomic profiling of urinary biomarkers in acute myocarditis patients: a cross-sectional study

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 18, 2025

Acute myocarditis, characterized by inflammatory myocardial injury, significantly risks heart failure and sudden death. Despite its severity, specific biomarkers are lacking. This study applied metabolomic analysis to urine samples from 21 acute myocarditis patients controls using UPLC-MS/MS, revealing 728 increased 820 decreased metabolites in patients. The affected pathways were predominantly related the amino acid metabolism, lipid carbohydrate nucleotide others. We have validated 19 with an area under receiver operating characteristic curve (AUC-ROC) greater than 0.7 a high level of identification confidence. Potential upregulated included phytosphingosine, N-acetylneuraminic acid, indolelactic L-glutamic 4-pyridoxic N1-methyl-2-pyridone-5-carboxamide, palmitic hydroxyphenyllactic riboflavin, nicotinic choline, N-formylkynurenine, guanine, hypoxanthine. Conversely, sebacic 4-vinylphenol sulfate, capryloylglycine, 4-ethylphenylsulfate, azelaic found be decreased. Collectively, profiling has uncovered distinct metabolic signatures myocarditis. metabolism appears play pivotal role pathogenesis offering potential avenues for diagnostic therapeutic development.

Language: Английский

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HKDC1 promotes ovarian cancer progression through boosting lipid metabolism and immune escape by stabilizing G6PC/G6PC2

Communications Biology, Journal Year: 2025, Volume and Issue: 8(1)

Published: April 15, 2025

Ovarian cancer (OC) is a significant health challenge, yet the mechanisms driving its progression remain unclear. This study explored role of hexokinase domain-containing protein 1 (HKDC1) in OC, focusing on tumor growth, lipid metabolism, and immune evasion. Human OC cell lines (SKOV3 HEY) murine line (ID8) were used to knock down overexpress HKDC1. An ID8-based epithelial mouse model was established validate vitro findings. Our results demonstrated that HKDC1 upregulated promoted proliferation, migration, invasion. enhanced accumulation by elevating levels free fatty acids (FFA), triglycerides, phospholipids, cholesterol, neutral lipid, while upregulating key enzymes (ACC1, FASN, SCD1, HMGCS1, HMGCR). It escape through PD-L1 upregulation, inhibiting T proliferation reducing IFN-γ, granzyme B, perforin increasing PD-1 levels. knockdown reversed these effects, which restored adding FFA. Mechanistically, interacted with stabilized glucose-6-phosphatase catalytic subunits (G6PC/G6PC2), supporting tumor-promoting functions. These findings confirmed an model, highlighting as driver biosynthesis suppression, offering potential therapeutic targets.

Language: Английский

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Multi-omics analysis constructs a novel neuroendocrine prostate cancer classifier and classification system

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 22, 2025

Neuroendocrine prostate cancer (NEPC), a subtype of (PCa) with poor prognosis and high heterogeneity, currently lacks accurate markers. This study aims to identify robust NEPC classifier provide new perspectives for resolving intra- tumoral heterogeneity. Multi-omics analysis included 19 bulk transcriptomics, 14 single-cell 1 spatial 16 published NE signatures 10 cellular experiments combined multiple machine learning algorithms construct novel classification. A comprehensive atlas was created from 70 samples, comprising 196,309 cells, among which 9% were identified as cells. Within this framework in combination total 100 high-quality NE-specific feature genes differentiated into NEPup sig NEPdown sig. The random forest (RF) algorithm proved be the most effective NEPC, leading establishment NEP100 model, demonstrated validation across various datasets. In clinical settings, use model can greatly improve diagnostic prognostic prediction NEPC. Hierarchical clustering based on revealed four distinct subtypes, designated VR_O, Prol_N, Prol_P, EMT_Y, each presented unique biological characteristics. allows us select different targeted therapeutic strategies subtypes phenotypic pathways. Notably, expression correlated positively neuroendocrine differentiation disease progression, while VR-NE phenotype dominated by VR_O cells indicated propensity treatment resistance. Furthermore, AMIGO2, component signature, associated chemotherapy resistance prognosis, indicating that it is pivotal target future strategies. used multi-omics classification system. provides clinically actionable diagnosis subtyping.

Language: Английский

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Maternal transcription factor OTX2 directly induces SETD1A and promotes embryonic genome activation in human pre-implantation embryos

Science China Life Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Language: Английский

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