Computing hematopoiesis plasticity in response to genetic mutations and environmental stimulations

Life Science Alliance, Journal Year: 2024, Volume and Issue: 8(2), P. e202402971 - e202402971

Published: Nov. 13, 2024

Cell plasticity (CP), describing a dynamic cell state, plays crucial role in maintaining homeostasis during organ morphogenesis, regeneration, and trauma-to-repair biological process. Single-cell-omics datasets provide an unprecedented resource to empower CP analysis. Hematopoiesis offers fertile opportunities develop quantitative methods for understanding CP. In this study, we generated high-quality lineage-negative single-cell RNA-sequencing under various conditions introduced working pipeline named scPlasticity interrogate naïve disturbed of hematopoietic stem progenitor cells with mutational or environmental challenges. Using embedding UMAP FA, continuum development is visually observed wild type where the confirms low proportion hybrid ( P hc , bias range: 0.4∼0.6) on transition trajectory. Upon Tet2 mutation, driver leukemia, treatment DSS, inducer colitis, increased was enhanced. We prioritized several transcription factors signaling pathways, which are responsible alterations. silico perturbation suggests knocking out EGR regulons pathways IL-1R1 β-adrenoreceptor partially reverses promoted by mutation inflammation.

Language: Английский

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Squidiff: Predicting cellular development and responses to perturbations using a diffusion model

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 18, 2024

Abstract Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and responses to environmental stimuli. However, mapping transcriptomic changes across diverse cell types in response various stimuli elucidating underlying disease mechanisms remains challenging. Studies involving physical stimuli, such as radiotherapy, or chemical like drug testing, demand labor-intensive experimentation, often hindering the rapid advancement mechanistic insight discovery. To address this, we present Squidiff, a diffusion model-based generative framework designed predict wide range changes. We demonstrate Squidiff’s robustness scenarios, including differentiation, gene perturbation, prediction. Through continuous denoising semantic feature integration, Squidiff effectively learns transient states predicts high-resolution landscapes over time conditions. Furthermore, applied model development blood vessel organoids neutron irradiation growth factors. Our results that enables silico screening molecular landscapes, facilitating hypothesis generation providing valuable insights for precision medicine.

Language: Английский

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Should Artificial Intelligence Play a Durable Role in Biomedical Research and Practice?

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(24), P. 13371 - 13371

Published: Dec. 13, 2024

During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted ask whether AI thinking should be durably involved in biomedical This problem addressed by examining three complementary questions (i) What are major barriers currently met investigators? suggested that during 2 decades there a shift towards growing need elucidate complex systems, and this not sufficiently fulfilled previously successful methods such as theoretical modeling or computer simulation (ii) potential meet aforementioned need? it recent well-suited perform classification prediction tasks on multivariate possibly help data interpretation, provided their efficiency properly validated. (iii) Recent representative results obtained with machine learning suggest may comparable displayed operators. concluded play an important role practice. Also, already other physics, combining conventional might generate further progress new applications, involving heuristic interpretation.

Language: Английский

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Development of a high-throughput 3D culture microfluidic platform for multi-parameter phenotypic and omics profiling of patient-derived organoids

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 29, 2024

Abstract Patient-derived organoids (PDOs) are poised to become central tools in clinical practice, preemptively identify patient optimal treatments, and drug discovery, overcoming the limitations of cancer cell lines. However, implementation PDOs both these settings has been hampered by several bottlenecks including sample requirements, assay time handling context high-throughput-based assays. We report here development a microfluidic-based device ( M icrofluidic P latform for O rganoids culture, MPO) that miniaturises greatly simplifies PDO cultures 384-plate format. Both retrospective prospective studies demonstrate its predictive value swift straightforward setting. Obtaining comprehensive functional molecular information on response drugs is becoming requirement discovery. MPO allows subcellular phenotypic imaging screenings, target engagement assessment efficacy therapies, alongside ability comprehensively concomitantly define genomic, transcriptomic, proteomic, lipidomic metabolomic landscape. In all, we potential our platform impact practice generating relevant sensitivity within frame could inform treatment decisions exploration mechanisms underlying compound resistance discovery efforts.

Language: Английский

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