bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–03–02
forty-five papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Visualization of Subcellular mTOR Complex 1 Activity with a FRET-Based Sensor (TORCAR).
  2. Monitoring Cellular Energy Balance in Single Cells Using Fluorescent Biosensors for AMPK.
  3. Combinatorial screen of targeted agents with the PI3K inhibitors inavolisib, alpelisib, duvelisib, and copanlisib in multi-cell type tumor spheroids.
  4. A Genetically Encoded Fluorescent Biosensor for Intracellular Measurement of Malonyl-CoA.
  5. p85β acts as a transcription cofactor and cooperates with BCLAF1 in the nucleus.
  6. Nellie: automated organelle segmentation, tracking and hierarchical feature extraction in 2D/3D live-cell microscopy.
  7. A benchmark comparison of CRISPRn guide-RNA design algorithms and generation of small single and dual-targeting libraries to boost screening efficiency.
  8. Dual Translational Control in Cardiomyocytes by Heterogeneous mTORC1 and Hypertrophic ERK Activation.
  9. Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens.
  10. Mass-spectrometry-based proteomics: from single cells to clinical applications.
  11. Dynamic and Biphasic Regulation of Cell Migration by Ras.
  12. goloco: a web application to create genome scale information from surprisingly small experiments.
  13. SpaceBar enables clone tracing in spatial transcriptomic data.
  14. Cancer hotspot mutations rewire ERK2 specificity by selective exclusion of docking interactions.
  15. Trajectory Inference for Single Cell Omics.
  16. pyOpenMS-viz: Streamlining Mass Spectrometry Data Visualization with pandas.
  17. Decoding heterogeneous single-cell perturbation responses.
  18. Attenuated growth factor signaling during cell death initiation sensitizes membranes towards peroxidation.
  19. A Quantitative Approach to Mapping Mitochondrial Specialization and Plasticity.
  20. Detecting somatic mutations in single-cell data with SComatic.
  21. Temporal dose inversion properties of adaptive biomolecular circuits.
  22. AXL promotes lymphangiogenesis by amplifying VEGF-C-mediated AKT pathway.
  23. Class I PI3Ks activate stretch-induced autophagy in trabecular meshwork cells.
  24. Protein Engineering for Spatiotemporally Resolved Cellular Monitoring.
  25. Organoids from pluripotent stem cells and human tissues: When two cultures meet each other.
  26. Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour.
  27. GitHub is an effective platform for collaborative and reproducible laboratory research.
  28. Tumorigenesis Driven by BRAFV600E Requires Secondary Mutations that Overcome it's Feedback Inhibition of RAC1 and Migration.
  29. Potent and selective SETDB1 covalent negative allosteric modulator reduces methyltransferase activity in cells.
  30. Use of metabolic imaging to monitor heterogeneity of tumour response following therapeutic mTORC1/2 pathway inhibition.
  31. Protein degradation and growth dependent dilution substantially shape mammalian proteomes.
  32. Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions.
  33. ETVs dictate hPSC differentiation by tuning biophysical properties.
  34. PTEN mutations impair CSF dynamics and cortical networks by dysregulating periventricular neural progenitors.
  35. Interpretable single-cell factor decomposition using sciRED.
  36. Unveiling the cell-type-specific landscape of cellular senescence through single-cell transcriptomics using SenePy.
  37. Cancer-independent somatic mutation of the wild-type NF1 allele in normal tissues in neurofibromatosis type 1.
  38. An endothelial SOX18-mevalonate pathway axis enables repurposing of statins for infantile hemangioma.
  39. Reappraising the relationship between hyperinsulinemia and insulin resistance in PCOS.
  40. Anti-resonance in developmental signaling regulates cell fate decisions.
  41. Examining patient-specific responses to PARP inhibitors in a novel, human induced pluripotent stem cell-based model of breast cancer.
  42. OCT4 translationally promotes AKT signaling as an RNA-binding protein in stressed pluripotent stem cells.
  43. Donor Variability Alters the Characteristics of Human Brain Microvascular Endothelial Cells.
  44. Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2.
  45. Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation.
  1. Methods Mol Biol. 2025 ;2882 139-162
    Visualization of Subcellular mTOR Complex 1 Activity with a FRET-Based Sensor (TORCAR).
    Ayse Z Sahan, Sohum Metha, Jin Zhang.
      The mechanistic target of rapamycin complex 1 (mTORC1) is a nutrient-sensing complex that integrates inputs from several pathways to promote cell growth and proliferation. mTORC1 localizes to many cellular compartments, including the nucleus, lysosomes, and plasma membrane. However, little is known about the spatial regulation of mTORC1 and the specific functions of mTORC1 at these locations. To address these questions, we previously developed a Förster resonance energy transfer (FRET)-based mTORC1 activity reporter (TORCAR) to visualize the dynamic changes in mTORC1 activity within live cells. Here, we describe a detailed protocol for using subcellularly targeted TORCAR constructs to investigate subcellular mTORC1 activities via live-cell fluorescence microscopy.
    Keywords:  Biosensor; Compartmentalized signaling; Fluorescence; Location-specific
    DOI:  https://doi.org/10.1007/978-1-0716-4284-9_7
  2. Methods Mol Biol. 2025 ;2882 47-79
    Monitoring Cellular Energy Balance in Single Cells Using Fluorescent Biosensors for AMPK.
    Nicholaus DeCuzzi, Nont Kosaisawe, Michael Pargett, Markhus Cabel, John G Albeck.
      5'-Adenosine monophosphate-activated protein kinase (AMPK) senses cellular metabolic status and reflects the balance between ATP production and ATP usage. This balance varies from cell to cell and changes over time, creating a need for methods that can capture cellular heterogeneity and temporal dynamics. Fluorescent biosensors for AMPK activity offer a unique approach to measure metabolic status nondestructively in single cells in real time. In this chapter, we provide a brief rationale for using live-cell biosensors to measure AMPK activity, survey the current AMPK biosensors, and discuss considerations for using this approach. We provide methodology for introducing AMPK biosensors into a cell line of choice, setting up experiments for live-cell fluorescent microscopy of AMPK activity, and calibrating the biosensors using immunoblot data.
    Keywords:  AMPKAR; Biosensors; Fluorescent protein reporters; Forster resonance energy transfer (FRET); Live-cell microscopy; Metabolic signaling; Single cell
    DOI:  https://doi.org/10.1007/978-1-0716-4284-9_3
  3. SLAS Discov. 2025 Feb 23. pii: S2472-5552(25)00015-2. [Epub ahead of print] 100222
    Combinatorial screen of targeted agents with the PI3K inhibitors inavolisib, alpelisib, duvelisib, and copanlisib in multi-cell type tumor spheroids.
    Thomas S Dexheimer, Zahra Davoudi, Nathan P Coussens, Thomas Silvers, Joel Morris, Naoko Takebe, Rabih Said, Jeffrey A Moscow, James H Doroshow, Beverly A Teicher.
      Dysregulation of the phosphatidylinositol 3-kinase (PI3K) pathway is a key contributor to cancer, making PI3K inhibitors a promising approach for targeted therapy. The selectivity of available inhibitors varies across different PI3K isoforms. Alpelisib and inavolisib are selective for the α-isoform, while duvelisib targets the δ- and γ-isoforms, and copanlisib is a pan-PI3K inhibitor, active against all isoforms. This study investigated the activity of these four PI3K inhibitors in combination with other targeted agents using multi-cell type tumor spheroids composed of 60% malignant cells, 25% endothelial cells, and 15% mesenchymal stem cells. Twenty-nine tumor spheroid models were evaluated, including twenty-six patient-derived cancer cell lines from the NCI Patient-Derived Models Repository and three established cell lines from the NCI-60 human tumor cell line panel. Additive and/or synergistic effects were observed with alpelisib or inavolisib or copanlisib in combination with a RAS/MEK/ERK pathway inhibitor, either selumetinib (MEK), ravoxertinib (ERK 1/2), or tovorafenib (DAY101, RAF). Combinations of each of these three PI3K inhibitors with the KRAS mutation specific inhibitors MTRX1133 (KRAS G12D) or sotorasib (KRAS G12C) had selective activity in cell lines harboring the corresponding target. Lastly, combination effects were observed from vertical inhibition of the PI3K/AKT/mTOR pathway with a PI3K inhibitor in combination with either the mTORC1/2 inhibitor sapanisertib or an AKT inhibitor, ipatasertib or afuresertib.
    Keywords:  Inavolisib; PI3K; apelisib; copanlisib; drug combination; duvelisib; spheroids
    DOI:  https://doi.org/10.1016/j.slasd.2025.100222
  4. ACS Bio Med Chem Au. 2025 Feb 19. 5(1): 184-193
    A Genetically Encoded Fluorescent Biosensor for Intracellular Measurement of Malonyl-CoA.
    Brodie L Ranzau, Tiffany D Robinson, Jack M Scully, Edmund D Kapelczak, Teagan S Dean, Tara TeSlaa, Danielle L Schmitt.
      Malonyl-CoA is the essential building block of fatty acids and regulates cell function through protein malonylation and allosteric regulation of signaling networks. Accordingly, the production and use of malonyl-CoA is finely tuned by the cellular energy status. Most studies of malonyl-CoA dynamics rely on bulk approaches that take only a snapshot of the average metabolic state of a population of cells, missing out on heterogeneous differences in malonyl-CoA and fatty acid biosynthesis that could be occurring among a cell population. To overcome this limitation, we have developed a genetically encoded fluorescent protein-based biosensor for malonyl-CoA that can be used to capture malonyl-CoA dynamics in single cells. This biosensor, termed Malibu (malonyl-CoA intracellular biosensor to understand dynamics), exhibits an excitation-ratiometric change in response to malonyl-CoA binding. We first used Malibu to monitor malonyl-CoA dynamics during inhibition of fatty acid biosynthesis using cerulenin in Escherichia coli, observing an increase in Malibu response in a time- and dose-dependent manner. In HeLa cells, we used Malibu to monitor the impact of fatty acid biosynthesis inhibition on malonyl-CoA dynamics in single cells, finding that two inhibitors of fatty acid biosynthesis, cerulenin and orlistat, which inhibit different steps of fatty acid biosynthesis, increase malonyl-CoA levels. Altogether, we have developed a new genetically encoded biosensor for malonyl-CoA, which can be used to study malonyl-CoA dynamics in single cells, providing an unparalleled view into fatty acid biosynthesis.
    DOI:  https://doi.org/10.1021/acsbiomedchemau.4c00103
  5. Nat Commun. 2025 Feb 27. 16(1): 2042
    p85β acts as a transcription cofactor and cooperates with BCLAF1 in the nucleus.
    Panpan Wang, Victor Cy Mak, Ling Rao, Qiuqiu Wu, Yuan Zhou, Rakesh Sharma, S Chul Kwon, Lydia Wt Cheung.
      p85β is a regulatory subunit of the phosphoinositide 3-kinase (PI3K). Emerging evidence suggests that p85β goes beyond its role in the PI3K and is functional in the nucleus. In this study, we discover that nuclear p85β is enriched at gene loci and regulates gene transcription and that this regulatory role contributes to the oncogenic potential of nuclear p85β. A multi-omics approach reveals the physical interaction and functional cooperativity between nuclear p85β and a transcription factor BCLAF1. We observe genome-wide co-occupancy of p85β and BCLAF1 at gene targets associated with transcriptional responses. Intriguingly, the targetome includes BCLAF1 of which transcription is activated by p85β and BCLAF1, indicating a positive autoregulation. While BCLAF1 recruits p85β to BCLAF1 loci, p85β facilitates the assembly of BCLAF1, the scaffold protein TRIM28 and the zinc finger transcription factor ZNF263, which together act in concert to activate BCLAF1 transcription. Collectively, this study provides functional evidence and mechanistic basis to support a role of nuclear p85β in modulating gene transcription.
    DOI:  https://doi.org/10.1038/s41467-025-56532-3
  6. Nat Methods. 2025 Feb 27.
    Nellie: automated organelle segmentation, tracking and hierarchical feature extraction in 2D/3D live-cell microscopy.
    Austin E Y T Lefebvre, Gabriel Sturm, Ting-Yu Lin, Emily Stoops, Magdalena Preciado López, Benjamin Kaufmann-Malaga, Kayley Hake.
      Cellular organelles undergo constant morphological changes and dynamic interactions that are fundamental to cell homeostasis, stress responses and disease progression. Despite their importance, quantifying organelle morphology and motility remains challenging due to their complex architectures, rapid movements and the technical limitations of existing analysis tools. Here we introduce Nellie, an automated and unbiased pipeline for segmentation, tracking and feature extraction of diverse intracellular structures. Nellie adapts to image metadata and employs hierarchical segmentation to resolve sub-organellar regions, while its radius-adaptive pattern matching enables precise motion tracking. Through a user-friendly Napari-based interface, Nellie enables comprehensive organelle analysis without coding expertise. We demonstrate Nellie's versatility by unmixing multiple organelles from single-channel data, quantifying mitochondrial responses to ionomycin via graph autoencoders and characterizing endoplasmic reticulum networks across cell types and time points. This tool addresses a critical need in cell biology by providing accessible, automated analysis of organelle dynamics.
    DOI:  https://doi.org/10.1038/s41592-025-02612-7
  7. BMC Genomics. 2025 Feb 26. 26(1): 198
    A benchmark comparison of CRISPRn guide-RNA design algorithms and generation of small single and dual-targeting libraries to boost screening efficiency.
    Sebastian Lukasiak, Alex Kalinka, Nikhil Gupta, Angelos Papadopoulos, Khalid Saeed, Ultan McDermott, Gregory James Hannon, Douglas Ross-Thriepland, David Walter.
      Genome-wide CRISPR sgRNA libraries have emerged as transformative tools to systematically probe gene function. While these libraries have been iterated over time to be more efficient, their large size limits their use in some applications. Here, we benchmarked publicly available genome-wide single-targeting sgRNA libraries and evaluated dual targeting as a strategy for pooled CRISPR loss-of-function screens. We leveraged this data to design two minimal genome-wide human CRISPR-Cas9 libraries that are 50% smaller than other libraries and that preserve specificity and sensitivity, thus enabling broader deployment at scale.
    Keywords:  CRISPR-Cas9; Genome-wide; Pooled CRISPR screening; SgRNA selection algorithm
    DOI:  https://doi.org/10.1186/s12864-025-11386-3
  8. bioRxiv. 2025 Feb 11. pii: 2025.02.10.635974. [Epub ahead of print]
    Dual Translational Control in Cardiomyocytes by Heterogeneous mTORC1 and Hypertrophic ERK Activation.
    Keita Uchida, Emily A Scarborough, Benjamin L Prosser.
       Background: Cardiac hypertrophy allows post-mitotic cardiomyocytes to meet increased hemodynamic demands but can predispose the heart to adverse clinical outcomes. Despite its central role in cardiac adaptation, the translational control mechanisms that drive cardiac hypertrophy are poorly understood. In this study, we elucidate the relative contributions of the various translational control mechanisms operant during homeostasis and hypertrophic growth.
    Methods: A combination of immunofluorescence and single myocyte protein synthesis assays were used to dissect the single-cardiomyocyte mechanisms of translational control under basal and hypertrophic conditions in isolated adult rat cardiomyocytes. Translational control mechanism were examined in a mouse model of acute hypertrophic phenylephrine (PE) stimulation prior to overt cardiac growth.
    Results: We observed strikingly heterogeneous activity of mTORC1, the master regulator of translation, across cardiomyocytes both in situ and ex vivo . Heterogeneous mTORC1 activity drove heterogeneous protein synthesis, with translation primarily controlled via canonical mTORC1-dependent 4EBP1 phosphorylation at Thr36/Thr45/Thr69 under baseline conditions. Hypertrophic PE stimulation recruited more cardiomyocytes into a high mTORC1 activity state. PE induced a switch in 4EBP1 phosphorylation by increasing mTORC1-dependent phosphorylation at Thr36/Thr45, but not Thr69. Further, PE induced a novel mTORC1-independent, but MEK-ERK-dependent, pathway driving 4EBP1 phosphorylation at Ser64 in both isolated cardiomyocytes and in vivo . Ribosome biogenesis was also observed within hours upon hypertrophic stimulation, while the mTORC1-S6K-eEF2K-eEF2 pathway was not found to be a major driver of protein translation.
    Conclusions: Protein synthesis is heterogeneous across cardiomyocytes driven by heterogeneous mTORC1 activity. MEK-ERK signaling directly controls 4EBP1 phosphorylation to augment translation during cardiac hypertrophy and challenges the canonical model of translation initiation.
    Key points: mTORC1 activity is low and heterogeneous across cardiomyocytes at baseline.Heterogeneous mTORC1 activity drives variable 4EBP1 phosphorylation at Thr36/Thr45/Thr69, resulting in heterogeneous protein translation.Phenylephrine stimulation recruits more cardiomyocytes into a high mTORC1 activity state to augment protein synthesis through 4EBP1 phosphorylation at Thr36/Thr45, but not Thr69.Phenylephrine stimulation boosts protein translation through mTORC1-independent but ERK-dependent phosphorylation of 4EBP1 at Ser64.mTORC1-S6K-eEF2K-eEF2 pathway is not a major driver of global protein translation.Ribosome biogenesis is observed within hours after hypertrophic stimulation.The data demonstrates a dual input model of mTORC1 and ERK dependent phosphorylation of 4EBP1 to regulate protein translation in cardiomyocytes.
    DOI:  https://doi.org/10.1101/2025.02.10.635974
  9. Nat Cell Biol. 2025 Feb 26.
    Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens.
    Longda Jiang, Carol Dalgarno, Efthymia Papalexi, Isabella Mascio, Hans-Hermann Wessels, Huiyoung Yun, Nika Iremadze, Gila Lithwick-Yanai, Doron Lipson, Rahul Satija.
      Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but predicting causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single-cell sequencing (Perturb-seq) to systematically identify the targets of signalling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signalling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signalling pathway activation for in vivo and in situ samples. Our work enhances our understanding of signalling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.
    DOI:  https://doi.org/10.1038/s41556-025-01622-z
  10. Nature. 2025 Feb;638(8052): 901-911
    Mass-spectrometry-based proteomics: from single cells to clinical applications.
    Tiannan Guo, Judith A Steen, Matthias Mann.
      Mass-spectrometry (MS)-based proteomics has evolved into a powerful tool for comprehensively analysing biological systems. Recent technological advances have markedly increased sensitivity, enabling single-cell proteomics and spatial profiling of tissues. Simultaneously, improvements in throughput and robustness are facilitating clinical applications. In this Review, we present the latest developments in proteomics technology, including novel sample-preparation methods, advanced instrumentation and innovative data-acquisition strategies. We explore how these advances drive progress in key areas such as protein-protein interactions, post-translational modifications and structural proteomics. Integrating artificial intelligence into the proteomics workflow accelerates data analysis and biological interpretation. We discuss the application of proteomics to single-cell analysis and spatial profiling, which can provide unprecedented insights into cellular heterogeneity and tissue architecture. Finally, we examine the transition of proteomics from basic research to clinical practice, including biomarker discovery in body fluids and the promise and challenges of implementing proteomics-based diagnostics. This Review provides a broad and high-level overview of the current state of proteomics and its potential to revolutionize our understanding of biology and transform medical practice.
    DOI:  https://doi.org/10.1038/s41586-025-08584-0
  11. bioRxiv. 2025 Feb 16. pii: 2025.02.13.638204. [Epub ahead of print]
    Dynamic and Biphasic Regulation of Cell Migration by Ras.
    Yiyan Lin, Eleana Parajón, Qinling Yuan, Siyu Ye, Guanghui Qin, Yu Deng, Jane Borleis, Ariel Koyfman, Pablo A Iglesias, Konstantinos Konstantopoulos, Douglas N Robinson, Peter N Devreotes.
      Ras has traditionally been regarded as a positive regulator and therapeutic target due to its role in cell proliferation, but recent findings indicate a more nuanced role in cell migration, where suppressed Ras activity can unexpectedly promote migration. To clarify this complexity, we systematically modulate Ras activity using various RasGEF and RasGAP proteins and assess their effects on migration dynamics. Leveraging optogenetics, we assess the immediate, non-transcriptional effects of Ras signaling on migration. Local RasGEF recruitment to the plasma membrane induces protrusions and new fronts to effectively guide migration, even in the absence of GPCR/G-protein signaling whereas global recruitment causes immediate cell spreading halting cell migration. Local RasGAP recruitment suppresses protrusions, generates new backs, and repels cells whereas global relocation either eliminates all protrusions to inhibit migration or preserves a single protrusion to maintain polarity. Consistent local and global increases or decreases in signal transduction and cytoskeletal activities accompany these morphological changes. Additionally, we performed cortical tension measurements and found that RasGEFs generally increase cortical tension while RasGAPs decrease it. Our results reveal a biphasic relationship between Ras activity and cellular dynamics, reinforcing our previous findings that optimal Ras activity and cortical tension are critical for efficient migration.
    Significance: This study challenges the traditional view of Ras as solely a positive regulator of cell functions by controlling of gene expression. Using optogenetics to rapidly modulate Ras activity in Dictyostelium , we demonstrate a biphasic relationship between Ras activity and migration: both excessive and insufficient Ras activity impair cell movement. Importantly, these effects occur rapidly, independent of transcriptional changes, revealing the mechanism by which Ras controls cell migration. The findings suggest that optimal Ras activity and cortical tension are crucial for efficient migration, and that targeting Ras in cancer therapy should consider the cell's initial state, aiming to push Ras activity outside the optimal range for migration. This nuanced understanding of the role of Ras in migration has significant implications for developing more effective cancer treatments, as simply inhibiting Ras might inadvertently promote metastasis in certain contexts.
    DOI:  https://doi.org/10.1101/2025.02.13.638204
  12. BMC Bioinformatics. 2025 Feb 25. 26(1): 61
    goloco: a web application to create genome scale information from surprisingly small experiments.
    Sajid M Hossain, Yiyun Rao, Jahid O Hossain, Justin R Pritchard, Boyang Zhao.
       BACKGROUND: Functional genomics aims to decipher gene function by observing cellular changes when specific genes are disrupted using CRISPR technology. However, these experiments are limited by scalability, as comprehensive CRISPR screens require extensive resources, involving millions of cells and thousands of sgRNAs, making large-scale studies challenging. We propose a novel approach with "CRISPR lossy compression" to reduce the complexity of CRISPR screens by focusing on key genetic nodes that can infer genome-wide phenotypes. These condensed sets, comprising 100 to 1,000 genes, enable previously impractical genome-wide screens tractable.
    RESULTS: To make this approach accessible to the wider scientific community, we developed goloco, an interactive web application that allows users to explore genome-scale loss-of-function phenotypes from as few as 100 pooled measurements. The tool is complemented by a wide array of analyses, including volcano plot visualizations, regression and network analyses.
    CONCLUSIONS: This tool goloco empowers researchers to conduct genome-scale functional studies with minimal experimental overhead, broadening the accessibility of large-scale functional genomics research.
    Keywords:  CRISPR screens; Functional genomics; Genomic inference; Machine learning; Web application
    DOI:  https://doi.org/10.1186/s12859-025-06070-y
  13. bioRxiv. 2025 Feb 14. pii: 2025.02.10.637514. [Epub ahead of print]
    SpaceBar enables clone tracing in spatial transcriptomic data.
    Grant Kinsler, Caitlin Fagan, Haiyin Li, Jessica Kaster, Maggie Dunne, Robert J Vander Velde, Ryan H Boe, Sydney Shaffer, Meenhard Herlyn, Arjun Raj, Yael Heyman.
      We report a cellular barcoding strategy, SpaceBar, that enables simultaneous clone tracing and spatial transcriptomics profiling. Our approach uses a library of 96 synthetic barcode sequences that can be robustly detected by imaging based spatial transcriptomics (seqFISH), delivered such that each cell is labeled with a combination of barcodes. We used these barcodes to label melanoma cells in a tumor xenograft model and profiled both clone identity and spatial gene expression in situ . We developed a gene scoring metric that quantifies how strongly gene expression is driven by intrinsic cellular cues or extrinsic environmental signals. Our framework distinguishes between clonal dynamics and environmentally-driven transcriptional regulation in complex tissue contexts.
    DOI:  https://doi.org/10.1101/2025.02.10.637514
  14. J Biol Chem. 2025 Feb 25. pii: S0021-9258(25)00197-8. [Epub ahead of print] 108348
    Cancer hotspot mutations rewire ERK2 specificity by selective exclusion of docking interactions.
    Jaylissa Torres Robles, Amy L Stiegler, Titus J Boggon, Benjamin E Turk.
      The protein kinase ERK2 is recurrently mutated in human squamous cell carcinomas and other tumors. ERK2 mutations cluster in an essential docking recruitment site that interacts with short linear motifs found within intrinsically disordered regions of ERK substrates and regulators. Cancer-associated mutations do not disrupt ERK2 docking interactions altogether but selectively inhibit some interactions while sparing others. However, the full scope of disrupted or maintained interactions remains unknown, limiting our understanding of how these mutations contribute to cancer. We recently defined the docking interactome of wild-type ERK2 by screening a yeast two-hybrid library of proteomic short linear motifs. Here, we apply this approach to the two most recurrent cancer-associated mutants. We find that most sequences binding to WT ERK2 also interact with both mutant forms. Analysis of differentially interacting sequences revealed that ERK2 mutants selectively lose the ability to bind sequences conforming to a specific motif. We solved the co-crystal structure of ERK2 in complex with a peptide fragment of ISG20, a screening hit that binds exclusively to the WT kinase. This structure demonstrated the mechanism by which cancer hotspot mutations at Glu81, Arg135, Asp321, and Glu322 selectively impact peptide binding. Finally, we found that cancer-associated ERK2 mutations had decreased activity in phosphorylating GEF-H1/ARHGEF2, a known ERK substrate harboring a WT-selective docking motif. Collectively, our studies provide a structural rationale for how a broad set of interactions are disrupted by ERK2 hotspot mutations, suggesting mechanisms for pathway rewiring in cancers harboring these mutations.
    Keywords:  Protein kinases; cell signaling; mitogen-activated protein kinases; short linear motifs; substrate specificity
    DOI:  https://doi.org/10.1016/j.jbc.2025.108348
  15. ArXiv. 2025 Feb 13. pii: arXiv:2502.09354v1. [Epub ahead of print]
    Trajectory Inference for Single Cell Omics.
    Alexandre Hutton, Jesse G Meyer.
      Trajectory inference is used to order single-cell omics data along a path that reflects a continuous transition between cells. This approach is useful for studying processes like cell differentiation, where a stem cell matures into a specialized cell type, or investigating state changes in pathological conditions. In the current article, we provide a general introduction to trajectory inference, explaining the concepts and assumptions underlying the different methods. We then briefly discuss the strengths and weaknesses of different trajectory inference methods. We also describe best practices for using trajectory inference, such as how to validate the results and how to interpret them in the context of biological knowledge. Finally, the article will discuss some of the applications of trajectory inference in single-cell omics research. These applications include studying cell differentiation, development, and disease. We provide examples of how trajectory inference has been used to gain new insights into these processes.
  16. J Proteome Res. 2025 Feb 28.
    pyOpenMS-viz: Streamlining Mass Spectrometry Data Visualization with pandas.
    Justin Cyril Sing, Joshua Charkow, Axel Walter, Mingxuan Gao, Tom David Müller, Wout Bittremieux, Timo Sachsenberg, Hannes Luc Röst.
      Mass spectrometry data visualization is essential for a wide range of applications, such as validation of workflows and results, benchmarking new algorithms, and creating comprehensive quality control reports. Python offers a popular and powerful framework for analyzing and visualizing multidimensional data; however, generating commonly used mass spectrometry plots in Python can be cumbersome. Here we present pyOpenMS-viz, a versatile, unified framework for generating mass spectrometry plots. pyOpenMS-viz directly extends pandas DataFrame plotting for generating figures in a single line of code. This implementation enables easy integration across various Python-based mass spectrometry tools that already use pandas DataFrames to store MS data. pyOpenMS-viz is open-source under a BSD 3-Clause license and freely available at https://github.com/OpenMS/pyopenms_viz.
    Keywords:  mass-spectrometry; python; quality control; validation; visualization
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00873
  17. Nat Cell Biol. 2025 Feb 26.
    Decoding heterogeneous single-cell perturbation responses.
    Bicna Song, Dingyu Liu, Weiwei Dai, Natalie F McMyn, Qingyang Wang, Dapeng Yang, Adam Krejci, Anatoly Vasilyev, Nicole Untermoser, Anke Loregger, Dongyuan Song, Breanna Williams, Bess Rosen, Xiaolong Cheng, Lumen Chao, Hanuman T Kale, Hao Zhang, Yarui Diao, Tilmann Bürckstümmer, Janet D Siliciano, Jingyi Jessica Li, Robert F Siliciano, Danwei Huangfu, Wei Li.
      Understanding how cells respond differently to perturbation is crucial in cell biology, but existing methods often fail to accurately quantify and interpret heterogeneous single-cell responses. Here we introduce the perturbation-response score (PS), a method to quantify diverse perturbation responses at a single-cell level. Applied to single-cell perturbation datasets such as Perturb-seq, PS outperforms existing methods in quantifying partial gene perturbations. PS further enables single-cell dosage analysis without needing to titrate perturbations, and identifies 'buffered' and 'sensitive' response patterns of essential genes, depending on whether their moderate perturbations lead to strong downstream effects. PS reveals differential cellular responses on perturbing key genes in contexts such as T cell stimulation, latent HIV-1 expression and pancreatic differentiation. Notably, we identified a previously unknown role for the coiled-coil domain containing 6 (CCDC6) in regulating liver and pancreatic cell fate decisions. PS provides a powerful method for dose-to-function analysis, offering deeper insights from single-cell perturbation data.
    DOI:  https://doi.org/10.1038/s41556-025-01626-9
  18. Nat Commun. 2025 Feb 25. 16(1): 1774
    Attenuated growth factor signaling during cell death initiation sensitizes membranes towards peroxidation.
    André Gollowitzer, Helmut Pein, Zhigang Rao, Lorenz Waltl, Leonhard Bereuter, Konstantin Loeser, Tobias Meyer, Vajiheh Jafari, Finja Witt, René Winkler, Fengting Su, Silke Große, Maria Thürmer, Julia Grander, Madlen Hotze, Sönke Harder, Lilia Espada, Alexander Magnutzki, Ronald Gstir, Christina Weinigel, Silke Rummler, Günther Bonn, Johanna Pachmayr, Maria Ermolaeva, Takeshi Harayama, Hartmut Schlüter, Christian Kosan, Regine Heller, Kathrin Thedieck, Michael Schmitt, Takao Shimizu, Jürgen Popp, Hideo Shindou, Marcel Kwiatkowski, Andreas Koeberle.
      Cell death programs such as apoptosis and ferroptosis are associated with aberrant redox homeostasis linked to lipid metabolism and membrane function. Evidence for cross-talk between these programs is emerging. Here, we show that cytotoxic stress channels polyunsaturated fatty acids via lysophospholipid acyltransferase 12 into phospholipids that become susceptible to peroxidation under additional redox stress. This reprogramming is associated with altered acyl-CoA synthetase isoenzyme expression and caused by a decrease in growth factor receptor tyrosine kinase (RTK)-phosphatidylinositol-3-kinase signaling, resulting in suppressed fatty acid biosynthesis, for specific stressors via impaired Akt-SREBP1 activation. The reduced availability of de novo synthesized fatty acids favors the channeling of polyunsaturated fatty acids into phospholipids. Growth factor withdrawal by serum starvation mimics this phenotype, whereas RTK ligands counteract it. We conclude that attenuated RTK signaling during cell death initiation increases cells' susceptibility to oxidative membrane damage at the interface of apoptosis and alternative cell death programs.
    DOI:  https://doi.org/10.1038/s41467-025-56711-2
  19. Res Sq. 2025 Feb 14. pii: rs.3.rs-5961609. [Epub ahead of print]
    A Quantitative Approach to Mapping Mitochondrial Specialization and Plasticity.
    Martin Picard, Anna Monzel, Jack Devine, Darshana Kapri, Jose Enriquez, Caroline Trumpff.
      Mitochondria are a diverse family of organelles that specialize to accomplish complimentary functions 1-3. All mitochondria share general features, but not all mitochondria are created equal 4.Here we develop a quantitative pipeline to define the degree of molecular specialization among different mitochondrial phenotypes - or mitotypes. By distilling hundreds of validated mitochondrial genes/proteins into 149 biologically interpretable MitoPathway scores (MitoCarta 3.0 5) the simple mitotyping pipeline allows investigators to quantify and interpret mitochondrial diversity and plasticity from transcriptomics or proteomics data across a variety of natural and experimental contexts. We show that mouse and human multi-organ mitotypes segregate along two main axes of mitochondrial specialization, contrasting anabolic (liver) and catabolic (brain) tissues. In cultured primary human fibroblasts exhibiting robust time-dependent and treatment-induced metabolic plasticity 6-8, we demonstrate how the mitotype of a given cell type recalibrates i) over time in parallel with hallmarks of aging, and ii) in response to genetic, pharmacological, and metabolic perturbations. Investigators can now use MitotypeExplorer.org and the associated code to visualize, quantify and interpret the multivariate space of mitochondrial biology.
    DOI:  https://doi.org/10.21203/rs.3.rs-5961609/v1
  20. Nat Rev Cancer. 2025 Feb 25.
    Detecting somatic mutations in single-cell data with SComatic.
    Tim H H Coorens.
      
    DOI:  https://doi.org/10.1038/s41568-025-00799-7
  21. bioRxiv. 2025 Feb 11. pii: 2025.02.10.636967. [Epub ahead of print]
    Temporal dose inversion properties of adaptive biomolecular circuits.
    Eiji Nakamura, Franco Blanchini, Giulia Giordano, Alexander Hoffmann, Elisa Franco.
      Cells have the capacity to encode and decode information in the temporal features of molecular signals. Many pathways, for example, generate either sustained or pulsatile responses depending on the context, and such diverse temporal behaviors have a profound impact on cell fate. Here we focus on how molecular pathways can convert the temporal features of dynamic signals, in particular how they can convert transient signals into persistent downstream events and vice versa. We describe this type of behavior as temporal dose inversion, and we demonstrate that it can be achieved through adaptive molecular circuits. We consider motifs known as incoherent feedforward loop (IFFL) and negative feedback loop (NFL), and identify parametric conditions that enable temporal dose inversion. We next consider more complex versions of these circuits that could be realized using enzymatic signaling and gene regulatory networks, finding that both circuits can exhibit temporal dose inversion. Finally, we consider a generalized IFFL topology, and we find that both the time delay in the inhibition pathway and the relative signal intensities of the activation and inhibition signals are key determinants for temporal dose inversion. Our investigation expands the potential use of adaptive circuits as signal processing units and contributes to our understanding of the role of adaptive circuits in nature.
    DOI:  https://doi.org/10.1101/2025.02.10.636967
  22. Cell Mol Life Sci. 2025 Feb 27. 82(1): 95
    AXL promotes lymphangiogenesis by amplifying VEGF-C-mediated AKT pathway.
    Sébastien Pirson, Marine Gautier-Isola, Louis Baudin, Loïc Rouaud, Aline Vanwynsberghe, Jonathan Deroye, Sophie Bekisz, Fabrice Gucciardo, Alizée Lebeau, Florence Buntinx, Elitsa Ivanova, Bernard Staumont, Silvia Blacher, Christine Gilles, Agnès Noël.
      Lymphangiogenesis has gained considerable interest due to its established role in cancer progression and dissemination of metastatic cells through lymph nodes. Deciphering the molecular mechanisms that govern lymphangiogenesis within lymph nodes holds promise for revealing novel targetable molecules and pathways to inhibit metastasis. In this study, we revealed a previously unrecognized role of AXL, a tyrosine kinase receptor, in the lymphatic vessel formation. We first validated the expression of AXL in lymphatic endothelial cells (LECs), followed by functional studies using RNA interference and pharmacological inhibition with R428/Bemcentinib. These approaches provided compelling evidence that AXL promotes LEC migration in both 2D and 3D culture systems. Our findings demonstrated that AXL activation was induced by VEGF-C (Vascular Endothelial Growth Factor C) and further amplified downstream signaling via the AKT pathway. In vivo, the role of AXL in lymphatic vessel sprouting was demonstrated using R428 in a model of VEGF-C-induced lymphangiogenesis in lymph nodes. Interestingly, we discovered that AXL was predominantly expressed in MARCO+ LECs. Strikingly, under metastatic conditions, there was a notable increase in the density and penetration extent of these AXL-expressing LECs into the lymph node parenchyma. Collectively, our findings pinpoint AXL as a potent enhancer of lymphangiogenesis operating through the VEGF-C/AKT pathway. Furthermore, the identification of AXL expression within a distinct LEC subpopulation, particularly in the context of metastasis, underscores the intricate interplay between AXL signaling and lymphatic dynamics within the lymph node microenvironment.
    Keywords:  AKT pathway; AXL; Lymph node; Lymphangiogenesis; R428/Bemcentinib; VEGF-C pathway
    DOI:  https://doi.org/10.1007/s00018-024-05542-3
  23. Cell Mol Life Sci. 2025 Feb 22. 82(1): 82
    Class I PI3Ks activate stretch-induced autophagy in trabecular meshwork cells.
    Myoung Sup Shim, Ethan J Sim, Kevin Betsch, Vaibhav Desikan, Chien-Chia Su, Diego Pastor-Valverde, Yang Sun, Paloma B Liton.
      Elevated intraocular pressure (IOP) is the primary risk factor for glaucoma, a leading cause of irreversible blindness worldwide. IOP homeostasis is maintained through a balance between aqueous humor production and its drainage through the trabecular meshwork (TM)/Schlemm's Canal (SC) outflow pathway. Prior studies by our laboratory reported a key role of mechanical forces and primary cilia (PC)-dependent stretch-induced autophagy in IOP homeostasis. However, the precise mechanism regulating this process remains elusive. In this study, we investigated the upstream signaling pathway orchestrating autophagy activation during cyclic mechanical stretch (CMS) in primary cultured human TM cells, using biochemical and cell biological analyses. Our results indicate that TM cells express catalytic subunits of class IA PI3Ks (PIK3CA, B, and D), and that inhibition of class IA isoforms, but not class II and III, significantly prevent CMS-induced autophagy. Importantly, PIK3CA was found to localize in the PC. Furthermore, we identified a coordinated action of Class IA PI3Ks along INPP4A/B, a 4' inositol phosphatase, responsible for the formation of PI(3,4)P2 and PI(3)P and stretch-induced autophagy in TM cells. These findings contribute to a deeper understanding of the molecular mechanisms underlying IOP homeostasis.
    Keywords:  Autophagy; Glaucoma; Mechanical stress; PI3K; Primary cilia; Trabecular meshwork
    DOI:  https://doi.org/10.1007/s00018-025-05615-x
  24. Annu Rev Anal Chem (Palo Alto Calif). 2025 Feb 25.
    Protein Engineering for Spatiotemporally Resolved Cellular Monitoring.
    Guanwei Zhou, Wenjing Wang.
      Protein engineering has been extensively applied to the development of genetically encoded reporters for spatiotemporally resolved monitoring of dynamic biochemical activity across cellular compartments in living cells. Genetically encoded reporters facilitate the visualization and recording of cellular processes, including transmission of signaling molecules, protease activity, and protein-protein interactions. In this review, we describe and assess common reporter motifs and protein engineering strategies for designing genetically encoded reporters. We also discuss essential parameters for evaluating genetically encoded reporters, along with future protein engineering opportunities in this field.
    DOI:  https://doi.org/10.1146/annurev-anchem-070124-035857
  25. Dev Cell. 2025 Feb 24. pii: S1534-5807(25)00005-X. [Epub ahead of print]60(4): 493-511
    Organoids from pluripotent stem cells and human tissues: When two cultures meet each other.
    Benedetta Artegiani, Delilah Hendriks.
      Human organoids are a widely used tool in cell biology to study homeostatic processes, disease, and development. The term organoids covers a plethora of model systems from different cellular origins that each have unique features and applications but bring their own challenges. This review discusses the basic principles underlying organoids generated from pluripotent stem cells (PSCs) as well as those derived from tissue stem cells (TSCs). We consider how well PSC- and TSC-organoids mimic the different intended organs in terms of cellular complexity, maturity, functionality, and the ongoing efforts to constitute predictive complex models of in vivo situations. We discuss the advantages and limitations associated with each system to answer different biological questions including in the field of cancer and developmental biology, and with respect to implementing emerging advanced technologies, such as (spatial) -omics analyses, CRISPR screens, and high-content imaging screens. We postulate how the two fields may move forward together, integrating advantages of one to the other.
    Keywords:  CRISPR; adult; cancer; co-culture; development; fetal; imaging; organoids; pluripotent stem cells; tissue stem cells
    DOI:  https://doi.org/10.1016/j.devcel.2025.01.005
  26. Nat Commun. 2025 Feb 24. 16(1): 1931
    Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour.
    Dominik Schienstock, Jyh Liang Hor, Sapna Devi, Scott N Mueller.
      With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that enable researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that allow flexible, interactive and intuitive analysis from raw images to analysed data are lacking for many experimental use-cases. Notably, integrated software solutions for analysis of complex 3D and live cell images are sorely needed. To address this, we present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative multidimensional image analysis accessible for non-specialists. We describe the application of Cecelia to several immunologically relevant scenarios and the development of an unbiased approach to distinguish dynamic cell behaviours from live imaging data. Cecelia is available as a software package with a Shiny app interface ( https://github.com/schienstockd/cecelia ). We envision that this framework and its approaches will be of broad use for biological researchers.
    DOI:  https://doi.org/10.1038/s41467-025-57193-y
  27. ArXiv. 2025 Feb 10. pii: arXiv:2408.09344v2. [Epub ahead of print]
    GitHub is an effective platform for collaborative and reproducible laboratory research.
    Katharine Y Chen, Maria Toro-Moreno, Arvind Rasi Subramaniam.
      Laboratory research is a complex, collaborative process that involves several stages, including hypothesis formulation, experimental design, data generation and analysis, and manuscript writing. Although reproducibility and data sharing are increasingly prioritized at the publication stage, integrating these principles at earlier stages of laboratory research has been hampered by the lack of broadly applicable solutions. Here, we propose that the workflow used in modern software development offers a robust framework for enhancing reproducibility and collaboration in laboratory research. In particular, we show that GitHub, a platform widely used for collaborative software projects, can be effectively adapted to organize and document all aspects of a research project's lifecycle in a molecular biology laboratory. We outline a three-step approach for incorporating the GitHub ecosystem into laboratory research workflows: 1. designing and organizing experiments using issues and project boards, 2. documenting experiments and data analyses with a version control system, and 3. ensuring reproducible software environments for data analyses and writing tasks with containerized packages. The versatility, scalability, and affordability of this approach make it suitable for various scenarios, ranging from small research groups to large, cross-institutional collaborations. Adopting this framework from a project's outset can increase the efficiency and fidelity of knowledge transfer within and across research laboratories. An example GitHub repository based on this approach is available at https://github.com/rasilab/github_demo and a template repository that can be copied is available at https://github.com/rasilab/github_template.
  28. Cancer Res. 2025 Feb 24.
    Tumorigenesis Driven by BRAFV600E Requires Secondary Mutations that Overcome it's Feedback Inhibition of RAC1 and Migration.
    Sunyana Gadal, Jacob A Boyer, Simon F Roy, Noah A Outmezguine, Malvika Sharma, Hongyan Li, Ning Fan, Eric Chan, Yevgeniy Romin, Afsar Barlas, Qing Chang, Priya Pancholi, Neilawattie Merna Timaul, Michael Overholtzer, Rona Yaeger, Katia Manova-Todorova, Elisa de Stanchina, Marcus W Bosenberg, Neal Rosen.
      BRAFV600E mutations occur in 46% of melanomas and drive high levels of ERK activity and ERK-dependent proliferation. However, BRAFV600E is insufficient to drive melanoma in genetically engineered mouse models, and 82% of human benign nevi harbor BRAFV600E mutations. We found that BRAFV600E inhibited mesenchymal migration by causing feedback inhibition of RAC1 activity. ERK pathway inhibition induced RAC1 activation and restored migration and invasion. In cells with BRAFV600E, mutant RAC1 or PTEN inactivation restored RAC1 activity and cell motility. Together, these lesions occurred in 26% of melanomas with BRAFV600E mutations. Thus, although BRAFV600E activation of ERK deregulates cell proliferation, it prevents full malignant transformation by causing feedback inhibition of RAC1. Secondary mutations are, therefore, required for tumorigenesis. One mechanism underlying tumor evolution may be the selection of lesions that rescue the deleterious effects of oncogenic drivers.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-24-2220
  29. Nat Commun. 2025 Feb 24. 16(1): 1905
    Potent and selective SETDB1 covalent negative allosteric modulator reduces methyltransferase activity in cells.
    Mélanie Uguen, Devan J Shell, Madhushika Silva, Yu Deng, Fengling Li, Magdalena M Szewczyk, Ka Yang, Yani Zhao, Michael A Stashko, Jacqueline L Norris-Drouin, Jarod M Waybright, Serap Beldar, Justin M Rectenwald, Angie L Mordant, Thomas S Webb, Laura E Herring, Cheryl H Arrowsmith, Suzanne Ackloo, Steven P Gygi, Robert K McGinty, Dalia Barsyte-Lovejoy, Pengda Liu, Levon Halabelian, Lindsey I James, Kenneth H Pearce, Stephen V Frye.
      A promising drug target, SETDB1, is a dual methyl-lysine (Kme) reader and methyltransferase implicated in cancer and neurodegenerative disease progression. To help understand the role of the triple Tudor domain (3TD) of SETDB1, its Kme reader, we first identify a low micromolar potency small molecule ligand, UNC6535, which occupies simultaneously both the TD2 and TD3 reader binding sites. Further optimization leads to the discovery of UNC10013, a covalent 3TD ligand targeting Cys385 of SETDB1. UNC10013 is potent with a kinact/KI of 1.0 × 106 M-1s-1 and demonstrates proteome-wide selectivity. In cells, negative allosteric modulation of SETDB1-mediated Akt methylation occurs after treatment with UNC10013. Therefore, UNC10013 is a potent, selective, and cell-active covalent ligand for the 3TD of SETDB1, demonstrating negative allosteric modulator properties and making it a promising tool to study the biological role of SETDB1 in disease progression.
    DOI:  https://doi.org/10.1038/s41467-025-57005-3
  30. Dis Model Mech. 2025 Feb 01. pii: DMM050804. [Epub ahead of print]18(2):
    Use of metabolic imaging to monitor heterogeneity of tumour response following therapeutic mTORC1/2 pathway inhibition.
    Rosetta Consortium Cancer Research UK
      The PI3K-mTOR-AKT pathway regulates tumour proliferation, gene expression and metabolism, but pathway inhibition induces heterogeneous feedback reactivation, limiting anti-tumour responses. Measuring heterogeneity of pathway inhibition in tissues using protein biomarker phosphorylation or location is challenging. An integrated multi-modal imaging workflow was developed to assess the heterogeneity of AZD2014 (mTORC1/2 inhibitor) response in a PTEN-null renal cancer model. Spatial responses of metabolite biomarkers were analysed by mass spectrometry imaging (MSI). Control and treated tumours were classified according to metabolite-defined regions enriched in control versus AZD2014-treated tumours, respectively. Noticeably, AZD2014-treated tumours retained regions similar to regions dominant in untreated tumours. Imaging mass cytometry analysis of protein biomarkers in 'control-like' regions following AZD2014 treatment showed reduced phospho-S6, indicating suppression, but retained high expression of the glucose transporter GLUT1. Increasing PI3K-AKT inhibition by combining with AZD8186 (PI3Kβ inhibitor) further decreased the control-like metabolic signature, showing PI3K-dependent resistance. This demonstrates that MSI-based workflows yield novel insights into the pharmacodynamic effects of mTORC1/2 inhibition in tumours, which classical biomarkers do not resolve. Coupling these workflows with spatial-omics approaches can deliver greater insights into heterogeneity of treatment response.
    Keywords:  AKT; Imaging mass cytometry; Mass spectrometry imaging; PI3K; Pharmacodynamic; Spatial multi-omics; mTOR
    DOI:  https://doi.org/10.1242/dmm.050804
  31. bioRxiv. 2025 Feb 12. pii: 2025.02.10.637566. [Epub ahead of print]
    Protein degradation and growth dependent dilution substantially shape mammalian proteomes.
    Andrew Leduc, Nikolai Slavov.
      Cellular protein concentrations are maintained through a balance of synthesis and clearance. Clearance occurs through both protein degradation and growth-dependent dilution. At slow growth, clearance is dominated by degradation, which leads to the accumulation of long lived proteins. At fast growth, however, it is dominated by dilution, preventing this accumulation. Thus, the concentration of long lived proteins will be reduced unless cells compensate by preferentially increasing synthesis rates. To determine the dominant regulatory mechanisms, we quantified the degree of compensation between activated and resting human B cells and across mouse tissues. The results indicate that growth-dependent dilution is insufficiently compensated for by changes in protein synthesis, and it accounts for over a third of the concentration changes between high and low growth conditions. Furthermore, we find that about 25 % of the differences in protein concentration across all tissues are controlled by protein clearance. When comparing only slowly growing tissues such as the brain and pancreas, clearance differences explain as much as 42 %. Within a tissue or cell type, clearance variation is sufficient to account for 50 % of the abundance variation for all measured proteins at slow growth, contrasted with 7 % at fast growth. Thus, our model unifies previous observations with our new results and highlights a context-dependent and larger than previously appreciated contribution of protein degradation in shaping protein variation both across the proteome and across cell states.
    DOI:  https://doi.org/10.1101/2025.02.10.637566
  32. Mol Cell. 2025 Feb 19. pii: S1097-2765(25)00105-4. [Epub ahead of print]
    Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions.
    Ernst W Schmid, Johannes C Walter.
      Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying cellular processes is lacking. AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, but standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on curated datasets to train a structure prediction and omics-informed classifier (SPOC) that effectively separates true and false AF-M predictions of PPIs, including in proteome-wide screens. We applied SPOC to an all-by-all matrix of nearly 300 human genome maintenance proteins, generating ∼40,000 predictions that can be viewed at predictomes.org, where users can also score their own predictions with SPOC. High-confidence PPIs discovered using our approach enable hypothesis generation in genome maintenance. Our results provide a framework for interpreting large-scale AF-M screens and help lay the foundation for a proteome-wide structural interactome.
    Keywords:  AF-M database; AF-M score; AlphaFold-multimer; PPI database; PPI screen; SPOC; genome maintenance; in-silico interaction screen; predictomes; protein-protein interactions
    DOI:  https://doi.org/10.1016/j.molcel.2025.01.034
  33. Nat Commun. 2025 Feb 26. 16(1): 1999
    ETVs dictate hPSC differentiation by tuning biophysical properties.
    Natalia M Ziojła, Magdalena Socha, M Cecilia Guerra, Dorota Kizewska, Katarzyna Blaszczyk, Edyta Urbaniak, Sara Henry, Malgorzata Grabowska, Kathy K Niakan, Aryeh Warmflash, Malgorzata Borowiak.
      Stem cells maintain a dynamic dialog with their niche, integrating biochemical and biophysical cues to modulate cellular behavior. Yet, the transcriptional networks that regulate cellular biophysical properties remain poorly defined. Here, we leverage human pluripotent stem cells (hPSCs) and two morphogenesis models - gastruloids and pancreatic differentiation - to establish ETV transcription factors as critical regulators of biophysical parameters and lineage commitment. Genetic ablation of ETV1 or ETV1/ETV4/ETV5 in hPSCs enhances cell-cell and cell-ECM adhesion, leading to aberrant multilineage differentiation including disrupted germ-layer organization, ectoderm loss, and extraembryonic cell overgrowth in gastruloids. Furthermore, ETV1 loss abolishes pancreatic progenitor formation. Single-cell RNA sequencing and follow-up assays reveal dysregulated mechanotransduction via the PI3K/AKT signaling. Our findings highlight the importance of transcriptional control over cell biophysical properties and suggest that manipulating these properties may improve in vitro cell and tissue engineering strategies.
    DOI:  https://doi.org/10.1038/s41467-025-56591-6
  34. Nat Neurosci. 2025 Feb 24.
    PTEN mutations impair CSF dynamics and cortical networks by dysregulating periventricular neural progenitors.
    Tyrone DeSpenza, Emre Kiziltug, Garrett Allington, Daniel G Barson, Stephen McGee, David O'Connor, Stephanie M Robert, Kedous Y Mekbib, Pranav Nanda, Ana B W Greenberg, Amrita Singh, Phan Q Duy, Francesca Mandino, Shujuan Zhao, Anna Lynn, Benjamin C Reeves, Arnaud Marlier, Stephanie A Getz, Carol Nelson-Williams, Hermela Shimelis, Lauren K Walsh, Junhui Zhang, Wei Wang, Mackenzi L Prina, Annaliese OuYang, Asan F Abdulkareem, Hannah Smith, John Shohfi, Neel H Mehta, Evan Dennis, Laetitia R Reduron, Jennifer Hong, William Butler, Bob S Carter, Engin Deniz, Evelyn M R Lake, R Todd Constable, Mustafa Sahin, Siddharth Srivastava, Kellen Winden, Ellen J Hoffman, Marina Carlson, Murat Gunel, Richard P Lifton, Seth L Alper, Sheng Chih Jin, Michael C Crair, Andres Moreno-De-Luca, Bryan W Luikart, Kristopher T Kahle.
      Enlargement of the cerebrospinal fluid (CSF)-filled brain ventricles (ventriculomegaly) is a defining feature of congenital hydrocephalus (CH) and an under-recognized concomitant of autism. Here, we show that de novo mutations in the autism risk gene PTEN are among the most frequent monogenic causes of CH and primary ventriculomegaly. Mouse Pten-mutant ventriculomegaly results from aqueductal stenosis due to hyperproliferation of periventricular Nkx2.1+ neural progenitor cells (NPCs) and increased CSF production from hyperplastic choroid plexus. Pten-mutant ventriculomegalic cortices exhibit network dysfunction from increased activity of Nkx2.1+ NPC-derived inhibitory interneurons. Raptor deletion or postnatal everolimus treatment corrects ventriculomegaly, rescues cortical deficits and increases survival by antagonizing mTORC1-dependent Nkx2.1+ NPC pathology. Thus, PTEN mutations concurrently alter CSF dynamics and cortical networks by dysregulating Nkx2.1+ NPCs. These results implicate a nonsurgical treatment for CH, demonstrate a genetic association of ventriculomegaly and ASD, and help explain neurodevelopmental phenotypes refractory to CSF shunting in select individuals with CH.
    DOI:  https://doi.org/10.1038/s41593-024-01865-3
  35. Nat Commun. 2025 Feb 22. 16(1): 1878
    Interpretable single-cell factor decomposition using sciRED.
    Delaram Pouyabahar, Tallulah Andrews, Gary D Bader.
      Single-cell RNA sequencing maps gene expression heterogeneity within a tissue. However, identifying biological signals in this data is challenging due to confounding technical factors, sparsity, and high dimensionality. Data factorization methods address this by separating and identifying signals in the data, such as gene expression programs, but the resulting factors must be manually interpreted. We developed Single-Cell Interpretable REsidual Decomposition (sciRED) to improve the interpretation of scRNA-seq factor analysis. sciRED removes known confounding effects, uses rotations to improve factor interpretability, maps factors to known covariates, identifies unexplained factors that may capture hidden biological phenomena, and determines the genes and biological processes represented by the resulting factors. We apply sciRED to multiple scRNA-seq datasets and identify sex-specific variation in a kidney map, discern strong and weak immune stimulation signals in a PBMC dataset, reduce ambient RNA contamination in a rat liver atlas to help identify strain variation and reveal rare cell type signatures and anatomical zonation gene programs in a healthy human liver map. These demonstrate that sciRED is useful in characterizing diverse biological signals within scRNA-seq data.
    DOI:  https://doi.org/10.1038/s41467-025-57157-2
  36. Nat Commun. 2025 Feb 22. 16(1): 1884
    Unveiling the cell-type-specific landscape of cellular senescence through single-cell transcriptomics using SenePy.
    Mark A Sanborn, Xinge Wang, Shang Gao, Yang Dai, Jalees Rehman.
      Senescent cells accumulate in most tissues with organismal aging, exposure to stressors, or disease progression. It is challenging to identify senescent cells because cellular senescence signatures and phenotypes vary widely across distinct cell types and tissues. Here we developed an analytical algorithm that defines cell-type-specific and universal signatures of cellular senescence across a wide range of cell types and tissues. We utilize 72 mouse and 64 human weighted single-cell transcriptomic signatures of cellular senescence to create the SenePy scoring platform. SenePy signatures better recapitulate in vivo cellular senescence than signatures derived from in vitro senescence studies. We use SenePy to map the kinetics of senescent cell accumulation in healthy aging as well as multiple disease contexts, including tumorigenesis, inflammation, and myocardial infarction. SenePy characterizes cell-type-specific in vivo cellular senescence and could lead to the identification of genes that serve as mediators of cellular senescence and disease progression.
    DOI:  https://doi.org/10.1038/s41467-025-57047-7
  37. Nat Genet. 2025 Feb 25.
    Cancer-independent somatic mutation of the wild-type NF1 allele in normal tissues in neurofibromatosis type 1.
    Thomas R W Oliver, Andrew R J Lawson, Henry Lee-Six, Anna Tollit, Hyunchul Jung, Yvette Hooks, Rashesh Sanghvi, Matthew D Young, Timothy M Butler, Pantelis A Nicola, Taryn D Treger, Stefanie V Lensing, G A Amos Burke, Kristian Aquilina, Ulrike Löbel, Isidro Cortes-Ciriano, Darren Hargrave, Mette Jorgensen, Flora A Jessop, Tim H H Coorens, Adrienne M Flanagan, Kieren Allinson, Inigo Martincorena, Thomas S Jacques, Sam Behjati.
      Cancer predisposition syndromes mediated by recessive cancer genes generate tumors via somatic variants (second hits) in the unaffected allele. Second hits may or may not be sufficient for neoplastic transformation. Here we performed whole-genome and whole-exome sequencing on 479 tissue biopsies from a child with neurofibromatosis type 1, a multisystem cancer-predisposing syndrome mediated by constitutive monoallelic NF1 inactivation. We identified multiple independent NF1 driver variants in histologically normal tissues, but not in 610 biopsies from two nonpredisposed children. We corroborated this finding using targeted duplex sequencing, including a further nine adults with the same syndrome. Overall, truncating NF1 mutations were under positive selection in normal tissues from individuals with neurofibromatosis type 1. We demonstrate that normal tissues in neurofibromatosis type 1 commonly harbor second hits in NF1, the extent and pattern of which may underpin the syndrome's cancer phenotype.
    DOI:  https://doi.org/10.1038/s41588-025-02097-2
  38. J Clin Invest. 2025 Feb 25. pii: e179782. [Epub ahead of print]
    An endothelial SOX18-mevalonate pathway axis enables repurposing of statins for infantile hemangioma.
    Annegret Holm, Matthew S Graus, Jill Wylie-Sears, Jerry Wei Heng Tan, Maya Alvarez-Harmon, Luke Borgelt, Sana Nasim, Long Chung, Ashish Jain, Mingwei Sun, Liang Sun, Pascal Brouillard, Ramrada Lekwuttikarn, Yanfei Qi, Joyce Teng, Miikka Vikkula, Harry Kozakewich, John B Mulliken, Mathias Francois, Joyce Bischoff.
      Infantile hemangioma (IH) is the most common tumor in children and a paradigm for pathological vasculogenesis, angiogenesis, and regression. Propranolol, the mainstay treatment, inhibits IH vessel formation via a β-adrenergic receptor independent off-target effect of its R(+) enantiomer on the endothelial SRY box transcription factor 18 (SOX18). Transcriptomic profiling of patient-derived hemangioma stem cells (HemSC) uncovered the mevalonate pathway (MVP) as a target of R(+) propranolol. Loss and gain of function of SOX18 confirmed it is both necessary and sufficient for R(+) propranolol suppression of the MVP, including regulation of sterol regulatory element binding protein 2 (SREBP2) and the rate-limiting enzyme HMG-CoA reductase (HMGCR). AThe biological relevance of the endothelial SOX18-MVP axis in IH patient tissue was demonstrated by nuclear co-localization of SOX18 and SREBP2. Functional validation in a preclinical IH xenograft model revealed that statins - competitive inhibitors of HMGCR - efficiently suppress IH vessel formation. We propose an novel endothelial SOX18-MVP-axis as a central regulator of IH pathogenesis and suggest statin repurposing to treat IH. The pleiotropic effects of R(+) propranolol and statins along the SOX18-MVP axis to disable an endothelial-specific program may have therapeutic implications for other vascular disease entities involving pathological vasculogenesis and angiogenesis.
    Keywords:  Angiogenesis; Cholesterol; Endothelial cells; Transcription; Vascular biology
    DOI:  https://doi.org/10.1172/JCI179782
  39. J Endocrinol. 2025 Feb 01. pii: JOE-24-0269. [Epub ahead of print]
    Reappraising the relationship between hyperinsulinemia and insulin resistance in PCOS.
    Emma Jane Houston, Nicole Meredith Templeman.
      Polycystic ovary syndrome (PCOS), a reproductive endocrine disorder with quintessential features of metabolic dysfunction, affects millions of women worldwide. Hyperinsulinemia (i.e., elevated insulin without hypoglycemia) is a common metabolic feature of PCOS that worsens its reproductive symptoms by exacerbating pituitary hormone imbalances and increasing levels of bioactive androgens. Hyperinsulinemia in PCOS is often attributed to insulin resistance, based on the concept that impaired insulin-mediated glucose disposal would induce compensatory insulin hypersecretion. However, it is challenging to define the sequential relationship between insulin sensitivity and insulin secretion, as they are tightly interlinked, and evidence suggests that hyperinsulinemia can alternatively precede insulin resistance. Notably, other drivers of hyperinsulinemia (outside of insulin resistance) may be highly relevant in the context of PCOS. For instance, high androgen levels can augment both hyperinsulinemia and insulin resistance, generating a self-perpetuating cycle of reproductive and metabolic dysfunction. In this review, we evaluate the cause-and-effect relationships between insulin resistance and hyperinsulinemia in PCOS. We examine evidence for the prevailing theory of insulin resistance as the primary defect that causes secondary compensatory hyperinsulinemia, and an alternative framework of hyperinsulinemia as the earlier defect that perpetuates reproductive and metabolic features of PCOS. Considering the heterogenous nature of PCOS, it is improbable that its metabolic characteristics always follow the same progression. Comprehensively examining all mechanistic regulators of hyperinsulinemia and insulin resistance in PCOS might thereby lead to improved prevention and management strategies, and address critical knowledge gaps in the progression of PCOS pathogenesis.
    DOI:  https://doi.org/10.1530/JOE-24-0269
  40. bioRxiv. 2025 Feb 11. pii: 2025.02.04.636331. [Epub ahead of print]
    Anti-resonance in developmental signaling regulates cell fate decisions.
    Samuel J Rosen, Olivier Witteveen, Naomi Baxter, Ryan S Lach, Marianne Bauer, Maxwell Z Wilson.
      Cells process dynamic signaling inputs to regulate fate decisions during development. While oscillations or waves in key developmental pathways, such as Wnt, have been widely observed, the principles governing how cells decode these signals remain unclear. By leveraging optogenetic control of the Wnt signaling pathway in both HEK293T cells and H9 human embryonic stem cells, we systematically map the relationship between signal frequency and downstream pathway activation. We find that cells exhibit a minimal response to Wnt at certain frequencies, a behavior we term anti-resonance. We developed both detailed biochemical and simplified hidden variable models that explain how anti-resonance emerges from the interplay between fast and slow pathway dynamics. Remarkably, we find that frequency directly influences cell fate decisions involved in human gastrulation; signals delivered at anti-resonant frequencies result in dramatically reduced mesoderm differentiation. Our work reveals a previously unknown mechanism of how cells decode dynamic signals and how anti-resonance may filter against spurious activation. These findings establish new insights into how cells decode dynamic signals with implications for tissue engineering, regenerative medicine, and cancer biology.
    DOI:  https://doi.org/10.1101/2025.02.04.636331
  41. NPJ Precis Oncol. 2025 Feb 25. 9(1): 53
    Examining patient-specific responses to PARP inhibitors in a novel, human induced pluripotent stem cell-based model of breast cancer.
    Carly J Weddle, Malorie Blancard, Nnamdi Uche, Praeploy Pongpamorn, Romina B Cejas, Paul W Burridge.
      Preclinical models of breast cancer that better predict patient-specific drug responses are critical for expanding the clinical utility of targeted therapies, including for inhibitors of poly(ADP-ribose) polymerase (PARP). Reprogramming primary cancer cells into human induced pluripotent stem cells (hiPSCs) recently emerged as a powerful tool to model drug response phenotypes, but its use to date has been limited to hematopoietic malignancies. We designed an optimized reprogramming methodology to generate breast cancer-derived hiPSCs (BC-hiPSCs) from nine patients representing all major subtypes of breast cancer. BC-hiPSCs retain patient-specific oncogenic variants, including variants unique to individual tumor subclones. Additionally, we developed a protocol to differentiate BC-hiPSCs into mammary epithelial cells and mammary-like organoids for in vitro disease modeling, including drug response phenotyping. Using these tools, we demonstrated that BC-hiPSCs can be used to screen for differential sensitivity to PARP inhibitors and mechanistically investigated the causal genetic variant driving drug sensitivity in one patient.
    DOI:  https://doi.org/10.1038/s41698-025-00837-5
  42. Stem Cell Res Ther. 2025 Feb 23. 16(1): 84
    OCT4 translationally promotes AKT signaling as an RNA-binding protein in stressed pluripotent stem cells.
    Wenjie Chen, Xinyu Chen, Cheng Chen, Shiqi She, Xia Li, Lina Shan, Xiaobing Zhang, Songsong Dan, Yisha Wang, Yan-Wen Zhou, Qingyi Cao, Wenxin Wang, Jianwen Hu, Yaxun Wei, Yaqiang Xue, Yi Zhang, Songying Zhang, Ying-Jie Wang, Bo Kang.
       BACKGROUND: Despite numerous studies addressing the molecular mechanisms by which pluripotent stem cells (PSCs) maintain self-renewal and pluripotency under normal culture conditions, the fundamental question of how PSCs manage to survive stressful conditions remains largely unresolved. Post-transcriptional/translational regulation emerges to be vital for PSCs, but how PSCs coordinate and balance their survival and differentiation at translational level under extrinsic and intrinsic stress conditions is unclear.
    METHODS: The high-throughput sequencing of cross-linking immunoprecipitation cDNA library (HITS-CLIP) was employed to decipher the genome-wide OCT4-RNA interactome in human PSCs, a combined RNC-seq/RNA-seq analysis to assess the role of OCT4 in translational regulation of hypoxic PSCs, and an OCT4-protein interactome to search for OCT4 binding partners that regulate cap-independent translation initiation. By taking the Heterozygous Knocking In N-terminal Tags (HKINT) approach that specifically disrupts the 5'-UTR secondary structure and tagging its protein product of the mRNA from one allele while leaving that from the other allele intact, we examined the effect of disrupting the OCT4/5'-UTR interaction on translation of AKT1 mRNA.
    RESULTS: We revealed OCT4 as a bona fide RNA-binding protein (RBP) in human PSCs that bound to the 5'-UTR, 3'-UTR and CDS regions of mRNAs. Multiple known proteins participating in IRES-mediated translation initiation were detected in the OCT4-protein interactome, and a combined RNC-seq/RNA-seq analysis further confirmed a crucial role of OCT4 in translational regulation of PSCs in response to hypoxic stress. Remarkably, OCT4 bound to the GC-rich elements in the 5'-UTR of AKT1 and multiple PI3K/AKT-pathway-gene mRNAs, and promoted their translation initiation via IRES-mediated pathways under stress conditions. Specifically disrupting the AKT1 mRNA 5'-UTR structure and the OCT4/5'-UTR interaction by the HKINT approach significantly reduced the translation level of AKT1 that led to a higher susceptibility of PSCs to oxidative stress-induced apoptotic death and prioritized differentiation toward ectoderm and endoderm.
    CONCLUSIONS: Our results reveal OCT4 as an anti-stress RBP for translational regulation that critically coordinates the survival and differentiation of PSCs in response to various stressors.
    Keywords:  AKT; OCT4; Oxidative stress; Pluripotent stem cells (PSCs); RNA-binding protein (RBP); Translation initiation
    DOI:  https://doi.org/10.1186/s13287-025-04229-1
  43. Curr Issues Mol Biol. 2025 Jan 23. pii: 73. [Epub ahead of print]47(2):
    Donor Variability Alters the Characteristics of Human Brain Microvascular Endothelial Cells.
    Jingyuan Ya, Ulvi Bayraktutan.
      Primary brain microvascular endothelial cells (BMECs) are widely used in a large number of in vitro studies each year to better mimic their physiological characteristics in vivo. However, potential changes in primary endothelial cells stemming from donor variability or culture conditions may affect the reliability and reproducibility of the experiments. While working on a project regarding BMEC senescence, we noticed behavioral differences between two different batches of cells. Comparative analyses of cellular characteristics revealed that while one batch of BMECs developed a typical cobblestone morphology, the other batch displayed a spindle-shape morphology. Despite showing similar tubulogenic and barrier-forming capacities, the spindle-shaped BMECs displayed greater proliferation rates, stronger staining for CD34, a marker of stemness and higher resistance to oxidative stress-induced senescence and replicative senescence. Conversely, the spindle-shaped cells demonstrated a much weaker staining for the endothelial marker CD31. Taken together, these findings indicate that it is important to scrutinize endothelial characteristics to ensure experimental accuracy when cellular responses markedly vary between the so-called endothelial cells.
    Keywords:  blood–brain barrier; donor difference; endothelial cell; primary cell; senescence
    DOI:  https://doi.org/10.3390/cimb47020073
  44. Genome Biol. 2025 Feb 26. 26(1): 41
    Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2.
    Henri Schmidt, Minsi Zhang, Dimitar Chakarov, Vineet Bansal, Haralambos Mourelatos, Francisco J Sánchez-Rivera, Scott W Lowe, Andrea Ventura, Christina S Leslie, Yuri Pritykin.
      We present GuideScan2 for memory-efficient, parallelizable construction of high-specificity CRISPR guide RNA (gRNA) databases and user-friendly design and analysis of individual gRNAs and gRNA libraries for targeting coding and non-coding regions in custom genomes. GuideScan2 analysis identifies widespread confounding effects of low-specificity gRNAs in published CRISPR screens and enables construction of a gRNA library that reduces off-target effects in a gene essentiality screen. GuideScan2 also enables the design and experimental validation of allele-specific gRNAs in a hybrid mouse genome. GuideScan2 will facilitate CRISPR experiments across a wide range of applications.
    Keywords:  Algorithm; Burrows-Wheeler transform; CRISPR; Guide RNA; GuideScan2; Off-targets; Software; Web interface
    DOI:  https://doi.org/10.1186/s13059-025-03488-8
  45. Front Bioinform. 2025 ;5 1519468
    Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation.
    Mikhail Arbatsky, Ekaterina Vasilyeva, Veronika Sysoeva, Ekaterina Semina, Valeri Saveliev, Kseniya Rubina.
      Processing biological data is a challenge of paramount importance as the amount of accumulated data has been annually increasing along with the emergence of new methods for studying biological objects. Blind application of mathematical methods in biology may lead to erroneous hypotheses and conclusions. Here we narrow our focus down to a small set of mathematical methods applied upon standard processing of scRNA-seq data: preprocessing, dimensionality reduction, integration, and clustering (using machine learning methods for clustering). Normalization and scaling are standard manipulations for the pre-processing with LogNormalize (natural-log transformation), CLR (centered log ratio transformation), and RC (relative counts) being employed as methods for data transformation. The justification for applying these methods in biology is not discussed in methodological articles. The essential aspect of dimensionality reduction is to identify the stable patterns which are deliberately removed upon mathematical data processing as being redundant, albeit containing important minor details for biological interpretation. There are no established rules for integration of datasets obtained at different sampling times or conditions. Clustering calls for reconsidering its application specifically for biological data processing. The novelty of the present study lies in an integrated approach of biology and bioinformatics to elucidate biological insights upon data processing.
    Keywords:  ScRNA-seq; biocentric mathematics; cell clustering; datasets integration; dimension reduction
    DOI:  https://doi.org/10.3389/fbinf.2025.1519468
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