bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2023‒08‒06
27 papers selected by
Ralitsa Radostinova Madsen
MRC-PPU
  1. O-GlcNAcylation of Raptor transduces glucose signals to mTORC1.
  2. Automatic detection of spatio-temporal signaling patterns in cell collectives.
  3. A novel homeostatic mechanism tunes PI(4,5)P2-dependent signaling at the plasma membrane.
  4. Novel anti-PTEN C2 domain monoclonal antibodies to analyse the expression and function of PTEN isoform variants.
  5. Manipulating and studying gene function in human pluripotent stem cell models.
  6. To be (in a transcriptional complex) or not to be (promoting UBR5 ubiquitylation): That is an answer to how degradation controls gene expression.
  7. Scientific discovery in the age of artificial intelligence.
  8. Optogenetic clustering and membrane translocation of the BcLOV4 photoreceptor.
  9. Experimental insulin implant uses electricity to control genes.
  10. Proteomic profiling across breast cancer cell lines and models.
  11. Quantifying common and distinct information in single-cell multimodal data with Tilted Canonical Correlation Analysis.
  12. TRIB1 confers therapeutic resistance in GBM cells by activating the ERK and Akt pathways.
  13. Inhibition of PI3K p110δ activity reduces IgE production in IL-4 and anti-CD40 stimulated human B cell cultures.
  14. Individual cell types in C. elegans age differently and activate distinct cell-protective responses.
  15. Transcription Factor Dynamics: One Molecule at a Time.
  16. AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics.
  17. A spatiotemporal Notch interaction map from plasma membrane to nucleus.
  18. Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics.
  19. Systematic benchmarking of single-cell ATAC-sequencing protocols.
  20. How stra(i)nge are your controls? A comparative analysis of metabolic phenotypes in commonly used C57BL/6 substrains.
  21. Revisiting the Thorny Issue of Missing Values in Single-Cell Proteomics.
  22. Kinase-independent role of mTOR and on-/off-target effects of an mTOR kinase inhibitor.
  23. Sex matters: the frequently overlooked importance of considering sex in computational models.
  24. Gene expression networks involved in multiple cellular programs coexist in individual hepatocellular cancer cells.
  25. Toward a better understanding of PHTS heterogeneity: commentary on 'cell-type specific deficits in PTEN-mutant cortical organoids converge on abnormal circuit activity'.
  26. Providing open imaging data at scale: An EMBL-EBI perspective.
  27. scRNA-sequencing in chick suggests a probabilistic model for cell fate allocation at the neural plate border.
  1. Mol Cell. 2023 Jul 28. pii: S1097-2765(23)00526-9. [Epub ahead of print]
    O-GlcNAcylation of Raptor transduces glucose signals to mTORC1.
    Chenchen Xu, Xiaoqing Pan, Dong Wang, Yuanyuan Guan, Wenyu Yang, Xing Chen, Ying Liu.
      The mechanistic target of rapamycin complex 1 (mTORC1) regulates metabolism and cell growth in response to nutrient levels. Dysregulation of mTORC1 results in a broad spectrum of diseases. Glucose is the primary energy supply of cells, and therefore, glucose levels must be accurately conveyed to mTORC1 through highly responsive signaling mechanisms to control mTORC1 activity. Here, we report that glucose-induced mTORC1 activation is regulated by O-GlcNAcylation of Raptor, a core component of mTORC1, in HEK293T cells. Mechanistically, O-GlcNAcylation of Raptor at threonine 700 facilitates the interactions between Raptor and Rag GTPases and promotes the translocation of mTOR to the lysosomal surface, consequently activating mTORC1. In addition, we show that AMPK-mediated phosphorylation of Raptor suppresses Raptor O-GlcNAcylation and inhibits Raptor-Rags interactions. Our findings reveal an exquisitely controlled mechanism, which suggests how glucose coordinately regulates cellular anabolism and catabolism.
    Keywords:  O-GlcNAcylation; Raptor; glucose sensing; mTOR
    DOI:  https://doi.org/10.1016/j.molcel.2023.07.011
  2. J Cell Biol. 2023 10 02. pii: e202207048. [Epub ahead of print]222(10):
    Automatic detection of spatio-temporal signaling patterns in cell collectives.
    Paolo Armando Gagliardi, Benjamin Grädel, Marc-Antoine Jacques, Lucien Hinderling, Pascal Ender, Andrew R Cohen, Gerald Kastberger, Olivier Pertz, Maciej Dobrzyński.
      Increasing experimental evidence points to the physiological importance of space-time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.
    DOI:  https://doi.org/10.1083/jcb.202207048
  3. J Cell Sci. 2023 Aug 03. pii: jcs.261494. [Epub ahead of print]
    A novel homeostatic mechanism tunes PI(4,5)P2-dependent signaling at the plasma membrane.
    Rachel C Wills, Colleen P Doyle, James P Zewe, Jonathan Pacheco, Scott D Hansen, Gerald R V Hammond.
      The lipid molecule phosphatidylinositol (4,5)-bisphosphate (PI(4,5)P2) controls all aspects of plasma membrane (PM) function in animal cells, from its selective permeability to the attachment of the cytoskeleton. Although disruption of PI(4,5)P2 is associated with a wide range of diseases, it remains unclear how cells sense and maintain PI(4,5)P2 levels to support various cell functions. Here, we show that the PIP4K family of enzymes that synthesize PI(4,5)P2 via a minor pathway, also function as sensors of tonic PI(4,5)P2 levels. PIP4Ks are recruited to the PM by elevated PI(4,5)P2 levels, where they inhibit the major PI(4,5)P2-synthesizing PIP5Ks. Perturbation of this simple homeostatic mechanism reveals differential sensitivity of PI(4,5)P2-dependent signaling to elevated PI(4,5)P2 levels. These findings reveal that a subset of PI(4,5)P2-driven functions may drive disease associated with disrupted PI(4,5)P2 homeostasis.
    Keywords:  Phosphoinositide; Ptdlns; Signalling
    DOI:  https://doi.org/10.1242/jcs.261494
  4. PLoS One. 2023 ;18(8): e0289369
    Novel anti-PTEN C2 domain monoclonal antibodies to analyse the expression and function of PTEN isoform variants.
    Leire Torices, Caroline E Nunes-Xavier, José I López, Rafael Pulido.
      PTEN is a major tumor suppressor gene frequently mutated in human tumors, and germline PTEN gene mutations are the molecular diagnostic of PTEN Hamartoma Tumor Syndrome (PHTS), a heterogeneous disorder that manifests with multiple hamartomas, cancer predisposition, and neurodevelopmental alterations. A diversity of translational and splicing PTEN isoforms exist, as well as PTEN C-terminal truncated variants generated by disease-associated nonsense mutations. However, most of the available anti-PTEN monoclonal antibodies (mAb) recognize epitopes at the PTEN C-terminal tail, which may introduce a bias in the analysis of the expression of PTEN isoforms and variants. We here describe the generation and precise characterization of anti-PTEN mAb recognizing the PTEN C2-domain, and their use to monitor the expression and function of PTEN isoforms and PTEN missense and nonsense mutations associated to disease. These anti-PTEN C2 domain mAb are suitable to study the pathogenicity of PTEN C-terminal truncations that retain stability and function but have lost the PTEN C-terminal epitopes. The use of well-defined anti-PTEN mAb recognizing distinct PTEN regions, as the ones here described, will help to understand the deleterious effects of specific PTEN mutations in human disease.
    DOI:  https://doi.org/10.1371/journal.pone.0289369
  5. FEBS Lett. 2023 Jul 30.
    Manipulating and studying gene function in human pluripotent stem cell models.
    Elisa Balmas, Federica Sozza, Sveva Bottini, Maria Luisa Ratto, Giulia Savorè, Silvia Becca, Kirsten E Snijders, Alessandro Bertero.
      Human pluripotent stem cells (hPSCs) are uniquely suited to study human development and disease, and promise to revolutionize regenerative medicine. These applications rely on robust methods to manipulate gene function in hPSC models. This comprehensive review aims to both empower scientists approaching the field and update experienced stem cell biologists. We begin by highlighting challenges with manipulating gene expression in hPSCs and their differentiated derivatives, and relevant solutions (transfection, transduction, transposition, and genomic safe harbor editing). We then outline how to perform robust constitutive or inducible loss-, gain-, and change-of-function experiments in hPSCs models, both using historical methods (RNA interference, transgenesis, and homologous recombination) and modern programmable nucleases (particularly CRISPR/Cas9 and its derivatives, i.e., CRISPR interference, activation, base editing, and prime editing). We further describe extension of these approaches for arrayed or pooled functional studies, including emerging single cell genomics methods, and the related design and analytical bioinformatic tools. Finally, we suggest some directions for future advancements in all of these arenas. Mastering the combination of these transformative technologies will empower unprecedented advances in human biology and medicine.
    Keywords:  CRISPR interference and activation; CRISPR/Cas9; RNA interference; arrayed and pooled screens; base and prime editing; genomic safe harbors; homologous recombination; human pluripotent stem cells; single cell screens; transgenesis
    DOI:  https://doi.org/10.1002/1873-3468.14709
  6. Mol Cell. 2023 Aug 03. pii: S1097-2765(23)00524-5. [Epub ahead of print]83(15): 2616-2618
    To be (in a transcriptional complex) or not to be (promoting UBR5 ubiquitylation): That is an answer to how degradation controls gene expression.
    Laura A Hehl, Brenda A Schulman.
      Tsai et al.1 in this issue and Mark et al.2 in Cell reveal how the E3 ligase UBR5 mediates broad regulation by selectively targeting agonist-bound nuclear hormone receptors, MYC, and other transcriptional regulators not incorporated into active gene expression complexes.
    DOI:  https://doi.org/10.1016/j.molcel.2023.07.010
  7. Nature. 2023 Aug;620(7972): 47-60
    Scientific discovery in the age of artificial intelligence.
    Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Veličković, Max Welling, Linfeng Zhang, Connor W Coley, Yoshua Bengio, Marinka Zitnik.
      Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment and accelerate research, helping scientists to generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone. Here we examine breakthroughs over the past decade that include self-supervised learning, which allows models to be trained on vast amounts of unlabelled data, and geometric deep learning, which leverages knowledge about the structure of scientific data to enhance model accuracy and efficiency. Generative AI methods can create designs, such as small-molecule drugs and proteins, by analysing diverse data modalities, including images and sequences. We discuss how these methods can help scientists throughout the scientific process and the central issues that remain despite such advances. Both developers and users of AI toolsneed a better understanding of when such approaches need improvement, and challenges posed by poor data quality and stewardship remain. These issues cut across scientific disciplines and require developing foundational algorithmic approaches that can contribute to scientific understanding or acquire it autonomously, making them critical areas of focus for AI innovation.
    DOI:  https://doi.org/10.1038/s41586-023-06221-2
  8. Proc Natl Acad Sci U S A. 2023 08 08. 120(32): e2221615120
    Optogenetic clustering and membrane translocation of the BcLOV4 photoreceptor.
    Ayush Aditya Pal, William Benman, Thomas R Mumford, Zikang Huang, Brian Y Chow, Lukasz J Bugaj.
      Optogenetic tools respond to light through one of a small number of behaviors including allosteric changes, dimerization, clustering, or membrane translocation. Here, we describe a new class of optogenetic actuator that simultaneously clusters and translocates to the plasma membrane in response to blue light. We demonstrate that dual translocation and clustering of the BcLOV4 photoreceptor can be harnessed for novel single-component optogenetic tools, including for control of the entire family of epidermal growth factor receptor (ErbB1-4) tyrosine kinases. We further find that clustering and membrane translocation are mechanistically linked. Stronger clustering increased the magnitude of translocation and downstream signaling, increased sensitivity to light by ~threefold-to-fourfold, and decreased the expression levels needed for strong signal activation. Thus light-induced clustering of BcLOV4 provides a strategy to generate a new class of optogenetic tools and to enhance existing ones.
    Keywords:  cell signaling; clustering; intrinsically disordered regions; optogenetics
    DOI:  https://doi.org/10.1073/pnas.2221615120
  9. Nature. 2023 Aug 01.
    Experimental insulin implant uses electricity to control genes.
    Lilly Tozer.
      
    Keywords:  Diabetes; Molecular biology
    DOI:  https://doi.org/10.1038/d41586-023-02461-4
  10. Sci Data. 2023 Aug 04. 10(1): 514
    Proteomic profiling across breast cancer cell lines and models.
    Marian Kalocsay, Matthew J Berberich, Robert A Everley, Maulik K Nariya, Mirra Chung, Benjamin Gaudio, Chiara Victor, Gary A Bradshaw, Robyn J Eisert, Marc Hafner, Peter K Sorger, Caitlin E Mills, Kartik Subramanian.
      We performed quantitative proteomics on 60 human-derived breast cancer cell line models to a depth of ~13,000 proteins. The resulting high-throughput datasets were assessed for quality and reproducibility. We used the datasets to identify and characterize the subtypes of breast cancer and showed that they conform to known transcriptional subtypes, revealing that molecular subtypes are preserved even in under-sampled protein feature sets. All datasets are freely available as public resources on the LINCS portal. We anticipate that these datasets, either in isolation or in combination with complimentary measurements such as genomics, transcriptomics and phosphoproteomics, can be mined for the purpose of predicting drug response, informing cell line specific context in models of signalling pathways, and identifying markers of sensitivity or resistance to therapeutics.
    DOI:  https://doi.org/10.1038/s41597-023-02355-0
  11. Proc Natl Acad Sci U S A. 2023 08 08. 120(32): e2303647120
    Quantifying common and distinct information in single-cell multimodal data with Tilted Canonical Correlation Analysis.
    Kevin Z Lin, Nancy R Zhang.
      Multimodal single-cell technologies profile multiple modalities for each cell simultaneously, enabling a more thorough characterization of cell populations. Existing dimension-reduction methods for multimodal data capture the "union of information," producing a lower-dimensional embedding that combines the information across modalities. While these tools are useful, we focus on a fundamentally different task of separating and quantifying the information among cells that is shared between the two modalities as well as unique to only one modality. Hence, we develop Tilted Canonical Correlation Analysis (Tilted-CCA), a method that decomposes a paired multimodal dataset into three lower-dimensional embeddings-one embedding captures the "intersection of information," representing the geometric relations among the cells that is common to both modalities, while the remaining two embeddings capture the "distinct information for a modality," representing the modality-specific geometric relations. We analyze single-cell multimodal datasets sequencing RNA along surface antibodies (i.e., CITE-seq) as well as RNA alongside chromatin accessibility (i.e., 10x) for blood cells and developing neurons via Tilted-CCA. These analyses show that Tilted-CCA enables meaningful visualization and quantification of the cross-modal information. Finally, Tilted-CCA's framework allows us to perform two specific downstream analyses. First, for single-cell datasets that simultaneously profile transcriptome and surface antibody markers, we show that Tilted-CCA helps design the target antibody panel to complement the transcriptome best. Second, for developmental single-cell datasets that simultaneously profile transcriptome and chromatin accessibility, we show that Tilted-CCA helps identify development-informative genes and distinguish between transient versus terminal cell types.
    Keywords:  canonical correlation analysis; matrix factorization; multimodal data; multiview data; single-cell genomics
    DOI:  https://doi.org/10.1073/pnas.2303647120
  12. Sci Rep. 2023 08 01. 13(1): 12424
    TRIB1 confers therapeutic resistance in GBM cells by activating the ERK and Akt pathways.
    Karnika Singh, Chunhua Han, Jessica L Fleming, Aline P Becker, Joseph McElroy, Tiantian Cui, Benjamin Johnson, Ashok Kumar, Ebin Sebastian, Christian A Showalter, Morgan S Schrock, Matthew K Summers, Valesio Becker, Zhen-Yue Tong, Xiaomei Meng, Heather R Manring, Monica Venere, Erica H Bell, Pierre A Robe, A L Grosu, S Jaharul Haque, Arnab Chakravarti.
      GBM (Glioblastoma) is the most lethal CNS (Central nervous system) tumor in adults, which inevitably develops resistance to standard treatments leading to recurrence and mortality. TRIB1 is a serine/threonine pseudokinase which functions as a scaffold platform that initiates degradation of its substrates like C/EBPα through the ubiquitin proteasome system and also activates MEK and Akt signaling. We found that increased TRIB1 gene expression associated with worse overall survival of GBM patients across multiple cohorts. Importantly, overexpression of TRIB1 decreased RT/TMZ (radiation therapy/temozolomide)-induced apoptosis in patient derived GBM cell lines in vitro. TRIB1 directly bound to MEK and Akt and increased ERK and Akt phosphorylation/activation. We also found that TRIB1 protein expression was maximal during G2/M transition of cell cycle in GBM cells. Furthermore, TRIB1 bound directly to HDAC1 and p53. Importantly, mice bearing TRIB1 overexpressing tumors had worse overall survival. Collectively, these data suggest that TRIB1 induces resistance of GBM cells to RT/TMZ treatments by activating the cell proliferation and survival pathways thus providing an opportunity for developing new targeted therapeutics.
    DOI:  https://doi.org/10.1038/s41598-023-32983-w
  13. Immunology. 2023 Aug 02.
    Inhibition of PI3K p110δ activity reduces IgE production in IL-4 and anti-CD40 stimulated human B cell cultures.
    Anna Cutrina-Pons, Aloka De Sa, David J Fear, Hannah J Gould, Faruk Ramadani.
      Phosphoinositide 3-kinase (PI3K) p110δ signalling negatively regulates the production of mouse IgE. However, there are disparities between the mouse and human IgE biology, and the role of PI3K p110δ in the production of human IgE is yet to be determined. To investigate the effect of PI3K p110δ inhibition in the production of human IgE we isolated human B cells from tonsil tissue and stimulated them with IL-4 and anti-CD40 antibody to induce class switching to IgE and IgG1 in the presence or absence of IC87114, a small molecule inhibitor of PI3K p110δ. Using FACS, RT-PCR and ELISA we examined the effect of PI3K p110δ inhibition on IgE production and determined the mechanisms involved. Unlike in mice, we observed that PI3K p110δ inhibition significantly reduces the number of IgE+ switched cells and the amounts of secreted IgE in IL4 and anti-CD40 cultures. However, the number of IgG1+ cells and secreted IgG1 were largely unaffected by PI3K p110δ inhibition. The expression levels of AID, ε and γ1 germinal transcripts or other factors involved in the regulation of CSR to IgE and IgG1 were also unaffected by IC87114. However, we found that IC87114 significantly decreases the proliferation of tonsil B cells stimulated with IL-4 and anti-CD40, specifically reducing the frequency of cells that had undergone 4 divisions or more. In addition, PI3K p110δ inhibition reduced the levels of IRF4 expression in IgE+ germinal centre-like B cells leading to a block in plasma cell differentiation. In conclusion, PI3K p110δ signalling is required for the production of human IgE, which makes it a pharmacological target for the treatment of allergic disease.
    Keywords:  IgE; allergy; class-switching; human B cells; p110δsignal transduction; phosphoinositide 3-kinases
    DOI:  https://doi.org/10.1111/imm.13684
  14. Cell Rep. 2023 Aug 01. pii: S2211-1247(23)00913-0. [Epub ahead of print]42(8): 112902
    Individual cell types in C. elegans age differently and activate distinct cell-protective responses.
    Antoine Emile Roux, Han Yuan, Katie Podshivalova, David Hendrickson, Rex Kerr, Cynthia Kenyon, David Kelley.
      Aging is characterized by a global decline in physiological function. However, by constructing a complete single-cell gene expression atlas, we find that Caenorhabditis elegans aging is not random in nature but instead is characterized by coordinated changes in functionally related metabolic, proteostasis, and stress-response genes in a cell-type-specific fashion, with downregulation of energy metabolism being the only nearly universal change. Similarly, the rates at which cells age differ significantly between cell types. In some cell types, aging is characterized by an increase in cell-to-cell variance, whereas in others, variance actually decreases. Remarkably, multiple resilience-enhancing transcription factors known to extend lifespan are activated across many cell types with age; we discovered new longevity candidates, such as GEI-3, among these. Together, our findings suggest that cells do not age passively but instead react strongly, and individualistically, to events that occur during aging. This atlas can be queried through a public interface.
    Keywords:  CP: Cell biology; Caenorhabditis elegans; GEI-3; aging; aging signature; atlas; cell types; mitochondria; single-cell sequencing; stress response; transcription factor
    DOI:  https://doi.org/10.1016/j.celrep.2023.112902
  15. Annu Rev Cell Dev Biol. 2023 Aug 04.
    Transcription Factor Dynamics: One Molecule at a Time.
    Kaustubh Wagh, Diana A Stavreva, Arpita Upadhyaya, Gordon L Hager.
      Cells must tightly regulate their gene expression programs and yet rapidly respond to acute biochemical and biophysical cues within their environment. This information is transmitted to the nucleus through various signaling cascades, culminating in the activation or repression of target genes. Transcription factors (TFs) are key mediators of these signals, binding to specific regulatory elements within chromatin. While live-cell imaging has conclusively proven that TF-chromatin interactions are highly dynamic, how such transient interactions can have long-term impacts on developmental trajectories and disease progression is still largely unclear. In this review, we summarize our current understanding of the dynamic nature of TF functions, starting with a historical overview of early live-cell experiments. We highlight key factors that govern TF dynamics and how TF dynamics, in turn, affect downstream transcriptional bursting. Finally, we conclude with open challenges and emerging technologies that will further our understanding of transcriptional regulation. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 39 is October 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
    DOI:  https://doi.org/10.1146/annurev-cellbio-022823-013847
  16. Bioinformatics. 2023 Aug 01. pii: btad461. [Epub ahead of print]
    AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics.
    Elena Krismer, Isabell Bludau, Maximilian T Strauss, Matthias Mann.
      SUMMARY: The widespread application of mass spectrometry (MS)-based proteomics in biomedical research increasingly requires robust, transparent and streamlined solutions to extract statistically reliable insights. We have designed and implemented AlphaPeptStats, an inclusive python package with currently with broad functionalities for normalization, imputation, visualization, and statistical analysis of label-free proteomics data. It modularly builds on the established stack of Python scientific libraries, and is accompanied by a rigorous testing framework with 98% test coverage. It imports the output of a range of popular search engines. Data can be filtered and normalized according to user specifications. At its heart, AlphaPeptStats provides a wide range of robust statistical algorithms such as t-tests, ANOVA, PCA, hierarchical clustering and multiple covariate analysis-all in an automatable manner. Data visualization capabilities include heat maps, volcano plots, scatter plots in publication-ready format. AlphaPeptStats advances proteomic research through its robust tools that enable researchers to manually or automatically explore complex datasets to identify interesting patterns and outliers.AVAILABILITY: AlphaPeptStats is implemented in Python and part of the AlphaPept framework. It is released under a permissive Apache license. The source code and one-click installers are freely available and on GitHub at https://github.com/MannLabs/alphapeptstats.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btad461
  17. Sci Signal. 2023 08;16(796): eadg6474
    A spatiotemporal Notch interaction map from plasma membrane to nucleus.
    Alexandre P Martin, Gary A Bradshaw, Robyn J Eisert, Emily D Egan, Lena Tveriakhina, Julia M Rogers, Andrew N Dates, Gustavo Scanavachi, Jon C Aster, Tom Kirchhausen, Marian Kalocsay, Stephen C Blacklow.
      Notch signaling relies on ligand-induced proteolysis of the transmembrane receptor Notch to liberate a nuclear effector that drives cell fate decisions. Upon ligand binding, sequential cleavage of Notch by the transmembrane protease ADAM10 and the intracellular protease γ-secretase releases the Notch intracellular domain (NICD), which translocates to the nucleus and forms a complex that induces target gene transcription. To map the location and timing of the individual steps required for the proteolysis and movement of Notch from the plasma membrane to the nucleus, we used proximity labeling with quantitative, multiplexed mass spectrometry to monitor the interaction partners of endogenous NOTCH2 after ligand stimulation in the presence of a γ-secretase inhibitor and as a function of time after inhibitor removal. Our studies showed that γ-secretase-mediated cleavage of NOTCH2 occurred in an intracellular compartment and that formation of nuclear complexes and recruitment of chromatin-modifying enzymes occurred within 45 min of inhibitor washout. These findings provide a detailed spatiotemporal map tracking the path of Notch from the plasma membrane to the nucleus and identify signaling events that are potential targets for modulating Notch activity.
    DOI:  https://doi.org/10.1126/scisignal.adg6474
  18. Nat Methods. 2023 Aug 03.
    Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics.
    Lingfei Wang, Nikolaos Trasanidis, Ting Wu, Guanlan Dong, Michael Hu, Daniel E Bauer, Luca Pinello.
      Gene regulatory networks (GRNs) are key determinants of cell function and identity and are dynamically rewired during development and disease. Despite decades of advancement, challenges remain in GRN inference, including dynamic rewiring, causal inference, feedback loop modeling and context specificity. To address these challenges, we develop Dictys, a dynamic GRN inference and analysis method that leverages multiomic single-cell assays of chromatin accessibility and gene expression, context-specific transcription factor footprinting, stochastic process network and efficient probabilistic modeling of single-cell RNA-sequencing read counts. Dictys improves GRN reconstruction accuracy and reproducibility and enables the inference and comparative analysis of context-specific and dynamic GRNs across developmental contexts. Dictys' network analyses recover unique insights in human blood and mouse skin development with cell-type-specific and dynamic GRNs. Its dynamic network visualizations enable time-resolved discovery and investigation of developmental driver transcription factors and their regulated targets. Dictys is available as a free, open-source and user-friendly Python package.
    DOI:  https://doi.org/10.1038/s41592-023-01971-3
  19. Nat Biotechnol. 2023 Aug 03.
    Systematic benchmarking of single-cell ATAC-sequencing protocols.
    Florian V De Rop, Gert Hulselmans, Chris Flerin, Paula Soler-Vila, Albert Rafels, Valerie Christiaens, Carmen Bravo González-Blas, Domenica Marchese, Ginevra Caratù, Suresh Poovathingal, Orit Rozenblatt-Rosen, Michael Slyper, Wendy Luo, Christoph Muus, Fabiana Duarte, Rojesh Shrestha, S Tansu Bagdatli, M Ryan Corces, Lira Mamanova, Andrew Knights, Kerstin B Meyer, Ryan Mulqueen, Akram Taherinasab, Patrick Maschmeyer, Jörn Pezoldt, Camille Lucie Germaine Lambert, Marta Iglesias, Sebastián R Najle, Zain Y Dossani, Luciano G Martelotto, Zach Burkett, Ronald Lebofsky, José Ignacio Martin-Subero, Satish Pillai, Arnau Sebé-Pedrós, Bart Deplancke, Sarah A Teichmann, Leif S Ludwig, Theodore P Braun, Andrew C Adey, William J Greenleaf, Jason D Buenrostro, Aviv Regev, Stein Aerts, Holger Heyn.
      Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.
    DOI:  https://doi.org/10.1038/s41587-023-01881-x
  20. PLoS One. 2023 ;18(8): e0289472
    How stra(i)nge are your controls? A comparative analysis of metabolic phenotypes in commonly used C57BL/6 substrains.
    Annesha Sil, Marina Souza Matos, Mirela Delibegovic, Bettina Platt.
      In recent years, insufficiently characterised controls have been a contributing factor to irreproducibility in biomedical research including neuroscience and metabolism. There is now a growing awareness of phenotypic differences between the C57BL/6 substrains which are commonly used as control animals. We here investigated baseline metabolic characteristics such as glucose regulation, fasted serum insulin levels and hepatic insulin signalling in five different C57BL/6 substrains (N, J, JOla, JRcc) of both sexes, obtained from two commercial vendors, Charles River Laboratories (Crl) and Envigo (Env). Our results indicate systematic and tissue-specific differences between substrains, affected by both vendor and sex, in all parameters investigated, and not necessarily mediated by the presence of the NntC57BL/6J mutation. Not only were there differences between 6J and 6N as expected, all three 6J substrains exhibited different profiles, even from the same breeder. Two distinct metabolic profiles were identified, one in which low insulin levels resulted in impaired glucose clearance (6JCrl; both sexes) and the other, where sustained elevations in fasted basal insulin levels led to glucose intolerance (male 6JRccEnv). Further, 6JRccEnv displayed sex differences in both glucose clearance and hepatic insulin signalling markers. In comparison, the two 6N substrains of either sex, irrespective of vendor, did not exhibit considerable differences, with 6NCrl animals presenting a good choice as a healthy baseline 'control' for many types of experiments. Overall, our data emphasise the importance of selecting and characterising control subjects regarding background, sex, and supplier to ensure proper experimental outcomes in biomedical research.
    DOI:  https://doi.org/10.1371/journal.pone.0289472
  21. J Proteome Res. 2023 Aug 02.
    Revisiting the Thorny Issue of Missing Values in Single-Cell Proteomics.
    Christophe Vanderaa, Laurent Gatto.
      Missing values are a notable challenge when analyzing mass spectrometry-based proteomics data. While the field is still actively debating the best practices, the challenge increased with the emergence of mass spectrometry-based single-cell proteomics and the dramatic increase in missing values. A popular approach to deal with missing values is to perform imputation. Imputation has several drawbacks for which alternatives exist, but currently, imputation is still a practical solution widely adopted in single-cell proteomics data analysis. This perspective discusses the advantages and drawbacks of imputation. We also highlight 5 main challenges linked to missing value management in single-cell proteomics. Future developments should aim to solve these challenges, whether it is through imputation or data modeling. The perspective concludes with recommendations for reporting missing values, for reporting methods that deal with missing values, and for proper encoding of missing values.
    Keywords:  RNA-Seq; data analysis; imputation; mass spectrometry; missing values; proteomics; reproducible research; single-cell
    DOI:  https://doi.org/10.1021/acs.jproteome.3c00227
  22. Leukemia. 2023 Aug 02.
    Kinase-independent role of mTOR and on-/off-target effects of an mTOR kinase inhibitor.
    Cuiqing Fan, Mark Wunderlich, Xiongwei Cai, Zijun Yan, Feng Zhang, Ashley Kuenzi Davis, Lingli Xu, Fukun Guo, Q Richard Lu, Mohammad Azam, Weidong Tian, Yi Zheng.
      mTOR, as a serine/threonine kinase, is a widely pursued anticancer target. Multiple clinical trials of mTOR kinase inhibitors are ongoing, but their specificity and safety features remain lacking. Here, we have employed an inducible kinase-inactive D2338A mTOR knock-in mouse model (mTOR-/KI) together with a mTOR conditional knockout model (mTOR-/-) to assess the kinase-dependent/-independent function of mTOR in hematopoiesis and the on-/off-target effects of mTOR kinase inhibitor AZD2014. Despite exhibiting many similar phenotypes to mTOR-/- mice in hematopoiesis, the mTOR-/KI mice survived longer and showed differences in hematopoietic progenitor cells compared to mTOR-/- mice, suggesting a kinase-independent function of mTOR in hematopoiesis. Gene expression signatures in hematopoietic stem cells (HSCs) further revealed both kinase-dependent and independent effects of mTOR. AZD2014, a lead mTOR kinase inhibitor, appeared to work mostly on-target in suppressing mTOR kinase activity, mimicking that of mTOR-/KI HSCs in transcriptome analysis, but it also induced a small set of off-target responses in mTOR-/KI HSCs. In murine and human myeloid leukemia, besides kinase-inhibitory on-target effects, AZD2014 displayed similar off-target and growth-inhibitory cytostatic effects. These studies provide new insights into kinase-dependent/-independent effects of mTOR in hematopoiesis and present a genetic means for precisely assessing the specificity of mTOR kinase inhibitors.
    DOI:  https://doi.org/10.1038/s41375-023-01987-w
  23. Front Physiol. 2023 ;14 1186646
    Sex matters: the frequently overlooked importance of considering sex in computational models.
    K S Burrowes, M Ruppage, A Lowry, D Zhao.
      Personalised medicine and the development of a virtual human or a digital twin comprises visions of the future of medicine. To realise these innovations, an understanding of the biology and physiology of all people are required if we wish to apply these technologies at a population level. Sex differences in health and biology is one aspect that has frequently been overlooked, with young white males being seen as the "average" human being. This has not been helped by the lack of inclusion of female cells and animals in biomedical research and preclinical studies or the historic exclusion, and still low in proportion, of women in clinical trials. However, there are many known differences in health between the sexes across all scales of biology which can manifest in differences in susceptibility to diseases, symptoms in a given disease, and outcomes to a given treatment. Neglecting these important differences in the development of any health technologies could lead to adverse outcomes for both males and females. Here we highlight just some of the sex differences in the cardio-respiratory systems with the goal of raising awareness that these differences exist. We discuss modelling studies that have considered sex differences and touch on how and when to create sex-specific models. Scientific studies should ensure sex differences are included right from the study planning phase and results reported using sex as a biological variable. Computational models must have sex-specific versions to ensure a movement towards personalised medicine is realised.
    Keywords:  digital twin; healthcare; personalised medicine; physiological models; sex differences; sex-specific
    DOI:  https://doi.org/10.3389/fphys.2023.1186646
  24. Heliyon. 2023 Jul;9(7): e18305
    Gene expression networks involved in multiple cellular programs coexist in individual hepatocellular cancer cells.
    Jin Zhao, Ran Lu, Chen Jin, Siying Li, Yulin Chen, Qiaorong Huang, Xue Li, Wentong Meng, Hong Wu, Tianfu Wen, Xianming Mo.
      The gene expression networks of a single cell can be used to reveal cell type- and condition-specific patterns that account for cell states, cell identity, and its responses to environmental changes. We applied single cell sequencing datasets to define mRNA patterns and visualized potential cellular capacities among hepatocellular cancer cells. The expressing numbers and levels of genes were highly heterogenous among the cancer cells. The cellular characteristics were dependent strongly on the expressing numbers and levels of genes, especially oncogenes and anti-oncogenes, in an individual cancer cell. The transcriptional activations of oncogenes and anti-oncogenes were strongly linked to inherent multiple cellular programs, some of which oppose and contend against other processes, in a cancer cell. The gene expression networks of multiple cellular programs proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, ATP production, and neurogenesis coexisted in an individual cancer cell. The findings give rise a hypothesis that a cancer cell expresses balanced combinations of genes and undergoes a given biological process by rapidly transmuting gene expressing networks.
    Keywords:  Balanced combination of gene expressions; Cellular program; Gene expression networks; Hepatocellular carcinoma; Individual cancer cell; Oncogene and anti-oncogene expression
    DOI:  https://doi.org/10.1016/j.heliyon.2023.e18305
  25. Hum Mol Genet. 2023 Aug 04. pii: ddad127. [Epub ahead of print]
    Toward a better understanding of PHTS heterogeneity: commentary on 'cell-type specific deficits in PTEN-mutant cortical organoids converge on abnormal circuit activity'.
    Zhibing Tan, Bryan W Luikart.
      
    DOI:  https://doi.org/10.1093/hmg/ddad127
  26. Histochem Cell Biol. 2023 Aug 03.
    Providing open imaging data at scale: An EMBL-EBI perspective.
    Matthew Hartley, Andrii Iudin, Ardan Padwardhan, Ugis Sarkans, Aybüke Küpcü Yoldaş, Gerard J Kleywegt.
      Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have increased both the spatial and temporal resolutions at which we examine those systems, as well as enabling visualisation of larger tissue volumes. These advances have huge potential but also generate ever increasing amounts of imaging data that must be stored and analysed. Public image repositories provide a critical scientific service through open data provision, supporting reproducibility of scientific results, access to reference imaging datasets and reuse of data for new scientific discovery and acceleration of image analysis methods development. The scale and scope of imaging data provides both challenges and opportunities for open sharing of image data. In this article, we provide a perspective influenced by decades of provision of open data resources for biological information, suggesting areas to focus on and a path towards global interoperability.
    Keywords:  Bioimaging; Data integration; Data management; Metadata
    DOI:  https://doi.org/10.1007/s00418-023-02216-2
  27. Elife. 2023 Aug 02. pii: e82717. [Epub ahead of print]12
    scRNA-sequencing in chick suggests a probabilistic model for cell fate allocation at the neural plate border.
    Alexandre P Thiery, Ailin Leticia Buzzi, Eva Hamrud, Chris Cheshire, Nicholas M Luscombe, James Briscoe, Andrea Streit.
      The vertebrate 'neural plate border' is a transient territory located at the edge of the neural plate containing precursors for all ectodermal derivatives: the neural plate, neural crest, placodes and epidermis. Elegant functional experiments in a range of vertebrate models have provided an in-depth understanding of gene regulatory interactions within the ectoderm. However, these experiments conducted at tissue level raise seemingly contradictory models for fate allocation of individual cells. Here, we carry out single cell RNA sequencing of chick ectoderm from primitive streak to neurulation stage, to explore cell state diversity and heterogeneity. We characterise the dynamics of gene modules, allowing us to model the order of molecular events which take place as ectodermal fates segregate. Furthermore, we find that genes previously classified as neural plate border 'specifiers' typically exhibit dynamic expression patterns and are enriched in either neural, neural crest or placodal fates, revealing that the neural plate border should be seen as a heterogeneous ectodermal territory and not a discrete transitional transcriptional state. Analysis of neural, neural crest and placodal markers reveals that individual NPB cells co-express competing transcriptional programmes suggesting that their ultimate identify is not yet fixed. This population of 'border located undecided progenitors' (BLUPs) gradually diminishes as cell fate decisions take place. Considering our findings, we propose a probabilistic model for cell fate choice at the neural plate border. Our data suggest that the probability of a progenitor's daughters to contribute to a given ectodermal derivative is related to the balance of competing transcriptional programmes, which in turn are regulated by the spatiotemporal position of a progenitor.
    Keywords:  chicken; developmental biology
    DOI:  https://doi.org/10.7554/eLife.82717
This page is being maintained by Thomas Krichel. It was last updated on 2023‒08‒06 at 9:57.