bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2024–04–14
thirteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. A CRISPRi/a screening platform to study cellular nutrient transport in diverse microenvironments.
  2. scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders.
  3. A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening.
  4. SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data.
  5. Problem choice and decision trees in science and engineering.
  6. FLRT2 prevents endothelial cell senescence and vascular aging by regulating the ITGB4/mTORC2/p53 signaling pathway.
  7. Haploinsufficiency of phosphodiesterase 10A activates PI3K/AKT signaling independent of PTEN to induce an aggressive glioma phenotype.
  8. How to supercharge cancer-fighting cells: give them stem-cell skills.
  9. Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.
  10. Cryo-EM structures reveal two allosteric inhibition modes of PI3KαH1047R involving a re-shaping of the activation loop.
  11. Proxies introduce bias in decoding TORC1 activity.
  12. The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.
  13. Chromatin context-dependent regulation and epigenetic manipulation of prime editing.
  1. Nat Cell Biol. 2024 Apr 11.
    A CRISPRi/a screening platform to study cellular nutrient transport in diverse microenvironments.
    Christopher Chidley, Alicia M Darnell, Benjamin L Gaudio, Evan C Lien, Anna M Barbeau, Matthew G Vander Heiden, Peter K Sorger.
      Blocking the import of nutrients essential for cancer cell proliferation represents a therapeutic opportunity, but it is unclear which transporters to target. Here we report a CRISPR interference/activation screening platform to systematically interrogate the contribution of nutrient transporters to support cancer cell proliferation in environments ranging from standard culture media to tumours. We applied this platform to identify the transporters of amino acids in leukaemia cells and found that amino acid transport involves high bidirectional flux dependent on the microenvironment composition. While investigating the role of transporters in cystine starved cells, we uncovered a role for serotonin uptake in preventing ferroptosis. Finally, we identified transporters essential for cell proliferation in subcutaneous tumours and found that levels of glucose and amino acids can restrain proliferation in that environment. This study establishes a framework for systematically identifying critical cellular nutrient transporters, characterizing their function and exploring how the tumour microenvironment impacts cancer metabolism.
    DOI:  https://doi.org/10.1038/s41556-024-01402-1
  2. Nat Commun. 2024 Apr 06. 15(1): 2973
    scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders.
    Yichuan Cao, Xiamiao Zhao, Songming Tang, Qun Jiang, Sijie Li, Siyu Li, Shengquan Chen.
      Recent advancements for simultaneously profiling multi-omics modalities within individual cells have enabled the interrogation of cellular heterogeneity and molecular hierarchy. However, technical limitations lead to highly noisy multi-modal data and substantial costs. Although computational methods have been proposed to translate single-cell data across modalities, broad applications of the methods still remain impeded by formidable challenges. Here, we propose scButterfly, a versatile single-cell cross-modality translation method based on dual-aligned variational autoencoders and data augmentation schemes. With comprehensive experiments on multiple datasets, we provide compelling evidence of scButterfly's superiority over baseline methods in preserving cellular heterogeneity while translating datasets of various contexts and in revealing cell type-specific biological insights. Besides, we demonstrate the extensive applications of scButterfly for integrative multi-omics analysis of single-modality data, data enhancement of poor-quality single-cell multi-omics, and automatic cell type annotation of scATAC-seq data. Moreover, scButterfly can be generalized to unpaired data training, perturbation-response analysis, and consecutive translation.
    DOI:  https://doi.org/10.1038/s41467-024-47418-x
  3. bioRxiv. 2024 Mar 27. pii: 2024.03.25.585978. [Epub ahead of print]
    A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening.
    Ann Cirincione, Danny Simpson, Purnima Ravisankar, Sabrina C Solley, Jun Yan, Mona Singh, Britt Adamson.
      Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable editing efficiencies have complicated application of the approach to high-throughput functional genomics. Leveraging several recent advances, we assembled a prime editing platform capable of high-efficiency substitution editing across a set of engineered prime editing guide RNAs (epegRNAs) and corresponding target sequences (80% median intended editing). Then, using a custom library of 240,000 epegRNAs targeting >17,000 codons with 175 different substitution types, we benchmarked our platform for functional interrogation of small substitution variants (1-3 nucleotides) targeted to essential genes. Resulting data identified negative growth phenotypes for nonsense mutations targeted to ∼8,000 codons, and comparing those phenotypes to results from controls demonstrated high specificity. We also observed phenotypes for synonymous mutations that disrupted splice site motifs at 3' exon boundaries. Altogether, we establish and benchmark a high-throughput prime editing approach for functional characterization of genetic variants with simple readouts from multiplexed experiments.
    DOI:  https://doi.org/10.1101/2024.03.25.585978
  4. bioRxiv. 2024 Mar 26. pii: 2024.03.21.586132. [Epub ahead of print]
    SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data.
    Fabio Stossi, Pankaj K Singh, Michela Marini, Kazem Safari, Adam T Szafran, Alejandra Rivera Tostado, Christopher D Candler, Maureen G Mancini, Elina A Mosa, Michael J Bolt, Demetrio Labate, Michael A Mancini.
      Phenotypic profiling by high throughput microscopy has become one of the leading tools for screening large sets of perturbations in cellular models. Of the numerous methods used over the years, the flexible and economical Cell Painting (CP) assay has been central in the field, allowing for large screening campaigns leading to a vast number of data-rich images. Currently, to analyze data of this scale, available open-source software ( i.e. , CellProfiler) requires computational resources that are not available to most laboratories worldwide. In addition, the image-embedded cell-to-cell variation of responses within a population, while collected and analyzed, is usually averaged and unused. Here we introduce SPACe ( S wift P henotypic A nalysis of Ce lls), an open source, Python-based platform for the analysis of single cell image-based morphological profiles produced by CP experiments. SPACe can process a typical dataset approximately ten times faster than CellProfiler on common desktop computers without loss in mechanism of action (MOA) recognition accuracy. It also computes directional distribution-based distances (Earth Mover's Distance - EMD) of morphological features for quality control and hit calling. We highlight several advantages of SPACe analysis on CP assays, including reproducibility across multiple biological replicates, easy applicability to multiple (∼20) cell lines, sensitivity to variable cell-to-cell responses, and biological interpretability to explain image-based features. We ultimately illustrate the advantages of SPACe in a screening campaign of cell metabolism small molecule inhibitors which we performed in seven cell lines to highlight the importance of testing perturbations across models.
    DOI:  https://doi.org/10.1101/2024.03.21.586132
  5. Cell. 2024 Apr 11. pii: S0092-8674(24)00304-0. [Epub ahead of print]187(8): 1828-1833
    Problem choice and decision trees in science and engineering.
    Michael A Fischbach.
      Scientists and engineers often spend days choosing a problem and years solving it. This imbalance limits impact. Here, we offer a framework for problem choice: prompts for ideation, guidelines for evaluating impact and likelihood of success, the importance of fixing one parameter at a time, and opportunities afforded by failure.
    DOI:  https://doi.org/10.1016/j.cell.2024.03.012
  6. JCI Insight. 2024 Apr 08. pii: e172678. [Epub ahead of print]9(7):
    FLRT2 prevents endothelial cell senescence and vascular aging by regulating the ITGB4/mTORC2/p53 signaling pathway.
    Hyun Jung Hwang, Donghee Kang, Jae-Ryong Kim, Joon Hyuk Choi, Ji-Kan Ryu, Allison B Herman, Young-Gyu Ko, Heon Joo Park, Myriam Gorospe, Jae-Seon Lee.
      The roles of fibronectin leucine-rich transmembrane protein 2 (FLRT2) in physiological and pathological processes are not well known. Here, we identify a potentially novel function of FLRT2 in preventing endothelial cell senescence and vascular aging. We found that FLRT2 expression was lower in cultured senescent endothelial cells as well as in aged rat and human vascular tissues. FLRT2 mediated endothelial cell senescence via the mTOR complex 2, AKT, and p53 signaling pathway in human endothelial cells. We uncovered that FLRT2 directly associated with integrin subunit beta 4 (ITGB4) and thereby promoted ITGB4 phosphorylation, while inhibition of ITGB4 substantially mitigated the induction of senescence triggered by FLRT2 depletion. Importantly, FLRT2 silencing in mice promoted vascular aging, and overexpression of FLRT2 rescued a premature vascular aging phenotype. Therefore, we propose that FLRT2 could be targeted therapeutically to prevent senescence-associated vascular aging.
    Keywords:  Cell biology; Cellular senescence; Vascular biology
    DOI:  https://doi.org/10.1172/jci.insight.172678
  7. Genes Dev. 2024 Apr 08.
    Haploinsufficiency of phosphodiesterase 10A activates PI3K/AKT signaling independent of PTEN to induce an aggressive glioma phenotype.
    Nicholas Nuechterlein, Allison Shelbourn, Frank Szulzewsky, Sonali Arora, Michelle Casad, Siobhan Pattwell, Leyre Merino-Galan, Erik Sulman, Sumaita Arowa, Neriah Alvinez, Miyeon Jung, Desmond Brown, Kayen Tang, Sadhana Jackson, Stefan Stoica, Prashant Chittaboina, Yeshavanth K Banasavadi-Siddegowda, Hans-Georg Wirsching, Nephi Stella, Linda Shapiro, Patrick Paddison, Anoop P Patel, Mark R Gilbert, Zied Abdullaev, Kenneth Aldape, Drew Pratt, Eric C Holland, Patrick J Cimino.
      Glioblastoma is universally fatal and characterized by frequent chromosomal copy number alterations harboring oncogenes and tumor suppressors. In this study, we analyzed exome-wide human glioblastoma copy number data and found that cytoband 6q27 is an independent poor prognostic marker in multiple data sets. We then combined CRISPR-Cas9 data, human spatial transcriptomic data, and human and mouse RNA sequencing data to nominate PDE10A as a potential haploinsufficient tumor suppressor in the 6q27 region. Mouse glioblastoma modeling using the RCAS/tv-a system confirmed that Pde10a suppression induced an aggressive glioma phenotype in vivo and resistance to temozolomide and radiation therapy in vitro. Cell culture analysis showed that decreased Pde10a expression led to increased PI3K/AKT signaling in a Pten-independent manner, a response blocked by selective PI3K inhibitors. Single-nucleus RNA sequencing from our mouse gliomas in vivo, in combination with cell culture validation, further showed that Pde10a suppression was associated with a proneural-to-mesenchymal transition that exhibited increased cell adhesion and decreased cell migration. Our results indicate that glioblastoma patients harboring PDE10A loss have worse outcomes and potentially increased sensitivity to PI3K inhibition.
    Keywords:  PDE10A; PI3K/ATK pathway; RCAS/tv-a; glioblastoma; mesenchymal cell state
    DOI:  https://doi.org/10.1101/gad.351350.123
  8. Nature. 2024 Apr 10.
    How to supercharge cancer-fighting cells: give them stem-cell skills.
    Sara Reardon.
      
    Keywords:  Cancer; Immunology; Medical research
    DOI:  https://doi.org/10.1038/d41586-024-01043-2
  9. Nat Methods. 2024 Apr 09.
    Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.
    Srinivas Niranj Chandrasekaran, Beth A Cimini, Amy Goodale, Lisa Miller, Maria Kost-Alimova, Nasim Jamali, John G Doench, Briana Fritchman, Adam Skepner, Michelle Melanson, Alexandr A Kalinin, John Arevalo, Marzieh Haghighi, Juan C Caicedo, Daniel Kuhn, Desiree Hernandez, James Berstler, Hamdah Shafqat-Abbasi, David E Root, Susanne E Swalley, Sakshi Garg, Shantanu Singh, Anne E Carpenter.
      The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds' mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene's product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.
    DOI:  https://doi.org/10.1038/s41592-024-02241-6
  10. Structure. 2024 Mar 26. pii: S0969-2126(24)00089-3. [Epub ahead of print]
    Cryo-EM structures reveal two allosteric inhibition modes of PI3KαH1047R involving a re-shaping of the activation loop.
    Xiuliang Huang, Kailiang Wang, Jing Han, Xiumei Chen, Zhenglin Wang, Tianlun Wu, Bo Yu, Feng Zhao, Xinjuan Wang, Huijuan Li, Zhi Xie, Xiaotian Zhu, Wenge Zhong, Xiaoming Ren.
      PI3Kα is a lipid kinase that phosphorylates PIP2 and generates PIP3. The hyperactive PI3Kα mutation, H1047R, accounts for about 14% of breast cancer, making it a highly attractive target for drug discovery. Here, we report the cryo-EM structures of PI3KαH1047R bound to two different allosteric inhibitors QR-7909 and QR-8557 at a global resolution of 2.7 Å and 3.0 Å, respectively. The structures reveal two distinct binding pockets on the opposite sides of the activation loop. Structural and MD simulation analyses show that the allosteric binding of QR-7909 and QR-8557 inhibit PI3KαH1047R hyper-activity by reducing the fluctuation and mobility of the activation loop. Our work provides a strong rational basis for a further optimization and development of highly selective drug candidates to treat PI3KαH1047R-driven cancers.
    Keywords:  PI3Kα(H1047R); activation loop; allosteric inhibitor; breast cancer; cryo-EM; drug discovery
    DOI:  https://doi.org/10.1016/j.str.2024.03.007
  11. MicroPubl Biol. 2024 ;2024
    Proxies introduce bias in decoding TORC1 activity.
    Marco Caligaris, Claudio De Virgilio.
      The eukaryotic TORC1 kinase integrates and links nutritional, energy, and hormonal signals to cell growth and homeostasis, and its deregulation is associated with human diseases including neurodegeneration, cancer, and metabolic syndrome. Quantification of TORC1 activities in various genetic settings and defined physiological conditions generally relies on the assessment of the phosphorylation level of residues in TORC1 targets. Here we show that two commonly used TORC1 effectors in yeast, namely Sch9 and Rps6, exhibit distinct phosphorylation patterns in response to rapamycin treatment or changes in nitrogen availability, indicating that the choice of TORC1 proxies introduces a bias in decoding TORC1 activity.
    DOI:  https://doi.org/10.17912/micropub.biology.001170
  12. bioRxiv. 2024 Mar 28. pii: 2024.03.26.586728. [Epub ahead of print]
    The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.
    Jan Lause, Dmitry Kobak, Philipp Berens.
      A recent paper in PLOS Computational Biology (Chari and Pachter, 2023) claimed that t -SNE and UMAP embeddings of single-cell datasets fail to capture true biological structure. The authors argued that such embeddings are as arbitrary and as misleading as forcing the data into an elephant shape. Here we show that this conclusion was based on inadequate and limited metrics of embedding quality. More appropriate metrics quantifying neighborhood and class preservation reveal the elephant in the room: while t -SNE and UMAP embeddings of single-cell data do not represent high-dimensional distances, they can nevertheless provide biologically relevant information.
    DOI:  https://doi.org/10.1101/2024.03.26.586728
  13. Cell. 2024 Apr 05. pii: S0092-8674(24)00311-8. [Epub ahead of print]
    Chromatin context-dependent regulation and epigenetic manipulation of prime editing.
    Xiaoyi Li, Wei Chen, Beth K Martin, Diego Calderon, Choli Lee, Junhong Choi, Florence M Chardon, Troy A McDiarmid, Riza M Daza, Haedong Kim, Jean-Benoît Lalanne, Jenny F Nathans, David S Lee, Jay Shendure.
      We set out to exhaustively characterize the impact of the cis-chromatin environment on prime editing, a precise genome engineering tool. Using a highly sensitive method for mapping the genomic locations of randomly integrated reporters, we discover massive position effects, exemplified by editing efficiencies ranging from ∼0% to 94% for an identical target site and edit. Position effects on prime editing efficiency are well predicted by chromatin marks, e.g., positively by H3K79me2 and negatively by H3K9me3. Next, we developed a multiplex perturbational framework to assess the interaction of trans-acting factors with the cis-chromatin environment on editing outcomes. Applying this framework to DNA repair factors, we identify HLTF as a context-dependent repressor of prime editing. Finally, several lines of evidence suggest that active transcriptional elongation enhances prime editing. Consistent with this, we show we can robustly decrease or increase the efficiency of prime editing by preceding it with CRISPR-mediated silencing or activation, respectively.
    Keywords:  DNA damage repair; cis x trans interactions; cis-chromatin effect; epigenome editing; genome engineering; prime editing
    DOI:  https://doi.org/10.1016/j.cell.2024.03.020
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