bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2022‒02‒06
sixteen papers selected by
Ralitsa Radostinova Madsen
University College London Cancer Institute
  1. Hepatic FoxOs link insulin signaling with plasma lipoprotein metabolism through an apolipoprotein M/sphingosine-1-phosphate pathway.
  2. PTEN Regulates Dendritic Arborization by Decreasing Microtubule Polymerization Rate.
  3. Allostery, and how to define and measure signal transduction.
  4. Real-Time Analysis of AKT Signaling Activities at Single-Cell Resolution Using Cyclic Peptide-Based Probes.
  5. Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors.
  6. Cullin neddylation inhibitor attenuates hyperglycemia by enhancing hepatic insulin signaling through insulin receptor substrate stabilization.
  7. Mapping transcriptomic vector fields of single cells.
  8. CRISPR activation and interference screens decode stimulation responses in primary human T cells.
  9. Not all RAS mutations are equal: A detailed review of the functional diversity of RAS hot spot mutations.
  10. Universal prediction of cell-cycle position using transfer learning.
  11. Completing the cancer jigsaw puzzle with single-cell multiomics.
  12. A knowledge graph to interpret clinical proteomics data.
  13. Discovery through clinical sequencing in oncology.
  14. Protein-PAINT: Superresolution microscopy with signaling proteins.
  15. Human induced pluripotent stem cells display a similar mutation burden as embryonic pluripotent cells in vivo.
  16. Novel insights from a multiomics dissection of the hayflick limit.
  1. J Clin Invest. 2022 Feb 01. pii: e146219. [Epub ahead of print]
    Hepatic FoxOs link insulin signaling with plasma lipoprotein metabolism through an apolipoprotein M/sphingosine-1-phosphate pathway.
    María Concepción Izquierdo, Niroshan Shanmugarajah, Samuel X Lee, Michael J Kraakman, Marit Westerterp, Takumi Kitamoto, Michael Harris, Joshua R Cook, Galina A Gusarova, Kendra Zhong, Elijah Marbuary, InSug O-Sullivan, Nikolaus F Rasmus, Stefania Camastra, Terry G Unterman, Ele Ferrannini, Barry E Hurwitz, Rebecca A Haeusler.
      Multiple beneficial cardiovascular effects of HDL are dependent on sphingosine-1-phosphate (S1P). S1P associates with HDL by binding to apolipoprotein M (ApoM). Insulin resistance is a major driver of dyslipidemia and cardiovascular risk. However, the mechanisms linking alterations in insulin signaling with plasma lipoprotein metabolism are incompletely understood. The insulin-repressible FoxO transcription factors play a key role in mediating the effects of hepatic insulin action on glucose and lipoprotein metabolism. This work aims to determine whether hepatic insulin signaling regulates HDL-S1P, and the underlying molecular mechanisms.We report that insulin resistant, nondiabetic human subjects in two independent cohorts have decreased HDL-S1P levels, but no change in total plasma S1P. This also occurs in the mouse model of insulin resistance, db/db mice, which have low ApoM and a specific reduction of S1P in the HDL fraction, with no change in total plasma S1P. Using mice with hepatocyte deletion of the three insulin-repressible FoxO transcription factors (L-FoxO1,3,4), we found that hepatic FoxOs are required for ApoM expression and S1P association with HDL, without affecting total plasma S1P. In L-FoxO1,3,4 mice, total plasma S1P levels are similar to controls, but S1P is nearly absent from HDL, and is instead increased in the lipoprotein depleted plasma fraction. This phenotype is restored to normal by rescuing ApoM in L-FoxO1,3,4 mice. Our findings show that insulin resistance in humans and mice is associated with decreased HDL-associated S1P. Hepatic FoxO transcription factors are novel regulators of the ApoM-S1P pathway.
    Keywords:  Diabetes; Insulin signaling; Lipoproteins; Metabolism
    DOI:  https://doi.org/10.1172/JCI146219
  2. J Neurosci. 2022 Jan 31. pii: JN-RM-1835-21. [Epub ahead of print]
    PTEN Regulates Dendritic Arborization by Decreasing Microtubule Polymerization Rate.
    Stephanie A Getz, Kamran Tariq, Dylan H Marchand, Conor R Dickson, James R Howe Vi, Patrick D Skelton, Wei Wang, Meijie Li, Jeremy M Barry, Jennifer Hong, Bryan W Luikart.
      Phosphatase and tensin homolog (PTEN) is a major negative regulator of the PI3K/Akt/mechanistic target of rapamycin (mTOR) pathway. Loss-of-function mutations in PTEN have been found in a subset of patients with macrocephaly and autism spectrum disorder. PTEN loss in neurons leads to somal hypertrophy, aberrant migration, dendritic overgrowth, increased spine density, and hyperactivity of neuronal circuits. These neuronal overgrowth phenotypes are present upon Pten knockout (KO) and reconstitution with autism-associated point mutations. The mechanism underlying dendritic overgrowth in Pten deficient neurons is unclear. In this study, we examined how Pten loss impacts microtubule dynamics in both sexes using retroviral infection and transfection strategies to manipulate PTEN expression and tag the plus-end microtubule binding protein, EB3. We found Pten KO neurons sprout more new processes over time compared to wild-type (WT) neurons. We also found an increase in microtubule polymerization rate in Pten KO dendritic growth cones. Reducing microtubule polymerization rate to the WT level was sufficient to reduce dendritic overgrowth in Pten KO neurons in vitro and in vivo Finally, we found that rescue of dendritic overgrowth via inhibition of microtubule polymerization was sufficient to improve the performance of Pten KO mice in a spatial memory task. Taken together, our data suggests that one factor underlying PTEN loss dependent dendritic overgrowth is increased microtubule polymerization. This opens the possibility for an intersectional approach targeting microtubule polymerization and mTOR with low doses of inhibitors to achieve therapeutic gains with minimal side-effects in pathologies associated with loss of neuronal PTEN function.SIGNIFICANCE STATEMENT:Loss of Pten function due to genetic deletion or expression of mutations associated with autism spectrum disorder, results in overgrowth of neurons including increased total dendritic length and branching. We have discovered that this overgrowth is accompanied by increased rate of microtubule polymerization. The increased polymerization rate is insensitive to acute inhibition of mTorC1 or protein synthesis. Direct pharmacological inhibition of microtubule polymerization can slow the polymerization rate in Pten knockout neurons to rates seen in wild-type neurons. Correction of the microtubule polymerization rate rescues increased total dendritic arborization and spatial memory. Our studies suggest that PTEN inhibits dendritic growth through parallel regulation of protein synthesis and cytoskeletal polymerization.
    DOI:  https://doi.org/10.1523/JNEUROSCI.1835-21.2022
  3. Biophys Chem. 2022 Jan 29. pii: S0301-4622(22)00008-4. [Epub ahead of print]283 106766
    Allostery, and how to define and measure signal transduction.
    Ruth Nussinov, Chung-Jung Tsai, Hyunbum Jang.
      Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.
    Keywords:  Allosteric; Artificial intelligence; Cellular network; Deep learning; Neurodevelopmental disorders; Signaling
    DOI:  https://doi.org/10.1016/j.bpc.2022.106766
  4. Methods Mol Biol. 2022 ;2394 65-80
    Real-Time Analysis of AKT Signaling Activities at Single-Cell Resolution Using Cyclic Peptide-Based Probes.
    Fei Ji, Siwen Wang, Shiqun Shao, Priyanka Sarkar, Min Xue.
      Here we present a protocol for interrogating AKT signaling activities in living single cells, using a pair of cyclic peptide-based fluorescent probes. These probes are encapsulated in liposomes and delivered into cells, where they continuously report on AKT signaling activities through a Föster resonance energy transfer mechanism. We describe the use of a microwell chip to achieve single-cell resolution and demonstrate the procedure for on-chip immunostaining. Finally, we provide a method for data extraction, correction, and processing.
    Keywords:  AKT singling; Cyclic peptides; Dynamics; Föster resonance energy transfer; Immunostaining; Single-cell analysis
    DOI:  https://doi.org/10.1007/978-1-0716-1811-0_5
  5. J Cell Sci. 2022 Feb 02. pii: jcs.259685. [Epub ahead of print]
    Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors.
    Sergei Chavez-Abiega, Max L B Grönloh, T W J Gadella, Frank J Bruggeman, J Goedhart.
      Kinases play key roles in signaling networks that are activated by G protein-coupled receptors (GPCRs). Kinase activities are generally inferred from cell lysates, hiding cell-to-cell variability. To study the dynamics and heterogeneity of ERK and Akt, we employed high-content biosensor imaging with kinase translocation reporters. The kinases were activated with GPCR ligands. We observed ligand-concentration dependent response kinetics to histamine, α2-adrenergic, and S1P receptor stimulation. By using G protein inhibitors, we observed that Gq mediated the ERK and Akt responses to histamine. In contrast, Gi was necessary for ERK and Akt activation in response to α2-adrenergic receptor activation. ERK and Akt were also strongly activated by S1P, showing high heterogeneity at the single cell level, especially for ERK. Cluster analysis of time-series derived from 68,000 cells obtained under the different conditions revealed several distinct populations of cells that display similar response dynamics. ERK response dynamics to S1P showed high heterogeneity, which was reduced by the inhibition of Gi. To conclude, we have set up an imaging and analysis strategy that reveals substantial cell-to-cell heterogeneity in kinase activity driven by GPCRs.
    Keywords:  Biosensor; Fluorescence imaging; GPCR; Image analysis; Kinase; Signaling
    DOI:  https://doi.org/10.1242/jcs.259685
  6. Proc Natl Acad Sci U S A. 2022 Feb 08. pii: e2111737119. [Epub ahead of print]119(6):
    Cullin neddylation inhibitor attenuates hyperglycemia by enhancing hepatic insulin signaling through insulin receptor substrate stabilization.
    Cheng Chen, Lijie Gu, David J Matye, Yung-Dai Clayton, Mohammad Nazmul Hasan, Yifeng Wang, Jacob E Friedman, Tiangang Li.
      Hepatic insulin resistance is a hallmark feature of nonalcoholic fatty liver disease and type-2 diabetes and significantly contributes to systemic insulin resistance. Abnormal activation of nutrient and stress-sensing kinases leads to serine/threonine phosphorylation of insulin receptor substrate (IRS) and subsequent IRS proteasome degradation, which is a key underlying cause of hepatic insulin resistance. Recently, members of the cullin-RING E3 ligases (CRLs) have emerged as mediators of IRS protein turnover, but the pathophysiological roles and therapeutic implications of this cellular signaling regulation is largely unknown. CRLs are activated upon cullin neddylation, a process of covalent conjugation of a ubiquitin-like protein called Nedd8 to a cullin scaffold. Here, we report that pharmacological inhibition of cullin neddylation by MLN4924 (Pevonedistat) rapidly decreases hepatic glucose production and attenuates hyperglycemia in mice. Mechanistically, neddylation inhibition delays CRL-mediated IRS protein turnover to prolong insulin action in hepatocytes. In vitro knockdown of either cullin 1 or cullin 3, but not other cullin members, attenuates insulin-induced IRS protein degradation and enhances cellular insulin signaling activation. In contrast, in vivo knockdown of liver cullin 3, but not cullin 1, stabilizes hepatic IRS and decreases blood glucose, which recapitulates the effect of MLN4924 treatment. In summary, these findings suggest that pharmacological inhibition of cullin neddylation represents a therapeutic approach for improving hepatic insulin signaling and lowering blood glucose.
    Keywords:  MLN4924; cullin; diabetes; fatty liver; insulin resistance
    DOI:  https://doi.org/10.1073/pnas.2111737119
  7. Cell. 2022 Feb 01. pii: S0092-8674(21)01577-4. [Epub ahead of print]
    Mapping transcriptomic vector fields of single cells.
    Xiaojie Qiu, Yan Zhang, Jorge D Martin-Rufino, Chen Weng, Shayan Hosseinzadeh, Dian Yang, Angela N Pogson, Marco Y Hein, Kyung Hoi Joseph Min, Li Wang, Emanuelle I Grody, Matthew J Shurtleff, Ruoshi Yuan, Song Xu, Yian Ma, Joseph M Replogle, Eric S Lander, Spyros Darmanis, Ivet Bahar, Vijay G Sankaran, Jianhua Xing, Jonathan S Weissman.
      Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.
    Keywords:  RNA Jacobian; RNA metabolic labeling; cell-fate transitions; differential geometry analysis; dynamical systems theory; dynamo; hematopoiesis; in silico perturbation; least action path; vector field reconstruction
    DOI:  https://doi.org/10.1016/j.cell.2021.12.045
  8. Science. 2022 Feb 04. 375(6580): eabj4008
    CRISPR activation and interference screens decode stimulation responses in primary human T cells.
    Ralf Schmidt, Zachary Steinhart, Madeline Layeghi, Jacob W Freimer, Raymund Bueno, Vinh Q Nguyen, Franziska Blaeschke, Chun Jimmie Ye, Alexander Marson.
      Regulation of cytokine production in stimulated T cells can be disrupted in autoimmunity, immunodeficiencies, and cancer. Systematic discovery of stimulation-dependent cytokine regulators requires both loss-of-function and gain-of-function studies, which have been challenging in primary human cells. We now report genome-wide CRISPR activation (CRISPRa) and interference (CRISPRi) screens in primary human T cells to identify gene networks controlling interleukin-2 (IL-2) and interferon-γ (IFN-γ) production. Arrayed CRISPRa confirmed key hits and enabled multiplexed secretome characterization, revealing reshaped cytokine responses. Coupling CRISPRa screening with single-cell RNA sequencing enabled deep molecular characterization of screen hits, revealing how perturbations tuned T cell activation and promoted cell states characterized by distinct cytokine expression profiles. These screens reveal genes that reprogram critical immune cell functions, which could inform the design of immunotherapies.
    DOI:  https://doi.org/10.1126/science.abj4008
  9. Adv Cancer Res. 2022 ;pii: S0065-230X(21)00066-X. [Epub ahead of print]153 29-61
    Not all RAS mutations are equal: A detailed review of the functional diversity of RAS hot spot mutations.
    Rachel A Burge, G Aaron Hobbs.
      The RAS family of small GTPases are among the most frequently mutated oncogenes in human cancer. Approximately 20% of cancers harbor a RAS mutation, and >150 different missense mutations have been detected. Many of these mutations have mutant-specific biochemical defects that alter nucleotide binding and hydrolysis, effector interactions and cell signaling, prompting renewed efforts in the development of anti-RAS therapies, including the mutation-specific strategies. Previously viewed as undruggable, the recent FDA approval of a KRASG12C-selective inhibitor has offered real promise to the development of allele-specific RAS therapies. A broader understanding of the mutational consequences on RAS function must be developed to exploit additional allele-specific vulnerabilities. Approximately 94% of RAS mutations occur at one of three mutational "hot spots" at Gly12, Gly13 and Gln61. Further, the single-nucleotide substitutions represent >99% of these mutations. Within this scope, we discuss the mutational frequencies of RAS isoforms in cancer, mutant-specific effector interactions and biochemical properties. By limiting our analysis to this mutational subset, we simplify the analysis while only excluding a small percentage of total mutations. Combined, these data suggest that the presence or absence of select RAS mutations in human cancers can be linked to their biochemical properties. Continuing to examine the biochemical differences in each RAS-mutant protein will continue to provide additional breakthroughs in allele-specific therapeutic strategies.
    Keywords:  Allele-specific signaling; GDP exchange; GTP hydrolysis; Isoform-specific mutation frequencies; RAS GTPases
    DOI:  https://doi.org/10.1016/bs.acr.2021.07.004
  10. Genome Biol. 2022 Jan 31. 23(1): 41
    Universal prediction of cell-cycle position using transfer learning.
    Shijie C Zheng, Genevieve Stein-O'Brien, Jonathan J Augustin, Jared Slosberg, Giovanni A Carosso, Briana Winer, Gloria Shin, Hans T Bjornsson, Loyal A Goff, Kasper D Hansen.
      BACKGROUND: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data.RESULTS: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays.
    CONCLUSIONS: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data.
    Keywords:  Cell cycle; Single-cell RNA-sequencing; Transfer learning
    DOI:  https://doi.org/10.1186/s13059-021-02581-y
  11. Nat Cancer. 2021 Dec;2(12): 1260-1262
    Completing the cancer jigsaw puzzle with single-cell multiomics.
    Song Chen, Sarah A Teichmann.
      
    DOI:  https://doi.org/10.1038/s43018-021-00306-5
  12. Nat Biotechnol. 2022 Jan 31.
    A knowledge graph to interpret clinical proteomics data.
    Alberto Santos, Ana R Colaço, Annelaura B Nielsen, Lili Niu, Maximilian Strauss, Philipp E Geyer, Fabian Coscia, Nicolai J Wewer Albrechtsen, Filip Mundt, Lars Juhl Jensen, Matthias Mann.
      Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making.
    DOI:  https://doi.org/10.1038/s41587-021-01145-6
  13. Nat Cancer. 2020 Aug;1(8): 774-783
    Discovery through clinical sequencing in oncology.
    Mark T A Donoghue, Alison M Schram, David M Hyman, Barry S Taylor.
      The molecular characterization of tumors now informs clinical cancer care for many patients. This advent of molecular oncology has been driven by the expanding number of therapeutic biomarkers that can predict sensitivity to both approved agents and investigational agents. Beyond its role in driving clinical-trial enrollments and guiding therapy in individual patients, large-scale clinical genomics in oncology also represents a rapidly expanding research resource for translational scientific discovery. Here we review the progress, opportunities, and challenges of scientific and translational discovery from prospective clinical genomic screening programs now routinely conducted for patients with cancer.
    DOI:  https://doi.org/10.1038/s43018-020-0100-0
  14. Sci Signal. 2022 Feb;15(719): eabg9782
    Protein-PAINT: Superresolution microscopy with signaling proteins.
    Megan V Farrell, Andrea C Nunez, Zhengmin Yang, Pablo Pérez-Ferreros, Katharina Gaus, Jesse Goyette.
      Superresolution techniques have advanced our understanding of complex cellular structures and processes but require the attachment of fluorophores to targets through tags or antibodies, which can be bulky and result in underlabeling. To overcome these limitations, we developed a technique to visualize the nanoscale binding locations of signaling proteins by taking advantage of their native interaction domains. Here, we demonstrated that pPAINT (protein point accumulation in nanoscale topography) is a new, single-molecule localization microscopy (SMLM) technique and used it to investigate T cell signaling by visualizing the Src homology 2 (SH2) domain, which is common in signaling molecules. When SH2 domain-containing proteins relocate to the plasma membrane, the domains selectively, transiently, and reversibly bind to preferred phosphorylated tyrosine residues on receptors. This transient binding yields the stochastic blinking events necessary for SMLM when observed with total internal reflection microscopy and enables quantification of binding coefficients in intact cells. We used pPAINT to reveal the binding sites of several T cell receptor-proximal signaling molecules, including Zap70, PI3K, Grb2, Syk, Eat2, and SHP2, and showed that the probes could be multiplexed. We showed that the binding half-life of the tandem SH2 domain of PI3K correlated with binding site cluster size at the immunological synapses of T cells, but that longer binding lifetimes were associated with smaller clusters for the monovalent SH2 domain of Eat2. These results demonstrate the potential of pPAINT for investigating phosphotyrosine-mediated signaling processes at the plasma membrane.
    DOI:  https://doi.org/10.1126/scisignal.abg9782
  15. iScience. 2022 Feb 18. 25(2): 103736
    Human induced pluripotent stem cells display a similar mutation burden as embryonic pluripotent cells in vivo.
    Karlijn A L Hasaart, Freek Manders, Joske Ubels, Mark Verheul, Markus J van Roosmalen, Niels M Groenen, Rurika Oka, Ewart Kuijk, Susana M Chuva de Sousa Lopes, Ruben van Boxtel.
      Induced pluripotent stem cells (iPSCs) hold great promise for regenerative medicine, but genetic instability is a major concern. Embryonic pluripotent cells also accumulate mutations during early development, but how this relates to the mutation burden in iPSCs remains unknown. Here, we directly compared the mutation burden of cultured iPSCs with their isogenic embryonic cells during human embryogenesis. We generated developmental lineage trees of human fetuses by phylogenetic inference from somatic mutations in the genomes of multiple stem cells, which were derived from different germ layers. Using this approach, we characterized the mutations acquired pre-gastrulation and found a rate of 1.65 mutations per cell division. When cultured in hypoxic conditions, iPSCs generated from fetal stem cells of the assessed fetuses displayed a similar mutation rate and spectrum. Our results show that iPSCs maintain a genomic integrity during culture at a similar degree as their pluripotent counterparts do in vivo.
    Keywords:  Cell biology; Genomics; Stem cells research
    DOI:  https://doi.org/10.1016/j.isci.2022.103736
  16. Elife. 2022 Feb 04. pii: e70283. [Epub ahead of print]11
    Novel insights from a multiomics dissection of the hayflick limit.
    Michelle Chan, Han Yuan, Ilya Soifer, Tobias M Maile, Rebecca Y Wang, Andrea Ireland, Jonathon J O'Brien, Jérôme Goudeau, Leanne Jg Chan, Twaritha Vijay, Adam Freund, Cynthia Kenyon, Bryson D Bennett, Fiona E McAllister, David R Kelley, Margaret Roy, Robert L Cohen, Arthur D Levinson, David Botstein, David G Hendrickson.
      The process wherein dividing cells exhaust proliferative capacity and enter into replicative senescence has become a prominent model for cellular aging in vitro. Despite decades of study, this cellular state is not fully understood in culture and even much less so during aging. Here, we revisit Leonard Hayflick's original observation of replicative senescence in WI-38 human lung fibroblasts equipped with a battery of modern techniques including RNA-seq, single cell RNA-seq, proteomics, metabolomics, and ATAC-seq. We find evidence that the transition to a senescent state manifests early, increases gradually, and corresponds to a concomitant global increase in DNA accessibility in nucleolar and lamin associated domains. Furthermore, we demonstrate that senescent WI-38 cells acquire a striking resemblance to myofibroblasts in a process similar to the epithelial to mesenchymal transition (EMT) that is regulated by the transcription factors YAP1/TEAD1 and TGF-𝛽2. Lastly, we show that verteporfin inhibition of YAP1/TEAD1 activity in aged WI-38 cells robustly attenuates this gene expression program.
    Keywords:  chromosomes; gene expression; genetics; genomics; human
    DOI:  https://doi.org/10.7554/eLife.70283
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