bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2024–08–18
fourteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. mTORC1 phosphorylates and stabilizes LST2 to negatively regulate EGFR.
  2. Sex-dimorphic effects of glucose transporter-2 gene knockdown on hypothalamic primary astrocyte phosphoinositide-3-kinase (PI3K)/protein kinase B (PKB/Akt)/mammalian target of rapamycin (mTOR) cascade protein expression and phosphorylation.
  3. MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts.
  4. Beyond protein lists: AI-assisted interpretation of proteomic investigations in the context of evolving scientific knowledge.
  5. Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.
  6. Transient frequency preference responses in cell signaling systems.
  7. Guidelines for minimal information on cellular senescence experimentation in vivo.
  8. Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer.
  9. Distributed Collaboration for Data, Analysis Pipelines, and Results in Single-Cell Omics.
  10. Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning.
  11. Prelude to a Compositional Systems Biology.
  12. BioImage.IO Chatbot: a community-driven AI assistant for integrative computational bioimaging.
  13. Enhancing homology-directed repair efficiency with HDR-boosting modular ssDNA donor.
  14. Antibody characterization is critical to enhance reproducibility in biomedical research.
  1. Proc Natl Acad Sci U S A. 2024 Aug 20. 121(34): e2405959121
    mTORC1 phosphorylates and stabilizes LST2 to negatively regulate EGFR.
    Stefania Battaglioni, Louise-Marie Craigie, Sofia Filippini, Timm Maier, Michael N Hall.
      TORC1 (target of rapamycin complex 1) is a highly conserved protein kinase that plays a central role in regulating cell growth. Given the role of mammalian TORC1 (mTORC1) in metabolism and disease, understanding mTORC1 downstream signaling and feedback loops is important. mTORC1 recognizes some of its substrates via a five amino acid binding sequence called the TOR signaling (TOS) motif. mTORC1 binding to a TOS motif facilitates phosphorylation of a distinct, distal site. Here, we show that LST2, also known as ZFYVE28, contains a TOS motif (amino acids 401 to 405) and is directly phosphorylated by mTORC1 at serine 670 (S670). mTORC1-mediated S670 phosphorylation promotes LST2 monoubiquitination on lysine 87 (K87). Monoubiquitinated LST2 is stable and displays a broad reticular distribution. When mTORC1 is inactive, unphosphorylated LST2 is degraded by the proteasome. The absence of LST2 enhances EGFR (epidermal growth factor receptor) signaling. We propose that mTORC1 negatively feeds back on its upstream receptor EGFR via LST2.
    Keywords:  LST2; TOS motif; mTOR signaling; negative feedback; phosphorylation substrate
    DOI:  https://doi.org/10.1073/pnas.2405959121
  2. Mol Cell Endocrinol. 2024 Aug 10. pii: S0303-7207(24)00197-7. [Epub ahead of print]593 112341
    Sex-dimorphic effects of glucose transporter-2 gene knockdown on hypothalamic primary astrocyte phosphoinositide-3-kinase (PI3K)/protein kinase B (PKB/Akt)/mammalian target of rapamycin (mTOR) cascade protein expression and phosphorylation.
    Madhu Babu Pasula, Subash Sapkota, Paul W Sylvester, Karen P Briski.
      Glucose transporter-2 (GLUT2), a unique high capacity/low affinity, highly efficient membrane transporter and sensor, regulates hypothalamic astrocyte glucose phosphorylation and glycogen metabolism. The phosphoinositide-3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway participates in glucose homeostasis, but its sensitivity to glucose-sensory cues is unknown. Current research used a hypothalamic astrocyte primary culture model to investigate whether glucoprivation causes PI3K/Akt/mTOR pathway activation in one or both sexes by GLUT2-dependent mechanisms. Glucoprivation did not alter astrocyte PI3K levels, yet up-regulated both phosphorylated derivatives in female and down-regulated male p60 phosphoprotein expression. GLUT2 siRNA pretreatment diminished glucoprivic patterns of PI3K and phospho-PI3K expression in each sex. Astrocyte Akt and phospho-Akt/Thr308 proteins exhibited divergent, sex-contingent responses to GLUT2 gene knockdown or glucoprivation. GLUT2 siRNA pretreatment exacerbated glucoprivic-associated Akt diminution in the female, and either amplified (male) or reversed (female) glucoprivic regulation of phospho-Akt/Thr308 expression. GLUT2 gene silencing down- (male) or up-(female) regulated mTOR protein, and phospho-mTOR protein in male. Male astrocyte mTOR and phospho-mTOR profile were refractory to glucoprivation, but glucose-deprived females showed GLUT2-independent mTOR inhibition and GLUT2-dependent phospho-mTOR up-augmentation. Results identify a larger number of glucoprivic-sensitive PI3K/Akt/mTOR pathway proteins in female versus male astrocytes, and document divergent responses of common glucose-sensitive targets. GLUT2 stimulates phosphoPI3K protein expression in each sex, but imposes differential control of PI3K, Akt, phospho-Akt/Thr308, mTOR, and phospho-mTOR profiles in male versus female. Data implicate GLUT2 as a driver of distinctive pathway protein responses to glucoprivation in female, but not male.
    Keywords:  Akt; GLUT2; Glucoprivation; PI3K; mTOR
    DOI:  https://doi.org/10.1016/j.mce.2024.112341
  3. Nat Commun. 2024 Aug 09. 15(1): 6828
    MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts.
    Samir Rachid Zaim, Mark-Phillip Pebworth, Imran McGrath, Lauren Okada, Morgan Weiss, Julian Reading, Julie L Czartoski, Troy R Torgerson, M Juliana McElrath, Thomas F Bumol, Peter J Skene, Xiao-Jun Li.
      Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.
    DOI:  https://doi.org/10.1038/s41467-024-50612-6
  4. Nat Methods. 2024 Aug;21(8): 1387-1389
    Beyond protein lists: AI-assisted interpretation of proteomic investigations in the context of evolving scientific knowledge.
    Benjamin M Gyori, Olga Vitek.
      
    DOI:  https://doi.org/10.1038/s41592-024-02324-4
  5. Cell Syst. 2024 Aug 01. pii: S2405-4712(24)00201-1. [Epub ahead of print]
    Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.
    Dimitris Volteras, Vahid Shahrezaei, Philipp Thomas.
      Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  approximate Bayesian computation; cell cycle; gene expression noise; genomics; modeling; single-cell transcriptomics; statistical inference; time-resolved; transcription dynamics; transcriptional bursting
    DOI:  https://doi.org/10.1016/j.cels.2024.07.002
  6. NPJ Syst Biol Appl. 2024 Aug 11. 10(1): 86
    Transient frequency preference responses in cell signaling systems.
    Candela L Szischik, Juliana Reves Szemere, Rocío Balderrama, Constanza Sánchez de la Vega, Alejandra C Ventura.
      Ligand-receptor systems, covalent modification cycles, and transcriptional networks are the fundamental components of cell signaling and gene expression systems. While their behavior in reaching a steady-state regime under step-like stimulation is well understood, their response under repetitive stimulation, particularly at early time stages is poorly characterized. Yet, early-stage responses to external inputs are arguably as informative as late-stage ones. In simple systems, a periodic stimulation elicits an initial transient response, followed by periodic behavior. Transient responses are relevant when the stimulation has a limited time span, or when the stimulated component's timescale is slow as compared to the timescales of the downstream processes, in which case the latter processes may be capturing only those transients. In this study, we analyze the frequency response of simple motifs at different time stages. We use dose-conserved pulsatile input signals and consider different metrics versus frequency curves. We show that in ligand-receptor systems, there is a frequency preference response in some specific metrics during the transient stages, which is not present in the periodic regime. We suggest this is a general system-level mechanism that cells may use to filter input signals that have consequences for higher order circuits. In addition, we evaluate how the described behavior in isolated motifs is reflected in similar types of responses in cascades and pathways of which they are a part. Our studies suggest that transient frequency preferences are important dynamic features of cell signaling and gene expression systems, which have been overlooked.
    DOI:  https://doi.org/10.1038/s41540-024-00413-w
  7. Cell. 2024 Aug 08. pii: S0092-8674(24)00640-8. [Epub ahead of print]187(16): 4150-4175
    Guidelines for minimal information on cellular senescence experimentation in vivo.
    Mikolaj Ogrodnik, Juan Carlos Acosta, Peter D Adams, Fabrizio d'Adda di Fagagna, Darren J Baker, Cleo L Bishop, Tamir Chandra, Manuel Collado, Jesus Gil, Vassilis Gorgoulis, Florian Gruber, Eiji Hara, Pidder Jansen-Dürr, Diana Jurk, Sundeep Khosla, James L Kirkland, Valery Krizhanovsky, Tohru Minamino, Laura J Niedernhofer, João F Passos, Nadja A R Ring, Heinz Redl, Paul D Robbins, Francis Rodier, Karin Scharffetter-Kochanek, John M Sedivy, Ewa Sikora, Kenneth Witwer, Thomas von Zglinicki, Maximina H Yun, Johannes Grillari, Marco Demaria.
      Cellular senescence is a cell fate triggered in response to stress and is characterized by stable cell-cycle arrest and a hypersecretory state. It has diverse biological roles, ranging from tissue repair to chronic disease. The development of new tools to study senescence in vivo has paved the way for uncovering its physiological and pathological roles and testing senescent cells as a therapeutic target. However, the lack of specific and broadly applicable markers makes it difficult to identify and characterize senescent cells in tissues and living organisms. To address this, we provide practical guidelines called "minimum information for cellular senescence experimentation in vivo" (MICSE). It presents an overview of senescence markers in rodent tissues, transgenic models, non-mammalian systems, human tissues, and tumors and their use in the identification and specification of senescent cells. These guidelines provide a uniform, state-of-the-art, and accessible toolset to improve our understanding of cellular senescence in vivo.
    Keywords:  aging; humans; in vivo; mouse; senescence; senotherapy
    DOI:  https://doi.org/10.1016/j.cell.2024.05.059
  8. Nat Commun. 2024 Aug 15. 15(1): 7016
    Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer.
    Noah M Lancaster, Pavel Sinitcyn, Patrick Forny, Trenton M Peters-Clarke, Caroline Fecher, Andrew J Smith, Evgenia Shishkova, Tabiwang N Arrey, Anna Pashkova, Margaret Lea Robinson, Nicholas Arp, Jing Fan, Juli Hansen, Andrea Galmozzi, Lia R Serrano, Julie Rojas, Audrey P Gasch, Michael S Westphall, Hamish Stewart, Christian Hock, Eugen Damoc, David J Pagliarini, Vlad Zabrouskov, Joshua J Coon.
      Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.
    DOI:  https://doi.org/10.1038/s41467-024-51274-0
  9. bioRxiv. 2024 Jul 30. pii: 2024.07.30.605714. [Epub ahead of print]
    Distributed Collaboration for Data, Analysis Pipelines, and Results in Single-Cell Omics.
    Alexandre Hutton, Lizhuo Ai, Jesse G Meyer.
      Single-cell omics data analysis pipelines are complicated to design and difficult to share or reproduce. We describe a web platform that enables no-code analysis pipeline design, simple computing via the Open Science Grid, and sharing of entire data analysis pipelines, their input data, and interactive results. We expect this platform to increase the accessibility and reproducibility of single-cell omics.
    DOI:  https://doi.org/10.1101/2024.07.30.605714
  10. bioRxiv. 2024 Jul 31. pii: 2023.11.14.567038. [Epub ahead of print]
    Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning.
    Robert van Dijk, John Arevalo, Mehrtash Babadi, Anne E Carpenter, Shantanu Singh.
      Image-based cell profiling is a powerful tool that compares perturbed cell populations by measuring thousands of single-cell features and summarizing them into profiles. Typically a sample is represented by averaging across cells, but this fails to capture the heterogeneity within cell populations. We introduce CytoSummaryNet: a Deep Sets-based approach that improves mechanism of action prediction by 30-68% in mean average precision compared to average profiling on a public dataset. CytoSummaryNet uses self-supervised contrastive learning in a multiple-instance learning framework, providing an easier-to-apply method for aggregating single-cell feature data than previously published strategies. Interpretability analysis suggests that the model achieves this improvement by downweighting small mitotic cells or those with debris and prioritizing large uncrowded cells. The approach requires only perturbation labels for training, which are readily available in all cell profiling datasets. CytoSummaryNet offers a straightforward post-processing step for single-cell profiles that can significantly boost retrieval performance on image-based profiling datasets.
    DOI:  https://doi.org/10.1101/2023.11.14.567038
  11. ArXiv. 2024 Aug 01. pii: arXiv:2408.00942v1. [Epub ahead of print]
    Prelude to a Compositional Systems Biology.
    Eran Agmon.
      Composition is a powerful principle for systems biology, focused on the interfaces, interconnections, and orchestration of distributed processes. Whereas most systems biology models focus on the structure or dynamics of specific subsystems in controlled conditions, compositional systems biology aims to connect such models into integrative multiscale simulations. This emphasizes the space between models-a compositional perspective asks what variables should be exposed through a submodel's interface? How do coupled models connect and translate across scales? How can we connect domain-specific models across biological and physical research areas to drive the synthesis of new knowledge? What is required of software that integrates diverse datasets and submodels into unified multiscale simulations? How can the resulting integrative models be accessed, flexibly recombined into new forms, and iteratively refined by a community of researchers? This essay offers a high-level overview of the key components for compositional systems biology, including: 1) a conceptual framework and corresponding graphical framework to represent interfaces, composition patterns, and orchestration patterns; 2) standardized composition schemas that offer consistent formats for composable data types and models, fostering robust infrastructure for a registry of simulation modules that can be flexibly assembled; 3) a foundational set of biological templates-schemas for cellular and molecular interfaces, which can be filled with detailed submodels and datasets, and are designed to integrate knowledge that sheds light on the molecular emergence of cells; and 4) scientific collaboration facilitated by user-friendly interfaces for connecting researchers with datasets and models, and which allows a community of researchers to effectively build integrative multiscale models of cellular systems.
    Keywords:  composition; interfaces; multiscale modeling; simulation; systems biology
  12. Nat Methods. 2024 Aug;21(8): 1368-1370
    BioImage.IO Chatbot: a community-driven AI assistant for integrative computational bioimaging.
    Wanlu Lei, Caterina Fuster-Barceló, Gabriel Reder, Arrate Muñoz-Barrutia, Wei Ouyang.
      
    DOI:  https://doi.org/10.1038/s41592-024-02370-y
  13. Nat Commun. 2024 Aug 10. 15(1): 6843
    Enhancing homology-directed repair efficiency with HDR-boosting modular ssDNA donor.
    Ying-Ying Jin, Peng Zhang, Le-Le Liu, Xiang Zhao, Xiao-Qing Hu, Si-Zhe Liu, Ze-Kun Li, Qian Liu, Jian-Qiao Wang, De-Long Hao, Zhu-Qin Zhang, Hou-Zao Chen, De-Pei Liu.
      Despite the potential of small molecules and recombinant proteins to enhance the efficiency of homology-directed repair (HDR), single-stranded DNA (ssDNA) donors, as currently designed and chemically modified, remain suboptimal for precise gene editing. Here, we screen the biased ssDNA binding sequences of DNA repair-related proteins and engineer RAD51-preferred sequences into HDR-boosting modules for ssDNA donors. Donors with these modules exhibit an augmented affinity for RAD51, thereby enhancing HDR efficiency across various genomic loci and cell types when cooperated with Cas9, nCas9, and Cas12a. By combining with an inhibitor of non-homologous end joining (NHEJ) or the HDRobust strategy, these modular ssDNA donors achieve up to 90.03% (median 74.81%) HDR efficiency. The HDR-boosting modules targeting an endogenous protein enable a chemical modification-free strategy to improve the efficacy of ssDNA donors for precise gene editing.
    DOI:  https://doi.org/10.1038/s41467-024-50788-x
  14. Elife. 2024 Aug 14. pii: e100211. [Epub ahead of print]13
    Antibody characterization is critical to enhance reproducibility in biomedical research.
    Richard A Kahn, Harvinder Virk, Carl Laflamme, Douglas W Houston, Nicole K Polinski, Rob Meijers, Allan I Levey, Clifford B Saper, Timothy M Errington, Rachel E Turn, Anita Bandrowski, James S Trimmer, Meghan Rego, Leonard P Freedman, Fortunato Ferrara, Andrew R M Bradbury, Hannah Cable, Skye Longworth.
      Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the 'antibody characterization crisis', and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders - researchers, universities, journals, antibody vendors and repositories, scientific societies and funders - to increase the reproducibility of studies that rely on antibodies.
    Keywords:  RRID; YCharOS; antibody characterization; antibody validation; cell biology; immunology; inflammation; none; renewables; reproducibility
    DOI:  https://doi.org/10.7554/eLife.100211
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