bims-pideca 2024-11-24 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2024–11–24
thirty papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Rapid, potent, and persistent covalent chemical probes to deconvolute PI3Kα signaling.
PhosX: data-driven kinase activity inference from phosphoproteomics experiments.
Multi-layered proteomics identifies insulin-induced upregulation of the EphA2 receptor via the ERK pathway which is dependent on low IGF1R level.
Personalized phosphoproteomics of skeletal muscle insulin resistance and exercise links MINDY1 to insulin action.
Nutrient control of growth and metabolism through mTORC1 regulation of mRNA splicing.
Spatiotemporal Clusters of ERK Activity Coordinate Cytokine-induced Inflammatory Responses in Human Airway Epithelial Cells.
scMultiNODE: Integrative Model for Multi-Modal Temporal Single-Cell Data.
An organotypic atlas of human vascular cells.
A cell atlas foundation model for scalable search of similar human cells.
A multi-omic atlas of human embryonic skeletal development.
multiDGD: A versatile deep generative model for multi-omics data.
mTORC1, the maestro of cell metabolism and growth.
Starvation-induced metabolic rewiring affects mTORC1 composition in vivo.
Measuring FOXO Nuclear Shuttling Dynamics by Fluorescence Microscopy.
Reproducible processing of TCGA regulatory networks.
Pathologists' integration of prior biopsies of women with germline PTEN mutations may expedite the identification of this rare cancer predisposition syndrome.
A Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells.
All the single cells: Single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists.
Initiation and maintenance of the pluripotent epiblast in pre-implantation human development is independent of NODAL signaling.
Obesity predisposes to specific cancer driver mutations.
PTEN depletion reduces H3K27me3 levels to promote epithelial-to-mesenchymal transition in epithelial colorectal cancer cells.
KBTBD2 controls bone development by regulating IGF-1 signaling during osteoblast differentiation.
FOXO Transcription Factors: A Brief Overview.
mxfda: a comprehensive toolkit for functional data analysis of single-cell spatial data.
A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.
A randomised, placebo-controlled, phase III trial of leniolisib in activated phosphoinositide 3-kinase delta (PI3Kδ) syndrome (APDS): Adolescent and adult subgroup analysis.
Review and Practical Guide for Getting Started With Single-Cell Proteomics.
Flipping a switch on BRD4: How to control the do-it-all.
Computational technologies of the Human Cell Atlas.
Reporter Gene Assays to Measure FOXO-Specific Transcriptional Activity.

Chem Sci. 2024 Nov 12.

Rapid, potent, and persistent covalent chemical probes to deconvolute PI3Kα signaling.

Lukas Bissegger, Theodora A Constantin, Erhan Keles, Luka Raguž, Isobel Barlow-Busch, Clara Orbegozo, Thorsten Schaefer, Valentina Borlandelli, Thomas Bohnacker, Rohitha Sriramaratnam, Alexander Schäfer, Matthias Gstaiger, John E Burke, Chiara Borsari, Matthias P Wymann.

Chemical probes have gained importance in the elucidation of signal transduction in biology. Insufficient selectivity and potency, lack of cellular activity and inappropriate use of chemical probes has major consequences on interpretation of biological results. The catalytic subunit of phosphoinositide 3-kinase α (PI3Kα) is one of the most frequently mutated genes in cancer, but fast-acting, high-quality probes to define PI3Kα's specific function to clearly separate it from other class I PI3K isoforms, are not available. Here, we present a series of novel covalent PI3Kα-targeting probes with optimized intracellular target access and kinetic parameters. On-target TR-FRET and off-target assays provided relevant kinetic parameters (k chem, k inact and K i) to validate our chemical probes. Additional intracellular nanoBRET tracer displacement measurements showed rapid diffusion across the cell membrane and extremely fast target engagement, while investigations of signaling downstream of PI3Kα via protein kinase B (PKB/Akt) and forkhead box O (FOXO) revealed blunted pathway activity in cancer cell lines with constitutively activated PI3Kα lasting for several days. In contrast, persistent PI3Kα inhibition was rapidly bypassed by other class I PI3K isoforms in cells lacking functional phosphatase and tensin homolog (PTEN). Comparing the rapidly-diffusing, fast target-engaging chemical probe 9 to clinical reversible PI3Kα-selective inhibitors alpelisib, inavolisib and 9r, a reversible analogue of 9, revealed 9's superior potency to inhibit growth (up to 600-fold) associated with sustained suppression of PI3Kα signaling in breast cancer cell lines. Finally, using a simple washout protocol, the utility of the highly-selective covalent PI3Kα probe 9 was demonstrated by the quantification of the coupling of insulin, EGF and CXCL12 receptors to distinct PI3K isoforms for signal transduction in response to ligand-dependent activation. Collectively, these findings along with the novel covalent chemical probes against PI3Kα provide insights into isoform-specific functions in cancer cells and highlight opportunities to achieve improved selectivity and long-lasting efficacy.

DOI: https://doi.org/10.1039/d4sc05459h
Bioinformatics. 2024 Nov 19. pii: btae697. [Epub ahead of print]

PhosX: data-driven kinase activity inference from phosphoproteomics experiments.

Alessandro Lussana, Sophia Müller-Dott, Julio Saez-Rodriguez, Evangelia Petsalaki.

SUMMARY: The inference of kinase activity from phosphoproteomics data can point to causal mechanisms driving signalling processes and potential drug targets. Identifying the kinases whose change in activity explains the observed phosphorylation profiles, however, remains challenging, and constrained by the manually curated knowledge of kinase-substrate associations. Recently, experimentally determined substrate sequence specificities of human kinases have become available, but robust methods to exploit this new data for kinase activity inference are still missing. We present PhosX, a method to estimate differential kinase activity from phosphoproteomics data that combines state-of-the art statistics in enrichment analysis with kinases' substrate sequence specificity information. Using a large phosphoproteomics dataset with known differentially regulated kinases we show that our method identifies upregulated and downregulated kinases by only relying on the input phosphopeptides' sequences and intensity changes. We find that PhosX outperforms the currently available approach for the same task, and performs better or similarly to state-of-the-art methods that rely on previously known kinase-substrate associations. We therefore recommend its use for data-driven kinase activity inference.
AVAILABILITY AND IMPLEMENTATION: PhosX is implemented in Python, open-source under the Apache-2.0 licence, and distributed on the Python Package Index. The code is available on GitHub (https://github.com/alussana/phosx).
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btae697
Sci Rep. 2024 Nov 21. 14(1): 28856

Multi-layered proteomics identifies insulin-induced upregulation of the EphA2 receptor via the ERK pathway which is dependent on low IGF1R level.

Sarah Hyllekvist Jørgensen, Kristina Bennet Emdal, Anna-Kathrine Pedersen, Lene Nygaard Axelsen, Helene Faustrup Kildegaard, Damien Demozay, Thomas Åskov Pedersen, Mads Grønborg, Rita Slaaby, Peter Kresten Nielsen, Jesper Velgaard Olsen.

Insulin resistance impairs the cellular insulin response, and often precedes metabolic disorders, like type 2 diabetes, impacting an increasing number of people globally. Understanding the molecular mechanisms in hepatic insulin resistance is essential for early preventive treatments. To elucidate changes in insulin signal transduction associated with hepatocellular resistance, we employed a multi-layered mass spectrometry-based proteomics approach focused on insulin receptor (IR) signaling at the interactome, phosphoproteome, and proteome levels in a long-term hyperinsulinemia-induced insulin-resistant HepG2 cell line with a knockout of the insulin-like growth factor 1 receptor (IGF1R KO). The analysis revealed insulin-stimulated recruitment of the PI3K complex in both insulin-sensitive and -resistant cells. Phosphoproteomics showed attenuated signaling via the metabolic PI3K-AKT pathway but sustained extracellular signal-regulated kinase (ERK) activity in insulin-resistant cells. At the proteome level, the ephrin type-A receptor 2 (EphA2) showed an insulin-induced increase in expression, which occurred through the ERK signaling pathway and was concordantly independent of insulin resistance. Induction of EphA2 by insulin was confirmed in additional cell lines and observed uniquely in cells with high IR-to-IGF1R ratio. The multi-layered proteomics dataset provided insights into insulin signaling, serving as a resource to generate and test hypotheses, leading to an improved understanding of insulin resistance.

DOI: https://doi.org/10.1038/s41598-024-77817-5
Cell Metab. 2024 Nov 18. pii: S1550-4131(24)00416-9. [Epub ahead of print]

Personalized phosphoproteomics of skeletal muscle insulin resistance and exercise links MINDY1 to insulin action.

Elise J Needham, Janne R Hingst, Johan D Onslev, Alexis Diaz-Vegas, Magnus R Leandersson, Hannah Huckstep, Jonas M Kristensen, Kohei Kido, Erik A Richter, Kurt Højlund, Benjamin L Parker, Kristen Cooke, Guang Yang, Christian Pehmøller, Sean J Humphrey, David E James, Jørgen F P Wojtaszewski.

  Type 2 diabetes is preceded by a defective insulin response, yet our knowledge of the precise mechanisms is incomplete. Here, we investigate how insulin resistance alters skeletal muscle signaling and how exercise partially counteracts this effect. We measured parallel phenotypes and phosphoproteomes of insulin-resistant (IR) and insulin-sensitive (IS) men as they responded to exercise and insulin (n = 19, 114 biopsies), quantifying over 12,000 phosphopeptides in each biopsy. Insulin resistance involves selective and time-dependent alterations to signaling, including reduced insulin-stimulated mTORC1 and non-canonical signaling responses. Prior exercise promotes insulin sensitivity even in IR individuals by "priming" a portion of insulin signaling prior to insulin infusion. This includes MINDY1 S441, which we show is an AKT substrate. We found that MINDY1 knockdown enhances insulin-stimulated glucose uptake in rat myotubes. This work delineates the signaling alterations in IR skeletal muscle and identifies MINDY1 as a regulator of insulin action.

Keywords:  MINDY1; cell signaling; exercise; insulin; insulin resistance; phosphoproteomics; proteomics; skeletal muscle

DOI:  https://doi.org/10.1016/j.cmet.2024.10.020
Mol Cell. 2024 Nov 15. pii: S1097-2765(24)00877-3. [Epub ahead of print]

Nutrient control of growth and metabolism through mTORC1 regulation of mRNA splicing.

Takafumi Ogawa, Meltem Isik, Ziyun Wu, Kiran Kurmi, Jin Meng, Sungyun Cho, Gina Lee, L Paulette Fernandez-Cardenas, Masaki Mizunuma, John Blenis, Marcia C Haigis, T Keith Blackwell.

  Cellular growth and organismal development are remarkably complex processes that require the nutrient-responsive kinase mechanistic target of rapamycin complex 1 (mTORC1). Anticipating that important mTORC1 functions remained to be identified, we employed genetic and bioinformatic screening in C. elegans to uncover mechanisms of mTORC1 action. Here, we show that during larval growth, nutrients induce an extensive reprogramming of gene expression and alternative mRNA splicing by acting through mTORC1. mTORC1 regulates mRNA splicing and the production of protein-coding mRNA isoforms largely independently of its target p70 S6 kinase (S6K) by increasing the activity of the serine/arginine-rich (SR) protein RSP-6 (SRSF3/7) and other splicing factors. mTORC1-mediated mRNA splicing regulation is critical for growth; mediates nutrient control of mechanisms that include energy, nucleotide, amino acid, and other metabolic pathways; and may be conserved in humans. Although mTORC1 inhibition delays aging, mTORC1-induced mRNA splicing promotes longevity, suggesting that when mTORC1 is inhibited, enhancement of this splicing might provide additional anti-aging benefits.

Keywords:  C. elegans; SR proteins; development; gene expression; growth; human cell growth; longevity; mRNA splicing; mTORC1; metabolism; nutrient response

DOI:  https://doi.org/10.1016/j.molcel.2024.10.037
Am J Respir Cell Mol Biol. 2024 Nov 18.

Spatiotemporal Clusters of ERK Activity Coordinate Cytokine-induced Inflammatory Responses in Human Airway Epithelial Cells.

Nicholaus L DeCuzzi, Daniel Oberbauer, Kenneth J Chmiel, Michael Pargett, Justa M Ferguson, Devan Murphy, Marion Hardy, Abhineet Ram, Amir A Zeki, John G Albeck.

  Spatially coordinated ERK signaling events ("SPREADs") transmit radially from a central point to adjacent cells via secreted ligands for EGFR and other receptors. SPREADs maintain homeostasis in non-pulmonary epithelia, but it is unknown whether they play a role in the airway epithelium or are dysregulated in inflammatory disease. To address these questions, we measured SPREAD activity with live-cell ERK biosensors in human bronchial epithelial cell lines (HBE1 and 16HBE) and primary human bronchial epithelial (pHBE) cells, in both submerged and biphasic Air-Liquid Interface (ALI) culture conditions (i.e., differentiated cells). Airway epithelial cells were exposed to pro-inflammatory cytokines relevant to asthma and chronic obstructive pulmonary disease (COPD). Type 1 pro-inflammatory cytokines significantly increased the frequency of SPREADs, which coincided with epithelial barrier breakdown in differentiated pHBE cells. Furthermore, SPREADs correlated with IL-6 peptide secretion and the appearance of localized clusters of phospho-STAT3 immunofluorescence. To probe the mechanism of SPREADs, cells were co-treated with pharmacological treatments (gefitinib, tocilizumab, hydrocortisone) or metabolic modulators (insulin, 2-deoxyglucose). Hydrocortisone, inhibitors of receptor signaling, and suppression of metabolic function decreased SPREAD occurrence, implying that pro-inflammatory cytokines and glucose metabolism modulate SPREADs in human airway epithelial cells via secreted EGFR and IL6R ligands. We conclude that spatiotemporal ERK signaling plays a role in barrier homeostasis and dysfunction during inflammation of the airway epithelium. This novel signaling mechanism could be exploited clinically to supplement corticosteroid treatment for asthma and COPD.

Keywords:  forster resonance energy transfer (FRET); mitogen activated protein kinase (MAPK) , epidermal growth factor receptor (EGFR)

DOI:  https://doi.org/10.1165/rcmb.2024-0256OC
bioRxiv. 2024 Oct 29. pii: 2024.10.27.620531. [Epub ahead of print]

scMultiNODE: Integrative Model for Multi-Modal Temporal Single-Cell Data.

Jiaqi Zhang, Manav Chakravarthy, Ritambhara Singh.

Measuring single-cell genomic profiles at different timepoints enables our understanding of cell development. This understanding is more comprehensive when we perform an integrative analysis of multiple measurements (or modalities) across various developmental stages. However, obtaining such measurements from the same set of single cells is resource-intensive, restricting our ability to study them integratively. We propose an unsupervised integration model, scMultiNODE, that integrates gene expression and chromatin accessibility measurements in developing single cells while preserving cell type variations and cellular dynamics. scMultiNODE uses autoencoders to learn nonlinear low-dimensional cell representation and optimal transport to align cells across different measurements. Next, it utilizes neural ordinary differential equations to explicitly model cell development with a regularization term to learn a dynamic latent space. Our experiments on four real-world developmental single-cell datasets show that scMultiNODE can integrate temporally profiled multi-modal single-cell measurements better than existing methods that focus on cell type variations and tend to ignore cellular dynamics. We also show that scMultiNODE's joint latent space helps with the downstream analysis of single-cell development.
Availability: The data and code are publicly available at https://github.com/rsinghlab/scMultiNODE .

DOI: https://doi.org/10.1101/2024.10.27.620531
Nat Med. 2024 Nov 20.

An organotypic atlas of human vascular cells.

Sam N Barnett, Ana-Maria Cujba, Lu Yang, Ana Raquel Maceiras, Shuang Li, Veronika Kedlian, J Patrick Pett, Krzysztof Polanski, Antonio M A Miranda, Chuan Xu, James Cranley, Kazumasa Kanemaru, Michael Lee, Lukas Mach, Shani Perera, Catherine Tudor, Philomeena D Joseph, Sophie Pritchard, Rebecca Toscano-Rivalta, Kelvin Tuong, Liam Bolt, Robert Petryszak, Martin Prete, Batuhan Cakir, Alik Huseynov, Ioannis Sarropoulos, Rasheda A Chowdhury, Rasa Elmentaite, Elo Madissoon, Amanda Oliver, Lia Campos, Agnieska Brazovskaja, Tomás Gomes, Barbara Treutlein, Chang N Kim, Tomasz J Nowakowski, Kerstin B Meyer, Anna M Randi, Michela Noseda, Sarah A Teichmann.

The human vascular system, comprising endothelial (EC) and mural cells, covers a vast surface area in the body, providing a critical interface between blood and tissue environments. Functional differences exist across specific vascular beds, but their molecular determinants across tissues remain largely unknown. Here, we integrated single-cell transcriptomics data from 19 human organs and tissues, and defined 42 vascular cell states from ~67,000 cells (62 donors), including angiotypic transitional signatures along the arterial endothelial axis from large to small calibre vessels. We also characterised organotypic populations, including splenic littoral ECs and blood-brain barrier cells, thus clarifying the molecular profiles of these important cell states. Interrogating endothelial-mural cell molecular crosstalk revealed angiotypic and organotypic communication pathways related to Notch, Wnt, retinoic acid, prostaglandin, and cell adhesion signalling. Transcription factor network analysis revealed differential regulation of downstream target genes in tissue-specific modules, such as FOXF1 target genes across multiple lung vascular subpopulations. Additionally, we make mechanistic inferences of vascular drug targets within different vascular beds. This open access resource enhances our understanding of angiodiversity and organotypic molecular signatures in human vascular cells and has therapeutic implications for vascular diseases across tissues.

DOI: https://doi.org/10.1038/s41591-024-03376-x
Nature. 2024 Nov 20.

A cell atlas foundation model for scalable search of similar human cells.

Graham Heimberg, Tony Kuo, Daryle J DePianto, Omar Salem, Tobias Heigl, Nathaniel Diamant, Gabriele Scalia, Tommaso Biancalani, Shannon J Turley, Jason R Rock, Héctor Corrada Bravo, Josh Kaminker, Jason A Vander Heiden, Aviv Regev.

Single-cell RNA-seq (scRNA-seq) has profiled hundreds of millions of human cells across organs, diseases, development, and perturbations to date. Mining these growing atlases could reveal cell-disease associations, discover cell states in unexpected tissue contexts, and relate in vivo biology to in vitro models. These require a common measure of cell similarity across the body and an efficient way to search. Here, we develop SCimilarity, a metric learning framework to learn a unified and interpretable representation that enables rapid queries of tens of millions of cell profiles from diverse studies for cells that are transcriptionally similar to an input cell profile or state. We use SCimilarity to query a 23.4 million cell atlas of 412 scRNA-seq studies for macrophage and fibroblast profiles from interstitial lung disease1 and reveal similar cell profiles across other fibrotic diseases and tissues. The top scoring in vitro hit for the macrophage query was a 3D hydrogel system2, which we experimentally demonstrated reproduces this cell state. SCimilarity serves as a foundation model for single-cell profiles that enables researchers to query for similar cellular states across the human body, providing a powerful tool for generating biological insights from the Human Cell Atlas.

DOI: https://doi.org/10.1038/s41586-024-08411-y
Nature. 2024 Nov;635(8039): 657-667

A multi-omic atlas of human embryonic skeletal development.

Ken To, Lijiang Fei, J Patrick Pett, Kenny Roberts, Raphael Blain, Krzysztof Polański, Tong Li, Nadav Yayon, Peng He, Chuan Xu, James Cranley, Madelyn Moy, Ruoyan Li, Kazumasa Kanemaru, Ni Huang, Stathis Megas, Laura Richardson, Rakesh Kapuge, Shani Perera, Elizabeth Tuck, Anna Wilbrey-Clark, Ilaria Mulas, Fani Memi, Batuhan Cakir, Alexander V Predeus, David Horsfall, Simon Murray, Martin Prete, Pavel Mazin, Xiaoling He, Kerstin B Meyer, Muzlifah Haniffa, Roger A Barker, Omer Bayraktar, Alain Chédotal, Christopher D Buckley, Sarah A Teichmann.

Human embryonic bone and joint formation is determined by coordinated differentiation of progenitors in the nascent skeleton. The cell states, epigenetic processes and key regulatory factors that underlie lineage commitment of these cells remain elusive. Here we applied paired transcriptional and epigenetic profiling of approximately 336,000 nucleus droplets and spatial transcriptomics to establish a multi-omic atlas of human embryonic joint and cranium development between 5 and 11 weeks after conception. Using combined modelling of transcriptional and epigenetic data, we characterized regionally distinct limb and cranial osteoprogenitor trajectories across the embryonic skeleton and further described regulatory networks that govern intramembranous and endochondral ossification. Spatial localization of cell clusters in our in situ sequencing data using a new tool, ISS-Patcher, revealed mechanisms of progenitor zonation during bone and joint formation. Through trajectory analysis, we predicted potential non-canonical cellular origins for human chondrocytes from Schwann cells. We also introduce SNP2Cell, a tool to link cell-type-specific regulatory networks to polygenic traits such as osteoarthritis. Using osteolineage trajectories characterized here, we simulated in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential cell states and disease mechanisms. This work forms a detailed and dynamic regulatory atlas of bone and cartilage maturation and advances our fundamental understanding of cell-fate determination in human skeletal development.

DOI: https://doi.org/10.1038/s41586-024-08189-z
Nat Commun. 2024 Nov 20. 15(1): 10031

multiDGD: A versatile deep generative model for multi-omics data.

Viktoria Schuster, Emma Dann, Anders Krogh, Sarah A Teichmann.

Recent technological advancements in single-cell genomics have enabled joint profiling of gene expression and alternative modalities at unprecedented scale. Consequently, the complexity of multi-omics data sets is increasing massively. Existing models for multi-modal data are typically limited in functionality or scalability, making data integration and downstream analysis cumbersome. We present multiDGD, a scalable deep generative model providing a probabilistic framework to learn shared representations of transcriptome and chromatin accessibility. It shows outstanding performance on data reconstruction without feature selection. We demonstrate on several data sets from human and mouse that multiDGD learns well-clustered joint representations. We further find that probabilistic modeling of sample covariates enables post-hoc data integration without the need for fine-tuning. Additionally, we show that multiDGD can detect statistical associations between genes and regulatory regions conditioned on the learned representations. multiDGD is available as an scverse-compatible package on GitHub.

DOI: https://doi.org/10.1038/s41467-024-53340-z
Genes Dev. 2024 Nov 21.

mTORC1, the maestro of cell metabolism and growth.

Long He, Sungyun Cho, John Blenis.

  The mechanistic target of rapamycin (mTOR) pathway senses and integrates various environmental and intracellular cues to regulate cell growth and proliferation. As a key conductor of the balance between anabolic and catabolic processes, mTOR complex 1 (mTORC1) orchestrates the symphonic regulation of glycolysis, nucleic acid and lipid metabolism, protein translation and degradation, and gene expression. Dysregulation of the mTOR pathway is linked to numerous human diseases, including cancer, neurodegenerative disorders, obesity, diabetes, and aging. This review provides an in-depth understanding of how nutrients and growth signals are coordinated to influence mTOR signaling and the extensive metabolic rewiring under its command. Additionally, we discuss the use of mTORC1 inhibitors in various aging-associated metabolic diseases and the current and future potential for targeting mTOR in clinical settings. By deciphering the complex landscape of mTORC1 signaling, this review aims to inform novel therapeutic strategies and provide a road map for future research endeavors in this dynamic and rapidly evolving field.

Keywords:  cancer; cellular signaling; mT; mTOR complex 1; mTORC1

DOI:  https://doi.org/10.1101/gad.352084.124
Sci Rep. 2024 11 16. 14(1): 28296

Starvation-induced metabolic rewiring affects mTORC1 composition in vivo.

Kaade Edgar, Mausbach Simone, Erps Nina, Sylvester Marc, Shakeri Farhad, Ron D Jachimowicz, Gieselmann Volkmar, Thelen Melanie.

Lysosomes play a crucial role in metabolic adaptation to starvation, but detailed in vivo studies are scarce. Therefore, we investigated the changes of the proteome of liver lysosomes in mice starved short-term for 6h or long-term for 24h. We verified starvation-induced catabolism by weight loss, ketone body production, drop in blood glucose and an increase of 3-methylhistidine. Deactivation of mTORC1 in vivo after short-term starvation causes a depletion of mTORC1 and the associated Ragulator complex in hepatic lysosomes, resulting in diminished phosphorylation of mTORC1 target proteins. While mTORC1 lysosomal protein levels and activity in liver were restored after long-term starvation, the lysosomal levels of Ragulator remained constantly reduced. To determine whether this mTORC1 activity pattern may be organ-specific, we further investigated the key metabolic organs muscle and brain. mTORC1 inactivation, but not re-activation, occurred in muscle after a starvation of 12 h or longer. In brain, mTORC1 activity remained unchanged during starvation. As mTORC1 deactivation is known to induce autophagy, we further investigated the more than 150 non-lysosomal proteins enriched in the lysosomal fraction upon starvation. Proteasomal, cytosolic and peroxisomal proteins dominated after short-term starvation, while after long-term starvation, mainly proteasomal and mitochondrial proteins accumulated, indicating ordered autophagic protein degradation.

DOI: https://doi.org/10.1038/s41598-024-78873-7
Methods Mol Biol. 2025 ;2871 131-143

Measuring FOXO Nuclear Shuttling Dynamics by Fluorescence Microscopy.

Elizabeth Jose, Andrew L Paek.

  FOXO transcription factors respond to a number of different stresses by shuttling from the cytoplasm to the nucleus where they upregulate hundreds of target genes with diverse cellular functions. The cellular consequences of FOXO activation are both stress and cell-type specific. Recent evidence suggests that one way in which FOXO dictates stress-specific outcomes is through distinct nuclear/cytoplasmic shuttling dynamics. Here we outline methods for measuring FOXO nuclear shuttling dynamics using fluorescence-based reporters.

Keywords:  Cell fate; FOXO; Immunofluorescence; Nuclear to cytoplasmic shuttling; Protein dynamics; Time-lapse microscopy

DOI:  https://doi.org/10.1007/978-1-0716-4217-7_12
bioRxiv. 2024 Nov 07. pii: 2024.11.05.622163. [Epub ahead of print]

Reproducible processing of TCGA regulatory networks.

Viola Fanfani, Katherine H Shutta, Panagiotis Mandros, Jonas Fischer, Enakshi Saha, Soel Micheletti, Chen Chen, Marouen Ben Guebila, Camila M Lopes-Ramos, John Quackenbush.

Background: Technological advances in sequencing and computation have allowed deep exploration of the molecular basis of diseases. Biological networks have proven to be a useful framework for interrogating omics data and modeling regulatory gene and protein interactions. Large collaborative projects, such as The Cancer Genome Atlas (TCGA), have provided a rich resource for building and validating new computational methods resulting in a plethora of open-source software for downloading, pre-processing, and analyzing those data. However, for an end-to-end analysis of regulatory networks a coherent and reusable workflow is essential to integrate all relevant packages into a robust pipeline.
Findings: We developed tcga-data-nf, a Nextflow workflow that allows users to reproducibly infer regulatory networks from the thousands of samples in TCGA using a single command. The workflow can be divided into three main steps: multi-omics data, such as RNA-seq and methylation, are downloaded, preprocessed, and lastly used to infer regulatory network models with the netZoo software tools. The workflow is powered by the NetworkDataCompanion R package, a standalone collection of functions for managing, mapping, and filtering TCGA data. Here we show how the pipeline can be used to study the differences between colon cancer subtypes that could be explained by epigenetic mechanisms. Lastly, we provide pre-generated networks for the 10 most common cancer types that can be readily accessed.
Conclusions: tcga-data-nf is a complete yet flexible and extensible framework that enables the reproducible inference and analysis of cancer regulatory networks, bridging a gap in the current universe of software tools.

DOI: https://doi.org/10.1101/2024.11.05.622163
Pathology. 2024 Oct 16. pii: S0031-3025(24)00244-7. [Epub ahead of print]

Pathologists' integration of prior biopsies of women with germline PTEN mutations may expedite the identification of this rare cancer predisposition syndrome.

Gelareh Farshid, S Jan Ibbetson, Malcolm Pradhan, Nicholas David Manton, Andrew Dubowsky, Nicola Kazia Poplawski.

  PTEN hamartoma tumour syndrome (PHTS) is a rare cancer predisposition syndrome, caused chiefly by pathogenic and likely pathogenic (P/LP) variants in in the PTEN gene. Carriers have substantially elevated risks of various malignancies and develop benign lesions in multiple organ systems. The rarity of this disease, the decades-long unfolding of its clinical features, involvement of multiple sites and the absence of distinguishing features of each lesion hamper the identification of this condition, limiting opportunities for screening of affected individuals and their families. Given laboratory information systems are the repositories of patients' biopsies, we are interested in whether PHTS patients' prior biopsies may serve as clues to the possibility of this syndrome. With ethics committee approval, through a collaboration amongst our state-wide Adult Genetics Unit and all pathology laboratories in our state, we have undertaken a 28-year longitudinal survey (1990-2018) of the biopsy histories of 12 women known to have P/LP PTEN variants. Only one woman had a family history of Cowden syndrome, with the remaining 11 patients' mutations being discovered later. The earliest biopsy was at age 19. The most common finding was the development of multiple benign mucocutaneous lesions, with 10 women presenting with these, including a range of benign vascular lesions (eight patients), various fibromatous lesions of the skin and mucosal sites (six patients), a ganglioneuroma and a juvenile polyp. Ten women developed breast cancer, only four before the age of 40. Seven women developed a second breast cancer, two synchronously and five at intervals of 3-11 years. Other neoplasms included endometrial carcinoma (two patients) and dysplastic cerebellar gangliocytoma (three patients). Integrating the biopsy histories of PTEN P/LP variant carriers over time may assist in raising the possibility of an underlying cancer susceptibility syndrome, so appropriate clinical and genetic counselling and evaluation may be considered.

Keywords:  Cowden syndrome; PTEN; breast cancer; familial; screening

DOI:  https://doi.org/10.1016/j.pathol.2024.08.003
bioRxiv. 2024 Nov 04. pii: 2024.11.03.621734. [Epub ahead of print]

A Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells.

Sami Nourreddine, Yesh Doctor, Amir Dailamy, Antoine Forget, Yi-Hung Lee, Becky Chinn, Hammza Khaliq, Benjamin Polacco, Monita Muralidharan, Emily Pan, Yifan Zhang, Alina Sigaeva, Jan Niklas Hansen, Jiahao Gao, Jillian A Parker, Kirsten Obernier, Timothy Clark, Jake Y Chen, Christian Metallo, Emma Lundberg, Trey Ideker, Nevan Krogan, Prashant Mali.

Towards comprehensively investigating the genotype-phenotype relationships governing the human pluripotent stem cell state, we generated an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes. Using the transcriptional phenotypes, we created a minimum distortion embedding map of the pluripotent state, demonstrating rich recapitulation of protein complexes, such as strong co-clustering of MRPL, BAF, SAGA, and Ragulator family members. Additionally, we uncovered transcriptional regulators that are uncoupled from cell fitness, discovering potential novel pluripotency (JOSD1, RNF7) and metabolic factors (ZBTB41). We validated these findings via phenotypic, protein-interaction, and metabolic tracing assays. Finally, we propose a contrastive human-cell engineering framework (CHEF), a machine learning architecture that learns from perturbation cell atlases to predict perturbation recipes that achieve desired transcriptional states. Taken together, our study presents a comprehensive resource for interrogating the regulatory networks governing pluripotency.

DOI: https://doi.org/10.1101/2024.11.03.621734
Glia. 2024 Nov 19.

All the single cells: Single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists.

Katherine E Prater, Kevin Z Lin.

  Single-cell transcriptomics, epigenomics, and other 'omics applied at single-cell resolution can significantly advance hypotheses and understanding of glial biology. Omics technologies are revealing a large and growing number of new glial cell subtypes, defined by their gene expression profile. These subtypes have significant implications for understanding glial cell function, cell-cell communications, and glia-specific changes between homeostasis and conditions such as neurological disease. For many, the training in how to analyze, interpret, and understand these large datasets has been through reading and understanding literature from other fields like biostatistics. Here, we provide a primer for glial biologists on experimental design and analysis of single-cell RNA-seq datasets. Our goal is to further the understanding of why decisions are made about datasets and to enhance biologists' ability to interpret and critique their work and the work of others. We review the steps involved in single-cell analysis with a focus on decision points and particular notes for glia. The goal of this primer is to ensure that single-cell 'omics experiments continue to advance glial biology in a rigorous and replicable way.

Keywords:  RNA‐seq; analysis; glia; multiome; single‐cell; single‐nucleus; transcriptomics

DOI:  https://doi.org/10.1002/glia.24633
Dev Cell. 2024 Nov 15. pii: S1534-5807(24)00639-7. [Epub ahead of print]

Initiation and maintenance of the pluripotent epiblast in pre-implantation human development is independent of NODAL signaling.

A Sophie Brumm, Afshan McCarthy, Claudia Gerri, Todd Fallesen, Laura Woods, Riley McMahon, Athanasios Papathanasiou, Kay Elder, Phil Snell, Leila Christie, Patricia Garcia, Valerie Shaikly, Mohamed Taranissi, Paul Serhal, Rabi A Odia, Mina Vasilic, Anna Osnato, Peter J Rugg-Gunn, Ludovic Vallier, Caroline S Hill, Kathy K Niakan.

  The human blastocyst contains the pluripotent epiblast from which human embryonic stem cells (hESCs) can be derived. ACTIVIN/NODAL signaling maintains expression of the transcription factor NANOG and in vitro propagation of hESCs. It is unknown whether this reflects a functional requirement for epiblast development in human embryos. Here, we characterized NODAL signaling activity during pre-implantation human development. We showed that NANOG is an early molecular marker restricted to the nascent human pluripotent epiblast and was initiated prior to the onset of NODAL signaling. We further demonstrated that expression of pluripotency-associated transcription factors NANOG, SOX2, OCT4, and KLF17 were maintained in the epiblast in the absence of NODAL signaling activity. Genome-wide transcriptional analysis showed that NODAL signaling inhibition did not decrease NANOG transcription or impact the wider pluripotency-associated gene regulatory network. These data suggest differences in the signaling requirements regulating pluripotency in the pre-implantation human epiblast compared with existing hESC culture.

Keywords:  BMP signaling; NANOG; NODAL signaling; epiblast; human embryo; pluripotency

DOI:  https://doi.org/10.1016/j.devcel.2024.10.020
Nat Med. 2024 Nov 22.

Obesity predisposes to specific cancer driver mutations.

Karen O'Leary.



Keywords:  Cancer; Genomics; Obesity

DOI:  https://doi.org/10.1038/d41591-024-00080-8
PLoS One. 2024 ;19(11): e0313769

PTEN depletion reduces H3K27me3 levels to promote epithelial-to-mesenchymal transition in epithelial colorectal cancer cells.

Ahmed H Ghobashi, Jane W Kimani, Christopher A Ladaika, Heather M O'Hagan.

Epithelial-to-mesenchymal (EMT) transition is one of the best-known examples of tumor cell plasticity. EMT enhances cancer cell metastasis, which is the main cause of colorectal cancer (CRC)-related mortality. Therefore, understanding underlying molecular mechanisms contributing to the EMT process is crucial to finding druggable targets and more effective therapeutic approaches in CRC. In this study, we demonstrated that phosphatase and tensin homolog (PTEN) knockdown (KD) induces EMT in epithelial CRC, likely through the activation of AKT. PTEN KD modulated chromatin accessibility and reprogrammed gene transcription to mediate EMT in epithelial CRC cells. Active AKT can phosphorylate enhancer of zeste homolog 2 (EZH2) on serine 21, which switches EZH2 from a transcriptional repressor to an activator. Interestingly, PTEN KD reduced the global levels of trimethylation of histone 3 at lysine 27(H3K27me3) in an EZH2-phosphorylation-dependent manner. Additionally, EZH2 phosphorylation at serine 21 reduced the interaction of EZH2 with another polycomb repressive complex 2 (PRC2) component, suppressor of zeste 12 (SUZ12), suggesting that the reduced H3K27me3 levels in PTEN KD cells were due to a disruption of the PRC2 complex. Overall, we demonstrated that PTEN KD modulates changes in gene expression to induce the EMT process in epithelial CRC cells by phosphorylating EZH2 and activates transcription factors such as activator protein 1 (AP1).

DOI: https://doi.org/10.1371/journal.pone.0313769
Cell Death Differ. 2024 Nov 19.

KBTBD2 controls bone development by regulating IGF-1 signaling during osteoblast differentiation.

Yu Xun, Yiao Jiang, Aysha Khalid, Zeru Tian, Jonathan Rios, Zhao Zhang.

Kelch repeat and BTB (POZ) domain-containing 2 (KBTBD2) is known for its pivotal role in metabolic regulation, particularly in adipocytes. However, its significance in skeletal development has remained elusive. Here, we uncover a previously unrecognized function of KBTBD2 in bone formation. Conditional knockout of Kbtbd2 in embryonic osteochondroprogenitor cells or osteoblasts results in impaired osteogenic differentiation, leading to reduced skeletal growth and mineralization. Mechanistically, the loss of KBTBD2 during osteogenesis leads to the accumulation of p85α, a regulatory subunit encoded by phosphoinositide-3-kinase regulatory subunit 1 (Pik3r1), which exerts a potent inhibitory effect on insulin-like growth factor 1 (IGF-1)-induced activation of AKT. Moreover, our study extends the understanding of KBTBD2's relevance beyond bone biology to the context of SHORT syndrome, a rare genetic disorder marked by short stature and various physical abnormalities. We demonstrate that p85α harboring the p.(Arg649Trp) mutation, most frequently found in SHORT syndrome patients, exhibits reduced binding to KBTBD2, leading to impaired IGF-1-mediated activation of AKT. These findings reveal that KBTBD2 is essential in bone formation via regulating the IGF-1 signaling pathway and suggest loss of KBTBD2-mediated regulation of p85α as a potential mechanism for SHORT syndrome.

DOI: https://doi.org/10.1038/s41418-024-01416-0
Methods Mol Biol. 2025 ;2871 1-8

FOXO Transcription Factors: A Brief Overview.

Wolfgang Link, Bibiana I Ferreira.

  Forkhead box O (FOXO) transcription factors constitute a mammalian family of proteins, comprising FOXO1, FOXO3, FOXO4, and FOXO6. Originally recognized as downstream regulators within the insulin pathway, FOXO factors exhibit the ability to bind to diverse target gene promoters, thereby governing crucial facets of cellular homeostasis. These encompass cellular energy generation, resilience against oxidative stress, and the modulation of cell viability and proliferation. The dysregulation of FOXO proteins has been established as pivotal in metabolic disorders, human longevity, and the inhibition of tumorigenesis. Notably subject to posttranslational modifications for regulation, FOXO inactivation predominantly arises from excessive activation of their upstream modifying enzymes, presenting a plethora of potential avenues for pharmaceutical reinstatement of FOXO activity.

Keywords:  Cancer; Daf-16; FOXO1; FOXO3; FOXO4; FOXO6; Longevity; Therapeutic targets

DOI:  https://doi.org/10.1007/978-1-0716-4217-7_1
Bioinform Adv. 2024 ;4(1): vbae155

mxfda: a comprehensive toolkit for functional data analysis of single-cell spatial data.

Julia Wrobel, Alex C Soupir, Mitchell T Hayes, Lauren C Peres, Thao Vu, Andrew Leroux, Brooke L Fridley.

Summary: Technologies that produce spatial single-cell (SC) data have revolutionized the study of tissue microstructures and promise to advance personalized treatment of cancer by revealing new insights about the tumor microenvironment. Functional data analysis (FDA) is an ideal analytic framework for connecting cell spatial relationships to patient outcomes, but can be challenging to implement. To address this need, we present mxfda, an R package for end-to-end analysis of SC spatial data using FDA. mxfda implements a suite of methods to facilitate spatial analysis of SC imaging data using FDA techniques.
Availability and implementation: The mxfda R package is freely available at https://cran.r-project.org/package=mxfda and has detailed documentation, including four vignettes, available at http://juliawrobel.com/mxfda/.

DOI: https://doi.org/10.1093/bioadv/vbae155
Nat Methods. 2024 Nov 18.

A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.

Theodore Zhao, Yu Gu, Jianwei Yang, Naoto Usuyama, Ho Hin Lee, Sid Kiblawi, Tristan Naumann, Jianfeng Gao, Angela Crabtree, Jacob Abel, Christine Moung-Wen, Brian Piening, Carlo Bifulco, Mu Wei, Hoifung Poon, Sheng Wang.

Biomedical image analysis is fundamental for biomedical discovery. Holistic image analysis comprises interdependent subtasks such as segmentation, detection and recognition, which are tackled separately by traditional approaches. Here, we propose BiomedParse, a biomedical foundation model that can jointly conduct segmentation, detection and recognition across nine imaging modalities. This joint learning improves the accuracy for individual tasks and enables new applications such as segmenting all relevant objects in an image through a textual description. To train BiomedParse, we created a large dataset comprising over 6 million triples of image, segmentation mask and textual description by leveraging natural language labels or descriptions accompanying existing datasets. We showed that BiomedParse outperformed existing methods on image segmentation across nine imaging modalities, with larger improvement on objects with irregular shapes. We further showed that BiomedParse can simultaneously segment and label all objects in an image. In summary, BiomedParse is an all-in-one tool for biomedical image analysis on all major image modalities, paving the path for efficient and accurate image-based biomedical discovery.

DOI: https://doi.org/10.1038/s41592-024-02499-w
Clin Immunol. 2024 Nov 17. pii: S1521-6616(24)00509-6. [Epub ahead of print] 110400

A randomised, placebo-controlled, phase III trial of leniolisib in activated phosphoinositide 3-kinase delta (PI3Kδ) syndrome (APDS): Adolescent and adult subgroup analysis.

V Koneti Rao, Anna Šedivá, Virgil A S H Dalm, Alessandro Plebani, Catharina Schuetz, Anna Shcherbina, Antonino Trizzino, Yulia Zharankova, Alanvin Orpia, Elaine Kulm, Sharon Webster, Julia Körholz, Vassilios Lougaris, Yulia Rodina, Niall Conlon, Tanya Coulter, Jason Bradt, Anurag Relan, Gulbu Uzel.

  Activated phosphoinositide 3-kinase delta (PI3Kδ) syndrome (APDS) is an ultra-rare, progressive genetic disease, characterised by immune deficiency and dysregulation, affecting individuals from birth. In a 12-week phase III randomised placebo-controlled trial, leniolisib, a selective PI3Kδ inhibitor, was well-tolerated and met both co-primary endpoints (change from Baseline in log10-transformed sum of product of diameters of index lymph nodes and percentage of naïve/total B cells at Day 85). Here, prespecified subgroup analyses are reported in adolescents aged 12-17 years (leniolisib, n = 8; placebo, n = 4) and adults aged ≥18 (leniolisib, n = 13; placebo, n = 6). In both subgroups, leniolisib reduced lymphadenopathy (least squares mean change versus placebo: adolescents, -0.4 versus -0.1; adults, -0.3 versus 0.1) and increased the percentage of naïve B cells (least squares mean change: adolescents, 44.5 versus -16.5; adults, 28.4 versus -1.1). Leniolisib was well-tolerated in both adolescents and adults. These results show leniolisib is an effective APDS treatment in both subpopulations.

Keywords:  APDS; Adolescents; Leniolisib; PASLI; PI3Kδ inhibitor; Subgroups

DOI:  https://doi.org/10.1016/j.clim.2024.110400
Proteomics. 2024 Nov 16. e202400021

Review and Practical Guide for Getting Started With Single-Cell Proteomics.

Hsien-Jung L Lin, Kei G I Webber, Andikan J Nwosu, Ryan T Kelly.

  Single-cell proteomics (SCP) has advanced significantly in recent years, with new tools specifically designed for the preparation and analysis of single cells now commercially available to researchers. The field is sufficiently mature to be broadly accessible to any lab capable of isolating single cells and performing bulk-scale proteomic analyses. In this review, we highlight recent work in the SCP field that has significantly lowered the barrier to entry, thus providing a practical guide for those who are newly entering the SCP field. We outline the fundamental principles and report multiple paths to accomplish the key steps of a successful SCP experiment including sample preparation, separation, and mass spectrometry data acquisition and analysis. We recommend that researchers start with a label-free SCP workflow, as achieving high-quality and quantitatively accurate results is more straightforward than label-based multiplexed strategies. By leveraging these accessible means, researchers can confidently perform SCP experiments and make meaningful discoveries at the single-cell level.

Keywords:  cellular heterogeneity; data acquisition methods; liquid handling automation; sample preparation; single‐cell proteomics (SCP)

DOI:  https://doi.org/10.1002/pmic.202400021
Mol Cell. 2024 Nov 21. pii: S1097-2765(24)00879-7. [Epub ahead of print]84(22): 4257-4259

Flipping a switch on BRD4: How to control the do-it-all.

Femke A H van Hout, Anniina Vihervaara.

In this issue, Devaiah et al.1 identify JNK-catalyzed phosphorylation to convert bromodomain-containing protein 4 (BRD4) from a chromatin regulator to a transcription activator.

DOI: https://doi.org/10.1016/j.molcel.2024.10.039
Nature. 2024 Nov;635(8039): 773-775

Computational technologies of the Human Cell Atlas.

Amber Dance.



Keywords:  Biological techniques; Computational biology and bioinformatics; Genomics; Machine learning; Technology

DOI:  https://doi.org/10.1038/d41586-024-03762-y
Methods Mol Biol. 2025 ;2871 45-53

Reporter Gene Assays to Measure FOXO-Specific Transcriptional Activity.

Bruno Santos, Alba Orea-Soufi, Victor Mayoral-Varo, Wolfgang Link, Lucia Jimenez.

  The forkhead box O (FOXO) family of transcription factors translates environmental cues into precise gene expression patterns maintaining cellular equilibrium while influencing critical determinations of cell destiny and differentiation. FOXO proteins exert their effects through specific consensus binding to promoter sites within target genes. Notably, among the array of techniques available for assessing the transcriptional activity of FOXO factors, the utilization of luciferase-based reporters emerges as particularly distinctive. Luciferase, an enzyme sourced from bioluminescent organisms, instigates the oxidation of luciferin, culminating in the generation of oxyluciferin accompanied by discernible luminescence, a quantifiable event readily gauged using a luminometer. The adoption of luciferase activity as a measure in transcriptional assays is widespread due to its numerous advantages including simplicity, remarkable reproducibility, and high sensitivity. Moreover, the continuous advancements witnessed in luciferase-based vectors and measurement reagents bestow notable flexibility upon this methodology. Luciferase-based reporters offer a powerful tool for uncovering constituents within the signaling pathways governing FOXO factor function. Furthermore, these assays are also suitable for evaluating the efficacy of FOXO-targeting agents, whether they be inhibitors or activators. Here, we present a comprehensive, step-by-step elucidation of a commonly employed assay, adeptly quantifying the potential of small molecular compounds to amplify FOXO-specific transcriptional activity in U2OS cells.

Keywords:  AKT; FOXO; Luciferase; PI3K; Reporter assay; Transcriptional activity; mTOR

DOI:  https://doi.org/10.1007/978-1-0716-4217-7_5