bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2024‒10‒20
23 papers selected by
Ralitsa Radostinova Madsen, MRC-PPU



  1. bioRxiv. 2024 Oct 13. pii: 2024.10.08.617313. [Epub ahead of print]
      Single-cell tissue atlases commonly use RNA abundances as surrogates for protein abundances. Yet, protein abundance also depends on the regulation of protein synthesis and degradation rates. To estimate the contributions of such post transcriptional regulation, we quantified the proteomes of 5,883 single cells from human testis using 3 distinct mass spectrometry methods (SCoPE2, pSCoPE, and plexDIA). To distinguish between biological and technical factors contributing to differences between protein and RNA levels, we developed BayesPG , a Bayesian model of transcript and protein abundance that systematically accounts for technical variation and infers biological differences. We use BayesPG to jointly model RNA and protein data collected from 29,709 single cells across different methods and datasets. BayesPG estimated consensus mRNA and protein levels for 3,861 gene products and quantified the relative protein-to-mRNA ratio (rPTR) for each gene across six distinct cell types in samples from human testis. About 28% of the gene products exhibited significant differences at protein and RNA levels and contributed to about 1, 500 significant GO groups. We observe that specialized and context specific functions, such as those related to spermatogenesis are regulated after transcription. Among hundreds of detected post translationally modified peptides, many show significant abundance differences across cell types. Furthermore, some phosphorylated peptides covary with kinases in a cell-type dependent manner, suggesting cell-type specific regulation. Our results demonstrate the potential of inferring protein regulation in from single-cell proteogenomic data and provide a generalizable model, BayesPG , for performing such analyses.
    DOI:  https://doi.org/10.1101/2024.10.08.617313
  2. bioRxiv. 2024 Oct 11. pii: 2024.10.07.617121. [Epub ahead of print]
      Tuberous Sclerosis Complex (TSC), an autosomal dominant condition, is caused by heterozygous mutations in either the TSC1 or TSC2 genes, manifesting in systemic growth of benign tumors. In addition to brain lesions, neurologic sequelae represent the greatest morbidity in TSC patients. Investigations utilizing TSC1/2 -knockout animal or human stem cell models suggest that TSC deficiency-causing hyper-activation of mTOR signaling might precipitate anomalous neurodevelopmental processes. However, how the pathogenic variants of TSC1/2 genes affect the longitudinal trajectory of human brain development remains largely unexplored. Here, we employed 3-dimensional cortical organoids derived from induced pluripotent stem cells (iPSCs) from TSC patients harboring TSC2 variants, alongside organoids from age- and sex-matched healthy individuals as controls. Through comprehensively longitudinal molecular and cellular analyses of TSC organoids, we found that TSC2 pathogenic variants dysregulate neurogenesis, synaptogenesis, and gliogenesis, particularly for reactive astrogliosis. The altered developmental trajectory of TSC organoids significantly resembles the molecular signatures of neuropsychiatric disorders, including autism spectrum disorders, epilepsy, and intellectual disability. Intriguingly, single cell transcriptomic analyses on TSC organoids revealed that TSC2 pathogenic variants disrupt the neuron/reactive astrocyte crosstalk within the NLGN-NRXN signaling network. Furthermore, cellular and electrophysiological assessments of TSC cortical organoids, along with proteomic analyses of synaptosomes, demonstrated that the TSC2 variants precipitate perturbations in synaptic transmission, neuronal network activity, mitochondrial translational integrity, and neurofilament formation. Notably, similar perturbations were observed in surgically resected cortical specimens from TSC patients. Collectively, our study illustrates that disease-associated TSC2 variants disrupt the neurodevelopmental trajectories through perturbations of gene regulatory networks during early cortical development, leading to mitochondrial dysfunction, aberrant neurofilament formation, impaired synaptic formation and neuronal network activity.
    DOI:  https://doi.org/10.1101/2024.10.07.617121
  3. Cell Syst. 2024 Oct 16. pii: S2405-4712(24)00275-8. [Epub ahead of print]15(10): 893-894
      In single-cell omics studies, data are typically collected across multiple batches, resulting in batch effects: technical confounders that introduce noise and distort data distribution. Correcting these effects is challenging due to their unknown sources, nonlinear distortions, and the difficulty of accurately assigning data to batches that are optimal for integration methods.
    DOI:  https://doi.org/10.1016/j.cels.2024.09.011
  4. ArXiv. 2024 Sep 18. pii: arXiv:2409.11654v1. [Epub ahead of print]
      The cell is arguably the smallest unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells. Here we propose a vision of AI-powered Virtual Cells, where robust representations of cells and cellular systems under different conditions are directly learned from growing biological data across measurements and scales. We discuss desired capabilities of AI Virtual Cells, including generating universal representations of biological entities across scales, and facilitating interpretable in silico experiments to predict and understand their behavior using Virtual Instruments. We further address the challenges, opportunities and requirements to realize this vision including data needs, evaluation strategies, and community standards and engagement to ensure biological accuracy and broad utility. We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration. With open science collaborations across the biomedical ecosystem that includes academia, philanthropy, and the biopharma and AI industries, a comprehensive predictive understanding of cell mechanisms and interactions is within reach.
  5. Nature. 2024 Oct 16.
      
    Keywords:  Chemical biology; Diabetes; Drug discovery
    DOI:  https://doi.org/10.1038/d41586-024-03357-7
  6. EMBO Mol Med. 2024 Oct 14.
      Cerebral cavernous malformations (CCMs) are anomalies of the cerebral vasculature. Loss of the CCM proteins CCM1/KRIT1, CCM2, or CCM3/PDCD10 trigger a MAPK-Krüppel-like factor 2 (KLF2) signaling cascade, which induces a pathophysiological pattern of gene expression. The downstream target genes that are activated by KLF2 are mostly unknown. Here we show that Chromobox Protein Homolog 7 (CBX7), component of the Polycomb Repressive Complex 1, contributes to pathophysiological KLF2 signaling during zebrafish cardiovascular development. CBX7/cbx7a mRNA is strongly upregulated in lesions of CCM patients, and in human, mouse, and zebrafish CCM-deficient endothelial cells. The silencing or pharmacological inhibition of CBX7/Cbx7a suppresses pathological CCM phenotypes in ccm2 zebrafish, CCM2-deficient HUVECs, and in a pre-clinical murine CCM3 disease model. Whole-transcriptome datasets from zebrafish cardiovascular tissues and human endothelial cells reveal a role of CBX7/Cbx7a in the activation of KLF2 target genes including TEK, ANGPT1, WNT9, and endoMT-associated genes. Our findings uncover an intricate interplay in the regulation of Klf2-dependent biomechanical signaling by CBX7 in CCM. This work also provides insights for therapeutic strategies in the pathogenesis of CCM.
    Keywords:  CBX7; Cerebral Cavernous Malformation; KLF2; WNT9; endoMT
    DOI:  https://doi.org/10.1038/s44321-024-00152-9
  7. Nat Commun. 2024 Oct 17. 15(1): 8966
      Pluripotent stem cells have remarkable self-renewal capacity: the ability to proliferate indefinitely while maintaining the pluripotent identity essential for their ability to differentiate into almost any cell type in the body. To investigate the interplay between these two aspects of self-renewal, we perform four parallel genome-scale CRISPR-Cas9 loss-of-function screens interrogating stem cell fitness in hPSCs and the dissolution of primed pluripotent identity during early differentiation. These screens distinguish genes with distinct roles in pluripotency regulation, including mitochondrial and metabolism regulators crucial for stem cell fitness, and chromatin regulators that control pluripotent identity during early differentiation. We further identify a core set of genes controlling both stem cell fitness and pluripotent identity, including a network of chromatin factors. Here, unbiased screening and comparative analyses disentangle two interconnected aspects of pluripotency, provide a valuable resource for exploring pluripotent stem cell identity versus cell fitness, and offer a framework for categorizing gene function.
    DOI:  https://doi.org/10.1038/s41467-024-53284-4
  8. Nat Genet. 2024 Oct 18.
      Drug resistance is a principal limitation to the long-term efficacy of cancer therapies. Cancer genome sequencing can retrospectively delineate the genetic basis of drug resistance, but this requires large numbers of post-treatment samples to nominate causal variants. Here we prospectively identify genetic mechanisms of resistance to ten oncology drugs from CRISPR base editing mutagenesis screens in four cancer cell lines using a guide RNA library predicted to install 32,476 variants in 11 cancer genes. We identify four functional classes of protein variants modulating drug sensitivity and use single-cell transcriptomics to reveal how these variants operate through distinct mechanisms, including eliciting a drug-addicted cell state. We identify variants that can be targeted with alternative inhibitors to overcome resistance and functionally validate an epidermal growth factor receptor (EGFR) variant that sensitizes lung cancer cells to EGFR inhibitors. Our variant-to-function map has implications for patient stratification, therapy combinations and drug scheduling in cancer treatment.
    DOI:  https://doi.org/10.1038/s41588-024-01948-8
  9. bioRxiv. 2024 Oct 12. pii: 2024.10.11.617908. [Epub ahead of print]
      The intensity and duration of biological signals encode information that allows a few pathways to regulate a wide array of cellular behaviors. Despite the central importance of signaling in biomedical research, our ability to quantify it in individual cells over time remains limited. Here, we introduce INSCRIBE, an approach for reconstructing signaling history in single cells using endpoint fluorescence images. By regulating a CRISPR base editor, INSCRIBE generates mutations in genomic target sequences, at a rate proportional to signaling activity. The number of edits is then recovered through a novel ratiometric readout strategy, from images of two fluorescence channels. We engineered human cell lines for recording WNT and BMP pathway activity, and demonstrated that INSCRIBE faithfully recovers both the intensity and duration of signaling. Further, we used INSCRIBE to study the variability of cellular response to WNT and BMP stimulation, and test whether the magnitude of response is a stable, heritable trait. We found a persistent memory in the BMP pathway. Progeny of cells with higher BMP response levels are likely to respond more strongly to a second BMP stimulation, up to 3 weeks later. Together, our results establish a scalable platform for genetic recording and in situ readout of signaling history in single cells, advancing quantitative analysis of cell-cell communication during development and disease.
    DOI:  https://doi.org/10.1101/2024.10.11.617908
  10. bioRxiv. 2024 Oct 13. pii: 2024.10.11.617852. [Epub ahead of print]
      Hippo-YAP signaling orchestrates epithelial tissue repair and is therefore an attractive target in regenerative medicine. Yet it is unresolved how YAP controls the underlying transient proliferative response. Here we show that YAP-TEAD activation increases the nuclear cyclin D1/p27 protein ratio in G1 phase, towards a threshold level that dictates whether individual cells enter or exit the cell cycle. YAP increases this ratio indirectly, by increasing EGFR and other receptor activities that signal primarily through ERK. Conversely, contact inhibition suppresses YAP activity which gradually downregulates mitogen signaling and the cyclin D1/p27 ratio. Increasing YAP activity by ablating the suppressor Merlin/NF2 reveals a robust balancing mechanism in which YAP can still be inhibited after cell division further increases local cell density. Thus, critical for tissue repair, the proliferation response is intrinsically transient since the YAP-induced and mitogen-mediated increase in the cyclin D1/p27 ratio is reliably reversed through delayed contact inhibition of YAP.HIGHLIGHTS: YAP signaling controls cell cycle entry and exit by up- and down-regulating the cyclin D1/p27 ratio above and below a conserved thresholdYAP-induced proliferation is intrinsically transient since contact inhibition of YAP suppresses EGFR signaling after a delay to reduce this cyclin D1/p27 ratioYAP can still be robustly inhibited after Merlin/NF2 ablation but only at higher local cell densityThe YAP-regulated cyclin D1/p27 ratio is primarily controlled by MEK-ERK rather than mTOR activity.
    DOI:  https://doi.org/10.1101/2024.10.11.617852
  11. Mol Cell Endocrinol. 2024 Oct 15. pii: S0303-7207(24)00243-0. [Epub ahead of print] 112387
      OBJECTIVES: The insulin receptor (IR) and insulin like growth factor-1 receptor (IGF-1R) are heterodimers consisting of two extracellular α-subunits and two transmembrane β -subunits. Insulin αβ and insulin like growth factor-1 αβ hemi-receptors can heterodimerize to form hybrids composed of one IR αβ and one IGF-1R αβ. The function of hybrids in the endothelium is unclear. We sought insight by developing a small molecule capable of reducing hybrid formation in endothelial cells.METHODS: We performed a high-throughput small molecule screening, based on a homology model of the apo hybrid structure. Endothelial cells were studied using western blotting and qPCR to determine the effects of small molecules that reduced hybrid formation.
    RESULTS: Our studies unveil a first-in-class quinoline-containing heterocyclic small molecule that reduces hybrids by >50% in human umbilical vein endothelial cells (HUVECs) with no effects on IR or IGF-1R. This small molecule reduced expression of the negative regulatory p85α subunit of phosphatidylinositol 3-kinase, increased basal phosphorylation of the downstream target Akt and enhanced insulin/insulin-like growth factor-1 and shear stress-induced serine phosphorylation of Akt. In primary saphenous vein endothelial cells (SVEC) from patients with type 2 diabetes mellitus undergoing coronary artery bypass (CABG) surgery, hybrid receptor expression was greater than in patients without type 2 diabetes mellitus. The small molecule significantly reduced hybrid expression in SVEC from patients with type 2 diabetes mellitus.
    CONCLUSIONS: We identified a small molecule that decreases the formation of IR: IGF-1R hybrid receptors in human endothelial cells, without significant impact on the overall expression of IR or IGF-1R. In HUVECs, reduction of IR: IGF-1R hybrid receptors leads to an increase in insulin-induced serine phosphorylation of the critical downstream signalling kinase, Akt. The underpinning mechanism appears, at least in part to involve the attenuation of the inhibitory effect of IR: IGF-1R hybrid receptors on PI3-kinase signalling.
    Keywords:  diabetes; hybrid receptors; insulin receptors; insulin-like growth factor-1 receptors; small molecule.
    DOI:  https://doi.org/10.1016/j.mce.2024.112387
  12. bioRxiv. 2024 Sep 26. pii: 2024.09.25.614853. [Epub ahead of print]
      Epidermal growth factor receptor ligands (EGFRLs) consist of seven proteins. In stark contrast to the amassed knowledge concerning the epidermal growth factor receptors themselves, the extracellular dynamics of individual EGFRLs remain elusive. Here, employing fluorescent probes and a tool for triggering ectodomain shedding of EGFRLs, we show that EREG, a low-affinity EGFRL, exhibits the most rapid and efficient activation of EGFR in confluent epithelial cells and mouse epidermis. In Madin-Darby canine kidney (MDCK) renal epithelial cells, EGFR- and ERK-activation waves propagate during collective cell migration in an ADAM17 sheddase- and EGFRL-dependent manner. Upon induction of EGFRL shedding, radial ERK activation waves were observed in the surrounding receiver cells. Notably, the low-affinity ligands EREG and AREG mediated faster and broader ERK waves than the high-affinity ligands. The integrity of tight/adherens junctions was essential for the propagation of ERK activation, implying that the tight intercellular spaces prefer the low-affinity EGFRL to the high-affinity ligands for efficient signal transmission. To validate this observation in vivo , we generated EREG-deficient mice expressing the ERK biosensor and found that ERK wave propagation and cell migration were impaired during skin wound repair. In conclusion, we have quantitatively demonstrated the distinctions among EGFRLs in shedding, diffusion, and target cell activation in physiological contexts. Our findings underscore the pivotal role of low-affinity EGFRLs in rapid intercellular signal transmission.
    DOI:  https://doi.org/10.1101/2024.09.25.614853
  13. Bio Protoc. 2024 Oct 05. 14(19): e5077
      Phosphoinositides are rare membrane lipids that mediate cell signaling and membrane dynamics. PI(4)P and PI(3)P are two major phosphoinositides crucial for endolysosomal functions and dynamics, making them the lipids of interest in many studies. The acute modulation of phosphoinositides at a given organelle membrane can reveal important insights into their cellular function. Indeed, the localized depletion of PI(4)P and PI(3)P is a viable tool to assess the importance of these phosphoinositides in various experimental conditions. Here, we describe a live imaging method to acutely deplete PI(4)P and PI(3)P on endolysosomes. The depletion assay utilizes the GAI-GID1 or the FRB-FKBP inducible dimerization system to target the catalytic domain of the PI(4)P phosphatase, Sac1, or the PI(3)P phosphatase domain of MTM1 to the endolysosome for localized depletion of these phosphoinositides. By using the fluorescently tagged biosensors, 2xP4M and PX, we can validate and monitor the depletion of PI(4)P and PI(3)P, respectively, on endolysosomes in real-time. We discuss a method for normalizing the fluorescence measurements to appropriate the relative amount of these phosphoinositides in the organellar membranes (endolysosomes), which is required for monitoring PI(4)P or PI(3)P levels during the acute depletion assay. Since the localization of the dimerization partners is specified by the membrane targeting signal, our protocol will be useful for studying the signaling and functions of phosphoinositides at any membrane. Key features • Acute depletion and real-time monitoring of PI(3)P and PI(4)P on the endolysosomal membrane using chemically inducible dimerization systems. • Modifiable and adaptable to modulate other phosphoinositides on different organellar membranes.
    Keywords:  Chemically inducible dimerization system; Endolysosomes; High-resolution fluorescence microscopy; Live-cell imaging; PI(4)P; Phosphoinositides
    DOI:  https://doi.org/10.21769/BioProtoc.5078
  14. Nature. 2024 Oct 16.
      
    Keywords:  Chemical biology; Diabetes; Metabolism
    DOI:  https://doi.org/10.1038/d41586-024-03286-5
  15. Mol Cell. 2024 Oct 10. pii: S1097-2765(24)00779-2. [Epub ahead of print]
      Macrophages induce the expression of hundreds of genes in response to immune threats. However, current technology limits our ability to capture single-cell inducible gene expression dynamics. Here, we generated high-resolution time series single-cell RNA sequencing (scRNA-seq) data from mouse macrophages responding to six stimuli, and imputed ensembles of real-time single-cell gene expression trajectories (scGETs). We found that dynamic information contained in scGETs substantially contributes to macrophage stimulus-response specificity (SRS). Dynamic information also identified correlations between immune response genes, indicating biological coordination. Furthermore, we showed that the microenvironmental context of polarizing cytokines profoundly affects scGETs, such that measuring response dynamics offered clearer discrimination of the polarization state of individual macrophage cells than single time-point measurements. Our findings highlight the important contribution of dynamic information contained in the single-cell expression responses of immune genes in characterizing the SRS and functional states of macrophages.
    Keywords:  context dependence; dynamics; gene expression trajectories; inducible gene expression; information theory; machine learning; macrophage; single cell; stimulus-response specificity; trajectory ensembles
    DOI:  https://doi.org/10.1016/j.molcel.2024.09.023
  16. J Cell Biol. 2024 Dec 02. pii: e202309090. [Epub ahead of print]223(12):
      Excess dietary intake of saturated fatty acids (SFAs) induces glucose intolerance and metabolic disorders. In contrast, unsaturated fatty acids (UFAs) elicit beneficial effects on insulin sensitivity. However, it remains elusive how SFAs and UFAs signal differentially toward insulin signaling to influence glucose homeostasis. Here, using a croaker model, we report that dietary palmitic acid (PA), but not oleic acid or linoleic acid, leads to dysregulation of mTORC1, which provokes systemic insulin resistance. Mechanistically, we show that PA profoundly elevates acetyl-CoA derived from mitochondrial fatty acid β oxidation to intensify Tip60-mediated Rheb acetylation, which triggers mTORC1 activation by promoting the interaction between Rheb and FKBPs. Subsequently, hyperactivation of mTORC1 enhances IRS1 serine phosphorylation and inhibits TFEB-mediated IRS1 transcription, inducing impairment of insulin signaling. Collectively, our results reveal a conserved molecular insight into the mechanism by which Tip60-mediated Rheb acetylation induces mTORC1 activation and insulin resistance under the PA condition, which may provide therapeutic avenues to intervene in the development of T2D.
    DOI:  https://doi.org/10.1083/jcb.202309090
  17. Dev Cell. 2024 Oct 10. pii: S1534-5807(24)00543-4. [Epub ahead of print]
      Gene-expression noise can influence cell-fate choices across pathology and physiology. However, a crucial question persists: do regulatory proteins or pathways exist that control noise independently of mean expression levels? Our integrative approach, combining single-cell RNA sequencing with proteomics and regulator enrichment analysis, identifies 32 putative noise regulators. SON, a nuclear speckle-associated protein, alters transcriptional noise without changing mean expression levels. Furthermore, SON's noise control can propagate to the protein level. Long-read and total RNA sequencing shows that SON's noise control does not significantly change isoform usage or splicing efficiency. Moreover, SON depletion reduces state switching in pluripotent mouse embryonic stem cells and impacts their fate choice during differentiation. Collectively, we demonstrate a class of proteins that control noise orthogonally to mean expression levels. This work serves as a proof of concept that can identify other functional noise regulators throughout development and disease progression.
    Keywords:  SON; cell fate choice; differentiation; embryonic stem cells; gene-expression variability; mRNA processing; noise regulation; single-cell transcriptomics; stochastic noise
    DOI:  https://doi.org/10.1016/j.devcel.2024.09.015
  18. Nucleic Acids Res. 2024 Oct 17. pii: gkae901. [Epub ahead of print]
      A wealth of high-throughput biological data, of which omics constitute a significant fraction, has been made publicly available in repositories over the past decades. These data come in various formats and cover a range of species and research areas providing insights into the complexities of biological systems; the public repositories hosting these data serve as multifaceted resources. The potentially greater value of these data lies in their secondary utilization as the deployment of data science and artificial intelligence in biology advances. Here, we critically evaluate challenges in secondary data use, focusing on omics data of human embryonic kidney cell lines available in public repositories. The emerging issues are obstacles faced by secondary data users across diverse domains as they concern platforms and repositories, which accept deposition of data irrespective of their species type. The evolving landscape of data-driven research in biology prompts re-evaluation of open access data curation and submission procedures to ensure that these challenges do not impede novel research opportunities through data exploitation. This paper aims to draw attention to widespread issues with data reporting and encourages data owners to meticulously curate submissions to maximize not only their immediate research impact but also the long-term legacy of datasets.
    DOI:  https://doi.org/10.1093/nar/gkae901
  19. Trends Endocrinol Metab. 2024 Oct 16. pii: S1043-2760(24)00253-4. [Epub ahead of print]
      
    DOI:  https://doi.org/10.1016/j.tem.2024.09.001
  20. Nature. 2024 Oct 16.
      The risk of inducing hypoglycaemia (low blood glucose) constitutes the main challenge associated with insulin therapy for diabetes1,2. Insulin doses must be adjusted to ensure that blood glucose values are within the normal range, but matching insulin doses to fluctuating glucose levels is difficult because even a slightly higher insulin dose than needed can lead to a hypoglycaemic incidence, which can be anything from uncomfortable to life-threatening. It has therefore been a long-standing goal to engineer a glucose-sensitive insulin that can auto-adjust its bioactivity in a reversible manner according to ambient glucose levels to ultimately achieve better glycaemic control while lowering the risk of hypoglycaemia3. Here we report the design and properties of NNC2215, an insulin conjugate with bioactivity that is reversibly responsive to a glucose range relevant for diabetes, as demonstrated in vitro and in vivo. NNC2215 was engineered by conjugating a glucose-binding macrocycle4 and a glucoside to insulin, thereby introducing a switch that can open and close in response to glucose and thereby equilibrate insulin between active and less-active conformations. The insulin receptor affinity for NNC2215 increased 3.2-fold when the glucose concentration was increased from 3 to 20 mM. In animal studies, the glucose-sensitive bioactivity of NNC2215 was demonstrated to lead to protection against hypoglycaemia while partially covering glucose excursions.
    DOI:  https://doi.org/10.1038/s41586-024-08042-3
  21. Diabetologia. 2024 Oct 18.
    Metabol Study Group
      AIMS/HYPOTHESIS: Metabolic disorders associated with abdominal obesity, dyslipidaemia, arterial hypertension and hyperglycaemia are risk factors for the development of insulin resistance. Extracellular vesicles (EVs) may play an important role in the regulation of metabolic signalling pathways in insulin resistance and associated complications.METHODS: Circulating large EVs (lEVs) and small EVs (sEVs) from individuals with (IR group) and without insulin resistance (n-IR group) were isolated and characterised. lEVs and sEVs were administered by i.v. injection to mice and systemic, adipose tissue and liver insulin signalling were analysed. The role of phosphatases was analysed in target tissues and cells.
    RESULTS: Injection of lEVs and sEVs from IR participants impaired systemic, adipose tissue and liver insulin signalling in mice, while EVs from n-IR participants had no effect. Moreover, lEVs and sEVs from IR participants brought about a twofold increase in adipocyte size and adipogenic gene expression. EVs from IR participants expressed two types of phosphatases, phosphotyrosine 1 phosphatase (PTP1B) and protein phosphatase 2 (PP2A), IR lEVs being enriched with the active form of PTP1B while IR sEVs mainly carried active PP2A. Blockade of PTP1B activity in IR lEVs fully restored IRS1 and Akt phosphorylation in adipocytes and blunted insulin-induced Akt phosphorylation by inhibition of the macrophage secretome in hepatocytes. Conversely, blockade of PP2A activity in IR sEVs completely prevented insulin resistance in adipocytes and hepatocytes.
    CONCLUSIONS/INTERPRETATION: These data demonstrate that inhibition of phosphatases carried by EVs from IR participants rescues insulin signalling in adipocytes and hepatocytes and point towards PTP1B and PP2A carried by IR EVs as being novel potential therapeutic targets against insulin resistance in adipose tissue and liver and the development of obesity.
    Keywords:  Adipose tissue; Extracellular vesicles; Insulin resistance; Liver; Phosphatases
    DOI:  https://doi.org/10.1007/s00125-024-06288-0
  22. bioRxiv. 2024 Oct 13. pii: 2024.10.12.618047. [Epub ahead of print]
      Lysosome positioning, or lysosome cellular distribution, is critical for lysosomal functions in response to both extracellular and intracellular cues. Amino acids, as essential nutrients, have been shown to promote lysosome movement toward the cell periphery. Peripheral lysosomes are involved in processes such as lysosomal exocytosis, cell migration, and metabolic signaling-functions that are particularly important for cancer cell motility and growth. However, the specific types of amino acids that regulate lysosome positioning, their underlying mechanisms, and their connection to amino acid-regulated metabolic signaling remain poorly understood. In this study, we developed a high-content imaging system for unbiased, quantitative analysis of lysosome positioning. We examined the 15 amino acids present in cell culture media and found that 10 promoted lysosome redistribution toward the cell periphery to varying extents, with aromatic amino acids showing the strongest effect. This redistribution was mediated by promoting outward transport through SLC38A9-BORC-kinesin 1/3 axis and simultaneously reducing inward transport via inhibiting the recruitment of Rab7 and JIP4 onto lysosomes. When examining the effects of amino acids on mTOR activation-a central regulator of cell metabolism-we found that the amino acids most strongly promoting lysosome dispersal, such as phenylalanine, did not activate mTOR on their own. However, combining phenylalanine with arginine, which activates mTOR without affecting lysosome positioning, synergistically enhanced mTOR activity. This synergy was lost when lysosomes failed to localize to the cell periphery, as observed in kinesin 1/3 knockout (KO) cells. Furthermore, breast cancer cells exhibited heightened sensitivity to phenylalanine-induced lysosome dispersal compared to noncancerous breast cells. Inhibition of LAT1, the amino acid transporter responsible for phenylalanine uptake, reduced peripheral lysosomes and impaired cancer cell migration and proliferation, highlighting the importance of lysosome positioning in these coordinated cellular activities. In summary, amino acid-regulated lysosome positioning and mTOR signaling depend on distinct sets of amino acids. Combining lysosome-dispersing amino acids with mTOR-activating amino acids synergistically enhances mTOR activation, which may be particularly relevant in cancer cells.
    DOI:  https://doi.org/10.1101/2024.10.12.618047
  23. BMC Bioinformatics. 2024 Oct 18. 25(1): 334
      Traditional gene set enrichment analyses are typically limited to a few ontologies and do not account for the interdependence of gene sets or terms, resulting in overcorrected p-values. To address these challenges, we introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. mulea employs a progressive empirical false discovery rate (eFDR) method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains. This flexibility enables researchers to tailor enrichment analysis to their specific questions, such as identifying enriched transcriptional regulators in gene expression data or overrepresented protein domains in protein sets. To facilitate seamless analysis, mulea provides gene sets (in standardised GMT format) for 27 model organisms, covering 22 ontology types from 16 databases and various identifiers resulting in almost 900 files. Additionally, the muleaData ExperimentData Bioconductor package simplifies access to these pre-defined ontologies. Finally, mulea's architecture allows for easy integration of user-defined ontologies, or GMT files from external sources (e.g., MSigDB or Enrichr), expanding its applicability across diverse research areas. mulea is distributed as a CRAN R package downloadable from https://cran.r-project.org/web/packages/mulea/ and https://github.com/ELTEbioinformatics/mulea . It offers researchers a powerful and flexible toolkit for functional enrichment analysis, addressing limitations of traditional tools with its progressive eFDR and by supporting a variety of ontologies. Overall, mulea fosters the exploration of diverse biological questions across various model organisms.
    Keywords:  False discovery rate; GMT files; Gene set enrichment; Ontologies; Overrepresentation analysis; R package
    DOI:  https://doi.org/10.1186/s12859-024-05948-7