Differential control of ageing and lifespan by isoforms and splice variants across the mTOR network

Ageing can be defined as the gradual deterioration of physiological functions, increasing the incidence of age-related disorders and the probability of death. Therefore, the term ageing not only reflects the lifespan of an organism but also refers to progressive functional impairment and disease. The nutrient-sensing kinase mTOR (mammalian target of rapamycin) is a major determinant of ageing. mTOR promotes cell growth and controls central metabolic pathways including protein biosynthesis, autophagy and glucose and lipid homoeostasis. The concept that mTOR has a crucial role in ageing is supported by numerous reports on the lifespan-prolonging effects of the mTOR inhibitor rapamycin in invertebrate and vertebrate model organisms. Dietary restriction increases lifespan and delays ageing phenotypes as well and mTOR has been assigned a major role in this process. This may suggest a causal relationship between the lifespan of an organism and its metabolic phenotype. More than 25 years after mTOR's discovery, a wealth of metabolic and ageing-related effects have been reported. In this review, we cover the current view on the contribution of the different elements of the mTOR signalling network to lifespan and age-related metabolic impairment. We specifically focus on distinct roles of isoforms and splice variants across the mTOR network. The comprehensive analysis of mouse knockout studies targeting these variants does not support a tight correlation between lifespan prolongation and improved metabolic phenotypes and questions the strict causal relationship between them

Finding new edges:systems approaches to MTOR signaling

Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult - if not impossible - to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease

mTORC1 Crosstalk With Stress Granules in Aging and Age-Related Diseases

The mechanistic target of rapamycin complex 1 (mTORC1) kinase is a master regulator of metabolism and aging. A complex signaling network converges on mTORC1 and integrates growth factor, nutrient and stress signals. Aging is a dynamic process characterized by declining cellular survival, renewal, and fertility. Stressors elicited by aging hallmarks such as mitochondrial malfunction, loss of proteostasis, genomic instability and telomere shortening impinge on mTORC1 thereby contributing to age-related processes. Stress granules (SGs) constitute a cytoplasmic non-membranous compartment formed by RNA-protein aggregates, which control RNA metabolism, signaling, and survival under stress. Increasing evidence reveals complex crosstalk between the mTORC1 network and SGs. In this review, we cover stressors elicited by aging hallmarks that impinge on mTORC1 and SGs. We discuss their interplay, and we highlight possible links in the context of aging and age-related diseases

TGFβ-signaling and FOXG1-expression are a hallmark of astrocyte lineage diversity in the murine ventral and dorsal forebrain

Heterogeneous astrocyte populations are defined by diversity in cellular environment, progenitor identity or function. Yet, little is known about the extent of the heterogeneity and how this diversity is acquired during development. To investigate the impact of TGF (transforming growth factor) β-signaling on astrocyte development in the telencephalon we deleted the TGFBR2 (transforming growth factor beta receptor 2) in early neural progenitor cells in mice using a FOXG1 (forkhead box G1)-driven CRE-recombinase. We used quantitative proteomics to characterize TGFBR2-deficient cells derived from the mouse telencephalon and identified differential protein expression of the astrocyte proteins GFAP (glial fibrillary acidic protein) and MFGE8 (milk fat globule-EGF factor 8). Biochemical and histological investigations revealed distinct populations of astrocytes in the dorsal and ventral telencephalon marked by GFAP or MFGE8 protein expression. The two subtypes differed in their response to TGFβ-signaling. Impaired TGFβ-signaling affected numbers of GFAP astrocytes in the ventral telencephalon. In contrast, TGFβ reduced MFGE8-expression in astrocytes deriving from both regions. Additionally, lineage tracing revealed that both GFAP and MFGE8 astrocyte subtypes derived partly from FOXG1-expressing neural precursor cells.Fil: Weise, Stefan Christopher. Universität Freiburg Im Breisgau; AlemaniaFil: Villarreal, Alejandro. Universität Freiburg Im Breisgau; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Heidrich, Stefanie. Universität Freiburg Im Breisgau; AlemaniaFil: Dehghanian, Fariba. University Of Isfahan; Irán. Universität Freiburg Im Breisgau; AlemaniaFil: Schachtrup, Christian. Universität Freiburg Im Breisgau; AlemaniaFil: Nestel, Sigrun. Universität Freiburg Im Breisgau; AlemaniaFil: Schwarz, Jennifer. Universität Freiburg Im Breisgau; AlemaniaFil: Thedieck, Kathrin. Universität Oldenburg; Argentina. University of Groningen; Países BajosFil: Vogel, Tanja. Universität Freiburg Im Breisgau; Alemani

The TSC Complex-mTORC1 Axis:From Lysosomes to Stress Granules and Back

The tuberous sclerosis protein complex (TSC complex) is a key integrator of metabolic signals and cellular stress. In response to nutrient shortage and stresses, the TSC complex inhibits the mechanistic target of rapamycin complex 1 (mTORC1) at the lysosomes. mTORC1 is also inhibited by stress granules (SGs), RNA-protein assemblies that dissociate mTORC1. The mechanisms of lysosome and SG recruitment of mTORC1 are well studied. In contrast, molecular details on lysosomal recruitment of the TSC complex have emerged only recently. The TSC complex subunit 1 (TSC1) binds lysosomes via phosphatidylinositol-3,5-bisphosphate [PI(3,5)P2]. The SG assembly factors 1 and 2 (G3BP1/2) have an unexpected lysosomal function in recruiting TSC2 when SGs are absent. In addition, high density lipoprotein binding protein (HDLBP, also named Vigilin) recruits TSC2 to SGs under stress. In this mini-review, we integrate the molecular mechanisms of lysosome and SG recruitment of the TSC complex. We discuss their interplay in the context of cell proliferation and migration in cancer and in the clinical manifestations of tuberous sclerosis complex disease (TSC) and lymphangioleiomyomatosis (LAM)

Proteome Coverage after Simultaneous Proteo-Metabolome Liquid-Liquid Extraction

Proteomics and metabolomics are essential in systems biology, and simultaneous proteo-metabolome liquid-liquid extraction (SPM-LLE) allows isolation of the metabolome and proteome from the same sample. Since the proteome is present as a pellet in SPM-LLE, it must be solubilized for quantitative proteomics. Solubilization and proteome extraction are critical factors in the information obtained at the proteome level. In this study, we investigated the performance of two surfactants (sodium deoxycholate (SDC), sodium dodecyl sulfate (SDS)) and urea in terms of proteome coverage and extraction efficiency of an interphase proteome pellet generated by methanol-chloroform based SPM-LLE. We also investigated how the performance differs when the proteome is extracted from the interphase pellet or by direct cell lysis. We quantified 12 lipids covering triglycerides and various phospholipid classes, and 25 polar metabolites covering central energy metabolism in chloroform and methanol extracts. Our study reveals that the proteome coverages between the two surfactants and urea for the SPM-LLE interphase pellet were similar, but the extraction efficiencies differed significantly. While SDS led to enrichment of basic proteins, which were mainly ribosomal and ribonuclear proteins, urea was the most efficient extraction agent for simultaneous proteo-metabolome analysis. The results of our study also show that the performance of surfactants for quantitative proteomics is better when the proteome is extracted through direct cell lysis rather than an interphase pellet. In contrast, the performance of urea for quantitative proteomics was significantly better when the proteome was extracted from an interphase pellet than by direct cell lysis. We demonstrated that urea is superior to surfactants for proteome extraction from SPM-LLE interphase pellets, with a particularly good performance for the extraction of proteins associated with metabolic pathways. Data are available via ProteomeXchange with identifier PXD027338.</p

Functional Proteomics Identifies Acinus L as a Direct Insulin- and Amino Acid-Dependent Mammalian Target of Rapamycin Complex 1 (mTORC1) Substrate

The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation

CGEF-1 regulates mTORC1 signaling during adult longevity and stress response in

The mechanistic target of rapamycin (mTOR) kinase is central to metabolism and growth, and has a conserved role in aging. mTOR functions in two complexes, mTORC1 and mTORC2. In diverse eukaryotes, inhibition of mTORC1 signaling increases lifespan. mTORC1 transduces anabolic signals to stimulate protein synthesis and inhibits autophagy. In this study, we demonstrate that CGEF-1, theC. eleganshomolog of the human guanine nucleotide exchange factor Dbl, is a novel binding partner of RHEB-1 and activator of mTORC1 signaling inC. elegans.cgef-1mutants display prolonged lifespan and enhanced stress resistance. The transcription factors DAF-16/FoxO and SKN-1/Nrf are required for increased longevity and stress tolerance, and induce protective gene expression incgef-1mutants. Genetic evidence indicates thatcgef-1functions in the same pathway withrheb-1, the mTOR kinaselet-363, anddaf-15/Raptor. Whencgef-1is inactivated, phosphorylation of 4E-BP, a central mTORC1 substrate for protein translation is reduced inC. elegans. Moreover, autophagy is increased uponcgef-1and mTORC1 inhibition. In addition, we show that in human cells Dbl associates with Rheb and stimulates mTORC1 downstream targets for protein synthesis suggesting that the function of CGEF-1/Dbl in the mTORC1 signaling pathway is evolutionarily conserved. These findings have important implications for mTOR functions and signaling mechanisms in aging and age-related diseases

Molecular mechanisms of mTOR regulation by stress

Tumors are prime examples of cell growth in unfavorable environments that elicit cellular stress. The high metabolic demand and insufficient vascularization of tumors cause a deficiency of oxygen and nutrients. Oncogenic mutations map to signaling events via mammalian target of rapamycin (mTOR), metabolic pathways, and mitochondrial function. These alterations have been linked with cellular stresses, in particular endoplasmic reticulum (ER) stress, hypoxia, and oxidative stress. Yet tumors survive these challenges and acquire highly energy-demanding traits, such as overgrowth and invasiveness. In this review we focus on stresses that occur in cancer cells and discuss them in the context of mTOR signaling. Of note, many tumor traits require mTOR complex 1 (mTORC1) activity, but mTORC1 hyperactivation eventually sensitizes cells to apoptosis. Thus, mTORC1 activity needs to be balanced in cancer cells. We provide an overview of the mechanisms contributing to mTOR regulation by stress and suggest a model wherein stress granules function as guardians of mTORC1 signaling, allowing cancer cells to escape stress-induced cell death

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics