Extensive regulation of metabolism and growth during the cell division cycle

Yeast cells grown in culture can spontaneously synchronize their respiration, metabolism, gene expression and cell division. Such metabolic oscillations in synchronized cultures reflect single-cell oscillations, but the relationship between the oscillations in single cells and synchronized cultures is poorly understood. To understand this relationship and the coordination between metabolism and cell division, we collected and analyzed DNA-content, gene-expression and physiological data, at hundreds of time-points, from cultures metabolically-synchronized at different growth rates, carbon sources and biomass densities. The data enabled us to extend and generalize an ensemble-average-over-phases (EAP) model that connects the population-average gene-expression of asynchronous cultures to the gene-expression dynamics in the single-cells comprising the cultures. The extended model explains the carbon-source specific growth-rate responses of hundreds of genes. Our data demonstrate that for a given growth rate, the frequency of metabolic cycling in synchronized cultures increases with the biomass density. This observation underscores the difference between metabolic cycling in synchronized cultures and in single cells and suggests entraining of the single-cell cycle by a quorum-sensing mechanism. Constant levels of residual glucose during the metabolic cycling of synchronized cultures indicate that storage carbohydrates are required to fuel not only the G1/S transition of the division cycle but also the metabolic cycle. Despite the large variation in profiled conditions and in the time-scale of their dynamics, most genes preserve invariant dynamics of coordination with each other and with the rate of oxygen consumption. Similarly, the G1/S transition always occurs at the beginning, middle or end of the high oxygen consumption phases, analogous to observations in human and drosophila cells.Comment: 34 pages, 7 figure

Decoupling growth and protein production in CHO cells:A targeted approach

Fed-batch cultures of Chinese Hamster Ovary cells have been used to produce high quantities of biotherapeutics, particularly monoclonal antibodies. However, a growing number of next-generation biotherapeutics, such as bi-specific antibodies and fusion proteins, are difficult to express using standard fed-batch processes. Decoupling cell growth and biotherapeutic production is becoming an increasingly desired strategy for the biomanufacturing industry, especially for difficult-to-express products. Cells are grown to a high cell density in the absence of recombinant protein production (the growth phase), then expression of the recombinant protein is induced and cell proliferation halted (the production phase), usually by combining an inducible gene expression system with a proliferation control strategy. Separating the growth and production phases allows cell resources to be more efficiently directed toward either growth or production, improving growth characteristics and enhancing the production of difficult to express proteins. However, current mammalian cell proliferation control methods rely on temperature shifts and chemical agents, which interact with many non-proliferation pathways, leading to variable impacts on product quality and culture viability. Synthetic biology offers an alternative approach by strategically targeting proliferation pathways to arrest cell growth but have largely remained unused in industrial bioproduction. Due to recent developments in microbial decoupling systems and advances in available mammalian cell engineering tools, we propose that the synthetic biology approach to decoupling growth and production needs revisiting

Oncogenic R132 IDH1 Mutations Limit NADPH for De Novo Lipogenesis through (D)2-Hydroxyglutarate Production in Fibrosarcoma Sells.

Neomorphic mutations in NADP-dependent isocitrate dehydrogenases (IDH1 and IDH2) contribute to tumorigenesis in several cancers. Although significant research has focused on the hypermethylation phenotypes associated with (D)2-hydroxyglutarate (D2HG) accumulation, the metabolic consequences of these mutations may also provide therapeutic opportunities. Here we apply flux-based approaches to genetically engineered cell lines with an endogenous IDH1 mutation to examine the metabolic impacts of increased D2HG production and altered IDH flux as a function of IDH1 mutation or expression. D2HG synthesis in IDH1-mutant cells consumes NADPH at rates similar to de novo lipogenesis. IDH1-mutant cells exhibit increased dependence on exogenous lipid sources for in vitro growth, as removal of medium lipids slows growth more dramatically in IDH1-mutant cells compared with those expressing wild-type or enzymatically inactive alleles. NADPH regeneration may be limiting for lipogenesis and potentially redox homeostasis in IDH1-mutant cells, highlighting critical links between cellular biosynthesis and redox metabolism

Developing Regenerative Treatments for Developmental Defects, Injuries, and Diseases Using Extracellular Matrix Collagen-Targeting Peptides.

Collagen is the most widespread extracellular matrix (ECM) protein in the body and is important in maintaining the functionality of organs and tissues. Studies have explored interventions using collagen-targeting tissue engineered techniques, using collagen hybridizing or collagen binding peptides, to target or treat dysregulated or injured collagen in developmental defects, injuries, and diseases. Researchers have used collagen-targeting peptides to deliver growth factors, drugs, and genetic materials, to develop bioactive surfaces, and to detect the distribution and status of collagen. All of these approaches have been used for various regenerative medicine applications, including neovascularization, wound healing, and tissue regeneration. In this review, we describe in depth the collagen-targeting approaches for regenerative therapeutics and compare the benefits of using the different molecules for various present and future applications

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II–III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context

Metabolic Signatures of Prostate Cancer and Renal Cell Carcinoma using High-Resolution NMR and Hyperpolarized 13C MRI

Non-invasive techniques to assess metabolic reprogramming during cancer progression can be used to improve therapeutic selection and provide an early assessment of therapeutic response or resistance in individual patients. Prior studies have shown that metabolic reprogramming plays a key role in the development of prostate cancer and renal cell carcinoma (RCC). This dissertation further elucidates the metabolic alterations that occur in treatment-resistant prostate cancer and in patient-derived models of RCC using high-resolution nuclear magnetic resonance (NMR) spectroscopy and hyperpolarized (HP) 13C magnetic resonance imaging (MRI), with the goal of identifying new non-invasive diagnostic imaging tools. Glycolysis, metabolism of pyruvate and glutamate via the tricarboxylic acid (TCA) cycle, glutaminolysis, and glutathione synthesis are upregulated in castration-resistant prostate cancer (CRPC) compared to their androgen-dependent counterparts, using human cell lines as well a treatment-driven transgenic murine model. These metabolic alterations were reversed in castration-resistant murine tumors by treatment with a secondary androgen pathway inhibitor, apalutamide, suggesting that early metabolic responses to treatment can be monitored using non-invasive imaging techniques. Furthermore, treatment-emergent small cell neuroendocrine prostate cancer, a consequence of protracted treatment with primary androgen deprivation therapy and secondary androgen pathway inhibitors, exhibits significantly upregulated glycolysis, TCA cycle metabolism of pyruvate and glutamate, and glutaminolysis, as well as significantly altered redox capacity compared to castration-resistant prostate adenocarcinoma using patient-derived xenograft models. Finally, the metabolic differences associated with the tumor microenvironment were compared between various patient-derived models of RCC, finding that RCC patient-derived xenografts (PDXs) displayed higher redox capacity and were more proliferative than cells and tissue slices derived from the PDXs and maintained ex vivo. The work presented in this dissertation suggests that a combination of HP [1-13C]pyruvate, [2-13C]pyruvate, [5-13C]glutamine, and [1-13C]dehydroascorbate can be used to distinguish advanced prostate cancer and RCC subtypes in future HP 13C MRI of patients for improved treatment selection and monitoring

Dispensability of Escherichia coli's latent pathways

Gene-knockout experiments on single-cell organisms have established that expression of a substantial fraction of genes is not needed for optimal growth. This problem acquired a new dimension with the recent discovery that environmental and genetic perturbations of the bacterium Escherichia coli are followed by the temporary activation of a large number of latent metabolic pathways, which suggests the hypothesis that temporarily activated reactions impact growth and hence facilitate adaptation in the presence of perturbations. Here we test this hypothesis computationally and find, surprisingly, that the availability of latent pathways consistently offers no growth advantage, and tends in fact to inhibit growth after genetic perturbations. This is shown to be true even for latent pathways with a known function in alternate conditions, thus extending the significance of this adverse effect beyond apparently nonessential genes. These findings raise the possibility that latent pathway activation is in fact derivative of another, potentially suboptimal, adaptive response