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The Warburg effect is the long-standing riddle of cancer biology. How does aerobic glycolysis, inefficient in producing ATP, confer a growth advantage to cancer cells? A new evaluation of a large set of literature findings covering the Warburg effect and its yeast counterpart, the Crabtree effect, led to an innovative working hypothesis presented here. It holds that enhanced glycolysis partially inactivates oxidative phosphorylation to induce functional rewiring of a set of TCA cycle enzymes to generate new non-canonical metabolic pathways that sustain faster growth rates. The hypothesis has been structured by constructing two metabolic maps, one for cancer metabolism and the other for the yeast Crabtree effect. New lines of investigation, suggested by these maps, are discussed as instrumental in leading toward a better understanding of cancer biology in order to allow the development of more efficient metabolism-targeted anticancer drugs. [ABSTRACT FROM AUTHOR]

Highlights: [•] We briefly review the role of astrocytes in brain function. [•] We review the main pathways in astrocytic dysfunction. [•] We focus on astroglial-specific targets for clinical management of neurodegenerative disorders. [•] We describe the usefulness of a systems biology approach in drug discovery for neurodegenerative disorders. [Copyright &y& Elsevier]

Abstract: In this review we summarize the major connections between cell growth and cell cycle in the model eukaryote Saccharomyces cerevisiae. In S. cerevisiae regulation of cell cycle progression is achieved predominantly during a narrow interval in the late G1 phase known as START (Pringle and Hartwell, 1981). At START a yeast cell integrates environmental and internal signals (such as nutrient availability, presence of pheromone, attainment of a critical size, status of the metabolic machinery) and decides whether to enter a new cell cycle or to undertake an alternative developmental program. Several signaling pathways, that act to connect the nutritional status to cellular actions, are briefly outlined. A Growth & Cycle interaction network has been manually curated. More than one fifth of the edges within the Growth & Cycle network connect Growth and Cycle proteins, indicating a strong interconnection between the processes of cell growth and cell cycle. The backbone of the Growth & Cycle network is composed of middle-degree nodes suggesting that it shares some properties with HOT networks. The development of multi-scale modeling and simulation analysis will help to elucidate relevant central features of growth and cycle as well as to identify their system-level properties. Confident collaborative efforts involving different expertises will allow to construct consensus, integrated models effectively linking the processes of cell growth and cell cycle, ultimately contributing to shed more light also on diseases in which an altered proliferation ability is observed, such as cancer. [Copyright &y& Elsevier]

Abstract: Following a brief description of the operational procedures of systems biology (SB), the cell cycle of budding yeast is discussed as a successful example of a top-down SB analysis. After the reconstruction of the steps that have led to the identification of a sizer plus timer network in the G1 to S transition, it is shown that basic functions of the cell cycle (the setting of the critical cell size and the accuracy of DNA replication) are system-level properties, detected only by integrating molecular analysis with modelling and simulation of their underlying networks. A detailed network structure of a second relevant regulatory step of the cell cycle, the exit from mitosis, derived from extensive data mining, is constructed and discussed. To reach a quantitative understanding of how nutrients control, through signalling, metabolism and transcription, cell growth and cycle is a very relevant aim of SB. Since we know that about 900 gene products are required for cell cycle execution and control in budding yeast, it is quite clear that a purely systematic approach would require too much time. Therefore lines for a modular SB approach, which prioritises molecular and computational investigations for faster cell cycle understanding, are proposed. The relevance of the insight coming from the cell cycle SB studies in developing a new framework for tackling very complex biological processes, such as cancer and aging, is discussed. [Copyright &y& Elsevier]

Abstract: Molecular systems biology aims to describe the functions of complex biological processes through recursive integration of molecular analysis, modeling, simulation and theory. It focuses on networks that originate from interconnection of genes, proteins and metabolites whose dynamic interactions generate, as an emergent property of the system, the corresponding function. Although evolutionary optimized, intracellular biochemical parameters, such as the expression level of gene products or the affinity between two or more proteins, must have a permissible range that gives robustness against perturbations to the system. Using the yeast G1-to-S transition network as an example we show that sophisticated relations exist among network structure, emergent property and robustness. Different emergent properties are generated from the same network by changing the strength of its interactions, not only by altering expression level, but also through mono and multi-site phosphorylation/dephosphorylation. Besides, multi-site protein phosphorylation modules, widespread in cell cycle, may ensure robust and coherent timing of cell cycle transitions as it happens for the onset of DNA replication. In conclusion, the modulation of biological function/emergent property by modifying interaction strength provides an efficient, highly tunable device to regulate biological processes. Furthermore, the principles outlined herein may provide new insight to network analysis in drug discovery. [Copyright &y& Elsevier]

Background: The integration of data from multiple genome-wide assays is essential for understanding dynamic spatio-temporal interactions within cells. Such integration, which leads to a more complete view of cellular processes, offers the opportunity to rationalize better the high amount of "omics" data freely available in several public databases. In particular, integration of microarray-derived transcriptome data with other high-throughput analyses (genomic and mutational analysis, promoter analysis) may allow us to unravel transcriptional regulatory networks under a variety of physio-pathological situations, such as the alteration in the cross-talk between signal transduction pathways in transformed cells. Results: Here we sequentially apply web-based and statistical tools to a case study: the role of oncogenic activation of different signal transduction pathways in the transcriptional regulation of genes encoding proteins involved in the cAMP-PKA pathway. To this end, we first re-analyzed available genome-wide expression data for genes encoding proteins of the downstream branch of the PKA pathway in normal tissues and human tumor cell lines. Then, in order to identify mutation-dependent transcriptional signatures, we classified cancer cells as a function of their mutational state. The results of such procedure were used as a starting point to analyze the structure of PKA pathway-encoding genes promoters, leading to identification of specific combinations of transcription factor binding sites, which are neatly consistent with available experimental data and help to clarify the relation between gene expression, transcriptional factors and oncogenes in our case study. Conclusions: Genome-wide, large-scale "omics" experimental technologies give different, complementary perspectives on the structure and regulatory properties of complex systems. Even the relatively simple, integrated workflow presented here offers opportunities not only for filtering data noise intrinsic in high throughput data, but also to progressively extract novel information that would have remained hidden otherwise. In fact we have been able to detect a strong transcriptional repression of genes encoding proteins of cAMP/PKA pathway in cancer cells of different genetic origins. The basic workflow presented herein may be easily extended by incorporating other tools and can be applied even by researchers with poor bioinformatics skills. [ABSTRACT FROM AUTHOR]

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease. [ABSTRACT FROM AUTHOR]

Saccharomyces cerevisiae must reach a carbon source-modulated critical cell size, protein con- tent per cell at the onset of DNA replication (Ps), in order to enter S phase. Cells grown in glucose are larger than cells grown in ethanol. Here, we show that an increased level of the cyclin-dependent inhibitor Fan increases cell size, whereas far 1δ cells start bud emergence and DNA replication at a smaller size than wild lype. Cln3δ, far 1δ, and strains overexpressing Fan1 do not delay budding during an ethanol glucose shift-up as wild type does. Together, these findings indicate that Cln3 has to overcome Fan to trigger Cln-Cdc28 activation, which then turns on SBF- and MBF-dependent transcription. We show that a second threshold is required together with the Cln3/Far1 threshold for carbon source modulation of Ps. A new molecular network accounting for the selling of Ps is proposed. [ABSTRACT FROM AUTHOR]

The understanding of the organisation of cell cycle events is of utmost importance to devise effective therapeutic strategies for cancer. In this article we gather evidences from the literature in support of a system model of the cell cycle, in which a growth-sensitive threshold controls entry into S phase and the sequential activation of cyclin-dependent kinases. The cycle is terminated by an End function, that comprises events from the onset of mitosis to cell division and that may also be modulated by the increase of cell size. This blueprint allows quantitative predictions by computer simulations of steady and transitory states. In fact, we show that the proposed control system applies to budding yeast populations during nutritional shift-up and following hyperactivation of the cAMP signalling pathway. Besides the growth-sensitive control system it is shown to apply to mammalian cells both in the exit from quiescence and in active proliferation. The putative molecular determinants that set the threshold controlling S phase entry are consistently altered in cancer cells. Finally, we discuss an input/output analysis based on the simulated behaviour derived from the blueprint as a new tool to investigate the road to cancer. Oncogene (2001) 20, 1128–1134. [ABSTRACT FROM AUTHOR]

Neuronal differentiation is regulated by nerve growth factor (NGF) and other neurotrophins. We explored the impact of NGF on mitochondrial dynamics and metabolism through time‐lapse imaging, metabolomics profiling, and computer modeling studies. We show that NGF may direct differentiation by stimulating fission, thereby causing selective mitochondrial network fragmentation and mitophagy, ultimately leading to increased mitochondrial quality and respiration. Then, we reconstructed the dynamic fusion–fission–mitophagy cycling of mitochondria in a computer model, integrating these processes into a single network mechanism. Both the computational model and the simulations are able to reproduce the proposed mechanism in terms of mitochondrial dynamics, levels of reactive oxygen species (ROS), mitophagy, and mitochondrial quality, thus providing a computational tool for the interpretation of the experimental data and for future studies aiming to detail further the action of NGF on mitochondrial processes. We also show that changes in these mitochondrial processes are intertwined with a metabolic function of NGF in differentiation: NGF directs a profound metabolic rearrangement involving glycolysis, TCA cycle, and the pentose phosphate pathway, altering the redox balance. This metabolic rewiring may ensure: (a) supply of both energy and building blocks for the anabolic processes needed for morphological reorganization, as well as (b) redox homeostasis. [ABSTRACT FROM AUTHOR]

Highlights a study which analyzed the association of the cellular environment, properties of growth and cell cycle progression. Analysis of the Saccharomyces cerevisiae cells' dynamic reactions to changes and manipulations of their surroundings; Growth of the cerevisiae populations; Methodology used to conduct the study; Results of the study.

Nicotinamide, nicotinic acid and nicotinamide riboside are vitamin B3 precursors of NAD+ in the human diet. NAD+ has a fundamental importance for cellular biology, that derives from its essential role as a cofactor of various metabolic redox reactions, as well as an obligate co-substrate for NAD+-consuming enzymes which are involved in many fundamental cellular processes including aging/longevity. During aging, a systemic decrease in NAD+ levels takes place, exposing the organism to the risk of a progressive inefficiency of those processes in which NAD+ is required and, consequently, contributing to the age-associated physiological/functional decline. In this context, dietary supplementation with NAD+ precursors is considered a promising strategy to prevent NAD+ decrease and attenuate in such a way several metabolic defects common to the aging process. The metabolism of NAD+ precursors and its impact on cell longevity have benefited greatly from studies performed in the yeast Saccharomyces cerevisiae, which is one of the most established model systems used to study the aging processes of both proliferating (replicative aging) and non-proliferating cells (chronological aging). In this review we summarize important aspects of the role played by nicotinamide, nicotinic acid and nicotinamide riboside in NAD+ metabolism and how each of these NAD+ precursors contribute to the different aspects that influence both replicative and chronological aging. Taken as a whole, the findings provided by the studies carried out in S. cerevisiae are informative for the understanding of the complex dynamic flexibility of NAD+ metabolism, which is essential for the maintenance of cellular fitness and for the development of dietary supplements based on NAD+ precursors. [ABSTRACT FROM AUTHOR]

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulation controls the metabolic flux through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible enzyme. High-throughput data, such as metabolomics and transcriptomics data, if analyzed separately, do not accurately characterize the hierarchical regulation of metabolism outlined above. They must be integrated to disassemble the interdependence between different regulatory layers controlling metabolism. To this aim, we propose INTEGRATE, a computational pipeline that integrates metabolomics and transcriptomics data, using constraint-based stoichiometric metabolic models as a scaffold. We compute differential reaction expression from transcriptomics data and use constraint-based modeling to predict if the differential expression of metabolic enzymes directly originates differences in metabolic fluxes. In parallel, we use metabolomics to predict how differences in substrate availability translate into differences in metabolic fluxes. We discriminate fluxes regulated at the metabolic and/or gene expression level by intersecting these two output datasets. We demonstrate the pipeline using a set of immortalized normal and cancer breast cell lines. In a clinical setting, knowing the regulatory level at which a given metabolic reaction is controlled will be valuable to inform targeted, truly personalized therapies in cancer patients. Author summary: The study of metabolism and its regulation finds increasing application in various fields, including biotransformations, wellness, and health. Metabolism can be studied using post-genomic technologies. Transcriptomics, proteomics and metabolomics provide snapshots of transcripts, enzyme levels and metabolites in specific physio-pathological conditions. In the health field, the transcriptome and, more recently, the metabolome have been broadly profiled at the pre-clinical and clinical levels, while only more recently proteomic studies profiling metabolic enzymes are becoming available. However, the informative power of single omic technologies is inadequate since metabolism regulation involves a complex interplay of regulatory steps. Gene expression regulates metabolism by setting the upper level of metabolic enzymes, whereas the interaction of metabolites with metabolic enzymes directly auto-regulates metabolism. Therefore, there is a need for methods that integrate multiple data sources. We present INTEGRATE, a computational pipeline that captures dynamic features from the static snapshots provided by transcriptomics and metabolomics data. Through integration in a steady-state metabolic model, the pipeline predicts which reactions are controlled purely by metabolic control rather than by gene expression or a combination of the two. This knowledge is crucial in a clinical setting to develop personalized therapies in patients of multifactorial diseases, such as cancer. Besides cancer, INTEGRATE can be applied to different fields where metabolism plays a driving role. [ABSTRACT FROM AUTHOR]

RATIONALE Quantitative phosphoproteomics represents a front line for functional proteomics and hence for systems biology. Here we present a new application of the surface-activated chemical ionization (SACI) technology for quantitative phosphoproteomics analysis. The main advantages of SACI-MS technology are high sensitivity, quantitative accuracy and matrix effect reduction, which allow quantitative estimations. METHODS A SACI-MS approach was used to investigate the quantitative in vivo phosphorylation of the cyclin-dependent kinase inhibitor Sic1, a low-abundance protein of Saccharomyces cerevisiae, which is phosphorylated on Ser201 by casein kinase 2 (CK2) and compared its phosphorylation status in cells growing in two different carbon sources (glucose or ethanol). RESULTS Our relative quantification indicated that the Sic1-Ser201 phosphorylation level is about 2-fold higher in ethanol- than in glucose-growing cells, proportional to the Sic1 protein level. This finding is coherent with results of western blot analysis using anti-phospho-Ser201-specific antibody, validating the results obtained with this new SACI approach. CONCLUSIONS The findings presented in this paper indicate that the innovative LC/SACI-MS method, coupled with immunoprecipitation, is a powerful device to obtain quantitative information on the phosphorylation state of low abundance proteins. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: In eukaryotes DNA replication takes place in the S phase of the cell cycle. It initiates from hundreds to thousands of replication origins in a coordinated manner, in order to efficiently duplicate the genome. The sequence of events leading to the onset of DNA replication is conventionally divided in two interdependent processes: licensing—a process during which replication origins acquire replication competence but are kept inactive— and firing—a process during which licensed origins are activated but not re-licensed. In this review we investigate the evolutionary conservation of the molecular machinery orchestrating DNA replication initiation both in yeast and in mammalian cells, highlighting a remarkable conservation of the general architecture of this central biological mechanism. Many steps are conserved down to molecular details and are performed by orthologous proteins with high sequence conservation, while differences in molecular structure of the performing proteins and their interactions are apparent in other steps. Tight regulation of initiation of DNA replication is achieved through protein phosphorylation, exerted mostly by Cyclin-dependent kinases in order to ensure that each chromosome is fully replicated once, and only once, during each cycle, and to avoid the formation of aberrant DNA structures and incorrect chromosomal duplication, that in mammalian cells are a prerequisite for genome instability and tumorigenesis. We then consider a molecular mathematical model of DNA replication, recently proposed by our group in a collaborative project, as a frame of reference to discuss similarities and differences observed in the regulatory program controlling DNA replication initiation in yeast and in mammalian cells and discuss whether they may be dependent upon different functional constraints. We conclude that a systems biology approach, integrating molecular analysis with modeling and computational investigations, is the best choice to investigate the control of DNA replication in mammalian cells. [Copyright &y& Elsevier]

Computational and experimental studies have yielded quantitative insights into the role for multisite phosphorylation, and other protein modifications, in cell function. This work has emphasized the creation of thresholds and switches for cellular decisions. To date, the dynamics of phosphorylation events have been disregarded yet could be equally relevant for cell function. Here, we discuss theoretical predictions about the kinetic functions of multisite phosphorylation in regulatory networks and how these predictions relate to experimental findings. Using DNA replication as an example, we demonstrate that multisite phosphorylations can support coherent origin firing and robustness against rereplication. We suggest that multisite protein modifications provide a molecular mechanism to robustly time cellular events in the cell cycle, the circadian clock and signal transduction. [ABSTRACT FROM AUTHOR]

Besides being the favorite carbon and energy source for the budding yeast Sacchromyces cerevisiae, glucose can act as a signaling molecule to regulate multiple aspects of yeast physiology. Yeast cells have evolved several mechanisms for monitoring the level of glucose in their habitat and respond quickly to frequent changes in the sugar availability in the environment: the cAMP/PKA pathways (with its two branches comprising Ras and the Gpr1/Gpa2 module), the Rgt2/Snf3-Rgt1 pathway and the main repression pathway involving the kinase Snf1. The cAMP/PKA pathway plays the prominent role in responding to changes in glucose availability and initiating the signaling processes that promote cell growth and division. Snf1 (the yeast homologous to mammalian AMP-activated protein kinase) is primarily required for the adaptation of yeast cell to glucose limitation and for growth on alternative carbon source, but it is also involved in the cellular response to various environmental stresses. The Rgt2/Snf3-Rgt1 pathway regulates the expression of genes required for glucose uptake. Many interconnections exist between the diverse glucose sensing systems, which enables yeast cells to fine tune cell growth, cell cycle and their coordination in response to nutritional changes. [ABSTRACT FROM AUTHOR]

Abstract: Carbonylation of proteins is an irreversible oxidative damage that increases during both chronological and replicative yeast aging. In the latter, a spatial protein quality control system that relies on Sir2 is responsible for the asymmetrical damage segregation in the mother cells. Proper localization of Sir2 on chromatin depends on the deubiquitinating enzyme Ubp10, whose loss of function deeply affects the recombination and gene-silencing activities specific to Sir2. Here, we have analyzed the effects of SIR2 and UBP10 inactivations on carbonylated protein patterns obtained in two aging models such as stationary phase cells and size-selected old mother ones. In line with the endogenous situation of higher oxidative stress resulting from UBP10 inactivation, an increase of protein carbonylation has been found in the ubp10Δ stationary phase cells compared with sir2Δ ones. Moreover, Calorie Restriction had a salutary effect for both mutants by reducing carbonylated proteins accumulation. Remarkably, in the replicative aging model, whereas SIR2 inactivation resulted in a failure to establish damage asymmetry, the Sir2-dependent damage inheritance is maintained in the ubp10Δ mutant which copes with the increased oxidative damage by retaining it in the mother cells. This indicates that both Ubp10 and a correct association of Sir2 with the silenced chromatin are not necessary in such a process but also suggests that additional Sir2 activities on non-chromatin substrates are involved in the establishment of damage asymmetry. [Copyright &y& Elsevier]

Histone modifications influence chromatin structure and thus regulate the accessibility of DNA to replication, recombination, repair, and transcription. We show here that the histone deubiquitinating enzyme Ubp10 contributes to the formation/maintenance of silenced chromatin at the rDNA by affecting Sir2p association. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the production of recombinant Hepatitis C virus (HCV) derived proteins from transformed Saccharomyces cerevisiae yeast cells is reported. Three different yeast strains (GRF18U, BY4743-4A and CENPK 113-5D) have been transformed for the intracellular expression of five antigens of different dimensions (from 32.8 to 85.2kDa), all derived from the non-structural (NS) region of different HCV viruses’ genotypes and posed under the control of a glycolytic promoter. The putative trans-membrane domains contained in four antigens seem responsible of their accumulation as protein aggregates. Good productions of the smaller and of the bigger antigens (50 and 30mgl−1, respectively) have been observed in simple flask batch cultures. Productions are strongly dependent from the genetic background of the yeast host and from the cellular localization of the antigen, while they appear independent from the growth rate of the transformed hosts. For every recombinant antigen tested, the highest production levels were achieved with the CENPK 113-5D-host strain, while the GRF18U strain shows symptoms of a heavily stressed phenotype. [Copyright &y& Elsevier]

UBP10 codes for a deubiquitinating enzyme of Saccharomyces cerevisiae whose loss of function determines slow growth rate and partial impairment of silencing at telomeres and HM loci. A genome-wide analysis performed on a ubp10 disruptant revealed alterations in expression of subtelomeric genes together with a broad change in the whole transcriptional profile, closely parallel to that induced by oxidative stress. This response was accompanied by intracellular accumulation of teactire oxygen species as well as by DNA fragmentation and phosphatidylserine externalization, two markers of apoptosis. SIR4 inactivation mitigated the wide transcriptome remodeling of the ubp10 null mutant affecting particularly the stress transcriptional profile. Moreover, the ubp10sir4 disruptant did not display apoptotic markers. These results argue in favor of an involvement of deubiquitination in transcriptional control and suggest a linkage between oxidative stress and apoptotic pathway in budding yeast. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. Methods: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks.Methods: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology.Results: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets.Conclusions: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care. [ABSTRACT FROM AUTHOR]

A detailed analysis of the cell size, monitored as protein content, has been performed in glucose-limited continuous cultures, so as to obtain the values of the average protein content for various subpopulations at different cell cycle stages, as a function of the growth rate. Glucose metabolism appears to affect cell size, since there is an increase of the average protein content of the population when cells produce ethanol above the critical dilution rate. If the production of ethanol is forced at low growth rates by the addition of formate, the average protein content increases. These results indicate a link between glucose metabolism and cell size in budding yeast, as observed for mammalian cells. [ABSTRACT FROM AUTHOR]

• High content and physiological readouts allow precise definition of the system-level metabolic state of cells or tissues. • Constraint-based metabolic models provide a knowledge-based opportunity to integrate bulk, single-cell and multi-omic data. • Systems metabolomics combines a wide array of techniques to obtain detailed pictures of the dynamic state of metabolism. • Routine clinical application requires appropriate proxy readouts designed upon identification of design principles. Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutrition and wellness to design and optimization of cell factories. The integration of metabolic snapshots with metabolic fluxes, physiological readouts, metabolic models, and knowledge-informed Artificial Intelligence tools, is required to obtain a system-level understanding of metabolism. The emerging power of multi-omic approaches and the development of integrated experimental and computational tools, able to dissect metabolic features at cellular and subcellular resolution, provide unprecedented opportunities for understanding design principles of metabolic (dis)regulation and for the development of precision therapies in multifactorial diseases, such as cancer and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Motivation The elucidation of dysfunctional cellular processes that can induce the onset of a disease is a challenging issue from both the experimental and computational perspectives. Here we introduce a novel computational method based on the coupling between fuzzy logic modeling and a global optimization algorithm, whose aims are to (1) predict the emergent dynamical behaviors of highly heterogeneous systems in unperturbed and perturbed conditions, regardless of the availability of quantitative parameters, and (2) determine a minimal set of system components whose perturbation can lead to a desired system response, therefore facilitating the design of a more appropriate experimental strategy. Results We applied this method to investigate what drives K-ras-induced cancer cells, displaying the typical Warburg effect, to death or survival upon progressive glucose depletion. The optimization analysis allowed to identify new combinations of stimuli that maximize pro-apoptotic processes. Namely, our results provide different evidences of an important protective role for protein kinase A in cancer cells under several cellular stress conditions mimicking tumor behavior. The predictive power of this method could facilitate the assessment of the response of other complex heterogeneous systems to drugs or mutations in fields as medicine and pharmacology, therefore paving the way for the development of novel therapeutic treatments. Availability and implementation The source code of FUMOSO is available under the GPL 2.0 license on GitHub at the following URL: https://github.com/aresio/FUMOSO Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Metabolic reprogramming is a general feature of cancer cells. Regrettably, the comprehensive quantification of metabolites in biological specimens does not promptly translate into knowledge on the utilization of metabolic pathways. By estimating fluxes across metabolic pathways, computational models hold the promise to bridge this gap between data and biological functionality. These models currently portray the average behavior of cell populations however, masking the inherent heterogeneity that is part and parcel of tumorigenesis as much as drug resistance. To remove this limitation, we propose single-cell Flux Balance Analysis (scFBA) as a computational framework to translate single-cell transcriptomes into single-cell fluxomes. We show that the integration of single-cell RNA-seq profiles of cells derived from lung adenocarcinoma and breast cancer patients into a multi-scale stoichiometric model of a cancer cell population: significantly 1) reduces the space of feasible single-cell fluxomes; 2) allows to identify clusters of cells with different growth rates within the population; 3) points out the possible metabolic interactions among cells via exchange of metabolites. The scFBA suite of MATLAB functions is available at , as well as the case study datasets. [ABSTRACT FROM AUTHOR]

Abstract Mitochondria play essential metabolic functions in eukaryotes. Although their major role is the generation of energy in the form of ATP, they are also involved in maintenance of cellular redox state, conversion and biosynthesis of metabolites and signal transduction. Most mitochondrial functions are conserved in eukaryotic systems and mitochondrial dysfunctions trigger several human diseases. By using multi-omics approach, we investigate the effect of methionine supplementation on yeast cellular metabolism, considering its role in the regulation of key cellular processes. Methionine supplementation induces an up-regulation of proteins related to mitochondrial functions such as TCA cycle, electron transport chain and respiration, combined with an enhancement of mitochondrial pyruvate uptake and TCA cycle activity. This metabolic signature is more noticeable in cells lacking Snf1/AMPK, the conserved signalling regulator of energy homeostasis. Remarkably, snf1 Δ cells strongly depend on mitochondrial respiration and suppression of pyruvate transport is detrimental for this mutant in methionine condition, indicating that respiration mostly relies on pyruvate flux into mitochondrial pathways. These data provide new insights into the regulation of mitochondrial metabolism and extends our understanding on the role of methionine in regulating energy signalling pathways. Graphical abstract Unlabelled Image Highlights • Methionine supplementation increases mitochondrial functions. • Methionine addition enhances mitochondrial pyruvate uptake and TCA cycle activity. • Loss of pyruvate transport in snf1 Δ cells is detrimental in methionine condition. [ABSTRACT FROM AUTHOR]

Cancer cells share several metabolic traits, including aerobic production of lactate from glucose (Warburg effect), extensive glutamine utilization and impaired mitochondrial electron flow. It is still unclear how these metabolic rearrangements, which may involve different molecular events in different cells, contribute to a selective advantage for cancer cell proliferation. To ascertain which metabolic pathways are used to convert glucose and glutamine to balanced energy and biomass production, we performed systematic constraint-based simulations of a model of human central metabolism. Sampling of the feasible flux space allowed us to obtain a large number of randomly mutated cells simulated at different glutamine and glucose uptake rates. We observed that, in the limited subset of proliferating cells, most displayed fermentation of glucose to lactate in the presence of oxygen. At high utilization rates of glutamine, oxidative utilization of glucose was decreased, while the production of lactate from glutamine was enhanced. This emergent phenotype was observed only when the available carbon exceeded the amount that could be fully oxidized by the available oxygen. Under the latter conditions, standard Flux Balance Analysis indicated that: this metabolic pattern is optimal to maximize biomass and ATP production; it requires the activity of a branched TCA cycle, in which glutamine-dependent reductive carboxylation cooperates to the production of lipids and proteins; it is sustained by a variety of redox-controlled metabolic reactions. In a K-ras transformed cell line we experimentally assessed glutamine-induced metabolic changes. We validated computational results through an extension of Flux Balance Analysis that allows prediction of metabolite variations. Taken together these findings offer new understanding of the logic of the metabolic reprogramming that underlies cancer cell growth. [ABSTRACT FROM AUTHOR]

The metabolic rearrangements occurring in cancer cells can be effectively investigated with a Systems Biology approach supported by metabolic network modeling. We here present tissue-specific constraint-based core models for three different types of tumors (liver, breast and lung) that serve this purpose. The core models were extracted and manually curated from the corresponding genome-scale metabolic models in the Human Metabolic Atlas database with a focus on the pathways that are known to play a key role in cancer growth and proliferation. Along similar lines, we also reconstructed a core model from the original general human metabolic network to be used as a reference model. A comparative Flux Balance Analysis between the reference and the cancer models highlighted both a clear distinction between the two conditions and a heterogeneity within the three different cancer types in terms of metabolic flux distribution. These results emphasize the need for modeling approaches able to keep up with this tumoral heterogeneity in order to identify more suitable drug targets and develop effective treatments. According to this perspective, we identified key points able to reverse the tumoral phenotype toward the reference one or vice-versa. [ABSTRACT FROM AUTHOR]

HSPA8/hsc70 (70-kDa heat shock cognate) chaperone protein exerts multiple protective roles. Beside its ability to confer to the cells a generic resistance against several metabolic stresses, it is also involved in at least two critical processes whose activity is essential in preventing Parkinson’s disease (PD) pathology. Actually, hsc70 protein acts as the main carrier of chaperone-mediated autophagy (CMA), a selective catabolic pathway for alpha-synuclein, the main pathogenic protein that accumulates in degenerating dopaminergic neurons in PD. Furthermore, hsc70 efficiently fragments alpha-synuclein fibrils in vitro and promotes depolymerization into non-toxic alpha-synuclein monomers. Considering that the mitochondrial complex I inhibitor rotenone, used to generate PD animal models, induces alpha-synuclein aggregation, this study was designed in order to verify whether rotenone exposure leads to hsc70 alteration possibly contributing to alpha-synuclein aggregation. To this aim, human SH-SY5Y neuroblastoma cells were treated with rotenone and hsc70 mRNA and protein expression were assessed; the effect of rotenone on hsc70 was compared with that exerted by hydrogen peroxide, a generic oxidative stress donor with no inhibitory activity on mitochondrial complex I. Furthermore, the effect of rotenone on hsc70 was verified in primary mouse cortical neurons. The possible contribution of macroautophagy to rotenone-induced hsc70 modulation was explored and the influence of hsc70 gene silencing on neurotoxicity was assessed. We demonstrated that rotenone, but not hydrogen peroxide, induced a significant reduction of hsc70 mRNA and protein expression. We also observed that the toxic effect of rotenone on alpha-synuclein levels was amplified when macroautophagy was inhibited, although rotenone-induced hsc70 reduction was independent from macroautophagy. Finally, we demonstrated that hsc70 gene silencing up-regulated alpha-synuclein mRNA and protein levels without affecting cell viability and without altering rotenone- and hydrogen peroxide-induced cytotoxicity. These findings demonstrate the existence of a novel mechanism of rotenone toxicity mediated by hsc70 and indicate that dysfunction of both CMA and macroautophagy can synergistically exacerbate alpha-synuclein toxicity, suggesting that hsc70 up-regulation may represent a valuable therapeutic strategy for PD. [ABSTRACT FROM AUTHOR]

Modulation of extracellular matrix (ECM) remodeling after peripheral nerve injury (PNI) could represent a valid therapeutic strategy to prevent maladaptive synaptic plasticity in central nervous system (CNS). Inhibition of matrix metalloproteinases (MMPs) and maintaining a neurotrophic support could represent two approaches to prevent or reduce the maladaptive plastic changes in the ventral horn of spinal cord following PNI. The purpose of our study was to analyze changes in the ventral horn produced by gliopathy determined by the suffering of motor neurons following spared nerve injury (SNI) of the sciatic nerve and how the intrathecal (i.t.) administration of GM6001 (a MMPs inhibitor) or the NGF mimetic peptide BB14 modulate these events. Immunohistochemical analysis of spinal cord sections revealed that motor neuron disease following SNI was associated with increased microglial (Iba1) and astrocytic (GFAP) response in the ventral horn of the spinal cord, indicative of reactive gliosis. These changes were paralleled by decreased glial aminoacid transporters (glutamate GLT1 and glycine GlyT1), increased levels of the neuronal glutamate transporter EAAC1, and a net increase of the Glutamate/GABA ratio, as measured by HPLC analysis. These molecular changes correlated to a significant reduction of mature NGF levels in the ventral horn. Continuous i.t. infusion of both GM6001 and BB14 reduced reactive astrogliosis, recovered the expression of neuronal and glial transporters, lowering the Glutamate/GABA ratio. Inhibition of MMPs by GM6001 significantly increased mature NGF levels, but it was absolutely ineffective in modifying the reactivity of microglia cells. Therefore, MMPs inhibition, although supplies neurotrophic support to ECM components and restores neuro-glial transporters expression, differently modulates astrocytic and microglial response after PNI. [ABSTRACT FROM AUTHOR]

Cancer cells often rely on glycolysis to obtain energy and support anabolic growth. Several studies showed that glycolytic cells are susceptible to cell death when subjected to low glucose availability or to lack of glucose. However, some cancer cells, including glycolytic ones, can efficiently acquire higher tolerance to glucose depletion, leading to their survival and aggressiveness. Although increased resistance to glucose starvation has been shown to be a consequence of signaling pathways and compensatory metabolic routes activation, the full repertoire of the underlying molecular alterations remain elusive. Using omics and computational analyses, we found that cyclic adenosine monophosphate-Protein Kinase A (cAMP-PKA) axis activation is fundamental for cancer cell resistance to glucose starvation and anoikis. Notably, here we show that such a PKA-dependent survival is mediated by parallel activation of autophagy and glutamine utilization that in concert concur to attenuate the endoplasmic reticulum (ER) stress and to sustain cell anabolism. Indeed, the inhibition of PKA-mediated autophagy or glutamine metabolism increased the level of cell death, suggesting that the induction of autophagy and metabolic rewiring by PKA is important for cancer cellular survival under glucose starvation. Importantly, both processes actively participate to cancer cell survival mediated by suspension-activated PKA as well. In addition we identify also a PKA/Src mechanism capable to protect cancer cells from anoikis. Our results reveal for the first time the role of the versatile PKA in cancer cells survival under chronic glucose starvation and anoikis and may be a novel potential target for cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Recent advances in large datasets analysis offer new insights to modern biology allowing system-level investigation of pathologies. Here we describe a novel computational method that exploits the ever-growing amount of "omics" data to shed light on Alzheimer's and Parkinson's diseases. Neurological disorders exhibit a huge number of molecular alterations due to a complex interplay between genetic and environmental factors. Classical reductionist approaches are focused on a few elements, providing a narrow overview of the etiopathogenic complexity of multifactorial diseases. On the other hand, high-throughput technologies allow the evaluation of many components of biological systems and their behaviors. Analysis of Parkinson's Disease (PD) and Alzheimer's Disease (AD) from a network perspective can highlight proteins or pathways common but differently represented that can be discriminating between the two pathological conditions, thus highlight similarities and differences. Results: In this work we propose a strategy that exploits network community structure identified with a state-of-the-art network community discovery algorithm called InfoMap, which takes advantage of information theory principles. We used two similarity measurements to quantify functional and topological similarities between the two pathologies. We built a Similarity Matrix to highlight similar communities and we analyzed statistically significant GO terms found in clustered areas of the matrix and in network communities. Our strategy allowed us to identify common known and unknown processes including DNA repair, RNA metabolism and glucose metabolism not detected with simple GO enrichment analysis. In particular, we were able to capture the connection between mitochondrial dysfunction and metabolism (glucose and glutamate/glutamine). Conclusions: This approach allows the identification of communities present in both pathologies which highlight common biological processes. Conversely, the identification of communities without any counterpart can be used to investigate processes that are characteristic of only one of the two pathologies. In general, the same strategy can be applied to compare any pair of biological networks. [ABSTRACT FROM AUTHOR]

Reactive astrocytes and activated microglia are the key players in several pathophysiologic modifications of the central nervous system. We used the spared nerve injury (SNI) of the sciatic nerve to induce glial maladaptive response in the ventral horn of lumbar spinal cord and examine its role in the remodeling of the tripartite synapse plasticity. Imaging the ventral horn revealed that SNI was associated with both an early microglial and astrocytic activation, assessed, respectively, by analysis of Iba1 and GFAP expression. Microglia, in particular, localized peculiarly surrounding the motor neurons somata. Perineuronal astrocytes, which play a key role in maintaining the homeostasis of neuronal circuitry, underwent a substantial phenotypic change following peripheral axotomy, producing reactive gliosis. The gliosis was associated with the reduction of glial aminoacid transporters (GLT1 and GlyT1) and increase of neuronal glutamate transporter EAAC1. Although the expression of GABAergic neuronal marker GAD65/67 showed no change, glutamate increase, as demonstrated by HPLC analysis, shifted the excitatory/inhibitory balance as showed by the net increase of the glutamate/GABA ratio. Moreover, endogenous NGF levels were altered in SNI animals and not restored by the intrathecal NGF administration. This treatment reverted phenotypic changes associated with reactive astrocytosis, but failed to modify microglia activation. These findings on one hand confirm the correlation between gliopathy and maladaptive plasticity of the spinal synaptic circuitry, on the other hand add new data concerning the complex peculiar behavior of different glial cells in neuronal degenerative processes, defining a special role of microglia in sustaining the inflammatory response. [ABSTRACT FROM AUTHOR]

The metabolism of proliferating cells shows common features even in evolutionary distant organisms such as mammals and yeasts, for example the requirement for anabolic processes under tight control of signaling pathways. Analysis of the rewiring of metabolism, which occurs following the dysregulation of signaling pathways, provides new knowledge about the mechanisms underlying cell proliferation. The key energy regulator in yeast Snf1 and its mammalian ortholog AMPK have earlier been shown to have similar functions at glucose limited conditions and here we show that they also have analogies when grown with glucose excess. We show that loss of Snf1 in cells growing in 2% glucose induces an extensive transcriptional reprogramming, enhances glycolytic activity, fatty acid accumulation and reliance on amino acid utilization for growth. Strikingly, we demonstrate that Snf1/AMPK-deficient cells remodel their metabolism fueling mitochondria and show glucose and amino acids addiction, a typical hallmark of cancer cells. [ABSTRACT FROM AUTHOR]

Significance: Histone deacetylases (HDACs) activity and cell metabolism are considered important targets for cancer therapy, as both are deregulated and associated with the onset and maintenance of tumors. Recent Advances: Besides the classical function of HDACs as HDAC enzymes controlling the transcription, it is becoming increasingly evident that these proteins are involved in the regulation of several other cellular processes by their ability to deacetylate hundreds of proteins with different functions in both the cytoplasm and the nucleus. Importantly, recent high-throughput studies have identified as important target proteins several enzymes involved in different metabolic pathways. Conversely, it has been also shown that metabolic intermediates may control HDACs activity. Consequently, the acetylation/deacetylation of metabolic enzymes and the ability of metabolic intermediates to modulate HDACs may represent a cross-talk connecting cell metabolism, transcription, and other HDACs-controlled processes in physiological and pathological conditions. Critical Issues: Since metabolic alterations and HDACs deregulation are important cancer hallmarks, disclosing connections among them may improve our understanding on cancer mechanisms and reveal novel therapeutic protocols against this disease. Future Directions: High-throughput metabolic studies performed by using more sophisticated technologies applied to the available models of conditional deletion of HDACs in cell lines or in mice will fill the gap in the current understanding and open directions for future research. Antioxid. Redox Signal. 23, 30-50. [ABSTRACT FROM AUTHOR]

Constraint-based modeling is largely used in computational studies of metabolism. We propose here a novel approach that aims to identify ensembles of flux distributions that comply with one or more target phenotype(s). The methodology has been tested on a small-scale model of yeast energy metabolism. The target phenotypes describe the differential pattern of ethanol production and O consumption observed in 'Crabtree-positive' and 'Crabtree-negative' yeasts in changing environment (i.e., when the upper limit of glucose uptake is varied). The ensembles were obtained either by selection among sampled flux distributions or by means of a search heuristic (genetic algorithm). The former approach provided indication about the probability to observe a given phenotype, but the resulting ensembles could not be unambiguously partitioned into 'Crabtree-positive' and 'Crabtree-negative' clusters. On the contrary well-separated clusters were obtained with the latter method. The cluster analysis further allowed identification of distinct groups within each target phenotype. The method may thus prove useful in characterizing the design principles underlying metabolic plasticity arising from evolving physio-pathological or developmental constraints. [ABSTRACT FROM AUTHOR]

Highlights: [•] Astrocytes and neurones show common set of channels, receptors and transporters underlying glia–neuron interplay. [•] Altered glial functions following different kind of stressors characterize the reactive gliosis. [•] Enduring reactive gliosis induces the development of a complex phenotype defined “gliopathy”. [•] Gliopathy is associated to the maladaptive plasticity, a perturbation of neuronal network. [•] Gliopathy and maladaptive plasticity characterize onset, progression and outcome of several neurological disease. [Copyright &y& Elsevier]

Abstract: Snf1, the yeast AMP-activated kinase homolog, regulates the expression of several genes involved in adaptation to glucose limitation and in response to cellular stresses. We previously demonstrated that Snf1 interacts with Swi6, the regulatory subunit of SBF and MBF complexes, and activates CLB5 transcription. Here we report that, in α-factor synchronized cells in 2% glucose, the loss of the Snf1 catalytic subunit impairs the binding of SBF and MBF complexes and the subsequent recruitment of the FACT complex and RNA Polymerase II to promoters of G1-genes. By using an analog-sensitive allele of SNF1, SNF1as (I132G), encoding a protein whose catalytic activity is selectively inhibited in vivo by 2-naphthylmethyl pyrazolopyrimidine 1, we show that the inhibition of Snf1 catalytic activity affects the expression of G1-genes causing a delayed entrance into S phase in cells synchronized in G1 phase by α-factor treatment or by elutriation. Moreover, Snf1 is detected in immune complexes of Rpb1, the large subunit of RNA Polymerase II, and is present at both promoters and coding regions of SBF- and MBF-regulated genes 20min after α-factor release, suggesting a direct role for Snf1 in the activation of the G1-regulon transcription. [Copyright &y& Elsevier]

Abstract: Mutations of RAS genes are critical events in the pathogenesis of different human tumors and Ras proteins represent a major clinical target for the development of specific inhibitors to use as anticancer agents. Here we present RasGRF1-derived peptides displaying both in vitro and in vivo Ras inhibitory properties. These peptides were designed on the basis of the down-sizing of dominant negative full-length RasGRF1 mutants. The over-expression of these peptides can revert the phenotype of K-RAS transformed mouse fibroblasts to wild type, as monitored by several independent biological readouts, including Ras–GTP intracellular levels, ERK activity, morphology, proliferative potential and anchorage independent growth. Fusion of the RasGRF1-derived peptides with the Tat protein transduction domain allows their uptake into mammalian cells. Chemically synthesized Tat-fused peptides, reduced to as small as 30 residues on the basis of structural constraints, retain Ras inhibitory activity. These small peptides interfere in vitro with the GEF catalyzed nucleotide dissociation and exchange on Ras, reduce cell proliferation of K-RAS transformed mouse fibroblasts, and strongly reduce Ras-dependent IGF-I-induced migration and invasion of human bladder cancer cells. These results support the use of RasGRF1-derived peptides as model compounds for the development of Ras inhibitory anticancer agents. [Copyright &y& Elsevier]

Abstract: Peptidomimetics hold a great promise as therapeutic agents for neurodegenerative disorders. We previously described a Nerve Growth Factor (NGF)-like peptide, now named BB14, which was found to act as a strong TrkA agonist and to be effective in the sciatic nerve injury model of neuropathic pain. In this report we present the effects of BB14 in reducing reactive astrocytosis and reverting neuroplastic changes of the glutamate/GABAergic circuitry in the lumbar spinal cord following spared nerve injury (SNI) of the sciatic nerve. Immunohistochemical analysis of spinal cord sections revealed that SNI was associated with increased microglial (Iba1) and astrocytic (GFAP) responses, indicative of reactive gliosis. These changes were paralleled by ( i ) decreased glial aminoacid transporters (GLT1 and GlyT1) and increased levels of ( ii ) neuronal glutamate transporter EAAC1, ( iii ) neuronal vesicular GABA transporter (vGAT) and ( iv ) the GABAergic neuron marker GAD65/67. A remarkable increase of the Glutamate/GABA ratio and the reduction of glutathione (GSH) levels were also indicative of modifications of glial function in neuroprotection. All these molecular changes were found to be linked to an alteration of endogenous NGF metabolism, as demonstrated by decreased levels of mature NGF, increase of proNGF and increased activity of NGF-degrading methallo-proteinases (MMPs). Biochemical alterations and SNI-related neuropathic behavior, characterized by allodynia and hyperalgesia, were reversed by 7-days i.t. administration of the NGF-like peptide BB14, as well as by increasing endogenous NGF levels by i.t. infusion of GM6001, a MMPs inhibitor. All together, while confirming the correlation between reactive astrogliosis and perturbation of synaptic circuitry in the SNI model of peripheral nerve injury, these data strongly support the beneficial effect of BB14 in reducing reactive astrogliosis and restoring synaptic homeostasis under pathological conditions linked to alteration of NGF availability and signaling, thereby suggesting a potential role of BB14 as a therapeutic agent. [Copyright &y& Elsevier]

Abstract: Neuroglial cells are fundamental for control of brain homeostasis and synaptic plasticity. Decades of pathological and physiological studies have focused on neurons in neurodegenerative disorders, but it is becoming increasingly evident that glial cells play an irreplaceable part in brain homeostasis and synaptic plasticity. Animal models of brain injury and neurodegenerative diseases have largely contributed to current understanding of astrocyte-specific mechanisms participating in brain function and neurodegeneration. Specifically, gliotransmission (presence of glial neurotransmitters, and their receptors and active transporters), trophic support (release, maturation and degradation of neurotrophins) and metabolism (production of lactate and GSH components) are relevant aspects of astrocyte function in neuronal metabolism, synaptic plasticity and neuroprotection. Morpho-functional changes of astrocytes and microglial cells after traumatic or toxic insults to the central nervous system (namely, reactive gliosis) disrupt the complex neuro-glial networks underlying homeostasis and connectivity within brain circuits. Thus, neurodegenerative diseases might be primarily regarded as gliodegenerative processes, in which profound alterations of glial activation have a clear impact on progression and outcomes of neuropathological processes. This review provides an overview of current knowledge of astrocyte functions in the brain and how targeting glial-specific pathways might ultimately impact the development of therapies for clinical management of neurodegenerative disorders. [Copyright &y& Elsevier]

Abstract: The FAR1 gene encodes an 830 residue bifunctional protein, whose major function is inhibition of cyclin-dependent kinase complexes involved in the G1/S transition. FAR1 transcription is maximal between mitosis and early G1 phase. Enhanced FAR1 transcription is necessary but not sufficient for the pheromone-induced G1 arrest, since FAR1 overexpression itself does not trigger cell cycle arrest. Besides its well established role in the response to pheromone, recent evidences suggest that Far1 may also regulate the mitotic cell cycle progression: in particular, it has been proposed that Far1, together with the G1 cyclin Cln3, may be part of a cell sizer mechanism that controls the entry into S phase. Far1 is an unstable protein throughout the cell cycle except during G1 phase. Far1 levels peak in newborn cells as a consequence of a burst of synthetic activity at the end of the previous cycle, and the amounts per cell remain roughly constant during the G1 phase. Phosphorylation (at serine 87) by Cdk1–Cln complexes primes Far1 for ubiquitin-mediated proteolysis. By coupling a genome-wide transcriptional analysis of FAR1-overexpressing and far1Δ cells grown in ethanol- or glucose-supplemented minimal media with a range of phenotypic analysis, we show that FAR1 overexpression not only coordinately increases RNA and protein accumulation, but induces strong transcriptional remodeling, metabolism being the most affected cellular property, suggesting that the Far1/Cln3 sizer regulates cell growth either directly or indirectly by affecting metabolism and pathways known to modulate ribosome biogenesis. A crucial role in mediating the effect of Far1 overexpression is played by the Sfp1 protein, a key transcriptional regulator of ribosome biogenesis, whose presence is mandatory to allow a coordinated increase in both RNA and protein levels in ethanol-grown cells. [Copyright &y& Elsevier]

Abstract: The multi-domain protein hSos1 plays a major role in cell growth and differentiation through its Ras-specific guanine nucleotide exchange domain whose complex regulation involves intra-molecular, inter-domain rearrangements. We present a stochastic mathematical model describing intra-molecular regulation of hSos1 activity. The population macroscopic effect is reproduced through a Monte-Carlo approach. Key model parameters have been experimentally determined by BIAcore analysis. Complementation experiments of a Saccharomyces cerevisiae cdc25 ts strain with Sos deletion mutants provided a comprehensive data set for estimation of unknown parameters and model validation. The model is robust against parameter alteration and describes both the behavior of Sos deletion mutants and modulation of activity of the full length molecule under physiological conditions. By incorporating the calculated effect of aminoacid changes at an inter-domain interface, the behavior of a mutant correlating with a developmental syndrome could be simulated, further validating the model. The activation state of Ras-specific guanine nucleotide exchange domain of hSos1 arises as an “emergent property” of its multi-domain structure that allows multi-level integration of a complex network of intra- and inter-molecular signals. [Copyright &y& Elsevier]