Claudio Angione, Human Systems Biology and Metabolic Modelling: A Review—From Disease Metabolism to Precision Medicine, Biomed Research International, 2019 (2019) 1-16.
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Marc Brehme et al., A Chaperome Subnetwork Safeguards Proteostasis in Aging and Neurodegenerative Disease, Cellreports, 9 (2014) 1135-1150.
Brehme et al. have examined the chaper- ome from C. elegans to humans using functional assays and expression as well as protein-interactome analysis. The au- thors identify a conserved C. elegans chaperome subnetwork of 16 chaperone genes, corresponding to 28 human or- thologs that are affected in brain aging and diseases associated with protein aggregation.
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Roger C Conant and W Ross Ashby, Every good regulator of a system must be a model of that system †, International Journal Of Systems Science, 1 (2007) 89-97.
The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto heen regarded as optional, as merely one of many possiblc ways.
In this paper a theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with thc system being regulated. (The exact assumptions are given.) Making a model is thus necessary.
The theorern has the interesting corollary that the living brain, so far as it is to ha successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment.
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Ivan J Cajigas et al., Focus Review Protein homeostasis and synaptic plasticity, The Embo Journal, 29 (2010) 2746-2752.
It is clear that de novo protein synthesis has an important function in synaptic transmission and plasticity. A substantial amount of work has shown that mRNA translation in the hippocampus is spatially controlled and that dendritic protein synthesis is required for different forms of long-term synaptic plasticity. More recently, several studies have highlighted a function for protein degradation by the ubiquitin proteasome system in synaptic plasticity. These observations suggest that changes in synaptic transmission involve extensive regulation of the synaptic proteome. Here, we review experimental data supporting the idea that protein homeostasis is a regulatory motif for synaptic plasticity.
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Jordi Chan and Enrico Coen, Interaction between Autonomous and Microtubule Guidance Systems Controls Cellulose Synthase Trajectories, Current Biology, 2020 pp. 1-16.
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D Duboule, Time for Chronomics?, Science, 301 (2003) 277-277.
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Bob Eisenberg, Energetic Controls are Essential, Biophysical Journal, 2020 pp. 1-5.
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Christian K Euler and Radhakrishnan Mahadevan, Protein-Level Control of Metabolism: Design Principles and Prospects from a Representative System, Ifac-Papersonline, 49 (2016) 165-170.
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Shohini Ghosh-Choudhary et al., Metabolic Regulation of Cell Fate and Function, Trends In Cell Biology, 2020 pp. 1-12.
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Eisuke Itakura et al., Heparan sulfate is a clearance receptor for aberrant extracellular proteins, Journal Of Cell Biology, 219 (2020) 909-17.
The accumulation of aberrant proteins leads to various neurodegenerative disorders. Mammalian cells contain several intracellular protein degradation systems, including autophagy and proteasomal systems, that selectively remove aberrant intracellular proteins. Although mammals contain not only intracellular but also extracellular proteins, the mechanism underlying the quality control of aberrant extracellular proteins is poorly understood. Here, using a novel quantitative fluorescence assay and genome-wide CRISPR screening, we identified the receptor-mediated degradation pathway by which misfolded extracellular proteins are selectively captured by the extracellular chaperone Clusterin and undergo endocytosis via the cell surface heparan sulfate (HS) receptor. Biochemical analyses revealed that positively charged residues on Clusterin electrostatically interact with negatively charged HS. Furthermore, the Clusterin–HS pathway facilitates the degradation of amyloid β peptide and diverse leaked cytosolic proteins in extracellular space. Our results identify a novel protein quality control system for preserving extracellular proteostasis and highlight its role in preventing diseases associated with aberrant extracellular proteins.
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Boris N Kholodenko, Cell-signalling dynamics in time and space., Nature Reviews. Molecular Cell Biology, 7 (2006) 165-176.
The specificity of cellular responses to receptor stimulation is encoded by the spatial and temporal dynamics of downstream signalling networks. Temporal dynamics are coupled to spatial gradients of signalling activities, which guide pivotal intracellular processes and tightly regulate signal propagation across a cell. Computational models provide insights into the complex relationships between the stimuli and the cellular responses, and reveal the mechanisms that are responsible for signal amplification, noise reduction and generation of discontinuous bistable dynamics or oscillations.
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Osvaldo D Kim et al., A Review of Dynamic Modeling Approaches and Their Application in Computational Strain Optimization for Metabolic Engineering, Frontiers In Microbiology, 9 (2018) 38-22.
Mathematical modeling is a key process to describe the behavior of biological networks.Mathematical modeling is a key process to describe the behavior of biological networks.
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Courtney L Klaips et al., Pathways of cellular proteostasis in aging and disease, Journal Of Cell Biology, 217 (2017) 51-63.
Ensuring cellular protein homeostasis, or proteostasis, requires precise control of protein synthesis, folding, conformational maintenance, and degradation. A complex and adaptive proteostasis network coordinates these processes with molecular chaperones of different classes and their regulators functioning as major players. This network serves to ensure that cells have the proteins they need while minimizing misfolding or aggregation events that are hallmarks of age-associated proteinopathies, including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. It is now clear that the capacity of cells to maintain proteostasis undergoes a decline during aging, rendering the organism susceptible to these pa- thologies. Here we discuss the major proteostasis pathways in light of recent research suggesting that their age-dependent failure can both contribute to and result from disease. We consider different strategies to modulate proteostasis capacity, which may help develop urgently needed therapies for neurodegeneration and other age-dependent pathologies.
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Ali Sinan Köksal et al., Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data, Cellreports, 24 (2018) 3607-3618.
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Michael Levin, Morphogenetic fields in embryogenesis, regeneration, and cancer: Non-local control of complex patterning, Biosystems, 109 (2012) 243-261.
Establishment of shape during embryonic development, and the maintenance of shape against injury or tumorigenesis, requires constant coordination of cell behaviors toward the patterning needs of the host organism. Molecular cell biology and genetics have made great strides in understanding the mechanisms that regulate cell function. However, generalized rational control of shape is still largely beyond our current capabilities. Significant instructive signals function at long range to provide positional information and other cues to regulate organism-wide systems properties like anatomical polarity and size control. Is complex morphogenesis best understood as the emergent property of local cell interactions, or as the outcome of a computational process that is guided by a physically-encoded map or template of the final goal state? Here I review recent data and molecular mechanisms relevant to morphogenetic fields: large-scale systems of physical properties that have been proposed to store patterning information during embryogenesis, regenerative repair, and cancer suppression that ultimately controls anatomy. Placing special emphasis on the role of endogenous bioelectric signals as an important component of the morphogenetic field, I speculate on novel approaches for the computational modeling and control of these fields with applications to synthetic biology, regenerative medicine, and evolutionary developmental biology.
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Michael Levin, The Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation, Bioessays, 42 (2020) 1900146-17.
Evolution exploits the physics of non-neural bioelectricity to implement anatomical homeostasis: a process in which embryonic patterning, remodeling, and regeneration achieve invariant anatomical outcomes despite external interventions. Linear “developmental pathways” are often inadequate explanations for dynamic large-scale pattern regulation, even when they accurately capture relationships between molecular components. Biophysical and computational aspects of collective cell activity toward a target morphology reveal interesting aspects of causation in biology. This is critical not only for unraveling evolutionary and developmental events, but also for the design of effective strategies for biomedical intervention. Bioelectrical controls of growth and form, including stochastic behavior in such circuits, highlight the need for the formulation of nuanced views of pathways, drivers of system-level outcomes, and modularity, borrowing from concepts in related disciplines such as cybernetics, control theory, computational neuroscience, and information theory. This approach has numerous practical implications for basic research and for applications in regenerative medicine and synthetic bioengineering.
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Etienne J P Maes et al., Causal evidence supporting the proposal that dopamine transients function as temporal difference prediction errors, Nature Neuroscience, 2020 pp. 1-12.
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Tami A Martino and Michael J Sole, Molecular Time, Circulation Research, 105 (2009) 1047-1061.
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Roxanne Oshidari et al., DNA repair by Rad52 liquid droplets, Nature Communications, 2020 pp. 1-8.
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Diego A Oyarzún et al., Sequential Activation of Metabolic Pathways: a Dynamic Optimization Approach, Bulletin Of Mathematical Biology, 71 (2009) 1851-1872.
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Benjamin Russell and Herschel Rabitz, Common foundations of optimal control across the sciences: evidence of a free lunch, Philosophical Transactions Of The Royal Society A: Mathematical, Physical And Engineering Sciences, 375 (2017) 20160210-14.
A common goal in the sciences is optimization of an objective function by selecting control variables such that a desired outcome is achieved. This scenario can be expressed in terms of a control landscape of an objective considered as a function of the control variables. At the most basic level, it is known that the vast majority of quantum control landscapes possess no traps, whose presence would hinder reaching the objective. This paper reviews and extends the quantum control landscape assessment, presenting evidence that the same highly favourable landscape features exist in many other domains of science. The implications of this broader evidence are discussed. Specifically, control landscape examples from quantum mechanics, chemistry and evolutionary biology are presented. Despite the obvious differences, commonalities between these areas are highlighted within a unified mathematical framework. This mathematical framework is driven by the wide-ranging experimental evidence on the ease of finding optimal controls (in terms of the required algorithmic search effort beyond the laboratory set-up overhead). The full scope and implications of this observed common control behaviour pose an open question for assessment in further work.
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Frederick Verbruggen et al., Banishing the Control Homunculi in Studies of Action Control and Behavior Change, Perspectives On Psychological Science, 9 (2014) 497-524.
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Suzanne Wolff et al., Differential Scales of Protein Quality Control, Cell, 157 (2014) 52-64.
Proteins are notorious for their unpleasant behavior—continually at risk of misfolding, collecting damage, aggregating, and causing toxicity and disease. To counter these challenges, cells have evolved elaborate chaperone and quality control networks that can resolve damage at the level of the protein, organelle, cell, or tissue. On the smallest scale, the integrity of individual proteins is monitored during their synthesis. On a larger scale, cells use compartmentalized defenses and net- works of communication, capable sometimes of signaling between cells, to respond to changes in the proteome’s health. Together, these layered defenses help protect cells from damaged proteins.
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Alon Zaslaver et al., Just-in-time transcription program in metabolic pathways, Nature Genetics, 36 (2004) 486-491.
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Gerhild van Echten-Deckert, Metabolic Pathways, , 2017 pp. 1-32.
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