A composite computational model of liver glucose homeostasis. I. Building the composite model

A computational model of the glucagon/insulin-driven liver glucohomeostasis function, focusing on the buffering of glucose into glycogen, has been developed. The model exemplifies an ‘engineering’ approach to modelling in systems biology, and was produced by linking together seven component models of separate aspects of the physiology. The component models use a variety of modelling paradigms and degrees of simplification. Model parameters were determined by an iterative hybrid of fitting to high-scale physiological data, and determination from small-scale in vitro experiments or molecular biological techniques. The component models were not originally designed for inclusion within such a composite model, but were integrated, with modification, using our published modelling software and computational frameworks. This approach facilitates the development of large and complex composite models, although, inevitably, some compromises must be made when composing the individual models. Composite models of this form have not previously been demonstrated.     

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist ‘Eve’ designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.     

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata—a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure—the ‘feed-forward loop’—a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.     

Single molecule dynamics in a virtual cell: a three-dimensional model that produces simulated fluorescence video-imaging data

The analysis of single molecule imaging experiments is complicated by the stochastic nature of single molecule events, by instrument noise and by the limited information which can be gathered about any individual molecule observed. Consequently, it is important to cross check experimental results using a model simulating single molecule dynamics (e.g. movements and binding events) in a virtual cell-like environment. The output of such a model should match the real data format allowing researchers to compare simulated results with the real experiments. The proposed model exploits the advantages of ‘object-oriented’ computing. First of all, the ability to create and manipulate a number of classes, each containing an arbitrary number of single molecule objects. These classes may include objects moving within the ‘cytoplasm’; objects moving at the ‘plasma membrane’; and static objects located inside the ‘body’. The objects of a given class can interact with each other and/or with the objects of other classes according to their physical and chemical properties. Each model run generates a sequence of images, each containing summed images of all fluorescent objects emitting light under given illumination conditions with realistic levels of noise and emission fluctuations. The model accurately reproduces reported single molecule experiments and predicts the outcome of future experiments.     

A dynamic broadband reflector built from microscopic silica spheres in the ‘disco’ clam Ctenoides ales

The ‘disco’ or ‘electric’ clam Ctenoides ales (Limidae) is the only species of bivalve known to have a behaviourally mediated photic display. This display is so vivid that it has been repeatedly confused for bioluminescence, but it is actually the result of scattered light. The flashing occurs on the mantle lip, where electron microscopy revealed two distinct tissue sides: one highly scattering side that contains dense aggregations of spheres composed of silica, and one highly absorbing side that does not. High-speed video confirmed that the two sides act in concert to alternate between vivid broadband reflectance and strong absorption in the blue region of the spectrum. Optical modelling suggests that the diameter of the spheres is nearly optimal for scattering visible light, especially at shorter wavelengths which predominate in their environment. This simple mechanism produces a striking optical effect that may function as a signal.     

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis

Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or ‘retrodict’, compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data.     

Next-generation tools for evolutionary invasion analyses

Evolutionary invasion analysis is a powerful technique for modelling in evolutionary biology. The general approach is to derive an expression for the growth rate of a mutant allele encoding some novel phenotype, and then to use this expression to predict long-term evolutionary outcomes. Mathematically, such ‘invasion fitness’ expressions are most often derived using standard linear stability analyses from dynamical systems theory. Interestingly, there is a mathematically equivalent approach to such stability analyses that is often employed in mathematical epidemiology, and that is based on so-called ‘next-generation’ matrices. Although this next-generation matrix approach has sometimes also been used in evolutionary invasion analyses, it is not yet common in this area despite the fact that it can sometimes greatly simplify calculations. The aim of this article is to bring the approach to a wider evolutionary audience in two ways. First, we review the next-generation matrix approach and provide a novel, and easily intuited, interpretation of how this approach relates to more standard techniques. Second, we illustrate next-generation methods in evolutionary invasion analysis through a series of informative examples. Although focusing primarily on evolutionary invasion analysis, we provide several insights that apply to biological modelling in general.     

Cancer therapeutic potential of combinatorial immuno- and vasomodulatory interventions

Currently, most of the basic mechanisms governing tumour–immune system interactions, in combination with modulations of tumour-associated vasculature, are far from being completely understood. Here, we propose a mathematical model of vascularized tumour growth, where the main novelty is the modelling of the interplay between functional tumour vasculature and effector cell recruitment dynamics. Parameters are calibrated on the basis of different in vivo immunocompromised Rag1^−/− and wild-type (WT) BALB/c murine tumour growth experiments. The model analysis supports that tumour vasculature normalization can be a plausible and effective strategy to treat cancer when combined with appropriate immunostimulations. We find that improved levels of functional tumour vasculature, potentially mediated by normalization or stress alleviation strategies, can provide beneficial outcomes in terms of tumour burden reduction and growth control. Normalization of tumour blood vessels opens a therapeutic window of opportunity to augment the antitumour immune responses, as well as to reduce intratumoral immunosuppression and induced hypoxia due to vascular abnormalities. The potential success of normalizing tumour-associated vasculature closely depends on the effector cell recruitment dynamics and tumour sizes. Furthermore, an arbitrary increase in the initial effector cell concentration does not necessarily imply better tumour control. We evidence the existence of an optimal concentration range of effector cells for tumour shrinkage. Based on these findings, we suggest a theory-driven therapeutic proposal that optimally combines immuno- and vasomodulatory interventions.     

Electrophoretic coating of amphiphilic chitosan colloids on regulating cellular behaviour

In this communication, we report a facile nanotopographical control over a stainless steel surface via an electrophoretic deposition of colloidal amphiphilic chitosan for preferential growth, proliferation or migration of vascular smooth muscle cells (VSMCs) and human umbilical vein endothelial cells (HUVECs). Atomic force microscopy revealed that the colloidal surface exhibited a deposition time-dependent nanotopographical evolution, wherein two different nanotopographic textures indexed by ‘kurtosis’ (R_kur) value were easily designed, which were termed as ‘sharp’ (i.e. high peak-to-valley texture) surface and ‘flat’ (i.e. low peak-to-valley texture) surface. Cellular behaviour of VSMCs and HUVECs on both surfaces demonstrated topographically dependent morphogenesis, adherent responses and biochemical properties in comparison with bare stainless steel. The formation of a biofunctionalized surface upon a facile colloidal chitosan deposition envisions the potential application towards numerous biomedical devices, and this is especially promising for cardiovascular stents wherein a new surface with optimized texture can be designed and is expected to create an advantageous environment to stimulate HUVEC growth for improved healing performance.     

A search game model of the scatter hoarder's problem

Scatter hoarders are animals (e.g. squirrels) who cache food (nuts) over a number of sites for later collection. A certain minimum amount of food must be recovered, possibly after pilfering by another animal, in order to survive the winter. An optimal caching strategy is one that maximizes the survival probability, given worst case behaviour of the pilferer. We modify certain ‘accumulation games’ studied by Kikuta & Ruckle (2000 J. Optim. Theory Appl.) and Kikuta & Ruckle (2001 Naval Res. Logist.), which modelled the problem of optimal diversification of resources against catastrophic loss, to include the depth at which the food is hidden at each caching site. Optimal caching strategies can then be determined as equilibria in a new ‘caching game’. We show how the distribution of food over sites and the site-depths of the optimal caching varies with the animal''s survival requirements and the amount of pilfering. We show that in some cases, ‘decoy nuts’ are required to be placed above other nuts that are buried further down at the same site. Methods from the field of search games are used. Some empirically observed behaviour can be shown to be optimal in our model.     

Optimal control strategies of eradicating invisible glioblastoma cells after conventional surgery

Glioblastoma, the most aggressive type of brain cancer, has median survival time of 1 year after diagnosis. It is characterized by alternating modes of rapid proliferation and aggressive invasion in response to metabolic stress in the microenvironment. A particular microRNA, miR-451, and its downstream signalling molecules, AMPK complex, are known to be key determinants in switching cell fate. These components form a core control system determining a balance between cell growth and migration which is regulated by fluctuating glucose levels in the microenvironment. An important factor from the treatment point of view is that low levels of glucose affect metabolism and activate cell migration through the miR-451-AMPK control system, creating ‘invisible’ migratory cells and making them inaccessible by conventional surgery. In this work, we apply optimal control theory to deal with the problem of maintaining upregulated miR-451 levels that prevent cell infiltration to surrounding brain tissue and thus induce localization of these cancer cells at the surgical site. The model also considers the effect of a drug that blocks inhibitive pathways of miR-451 from AMPK complex. Glucose infusion control and drug infusion control are chosen to represent dose rates of glucose and drug intravenous administrations, respectively. The characteristics of optimal control lead us to investigate the structure of optimal intravenous infusion regimen under various circumstances and predict best clinical outcomes with minimum expense possible.     

Asymptotic burnout and homeostatic awakening: a possible solution to the Fermi paradox?

Previous studies show that city metrics having to do with growth, productivity and overall energy consumption scale superlinearly, attributing this to the social nature of cities. Superlinear scaling results in crises called ‘singularities’, where population and energy demand tend to infinity in a finite amount of time, which must be avoided by ever more frequent ‘resets’ or innovations that postpone the system''s collapse. Here, we place the emergence of cities and planetary civilizations in the context of major evolutionary transitions. With this perspective, we hypothesize that once a planetary civilization transitions into a state that can be described as one virtually connected global city, it will face an ‘asymptotic burnout’, an ultimate crisis where the singularity-interval time scale becomes smaller than the time scale of innovation. If a civilization develops the capability to understand its own trajectory, it will have a window of time to affect a fundamental change to prioritize long-term homeostasis and well-being over unyielding growth—a consciously induced trajectory change or ‘homeostatic awakening’. We propose a new resolution to the Fermi paradox: civilizations either collapse from burnout or redirect themselves to prioritizing homeostasis, a state where cosmic expansion is no longer a goal, making them difficult to detect remotely.     

Mechanistic analysis of the search behaviour of Caenorhabditis elegans

A central question in movement research is how animals use information and movement to promote encounter success. Current random search theory identifies reorientation patterns as key to the compromise between optimizing encounters for both nearby and faraway targets, but how the balance between intrinsic motor programmes and previous environmental experience determines the occurrence of these reorientation behaviours remains unknown. We used high-resolution tracking and imaging data to describe the complete motor behaviour of Caenorhabditis elegans when placed in a novel environment (one in which food is absent). Movement in C. elegans is structured around different reorientation behaviours, and we measured how these contributed to changing search strategies as worms became familiar with their new environment. This behavioural transition shows that different reorientation behaviours are governed by two processes: (i) an environmentally informed ‘extrinsic’ strategy that is influenced by recent experience and that controls for area-restricted search behaviour, and (ii) a time-independent, ‘intrinsic’ strategy that reduces spatial oversampling and improves random encounter success. Our results show how movement strategies arise from a balance between intrinsic and extrinsic mechanisms, that search behaviour in C. elegans is initially determined by expectations developed from previous environmental experiences, and which reorientation behaviours are modified as information is acquired from new environments.     

Overcoming the blood–brain barrier in neurodegenerative disorders and brain tumours

Drug delivery is one of the major challenges in the treatment of central nervous system disorders. The brain needs to be protected from harmful agents, which are done by the capillary network, the so‐called blood–brain barrier (BBB). This protective guard also prevents the delivery of therapeutic agents to the brain and limits the effectiveness of treatment. For this reason, various strategies have been explored by scientists for overcoming the BBB from disruption of the BBB to targeted delivery of nanoparticles (NPs) and cells and immunotherapy. In this review, different promising brain drug delivery strategies including disruption of tight junctions in the BBB, enhanced transcellular transport by peptide‐based delivery, local delivery strategies, NP delivery, and cell‐based delivery have been fully discussed.Inspec keywords: drugs, tumours, neurophysiology, blood, biochemistry, brain, drug delivery systems, nanoparticles, biomedical materials, molecular biophysics, cellular biophysics, nanomedicine, diseases, proteins, reviewsOther keywords: blood–brain barrier, neurodegenerative disorders, central nervous system disorders, BBB, therapeutic agents, targeted delivery, peptide‐based delivery, local delivery strategies, NP delivery, cell‐based delivery, brain drug delivery strategies, brain tumours, nanoparticles, immunotherapy, review     

Optimal control methods for drug delivery in cancerous tumour by anti‐angiogenic therapy and chemotherapy

There are numerous mathematical models simulating the behaviour of cancer by considering variety of states in different treatment strategies, such as chemotherapy. Among the models, one is developed which is able to consider the blood vessel‐production (angiogenesis) in the vicinity of the tumour and the effect of anti‐angiogenic therapy. In the mentioned‐model, normal cells, cancer cells, endothelial cells, chemotherapy and anti‐angiogenic agents are taking into account as state variables, and the rate of injection of the last two are considered as control inputs. Since controlling the cancerous tumour growth is a challenging matter for patient''s life, the time schedule design of drug injection is very significant. Two optimal control strategies, an open‐loop (calculus of variations) and a closed‐loop (state‐dependent Riccati equation), are applied on the system in order to find an optimal time scheduling for each drug injection. By defining a proper cost function, an optimal control signal is designed for each one. Both obtained control inputs have reasonable answers, and the system is controlled eventually, but by comparing them, it is concluded that both methods have their own benefits which will be discussed in details in the conclusion section.     

Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity

To study the kinetics of lymphocytes, models have divided the cell population into subpopulations with different turnover rates. These have been called ‘kinetic heterogeneity models’ so as to distinguish them from ‘temporal heterogeneity models’, in which a cell population may have different turnover rates at different times, e.g. when resting versus when activated. We model labelling curves for temporally heterogeneous populations, and predict that they exhibit equal biphasic up- and downslopes. We show when cells divide only once upon activation, these slopes are dominated by the slowest exponent, yielding underestimates of the average turnover rate. When cells undergo more than one division, the labelling curves allow fitting of the two exponential slopes in the temporal heterogeneity model. The same data can also be described with a two-compartment kinetic heterogeneity model. In both instances, the average turnover rate is correctly estimated. Because both models assume a different cell biology but describe the data equally well, the parameters of either model have no simple biological interpretation, as each parameter could reflect a combination of parameters of another biological process. Thus, even if there are sufficient data to reliably estimate all exponentials, one can only accurately estimate an average turnover rate. We illustrate these issues by re-fitting labelling data from healthy and HIV-infected individuals.     

An in vivo ratio control mechanism for phospholipid homeostasis: evidence from lipidomic studies

While it is widely accepted that the lipid composition of eukaryotic membranes is under homeostatic control, the mechanisms through which cells sense lipid composition are still the subject of debate. It has been postulated that membrane curvature elastic energy is the membrane property that is regulated by cells, and that lipid composition is maintained by a ratio control function derived from the concentrations of type II and type 0 lipids, weighted appropriately. We assess this proposal by seeking a signature of ratio control in quantified lipid composition data obtained by electrospray ionization mass spectrometry from over 40 independent asynchronous cell populations. Our approach revealed the existence of a universal ‘pivot’ lipid, which marks the boundary between type 0 lipids and type II lipids, and which is invariant between different cell types or cells grown under different conditions. The presence of such a pivot species is a distinctive signature of the operation in vivo, in human cell lines, of a control function that is consistent with the hypothesis that membrane elastic energy is homeostatically controlled.