Preface (2008)

You have accessMoreSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditEmail Cite this article Mosekilde Erik and Tass Peter A 2008PrefacePhil. Trans. R. Soc. A.3663437–3444http://doi.org/10.1098/rsta.2008.0130SectionYou have accessPreface Erik Mosekilde Erik Mosekilde Department of Physics, Technical University of Denmark2800 Kongens Lyngby, Denmark [email protected] Google Scholar Find this author on PubMed Search for more papers by this author and Peter A Tass Peter A Tass Research Center Jülich52425 Jülich, Germany Google Scholar Find this author on PubMed Search for more papers by this author Erik Mosekilde Erik Mosekilde Department of Physics, Technical University of Denmark2800 Kongens Lyngby, Denmark [email protected] Google Scholar Find this author on PubMed Search for more papers by this author and Peter A Tass Peter A Tass Research Center Jülich52425 Jülich, Germany Google Scholar Find this author on PubMed Search for more papers by this author Published:16 July 2008https://doi.org/10.1098/rsta.2008.0130Developing a coherent and quantitative description of the complex structures and functions we meet in the living world represents a fantastic challenge not only to the biological and medical sciences but also to physics, mathematics and computational science. This issue of Phil. Trans. R. Soc. A presents contributions from leading research groups in the field of ‘Biomedical applications of systems biology and biological physics’. The aim is to show how systems biology can help us establish a more detailed understanding of the processes underlying the regulation and functioning of living systems and how biological physics can provide us with new effective tools to investigate biological phenomena at the molecular as well as the cellular and the physiological levels. We also demonstrate how these insights and techniques can contribute towards a better treatment of patients with diseases such as cancer and Parkinson's tremor.Biological complexity arises partly from the enormous number of interacting processes that take place in the individual cell and functional unit. The human genome, for instance, codes for more than 100 000 different proteins, and the number of possible interactions between the genome and its protein products are inconceivable and, even if we knew them, unmanageable in any form of detailed mathematical model.Biological complexity also arises from the heterogeneity of the different tissues, from the many levels of hierarchical control, and from the enormous spans of time and space over which this control takes place. At the cellular level temporal scales of the order of 10−9 s, characteristic for instance of molecular conformation changes, are important whereas processes such as the remodelling of the vascular system or bone structure during ageing involve time scales of the order of years (108 s). Similarly, while molecular interactions take place on a nanometre scale (10−9 m), nerve signals to activate skeletal muscles or report on changes in skin temperature travel over distances of the order of a metre. Each time the description passes from one level to the next in the structural hierarchy, new phenomena tend to emerge from interactions that occur at the lower level, and it is probably correct to say that we dispose of neither the physical concepts nor the mathematical tools to deal with such multi-hierarchical and heterogeneous structures in a realistic model.Many diseases are considered not only to have a genetic origin but also to depend on the living conditions and the lifestyle of the patient. The diseases typically manifest themselves through the dysfunction of particular cells or regulatory mechanisms, and most of the drugs we use today must be considered to act on the cellular level. There is an obvious need for an approach that can integrate these different levels and scales. The so-called adiabatic approach that we use in many areas of physics to separate processes on different time scales is clearly much more problematic in the biological realm where the integration and mutual interaction among the various processes often play an essential role.A third contribution to the complexity that we observe in living systems derives from the fact that such systems operate at far-from-equilibrium conditions. This is, perhaps, most clearly demonstrated through the significant differences in the concentrations of different ions that the cells maintain across their plasma membranes. These differences allow the cells to produce the often complicated electrophysiological signals they need to regulate their internal processes and to communicate with neighbouring cells. The cells may also produce other types of oscillatory dynamics associated with their metabolic activity or with the mechanism of calcium-induced calcium release. This latter mechanism, which is involved, for instance, in the activation of the smooth muscle cells in the arteriolar walls, produces a positive feedback by which the influx of calcium through the cell membrane can cause the release of additional calcium from stores in the cell. Interaction among the various oscillatory processes can produce even more complicated nonlinear dynamic phenomena such as synchronization, bursting and different types of deterministic chaos. As several contributions to the present issue will show, such phenomena can be part of the normal physiological regulation, or they can mark a state of disease.Under these conditions, a model can never be ‘true’ or ‘complete’, but modelling becomes an ‘art’ associated with the ability to isolate the essential explanatory factors of a particular phenomenon and to combine these factors into a coherent picture. The model becomes a vehicle for learning and a tool for the gradual accumulation and consolidation of information. The validation of the model is based on its ability to reproduce a broad spectrum of different observations in terms of physiologically realistic mechanisms and with independently determined parameter values. The ‘value’ of the model is judged on its ability to create insights and to predict phenomena that have not previously been observed.As mentioned above, biological physics can contribute through the development of new effective techniques to investigate biological phenomena at the molecular and cellular levels. Optical tweezers, for instance, allow us to move individual protein molecules in the cellular membrane or to follow the motion of individual vesicles in the live cell. Hence, we can determine the fluidity of the membrane and examine the processes by which vesicles are transported through the cell. In vitro experiments allow us to measure the elastic properties of individual microtubules and thus, for instance, analyse the effect of certain anti-cancer drugs that work by distorting the growth of microtubules, thus inhibiting cell division. Similarly, the combined techniques of surface-enhanced Raman spectroscopy and chiral vibrational spectroscopy allow us to study conformational changes of biological molecules in the living cell at submicromolar concentrations. In this way we can distinguish, for instance, between different binding states of haemoglobin.In the first contribution to the present issue, Mukhtarov et al. (2008) demonstrate and characterize two new genetically encoded fluorescent probes that can be used, respectively, to monitor intracellular chloride concentrations and the activity of glycine-activated chloride channels. Genetically encoded optical probes are particularly powerful tools for non-invasive studies of cellular ion and protein distributions because they can be expressed in specific cellular compartments, remain in the cells for a relatively long time and are non-toxic. The second of the two probes appears to be the first example of a molecular probe for non-invasive monitoring of receptor-operated channel function. The authors first show results for the temporal variation of the intracellular chloride concentration in rat retina cells and for the age-related changes in this variation. Next, the authors illustrate the distribution of glycine receptors as observed in a confocal microscope by means of their fluorescent probe and obtain current-voltage characteristics for the glycine-induced chloride current in Chinese hamster ovary cells.The second contribution, by Brazhe et al. (2008), presents the results of a laser interference microscopy study of the morphology and dynamic properties of myelinated nerve fibres from the grass frog Rana temporaria. The authors determine the rhythmic activity in various parts of the cells and identify some of the most pronounced components as arising from potassium fluxes through the plasma membrane and from ‘breathing’ movements of Schwann cell lamellae. Laser interference microscopy represents another new technique for non-invasive studies of live cells. In this case, the approach is based on measuring the phase shift of a light beam that passes through the cell. This phase shift depends on the intrinsic optical properties along the beam and thus reflects variations in membrane potential and fluidity, motion of membrane-bound proteins, changes in intracellular calcium concentrations, displacements of organelles and transport of vesicles, as well as several other processes. A particular asset of this technique is that these different processes are all detected simultaneously. Hence, the technique can reveal existing interactions among the biological processes. On the other hand, one needs to combine measurements performed under a variety of different conditions with advanced statistical methods to unravel the various contributions.The next two contributions use relatively detailed cellular models to study the effect of intercellular coupling. Jacobsen et al. (2008) consider the role of cellular heterogeneity and weak coupling in explaining the experimentally observed gradual synchronization characteristics for smooth muscle cells in vascular resistance vessels. Fluorescent microscopic studies show that these cells at low activation levels display asynchronous wave-like fluctuations in their cytoplasmic calcium concentrations. As the muscles are activated, by rising blood pressure for instance, an increasing number of cells are recruited into a synchronized oscillatory state, and this transition gives rise to the relatively low-frequency rhythmic contractions of the vessel, known as vasomotion. The model considers a system of some 20 cells arranged in a two-dimensional lattice and coupled via gap junctions. Cellular heterogeneity is represented through a statistical distribution of volume fractions of sarcoplasmic reticulum (the main intracellular calcium store), and the simulated percentage of quiescent cells is compared with experimentally obtained curves for varying concentrations of noradrenalin.Zhang et al. (2008) study the coupling of mouse pancreatic β-cells. Over the years, patch clamping and other experimental techniques have provided a relatively clear picture of the stimulus-secretion coupling in pancreatic β-cells: via a metabolically induced increase in the ATP:ADP ratio, increasing glucose level leads to closure of KATP channels, the depolarization of the cell membrane, firing of action potentials and opening of the voltage-gated calcium channels. The influx of calcium then initiates the exocytosis of insulin-carrying granules. So far, most patch-clamp experiments have been performed on isolated cells maintained in short-term culture. There is accumulating evidence to show, however, that the cellular properties may change when the cells are deprived of their normal environment. The authors have developed a method that allows experiments to be made on cells in intact islets. Using a combination of different patch-clamp techniques, the authors determine the gap junctional coupling among the β-cells in an islet and show that the β-cells do not couple to other pancreatic cells. By modelling a system of coupled β-cells, they hereafter show that the measured coupling strengths and coordination numbers can explain the experimentally observed propagation of cytoplasmic calcium waves across the islets.The contribution by Pedersen et al. (2008) continues the analysis of insulin secretion by pancreatic β-cells. When the pancreas responds to a rapidly rising glucose level, the response typically displays a biphasic pattern, i.e. an initial relatively fast and short response is succeeded by a slower and more permanent response. The paper develops a model of this phenomenon based on the notion of three distinct intracellular pools of insulin-carrying granules combined with presently accepted ideas about the mechanisms that control the mobilization of the granules, priming, exocytosis and the so-called kiss-and-run events. The model also assumes that different β-cells may activate at different glucose concentrations. These assumptions allow the authors to reproduce a range of experimental observations, including the so-called staircase phenomenon that underlies the notion of ‘pancreatic derivative control’, i.e. that the pancreas can respond to the rate of change of the blood glucose concentration.The following two contributions reassume the discussion of synchronization, but now from the point of using mathematical analyses of cellular synchronization phenomena to improve the treatment of patients with tremor (caused by type 2 spinocerebellar ataxia) and intestinal cancer.High-frequency test stimulation is a standard procedure for target localization in deep brain stimulation treatments of patients with tremor. However, this method does not work in cases where the tremor disappears under global anaesthesia as applied during the insertion of the electrode. To avoid this problem, Barnikol et al. (2008) have developed a stimulation technique that evokes tremor in a well-defined and quantifiable manner. The new technique uses patterned low-frequency stimulation, i.e. brief high-frequency pulse trains applied at pulse rates similar to typical neuronal burst frequencies. Without violating safety criteria, this technique makes it possible to attain significantly higher charge densities in the target area than single pulse stimulation. By numerically simulating a network of interacting neurons, the authors have demonstrated that patterned low-frequency stimulation, even at relatively low amplitudes, can synchronize the cells in a mode that is phase-locked to the stimulation pulse, and that this effect is little sensitive to the stimulation frequency. The approach was subsequently applied to a patient with pronounced tremor that vanished under general anaesthesia. The results were found to be in accordance with the mathematical predictions and the target selection was confirmed by excellent postoperative tremor suppression.While coordinated by hypothalamic pacemaker signals, the circadian timing system is present in every single cell of the human body. It modulates physical activity, hormonal secretion, metabolic rates for many drugs and many other processes. The potential benefits from a chronotherapeutic approach to the treatment of cancer are associated with the tight relation that exists between the circadian rhythm and both the cell proliferation cycle and the variation in toxicity and efficacy of many anti-cancer drugs. In previous work, Lévi et al. demonstrated that an 8 hour shift in dosing time in experimental models may account for an eightfold increase in tolerability for more than 30 anti-cancer drugs, and these findings have led to the development of a circadian delivery schedule that produces fivefold fewer incidents of severe toxicity than a constant or incorrectly timed dosing. In order to establish an optimal basis for the use of chronotherapy in the treatment of colorectal cancer, Lévi et al. (2008) develop both a cell cycle automaton model synchronized by the circadian clock and a deterministic model of anti-cancer drug chronopharmacodynamics. In silico testing of these models reveals the key roles played by variability in the cell cycle phase durations and by the degree of circadian entrainment. The simulations also reveal new and optimal circadian schedules for anti-cancer drug delivery, depending on the therapeutic strategy adopted for a given patient.In spite of the significant improvements that may derive from chronotherapy not only of cancer, but of many other diseases as well, identification of new biomarkers for the early detection of neoplastic cells and the development of new types of anti-cancer drugs remain a primary focus. However, as demonstrated by the above contributions, the development of detailed mechanistic models of the cell cycle regulation and of the way anti-cancer drugs interfere with the processes of cell division must go hand in hand with experimental and clinical work.The objective of the contribution by Lehotzky et al. (2008) is to demonstrate the effects of KAR-2, a potent anti-mitotic component, and TPPP/p25 (25 kDa tubulin polymerization promoting protein), a new brain-specific, intrinsically unstructured protein, on the functional and structural characteristics of the microtubular system. This system is consistently restructured during the cell cycle and plays an important role in the actual cell division process (duplication of the microtubular organizing centres must occur, for instance, before the gene pairs can be separated). Whereas KAR-2 directly targets mitotic spindles resulting in the arrest of cell division in the M phase of the cell cycle, the mechanisms underlying the observed anti-mitotic effects of TPPP/p25 are less clear. It appears that this protein can also be expressed in non-central nervous system tissue and that upregulation of its expression leads to cell differentiation and to prolonged phases a quiescent (neuron-like) behaviour. Other important conclusions of the study are that KAR-2 demonstrates unique bioavailability properties. The obtained data suggest that KAR-2 displays a better absorption profile, a broader tissue distribution and a more effective penetration to cancer cells than its mother drug, vinblastine.Using a model of relevance to drug development as an example, the contribution by Sahle et al. (2008) presents a new strategy for assessing parameter sensitivity for large biological models. In practice, the values of many parameters used in such models may not be determined very accurately or they are not amenable to direct measurement. Sensitivity analysis may then be applied to quantify the importance of the various parameters to the overall behaviour of the model and, thus, to evaluate the accuracy of the model predictions. In this connection, it is important to realize that a physiologically based model may contain many parameters, to the value of which the model shows little sensitivity. To avoid the expensive computations required to perform a complete sensitivity analysis the authors suggest an approach that is based on a combination of optimization techniques and random sampling methods. The authors demonstrate their idea by finding the maximum and minimum values of the metabolic control coefficients in a model of skeletal muscle glycolysis.The nephrons of the kidney are known to regulate their incoming blood flow through two different mechanisms, a myogenic mechanism that is related to the vasomotor phenomena discussed by Jacobsen et al. (2008) and a so-called tubuloglomerular feedback (TGF) mechanism that regulates the diameter of the afferent arteriole in response to variations in the salt concentration near the terminal point of the loop of Henle. Tubular pressure measurements on rats have shown that the TGF mechanism produces oscillations in the nephron pressures and flows at frequencies of approximately 0.02–0.05 Hz, and that these oscillations can synchronize among neighbouring nephrons. Gorbach et al. (2008) apply a high-resolution infrared camera to assess rhythmicity in the local blood flow at the kidney surface and to determine the extent of regions with spontaneous oscillations. This new approach was found capable of following changes in renal perfusion during baseline conditions, occlusion of the main renal artery and administration of either saline or papaverin (a calcium channel blocker that relaxes heart and smooth muscle tissue). This supports the use of the IR imaging technique to check blood perfusion after kidney transplantation. At the same time, spontaneous vascular oscillations centred approximately at 0.02–0.05 Hz and near 0.01 Hz could be reproducibly detected. Similar very-low frequency vasomotor oscillations have recently been observed in other vascular beds and, in combination with other techniques, the use of highly sensitive IR imaging techniques holds promise for a better understanding of the role and underlying causal factors of vasomotor activity.The blood coagulation system plays a principal role in maintaining proper conditions for the flow of blood. The insufficient activity of this system may lead to bleeding and the loss of blood. Excessive activity, on the other hand, may cause intravascular blood coagulation, thromboses and embolization. It is also known that changes in the blood coagulation processes can occur fairly rapidly. However, most of the methods that are currently used for monitoring the blood coagulation system from the of In the contribution to this issue, et al. 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