Bridging the gaps in systems biology

Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding—the elucidation of the basic and presumably conserved “design” and “engineering” principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.     

Global dynamic optimization approach to predict activation in metabolic pathways

Background

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been succesfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework.

Results

In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results.

Conclusions

The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.     

Timing matters

Cells are entities in space and time. Systems biology strives to understand their composition, structural organization as well as dynamic behavior under different conditions. Here, measures for dynamic properties such as characteristic times, time hierarchy and time-dependent response are reviewed. Using a number of examples from yeast and micro-organism systems biology, the importance of considering the timing in experimental and theoretical research is discussed.     

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. AVAILABILITY: http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.     

How the gene content of human sex chromosomes evolved

The X and Y chromosomes of humans and other mammals both have very atypical gene contents. The degenerate Y bears only a handful of genes that are specialized for male sex and reproduction. Now it seems that the X over-represents genes controlling reproductive traits and intelligence. This is hard to explain in terms of function but makes excellent sense in terms of evolution. Comparisons between the gene content of the X and Y in humans, distantly related mammals, and other vertebrates, define the evolutionary past of our sex chromosomes and suggest how special selective forces act on the X and Y.     

Genome-wide analysis of the diatom cell cycle unveils a novel type of cyclins involved in environmental signaling

Background

Despite the enormous importance of diatoms in aquatic ecosystems and their broad industrial potential, little is known about their life cycle control. Diatoms typically inhabit rapidly changing and unstable environments, suggesting that cell cycle regulation in diatoms must have evolved to adequately integrate various environmental signals. The recent genome sequencing of Thalassiosira pseudonana and Phaeodactylum tricornutum allows us to explore the molecular conservation of cell cycle regulation in diatoms.

Results

By profile-based annotation of cell cycle genes, counterparts of conserved as well as new regulators were identified in T. pseudonana and P. tricornutum. In particular, the cyclin gene family was found to be expanded extensively compared to that of other eukaryotes and a novel type of cyclins was discovered, the diatom-specific cyclins. We established a synchronization method for P. tricornutum that enabled assignment of the different annotated genes to specific cell cycle phase transitions. The diatom-specific cyclins are predominantly expressed at the G1-to-S transition and some respond to phosphate availability, hinting at a role in connecting cell division to environmental stimuli.

Conclusion

The discovery of highly conserved and new cell cycle regulators suggests the evolution of unique control mechanisms for diatom cell division, probably contributing to their ability to adapt and survive under highly fluctuating environmental conditions.     

Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation

Parameterized models of biophysical and mechanical cell properties are important for predictive mathematical modeling of cellular processes. The concepts of turgor, cell wall elasticity, osmotically active volume, and intracellular osmolarity have been investigated for decades, but a consistent rigorous parameterization of these concepts is lacking. Here, we subjected several data sets of minimum volume measurements in yeast obtained after hyper-osmotic shock to a thermodynamic modeling framework. We estimated parameters for several relevant biophysical cell properties and tested alternative hypotheses about these concepts using a model discrimination approach. In accordance with previous reports, we estimated an average initial turgor of 0.6 ± 0.2 MPa and found that turgor becomes negligible at a relative volume of 93.3 ± 6.3% corresponding to an osmotic shock of 0.4 ± 0.2 Osm/l. At high stress levels (4 Osm/l), plasmolysis may occur. We found that the volumetric elastic modulus, a measure of cell wall elasticity, is 14.3 ± 10.4 MPa. Our model discrimination analysis suggests that other thermodynamic quantities affecting the intracellular water potential, for example the matrix potential, can be neglected under physiological conditions. The parameterized turgor models showed that activation of the osmosensing high osmolarity glycerol (HOG) signaling pathway correlates with turgor loss in a 1:1 relationship. This finding suggests that mechanical properties of the membrane trigger HOG pathway activation, which can be represented and quantitatively modeled by turgor.     

Mortality and major disease risk among migrants of the 1991–2001 Balkan wars to Sweden: A register-based cohort study

BackgroundIn recent decades, millions of refugees and migrants have fled wars and sought asylum in Europe. The aim of this study was to quantify the risk of mortality and major diseases among migrants during the 1991–2001 Balkan wars to Sweden in comparison to other European migrants to Sweden during the same period.Methods and findingsWe conducted a register-based cohort study of 104,770 migrants to Sweden from the former Yugoslavia during the Balkan wars and 147,430 migrants to Sweden from 24 other European countries during the same period (1991–2001). Inpatient and specialized outpatient diagnoses of cardiovascular disease (CVD), cancer, and psychiatric disorders were obtained from the Swedish National Patient Register and the Swedish Cancer Register, and mortality data from the Swedish Cause of Death Register. Adjusting for individual-level data on sociodemographic characteristics and emigration country smoking prevalence, we used Cox regressions to contrast risks of health outcomes for migrants of the Balkan wars and other European migrants. During an average of 12.26 years of follow-up, being a migrant of the Balkan wars was associated with an elevated risk of being diagnosed with CVD (HR 1.39, 95% CI 1.34–1.43, p < 0.001) and dying from CVD (HR 1.45, 95% CI 1.29–1.62, p < 0.001), as well as being diagnosed with cancer (HR 1.16, 95% CI 1.08–1.24, p < 0.001) and dying from cancer (HR 1.27, 95% CI 1.15–1.41, p < 0.001), compared to other European migrants. Being a migrant of the Balkan wars was also associated with a greater overall risk of being diagnosed with a psychiatric disorder (HR 1.19, 95% CI 1.14–1.23, p < 0.001), particularly post-traumatic stress disorder (HR 9.33, 95% CI 7.96–10.94, p < 0.001), while being associated with a reduced risk of suicide (HR 0.68, 95% CI 0.48–0.96, p = 0.030) and suicide attempt (HR 0.57, 95% CI 0.51–0.65, p < 0.001). Later time period of migration and not having any first-degree relatives in Sweden at the time of immigration were associated with greater increases in risk of CVD and psychiatric disorders. Limitations of the study included lack of individual-level information on health status and behaviors of migrants at the time of immigration.ConclusionsOur findings indicate that migrants of the Balkan wars faced considerably elevated risks of major diseases and mortality in their first decade in Sweden compared to other European migrants. War migrants without family members in Sweden or with more recent immigration may be particularly vulnerable to adverse health outcomes. Results underscore that persons displaced by war are a vulnerable group in need of long-term health surveillance for psychiatric disorders and somatic disease.

Edda Bjork Thordardottir and co-workers study health outcomes among migrants from the former Yugoslavia to Sweden.     

Decline in serum antibodies to methyltetrahydrophthalic anhydride after cessation of exposure.Implications for use as a biomarker

T he association between exposure intensity and serum levels of immunoglobulins E and G against low molecular weight compounds was evaluated. The decay of levels of specific IgE and IgG antibodies was studied after cessation of exposure in workers exposed to the inhalant allergen methyltetrahydrophthalic anhydride in a plant using epoxy resins. Sera have been collected in workers for 18-84 (mean value 54) months after cessation of exposure. Specific IgE and IgG was assessed by RAST and ELISA, respectively. The mean of individual half-times for IgE ( N = 10) and IgG ( N = 8) was 0 9 (range 0 1-1 8) and 0 4 (range 0 2-0 6) years, respectively, after total avoidance of exposure. Corresponding decreases of IgE and IgG were also observed after reduction, but not total elimination, of exposure. No correlation was seen between biologic halftimes of specific IgE and total IgE, atopy, smoking habits or gender. The results indicate that the levels of specific antibodies in sensitized individuals reflect long term exposure, and may persist for years after the end of exposure.