Innovation at the intersection of synthetic and systems biology

The promises of modern biotechnology hinge upon the hope that we can understand microscopic cellular complexity and in doing so create novel function. In this regard, the fields of systems and synthetic biology are important for accelerating both our understanding of biological systems and our ability to quantitatively engineer cells. At the nexus of these two fields is a unique synergy that can help attain these goals. Thus, the next greatest advances in biology and biotechnology are arising at the intersection of the top-down systems approach and the bottom-up synthetic approach. Collectively, these developments enable the precise control of cellular state for systems studies and the discovery of novel parts, control strategies, and interactions for the design of robust synthetic function. This review seeks to highlight this activity as well as provide a perspective for future directions. Combining these efforts can provide novel insights into cellular function and lead to robust, novel synthetic design.     

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage‐structured, seasonal, nonlinear, two‐sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture‐mark‐recapture analysis, we find that seasonal sea ice concentration anomalies (SIC_a) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SIC_a, because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SIC_a. We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SIC_a, which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.     

Does Dormancy Increase Fitness of Bacterial Populations in Time-Varying Environments?

A simple family of models of a bacterial population in a time varying environment in which cells can transit between dormant and active states is constructed. It consists of a linear system of ordinary differential equations for active and dormant cells with time-dependent coefficients reflecting an environment which may be periodic or random, with alternate periods of low and high resource levels. The focus is on computing/estimating the dominant Lyapunov exponent, the fitness, and determining its dependence on various parameters and the two strategies—responsive and stochastic—by which organisms switch between dormant and active states. A responsive switcher responds to good and bad times by making timely and appropriate transitions while a stochastic switcher switches continuously without regard to the environmental state. The fitness of a responsive switcher is examined and compared with fitness of a stochastic switcher, and with the fitness of a dormancy-incapable organism. Analytical methods show that both switching strategists have higher fitness than a dormancy-incapable organism when good times are rare and that responsive switcher has higher fitness than stochastic switcher when good times are either rare or common. Numerical calculations show that stochastic switcher can be most fit when good times are neither too rare or too common. This research was supported by NSF Grant DMS 0414270, Department of Mathematics, Arizona State University, Tempe, AZ.     

Analysis of Spix's disc-winged bat association patterns and roosting home ranges reveal a novel social structure among bats

Spix's disc-winged bats, Thyroptera tricolor, roost in young, rolled leaves of Heliconia or Calathea plants. In this paper, we examined how the combination of high habitat availability, low occupancy rate and short longevity of those roosts may affect the pattern of interactions among individuals in the population. We regularly censused a 5.69-ha study area in northeastern Costa Rica and examined patterns of association using mark-recapture data. Thyroptera tricolor formed behaviourally cohesive social groups of mixed sex, ranging in size from four to 14 individuals. Approximately 85% of dyads maintained associations over time periods of up to 100 days, and 40% of dyads maintained longer-term associations of at least 420 days across sex classes. Individuals within social groups did not always roost together, but they shared a small common roosting home range, which averaged just 0.19 ha. Members of different social groups rarely associated, although limited associations between members of select social groups in one subunit were observed. However, roosting home ranges of adjacent social groups often overlapped (up to 39% of home ranges, and up to 92% of the area of the smaller home range), and home range centres were situated less than 100 m apart. Thus, social groups rarely interacted but overlapped in space. The features of this social system are unique among bats and mammals in general, and point to groupings based on kinship or cooperation.     

Spatio-temporal variation in Markov chain models of subtidal community succession

In this paper we ask whether succession in a rocky subtidal community varies in space and time, and if so how much affect that variation has on predictions of community dynamics and structure. We describe succession by Markov chain models based on observed frequencies of species replacements. We use loglinear analysis to detect and quantify spatio‐temporal variation in the transition matrices describing succession. The analysis shows that space and time, but not their interaction, have highly significant effects on transition probabilities. To explore the ecological importance of the spatio‐temporal variability detected in this analysis, we compare the equilibria and the transient dynamics among three Markov chain models: a time‐averaged model that includes the effects of space on succession, a spatially averaged model that include the effects of time, and a constant matrix that averages over the effects of space and time. All three models predicted similar equilibrium composition and similar rates of convergence to equilibrium, as measured by the damping ratio or the subdominant Lyapunov exponent. The predicted equilibria from all three models were very similar to the observed community structure. Thus, although spatial and temporal variation is statistically significant, at least in this system this variation does not prevent homogeneous models from predicting community structure.