Organism survival and cell integrity in a freeze-tolerant insect

Larvae and isolated fat body cells of the freeze-tolerant Heleomyza borealis (Diptera, Heleomyzidae) were cooled to sub-zero temperatures between -5 and -40°C at 0.1°C min-1 and then rewarmed at the same rate. Survival of the whole organism, cells cooled in vitro and cells cooled in vivo were assessed using two fluorescent viability stains. The whole animal supercooling point distribution was bimodal, the two groups having means of -2.3 and -9.7°C, suggesting a deficiency of potent ice-nucleating agents in the latter. Whole organism survival declined rapidly below -30°C. Survival of cells cooled within the organism remained in excess of 95% above -25°C and approached 80% at -35°C, whereas the survival of cells cooled in vitro (isolated cells) declined rapidly at -20, reaching 45% at -40°C. The reduced survival of isolated cells is attributed to protective factors within the extra-cellular fluid or tissue structure of the larvae. The pattern of cell survival suggests membrane rupture arising from shrinkage as the cause of cell death, whereas the pattern of whole organism survival is indicative of intra-cellular ice formation or failure of chill injury protective mechanisms at a specific temperature causing death of the organism

Discrete event multi-level models for systems biology

Abstract. Diverse modeling and simulation methods are being applied in the area of Systems Biology. Most models in Systems Biology can easily be located within the space that is spanned by three dimensions of modeling: continuous and discrete; quantitative and qualitative; stochastic and deterministic. These dimensions are not entirely independent nor are they exclusive. Many modeling approaches are hybrid as they combine continuous and discrete, quantitative and qualitative, stochastic and deterministic aspects. Another important aspect for the distinction of modeling approaches is at which level a model describes a system: is it at the “macro ” level, at the “micro ” level, or at multiple levels of organization. Although multi-level models can be located anywhere in the space spanned by the three dimensions of modeling and simulation, clustering tendencies can be observed whose implications are discussed and illustrated by moving from a continuous, deterministic quantitative macro model to a stochastic discrete-event semi-quantitative multi-level model.