Quantitative evolutionary design

Abstract

The field of quantitative evolutionary design uses evolutionary reasoning (in terms of natural selection and ultimate causation) to understand the magnitudes of biological reserve capacities, i.e. excesses of capacities over natural loads. Ratios of capacities to loads, defined as safety factors, fall in the range 1.2-10 for most engineered and biological components, even though engineered safety factors are specified intentionally by humans while biological safety factors arise through natural selection. Familiar examples of engineered safety factors include those of buildings, bridges and elevators (lifts), while biological examples include factors of bones and other structural elements, of enzymes and transporters, and of organ metabolic performances. Safety factors serve to minimize the overlap zone (resulting in performance failure) between the low tail of capacity distributions and the high tail of load distributions. Safety factors increase with coefficients of variation of load and capacity, with capacity deterioration with time, and with cost of failure, and decrease with costs of initial construction, maintenance, operation, and opportunity. Adaptive regulation of many biological systems involves capacity increases with increasing load; several quantitative examples suggest sublinear increases, such that safety factors decrease towards 1.0. Unsolved questions include safety factors of series systems, parallel or branched pathways, elements with multiple functions, enzyme reaction chains, and equilibrium enzymes. The modest sizes of safety factors imply the existence of costs that penalize excess capacities. Those costs are likely to involve wasted energy or space for large or expensive components, but opportunity costs of wasted space at the molecular level for minor components.

Figure 1

Examples of the frequency distribution of a capacity and of the load upon it (ordinate), as a function of load units (abscissa) The failure zone (shaded) represents the range of load units over which the load exceeds the capacity, so that system performance fails. The ratio of the mean value of capacity to load (A/B) is defined as the safety factor. Upper panel, high coefficients of variation of capacity and load; lower panel, low coefficients of variation. Note that more variable capacities or loads mandate higher safety factors in order to reduce the failure zone to an acceptably low value. Modified from Fig. 1a of Alexander (1981).

Figure 3

The safety factor for the small intestinal brush border glucose transporter SGLT1 of female mice as a function of glucose intake, which increases during lactation, at low ambient temperature, and with increased pup mass Data are from the experiments of Fig. 2 plus experiments involving increased pup mass. Symbols: virgin mice at a temperature of 23 °C (•) or 5 °C (▪); lactating mice at 23 °C (▿, ⋄) or 5 °C (□); lactating mice at 23 °C with pup mass increased above normal by experimentally prolonging the obligate period of lactation (▵). Note that the safety factor decreases towards 1.0 with increasing glucose intake, because glucose transport (proportional to intestinal mass) increases with glucose intake with a slope less than 1.0 (Fig. 2).

Figure 2

Intestinal hypertrophy with hyperphagia: mass of a female mouse's small intestine as a function of the mouse's daily load intake, which increases during lactation and at low ambient temperature Symbols: virgin mice at a temperature of 23 °C (•) or 5 °C (▴); lactating mice at 23 °C (□) or 5 °C (▵). Data are from Hammond & Diamond (1992, 1994) and from Hammond et al. (1994). Note that intestinal mass increases linearly with food intake, but with a slope of less than 1.0.