Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Mar 9;107(10):4607-11.
doi: 10.1073/pnas.0912198107. Epub 2010 Feb 8.

Amoeboid organism solves complex nutritional challenges

Affiliations

Amoeboid organism solves complex nutritional challenges

Audrey Dussutour et al. Proc Natl Acad Sci U S A. .

Abstract

A fundamental question in nutritional biology is how distributed systems maintain an optimal supply of multiple nutrients essential for life and reproduction. In the case of animals, the nutritional requirements of the cells within the body are coordinated by the brain in neural and chemical dialogue with sensory systems and peripheral organs. At the level of an insect society, the requirements for the entire colony are met by the foraging efforts of a minority of workers responding to cues emanating from the brood. Both examples involve components specialized to deal with nutrient supply and demand (brains and peripheral organs, foragers and brood). However, some of the most species-rich, largest, and ecologically significant heterotrophic organisms on earth, such as the vast mycelial networks of fungi, comprise distributed networks without specialized centers: How do these organisms coordinate the search for multiple nutrients? We address this question in the acellular slime mold Physarum polycephalum and show that this extraordinary organism can make complex nutritional decisions, despite lacking a coordination center and comprising only a single vast multinucleate cell. We show that a single slime mold is able to grow to contact patches of different nutrient quality in the precise proportions necessary to compose an optimal diet. That such organisms have the capacity to maintain the balance of carbon- and nitrogen-based nutrients by selective foraging has considerable implications not only for our understanding of nutrient balancing in distributed systems but for the functional ecology of soils, nutrient cycling, and carbon sequestration.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Experimental setup. (A) No-choice experiment, diet 1:2, with a total concentration of 40 g·L−1. (B) Choice experiment, diet 6:1 vs. diet 1:2. (C) Multiple-choice experiment. The slime mold was initially placed at the center of the petri dish.
Fig. 2.
Fig. 2.
Performance responses. Data were recorded for individual slime molds confined for 60 h to 1 of 35 diets varying in both the ratio and total amount of protein and carbohydrate (40 g·L−1, 9 ratios; 80 g·L−1, 17 ratios; and 160 g·L−1, 9 ratios). Response surfaces were visualized using nonparametric thin-plate splines, which were fitted using the fields package (National Center for Atmospheric Research, Boulder, CO) in the statistical software R (36). Red indicates the highest values for the experimental variable on a given response surface, with values descending to lowest values in dark blue regions. (A) Effect of carbohydrate (C) concentration on proportion of slime that survived. The logistic regression analysis yielded a significant relationship between survival and carbohydrate concentration (χ2 = 299.81, P < 0.001; z = 18.91, P < 0.001). (B) Effects of diet composition on slime mold density [final mass (mg)/final area (cm2)]. The slime molds that did not survive were not included. (C) Effects of diet composition on growth rate [initial mass (mg)/final mass (mg)]. (D) Mean growth rate on a mass basis ± SD as a function of the proportion of carbohydrate in the diet: C/(P + C). The polynomial regression analysis yielded a significant relationship between growth rate and proportion of carbohydrate in the diet (R2 = 0.90, F2,14 = 63.46, P < 0.001). (E) Effects of diet composition on expansion rate [(initial area (cm2)/final area (cm2)]. The response surface regression analyses yielded significant relationships as follows: R2 = 0.65, F5,344 = 125.54, P < 0.001 for survival (surface not plotted, Table S1); R2 = 0.50, F5,294 = 57.74, P < 0.001 for density (Fig. 2B and Table S2); R2 = 0.50, F5,344 = 69.80, P < 0.001 for growth rate (Fig. 2C and Table S1), and R2 = 0.54, F5,344 = 80.44, P < 0.001 for expansion rate (Fig. 2E and Table S1).
Fig. 3.
Fig. 3.
“Intake” regulation when faced with two foods varying in protein (P) and carbohydrate (C) content. Mean growth rate [initial mass (mg)/final mass (mg)] ± SD as a function of the mean proportion of carbohydrates ingested ± SD [C intake/(P intake + C intake)], measured for the binary choice experiment (SI Text describes method used to estimate intake) (n = 10 slime mold fragments per choice treatment, total dietary concentration of P and C in each food was 80 g·L−1). The black curve comes from the no-choice experiments (Fig. 2C).
Fig. 4.
Fig. 4.
“Intake” regulation when faced with multiple foods varying in protein and carbohydrate content. (A) Observed proportional coverage by slime molds of the different foods in the 11-food array compared with the expected proportion if slime molds had grown to cover foods indiscriminately (n = 30 slime molds). To test whether slime molds preferred particular nutrient ratios over others, we used a binomial test on the number of slime molds covering each diet. The null hypothesis was that slime molds could cover each food with equal probability (we computed the probability to cover a particular food knowing that one slime mold could cover between 1 and 3 foods at a time but not more). Slime molds significantly avoided extremely carbohydrate (C)-biased diets (binomial test: P < 0.05 for 1:4, 1:6, and 1:9 ratios) and preferred diets that contained equal proportions of protein (P) and carbohydrate or were slightly protein-biased (binomial test: P < 0.05 for 1:1 and 2:1 ratios). (B) Mean growth rate in term of mass ± SD as a function of the mean proportion of carbohydrates ingested ± SD [C intake/(P intake + C intake)], measured for the multiple-choice experiment (n = 30 slime molds, 11 foods all with a macronutrient concentration of 80 g·L−1). The black curve comes from the no-choice experiments (Fig. 2C).

Comment in

References

    1. Nakagaki T, Yamada H, Tóth A. Maze-solving by an amoeboid organism. Nature. 2000;407:470. - PubMed
    1. Saigusa T, Tero A, Nakagaki T, Kuramoto Y. Amoebae anticipate periodic events. Phys Rev Lett. 2008;100:018101–018104. - PubMed
    1. Latty T, Beekman M. Going into the light: Food quality and the risk of light exposure affect patch choice decisions in the acellular slime mould Physarum polycephalum. Ecology. 2009 in press. - PubMed
    1. Ashworth JM, Dee J. The Biology of Slime Moulds. London: Edward Arnold Ltd.; 1975.
    1. Sauer HW. Developmental Biology of Physarum. Cambridge, UK: Cambridge Univ Press; 1982.

Publication types

MeSH terms

LinkOut - more resources