David B. Dusenbery Explained

David B. Dusenbery is a biophysicist with a central interest in how information influences the behavior of organisms. In later years, he also considered the physical constraints hydrodynamics imposes on microorganisms and gametes.

Research

Most of Dusenbery's research deals with how information controls behavior. At Caltech and the early years at Georgia Tech, Dusenbery focused on experimental studies of the nematode Caenorhabditis elegans because of its small nervous system and favorable genetics.

These experimental studies inspired the development of several innovative techniques:

Initially, Dusenbery was attempting to understand the flow of information in the nervous system of this simple animal. Later, he turned to the flow of information outside the organism, and how physics constrains how organisms behave.[9] More recently, he has also considered hydrodynamic constraints on small organisms, which can only swim at low speeds, where viscosity is far more important than inertia (low Reynolds numbers).[10]

From physical analysis, Dusenbery predicted[11] that the long-held belief that bacteria were too small to employ spatial sensing mechanisms to follow chemical gradients[12] [13] [14] [15] [16] [17] [18] [19] was erroneous and predicted that bacteria following steep gradients of chemicals at high concentrations would benefit from using a spatial mechanism. In 2003, a new bacterial species was discovered that swim sideways and respond to differences in oxygen concentration at the two ends of the cell, allowing them to follow steep gradients of oxygen.[20]

Similar considerations have also been applied to the behaviors of gametes, leading to an explanation of why the sperm/egg (ovum) and thus the male/female distinctions exist.[21] [22] [23]

References

  1. Dusenbery, David B. (1973). Countercurrent separation: A new method for studying behavior of small aquatic organisms. Proceedings of the National Academy of Sciences USA, Vol. 70, pp. 1349-1352.
  2. Dusenbery, D.B. (1980). Responses of nematode C. elegans to controlled chemical stimulation. Journal of Comparative Physiology, Vol. 136, pp. 327-331.
  3. Dusenbery, D.B. (1985). Using a microcomputer and video camera to simultaneously track 25 animals. Computers in Biology & Medicine, Vol. 15, pp. 169-175.
  4. Dusenbery, D.B. (1985). Using a microcomputer and video camera to simultaneously track 25 animals. Journal of Chemical Ecology, Vol. 11, pp. 1239-1247.
  5. M.E. Mccallum and D.B. Dusenbery. (1992). Responses of nematode C. elegans to controlled chemical stimulation. Journal of Chemical Ecology, Vol. 18, pp. 585-592.
  6. P.L. Williams & D.B. Dusenbery (1988). Using the nematode C. elegans to predict mammalian acute lethality to metallic salts. Toxicology and Industrial Health, Vol. 4, pp. 469-478.
  7. S.G. Donkin & D.B. Dusenbery (1993).A soil toxicity test using the nematode Caenorhabditis elegans and an effective method of recovery. Archives of Environmental Contamination and Toxicology, Vol. 25, pp. 145-151.
  8. P.J. Middendorf & D.B. Dusenbery (1993). Fluoroacetic acid is a potent and specific inhibitor of reproduction in the nematode Caenorhabditis elegans. Journal of Nematology, Vol. 25, pp. 573-577.
  9. Dusenbery, David B. (1992). Sensory Ecology. W.H. Freeman., New York. .
  10. Dusenbery, David B. (2009). Living at Micro Scale. Harvard U. Press. .
  11. David B. Dusenbery (1998). Spatial Sensing of Stimulus Gradients Can Be Superior to Temporal Sensing for Free-Swimming Bacteria. Biophysical Journal, Vol. pp. 2272–2277.
  12. Macnab, R. M., and D. E. Koshland, Jr. 1972. The gradient-sensing mechanism in bacterial chemotaxis. Proc. Natl. Acad. Sci. U.S.A. 69: 2509 –2512.
  13. Adler, J. 1975. Chemotaxis in bacteria. Annu. Rev. Biochem. 44:341–356.
  14. Macnab, R. M. 1978. Motility and chemotaxis. In Escherichia coli and Salmonella typhimurium: Cellular and Molecular Biology. F. C. Neid- hardt, editor. Am. Soc. Microbiol., Washington, D.C. 732–759.
  15. Carlile, M. J. 1980. Positioning mechanisms: the role of motility, taxis and tropism in the life of microorganisms. In Contemporary Microbial Ecol- ogy. D. C. Ellwood, M. J. Latham, J. N. Hedger, J. M. Lynch, and J. H. Slater, editors. Academic Press, London. 55–74.
  16. Jackson, G. A. 1987. Simulating chemosensory responses of marine mi- croorganism. Limnol. Oceanogr. 32:1253–1266.
  17. Jackson, G. A. 1989. Simulation of bacterial attraction and adhesion to falling particles in an aquatic environment. Limnol. Oceanogr. 34: 514–530.
  18. Ford, R. M. 1992. Mathematical modeling and quantitative characterization of bacterial motility and chemotaxis. In Modeling the Metabolic and Physiology Activities of Microorganisms. Wiley, New York. 177–215.
  19. Mitchell, J. G., L. Pearson, S. Dillon, and K. Kantalis. 1995. Natural assemblages of marine bacteria exhibiting high-speed motility and large accelerations. Appl. Environ. Microbiol. 61:4436–4440.
  20. Roland Thar and Michael Kühl (2003). Bacteria are not too small for spatial sensing of chemical gradients: An experimental evidence. Proc. Natl. Acad. Sci. USA, Vol. 100, pp. 5748–5753.
  21. Dusenbery, D.B. (2000). Selection for high gamete encounter rates explains the success of male and female mating types. J. Theoret. Biol. 202:1-10.
  22. Dusenbery, D.B. (2002). Ecological Models Explaining the Success of Distinctive Sperm and Eggs (Oogamy). J. Theoretical Biol. 219:1-7.
  23. Dusenbery, D.B. (2006). Selection for high gamete encounter rates explains the evolution of anisogamy using plausible assumptions about size relationships of swimming speed and duration. J. Theoretical Biol. 241:33-8.

Notable publications

Books

Research papers

External links