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Microbial Ecology

, Volume 28, Issue 2, pp 273–285 | Cite as

The physical base of marine bacterial ecology

  • D. K. Button
Controls of the Microbial Loop: Nutrient Limitations

Abstract

Specific affinity theory is compared with traditional ways of understanding the nutrient concentration dependency of microbial growth. It is demonstrated that the Michaelis constant increases with the ratio of metabolic enzyme to membrane permease content of bacteria so that small values can reflect specialization for nutrient collection. When compared to the specific affinity, Kt gives a measure of oligotrophic capacity. Specific affinity, on the other hand, reflects nutrient collection ability directly, and increases with the number of permeases. It can be estimated, along with the other kinetic constant, Vmax, by use of isotopes in natural samples. Because of systematic errors in estimating Vmax, specific affinity is the preferred measure of substrate accumulation ability. The advantage of simultaneous collection of multiple substrates in dilute solution is demonstrated. The structural basis of this advantage is computed from collision frequency and recollision probability, computations that further show that multisubstrate usage is essential for bacterial growth under low-nutrient conditions. Computed growth rates from specific affinities require that several substrates be used simultaneously for growth at measured concentrations. Formulations anticipate that the surface of oligobacteria should be occupied by a diversity of transporter types, that each type of transporter should occupy only a small portion of the cell surface, and the number of cytoplasmic enzymes can be small, allowing small cell size to give a large surface-to-volume ratio for high specific affinity. The large number of substrate types that may be accumulated by a single oligobacterial species is consistent with extensive species diversity.

Keywords

Collision Frequency Prefer Measure Small Cell Size Specific Affinity Multiple Substrate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New Fork Inc 1994

Authors and Affiliations

  • D. K. Button
    • 1
  1. 1.Institute of Marine Science and Department of ChemistryUniversity of AlaskaFairbanksUSA

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