摘要
Cyanobacteria are oxygenic photosynthetic Gram-negative bacteria that can form potentially toxic blooms in eutrophic and slow flowing aquatic ecosystems. Bloom toxicity varies spatially and temporally, but understanding the mechanisms that drive these changes remains largely a mystery. Changes in bloom toxicity may result from changes in intracellular toxin pool sizes of cyanotoxins with differing molecular toxicities, and/or from changes in the cell concentrations of toxic and non-toxic cyanobacterial species or strains within bloom populations. We show here how first-order rate kinetics at the cellular level can be used to explain how environmental conditions drive changes in bloom toxicity at the ecological level. First order rate constants can be calculated for changes in cell concentration( μ_c : specific cell division rate) or the volumetric biomass concentration( μ_g : specific growth rate) between short time intervals throughout the cell cycle. Similar first order rate constants can be calculated for changes in nett volumetric cyanotoxin concentration( μ_(tox) : specific cyanotoxin production rate) over similar time intervals. How μ_c(or μ_g) covaries with μ tox over the cell cycle shows conclusively when cyanotoxins are being produced and metabolised, and how the toxicity of cells change in response to environment stressors. When μ_(tox)/μ_c >1, cyanotoxin cell quotas increase and individual cells become more toxic because the nett cyanotoxin production rate is higher than the cell division rate. When μ_(tox)/μ_c =1, cell cyanotoxin quotas remains fixed because the nett cyanotoxin production rate matches the cell division rate. When μ_(tox)/μ_c <1, the cyanotoxin cell quota decreases because either the nett cyanotoxin production rate is lower than the cell division rate, or metabolic breakdown and/or secretion of cyanotoxins is occurring. These fundamental equations describe cyanotoxin metabolism dynamics at the cellular level and provide the necessary physiological background to understand how environmental stressors drive changes in bloom toxicity.
Cyanobacteria are oxygenic photosynthetic Gram-negative bacteria that can form potentially toxic blooms in eutrophic and slow flowing aquatic ecosystems. Bloom toxicity varies spatially and temporally, but understanding the mechanisms that drive these changes remains largely a mystery. Changes in bloom toxicity may result from changes in intracellular toxin pool sizes of cyanotoxins with differing molecular toxicities, and/or from changes in the cell concentrations of toxic and non-toxic cyanobacterial species or strains within bloom populations. We show here how first-order rate kinetics at the cellular level can be used to explain how environmental conditions drive changes in bloom toxicity at the ecological level. First order rate constants can be calculated for changes in cell concentration（ μc ： specific cell division rate） or the volumetric biomass concentration（ μg ： specific growth rate） between short time intervals throughout the cell cycle. Similar first order rate constants can be calculated for changes in nett volumetric cyanotoxin concentration（ μtox ： specific cyanotoxin production rate） over similar time intervals. How μc（or μg） covaries with μ tox over the cell cycle shows conclusively when cyanotoxins are being produced and metabolised, and how the toxicity of cells change in response to environment stressors. When μtox/μc 〉1, cyanotoxin cell quotas increase and individual cells become more toxic because the nett cyanotoxin production rate is higher than the cell division rate. When μtox/μc =1, cell cyanotoxin quotas remains fixed because the nett cyanotoxin production rate matches the cell division rate. When μtox/μc 〈1, the cyanotoxin cell quota decreases because either the nett cyanotoxin production rate is lower than the cell division rate, or metabolic breakdown and/or secretion of cyanotoxins is occurring. These fundamental equations describe cyanotoxin metabolism dynamics at the cellular level and provide the necessary physiological background to understand how environmental stressors drive changes in bloom toxicity.
基金
Supported by the Griffith University
