Limits...
The Biokinetic Spectrum for Temperature.

Corkrey R, McMeekin TA, Bowman JP, Ratkowsky DA, Olley J, Ross T - PLoS ONE (2016)

Bottom Line: We found another peak at 67°C and a steady decline in maximum rates thereafter.We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins.The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

View Article: PubMed Central - PubMed

Affiliation: Tasmanian Institute of Agriculture / School of Land and Food, University of Tasmania, Hobart, Tasmania, Australia.

ABSTRACT
We identify and describe the distribution of temperature-dependent specific growth rates for life on Earth, which we term the biokinetic spectrum for temperature. The spectrum has the potential to provide for more robust modeling in thermal ecology since any conclusions derived from it will be based on observed data rather than using theoretical assumptions. It may also provide constraints for systems biology model predictions and provide insights in physiology. The spectrum has a Δ-shape with a sharp peak at around 42°C. At higher temperatures up to 60°C there was a gap of attenuated growth rates. We found another peak at 67°C and a steady decline in maximum rates thereafter. By using Bayesian quantile regression to summarise and explore the data we were able to conclude that the gap represented an actual biological transition between mesophiles and thermophiles that we term the Mesophile-Thermophile Gap (MTG). We have not identified any organism that grows above the maximum rate of the spectrum. We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins. The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

No MeSH data available.


Related in: MedlinePlus

Fitted quantile curves.The observed rate of growth for the 10956 data points strains versus temperature and posterior mean fits for the quantiles. The percentile values per curve are shown on the left hand side. We show the fitted quantile curves as black lines and the data as points coloured according to the quantile in which they appeared. The inset shows the observed rate of growth for those strains with Topt ≤ 50°C (left) Topt > 50°C (right) with fitted quantile curves for each case.
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pone.0153343.g002: Fitted quantile curves.The observed rate of growth for the 10956 data points strains versus temperature and posterior mean fits for the quantiles. The percentile values per curve are shown on the left hand side. We show the fitted quantile curves as black lines and the data as points coloured according to the quantile in which they appeared. The inset shows the observed rate of growth for those strains with Topt ≤ 50°C (left) Topt > 50°C (right) with fitted quantile curves for each case.

Mentions: We show in Fig 2 the fitted quantile curves and give the coefficients in Table 1. Examination of the quantile curves indicated that they conformed to the data on the ascending curve up to Tsup. The temperatures at which the quantile curves peaked did not deviate greatly from the Tsup observed from the data. This meant that even if the fastest growing strains such as Clostridium perfringens were deleted the resulting quantiles would still have peaks at about the same temperature. This agreement of the peaks in successive quantiles suggests that a transition of some nature occurs at about this temperature and which is common to all life, or perhaps, speculatively, involves an environmental influence, such as the structure of water. We also noted that the Eppley curve [8] closely corresponded to the 60% quantile curve (not shown). Although not as visually impressive as the ascending curves, the descending quantile curves conformed to the data and served to emphasize the MTG. This suggested that if the MTG was real then there were actually two groups of strains, one predominantly below approximately 50°C and another above. Therefore, we also fitted another set of quantile curves for strains with Topt ≤ 50°C and Topt > 50°C. The Topt is the temperature at which an individual strain grows most rapidly. We show the resulting quantiles in the inset in Fig 2 and the coefficients in Table 2. The conformation of these curves appeared to be a better visual match to the observations. However, the quantile curves also appeared to differ radically in shape between the two groups.


The Biokinetic Spectrum for Temperature.

Corkrey R, McMeekin TA, Bowman JP, Ratkowsky DA, Olley J, Ross T - PLoS ONE (2016)

Fitted quantile curves.The observed rate of growth for the 10956 data points strains versus temperature and posterior mean fits for the quantiles. The percentile values per curve are shown on the left hand side. We show the fitted quantile curves as black lines and the data as points coloured according to the quantile in which they appeared. The inset shows the observed rate of growth for those strains with Topt ≤ 50°C (left) Topt > 50°C (right) with fitted quantile curves for each case.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835062&req=5

pone.0153343.g002: Fitted quantile curves.The observed rate of growth for the 10956 data points strains versus temperature and posterior mean fits for the quantiles. The percentile values per curve are shown on the left hand side. We show the fitted quantile curves as black lines and the data as points coloured according to the quantile in which they appeared. The inset shows the observed rate of growth for those strains with Topt ≤ 50°C (left) Topt > 50°C (right) with fitted quantile curves for each case.
Mentions: We show in Fig 2 the fitted quantile curves and give the coefficients in Table 1. Examination of the quantile curves indicated that they conformed to the data on the ascending curve up to Tsup. The temperatures at which the quantile curves peaked did not deviate greatly from the Tsup observed from the data. This meant that even if the fastest growing strains such as Clostridium perfringens were deleted the resulting quantiles would still have peaks at about the same temperature. This agreement of the peaks in successive quantiles suggests that a transition of some nature occurs at about this temperature and which is common to all life, or perhaps, speculatively, involves an environmental influence, such as the structure of water. We also noted that the Eppley curve [8] closely corresponded to the 60% quantile curve (not shown). Although not as visually impressive as the ascending curves, the descending quantile curves conformed to the data and served to emphasize the MTG. This suggested that if the MTG was real then there were actually two groups of strains, one predominantly below approximately 50°C and another above. Therefore, we also fitted another set of quantile curves for strains with Topt ≤ 50°C and Topt > 50°C. The Topt is the temperature at which an individual strain grows most rapidly. We show the resulting quantiles in the inset in Fig 2 and the coefficients in Table 2. The conformation of these curves appeared to be a better visual match to the observations. However, the quantile curves also appeared to differ radically in shape between the two groups.

Bottom Line: We found another peak at 67°C and a steady decline in maximum rates thereafter.We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins.The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

View Article: PubMed Central - PubMed

Affiliation: Tasmanian Institute of Agriculture / School of Land and Food, University of Tasmania, Hobart, Tasmania, Australia.

ABSTRACT
We identify and describe the distribution of temperature-dependent specific growth rates for life on Earth, which we term the biokinetic spectrum for temperature. The spectrum has the potential to provide for more robust modeling in thermal ecology since any conclusions derived from it will be based on observed data rather than using theoretical assumptions. It may also provide constraints for systems biology model predictions and provide insights in physiology. The spectrum has a Δ-shape with a sharp peak at around 42°C. At higher temperatures up to 60°C there was a gap of attenuated growth rates. We found another peak at 67°C and a steady decline in maximum rates thereafter. By using Bayesian quantile regression to summarise and explore the data we were able to conclude that the gap represented an actual biological transition between mesophiles and thermophiles that we term the Mesophile-Thermophile Gap (MTG). We have not identified any organism that grows above the maximum rate of the spectrum. We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins. The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

No MeSH data available.


Related in: MedlinePlus