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Applied and Environmental Microbiology, January 2006, p. 914-917, Vol. 72, No. 1
0099-2240/06/$08.00+0 doi:10.1128/AEM.72.1.914-917.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
University of Bristol, Collagen Research Group, School of Veterinary Science, Langford, Bristol BS40 5DU, United Kingdom
Received 21 July 2005/ Accepted 19 September 2005
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10,000 copies) (2), and the observed kinetics of cell death, which do not show a shoulder region that is long enough, are incompatible with existing critical target theory (4). In the analysis described below I modified critical target theory by analyzing the survival of cells following a life-threatening treatment (which is undefined and could be heat treatment, irradiation, bathing in antibiotic or cytotoxin, or other chemical procedure, such as deletion or insertion of a gene). I focused on what is essential for the life of the cell rather than on the effect of a particular treatment and recognized that some components of the cell are vital to its existence, while others are useful but not essential. The theory thus incorporates the recent discovery of essential and nonessential genes (3). It also incorporates the molecular nature of the action of antibiotics and reexamines how cell killing is affected by the numbers of copies of critical components within the cell. The analysis provides a general equation for cell survival following critical damage to critical components and then calculates cell survival as a function of time for isothermal heat damage and as a function of temperature for temperature scanning. Existing critical target theory is a special case of this general equation. I start by defining terms and then apply some mathematics.
A critical component of the cell is defined here as a component whose number of functioning copies within the cell must remain above a critical level (which may be zero) for the cell to survive or reproduce. Furthermore, if the number of functioning copies of a critical component falls below the critical level, the cell cannot increase the number of copies by resynthesis. For example, ribosomes are required for the cell to survive and reproduce, and new ribosomes cannot be resynthesized by a cell devoid of ribosomes. Thus, ribosomes are critical components. Other examples of critical components include DNA, the cell envelope, and RNA polymerase.
Critical components have one or more essential functions. Essential functions are functions that must be carried out by the cell for it to survive or reproduce. Critical damage is defined here as irrecoverable damage that stops any essential function of a critical component. Thus, for example, deletion of an essential gene from the genome is critical damage, while deletion of a nonessential gene is not, since cells without essential genes are not viable but cells without nonessential genes may be viable (3). Here the critical component is the DNA, and the essential function is provision of the genetic code required to make the protein or nucleic acid that is essential for a viable cell.
In order for damage to a cell to be lethal, at least one critical component must be critically damaged at or above a critical intensity. Consider, for example, a single prokaryote cell that may contain 10,000 or more ribosomes (2). If just one of these ribosomes were critically damaged, would that be sufficient for cell death to ensue? Surely the remaining thousands of noncritically damaged ribosomes could cope with the required essential function of protein synthesis. At the other extreme, if all copies were critically damaged, the cell clearly could not survive. At either of these extremes or somewhere between them lies the critical intensity, the amount of critical damage that is required for the cell to die or fail to reproduce. Mathematically, the probability of a cell surviving and being capable of reproduction after critical damage to the jth critical component is Pj(rj), where rj is the number of copies of the jth critical component that are not critically damaged.
To summarize, for a cell to die or fail to reproduce, I hypothesize that one or more critical components must be critically damaged and that the probability of surviving critical damage to a critical component depends on the number of copies that the cell contains which are not critically damaged (or equally, the number of copies that are critically damaged).
Armed with this vocabulary, we can analyze the life or death response of an individual cell to a life-threatening treatment. Let us suppose that the treatment critically damages one of the critical components, while the other critical components in the cell are not critically damaged. Let the probability, in the population of cells as a whole, that a particular critical component (a ribosome, for example) is critically damaged be indicated by x. The probability that it is not critically damaged is therefore 1 x. In an individual cell, each copy of the critical component can be arbitrarily labeled as follows: copy 1, copy 2, ... .copy n. By drawing probability trees for possible outcomes, we can calculate the probabilities for different outcomes in a cell containing n copies (Fig. 1):
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FIG. 1. Probability tree for a cell containing three copies of a particular critical component. Starting from the two possible results for the first copy (it may be critically damaged [D] or not critically damaged [ND]), we can construct the set of all possible results for the second and third copies. If the probability that the critical component is critically damaged is x, the diagram can be used to show that the probability that all copies are critically damaged is x3. The probability that two copies are critically damaged and one copy is not critically damaged is 3x2(1 x). The probability that one copy is critically damaged and two copies are not critically damaged is 3x(1 x)2, and the probability that all three copies are not critically damaged is (1 x)3.
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![]() | (1) |
![]() | (2) |
![]() | (3) |
Figures 2 and 3 show calculations of S using equation 2 for various values of the functions x and P (see Appendix). Figure 2 shows the results for isothermal solutions. Figure 3 shows the results for dS/dT under temperature-scanning conditions. The differential is calculated to make the results comparable with differential calorimetry results and to show how the shape and position of the peaks are affected by n and P. Figures 2a and 3a show the results for solutions at one extreme value for the probability function P (representing the condition that the cell will survive if at least one copy of the critical component is not critically damaged). Figures 2b and 3b show the results for solutions at the other extreme (that a cell will survive only if all copies of the critical component are not critically damaged). Figures 2c and 3c show the results for intermediate values. In order to compare cell death (S) with critical component damage (x), it is important to know that 1 x is given by the line n = 1 in Fig. 2a and 2b and dx/dT = dS/dT when n = 1 in Fig. 3a and 3b. It is also important to note that these lines (n = 1) also represent cell survival, irrespective of the value of n, if P(r) = r/n (see Appendix).
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FIG. 2. Calculations using equation A3 of the proportion of cells surviving an isothermal heat treatment in which the probability of critical damage to a critical component is x = 1 exp(kt). (a) Plot assuming that all copies of a critical component must be critically damaged for a cell to die (R = 1). The numbers indicate the number of copies per cell (n). The line for n = 1 also represents 1 x. (b) Plot assuming that no copies of a critical component must be damaged for the cell to survive (R = n). The numbers indicate the number of copies per cell (n). (c) Plot assuming that the total number of copies of the critical component per cell is 100. The number (R) of copies that are not critically damaged per cell is indicated beside each line.
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FIG. 3. Calculations for the rate of decline of surviving cells during temperature scanning based on differentiating equation A3. (a) Plot assuming that all copies of a critical component must be critically damaged for a cell to die (R = 1). The numbers indicate the number of copies per cell (n). The line for n = 1 also represents the rate of critical damage of the critical component, dx/dT. (b) Plot assuming that no copies of a critical component must be damaged for the cell to survive (R = n). The numbers indicate the number of copies per cell (n). (c) Plot assuming that the total number (n) of copies of the critical component per cell is 100. The number (R) of copies that are not critically damaged per cell is indicated beside each line. The fraction of critical components that are critically damaged is x = 1 exp[exp(0.4606T 25.333)], representing a process with a D value of 0.5 min at 55°C and a z value of 5°C for scanning at a rate of 10°C/min (9).
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![]() | (A1) |
![]() | (A2) |
P(r) is more complicated. It depends on the critical component and the nature of the critical damage. I consider here just two types of function. (i) The first type of function is a step function, P(r) = 1, r
R and P(r) = 0, r < R. In this case, the proportion of cells surviving is given by the probability that a cell contains R or more copies that are not critically damaged
![]() | (A3) |
![]() | (A4) |
![]() | (A5) |
(ii) The second type of function is a linear function, P(r) = r/n. In this case the probability that a cell will survive is proportional to the number of copies that are not critically damaged that it contains. When this is inserted in equation 2,
![]() | (A6) |
![]() | (A7) |
Thus, the proportion of survivors is the same as the proportion of copies of the critical component that are not critically damaged, irrespective of the total number of copies per cell. Another way of looking at this is that cells survive as if there were only one copy of the critical component per cell (put n = 1 in equation A4 or A5) and the two processes (cell death and critical damage to the critical component) are coincident in both isothermal and temperature-scanning conditions.
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