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Mathematical Issues Arising From the Directed Mutation Controversy
Qi Zhengaa Department of Statistics, Texas A&M University, College Station, Texas 77843
Corresponding author: Qi Zheng
Communicating editor: Y.-X. FU
| ABSTRACT |
|---|
During the past 14 years or so a large body of new evidence that supposedly supports the directed mutation hypothesis has accumulated. Interpretation of some of the evidence depends on mathematical reasoning, which can be subtler than it appears at first sight. This article attempts to clarify some of the mathematical issues arising from the directed mutation controversy, thereby offering alternative interpretations of some of the evidence.
A long-held fundamental tenet in evolutionary biology posits that mutations occur at random, regardless of fitness consequences to the resulting mutants; in nature it is selection that decides which mutations will be preserved. This so-called random mutation hypothesis has been repeatedly challenged and defended since early the last century, but experiments conducted since 1988 presented decisively new findings, supposedly lending stronger support to an alternative hypothesis that mutations are more likely to occur when the environment favors the survival of the resulting mutants. These new findings impinged on evolutionary thinking with long-lasting repercussions. However, a few mathematical issues inseparably intertwined with the controversy have so far received surprisingly little attention. This neglect has caused considerable confusion, severely impeding progress in resolving a fundamental controversy in modern history of evolutionary biology. This article attempts to address some of these issues.
The foregoing alternative hypothesis has acquired numerous names in the course of the controversy, but it is most commonly called the directed mutation hypothesis. To avoid nomenclature difficulties, we first articulate an interpretation of the random mutation hypothesis: The rate of occurrence of mutation is independent of fitness that the mutation confers to the mutants. This interpretation serves as a contrast by which the directed mutation hypothesis can be more easily comprehended. Thus, a mutation mediated by a newfound mechanism does not automatically qualify as a directed mutation, for the existence of an undocumented mutational mechanism itself is not a deviation from the random mutation hypothesis. However, if this mutation can be proven to occur only under some specific environmental conditions that favor the survival of the resulting mutants, then that mutation can be a possible example of directed mutation. A less stringent criterion is whether a certain type of mutation occurs more often under conditions favorable to the survival of the resulting mutants.
That is the viewpoint from which this article reexamines some of the new evidence produced since 1988 to support the directed mutation hypothesis. Mutations occurring in nondividing cells characterize the new evidence. It is worth noting that ![]()
| THE MUTATION-MUTANT PRINCIPLE |
|---|
In the 1940s the focus of the controversy was whether bacterial mutants resistant to a virus can arise spontaneously. ![]()
![]()
![]()
![]()
![]()
In light of the mutation-mutant principle, the number of mutant colonies due to postplating mutations shall follow a Poisson distribution, regardless of possible mechanisms by which postplating mutations arise. Only when spontaneous mutations cease to occur shortly after plating (e.g., when selection is lethal) can one assume that Poisson-distributed colonies may be an indicator of directed mutation. To ignore this point amounts to assuming that spontaneous mutation can be inhibited by any selective agent, lethal or nonlethal. This is logically unwarranted, although the central question of the debate was often posed in that spirit, as is evident from the way the "old question" was paraphrased: "What proves that the mutants detected by some selective procedure were present in the population before it had been subjected to selection?" (![]()
| RYAN'S DISCOVERY AND ITS RAMIFICATIONS |
|---|
Almost half a century ago ![]()
Let N0 denote the initial size of a nondividing cell population and
denote the cell death rate (per cell per unit time). If cells undergo mutation at a constant rate µ (per cell per unit time), then at time t the size of the nonmutant population is expressible by N(t) = N0e-(
+µ)t. Because N(t) was large in Ryan's experiments, the occurrence of mutations can be viewed as a Poisson process having rate µN(t). Therefore, the average number of mutations accumulated in a time period between t1 and t2 is
![]() |
(1) |
Furthermore, if
is small, a useful approximation valid for moderate t1 and t2 is
![]() |
(2) |
Equation 1 was essentially known to ![]()
is small. First, mutation will continue to occur in accord with a Poisson process for a long time. Second, during a long initial period, the expected number of mutations is approximately proportional to the duration of the process. These observations cannot be accounted for by the classic Luria-Delbrück type model, as emphasized by ![]()
His+ reversion was µ
1.2 x 10-9h-1/His- cell and His- cells die at the rate
0.018h-1/cell. If a plate initially contains N0
2.4 x 108 nondividing His- cells, then even at the 10th day the daily average number of mutations is m(216, 240) = 0.086.
Another important finding of Ryan is that, in terms of physical time, mutation due to cell division is 40 times as fast as mutation occurring in nondividing cells. This finding explains why in laboratory replication-independent mutations are rare compared to replication-dependent mutations. Under laboratory conditions, cell division is immensely accelerated, and so is the rate of replication-dependent mutation when measured in physical time. But other types of mutation (e.g., mutation mediated by insertion sequence) may not be as easily accelerated by increased growth. A 4-day period is equivalent to
192 generations, during which time a single cell can theoretically expand to
6.28 x 1057 cells. Because end-product toxicity will reach a lethal level long before the cell population can attain such a large size, the time period during which replication-independent mutations are allowed to occur is short. One obvious way of lengthening this period is nutrition control, prolonged starvation being the most efficient. The fact that dividing cells also undergo replication-independent mutation was ingeniously demonstrated by ![]()
40 times longer than that in laboratory.
| THE SCOPE OF FLUCTUATION TEST |
|---|
The first experimental example that rekindled interest in the directed mutation hypothesis is the observation that in a fluctuation experiment the number of mutant colonies appearing on a plate may follow a Poisson-like distribution, not a Luria-Delbrück jackpot distribution (![]()
![]()
In light of the mutation-mutant principle, the Poisson-distributed Lac+ colonies appearing on a plate of lacZam cells is a phenomenon to be expected. As long as cells are immobilized on a solid medium, the number of Lac+ colonies occurring in any time interval is Poisson distributed. Furthermore, if birth and death of lacZam cells are negligible, then the expected number of Lac+ colonies should be approximately proportional to the length of postplating incubation, according to Equation 2. The status of starvation and the availability of a potentially usable carbon source might be purely coincidental factors. The key question is whether these two concomitant factors actually enhance mutation rate, but to answer this question is clearly out of the scope of the Luria-Delbrück fluctuation test.
Several explanations have been put forward for the appearance of Poisson-distributed colonies. For instance, ![]()
![]()
![]()
![]()
| THE STARVATION DILEMMA |
|---|
The occurrence of a mutation is directly responsible for only a single mutant cell (or at most two mutant cells when the mutation is replication mediated); many environmental factors (e.g., temperature, pH, and nutrition) are responsible for allowing a first-generation mutant to grow into a detectable colony. In laboratory, a mutant colony can be detected mainly for two reasons: Either appropriate conditions cause a first-generation mutant to grow into a colony or a large number of first-generation mutants cluster together to give the appearance of a colony. The second possibility is highly implausible. The first possibility poses an unexpected dilemma in the context of experiments like that involving lacZam cells. Lactose plays two roles in such an experimentas a nutrient necessary for a Lac+ revertant to grow into a colony and as a supposed environmental factor responsible for "directing" mutations. Without a carbon source, all Lac-
Lac+ mutations would remain invisible; with a carbon source of lactose, the origin of mutations becomes moot; with any carbon source other than lactose, there might be no starvation stress.
The difficulties in overcoming the starvation dilemma were evident in many experiments involving auxotrophic bacteria. For example, ![]()
![]()
![]()
![]()
| THE CAUSES OF THE MU EXCISION |
|---|
In E. coli strain MCS2, part of the ara operon including a regulatory region has been joined with the lacZ gene by a DNA segment of phage Mu. Because the phage Mu segment contains transcription terminating signals, MCS2 cells can use neither lactose nor arabinose for growth. (Intact ara and lac operons are missing in MCS2 cells.) However, the inability of MCS2 cells to use lactose can be circumvented by their excising properly the Mu phage DNA. This Mu excision creates a hybrid coding sequence, enabling MCS2 cells to use lactose with arabinose as an inducer. We denote the latter phenotype by Lac+|Ara and the phenotype before Mu excision by Lac-|Ara. A key question has been whether Mu excisions occur more often when Lac-|Ara cells are starving and exposed to both lactose and arabinose.
A major obstacle to unraveling the mystery of this case is the starvation dilemma. The experiment conducted by ![]()
![]()
![]()
![]()
The originators of both experiments postulated that starvation nonselectively enhanced mutation rates. There seems to be an alternative conjecture. The primary role of starvation may be to allow Lac-|Ara cells sufficient time to mutate at their intrinsic mutation rates. The first evidence supporting this conjecture is the observation that continued aeration allowed more Lac+|Ara cells to be detected than static incubation allowed (![]()
![]()
![]()
![]()
![]()
| THE PUZZLE OF DOUBLE MUTANTS |
|---|
Earlier investigators have apparently pondered the mechanisms by which multiple mutants arise (![]()
![]()
In wild-type E. coli the bglR gene is cryptic in the sense that the gene cannot be expressed unless it undergoes a certain type of mutation. In E. coli strain
342LD the bglF gene is also inactive due to the presence of an insertion sequence. Thus two mutations are necessary for a
342LD cell to gain the ability to use salicin for growth: one to activate the bglR gene and one to rid the bglF gene of the insertion sequence (![]()
![]()
342LD cells were starved for 20 days in the presence of salicin, and only 7 of the 27 colonies (each consisting of
109 cells) tested contained no Sal+ cells. This was considered a case of directed mutation in the following computations: (1) If both mutations occur at random, then the probability that a double revertant appears is 6 x 10-8 x 2 x 10-10 = 1.2 x 10-17 and (2) because the mean number of cells in the 7 colonies decreased to 6.7 x 107 at the end of the 20th day, the mutation rate per cell is -log(7/27)/(6.7 x 107)
2 x 10-8. Therefore, "the frequency of the Sal+ double mutants is about 12 orders of magnitude higher than expected on the basis of the mutation rates measured during growth" (![]()
![]()
![]()
The FCY6 strain of E. coli harbors two mutations in the trp operon, one in the trpB gene and one in the trpA gene. Thus an FCY6 cell must acquire two reversion mutations to recover its ability to synthesize tryptophan. By experiments with cells that harbor one of the two types of mutation, it was found that the two mutation rates are µ1 = 5.2 x 10-10 and µ2 = 6.4 x 10-10/cell/day, respectively. On the other hand, 9254 colonies of FCY6 cells were grown to about the size of 2.8 x 108 cells/colony and were then starved for 30 days. At the end 37 of the 9254 colonies were believed to contain double revertants. It was further inferred that FCY6 cells in starvation produce Trp+ double revertants at the rate of 9.9 x 10-11/cell/day, which is
108 times the quantity µ1 x µ2 = 3.3 x 10-19. Therefore, FCY6 cells under starvation stress seemed to produce double revertants "108 times more often than expected," the most plausible explanation being that the two types of mutation occurred simultaneously in response to the selective stress (![]()
![]()
= 0.14/cell/day. Even with this additional information, it was found that "the observed number of double revertants is still considerably more than would be expected if the mutations were independent" (![]()
![]()
![]() |
(3) |
Here µ1 and µ2 are the rates of two sequentially occurring mutations. Let us consider a slightly simplified case in which trpA trpB+ cells grow at the rate of ß = 0.54/cell/day for an entire 30-day period. This simplification still gives a biologically possible scenario. For example, if a trpA trpB+ cell occurs at the outset of the experiment, it may expand to
1.1 x 107 cells; but if a trpA trpB+ cell occurs at the 10th day, it may grow to only
4.9 x 104 cells. We now replace other parameters in Equation 3 with experimental values, e.g.,
= 0.12 and N0 = 2.8 x 108. The probability of one or more double mutants in a particular colony by day 10 is 5.7 x 10-8, but the probability increases to 0.0028 by day 30. Fig 1 depicts the time course of the process, which bears a striking resemblance to actual experimental data (![]()
|
| CONCLUDING REMARKS |
|---|
This article does not attempt to refute the directed mutation hypothesis. However, from a mathematical point of view, this article suggests that some of the evidence accumulated to date to support the directed mutation hypothesis is weaker than was originally thought and may be invalid. In summary, we have offered several conjectures to explain some of the evidence. Mutations mediated by mechanisms other than DNA replication are not peculiar to cells under starvation stress, and in nature such mutations may occur spontaneously at rates possibly comparable to those of replication-dependent mutations. In laboratory starvation or another nutritional control procedure can allow an organism to acquire replication-independent mutations at their intrinsic rates, and physiological changes caused by starvation stress may play a secondary role. In nature it is common for an organism to acquire multiple mutations in a random and sequential manner; even in laboratory it is not uncommon that a cell in a plate acquires two mutations sequentially and randomly in a matter of a few weeks.
| ACKNOWLEDGMENTS |
|---|
I extend my sincere gratitude to an anonymous referee and an associate editor who encouraged me to improve the presentation. A major portion of this work was performed while I was with the National Center for Toxicological Research. This work was supported in part by grant CA-90301 from the National Cancer Institute.
Manuscript received April 30, 2002; Accepted for publication January 9, 2003.
| APPENDIX |
|---|
DERIVATION OF Equation 3
Consider a two-compartment model. Let the first compartment represent trpA trpB+ cells, and the second compartment Trp+ cells. Following ![]()
t, and cells in the first compartment replicate at rate ß. In addition, cells in the first compartment migrate to the second compartment at rate µ2. Since this model is a slight variation of a so-called A2/0/0 mutation model, the reader is referred to ![]()
From a standard procedure it follows readily that the probability generating function G(z1, z2; t) for this model satisfies the partial differential equation
![]() |
(A1) |
subject to the initial condition G(z1, z2; 0) = 1. Because we are interested only in p0(t) = G(1, 0; t), we set z2 = 0 in Equation A1 to yield a simplified partial differential equation

To solve for p0(t), we resort to a so-called characteristic curve z(s) defined by
![]() |
(A2) |
This device reduces the above partial differential equation to an ordinary differential equation

That is,

Solving Equation A2 yields

Therefore,

Making a change of variable y = t - s, we get

whence we obtain Equation 3.
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