INTRODUCTION

Top Abstract Introduction Materials and methods Results and discussion References

When multiple virus genotypes coinfect the same host cell, an individual virus may experience decreased fitness due to heightened intracellular competition (3, 11, 25). A consequence of such competition is the evolution of defective interfering (DI) particles. DI particles are effectively viral genomes that become deleted for protein coding regions but retain and duplicate the target sequences recognized by the replication and encapsidation machinery (9, 10). By virtue of their smaller size and multiple targets, DI particles gain an intracellular replicative and competitive advantage over ordinary viruses during coinfection. Although DI particles generally evolve during very high multiplicities of infection (the ratio of phage to host cells in a given mixture), recent work has shown that even moderate coinfection can be costly to a virus (23). Here evolution does not lead to DI particles but to intact viruses with adaptations that enhance their intracellular fitness at the expense of their ability to exploit the host. Thus, viruses that can limit or prevent coinfection should possess a selective advantage, and it is not surprising that numerous viruses have evolved mechanisms to do so (19, 20, 26).

In this study, we tested whether and to what number of viruses coinfection is limited in bacteriophage 6. When multiple 6 parent phages coinfect the same host cell, hybrid progeny are generated that possess genetic markers from more than one parent (13). Because coinfection is necessary for the creation of hybrids, we noted that the limit to coinfection (the maximum number of viruses that enter a single host cell) can be estimated from the frequency of hybrids observed at different multiplicities of infection. For any given limit, increasing the multiplicity of infection above the limit should have a diminishing effect on hybrid production. Our estimate is derived by comparing observed frequencies of hybrids to a series of theoretical distributions based on differing limits to coinfection.

Although a limit was established previously by Olkkonen and Bamford (16), who used the amount of incorporated ¹⁴C label as a measure of the number of phage entering a cell, we have reestimated the limit through development and application of a genetic approach. Aside from providing a test of the previous estimate, our motivation was to develop a simpler method that could be easily adapted to a variety of viruses and culture conditions. More-readily-obtained estimates of the limit to coinfection have recently become important because many theoretical models and studies of viral evolution require knowledge of the rate of coinfection (2, 4, 5, 13, 17, 23). Intracellular competition clearly creates a cost to coinfection, but it has been argued that coinfection is advantageous because the replication of more than one virus within a cell allows for sexual reproduction (3). Thus, a testable expectation is that viruses may benefit by evolving a limit, but the limit should not be as low as one virus per cell.

Experimental design. Because the genome of 6 is comprised of three double-stranded RNA segments denoted small, medium, and large (8, 12, 14, 18), and recombination in 6 is lacking or occurs at an extremely low rate (13), the generation of hybrid progeny during coinfection is strictly through segment reassortment. To monitor the frequency of hybrids produced, we crossed two 6 strains, MX and LX, which were genetically marked on the middle and large segments, respectively. Letting X denote the marked segment and + denote the unmarked or wild-type segment, the genotypes of MX and LX are therefore (+ X +) and (++ X).

The model. (i) Expected frequency of hybrids. To generate the expected values, we created a model that predicts the frequency of (+++) hybrids over a range of multiplicities of infection in crosses between MX and LX phages. Five assumptions are implicit in the model: (i) phages attach randomly and irreversibly to cells; (ii) phages enter and infect a cell up to the designated limit to coinfection; (iii) in a host cell infected by either MX or LX phages alone, the number of progeny phage produced depends on the replicative ability of each parental phage and is independent of the number of infecting parental phage; (iv) in a host cell infected by both MX and LX, the wild-type markers are dominant and the number of progeny produced is equal to that of a cell infected by only a wild-type (+++) phage (7); and (v) hybrids are created by random reassortment of segments.

(1)

(2)

(3)

(3a)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(10a)

(11)

(12)

(13)

(14)

(15)

(ii) Parameter estimation. Using equation 15 to measure the limit to coinfection requires estimates of the values of the fitness parameters d_M, d_L, W_M, and W_L.

(16)

(17)

(18)

(19)

(20)

(21)

4

	MATERIALS AND METHODS

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Stocks and culture conditions. All phages and bacteria were grown, plated, incubated, and diluted at 25°C in LC medium (13) by standard microbiological and previously described methods (4). The wild-type 6 and its host bacterium, Pseudomonas phaseolicola, were obtained from the American Type Culture Collection (no. 21781-B1 and 21781, respectively). From L. Mindich (Public Health Research Institute, New York City) we obtained LM1034, a P. phaseolicola host containing plasmid pLM746, which encodes the beta subunit of the -galactosidase (B-Gal) gene (17); MX, the 6 phage with a -Gal marker on the medium segment; and LX, the 6 phage with a -Gal marker on the large segment.

Genetic markers. The -Gal marker encodes the alpha subunit of the -Gal gene. On selective plates containing 0.4% X-Gal (5-bromo-4-chloro-3-indolyl--D-galactopyranoside) and a 200-µl lawn of overnight LM1034 culture, marked and unmarked phages form blue and white plaques, respectively. All phages in this study can be symbolized by their segment markers (small, medium, large), where + refers to wild-type and X refers to marked segments as follows: wild type (+++), MX (+ X +), and LX (++ X). The -Gal marker was found to be extremely stable in MX and LX (data not shown), such that revertants could be ignored in our experiments.

Crosses. Two phages were crossed by single-burst experiments (22), which correspond to one cycle of infection and reproduction in a host cell. The phage were mixed at a 1:1 ratio and allowed 40 min adsorption to the host bacterium in LC broth at the desired multiplicity of infection. To obtain the desired multiplicity, phage numbers were adjusted by dilution and added to the bacteria that had been determined by spectrophotometer to be at a density of 4 × 10⁸ cells ml¹. To remove free phage after the adsorption period, infected cells were washed three times by centrifugation for 1 min at 6,000 rpm in an Eppendorf microcentrifuge, and the pellet was resuspended in LC broth, a derivative of Luria broth. After an additional 80 min, at which point most of the cells have burst (24), the lysate was filtered (0.22-µm-pore-size; Durapore, Millipore) to remove surviving cells and to obtain the viral progeny containing the hybrid phage. The progeny were assayed by plating on X-Gal plates to determine the total number of phage and the frequency of (+++) hybrid phage, which do not carry any marked segments and therefore form white plaques.

Computer modeling. All iterations were by a Quick Basic program that is available upon request.

	RESULTS AND DISCUSSION

Top Abstract Introduction Materials and methods Results and discussion References

By applying equation 16, estimates of W_M and W_L were obtained by measuring q and q' at a multiplicity of infection of 0.02. On the basis of three independent replicates, it was determined that W_M = 0.228 ± 0.029 standard error and W_L = 0.599 ± 0.086 standard error. Following the described protocol (see (Parameter estimation), d_M, d_L, and N were estimated by solving equations 15 and 21 simultaneously. For an assumed value of N, the corresponding values of d_M and d_L were substituted into equation 15 to generate a curve describing the relationship between the expected values of H for multiplicities of infection ranging from 1 to 25. A family of curves was then generated by assuming values of N from 1 to infinity (i.e., N  100) (Fig. 1). As indicated earlier, experimental estimates of P were required for the initial solutions of equation 21, and values of 0.865 ± 0.017 standard error and 0.653 ± 0.010 standard error were obtained, respectively, from MX × wild-type and LX × wild-type crosses at a multiplicity of 5. As the multiplicity of infection is increased for the larger values of N in Fig. 1, the expected values of H asymptote above 0.25 because of the fitness disadvantage suffered by marked phage and segments. In the absence of any fitness difference, the asymptote should be 0.25 (see Experimental design).

View larger version (16K): [in this window] [in a new window]   FIG. 1.   Comparison between expected and observed values of H, frequency of (+++) hybrids generated in crosses between genotypes MX (+ X +) and LX (++ X). Curves were generated by a mathematical model that predicts H over a range of multiplicities of infection (m), assuming a defined limit to coinfection (N). Expected values for H are adjusted if marked segments experience a replicative disadvantage relative to wild type (see text for details). Observed values of H were generated in two replicate experimental crosses between phages MX and LX at eight multiplicities of infection (0.02, 1, 2, 3, 4, 5, 10, 25). Each point represents an independent estimate. Observed H saturates at a value corresponding to a limit of between two and three phages per cell.

To determine an estimate of N by a fit of observed values of H to the curves in Fig. 1, MX and LX phage were crossed over a range of increasing multiplicities of infection. Crosses were replicated two times at each multiplicity, and the frequency of (+++) hybrids was measured by sampling the progeny population by three independent dilutions. The mean of the three samples provided the experimental estimates of H and are presented as a function of the multiplicity in Fig. 1. These data reveal that hybrid frequency increases with multiplicity but reaches a plateau of approximately H = 0.23. The observed maximum matches our mathematical model for a limit to coinfection between two and three phages per cell and Olkkonen and Bamford's (16) earlier estimate of three phages per cell.

Observed values are greater than expected at very low multiplicities of infection (Fig. 1), suggesting that coinfection at low multiplicities may be enhanced above the rate predicted by a random Poisson sampling. A possible explanation for the enhancement is the outer lipid membrane of 6 (1, 15). The stickiness of the membrane causes the phage to clump and may therefore enhance the entry of multiple phages into a cell. As a limit to coinfection may have evolved in viruses to prevent competition (see above), it is appealing to consider whether any enhancement, by clumping or an alternative mechanism, is either a passive consequence of the physiology of the phage or an evolved adaptation. Previous studies with 6 have shown that coinfection can be advantageous to the phage because it leads to sexual reproduction (segment reassortment); sex is advantageous because it combats the buildup of deleterious mutations by recreating (from mutated genomes) progeny with no or fewer mutations (2, 4, 5). Overall, our data suggest that 6 may have evolved mechanisms to enhance coinfection at low multiplicities of infection and to limit coinfection at high multiplicities. Such adaptations would serve to balance the costly and beneficial effects associated with viral coinfection.

It is hoped that the results of this study will encourage additional studies of the existence and mechanism for a limit to coinfection in viruses. Many issues clearly remain unanswered. How widespread is the phenomenon? To what extent is the limit controlled by viral or host genes? The model presented here potentially provides an easier method for detecting the limit in viruses capable of forming genetic hybrids. An immediately obvious advantage of the method is that the larger sample sizes it generates could be used to identify additional processes such as the enhancement of coinfection at low multiplicities.