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Appl Environ Microbiol. 2010 July; 76(13): 4583–4586.
Published online 2010 May 7. doi:  10.1128/AEM.01682-09
PMCID: PMC2897423

Assessing the Potential of an Induced-Mutation Strategy for Avermectin Overproducers[down-pointing small open triangle] §


Mutant libraries of avermectin-producing Streptomyces avermitilis strains were constructed by different mutagenesis strategies. A metric was applied to assess the mutation spectrum by calculating the distribution of average phenotypic distance of each population. The results showed for the first time that a microgravity environment could introduce larger phenotype distribution and diversity than UV and N-methyl-N-nitro-N-nitrosoguanidine (NTG) could.

Induced mutagenesis is a classical and successful method for improving strains to increase the productivity of commercially significant microbial metabolites. To evaluate different induced-mutagenesis approaches, Klein-Marcuschamer and Stephanopoulos presented a metric based on the quantification of phenotypic diversity to evaluate strain improvement approaches (14).

New approaches of inducing mutagenesis emerged with the development of biotechnology, and of these new approaches, spaceflight-induced mutagenesis has led to great progress in strain improvement (6, 15, 26). In outer space, cosmic rays, high vacuum, intense magnetic field, and microgravity induced chromosomal aberrations, which lead to genetic mutations in microorganisms (13). However, it is difficult to carry out spaceflight-induced mutagenesis extensively owing to the limitations of high cost and few chances to board spaceships. Therefore, ground-based simulated experiments have greater practical significance, and high-magnetogravity experiments are a good choice to simulate the space environment (16).

Avermectins and its analogues, produced by Streptomyces avermitilis, are major commercial antiparasitic agents for animal health, agriculture, and human infections (7). A variety of mutagenesis methods have been developed to increase the productivity of S. avermitilis (18, 19, 21-23, 25). Though most of them can produce higher mutation rates, the potential of their success in strain improvement is different.

In this study, mutant libraries of S. avermitilis strains were constructed by three mutagenesis-inducing strategies: UV, N-methyl-N-nitro-N-nitrosoguanidine (NTG), and high-magnetogravitational environment (HMGE). For each population, the distribution of average phenotypic distance was calculated on the basis of the modified version (15) of the metric of Klein-Marcuschamer and Stephanopoulos (14). The mutation rate was also calculated. A good correlation between the distribution of average phenotypic distance and the percent improvement was found and analyzed. In this way, the potential to produce mutations among different induced-mutagenesis approaches was evaluated to find the most effective one for S. avermitilis.

The industrial avermectin-producing S. avermitilis 3-115 strain and the mutants derived from strain 3-115 were grown on YMG agar medium (10). For diversity quantification and preliminary screening, fermentation was carried out in high-throughput format at 28°C. For confirmation of results and secondary screening, mutants that exhibited a higher yield than the wild-type strain were inoculated into shake flasks (10, 11). A high-magnetogravitational experimental platform using the large gradient superconducting magnet was described in detail by Qian et al. (20).

The mutant libraries were prepared from S. avermitilis 3-115 by three different mutagenesis strategies. Spore suspensions were prepared in sterile water (106 spores/ml). For UV-induced mutagenesis, 4-ml aliquots of the spore suspension were transferred into sterile petri dishes with a diameter of 80 mm. The petri dishes were then exposed to UV light in a UV-dispensing cabinet fitted with 15-W lamps with about 90% of its radiation at 265 nm. The dishes were placed at a distance of 30.0 cm away from the center of the UV light source and exposed to UV light for 15, 30, 45, 60, 75, and 90 s. The UV-exposed aliquots were then stored in the dark overnight to avoid photoreactivation. For NTG-induced mutagenesis, 9 ml of the spore suspension was added to 1 ml of a sterile solution of NTG (3 mg/ml NTG in phosphate buffer; solution freshly prepared 1 h before use). The samples were shaken at 28°C for 30 min and immediately centrifuged for 10 min at 5,000 rpm, and the supernatant was decanted. The cells were washed three times with sterile water and resuspended in 10 ml of sterile phosphate buffer (pH 7.2). All of the experimental samples were serially diluted with sterile water and plated on YMG plates. For HMGE-induced mutagenesis, the superconducting magnet generated three different magnetic force fields in different places, which corresponded to three apparent levels of gravity (0, 1, and 2 g) and two magnetic induction intensities (12 and 16 T). Specifically, there were three treatment groups in this study: 0-g group (0 g, 12 T), 2-g group (2 g, 12 T), and 1-g group (1 g, 16 T). The YMG plates (plated with 4 ml of spore suspension) were placed at the corresponding places in the platform for 7 days at 28°C to simulate strains grown in space. For all of above induced-mutagenesis experiments, when single colonies were visible on YMG agar medium, they were transferred to 96-well plates for cultivation.

To quantify avermectin production, UV absorbance of culture was measured on a multiplate reader (11), and all experiments were repeated twice except where specifically noted. More than 165 clones from each library were screened. The phenotypic distributions of five different populations (including the control) were quantified. We used the optical density at 245 nm (OD245) of the culture as the phenotype for diversity quantification of each mutant library. All data were analyzed with MATLAB (MathWorks, USA). Average phenotypic distance (d) was calculated as follows:

equation M1

equation M2

where the brackets indicate an average over all pairs of members of the population (colonies i and j) and Pi is the phenotype of colony i and Pj is the phenotype of colony j. In this case, the logarithm of the OD245 was used as the phenotypic measure (Oi) because it was found to be lognormally distributed:

equation M3

The strains from improved wells with respect to the control OD245 were cultured in shake flasks to verify the results. The production of avermectins was determined by high-performance liquid chromatography (HPLC) (Agilent 1200) (8, 11). The positive mutants were defined as the strains that showed increased avermectin B1a production (increased by more than 10%) compared to the original strains. The negative mutants were defined as the strains that showed decreased avermectin B1a production (decreased by more than 10%) compared with the original strains. The mutation rate was calculated as the number of either positive or negative mutants divided by the total number of screened mutants, and the calculation was based on the results of preliminary screening.

The distributions of the average phenotypic distances of five different populations were calculated. Bootstrapping was used to derive these distributions, and the results were displayed in a histogram (Fig. (Fig.11 a). To see the statistical significance of the difference between the different groups, the mean and standard deviation of each histogram in Fig. Fig.1a1a were calculated (Fig. (Fig.1b).1b). Homogeneous populations had small average phenotypic distances, whereas diverse populations had larger ones. Larger distance implied larger phenotypic dissimilarity among members of a population. Figure 1a and b showed that the phenotypic diversities in decreasing order were HMGE, NTG, and UV. Among HMGE-induced-mutagenesis libraries, phenotypic diversities in decreasing order were 0-g group (0 g, 12 T), 2-g group (2 g, 12 T), and 1-g group (1 g, 16 T) (Fig. 1a and b). For comparison, the traditional evaluation index, the mutation rate, was also calculated (Fig. (Fig.1c).1c). By using the mutation rate, the positive mutation rate of NTG was the highest, while that of UV was the lowest. Among HMGE-induced-mutagenesis libraries, the mutation rates in decreasing order were 1-g group (1 g, 16 T), 2-g group (2 g, 12 T), and 0-g group (0 g, 12 T) (Fig. (Fig.1c1c).

FIG. 1.
Avermectin production spectrum evaluation of five different mutagenized S. avermitilis populations and the untreated control. Mutations were induced by UV, NTG (N-methyl-N-nitro-N-nitrosoguanidine), or high-magnetogravitational environment (HMGE) treatment. ...

Figure Figure22 shows the percentages of mutants that exhibited higher yield in both preliminary and secondary screening (percent improved), considering the instability of mutants in induced mutagenesis. The results parallel the findings of the diversity metric (Fig. (Fig.1b),1b), not the mutation rate (Fig. (Fig.1c).1c). To investigate the predictability of the divergence for improved phenotypes, the correlation between the divergence (average phenotype distance) and the occurrence of a mutant with improved production was investigated. Figure Figure33 shows the correlation between divergence and the percent improved. A sigmoid fit and a correlation of R2 = 1 were obtained. The results indicated that for medium divergence (0.6 < divergence < 0.8), improved diversity increased rapidly with the probability of isolating mutants with improved phenotype, while for divergence which was less than 0.6 or more than 0.8, the correlation of divergence with the probability of finding improved mutants was relatively low.

FIG. 2.
Percentage of improved mutants that produce 10% more avermectin B1a than the parent strain. The percentage represents the fraction of “successful” screening events (produce more avermectin B1a on secondary screening) and is a measure ...
FIG. 3.
Correlation of divergence and percentage of improved mutants. A sigmoid fit was used (equations shown in the figure).

Traditionally, the positive mutation rate is used to evaluate mutation spectrum. However, the positive mutation rate describes only the mutations that occur and cannot describe the extent of mutation or how broad the mutation spectrum is. Therefore, in this study, divergence of mutant libraries was calculated to assess the mutation effect, and divergence was used to evaluate the effect of different induced-mutation strategies, including HMGE, a new spaceflight-simulated mutation strategy. The results of this study indicated the following. (i) HMGE-induced mutagenesis enhanced average phenotype distance and diversity better than UV and NTG mutagenesis did for S. avermitilis. (ii) Microgravity introduced the largest diversity in the genome of S. avermitilis under HMGE conditions. (iii) For medium divergence (0.6 < divergence < 0.8), improved diversity increased the probability of isolating mutants with improved phenotype.

NTG was far more efficient than UV irradiation, a conclusion that many other researchers have reached; however, in a study on the efficiency of mutagenesis on spectinomycin resistance in Streptomyces fradiae, it was reported that NTG was more efficient than UV (1-5, 17). The platform of HMGE was developed to simulate the space environment, which has been reported to improve production of certain antibiotics in microorganisms (20). The results indicated that the simulated weightless environment significantly affected cell population and suggested that microgravity may cause the main mutagenic effects on the strains. Results reported here add empirical support to the hypothesis that microgravity is the most important mutagenic factor in spaceflight (12). Microgravity may increase the growth rate of microorganisms, because under microgravity conditions, oxygen in air can be supplied to microorganisms on all surfaces equally, an advantage in the production of biological matter in space (13). It has been hypothesized that microgravity may disturb the system of DNA repair, which blocks or delays the repair of DNA strand breakage. However, some researchers (24) have demonstrated that is not true, and the mutation mechanism is still not clear.

Diversity has been reported to be correlated with the probability of finding improved mutants, and improved diversity would increase the probability of isolating mutants with improved phenotype (14). Results from our study partly supported this view. For medium divergence (0.6 < divergence < 0.8), there was a significant correlation between diversity and the probability of isolating mutants with improved phenotype. An optimal mutation rate, which functioned as a balance between uniqueness and retention of function, was proved to exist (9). In addition, those findings demonstrated how optimal error-prone PCR mutation rates may be calculated and indicated that “optimal” rates depended on both the protein and the mutagenesis protocol. Our results concurred with the above findings and showed that no significant correlation was detected for divergence which is less than 0.6 or more than 0.8 but that an optimal mutation rate for medium divergence (0.6 < divergence < 0.8) exists. The findings indicated the existence of a balance between mutation rate and improved phenotype, which implies that too high a mutation rate would cause dysfunction in some gene sequences, while certain mutation rates would produce a few mutated gene sequences helpful for improving productivity.


We thank Fengzhu Sun, Yaqiao Li, Elizabeth Ashforth, and Arnold Demain for helpful discussions.

This work was supported in part by grants from National 863 Project (2006AA09Z402 and 2007AA09Z443), National Basic Research Program of China (project 2004CB719601), National Natural Science Foundation of China (projects 30560001 and 30600001), National Key Technology R&D Program (2007BAI26B02), the National Science & Technology Pillar Program (200703295000-02), Important National Science & Technology Specific Projects (2008ZX09401-005), Science and Technology Planning Project of Guangdong Province of China (2006A50103001), and Key Project of International Cooperation (2007DFB31620). L.Z. received funding from the Hundred Talents Program.


[down-pointing small open triangle]Published ahead of print on 7 May 2010.

§This article is dedicated to the memory of our coauthor Jintao Liu.


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