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Conidial vigor vs. viability as predictors of virulence of entomopathogenic fungi
Accepted Manuscript Conidial Vigor vs. Viability as Predictors of Virulence of Entomopathogenic Fungi Marcos Faria, Rogério Biaggioni Lopes, Daniela Aguiar Souza, Stephen P. Wraight PII: DOI: Reference:
S0022-2011(14)00190-6 http://dx.doi.org/10.1016/j.jip.2014.12.012 YJIPA 6627
To appear in:
Journal of Invertebrate Pathology
Received Date: Revised Date: Accepted Date:
24 September 2014 18 December 2014 27 December 2014
Please cite this article as: Faria, M., Lopes, R.B., Souza, D.A., Wraight, S.P., Conidial Vigor vs. Viability as Predictors of Virulence of Entomopathogenic Fungi, Journal of Invertebrate Pathology (2014), doi: http:// dx.doi.org/10.1016/j.jip.2014.12.012
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For publication in: Journal of Invertebrate Pathology
Corresponding author Stephen Wraight Research Ecologist / Insect Pathologist USDA - Agricultural Research Service Robert W. Holley Center for Agriculture and Health 538 Tower Road, Cornell University Ithaca, NY 14853 Office: 607-255-2458 Lab: 607-255-0496 Fax: 607-255-1132 E-mail: [email protected]
Conidial Vigor vs. Viability as Predictors of Virulence of Entomopathogenic Fungi
Marcos Fariaa, Rogério Biaggioni Lopesa, Daniela Aguiar Souzaa, and Stephen P. Wraightb
a
EMBRAPA Genetic Resources and Biotechnology, Parque Estação Biológica, W5 Norte, 70770-917, Brasilia, DF, Brazil b
USDA-ARS, Robert W. Holley Center for Agriculture and Health Tower Road, Ithaca, NY 14853 USA
Abstract - We tested the hypothesis that debilitated conidia exhibiting slow-germination (requiring > 16 h to germinate) are less virulent than vigorous conidia exhibiting fast germination (requiring ≤ 16 h to germinate). Preparations of Beauveria bassiana s.l. strain CG 1027 with variable ratios of vigorous to debilitated conidia were assayed against third-instar larvae of Spodoptera frugiperda. As the proportion of debilitated conidia in test preparations increased, LC50 expressed in terms of total viable conidia increased, while LC50 expressed solely in terms of vigorous conidia remained constant, indicating that vigorous conidia were responsible for nearly all mortality observed in the assays. Larvae treated with conidia from low-quality batches (with high proportions of debilitated conidia) survived consistently longer than those treated with comparable doses of conidia from high-quality batches. These results confirm our previous hypotheses that inclusion of debilitated conidia in viability assessments can lead to overestimation of the quality (potency) of mycoinsecticide preparations and support our recommendation for use of short incubation periods for assessing viability whenever viability is relied upon as an indicator of product quality. Keywords: Entomopathogenic fungi; Beauveria bassiana s.l.; biopesticides; mycoinsecticides; germination protocol; quality control
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1. Introduction
Spore viability is widely relied upon as a measure of the quality of fungal inocula used in biological control research and applications (Jenkins and Grzywacz 2000; Goettel et al. 2000). The most common approach in determining viability relies on direct microscopic observations of propagules incubated on a solid semi-synthetic substrate (Goettel and Inglis 1997). Protocols generally call for incubation periods of ca. 24 h; however, methods based on vital staining or incubation in the presence of benzimidazole fungicides, which inhibit germ tube elongation, have been developed with claims of greater accuracy due to elimination of bias that results when germ tube growth from early-germinating conidia obscures inviable conidia on agar surfaces (see Goettel and Inglis 1997). These techniques have, respectively, also enabled researchers to make very rapid assessments and provided flexibility in assessing large numbers of treatments/samples. Vigor is a relatively recent term that relates to the strength of spore germination and germ tube growth, being strongly influenced by factors such as the fermentation system (type and amount of nutrients in the cell) and downstream processing (Jin et al. 1992). Speed of germination is one of the most commonly reported indicators of vigor. Studies have shown that long-term storage or even short periods of storage under unfavorable conditions of high relative humidity, temperature, and/or O2 (factors that boost metabolic activity) have negative impacts on the speed of germination of Beauveria bassiana and Metarhizium anisopliae conidia (Alves et al. 1996; Faria et al. 2010; Lopes et al. 2013). Vigorous, non-stressed conidia of these fungi germinate within 18–24 h post-inoculation (hpi), whereas germination of storage-stressed (debilitated) conidia is delayed and asynchronous, occurring between 24 and 72 hpi (Faria et al. 2010).
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High vigor expressed as fast germination is a desirable trait of entomopathogenic fungi and has been identified as a virulence factor in a number of host-pathogen associations (AlAidroos and Roberts 1978; Hassan et al. 1989; Alves et al. 1996; Altre et al. 2001). Correlations between germination speed and virulence, however, are not always evident (Chandler et al. 1993; Alves et al. 1996). In this work we investigated the hypothesis that calculations of doses based on viability assessments that measure vigor (doses based on numbers of fast-germinating conidia) are more consistent predictors of the potency of a conidial preparation than doses based on viability alone (doses based on total fast- + slowgerminating conidia). As a model, we used an isolate of B. bassiana sensu lato and thirdinstar larvae of Spodoptera frugiperda (Lepidoptera: Noctuidae).
2. Material and Methods
2.1. Preparation of conidial suspensions and germination assessments Pure conidia of commercial strain CG1027 (also known as ESALQ PL63) of Beauveria bassiana s.l., isolated from Atta sp. (Hymenoptera: Formicidae), were previously used in shelf-life experiments in which propagules were exposed to different temperatures and relative humidities for varying periods of time and then stored frozen (ca. –4 ºC) until use in this study. The germination protocol followed recommendations by Lopes et al. (2013). Briefly, dry conidia were suspended in 0.05% Tween 80 and drop-inoculated onto agar plates (20 µl/drop). The inoculated plates were dried in a laminar flow hood for 15 min and then sealed with Parafilm and incubated at 25 ºC. Percentages of vigorous conidia were determined by assessing viability after incubation on potato dextrose agar (PDA) for 16 h. Percentages of total viable conidia were determined via incubation on PDA+carbendazim (25 µg/L) for 48 h.
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Germination was assessed by direct microscopic observation at 400x magnification (without addition of stain/fixative solutions or coverslips); germinated conidia were identified as those with germ tubes longer than the width of an ungerminated conidium.
2.2. Bioassays with Spodoptera frugiperda larvae Five-dose bioassays were performed with third-instar Spodoptera frugiperda (Lepidoptera: Noctuidae) larvae using batches of unformulated conidia with contrasting viabilities and vigor (see treatments, Table 1). Stock suspensions were prepared and serially diluted in 0.05% Tween 80 and then applied as 2-mL aliquots using a spray tower. Spray deposition was sampled during every application, and numbers of conidia per mm2 were determined. Each assay included a control batch of larvae sprayed with Tween solution. Larvae were treated in groups (12 larvae/dose + control = 72 larvae/assay), and each assay was replicated 4 times (each replicate assay testing a conidial-batch subsample independently characterized with respect to the proportions of vigorous vs. total viable conidia and actual doses applied). Treated larvae were held individually in the cells of 24-well tissue culture plates (TPP Techno Plastic Products AG, Switzerland) containing corn leaves, and mortality was assessed daily for ten days. The experiment comprised three tests conducted on different dates over a period of nine weeks. In each test, assays were conducted with a batch of conidia with reduced vigor (variable across tests) and a “standard” batch with high vigor (see Table 1).
2.3 Statistical analyses From each of the individual 5-dose assays, two estimates of LC50 were determined based on probit analyses with two alternative expressions of dose (dose classes): dose expressed in terms of vigorous conidia (numbers of germinated conidia counted in the 16-h viability
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assessments) vs. dose expressed in terms of total viable conidia (numbers of vigorous + slowgerminating conidia counted in the 48-h assessments). Within each test, data were analyzed by mixed-model ANOVA treating assay (nested within conidial batch) as a random effect and conidial batch quality (high vs. low) and dose class (vigorous vs. total viable conidia) as fixed effects. The mean alternative LC50 estimates for low-quality batches of conidia were ultimately compared to the corresponding estimates for the high-quality (standard) batches via single-degree-of-freedom F-tests, allowing for unequal variances (Welch’s Test). The abovedescribed ANOVAs were conducted with each log LC50 estimate unweighted or weighted by the inverse of its variance. The influence of debilitated vs. vigorous conidia on estimates of conidial batch potency was further illustrated via linear regression of LC50s (inverse-variance weighted) on proportion conidia debilitated among total viable conidia. Finally, spray treatments within test were sorted into five dose categories, each including as many of the 12larva treatment groups as possible within the discrete ranges shown in Table 2. Within-test daily mortality of larvae exposed to these dose categories was then analyzed by Cox proportional hazard regression for comparison of survival times in terms of ST50 and/or ST30 (days until death of 50% or 30% of treated larvae). Probit analyses were conducted using SAS PROC PROBIT (SAS 9.3, SAS Institute, Inc., 2012); all other analyses were conducted using JMP Pro 11.0.0 (SAS Institute, 2013). LC50 determinations were based on mortalities recorded at 7 days post-inoculation; however, monitoring was continued for an additional three days to increase accuracy of the survival time estimates.
3. Results Bioassay results are presented in Table 1. Inverse-variance weighting had no effect on the hypothesis test conclusions. Each of the within-test, mixed-model ANOVAs revealed a
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highly significant interaction between dose class and batch quality (all P values < 0.002). Comparisons of the LC50 estimates for high- vs. low-quality batches of conidia (for each dose class) were therefore made within tests (Table 1). Estimates of LC50 based on counts of vigorous conidia (conidia germinating within 16 h) were relatively stable regardless of the percentage of debilitated conidia in the batch. LC50s did not differ significantly between batches of healthy vs. low quality batches of conidia (Table 1). In contrast, LC50 estimates based on total viable conidia (fast + slow-germinating conidia) were significantly higher for the low- vs. high-quality batches in all three tests, with the greatest difference observed in the Test 3 comparison of vigorous vs. severely debilitated conidia (365 vs. 4,341 viable conidia/mm2). The relative stability of LC50 estimates based on vigorous conidia compared to estimates based on total viable conidia is clearly evident in the regressions (Fig. 1). There was a direct linear relationship between Log LC50s based on total viable conidia and the proportion of debilitated conidia (PDC); i.e., log LC50 increased when debilitated conidia were included in the dose counts (highly significant positive regression: y = 2.783 + 0.859x; F1,22 = 33.1, P < 0.0001, R2 = 0.60) (Fig 1a). There was no significant test x PDC interaction (F2,18 = 0.5, P = 0.061). In contrast, log LC50 based on counts of vigorous conidia alone remained relatively stable despite increasing numbers of debilitated conidia in the preparations. The simple linear regression of log LC50 on PDC was not significant (y = 2.834 – 0.124x; F1,22 = 0.4, P = 0.54, R2 = 0.017 (Fig. 1b). In this case, however, there was a significant test x PDC interaction (F2,18 = 9.6, P = 0.002), with the data from Test 3 comparing healthy vs. severely debilitated conidia exhibiting a significant negative regression (y = 2.607 – 0.487x; F1,6 = 0.8, P = 0.026. Median and 30th percentile survival times were consistently shorter for S. frugiperda larvae exposed to the high- vs. low-quality batches of conidia (Table 2). Survival times
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decreased with increasing dose, and there were no significant batch quality x dose category interactions. In all tests, larvae treated with conidia from low-quality batches survived longer than those treated with conidia from the high-quality batches (all batch quality main effect P values < 0.0001) (Table 2). ST30s of larvae treated with vigorous conidia averaged 1.2–4.1 days shorter than those treated with debilitated conidia.
4. Discussion In this study we tested conidial preparations comprising mixtures of fast- vs. slowgerminating (vigorous vs. debilitated) conidia. If the debilitated conidia in these preparations were, in fact, so debilitated as to be considerably less virulent than fast-germinating conidia, one would expect estimates of LC50 derived from dose counts that included these conidia to increase with the increasing proportion of debilitated conidia. On the other hand, LC50s derived from dose counts excluding these conidia would show little variability. These were precisely our experimental observations (presented in Fig. 1), which leads us to conclude that the vigorous conidia in our test preparations were responsible for nearly all lethal infections observed in the S. frugiperda larvae. Although virulence was almost completely related to concentration of vigorous conidia (those capable of germinating within 16 h incubation at 25 ºC) in preparations, it is reasonable to assume that propagules labeled as 'debilitated' yet capable of germination soon after 16 h incubation are nearly as virulent as conidia classified as vigorous, whereas those germinating near 48 h (and perhaps other categories in between) are likely to be avirulent (or almost so) or virulent but incapable of contributing to total mortality in fast-molting insects. Estimates of the survival times of S. frugiperda treated with conidial preparations with equivalent concentrations of total viable conidia but different concentration of debilitated conidia showed that both ST30 and ST50 systematically increased as the concentration of slow-germinating conidia increased, suggesting, as expected, that fast-
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germinating propagules are also more virulent in terms of post-inoculation speed of kill. The observation of a mean ST50 for larvae treated with severely debilitated conidia > 5 days longer than that for larvae treated with vigorous conidia further suggests that debilitation affects not only speed of germination but also infectivity or pathogenicity post infection. Because the potency (efficacy) of a conidial preparation is likely to be overestimated when viability is assessed after prolonged incubation periods, we recommend that the minimum incubation times at 25 ºC required for full germination of high-quality batches should be used for vigor estimation. Incubation times required for germination of high-quality conidia are known to be species- and strain-specific, and for dry preparations are 16–18 h for isolate GHA of B. bassiana and ca. 20-24 h for many Metarhizium spp. isolates (Faria et al. 2010; Xavier-Santos et al. 2011). Previous works reporting bioassay results with insects and field trials have assessed viability after incubation times often considerably ≥ 16-18 h for B. bassiana. We have observed, however, that readings performed at 22 h may be > 40% percentage points higher than vigor determinations at 16 h for some low-quality B. bassiana batches. Obviously, we would further recommend that viability assessments based on delayed counts of conidia germinated under the influence of benzimidazole fungicides as well as those not based on direct observations of germination (e.g., use of vital stains or counting of colony forming units) should be avoided for vigor determinations, as they do not discriminate between fast- and slow-germinating spores. In an insightful study with nymphs of Bemisia tabaci, comparisons of conidia with high vs. low viabilities following storage did not show differences in virulence, and it was therefore concluded that the quality of the surviving propagules had not decreased with storage time (James and Jaronski 2000). In that study, doses were adjusted for germination percentages recorded after incubation for only 18 h at 25 ºC on Sabouraud dextrose agar. Terminologically speaking these authors determined vigor instead of overall viability, and
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their findings support our hypothesis that germination protocols adopting shorter incubation times provide the most accurate estimates of fungal quality. Therefore, a more precise statement of their conclusion is that as long as the concentrations of vigorous conidia are comparable, product batches should have similar quality, even if the spores came from production lots that differed in initial percent viability (with the possible exception of very low-quality batches as discussed below). Jin et al. (1992) proposed that slow-germinating propagules are not effective in biocontrol using fungal pathogens, and blastospores of insect pathogenic fungi have been promoted as potentially more efficacious than conidia due to their capacity for rapid germination (Vega et al. 1999). Our results are in agreement with these findings. The third larval instar of S. frugiperda is short, lasting an average of 36 h at 25 ºC (Pitre and Hogg 1983). Thus, many slow-germinating conidia were likely cast off with the molt to fourth instar before they could complete the infection process. But even in our assays against a rapidly developing host, debilitated conidia appeared to make at least a small contribution to mortality. Undoubtedly, B. bassiana conidia capable of germinating not long after 16 h retain a considerable degree of virulence. In fact, in the Test 3 assays of a low-quality batch showing a vigorous/total viable ratio of only 0.058 (almost 94% of viable conidia in the slowgerminating category), mean LC50 based on vigorous conidia was lower than that based on healthy conidia (evidenced by the significant negative regression). The same phenomenon was observed by James and Jaronski (2000) in assays with three B. bassiana batches: the batch with the lowest germination assessed at 18 h incubation showed the lowest LC50. According to these authors, “one such effect might be the occurrence of exotoxins produced by conidia before they died” (sic), but our results indicate that this effect was likely due to infections arising from slow-germinating conidia. The exceedingly poor condition of the Test 3 low-quality conidia likely also explains the highly variable estimates of LC50 (Fig. 1). One
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would expect efficacy of slow-germinating conidia to be extremely sensitive to application timing relative to the onset of molting. In addition, though not statistically significant within (or across) tests, mean probit regression slopes were consistently lowest for the low-quality batches (Table 2), and low slope is a reflection of high variability in host susceptibility, such as might result from variance in the times of molt. The present study has clearly demonstrated that debilitation/slow germination is a significant determinant of virulence of conidia applied against fast-developing insect larvae. It is important to note, however, that this may not be the case in all entomopathogenic fungusinsect associations. For example, larval insects with substantially longer intermolt periods and adult insects could be quite susceptible to slow-germinating conidia, particularly during protracted periods of favorable environmental conditions. On the other hand, there is little doubt that discrete periods of favorable conditions representing windows of opportunity for fungal infection (e.g., overnight periods of high-humidity/low UV radiation) can be as limiting as intermolt period in many situations. In addition, slow germination of primary inocula and infections resulting from secondary acquisition of inocula from treated substrates following a molt also translate to longer survival of targeted pests, which can reduce biocontrol efficacy, especially against insects with very short pre-reproductive periods (see Baverstock et al. 2006). Our findings underscore a need for additional studies to evaluate effectiveness of slow-germinating conidia in fungal preparations applied under the highly variable conditions encountered in crop production. In previous publications we have expressed our belief that germination protocols that allow inclusion of debilitated conidia due to longer-than-ideal incubation times could result in misleading assessments of the true quality of conidial preparations (Faria et al. 2010; Lopes et al. 2013). In conclusion, in the present work we have shown that conidial vigor (% fastgerminating conidia) measured through a germination protocol based on a short incubation
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period, is a better predictor of the potency (and thus potential efficacy) of B. bassiana-based conidial preparations than overall viability. If a substantial proportion of the conidia in a preparation/formulated product were characterized as viable (and thus healthy), but in fact were debilitated/slow-germinating propagules, then application at the recommended rate might not be effective.
Acknowledgements The research described in this publication was funded by EMBRAPA (Brazilian Corporation for Agricultural Research) and the Brazilian National Research Council (CNPq). We thank Dayane Garcia for assistance in bioassays.
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References
Al-Aidroos, K., Roberts, D.W. 1978. Mutants of Metarhizium anisopliae with increased virulence toward mosquito larvae. Can. J. Genet. Cytol. 20, 211–219 Alves, S.B., Pereira, R.M., Stimac, J.L., Vieira, S.A. 1996. Delayed germination of Beauveria bassiana conidiaafter prolonged storage at low, above-freezing temperatures. Biocontrol Sci. Technol. 6, 575–581. Altre, J.A., Vandenberg, J.D., 2001. Factors influencing the infectivity of isolates of Paecilomyces fumosoroseus against diamondback moth, Plutella xylostella. J. Invertebr. Pathol. 78, 31–36. Baverstock, J., Roy H.E., Clark S. J., Alderson P.G., Pell, J.K. 2006. Effect of fungal infection on the reproductive potential of aphids and their progeny. J. Invertebr. Pathol. 91, 136-139. Chandler, D., Heale, J.B., Gillespie, A.T., 1993. Germination of the entomopathogenic fungus Verticillium lacanii on scales of the glasshouse whitefly Trialeurodes vaporariorum. Biocontrol Sci. Technol. 3, 161–164. Faria, M., Hotchkiss, J.H., Hajek, A.E., Wraight, S.P., 2010. Debilitation in conidia of the entomopathogenic fungi Beauveria bassiana and Metarhizium anisopliae and implication with respect to viability determinations and mycopesticide quality assessments. J. Invertebr. Pathol.105, 74–83. Goettel, M.S., Inglis, G.D., 1997. Fungi: Hyphomycetes. In: Lacey, L.A. (Ed.), Manual of Techniques in Insect Pathology. Academic Press, New York, NY, pp. 213–249. Goettel, M.S., Inglis, G.D., Wraight, S.P. 2000. Overview of Pathogen Groups: Fungi. In: Lacey, L.A., Kaya, H.K. (Eds.), Field Manual of Techniques in Invertebrate Pathology. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 255–282.
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Hassan, A.E.M., Dillon, R.J., Charnley, A.K. 1989. Influence of accelerated germination of conidia on pathogenicity of Metarhizium anisopliae for Manduca sexta. J. Invertebr. Pathol. 54, 277–279. James, R.R., S.T. Jaronski S.T., 2000. Effect of low viability on infectivity of Beauveria bassiana conidia toward the silverleaf whitefly. J. Invertebr. Pathol. 76, 227–228. Jenkins, N.E., Grzywacz, D.,2000. Quality control of fungal and viral biocontrol agents–– assurance of product performance. Biocontrol Sci. Technol. 10, 753–777. Jin, X., Hayes, C.K., Harman, G.E., 1992. Principles in the development of biological control systems employing Trichoderma species against soil-borne plant pathogenic fungi. In: Leatham, G.F. (Ed.), Frontiers in Industrial Mycology. Champman & Hall, New York, NY, pp. 174–195. Lopes, R.B., Martins, I., Souza, D.A., Faria, M., 2013. Influence of some parameters on the germination assessment of mycopesticides. J. Invertebr. Pathol. 112, 236–242. Pitre, H.N., Hogg, D.B., 1983. Development of the fall armyworm (Lepidoptera, Noctuidae) on cotton, soybean and corn. J. Georgia Entomol. Soc. 18, 182-187. Vega, F.E., Jackson, M.A., McGuire, M.R., 1999. Germination of conidia and blastospores of Paecilomyces fumosoroseus on the cuticle of silverleaf whitefly, Bemisia argentifolii. Mycopathologia 147, 33-35. Xavier-Santos, S., Lopes, R.B., Faria, M., 2011. Emulsifiable oils protect Metarhizium robertsii and Metarhizium pingshaense conidia from imbibitional damage. Biol. Control 59, 261-267.
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Figure Legend
Fig. 1. Relationship between proportion of debilitated conidia (among total viable conidia comprising a conidial preparation) and log LC50 expressed in terms of either total viable conidia or vigorous conidia per mm2 (Figs. a and b, respectively).
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Figure
Log LC50 (total viable conidia)
4.5
a
H
4
H
3.5
B B B
3
B
B
H
B J
J J J
H
B HJ J H J 2.5 H H
B Test 1
B
J Test 2
H Test 3
2
Log LC50 (vigorous conidia)
3.5
b
3
B B B
B
B
B
H
B
J J J J
HJ J J H J 2.5 H H
H
B H
2 H
1.5 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Debilitated conidia / total viable conidia
0.8
0.9
1
Tables
1
Table 1. Effect of conidia quality on virulence of Beauveria bassiana isolate CG1027 against Spodoptera frugiperda larvae. Quality/condition of conidia batch
Percent vigorous a
Total Vigorous/ LC50 (log LC50) based on indicated dose class c, d percent total viable Vigorous conidia/mm2 Total viable conidia/mm2 ratio viable b Test 1. Healthy/vigorous vs. moderately stressed/debilitated batches of conidia
Probit regression line slope ± SE d
High quality (healthy/vigorous)
83.3 ± 0.2
89.0 ± 0.9
0.935
587 (2.769 ± 0.154) a
628 (2.798 ± 0.154) a
2.682 ± 0.829 a
Low quality (debilitated)
44.5 ± 2.3
79.1 ± 0.8
0.563
1223 (3.087 ± 0.042) a
2180 (3.338 ± 0.043) b
2.318 ± 0.614 a
Test 2. Healthy/vigorous vs. highly stressed/debilitated batches of conidia High quality
90.1 ± 0.1
92.4 ± 0.3
0.975
417 (2.620 ± 0.018) a
428 (2.632 ± 0.017) a
2.319 ± 0.648 a
Low quality
22.8 ± 0.7
71.2 ± 1.0
0.321
420 (2.623 ± 0.048) a
1310 (3.117 ± 0.051) b
1.469 ± 0.187 a
Test 3. Healthy/vigorous vs. severely stressed/debilitated batches of conidia
2 3 4 5 6 7
High quality
93.4 ± 1.0
95.7 ± 1.0
0.977
356 (2.552 ± 0.053) a
365 (2.562 ± 0.050) a
1.611 ± 0.316 a
Low quality
3.6 ± 0.6
64.9 ± 4.7
0.058
234 (2.369 ± 0.253) a
4341 (3.638 ± 0.284) b
1.159 ± 0.255 a
a
Percent of conidia (mean ± standard error, n = 4) that germinated within 16 hours. Percent of conidia (mean ± standard error, n = 4) that germinated within 48 h (total percent viable). c Mean LC50 based on mortality recorded 7 days post-treatment. LC50s obtained by back-transformation of mean log LC50 values (± values are standard errors, n = 4). Mean mortalities of control larvae sprayed with 0.05% Tween 80 in tests 1–3 were 4.2%, 14.6%, and 2.1%, respectively. d Means within tests within columns followed by the same letter are not significantly different (Welch tests, P < 0.05). b
Table 2
1 Table 2. Survival times of Spodoptera frugiperda larvae following treatment with high- vs. low-quality batches of Beauveria bassiana isolate CG1027 conidia in 2 multiple-dose bioassays. 3 Test
ST50 (95% confidence interval) a ST30 (95% confidence interval) b Dose range (mean) Percent mortality after 10 days (number of larvae dead/total treated) Low dose
Medium-low dose
Medium dose
Medium-high dose
High dose
High quality (0.935)
10.1 (7.8–13.2) 7.2 (5.7–9.1) 318–498 (380) 47 (17/36)
7.2 (5.9–8.7) 5.0 (4.1–6.0) 850–1107 (972) 65 (39/60)
6.9 (5.9–8.2) 5.2 (4.5–6.2) 1133–1777 (1455) 71 (34/48)
6.2 (5.2–7.5) 4.5 (3.8–5.4) 1828–2884 (2226) 71 (34/48)
Test 1
Test 2
Test 3
a
Quality of conidial batch (vigorous/ total viable ratio)
c
Mean ST50 / ST30 (95% CI); pooled data
Cox proportional hazard regression analysis (within test)
4.1 (3.6–4.6) 3.3 (2.9–3.8) 3374–3726 (3528) 97 (35/36)
6.6 (6.1–7.2) 4.7 (4.3 –5.2)
Quality (Q): X 21 = 20.0, P < 0.0001 Dose Category (DC): X 24 = 30.8, P < 0.0001
Low Quality (0.563)
NC 9.8 (6.9–13.8) 296–587 (444) 31 (11/36)
NC 7.9 (4.9–12.9) 793–999 (900) 36 (13/36)
9.7 (7.5–12.5) 7.0 (5.6–8.7) 1091–1724 (1449) 50 (18/36)
7.3 (5.8–9.2) 5.5 (4.4–6.9) 2494–2525 (2510) 67 (18/24)
7.5 (5.9–9.5) 5.6 (4.4–7.1) 2723–3371 (3047) 63 (15/24)
10.3 (8.8– 12.0) 6.8 (6.0–7.8)
Q x DC: X 24 = 4.4, P = 0.35
High quality (0.975)
7.0 (6.5–7.5) 6.1 (5.6–6.6) 259–339 (306) 94 (45/48)
6.8 (6.1–7.5) 5.7 (5.1–6.4) 437–553 (482) 100 (37/37)
6.3 (5.6–7.2) 5.4 (4.7–6.2) 606–734 (670) 92 (22/24)
6.2 (5.4–7.1) 5.0 (4.3–5.7) 847–945 (906) 92 (33/36)
3.5 (3.0–4.0) 2.7 (2.3–3.1) 3022–3735 (3412) 92 (44/48)
5.7 (5.3–6.1) 4.4 (4.1–4.7)
Quality (Q): X 21 = 20.0, P < 0.0001
Low Quality (0.321)
10.6 (8.9–12.6) 7.8 (6.7–9.0) 199–384 (267) 50 (36/72)
7.3 (6.3–8.5) 6.1 (5.2–7.1) 438–535 (487) 88 (21/24)
6.6 (5.5–7.9) 5.2 (4.3–6.3) 755–769 (762) 88 (21/24)
7.1 (5.6–9.1) 5.2 (4.0–6.7) 851–899 (875) 79 (19/24)
5.3 (4.6–6.1) 4.1 (3.6–4.8) 3604–4544 (4174) 83 (40/48)
7.5 (6.9–8.2) 5.6 (5.1–6.1)
High quality (0.977)
NC 7.9 (5.4–11.7) 203–323 (246) 36 (13/36)
6.6 (4.6–9.6) 3.9 (2.8–5.6) 406–498 (437) 58 (21/36)
7.9 (5.1–12.4) 4.3 (2.9–6.5) 582–692 (634) 53 (19/36)
3.5 (2.8–4.2) 2.4 (1.9–3.0) 1319-1947 (1631) 83 (40/48)
2.9 (2.6–3.4) 2.3 (2.0–2.7) 3405-4559 (3984) 94 (45/48)
5.2 (4.5–5.9) 3.2 (2.8–3.6)
NC 10.1 (8.4–12.3) 194–338 (273) 28 (10/36)
NC 8.8 (7.1–10.9) 407–520 (476) 38 (18/48)
NC 10.4 (7.0–15.5) 663–889 (787) 28 (10/36)
9.0 (6.3–13.0) 5.6 (4.1–7.8) 1716–2066 (1868) 50 (18/36)
6.7 (5.6–8.1) 4.9 (4.0–5.9) 4514–6024 (5498) 69 (33/48)
11.0 (9.5– 12.7) 7.3 (6.48.2)
Low Quality (0.058)
4 5 a ST50: median survival time (days until death of 50% of the treated population); ST30: days until death of 30% of treated population. 6 b Dose expressed as total viable conidia per square mm of spray-target surface. 7 c ST50 not calculable (NC), as mortality was substantially less than 50%.
Dose Category (DC): X 24 = 56.8, P < 0.0001 Q x DC: X 24 = 8.7, P = 0.069
Quality (Q): X 21 = 36.1, P < 0.0001 Dose Category (DC): X 24 = 67.7, P < 0.0001 Q x DC: X 24 = 2.8, P = 0.59
GRAPHICAL ABSTRACT
HIGHLIGHTS
•
Speed of germination of fungal conidia is a highly significant virulence factor
•
LC50s of conidia are directly related to the proportion of slow-germinating conidia
•
LC50s based solely on fast-germinating (vigorous) conidia tend to be constant
•
Vigorous conidia lead to shorter survival times of Spodoptera frugiperda larvae
•
Conidial vigor is a better predictor of mycoinsecticide quality than viability
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S0022-2011(14)00190-6 http://dx.doi.org/10.1016/j.jip.2014.12.012 YJIPA 6627
To appear in:
Journal of Invertebrate Pathology
Received Date: Revised Date: Accepted Date:
24 September 2014 18 December 2014 27 December 2014
Please cite this article as: Faria, M., Lopes, R.B., Souza, D.A., Wraight, S.P., Conidial Vigor vs. Viability as Predictors of Virulence of Entomopathogenic Fungi, Journal of Invertebrate Pathology (2014), doi: http:// dx.doi.org/10.1016/j.jip.2014.12.012
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For publication in: Journal of Invertebrate Pathology
Corresponding author Stephen Wraight Research Ecologist / Insect Pathologist USDA - Agricultural Research Service Robert W. Holley Center for Agriculture and Health 538 Tower Road, Cornell University Ithaca, NY 14853 Office: 607-255-2458 Lab: 607-255-0496 Fax: 607-255-1132 E-mail: [email protected]
Conidial Vigor vs. Viability as Predictors of Virulence of Entomopathogenic Fungi
Marcos Fariaa, Rogério Biaggioni Lopesa, Daniela Aguiar Souzaa, and Stephen P. Wraightb
a
EMBRAPA Genetic Resources and Biotechnology, Parque Estação Biológica, W5 Norte, 70770-917, Brasilia, DF, Brazil b
USDA-ARS, Robert W. Holley Center for Agriculture and Health Tower Road, Ithaca, NY 14853 USA
Abstract - We tested the hypothesis that debilitated conidia exhibiting slow-germination (requiring > 16 h to germinate) are less virulent than vigorous conidia exhibiting fast germination (requiring ≤ 16 h to germinate). Preparations of Beauveria bassiana s.l. strain CG 1027 with variable ratios of vigorous to debilitated conidia were assayed against third-instar larvae of Spodoptera frugiperda. As the proportion of debilitated conidia in test preparations increased, LC50 expressed in terms of total viable conidia increased, while LC50 expressed solely in terms of vigorous conidia remained constant, indicating that vigorous conidia were responsible for nearly all mortality observed in the assays. Larvae treated with conidia from low-quality batches (with high proportions of debilitated conidia) survived consistently longer than those treated with comparable doses of conidia from high-quality batches. These results confirm our previous hypotheses that inclusion of debilitated conidia in viability assessments can lead to overestimation of the quality (potency) of mycoinsecticide preparations and support our recommendation for use of short incubation periods for assessing viability whenever viability is relied upon as an indicator of product quality. Keywords: Entomopathogenic fungi; Beauveria bassiana s.l.; biopesticides; mycoinsecticides; germination protocol; quality control
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1. Introduction
Spore viability is widely relied upon as a measure of the quality of fungal inocula used in biological control research and applications (Jenkins and Grzywacz 2000; Goettel et al. 2000). The most common approach in determining viability relies on direct microscopic observations of propagules incubated on a solid semi-synthetic substrate (Goettel and Inglis 1997). Protocols generally call for incubation periods of ca. 24 h; however, methods based on vital staining or incubation in the presence of benzimidazole fungicides, which inhibit germ tube elongation, have been developed with claims of greater accuracy due to elimination of bias that results when germ tube growth from early-germinating conidia obscures inviable conidia on agar surfaces (see Goettel and Inglis 1997). These techniques have, respectively, also enabled researchers to make very rapid assessments and provided flexibility in assessing large numbers of treatments/samples. Vigor is a relatively recent term that relates to the strength of spore germination and germ tube growth, being strongly influenced by factors such as the fermentation system (type and amount of nutrients in the cell) and downstream processing (Jin et al. 1992). Speed of germination is one of the most commonly reported indicators of vigor. Studies have shown that long-term storage or even short periods of storage under unfavorable conditions of high relative humidity, temperature, and/or O2 (factors that boost metabolic activity) have negative impacts on the speed of germination of Beauveria bassiana and Metarhizium anisopliae conidia (Alves et al. 1996; Faria et al. 2010; Lopes et al. 2013). Vigorous, non-stressed conidia of these fungi germinate within 18–24 h post-inoculation (hpi), whereas germination of storage-stressed (debilitated) conidia is delayed and asynchronous, occurring between 24 and 72 hpi (Faria et al. 2010).
3
High vigor expressed as fast germination is a desirable trait of entomopathogenic fungi and has been identified as a virulence factor in a number of host-pathogen associations (AlAidroos and Roberts 1978; Hassan et al. 1989; Alves et al. 1996; Altre et al. 2001). Correlations between germination speed and virulence, however, are not always evident (Chandler et al. 1993; Alves et al. 1996). In this work we investigated the hypothesis that calculations of doses based on viability assessments that measure vigor (doses based on numbers of fast-germinating conidia) are more consistent predictors of the potency of a conidial preparation than doses based on viability alone (doses based on total fast- + slowgerminating conidia). As a model, we used an isolate of B. bassiana sensu lato and thirdinstar larvae of Spodoptera frugiperda (Lepidoptera: Noctuidae).
2. Material and Methods
2.1. Preparation of conidial suspensions and germination assessments Pure conidia of commercial strain CG1027 (also known as ESALQ PL63) of Beauveria bassiana s.l., isolated from Atta sp. (Hymenoptera: Formicidae), were previously used in shelf-life experiments in which propagules were exposed to different temperatures and relative humidities for varying periods of time and then stored frozen (ca. –4 ºC) until use in this study. The germination protocol followed recommendations by Lopes et al. (2013). Briefly, dry conidia were suspended in 0.05% Tween 80 and drop-inoculated onto agar plates (20 µl/drop). The inoculated plates were dried in a laminar flow hood for 15 min and then sealed with Parafilm and incubated at 25 ºC. Percentages of vigorous conidia were determined by assessing viability after incubation on potato dextrose agar (PDA) for 16 h. Percentages of total viable conidia were determined via incubation on PDA+carbendazim (25 µg/L) for 48 h.
4
Germination was assessed by direct microscopic observation at 400x magnification (without addition of stain/fixative solutions or coverslips); germinated conidia were identified as those with germ tubes longer than the width of an ungerminated conidium.
2.2. Bioassays with Spodoptera frugiperda larvae Five-dose bioassays were performed with third-instar Spodoptera frugiperda (Lepidoptera: Noctuidae) larvae using batches of unformulated conidia with contrasting viabilities and vigor (see treatments, Table 1). Stock suspensions were prepared and serially diluted in 0.05% Tween 80 and then applied as 2-mL aliquots using a spray tower. Spray deposition was sampled during every application, and numbers of conidia per mm2 were determined. Each assay included a control batch of larvae sprayed with Tween solution. Larvae were treated in groups (12 larvae/dose + control = 72 larvae/assay), and each assay was replicated 4 times (each replicate assay testing a conidial-batch subsample independently characterized with respect to the proportions of vigorous vs. total viable conidia and actual doses applied). Treated larvae were held individually in the cells of 24-well tissue culture plates (TPP Techno Plastic Products AG, Switzerland) containing corn leaves, and mortality was assessed daily for ten days. The experiment comprised three tests conducted on different dates over a period of nine weeks. In each test, assays were conducted with a batch of conidia with reduced vigor (variable across tests) and a “standard” batch with high vigor (see Table 1).
2.3 Statistical analyses From each of the individual 5-dose assays, two estimates of LC50 were determined based on probit analyses with two alternative expressions of dose (dose classes): dose expressed in terms of vigorous conidia (numbers of germinated conidia counted in the 16-h viability
5
assessments) vs. dose expressed in terms of total viable conidia (numbers of vigorous + slowgerminating conidia counted in the 48-h assessments). Within each test, data were analyzed by mixed-model ANOVA treating assay (nested within conidial batch) as a random effect and conidial batch quality (high vs. low) and dose class (vigorous vs. total viable conidia) as fixed effects. The mean alternative LC50 estimates for low-quality batches of conidia were ultimately compared to the corresponding estimates for the high-quality (standard) batches via single-degree-of-freedom F-tests, allowing for unequal variances (Welch’s Test). The abovedescribed ANOVAs were conducted with each log LC50 estimate unweighted or weighted by the inverse of its variance. The influence of debilitated vs. vigorous conidia on estimates of conidial batch potency was further illustrated via linear regression of LC50s (inverse-variance weighted) on proportion conidia debilitated among total viable conidia. Finally, spray treatments within test were sorted into five dose categories, each including as many of the 12larva treatment groups as possible within the discrete ranges shown in Table 2. Within-test daily mortality of larvae exposed to these dose categories was then analyzed by Cox proportional hazard regression for comparison of survival times in terms of ST50 and/or ST30 (days until death of 50% or 30% of treated larvae). Probit analyses were conducted using SAS PROC PROBIT (SAS 9.3, SAS Institute, Inc., 2012); all other analyses were conducted using JMP Pro 11.0.0 (SAS Institute, 2013). LC50 determinations were based on mortalities recorded at 7 days post-inoculation; however, monitoring was continued for an additional three days to increase accuracy of the survival time estimates.
3. Results Bioassay results are presented in Table 1. Inverse-variance weighting had no effect on the hypothesis test conclusions. Each of the within-test, mixed-model ANOVAs revealed a
6
highly significant interaction between dose class and batch quality (all P values < 0.002). Comparisons of the LC50 estimates for high- vs. low-quality batches of conidia (for each dose class) were therefore made within tests (Table 1). Estimates of LC50 based on counts of vigorous conidia (conidia germinating within 16 h) were relatively stable regardless of the percentage of debilitated conidia in the batch. LC50s did not differ significantly between batches of healthy vs. low quality batches of conidia (Table 1). In contrast, LC50 estimates based on total viable conidia (fast + slow-germinating conidia) were significantly higher for the low- vs. high-quality batches in all three tests, with the greatest difference observed in the Test 3 comparison of vigorous vs. severely debilitated conidia (365 vs. 4,341 viable conidia/mm2). The relative stability of LC50 estimates based on vigorous conidia compared to estimates based on total viable conidia is clearly evident in the regressions (Fig. 1). There was a direct linear relationship between Log LC50s based on total viable conidia and the proportion of debilitated conidia (PDC); i.e., log LC50 increased when debilitated conidia were included in the dose counts (highly significant positive regression: y = 2.783 + 0.859x; F1,22 = 33.1, P < 0.0001, R2 = 0.60) (Fig 1a). There was no significant test x PDC interaction (F2,18 = 0.5, P = 0.061). In contrast, log LC50 based on counts of vigorous conidia alone remained relatively stable despite increasing numbers of debilitated conidia in the preparations. The simple linear regression of log LC50 on PDC was not significant (y = 2.834 – 0.124x; F1,22 = 0.4, P = 0.54, R2 = 0.017 (Fig. 1b). In this case, however, there was a significant test x PDC interaction (F2,18 = 9.6, P = 0.002), with the data from Test 3 comparing healthy vs. severely debilitated conidia exhibiting a significant negative regression (y = 2.607 – 0.487x; F1,6 = 0.8, P = 0.026. Median and 30th percentile survival times were consistently shorter for S. frugiperda larvae exposed to the high- vs. low-quality batches of conidia (Table 2). Survival times
7
decreased with increasing dose, and there were no significant batch quality x dose category interactions. In all tests, larvae treated with conidia from low-quality batches survived longer than those treated with conidia from the high-quality batches (all batch quality main effect P values < 0.0001) (Table 2). ST30s of larvae treated with vigorous conidia averaged 1.2–4.1 days shorter than those treated with debilitated conidia.
4. Discussion In this study we tested conidial preparations comprising mixtures of fast- vs. slowgerminating (vigorous vs. debilitated) conidia. If the debilitated conidia in these preparations were, in fact, so debilitated as to be considerably less virulent than fast-germinating conidia, one would expect estimates of LC50 derived from dose counts that included these conidia to increase with the increasing proportion of debilitated conidia. On the other hand, LC50s derived from dose counts excluding these conidia would show little variability. These were precisely our experimental observations (presented in Fig. 1), which leads us to conclude that the vigorous conidia in our test preparations were responsible for nearly all lethal infections observed in the S. frugiperda larvae. Although virulence was almost completely related to concentration of vigorous conidia (those capable of germinating within 16 h incubation at 25 ºC) in preparations, it is reasonable to assume that propagules labeled as 'debilitated' yet capable of germination soon after 16 h incubation are nearly as virulent as conidia classified as vigorous, whereas those germinating near 48 h (and perhaps other categories in between) are likely to be avirulent (or almost so) or virulent but incapable of contributing to total mortality in fast-molting insects. Estimates of the survival times of S. frugiperda treated with conidial preparations with equivalent concentrations of total viable conidia but different concentration of debilitated conidia showed that both ST30 and ST50 systematically increased as the concentration of slow-germinating conidia increased, suggesting, as expected, that fast-
8
germinating propagules are also more virulent in terms of post-inoculation speed of kill. The observation of a mean ST50 for larvae treated with severely debilitated conidia > 5 days longer than that for larvae treated with vigorous conidia further suggests that debilitation affects not only speed of germination but also infectivity or pathogenicity post infection. Because the potency (efficacy) of a conidial preparation is likely to be overestimated when viability is assessed after prolonged incubation periods, we recommend that the minimum incubation times at 25 ºC required for full germination of high-quality batches should be used for vigor estimation. Incubation times required for germination of high-quality conidia are known to be species- and strain-specific, and for dry preparations are 16–18 h for isolate GHA of B. bassiana and ca. 20-24 h for many Metarhizium spp. isolates (Faria et al. 2010; Xavier-Santos et al. 2011). Previous works reporting bioassay results with insects and field trials have assessed viability after incubation times often considerably ≥ 16-18 h for B. bassiana. We have observed, however, that readings performed at 22 h may be > 40% percentage points higher than vigor determinations at 16 h for some low-quality B. bassiana batches. Obviously, we would further recommend that viability assessments based on delayed counts of conidia germinated under the influence of benzimidazole fungicides as well as those not based on direct observations of germination (e.g., use of vital stains or counting of colony forming units) should be avoided for vigor determinations, as they do not discriminate between fast- and slow-germinating spores. In an insightful study with nymphs of Bemisia tabaci, comparisons of conidia with high vs. low viabilities following storage did not show differences in virulence, and it was therefore concluded that the quality of the surviving propagules had not decreased with storage time (James and Jaronski 2000). In that study, doses were adjusted for germination percentages recorded after incubation for only 18 h at 25 ºC on Sabouraud dextrose agar. Terminologically speaking these authors determined vigor instead of overall viability, and
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their findings support our hypothesis that germination protocols adopting shorter incubation times provide the most accurate estimates of fungal quality. Therefore, a more precise statement of their conclusion is that as long as the concentrations of vigorous conidia are comparable, product batches should have similar quality, even if the spores came from production lots that differed in initial percent viability (with the possible exception of very low-quality batches as discussed below). Jin et al. (1992) proposed that slow-germinating propagules are not effective in biocontrol using fungal pathogens, and blastospores of insect pathogenic fungi have been promoted as potentially more efficacious than conidia due to their capacity for rapid germination (Vega et al. 1999). Our results are in agreement with these findings. The third larval instar of S. frugiperda is short, lasting an average of 36 h at 25 ºC (Pitre and Hogg 1983). Thus, many slow-germinating conidia were likely cast off with the molt to fourth instar before they could complete the infection process. But even in our assays against a rapidly developing host, debilitated conidia appeared to make at least a small contribution to mortality. Undoubtedly, B. bassiana conidia capable of germinating not long after 16 h retain a considerable degree of virulence. In fact, in the Test 3 assays of a low-quality batch showing a vigorous/total viable ratio of only 0.058 (almost 94% of viable conidia in the slowgerminating category), mean LC50 based on vigorous conidia was lower than that based on healthy conidia (evidenced by the significant negative regression). The same phenomenon was observed by James and Jaronski (2000) in assays with three B. bassiana batches: the batch with the lowest germination assessed at 18 h incubation showed the lowest LC50. According to these authors, “one such effect might be the occurrence of exotoxins produced by conidia before they died” (sic), but our results indicate that this effect was likely due to infections arising from slow-germinating conidia. The exceedingly poor condition of the Test 3 low-quality conidia likely also explains the highly variable estimates of LC50 (Fig. 1). One
10
would expect efficacy of slow-germinating conidia to be extremely sensitive to application timing relative to the onset of molting. In addition, though not statistically significant within (or across) tests, mean probit regression slopes were consistently lowest for the low-quality batches (Table 2), and low slope is a reflection of high variability in host susceptibility, such as might result from variance in the times of molt. The present study has clearly demonstrated that debilitation/slow germination is a significant determinant of virulence of conidia applied against fast-developing insect larvae. It is important to note, however, that this may not be the case in all entomopathogenic fungusinsect associations. For example, larval insects with substantially longer intermolt periods and adult insects could be quite susceptible to slow-germinating conidia, particularly during protracted periods of favorable environmental conditions. On the other hand, there is little doubt that discrete periods of favorable conditions representing windows of opportunity for fungal infection (e.g., overnight periods of high-humidity/low UV radiation) can be as limiting as intermolt period in many situations. In addition, slow germination of primary inocula and infections resulting from secondary acquisition of inocula from treated substrates following a molt also translate to longer survival of targeted pests, which can reduce biocontrol efficacy, especially against insects with very short pre-reproductive periods (see Baverstock et al. 2006). Our findings underscore a need for additional studies to evaluate effectiveness of slow-germinating conidia in fungal preparations applied under the highly variable conditions encountered in crop production. In previous publications we have expressed our belief that germination protocols that allow inclusion of debilitated conidia due to longer-than-ideal incubation times could result in misleading assessments of the true quality of conidial preparations (Faria et al. 2010; Lopes et al. 2013). In conclusion, in the present work we have shown that conidial vigor (% fastgerminating conidia) measured through a germination protocol based on a short incubation
11
period, is a better predictor of the potency (and thus potential efficacy) of B. bassiana-based conidial preparations than overall viability. If a substantial proportion of the conidia in a preparation/formulated product were characterized as viable (and thus healthy), but in fact were debilitated/slow-germinating propagules, then application at the recommended rate might not be effective.
Acknowledgements The research described in this publication was funded by EMBRAPA (Brazilian Corporation for Agricultural Research) and the Brazilian National Research Council (CNPq). We thank Dayane Garcia for assistance in bioassays.
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References
Al-Aidroos, K., Roberts, D.W. 1978. Mutants of Metarhizium anisopliae with increased virulence toward mosquito larvae. Can. J. Genet. Cytol. 20, 211–219 Alves, S.B., Pereira, R.M., Stimac, J.L., Vieira, S.A. 1996. Delayed germination of Beauveria bassiana conidiaafter prolonged storage at low, above-freezing temperatures. Biocontrol Sci. Technol. 6, 575–581. Altre, J.A., Vandenberg, J.D., 2001. Factors influencing the infectivity of isolates of Paecilomyces fumosoroseus against diamondback moth, Plutella xylostella. J. Invertebr. Pathol. 78, 31–36. Baverstock, J., Roy H.E., Clark S. J., Alderson P.G., Pell, J.K. 2006. Effect of fungal infection on the reproductive potential of aphids and their progeny. J. Invertebr. Pathol. 91, 136-139. Chandler, D., Heale, J.B., Gillespie, A.T., 1993. Germination of the entomopathogenic fungus Verticillium lacanii on scales of the glasshouse whitefly Trialeurodes vaporariorum. Biocontrol Sci. Technol. 3, 161–164. Faria, M., Hotchkiss, J.H., Hajek, A.E., Wraight, S.P., 2010. Debilitation in conidia of the entomopathogenic fungi Beauveria bassiana and Metarhizium anisopliae and implication with respect to viability determinations and mycopesticide quality assessments. J. Invertebr. Pathol.105, 74–83. Goettel, M.S., Inglis, G.D., 1997. Fungi: Hyphomycetes. In: Lacey, L.A. (Ed.), Manual of Techniques in Insect Pathology. Academic Press, New York, NY, pp. 213–249. Goettel, M.S., Inglis, G.D., Wraight, S.P. 2000. Overview of Pathogen Groups: Fungi. In: Lacey, L.A., Kaya, H.K. (Eds.), Field Manual of Techniques in Invertebrate Pathology. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 255–282.
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Hassan, A.E.M., Dillon, R.J., Charnley, A.K. 1989. Influence of accelerated germination of conidia on pathogenicity of Metarhizium anisopliae for Manduca sexta. J. Invertebr. Pathol. 54, 277–279. James, R.R., S.T. Jaronski S.T., 2000. Effect of low viability on infectivity of Beauveria bassiana conidia toward the silverleaf whitefly. J. Invertebr. Pathol. 76, 227–228. Jenkins, N.E., Grzywacz, D.,2000. Quality control of fungal and viral biocontrol agents–– assurance of product performance. Biocontrol Sci. Technol. 10, 753–777. Jin, X., Hayes, C.K., Harman, G.E., 1992. Principles in the development of biological control systems employing Trichoderma species against soil-borne plant pathogenic fungi. In: Leatham, G.F. (Ed.), Frontiers in Industrial Mycology. Champman & Hall, New York, NY, pp. 174–195. Lopes, R.B., Martins, I., Souza, D.A., Faria, M., 2013. Influence of some parameters on the germination assessment of mycopesticides. J. Invertebr. Pathol. 112, 236–242. Pitre, H.N., Hogg, D.B., 1983. Development of the fall armyworm (Lepidoptera, Noctuidae) on cotton, soybean and corn. J. Georgia Entomol. Soc. 18, 182-187. Vega, F.E., Jackson, M.A., McGuire, M.R., 1999. Germination of conidia and blastospores of Paecilomyces fumosoroseus on the cuticle of silverleaf whitefly, Bemisia argentifolii. Mycopathologia 147, 33-35. Xavier-Santos, S., Lopes, R.B., Faria, M., 2011. Emulsifiable oils protect Metarhizium robertsii and Metarhizium pingshaense conidia from imbibitional damage. Biol. Control 59, 261-267.
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Figure Legend
Fig. 1. Relationship between proportion of debilitated conidia (among total viable conidia comprising a conidial preparation) and log LC50 expressed in terms of either total viable conidia or vigorous conidia per mm2 (Figs. a and b, respectively).
15
Figure
Log LC50 (total viable conidia)
4.5
a
H
4
H
3.5
B B B
3
B
B
H
B J
J J J
H
B HJ J H J 2.5 H H
B Test 1
B
J Test 2
H Test 3
2
Log LC50 (vigorous conidia)
3.5
b
3
B B B
B
B
B
H
B
J J J J
HJ J J H J 2.5 H H
H
B H
2 H
1.5 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Debilitated conidia / total viable conidia
0.8
0.9
1
Tables
1
Table 1. Effect of conidia quality on virulence of Beauveria bassiana isolate CG1027 against Spodoptera frugiperda larvae. Quality/condition of conidia batch
Percent vigorous a
Total Vigorous/ LC50 (log LC50) based on indicated dose class c, d percent total viable Vigorous conidia/mm2 Total viable conidia/mm2 ratio viable b Test 1. Healthy/vigorous vs. moderately stressed/debilitated batches of conidia
Probit regression line slope ± SE d
High quality (healthy/vigorous)
83.3 ± 0.2
89.0 ± 0.9
0.935
587 (2.769 ± 0.154) a
628 (2.798 ± 0.154) a
2.682 ± 0.829 a
Low quality (debilitated)
44.5 ± 2.3
79.1 ± 0.8
0.563
1223 (3.087 ± 0.042) a
2180 (3.338 ± 0.043) b
2.318 ± 0.614 a
Test 2. Healthy/vigorous vs. highly stressed/debilitated batches of conidia High quality
90.1 ± 0.1
92.4 ± 0.3
0.975
417 (2.620 ± 0.018) a
428 (2.632 ± 0.017) a
2.319 ± 0.648 a
Low quality
22.8 ± 0.7
71.2 ± 1.0
0.321
420 (2.623 ± 0.048) a
1310 (3.117 ± 0.051) b
1.469 ± 0.187 a
Test 3. Healthy/vigorous vs. severely stressed/debilitated batches of conidia
2 3 4 5 6 7
High quality
93.4 ± 1.0
95.7 ± 1.0
0.977
356 (2.552 ± 0.053) a
365 (2.562 ± 0.050) a
1.611 ± 0.316 a
Low quality
3.6 ± 0.6
64.9 ± 4.7
0.058
234 (2.369 ± 0.253) a
4341 (3.638 ± 0.284) b
1.159 ± 0.255 a
a
Percent of conidia (mean ± standard error, n = 4) that germinated within 16 hours. Percent of conidia (mean ± standard error, n = 4) that germinated within 48 h (total percent viable). c Mean LC50 based on mortality recorded 7 days post-treatment. LC50s obtained by back-transformation of mean log LC50 values (± values are standard errors, n = 4). Mean mortalities of control larvae sprayed with 0.05% Tween 80 in tests 1–3 were 4.2%, 14.6%, and 2.1%, respectively. d Means within tests within columns followed by the same letter are not significantly different (Welch tests, P < 0.05). b
Table 2
1 Table 2. Survival times of Spodoptera frugiperda larvae following treatment with high- vs. low-quality batches of Beauveria bassiana isolate CG1027 conidia in 2 multiple-dose bioassays. 3 Test
ST50 (95% confidence interval) a ST30 (95% confidence interval) b Dose range (mean) Percent mortality after 10 days (number of larvae dead/total treated) Low dose
Medium-low dose
Medium dose
Medium-high dose
High dose
High quality (0.935)
10.1 (7.8–13.2) 7.2 (5.7–9.1) 318–498 (380) 47 (17/36)
7.2 (5.9–8.7) 5.0 (4.1–6.0) 850–1107 (972) 65 (39/60)
6.9 (5.9–8.2) 5.2 (4.5–6.2) 1133–1777 (1455) 71 (34/48)
6.2 (5.2–7.5) 4.5 (3.8–5.4) 1828–2884 (2226) 71 (34/48)
Test 1
Test 2
Test 3
a
Quality of conidial batch (vigorous/ total viable ratio)
c
Mean ST50 / ST30 (95% CI); pooled data
Cox proportional hazard regression analysis (within test)
4.1 (3.6–4.6) 3.3 (2.9–3.8) 3374–3726 (3528) 97 (35/36)
6.6 (6.1–7.2) 4.7 (4.3 –5.2)
Quality (Q): X 21 = 20.0, P < 0.0001 Dose Category (DC): X 24 = 30.8, P < 0.0001
Low Quality (0.563)
NC 9.8 (6.9–13.8) 296–587 (444) 31 (11/36)
NC 7.9 (4.9–12.9) 793–999 (900) 36 (13/36)
9.7 (7.5–12.5) 7.0 (5.6–8.7) 1091–1724 (1449) 50 (18/36)
7.3 (5.8–9.2) 5.5 (4.4–6.9) 2494–2525 (2510) 67 (18/24)
7.5 (5.9–9.5) 5.6 (4.4–7.1) 2723–3371 (3047) 63 (15/24)
10.3 (8.8– 12.0) 6.8 (6.0–7.8)
Q x DC: X 24 = 4.4, P = 0.35
High quality (0.975)
7.0 (6.5–7.5) 6.1 (5.6–6.6) 259–339 (306) 94 (45/48)
6.8 (6.1–7.5) 5.7 (5.1–6.4) 437–553 (482) 100 (37/37)
6.3 (5.6–7.2) 5.4 (4.7–6.2) 606–734 (670) 92 (22/24)
6.2 (5.4–7.1) 5.0 (4.3–5.7) 847–945 (906) 92 (33/36)
3.5 (3.0–4.0) 2.7 (2.3–3.1) 3022–3735 (3412) 92 (44/48)
5.7 (5.3–6.1) 4.4 (4.1–4.7)
Quality (Q): X 21 = 20.0, P < 0.0001
Low Quality (0.321)
10.6 (8.9–12.6) 7.8 (6.7–9.0) 199–384 (267) 50 (36/72)
7.3 (6.3–8.5) 6.1 (5.2–7.1) 438–535 (487) 88 (21/24)
6.6 (5.5–7.9) 5.2 (4.3–6.3) 755–769 (762) 88 (21/24)
7.1 (5.6–9.1) 5.2 (4.0–6.7) 851–899 (875) 79 (19/24)
5.3 (4.6–6.1) 4.1 (3.6–4.8) 3604–4544 (4174) 83 (40/48)
7.5 (6.9–8.2) 5.6 (5.1–6.1)
High quality (0.977)
NC 7.9 (5.4–11.7) 203–323 (246) 36 (13/36)
6.6 (4.6–9.6) 3.9 (2.8–5.6) 406–498 (437) 58 (21/36)
7.9 (5.1–12.4) 4.3 (2.9–6.5) 582–692 (634) 53 (19/36)
3.5 (2.8–4.2) 2.4 (1.9–3.0) 1319-1947 (1631) 83 (40/48)
2.9 (2.6–3.4) 2.3 (2.0–2.7) 3405-4559 (3984) 94 (45/48)
5.2 (4.5–5.9) 3.2 (2.8–3.6)
NC 10.1 (8.4–12.3) 194–338 (273) 28 (10/36)
NC 8.8 (7.1–10.9) 407–520 (476) 38 (18/48)
NC 10.4 (7.0–15.5) 663–889 (787) 28 (10/36)
9.0 (6.3–13.0) 5.6 (4.1–7.8) 1716–2066 (1868) 50 (18/36)
6.7 (5.6–8.1) 4.9 (4.0–5.9) 4514–6024 (5498) 69 (33/48)
11.0 (9.5– 12.7) 7.3 (6.48.2)
Low Quality (0.058)
4 5 a ST50: median survival time (days until death of 50% of the treated population); ST30: days until death of 30% of treated population. 6 b Dose expressed as total viable conidia per square mm of spray-target surface. 7 c ST50 not calculable (NC), as mortality was substantially less than 50%.
Dose Category (DC): X 24 = 56.8, P < 0.0001 Q x DC: X 24 = 8.7, P = 0.069
Quality (Q): X 21 = 36.1, P < 0.0001 Dose Category (DC): X 24 = 67.7, P < 0.0001 Q x DC: X 24 = 2.8, P = 0.59
GRAPHICAL ABSTRACT
HIGHLIGHTS
•
Speed of germination of fungal conidia is a highly significant virulence factor
•
LC50s of conidia are directly related to the proportion of slow-germinating conidia
•
LC50s based solely on fast-germinating (vigorous) conidia tend to be constant
•
Vigorous conidia lead to shorter survival times of Spodoptera frugiperda larvae
•
Conidial vigor is a better predictor of mycoinsecticide quality than viability
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