Selection of inductors for thermotolerant conidia production of the entomopathogenic fungus Metarhizium rileyi Nm017

ABSTRACT

The insecticidal potential of Metarhizium rileyi could be affected by thermal and hydric stress. In this study, 21 thermo-inductors were added to a fermentation medium to obtain thermotolerant conidia of M. rileyi Nm017. The first screening by a thermotolerance test concluded that using linoleic acid, NaCl, and menadione, conidia reached relative germinations higher than the treatment without inductors. Conidia produced with linoleic acid at 20 and 40 ml kg⁻¹ showed relative germinations of 23.5% and 21.1% after the thermotolerance test, and their germination after a drying process was not affected compared to the control (80.2%). Manufactured costs using linoleic acid, NaCl, and menadione were estimated.

KEYWORDS:

• Thermo inductor
• thermotolerance
• Metarhizium rileyi
• manufactured costs

The entomopathogenic fungus Metarhizium rileyi has a great biocontrol potential and can induce high mortality rates in larval states of Lepidoptera, especially in the Noctuidae family (Fronza et al., 2017). However, it is very sensitive to nutritional conditions and environmental changes (Grijalba et al., 2018). Thermal and hydric stress on conidia can significantly decrease their viability and insecticidal activity, which reduces their potential as an active ingredient in biopesticides. Therefore, methods to minimise these negative effects are necessary (Jaronski & Mascarin, 2017).

Chemical supplementation of culture media could modify the physiological conditions of conidia, enhancing their stress tolerance, especially to heat and dry conditions. This strategy is based on the fungal metabolism readjusted when the cell grows in diverse environments (Rangel et al., 2008). Therefore, the addition of thermotolerance inductors to the fermentation medium for M. rileyi conidia production needs to be further investigated. Furthermore, the effect of the thermo-inductors on manufactured costs must be estimated for the development of a future biopesticide.

Here, twenty-one chemical compounds were evaluated by adding them to a solid-state fermentation to produce M. rileyi Nm017 conidia in the laboratory. These thermo-inductors were shown to improve thermotolerant capacity and resistance to hydric stress in yeasts, fungi, and bacteria, and classified according to its mechanism of action to stress, such as cross-protection, production, and accumulation of compatibles solutes, and modification of the membrane composition (Kim et al., 2010; Park et al., 2018; Rangel et al., 2008). The following reagent grade inducers were selected and obtained from Sigma-Aldrich, Merck^®, Germany, unless otherwise specified: vitamin (menadione), phenolic acid (salicylic acid), oxidising agent (H₂O₂) (Supelco, Merck^®, Germany), sugars [lactose (USP grade, Ciacomeq^®, Colombia), glucose (Millipore, Merck^®, Germany), trehalose, sucrose, and whey permeate (USP grade, Bellchem^®, Colombia)], polyols [sorbitol (PanReac^®, Germany), glycerol, mannitol (Scharlau, ScharLab^®, Spain), and myo-inositol (Millipore, Merck^®, Germany)], salts [NaCl and KCl (Supelco, Merck^®, Germany)], amino acids [L-tyrosine (Millipore, Merck^®, Germany) and glycine], oils (corn oil, soybean oil, and sunflower oil), and fatty acids (linoleic and oleic acids). The basic medium was a mixture of 66.7% rice and 33.3% of a nutritional solution [2% v/v V8^® Vegetable Juice (Campell’s, U.S.A)], for hydration. The concentration of inducers used in this study was the highest effective concentration reported and the amount added was determined by the total weight of rice. Substances were mixed with the medium before sterilisation, except H₂O₂, vegetable oils, and fatty acids. Before being added to the medium, vegetable oils and fatty acids were emulsified in a sterile solution of 1% v/v polysorbate 80 with a disperser at 7200 rpm for 1 min (T25 Ultraturrax^® IKA). The medium without inductors was the control treatment. Mediums were placed in aluminum trays of 11 cm × 4 cm × 3.5 cm, inoculated with a conidia suspension adjusted to 4.2 × 10⁶ conidia ml⁻¹ by spray, and covered with a polyethylene-polypropylene film to keep a relative humidity close to 80% inside the trays. All treatments (two repetitions over time and five replicates per treatment) were incubated in a room for 7 days, at 25 ± 2°C, with 40 ± 10% relative humidity and constant exposure to LED light.

Once the fermentation was finished, 1 g of colonised substrate was diluted in 9 ml solution of 1% v/v polysorbate 80 to determine the fresh conidia concentration by counting in a hemocytometre; conidia germination was evaluated on bacteriological agar plus 2% v/v V8^® juice, 2% w/v yeast extract, and 0.00006% w/v Benomyl [Benlate 50% w/w (WP)]. Petri dishes were incubated at 28 ± 2°C for 48 h, lactophenol blue was added to stop the growth, and at least 100 conidia were counted to determine the ratio of germinated and ungerminated conidia. Conidia suspensions were made from the colonised substrates and adjusted to 1 × 10⁷ conidia ml⁻¹, to expose samples of 1 ml to a thermotolerance assessment (thermostat bath at 45 ± 0.5°C for 3 h). The germination was evaluated as described above, and the result was reported as relative germination (RG) using the following equation, modified from Braga et al. (2001): (1) $RG\left(\text{\%}\right)=\left({\displaystyle \frac{G_f}{G_b}}\right)\ast 100$(1) Where: G_b and G_a are the percentages of germination before and after the thermotolerance test for each treatment, respectively.

The results were verified for data normality (Shapiro–Wilk test) and the homoscedasticity (Levene’s test). Also, analysis of variance (ANOVA) was performed to define significant differences. Tukey HSD test was also done to check variance with a confidence level of 95%.

The conidia production using glucose, sorbitol, corn oil, soybean oil, sunflower oil, oleic acid, linoleic acid, KCl, glycerol, mannitol, NaCl, and H₂O₂ showed a significant decrease in concentration compared to the control (F_21,197 = 68.70, P ≤ 0.001; Figure 1A). On the other hand, no differences were found between the control medium and the treatments with glycine, menadione, salicylic acid, myo-inositol, whey protein, lactose, sucrose, and tyrosine. Germination after fermentation revealed that 15 of 21 chemicals kept values no statistical different to the control (F_21,198= 17.35, P ≤ 0.001; Figure 1A). Relative germination represented the fraction of conidia that survive the thermal treatment. In our results, the relative germination of menadione (6.9%), linoleic acid (22%), oleic acid (2.8%), NaCl (12%), and KCl (3.2%), were significantly higher than the control (F_4,45= 17.57, P ≤ 0.001). Hence, conidia obtained from the substrate supplemented with the mentioned compounds exhibited the highest relative germination, which suggests that they enhanced conidia thermal protection, potentiating their germination. The remaining 16 substances and the control showed a relative germination lower than 1%.

Figure 1. (A) Concentration (bars) and germination (line) of fresh conidia, and (B) Dry conidia concentration for fermentation for thermotolerant conidia production of M. rileyi Nm017. Variables with the same upper or lowercase letter did not differ significantly according to the Tukey HSD test (P > 0.05). Each variable was subjected to an independent statistical analysis.

The highest relative germination between the fatty acids was obtained with linoleic acid, whose conidia concentration did not show statistical differences compared to oleic acid (Figure 1A). The same trend was observed with both salts NaCl and KCl, with Nacl having more inducing potential between the two compounds. The third compound that presented one of the highest relative germination and conidia concentration values was menadione. Therefore, a second experiment was done to evaluate different concentrations of linoleic acid, NaCl, and menadione, and their effect on thermotolerant capacity after the thermotolerance test and a drying process, as well as performance parameters.

In the second part of this study, the concentrations of NaCl and linoleic acid were adjusted to 50% and 75% of the initial concentration, while for menadione, the concentrations were ± 50% of the initial concentration (Table 1). For this evaluation, five replicates per treatment and three repetitions over time were done. The fermentation conditions of each treatment of the thermotolerance assessment were performed as was described previously. Afterwards, a drying process was performed: the plastic film was removed from the trays and was covered with cellulose membrane (pore size: 0.05 cm²; density: 20 pore cm⁻²) and placed in a room at 25 ± 2°C and 40 ± 10% RH for 7 days, until the colonised substrate reached a moisture content ≤10%. Subsequently, conidia concentration and relative germination were assessed as described above. The substrate obtained from the drying process was weighed and sieved using a mesh with a size opening of 500 µm; the recovered biomass was weighed, and the moisture content was determined by a halogen balance (MLS 50-3, Kern), to calculate yield of biomass/substrate (g biomass kg⁻¹ substrate) and yield of conidia/dry biomass (conidia g⁻¹ dry biomass). Variables were statistically analyzed as described above.

Table 1. Microbiological quality, process efficient performance, and manufactured cost modelling for thermotolerant conidia production of M. rileyi Nm017.

Treatment	Concentration	Relative germination (%)		Process Yields		Total Cost (USD $)
		Thermotolerant assessment	Dry conidia	Conidia/biomass (conidia g^−1)	Biomass/substrate (g kg^−1)
Control	–	N.G.	80.2 ± 7.6 ^abc	1.4 ± 0.3 × 10^8 ^cd	4.7 ± 0.3 ^b	19.61
Menadione	0.026 g kg^−1	N.G.	78.8 ± 8.7 ^abc	1.6 ± 0.4 × 10^8 ^c	3.2 ± 0.4 ^d	17.97
Menadione	0.017 g kg^−1	N.G.	86.4 ± 5.6 ^ab	2.9 ± 0.8 × 10^8 ^b	3.4 ± 0.1 ^d	18.19
Menadione	0.009 g kg^−1	N.G.	88.4 ± 11.3 ^ab	5.0 ± 0.9 × 10^8 ^a	4.1 ± 0.2 ^c	18.42
NaCl	58.4 g kg^−1	5.8 ± 2.8 ^c	85.0 ± 7.4 ^ab	3.7 ± 2.3 × 10^6 ^h	2.4 ± 0.1 ^e	21.20
NaCl	29.1 g kg^−1	N.G.	65.6 ± 12.5 ^c	6.3 ± 1.9 × 10^6 ^g	4.8 ± 0.2 ^ab	24.43
NaCl	14.6 g kg^−1	N.G.	68.8 ± 14.3 ^c	1.5 ± 0.3 × 10^7 ^f	5.1 ± 0.3 ^a	25.70
Linoleic acid	80 ml kg^−1	14.9 ± 3.5 ^b	95.0 ± 3.4 ^a	3.8 ± 0.8 × 10^7 ^e	3.4 ± 0.3 ^d	35.26
Linoleic acid	40 ml kg^−1	22.0 ± 6.1 ^a	91.6 ± 4.9 ^ab	1.1 ± 0.2 × 10^8 ^d	3.3 ± 0.3 ^d	26.07
Linoleic acid	20 ml kg^−1	23.8 ± 8.2 ^a	87.3 ± 4.5 ^ab	1.9 ± 0.5 × 10^8 ^c	4.3 ± 0.3 ^c	22.59

N.G.: no germinated conidia were observed after the thermotolerant assessment.

Columns with the same letter did not differ significantly according to the Tukey HSD test (P > 0.05). Each variable was subjected to an independent statistical analysis.

After thermotolerance assessment, the significantly highest germination was obtained with 20 and 40 ml kg⁻¹ of linoleic acid (F_3,36= 19.5, P < 0.001; Table 1). Instead, the control did not present germinated conidia after the test.

After the drying process, the conidia concentrations of 58.4 g kg⁻¹ NaCl and 80 ml kg⁻¹ linoleic acid produced the lowest concentrations, decreasing 16.3% and 19.8% from the control, respectively (F_9,82= 121.5, P < 0.001; Figure 1B); the other treatments were not statistically different. Regarding the relative germination reached by dry conidia, all menadione and linoleic acid treatments, NaCl at 58.4 g kg⁻¹, and the control were equal (F_9,88= 6.75, P < 0.001; Table 1). The thermal protection with linoleic acid increased around 7.1% and 14.8%, compared to the control.

The results showed that the use of lower concentrations of linoleic acid, NaCl, and menadione promoted biomass production, exceeding the biomass/substrate yield obtained in the control treatment. The biomass/substrate yield of M. rileyi Nm017 showed significant variation between treatments and control (F_9,90= 120.93, P < 0.001; Table 1). Treatments with NaCl at 14.6 and 29.1 g kg⁻¹, and the control had the highest biomass/substrate yield; meanwhile, with the remaining treatments, this parameter decreased between 9.5% and 49.1% from the control. Furthermore, the conidia/biomass yield with concentrations 0.009 and 0.017 g kg⁻¹ of menadione were significantly higher compared to the control (F_9,88= 411.17, P < 0.001; Table 1), and increased by 3.8% and 6.7%, respectively. Also, the yield decreased between 7% and 20.3% using linoleic acid at 80 ml kg⁻¹ C1 and all NaCl treatments, respectively. There were no significant differences between the control and the other treatments.

The manufactured costs at pilot-scale of the thermotolerant inductors selected from the first experiment (linoleic acid, NaCl, and menadione) were estimated to compare to the control production costs. For this, a base calculation of one kilogram of the processed substrate was used. The cost modelling developed by AGROSAVIA’s Bioproducts Department was used to determine the costs of raw material, personnel, etc., in both direct and indirect measures (Equation 2). Total costs were statistically analyzed as described previously. (2) $\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{o}\mathrm{s}\mathrm{t}\left(USD\mathrm{\$}\right)=DRM+DLC+ILC+IRM+OIC$(2) Where: DRM (direct raw material) is the consumption of each raw material required multiplied by the price of raw materials; DLC (direct labour cost) is the cost of man-hours required for each level of staff training; ILC (indirect labour cost) is the cost of man-hours required for personnel performing supervision; IRM (indirect raw material) which corresponds to 10% of the total of raw material costs (general commodities); OIC (other indirect costs) corresponds to 10% of net costs (infrastructure, equipment, leases, and waste collection). DRM, DLC, and IRM are variable costs, while ILC and OIC are fixed costs.

The elements that most affected the total cost of production for the three most influential chemicals (menadione, NaCl, and linoleic acid) were those related to raw materials and direct labour. In the cost modelling analysis, 1 kg of the substrate used to produce M. rileyi Nm017 conidia by baseline fermentation system had a final cost of USD $19.61, and the most influenced cost was direct labour, which represents 28–45% of the total cost. The production cost with treatments with 58.4 g kg⁻¹ NaCl and 80 ml kg⁻¹ linoleic acid, which had the best response to thermal and hydric stress, increased this price by USD $1.59 and USD $15.60, respectively, from the conventional process. A lower production cost and higher yield were evidenced with 0.0017 g kg⁻¹ menadione. Similarly, the lowest cost from NaCl treatments was achieved with the highest concentration. Treatments with linoleic acid at 40 and 80 ml kg⁻¹ were the costliest processes, with raw material costs being most impactful. Meanwhile, with 20 ml kg⁻¹ concentration, direct labour was the least influenced cost, and had an increase in yield and biomass production. While the use of linoleic acid increases operational costs, it could also increase tolerance to thermal and hydric stress factors, beneficial for the conservation of viability during downstream processes and application in field conditions.

Thermo-inductors are commonly used in culture medium for several microorganisms to improve physiological responses to stressors and enhance protective mechanisms as cross-protection, compatible solutes accumulation, and modification of the cell membrane (Kim et al., 2010). The use of substances whose bioactivity is related to changes in the cell membrane, such as culture medium with grains rich in fatty acids (millet, corn), improved the thermal profile of B. bassiana and M. anisopliae conidia through an accumulation of phospholipids in the cell membrane (Kim et al., 2010; Yu et al., 2020). Kim et al. (2010) proved that culture medium with fatty acids increased the thermotolerance of Isaria fumosorosea SFP-198 by 41% compared to the control (36.8%), after conidia were subjected to 50°C for 2 h. In the present study, the results showed that the substance with the greatest inducing effect was linoleic acid.

The external lipid supply likely influenced the modification of the cell membrane and enabled a thermal protection response. Certain concentrations of lipid sources can change their cell morphology, reducing cell damage in response to thermal shocks. Therefore, lipid synthesis is facilitated through the transport of precursors and improves cell structure. Hence, the use of linoleic acid in low concentrations could be implemented to increase the thermal resistance of conidia (Ianutsevich et al., 2016).

Dry conidia production from linoleic acid treatments differed significantly from the control, probably due to the biogenesis of these structures, involving the synthesis and accumulation of neutral lipids that contribute to growth and conidiation in standard culture medium. However, a high concentration of fatty acids produces an immobilisation of lipids within the endoplasmic reticulum, and causes a delay in growth and conidiation (Keyhani, 2018). Therefore, the use of linoleic acid for M. rileyi Nm017 production influenced development, by decreasing conidiation at the end of the fermentation time. In contrast, high concentrations of fatty acid induced a cell delay and increased growth time, due to the metabolic retention of lipids within the cell (Keyhani, 2018).

In conclusion, the inductors linoleic acid, NaCl, and menadione added to the culture medium decreased the thermal sensitivity of M. rileyi Nm017 conidia after a thermotolerance test. Linoleic acid was the substance that most favourably influenced the production of thermotolerant conidia, and this indicates that it is a potentially promising culture condition. Its use in concentrations lower than 80 ml kg⁻¹ can improve conidia viability and protects the cell from the drying process, although the manufactured costs increased in regard to the baseline process. However, the possibility to obtain conidia more resistant to thermal and hydric stress could enhance its performance during the technological development. In fact, the increased manufacturing costs can be offset by longer shelf life, a greater number of geographic areas where the product can be used, and greater appeal to consumers.

Acknowledgments

The authors would like to thank Ministerio de Agricultura y Desarrollo Rural (MADR) for funding this study. Also, to AGROSAVIA’s professional and assistant Jaime Rocha and Stella Rincon, who were always willing to collaborate in all the activities related to this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by the Ministerio de Agricultura y Desarrollo Rural (MADR).