Next Article in Journal
Two Species Delimitation of Pseudaulacaspis (Hemiptera: Diaspididae) Based on Morphology, Molecular Clustering, and Niche Differentiation
Previous Article in Journal
Potential of Entomopathogenic Nematodes to Control the Cabbage Stem Flea Beetle Psylliodes chrysocephala
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Insects
Volume 14
Issue 8
10.3390/insects14080667
insects-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Increased Phenoloxidase Activity Constitutes the Main Defense Strategy of Trichoplusia ni Larvae against Fungal Entomopathogenic Infections

by
Kristin R. Duffield
1,*,
Alayna M. Rosales
2,
Ephantus J. Muturi
1,
Robert W. Behle
1 and
José L. Ramirez
1,*
1
USDA-ARS, National Center for Agricultural Utilization Research, Crop BioProtection Research Unit, 1815 N. University St., Peoria, IL 61604, USA
2
Biology Department, Bradley University, Peoria, IL 61604, USA
*
Authors to whom correspondence should be addressed.
Insects 2023, 14(8), 667; https://doi.org/10.3390/insects14080667
Submission received: 21 June 2023 / Revised: 18 July 2023 / Accepted: 20 July 2023 / Published: 25 July 2023
(This article belongs to the Section Insect Behavior and Pathology)
Browse Figures
Review Reports Versions Notes

Abstract

:

Simple Summary

The cabbage looper is an important agricultural pest worldwide and is frequently used as a model organism for measuring the effectiveness of biopesticides, including those derived from pesticidal fungi. To better understand how cabbage loopers resist and survive infection of insect-killing fungi, we measured several insect defense parameters following exposure to two species of fungi. Our results indicate that the cabbage looper’s main defense mechanism is the melanization cascade, with activation of several melanization-related genes soon after infection. This differs from what has been reported in other insect–fungi studies and might represent a target for disruption in future cabbage looper control strategies that integrate fungal biopesticides. Our study also shows that one well-known insect antifungal immune response does not participate in the cabbage looper antifungal defense, differentiating this important pest from other insects. Overall, this study provides insights into the host response strategies employed by cabbage loopers for protection against pesticidal fungi and aids in the design of more effective biological control strategies for this pest.

Abstract

The cabbage looper Trichoplusia ni is an important agricultural pest worldwide and is frequently used as a model organism for assessing entomopathogenic fungi virulence, though few studies have measured the host response repertoire to fungal biocontrol agents. Here, we quantified the immune response of T. ni larvae following exposure to two entomopathogenic fungal species: Beauveria bassiana and Cordyceps javanica. Results from our study demonstrate that T. ni larvae exposed to fungal entomopathogens had higher total phenoloxidase activity compared to controls, indicating that the melanization cascade is one of the main immune components driving defense against fungal infection and contrasting observations from other insect–fungi interaction studies. We also observed differences in host response depending on the species of entomopathogenic fungi, with significantly higher induction observed during infections with B. bassiana than with C. javanica. Larvae exposed to B. bassiana had an increased expression of genes involved in prophenoloxidase response and the Imd, JNK, and Jak/STAT immune signaling pathways. Our results indicate a notable absence of Toll pathway-related responses, further contrasting results to other insect–fungi pathosystems. Important differences were also observed in the induction of antimicrobial effectors, with B. bassiana infections eliciting three antimicrobial effectors (lysozyme, gloverin, and cecropin), while C. javanica only induced cecropin expression. These results provide insight into the host response strategies employed by T. ni for protection against entomopathogenic fungi and increase our understanding of insect–fungal entomopathogen interactions, aiding in the design of more effective microbial control strategies for this important agricultural pest.

1. Introduction

Entomopathogenic fungi abound in nature, where they act as natural regulators of insect populations [1,2]. Due to their efficacy, mode of direct contact transmission, and range of host specificity, fungal pathogens have been used as biological control agents against insect pests for centuries. Since the 1970s, the development of commercialized products utilizing entomopathogenic fungi (e.g., from Metarhizium, Beauveria, and Cordyceps genera) as environmentally friendly alternatives to traditional chemical pesticides has greatly expanded [3,4]. Importantly, the success of fungal pathogens depends on both host (e.g., physical state, resistance) and environmental factors (e.g., temperature, humidity, UV exposure) [5], which can impose severe limitations on their use as a cost-effective biological control [6]. Moreover, compared to chemical pesticides, fungal pathogens have lower virulence (i.e., slow kill speed with a higher inoculum required). Recent research efforts have considerably improved fungal biocontrol agents [7,8]. For example, genetic modifications have resulted in fungal strains with increased virulence and resistance to abiotic stress [9,10].
Entomopathogenic fungi are typically screened in agricultural pests via bioassays that measure host mortality, and often mycosis, across increasing doses (e.g., survival analysis) [11]. However, little consideration is given to evaluating insect host responses following exposure to fungal pathogens despite their role in determining infection outcomes. Consequently, we know far less about the host response of many agricultural insect pests to entomopathogenic fungi [12]. Understanding the host response (i.e., immunity) of target pests to entomopathogenic fungi may improve the modification, selection, and application of mycoinsecticides, as characterizing immune responses across groups could reveal variables of host susceptibility. For example, solitary migratory locusts, Locusta migratoria, were found to be less susceptible to Metarhizium anisopliae infection than gregarious migratory locusts. Transcriptome analysis of these two populations revealed that locusts from gregarious populations were prophylactically upregulating immune function, which likely conferred greater protection [13].
Insects possess a suite of countermeasures to fight and defend against infection by fungal pathogens, and populations can adapt their responses over time [14] and within generations via immune priming [15]. Most of what is known about the molecular basis of the insect immune response to fungal infections comes from work in Drosophila melanogaster [16,17] and some lepidopteran [18] and mosquito species [19,20,21]. For infection to establish, fungal spores (or conidia) must attach to and penetrate the insect cuticle via a combination of enzymes, after which fungal blastospores bud off hyphae, multiply, and circulate within the insect hemocoel. There, fungal cells are detected via pattern recognition receptors (PRRs), which quickly activate innate immune defenses, including both humoral and cellular immunity [22]. Within the humoral defense, the Toll pathway is the primary immune signaling pathway to respond to fungi in Drosophila [23]. Additionally, the immunodeficiency (Imd), Janus kinase-signal transducer and activator of transcription (Jak-STAT), and c-Jun N-terminal kinase (JNK) pathways play important roles in insect defense against pathogens, including fungi [24]. Upon pathogen recognition, signals then pass through intracellular signal transduction cascades, leading to the expression of potent antimicrobial effectors that are primarily produced in the fat bodies but also by epidermis cells and hemocytes [25]. Lepidopterans are known to produce several classes of antimicrobial effectors, such as lysozymes, cecropins, gloverins [26], and defensins [27], including gallerimycin [28]. While the role that specific antimicrobial effectors play in entomopathogenic fungi defense is largely unknown, there are some reported examples. For instance, cecropin A and gloverin2 were found to have high antifungal activity against Beauveria bassiana in silkworm larvae (Bombyx mori) [29,30].
The prophenoloxidase (proPO) activation system is another component of the insect humoral immune response, which regulates the coagulation and melanization of hemolymph in response to pathogens. It comprises both short (e.g., reactive quinones) and long-lasting (e.g., melanin) products that are quickly deposited to surround invading fungi to encapsulate and kill [31]. Mounting a potent immune response not only attacks pathogens but can also cause collateral damage to host cells. As such, antioxidant enzymes are deployed following exposure to biotic and abiotic stressors, including pathogens, to protect host cells from Reactive Oxygen Species (ROS).
The cabbage looper Trichoplusia ni (Lepidoptera: Noctuidae) is a common agricultural pest throughout much of the world and has long been used as a representative lepidopteran for studying insect physiology [32,33,34,35], including insect pathology [36,37,38,39]. Furthermore, T. ni has frequently been used as a model insect for assessing the efficacy of biopesticides [40,41,42,43,44] as well as resistance evolution, as T. ni is known to have developed resistance to Bacillus thuringiensis (Bt), a widely used microbial insecticide [45,46]. However, less is known about the immune response of T. ni to fungal entomopathogens, especially at the transcription level. In the present study, we characterized the immune response of T. ni larvae to two entomopathogenic fungal species, B. bassiana (MBC 076) and Cordyceps javanica (MBC 439) (formerly Isaria javanica). Both fungal species are known to infect a broad insect host range [47], including lepidopterans. Here, we quantified the total phenoloxidase (PO) activity in addition to measuring the expression of immune gene markers across Toll, Imd, Jak/STAT, and JNK immune signaling pathways; propohenoloxidase (proPO) response; and stress and detoxification response using real-time PCR (qPCR).

2. Materials and Methods

2.1. Insect Rearing

We assessed immune responses following fungal exposure in 5-day-old cabbage looper larvae. Larvae were reared in individual cups in the dark on ‘general purpose lepidoptera diet’ (Frontier Agricultural Sciences, Newark, DE, USA) at 27 ± 2 °C and 55 ± 10% relative humidity until fungal exposure at 5 days old.

2.2. Entomopathogenic Fungi Exposure

Larvae were exposed to two common entomopathogenic fungal strains: Beauveria bassiana (MBC 076) and Cordyceps javanica (MBC 439). Fungal cultures were conducted as previously described [21]. Briefly, cultures of B. bassiana (MBC 076) and C. javanica (MBC 439) were grown on ¼ strength Sabouraud dextrose agar and yeast extract (SDAY) medium at 26 °C for 15 days. Conidia were harvested from plates with a sterile inoculation loop and suspended in 3 mL of 0.04% Tween-20 (Invitrogen, ThermoFisher Scientific, Waltham, MA, USA). To remove mycelia, conidia were filtered using a syringe filter (1 mL) which were then used to make 1 × 108 concentrations for inoculation.
For fungal inoculation, ten larvae were placed into small cups containing 2 mL of their respective treatment (either 1 × 108 B. bassiana conidia in 0.04% Tween-20, 1 × 108 C. javanica conidia in 0.04% Tween-20, or 0.04% Tween-20 for control larvae). Larvae were gently swirled for 20 s and then carefully removed with wide-tip entomology forceps and placed on a dry paper towel before being returned to their original rearing environment.

2.3. Phenoloxidase Activity Assay

The melanization cascade is often an important antifungal defense within insects. Here, we measured total phenoloxidase (PO) activity as described in Sadd et al. [48], with some modifications. Briefly, T. ni larvae that have undergone fungal exposure were transferred to their original rearing cup and maintained under rearing conditions described above. At 2 days post-infection, larvae were cold anesthetized on ice, and their back proleg was cut with sterile micro scissors to collect 10 µL of outflowing hemolymph. The collected hemolymph was mixed with 40 µL of cold 1× PBS, flash-frozen with liquid nitrogen, and stored at −80 °C. PO assays were conducted with 15 µL of sample (hemolymph in 1× PBS) or 15 µL of 1× PBS (negative control). Samples were transferred to a flat-bottomed 96-well plate containing 140 µL of molecular-grade water and 20 µL 1× PBS. A 20 µL L-Dopa suspension (4 mg/mL H2); 3,4 dihyroxy-L-phenylalanine was then added to each well and mixed for 5 s at 30 °C in a spectrophotometer (Multiskan GO, Thermo Scientific, Waltham, MA, USA). The absorbance was read at 490 nm every 15 s with 5 s of shaking between reads. PO activity was calculated from the slope (Vmax) of the reaction curve during its linear phase over 160 readings. Each sample was read in duplicate and the average was used to evaluate statistical significance. Three independent experiments were conducted with 10 individuals per treatment and each experiment was conducted with a fresh batch of larvae and fungal spores.

2.4. Reverse Transcriptase Quantitative PCR (RT-qPCR) Detection and Quantification

To assess immune function at the transcription level, we performed gene expression analysis of genes across multiple immune pathways. Here, larvae were killed 2 days post-infection (sample size = 13 larvae per treatment) by freezing. RNA was extracted from individual whole-bodied larvae using TRIzol (Invitrogen) according to the manufacturer’s instructions. Concentration and quality of the extracted RNA were evaluated via NanoDrop (Thermo Scientific, Waltham, MA, USA). Synthesis of cDNA was conducted on normalized amounts of RNA using the QuantiTec reverse transcription kit with DNA Wipeout (Qiagen, Hilden, Germany).
To assess a range of potential genes involved in the antifungal immune response, we targeted multiple genes across different facets of insect immunity, including those involved in the prophenoloxidase (proPO) response as well as the Toll, Imd, Jak/STAT, and JNK immune signaling pathways and the stress and detoxification response. We screened several previously established gene targets of T. ni predicted to be involved in immune function [37,38] We also designed several primers targeting key immune genes (Table 1) using Primer3 (v 0.4.0) [49,50] based on other previous studies [51,52]. Fungal and bacterial load was quantified by measuring the transcript abundance of the 18s rRNA gene using fungal-specific primers designed to amplify a highly conserved region among fungi [53] and the 16s rRNA gene using bacterial-specific primers designed to amplify a highly conserved region among bacteria (all primers from IDT, Inc., Newark, NJ, USA).
We used a primer targeting the mitochondrial ribosomal protein S18 (Table 1) as our reference gene target throughout for quantification purposes. This gene was selected based on its superior performance/ranking to other genes via RefFinder [54,55], which uses the algorithm from major computational programs such as geNorm, Normfinder, and Best-Keeper to compare and rank candidate reference genes. Prior to conducting qPCR assays, RNA was normalized to 1 µg, treated with DNA Wipeout, and then converted to cDNA using the QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany).
Real-time qPCR reactions were run on a Quant-Studio 6 Real-Time PCR instrument (Thermo Fisher Scientific, Waltham, MA, USA), and included a melt-curve stage to confirm product specificity. One microliter of cDNA product was used in a 10 µL qPCR reaction using gene-specific primers (Table 1) and PowerUp SYBR Green Master Mix kit (Qiagen). qPCR cycling conditions consisted of holding at 50 °C for 2 min and 95 °C for 2 min and 40 cycles of 1 s at 95 °C and 30 min at 60 °C. Gene expression profiles were evaluated post-run using the ΔΔCt method [56].

2.5. Survival

To measure the impact of our fungal treatments on survival, mortality was measured daily following fungal treatment inoculation until pupation (n = 30 per treatment). In a separate group of larvae, if an individual survived to pupation, they were included as censored values in the subsequent analysis.

2.6. Statistical Analysis

All statistical analyses were conducted using GraphPad Prism 9 (Version 9.4.1). For expression data, we first removed outliers via ROUT using default settings (Q = 1%) [57]. To fit assumptions of normality, expression data for most target genes were log2 transformed. The exceptions to this were for expression of Gallerimycin, which was square-root transformed, as well as PO activity, STAT5B, Defensin, JNK, JUN, and fungal 16s rRNA; all of which were not transformed.
For most tests, we analyzed the expression data and PO activity with a standard one-way ANOVA with Dunnett’s multiple comparisons test. However, due to unequal standard deviations in some cases, we employed a Welch ANOVA with Dunnett’s multiple comparisons test for expression of the genes PPO2, Cactus-like, Relish, JNK, and Gloverin. Expression data for STAT5B and fungal 18s rRNA were analyzed with the nonparametric Kruskal–Wallis test with Dunn’s multiple comparisons test. Larval survival to pupation was analyzed via a Kaplan–Meier with Log-rank test. For all tests, statistical significance was assessed at p < 0.05, with the strength of the significance represented with asterisks (* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

3. Results

3.1. Survival

In a subset of T. ni larvae, we quantified survival rate to pupation following exposure to sublethal doses of B. bassiana and C. javanica. Mortality was very low across all larvae. Within each treatment group, two out of thirty (6.7%) larvae died prior to pupal molt, and neither exposure to C. javanica nor B. bassiana increased mortality in T. ni larvae (Mantel-Cox: χ22 = 0.001; p = 0.9993).

3.2. Microbial Loads

We evaluated the total fungal and bacterial load in T. ni across fungal treatments by quantifying the expression of fungal 18s rRNA or bacterial 16s rRNA, respectively. Our fungal treatments significantly affected total fungal loads within T. ni larvae (Kruskal–Wallis test: H = 10.69, p = 0.0048; Figure 1). Specifically, both T. ni larvae exposed to C. javanica (Dunn’s: p = 0.0024) and B. bassiana (Dunn’s: p = 0.0292) had a higher expression of fungal 18s rRNA compared to control larvae. For bacterial 16s rRNA, our main ANOVA model was statistically significant (ANOVA: F2, 36 = 3.340; p = 0.0467); however, neither larvae exposed to C. javanica (Dunnett’s: p = 0.9352) nor B. bassiana (Dunnett’s: p = 0.0823) had different total bacterial loads compared to controls (Figure 1).

3.3. Total Phenoloxidase (PO) Activity

Using an enzymatic assay, we assessed the phenoloxidase activity following exposure to our fungal treatments. Larvae exposed to either fungal species in this study exhibited significantly higher PO activity 2 days post-exposure compared to controls (ANOVA: F2, 107 = 20.30; p < 0.0001; Dunnett’s: B. bassiana p < 0.0001; C. javanica p = 0.0077; Figure 2A).

3.4. Gene Expression

We evaluated the relative expression of genes involved in the prophenoloxidase response, immune signaling pathways (Toll, Imd, JNK, and Jak/STAT), multiple antimicrobial effectors (Cecropin, Defensin, Lysozyme, Gallerimycin, and Gloverin), and Catalase, which plays a role in detoxification of ROS as well as the host stress response.

3.4.1. Prophenoloxidase (proPO)

Multiple genes involved in the prophenoloxidase response of T. ni larvae were induced by inoculation of our fungal pathogen treatments (ANOVA: PPOAE: F2, 34 = 7.596; p = 0.0019; PPO2: W2, 21.29 = 7.664; p = 0.0031; Figure 2B). Specifically, T. ni larvae exposed to B. bassiana had a higher expression of both ProPO activating enzyme (PPOAE) and ProPO subunit 2 (PPO2) (Dunnett’s: PPOAE: p = 0.0012, PPO2: p = 0.0016; Figure 2B), while C. javanica-treated larvae had similar expression levels to control larvae (Dunnett’s: PPOAE: p = 0.5221, PPO2: p = 0.0751; Figure 2B). The expression of ProPO subunit 1 (PPO1) was similar across all treatment groups (ANOVA: F2, 36 = 2.243; p = 0.1208; Dunnett’s: B. bassiana p = 0.0750; C. javanica p = 0.5283; Figure 2B).

3.4.2. Immune Signaling Pathways

Based on our data, neither B. bassiana nor C. javanica induced gene targets in the Toll immune signaling pathway of T. ni larvae 2 days post-infection (Figure 3A). Expression of Tollo (ANOVA: F2,36 = 1.254; p = 0.2974), Toll-7 (ANOVA: F2,36 = 1.269; p = 0.2934), Cactus-like (Welch ANOVA: W2,23.15 = 2.263; p = 0.1266), and Dorsal/Dif (ANOVA: F2,35 = 0.4302; p = 0.6538) was similar across all groups.
Within the Imd immune signaling pathway, the expression of Relish was significantly higher in larvae exposed to B. bassiana compared to controls (Welch ANOVA: W2,21.24 = 3.261; p = 0.0582; Dunnett’s: p = 0.0373), but similar to controls in larvae exposed to C. javanica (Dunnett’s: p = 0.5496; Figure 3B). IKK-β expression was comparable across all treatments (ANOVA: F2,35 = 0.2261; p = 0.7988; Figure 3B).
JNK expression was significantly higher in B. bassiana-treated larvae (Welch ANOVA: W2,19.45 = 3.658; p = 0.0448; Dunnett’s: p = 0.0272), but similar in control and C. javanica-treated larvae (Dunnett’s: p = 0.5612; Figure 3C). JUN, another target within the JNK immune signaling pathway, was similar across all treatments (ANOVA: F2,35 = 0.01312; p = 0.9870; Figure 3C).
Finally, within the Jak/STAT immune signaling pathway, the expression of STAT5B was significantly higher in larvae exposed to B. bassiana (Kruskal–Wallis test: H = 5.788, p = 0.0553; Dunn’s: p = 0.0336), while the expression in C. javanica-exposed larvae and controls did not differ from each other (Dunn’s: p = 0.3068; Figure 4A).

3.4.3. Stress Response-Detoxification

Catalase was not differentially expressed across fungal treatments (ANOVA: F2,34 = 1.903; p = 0.1647; Figure 4B).

3.4.4. Antimicrobial Effector Molecules

Cecropin was expressed significantly higher in both fungal treatments compared to controls (ANOVA: F2,34 = 36.29; p < 0.0001; Dunnett’s: B. bassiana p < 0.0001; C. javanica p = 0.0026; Figure 4C). Additionally, larvae exposed to B. bassiana had a higher expression of both Lysozyme (ANOVA: F2,34 = 3.197; p = 0.0534; Dunnett’s: p = 0.0315) and Gloverin (Welch ANOVA: W2,20.85 = 6.672; p = 0.0058; Dunnett’s: p = 0.0037); however, there was no change in expression between C. javanica-exposed larvae and controls (Dunnett’s: Lysozyme p = 0.5339; Gloverin p = 0.3377; Figure 4C). Finally, the expression of Defensin (ANOVA: F2,36 = 1.572; p = 0.2215) and Gallerimycin (ANOVA: F2,33 = 1.660; p = 0.2057; Figure 4C) was similar across all groups.

4. Discussion

Host-derived responses and differences in fungal strain virulence are known to significantly influence the outcome of fungal entomopathogenic infections in insects. In this study, we evaluated the T. ni larvae anti-fungal host response following a challenge with two different species of entomopathogenic fungi.
Our survival bioassays indicated low mortality of T. ni larvae exposed to B. bassiana (MBC 076) or C. javanica (MBC 439). This is similar to what has been previously documented with bioassays that include exposure of second instar T. ni larvae to B. bassiana [58] but contrasts with findings from other studies [44]. One likely explanation for this is the variation in fungal virulence among fungal strains and the mode of infection used in these studies. Additionally, it could be due to differences in the age of larvae at the time of inoculation. While we chose to infect at 5 days old when larvae were easier to handle without risk of injury, many previous studies have demonstrated significant mortality to neonate larvae [59]. These results suggest that T. ni larvae are only susceptible to these fungal strains for a very short time, which could have important implication in field applications. Future studies exploring the effect of host age on fungal susceptibility, in addition to changes in host immune response, would provide critical information on host susceptibility in this model system. Still, fungal loads were higher in both fungal treatment groups compared to controls, suggesting either that fungi were able to proliferate within the host, yielding a sublethal infection, or that they are confined within the cuticle and unable to infect the host. We argue that the former scenario is more likely due to the upregulation of the immunity of inoculated larvae observed in this study.
Our study indicates that the melanization cascade is one of the main components driving the T. ni larval defense against fungal infection. We found a significant induction of phenoloxidase activity in larvae infected with both species of fungi, with larvae exposed to B. bassiana having significantly higher PO activity in comparison to C. javanica, which might indicate a higher virulence of B. bassiana. These results are further corroborated by the significant induction of PPOAE and PPO2, two important prophenoloxidase cascade genes, in B. bassiana-infected larvae. A similar induction in PO activity has been observed in the Asian corn borer Ostrinia furnacalis during infections with B. bassiana [60]. However, this contrasts with the significant decrease in PO activity observed in the greater wax moth Galleria mellonella–B. bassiana infection system [61]. Prophenoloxidase responses post-fungal infection have been shown to vary according to the host–fungal combination [61,62], and it is most likely determined in part by fungal virulence. For instance, studies conducted by Vertyporokh and Wojda [63] demonstrated strong PO activation in G. mellonella larvae injected with sublethal doses of the fungus Candida albicans but a significant inhibition with injections of lethal doses. Provided C. albicans is not a known entomopathogenic fungus, these findings might indicate a plasticity of the prophenoloxidase cascade response during microbial infections, with the intensity of the response increasing with sublethal doses (i.e., focalized infections) but suppressed when infections are well established or disseminated in the insect body. Phenoloxidase activation and the process of melanization generate highly cytotoxic quinones and other reactive compounds that are designed to control microbial infection [64]. Thus, a potential modulation of the proPO cascade that is dependent on infection level could represent a strategy to overcome the costly and potentially deleterious effect of the overactivation of the prophenoloxidase cascade to host tissues, at a time when other immune-related defenses are much more appropriate or effective. However, further studies evaluating the diverse set of genes and pathways associated with prophenoloxidase control are needed to discern their role in the progression of fungal infections. Fungal infection and dissemination in insects are also restricted by the action of immune signaling pathways, such as Toll, Imd, and Jak/STAT. Surprisingly, the Toll pathway, which is mainly responsible for the recognition and defense against fungi and Gram-positive bacteria in insects, was not induced by any of the two entomopathogenic fungi tested. This differs from its upregulation in domestic silkworm Bombyx mori infections with B. bassiana [65,66] or those observed in mosquitoes [19]. This difference might be due to either the infecting strain, the sublethal dose of infection, or the characteristic of T. ni at this larval stage. Further studies are needed to fully elucidate this pathway during fungal infections in this lepidopteran host.
Further analysis of other important immune pathway components suggests that the antifungal immune repertoire of T. ni larvae includes the participation of the Imd, JNK, and Jak/STAT pathways. However, this appears to be fungal-strain-specific, with significant induction following B. bassiana infections but less apparent following C. javanica infections. Similar infection phenotypes, with inductions of the Imd and JAK/STAT pathways, have been found in B. mori during infections with B. bassiana [65,67] but to our knowledge, our studies are the first to report their potential implications in the antifungal response of T. ni larvae.
The elicitation of immune signaling cascades during microbial infections results in the production of antimicrobial effectors aimed at halting the spread of the infection [16]. In particular, the production of antimicrobial peptides (AMPs) is recognized to be paramount in the insect response to microbial infections. In our study, exposure to both fungal pathogens resulted in the significant induction of the antimicrobial peptide Cecropin. In contrast, following the same trend of immune pathway induction, only infections with B. bassiana resulted in higher expression of the antimicrobial effectors Lysozyme and Gloverin. These antimicrobial effectors are also elicited in other lepidopteran hosts; for instance, during B. bassiana infection in B. mori [29,65], the cotton bollworm Helicoverpa armigera [68], and in the fall armyworm Spodoptera frugiperda in response to Metarhizium rileyi infections [69]. Furthermore, it appears that some AMPs are working in concert to limit fungal infection similar to cecA and gloverin during B. mori responses to B. bassiana [30]. Overall, infections with B. bassiana had a greater impact on T. ni larvae immune induction compared to C. javanica. This is likely attributed to the higher virulence of B. bassiana. Whether additional AMPs are implicated in the defense response to C. javanica remains to be explored. Finally, while our results indicate different gene expression dynamics of the canonical immune pathways, it does not consider potential post-translational modifications that might affect the action of these immune signaling pathways. Further research (i.e., protein analysis or functional assays) is needed to confirm the contribution of these immune-related genes.

5. Conclusions

In conclusion, our study assessed the immune response of T. ni larvae to sublethal infections of two important entomopathogenic fungi. Five-day-old larvae were able to mount a robust response to fungal inoculation by exhibiting increased phenoloxidase activity, as well as upregulating expression across several key immune signaling pathways. These results, including the diverging larval responses to different fungal strains, provide insight into the immune strategies employed by T. ni for protection against entomopathogenic fungi. Moreover, these results increase our understanding of insect–fungal entomopathogen interactions and could aid in the development of more effective microbial control strategies for this ubiquitous pest of agricultural importance.

Author Contributions

Conceptualization, J.L.R.; methodology, J.L.R.; Validation, A.M.R., K.R.D. and J.L.R.; formal analysis, K.R.D. and E.J.M.; investigation, A.M.R., K.R.D. and J.L.R.; resources, R.W.B. and J.L.R.; data curation, A.M.R., K.R.D. and J.L.R.; writing—original draft, K.R.D. and J.L.R.; writing—review and editing, all authors; visualization, K.R.D.; supervision, J.L.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported in part by the U.S. Department of Agriculture, Agricultural Research Service. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

Data Availability Statement

Data will be made available upon acceptance.

Acknowledgments

We sincerely thank Erica Goett, Molly Schumacher, Kylie Hampton, and Haley Gore for their technical assistance on this project.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hesketh, H.; Roy, H.; Eilenberg, J.; Pell, J.; Hails, R. Challenges in modelling complexity of fungal entomopathogens in semi-natural populations of insects. BioControl 2010, 55, 55–73. [Google Scholar] [CrossRef]
  2. Roy, H.E.; Steinkraus, D.; Eilenberg, J.; Hajek, A.; Pell, J.K. Bizarre interactions and endgames: Entomopathogenic fungi and their arthropod hosts. Annu. Rev. Entomol. 2006, 51, 331–357. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Bartlett, M.; Jaronski, S. Mass production of entomogenous fungi for biological control of insects. In Fungi in Biological Control Systems; Burge, M.N., Ed.; Manchester University Press: Manchester, UK, 1988; pp. 61–85. [Google Scholar]
  4. Jaronski, S. Mass production of entomopathogenic fungi—State of the art. In Mass Production of Beneficial Organisms: Invertebrates and Entomopathogens; Morales-Ramos, J.A., Guadalupe Rojas, M., Shapiro-Ilan, D.I., Eds.; Academic Press: San Diego, CA, USA, 2014; pp. 357–413. [Google Scholar] [CrossRef]
  5. Jaronski, S.T. Ecological factors in the inundative use of fungal entomopathogens. BioControl 2010, 55, 159–185. [Google Scholar] [CrossRef]
  6. Jackson, M.A.; Dunlap, C.A.; Jaronski, S.T. Ecological considerations in producing and formulating fungal entomopathogens for use in insect biocontrol. BioControl 2010, 55, 129–145. [Google Scholar] [CrossRef]
  7. Ortiz-Urquiza, A.; Luo, Z.; Keyhani, N.O. Improving mycoinsecticides for insect biological control. Appl. Microbiol. Biotechnol. 2015, 99, 1057–1068. [Google Scholar] [CrossRef]
  8. Wang, C.; Wang, S. Insect pathogenic fungi: Genomics, molecular interactions, and genetic improvements. Annu. Rev. Entomol. 2017, 62, 73–90. [Google Scholar] [CrossRef]
  9. Lovett, B.; St. Leger, R.J. Genetically engineering better fungal biopesticides. Pest Manag. Sci. 2018, 74, 781–789. [Google Scholar] [CrossRef]
  10. Zhao, H.; Lovett, B.; Fang, W. Chapter Five–Genetically engineering entomopathogenic fungi. In Advances in Genetics; Lovett, B., St. Leger, R.J., Eds.; Academic Press: San Diego, CA, USA, 2016; pp. 137–163. [Google Scholar] [CrossRef]
  11. Butt, T.; Goettel, M. Bioassays of entomogenous fungi. In Bioassays of Entomopathogenic Microbes and Nematodes; Navon, A., Ascher, K.R.S., Eds.; CABI Publishing: New York, NY, USA, 2000; pp. 141–195. [Google Scholar]
  12. Xu, L.; Zhang, Y.; Zhang, S.; Deng, J.; Lu, M.; Zhang, L.; Zhang, J. Comparative analysis of the immune system of an invasive bark beetle, Dendroctonus valens, infected by an entomopathogenic fungus. Dev. Comp. Immunol. 2018, 88, 65–69. [Google Scholar] [CrossRef] [PubMed]
  13. Wang, Y.; Yang, P.; Cui, F.; Kang, L. Altered immunity in crowded locust reduced fungal (Metarhizium anisopliae) pathogenesis. PLoS Pathog. 2013, 9, e1003102. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Tinsley, M.; Blanford, S.; Jiggins, F. Genetic variation in Drosophila melanogaster pathogen susceptibility. Parasitology 2006, 132, 767–773. [Google Scholar] [CrossRef] [Green Version]
  15. Pham, L.N.; Dionne, M.S.; Shirasu-Hiza, M.; Schneider, D.S. A specific primed immune response in Drosophila is dependent on phagocytes. PLoS Pathog. 2007, 3, e26. [Google Scholar] [CrossRef]
  16. Lu, H.-L.; Leger, R.S. Insect immunity to entomopathogenic fungi. Adv. Genet. 2016, 94, 251–285. [Google Scholar] [CrossRef] [PubMed]
  17. Qu, S.; Wang, S. Interaction of entomopathogenic fungi with the host immune system. Dev. Comp. Immunol. 2018, 83, 96–103. [Google Scholar] [CrossRef]
  18. Kanost, M.R.; Jiang, H.; Yu, X.Q. Innate immune responses of a lepidopteran insect, Manduca sexta. Immunol. Rev. 2004, 198, 97–105. [Google Scholar] [CrossRef] [PubMed]
  19. Ramirez, J.L.; Dunlap, C.A.; Muturi, E.J.; Barletta, A.B.; Rooney, A.P. Entomopathogenic fungal infection leads to temporospatial modulation of the mosquito immune system. PLoS Neglected Trop. Dis. 2018, 12, e0006433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Ramirez, J.L.; Muturi, E.J.; Dunlap, C.; Rooney, A.P. Strain-specific pathogenicity and subversion of phenoloxidase activity in the mosquito Aedes aegypti by members of the fungal entomopathogenic genus Isaria. Sci. Rep. 2018, 8, 9896. [Google Scholar] [CrossRef] [Green Version]
  21. Ramirez, J.L.; Muturi, E.J.; Barletta, A.B.; Rooney, A.P. The Aedes aegypti IMD pathway is a critical component of the mosquito antifungal immune response. Dev. Comp. Immunol. 2019, 95, 1–9. [Google Scholar] [CrossRef]
  22. Lemaitre, B.; Hoffmann, J. The host defense of Drosophila melanogaster. Annu. Rev. Immunol. 2007, 25, 697–743. [Google Scholar] [CrossRef] [Green Version]
  23. Valanne, S.; Wang, J.-H.; Rämet, M. The Drosophila toll signaling pathway. J. Immun. 2011, 186, 649–656. [Google Scholar] [CrossRef] [Green Version]
  24. Uvell, H.; Engström, Y. A multilayered defense against infection: Combinatorial control of insect immune genes. Trends Genet. 2007, 23, 342–349. [Google Scholar] [CrossRef]
  25. Lavine, M.; Chen, G.; Strand, M. Immune challenge differentially affects transcript abundance of three antimicrobial peptides in hemocytes from the moth Pseudoplusia includens. Insect Biochem. Mol. Biol. 2005, 35, 1335–1346. [Google Scholar] [CrossRef] [PubMed]
  26. Xu, X.-X.; Zhong, X.; Yi, H.-Y.; Yu, X.-Q. Manduca sexta gloverin binds microbial components and is active against bacteria and fungi. Dev. Comp. Immunol. 2012, 38, 275–284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Jiang, H.; Vilcinskas, A.; Kanost, M.R. Immunity in lepidopteran insects. In Invertebrate Immunity; Söderhäll, K., Ed.; Springer: New York, NY, USA, 2010; pp. 181–204. [Google Scholar] [CrossRef]
  28. Langen, G.; Imani, J.; Altincicek, B.; Kieseritzky, G.; Kogel, K.-H.; Vilcinskas, A. Transgenic expression of gallerimycin, a novel antifungal insect defensin from the greater wax moth Galleria mellonella, confers resistance to pathogenic fungi in tobacco. Biol. Chem. 2006, 387, 549–557. [Google Scholar] [CrossRef] [PubMed]
  29. Lu, D.; Geng, T.; Hou, C.; Huang, Y.; Qin, G.; Guo, X. Bombyx mori cecropin A has a high antifungal activity to entomopathogenic fungus Beauveria bassiana. Gene 2016, 583, 29–35. [Google Scholar] [CrossRef]
  30. Lu, D.; Geng, T.; Hou, C.; Qin, G.; Gao, K.; Guo, X. Expression profiling of Bombyx mori gloverin2 gene and its synergistic antifungal effect with cecropin A against Beauveria bassiana. Gene 2017, 600, 55–63. [Google Scholar] [CrossRef]
  31. Cerenius, L.; Lee, B.L.; Söderhäll, K. The proPO-system: Pros and cons for its role in invertebrate immunity. Trends Immunol. 2008, 29, 263–271. [Google Scholar] [CrossRef]
  32. Jones, D.; Jones, G.; Hammock, B. Growth parameters associated with endocrine events in larval Trichoplusia ni (Hübner) and timing of these events with developmental markers. J. Insect Physiol. 1981, 27, 779–788. [Google Scholar] [CrossRef]
  33. Herde, M.; Howe, G.A. Host plant-specific remodeling of midgut physiology in the generalist insect herbivore Trichoplusia ni. Insect Biochem. Mol. Biol. 2014, 50, 58–67. [Google Scholar] [CrossRef]
  34. Tak, J.-H.; Isman, M.B. Metabolism of citral, the major constituent of lemongrass oil, in the cabbage looper, Trichoplusia ni, and effects of enzyme inhibitors on toxicity and metabolism. Pestic. Biochem. Physiol. 2016, 133, 20–25. [Google Scholar] [CrossRef]
  35. Kolosov, D.; Donly, C.; MacMillan, H.; O’Donnell, M.J. Transcriptomic analysis of the Malpighian tubules of Trichoplusia ni: Clues to mechanisms for switching from ion secretion to ion reabsorption in the distal ileac plexus. J. Insect Physiol. 2019, 112, 73–89. [Google Scholar] [CrossRef]
  36. Jones, D.; Jones, G.; Rudnicka, M.; Click, A.; Reck-Malleczewen, V.; Iwaya, M. Pseudoparasitism of host Trichoplusia ni by Chelonus spp. as a new model system for parasite regulation of host physiology. J. Insect Physiol. 1986, 32, 315–328. [Google Scholar] [CrossRef]
  37. Freitak, D.; Wheat, C.W.; Heckel, D.G.; Vogel, H. Immune system responses and fitness costs associated with consumption of bacteria in larvae of Trichoplusia ni. BMC Biol. 2007, 5, 56. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Freitak, D.; Heckel, D.G.; Vogel, H. Bacterial feeding induces changes in immune-related gene expression and has trans-generational impacts in the cabbage looper (Trichoplusia ni). Front. Zool. 2009, 6, 7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Chen, E.; Kolosov, D.; O’Donnell, M.J.; Erlandson, M.A.; McNeil, J.N.; Donly, C. The effect of diet on midgut and resulting changes in infectiousness of AcMNPV baculovirus in the cabbage looper, Trichoplusia ni. Front. Physiol. 2018, 9, 1348. [Google Scholar] [CrossRef] [Green Version]
  40. Tamez-Guerra, P.; McGuire, M.R.; Behle, R.W.; Shasha, B.S.; Galn Wong, L.J. Assessment of microencapsulated formulations for improved residual activity of Bacillus thuringiensis. J. Econ. Entomol. 2000, 93, 219–225. [Google Scholar] [CrossRef]
  41. Tamez-Guerra, P.; Damas, G.; Iracheta, M.M.; Oppert, B.; Gomez-Flores, R.; Rodríguez-Padilla, C. Differences in susceptibility and physiological fitness of Mexican field Trichoplusia ni strains exposed to Bacillus thuringiensis. J. Econ. Entomol. 2006, 99, 937–945. [Google Scholar] [CrossRef]
  42. Behle, R.W.; Compton, D.L.; Laszlo, J.A.; Shapiro-Ilan, D.I. Evaluation of soyscreen in an oil-based formulation for UV protection of Beauveria bassiana conidia. J. Econ. Entomol. 2009, 102, 1759–1766. [Google Scholar] [CrossRef]
  43. Hay, W.T.; Behle, R.W.; Berhow, M.A.; Miller, A.C.; Selling, G.W. Biopesticide synergy when combining plant flavonoids and entomopathogenic baculovirus. Sci. Rep. 2020, 10, 6806. [Google Scholar] [CrossRef] [Green Version]
  44. Sayed, A.M.M.; Behle, R.W. Evaluating a dual microbial agent biopesticide with Bacillus thuringiensis var. kurstaki and Beauveria bassiana blastospores. Biocontrol Sci. Technol. 2017, 27, 461–474. [Google Scholar] [CrossRef]
  45. Ericsson, J.D.; Janmaat, A.F.; Lowenberger, C.; Myers, J.H. Is decreased generalized immunity a cost of Bt resistance in cabbage loopers Trichoplusia ni? J. Invertebr. Pathol. 2009, 100, 61–67. [Google Scholar] [CrossRef]
  46. Janmaat, A.F.; Myers, J. Rapid evolution and the cost of resistance to Bacillus thuringiensis in greenhouse populations of cabbage loopers, Trichoplusia ni. Proc. R. Soc. B 2003, 270, 2263–2270. [Google Scholar] [CrossRef]
  47. Mascarin, G.M.; Jaronski, S.T. The production and uses of Beauveria bassiana as a microbial insecticide. World J. Microbiol. Biotechnol. 2016, 32, 177. [Google Scholar] [CrossRef] [PubMed]
  48. Sadd, B.; Holman, L.; Armitage, H.; Lock, F.; Marland, R.; Siva-Jothy, M.T. Modulation of sexual signalling by immune challenged male mealworm beetles (Tenebrio molitor, L.): Evidence for terminal investment and dishonesty. J. Evol. Biol. 2006, 19, 321–325. [Google Scholar] [CrossRef]
  49. Koressaar, T.; Remm, M. Enhancements and modifications of primer design program Primer3. Bioinformatics 2007, 23, 1289–1291. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Untergasser, A.; Cutcutache, I.; Koressaar, T.; Ye, J.; Faircloth, B.C.; Remm, M.; Rozen, S.G. Primer3—New capabilities and interfaces. Nucleic Acids Res. 2012, 40, e115. [Google Scholar] [CrossRef] [Green Version]
  51. Chen, W.; Yang, X.; Tetreau, G.; Song, X.; Coutu, C.; Hegedus, D.; Blissard, G.; Fei, Z.; Wang, P. A high-quality chromosome-level genome assembly of a generalist herbivore, Trichoplusia ni. Mol. Ecol. Resour. 2019, 19, 485–496. [Google Scholar] [CrossRef] [PubMed]
  52. Shrestha, A.; Bao, K.; Chen, W.; Wang, P.; Fei, Z.; Blissard, G.W. Transcriptional responses of the Trichoplusia ni midgut to oral infection by the baculovirus Autographa californica Multiple Nucleopolyhedrovirus. J. Virol. 2019, 93, e00353-19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Bell, A.S.; Blanford, S.; Jenkins, N.; Thomas, M.B.; Read, A.F. Real-time quantitative PCR for analysis of candidate fungal biopesticides against malaria: Technique validation and first applications. J. Invertebr. Pathol. 2009, 100, 160–168. [Google Scholar] [CrossRef] [Green Version]
  54. Silver, N.; Best, S.; Jiang, J.; Thein, S.L. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol. Biol. 2006, 7, 33. [Google Scholar] [CrossRef] [Green Version]
  55. Xie, F.; Xiao, P.; Chen, D.; Xu, L.; Zhang, B. miRDeepFinder: A miRNA analysis tool for deep sequencing of plant small RNAs. Plant Mol. Biol. 2012, 80, 75–84. [Google Scholar] [CrossRef]
  56. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  57. Motulsky, H.J.; Brown, R.E. Detecting outliers when fitting data with nonlinear regression–a new method based on robust nonlinear regression and the false discovery rate. BMC Bioinform. 2006, 7, 123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Wraight, S.P.; Ramos, M.E.; Avery, P.B.; Jaronski, S.T.; Vandenberg, J.D. Comparative virulence of Beauveria bassiana isolates against lepidopteran pests of vegetable crops. J. Invertebr. Pathol. 2010, 103, 186–199. [Google Scholar] [CrossRef] [PubMed]
  59. Ignoffo, C.; Garcia, C.; Kroha, M.; Couch, T. Use of larvae of Trichoplusia ni to bioassay conidia of Beauveria bassiana. J. Econ. Entomol. 1982, 75, 275–276. [Google Scholar] [CrossRef]
  60. Chu, Y.; Liu, Y.; Shen, D.; Hong, F.; Wang, G.; An, C. Serine proteases SP1 and SP13 mediate the melanization response of Asian corn borer, Ostrinia furnacalis, against entomopathogenic fungus Beauveria bassiana. J. Invertebr. Pathol. 2015, 128, 64–72. [Google Scholar] [CrossRef]
  61. Boguś, M.I.; Kędra, E.; Bania, J.; Szczepanik, M.; Czygier, M.; Jabłoński, P.; Pasztaleniec, A.; Samborski, J.; Mazgajska, J.; Polanowski, A. Different defense strategies of Dendrolimus pini, Galleria mellonella, and Calliphora vicina against fungal infection. J. Invertebr. Pathol. 2007, 53, 909–922. [Google Scholar] [CrossRef]
  62. Stączek, S.; Zdybicka-Barabas, A.; Pleszczyńska, M.; Wiater, A.; Cytryńska, M. Aspergillus niger α-1,3-glucan acts as a virulence factor by inhibiting the insect phenoloxidase system. J. Invertebr. Pathol. 2020, 171, 107341. [Google Scholar] [CrossRef]
  63. Vertyporokh, L.; Wojda, I. Immune response of Galleria mellonella after injection with non-lethal and lethal dosages of Candida albicans. J. Invertebr. Pathol. 2020, 170, 107327. [Google Scholar] [CrossRef]
  64. Zdybicka-Barabas, A.; Mak, P.; Jakubowicz, T.; Cytryńska, M. Lysozyme and defense peptides as suppressors of phenoloxidase activity in Galleria mellonella. Arch. Insect Biochem. Physiol. 2014, 87, 1–12. [Google Scholar] [CrossRef]
  65. Geng, T.; Lu, F.; Wu, H.; Lou, D.; Tu, N.; Zhu, F.; Wang, S. Target antifungal peptides of immune signalling pathways in silkworm, Bombyx mori, against Beauveria bassiana. Insect Mol. Biol. 2021, 30, 102–112. [Google Scholar] [CrossRef]
  66. Liu, W.; Liu, J.; Lu, Y.; Gong, Y.; Zhu, M.; Chen, F.; Liang, Z.; Zhu, L.; Kuang, S.; Hu, X.; et al. Immune signaling pathways activated in response to different pathogenic micro-organisms in Bombyx mori. Mol. Immunol. 2015, 65, 391–397. [Google Scholar] [CrossRef] [PubMed]
  67. Geng, T.; Lv, D.-D.; Huang, Y.-X.; Hou, C.-X.; Qin, G.-X.; Guo, X.-J. JAK/STAT signaling pathway-mediated immune response in silkworm (Bombyx mori) challenged by Beauveria bassiana. Gene 2016, 595, 69–76. [Google Scholar] [CrossRef] [PubMed]
  68. Xiong, G.-H.; Xing, L.-S.; Lin, Z.; Saha, T.T.; Wang, C.; Jiang, H.; Zou, Z. High throughput profiling of the cotton bollworm Helicoverpa armigera immunotranscriptome during the fungal and bacterial infections. BMC Genom. 2015, 16, 321. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Wang, J.-L.; Yang, K.-H.; Wang, S.-S.; Li, X.-L.; Liu, J.; Yu, Y.-X.; Liu, X.-S. Infection of the entomopathogenic fungus Metarhizium rileyi suppresses cellular immunity and activates humoral antibacterial immunity of the host Spodoptera frugiperda. Pest Manag. Sci. 2022, 78, 2828–2837. [Google Scholar] [CrossRef]
Insects 14 00667 g001 550
Figure 1. Fungal and bacterial loads via relative quantification of fungal 18s rRNA and bacterial 16s rRNA, respectively, in the whole bodies of T. ni larvae infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva, with horizontal lines representing the median (fungal load) or mean (bacterial load) expression with interquartile range (fungal load) or 95% confidence intervals (bacterial load). * p < 0.05; ** p < 0.01; ns = not significant.
Figure 1. Fungal and bacterial loads via relative quantification of fungal 18s rRNA and bacterial 16s rRNA, respectively, in the whole bodies of T. ni larvae infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva, with horizontal lines representing the median (fungal load) or mean (bacterial load) expression with interquartile range (fungal load) or 95% confidence intervals (bacterial load). * p < 0.05; ** p < 0.01; ns = not significant.
Insects 14 00667 g001
Insects 14 00667 g002 550
Figure 2. Gene expression profiles of (A) phenoloxidase activity (sample sizes: control = 36, B. bassiana = 38, C. javanica = 36) and (B) prophenoloxidase (sample size = 13 larvae/treatment) in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection. Each dot represents a single larva, with horizontal lines representing mean with 95% confidence intervals. ** p < 0.01; **** p < 0.0001; ns = not significant.
Figure 2. Gene expression profiles of (A) phenoloxidase activity (sample sizes: control = 36, B. bassiana = 38, C. javanica = 36) and (B) prophenoloxidase (sample size = 13 larvae/treatment) in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection. Each dot represents a single larva, with horizontal lines representing mean with 95% confidence intervals. ** p < 0.01; **** p < 0.0001; ns = not significant.
Insects 14 00667 g002
Insects 14 00667 g003 550
Figure 3. Gene expression profiles of (A) Toll, (B) Imd, and (C) JNK immune signaling pathways in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva, with horizontal lines representing mean expression with 95% confidence intervals. * p < 0.05; ns = not significant.
Figure 3. Gene expression profiles of (A) Toll, (B) Imd, and (C) JNK immune signaling pathways in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva, with horizontal lines representing mean expression with 95% confidence intervals. * p < 0.05; ns = not significant.
Insects 14 00667 g003
Insects 14 00667 g004 550
Figure 4. Gene expression profiles of genes involved in (A) Jak/STAT immune signaling pathway, (B) stress response/detoxification, and (C) antimicrobial effectors in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva with horizontal lines representing mean expression with 95% confidence intervals (STATB represents median and interquartile range). * p < 0.05; ** p < 0.01; **** p < 0.0001; ns = not significant.
Figure 4. Gene expression profiles of genes involved in (A) Jak/STAT immune signaling pathway, (B) stress response/detoxification, and (C) antimicrobial effectors in T. ni infected with either B. bassiana or C. javanica, evaluated at 2 days post-infection (sample size = 13 larvae/treatment). Each dot represents a single larva with horizontal lines representing mean expression with 95% confidence intervals (STATB represents median and interquartile range). * p < 0.05; ** p < 0.01; **** p < 0.0001; ns = not significant.
Insects 14 00667 g004
Table
Table 1. Reverse Transcriptase Quantitative PCR (RT-qPCR) primers used to quantify gene expression in Trichoplusia ni larvae in this study.
Table 1. Reverse Transcriptase Quantitative PCR (RT-qPCR) primers used to quantify gene expression in Trichoplusia ni larvae in this study.
TargetGene IDPrimer SequenceReference
TolloXP_026733502.1ACTCGACTGCAAAGCGAAATPresent study
TAAACCGTGTGGGGAACATT
Toll 7XP_026744547.1ATCTCAAAACAGGGTCGCGT
AACACAGGTGATCGCTCAGG
NF-kappa-B inhibitor cactus-likeXP_026732956.1GAGCTTCTTGGTGACCTGCT
AGTGCTTACAAGCGCTGCTC
Dorsal/DifXP_026732895.1CCGCCTACAGGTTCCCTAAC
CCGGCGAGTACATCCTTTCA
RelishXP_026737640.1CTCCCTTGATCAGGCACAAT
CCCTGAGGAACACCCTCATA
IKK-βXP_026741558.1TGTTACAGACCTGCCGGAAC
CTTTGAGGCCCGAACAGGAT
STAT5BXP_026748140.1GTGGACAATCACCACGACAG
CTGTTCCAGTCGCAGTTCAA
JUNXP_026743727.1CGTGCTCCTTTAGCTTGACC
CTCCAAGCTGGAAGACAAGG
JNKXP_026741510.1AACGTGTGAGGGGTTCGTAG
TGTTACCGCCCAGCTTTATC
CatalaseXP_026730481.1GACCTCAAAGATTCTCCTGGCT
AGAGCTGGTCCATTCTTGCC
CecropinXP_026734190.1TAGCCAAAATTGGAGCGAAG
AACCAGCTAGAGCGCCAATA
DefensinEU016385.1CAATAAGCAGTGAAGCCTTGG[37]
GCATATGCCGTAGTTGTAGCC
LysozymeEU016396.1ATGCGCCAAGAAGATCTACAA
GTTTAGCATTTGCTGATGTCG
GallerimycinEU016388.1TGCATTGCCAGTTGTAGACAG
ATAGCCTCAAGCTCATCACCA
GloverinEU016389.1CTTGATGTCCACAAGCAGGTT
CAAAGGTCTTGTCCAGATTGC
ProPO activating enzyme (PPOAE)EU016397.1AAGTCGGAAGAAGAGGTCGAG
CTGGCGTGTAACATGATCCTT
ProPO subunit 1 (PPO1)XP_026730296.1GCTCCATGTATGCCAAGTGTTPresent study
TTGGCCTTTCCATGAATGAT
ProPO subunit 2 (PPO2)XP_026731374.1TCGTGGCGAACTTTTCTTCT
AGACTGTCCAGCTTCGGAAA
Ribosomal protein S18EU016398.1TGTCCTATTTGTCGGGATGAG[37]
TGGTCCCATGCTCTTTCTATG
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Duffield, K.R.; Rosales, A.M.; Muturi, E.J.; Behle, R.W.; Ramirez, J.L. Increased Phenoloxidase Activity Constitutes the Main Defense Strategy of Trichoplusia ni Larvae against Fungal Entomopathogenic Infections. Insects 2023, 14, 667. https://doi.org/10.3390/insects14080667

AMA Style

Duffield KR, Rosales AM, Muturi EJ, Behle RW, Ramirez JL. Increased Phenoloxidase Activity Constitutes the Main Defense Strategy of Trichoplusia ni Larvae against Fungal Entomopathogenic Infections. Insects. 2023; 14(8):667. https://doi.org/10.3390/insects14080667

Chicago/Turabian Style

Duffield, Kristin R., Alayna M. Rosales, Ephantus J. Muturi, Robert W. Behle, and José L. Ramirez. 2023. "Increased Phenoloxidase Activity Constitutes the Main Defense Strategy of Trichoplusia ni Larvae against Fungal Entomopathogenic Infections" Insects 14, no. 8: 667. https://doi.org/10.3390/insects14080667

APA Style

Duffield, K. R., Rosales, A. M., Muturi, E. J., Behle, R. W., & Ramirez, J. L. (2023). Increased Phenoloxidase Activity Constitutes the Main Defense Strategy of Trichoplusia ni Larvae against Fungal Entomopathogenic Infections. Insects, 14(8), 667. https://doi.org/10.3390/insects14080667

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop