Front. Microbiol. Frontiers in Microbiology Front. Microbiol. 1664-302X Frontiers Media S.A. 10.3389/fmicb.2017.01421 Microbiology Original Research The Entomopathogenic Fungi Isaria fumosorosea Plays a Vital Role in Suppressing the Immune System of Plutella xylostella: RNA-Seq and DGE Analysis of Immunity-Related Genes Xu Jin 1 † Xu Xiaoxia 1 † Shakeel Muhammad 1 * Li Shuzhong 1 Wang Shuang 1 Zhou Xianqiang 2 Yu Jialin 2 Xu Xiaojing 2 Yu Xiaoqiang 3 Jin Fengliang 1 * 1Laboratory of Bio-Pesticide and Application of Guangdong Province, College of Agriculture, South China Agricultural University Guangzhou, China 2Beijing Genomic Institute Shenzhen, China 3School of Biological Sciences, University of Missouri-Kansas Kansas City, MO, United States

Edited by: Jason Paul Gigley, University of Wyoming, United States

Reviewed by: Maryam Dadar, Razi Vaccine and Serum Research Institute, Iran; Erjun Ling, Plant Physiology and Ecology, SIBS, CAS, China

*Correspondence: Muhammad Shakeel faizaneabiwaqas@scau.edu.cn,

Fengliang Jin jflbang@scau.edu.cn

This article was submitted to Microbial Immunology, a section of the journal Frontiers in Microbiology

†These authors have contributed equally to this work.

 28 07 2017 2017 8 1421 22 05 2017 13 07 2017 Copyright © 2017 Xu, Xu, Shakeel, Li, Wang, Zhou, Yu, Xu, Yu and Jin. 2017 Xu, Xu, Shakeel, Li, Wang, Zhou, Yu, Xu, Yu and Jin

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Most, if not all, entomopathogenic fungi have been used as alternative control agents to decrease the insect resistance and harmful effects of the insecticides on the environment. Among them, Isaria fumosorosea has also shown great potential to control different insect pests. In the present study, we explored the immune response of P. xylostella to the infection of I. fumosorosea at different time points by using RNA-Sequencing and differential gene expression technology at the genomic level. To gain insight into the host-pathogen interaction at the genomic level, five libraries of P. xylostella larvae at 12, 18, 24, and 36 h post-infection and a control were constructed. In total, 161 immunity-related genes were identified and grouped into four categories; immune recognition families, toll and Imd pathway, melanization, and antimicrobial peptides (AMPs). The results of differentially expressed immunity-related genes depicted that 15, 13, 53, and 14 up-regulated and 38, 51, 56, and 49 were down-regulated in P. xylostella at 12, 18, 24, and 36 h post-treatment, respectively. RNA-Seq results of immunity-related genes revealed that the expression of AMPs was reduced after treatment with I. fumosorosea. To validate RNA-Seq results by RT-qPCR, 22 immunity-related genes were randomly selected. In conclusion, our results demonstrate that I. fumosorosea has the potential to suppress the immune response of P. xylostella and can become a potential biopesticide for controlling P. xylostella.

 Plutella xylostella RNA-Seq Isaria fumosorosea immune genes DGE 31371989 31572069 National Natural Science Foundation of China10.13039/501100001809 Introduction

Insects are surrounded by an environment rich with harmful microorganisms and recurring infections are common in the natural environment. In order to combat these potentially infectious pathogens, insects have evolved various defense systems, including the potent immune system. Unlike mammals, insects solely rely on innate immune responses for host defense. The innate immune responses are usually comprised of cellular and humoral defense responses. The former is best demonstrated by the action of hemocytes in the phagocytosis (Kanost et al., 2004) whereas the hallmark of latter is the synthesis of antimicrobial peptides (AMPs) (Hoffmann and Reichhart, 2002). Upon microbial infection, cellular, and humoral responses are activated by insects, to clear the infection, through different steps (Söderhäll and Cerenius, 1998). The invading pathogen is recognized via pattern recognition receptors (PRRs) (Hultmark, 2003) leading to the amplification of signal of infection by serine proteases following the activation of signaling pathways (Jiang and Kanost, 2000; Osta et al., 2004). Finally, the effector factors are induced in the specific tissues to combat the pathogens.

To counter the defense system of the host, insect pathogenic fungi have also developed their mechanisms. The pathogens use a set of enzymes to breach the cuticle (Butt, 2002) and also release secondary metabolites, to suppress the immune system of the host, during colonization (Vilcinskas et al., 1997; Vey et al., 2002). Among these entomopathogenic fungi, on one hand, Metarhizium anisopliae has developed a new technique to evade the immune system of host via masking the cell wall during hemocoel colonization (Wang and Leger, 2006), and on the other hand, Isaria fumosorosea releases chitinase, chitosanase, lipase, to physically penetrate the host and suppress its regulatory system, and a beauvericin compound to paralyze the host (Hajek and St. Leger, 1994; Ali et al., 2010).

The diamondback moth (DBM), Plutella xylostella (L.) (Lepidoptera: Plutellidae), is one of the devastating pests of brassicaceous crops and costs approximately US$4-5 billion per year worldwide (Zalucki et al., 2012). P. xylostella is commonly known to rapidly evolve resistance against almost all types of insecticides including products of Bacillus thuringiensis (Shakeel et al., 2017). Consequently, entomopathogenic fungi have received an increased attention as an environmentally friendly alternative control measure to insecticides for controlling P. xylostella. Several strains of fungi have been isolated and used to control various insect pests including P. xylostella (Altre et al., 1999; Leemon and Jonsson, 2008; Bukhari et al., 2011). Of these entomopathogenic fungi, I. fumosorosea is considered as one of the promising species of fungi to be used as biological control of insect pests and various mycopesticide based on I. fumosorosea have been developed worldwide (Zimmermann, 2008). Isaria fumosorosea, a well-known entomopathogenic fungi, is distributed worldwide. It was previously known as Paecilomyces fumosoroseus, however, now it has been transferred to Isaria genus (Zimmermann, 2008). Due to wide host range, it has become a promising biological control agent and its potential as a biological control agent, other than immunity, has been tested to control various insect pests, including Diaphorina citri (Avery et al., 2011), Bemisia tabaci (Huang et al., 2010), Trialeurodes vaporariorum (Gökçe and Er, 2005), and P. xylostella (Huang et al., 2010).

Previously, most of the reports on insect immunity preferred model insects, including Drosophila melanogaster (Wraight et al., 2010), Manduca sexta (Kanost et al., 2004), and Tenebrio molitor (Kim et al., 2008) against insect pathogenic fungi such as M. acridium and Beauveria bassiana (Xiong et al., 2015; Zhang et al., 2015). It is only recently that P. xylostella immunity has received the attention of few researchers, thanks to the availability of the genome sequence of P. xylostella (You et al., 2013). Although, a recent report on the immune response of P. xylostella to B. bassiana improved our information of insect-pathogen interaction (Chu et al., 2016). However, the changes that occur in response to I. fumosorosea in P. xylostella are largely unclear, restricting the development of fungal species other than M. anisopliae and B. bassiana to be adopted as a biological control agent in P. xylostella and other lepidopteran pests' control.

To gain deep insight into the immunogenetics of P. xylostella, the present study conducted a genome-wide profiling analysis of I. fumosorosea challenged P. xylostella larvae at 12, 18, 24, and 36 h post-infection using RNA-Seq and digital gene expression (DGE). Additionally, a global survey of the activities of anti-fungal immune defense genes in P. xylostella may also contribute to the in-depth analysis of candidate genes in P. xylostella immunity.

 Materials and methods Insect stock

The population of susceptible P. xylostella was kindly provided by Institute of Plant Protection, Guangdong Academy of Agricultural Sciences, China and was maintained in the Engineering Research Centre of Biological Control Ministry of Education, South China Agricultural University, Guangzhou, Guangdong province, P. R. China for five years without exposure to pesticides. Larvae were maintained at 25 ± 1°C with a light: dark cycle of 16:8 h and 60–70% relative humidity.

 Fungus culture, conidia suspension preparation, and samples collection

The I.fumosorosea IfB01 strain (China Center for Type Culture Collection access number: CCTCC M 2012400) was cultured on a potato dextrose agar (PDA) plate at 26°C. The conidia were collected from 10 days old culture and suspended with 0.05% Tween-80 into standardized 1 × 108 spores/mL (Huang et al., 2010). Healthy P. xylostella larvae (third-instar) were selected and separated into two groups. One group (treatment) was treated with the 1 × 107 spores/ mL suspension, whereas the other group (control) was treated with sterile deionized water containing 0.05% Tween-80. The samples of 50 surviving larvae were collected from the treatment group and the control group at 12, 18, 24, and 36 h, respectively, forming three pairs of hour post-treatment infection and hours post treatment control. Different time-points of sampling were selected to observe infection dynamics (Abkallo et al., 2015) and dynamical changes (Bar-Joseph et al., 2012) of differentially expressed genes (DEGs) in response to Isaria fumosorosea in Plutella xylostella, as the gene expression profiling of different time points can provide DEGs dynamical behavior information.

 Preparation of cDNA library and illumina sequencing

A total of five DGE libraries (12, 18, 24, 36 h, and control) were produced by the Illumina Gene Expression Sample Prep Kit (Illumina, San Diego, CA). Total RNA (10 μg) was isolated from each treatment and control for the isolation of poly (A)+ mRNA using oligo (dT) magnetic beads. cDNAs (First- and second-strand) were prepared using random hexamers, RNase H, and DNA polymerase I. Magnetic beads were used to purify the double strand cDNA and finally, ligation of fragments was carried out with sequencing adaptors. To quantify and qualify the libraries of samples, Agilent 2100 Bioanalyzer and ABI Step One Plus Real-Time PCR System were employed and then sequencing was done on the Illumina HiSeq™ 2000 system (Illumina, USA). Illumina sequencing was carried out at the Beijing Genomics Institute (BGI-Shenzhen, China).

 Mapping and functional analysis of differentially expressed genes

The process of filtration was performed in such a way that raw reads with adopters and unknown bases (more than 10%) were removed. After filtering, the remaining clean reads were mapped to reference gene using Bowtie (Langmead et al., 2009) and HISAT (Kim et al., 2015) was employed to map the reference genome. Finally, normalization of all data was done as fragments per kilobase of transcript per million fragments mapped (FPKM). The analysis of differential expression was employed by a rigorous algorithm. The false discovery rate (FDR) methodology was adopted in multiple tests (Kim and van de Wiel, 2008) for determination of threshold of P-value. Genes with significant differential expression were searched out according to a standard threshold having an FDR value of < 0.001 and the absolute value of log2 ratio ≥ 1. The genome database of P. xylostella was used as the background to determine significantly enriched GO terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched within the DEG dataset using hypergeometric test and a corrected P-value (≤0.05) as a threshold.

 Validation of DEGs libraries by RT-qPCR

In order to validate mRNA expression levels exhibited by RNA-Seq results, Real-time quantitative PCR (RT-qPCR) was performed with 22 immunity-related DEGs chosen from the comparison of control vs. treatments. Total RNA isolation method was same as described earlier. In total, 1 μg of total RNA was treated with DNaseI (Fermentas, Glen Burnie, MD, USA) according to the instructions of the manufacturer and then cDNA was prepared using M-MLV reverse transcriptase (Promega, USA). The RT-qPCR was performed on a Bio-Rad iQ2 optical system (Bi-Rad) using SsoFast EvaGreen Supermix (Bio-Rad, Hercules, CA, USA) according to guidelines provided by the manufacturer. To confirm the PCR products purity, the amplification cycling parameters were set as; 95°C for 30 s, 40 cycles of 95°C for 5 s, and 55°C for 10 s with a dissociation curve generated from 65 to 95°C (Shakeel et al., 2015). For normalization, ribosomal protein S13 (RPS13) was used as an internal control (Fu et al., 2013) and the relative expression of genes was calculated using the 2−ΔΔCT method (Livak and Schmittgen, 2001). The primers used for RT-qPCR are listed in Table 1.

Primers used for RT-qPCR in the present study.

Gene name Gene ID Direction Sequence (5′–3′)
Px_Tryp_SPN12 105393249 Forward GCAGACCTTGGTTATATC
Reverse GATGAAGCTCTTGTACTC
Px_ChymTryp_SP6 105397690 Forward GAAGTGTTCTGATTGGAG
Reverse TAGATACGAGCGTTGATC
Px_PPO1 105393828 Forward GATCAAGCCTAAGGTATG
Reverse GTCACCATCTTCTGTATC
Px_Catalase1 105398438 Forward CCGTTTTCTACACTAAGG
Reverse GGTACTTCTTGTAAGGAG
Px_Lectin2 105395555 Forward GAGACAGTTTAGTTCCCT
Reverse GAAGTAGCCCTTGTTATC
Px_SP20 105380853 Forward GCTATGTTGTGCATACAG
Reverse CATATTCTGCGAGTAGTC
Px_PGRP1 105387866 Forward GTATAATTTCTGCGTGGG
Reverse CTCCAATCTCCAATAAGAC
Px_Lectin6 105392913 Forward GATCAAGAGGATGGTTAC
Reverse CTTCAGTTCCCTTCTATC
Px_Moricin1 105392531 Forward ATGAGATTCCTCCACTTG
Reverse CCTTCCGAATAACTCTTC
Px_Serpin1 105396587 Forward GACTCGGAGGATATTTAC
Reverse CCAGGTCTAAGATGTATTG
Px_βGBP1 105380182 Forward GGAAAGGATACCTGAAAG
Reverse GAAGTCGTCATAGAAGAC
Px_Tryp_SP1 105381636 Forward CCAGGAGAAGGATATTCT
Reverse CATGATAGAGTCATCCTC
Px_βGBP3 105391537 Forward CAACTACTACCATGAAGG
Reverse GCTCTAGGTTTATCTCAG
Px_Cecropin1 105394859 Forward CAGGTGGAATCCGTTCAA
Reverse GAAGTGGCTTGTCCTATGA
Px_Moricin3 105392532 Forward GATTCTTCCACTTGCTGATG
Reverse CCTTCCGTATAACTCTTCCG
Px_Lectin4 105392416 Forward CAGGATAAGGTGAAGTACATCT
Reverse CCGTCGTTGTAGAAGTTGT
Px_Hemolin1 105394779 Forward GATTGGTGGAGCAGTATGT
Reverse TGGTGTTCTTGATGATGAGT
Px_Peroxidase2 105388497 Forward CCACCGAGCAACAAGAAT
Reverse GAACCATACCGTCATCAGAT
Px_Gloverin2 105389803 Forward GCCACTCAAGGACATCTT
Reverse CTCACTGTTCTTGCCAATC
Px_SCR6 105393261 Forward GAAGACGGCATCCAACTG
Reverse CATAGAACAAGCGGTGACA
Px_SCR7 105394486 Forward GAAGACGGCATCCAACTG
Reverse TAGAGCAAGCGGTGACAT
Px_SP4 105380869 Forward CTCTGGTGCTATTGCTCTT
Reverse GATGGTAGATGTGGTGATGA
RPS13 Reference gene Forward TCAGGCTTATTCTCGTCG
Reverse GCTGTGCTGGATTCGTAC
Results and discussion Features of the sequenced cDNA libraries

To identify genes involved in P. xylostella immunity in response to I. fumosorosea, five cDNA libraries were constructed from 3rd larval instar of P. xylostella at 12, 18, 24, 36 h after fungal treatment and control. A total of 11,652,857, 11,819,310, 12,051,947, 11,744,46, and 11,683,647 reads were generated from these five libraries (12, 18, 24, 36 h, and control respectively), from which 70.01, 73.55, 73.23, 70.11, and 71.94% reads could be successfully mapped to the reference genome (Table 2).

DGE sequencing statistics.

Sample Clean reads Total mapped of clean data (%)
12 h 11,652,857 70.01
18 h 11,819,310 73.55
24 h 12,051,947 73.23
36 h 11,744,46 70.11
Control 11,683,647 71.94
Dynamics of differentially expressed immunity-related genes in response to <italic>I. fumosorosea</italic>

To study the gene expression of P. xylostella larvae infected with I. fumosorosea, the pairwise comparison was carried out between libraries to determine the DEGs. The analysis of five libraries was carried out by determining the number of fragments per kb per million (FPKM) of clean reads. Relative to control, genes with (FDR) ≤ 0.001 and |log2Ratio| ≥ 1 were recognized as differentially expressed. Our results exhibited that, compared to the control, there were 53 (15 up-regulated and 38 down-regulated), 64 (13 up- and 51 down-regulated), 109 (53 up-regulated and 56 down-regulated), and 63 (14 up- and 49 down-regulated) immune-related genes that were significantly changed in P. xylostella after 12, 18, 24, and 36 h, respectively (Figure 1). A Venn diagram analysis showed that only 11 immunity-related DEGs were commonly expressed among all the treatments, whereas 7, 13, 45, and 12 immunity-related DEGs were specifically expressed in 12, 18, 24, and 36 h, respectively (Figure 2).

Screening of immunity-related DEGs in response to I. fumosorosea at 12, 18, 24, and 36 h post-infection.

A Venn diagram of differentially expressed immunity-related genes in P. xylostella at 12, 18, 24, and 36 h post-infection. The numbers in each circle show differentially expressed genes in each comparison treatment and the overlapping regions display genes that are commonly expressed among the comparison treatments.

 GO and KEGG classification and enrichment analysis of immunity-related genes in response to <italic>I. fumosorosea</italic>

Following GO annotation, the immunity-related genes were classified into 26 different groups belonging to biological process, cellular component, and molecular function categories (Figure 3). In the biological process category, the two most enriched groups were the response to stimulus and biological regulation, whereas membrane and regulation of biological process were the top two enriched groups in the cellular component. The number of genes involved in catalytic activity and binding were the dominant groups in the category of molecular function (Figure 3). The KEGG classification system categorized immunity-related genes into 21 different groups (Figure 4). The top five enriched groups among KEGG categories included infectious diseases (viral), signaling molecules and interaction, digestive system, infectious diseases (parasitic), and signal transduction (Figure 4).

Summary of Gene ontology annotation. Functional classification of immunity- related DEGs at 12, 18, 24, and 36 h post-infection in P. xylostella using gene ontology terms.

KEGG pathway annotation classification of immunity-related genes in P. xylostella infected with I. fumosorosea at 12, 18, 24, and 36 h. The abscissa is the KEGG classification, and the ordinate left is the gene number.

 Verification of DEG results by RT-qPCR

To validate DEG results, 13 randomly selected immunity-related DEGs were analyzed by RT-qPCR. The results exhibited that the trend of expression level for all the selected genes was in consistence to that of RNA-Seq (Figure 5).

Validation of differential expression ratio (log2) achieved by RT-qPCR and RNA-Seq for immunity-related genes. ChymTryp_SP6, Chymotrypsin like serine protease (Px_105397690); Moricin1, Moricin (Px_105392531); PPO1, prophenoloxidase (Px_105393828); SCR6, Scavenger Receptor (Px_105393261); SCR7, Scavenger Receptor (Px_105394486); Serpin1, Serpin (Px_105396587); Tryp_SPN12, Trypsin-like Serine Protease (Px_105393249); βGBP1, β-1,3-Glucan Binding Protein (Px_105380182); Catalase1, Catalase (Px_105398438); Cecropin1, Cecropin (Px_105394859); Gloverin2, Gloverin (Px_105389803); Hemolin1, Hemolin (Px_105394779); Lectin2, Lectin (Px_105395555); Lectin4, Lectin (Px_105392416); Lectin6, Lectin (Px_105392913); Moricin3, Moricin (Px_105392532); Peroxidase2, Peroxidase (Px_105388497); PGRP1, Peptidoglycan Recognition Protein (Px_105387866); SP20, Serine Protease (Px_105380853); SP4, Serine Protease (Px_105380869); βGBP3, β-1,3-Glucan Binding Protein (Px_105391537); Tryp_SP1, Trypsin-like Serine Protease (Px_105381636).

 Identification of immunity-related genes

To identify immunity-related genes in response to I. fumosorosea, we searched out the genome of P. xylostella and combined BLAST search and GO annotation results. A number of genes having fold change less than one and those annotated as hypothetical or unknown proteins were not selected. Finally, a good number (161) of immunity-related genes were identified and classified as immune recognition families, toll and Imd signaling pathways, melanization, AMPs, and others (Table 3).

Summary of immunity-related genes identified in Plutella xylostella genome.

Gene name Gene ID Accession no. Gene length Protein length E-value Nr identity Log2
12 h 18 h 24 h 36 h
RECOGNITION
Peptidoglycan recognition protein
Px_PGRP1 105387866 AFV15800.1 815 206 2.8223E-60 60.23 −1.4564 −2.6013 −1.6344
Px_PGRP2 105386206 ADU33187.1 1098 211 1.3699E-67 58.71 −1.6343 −1.2606
Px_PGRP3 105387860 ADU33187.1 824 211 3.5191E-66 58.21 −1.7588 1.3324
Px_PGRP4 105386207 AFV15800.1 761 205 6.5034E-61 60.8 −2.2113 1.1212
Px_PGRP5 105388663 AFP23116.1 993 193 1.095E-57 59.2 −1.1736
Px_PGRP6 105391041 BAF36823.1 690 195 4.9765E-91 87.1 −1.4843 −1.0507
Px_PGRP7 105391791 BAF36823.1 863 186 7.9578E-64 64.57 −1.4168 −1.7257
β-1,3-Glucan binding protein
Px_βGBP1 105380182 AHD25001.1 1424 473 6.084E-125 50.22 1.6692
Px_βGBP2 105394612 Q8MU95.1 1582 482 1.239E-121 46.43 −3.1341 −4.8773 1.1633 −2.7570
Px_βGBP3 105391537 Q8MU95.1 1589 482 3.502E-124 46.53 −2.4046 −8.9744 −2.1931
Px_βGBP4 105390013 Q8MU95.1 1467 481 1.326E-122 48.51 1.0306
Px_βGBP5 105389999 Q8MU95.1 1577 490 0 65.91 −1.2506 1.1221
Px_βGBP6 105380252 Q8MU95.1 2875 930 9.183E-111 43.64 1.0275 −1.9780
Px_βGBP7 105391544 Q8MU95.1 765 254 9.5958E-44 40.55 5.4919
Px_βGBP8 105397355 Q8MU95.1 1429 428 0 66.95 1.6163
Px_βGBP9 105388931 AFC35297.1 1494 426 2.159E-112 45.23 −5.3923 −5.3923 −5.3923
Px_βGBP10 105388956 AFC35297.1 1098 306 2.5257E-29 44.58 −8.8948 −2.6469 1.2345 −8.8948
Px_βGBP11 105390015 AGT95925.1 755 244 7.8321E-51 45 1.6273
Px_βGBP12 105394615 AFC35297.1 1391 426 6.98E-110 46.05 −5.7549
Px_βGBP13 105388955 NP_001128672.1 2895 922 2.792E-107 42.22 2.3049 −4.0875
Px_βGBP14 105391545 NP_001128672.1 2967 758 2.9017E-89 50 −4.9069 −4.9069 1.0238
Px_βGBP15 105394614 NP_001128672.1 1476 491 2.714E-99 42 −4.9542 1.3496 1.9527
Px_βGBP16 105394613 NP_001128672.1 1153 358 1.5059E-96 44.83 −7.0334
Scavenger receptor
Px_SCR1 105381120 EHJ69946.1 688 229 8.4588E-67 52.21 2.0233
Px_SCR2 105394003 NP_001164650.1 1,426 369 3.325E-147 64.96 1.8605
Px_SCR3 105394000 NP_001164651.1 3,147 495 7.71E-151 52.2 1.3314
Px_SCR4 105392382 XP_004930787.1 2,049 577 0 62.17 2.2657
Px_SCR5 105393137 XP_004930826.1 2148 633 0 72.76 −1.6092 −2.0639 1.3051
Px_SCR6 105393261 XP_004930796.1 2,478 571 1.336E-179 54.48 1.2530 2.3480
Px_SCR7 105394486 XP_004930796.1 1,778 461 9.582E-150 55.73 2.3282 2.5486
Px_SCR8 105389099 XP_004930796.1 1,922 461 9.814E-172 55 1.2243 2.7444
Px_SCR9 105383111 EHJ75193.1 2,421 512 6.793E-128 45.65 −1.4056
Lectin
Px_Lectin1 105383612 BAM17981.1 1,372 293 2.0017E-94 86.32 −1.1543 −1.6011 −1.1441
Px_Lectin2 105395555 BAM17857.1 4,54 123 2.6181E-42 83.33 −2.9970 2.0541
Px_Lectin3 105382435 AFM52345.1 1,271 223 8.835E-125 93.27 −1.0849
Px_Lectin4 105392416 NP_001091747.1 1,268 223 6.618E-115 95.26 2.9364 −1.4820
Px_Lectin5 105398492 NP_001165397.1 1,156 220 2.173E-111 96.3 −3.5082 −2.6126 1.7611 −2.3971
Px_Lectin6 105392913 EHJ77925.1 1,870 578 1.697E-112 43.03 −1.1576
Px_Lectin7 105398161 EHJ77925.1 1,810 578 8.125E-112 43.03 1.1921
Px_Lectin8 105383689 AFC35299.1 1,290 307 7.979E-89 52.12 −1.8414 1.2602
MODULATION
Serine protease
Px_SP1 105394363 ADT80832.1 688 200 4.247E-26 37.5 1.2497 1.0804 1.1609 −1.7919
Px_SP2 105381934 AGR92345.1 1,091 270 1.6486E-73 55.74 −1.1914 −3.4241
Px_SP3 105380905 AGR92345.1 2,407 785 2.459E-138 93.33 −1.4117 −2.4052
Px_SP4 105380869 AGR92345.1 827 252 1.8037E-94 68.07 −2.1802 −2.8343 −4.0062 −1.7866
Px_SP5 105393891 AGR92347.1 275 69 1.6748E-12 68.63 10.7756
Px_SP6 105388678 AGR92345.1 850 260 3.5909E-77 55.38 2.7790 −3.8940
Px_SP7 105386078 AGR92347.1 894 262 1.1877E-57 50 2.4196
Px_SP8 105393886 AGR92347.1 637 199 3.697E-108 98.97 −1.5772 −4.4863 1.1192
Px_SP9 105391896 AGR92347.1 633 199 4.768E-108 100 −1.0298
Px_SP10 105388683 AGR92345.1 919 255 4.503E-140 94.12 −1.0937
Px_SP11 105386077 AGR92347.1 891 264 9.174E-143 100 −1.3944
Px_SP12 105391590 AGR92345.1 839 265 2.1485E-74 53.88 −1.7680
Px_SP13 105391006 AGR92346.1 1,129 291 1.144E-109 73.53 −1.8202
Px_SP14 105391005 AGR92346.1 974 292 1.594E-130 86.96 −2.3859
Px_SP15 105391007 AGR92346.1 1,168 298 1.796E-121 74.32 −2.4715
Px_SP16 105388679 AGR92345.1 820 258 1.9699E-85 59.69 −2.6043 −1.2320
Px_SP17 105386722 AGR92347.1 684 193 1.3776E-37 46.99 −1.8340
Px_SP18 105392197 ACR15995.1 2,022 269 1.6161E-55 41.95 1.2420
Px_SP19 105390022 ACR15995.1 1,011 263 1.054E-47 39.74 1.1368 1.3599 −1.7433
Px_SP20 105380853 ADT80829.1 987 273 1.8982E-62 45.42 −1.5318 −3.4960 −2.1187 −3.1187
Px_SP21 105391955 ACR15993.2 871.8 241 8.7168E-26 34.21 −2.2016
Px_SP22 105382233 ADT80828.1 1,954 609 9.247E-101 63.64 −1.6997
Px_SP23 105389290 EHJ71121.1 5,328 1550 0 60.74 −3.2208
Px_SP24 105392198 AGR92347.1 880 265 6.7877E-58 46.09 −1.2299
Px_SP25 105398563 XP_004929850.1 1,699 493 0 63.36 −1.3465 −2.6139
Px_SP26 105380609 XP_004922188.1 1,544 416 6.376E-107 51.3 1.7734
Serine protease inhibitor
Serine Protease Inhibitor 105390805 EHJ65124.1 4,044 1003 0 54.85 1.0193
Serine proteinase
Px_SPN1 105384594 ACI45418.1 783.9 241 4.7416E-25 37.6 −1.6253
Px_SPN2 105383822 AAQ22771.1 884 156 4.6358E-14 40.4 1.8963
Px_SPN3 105394347 EHJ70457.1 1,615 450 2.5981E-82 41.12 1.1541
Px_SPN4 105383519 NP_001040462.1 1,220 390 7.011E-132 60.31 −1.3974 1.3535 −2.0712
Px_SPN5 105395635 NP_001040462.1 769 244 2.1607E-35 60.16 −6.9542 1.2257
Px_SPN6 105396174 AAR29602.1 1,874 484 1.6616E-83 51.49 1.7106
Trypsin-like serine protease
Px_Tryp_SP1 105381636 AAD21835.1 1,038 317 4.5535E-94 71.86 −4.3552 −9.2621 1.3827 −4.2621
Px_Tryp_SP2 105383595 ADK66277.1 728 225 3.7446E-55 46.64 1.0655
Px_Tryp_SP3 105393197 EHJ67268.1 2,824 806 1.303E-101 52.21 −1.0000
Px_Tryp_SP4 105380873 EHJ67268.1 2,612 805 3.687E-103 48.54 −1.7116
Px_Tryp_SP5 105392836 AIR09766.1 696 156 2.696E-44 61.87 −1.5053 −2.6967
Px_Tryp_SP6 105385090 AIR09766.1 872 156 3.2071E-44 61.87 −1.5560
Px_Tryp_SP7 105394340 ACI32835.1 1,744 467 1.35E-148 65.95 1.1500
Px_Tryp_SP8 105380637 ACI32835.1 1,705 464 1.891E-147 65.41 1.0114
Px_Tryp_SP9 105392869 AIR09766.1 1,322 366 3.4186E-34 66.36 −1.6239
Trypsin-like serine protease
Px_Tryp_SPN1 105383936 ADK66277.1 1,277 271 7.1991E-50 42.63 −1.0741
Px_Tryp_SPN2 105383572 ADK66277.1 902 271 2.0689E-49 46.75 1.7144
Px_Tryp_SPN3 105385127 AEP25403.1 593 185 7.1148E-65 71.88 −3.7577 −1.5964
Px_Tryp_SPN4 105387434 ADK66277.1 756 241 1.0998E-60 55.25 −4.6136 −2.3314
Px_Tryp_SPN5 105383573 gb|ADK66277.1 1,020 270 2.1392E-48 42.7 2.9095 −4.5912
Px_Tryp_SPN6 105392752 ADK66277.1 963 286 2.3853E-46 39.63 −2.8735
Px_Tryp_SPN7 105383574 ADK66277.1 865 272 8.8986E-47 40 −2.8880
Px_Tryp_SPN8 105383571 ADK66277.1 1,024 258 9.2395E-84 58.14 −3.6847
Px_Tryp_SPN9 105387433 ADK66277.1 992 247 2.9458E-79 60.08 −4.1164
Px_Tryp_SPN10 105386251 ADK66277.1 809 249 6.6173E-62 50.85 −10.300353
Px_Tryp_SPN11 105386106 AEP25404.1 1,738 536 1.069E-129 92.13 −1.1830
Px_Tryp_SPN12 105393249 AFK93534.1 1,904 490 1.017E-120 50.75 1.0059 3.0422
Px_Tryp_SPN13 105397224 AFK93534.1 1,673 290 3.867E-121 51.01 1.5802 3.9802
Px_Tryp_SPN14 105386282 AFK93534.1 2,100 657 2.7677E-82 50.18 3.9580 −1.1229
Px_Tryp_SPN15 105391595 AFK93534.1 1,629 485 1.285E-137 50.72 1.9038
Chymotrypsin like serine protease
Px_ChymTryp_SP1 105388850 EHJ70525.1 944 300 6.2658E-52 44.84 −3.8146
Px_ChymTryp_SP2 105381896 AFM77773.1 973 249 5.0365E-76 56.41 1.6944
Px_ChymTryp_SP3 105380855 AFM77775.1 944 282 2.877E-89 57.8 −1.1103 −1.8191
Px_ChymTryp_SP4 105388849 NP_001040430.1 1,147 304 3.1128E-60 47.08 −3.2694
Px_ChymTryp_SP5 105394289 AIR09764.1 1,054 300 7.4974E-52 43.32 −3.4467 1.0378
Px_ChymTryp_SP6 105397690 ACI45417.1| 318 91 4.39E-18 48.91 2.5571
Px_ChymTryp_SP7 105383260 NP_001040178.1 939 289 8.9544E-67 47.81 2.2236
Kazal-type inhibitor
Px_KTI1 105382984 ADF97836.1 802 190 1.5693E-23 37.72 −1.1667
Serpin
Px_Serpin1 105396587 BAF36821.1 1,659 450 0 99.33 1.1162
Px_Serpin2 105387806 BAF36820.1 1,262 394 0 99.75 −1.1952 −1.3669
Px_Serpin3 105392292 dbj|BAF36820.1 601 199 5.9941E-06 55.81 −1.7840 −2.4646
Px_Serpin4 105392280 BAF36820.1 1,321 400 0 97 −1.4842
Px_Serpin5 105383392 BAM18904.1 1,931 510 0 66.23 −4.5814 −1.3755 −3.1685
Px_Serpin6 105387001 AEW46892.1 1,523 413 9.804E-169 72.17 −1.4818 1.6229
Px_Serpin7 105390554 AEW46895.1 1,742 398 8.829E-108 48.26 −1.5187
Px_Serpin8 105383829 NP_001037021.1 445 138 3.1274E-32 46.58 −1.5259 −1.3060
Px_Serpin9 105398773 EHJ65045.1 2,173 607 2.5594E-38 55.78 1.5502 1.5146 −1.4854
Px_Serpin10 105381092 EHJ65951.1 2,169 651 1.2911E-90 71.37 −1.2257
Px_Serpin11 105386098 ACG61190.1 5,485 1418 0 54.61 −1.6450
Px_Serpin12 105390552 NP_001037205.1 1,683 397 3.282E-136 60.2 −1.0957
Px_Serpin13 105383513 NP_001139702.1 2,683 387 5.0332E-63 36.75 −1.6280 −5.0875 1.3388
Px_Serpin14 105389206 NP_001139706.1 1,763 407 2.4774E-57 34.28 1.3641
Px_Serpin15 105387669 NP_001139701.1 1,391 401 2.0403E-93 46.21 −1.0807
SIGNALLING PATHWAY
Px_Myd88 105393101 AFK24444.1 1,305 381 8.633E-107 52.16 2.2204
Px_Spatzle 105385965 NP_001243947.1 1,797 418 2.561E-142 59.08 −2.5386
EFFECTORS
Prophenoloxidase
Px_PPO1 105393828 BAF36824.1 1,558 405 0 92.58 −1.5230 2.7326
Px_PPO2 105393465 BAF36824.1 2,479 790 1.822E-144 92.28 2.1137
Moricin
Px_Moricin1 105392531 ABQ42576.1 434 65 1.9938E-10 76.32 7.2646 −7.9307
Px_Moricin2 105392533 ABQ42576.1 436 65 1.0544E-11 75 −1.9629 −2.1231 3.9596 −3.3033
Px_Moricin3 105392532 ABQ42576.1 451 65 2.0342e-10/ 76.32 −9.5793 −2.4708 5.5358 −1.8311
Cecropin
Px_Cecropin1 105394859 ADA13281.1 684 65 1.5836E-17 73.85 −2.5093 −6.0395 −4.6154
Px_Cecropin2 105397888 ADA13281.1 582 65 1.0647E-17 73.85 −3.4452 −6.0700 −3.9365
Px_Cecropin3 105394858 ADA13281.1 512 65 2.0599E-17 73.85 −4.5206 −3.2365
Px_Cecropin4 105392561 ADR51147.1 398 61 1.2033E-15 65.08 −5.2695 −5.1013
Px_Cecropin5 105394860 BAF36816.1 510 65 1.0252E-16 73.02 −1.9265 −5.0688
Gloverin
Px_Gloverin1 105389810 ACM69342.1 628 172 5.0444E-54 60.57 −1.2012 −4.8084
Px_Gloverin2 105389803 ACM69342.1 489 128 1.9253E-51 89.91 −1.3116 −4.8361 −2.6256
Lysozyme
Px_Lys1 105382813 EHJ67777.1 548 140 6.7928E-50 71.54 −1.3225
Px_Lys2 105381977 NP_001093293.1 1,345 143 1.8353E-51 75.63 −10.871135 −3.2201 −1.9733 −4.2418
OTHERS
Peroxidase
Px_Peroxidase1 105382493 XP_004924228.1 2,008 640 3.621E-124 39.14 1.1018
Px_Peroxidase2 105388497 BAM17900.1 2,079 627 1.319E-177 50.66 1.9139 −1.2812 −2.7023 2.2984
Px_Peroxidase3 105389833 EHJ67854.1 824 271 8.222E-132 82.02 −7.6724 −1.5227 1.1856
Px_Peroxidase4 105390475 EHJ75729.1 2,917 753 0 67.72 1.0000
Px_Peroxidase5 105396491 BAM17900.1 1,614 537 4.194E-157 51.61 −2.6129 −1.6793 2.1894
Px_Peroxidase6 105394585 EHJ75729.1 2,218 548 0 73.16 −1.3796
Integrin
Px_Integrin1 105383688 ABF59518.1 630 176 3.8043E-26 57.14 2.5850 2.9336 2.7137
Px_Integrin2 105383715 ABF59518.1 992 290 1.1377E-22 28.99 −1.0139 −1.0806
Px_Integrin3 105392513 ABF59518.1 1,922 639 5.9709E-44 27.22 −1.4097 1.3976
Px_Integrin4 105386410 EHJ72232.1 627 172 1.3367E-30 48.3 1.3943
Px_Integrin5 105387843 EHJ72232.1 2,713 876 0 50.79 1.4047 1.2135
Px_Integrin6 105394193 ACS66819.1 2,349 746 0 90.3 −1.0118 −1.2063
Px_Integrin7 105393654 AAO85804.1 1,669 556 0 69.45 −1.1524 −1.1137
Px_Integrin8 105380096 AII79417.1 2,240 543 3.284E-113 69.72 −1.0752 −1.5091
Transferrin
Px_Transferrin1 105393952 dbj|BAF36818.1 1,006 325 0 99.05 −2.6292 2.0508 −1.2249
Px_Transferrin2 105384728 BAF36818.1 1,904 534 0 96.89 −2.7590 1.3416 −1.3851
Thioredoxin
Px_Thioredoxin1 105380321 AHK05704.1 1,232 247 6.452E-125 87.45 −1.3545 −1.0976
Px_Thioredoxin2 105398803 XP_004925107.1 1,861 266 2.975E-117 77.73 −2.1099
Catalase
Px_Catalase1 105398438 NP_001036912.1 1,767 508 0 82.09 1.3045 −1.6592
Px_Catalase2 105390515 NP_001036912.1 1,686 508 0 82.48 −1.4120
Px_Catalase3 105389213 XP_004924808.1 1,429 474 1.83E-145 53.4 1.3567 −3.6721
Px_Catalase4 105385727 XP_004924808.1 1,676 530 2.181E-148 52.87 1.2412 −3.1595
Hemolin
Px_Hemolin1 105394779 ACN69054.1 1,451 415 0 94.46 −1.3656 −2.2910 −1.9475
Px_Hemolin2 105382056 ACN69054.1 1,403 415 0 94.46 −2.7738 −1.4243
Oxidase
Px_Oxidase 105390649 BAM20596.1 3,273 1032 0 84.16 3.1726 −1.6638

The entomopathogenic fungi are recognized as an environmentally friendly tactic for controlling the insect pests. Previously, the entomopathogenic fungi like M. anisopliae and B. bassiana have received an increasing attention due to wide host range and capability of mass production (Butt et al., 2001). Recently, it has been shown that I. fumosorosea also has the potential to control various insect pests (Gökçe and Er, 2005; Huang et al., 2010; Avery et al., 2011). Therefore, considering the importance of I. fumosorosea, a genomic analysis of immune response of P. xylostella following infection of I. fumosorosea at different time points using high-throughput sequencing Illumina was performed in the present study.

Immune recognition families

Recognition of pathogen is the initial step in the defense against invading microbes, eliciting cellular and humoral responses. Pathogens produce conserved pathogen-associated molecular patterns (PAMPs) and the host produces pattern-recognition receptors (PRRs) in response (Mogensen, 2009). PRRs like peptidoglycan recognition proteins (PGRPs), β -Glucan binding proteins (GNBPs), lectins, scavenger receptors, and hemolin bind to the PAMPs (Hultmark, 2003). Insect PGRPs can trigger signal transduction through the Toll pathway, leading to the activation of AMP production (Zaidman-Rémy et al., 2011). In the present report, 14 PGRPs were identified and most of them were down-regulated after treatment with I. fumosorosea (Figure 6 and Table 3). Among the down-regulated PGRPs, two PGRP transcripts (px_105387866 and px_105386207) were down-regulated up to 2-fold (−2.60 and −2.21), respectively at 12 h post-treatment. Previously, it has also been shown that PGRPs were down-regulated after the injection of secondary metabolite (destruxin) of M. anisopliae in D. melanogaster (Pal et al., 2007), whereas in contrast, PGRPs were up-regulated in response to M. acridium and Beauveria bassiana in Helicoverpa armigera and Ostrinia furnacallis (Liu et al., 2014; Xiong et al., 2015). The expression of other PRRs like lectins, hemolin, and GNBPs was also down-regulated after treatment with I. fumosorosea (Figure 6 and Table 3). Among PRRs, only the scavenger receptors were up-regulated at all-time points post-infection. Our results are in accordance with a previous report showing that among PRRs, only scavenger receptors were up-regulated in response to destruxin A in D. melanogaster (Pal et al., 2007). Our results suggest that PRRs like PGRPs, GNBPs, lectins, and hemolin may be the target of I. fumosorosea and scavenger receptors are responsible for the activation of the immune response of P. xylostella to I. fumosorosea.

Functional classification of immunity- related DEGs in response to I. fumosorosea.

 Toll and imd signaling pathways

The Toll pathway is primarily activated by fungi and Gram-positive bacteria while the Gram-negative bacteria triggers the activation of Imd pathway leading to the production of AMPs (Aggarwal and Silverman, 2008; Hetru and Hoffmann, 2009). Here, in our study, we found that only spatzle and MyD88 showed differential expression while the other immune genes of toll pathway were not induced after treatment with I. fumosorosea (Figure 6 and Table 3). Of note, Imd pathway was also not induced after the treatment with I. fumosorosea at different time points. The expression of MyD88 was up-regulated whereas, spatzle showed down-regulated expression after treatment (Figure 6 and Table 3). Previously, a similar phenomenon was observed in D. melanogaster where only pelle and toll showed differential expression in the Toll pathway, and Imd pathway was not induced after injection of destruxin A (Pal et al., 2007). Thus, our results show that I. fumosorosea has the ability to suppress the expression of toll pathway genes and in the meantime P. xylostella could resist the infection of I. fumosorosea.

 Melanization

Melanization is considered as a vital component of the immune system of insects. It regulates the melanin cascade mediated by prophenoloxidases (PPO) (Taft et al., 2001). When a pathogen invades, PPO gets activated and transformed into PO following transformation of phenolic substances into quinone intermediates and ultimately killing pathogens. Here, only three PPO were found after the treatment of P. xylostella with I. fumosorosea and two of them were up-regulated up to 2-fold at 12 h post-infection.

Serine proteases represent a very large group of enzymes in almost all organisms and are involved in various biological processes (Ross et al., 2003). The structure of serine proteases consists of His, Asp, and Ser amino acid residues forming a catalytic triad (Perona and Craik, 1995). Generally, serine proteases are inactive pro-enzymes and need proteolytic cleavage for activation (Ross et al., 2003). Notably, many serine proteases identified in our study showed up- and down-regulated expression with a serine protease (px_105393891) showing highly up-regulated expression (10.77) and a serine protease (px_105381636) showing down-regulated expression (−9.26) after treatment with I. fumosorosea at 18 h post-infection (Figure 6 and Table 3). It has been reported that the serine proteases showed same up- and down-regulated expression in P. xylostella and D. melanogaster after treatment with destruxin A (Pal et al., 2007; Han et al., 2013).

Serpins, a super-family of proteins, are found in nearly all organisms (Gettins, 2002). In general, they contain 350–400 amino acid residues. The similarity of amino acid sequence ranges from 17 to 95% among all serpins. They contain three β-sheets and seven to nine α-helices folding into a conserved tertiary structure with a reactive center loop (RCL) (Gettins, 2002). The RCL of these serpins binds to the specific active site of the target proteinase. When the cleavage of the serpin takes place at scissile bond, it goes through an important conformational change, trapping the target proteinase covalently (Dissanayake et al., 2006; Ulvila et al., 2011). Interestingly, almost all the serpins were down-regulated at an early stage of treatment at 12 h post-infection. In contrast, the expression level of serpins was up-regulated in P. xylostella after treatment with Diadegma semiclausum parasitization (Etebari et al., 2011; Han et al., 2013). The activation of serpins by D. semiclausum in previous reports may be a strategy to suppress the activity of PPO in the host defense system.

 Antimicrobial peptides

AMPs are evolutionarily conserved low molecular weight proteins and play a vital part in the insect defense system against microorganisms (Bulet and Stocklin, 2005). Here, in the present study, lysozyme, moricin, gloverin, and cecropin were identified after the treatment of P. xylostella with I. fumosorosea at different time periods. Interestingly, all the AMPs were down-regulated after treatment with I. fumosorosea (Figure 6 and Table 3) The expression of lysozyme (px_105381977) was decreased up to 10-fold (−10. 87) at 12 h post-infection, moricin (px_105392532) expression was decreased up to 9-fold (−9.57) at 12 h post-infection, gloverin (px_105389810) expression was reduced up to 4-fold (−4.80) at 18 h post-infection, and the expression of cecropin (px_105394859) was down-regulated up to 6-fold (−6.03) at 18 h post-infection of I. fumosorosea. Previously, most of the reports on immune response of insects to entomopathogenic fungi identified that the expression of AMPs was up-regulated after the treatment leading to a conclusion that the entomopathogenic fungi were unable to suppress the immune system (Liu et al., 2014; Xiong et al., 2015; Zhang et al., 2015). However, varroa mites and destruxin A were reported to suppress the expression of AMPs in Apis mellifera and D. melanogaster (Gregory et al., 2005; Pal et al., 2007). The immune response suppression in host by an entomopathogenic fungi such as, I. fumosorosea would have obvious benefits for success of pathogenic fungi. Previously, it was observed that when mutations were introduced in Toll and IMD pathways, the D. melanogaster was unable to produce AMPs resulting in extreme vulnerability to fungal challenge (Lemaitre et al., 1996; Tzou et al., 2002). Thus, the ability to reduce AMP production is likely to aid fungal survival in a variety of insect hosts. A similar suppression of AMPs in our study by I. fumosorosea adds a new dimension to the dynamics of host-pathogen interactions.

 Conclusion

Concluding our findings, the present study adopted genomic analysis with RNA-Seq and DGE technology to find out DEGs especially focusing on immunity-related DEGs after treatment with I. fumosorosea. It is speculated that the entomopathogenic fungi I. fumosorosea not only down-regulated the expression of PRRs and other immune genes but also the activity of AMPs was inhibited leading to the ultimate suppression of the immune system of P. xylostella. Thus, it shows that I. fumosorosea has the potential to suppress the immune system of P. xylostella and can be adopted as a bio-pesticide for P. xylostella control. Our study explores a new avenue in research to develop bio-pesticides for controlling P. xylostella by focusing on the insect immune system.

 Ethics statement

Our work confirms to the legal requirements of the country in which it was carried out.

 Author contributions

Conceived and designed the experiments: FJ, MS, XiaoxX, and JX. Performed the experiments: JX, XiaoxX, and MS. Analyzed the data: XiaojX, JY, XZ, and JX. Contributed reagents/materials/analysis tools: SL and SW. Wrote the manuscript: MS, XiaoxX, and JX. Revised the manuscript: MS, FJ, and XY.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The authors thank BGI-Shenzhen for assisting in the sequencing.

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Funding. This work was supported by grant from The National Natural Science Foundation of China (31371989, 31572069), Science and Technology Program of Guangzhou China (201509010023) and Department of Science and Technology of Guangdong China (2014A020208106).