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. 2021 Dec 14;18:250. doi: 10.1186/s12985-021-01721-x

Transcriptional responses of Daphnis nerii larval midgut to oral infection by Daphnis nerii cypovirus-23

Wendong Kuang 1,#, Chenghua Yan 3,#, Zhigao Zhan 1,#, Limei Guan 1, Jinchang Wang 1, Junhui Chen 1, Jianghuai Li 1, Guangqiang Ma 3,✉, Xi Zhou 1,2,✉, Liang Jin 1,✉
PMCID: PMC8670114  PMID: 34906167

Abstract

Background

Daphnis nerii cypovirus-23 (DnCPV-23) is a new type of cypovirus and has a lethal effect on the oleander hawk moth, Daphnis nerii which feeds on leave of Oleander and Catharanthus et al. After DnCPV-23 infection, the change of Daphnis nerii responses has not been reported.

Methods

To better understand the pathogenic mechanism of DnCPV-23 infection, 3rd-instar Daphnis nerii larvae were orally infected with DnCPV-23 occlusion bodies and the transcriptional responses of the Daphnis nerii midgut were analyzed 72 h post-infection using RNA-seq.

Results

The results showed that 1979 differentially expressed Daphnis nerii transcripts in the infected midgut had been identified. KEGG analysis showed that protein digestion and absorption, Toll and Imd signaling pathway were down-regulated. Based on the result, we speculated that food digestion and absorption in insect midgut might be impaired after virus infection. In addition, the down-regulation of the immune response may make D. nerii more susceptible to bacterial infections. Glycerophospholipid metabolism and xenobiotics metabolism were up-regulated. These two types of pathways may affect the viral replication and xenobiotic detoxification of insect, respectively.

Conclusion

These results may facilitate a better understanding of the changes in Daphnis nerii metabolism during cypovirus infection and serve as a basis for future research on the molecular mechanism of DnCPV-23 invasion.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-021-01721-x.

Keywords: Daphnis nerii cypovirus-23, Midgut, Transcriptome analysis

Introduction

The oleander hawk moth, Daphnis nerii (D. nerii), belongs to Lepidoptera, Sphingidae family, is a worldwide pest [1]. D. nerii larvae damages leave of Oleander, Catharanthus, Vinca, Adenium, Vitis, Tabernaemontana, Gardenia, Trachelospermum, Amsonia, Asclepias, Carissa, Rhazya, Thevetia, Jasminum and Ipomoea [2, 3], which affect the landscape and the medicinal value of these plants. At present, the chemical pesticide decamethrin is used to control D. nerii [2].

Cypovirus is a member of the Reoviridae family, and is characterized by its single layered capsid [4]. DnCPV-23 was isolated from naturally diseased D. nerii larvae. This was a new type of cypovirus based on different electrophoretic migration patterns and conserved terminal sequences [1, 5, 6]. In addition to Daphnis nerii, it has been found that DnCPV-23 can also induce infection and death in many species of Sphingidae insects, such as Cephonodes hylas Linnaeus, Ampelophaga rubiginosa Bremer & Grey, and Agathia lycaenaria Kollar. The genome of DnCPV-23 consists of ten segments of linear double-stranded RNA, referred to as genomic segments 1 (S1) to 10 (S10), in accordance with the fragments from longest to shortest [7]. Our previous research and unpublished data demonstrated that the virus could successfully replicate on the Sf9 [8] and Manduca sexta cell lines QB-MS 2-2 [9]. However, the molecular mechanism of the interactions between the new type cypovirus and its hosts remains unclear. It is necessary to identify the interactions between the virus and its hosts to achieve an in-depth understanding and reveal the exploitation potential of the virus for future insecticide development.

Recently, many studies in the field have generated large amounts of data using the aforementioned high-throughput approaches, from the silkworms or BmN cells infected with BmCPV, including (1) The possible host’s RNAi response against BmCPV challenge in persistent and pathogenic Bombyx mori model was compared. During the pathogenic infection, it was found that higher level RNAi responses against BmCPV were observed, which further demonstrated the importance of RNAi as an antiviral mechanism [10]. (2) Gene expression profiles [11–19], DNA methylation [20], and lipidomic profile [21] of silkworm midgut or BmN cells after BmCPV infection were analyzed. These results suggested that many genes (for example, genes expressing Calreticulin, FK506-binding protein, and protein kinase c inhibitor gene, microRNAs, and activated protein kinase C) may play important roles in BmCPV replication. In addition, epigenetic regulation may influence silkworm-virus interaction, and BmCPV may modulate the lipid metabolism of cells for their self-interest.

Until now, the molecular mechanism underlying the midgut infection of DnCPV-23 is not clearly understood. Furthermore, since transcriptome analyses regarding D. nerii or DnCPV-23 have not yet been performed, this study aims to fill this gap about the new type cypovirus. The data and analysis presented here provide insights into the possible mechanism of DnCPV-23 infection and host defense and a basis for future DnCPV-23 relevant studies.

Materials and methods

Daphnis nerii larval midgut and virus stock

Newly wild-caught second instar larvae with a similar mass were used in this research investigation for the virus infection. Before infection, the D. nerii were supplied with 12-h day/night cycles under 50 ± 5% relative humidity conditions and were nurtured on oleander leaves at 27 ± 1 ℃ for three days. The midgut tissues were collected from four pathogenically infected larvae at 72 h [13, 15] after feeding with DnCPV-23. The same tissues were also collected from three uninfected control larvae at the same time point. DnCPV was originally isolated from the larvae of D. nerii and propagated in D. nerii larvae [1]. The polyhedra suspension of DnCPV-23 utilized for infecting the D. nerii was stored at 4 °C in the dark.

Virus inoculation

In this study, the DnCPV-23 viral stock was suspended in distilled water at a concentration of 2 × 107 polyhedra/mL. Then, 100 μL of the viral suspension was spread evenly on one piece of oleander leaf measuring approximately 4 cm × 1.5 cm each in size. The leaf was then fed to four D. nerii larvae. The dose of infection was calculated as 2 × 106 polyhedra per larva. In addition, three control larvae were fed the same quantity of leaves treated with only distilled water. After approximately 12 h, fresh oleander leaves were used to feed the inoculated larvae after the DnCPV-23-inoculated leaves had been completely consumed.

Sample preparation

The midguts of both DnCPV-23-infected and control larvae were collected at 72 h post-inoculation by dissecting the larvae on ice. The isolated midgut was then quickly washed in 0.8% diethylpyrocarbonate (DEPC)-treated physiologic saline solution to remove the attached leaf pieces, and then frozen in liquid nitrogen [13, 22].

RNA sequencing

All of the RNA-seq procedures were conducted by the Oebiotech Company (Shanghai, China). The total RNA was extracted from the D. nerii midgut tissue using TRIzol reagent (Invitrogen, USA) according to the manufacture’s protocols. The RNA integrity and concentrations were checked using an Agilent 2100 Bioanalyzer (Agilent Technologies, USA). In addition, seven RNA samples (including three uninfected samples and four infected samples) with RNA integrity were used to construct the libraries. The cDNA libraries were prepared using a TruSeq RNA Sample Preparation Kit (Illumina, USA) according to the manufacturer’s protocols. Thereafter, the obtained cDNA libraries were sequenced on the Illumina HiSeq2500 platform, which generated paired-end raw reads of 125 bp.

De novo assembly and functional annotation

The raw data was pretreated by discarding reads with adaptors and low quality (quality scores < 30). Then, the raw data was assembled using Trinity software with default parameters for de novo transcriptome assembly. Transcripts that were not shorter than 300 bp were used for subsequent analysis. To obtain the functional annotations of predicted protein-coding sequences, we searched against various databases, including the NCBI non-redundant (NR) protein, SwissProt, and euKaryotic Orthologous Groups (KOG) using Blastx with an E-value < 10−5. The top hit was utilized to assign gene names. Whereafter, the Gene Ontology (GO) annotations of the transcripts were then analyzed based on SwissProt annotations, and functional classifications were assigned by WeGO software. In addition, for the purpose of determining the biological pathways involved, the KEGG pathway was annotated based on the KEGG Orthology (KO) identifiers.

Differential gene expression analysis

RNA sequencing results from the two groups were mapped to the assembled transcriptome using bowtie2 [23] and express [24]. The FPKM (fragments per kb per million reads) method [25] was utilized to calculate the expression levels of the unigenes, which eliminated the influencing effects of the different gene lengths and sequencing levels. The differences in the unigene expressions between the two groups were calculated with DESeq [26] and any significant differences were determined with P < 0.05 and an absolute value of log2 fold change > 1.

Real-time quantitative reverse transcription PCR (Real-Time qRT-PCR)

This study utilized qRT-PCR to analyze the expression level of DnCPV-23 S1, S10 genes of transcriptome samples, and verify the DEGs recognized by the RNA-seq. The total RNA was isolated from the samples of the transcriptomic analysis using TRIzol reagent (Life Technologies) and was then treated with DNase I (Fermentas, Glen Burnie, MD, USA). We reversely transcribed 1 μg of the total RNA per sample into complementary DNA (cDNA) using a PrimeScript RT Reagent Kit (Takara). Then, qRT-PCR was performed using Talent qPCR PreMix SYBR Green (Tiangen, China) on a QuantStudio™ 7 Flex Real-Time PCR System (Applied Biosystems™). One cycle was added for melting curve analysis for all the reactions to verify the product specificity. The expression level of each gene relative to that of the RPL13 gene was calculated using the 2−△△CT method [27]. All of the primers for the aforementioned target genes are listed in Table 1. Results are representative of two to three independent experiments.

Table 1.

Primers used in the qRT-PCR for the the viral RNA detection of transcriptome samples and validation of the RNA-seq

No Primer name Primer sequence (5' to 3') Tm (°C) Gene id Target gene
S1-RTPCR-F GTGCTGATGGTCTGCTAA 49.6 N/A DnCPV S1
S1-RTPCR-R TGATTGATGACGACATTGAG 51.5
S10-RTPCR-F GTCCGCCAATACTCTCAG 52.6 N/A DnCPV S10
S10-RTPCR-R CGTAGTCCATCGTCAATCA 51.3
1 CASP8-F ACTGGAGAAGACTATGAGGTTA 51.5 TRINITY_DN10280_c0_g1_i1_3 CASP8
2 CASP8-R ACGCTGTCATCTTGGCTAA 53.7
3 CYP6AB13-F GATTCACACCAGCATTCAG 51.0 TRINITY_DN11437_c0_g1_i1_6 CYP6AB13
4 CYP6AB13-R CAGTCGTATATCTCGCCATA 50.5
5 CYP6B45-F GCGATACCGAACCAGAAC 53.4 TRINITY_DN12532_c0_g7_i1_1 CYP6B45
6 CYP6B45-R ATTGGCAGTAAGTGTGAGTT 51.0
7 DHRS4-F TCTTCTATCGCCGCATATCA 52.8 TRINITY_DN12896_c1_g2_i3_3 DHRS4
8 DHRS4-R CACCACCTCATTAGCAATCG 53.5
9 PNLIP-F CACCTCGTAGACTTGGAAGA 53.5 TRINITY_DN12381_c0_g2_i1_6 PNLIP
10 PNLIP-R GTTAGCGTTGCCATTGACA 53.2
11 PRSS1_2_3-F CCTGGAAGATGGCGTGTT 55.4 TRINITY_DN10836_c0_g5_i1_6 PRSS1_2_3
12 PRSS1_2_3-R TCGGCGGTAATTCGGTTAT 53.5
13 RDH12-F GTCTAATCGTCCGCTATTGAG 52.5 TRINITY_DN14445_c0_g1_i1_3 RDH12
14 RDH12-R CTGTAGGTGAAGATTGCCATT 52.2
15 SCARB1-F AACACAACAAGAGGCATCAC 53.0 TRINITY_DN14140_c0_g1_i1_6 SCARB1
16 SCARB1-R GTCGTCGGTTCAATATCCATAA 51.7
17 SLC46A1-F TGGAACGACACGACAAGT 53.7 TRINITY_DN8071_c0_g1_i2_5 SLC46A1
18 SLC46A1-R CAACAGAGTGCGAACAGTATA 51.7
19 SLC52A3-F AAGCGATTGTGGAAGATGTC 52.5 TRINITY_DN11521_c0_g1_i2_4 SLC52A3
20 SLC52A3-R CGGCATACACGAGTACGA 54.4
21 ABCA3-F CGATATACGCCGCAAGTAAG 53.3 TRINITY_DN12365_c0_g1_i6_2 ABCA3
22 ABCA3-R GCAGTTCTCTACATTCAGTTGA 51.8
23 ABCC4-F AGTGGATGGAAGGTTGGAAT 53.3 TRINITY_DN11997_c1_g1_i24_2 ABCC4
24 ABCC4-R CGGCTCTTGTGGTATAATTGA 51.9
25 CYP6B6-F GGACTATTGTTGGCGAATC 50.7 TRINITY_DN13898_c0_g1_i1_4 CYP6B6
26 CYP6B6-R TTGTGGAAGAAGACGATGT 50.5
GAPDH-F TATGTTCGTTGTCGGAGTTA 50.1 TRINITY_DN5984_c0_g1_i2_2 GAPDH
GAPDH-R TAGCAGTAGTGGCGTGTA 52.4
27 LYPLA3-F ACATCCACGACACAAGACTA 52.8 TRINITY_DN10250_c0_g1_i1_1 LYPLA3
28 LYPLA3-R GACCGATAATGAACTCCTGAAT 51.5
29 NTE-F CAGCCTGGAAGGTAAGTAGT 53.6 TRINITY_DN14343_c0_g2_i1_4 NTE
30 NTE-R CTCATAGACGAGCGACAGT 53.8
31 UGT-F GCATTCATTCAAGTCCATCAG 51.3 TRINITY_DN14215_c0_g5_i7_5 UGT
32 UGT-R GCCTCCATCAATAATCACCAA 52.2
33 DnRPL13-F GAACTATTGGCATTGCTGTTG 52 TRINITY_DN4717_c0_g1_i2_3 RPL13
34 DnRPL13-R TCCTCCTCATTGGCTTCAC 54.5
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Results

Virus infection of the samples

Prior to the transcriptome analysis, qRT-PCR was used to detect the mRNA levels of the DnCPV-23 S1 and S10 genes in the infected and uninfected samples. The results showed that the infected group had been successfully infected based on the high relative expression of the viral gene mRNA compared with uninfected group (Fig. 1).

Fig. 1.

Fig. 1

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Detection of the viral RNA in transcriptome samples at 72 hpi (hours post infection). After feeding for 72 h, the mRNA levels of DnCPV-23 S1 (A) and S10 (B) in the midgut of D. nerii were detected. The asterisk (***) denotes the presence of a statistically significant difference (p < 0.001) by unpaired Student's t test

Transcriptome sequencing and assembly

The RNA-Seq data from the DnCPV-23-infected and control groups contained 346.39 million reads, and 334.60 million clean reads after trimming, among which 96.17 to 97.39% per sample were determined to be useful. The acquired clean reads were assembled into 31,696 unigenes (> 300 bp). The average length of these unigenes was 1347.61 bp, and the N50 length was 2348 bp; other information about these unigenes were shown in Table 2. This study then assembled 31.696 unigenes ranging from 301 bp to 32,420 bp. The total unigene length was 42,713,980.

Table 2.

Statistics of the assembly results

Term All  >  = 500 bp  >  = 1000 bp N50 Total_Length Max_Length Min_Length Average_Length
Unigene 31,696 20,703 12,663 2348 42,713,980 32,420 301 1347.61
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Transcriptome annotation

A total of 31,696 assembled unigenes were searched against the public databases, including the NR, Swissprot, KOG, GO, and KEGG databases, among which 16,820 (53.1%) (Fig. 2) unigenes were annotated. The distribution patterns of the unigenes in the different databases were as follows: 16,615 unigenes in the NR database, 11,152 unigenes in the Swissprot database, 10,374 unigenes in the KOG, 10,468 unigenes in the GO, and 5501 unigenes in the KEGG databases (Table 3). Figure 2 shows the degree of overlap between the unigenes annotated in the different databases. It was found that 4353 (13.7%) unigenes overlapped in all five databases, while 12,390 (73.7%) unigenes overlapped in two or more databases.

Fig. 2.

Fig. 2

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Venn diagram showing the degree of overlapping of the unigenes annotated based on different databases. Numbers in different colors represent the number of unigenes annotated through one or more annotation libraries

Table 3.

Annotation statistics for each database

Anno_Database Annotated_Number 300 <  = length < 1000 Length >  = 1000
NR 16,615(52.42%) 6217(19.61%) 10,398(32.81%)
Swissprot 11,152(35.18%) 2921(9.22%) 8231(25.97%)
KEGG 5501(17.36%) 1694(5.34%) 3807(12.01%)
KOG 10,374(32.73%) 2758(8.70%) 7616(24.03%)
eggNOG 15,249(48.11%) 5239(16.53%) 10,010(31.58%)
GO 10,468(33.03%) 2670(8.42%) 7798(24.60%)
Pfam 10,594(33.42%) 2505(7.90%) 8089(25.52%)
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Significant impacts of the viral infection on the hosts’ transcriptome expressions

As shown in Fig. 3, the main component PCA1 had reached 41.56%, and the main component PCA2 had reached 27.23%. Therefore, the percentage total of the two was 68.79%, which accounted for a high proportion and represented the overall population to a large extent. This study’s principal component analysis manifested a clear separation of the samples with the two treatments (Fig. 3A), which indicated that the samples had good repeatability. The heat map of the gene expressions is presented in Fig. 3B. The results suggested that these DEGs could distinguish the samples. The results revealed that the viral infection could exert apparent influences on the midgut gene expressions. In addition, the transcriptome results showed that 1166 genes were down-regulated (accounting for 3.68% of the total assembled unigenes) and 812 genes (accounting for 2.56% of the total assembled unigenes) were up-regulated as a response to the DnCPV-23 infection (Fig. 3C).

Fig. 3.

Fig. 3

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Influence of DnCPV-23 infection on D. nerii transcriptome: A Plot of the 1st and 2nd principal component of the sample variations using the principal component analysis, in which the red dots represent samples without DnCPV-23 infection, and the green dots denote infected samples. B Heat map of 1,978 differently expressed genes (DEGs) in the infected samples and controls. C After infection, 812 genes were up-regulated (red bars) and 1166 genes were down-regulated (blue bars)

Analysis of the differently expressed genes

In this study, KEGG function enrichment analysis was performed on the differential genes expressed in the DnCPV-23-infected and uninfected control groups to clarify the relevant biological pathways involved in the differential genes. Among all of the DEGs, 298 DEGs had KEGG annotations, of which 118 were up-regulated genes and 180 were down-regulated genes. According to the pValue of KEGG analysis of up-regulated and down-regulated signal pathways, we identified 20 most significant signal pathways each. These pathways play an important role in insect reproduction, immunity, digestion and absorption and xenobiotic metabolism and so on (Fig. 4).

Fig. 4.

Fig. 4

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KEGG classifications of DEGs after DnCPV-23 infection (Top 20): A. Down-regulated pathways; B. Up-regulated pathways. Horizontal axis of the figure is the enrichment score. The larger the bubble, the more the number of DEGs. The bubble color changes from purpl E-blu E-green–red, indicating that the smaller the enrichment pValue and the greater the significance

qRT-PCR validation of DEGs

To verify the reliability of the transcriptome data and the DEG results obtained by RNA-seq, seventeen DEGs were selected for qPCR analysis. As shown in Fig. 5, the fold-change values of DnCPV_1 sample vs Mock_1 sample obtained in the qPCR analysis results were consistent with the values obtained by the RNA-seq for all of the selected genes.

Fig. 5.

Fig. 5

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Validation of RNA-seq profiles by real-time qPCR. To validate the RNA-seq data, the relative mRNA levels of 17 selected DEGs in the DnCPV_1 sample were examined by qPCR; The mRNA levels by qPCR are presented as the fold change compared with the Mock_1 sample after normalization against RPL13. The relative expression levels from the RNA-seq analysis were calculated as RPKM values. Error bars show mean ± SEM

Discussion

This study analyzed the transcriptome of the uninfected D. nerii midgut and the DnCPV-23- infected D. nerii midgut presented unique gene expression profiles induced by DnCPV-23 infection for the first time. In addition, KEGG function enrichment analysis was performed on the differential genes expressed after DnCPV-23 infection. Compared with uninfected D. nerii midgut, the transcriptome profiles of the infected samples displayed universally changed transcript abundances for many pathways.

Based on the pValue of KEGG analysis regarding up-regulated and down-regulated signal pathways, we identified 20 most significant signal pathways each. Among these signal pathways, the retinol metabolism pathway, vitamin digestion, and absorption signal pathway were down-regulated, consistent with the transcriptome study about BmCPV infected midgut vs non-infected midgut [13]. In addition, protein digestion and absorption pathway way was down-regulated in accord with previous research [10]. DnCPV infection may destroy the functions of digestion and the absorption of midguts, which causes the disturbance of protein and amino acid metabolism in D. nerii [13, 28]. Peptidoglycan recognition proteins (PGRPs) are pattern recognition molecules that are conserved from insects to mammals. PGRPs are the first receptors known to recognize, bind, or catalytically cleave the pathogenic microorganisms [29], PGRPs recognize bacteria and their unique cell wall component, eptidoglycan [30, 31]. This study observed nine transcripts of D. nerii isoforms of PGRP genes. Six transcripts were found to be down-regulated in the infected D. nerii midgut. The most highly expressed and most dramatically down-regulated was TRINITY_DN13195_c0_g1_i3_3, which was down-regulated by as much as 51-fold. The down-regulation of PGRP expression can lead to a decrease in the ability of the D. nerii’s innate immune system to recognize bacterial peptidoglycans (PGN), which may lead to D. nerii more susceptible to bacterial infections. In addition, BmPGRP-S2 was up-regulated upon BmCPV infection, overexpression of which can activate the Imd pathway and induce increased AMPs to enhance the antiviral capacity of transgenic silkworm against BmCPV [32]. Moreover, previous study demonstrates [33] that PGRPS2-1 and PGRPS2-2 can prevent BmCPV replication. Based on this work, was speculated that the down-regulation of PGRP was conducive to the replication of DnCPV-23.The gene CASP8 (KEGG gene name: caspase-8, Gene id: TRINITY_DN10280_c0_g1_i1_3) (Dredd in Drosophila) was down-regulated more than two folds, and other caspase genes changed non-significantly. It is predicted to be involved in the cleavage of Relish, the Drosophila homolog of mammalian NF-κB, resulting in activating the immune-deficient pathway (IMD)-induced expression of antimicrobial peptides in response to Gram-negative bacteria [34–36], fungi and viruses [37]. Research performed by Li et al. proved BmDredd interacts with BmSTING to enhance antiviral signaling [38]. The down-regulation of this gene may be very important for DnCPV-23 to escape from the host innate immune system and replicate in the midgut. Our result conflicted with the work by Guo et al. [11]. We speculated the contradiction might be related to the different stages of virus-host interaction or the heterogeneity of different species against virues. The pathways and the genes mentioned above are listed in Table 4 (The expression of genes in each sample is shown in Additional file 1).

Table 4.

The down-regulated pathways focused in the discussion section

id Term pValue Enrichment_score gene_id BaseMean_control_mock BaseMean_case_DnCPV FoldChange pValue qValue Regulation NR annotation KEGG gene name
ko04974 Protein digestion and absorption 1.33E−17 6.845688889 TRINITY_DN12884_c1_g5_i1_1 2843.901036 282.1111777 0.099198662 1.72 E−06 0.0007668 Down LOW QUALITY PROTEIN: carboxypeptidase B [Bombyx mori] CPA2
TRINITY_DN13745_c3_g2_i2_4 37,228.13358 6283.238748 0.168776625 0.04653249 0.7667028 Down putative chymotrypsin, partial [Samia ricini] CELA2
TRINITY_DN13546_c1_g2_i2_1 33,763.67895 179.8629852 0.005327115 1.26 E−10 2.06 E−07 Down RecName: Full = Trypsin, alkaline C; Flags: Precursor PRSS1_2_3
TRINITY_DN11633_c0_g1_i2_3 576.0371804 28.38155477 0.049270352 1.62 E−08 1.12 E−05 Down trypsin, alkaline C-like [Spodoptera litura] PRSS1_2_3
TRINITY_DN13619_c0_g2_i1_3 701.0350489 199.5322761 0.28462525 0.00871419 0.3479086 Down sodium/potassium-transporting ATPase subunit alpha isoform X6 [Bombyx mori] ATP1A
TRINITY_DN13597_c0_g2_i2_4 683.1424229 36.96948382 0.054116803 0.03730582 0.7023823 Down serine protease 62 [Mamestra configurata] PRSS1_2_3
TRINITY_DN10836_c0_g7_i1_6 407.2114124 52.04490715 0.127808076 0.00142694 0.1232753 Down trypsin, partial [Manduca sexta] PRSS1_2_3
TRINITY_DN7116_c0_g1_i1_5 140.0397486 41.73985284 0.298057182 0.02906 0.6296715 Down Prolylcarboxypeptidase [Danaus plexippus plexippus] PRCP
TRINITY_DN5681_c0_g1_i1_6 1202.562374 41.63057875 0.034618228 0.00013096 0.0240473 Down chymotrypsinogen-like protein 3 [Manduca sexta] PRSS1_2_3
TRINITY_DN10836_c0_g5_i1_6 3539.814633 11.52410727 0.003255568 0.00393418 0.2234223 Down trypsin, alkaline C [Bombyx mori] PRSS1_2_3
TRINITY_DN14237_c1_g1_i3_3 2139.270665 126.8457966 0.059293945 0.00362815 0.2142243 Down hypothetical protein B5V51_4161 [Heliothis virescens] PRSS1_2_3
TRINITY_DN18044_c0_g1_i1_4 61.20950346 0 0 0.00262208 0.1786659 Down RecName: Full = Trypsin, alkaline C; Flags: Precursor PRSS1_2_3
TRINITY_DN13619_c0_g3_i1_3 1098.504638 384.681457 0.350186466 0.02344348 0.5771173 Down Sodium/potassium-transporting ATPase subunit alpha [Papilio xuthus] ATP1A
TRINITY_DN12770_c1_g2_i2_6 33,988.65545 2472.057397 0.072731838 0.03984473 0.7217322 Down serine protease 62 [Mamestra configurata] PRSS1_2_3
TRINITY_DN14161_c2_g2_i3_3 150,880.9838 10,699.40148 0.070912856 0.027439 0.6151748 Down trypsin, alkaline C-like [Spodoptera litura] PRSS1_2_3
TRINITY_DN12929_c2_g1_i1_6 9158.048497 41.0899202 0.004486755 0.00143302 0.1232753 Down trypsin [Manduca sexta] PRSS1_2_3
TRINITY_DN10836_c0_g1_i4_6 157,887.1736 53,448.64932 0.338524328 0.02226533 0.5641697 Down trypsin, alkaline C-like [Bombyx mori] PRSS1_2_3
TRINITY_DN12646_c0_g1_i3_6 18,799.76899 343.0033323 0.018245082 0.00558226 0.271197 Down trypsin, alkaline C-like [Spodoptera litura] PRSS1_2_3
TRINITY_DN3826_c0_g1_i1_3 4708.243184 116.815754 0.024810901 0.00083317 0.0853474 Down serine protease 5 [Mamestra configurata] PRSS1_2_3
TRINITY_DN12903_c0_g1_i1_6 588.272948 19.69837276 0.03348509 7.39 E−10 8.85 E−07 Down silk gland derived serine protease [Bombyx mori] PRSS1_2_3
TRINITY_DN14269_c4_g1_i5_4 15,015.14212 207.7199418 0.013834031 0.00010037 0.019782 Down trypsin [Manduca sexta] PRSS1_2_3
TRINITY_DN8384_c0_g2_i8_4 4501.305649 35.57861617 0.007904066 0.00033725 0.0475214 Down chymotrypsinogen-like protein 3 [Manduca sexta] PRSS1_2_3
TRINITY_DN17232_c0_g1_i1_5 229.0935699 80.06529495 0.349487308 0.03584292 0.6919927 Down proton-coupled amino acid transporter-like protein CG1139 [Trichoplusia ni] SLC36A, PAT
TRINITY_DN8969_c0_g1_i1_6 1070.195299 24.35172941 0.022754472 0.00153816 0.1284174 Down carboxypeptidase B [Bombyx mori] CPA2
TRINITY_DN12498_c2_g2_i1_5 3577.880426 0 0 0.00308839 0.197654 Down trypsin CFT-1-like [Trichoplusia ni] PRSS1_2_3
TRINITY_DN9363_c0_g1_i1_5 2166.100895 67.76280065 0.031283308 7.81 E−11 1.52 E−07 Down trypsin precursor AiD2, partial [Agrotis ipsilon] PRSS1_2_3
TRINITY_DN7771_c0_g1_i1_1 166.8439433 24.32627007 0.145802536 0.01850363 0.5173478 Down hypothetical protein B5V51_4161 [Heliothis virescens] PRSS1_2_3
TRINITY_DN1220_c0_g1_i1_5 14,636.6041 1623.956772 0.110951745 6.30 E−06 0.0020452 Down trypsin, alkaline C-like [Spodoptera litura] PRSS1_2_3
ko04977 Vitamin digestion and absorption 8.59 E−05 4.753950617 TRINITY_DN8071_c0_g1_i2_5 159.1367963 7.893169411 0.049599901 2.35 E−05 0.0062453 Down proton-coupled folate transporter isoform X2 [Bombyx mori] SLC46A1
TRINITY_DN12381_c0_g2_i1_6 15,115.15447 69.82405532 0.004619473 1.51 E−05 0.0042801 Down pancreatic triacylglycerol lipas E−like [Spodoptera litura] PNLIP, PL
TRINITY_DN9781_c0_g1_i1_3 75.2460337 20.63729453 0.274264217 0.03100164 0.6531949 Down scavenger receptor class B type 1 like protein 12 [Bombyx mori] SCARB1
TRINITY_DN11521_c0_g1_i2_4 1196.401288 280.0407483 0.234069247 0.00250876 0.1751687 Down solute carrier family 52, riboflavin transporter, member 3-B isoform X3 [Trichoplusia ni] SLC52A3, RFT2
TRINITY_DN14080_c0_g1_i4_5 13,236.92182 908.4409062 0.068629317 0.03090689 0.6516395 Down pancreatic triacylglycerol lipase [Bombyx mori] PNLIP, PL
TRINITY_DN17108_c0_g1_i1_5 19.89691746 1.317177118 0.066200059 0.0121168 0.4110339 Down hypothetical protein B5V51_177 [Heliothis virescens] SLC46A1
TRINITY_DN14140_c0_g1_i1_6 6399.436654 1095.005085 0.171109606 0.00016917 0.0286312 Down sensory neuron membrane protein 2 [Bombyx mori] SCARB1
ko04624 Toll and Imd signaling pathway 0.00016 3.943369176 TRINITY_DN13195_c0_g1_i3_3 48,818.06612 740.1059156 0.015160492 2.79 E−06 0.0010722 Down peptidoglycan recognition protein 2 [Manduca sexta] PGRP
TRINITY_DN1052_c0_g1_i2_5 74.58752535 0 0 0.02832612 0.6208957 Down Bacteriophage T7 lysozym E−like protein 1 (BTL-LP1) [Bombyx mori] PGRP
TRINITY_DN10280_c0_g1_i1_3 1415.480197 536.8363029 0.379260907 0.04150037 0.7315422 Down caspas E−6 [Manduca sexta] CASP8
TRINITY_DN14006_c2_g1_i2_4 16,714.28346 318.7737419 0.019071936 3.82 E−10 5.17 E−07 Down peptidoglycan recognition protein 2 [Manduca sexta] PGRP
ko00830 Retinol metabolism 0.000409 3.492698413 TRINITY_DN14190_c1_g2_i2_4 4018.349256 720.63212 0.179335362 0.04158394 0.7316189 Down UDP-glucosyltransferase isoform X1 [Bombyx mori] UGT
TRINITY_DN12319_c0_g2_i1_4 4465.699274 170.972127 0.038285634 2.79 E−06 0.0010722 Down UDP-glycosyltransferase UGT340C2 [Bombyx mori] UGT
TRINITY_DN12896_c1_g2_i3_3 4251.17249 1508.008769 0.35472773 0.02274633 0.5685456 Down PREDICTED: RNA-directed DNA polymerase from mobile element jockey-like [Papilio machaon] DHRS4
TRINITY_DN13518_c1_g1_i6_6 745.6825793 119.2237632 0.159885408 0.0001628 0.0278557 Down UDP-glycosyltransferase UGT340C1 precursor [Bombyx mori] UGT
TRINITY_DN14445_c0_g1_i1_3 151.0781746 54.27468401 0.359249006 0.04671659 0.7685163 Down hypothetical protein B5X24_HaOG201493 [Helicoverpa armigera] RDH12
TRINITY_DN9738_c0_g1_i1_6 438.41149 83.17535239 0.189719828 0.04256225 0.7412925 Down uncharacterized protein LOC112052352 [Bicyclus anynana] UGT
TRINITY_DN8673_c0_g1_i3_3 839.7824168 167.2848772 0.199200262 0.00073535 0.0803495 Down PREDICTED: UDP-glucuronosyltransferase 2B19-like isoform X6 [Amyelois transitella] UGT
TRINITY_DN17220_c0_g1_i1_4 6379.593263 3.929259199 0.000615911 0.00570705 0.2744919 Down UDP-glycosyltransferase UGT340C1 precursor [Bombyx mori] UGT
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In this study, the up-regulation of glycerophospholipid metabolism was consistent with Zhang’s research [21]. The up-regulation of this pathway may be related to the viral replication [39, 40]. In addition, Glycine, serine and threonine metabolism were up-regulated in this transcriptome analysis. In the study by Wu et al., two genes related to this signaling pathway were up-regulated and the other down-regulated. In our study, the expression levels of the phosphoserine phosphatase genes were significantly higher in DnCPV-23-infected midgut than in the non-infected group, suggesting that serine metabolism disorders were induced after DnCPV-23 infection. Expression of many UGT genes was up-regulated; UDP-glucuronosyltransferase (UGT) isozymes take endogenic and exogenic toxic substances as substrates, catalyze detoxification of many chemical toxins in our daily diet and environment by conjugation to glucuronic acid or glucose [41, 42]. After DnCPV-23 infection, it was speculated that the D. nerii tended to strengthen the elimination of lipophilic endobiotics such as hormones and xenobiotics including phytoalexins and drugs conjugated by invertebrates and plants mainly with glucose [42] through promoting the transcription of UGTs by regulating the activities of nuclear-receptor family (CAR, PXR, FXR, LXR, and PPAR), the arylhydrocarbon receptor [43] or ubiquitous transcription factors (FOXA1, Sp1, and Cdx2) [44]. However, the interactions between UGT and cypovirus still remain unclear. In Table 5, there were the pathways and genes mentioned above and genes expression of each sample is shown in Additional file 1.

Table 5.

The up-regulated pathways focused in the discussion section

id Term pValue Enrichment_score Gene_id BaseMean_control_mock BaseMean_case_DnCPV FoldChange pValue qValue Regulation NR annotation KEGG gene name
ko00564 Glycerophospholipid metabolism 0.00046 3.794540796 TRINITY_DN14020_c0_g1_i1_6 1066.209777 3311.867512 3.106206287 0.027085 0.610813421 Up phosphatidate phosphatase LPIN2 isoform X2 [Trichoplusia ni] LPIN
TRINITY_DN14343_c0_g2_i1_4 25.87214477 100.8782352 3.899106012 0.02501 0.591372647 Up hypothetical protein B5V51_748 [Heliothis virescens] NTE, NRE
TRINITY_DN14343_c2_g1_i1_5 1212.926019 3816.360113 3.146407986 0.018214 0.514696311 Up phosphatidate phosphatase LPIN3 isoform X1 [Bombyx mori] LPIN
TRINITY_DN2180_c0_g1_i1_3 5.852454693 49.91148246 8.528298822 0.005837 0.276535057 Up group XV phospholipase A2-like [Trichoplusia ni] LYPLA3
TRINITY_DN10250_c0_g1_i1_1 73.45139125 221.6966763 3.018277429 0.037654 0.703084732 Up group XV phospholipase A2-like [Trichoplusia ni] LYPLA3
TRINITY_DN11518_c6_g1_i1_2 52.98336083 709.749683 13.39570899 0.008188 0.337015221 Up Phosphatidylserine decarboxylase [Operophtera brumata] psd, PISD
TRINITY_DN12265_c0_g2_i1_2 21.24218102 111.7071749 5.258743197 0.006687 0.296214335 Up Neuropathy target esterase sws [Papilio xuthus] NTE, NRE
ko00260 Glycine, serine and threonine metabolism 0.00232 4.238058552 TRINITY_DN9933_c0_g1_i2_6 782.5009178 4185.641092 5.349055824 0.025238 0.593696583 Up phosphoserine phosphatase isoform X3 [Trichoplusia ni] serB, PSPH
TRINITY_DN7804_c0_g1_i1_2 11.1084935 91.01956837 8.193691462 0.032267 0.660850357 Up glucose dehydrogenase [FAD, quinone] [Bombyx mori] betA, CHDH
TRINITY_DN12220_c1_g1_i9_4 107.649078 517.8794976 4.8108122 0.00313 0.19793455 Up PREDICTED: phosphoserine phosphatase [Amyelois transitella] serB, PSPH
TRINITY_DN10934_c0_g2_i2_1 2279.078944 10,414.52625 4.569620669 0.002617 0.17866588 Up phosphoserine phosphatase isoform X1 [Bombyx mori] serB, PSPH
ko00982 Drug metabolism—cytochrome P450 0.0002 4.29382248 TRINITY_DN11538_c1_g1_i3_2 228.6892992 2097.050761 9.169868326 0.023489 0.577337157 Up hypothetical protein B5V51_11710 [Heliothis virescens] UGT
TRINITY_DN14215_c0_g5_i7_5 127.0025656 13,180.97268 103.7850898 0.020886 0.5511394 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN7938_c0_g2_i1_2 3.93470221 637.5929402 162.0435058 6.29 E−05 0.013882511 Up PREDICTED: uncharacterized protein LOC106102769 [Papilio polytes] GST, gst
TRINITY_DN13727_c0_g2_i1_5 185.9951388 4205.660038 22.61166644 0.002663 0.180041496 Up UDP-glycosyltransferase UGT340C2 [Bombyx mori] UGT
TRINITY_DN13616_c0_g3_i6_5 25.95433532 8843.383538 340.7285692 0.014481 0.449089688 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN11622_c2_g4_i1_2 0 23.44067936 Inf 0.026206 0.601380717 Up UDP-glucuronosyltransferase 2B15-like isoform X1 [Helicoverpa armigera] UGT
TRINITY_DN11402_c0_g2_i13_2 663.9094166 6959.047076 10.48192254 0.000742 0.080554531 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
ko00980 Metabolism of xenobiotics by cytochrome P450 0.00043 3.839182453 TRINITY_DN11538_c1_g1_i3_2 228.6892992 2097.050761 9.169868326 0.023489 0.577337157 Up hypothetical protein B5V51_11710 [Heliothis virescens] UGT
TRINITY_DN14215_c0_g5_i7_5 127.0025656 13,180.97268 103.7850898 0.020886 0.5511394 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN7938_c0_g2_i1_2 3.93470221 637.5929402 162.0435058 6.29 E− E−05 0.013882511 Up PREDICTED: uncharacterized protein LOC106102769 [Papilio polytes] GST, gst
TRINITY_DN13727_c0_g2_i1_5 185.9951388 4205.660038 22.61166644 0.002663 0.180041496 Up UDP-glycosyltransferase UGT340C2 [Bombyx mori] UGT
TRINITY_DN13616_c0_g3_i6_5 25.95433532 8843.383538 340.7285692 0.014481 0.449089688 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN11622_c2_g4_i1_2 0 23.44067936 Inf 0.026206 0.601380717 Up UDP-glucuronosyltransferase 2B15-like isoform X1 [Helicoverpa armigera] UGT
TRINITY_DN11402_c0_g2_i13_2 663.9094166 6959.047076 10.48192254 0.000742 0.080554531 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
ko00983 Drug metabolism—other enzymes 0.00101 3.107909605 TRINITY_DN11538_c1_g1_i3_2 228.6892992 2097.050761 9.169868326 0.023489 0.577337157 Up hypothetical protein B5V51_11710 [Heliothis virescens] UGT
TRINITY_DN14215_c0_g5_i7_5 127.0025656 13,180.97268 103.7850898 0.020886 0.5511394 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN7938_c0_g2_i1_2 3.93470221 637.5929402 162.0435058 6.29 E−05 0.013882511 Up PREDICTED: uncharacterized protein LOC106102769 [Papilio polytes] GST, gst
TRINITY_DN13727_c0_g2_i1_5 185.9951388 4205.660038 22.61166644 0.002663 0.180041496 Up UDP-glycosyltransferase UGT340C2 [Bombyx mori] UGT
TRINITY_DN11728_c0_g1_i4_2 1306.667581 6467.759766 4.949812684 0.001549 0.128973078 Up uridine phosphorylase 1 isoform X2 [Bombyx mori] udp, UPP
TRINITY_DN13616_c0_g3_i6_5 25.95433532 8843.383538 340.7285692 0.014481 0.449089688 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
TRINITY_DN11622_c2_g4_i1_2 0 23.44067936 Inf 0.026206 0.601380717 Up UDP-glucuronosyltransferase 2B15-like isoform X1 [Helicoverpa armigera] UGT
TRINITY_DN11402_c0_g2_i13_2 663.9094166 6959.047076 10.48192254 0.000742 0.080554531 Up UDP-glucuronosyltransferase 1-7C-like [Trichoplusia ni] UGT
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Conclusion

This study revealed substantial differences in the transcriptions of the D. nerii genes related to digestion, immunity, glycerophospholipid metabolism and toxic substances metabolism induced by DnCPV-23 replication. Findings obtained in this research further enriched the understanding of cypovirus-Spodoptera insect interactions in midgut and provided additional basic information for the future exploitation of DnCPV-23.

Supplementary Information

12985_2021_1721_MOESM1_ESM.xls (653KB, xls)

Additional file 1. All the different expression genes in the midgut after DnCPV-23 infection.

Acknowledgements

Thanks to the molecular experiment platform provided by the Institute of Microbiology, Jiangxi Academy of Sciences.

Abbreviations

DnCPV-23

Daphnis nerii Cypovirus-23

D. nerii

Daphnis nerii

PGRP

Peptidoglycan Recognition Protein;

CASP-8

Caspase-8

Authors' contributions

KW, YC designed and performed the experiments and analysed the data. ZZ was responsible for revising the manuscript. ZZ, GL and CJ collected Daphnis nerii larval. WJ and LJ provided suggestions. KW, YC and JL wrote the manuscript. JL, ZX, and MG supervised the project and revised the manuscript. All Authors have read and approved the final version of the manuscript.

Funding

This research was supported by the Doctoral Research Startup Project of Jiangxi Academy of Sciences (2019-XTPH1-04), the Doctoral Research Startup Fund of Jiangxi University of Traditional Chinese Medicine (2020BSZR012), the Natural Science Foundation of Jiangxi Province (20192ACB20008), the key Research and Development Project of Jiangxi Province (20192BBF60056) and the key Research and Development Project of Jiangxi Province (20202BBFL63050).

Availability of data and materials

The original data of the transcriptome will be released on 2021-10-05 or upon publicationhas, BioProject accession: PRJNA766516.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent to publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Wendong Kuang, Chenghua Yan and Zhigao Zhan have contributed equally to this work

Contributor Information

Wendong Kuang, Email: kuangwendong@163.com.

Chenghua Yan, Email: yanchenghua23@126.com.

Zhigao Zhan, Email: zgzhan_iom@163.com.

Limei Guan, Email: glmnh@126.com.

Jinchang Wang, Email: wangjinchang75@163.com.

Junhui Chen, Email: 1203854526@qq.com.

Jianghuai Li, Email: 35363052@qq.com.

Guangqiang Ma, Email: maguangqiang@163.com.

Xi Zhou, Email: zhouxi@wh.iov.cn.

Liang Jin, Email: jinliang079@163.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12985_2021_1721_MOESM1_ESM.xls (653KB, xls)

Additional file 1. All the different expression genes in the midgut after DnCPV-23 infection.

Data Availability Statement

The original data of the transcriptome will be released on 2021-10-05 or upon publicationhas, BioProject accession: PRJNA766516.

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