The frozen beetles were dissected to extract their guts, which were then placed in 2 mL analytical vials containing 100 μL of cold pentane (10 guts per vial). The beetle bodies were placed in separate vials containing 1 mL of chloroform (10 beetle bodies per vial). The extracts are obtained after overnight incubation at 4°C and tissue free solvents were separated using a short centrifuge (4,000 rpm,30s) and used for injection.

A Pegasus 4D GC × GC–MS system (LECO, St. Joseph, MI, USA) employing an Agilent 7,890 B and a consumable-free modulator was used to analyze the samples. One microliter of the extract was injected into a cold PTV injector (20C) in split mode at a ratio of 1:3. After injection, the inlet was heated to 275°C at a rate of 8°C/s. Separation was conducted on an HP-5MS UI capillary column (30 m, 0.25 mm i.d., 0.25 μm film thickness, Agilent) coupled to BPX-50 (1.2 m, 0.1 mm i.d., 0.1 μm film thickness, SGE). The GC oven temperature program was as follows: 40°C for 2 min; then ramped at a rate of 10°C min⁻¹ to 200°C; then at 5°C min⁻¹ to 320°C and held for 15 min. The second-dimension oven modulator had offsets of 5°C and 15°C, respectively. The modulation period was 5 s. The total GC runtime was 57 min. Ions (ionization energy of 70 eV) were collected in the mass range of 35–500 Da at a frequency of 100 Hz.

Automated spectral deconvolution and peak-finding algorithms were applied using ChromaTOF software (LECO, St. Joseph, MI, USA). For identification of the compounds, the mass spectra and retention indexes from the National Institute of Standards and Technology (NIST, 2017) mass spectral customized library were used. In the case of fatty acid ester (oleate) was identified using a targeted search using mass spectra and retention indexes obtained from synthetic standards (Chiu et al., 2018) measured under same conditions as in our previous studies (Ramakrishnan et al., 2022a). Relative abundances were defined as the percentage of the peak area of the targeted metabolite in relation to the sum of peak areas of all peaks in the chromatogram.

The polar fraction of guts was extracted by adding methanol, water, and acetic acid in a ratio of 70/30/0.5 (v/v) at a volume of 7 mL per gut. The mixture contained ¹³C2-myristic acid (1 μg/mL) as an internal standard. The gut tissue was sonicated on ice for 5 min and disrupted using a pre-chilled Eppendorf tip. The samples were then centrifuged at 4000 RPM for 3 min, and the supernatant collected in a new vial with a 100 μL glass insert. The polar fractions of gut extracts were subjected to UHPLC-HRMS/MS analysis.

UHPLC-ESI-HRMS/MS was performed using an Ultimate 3,000 series RSLC system (Dionex) coupled to a Q-Exactive HF-X mass spectrometer (Thermo Fisher Scientific). Solvents A-water and B-acetonitrile (LiChrosolv hyper grade for LC–MS; Merck, Darmstadt, Germany), both with 0.1% v/v formic acid (eluent for LC–MS, Sigma Aldrich, Steinheim, Germany), were used for the binary solvent system. 10 μL of the extract was injected, and chromatographic separation was performed with a constant flow rate of 300 μL/min using an Acclaim C18 column (150 × 2.1 mm, 2.2 μm; Dionex, Borgenteich, Germany). Solvent gradients (B 0.5–100% v/v for 15 min; 100% B for 5 min; 100–0.5% v/v for 0.1 min; 0.5% for 5 min) were used. Ionization in the HESI ion source was achieved by 4.2 kV cone voltage, 35 V capillary voltage, and 300°C capillary temperature in the transfer tube in positive ion mode and 3.3 kV cone voltage, 35 V capillary voltage, and 320°C capillary temperature in negative mode. Mass spectra were recorded in both modes at a mass range of m/z 80–800 in duplicate. The obtained fragments with retention time values were interpreted using XCALIBUR software (Thermo Fisher Scientific, Waltham, United States; Ramakrishnan et al., 2022a,b). Metabolite samples were compared and statistically evaluated using MetaboAnalyst 4.0, and the determined masses were compared with the database (Chong et al., 2018). The amounts of three diglycosides of oxygenated monoterpenes (verbenol) were determined with mass spectra obtained from our previous work (Ramakrishnan et al., 2022b).

The beetle guts were dissected in RNAlater. Four biological replicate included three technical replicates each containing 10 pooled guts was used. Total RNA was extracted from male gut tissue samples using a pre-optimized protocol (Sellamuthu et al., 2022) and sent for sequencing with a NOVAseq6000 (PE150, 30 million raw reads) after quality determination using an agarose gel and a bioanalyzer. RNA (1 μg) was used for cDNA synthesis using the M-MLV reverse transcriptase kit following the manufacturer’s protocol and stored at −80°C for downstream analysis.

RNA-seq. Data were analyzed using CLC workbench 21.0.5 (QIAGEN Aarhus, Denmark) with a pre-optimized setting for mapping exon regions with genome reference (Naseer et al., 2023). Furthermore, sequence datasets and relative transcript expression levels were obtained using TPM values. Finally, an empirical DGE analysis was performed using the optimum parameters (Ramakrishnan et al., 2022a). Genes with a false discovery rate (FDR)-corrected value of p cut-off of <0.05 and a fold change cut-off of ± four-fold as a threshold value for being significant. Differentially expressed genes were functionally searched in a cloud BLAST using the CLC Genomic Workbench. Gene Ontology term identification was performed using three categories (biological processes, molecular functions, and cellular components), and similar names were identified from the Kyoto Encyclopedia of Genes and Genomes pathway database (Kanehisa, 2002; Kanehisa et al., 2017).

To validate the RNA seq. Data, genes were selected for qRT-PCR based on their varied expression levels. Primers were designed using IDT primer design software (Supplementary Table 4). A synthesized cDNA template was used for qRT-PCR validation using SYBR^™ Green PCR master mix (Applied Biosystems, United States) under the following parameters: 95°C for 3 min, 40 cycles of 95°C for 3 s, and 60°C for 34 s. A melting curve was generated to ensure single-product amplification and eliminate the possibility of primer dimers and nonspecific amplicons. The relative expression levels of the target genes were calculated using the 2^-ΔΔCt method with two housekeeping genes (Sellamuthu et al., 2022) as a reference for normalization with four biological replications.

Frozen beetles were dissected under on dry ice, and four biological replicates of each treatment were used for protein extraction and analysis. Each biological replicate contained tissue of three individual guts. Protein extraction was lysed in cold buffer containing 50 mm Tris–HCl, pH 7.5, 1 mM EDTA, 150 mM NaCl, 1% N-octylglycoside, and 0.1% sodium deoxycholate. Gut tissue in the buffer with protease inhibitor mixture (Roche) was incubated for 15 min on ice. Lysates were cleared by centrifugation, and after precipitation with chloroform/methanol, proteins were resuspended in 6 m urea, 2 m thiourea, 10 mm HEPES, pH 8.0 and proceeded for digestion (Cox et al., 2014).

The samples were homogenized and lysed by boiling at 95°C for 10 min in 100 mM TEAB (triethylammonium bicarbonate) containing 2% SDC (sodium deoxycholate), 40 mM chloroacetamide, and 10 mM Tris (2-carboxyethyl) phosphine, and further sonicated (Bandelin Sonoplus Mini 20, MS 1.5). The protein concentration was determined using a standard protein assay kit (Thermo Fisher Scientific). About 30 μg of protein per sample was used for MS sample preparation.

SP3 beads were used for sample processing. Five μl of SP3 beads were mixed with 30 μg protein in a lysis buffer and made up to 50 μL with TEAB (100 mM). Protein binding was induced by adding ethanol to a final concentration of 60% (vol/vol). The samples were thoroughly mixed and incubated at 24°C for 5 min. After SP3 was bound to the proteins, the tubes were placed on a magnetic rack, and the remaining unbound supernatant was discarded. Using 180 μL of 80% ethanol, beads were washed twice. After washing, samples were digested with trypsin (trypsin/protein ratio 1/30) and reconstituted in 100 mM TEAB at 37°C overnight. Digested samples were acidified with trifluoro acetic acid (TFA) to a final concentration of 1%. Finally, peptides were desalted using in-house stage tips packed with C18 disks (Empore; Rappsilber et al., 2007).

nLC–MS/MS analysis was performed with nano-reversed-phase columns (EASY-Spray column, 50 cm × 75 μm ID, PepMap C18, 2 μm particles, 100 μm pore size). In this analysis, mobile phase buffer A (0.1% formic acid in water) and mobile phase buffer B (acetonitrile and 0.1% formic acid) were used. Samples were loaded in a trap column of C18 PepMap100, 5 μm particle size, 300 μm x 5 mm from Thermo Scientific. About 4 min at 18 μL/min loading buffer with water, 2% acetonitrile, and 0.1% trifluoroacetic acid were used for loading. Peptides were eluted with a mobile phase B gradient of 4–35% over 120 min. The eluted peptide cations were converted into gas-phase ions by electrospray ionization. A Thermo Orbitrap Fusion (Q-OT-qIT, Thermo Scientific) was used for the analysis. Survey scans of peptide precursors from 350 to 1,400 m/z were performed using an Orbitrap at 120 K resolution (200 m/z) with a 5 × 10⁵ ion count target. Tandem MS was isolated at 1,5 Th using a quadrupole, HCD fragmentation with a normalized collision energy of 30, and rapid scan analysis in the ion trap. The second mass spectral ion count target was set to 10⁴, and the maximum injection time was 35 ms. Precursors with charge state 2–6 were strictly sampled. The dynamic exclusion duration was set to 30 s with a 10 ppm tolerance around the selected precursor and its isotopes. Monoisotopic precursor selection was then performed. The instrument was run in top-speed mode with 2 s cycles (Hebert et al., 2014).

All data were analyzed and quantified using MaxQuant software (version 2.0.2.0; Cox and Mann, 2008). The FDR was limited to 1% for both full proteins and small peptides. The peptide lengths of the seven amino acids are specified. An MS/MS spectral search was performed using the Andromeda search engine against the I. typographus genome database. The C-termini of Arg and Lys were set for enzyme specificity, allowing the cleavage of proline bonds with a maximum of two missed cleavages. Cysteine dithiomethylation was selected as the fixed modification. Various modifications were considered with N-N-terminal protein acetylation and methionine oxidation. Matches between the run features from MaxQuant were used to transfer the identified peaks to other LC–MS/MS systems. Runs based on masses and retention times (with a maximum deviation of 0.7 min) were also considered for quantification. A label-free MaxQuant algorithm was used for quantification (Cox et al., 2014). Data analysis was performed using Perseus 1.6.15.0 (Tyanova et al., 2016).

Extracts of the guts and bodies of male and female I. typographus beetles subjected to JHIII treatment, were compared to their respective control groups, using comprehensive two-dimensional gas chromatography.

The initial Principal Component Analysis (PCA) revealed a distinct separation of JH III treated male gut samples from control samples treated with acetone. The first two components of the PCA plot accounted for 46.5% of the variance in the data (see Figure 4A). The primary compound responsible for this separation was identified as the main I. typographus aggregation pheromone component, 2-methyl-3-buten-2-ol. Additionally, compounds such as cis-verbenol and phenylethanol (male-specific compound) also contributed to this separation. In contrast, control male guts contained only phenylethanol and trace amounts of cis-verbenol, along with traces of other compounds such as verbenone, ipsdienol, and myrtenol (refer to Supplementary Figure 1).

The relative abundance of the pheromone precursor verbenyl oleate was determined in extracts from both the guts and the bodies (including the fat body) of beetles following JH III treatment and compared to a control (see Figure 4B). In both male and female beetle body extracts, JH III topical treatment led to a significant increase (1.5x in males, 15x in females) in the levels of verbenyl oleate compared to the control group.

This trend was also observed in extracts from female guts (15x increase). However, in the gut extracts of male beetles, JH III treatment resulted in a significant decrease (1.8x decrease) in the relative abundance of verbenyl oleate compared to the control group. This decrease is likely attributable cleavage of these monoterpene conjugates to give the free pheromone cis-verbenol (refer to Figure 4B). The absolute amount of verbenyl oleate in different beetle life stadia was 250 ng/mg of beetle body weight, as previously quantified (Ramakrishnan et al., 2022a) The content of free cis-verbenol in the guts of freshly emerged beetle was 5 ng/gut, which can be compared with control beetles in this study.

Metabolic profiling of non-volatile and polar compounds in the gut tissues of JH III-treated males and females was conducted using a non-targeted analysis via UHPLC/HRMS in both positive and negative ion modes. An unsupervised multivariate PCA was employed to assess differences among the sample groups.

In both ion modes measurements, JH III-treated males and females clustered distinct from the control group. In the negative ion mode, the PC analysis explained 55 and 61.2% of the total variance in males and females, respectively, (see Figure 5A, left). In the positive ion mode, the PC explained 60 and 50% of the total variance in males and females, respectively, (see Figure 5A, right). The determination of the total abundance of verbenyl diglycosides was calculated as the sum of the peak areas from the three individual verbenyl diglycoside peaks. After treatment with JH III in beetles, the total abundance of diglycosides content significantly increased in the guts of both sexes compared to the acetone-treated controls. There was no significant difference in the induction of these compounds by JH III between males and females (see Figure 5B). The actual amount of these compounds per beetle gut could not be determined due to the lack of standards.

Overall, DGE analysis using the CLC workbench from the RNA sequence data obtained from beetle guts provided a clear distinction between gene sets in JH III-treated versus control beetles and males versus females, with samples from each group clustered together in principal component analysis (Supplementary Figure 2A). After JH III treatment, approximately 710 transcripts were upregulated, and 545 were downregulated in male gut tissue only, as depicted in a Venn diagram (Figure 6A). On the other hand, in female gut tissue only a total of 518 transcripts were upregulated, and 456 transcripts were downregulated. However, approximately 5,155 transcripts were upregulated, and 4,595 transcripts were downregulated in both male and female gut tissues. Notably, the total number of genes upregulated after treatment in the male beetle gut was higher (10,385 transcripts) than that in the female beetles (9,682 transcripts; Figure 6A; Supplementary Table 1).

The results of the DPE analysis of JH III-treated beetle gut tissue yielded a comprehensive list of identified proteins exhibiting a significant fold change in their expression following treatment. Samples from each treatment (JH III vs. control) were clustered in principal component analysis (Supplementary Figure 2B). It is noteworthy that although JH III treatment is conventionally associated with pheromone production in adult male beetles, the female beetle gut tissue exhibited a higher number of identified proteins after treatment, 449 versus 229 in males. Among the total number of upregulated proteins, 79 were male-specific, 302 were female specific and 145 were detected in both male and female guts. Among the total number of downregulated proteins, 68 proteins male specific, 69 were female specific and 27 were detected in both male and female guts (Figure 6B; Supplementary Table 2).

To narrow down the upregulated genes from male gut tissue with possible functional significance, we compared the contig lists from the DGE and DPE analyses (Figure 6C). Although the number of identified proteins was 100-fold lower than the number of transcripts from the DGE analysis, the results of the comparison helped identify a unique set of gene contigs for further evaluation. The male gut tissue had 129 contigs from transcript and protein analysis, names are provided in Supplementary Table 3A. The key mevalonate pathway gene Ityp09271, isoprenyl-diphosphate synthase (IPDS) gene (functionally proposed for 2-methyl-3-buten-2-ol synthesis), was among the highly upregulated gene contigs. Other mevalonate pathway genes such as Ityp06045 phosphomevalonate kinase (PMK), Ityp09137, 3-hydroxy-3methyl glutaryl Co-A synthase (HMG-S), and Ityp04875, isopentenyl-di-phosphate isomerase (IPPI) were also upregulated at the gene transcript level. A similar pattern was seen for the contigs involved in hydrolase function (listed in the table as myrosinase), which are known to have a functional role for glycosyl hydrolase activity, acting on glycosyl bonds (GO:0016798), and transferase contigs, such as acetyltransferase and UDP-glucuronosyltransferase (highlighted in Supplementary Table 3A). Many ribosomal and membrane transporter contigs, such as V-type ATPases, were also upregulated, while several genes that have an unknown function were identified among the male-specific upregulated gene contigs (Supplementary Table 3A).

The female gut tissue had approximately 183 contigs from transcripts and protein analysis (Figure 6C; Supplementary Table 3B). Although the number identified in females was higher than that in males, mevalonate pathway genes were not predominant in the list of identified contigs in females. However, another geranyl-diphosphate synthase (Ityp17861) was upregulated. Furthermore, gene families, such as glycine dehydrogenase, ubiquitin carboxyl-terminal hydrolase, and vitellogenin-like, with functions likely in detoxification and oocyte formation, were found to be upregulated (Supplementary Table 3B). Similar to males, many genes related to mitochondria-related ribosomal proteins, elongation factors, binding proteins, and many functionally unknown genes and proteins were also found to be upregulated (Supplementary Table 3B).

Combining gene and protein expression with qRT-PCR allowed a more comprehensive overview of the effect of JHIII treatment and sex on the steps of the mevalonate pathway, which makes the I. typographus aggregation pheromones and pheromone precursors de novo. Information was obtained for the upregulation of the following genes by RNA-Seq and qRT-PCR: PMK (Ityp06045), HMG-S (Ityp09137), HMG-R (Ityp17150), IPPI (Ityp04875), and IPDS (Ityp09271; Figure 7A). Not all of these steps were identified at the protein level, but analysis revealed the upregulation of HMG-S, IPPI, and IPDS. Notably, we found that the IPDS gene was upregulated by up to 35-fold in male gut tissue compared with that in female gut tissue after JH III treatment (Figure 7B). Besides the IPDS gene, HMG-S was also significantly upregulated in JH III treated male gut tissue compared with that in treated females (Figure 7B). Additionally, we also found that IPPI was exclusively abundant in proteins from female gut tissue after treatment (Supplementary Figure 3).

A similar combined approach was taken to explore the regulation of CyP450 genes that are involved in pheromone biosynthesis by RNA-Seq and qRT-PCR; no proteins of this family were detected in our proteomic investigation. CyP450 contigs showing expression patterns above a 2-fold change with a significant value of p (p < 0.05) were confirmed by qRT-PCR analysis. Among the contigs previously proposed to be involved in pheromone biosynthesis (Ramakrishnan et al., 2022a), contigs Ityp3903 and Ityp0496 (proposed for verbenol synthesis), contigs Ityp3140 (proposed for detoxification), and Ityp3153 (proposed for ipsdienol) were all found to be upregulated genes in the JH III-treated male gut and are among the most highly upregulated genes measured in this study (Figure 8).

Among the esterase genes proposed for converting the stored verbenyl ester to cis-verbenol, Ityp11977 (which occurred in the early life stage) was not significantly influenced by JH III treatment in males according to transcriptome and proteome analysis. However, another esterase contig, Ityp09460, was found to be upregulated in the protein analysis and qRT-PCR but downregulated in the RNA-Seq. transcriptome (Figure 9A). In female gut tissue, none of these contigs were detected, except for Ityp11977 in qRT-PCR (Figure 9B).

When comparing DGE and DPE analyses in male gut tissue, a set of gene families known for glycosyl-hydrolase function (GO:0016798) was significantly upregulated after JHIII treatment at both the transcript and protein levels with male specificity. This gene family nearly as abundant as the genes of the mevalonate pathway, may cleave stored verbenyl glucoside conjugates to give the free pheromone. Twelve gene contigs were detected from the family, four of which were also detected and significantly upregulated at the protein level, Ityp11770, Ityp00535, Ityp00943, and Ityp04256. These were also upregulated by qRT-PCR except for contig Ityp11770 (Figure 10A). All three contigs were more upregulated in males than in females (Figure 10B); for females, DGE, DPE, and qRT-PCR did not show consistent upregulation after JHIII treatment (Figure 10B; Supplementary Figure 4).