For a start-up colony, bed bugs were supplied by Harold Harlan (Crownsville, MD, USA) and were collected in infested apartments in Vancouver (BC, Canada). The bed bug colony was maintained as previously described (52). Briefly, bed bugs were kept in the insectary of Simon Fraser University (SFU) at a temperature of ∼24°C, ambient relative humidity, and a photoperiod of 14 h light to 10 h dark. Groups of 150 bed bugs were maintained in 50-mL glass jars fitted with a square of cardboard (2 cm × 2 cm) at the bottom and a strip of cardboard (2 cm × 4 cm) diagonally across the jar. Bed bugs in separate jars were fed on the forearm of a volunteer (Regine Gries) once every month. For feeding, jars were covered with fine mesh, inverted, and pressed against the forearm so that the bed bugs could feed through the mesh.

Live bacteria (instead of isolated lipopolysaccharides, lipoteichoic acid, or peptidoglycans) were used to simultaneously elicit multiple immune responses. We selected Escherichia coli (K12/D31) and Bacillus subtilis subsp. spizizenii (ATCC 6633) because of their well-characterized immune-stimulatory properties and to establish a baseline understanding of bed bug immune responses. Future studies will then focus on pathogenic bacteria.

Escherichia coli and B. subtilis were grown in separate Lysogeny Broth (LB) (53) for 17 h at 30°C in a shaking incubator (220 revolutions per minute). Subsequently, aliquots of bacterial broth were reinoculated into fresh broth and incubated 4 h under the same conditions to reach the log phase of growth. The bacteria were then washed three times in sterile phosphate buffered saline (PBS; 0.01 M phosphate buffer, 2.7 mM potassium chloride, 0.137 M sodium chloride, pH 7.4), and were diluted in sterile defibrinated rabbit blood (void of viruses and endotoxins; Hemostat, Dixon, CA, USA) to a final concentration of ~1 × 10⁶ cells/mL. Male adult bed bugs (food-deprived >20 days) fed 1 h on defibrinated, microbe-laced (E. coli or B. subtilis) rabbit blood in a water-jacketed membrane feeder (Thermo Fisher Scientific Isotemp 2150 B14, USA) set to 37°C, with stretched out parafilm as the membrane. Control bed bugs ingested sterile blood. As both female and male immune-challenged bed bugs upregulate their immune responses, we worked with males because they pose no risk of starting a new infestation in case of their accidental escape from laboratory confinements. Fully engorged bed bugs were separated and housed in glass jars until analysis. For tissue isolation, RNA extraction and transcriptome assembly (see below), we used three (out of five) top-quality replicates, with each replicate containing five insects in treatment and control samples.

Midgut and RoB tissues (RoB = rest of the body: bodies without heads and midgut tissues) of treatment and control adult male bed bugs were dissected by hand (using fine dissection tools) 12 h after an immune challenge, and total RNA was extracted using TRizol reagent (Invitrogen) following the manufacturer’s recommendations. Midguts of bed bugs were washed three times in PCR before RNA extraction. RNA quantity and quality were assessed using Nanodrop 1000 spectrophotometer v. 3.7 (Thermo Fisher Scientific, USA), Qubit Fluorometer (Thermo Fisher Scientific, USA), gel electrophoresis, RNA ScreenTape assay (Agilent, USA), and RT-qPCR with RPL18 (internal control) (54) and CL-defensin3. Only RNA that passed this rigorous quality assessment was used for transcriptome assembly.

We created a de novo transcriptome assembly from RNA extracted from midgut and RoB tissues of male bed bugs 12 h after ingesting blood containing E. coli or B. subtilis. RNA purification, first and second strand synthesis, adaptor ligation, quantification, validation, and Illumina sequencing were all done at GENEWIZ LLC. (South Plainfield, NJ, USA).

The RNA samples were sequenced using a paired-end (PE) configuration, consisting of two 150 base pair (bp) strands. HiSeq Control Software (HCS) was used for image analysis and base calling. Raw sequence data (.bcl files) generated from Illumina HiSeq were converted into fastq files and demultiplexed with bcl2fastq 2.17 software (Illumina Inc, San Diego, CA, USA). For index sequence identification, one mismatch was allowed. After examining the quality of raw data, adapter sequences and nucleotides of poor quality were removed from sequence reads using Trimmomatic v.0.36. The trimmed reads were mapped to the reference genome available on ENSEMBL, using STAR aligner v.2.5.2b which utilizes a splice aligner to detect splice junctions and incorporates them to help align the entire read sequences to generate Binary Alignment Map (BAM) files. In the Subread package version 1.5.2, we used the ‘Counts’ feature to calculate the unique gene count. Only reads predicted to fall within exons were counted.

We used the gene hit counts table for downstream differential expression (DE) analysis, using DESeq2 (55) to compare gene expression among groups of samples. We used the Wald’s test to generate p-values and Log2 Fold Changes (Log2FC). We considered genes to be differentially expressed (DE) when adjusted p-values were < 0.05 and the overall absolute Log2FC was > 1. The data for immune transcripts were mined to evaluate their expression levels, and are reported as transcripts per million (TPM). Additional transcriptome studies on C. lectularius are accessible on VectorBase (https://vectorbase.org/vectorbase/app/search?q=cimex), providing a valuable resource for future comparative analysis.

All analyses were performed in R v.4.2.1 (56) using the Rstudio environment v. 2022.12.0 Build 353. The following packages were used: DESeq2 (57), ggplot2 (58), tidyverse (59), EnhancedVolcano (60), clusterProfiler (61), pathview (62), ggvenn (63), pheatmap (64), and RcolorBrewer (65). Gene orthologues to known D. melanogaster genes were found using the R package orthogene (66). Immune-related genes were named after Benoit et al. (2016). Gene Ontology (GO, http://geneontology.org/) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.kegg.jp/) pathway analyses were performed using the R package clusterProfiler (61). Results with P < 0.05 were considered statistically significant.

The set of genes expressed in midgut and RoB samples of male bed bugs was strikingly similar regardless of tissue type and experimental treatment, the ingestion of sterile or bacteria-laced blood. Among the three midgut sample types (midgut/control, midgut/Gr+, and midgut/Gr–), 91.9% of transcripts were shared ( Figure 1B ), with most (1.8%) of the non-shared transcripts being present in midgut/control samples. Among the three RoB sample types (RoB/control, RoB/Gr+, and RoB/Gr–), 96.6% of expressed genes were shared ( Figure 1C ). Sterile blood ingestion afforded similar effects in midgut and RoB samples, with 94.2% of transcripts being shared ( Figure 1A ), suggesting that these two tissue types have similar transcribed genes. In contrast, levels of gene expression markedly differed between midgut and RoB samples irrespective of treatment ( Figure 1D ), as revealed by principal component analysis (PCA), where the two main PCA axes explained 93% of variations. Control samples (obtained from bed bugs that ingested sterile blood) were better separated from treatment samples (obtained from bed bugs that ingested bacteria-laced blood) in midgut tissues than in RoB tissues ( Figure 1D ).

Genes with an adjusted p-value of <0.05, and an overall absolute log2FC >1, were considered DE genes for all comparisons, and are listed in Supplementary Table S2 . Figure 2 and Supplementary Table S3 display volcano plots for significant DE genes in various pairwise comparisons. Top-30 highly up-regulated genes in each of the comparisons are discussed below.

The number of immune-related DE genes found in pairwise sample comparisons are summarized in Table 1 , and all immune-related DE genes are reported in Supplementary Table S4 . Most DE genes, particularly up-regulated DE genes, were found in pairwise comparisons of midgut and RoB samples ( Table 1 ; bottom three rows). Numbers and proportions of DE genes in control sample comparisons (RoB/control vs. midgut/control) differed from those of treatment vs. control sample comparisons. Particularly, in sample comparisons of RoB/control and midgut/Gr+, and RoB/control and midgut/Gr–, only 7% and 13% of DE genes, respectively, were down-regulated ( Table 1 ). To further elucidate the roles of DE genes in immunological responses, we focused on specific effector molecules and immune pathways.

We analyzed enriched GO and KEGG (Kyoto Encyclopedia of Genes & Genomes) terms in all pairwise comparisons ( Figures 5 , 6 ). There were enriched GO terms in midgut/Gr+ and midgut/Gr– samples relative to midgut/controls ( Figures 5A–D ), and in RoB/Gr– samples relative to RoB/controls ( Figures 5E, F ) and other comparisons ( Supplementary Table S5 ). No significantly suppressed GO terms were found in RoB/Gr+ samples relative to RoB/controls. In the midgut, striking parallels emerged in response to both Gr+ and Gr– bacteria ( Figures 5A–D ). Key cellular and molecular pathways displayed consistent modulation, emphasizing the possibility of conserved immune responses in these insects. Terms associated with core cellular machinery like ‘Endomembrane system’ and ‘RNA processing’, along with different metabolics, such as ‘Cellular nitrogen compound metabolic process’, were ubiquitously up-regulated regardless of the type of bacteria ( Figure 5 ). Conversely, structural components of the cell, including ‘Cilium movement’ and ‘Cilium-dependent cell motility’, were consistently down-regulated ( Figures 5A, C ).

In RoB/Gr– samples, several pathways and terms predominantly associated with lipid dynamics and cellular secretions, such as ‘Cytoplasm’, ‘Endomembrane system’, and ‘Fatty acid biosynthesis’, were uniformly up-regulated in the wake of exposure to Gr– bacteria ( Figures 5E, F ). The enrichment map for the midgut shows three main GO clusters related to protein localization, protein metabolism, and various hydrolase activities ( Supplementary Figure S1 ). Up-regulated and down-regulated GO terms associated with other comparisons, such as midgut/control vs. RoB/control, midgut/Gr– vs. RoB/Gr–, and midgut/Gr+ vs. RoB/Gr+, are represented in Supplementary Table S5 . There were no enriched GO terms in comparisons of RoB/Gr+ vs. RoB/Gr– samples.

KEGG-enriched pathways are illustrated in Figure 6 and in Supplementary Figures S1 , S2 . After bed bugs ingested Gr+ or Gr– bacteria, overlapping response patterns emerged in the midgut. Notably, several pathways related to core cellular functions, protein turnover, and metabolism, such as ‘protein processing in the endoplasmic reticulum’, ‘ribosome biogenesis in eukaryotes’, ‘N-Glycan biosynthesis’, ‘Protein export’ and fatty acid-related pathways were consistently up-regulated after exposure to both types of bacteria ( Figures 6A–D ). This overlap in response to bacteria exposure indicates heightened cellular activity, especially concerning protein synthesis and modification. Conversely, pathways associated with ‘purine metabolism’, ‘longevity-associated pathways’, and ‘arginine and proline metabolism’ were commonly down-regulated in response to ingested bacteria ( Figure 6 ). Metabolic pathways centered around amino acids were either up- or down-regulated depending on the specific role of the pathway and the type of bacteria.

Ingestion of Gr+ or Gr– bacteria caused upregulation of genes in the RoB related to metabolism, protein processing, and transport, such as ‘metabolic pathways’, ‘protein processing in endoplasmic reticulum’, ‘fatty acid metabolism’, and ‘fatty acid biosynthesis’ ( Figures 6E–H ). Conversely, in the RoB, ‘longevity regulating pathway’ was down-regulated in response to both types of bacteria ( Figures 6E–H ). The enrichment map for the midgut and RoB is represented in Supplementary Figure S2 . KEGG pathway plots were also assessed in these comparisons ( Supplementary Table S5 ): midgut control vs. RoB control; midgut/Gr– vs. RoB/Gr–; midgut/Gr+ vs. RoB/Gr+; and midgut/Gr+ vs. midgut/Gr–. Notably, no enriched pathways were identified in comparisons of RoB samples (RoB/Gr+ vs. RoB/Gr–). These comprehensive pathway analyses unveil a multi-faceted, and possibly conserved, response strategy in the bed bugs’ midgut and RoB when challenged with our test bacteria, implying an intricate balance of metabolic and cellular adaptations to mediate immune responses.

Our study reveals a metabolic pivot in immune-challenged bed bugs, and substantiates similar phenomena reported in other insect studies (49, 51). When bed bugs ingested bacteria-laced blood, GO and KEGG terms related to metabolic pathways changed significantly. For example, longevity-associated pathways in the midgut were down-regulated irrespective of the type of bacteria used and other metabolic processes increased, including fatty acid biosynthesis and metabolism. The longevity-associated pathways that were down-regulated are often part of insulin/insulin-like growth factor signaling (IIS) and Target of Rapamycin (TOR) mechanisms, particularly in model organisms like D. melanogaster (90–93). These systems generally govern growth, development, and lifespan, and typically are down-regulated during infections to conserve energy for immunological defenses (90–93). Furthermore, the activation of the immune system often enhances the production of phospholipids in the endoplasmic reticulum, an organelle fundamental to the synthesis and secretion of antimicrobial peptides (51). This shift in lipid metabolism serves to support immune responses (51). Our findings support the observed metabolic responses to infections reported across insect species. Our data further highlight the critical role of the bed bugs’ midgut as an immune-related organ (69, 86, 94).

This is the first whole-transcriptome study on bed bugs in response to ingestion of sterile and bacteria-laced blood. Our data show that ingestion of blood infected with Gr+ or Gr– bacteria triggers a strong innate immune response in both the bed bugs’ midgut and RoB tissue. The midgut is the primary tissue that deals with incoming blood meals, and produces and secretes most of the digestive enzymes. It is the first site of digestion and the first site of defense against ingested pathogens. The fat body, on the other hand, is involved in nutrient storage, synthesis and transport of biomolecules, vitellogenesis, and the detoxification of dietary metabolites (49, 86, 95). The fat body is also the main immune organ in insects, producing AMPs and regulating cellular and humoral immune responses (49, 86, 95).

In our study, the immune responses in the bed bugs’ midgut and RoB differed, probably related to the mode of bacterial entry into the insects. When bed bugs ingested sterile blood, the midgut had higher transcription levels of AMP-related genes than the RoB. When bed bugs ingested bacteria-infected blood, immune-related genes were strongly up-regulated in both the midgut and RoB, but there were more DE genes in midgut than in RoB samples. Moreover, ingestion of Gr– bacteria produced more DE genes in both tissue types than ingestion of Gr+ bacteria. All data combined suggest that the midgut is more responsive to blood-fed bacterial infection than the RoB and presents a stronger basal barrier to blood feeding-related infections. In particular, intake of blood with Gr+ or Gr– bacteria triggered both Toll and Imd pathways, and prompted the production of AMPs such as defensins and prolixicins. Particularly noteworthy, the Caspar gene – which inhibits immune responses – was down-regulated in response to both kinds of bacterial infection tested. Down-regulation of Caspar affords increased resistance to bacterial infections in bed bug hemocytes (96).

Our results complement previous findings obtained with male bed bugs (94) that Gr+ bacteria trigger more sustained AMP expression than Gr– bacteria. Our results also show that Toll and Imd pathways are activated by B. subtilis and E. coli, indicating cross-talk and cross-activation of the main innate immune pathways in bed bugs. In each comparison between tissue types and treatment conditions, whether the blood ingested was sterile or bacteria-infected, a considerable portion of the most DE genes remained unidentified and uncharacterized. This lack of identification of many transcripts is common in transcriptome studies; the sialome of bed bugs features a high concentration of as-yet unidentified proteins (31). Collectively, these unidentified genes and proteins represent an intriguing area for future scientific exploration. Furthermore, whereas our study reveals the immune response 12 h post infection, further investigations at additional time points are needed to understand immune responses over time.

In conclusion, our transcriptomic analyses have shed light on the intricate interplay between midgut and RoB tissues of male bed bugs after ingestion of Gr– and Gr+ bacteria. We observed a high degree of shared gene expressions but also found distinct differences, notably in immune-related genes and metabolic pathways. These expression changes imply a multi-faceted strategy for immune defense, energy conservation, and resource reallocation, underscoring the complex physiology of bed bugs in response to pathogens. Basal expression levels of immune-related genes were higher in the midgut than in RoB tissues of male bed bugs, and ingestion of bacteria further activated their innate immune responses. This activation involves intricate cross-talk between and among various immune pathways. This study expands our current understanding of the bed bugs’ responses to pathogens and emphasizes the need to identify and characterize the numerous unidentified DE genes that are activated in response to the ingestion of bacteria. These unidentified genes and proteins present exciting new avenues for future research and may help clarify why bed bugs are the only major blood-feeding pest of humans that is not responsible for the transmission of vector borne parasites and pathogens and the diseases they cause.