Transcriptomic and proteomic responses of sweetpotato whitefly, Bemisia tabaci, to thiamethoxam

Abstract

Background: The sweetpotato whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae), is one of the most widely distributed agricultural pests. Although it has developed resistance to many registered insecticides including the neonicotinoid insecticide thiamethoxam, the mechanisms that regulate the resistance are poorly understood. To understand the molecular basis of thiamethoxam resistance, "omics" analyses were carried out to examine differences between resistant and susceptible B. tabaci at both transcriptional and translational levels.

Results: A total of 1,338 mRNAs and 52 proteins were differentially expressed between resistant and susceptible B. tabaci. Among them, 11 transcripts had concurrent transcription and translation profiles. KEGG analysis mapped 318 and 35 differentially expressed genes and proteins, respectively, to 160 and 59 pathways (p<0.05). Thiamethoxam treatment activated metabolic pathways (e.g., drug metabolism), in which 118 transcripts were putatively linked to insecticide resistance, including up-regulated glutathione-S-transferase, UDP glucuronosyltransferase, glucosyl/glucuronosyl transferase, and cytochrome P450. Gene Ontology analysis placed these genes and proteins into protein complex, metabolic process, cellular process, signaling, and response to stimulus categories. Quantitative real-time PCR analysis validated "omics" response, and suggested a highly overexpressed P450, CYP6CX1, as a candidate molecular basis for the mechanistic study of thiamethoxam resistance in whiteflies. Finally, enzymatic activity assays showed elevated detoxification activities in the resistant B. tabaci.

Conclusions: This study demonstrates the applicability of high-throughput omics tools for identifying molecular candidates related to thiamethoxam resistance in an agricultural important insect pest. In addition, transcriptomic and proteomic analyses provide a solid foundation for future functional investigations into the complex molecular mechanisms governing the neonicotinoid resistance in whiteflies.

Figure 1. Differentially expressed genes between thiamethoxam resistance and susceptible B. tabaci.

(A) All 338 differentially expressed genes between the two B. tabaci strains were selected with a cutoff value of FDR≤0.001 and |log 2 Ratio|≥1. (B) The distribution of differentially expressed genes based on fold of changes.

Figure 2. Gene Ontology classification of differentially expressed genes and proteins between thiamethoxam resistance and susceptible B.

tabaci . The differentially expressed genes or proteins are grouped into three hierarchically-structured GO terms, biological process, cellular component, and molecular function. The y-axis indicates the number of genes or proteins in each GO term. (A) Differentially expressed genes identified by RNA-seq. (B) Differentially expressed proteins identified by iTRAQ.

Figure 3. Correlation between the differently expressed proteins and genes.

Scatter plots illustrates the distribution of differentially expressed proteins and related genes. The Pearson correlation coefficient between proteins and mRNA expression profiles is shown in the upper left corner of the plot.

Figure 4. Quantitative real-time PCR analysis.

The relative gene expression of selected target genes was normalized to a BestKeeper composed of endogenous reference genes EF-1a and β-actin. Standard errors were generated from the three biological replicates. Asterisks denote significant gene expression differences between resistant and susceptible B. tabaci, as determined by a paired t-tests (* p<0.05, ** p<0.01).

Figure 5. Venn diagram summarizing the proportion of proteins and genes significantly expressed between thiamethoxam resistance and susceptible B. tabaci.

Differentially expressed transcripts and peptides are represented in respective circles. The overlapping region denotes specific transcripts with their corresponding peptides.