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. 2013 Sep;4(3):320-38.
doi: 10.3390/insects4030320.

Immune Signaling and Antimicrobial Peptide Expression in Lepidoptera

Affiliations

Immune Signaling and Antimicrobial Peptide Expression in Lepidoptera

Ángel M Casanova-Torres et al. Insects. 2013 Sep.

Abstract

Many lepidopteran insects are agricultural pests that affect stored grains, food and fiber crops. These insects have negative ecological and economic impacts since they lower crop yield, and pesticides are expensive and can have off-target effects on beneficial arthropods. A better understanding of lepidopteran immunity will aid in identifying new targets for the development of specific insect pest management compounds. A fundamental aspect of immunity, and therefore a logical target for control, is the induction of antimicrobial peptide (AMP) expression. These peptides insert into and disrupt microbial membranes, thereby promoting pathogen clearance and insect survival. Pathways leading to AMP expression have been extensively studied in the dipteran Drosophila melanogaster. However, Diptera are an important group of pollinators and pest management strategies that target their immune systems is not recommended. Recent advances have facilitated investigation of lepidopteran immunity, revealing both conserved and derived characteristics. Although the general pathways leading to AMP expression are conserved, specific components of these pathways, such as recognition proteins have diverged. In this review we highlight how such comparative immunology could aid in developing pest management strategies that are specific to agricultural insect pests.

Keywords: Lepidoptera; antimicrobial peptide; pest control; recognition; signaling.

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Figures

Figure 1
Figure 1
Toll-activating signal transduction pathways in D. melanogaster and Manduca sexta. (A) The D. melanogaster Toll pathway based on the revised model presented in Ashok 2009 [107]. MAMP/PRR-dependent or a MAMP-independent danger signal cascades can both activate Toll. (B) Current knowledge of the M. sexta Toll pathway. The M. sexta Toll pathway can be activated by MAMPs, but the specific PRRs and proteolytic cascade(s) responsible for this activation have not been reported. Known components of Spätzle-activation include the proteases HP6 and HP8, which are most closely related to the danger-pathway proteases of D. melanogaster. However, the induction of the Toll pathway by MAMP-independent signals has not been documented yet in M. sexta. Dashed lines indicate potential pathways that have not been experimentally proven in M. sexta. Orange boxes represent key differences between D. melanogaster and M. sexta Toll pathway; a red border highlights proteins or pathways not yet identified in M. sexta. Boxes with same color are for putative orthologous steps. PGRP, peptidoglycan recognition protein; GNBP, gram negative binding protein; SPE, Spätzle processing enzyme; HP, hemolymph proteinase.
Figure 2
Figure 2
Phylogenetic relationships among serine proteases involved in Toll pathway activation. Sequence alignment and tree construction were performed using the amino acid sequence of D. melanogaster (Dm) Grass (Q86PB3), SPE (NP_651168.1), Persephone (Q9VWU1) and Spätzle (NP_524526.1); M. sexta (Ms) HP6 (AAV91004.1), HP8 (AAV91006.1) and Spätzle (ACU68553.1); and B. mori (Bm) fcaL22M01 (AK384444), BAEE (H9J6N1), and Spätzle (NM_001114594). Bm serine proteases were identified by TBLASTN [120] analysis the Bm genome for homologs of Ms serine proteases. The roles of these Bm proteins in Toll pathway activation have not been shown experimentally. One thousand bootstrap repetitions were performed to estimate the reliability of the tree; the percent values obtained are indicated on the nodes. Sequence alignment was performed using Clustal Omega [121,122] bootstrapping analysis, matrix calculation, matrix transformation were conducted by the Fitch-Margoliash method and the combination of the 1,000 resulting trees was identified using the Seqboot, Protdist, Fitch and Consense programs within the Phylip phylogenetic analysis package [123]. The phylogenetic tree was constructed using Phylodendron software version 0.8d, by D.G. Gilbert [124]. The phylogenetic relationships observed are consistent with those previously published [116,119]. Colored boxes for each protein match those presented in Figure 1.

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