Jianyang Bai1, Zhe Xu1, Lu Li1, Wei Ma2, Letian Xu3, Ling Ma1,4. 1. Department of Forest Protection, College of Forestry, Northeast Forestry University, Harbin, China. 2. College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, China. 3. State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China. 4. Forest Protection Technology Innovation Center, Harbin, China.
Abstract
BACKGROUND: Lymantria dispar is an economically impactful forest pest worldwide. The entomopathogenic fungi Beauveria bassiana shows great promise in pest management due to its high lethality in Lymantria dispar. A complete understanding of the immune interactions between the pest and the pathogenic fungus is essential to actualizing biological pest management. RESULTS: Following the infection of Lymantria dispar by Beauveria bassiana spores, we performed a time-course analysis of transcriptome in Lymantria dispar fat bodies and hemocytes to explore host immune response. A total of 244 immunity-related genes including pattern recognition receptors, extracellular signal modulators, immune pathways (Toll, IMD, JNK and JAK/STAT), and response effectors were identified. We observed contrasting tissue and time-specific differences in the expression of immune genes. At the early stage of infection, several recognition receptors and effector genes were activated, while the signal modulation and effector genes were suppressed at later stages. Further enzyme activity-based assays coupled with gene expression analysis of prophenoloxidase revealed a significant upregulation of phenoloxidase activity at 48- and 72-h post-infection. Moreover, fungal infection led to dysbiosis in gut microbiota that seems to be partially attributed to reduced gut hydrogen peroxide (H2 O2 ) amount, which indicates a significant impact of fungal infection on host gut microbes. CONCLUSION: Our study provides a comprehensive sequence resource and crucial new insights about an economically important forest pest. Specifically, we elucidate the complicated multipartite interaction between host and fungal pathogen and contribute to a better understanding of Lymantria dispar anti-fungal immunity, resulting in better tools for biological pest control.
BACKGROUND:Lymantria dispar is an economically impactful forest pest worldwide. The entomopathogenic fungi Beauveria bassiana shows great promise in pest management due to its high lethality in Lymantria dispar. A complete understanding of the immune interactions between the pest and the pathogenic fungus is essential to actualizing biological pest management. RESULTS: Following the infection of Lymantria dispar by Beauveria bassiana spores, we performed a time-course analysis of transcriptome in Lymantria dispar fat bodies and hemocytes to explore host immune response. A total of 244 immunity-related genes including pattern recognition receptors, extracellular signal modulators, immune pathways (Toll, IMD, JNK and JAK/STAT), and response effectors were identified. We observed contrasting tissue and time-specific differences in the expression of immune genes. At the early stage of infection, several recognition receptors and effector genes were activated, while the signal modulation and effector genes were suppressed at later stages. Further enzyme activity-based assays coupled with gene expression analysis of prophenoloxidase revealed a significant upregulation of phenoloxidase activity at 48- and 72-h post-infection. Moreover, fungal infection led to dysbiosis in gut microbiota that seems to be partially attributed to reduced gut hydrogen peroxide (H2 O2 ) amount, which indicates a significant impact of fungal infection on host gut microbes. CONCLUSION: Our study provides a comprehensive sequence resource and crucial new insights about an economically important forest pest. Specifically, we elucidate the complicated multipartite interaction between host and fungal pathogen and contribute to a better understanding of Lymantria dispar anti-fungal immunity, resulting in better tools for biological pest control.