Analysis of the Gynaephora qinghaiensis pupae immune transcriptome in response to parasitization by Thektogaster sp

Multi-Omic Identification of Venom Proteins Collected from Artificial Hosts of a Parasitoid Wasp

Habrobracon hebetor is a parasitoid wasp capable of infesting many lepidopteran larvae. It uses venom proteins to immobilize host larvae and prevent host larval development, thus playing an important role in the biocontrol of lepidopteran pests. To identify and characterize its venom proteins, we developed a novel venom collection method using an artificial host (ACV), i.e., encapsulated amino acid solution in paraffin membrane, allowing parasitoid wasps to inject venom. We performed protein full mass spectrometry analysis of putative venom proteins collected from ACV and venom reservoirs (VRs) (control). To verify the accuracy of proteomic data, we also collected venom glands (VGs), Dufour's glands (DGs) and ovaries (OVs), and performed transcriptome analysis. In this paper, we identified 204 proteins in ACV via proteomic analysis; compared ACV putative venom proteins with those identified in VG, VR, and DG via proteome and transcriptome approaches; and verified a set of them using quantitative real-time polymerase chain reaction. Finally, 201 ACV proteins were identified as potential venom proteins. In addition, we screened 152 and 148 putative venom proteins identified in the VG transcriptome and the VR proteome against those in ACV, and found only 26 and 25 putative venom proteins, respectively, were overlapped with those in ACV. Altogether, our data suggest proteome analysis of ACV in combination with proteome-transcriptome analysis of other organs/tissues will provide the most comprehensive identification of true venom proteins in parasitoid wasps.

Antibiotics accelerate growth at the expense of immunity

Antibiotics have long been used in the raising of animals for agricultural, industrial or laboratory use. The use of subtherapeutic doses in diets of terrestrial and aquatic animals to promote growth is common and highly debated. Despite their vast application in animal husbandry, knowledge about the mechanisms behind growth promotion is minimal, particularly at the molecular level. Evidence from evolutionary research shows that immunocompetence is resource-limited, and hence expected to trade off with other resource-demanding processes, such as growth. Here, we ask if accelerated growth caused by antibiotics can be explained by genome-wide trade-offs between growth and costly immunocompetence. We explored this idea by injecting broad-spectrum antibiotics into wood tiger moth (Arctia plantaginis) larvae during development. We follow several life-history traits and analyse gene expression (RNA-seq) and bacterial (r16S) profiles. Moths treated with antibiotics show a substantial depletion of bacterial taxa, faster growth rate, a significant downregulation of genes involved in immunity and significant upregulation of growth-related genes. These results suggest that the presence of antibiotics may aid in up-keeping the immune system. Hence, by reducing the resource load of this costly process, bodily resources may be reallocated to other key processes such as growth.

Genetic Diversity and Population Structure of Gynaephora qinghaiensis in Yushu Prefecture, Qinghai Province Based on the Mitochondrial COI Gene

Gynaephora qinghaiensis (Lepidoptera: Lymantriidae: Gynaephora), a serious economic pest in alpine meadows, is mainly distributed in Yushu prefecture, Qinghai province, China. In this study, we aimed to investigate the genetic diversity and population structure of G. qinghaiensis through analyzing the sequence of 194 mitochondrial cytochrome oxidase subunit (COI) genes (658 bp in length) identified from 10 geographic populations located in three different countries, including Zhiduo, Zaduo, and Chengduo, of Yushu prefecture. Eleven haplotypes were identified from all populations of G. qinghaiensis with high levels of haplotype diversity (0.78500) and low levels of nucleotide diversity (0.00511). High levels of genetic differentiation and low levels of gene flow were also detected among the populations of G. qinghaiensis. Analysis of molecular variance (AMOVA) showed that 90.13% of the variation was attributed to distribution among groups (Chengduo, Zhiduo, and Zaduo), and 5.22% and 4.65% were, respectively, attributed to distribution among populations, within group, and within populations. The result of mantel test showed a highly significant positive correlation (P < 0.01) between F_ST and geographical distance. A maximum likelihood tree showed that most haplotypes were grouped into three clusters corresponding to the three counties, suggesting a significant phylogeographic structure in the populations of G. qinghaiensis. The haplotype networks revealed that H2 may be the most primitive haplotype and the most adaptable in nature. Populations 7# and 8# had haplotype H2 and higher haplotype diversity; therefore, we speculated that the G. qinghaiensis in both populations were more adaptable to the environment and had greater outbreak potential and, therefore, should be focused on in terms of prevention and control. Our findings provide valuable information for further study of the population structure and phylogeny of G. qinghaiensis and provide a theoretical basis for the control of G. qinghaiensis.