No abstract

The fat body, a multifunctional organ analogous to the liver and fat tissue of vertebrates, plays an important role in insect life cycles. The fat body is involved in protein storage, energy metabolism, elimination of xenobiotics, and production of immunity regulator-like proteins. However, the molecular mechanism of the fat body’s physiological functions in the tephritid stem gall-forming fly, Procecidochares utilis, are still unknown. In this study, we performed transcriptome analysis of the fat body of P. utilis using Illumina sequencing technology. In total, 3.71 G of clean reads were obtained and assembled into 30,559 unigenes, with an average length of 539 bp. Among those unigenes, 21,439 (70.16%) were annotated based on sequence similarity to proteins in NCBI’s non-redundant protein sequence database (Nr). Sequences were also compared to NCBI’s non-redundant nucleotide sequence database (Nt), a manually curated and reviewed protein sequence database (SwissProt), and KEGG and gene ontology annotations were applied to better understand the functions of these unigenes. A comparative analysis was performed to identify unigenes related to detoxification, immunity and energy metabolism. Many unigenes involved in detoxification were identified, including 50 unigenes of putative cytochrome P450s (P450s), 18 of glutathione S-transferases (GSTs), 35 of carboxylesterases (CarEs) and 26 of ATP-binding cassette (ABC) transporters. Many unigenes related to immunity were identified, including 17 putative serpin genes, five peptidoglycan recognition proteins (PGRPs) and four lysozyme genes. In addition, unigenes potentially involved in energy metabolism, including 18 lipase genes, five fatty acid synthase (FAS) genes and six elongases of very long chain fatty acid (ELOVL) genes, were identified. This transcriptome improves our genetic understanding of P. utilis and the identification of a numerous transcripts in the fat body of P. utilis offer a series of valuable molecular resources for future studies on the functions of these genes.

Eocanthecona furcellata Wolff (Hemiptera: Pentatomidae) is a native generalist predator which attacks and kills its prey by first inserting its stylet into the prey's body and then injecting saliva into it. Here, we describe the histology and ultrastructure of its salivary glands. The study showed that the salivary glands were made up of pairs of principal and tubular accessory salivary glands. The principal salivary glands were bilobed and consisted of a smaller anterior lobe and a larger elongated posterior lobe. The ducts of the principal and accessory salivary glands were located in a narrow region between the anterior and posterior lobe known as the hilum. The principal salivary gland was lined with a single‐layered epithelium. The cells cytoplasm was enriched with rough endoplasmic reticulum and secretory, and the nucleus showed a higher level of uncondensed chromatin. The basal region of the cell had plasma membrane infoldings. The cytoplasm of the accessory gland was rich in rough endoplasmic reticulum and many large cavities. The ducts of the principal salivary gland were made up of a single layer of flattened cells which had a thin cuticle lining the apical portion. Variation in the lumen content of the different lobes, which made up the principal gland suggested that their chemical products also varied. These results indicate that these two salivary glands produce the proteins found in the saliva.

A b s t r a c t A r t i c l e I n f oA novel technology for rapid identification of Machilus Nees species using the visiblenear infrared spectrum (300-1100 nm) is described in this study. The reflectivities of new leaves of seedlings from 9 species of the genus Machilus Nees were collected. Stepwise discriminant analysis was applied to the spectral information of the leaves, and 18 unique bands were selected from 126 bands total. After obtaining the spectral information for the unique bands, the Bayesian discriminant method was applied to establish the discriminant analysis model for Machilus Nees species. According to the discrimination model, combinations of 6, 12, and 18 unique bands were selected, and the discrimination accuracies of 180 training samples reached 76.111%, 83.889%, and 93.889%, respectively, while the accuracies of 90 testing samples were 77.778%, 84.444%, and 95.556%, respectively. These results validated the discrimination model for Machilus Nees species constructed from the spectral information of 18 selected unique bands. The application of visible-near infrared spectrum technology combined with discriminant analysis could provide a novel approach for the rapid and accurate identification of Machilus Nees species.