INTERNATIONAL JOURNAL FOR PARASITOLOGY
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2021
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IF 3.981
Wenfeng Li,Yi Zhang,Hui Peng,Ruonan Zhang,Zhengwei Wang,Zachary Y. Huang,Yan Ping Chen,Richou Han
Honey bees ( Apis ) are important pollinators for food crops and wild plants, but are facing great threats from pathogens and parasites, especially an obligate ectoparasitic mite, Varroa destructor . Cell invasion is a key step for V. destructor to reproduce, and the parasite displays remarkable host preference in this process. Varroa destructor made its host-shift from its original host, the Asian honey bee Apis cerana, to the new host, the European honey bee Apis mellifera several decades ago. However, it remains largely unstudied whether V. destructor shows a cell invasion preference between the two host species. Using cell invasion bioassays on a modified four-well arena, we showed that V. destructor significantly preferred to invade the worker and drone larvae of A. mellifera rather than A. cerana , suggesting that the new host is much more attractive to the parasite than the original one. Using gas chromatography-mass spectrometry (GC-MS), we revealed significant differences between the cuticular hydrocarbon (CHC) profiles of worker and drone larvae of the two bee hosts. The amounts of methyl-branched alkanes and alkenes (unsaturated CHCs), but not n -alkanes, were significantly different, and A. mellifera worker and drone larvae were found to express significantly higher amounts of methyl-alkanes, while A. cerana larvae produced higher amounts of alkenes. Cell invasion bioassays with glass dummies showed that the mites preferred the glass dummies coated with the CHCs of A. mellifera worker or drone larvae, which indicates a role of larval CHCs in mediating the preferential cell invasion of Varroa . The findings from this study extend our understanding of the host preference of V. destructor , and can potentially contribute to the development of effective strategies for mite control.
研究领域:
昆虫学
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化学生态学
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DOI
PubMed
高影响因子
Scientific Reports
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2017
·Vol. 7
·期 1
·1-10
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IF 4.259
Dong Shihao,Wen Ping,Zhang Qi,Li Xinyu,Tan Ken,Nieh James
In highly social bees, queen mandibular pheromone (QMP) is vital for colony life. Both Apis cerana (Ac ) and Apis mellifera (Am ) share an evolutionarily conserved set of QMP compounds: ( E )-9-oxodec-2-enoic acid (9-ODA), ( E )-9-hydroxydec-2-enoic acid (9-HDA), ( E )-10-hydroxy-dec-2-enoic acid (10-HDA), 10-hydroxy-decanoic acid (10-HDAA), and methyl p –hydroxybenzoate (HOB) found at similar levels. However, evidence suggests there may be species-specific sensitivity differences to QMP compounds because Ac workers have higher levels of ovarian activation than Am workers. Using electroantennograms, we found species-specific sensitivity differences for a blend of the major QMP compounds and three individual compounds (9-HDA, 10-HDAA, and 10-HDA). As predicted, Am was more sensitive than Ac in all cases (1.3- to 2.7- fold higher responses). There were also species differences in worker retinue attraction to three compounds (9-HDA, HOB, and 10-HDA). In all significantly different cases, Am workers were 4.5- to 6.2-fold more strongly attracted than Ac workers were. Thus, Ac workers responded less strongly to QMP than Am workers, and 9-HDA and 10-HDA consistently elicited stronger antennal and retinue formation responses.
研究领域:
昆虫学
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动物行为学
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化学生态学
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产品关联
DOI
PubMed
高影响因子
ACS Omega
·
2023
·
IF 4.1
Angxin Tong,Xiaojun Tang,Haibin Liu,Honghu Gao,Xiaofei Kou,Qiang Zhang
The aim of this study is to enhance the classification performance of the back-propagation-artificial neural network (BP-ANN) algorithm for NaCl, NaOH, β-phenylethylamine (PEA), and their mixture, as well as to avoid the defects of the artificial bee colony (ABC) algorithm such as prematurity and local optimization. In this paper, a method that combined an improved adaptive artificial bee colony (IAABC) algorithm and BP-ANN algorithm was proposed. This method improved the ABC algorithm by adding an adaptive local search factor and mutation factor; meanwhile, it can enhance the abilities of the global optimization and local search of the ABC algorithm and avoid prematurity. The extracted score vectors of the principal component of the ultraviolet (UV) spectrum were used as the input variable of the BP-ANN algorithm. The IAABC algorithm was used to optimize the weight and threshold of the BP-ANN algorithm, and the iterative algorithm was repeated until the output accuracy was reached. The output variable was the classification results of NaCl, NaOH, PEA, and the mixture. Meanwhile, the proposed IAABC-BP-ANN algorithm was compared with discriminant analysis (DA), sigmaid-support vector machine (SVM), radial basis function-SVM (RBF-SVM), BP-ANN, and ABC-BP-ANN. Then, the above algorithms were used to classify NaCl, NaOH, PEA, and the mixture, respectively. In the experiment, four indicators, accuracy, recall, precision, and F-score, were used as the evaluation criteria. In addition, the regression equation parameters of the mixture for the testing set were obtained by BP-ANN, ABC-BP-ANN, and IAABC-BP-ANN models. All of the results showed that IAABC-BP-ANN exhibits better performance than other algorithms. Therefore, IAABC-BP-ANN combined with UV spectroscopy is a potential identification tool for the detection of NaCl, NaOH, PEA, and the mixture.
研究领域:
化学信息学
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分析化学
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产品关联
DOI
PubMed
高影响因子
iScience
·
2022
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IF 6.107
Wenxin Zhang,Liangliang Wang,Yinjiao Zhao,Yufei Wang,Chaoyang Chen,Yu Hu,Yuanxiang Zhu,Hao Sun,Ying Cheng,Qinmiao Sun,Jian Zhang,Dahua Chen
Summary The honeybee ( Apis mellifera ) is a well-known eusocial insect. In honeybee colonies, thousands of sterile workers, including nurse and forager bees, perform various tasks within or outside the hive, respectively. The queen is the only fertile female and is responsible for reproduction. The queen and workers share similar genomes but occupy different caste statuses. We established single-cell transcriptomic atlases of brains from queens and worker subcastes and identified five major cell groups: Kenyon, optic lobe, olfactory projection, glial, and hemocyte cells. By dividing Kenyon and glial cells into multiple subtypes based on credible markers, we observed that vitellogenin ( vg ) was highly expressed in specific glial-cell subtypes in brains of queens. Knockdown of vg at the early larval stage significantly suppressed the development into adult queens. We demonstrate vg expression as a "molecular signature" for the queen caste and suggest involvement of vg in regulating caste differentiation.
研究领域:
昆虫学
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分子生物学
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神经科学
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产品关联
DOI
PubMed
高影响因子
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