Laojun Sedthapong, Changbunjong Tanasak, Sumruayphol Suchada, Chaiphongpachara Tanawat
Department of Public Health and Health Promotion, College of Allied Health Sciences, Suan Sunandha Rajabhat University, Samut Songkhram 75000, Thailand.
Department of Pre-Clinic and Applied Animal Science, Faculty of Veterinary Science, Mahidol University, Nakhon Pathom 73170, Thailand; The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals (MoZWE), Faculty of Veterinary Science, Mahidol University, Nakhon Pathom 73170, Thailand.
Acta Trop. 2024 Feb;250:107093. doi: 10.1016/j.actatropica.2023.107093. Epub 2023 Dec 14.
Recent studies have revealed taxonomic signals within the wing cells of certain mosquito species. In our study, wing cell differentiation among mosquito vectors from the Tanaosri mountain range in Thailand was evaluated using the outline-based geometric morphometric (GM) approach. Our focus was on four specific wing cells for GM analysis: the wing contour (external cell), the second submarginal cell (internal cell 1), the first posterior cell (internal cell 2), and the third posterior cell (internal cell 3). Before proceeding with the GM approach, the identity of seven mosquito genera and 21 species was confirmed using molecular techniques. Our validated classification tests demonstrated that the performance of mosquito species classification varies according to genus. Notably, three Aedes species exhibited the highest accuracy for both internal cell 2 and internal cell 3, each registering a score of 93.20 %. In the case of two Mansonia species, the wing contour displayed a remarkable accuracy of 98.57 %. Consequently, we suggest the use of the outline-based GM approach, particularly focusing on the wing contour, for differentiating Mansonia annulifera and Mansonia uniformis. In contrast, the highest accuracy for classifying Culex species was found in internal cell 1, at 75.51 %, highlighting the challenges due to similarities in wing cells within this genus. These findings provide a guideline for future applications of the outline-based GM approach, focusing on wing cells, as an alternative method to classify mosquito vector species.
最近的研究揭示了某些蚊种翅细胞内的分类信号。在我们的研究中，使用基于轮廓的几何形态测量（GM）方法评估了泰国塔纳奥斯里山脉蚊虫媒介的翅细胞分化。我们的重点是用于GM分析的四个特定翅细胞：翅轮廓（外部细胞）、第二亚缘细胞（内部细胞1）、第一后缘细胞（内部细胞2）和第三后缘细胞（内部细胞3）。在采用GM方法之前，使用分子技术确认了七个蚊属和21个蚊种的身份。我们经过验证的分类测试表明，蚊种分类的性能因属而异。值得注意的是，三种伊蚊对内部细胞2和内部细胞3的分类准确率最高，均达到93.20%。对于两种曼蚊属蚊虫，翅轮廓的分类准确率高达98.57%。因此，我们建议使用基于轮廓的GM方法，特别是关注翅轮廓，来区分环纹曼蚊和纯色曼蚊。相比之下，库蚊属蚊虫分类的最高准确率出现在内部细胞1，为75.51%，这凸显了该属内翅细胞相似性带来的挑战。这些发现为基于轮廓的GM方法未来在翅细胞方面的应用提供了指导，作为一种分类蚊虫媒介物种的替代方法。
