Campos Túlio L, Korhonen Pasi K, Young Neil D, Chang Bill C H, Gasser Robin B
Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia.
Núcleo de Bioinformática, Instituto Aggeu Magalhães, Fiocruz., Av. Professor Moraes Rego, s/n, Cidade Universitária, Recife, PE CEP 50740-465, Brazil.
Comput Struct Biotechnol J. 2024 Aug 2;23:3081-3089. doi: 10.1016/j.csbj.2024.07.025. eCollection 2024 Dec.
Detailed explorations of the model organisms (elegant worm) and (vinegar fly) have substantially improved our knowledge and understanding of biological processes and pathways in metazoan organisms. Extensive functional genomic and multi-omic data sets have enabled the discovery and characterisation of 'essential' genes that are critical for the survival of these organisms. Recently, we showed that a machine learning (ML)-based pipeline could be utilised to predict essential genes in both and using features from DNA, RNA, protein and/or cellular data or associated information. As these distantly-related species are within the Ecdysozoa, we hypothesised that this approach could be suited for non-model organisms within the same group (phylum) of protostome animals. In the present investigation, we cross-predicted essential genes within the phylum Nematoda - between and the parasitic filarial nematodes and , and then ranked and prioritised these genes. Highly ranked genes were linked to key biological pathways or processes, such as ribosome biogenesis, translation and RNA processing, and were expressed at relatively high levels in the germline, gonad, hypodermis and/or nerves. The present workflow is hoped to expedite the identification of drug targets in parasitic organisms for subsequent experimental validation in the laboratory.
对模式生物（秀丽隐杆线虫）和（黑腹果蝇）的详细研究极大地增进了我们对后生动物生物过程和通路的认识与理解。大量的功能基因组学和多组学数据集使得对这些生物生存至关重要的“必需”基因得以发现和表征。最近，我们表明基于机器学习（ML）的流程可利用来自DNA、RNA、蛋白质和/或细胞数据或相关信息的特征来预测秀丽隐杆线虫和黑腹果蝇中的必需基因。由于这些亲缘关系较远的物种属于蜕皮动物，我们推测这种方法可能适用于原口动物同一类群（门）内的非模式生物。在本研究中，我们对线虫门内的必需基因进行了交叉预测——在秀丽隐杆线虫与寄生丝状线虫和之间，然后对这些基因进行排序和优先级划分。排名靠前的基因与关键生物通路或过程相关，如核糖体生物合成、翻译和RNA加工，并且在生殖系、性腺、皮下组织和/或神经中相对高水平表达。目前的工作流程有望加快寄生生物中药物靶点的鉴定，以便随后在实验室进行实验验证。
