Novel antimicrobials for swine health

有益于猪健康的新型抗菌剂

• 批准号: 513503-2017
• 负责人: Gray, Christopher
• 金额: $ 1.46万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=619124
• 关键词: Novel; antimicrobials; swine; health

With development of antibacterial resistance among numerous strains of infectious bacteria, antimicrobial peptides (AMPs) are considered to be among the best candidates to replace traditional antibiotics. AMPs are produced and employed by immune system of most organisms.Most of the naturally occurring AMPs are active against several types of infectious bacteria, but many of them are toxic to mammalians at therapeutic dosages. Use of machine learning (ML) methods, together with our current knowledge of natural AMPs, we can discover novel AMPs, with much less toxicity to mammalians and increased effectiveness against pathogens.In this project, we will use ML to develop novel AMPs, specifically for targeting the intestinal salmonella infections in pig farms. Data from previously known and studied AMPs will be used as input to the ML calculations. Within a projected two-year period for this project, we expect to deliver better antimicrobials for treating intestinal salmonella infections in pigs. AMPs discovered using ML methods will be tested in vitro for their antimicrobial activity and cytotoxicity. The secondary structure of the best candidate AMPs from this stage will be determined using nuclear magnetic resonance spectroscopy and used in atomistic molecular dynamics simulations to obtain a detailed picture of antimicrobial activity.We will examine our best candidate AMP (currently, HHC-36) for its effectiveness and resistance to proteolytic degradation through a number of in vitro tests.When administered orally to the infected animal, we require that the peptide resists to degradation by the digestive enzymes and the highly acidic environment of the stomach. We will therefore study the survival rate of the peptide as it passes through simulated intestinal track of the swine. If needed, delivery methods such as use of capsules for preserving the peptide in the pig's digestive system will also be considered and proposed for future animal trials.

随着许多感染性细菌菌株的耐药性的发展，抗菌肽（AMPs）被认为是取代传统抗生素的最佳候选之一。amp是大多数生物体的免疫系统产生和利用的物质。大多数天然产生的抗菌肽对几种感染性细菌有活性，但其中许多在治疗剂量下对哺乳动物有毒。利用机器学习（ML）方法，结合我们目前对天然抗菌肽的了解，我们可以发现对哺乳动物毒性小得多的新型抗菌肽，并提高对病原体的有效性。在本项目中，我们将利用ML开发新型抗菌肽，专门针对猪场肠道沙门氏菌感染。来自先前已知和研究的amp的数据将用作ML计算的输入。在该项目预计的两年期间内，我们希望提供更好的抗微生物药物来治疗猪的肠道沙门氏菌感染。使用ML方法发现的AMPs将在体外测试其抗菌活性和细胞毒性。这一阶段最佳候选抗菌肽的二级结构将使用核磁共振波谱确定，并用于原子分子动力学模拟，以获得抗菌活性的详细图像。我们将通过一系列体外测试来检验我们的最佳候选AMP（目前是HHC-36）的有效性和对蛋白水解降解的抗性。当被感染的动物口服时，我们要求肽能抵抗消化酶的降解和胃的高酸性环境。因此，我们将研究肽通过猪的模拟肠道时的存活率。如果需要，也将考虑使用胶囊在猪的消化系统中保存肽的递送方法，并为未来的动物试验提出建议。