Isolation and characterisation of antimicrobial peptides to enteric bacterial pathogens with porcine host specificity.

肠道细菌感染是影响生猪生产的最常见和经济意义重大的疾病之一（Moxley和Duhamel， 1999年）。由于全球消费的肉类中有38%是猪肉，因此猪家畜肠道细菌致病机制对全球粮食安全构成的威胁是一个主要问题（Madzimure et al., 2012）。然而，抗生素在兽医学和畜牧业中的广泛使用，特别是在牲畜中作为生长促进剂，正在导致细菌病原体中抗生素耐药性的日益普遍。因此，迫切需要在保持动物健康和生产力的同时控制病原微生物的替代方法，以取代对抗生素的依赖，并缓解日益严重的粮食不安全问题。抗菌肽（AMPs）目前未得到充分利用，但提出了一种假定的传统抗生素的新型治疗替代方案。amp是进化保守的寡肽，普遍存在于所有生命形式中，这些肽是先天免疫的一个组成部分，具有广谱活性。细菌（革兰氏阴性和革兰氏阳性）、真菌、单细胞原虫和病毒（Mahlapuu et al., 2016）。通常，amp是短的（少于100个氨基酸），阳离子（+2到+11个总正电荷），疏水（少于50%的疏水氨基酸）肽，折叠成各种不同的结构，表现出两亲构象（Shai, 2002； Bahar和Ren, 2013； Mahlapuu等人，2016）。细菌靶向amp，与真核生物的两性离子膜弱相互作用，因为它们的作用模式集中在它们的高亲和力上，破坏阴离子细菌膜的完整性。因此，上述性质使amp被视为用于治疗牲畜细菌感染的新兴治疗分子。因此，该博士项目旨在概述噬菌体展示抗菌肽发现管道。更具体地说，从Wang等人2016年抗菌肽数据库（APD3）中获得的202个已知抗菌肽的数据库被输入到机器学习算法中进行成分分析。使用VNN或NNK退化引物随机生成两个16-mer噬菌体（pIII融合）展示文库。我们假设VNN随机化方案将产生一个偏于阳离子和疏水性肽的肽库。VNN和NNK肽噬菌体文库的筛选将有效鉴定对猪肠道细菌病原体具有特异性结合和抗菌活性的肽。

Enteric bacterial infections are amongst the most common and economically significant diseases that affects pig production (Moxley and Duhamel, 1999). As 38% of meat consumed globally is pork, the global threat to food security posed by the pathogenesis of enteric bacteria in pig livestock is a major concern (Madzimure et al., 2012). However, the widespread utilisation of antibiotics in veterinary medicine and animal agriculture, particularly as growth promoters in livestock, is contributing to the ever-increasing prevalence of antibiotic resistance in bacterial pathogens. Consequently, alternative approaches that control pathogenic microorganisms whilst maintaining animal health and productivity will be urgently required to both usurp the reliance on antibiotics and alleviate growing food insecurity concerns. Antimicrobial peptides (AMPs) are currently underutilised but, present a putative novel therapeutic alternative to conventional antibiotics. AMPs are evolutionary conserved oligopeptides ubiquitously produced in all life forms and these peptides form an integral part of the innate immunity, exhibiting broad spectrum activity against; bacteria (Gram-negative and Gram-positive), fungi, unicellular protozoa and viruses (Mahlapuu et al., 2016). Typically, AMPs are short ( less than 100 amino acids), cationic (+2 to +11 overall positive net charge), hydrophobic (less than 50% hydrophobic amino acids) peptides that fold into a variety of diverse structures exhibiting amphipathic conformations (Shai, 2002; Bahar and Ren, 2013; Mahlapuu et al., 2016). Bacteria targeting-AMPs, weakly interact with the zwitterionic membranes of eukaryotes, as their mode of action centres on their high affinity to disrupt the integrity of anionic bacterial membranes. Thus, the aforementioned properties afford AMPs to be regarded as an emerging class of therapeutic molecules for the treatment of bacterial infections in livestock.This PhD project therefore aims to outline a phage display antimicrobial peptide discovery pipeline. More specifically, a database of 202 known AMPs obtained from Wang et al., 2016 Antimicrobial Peptide Database (APD3) were inputted into machine learning algorithms for compositional analysis. Two 16-mer phage (pIII fused) display libraries randomised using either a VNN or NNK degenerate primers will be generated. We hypothesise that the VNN randomisation scheme will produce a peptide library which is biased for cationic and hydrophobic peptides. VNN and NNK peptide phage libraries will be screened to efficiently identify peptides with specific binding and antimicrobial activity against several enteric bacterial pathogens of pigs.