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

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.