The aim of broth and agar dilution methods is to determine the lowest concentration of the assayed antimicrobial agent (minimal inhibitory concentration, MIC) that, under defined test conditions, inhibits the visible growth of the bacterium being investigated. MIC values are used to determine susceptibilities of bacteria to drugs and also to evaluate the activity of new antimicrobial agents. Agar dilution involves the incorporation of different concentrations of the antimicrobial substance into a nutrient agar medium followed by the application of a standardized number of cells to the surface of the agar plate. For broth dilution, often determined in 96-well microtiter plate format, bacteria are inoculated into a liquid growth medium in the presence of different concentrations of an antimicrobial agent. Growth is assessed after incubation for a defined period of time (16-20 h) and the MIC value is read. This protocol applies only to aerobic bacteria and can be completed in 3 d.

For 70 years antibiotics have saved countless lives and enabled the development of modern medicine, but it is becoming clear that the success of antibiotics may have only been temporary and we now anticipate a long-term, generational and perhaps never-ending challenge to find new therapies to combat antibiotic-resistant bacteria. As the search for new conventional antibiotics has become less productive and there are no clear strategies to improve success, a broader approach to address bacterial infection is needed. This review of potential alternatives to antibiotics (A2As) was commissioned by the Wellcome Trust, jointly funded by the Department of Health, and involved scientists and physicians from academia and industry. For the purpose of this review, A2As were defined as non-compound approaches (that is, products other than classical antibacterial agents) that target bacteria or approaches that target the host. In addition, the review was limited to agents that had potential to be administered orally, by inhalation or by injection for treatment of systemic/invasive infection. Within these criteria, the review has identified 19 A2A approaches now being actively progressed. The feasibility and potential clinical impact of each approach was considered. The most advanced approaches (and the only ones likely to deliver new treatments by 2025) are antibodies, probiotics, and vaccines now in Phase II and Phase III trials. These new agents will target infections caused by P. aeruginosa, C. difficile and S. aureus. However, other than probiotics for C. difficile, this first wave will likely best serve as adjunctive or preventive therapies. This suggests that conventional antibiotics will still be needed. The economics of pathogen-specific therapies must improve to encourage innovation, and greater investment into A2As with broad-spectrum activity (e.g. antimicrobial-, host defense-and, anti-biofilm peptides) is needed. Increased funding, estimated at >£1.5 bn over 10 years is required to validate and then develop these A2As. Investment needs to be partnered with translational expertise and targeted to support the validation of these approaches at Clinical Phase II proof of concept. Such an approach could transform our understanding of A2As as effective new therapies and should provide the catalyst required for both active engagement and investment by the pharma/biotech industry. Only a sustained, concerted and coordinated international effort will provide the solutions needed for the next decade.

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Cationic antimicrobial peptides are able to kill a broad variety of Gram-negative and Gram positive bacteria and thus are good candidates for a new generation of antibiotics to treat multidrug-resistant bacteria. Here we describe a high-throughput method to screen large numbers of peptides for improved antimicrobial activity. The method relies on peptide synthesis on a cellulose support and a Pseudomonas aeruginosa strain that constitutively expresses bacterial luciferase. A complete substitution library of 12-amino-acid peptides based on a linearized variant (RLARIVVIRVAR-NH(2)) of the bovine peptide bactenecin was screened and used to determine which substitutions at each position of the peptide chain improved activity. By combining the most favorable substitutions, we designed optimized 12-mer peptides showing broad spectrum activities with minimal inhibitory concentrations (MIC) as low as 0.5 microg/ml against Escherichia coli. Similarly, we generated an 8-mer substituted peptide that showed broad spectrum activity, with an MIC of 2 microg/ml, against E. coli and Staphylococcus aureus.

Increased multiple antibiotic resistance in the face of declining antibiotic discovery is one of society's most pressing health issues. Antimicrobial peptides represent a promising new class of antibiotics. Here we ask whether it is possible to make small broad spectrum peptides employing minimal assumptions, by capitalizing on accumulating chemical biology information. Using peptide array technology, two large random 9-amino-acid peptide libraries were iteratively created using the amino acid composition of the most active peptides. The resultant data was used together with Artificial Neural Networks, a powerful machine learning technique, to create quantitative in silico models of antibiotic activity. On the basis of random testing, these models proved remarkably effective in predicting the activity of 100,000 virtual peptides. The best peptides, representing the top quartile of predicted activities, were effective against a broad array of multidrug-resistant "Superbugs" with activities that were equal to or better than four highly used conventional antibiotics, more effective than the most advanced clinical candidate antimicrobial peptide, and protective against Staphylococcus aureus infections in animal models.