To combat infection by microorganisms host organisms possess a primary arsenal via the innate immune system. Among them are defense peptides with the ability to target a wide range of pathogenic... Show moreTo combat infection by microorganisms host organisms possess a primary arsenal via the innate immune system. Among them are defense peptides with the ability to target a wide range of pathogenic organisms, including bacteria, viruses, parasites, and fungi. Here, we present the development of a novel machine learning model capable of predicting the activity of antimicrobial peptides (AMPs), CalcAMP. AMPs, in particular short ones (<35 amino acids), can become an effective solution to face the multi-drug resistance issue arising worldwide. Whereas finding potent AMPs through classical wet-lab techniques is still a long and expensive process, a machine learning model can be useful to help researchers to rapidly identify whether peptides present potential or not. Our prediction model is based on a new data set constructed from the available public data on AMPs and experimental antimicrobial activities. CalcAMP can predict activity against both Gram-positive and Gram-negative bacteria. Different features either concerning general physicochemical properties or sequence composition have been assessed to retrieve higher prediction accuracy. CalcAMP can be used as an promising prediction asset to identify short AMPs among given peptide sequences. Show less
Prosthetic joint infection (PJI) is a severe complication of arthroplasty. Due to biofilm and persister formation current treatment strategies often fail. Therefore, innovative anti-biofilm and... Show moreProsthetic joint infection (PJI) is a severe complication of arthroplasty. Due to biofilm and persister formation current treatment strategies often fail. Therefore, innovative anti-biofilm and anti-persister agents are urgently needed. Antimicrobial peptides with their broad antibacterial activities may be such candidates. An in vitro model simulating PJI comprising of rifampicin/ciprofloxacin-exposed, mature methicillin-resistant Staphylococcus aureus (MRSA) biofilms on polystyrene plates, titanium/aluminium/niobium disks, and prosthetic joint liners were developed. Bacteria obtained from and residing within these biofilms were exposed to SAAP-148, acyldepsipeptide-4, LL-37, and pexiganan. Microcalorimetry was used to monitor the heat flow by the bacteria in these models. Daily exposure of mature biofilms to rifampicin/ciprofloxacin for 3 days resulted in a 4-log reduction of MRSA. Prolonged antibiotic exposure did not further reduce bacterial counts. Microcalorimetry confirmed the low metabolic activity of these persisters. SAAP-148 and pexiganan, but not LL-37, eliminated the persisters while ADEP4 reduced the number of persisters. SAAP-148 further eradicated persisters within antibiotics-exposed, mature biofilms on the various surfaces. To conclude, antibiotic-exposed, mature MRSA biofilms on various surfaces have been developed as in vitro models for PJI. SAAP-148 is highly effective against persisters obtained from the biofilms as well as within these models. Antibiotics-exposed, mature biofilms on relevant surfaces can be instrumental in the search for novel treatment strategies to combat biofilm-associated infections. Show less
Omardien, S.; Drijfhout, J.W.; Zaat, S.A.; Brul, S. 2018
