RESUMEN
Antimicrobial resistance (AMR) continues to evolve as a major threat to human health, and new strategies are required for the treatment of AMR infections. Bacteriophages (phages) that kill bacterial pathogens are being identified for use in phage therapies, with the intention to apply these bactericidal viruses directly into the infection sites in bespoke phage cocktails. Despite the great unsampled phage diversity for this purpose, an issue hampering the roll out of phage therapy is the poor quality annotation of many of the phage genomes, particularly for those from infrequently sampled environmental sources. We developed a computational tool called STEP3 to use the "evolutionary features" that can be recognized in genome sequences of diverse phages. These features, when integrated into an ensemble framework, achieved a stable and robust prediction performance when benchmarked against other prediction tools using phages from diverse sources. Validation of the prediction accuracy of STEP3 was conducted with high-resolution mass spectrometry analysis of two novel phages, isolated from a watercourse in the Southern Hemisphere. STEP3 provides a robust computational approach to distinguish specific and universal features in phages to improve the quality of phage cocktails and is available for use at http://step3.erc.monash.edu/. IMPORTANCE In response to the global problem of antimicrobial resistance, there are moves to use bacteriophages (phages) as therapeutic agents. Selecting which phages will be effective therapeutics relies on interpreting features contributing to shelf-life and applicability to diagnosed infections. However, the protein components of the phage virions that dictate these properties vary so much in sequence that best estimates suggest failure to recognize up to 90% of them. We have utilized this diversity in evolutionary features as an advantage, to apply machine learning for prediction accuracy for diverse components in phage virions. We benchmark this new tool showing the accurate recognition and evaluation of phage component parts using genome sequence data of phages from undersampled environments, where the richest diversity of phage still lies.
RESUMEN
Numerous prevalence studies and outbreaks of Vibrio parahaemolyticus infection have been extensively reported in shellfish and crustaceans. Information on the quantitative detection of V. parahaemolyticus in finfish species is limited. In this study, short mackerels (Rastrelliger brachysoma) obtained from different retail marketplaces were monitored with the presence of total and pathogenic strains of V. parahaemolyticus. Out of 130 short mackerel samples, 116 (89.2%) were detected with the presence of total V. parahaemolyticus and microbial loads of total V. parahaemolyticus ranging from <3 to >105 MPN/g. Prevalence of total V. parahaemolyticus was found highest in wet markets (95.2%) followed by minimarkets (89.1%) and hypermarkets (83.3%). Pathogenic V. parahaemolyticus strains (tdh+ and/or trh+) were detected in 16.2% (21 of 130) of short mackerel samples. The density of tdh+ V. parahaemolyticus strains were examined ranging from 3.6 to >105 MPN/g and microbial loads of V. parahaemolyticus strains positive for both tdh and trh were found ranging from 300 to 740 MPN/g. On the other hand, antibiotic susceptibility profiles of V. parahaemolyticus strains isolated from short mackerels were determined through disc diffusion method in this study. Assessment of antimicrobial susceptibility profile of V. parahaemolyticus revealed majority of the isolates were highly susceptible to ampicillin sulbactam, meropenem, ceftazidime, and imipenem, but resistant to penicillin G and ampicillin. Two isolates (2.99%) exhibited the highest multiple antibiotic resistance (MAR) index value of 0.41 which shown resistance to 7 antibiotics. Results of the present study demonstrated that the occurrence of pathogenic V. parahaemolyticus strains in short mackerels and multidrug resistance of V. parahaemolyticus isolates could be a potential public health concerns to the consumer. Furthermore, prevalence data attained from the current study can be further used to develop a microbial risk assessment model to estimate health risks associated with the consumption of short mackerels contaminated with pathogenic V. parahaemolyticus.
RESUMEN
The aim of the present study was to investigate the prevalence of Salmonella spp., Salmonella Enteritidis and Salmonella Typhimurium in retail beef from different retail markets of Selangor area, as well as, to assess their pathogenic potential and antimicrobial resistance. A total of 240 retail beef meat samples (chuck = 60; rib = 60; round = 60; sirloin = 60) were randomly collected. The multiplex polymerase chain reaction (mPCR) in combination with the most probable number (MPN) method was employed to detect Salmonella spp., S. Enteritidis and S. Typhimurium in the meat samples. The prevalence of Salmonella spp., S. Enteritidis and S. Typhimurium in 240 beef meat samples were 7.50, 1.25, and 0.83%, respectively. The microbial loads of total Salmonella was found in the range of <3 to 15 MPN/g. Eight different serovars of Salmonella were identified among the 23 isolates, and S. Agona was the predominant serovar (26.09%). Interestingly, all the Salmonella isolates were resistant to penicillin, erythromycin and vancomycin, but the sensitivity was observed for tetracycline, gentamicin and amoxicillin/clavulanic acid. All 23 isolates were resistant to at least three antibiotics. Two S. Typhimurium isolates (8.70%) exhibited the highest multiple antibiotic resistance (MAR) index value of 0.56 which shown resistance to nine antibiotics. PCR analysis of virulence genes showed that all Salmonella isolates (100%) were positive for the invA gene. Meanwhile, pefA was only identified in S. Enteritidis and S. Typhimurium. The findings in this study indicate that retail beef products tested were widely contaminated with multi-drug resistant (MDR) Salmonella and various virulence genes are present among the isolated Salmonella serovars.