Background: Acinetobacter baumannii is one of the top priority pathogens in the WHOs list for the development of new antibiotics, mainly due to the genus’ intrinsic resistance against certain antimicrobials, as well as natural competence to pick up resistance-conferring genes from the environment with relative ease. Prophages present in the bacterial genome often increase the evolutionary fitness of the bacteria, and provide a novel way to target resistance and virulence.

Aim: To compare the different bioinformatic tools available to predict prophage sequences in the bacterial genome.

Methods: The prophage finding tools such as PHASTER, Phigaro and PhiSpy were used to predict the prophage sequences in the A. baumannii genome. A total of 916 available sequences were used for the comparison, of which 311 were chromosomal DNA and 605 were plasmid DNA.

Result: The methods to identify and annotate prophages have large discrepancies in their results. The output of each tool is of a different format, with Phigaro giving the taxonomy of all available prophages while PHASTER and PhiSpy giving the activity of the prophages detected.

Conclusion: This study highlights the need for a standardised, uniformly used method to identify and
annotate prophages to prevent the differing results throughout different scientific communities