Prokaryotic Autolysin Database Construction

Databases are valuable resources that are capable of collecting and disseminating sizeable quantities of data with the purpose of furthering research done in that particular field. Currently, there are databases for organismal genomes and classes of proteins, but currently there is no database for bacterial autolysins in particular. Autolysins such as LytA in Streptococcus pneumoniae are of vital importance as it allows the bacterium to evade antimicrobial peptides (Kietzman et. al, 2015). Additionally autolysins have been found to promote horizontal gene transfer in S. pneumoniae, as well as promoting sporulation in Bacillus subtilis (Allocati et. al, 2015). While some methods currently exist to manipulate autolysin expression, such as a broth with 2% choline, a large scale computational analysis of these proteins may provide more insight to these mechanisms (Balachandran et al, 2001). 11,458 proteomes encompassing all available Streptococcus (n=9,341), Bacillus (n=1,003), and Listeria (n=1,114) were obtained from GenBank, and 5 autolytic domains including amidase 3 and glucosaminidase were detected using hmmer with an E-value threshold of 10^-5. Resulting 68,748 output files were analyzed indicating 35,319 positive results containing at least one detected domain. This revealed that certain domains such as Glucosaminidase and LysM are highly conserved having been detected in 98.6%, 93.6%, and 99.9% of Streptococcus, Bacillus, and Listeria proteomes respectively, whereas others were noticeably more prevalent in a particular genus such as amidase 2 (75.5% Streptococcus, 92.1% Bacillus, 76.5% Listeria). Additionally, the proteomic locus of each detected domain has been recorded. Currently we aim to organize and compile data into a useful database using SQLite. Additionally, more genera are expected to be added to eventually encompass all bacterial proteomes. Moreover we aim to determine associated domains using hmm scan.