KURTH daniel German
congresos y reuniones científicas
Plasmid prediction in Micrococcus bacterial strains
Congreso; XI Congreso Argentino de Bioinformática y Biología Computacional; 2021
Institución organizadora:
Background: Plasmids are circular or linear extrachromosomal DNA molecules that replicate autonomously andoccasionally provide their guests with bacterial extra genetic material important for their survival and adaptation.The sequencing of bacterial genomes has generated a vast wealth of data that can be processed by differentcomputational tools to identify plasmid sequences. This would allow expanding the knowledge about plasmidsand their diversity in barely studied bacterial genera such as Micrococcus. These are environmental bacteria, andthe most known species M. luteus, is sometimes associated with skin and opportunistic infections. Other speciesshow potential for biotechnological applications, as they are able to produce antibiotics, biofuels, enzymes andcould be applied as biofertilizers or in bioremediation processes.Results: Draft genomes were obtained from sequencing reads of 20 strains of Micrococcus. The combination ofdifferent methods on these genomes allowed us to detect the presence of sequences associated with plasmids in17 of the selected strains. In these sequences, genes directly associated with plasmid functions (replication andsegregation) were detected, as well as accessory genes related to resistance to compounds toxins, oxidativestress, and antibiotics.In order to test the novelty of these predictions, a bipartite bacterial network was constructed with the plasmidpredictions and known actinobacterial plasmids. These networks include two types of nodes: ?genomic? nodesrepresenting each plasmid or genetic unit, and ?protein? nodes representing clusters of protein sequencesencoded by the different plasmids. Our network included 833 actinobacterial plasmids, 17 predictions, and112878 proteins. The network had poor connectivity, with most of the nodes consisting of single elements relatedto isolated plasmids. From 60615 nodes, 25659 were hypothetical proteins and 41497 included only one proteinsequence. From the non-hypothetical proteins, 2138 were annotated as transposases, an abundant element inplasmids, and they formed the largest clusters. This suggests that most actinobacterial plasmids are ?unique? andhighlights the lack of knowledge on the biology and roles of these mobile genetic elements in Actinobacteria.From a total of 1386 proteins encoded in the plasmid predictions, 915 clusters formed, and 505 of them wereexclusively associated with predictions. From these, only 100 were assigned a functional category in the KEGGdatabase, 51 of them encoding proteins associated with genetic information processing and the rest includingproteins associated with aminoacids, lipids, energy, and other metabolisms. All categories were already presentin the full actinobacterial dataset. Still, this represents a significant addition to the Micrococcus plasmidsequences pool.Conclusions:Plasmid prediction methods applied to public databases could significantly enrich the known plasmid diversity.Our network analysis allowed to identify the novelty of our predictions in the context of the actinobacterialplasmids. The abundance of hypothetical proteins in the dataset highlights the limited knowledge on plasmidbiology, particularly in Actinobacteria