A Bioinformatic Analysis of Globin-Coupled Sensor Signalling in Pectobacterium Carotovorum
Open Access
- Author:
- Jordache, Lydia
- Area of Honors:
- Microbiology
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Emily E Weinert, Thesis Supervisor
Lorraine C Santy, Thesis Honors Advisor - Keywords:
- Oxygen sensing
oxygen-sensing
bacteria
GCS
c-di-GMP
Globin-coupled Sensor
Pectobacteria
soft-rot
motility
biofilm
bioinformatics
DGC
Genome Neighborhood Analysis
Sequence Conservation Analysis
Molecular modeling - Abstract:
- Pectobacterium carotovorum is a bacterial plant pathogen which induces soft rot in several agriculturally and economically important plants, particularly potatoes. Among the most notable causes of soft rot is the ability of P. carotovorum to produce biofilm, a complex polymeric substance which serves to adhere and protect bacteria and accelerate disease progression. Motility is often controlled by the same mechanisms as biofilm formation. Related to biofilm production and motility are diguanylate cyclases (DGCs), which produce the bacterial second messenger molecule cyclic di-GMP (c-di-GMP). In P. carotovorum subsp. carotovorum, an oxygen-sensing protein known as globin-coupled sensors (GCSs) contains a DGC domain, resulting in c-di-GMP production that varies in response to extracellular oxygen levels. Previous research indicates that c-di-GMP plays a major role in biofilm regulation and motility. To understand both the genetic and mechanistic relationship between GCSs and the motility phenotype, a bioinformatic assessment of Pectobacteria genomes and protein structures was performed. As a part of this assessment, the genome neighborhoods of Pectobacteria containing genes of PccGCS homologues located near motility genes were isolated. The protein products of these genes were analyzed and compared to the sequences of homologues with no inherent relationship to Pectobacteria or proximity to GCS or motility genes. By this comparison, specific amino acid mutations were identified in cases where GCS and motility genes were located near each other. Computer-generated docking simulations were performed to determine their influence in potential protein-protein binding. In total, this bioinformatic approach has served as a model for predicting protein interactions via genome neighborhood and conserved residue analyses.