Volume 29, Issue 1
DOI: 10.53555/03276716.2020.20
Pathogenic Protein Identification and Localization Prediction in Pseudomonas fuscovaginae: A Study on Sheath Brown Rot in Rice.
Abstract
P. fuscovaginae poses a concern to rice cropping systems since it is readily found on asymptomatic
seeds.The fluorescent, Gram-negative P. fuscovaginae (Pfv) belongs to the Gamma proteobacteria class of
bacteria. P. fuscovaginae LMG 2158's genome is a single circular chromosome with a 6592354 bp total GC
content. The bacterial disease known as brown sheath rot affects rice fields almost everywhere from sea
level to 1200–1700 m above sea level, low temperature (20–22°C), and high humidity, in both temperate
and tropical climates. Symptoms of P. fuscovaginae can be found at various crop cycle stages. The most
typical signs include unfilled grains, kernel spotting, poor panicle emergence, sterility, dark necrotic spots
on the flag leaf's sheath that vary in length, or as necrosis spreads on the sheaths. The disease's severity
varies by region, with some strains showing biochemical and physiological variability.
Pathogenic proteins plays a vital role in host-pathogen interaction. To computationally identify such
pathogenic proteins, MP3 software were used to analyse the proteome in the Fasta file that was
downloaded from the NCBI. We analysed the 5778 proteins using the MP3 software, The predictions found
670 proteins as pathogenic by the SVM approach, 441 proteins by the HMM method, and 880 proteins by
the HYBRID method. We selected the top 500 proteins for our further investigation. Nine distinct
sub-cellular localisation prediction servers are used to forecast the sub-cellular locations of 500 proteins.
BUSCA, Cello v.2.5, Cell-PLoc v.2.0, PSORTb v.3.0, PSL-Pred, SLP-Local, ngLOC, gram-LocEN, and CELLO2GO
are the servers were employed. The results of the servers used to prediction of the sub-cellular location of
proteins vary. Our findings were roughly categorised into six groups: extracellular space proteins, plasma
membrane proteins, and cytoplasmic proteins and a combination of them. Out of 500 proteins, we were
able to predict 32 proteins as exclusively Extra-cellular, 370 as exclusively Plasma membrane associated, 62
as exclusively Cytoplasmic proteins, 7 as both Extra-cellular and Plasma membrane associated, 28 as Plasma
membrane associated and Cytoplasmic protein and 01 with Extra-cellular and Cytoplasmic in nature.
VirulentPred and VICM-pred were utilised for 500 proteins for further virulence prediction. By using
VirulentPred, 337 out of 500 proteins were identified to be virulent, by VICM 52 to be virulent. We
identified 107 proteins as pathogenic out of 500 proteins based on predictions from 3 servers/tools by vote
of majority. We also identified the sub-cellular localisation of such proteins. 80 of the proteins were
projected to be linked with the plasma membrane, 18 to be extracellular, and 19 to be cytoplasmic. A few
proteins were predicted to have multiple sites.
Keywords
P. fuscovaginae LMG - 2158, Oryza sativa L. , MP3, PSI BLAST, HMM, BUSCA.