Hypothetical Proteins of Mycoplasma synoviae Reannotation and Expression Changes Identified via RNA-Sequencing.
Duoduo SiJialin SunLei GuoFei YangXingmiao TianShenghu HeJidong LiPublished in: Microorganisms (2023)
Mycoplasma synoviae infection rates in chickens are increasing worldwide. Genomic studies have considerably improved our understanding of M. synoviae biology and virulence. However, approximately 20% of the predicted proteins have unknown functions. In particular, the M. synoviae ATCC 25204 genome has 663 encoding DNA sequences, among which 155 are considered encoding hypothetical proteins (HPs). Several of these genes may encode unknown virulence factors. This study aims to reannotate all 155 proteins in M. synoviae ATCC 25204 to predict new potential virulence factors using currently available databases and bioinformatics tools. Finally, 125 proteins were reannotated, including enzymes (39%), lipoproteins (10%), DNA-binding proteins (6%), phase-variable hemagglutinin (19%), and other protein types (26%). Among 155 proteins, 28 proteins associated with virulence were detected, five of which were reannotated. Furthermore, HP expression was compared before and after the M. synoviae infection of cells to identify potential virulence-related proteins. The expression of 14 HP genes was upregulated, including that of five virulence-related genes. Our study improved the functional annotation of M. synoviae ATCC 25204 from 76% to 95% and enabled the discovery of potential virulence factors in the genome. Moreover, 14 proteins that may be involved in M. synoviae infection were identified, providing candidate proteins and facilitating the exploration of the infection mechanism of M. synoviae .
Keyphrases
- escherichia coli
- pseudomonas aeruginosa
- staphylococcus aureus
- antimicrobial resistance
- biofilm formation
- poor prognosis
- induced apoptosis
- gene expression
- dna methylation
- machine learning
- binding protein
- signaling pathway
- single molecule
- cell free
- risk assessment
- climate change
- copy number
- endoplasmic reticulum stress
- big data
- amino acid
- genome wide identification