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A new target of multiple lysine methylation in bacteria

ABSTRACT: The methylation of ε-amino groups in protein lysine residues is an important posttranslational modification in eukaryotes, influencing various biological processes. In prokaryotes, this modification has been less studied, but recent findings suggest its role in bacterial immune evasion and host cell adhesion. Here, we analyzed Acinetobacter sp. Tol 5 cell surface proteins using LC‒MS, discovering that lysine residues of its trimeric autotransporter adhesin (TAA), AtaA, are specifically methylated. Over 130 of 232 lysine residues in AtaA were methylated. We identified the outer membrane protein lysine methyltransferase (OM PKMT) KmtA, responsible for the methylation. Bioinformatic analysis revealed the wide distribution of OM PKMT genes among gram-negative bacteria, including pathogens with TAAs that promote infection, such as Burkholderia mallei and Haemophilus influenzae. Clustering analysis suggested that KmtA is a new type of OM PKMT. Deletion of Tol 5 KmtA increased AtaA on the cell surface, enhancing adhesion and slowing growth.

ORGANISM(S): Acinetobacter Sp. Tol 5

SUBMITTER: Katsutoshi Hori

PROVIDER: PXD052460 | JPOST Repository | Wed May 22 00:00:00 BST 2024

REPOSITORIES: jPOST

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			Action	DRS
	Tol5LB_%C3%8E%E2%80%9DKmtA1.raw	Raw
	Tol5LB_%C3%8E%E2%80%9DKmtA1_PeptideGroups.txt	Txt
	Tol5LB_%C3%8E%E2%80%9DKmtA1_Proteins.txt	Txt
	Tol5LB_%C3%8E%E2%80%9DKmtA2.raw	Raw
	Tol5LB_%C3%8E%E2%80%9DKmtA2_PeptideGroups.txt	Txt

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Project description:The covalent attachment of methyl groups to the side-chain of arginine residues is known to play essential roles in regulation of transcription, protein function and RNA metabolism. The specific N-methylation of arginine residues is catalyzed by a small family of gene products known as protein arginine methyltransferases; however, very little is known about which arginine residues become methylated on target substrates. Here we describe an unbiased methodology that combines single-step immunoenrichment of methylated peptides with high-resolution mass spectrometry to identify endogenous arginine mono-methylation (MMA) sites. We thereby identify 1,027 site-specific MMA sites on 494 human proteins, discovering numerous novel mono-methylation targets and confirming the majority of currently known MMA substrates. Nuclear RNA-binding proteins involved in RNA processing, RNA localization, transcription, and chromatin remodeling are prominently found modified with MMA. Despite this, MMA sites prominently are located outside RNA-binding domains as compared to the proteome-wide distribution of arginine residues. Quantification of arginine methylation in cells treated with Actinomycin D uncovers strong site-specific regulation of MMA sites during transcriptional arrest. Interestingly, several MMA sites are down-regulated after a few hours of under transcriptional arrest. In contrast, the corresponding di-methylation or protein expression level is not altered in expression, confirming that MMA sites contain regulated functions on their own. Collectively, we present a site-specific MMA dataset in human cells and demonstrate for the first time that MMA is a dynamic post-translational modification regulated during transcriptional arrest by a hitherto uncharacterized arginine demethylase. Data analysis: All raw data analysis was performed with MaxQuant software suite version 1.2.6.20 supported by the Andromeda search engine. Data was searched against a concatenated target/decoy (forward and reversed) version of the UniProtKB Human database encompassing 71,434 protein entries. Mass tolerance for searches was set to maximum 7 ppm for peptide masses and 20 ppm for HCD fragment ion masses. Data was searched with carbamidomethylation as a fixed modification and protein N-terminal acetylation, methionine oxidation and mono-methylation on lysine and arginine as variable modifications. A maximum of three mis-cleavages was allowed while requiring strict trypsin specificity, and only peptides with a minimum sequence length of seven were considered for further data analysis. Peptide assignments were statistically evaluated in a Bayesian model on the basis of sequence length and Andromeda score. Only peptides and proteins with a false discovery rate (FDR) of less than 1% were accepted, estimated on the basis of the number of accepted reverse hits. Protein sequences of common contaminants such as human keratins and proteases used were added to the database.

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A new target of multiple lysine methylation in bacteria

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