Enzymology and significance of protein histidine methylation

Cells synthesize proteins using 20 standard amino acids and expand their biochemical repertoire through intricate enzyme-mediated post-translational modifications (PTMs). PTMs can either be static and represent protein editing events or be dynamically regulated as a part of a cellular response to specific stimuli. Protein histidine methylation (Hme) was an elusive PTM for over 5 decades and has only recently attracted considerable attention through discoveries concerning its enzymology, extent, and function. Here, we review the status of the Hme field and discuss the implications of Hme in physiological and cellular processes. We also review the experimental toolbox for analysis of Hme and discuss the strengths and weaknesses of different experimental approaches. The findings discussed in this review demonstrate that Hme is widespread across cells and tissues and functionally regulates key cellular processes such as cytoskeletal dynamics and protein translation. Collectively, the findings discussed here showcase Hme as a regulator of key cellular functions and highlight the regulation of this modification as an emerging field of biological research

Structure, activity and function of the dual protein lysine and protein n‐terminal methyltransferase mettl13

METTL13 (also known as eEF1A‐KNMT and FEAT) is a dual methyltransferase reported to target the N‐terminus and Lys55 in the eukaryotic translation elongation factor 1 alpha (eEF1A). METTL13‐mediated methylation of eEF1A has functional consequences related to translation dynamics and include altered rate of global protein synthesis and translation of specific codons. Aberrant regulation of METTL13 has been linked to several types of cancer but the precise mechanisms are not yet fully understood. In this article, the current literature related to the structure, activity, and function of METTL13 is systematically reviewed and put into context. The links between METTL13 and diseases, mainly different types of cancer, are also summarized. Finally, key challenges and opportunities for METTL13 research are pinpointed in a prospective outlook

Comprehending the proteomic landscape of ovarian cancer : A road to the discovery of disease biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice

Proteomic response in Streptococcus gordonii DL1 biofilm cells during attachment to salivary MUC5B

Background Salivary mucin MUC5B seems to promote biodiversity in dental biofilms, and thereby oral health, for example, by inducing synergistic 'mucolytic' activities in a variety of microbial species that need to cooperate for the release of nutrients from the complex glycoprotein. Knowledge of how early colonizers interact with host salivary proteins is integral to better understand the maturation of putatively harmful oral biofilms and could provide key insights into biofilm physiology. Methods The early oral colonizer Streptococcus gordonii DL1 was grown planktonically and in biofilm flow cell systems with uncoated, MUC5B or low-density salivary protein (LDP) coated surfaces. Bacterial cell proteins were extracted and analyzed using a quantitative mass spectrometry-based workflow, and differentially expressed proteins were identified. Results and conclusions Overall, the proteomic profiles of S. gordonii DL1 were similar across conditions. Six novel biofilm cell proteins and three planktonic proteins absent in all biofilm cultures were identified. These differences may provide insights into mechanisms for adaptation to biofilm growth in this species. Salivary MUC5B also elicited specific responses in the biofilm cell proteome. These regulations may represent mechanisms by which this mucin could promote colonization of the commensal S. gordonii in oral biofilms

Hydroxylation of the Acetyltransferase NAA10 Trp38 Is Not an Enzyme-Switch in Human Cells

NAA10 is a major N-terminal acetyltransferase (NAT) that catalyzes the cotranslational N-terminal (Nt-) acetylation of 40% of the human proteome. Several reports of lysine acetyltransferase (KAT) activity by NAA10 exist, but others have not been able to find any NAA10-derived KAT activity, the latter of which is supported by structural studies. The KAT activity of NAA10 towards hypoxia-inducible factor 1α (HIF-1α) was recently found to depend on the hydroxylation at Trp38 of NAA10 by factor inhibiting HIF-1α (FIH). In contrast, we could not detect hydroxylation of Trp38 of NAA10 in several human cell lines and found no evidence that NAA10 interacts with or is regulated by FIH. Our data suggest that NAA10 Trp38 hydroxylation is not a switch in human cells and that it alters its catalytic activity from a NAT to a KAT

Effects of active farnesoid X receptor on GLUTag enteroendocrine L cells

Activated transcription factor (TF) farnesoid X receptor (FXR) represses glucagon-like peptide-1 (GLP-1) secretion in enteroendocrine L cells. This, in turn, reduces insulin secretion, which is triggered when β cells bind GLP-1. Preventing FXR activation could boost GLP-1 production and insulin secretion. Yet, FXR's broader role in L cell biology still lacks understanding. Here, we show that FXR is a multifaceted TF in L cells using proteomics and gene expression data generated on GLUTag L cells. Most striking, 252 proteins regulated upon glucose stimulation have their abundances neutralized upon FXR activation. Mitochondrial repression or glucose import block are likely mechanisms of this. Further, FXR physically targets bile acid metabolism proteins, growth factors and other TFs, regulates ChREBP, while extensive text-mining found 30 FXR-regulated proteins to be well-known in L cell biology. Taken together, this outlines FXR as a powerful TF, where GLP-1 secretion block is just one of many downstream effects

Assessment of HSPA1-Lys561 methylation status in HGSC and breast carcinoma effusions.

<p>(A) Quantitative mass spectrometry analysis of HSPA1-Lys561 methylation. Samples were analyzed as exemplified in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140168#pone.0140168.g001" target="_blank">Fig 1</a>. The relative abundance of the various methylation states (me0, me1, me2 and me3) of Lys561 in HSPA1 in 17 breast carcinoma (cases # 1–17) and 53 HGSC (cases # 18–70) samples is shown. The data are grouped by cancer type and sorted by increasing relative abundance of me3. (B) Reproducibility of the analysis. A second analysis of 2 randomly chosen breast cancer samples and 5 randomly chosen HGSC samples was performed, and the results were plotted versus the original data set. Data points for the various lysine methylation states are color-coded as in (A) and each tumor sample is represented by a unique geometrical figure.</p

Representative mass spectrometry data from quantitative analysis of HSPA1-Lys561 methylation status.

<p>(A)-(D) Methylation status of Lys561 in HSPA1 in tumor sample # 14. Left panels, chromatograms were generated by gating for mass-to-charge ratios of the (A) unmethylated (me0), (B) monomethylated (me1), (C) dimethylated (me2) and (D) trimethylated (me3) state of the AspN-generated proteolytic peptide encompassing Asp555-Ala565 in HSPA1. The elution time (arrow) and the area under each curve (in brackets), as well as the calculated relative abundance (as percentage) of the various lysine methylation states, are indicated. Right panels, annotated tandem mass spectra supporting the identity of analyzed peptides.</p

HSPA1 methylation and patient survival in HGSC.

<p>^aNumber of methyl groups on Lys-561 in HSPA1, calculated from the data in the three previous columns according to the following formula: (Me1 + 2∙Me2 + 3∙Me3)/100</p><p>^bPatient was alive with disease at the end of the follow-up period (110 mo), and was therefore censored in OS curve (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140168#pone.0140168.g003" target="_blank">Fig 3A</a>)</p><p>^cPatient was alive without disease after the end of the follow-up period (132 mo for OS and 127 mo for PFS), and was therefore censored in OS and PFS curves (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140168#pone.0140168.g003" target="_blank">Fig 3</a>)</p><p>HSPA1 methylation and patient survival in HGSC.</p