Increased chemical acetylation of peptides and proteins in rats after daily ingestion of diacetyl analyzed by Nano-LC-MS/MS

Hist-i-fy-a multiple histidine post-translational-modification (PTM) prediction server based on protein sequences using convolution neural network: a case study on mass spectroscopy data

Computational characterization of multiple Histidine (His) post-translational-modifications (PTM) at enzyme active sites complements tedious experimental characterization in proteins-of-unknown-functions (PUFs) and domain-of-unknown-functions (DUFs). There are only a handful of Histidine-PTM-prediction-tools and those also annotate only a single function. Here, we addressed the problem using artificial neural networks on functional histidine dataset curated from enzyme (protein) sequences available in UniProt database (sample size n = 1584). The convolution-neural-network (CNN) model ('Hist-i-fy') performed the best with 75% overall accuracy/F1-score. A case study was performed on histidine-phosphorylation (n = 34) obtained from mass spectroscopy data. For the first time, we report multiple His-PTM-prediction-tool (https://histify.streamlit.app/& https://github.com/dibyansu24-maker/Histify), with optimal performance. The inputs to the tool are (i) protein sequence containing histidine, and (ii) the histidine residue number. Prediction output is one out of the eight histidine functions-acetylation, ribosylation, glycosylation, hydroxylation, methylation, oxidation, phosphorylation, and protein splicing.Communicated by Ramaswamy H. Sarma.

Exceptionally versatile – arginine in bacterial post-translational protein modifications

Post-translational modifications (PTM) are the evolutionary solution to challenge and extend the boundaries of genetically predetermined proteomic diversity. As PTMs are highly dynamic, they also hold an enormous regulatory potential. It is therefore not surprising that out of the 20 proteinogenic amino acids, 15 can be post-translationally modified. Even the relatively inert guanidino group of arginine is subject to a multitude of mostly enzyme mediated chemical changes. The resulting alterations can have a major influence on protein function. In this review, we will discuss how bacteria control their cellular processes and develop pathogenicity based on post-translational protein-arginine modifications.

Effects of Diacetyl Flavoring Exposure in Mice Metabolism

Diacetyl is a flavoring that imparts a buttery flavor to foods, but the use or exposure to diacetyl has been related to some diseases. We investigated the effect of oral intake of diacetyl in male and female C57/Bl mice. We performed a target metabolomics assay using ultraperformance liquid chromatography paired with triple quadrupole mass spectrometry (UPLC-MS/MS) for the determination and quantification of plasmatic metabolites. We observed alterations in metabolites present in the urea and tricarboxylic acid (TCA) cycles. Peroxynitrite plasmatic levels were evaluated by a colorimetric method, final activity of superoxide dismutase (SOD) was evaluated by an enzymatic method, and mouse behavior was evaluated. Majority of the assay showed differences between control and treatment groups, as well as between genders. This may indicate the involvement of sex hormones in the regulation of a normal metabolic profile, and the implication of sex differences in metabolite disease response.