Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS

Covalent adduct formation of histone with organophosphorus pesticides in vitro

It is established that organophosphorus pesticide (OPP) toxicity results from modification of amino acids in active sites of target proteins. OPPs can also modify unrelated target proteins such as histones and such covalent histone modifications can alter DNA-binding properties and lead to aberrant gene expression. In the present study, we report on non-enzymatic covalent modifications of calf thymus histones adducted to selected OPPs and organophosphate flame retardants (OPFRs) in vitro using a bottom-up proteomics method approach. Histones were not found to form detectable adducts with the two tested OPFRs but were avidly modified by a few of the seven OPPs that were tested in vitro. Dimethyl phosphate (or diethyl phosphate) adducts were identified on Tyr, Lys and Ser residues. Most of the dialkyl phosphate adducts were identified on Tyr residues. Methyl and ethyl modified histones were also detected. Eleven amino residues in histones showed non-enzymatic covalent methylation by exposure of dichlorvos and malathion. Our bottom-up proteomics approach showing histone-OPP adduct formation warrants future studies on the underlying mechanism of chronic illness from exposure to OPPs.

Bottom-up proteomics analysis for adduction of the broad-spectrum herbicide atrazine to histone

Histones are the major proteinaceous components of chromatin in eukaryotic cells and an important part of the epigenome. The broad-spectrum herbicide atrazine (2-chloro-4-[ethylamino]-6-[isopropylamino]-1, 3, 5-triazine) and its metabolites are known to form protein adducts, but the formation of atrazine-histone adducts has not been studied. In this study, a bottom-up proteomics analysis method was optimized and applied to identify histone adduction by atrazine in vitro. Whole histones of calf thymus or human histone H3.3 were incubated with atrazine. After solvent-based protein precipitation, the protein was digested by trypsin/Glu-C and the resulting peptides were analyzed by high-resolution mass spectrometry using an ultra-high-performance liquid chromatograph interfaced with a quadrupole Exactive-Orbitrap mass spectrometer. The resulting tryptic/Glu-C peptide of DTNLCAIHAK from calf thymus histone H3.1 or human histone H3.3 was identified with an accurate mass shift of  +179.117 Da in atrazine incubated samples. It is deduced that a chemical group with an elemental composition of C8H13N5 (179.1171 Da) from atrazine adducted with calf thymus histone H3.1 or human histone H3.3. It was confirmed by MS/MS analysis that the adduction position was at its cysteine 110 residue. Time- and concentration-dependent assays also confirmed the non-enzymatic covalent modification of histone H3.3 by atrazine in vitro. Thus, the potential exists that atrazine adduction may lead to the alteration of histones that subsequently disturbs their normal function.

The Final Maturation State of β-actin Involves N-terminal Acetylation by NAA80, not N-terminal Arginylation by ATE1

Actin is a hallmark protein of the cytoskeleton in eukaryotic cells, affecting a range of cellular functions. Actin dynamics is regulated through a myriad of actin-binding proteins and post-translational modifications. The mammalian actin family consists of six different isoforms, which vary slightly in their N-terminal (Nt) sequences. During and after synthesis, actins undergo an intricate Nt-processing that yields mature actin isoforms. The ubiquitously expressed cytoplasmic β-actin is Nt-acetylated by N-alpha acetyltransferase 80 (NAA80) yielding the Nt-sequence Ac-DDDI-. In addition, β-actin was also reported to be Nt-arginylated by arginyltransferase 1 (ATE1) after further peptidase-mediated processing, yielding RDDI-. To characterize in detail the Nt-processing of actin, we used state-of-the-art proteomics. To estimate the relative cellular levels of Nt-modified proteoforms of actin, we employed NAA80-lacking cells, in which actin was not Nt-acetylated. We found that targeted proteomics is superior to a commercially available antibody previously used to analyze Nt-arginylation of β-actin. Significantly, despite the use of sensitive mass spectrometry-based techniques, we could not confirm the existence of the previously claimed Nt-arginylated β-actin (RDDI-) in either wildtype or NAA80-lacking cells. A very minor level of Nt-arginylation of the initially cleaved β-actin (DDDI-) could be identified, but only in NAA80-lacking cells, not in wildtype cells. We also identified small fractions of cleaved and unmodified β-actin (DDI-) as well as cleaved and Nt-acetylated β-actin (Ac-DDI-). In sum, we show that the multi-step Nt-maturation of β-actin is terminated by NAA80, which Nt-acetylates the exposed Nt-Asp residues, in the virtual absence of previously claimed Nt-arginylation.

Ring finger protein 213 assembles into a sensor for ISGylated proteins with antimicrobial activity

ISG15 is an interferon-stimulated, ubiquitin-like protein that can conjugate to substrate proteins (ISGylation) to counteract microbial infection, but the underlying mechanisms remain elusive. Here, we use a virus-like particle trapping technology to identify ISG15-binding proteins and discover Ring Finger Protein 213 (RNF213) as an ISG15 interactor and cellular sensor of ISGylated proteins. RNF213 is a poorly characterized, interferon-induced megaprotein that is frequently mutated in Moyamoya disease, a rare cerebrovascular disorder. We report that interferon induces ISGylation and oligomerization of RNF213 on lipid droplets, where it acts as a sensor for ISGylated proteins. We show that RNF213 has broad antimicrobial activity in vitro and in vivo, counteracting infection with Listeria monocytogenes, herpes simplex virus 1, human respiratory syncytial virus and coxsackievirus B3, and we observe a striking co-localization of RNF213 with intracellular bacteria. Together, our findings provide molecular insights into the ISGylation pathway and reveal RNF213 as a key antimicrobial effector.

Quality control in mass spectrometry-based proteomics

Mass spectrometry is a highly complex analytical technique and mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining accurate and reproducible results. Therefore, a comprehensive and systematic approach to quality control is an essential requirement to inspire confidence in the generated results. A typical mass spectrometry experiment consists of multiple different phases including the sample preparation, liquid chromatography, mass spectrometry, and bioinformatics stages. We review potential sources of variability that can impact the results of a mass spectrometry experiment occurring in all of these steps, and we discuss how to monitor and remedy the negative influences on the experimental results. Furthermore, we describe how specialized quality control samples of varying sample complexity can be incorporated into the experimental workflow and how they can be used to rigorously assess detailed aspects of the instrument performance.

Elucidating Escherichia coli Proteoform Families Using Intact-Mass Proteomics and a Global PTM Discovery Database

A proteoform family is a group of related molecular forms of a protein (proteoforms) derived from the same gene. We have previously described a strategy to identify proteoforms and elucidate proteoform families in complex mixtures of intact proteins. The strategy is based upon measurements of two properties for each proteoform: (i) the accurate proteoform intact-mass, measured by liquid chromatography/mass spectrometry (LC-MS), and (ii) the number of lysine residues in each proteoform, determined using an isotopic labeling approach. These measured properties are then compared with those extracted from a catalog of theoretical proteoforms containing protein sequences and localized post-translational modifications (PTMs) for the organism under study. A match between the measured properties and those in the catalog constitutes an identification of the proteoform. In the present study, this strategy is extended by utilizing a global PTM discovery database and is applied to the widely studied model organism Escherichia coli, providing the most comprehensive elucidation of E. coli proteoforms and proteoform families to date.

Elucidating Proteoform Families from Proteoform Intact-Mass and Lysine-Count Measurements

Proteomics is presently dominated by the “bottom-up” strategy, in which proteins are enzymatically digested into peptides for mass spectrometric identification. Although this approach is highly effective at identifying large numbers of proteins present in complex samples, the digestion into peptides renders it impossible to identify the proteoforms from which they were derived. We present here a powerful new strategy for the identification of proteoforms and the elucidation of proteoform families (groups of related proteoforms) from the experimental determination of the accurate proteoform mass and number of lysine residues contained. Accurate proteoform masses are determined by standard LC–MS analysis of undigested protein mixtures in an Orbitrap mass spectrometer, and the lysine count is determined using the NeuCode isotopic tagging method. We demonstrate the approach in analysis of the yeast proteome, revealing 8637 unique proteoforms and 1178 proteoform families. The elucidation of proteoforms and proteoform families afforded here provides an unprecedented new perspective upon proteome complexity and dynamics.

Bioinformatics for proteomics: opportunities at the interface between the scientists, their experiments, and the community

Within the last decade, bioinformatics has moved from command line scripts dedicated to single experiments towards production grade software integrated in experimental workflows providing a rich environment for biological investigation. Located at the interface between the scientists, their experiments, and the community, bioinformatics acts as a gateway to a wide source of information. This chapter does not list tools and methods, but rather hints at how bioinformatics can help in improving biological projects, all the way from their initial design to the dissemination of the results.