The reversible and substoichiometric modification of RNA has recently emerged as an additional layer of translational regulation in normal biological function and disease. Modifications are often enzymatically deposited in and removed from short (~5 nt) consensus motif sequences to carefully control the translational output of the cell. Although characterization of modification occupancy at consensus motifs can be accomplished using RNA sequencing methods, these approaches are generally time-consuming and do not directly detect post-transcriptional modifications. Here, we present a nuclease protection assay coupled with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) to rapidly characterize modifications in consensus motifs, such as GGACU, which frequently harbor N6-methyladenosine (m6A). While conventional nuclease protection methods rely on long (~30 nt) oligonucleotide probes that preclude the global assessment of consensus motif modification stoichiometry, we investigated a series of ion-tagged oligonucleotide (ITO) probes and found that a benzylimidazolium-functionalized ITO (ABzIM-ITO) conferred significantly improved nuclease resistance for GGACU targets. After optimizing the conditions of the nuclease protection assay, we applied the ITO and MALDI-MS-based method for determining the stoichiometry of GG(m6A)CU and GGACU in RNA mixtures. Overall, the ITO-based nuclease protection and MALDI-MS method constitutes a rapid and promising approach for determining modification stoichiometries of consensus motifs.

Mass spectrometry imaging (MSI) is a tool to rapidly map the spatial location of analytes without the need for tagging or a reporter system. Niemann-Pick disease type C1 (NPC1) is a neurodegenerative, lysosomal storage disorder characterized by accumulation of unesterified cholesterol and sphingolipids in the endo-lysosomal system. Here, we use MSI to visualize lipids including cholesterol in cerebellar brain tissue from the NPC1 symptomatic mouse model and unaffected controls. To complement the imaging studies, a data-processing pipeline was developed to generate consensus mass spectra, thereby using both technical and biological image replicates to assess differences. The consensus spectra are used to determine true differences in lipid relative abundance; lipid distributions can be determined in an unbiased fashion without prior knowledge of location. We show the cerebellar distribution of gangliosides GM1, GM2, and GM3, including variants of lipid chain length. We also performed MALDI-MSI of cholesterol. Further analysis of lobules IV/V and X of the cerebellum gangliosides indicates regional differences. The specificity achieved highlights the power of MSI, and this new workflow demonstrates a universal approach for addressing reproducibility in imaging experiments applied to NPC1.

The authors describe the presentday possibilities of routine and molecular microbiologic diagnostics of infective endocarditis (IE). Routine diagnostics employs automated microbial growth and biochemical detection systems. Molecular methods are based on polymerase chain reaction (PCR) and matrix assisted laser desorption/ ionization time of flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS first appeared in the new guidelines for the management of IE of the European Society of Cardiology published in 2015. The greatest benefit of MALDITOF MS is the short time of pathogen identification. The main disadvantages are the necessity of routine agar cultures and lack of antimicrobial susceptibility estimation. So far, there has been no Polish literature report on MALDI-TOF MS used for pathogen identification in suspected IE. This may well result from scarce accessibility of the method in Poland. The paper aims to stress the importance of an up-todate technology in the diagnostics of difficult, blood culture negative cases of IE. It also takes into consideration the limitations of mass spectrometry in the ESC diagnostic scheme of IE.

Mass spectrometry imaging (MSI) has been widely used for the direct molecular assessment of tissue samples and has demonstrated great potential to complement current histopathological methods in cancer research. It is now well established that tissue preparation is key to a successful MSI experiment; for histologically heterogeneous tumor tissues, other parts of the workflow are equally important to the experiment\'s success. To demonstrate these facets here we describe a matrix-assisted laser desorption/ionization MSI biomarker discovery investigation of high-grade, complex karyotype sarcomas, which often have histological overlap and moderate response to chemo-/radio-therapy. Multiple aspects of the workflow had to be optimized, ranging from the tissue preparation and data acquisition protocols, to the post-MSI histological staining method, data quality control, histology-defined data selection, data processing and statistical analysis. Only as a result of developing every step of the biomarker discovery workflow was it possible to identify a panel of protein signatures that could distinguish between different subtypes of sarcomas or could predict patient survival outcome. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Both bacteremia and infective endocarditis caused by Staphylococcus aureus are common and severe diseases. The prognosis may darken not infrequently, especially in the presence of intracardiac devices or methicillin-resistance. Indeed, the optimization of the antimicrobial therapy is a key step in the outcome of these infections. The high rates of treatment failure and the increasing interest in the influence of vancomycin susceptibility in the outcome of infections caused by both methicillin-susceptible and -resistant isolates has led to the research of novel therapeutic schemes. Specifically, the interest raised in recent years on the new antimicrobials with activity against methicillin-resistant staphylococci has been also extended to infections caused by susceptible strains, which still carry the most important burden of infection. Recent clinical and experimental research has focused in the activity of new combinations of antimicrobials, their indication and role still being debatable. Also, the impact of an appropriate empirical antimicrobial treatment has acquired relevance in recent years. Finally, it is noteworthy the impact of the implementation of a systematic bundle of measures for improving the outcome. The aim of this clinical guideline is to provide an ensemble of recommendations in order to improve the treatment and prognosis of bacteremia and infective endocarditis caused by S. aureus, in accordance to the latest evidence published.

Bacteremia and infective endocarditis caused by Staphylococcus aureus are common and severe diseases. Optimization of treatment is fundamental in the prognosis of these infections. The high rates of treatment failure and the increasing interest in the influence of vancomycin susceptibility in the outcome of infections caused by both methicillin-susceptible and -resistant isolates have led to research on novel therapeutic schemes. The interest in the new antimicrobials with activity against methicillin-resistant staphylococci has been extended to susceptible strains, which still carry the most important burden of infection. New combinations of antimicrobials have been investigated in experimental and clinical studies, but their role is still being debated. Also, the appropriateness of the initial empirical therapy has acquired relevance in recent years. The aim of this guideline is to update the 2009 guidelines and to provide an ensemble of recommendations in order to improve the treatment of staphylococcal bacteremia and infective endocarditis, in accordance with the latest published evidence.

Neutrophil extracellular traps (NETs) consist of antimicrobial molecules embedded in a web of extracellular DNA. Formation of NETs is considered to be a defense mechanism utilized by neutrophils to ensnare and kill invading pathogens, and has been recently termed NETosis. Neutrophils can be stimulated to undergo NETosis ex vivo, and are predicted to contain high levels of serine proteases, such as neutrophil elastase (NE), cathepsin G (CG) and proteinase 3 (PR3). Serine proteases are important effectors of neutrophil-mediated immunity, which function directly by degrading pathogenic virulent factors and indirectly via proteolytic activation or deactivation of cytokines, chemokines and receptors. In this study, we utilized a diverse and unbiased peptide library to detect and profile protease activity associated with NETs induced by phorbol-12-myristate-13-acetate (PMA). We obtained a \"proteolytic signature\" from NETs derived from healthy donor neutrophils and used proteomics to assist in the identification of the source of this proteolytic activity. In addition, we profiled each neutrophil serine protease and included the newly identified enzyme, neutrophil serine protease 4 (NSP4). Each enzyme had overlapping yet distinct endopeptidase activities and often cleaved at unique sites within the same peptide substrate. The dominant proteolytic activity in NETs was attributed to NE; however, cleavage sites corresponding to CG and PR3 activity were evident. When NE was immunodepleted, the remaining activity was attributed to CG and to a lesser extent PR3 and NSP4. Our results suggest that blocking NE activity would abrogate the major protease activity associated with NETs. In addition, the newly identified substrate specificity signatures will guide the design of more specific probes and inhibitors that target NET-associated proteases.

We propose to divide matrix suppression in matrix-assisted laser desorption ionization into two parts, normal and anomalous. In quantification of peptides, the normal effect can be accounted for by constructing the calibration curve in the form of peptide-to-matrix ion abundance ratio versus concentration. The anomalous effect forbids reliable quantification and is noticeable when matrix suppression is larger than 70%. With this 70% rule, matrix suppression becomes a guideline for reliable quantification, rather than a nuisance. A peptide in a complex mixture can be quantified even in the presence of large amounts of contaminants, as long as matrix suppression is below 70%. The theoretical basis for the quantification method using a peptide as an internal standard is presented together with its weaknesses. A systematic method to improve quantification of high concentration analytes has also been developed.

Multiple residues with consensus sequence, i.e. motif, on proteins are closely related to protein function. However, there is no effective method for targeted analysis of such proteins. The challenge for analysis of these classes of proteins by MS is how to selectively enrich peptides containing consensus sequence from protein digest. Although enrichment of peptides containing one type of amino acid residue was successfully achieved by chemically labeling followed by chromatographic isolation, however, it is almost impossible to label and isolate signature peptides containing multiple residues with consensus sequence by chemical approach. Herein, we developed an enzymatic approach based on the specific recognition between enzyme and its substrates to enrich such peptides. This approach was realized by modification of a residue in the consensus sequence via enzyme that can recognize the sequence followed by the isolation of the modified peptides. cAMP-dependent protein kinase was used to validate this approach and 168 peptides containing consensus motif were identified with selectivity of 67.2%. Those peptides resulted in the identification of 88 proteins with consensus sequence from serum sample. As this motif-oriented peptide enrichment approach allows targeted analysis of a subset of proteins with consensus sequence, it will have broad application in biological studies.

Progress is continuously being made in the quest for stable biomarkers linked to complex diseases. Mass spectrometers are one of the devices for tackling this problem. The data profiles they produce are noisy and unstable. In these profiles, biomarkers are detected as signal regions (peaks), where control and disease samples behave differently. Mass spectrometry (MS) data generally contain a limited number of samples described by a high number of features. In this work, we present a novel class of evolutionary algorithms, estimation of distribution algorithms (EDA), as an efficient peak selector in this MS domain. There is a trade-of f between the reliability of the detected biomarkers and the low number of samples for analysis. For this reason, we introduce a consensus approach, built upon the classical EDA scheme, that improves stability and robustness of the final set of relevant peaks. An entire data workflow is designed to yield unbiased results. Four publicly available MS data sets (two MALDI-TOF and another two SELDI-TOF) are analyzed. The results are compared to the original works, and a new plot (peak frequential plot) for graphically inspecting the relevant peaks is introduced. A complete online supplementary page, which can be found at http://www.sc.ehu.es/ccwbayes/members/ruben/ms, includes extended info and results, in addition to Matlab scripts and references.