Proceedings of the EuBIC-MS 2020 Developers’ Meeting

Clinical proteomics involves the analysis of protein expression of disease proteomes, with the aim of solving a specific clinical problem. Discoveries made from proteomicbased studies contribute to the growing need for innovative medical diagnostics for disease detection. Taking into consideration the global health burden of cardiac disease, clinical proteomics is a valuable tool to improve risk stratification associated with this disease. In cardiovascular medicine, the identification of novel proteins, or biomarkers, that are differentially expressed in cardiac disease proteomes may enable early detection of the disease state, thereby preventing progression to disease end points. This review outlines various proteomic platforms and their technical advancements and relates these to the cardiovascular sciences. The entire protein complement of the cell, or proteome, is dynamic and changes in response to the disease state. 1 Proteomic-based experiments can be used to characterize such alterations in protein expression during disease progression. 2 With combined improvements in mass spectrometry (MS) technology as well as innovative molecular biology screening tools, there has been widespread growth in the characterization of cardiac disease proteomes. In fact, proteomic technology has been an important tool in the analysis of heart failure (HF), 3,4 cardiac hypertrophy, 5,6 and dilated cardiomyopathy.7 Several of the overarching aims of such studies include providing greater understanding of general biological mechanisms as well as identifying unique proteins that are clinically useful in the detection of cardiac disease in the early stages or potentially used as novel therapeutic targets. Clinical proteomics continues to benefit from advancements in technologies that allow for fast and consistent identification of proteins with corresponding increases in the dynamic range of proteins detectable in the disease proteome. MS-related technologies have improved in their ability to detect low-abundance proteins as well as membrane proteins and have benefited from sample preprocessing strategies that decrease the complexity of large-scale analyses. With the emergence of different methodologies for biomarker identification, the following 3 criteria must be taken into careful consideration to determine whether the protein is, in fact,

FROM THE DECLINE AND FALL OF PROTEIN CHEMISTRY TO PROTEOMICS

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of ~103) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 106 for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.

This is certainly the most important book dealing with gas and liquid chromatography that has appeared for many years. Two-dimensional (2D) chromatography dates back almost to the beginnings of the modern era of chromatography, and 2D GC systems have been used since the 1960s. Indeed, Deans who was the first to publish pneumatic switching, believed that all GC problems at that time could be solved by multiple column combinations. The idea of comprehensive 2D chromatography (where all peaks from one column pass to a second, different column) dates back 20 years, but it is only within the last 10 years that it has been taken up by a few enthusiasts most of whom appear as contributors to this book. In particular the editor, Mondello, appears as a co-author in no less than six of the 12 chapters. The potential advantages of comprehensive 2D chromatography are clear, but the practical problems are formidable and this book does not disguise this fact. After a short introductory chapter to set the scene, the book properly starts with a chapter on theoretical aspects of multidimensional gas chromatography by Blumberg. This chapter reminded me of my student course on thermodynamics—after a year of lectures and some 230 equations I was little the wiser. The author manages 91 equations in 46 pages, but in fairness he does try hard to stress the conclusions of his work by inserting paragraphs in italics that outline the practical significance of his theoretical analysis. It is worth quoting a slightly condensed version of his concluding italic paragraph—‘‘GC x GC has the potential to provide at least one order of magnitude larger peak capacity than 1D GC. When the hardware problems are solved the separation performance will be out of reach of any known alternative GC technique. Further significant increase in peak capacity can be obtained by improved data analysis’’. The next chapter deals with the theoretical aspects of multidimensional LC, but fortunately this is considerably simpler than the preceding chapter (a mere 27 equations in 26 pages!). Chapter 4 deals with more practical aspects of comprehensive 2D GC, in particular with the various ‘‘modulators’’ that have been developed. The modulator is the device that samples at short time intervals the peaks emerging from the first column and sends them to the second column. To get reliable determination of peak area at least ten data points per peak should be collected and this places severe demands on the modulator (and also on the detector and data handling system). Indeed the performance of the modulator is the most important of the ‘‘hardware problems’’ touched on in Blumberg’s summary quoted above. Chapter 5 by Seeley describes what seems to me to be possibly the best solution of the modulator problem using flow modulation, since it is by far the least demanding of equipment and operating costs although as always there are E. R. Adlard (&) Burton, South Wirral, UK e-mail: chromatographia@springer.com

9th Siena MeetingSiena, Italy, 26–30 August 2012Auditorium Giurisprudenza e Scienze PoliticheThe Siena Meeting has been held biannually since 1994, when for the first time the concept of the proteome was introduced to a large scientific audience. Over the years, the meeting has grown to be a major international conference in the field of proteomics and has attracted excellent scientists from all corners of the world. The 9th Siena Meeting: ‘from Genome to Proteome: Open Innovations’ was attended by 300 scientists. There were four plenary and eight parallel sessions with 50 invited talks and three poster sessions with 94 posters covering wide range of functional proteomics, signaling, biomarkers, cancer, neuroscience, glycoproteomics, mass spectrometry and bioinformatics. As in the past, this year’s Siena Meeting maintained its tradition of placing science at centre stage, which generated a wide range of discussions of major importance for the future.

Protein S-nitrosylation mediated by cellular nitric oxide (NO) plays a primary role in executing biological functions in cGMP-independent NO signaling. Although S-nitrosylation appears similar to Cys oxidation induced by reactive oxygen species, the molecular mechanism and biological consequence remain unclear. We investigated the structural process of S-nitrosylation of protein-tyrosine phosphatase 1B (PTP1B). We treated PTP1B with various NO donors, including S-nitrosothiol reagents and compound-releasing NO radicals, to produce site-specific Cys S-nitrosylation identified using advanced mass spectrometry (MS) techniques. Quantitative MS showed that the active site Cys-215 was the primary residue susceptible to S-nitrosylation. The crystal structure of NO donor-reacted PTP1B at 2.6 A resolution revealed that the S-NO state at Cys-215 had no discernible irreversibly oxidized forms, whereas other Cys residues remained in their free thiol states. We further demonstrated that S-nitrosylation of the Cys-215 residue protected PTP1B from subsequent H(2)O(2)-induced irreversible oxidation. Increasing the level of cellular NO by pretreating cells with an NO donor or by activating ectopically expressed NO synthase inhibited reactive oxygen species-induced irreversible oxidation of endogenous PTP1B. These findings suggest that S-nitrosylation might prevent PTPs from permanent inactivation caused by oxidative stress.

Applications of Modern Mass Spectrometry, Volume 2, covers the latest advances in mass spectrometry in scientific research. The series presents readers with information on the broad range of mass spectrometry techniques and configurations, data analysis, and practical applications. Each volume contains contributions from eminent researchers who present their findings in an easy-to-read format. The multidisciplinary nature of the works presented in each volume of this book series makes it a valuable reference on mass spectrometry to academic researchers and industrial R&D specialists in applied sciences, biochemistry, life sciences, and allied fields. The second volume of the series presents 6 reviews: Ion Mobility-Mass Spectrometry for Macromolecule Analysis - Recent Advancements in Detection of Organic Contaminants in Wastewater Using Advanced Mass Spectrometry - Poisonous Substances in Tropical Medicinal and Edible Plants: Traditional Uses, Toxicology, and Characterization by Hyphenated Mass Spectrometry Techniques - LC-MS Analysis of Endogenous Neuropeptides from Tissues of Central Nervous System: An Overview - Advances in Structural Proteomics Using Mass Spectrometry and Recent Trends of Modern Mass Spectrometry: Application towards Drug Discovery and Development Process.

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Unraveling the Complex Proteome for Biomarker Discovery in Gastrointestinal and Liver Diseases

Investigation on the co-combustion mechanism of coal and biomass on a fixed-bed reactor with advanced mass spectrometry

It is now becoming obvious that the rapidly developing fields of genomics, proteomics and bioinformatics will prove to be complementary in the comprehensive understanding of biological processes and the rapid development of novel pharmaceuticals. In the field of proteomics [1], the separation sciences will obviously pay a pivotal role in such studies, coupled with highly sensitive and specific down stream analytical techniques such as mass spectrometry. To date 2-D gel electrophoresis has been routinely used as the preferred method for the separation of complex mixtures of cellular proteins. However, it is now realised that this technique has its limitations, in particular for the identification of low abundance proteins (e.g. growth factors, receptors and proteins involved in signal transduction).

Recent liquid chromatographic–(tandem) mass spectrometric applications in proteomics

Advances in mass spectrometry have had a great impact on the field of proteomics. A major challenge of proteomic analysis has been the elucidation of glycan modifications of proteins in complex proteomes. Glycosylation is the most structurally elaborate and diverse type of protein post-translational modification and, because of this, proteomics and glycomics have largely developed independently. However, given that such a large proportion of proteins contain glycan modifications, and that these may be important for their function or may produce biologically relevant protein variation, a convergence of the fields of glycomics and proteomics would be highly desirable. Here we review the current status of glycoproteomic efforts, focusing on the identification of glycoproteins as cancer biomarkers.

Leptomeningeal metastasis (LM) is a devastating complication that occurs in 5% of patients with breast cancer. Early diagnosis and initiation of treatment are essential to prevent neurological deterioration. However, early diagnosis of LM remains challenging because 25% of cerebrospinal fluid (CSF) samples produce false-negative results at first cytological examination. We developed a new, MS-based method to investigate the protein expression patterns present in the CSF from patients with breast cancer with and without LM. CSF samples from 106 patients with active breast cancer (54 with LM and 52 without LM) and 45 control subjects were digested with trypsin. The resulting peptides were measured by MALDI-TOF MS. Then, the mass spectra were analyzed and compared between patient groups using newly developed bioinformatics tools. A total of 895 possible peak positions was detected, and 164 of these peaks discriminated between the patient groups (Kruskal-Wallis, p<0.01). The discriminatory masses were clustered, and a classifier was built to distinguish patients with breast cancer with and without LM. After bootstrap validation, the classifier had a maximum accuracy of 77% with a sensitivity of 79% and a specificity of 76%. Direct MALDI-TOF analysis of tryptic digests of CSF gives reproducible peptide profiles that can assist in diagnosing LM in patients with breast cancer. The same method can be used to develop diagnostic assays for other neurological disorders.