PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results.

Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study.

Characterization of Site-Specific N-Glycopeptide Isoforms of α-1-Acid Glycoprotein from an Interlaboratory Study Using LC-MS/MS.

Glycoprotein conformations are complex and heterogeneous. Currently, site-specific characterization of glycopeptides is a challenge. We sought to establish an efficient method of N-glycoprotein characterization using mass spectrometry (MS). Using alpha-1-acid glycoprotein (AGP) as a model N-glycoprotein, we identified its tryptic N-glycopeptides and examined the data reproducibility in seven laboratories running different LC-MS/MS platforms. We used three test samples and one blind sample to evaluate instrument performance with entire sample preparation workflow. 165 site-specific N-glycopeptides representative of all N-glycosylation sites were identified from AGP 1 and AGP 2 isoforms. The glycopeptide fragmentations by collision-induced dissociation or higher-energy collisional dissociation (HCD) varied based on the MS analyzer. Orbitrap Elite identified the greatest number of AGP N-glycopeptides, followed by Triple TOF and Q-Exactive Plus. Reproducible generation of oxonium ions, glycan-cleaved glycopeptide fragment ions, and peptide backbone fragment ions was essential for successful identification. Laboratory proficiency affected the number of identified N-glycopeptides. The relative quantities of the 10 major N-glycopeptide isoforms of AGP detected in four laboratories were compared to assess reproducibility. Quantitative analysis showed that the coefficient of variation was <25% for all test samples. Our analytical protocol yielded identification and quantification of site-specific N-glycopeptide isoforms of AGP from control and disease plasma sample.

Evaluating the use of HILIC in large-scale, multi dimensional proteomics: Horses for courses?

Despite many recent advances in instrumentation, the sheer complexity of biological samples remains a major challenge in large-scale proteomics experiments, reflecting both the large number of protein isoforms and the wide dynamic range of their expression levels. However, while the dynamic range of expression levels for different components of the proteome is estimated to be ∼107-8, the equivalent dynamic range of LC-MS is currently limited to ∼106. Sample pre-fractionation has therefore become routinely used in large-scale proteomics to reduce sample complexity during MS analysis and thus alleviate the problem of ion suppression and undersampling. There is currently a wide range of chromatographic techniques that can be applied as a first dimension separation. Here, we systematically evaluated the use of hydrophilic interaction liquid chromatography (HILIC), in comparison with hSAX, as a first dimension for peptide fractionation in a bottom-up proteomics workflow. The data indicate that in addition to its role as a useful pre-enrichment method for PTM analysis, HILIC can provide a robust, orthogonal and high-resolution method for increasing the depth of proteome coverage in large-scale proteomics experiments. The data also indicate that the choice of using either HILIC, hSAX, or other methods, is best made taking into account the specific types of biological analyses being performed.

Post-translational modification of lysine residues in erythrocyte α-synuclein.

α-Synuclein is a protein linked to various synuclein-associated diseases ('synucleinopathies'), including Parkinson's disease, dementia with Lewy Bodies and multiple system atrophy, and is highly expressed in the central nervous system and in erythrocytes. Moreover, α-synuclein-containing erythrocyte-derived extracellular vesicles may be involved in the pathogenesis of synucleinopathies and their progression across the blood-brain barrier. Several post-translational modifications of α-synuclein have been reported in brain inclusions, including S129 phosphorylation, but fewer have been found in erythrocytes. In this study, we analysed the post-translational modifications of erythrocyte α-synuclein using liquid chromatography-mass spectrometry. We found that all lysine residues in the α-synuclein protein could be modified by acetylation, glycation, ubiquitination or SUMOylation but that phosphorylation, nitration and acylation were uncommon minor post-translational modifications in erythrocytes. Since the post-translational modification of lysine residues has been implicated in both membrane association and protein clearance, our findings provide new insight into how synucleinopathies may progress and suggest possible therapeutic strategies designed to target α-synuclein.

Histone modification in Saccharomyces cerevisiae: A review of the current status.

The budding yeast Saccharomyces cerevisiae is a well-characterized and popular model system for investigating histone modifications and the inheritance of chromatin states. The data obtained from this model organism have provided essential and critical information for understanding the complexity of epigenetic interactions and regulation in eukaryotes. Recent advances in biotechnology have facilitated the detection and quantitation of protein post-translational modification (PTM), including acetylation, methylation, phosphorylation, ubiquitylation, sumoylation, and acylation, and led to the identification of several novel modification sites in histones. Determining the cellular function of these new histone markers is essential for understanding epigenetic mechanisms and their impact on various biological processes. In this review, we describe recent advances and current views on histone modifications and their effects on chromatin dynamics in S. cerevisiae.

Discovery of a biomarker for ß-Thalassemia by HPLC-MS and improvement from Proton Transfer Reaction - Parallel Ion Parking.

ß-thalassemia is a quantitative hemoglobin (Hb) disorder resulting in reduced production of Hb A and increased levels of Hb A2. Diagnosis of ß-thalassemia can be problematic when combined with other structural Hb variants, so that the separation approaches in routine clinical centers are not sufficiently decisive to obtain accurate results. Here, we separate the intact Hb subunits by high-performance liquid chromatography, followed by top-down tandem mass spectrometry of intact subunits to distinguish Hb variants. Proton transfer reaction-parallel ion parking (PTR-PIP), in which a radical anion removes protons from multiply charged precursor ions and produces charge-reduced ions spanning a limited m/z range, was used to increase the signal-to-noise ratio of the subunits of interest. We demonstrate that the δ/ß ratio can act as a biomarker to identify ß-thalassemia in normal electrospray ionization MS1 and PTR-PIP MS1. The application of PTR-PIP significantly increases the sensitivity and specificity of the HPLC-MS method to identify δ/ß ratio as a thalassemia biomarker.

Computational tools for exploring peptide-membrane interactions in gram-positive bacteria.

The vital cellular functions in Gram-positive bacteria are controlled by signaling molecules known as quorum sensing peptides (QSPs), considered promising therapeutic interventions for bacterial infections. In the bacterial system QSPs bind to membrane-coupled receptors, which then auto-phosphorylate and activate intracellular response regulators. These response regulators induce target gene expression in bacteria. One of the most reliable trends in drug discovery research for virulence-associated molecular targets is the use of peptide drugs or new functionalities. In this perspective, computational methods act as auxiliary aids for biologists, where methodologies based on machine learning and in silico analysis are developed as suitable tools for target peptide identification. Therefore, the development of quick and reliable computational resources to identify or predict these QSPs along with their receptors and inhibitors is receiving considerable attention. The databases such as Quorumpeps and Quorum Sensing of Human Gut Microbes (QSHGM) provide a detailed overview of the structures and functions of QSPs. The tools and algorithms such as QSPpred, QSPred-FL, iQSP, EnsembleQS and PEPred-Suite have been used for the generic prediction of QSPs and feature representation. The availability of compiled key resources for utilizing peptide features based on amino acid composition, positional preferences, and motifs as well as structural and physicochemical properties, including biofilm inhibitory peptides, can aid in elucidating the QSP and membrane receptor interactions in infectious Gram-positive pathogens. Herein, we present a comprehensive survey of diverse computational approaches that are suitable for detecting QSPs and QS interference molecules. This review highlights the utility of these methods for developing potential biomarkers against infectious Gram-positive pathogens.

Drugging the Epigenome: Overcoming Resistance to Targeted and Immunotherapies in Melanoma.

This past decade has seen tremendous advances in understanding the molecular pathogenesis of melanoma and the development of novel effective therapies for melanoma. Targeted therapies and immunotherapies that extend survival of patients with advanced disease have been developed; however, the vast majority of patients experience relapse and therapeutic resistance over time. Moreover, cellular plasticity has been demonstrated to be a driver of therapeutic resistance mechanisms in melanoma and other cancers, largely functioning through epigenetic mechanisms, suggesting that targeting of the cancer epigenetic landscape may prove a worthwhile endeavor to ensure durable treatment responses and cures. Here, we review the epigenetic alterations that characterize melanoma development, progression, and resistance to targeted therapies as well as epigenetic therapies currently in use and under development for melanoma and other cancers. We further assess the landscape of epigenetic therapies in clinical trials for melanoma and provide a framework for future advances in epigenetic therapies to circumvent the development of therapeutic resistance in melanoma.

Molecular phenotyping approaches for the detection and monitoring of carbapenem-resistant Enterobacteriaceae by mass spectrometry.

Antimicrobial resistance is increasing in prevalence and there is a clear need for the development of rapid detection methods in clinical diagnostics. This review explores -omics studies utilising mass spectrometry to investigate the molecular phenotype associated with carbapenem resistance. Whilst the specific mechanisms of carbapenem resistance are well characterised, the resistant phenotype is poorly understood. Understanding how the acquisition of resistance affects cellular physiology and cell metabolism through molecular phenotyping is a necessary step towards detecting resistance by diagnostic means. In addition, this article examines the potential of mass spectrometry for the identification of resistance biomarkers through molecular profiling of bacteria. Developments in mass spectrometry platforms are expanding the biomarker-based diagnostic landscape. Targeted measures, such as high-resolution mass spectrometry coupled with chromatographic separation show considerable promise for the identification of molecular signatures and the development of a rapid diagnostic assay for the detection of carbapenem resistance.

Infrared multiple photon dissociation (IRMPD) spectroscopy and its potential for the clinical laboratory.

Infrared multiple photon dissociation (IRMPD) spectroscopy is a powerful tool used to probe the vibrational modes-and, by extension, the structure-of an ion within an ion trap mass spectrometer. Compared to traditional FTIR spectroscopy, IRMPD spectroscopy has advantages including its sensitivity and its relative ability to handle complex mixtures. While IRMPD has historically been a technique for fundamental analyses, it is increasingly being applied in a more analytical fashion. Notable recent demonstrations pertinent to the clinical laboratory and adjacent interests include analysis of modified amino acids/residues and carbohydrates, structural elucidation (including isomeric differentiation) of metabolites, identification of novel illicit drugs, and structural studies of various biomolecules and pharmaceuticals. Improvements in analysis time, coupling to commercial instruments, and integration with separations methods are all drivers toward the realization of these analytical applications. Additional improvements in these areas, along with advances in benchtop tunable IR sources and increased cross-discipline collaboration, will continue to drive innovation and widespread adoption. The goal of this tutorial article is to briefly present the fundamentals and instrumentation of IRMPD spectroscopy, as an overview of the utility of this technique for helping to answer questions relevant to clinical analysis, and to highlight limitations to widespread adoption, as well as promising directions in which the field may be heading.

Post-Translational Modification of Cav1.2 and its Role in Neurodegenerative Diseases.

Cav1.2 plays an essential role in learning and memory, drug addiction, and neuronal development. Intracellular calcium homeostasis is disrupted in neurodegenerative diseases because of abnormal Cav1.2 channel activity and modification of downstream Ca2+ signaling pathways. Multiple post-translational modifications of Cav1.2 have been observed and seem to be closely related to the pathogenesis of neurodegenerative diseases. The specific molecular mechanisms by which Cav1.2 channel activity is regulated remain incompletely understood. Dihydropyridines (DHPs), which are commonly used for hypertension and myocardial ischemia, have been repurposed to treat PD and AD and show protective effects. However, further studies are needed to improve delivery strategies and drug selectivity. Better knowledge of channel modulation and more specific methods for altering Cav1.2 channel function may lead to better therapeutic strategies for neurodegenerative diseases.

Native and non-native host assessment towards metabolic pathway reconstructions of plant natural products.

Plant-based biopreparations are reasonably priced and are devoid of viral, prion and endotoxin contaminants. However, synthesizing these natural plant products by chemical methods is quite expensive. The structural complexity of plant-derived natural products poses a challenge for chemical synthesis at a commercial scale. Failure of commercial-scale synthesis is the chief reason why metabolic reconstructions in heterologous hosts are inevitable. This review discusses plant metabolite pathway reconstructions experimented in various heterologous hosts, and the inherent challenges involved. Plants as native hosts possess enhanced post-translational modification ability, along with rigorous gene edits, unlike microbes. To achieve a high yield of metabolites in plants, increased cell division rate is one of the requisites. This improved cell division rate will promote cellular homogeneity. Incorporation and maintenance of plant cell synchrony, in turn, can program stable product scale-up.

Cracking the Skin Barrier: Liquid-Liquid Phase Separation Shines under the Skin.

Central to forming and sustaining the skin's barrier, epidermal keratinocytes (KCs) fluxing to the skin surface undergo a rapid and enigmatic transformation into flat, enucleated squames. At the crux of this transformation are intracellular keratohyalin granules (KGs) that suddenly disappear as terminally differentiating KCs transition to the cornified skin surface. Defects in KGs have long been linked to skin barrier disorders. Through the biophysical lens of liquid-liquid phase separation (LLPS), these enigmatic KGs recently emerged as liquid-like membraneless organelles whose assembly and subsequent pH-triggered disassembly drive squame formation. To stimulate future efforts toward cracking the complex process of skin barrier formation, in this review, we integrate the key concepts and foundational work spanning the fields of LLPS and epidermal biology. We review the current progress in the skin and discuss implications in the broader context of membraneless organelles across stratifying epithelia. The discovery of environmentally sensitive LLPS dynamics in the skin points to new avenues for dissecting the skin barrier and for addressing skin barrier disorders. We argue that skin and its appendages offer outstanding models to uncover LLPS-driven mechanisms in tissue biology.

VectorMOD: Method for Bottom-Up Proteomic Characterization of rAAV Capsid Post-Translational Modifications and Vector Impurities.

Progress in recombinant AAV gene therapy product and process development has advanced our understanding of the basic biology of this critical delivery vector. The discovery of rAAV capsid post-translational modifications (PTMs) has spurred interest in the field for detailed rAAV-specific methods for vector lot characterization by mass spectrometry given the unique challenges presented by this viral macromolecular complex. Recent concerns regarding immunogenic responses to systemically administered rAAV at high doses has highlighted the need for investigators to catalog and track potentially immunogenic vector lot components including capsid PTMs and PTMs on host cell protein impurities. Here we present a simple step-by-step guide for academic rAAV laboratories and Chemistry, Manufacturing and Control (CMC) groups in industry to perform an in-house or outsourced bottom-up mass spectrometry workflow to characterize capsid PTMs and process impurities.

Methods for Proteomic Analyses of Mycobacteria.

The use of proteomic technologies to characterize and study the proteome of mycobacteria has provided important information in terms of function, diversity, protein-protein interactions, and host-pathogen interactions in Mycobacterium spp. There are many different mass spectrometry methodologies that can be applied to proteomics studies of mycobacteria and microorganisms in general. Sample processing and appropriate study design are critical to generating high-quality data regardless of the mass spectrometry method applied. Appropriate study design relies on statistical rigor and data curation using bioinformatics approaches that are widely applicable regardless of the organism or system studied. Sample processing, on the other hand, is often a niched process specific to the physiology of the organism or system under investigation. Therefore, in this chapter, we will provide protocols for processing mycobacterial protein samples for the specific application of Top-down and Bottom-up proteomic analyses.

The role of the multifaceted long non-coding RNAs: A nuclear-cytosolic interplay to regulate hyaluronan metabolism.

In the extracellular matrix (ECM), the glycosaminoglycan (GAG) hyaluronan (HA) has different physiological roles favouring hydration, elasticity and cell survival. Three different isoforms of HA synthases (HAS1, 2, and 3) are responsible for the production of HA. In several pathologies the upregulation of HAS enzymes leads to an abnormal HA accumulation causing cell dedifferentiation, proliferation and migration thus favouring cancer progression, fibrosis and vascular wall thickening. An intriguing new player in HAS2 gene expression regulation and HA production is the long non-coding RNA (lncRNA) hyaluronan synthase 2 antisense 1 (HAS2-AS1). A significant part of mammalian genomes corresponds to genes that transcribe lncRNAs; they can regulate gene expression through several mechanisms, being involved not only in maintaining the normal homeostasis of cells and tissues, but also in the onset and progression of different diseases, as demonstrated by the increasing number of studies published through the last decades. HAS2-AS1 is no exception: it can be localized both in the nucleus and in the cytosol, regulating cancer cells as well as vascular smooth muscle cells behaviour.

Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome - A multi-omics big data study.

Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19.

Cardio-Oncology: Understanding the Intersections Between Cardiac Metabolism and Cancer Biology.

An important priority in the cardiovascular care of oncology patients is to reduce morbidity and mortality, and improve the quality of life in cancer survivors through cross-disciplinary efforts. The rate of survival in cancer patients has improved dramatically over the past decades. Nonetheless, survivors may be more likely to die from cardiovascular disease in the long term, secondary, not only to the potential toxicity of cancer therapeutics, but also to the biology of cancer. In this context, efforts from basic and translational studies are crucial to understanding the molecular mechanisms causal to cardiovascular disease in cancer patients and survivors, and identifying new therapeutic targets that may prevent and treat both diseases. This review aims to highlight our current understanding of the metabolic interaction between cancer and the heart, including potential therapeutic targets. An overview of imaging techniques that can support both research studies and clinical management is also provided. Finally, this review highlights opportunities and challenges that are necessary to advance our understanding of metabolism in the context of cardio-oncology.

Human hepatitis D virus-specific T cell epitopes.

HDV is a small, defective RNA virus that requires the HBsAg of HBV for its assembly, release, and transmission. Chronic HBV/HDV infection often has a severe clinical outcome and is difficult to treat. The important role of a robust virus-specific T cell response for natural viral control has been established for many other chronic viral infections, but the exact role of the T cell response in the control and progression of chronic HDV infection is far less clear. Several recent studies have characterised HDV-specific CD4+ and CD8+ T cell responses on a peptide level. This review comprehensively summarises all HDV-specific T cell epitopes described to date and describes our current knowledge of the role of T cells in HDV infection. While we now have better tools to study the adaptive anti-HDV-specific T cell response, further efforts are needed to define the HLA restriction of additional HDV-specific T cell epitopes, establish additional HDV-specific MHC tetramers, understand the degree of cross HDV genotype reactivity of individual epitopes and understand the correlation of the HBV- and HDV-specific T cell response, as well as the breadth and specificity of the intrahepatic HDV-specific T cell response.

Genome mining strategies for ribosomally synthesised and post-translationally modified peptides.

Genome mining is a computational method for the automatic detection and annotation of biosynthetic gene clusters (BGCs) from genomic data. This approach has been increasingly utilised in natural product (NP) discovery due to the large amount of sequencing data that is now available. Ribosomally synthesised and post-translationally modified peptides (RiPPs) are a class of structurally complex NP with diverse bioactivities. RiPPs have recently been shown to occupy a much larger expanse of genomic and chemical space than previously appreciated, indicating that annotation of RiPP BGCs in genomes may have been overlooked in the past. This review provides an overview of the genome mining tools that have been specifically developed to aid in the discovery of RiPP BGCs, which have been built from an increasing knowledgebase of RiPP structures and biosynthesis. Given these recent advances, the application of targeted genome mining has great potential to accelerate the discovery of important molecules such as antimicrobial and anticancer agents whilst increasing our understanding about how these compounds are biosynthesised in nature.