Quantitative Comparison of Proteomes Using SILAC

Measuring 15N and 13C Enrichment Levels in Sparsely Labeled Proteins Using High-Resolution and Tandem Mass Spectrometry

Isotope labeling of both 15N and 13C in selected amino acids in a protein, known as sparse labeling, is an alternative to uniform labeling and is particularly useful for proteins that must be expressed using mammalian cells, including glycoproteins. High levels of enrichment in the selected amino acids enable multidimensional heteronuclear NMR measurements of glycoprotein three-dimensional structure. Mass spectrometry provides a means to quantify the degree of enrichment. Mass spectrometric measurements of tryptic peptides of a selectively labeled glycoprotein expressed in HEK293 cells revealed complicated isotope patterns which consisted of many overlapping isotope patterns from intermediately labeled peptides, which complicates the determination of the label incorporation. Two challenges are uncovered by these measurements. Metabolic scrambling of amino groups can reduce the 15N content of enriched amino acids or increase the 15N in nontarget amino acids. Also, undefined, unlabeled medium components may dilute the enrichment level of labeled amino acids. The impact of this unexpected metabolic scrambling was overcome by simulating isotope patterns for all isotope-labeled peptide states and generating linear combinations to fit to the data. This method has been used to determine the percent incorporation of 15N and 13C labels and has identified several metabolic scrambling effects that were previously undetected in NMR experiments. Ultrahigh mass resolution is also utilized to obtain isotopic fine structure, from which enrichment levels of 15N and 13C can be assigned unequivocally. Finally, tandem mass spectrometry can be used to confirm the location of heavy isotope labels in the peptides.

Automated Assignment of 15N And 13C Enrichment Levels in Doubly-Labeled Proteins

Uniform enrichment of 15N and 13C in proteins is commonly employed for 2D heteronuclear NMR measurements of the three-dimensional protein structure. Achieving a high degree of enrichment of both elements is important for obtaining high quality data. Uniform labeling of proteins and glycoproteins expressed in higher organisms (yeast or mammalian cell lines) is more challenging than expression in Escherichia coli, a prokaryote that grows on simple, chemically defined media but does not provide appropriate eukaryotic modifications. It is difficult to achieve complete incorporation of both heavy isotopes, and quality control measures are important for quantitating the level of their enrichment. Mass spectrometry measurements of the isotopic distribution of the intact protein or its proteolytic fragments provide the means to assess the enrichment level. A mass accuracy of 1 ppm or better is shown to be required to distinguish the correct combination of 13C and 15N enrichment due to subtle shifts in peak centroids with differences in the underlying, but unresolved, isotopic fine structure. A simple computer program was developed to optimize the fitting of experimental isotope patterns to statistically derived distributions. This method can determine the isotopic abundance from isotope patterns and isotopologue masses in conventional MS data for peptides, intact proteins, and glycans. For this purpose, MATLAB's isotope simulator, isotopicdist, has been modified to permit the variation of 15N and 13C enrichment levels and to perform a two-dimensional grid search of enrichment levels of both isotopes. We also incorporated an alternate isotope simulator, js-emass, into MATLAB for use in the same fitting program. Herein we benchmark this technique on natural abundance ubiquitin and uniformly [15N,13C]-labeled ubiquitin at both the intact and peptide level, outline considerations for data quality and mass accuracy, and report several improvements we have made to the previously reported analysis of the [15N,13C]-enriched human IgG Fc domain, a glycoprotein that has been expressed in Saccharomyces cerevisiae.

Astrocyte-induced Cdk5 expedites breast cancer brain metastasis by suppressing MHC-I expression to evade immune recognition

Brain metastases (BrMs) evade the immune response to develop in the brain, yet the mechanisms of BrM immune evasion remains unclear. This study shows that brain astrocytes induce the overexpression of neuronal-specific cyclin-dependent kinase 5 (Cdk5) in breast cancer-derived BrMs, which facilitates BrM outgrowth in mice. Cdk5-overexpressing BrMs exhibit reduced expression and function of the class I major histocompatibility complex (MHC-I) and antigen-presentation pathway, which are restored by inhibiting Cdk5 genetically or pharmacologically, as evidenced by single-cell RNA sequencing and functional studies. Mechanistically, Cdk5 suppresses MHC-I expression on the cancer cell membrane through the Irf2bp1-Stat1-importin α-Nlrc5 pathway, enabling BrMs to avoid recognition by T cells. Treatment with roscovitine-a clinically applicable Cdk5 inhibitor-alone or combined with immune checkpoint inhibitors, significantly reduces BrM burden and increases tumour-infiltrating functional CD8+ lymphocytes in mice. Thus, astrocyte-induced Cdk5 overexpression endorses BrM immune evasion, whereas therapeutically targeting Cdk5 markedly improves the efficacy of immune checkpoint inhibitors and inhibits BrM growth.

Fe-S cluster biosynthesis and maturation: Mass spectrometry-based methods advancing the field

Iron‑sulfur (FeS) clusters are inorganic protein cofactors that perform essential functions in many physiological processes. Spectroscopic techniques have historically been used to elucidate details of FeS cluster type, their assembly and transfer, and changes in redox and ligand binding properties. Structural probes of protein topology, complex formation, and conformational dynamics are also necessary to fully understand these FeS protein systems. Recent developments in mass spectrometry (MS) instrumentation and methods provide new tools to investigate FeS cluster and structural properties. With the unique advantage of sampling all species in a mixture, MS-based methods can be utilized as a powerful complementary approach to probe native dynamic heterogeneity, interrogate protein folding and unfolding equilibria, and provide extensive insight into protein binding partners within an entire proteome. Here, we highlight key advances in FeS protein studies made possible by MS methodology and contribute an outlook for its role in the field.

Bioorthogonal non-canonical amino acid tagging to track transplanted human induced pluripotent stem cell-specific proteome

BACKGROUND

Human induced pluripotent stem cells (hiPSCs) and their differentiated cell types have a great potential for tissue repair and regeneration. While the primary focus of using hiPSCs has historically been to regenerate damaged tissue, emerging studies have shown a more potent effect of hiPSC-derived paracrine factors on tissue regeneration. However, the precise contents of the transplanted hiPSC-derived cell secretome are ambiguous. This is mainly due to the lack of tools to distinguish cell-specific secretome from host-derived proteins in a complex tissue microenvironment in vivo.

METHODS

In this study, we present the generation and characterization of a novel hiPSC line, L274G-hiPSC, expressing the murine mutant methionyl-tRNA synthetase, L274GMmMetRS, which can be used for tracking the cell specific proteome via biorthogonal non-canonical amino acid tagging (BONCAT). We assessed the trilineage differentiation potential of the L274G-hiPSCs in vitro and in vivo. Furthermore, we assessed the cell-specific proteome labelling in the L274G-hiPSC derived cardiomyocytes (L274G-hiPSC-CMs) in vitro following co-culture with wild type human umbilical vein derived endothelial cells and in vivo post transplantation in murine hearts.

RESULTS

We demonstrated that the L274G-hiPSCs exhibit typical hiPSC characteristics and that we can efficiently track the cell-specific proteome in their differentiated progenies belonging to the three germ lineages, including L274G-hiPSC-CMs. Finally, we demonstrated cell-specific BONCAT in transplanted L274G-hiPSC-CMs.

CONCLUSION

The novel L274G-hiPSC line can be used to study the cell-specific proteome of hiPSCs in vitro and in vivo, to delineate mechanisms underlying hiPSC-based cell therapies for a variety of regenerative medicine applications.

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Selenium-based metabolic oligosaccharide engineering strategy for quantitative glycan detection

Metabolic oligosaccharide engineering (MOE) is a classical chemical approach to perturb, profile and perceive glycans in physiological systems, but probes upon bioorthogonal reaction require accessibility and the background signal readout makes it challenging to achieve glycan quantification. Here we develop SeMOE, a selenium-based metabolic oligosaccharide engineering strategy that concisely combines elemental analysis and MOE,enabling the mass spectrometric imaging of glycome. We also demonstrate that the new-to-nature SeMOE probes allow for detection, quantitative measurement and visualization of glycans in diverse biological contexts. We also show that chemical reporters on conventional MOE can be integrated into a bifunctional SeMOE probe to provide multimodality signal readouts. SeMOE thus provides a convenient and simplified method to explore the glyco-world.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Rapid headspace solid-phase microextraction sheets with direct analysis in real time mass spectrometry (SPMESH-DART-MS) of derivatized volatile phenols in grape juices and wines

Volatile phenols possess "smoky, spicy" aromas and are routinely measured in grapes, wines and other foodstuffs for quality control. Routine analyses of volatile phenols rely on gas chromatography - mass spectrometry (GC-MS), but slow throughput of GC-MS can cause challenges during times of surge demand, i.e. following 'smoke taint' events involving forest fires near vineyards. Parallel extraction of headspace volatiles onto sorbent sheets (HS-SPMESH) followed by direct analysis in real time mass spectrometry (DART-MS) is a rapid alternative to conventional GC-MS approaches. However, HS-SPMESH extraction is poorly suited for lower volatility odorants, including volatile phenols. This work reports development and validation of an HS-SPMESH-DART-MS approach for five volatile phenols (4-ethylphenol, 4-ethylguiacol, guaiacol, 4-methylguaiacol, and cresols). Prior to HS-SPMESH extraction, volatile phenols were acetylated to facilitate their extraction. A unique feature of this work was the use of d₆-Ac₂O as a derivatizing agent to overcome issues with isobaric interferences inherent to chromatography-free MS techniques. The use of alkaline conditions during derivatization resulted in cumulative measurement of both free and bound forms of volatile phenols. The validated HS-SPMESH-DART-MS method achieved a throughput of 24 samples in ∼60 min (including derivatization and extraction time) with low limits of detection (<1 μg L^-1) and good repeatability (3-6% RSD) in grape and wine matrices. Validation experiments with smoke-tainted grape samples indicated good correlation between total (free + bound) volatile phenols measured by HS-SPMESH-DART-MS and a gold standard GC-MS method.

Small-molecule probes from bench to bedside: advancing molecular analysis of drug-target interactions toward precision medicine

Over the past decade, remarkable advances have been witnessed in the development of small-molecule probes. These molecular tools have been widely applied for interrogating proteins, pathways and drug-target interactions in preclinical research. While novel structures and designs are commonly explored in probe development, the clinical translation of small-molecule probes remains limited, primarily due to safety and regulatory considerations. Recent synergistic developments - interfacing novel chemical probes with complementary analytical technologies - have introduced and expedited diverse biomedical opportunities to molecularly characterize targeted drug interactions directly in the human body or through accessible clinical specimens (e.g., blood and ascites fluid). These integrated developments thus offer unprecedented opportunities for drug development, disease diagnostics and treatment monitoring. In this review, we discuss recent advances in the structure and design of small-molecule probes with novel functionalities and the integrated development with imaging, proteomics and other emerging technologies. We further highlight recent applications of integrated small-molecule technologies for the molecular analysis of drug-target interactions, including translational applications and emerging opportunities for whole-body imaging, tissue-based measurement and blood-based analysis.

Protein biomarkers for radiation injury and testing of medical countermeasure efficacy: promises, pitfalls, and future directions

INTRODUCTION

Radiological/nuclear accidents, hostile military activity, or terrorist strikes have the potential to expose a large number of civilians and military personnel to high doses of radiation resulting in the development of acute radiation syndrome and delayed effects of exposure. Thus, there is an urgent need for sensitive and specific assays to assess the levels of radiation exposure to individuals. Such radiation exposures are expected to alter primary cellular proteomic processes, resulting in multifaceted biological responses.

AREAS COVERED

This article covers the application of proteomics, a promising and fast developing technology based on quantitative and qualitative measurements of protein molecules for possible rapid measurement of radiation exposure levels. Recent advancements in high-resolution chromatography, mass spectrometry, high-throughput, and bioinformatics have resulted in comprehensive (relative quantitation) and precise (absolute quantitation) approaches for the discovery and accuracy of key protein biomarkers of radiation exposure. Such proteome biomarkers might prove useful for assessing radiation exposure levels as well as for extrapolating the pharmaceutical dose of countermeasures for humans based on efficacy data generated using animal models.

EXPERT OPINION

The field of proteomics promises to be a valuable asset in evaluating levels of radiation exposure and characterizing radiation injury biomarkers.

An integrated workflow for phosphopeptide identification in natural killer cells (NK-92MI) and their targets (MDA-MB-231) during immunological synapse formation

Here, we present a protocol to identify and quantify phosphopeptides during the dynamic formation of an immunological synapse. We describe steps for mixing isotope-labeled immune and target cells, the stabilization of cell-to-cell conjugates by cross-linking, and their isolation by fluorescence-activated cell sorting. We detail the isolation of phosphopeptides by phosphopeptide enrichment and their subsequent measurement by mass spectrometry. Finally, we describe the analysis of the resulting data to separate cell-specific phosphopeptides using the isotope label and label-free quantification.

A guide to mass spectrometric analysis of extracellular vesicle proteins for biomarker discovery

Exosomes (small extracellular vesicles) in living organisms play an important role in processes such as cell proliferation or intercellular communication. Recently, exosomes have been extensively investigated for biomarker discoveries for various diseases. An important aspect of exosome analysis involves the development of enrichment methods that have been introduced for successful isolation of exosomes. These methods include ultracentrifugation, size exclusion chromatography, polyethylene glycol-based precipitation, immunoaffinity-based enrichment, ultrafiltration, and asymmetric flow field-flow fractionation among others. To confirm the presence of exosomes, various characterization methods have been utilized such as Western blot analysis, atomic force microscopy, electron microscopy, optical methods, zeta potential, visual inspection, and mass spectrometry. Recent advances in high-resolution separations, high-performance mass spectrometry and comprehensive proteome databases have all contributed to the successful analysis of exosomes from patient samples. Herein we review various exosome enrichment methods, characterization methods, and recent trends of exosome investigations using mass spectrometry-based approaches for biomarker discovery.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

SILAC-Based Quantitative Phosphoproteomics in Yeast

In this chapter, detailed procedures for stable isotope labeling with amino acids in cell culture, SILAC labeling of yeast auxotroph, optimization and evaluation of phosphopeptide enrichment, and sample preparation and analysis by high-resolution LC-MS/M, identification of phosphosites, and quantification methods are described.We report methods for the application of double SILAC to yeast using a combination of labeled lysine and labeled arginine.The combination of SILAC-based quantitation with phosphopeptides enrichment by TiO₂ in a batch that enables measurement of protein posttranslational modifications is a powerful application to analyze the global phosphoproteome for studies in signaling pathways.

Increasing cell size remodels the proteome and promotes senescence

Cell size is tightly controlled in healthy tissues, but it is unclear how deviations in cell size affect cell physiology. To address this, we measured how the cell's proteome changes with increasing cell size. Size-dependent protein concentration changes are widespread and predicted by subcellular localization, size-dependent mRNA concentrations, and protein turnover. As proliferating cells grow larger, concentration changes typically associated with cellular senescence are increasingly pronounced, suggesting that large size may be a cause rather than just a consequence of cell senescence. Consistent with this hypothesis, larger cells are prone to replicative, DNA-damage-induced, and CDK4/6i-induced senescence. Size-dependent changes to the proteome, including those associated with senescence, are not observed when an increase in cell size is accompanied by an increase in ploidy. Together, our findings show how cell size could impact many aspects of cell physiology by remodeling the proteome and provide a rationale for cell size control and polyploidization.

Polyphenols from Thinned Young Apples: HPLC-HRMS Profile and Evaluation of Their Anti-Oxidant and Anti-Inflammatory Activities by Proteomic Studies

The qualitative profile of thinned apple polyphenols (TAP) fraction (≈24% of polyphenols) obtained by purification through absorbent resin was fully investigated by LC-HRMS in positive and negative ion mode and using ESI source. A total of 68 polyphenols were identified belonging to six different classes: flavanols, flavonols, dihydrochalchones, flavanones, flavones and organic and phenolic acids. The antioxidant and anti-inflammatory activities were then investigated in cell models with gene reporter for NRF2 and NF-κB and by quantitative proteomic (label-free and SILAC) approaches. TAP dose-dependently activated NRF2 and in the same concentration range (10–250 µg/mL) inhibited NF-κB nuclear translocation induced by TNF-α and IL-1α as pro-inflammatory promoters. Proteomic studies elucidated the molecular pathways evoked by TAP treatment: activation of the NRF2 signaling pathway, which in turn up-regulates protective oxidoreductases and their nucleophilic substrates such as GSH and NADPH, the latter resulting from the up-regulation of the pentose phosphate pathway. The increase in the enzymatic antioxidant cellular activity together with the up-regulation of the heme-oxygenase would explain the anti-inflammatory effect of TAP. The results suggest that thinned apples can be considered as a valuable source of apple polyphenols to be used in health care products to prevent/treat oxidative and inflammatory chronic conditions.

Post-transcriptional regulation of ATG1 is a critical node that modulates autophagy during distinct nutrient stresses

Macroautophagy/autophagy is a highly conserved nutrient-recycling pathway that eukaryotes utilize to combat diverse stresses including nutrient depletion. Dysregulation of autophagy disrupts cellular homeostasis leading to starvation susceptibility in yeast and disease development in humans. In yeast, the robust autophagy response to starvation is controlled by the upregulation of ATG genes, via regulatory processes involving multiple levels of gene expression. Despite the identification of several regulators through genetic studies, the predominant mechanism of regulation modulating the autophagy response to subtle differences in nutrient status remains undefined. Here, we report the unexpected finding that subtle changes in nutrient availability can cause large differences in autophagy flux, governed by hitherto unknown post-transcriptional regulatory mechanisms affecting the expression of the key autophagyinducing kinase Atg1 (ULK1/ULK2 in mammals). We have identified two novel post-transcriptional regulators of ATG1 expression, the kinase Rad53 and the RNA-binding protein Ded1 (DDX3 in mammals). Furthermore, we show that DDX3 regulates ULK1 expression post-transcriptionally, establishing mechanistic conservation and highlighting the power of yeast biology in uncovering regulatory mechanisms that can inform therapeutic approaches.

An overview of technologies for MS-based proteomics-centric multi-omics

INTRODUCTION

Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems.

AREAS COVERED

Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics.

EXPERT COMMENTARY

Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.

A photoaffinity labeling strategy identified EF1A1 as a binding protein of cyclic dinucleotide 2'3'-cGAMP

2'3'-cyclic GMP-AMP (2'3'-cGAMP), generated by cyclic GMP-AMP synthase (cGAS) under activation by cytosolic DNA, has a vital role in innate immune response via its receptor protein stimulator of interferon genes (STING) to fight viral infections and tumors. In order to have a complete understanding of biological functions of 2'3'-cGAMP, it is important to find out whether 2'3'-cGAMP has other unrevealed binding proteins present in mammalian cells and executes unknown functions. Here we report the 2'3'-cGAMP-based photoaffinity probes that capture and isolate 2'3'-cGAMP-binding proteins. These probes enable the identification of some potential 2'3'-cGAMP-binding proteins from HeLa cells. EF1A1, an essential protein regulating protein synthesis, is further validated to associate with 2'3'-cGAMP in vitro and in cells to impede protein synthesis. Thus, our studies provide a powerful approach to enable identification of the 2'3'-cGAMP interactome, discover unknown functions of 2'3'-cGAMP, and understand its physiological/pathological roles in tumor immunity and immune-related diseases.

Evaluating Spatiotemporal Dynamics of Phosphorylation of RNA Polymerase II Carboxy-Terminal Domain by Ultraviolet Photodissociation Mass Spectrometry

The critical role of site-specific phosphorylation in eukaryotic transcription has motivated efforts to decipher the complex phosphorylation patterns exhibited by the carboxyl-terminal domain (CTD) of RNA polymerase II. Phosphorylation remains a challenging post-translational modification to characterize by mass spectrometry owing to the labile phosphate ester linkage and low stoichiometric prevalence, two features that complicate analysis by high-throughput MS/MS methods. Identifying phosphorylation sites represents one significant hurdle in decrypting the CTD phosphorylation, a problem exaggerated by a large number of potential phosphorylation sites. An even greater obstacle is decoding the dynamic phosphorylation pattern along the length of the periodic CTD sequence. Ultraviolet photodissociation (UVPD) is a high-energy ion activation method that provides ample backbone cleavages of peptides while preserving labile post-translational modifications that facilitate their confident localization. Herein, we report a quantitative parallel reaction monitoring (PRM) method developed to monitor spatiotemporal changes in site-specific Ser5 phosphorylation of the CTD by cyclin-dependent kinase 7 (CDK7) using UVPD for sequence identification, phosphosite localization, and differentiation of phosphopeptide isomers. We capitalize on the series of phospho-retaining fragment ions produced by UVPD to create unique transition lists that are pivotal for distinguishing the array of phosphopeptides generated from the CTD.

Clinical and Neurobiological Aspects of TAO Kinase Family in Neurodevelopmental Disorders

Despite the complexity of neurodevelopmental disorders (NDDs), from their genotype to phenotype, in the last few decades substantial progress has been made in understanding their pathophysiology. Recent accumulating evidence shows the relevance of genetic variants in thousand and one (TAO) kinases as major contributors to several NDDs. Although it is well-known that TAO kinases are a highly conserved family of STE20 kinase and play important roles in multiple biological processes, the emerging roles of TAO kinases in neurodevelopment and NDDs have yet to be intensively discussed. In this review article, we summarize the potential roles of the TAO kinases based on structural and biochemical analyses, present the genetic data from clinical investigations, and assess the mechanistic link between the mutations of TAO kinases, neuropathology, and behavioral impairment in NDDs. We then offer potential perspectives from basic research to clinical therapies, which may contribute to fully understanding how TAO kinases are involved in NDDs.

Dissecting the Structural Dynamics of the Nuclear Pore Complex

Cellular processes are largely carried out by macromolecular assemblies, most of which are dynamic, having components that are in constant flux. One such assembly is the nuclear pore complex (NPC), an ∼50 MDa assembly comprised of ∼30 different proteins called Nups that mediates selective macromolecular transport between the nucleus and cytoplasm. We developed a proteomics method to provide a comprehensive picture of the yeast NPC component dynamics. We discovered that, although all Nups display uniformly slow turnover, their exchange rates vary considerably. Surprisingly, this exchange rate was relatively unrelated to each Nup's position, accessibility, or role in transport but correlated with its structural role; scaffold-forming Nups exchange slowly, whereas flexible connector Nups threading throughout the NPC architecture exchange more rapidly. Targeted perturbations in the NPC structure revealed a dynamic resilience to damage. Our approach opens a new window into macromolecular assembly dynamics.

Approaches to Investigating the Protein Interactome of PTEN

The tumor suppressor phosphatase and tensin homologue (PTEN) is a redox-sensitive dual specificity phosphatase with an essential role in the negative regulation of the PI3K-AKT signaling pathway, affecting metabolic and cell survival processes. PTEN is commonly mutated in cancer, and dysregulation in the metabolism of PIP₃ is implicated in other diseases such as diabetes. PTEN interactors are responsible for some functional roles of PTEN beyond the negative regulation of the PI3K pathway and are thus of great importance in cell biology. Both high-data content proteomics-based approaches and low-data content PPI approaches have been used to investigate the interactome of PTEN and elucidate further functions of PTEN. While low-data content approaches rely on co-immunoprecipitation and Western blotting, and as such require previously generated hypotheses, high-data content approaches such as affinity pull-down proteomic assays or the yeast 2-hybrid system are hypothesis generating. This review provides an overview of the PTEN interactome, including redox effects, and critically appraises the methods and results of high-data content investigations into the global interactome of PTEN. The biological significance of findings from recent studies is discussed and illustrates the breadth of cellular functions of PTEN that can be discovered by these approaches.

Protein Synthesis by Day 16 Bovine Conceptuses during the Time of Maternal Recognition of Pregnancy

Interferon Tau (IFNT), the conceptus-derived pregnancy recognition signal in cattle, significantly modifies the transcriptome of the endometrium. However, the endometrium also responds to IFNT-independent conceptus-derived products. The aim of this study was to determine what proteins are produced by the bovine conceptus that may facilitate the pregnancy recognition process in cattle. We analysed by mass spectrometry the proteins present in conceptus-conditioned media (CCM) after 6 h culture of Day 16 bovine conceptuses (n = 8) in SILAC media (arginine- and lysine-depleted media supplemented with heavy isotopes) and the protein content of extracellular vesicles (EVs) isolated from uterine luminal fluid (ULF) of Day 16 pregnant (n = 7) and cyclic (n = 6) cross-bred heifers on day 16. In total, 11,122 proteins were identified in the CCM. Of these, 5.95% (662) had peptides with heavy labelled amino acids, i.e., de novo synthesised by the conceptuses. None of these proteins were detected in the EVs isolated from ULF. Pregnancy-associated glycoprotein 11, Trophoblast Kunitz domain protein 1 and DExD-Box Helicase 39A were de novo produced and present in the CCM from all conceptuses and in previously published CCM data following 6 and 24 h. A total of 463 proteins were present in the CCM from all the conceptuses in the present study, and after 6 and 24 h culture in a previous study, while expression of their transcripts was not detected in endometrium indicating that they are likely conceptus-derived. Of the proteins present in the EVs, 67 were uniquely identified in ULF from pregnant heifers; 35 of these had been previously reported in CCM from Day 16 conceptuses. This study has narrowed a set of conceptus-derived proteins that may be involved in EV-mediated IFNT-independent embryo–maternal communication during pregnancy recognition in cattle.

Identification of the differentially expressed proteins in nasopharyngeal carcinoma by proteomics

Background

We sought to determine the differences with respect to the proteome of nasopharyngeal tissues between patients with nasopharyngeal carcinoma (NPC) and healthy controls by using sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH^TM-MS) and ingenuity pathway analysis (IPA). Our primary purpose was to identify specific protein markers that can be applied for diagnosis or treatment of NPC.

Methods

The CNE-1, CNE-2 and H1299 cell lines were cultured in stable isotope labeling of amino acids in cell culture (SILAC) medium for 10 generations to obtain labeled proteins. Thirty samples of NPC and 30 healthy control nasopharyngeal tissues were collected from the Department of Otolaryngology of the First Affiliated Hospital of Jinan University. Proteome of the nasopharyngeal tissues were analyzed and compared by SWATH-MS to identify differently expressed proteins. Further, extraction of target proteins and biological pathways was performed by IPA. Super-SILAC technique and liquid chromatography-tandem mass spectrometry were used to verify the reliability of the data obtained using SWATH-MS.

Results

We identified 1,415 differentially expressed proteins between NPC patients and healthy controls. On IPA analysis, EIF2AK2 and MAPK1 proteins were found to be enriched in multiple biological pathways and functional networks.

Conclusions

The differentially expressed proteins EIF2AK2 and MAPK seem to play an important role in the biological network of NPC or may help discover the specific functional proteins of NPC. Further studies are required to identify the pathways and molecular mechanisms that underlie NPC.

Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review

Studying protein-protein interaction networks provide key evidence for the underlying molecular mechanisms. Mass spectrometry-based proteomic approaches have been playing a pivotal role in deciphering these interaction networks, along with precise quantification for individual interactions. In this mini-review we discuss the available techniques and methods for qualitative and quantitative elucidation of protein-protein interaction networks. We then summarize the down-stream computational strategies for identification and quantification of interactions from those techniques. Finally, we highlight the challenges and limitations of current computational pipelines in eliminating false positive interactors, followed by a summary of the innovative algorithms to address these issues, along with the scope for future improvements.

Proteome Analysis Using Gel-LC-MS/MS

This article describes processing of protein samples using 1D SDS gels prior to protease digestion for proteomics workflows that subsequently utilize reversed-phase nanocapillary ultra-high-pressure liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). The resulting LC-MS/MS data are used to identify peptides and thereby infer proteins present in samples ranging from simple mixtures to very complex proteomes. Bottom-up proteome studies usually involve quantitative comparisons across several or many samples. For either situation, 1D SDS gels represent a simple, widely available technique that can be used to either fractionate complex proteomes or rapidly clean up low microgram samples with minimal losses. After gel separation and staining/destaining, appropriate gel slices are excised, and in-gel reduction, alkylation, and protease digestion are performed. Digests are then processed for LC-MS/MS analysis. Protocols are described for either sample fractionation with high-throughput processing of many samples or simple cleanup without fractionation. An optional strategy is to conduct in-solution reduction and alkylation prior to running gels, which is advantageous when a large number of samples will be separated into large numbers of fractions. Optimization of trypsin digestion parameters and comparison to in-solution protease digestion are also described. © 2019 by John Wiley & Sons, Inc.