Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data.Post-translational modifications (PTMs)¹ are a rapidly expanding and important class of protein feature that broaden the functional diversity of proteins in a proteome. By definition, PTMs change protein structure and therefore have the potential to affect protein function by altering protein interactions, protein stability or catalytic activity (1, 2). As they have been found to occur on nearly every protein in the eukaryotic proteome, PTMs broadly impact nearly all known cellular processes. Over 300 different types of PTM are known, ranging from single atom modifications (e.g. oxide) to small protein modifiers (e.g. ubiquitin), which can occur on all but five amino acid residues resulting from enzymatic or nonenzymatic processes (3). Over 220,000 distinct PTM sites have been experimentally identified across ∼77,000 different proteins to date (dbPTM; http://dbptm.mbc.nctu.edu.tw/statistics.php) – numbers that continue to grow exponentially because of improved methods for high throughput detection by mass spectrometry (MS). By virtue of how they are detected, most PTM data are sequence-linked and lack structural context.The function of most PTMs is unknown because the rate of PTM detection far surpasses the rate at which any one modification can be studied empirically. Moreover, the functional impact of every PTM is likely not equivalent (4). For example, computational analysis of phosphorylation sites in yeast and human proteomes indicate that well-conserved phosphosites are more likely to have a functional consequence compared with poorly conserved sites, yet only a fraction of phosphosites are well conserved (5, 6). Consequently, the development of tools that provide functional prioritization of PTMs could have a broad impact on our understanding of protein regulation, biological mechanism, and molecular evolution.The emerging need for methods that predict the functional impact of a PTM has not yet been met. Longstanding methods capitalize predominantly on the sequence context of PTMs and have been used to predict sites of modification (expasy.org/proteomics/post-translational_modification) and to compare enzyme/substrate interactions (7–9). More recently, studies aimed at expanding the parameters associated with functional PTMs have emerged. In these cases, a set of common features correlated with functional importance are derived from the analysis of PTMs within and between organisms including: number of PTM observations at a multiple sequence alignment position (i.e. hotspots), measures of co-occurrence between different PTMs (e.g. distance between phosphorylation and ubiquitination sites), biological dynamics (up or down-regulation), and protein–protein interaction influence (7, 10–12). Recent efforts to provide structural context by linking individual PTMs to three-dimensional structures in the protein data bank (PDB) have also been described (13, 14). However, these resources are extensions of existing PTM databases that allow visualization of single instances of modification onto individual proteins, but do not provide quantitative or analytical value.In principle, combining PTM hotspot and structural analysis would offer multiple advantages over any one approach used in isolation. Sequence homology provides protein family membership—thereby clustering PTMs into hotspots for groups of proteins to provide information about: (1) the evolutionary conservation and (2) observation frequencies of PTMs within the family. A primary consequence of their sequence homology is that members of a protein family will exhibit similar structures and protein interactions—features that dictate the function of protein systems. A secondary consequence is that PTM hotspots generated by alignment can be projected onto family-representative protein structures, which places each PTM hotspot into a three-dimensional context that can be visualized for each family. The structural context enabled by this projection can also provide spatial information about the PTM site that can supplement the sequence characteristics of the hotspot, namely: (3) solvent accessibility, which provides an estimate of whether a modification could occur on the folded protein; and (4) protein interface residence, which indicates the potential of the PTM to disrupt protein–protein interactions. Despite the theoretical advantages, no single tool has been developed that exploits the quantitative output from both sequence and structural data to evaluate the function potential of PTMs.Here we describe a new analytical method – Structural Analysis of PTM Hotspots (SAPH-ire), which ranks PTM hotspots by their potential to impact biological function for distinct protein families (Fig. 1). We demonstrate the application of SAPH-ire to the complete set of PTMs for eight distinct protein families including large heterotrimeric G proteins—revealing high-ranking hotspots for which a biological function has not yet been determined. In particular, SAPH-ire revealed the N-terminal tail (Nt) of G protein gamma (Gγ) subunits as one of the highest ranking PTM hotspots for heterotrimeric G proteins (Gα, Gβ, and Gγ). We tested this prediction by monitoring the phosphorylation state and mutation effects of phosphorylation sites in the N terminus of the yeast Gγ subunit (Ste18). Consistent with SAPH-ire predictions, we found that phosphorylation of Ste18-Nt is biologically responsive to a GPCR stimulus and that phospho-null or phospho-mimic mutation of these sites controls protein abundance in an opposite manner in vivo. Thus, SAPH-ire is a powerful new method for predicting the function potential of PTM hotspots, which can guide empirical research toward the discovery of new protein regulatory elements based on high-throughput proteomics.Open in a separate windowFig. 1.Schematic diagram of the SAPH-ire method. A, SAPH-ire integrates InterPro, the Protein Data bank (PDB) and a customized database of experimentally validated PTMs. Uniprot entries with PTMs that belong to specific InterPro-classified protein families undergo multiple-sequence alignment (MSA) and PTM hotspot analysis (HSA), which layers all PTMs for a given alignment position in the MSA. The total PTMs observed in each hotspot and the conservation of a modifiable residue (e.g. conservation lysine at a ubiquitination hotspot) at the hotspot are quantified. B, PTM hotspots within the protein family are then projected onto all known crystal structures for the family using the Structural Projection of PTMs (SPoP) tool. From the structural topology of PTM hotspots generated by SPoP, the solvent accessible surface area (SASA) and protein interface residence is quantified for each hotspot. C, PTM Function Potential Calculator (FPC) integrates the output from HSA and SPoP, resulting in PTM function potential scores for each hotspot. The function potential score can be used to rank PTM hotspots within or between protein families – prioritizing hotspots with the greatest potential to be biologically regulated and/or effect a biological function for the protein family of interest.     

SysPTM: A Systematic Resource for Proteomic Research on Post-translational Modifications

With the rapid expansion of protein post-translational modification (PTM) research based on large-scale proteomic work, there is an increasing demand for a suitable repository to analyze PTM data. Here we present a curated, web-accessible PTM data base, SysPTM. SysPTM provides a systematic and sophisticated platform for proteomic PTM research equipped not only with a knowledge base of manually curated multi-type modification data but also with four fully developed, in-depth data mining tools. Currently, SysPTM contains data detailing 117,349 experimentally determined PTM sites on 33,421 proteins involving nearly 50 PTM types, curated from public resources including five data bases and four web servers and more than one hundred peer-reviewed mass spectrometry papers. Protein annotations including Pfam domains, KEGG pathways, GO functional classification, and ortholog groups are integrated into the data base. Four online tools have been developed and incorporated, including PTMBlast, to compare a user''s PTM dataset with PTM data in SysPTM; PTMPathway, to map PTM proteins to KEGG pathways; PTMPhylog, to discover potentially conserved PTM sites; and PTMCluster, to find clusters of multi-site modifications. The workflow of SysPTM was demonstrated by analyzing an in-house phosphorylation dataset identified by MS/MS. It is shown that in SysPTM, the role of single-type and multi-type modifications can be systematically investigated in a full biological context. SysPTM could be an important contribution to modificomics research. SysPTM is freely available online at www.sysbio.ac.cn/SysPTM.Post-translational modifications (PTMs)¹ are various processing events that change the maturity, activity, and/or turnover of proteins. More than 200 different types of PTMs have been found, with new ones still being reported (1). PTMs not only change the physicochemical properties of proteins (2) but also dynamically regulate various biological events such as protein degradation, subcellular localization, conformational change, protein-protein interaction, and signal transduction (3–5). Previous studies have revealed the central roles of PTMs in human health and disease. For example, phosphorylation of pRB1 has been associated with tumorigenesis through controlling cell division (6); S-nitrosylation of parkin regulates its E3 ligase activity, resulting in protein accumulation in sporadic Parkinson disease (7); and defects in protein glycosylation have been related to several forms of congenital muscular dystrophy (8). Given this important role in health and disease, PTMs have been regarded as potential disease biomarkers or therapeutic targets. For example, Erlotinib (Tarceva), an inhibitor of epidermal growth factor receptor tyrosine kinase, has been approved by the Food and Drug Administration to treat non-small cell lung cancer (9); and histone deacetylase inhibitors have been demonstrated to have a potential therapeutic role in Huntington disease (10). The broad range of important roles played by PTMs in physiological and pathological processes has made PTM research an active field in recent years. Yet we remain limited in our knowledge of the full scope of PTM distribution on proteins and the precise location of PTM sites.There are two major kinds of experimental methods to identify PTMs: 1) traditional biological experiments such as radiolabeling PTM proteins (11), Western analysis with antibodies against specific modifications (12), and site-directed mutagenesis of potential modification sites (13); and 2) large-scale proteomic experiments, especially multiple-dimensional liquid chromatography tandem mass spectrometry. Traditional experiments are laborious and time-consuming, resulting in slow data accumulation. By contrast, more recent MS/MS experiments have led to the discovery of thousands of new phosphorylation (14), glycosylation (15), acetylation (16), sumoylation (17), S-nitrosylation (18), and other modification sites. For example, based on MS/MS data, more than 6,000 phosphopeptides have been reported in HeLa cells (14), and 159 candidate sumoylated proteins have been found in yeast (17). Although advanced technologies have allowed PTM data to accumulate rapidly, it is impossible to identify all PTM sites for a set of proteins in one experiment, due to biased modification enrichment related to experimental protocol, limited sensitivity of mass spectrometer instrumentation, and failures in spectrum matching. Data bases are needed to amass PTM data from various experiments for comprehensive understanding of PTMs.Most data bases for storing PTM information have fallen into two general classes. One class focuses on a single modification type, such as Phospho.ELM (19) for phosphorylation or O-GLYCBASE (20) for glycosylation. Although these data bases have been widely used, they are limited in utility due to recording only a single modification type. The other class of PTM data base is the primary protein data base; these data bases collect PTM information with multiple modification types but are more broadly focused on providing diverse information about proteins, rather than PTM information specifically. Swiss-Prot (21) and HPRD (22) are examples of such data bases. As compared with either of the above two types of data base, integrated PTM data bases are more desirable. One example is dbPTM (23), which integrated experimentally determined PTM information from four external data bases. PhosphoSite started the harvesting of phosphorylation sites from published literature with a focus on in vivo mammalian phosphorylation data (24), but recently it has expanded to integrate nine other modification types. Even integrated data bases, however, have not taken into full consideration the aforementioned quickly accumulating PTM data from MS/MS experiments. These data, many of which are reported in the published literature but not collected in any data base, continue to increase rapidly due to new experiments. Such a wealth of information should be incorporated more comprehensively into the current PTM knowledge domain.At the same time, the high-throughput nature and complexity of MS/MS data pose computational challenges for proteome-scale PTM analyses in a biological context. A pure data repository is insufficient for such tasks. Powerful computational tools must accompany data repositories to allow knowledge extraction.To address these needs, we developed a systematic resource for PTM research, SysPTM, consisting of a PTM data base and four analysis tools. The SysPTM data base incorporates the existing features of numerous previous data bases, with an emphasis on collecting modification datasets from MS/MS experiments reported in the literature. The current release of SysPTM (v1.1) contains data detailing 117,349 PTM sites on 33,421 proteins involving nearly 50 modification types. The four analysis tools are PTMBlast, PTMPathway, PTMPhylog, and PTMCluster, which, respectively, can compare user PTM datasets with PTM data stored in SysPTM, map PTM proteins to KEGG pathways, discover potentially conserved PTM sites, and find significant clusters of multi-site modifications.In this work, an in-house MS/MS phosphorylation dataset from mouse embryonic stem cells was analyzed to demonstrate the SysPTM workflow. SysPTM can be accessed online.     

Glycoproteomic Analysis of Seven Major Allergenic Proteins Reveals Novel Post-translational Modifications

Allergenic proteins such as grass pollen and house dust mite (HDM) proteins are known to trigger hypersensitivity reactions of the immune system, leading to what is commonly known as allergy. Key allergenic proteins including sequence variants have been identified but characterization of their post-translational modifications (PTMs) is still limited.Here, we present a detailed PTM¹ characterization of a series of the main and clinically relevant allergens used in allergy tests and vaccines. We employ Orbitrap-based mass spectrometry with complementary fragmentation techniques (HCD/ETD) for site-specific PTM characterization by bottom-up analysis. In addition, top-down mass spectrometry is utilized for targeted analysis of individual proteins, revealing hitherto unknown PTMs of HDM allergens. We demonstrate the presence of lysine-linked polyhexose glycans and asparagine-linked N-acetylhexosamine glycans on HDM allergens. Moreover, we identified more complex glycan structures than previously reported on the major grass pollen group 1 and 5 allergens, implicating important roles for carbohydrates in allergen recognition and response by the immune system. The new findings are important for understanding basic disease-causing mechanisms at the cellular level, which ultimately may pave the way for instigating novel approaches for targeted desensitization strategies and improved allergy vaccines.Allergic respiratory disease is a global health problem and current clinical guidelines recommend a combination of allergen avoidance, pharmacotherapy, and allergen specific immunotherapy for treatment (1–4). At present allergy testing and vaccines are based on isolated crude antigen preparations from natural sources (i.e. HDM, pollens, etc.), but a move toward recombinant allergen design is ongoing (5, 6). This could have important functional implications because the production host will determine the repertoire of post-translational modifications (PTMs) and in particular glycan modifications presented on allergens.The carbohydrate structures found on allergens are in most cases not found in mammals and therefore frequently lead to the induction IgE antibodies named Cross-reactive Carbohydrate Determinants (CCD) (7–11). Moreover, glycans may directly be involved in and promote uptake and target allergens to carbohydrate lectin receptors on antigen presenting cells (APC) (12–14). Therefore, a full structural characterization of the glycans on the natural allergens is a prerequisite for understanding both antibody reactivity and lectin receptor mediated allergen recognition and modulation of the immune response (15, 16). Furthermore, a detailed characterization of PTMs of allergens is important for standardization of allergen products for diagnostic purposes as well as for vaccine use (17, 18). Although many major allergens and their etiology have been characterized in some detail, structural information on for example their immunological important PTM status is still incomplete (19–21).Mass spectrometry-based technologies offer sensitive and accurate analyses for identification and characterization of proteins. The common proteomics workflow typically adopts the bottom-up approach, i.e. in vitro proteolytic digestion of proteins followed by nanoflow-liquid chromatography-tandem mass spectrometry (nLC-MS/MS) for protein identification and PTM characterization. Electron- or collision-driven fragmentation techniques, e.g. electron transfer dissociation (ETD) (22) or higher energy collisional dissociation (HCD) (23) have enabled accurate identification of peptides of purified proteins, e.g. allergens (21, 24), or complex biological samples (25–27) with concurrent characterization of their PTMs. One advantage of bottom-up mass spectrometry is the ability to resolve modified peptides within a narrow chromatographic time frame thereby enabling in-depth characterization of site-specific features, e.g. glycoforms, on peptides. This peptide-level information is subsequently used to generate a protein-level view on the PTM status for a given protein. Importantly, the PTM connectivity of the protein (28) is lost upon proteolytic digestion, and alternative approaches are often required for comprehensive characterization of all proteoforms (29). Top-down mass spectrometry has emerged as an alternative approach to bottom-up proteomics, offering complementary MS and MS/MS information that may be used for protein identification and characterization (30, 31). With top-down MS, intact proteins are typically analyzed by high-resolution FTMS and characterized at the MS/MS level by CID, HCD, ECD, or ETD. This technique provides instant protein-level information on analytes, e.g. sequence variants, amino acid substitutions, PTMs, etc., which can be verified at the MS/MS level by different fragmentation modes. The combination of bottom-up and top-down mass spectrometry is therefore a powerful tool for the identification and characterization of proteins. Here, we combine top-down and bottom-up mass spectrometry for comprehensive characterization of seven major allergens as a first step toward unraveling the molecular mode of action of allergens with complex PTMs. By these methods, we demonstrate hitherto unknown PTMs of HDM allergens and identify more complex glycan structures than previously reported on the major grass pollen group 1 and 5 allergens. The new findings implicate important roles for carbohydrates in allergen recognition and response by the immune system.     

Succinylome Analysis Reveals the Involvement of Lysine Succinylation in Metabolism in Pathogenic Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), the causative agent of human tuberculosis, remains one of the most prevalent human pathogens and a major cause of mortality worldwide. Metabolic network is a central mediator and defining feature of the pathogenicity of Mtb. Increasing evidence suggests that lysine succinylation dynamically regulates enzymes in carbon metabolism in both bacteria and human cells; however, its extent and function in Mtb remain unexplored. Here, we performed a global succinylome analysis of the virulent Mtb strain H37Rv by using high accuracy nano-LC-MS/MS in combination with the enrichment of succinylated peptides from digested cell lysates and subsequent peptide identification. In total, 1545 lysine succinylation sites on 626 proteins were identified in this pathogen. The identified succinylated proteins are involved in various biological processes and a large proportion of the succinylation sites are present on proteins in the central metabolism pathway. Site-specific mutations showed that succinylation is a negative regulatory modification on the enzymatic activity of acetyl-CoA synthetase. Molecular dynamics simulations demonstrated that succinylation affects the conformational stability of acetyl-CoA synthetase, which is critical for its enzymatic activity. Further functional studies showed that CobB, a sirtuin-like deacetylase in Mtb, functions as a desuccinylase of acetyl-CoA synthetase in in vitro assays. Together, our findings reveal widespread roles for lysine succinylation in regulating metabolism and diverse processes in Mtb. Our data provide a rich resource for functional analyses of lysine succinylation and facilitate the dissection of metabolic networks in this life-threatening pathogen.Post-translational modifications (PTMs)¹ are complex and fundamental mechanisms modulating diverse protein properties and functions, and have been associated with almost all known cellular pathways and disease processes (1, 2). Among the hundreds of different PTMs, acylations at lysine residues, such as acetylation (3–6), malonylation (7, 8), crotonylation (9, 10), propionylation (11–13), butyrylation (11, 13), and succinylation (7, 14–16) are crucial for functional regulations of many prokaryotic and eukaryotic proteins. Because these lysine PTMs depend on the acyl-CoA metabolic intermediates, such as acetyl-CoA (Ac-CoA), succinyl-CoA, and malonyl-CoA, lysine acylation could provide a mechanism to respond to changes in the energy status of the cell and regulate energy metabolism and the key metabolic pathways in diverse organisms (17, 18).Among these lysine PTMs, lysine succinylation is a highly dynamic and regulated PTM defined as transfer of a succinyl group (-CO-CH₂-CH₂-CO-) to a lysine residue of a protein molecule (8). It was recently identified and comprehensively validated in both bacterial and mammalian cells (8, 14, 16). It was also identified in core histones, suggesting that lysine succinylation may regulate the functions of histones and affect chromatin structure and gene expression (7). Accumulating evidence suggests that lysine succinylation is a widespread and important PTM in both eukaryotes and prokaryotes and regulates diverse cellular processes (16). The system-wide studies involving lysine-succinylated peptide immunoprecipitation and liquid chromatography-mass spectrometry (LC-MS/MS) have been employed to analyze the bacteria (E. coli) (14, 16), yeast (S. cerevisiae), human (HeLa) cells, and mouse embryonic fibroblasts and liver cells (16, 19). These succinylome studies have generated large data sets of lysine-succinylated proteins in both eukaryotes and prokaryotes and demonstrated the diverse cellular functions of this PTM. Notably, lysine succinylation is widespread among diverse mitochondrial metabolic enzymes that are involved in fatty acid metabolism, amino acid degradation, and the tricarboxylic acid cycle (19, 20). Thus, lysine succinylation is reported as a functional PTM with the potential to impact mitochondrial metabolism and coordinate different metabolic pathways in human cells and bacteria (14, 19–22).Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a major cause of mortality worldwide and claims more human lives annually than any other bacterial pathogen (23). About one third of the world''s population is infected with Mtb, which leads to nearly 1.3 million deaths and 8.6 million new cases of TB in 2012 worldwide (24). Mtb remains a major threat to global health, especially in the developing countries. Emergence of multidrug resistant (MDR) and extensively drug-resistant (XDR) Mtb, and also the emergence of co-infection between TB and HIV have further worsened the situation (25–27). Among bacterial pathogens, Mtb has a distinctive life cycle spanning different environments and developmental stages (28). Especially, Mtb can exist in dormant or active states in the host, leading to asymptomatic latent TB infection or active TB disease (29). To achieve these different physiologic states, Mtb developed a mechanism to sense diverse signals from the host and to coordinately regulate multiple cellular processes and pathways (30, 31). Mtb has evolved its metabolic network to both maintain and propagate its survival as a species within humans (32–35). It is well accepted that metabolic network is a central mediator and defining feature of the pathogenicity of Mtb (23, 36–38). Knowledge of the regulation of metabolic pathways used by Mtb during infection is therefore important for understanding its pathogenicity, and can also guide the development of novel drug therapies (39). On the other hand, increasing evidence suggests that lysine succinylation dynamically regulates enzymes in carbon metabolism in both bacteria and human cells (14, 19–22). It is tempting to speculate that lysine succinylation may play an important regulatory role in metabolic processes in Mtb. However, to the best of our knowledge, no succinylated protein in Mtb has been identified, presenting a major obstacle to understand the regulatory roles of lysine succinylation in this life-threatening pathogen.In order to fill this gap in our knowledge, we have initiated a systematic study of the identities and functional roles of the succinylated protein in Mtb. Because Mtb H37Rv is the first sequenced Mtb strain (40) and has been extensively used for studies in dissecting the roles of individual genes in pathogenesis (41), it was selected as a test case. We analyzed the succinylome of Mtb H37Rv by using high accuracy nano-LC-MS/MS in combination with the enrichment of succinylated peptides from digested cell lysates and subsequent peptide identification. In total, 1545 lysine succinylation sites on 626 proteins were identified in this pathogen. The identified succinylated proteins are involved in various biological processes and render particular enrichment to metabolic process. A large proportion of the succinylation sites are present on proteins in the central metabolism pathway. We further dissected the regulatory role of succinylation on acetyl-CoA synthetase (Acs) via site-specific mutagenesis analysis and molecular dynamics (MD) simulations showed that reversible lysine succinylation could inhibit the activity of Acs. Further functional studies showed that CobB, a sirtuin-like deacetylase in Mtb, functions as a deacetylase and as a desuccinylase of Acs in in vitro assays. Together, our findings provide significant insights into the range of functions regulated by lysine succinylation in Mtb.     

Integrated Microfluidics for Protein Modification Discovery

Protein post-translational modifications mediate dynamic cellular processes with broad implications in human disease pathogenesis. There is a large demand for high-throughput technologies supporting post-translational modifications research, and both mass spectrometry and protein arrays have been successfully utilized for this purpose. Protein arrays override the major limitation of target protein abundance inherently associated with MS analysis. This technology, however, is typically restricted to pre-purified proteins spotted in a fixed composition on chips with limited life-time and functionality. In addition, the chips are expensive and designed for a single use, making complex experiments cost-prohibitive. Combining microfluidics with in situ protein expression from a cDNA microarray addressed these limitations. Based on this approach, we introduce a modular integrated microfluidic platform for multiple post-translational modifications analysis of freshly synthesized protein arrays (IMPA). The system''s potency, specificity and flexibility are demonstrated for tyrosine phosphorylation and ubiquitination in quasicellular environments. Unlimited by design and protein composition, and relying on minute amounts of biological material and cost-effective technology, this unique approach is applicable for a broad range of basic, biomedical and biomarker research.Protein post-translational modifications (PTMs)¹ vastly diversify eukaryotic proteomes and are integrated in essentially all cellular processes (1). Proteomic approaches, such as mass spectrometry (MS), have been instrumental in monitoring global molecular dynamics for research and clinical applications (2–5). However, even in this modern era, large-scale analyses of PTMs by MS is challenging because of the limited number of modified peptides derived from proteins that, by themselves, may not be abundant. Moreover, comprehensive PTM analysis by MS often requires significant amounts of biological material that may not be available. PTM analysis using protein arrays can overcome these limitations because of the equimolar amount of the arrayed proteins (6, 7). Large-scale protein arrays have been successfully integrated into PTM research (8, 9). However, this technology relies on pre-purified proteins that are arrayed on a surface and thus, incompatible with biochemically challenging proteins, let alone insoluble proteins. Moreover, the production of recombinant protein arrays is impractical in-house. Therefore, such arrays cannot be used fresh, and they are inherently limited to certain designs, protein compositions, and model organisms of high commercial value. To overcome the abovementioned limitations, we designed a modular integrated microfluidic platform for PTM analysis (IMPA).     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.     

Lysine Malonylation Is Elevated in Type 2 Diabetic Mouse Models and Enriched in Metabolic Associated Proteins

Protein lysine malonylation, a newly identified protein post-translational modification (PTM), has been proved to be evolutionarily conserved and is present in both eukaryotic and prokaryotic cells. However, its potential roles associated with human diseases remain largely unknown. In the present study, we observed an elevated lysine malonylation in a screening of seven lysine acylations in liver tissues of db/db mice, which is a typical model of type 2 diabetes. We also detected an elevated lysine malonylation in ob/ob mice, which is another model of type 2 diabetes. We then performed affinity enrichment coupled with proteomic analysis on liver tissues of both wild-type (wt) and db/db mice and identified a total of 573 malonylated lysine sites from 268 proteins. There were more malonylated lysine sites and proteins in db/db than in wt mice. Five proteins with elevated malonylation were verified by immunoprecipitation coupled with Western blot analysis. Bioinformatic analysis of the proteomic results revealed the enrichment of malonylated proteins in metabolic pathways, especially those involved in glucose and fatty acid metabolism. In addition, the biological role of lysine malonylation was validated in an enzyme of the glycolysis pathway. Together, our findings support a potential role of protein lysine malonylation in type 2 diabetes with possible implications for its therapy in the future.Post-translational modifications (PTMs)¹ have been recognized as a common feature of proteins (1–3). More than 300 types of PTMs have been identified according to the Swiss-Prot database (4, 5). Most of them use small molecular compounds as group donors. For example, adenosine-triphosphate (ATP) is used in phosphorylation, S-adenosylmethionine (SAM) in methylation, and acetyl-CoA in acetylation. Lysine acylations including malonylation (6), succinylation (7), butyrylation (8), propionylation (9), and crotonylation (10) represent a group of PTMs that use intermediates of energy metabolism like malonyl-CoA, succinyl-CoA, butyryl-CoA, propionyl-CoA, and crotonyl-CoA as group donors. Among the lysine acylations, lysine malonylation was first identified in Escherichia coli (E. coli) and HeLa cells using a specific anti-Kmal (anti-malonyllysine) antibody (6). It was found in three proteins in E. coli and 17 proteins in HeLa cells. Using a novel chemical fluorescent probe, another group identified more than 300 malonylated protein candidates in HeLa cells (11). Despite the rapid progress in detection technologies and tools, functional studies of lysine malonylation and its role in human diseases have been lagging behind.Type 2 diabetes is characterized by hyperglycemia and production of glycated proteins. For example, glycated hemoglobin A1c (HbA1c) has been clinically used as diagnostic criteria for diabetes. In addition to glycation, the role of other types of PTMs in type 2 diabetes remains to be revealed. In fact, elevated malonyl-CoA levels have been found in type 2 diabetic patients (12), and prediabetic rats (13). And hepatic overexpression of malonyl-CoA decarboxylase (MCD) decreased malonyl-CoA and reversed insulin resistance (14). Given the use of malonyl-CoA as malonyl donor in lysine malonylation, lysine malonylation is therefore anticipated to be of functional significance in the pathogenesis of type 2 diabetes.In the present study, we observed elevated lysine malonylation in liver tissues of db/db mice after unbiased screening seven types of lysine acylations. We then detected elevated levels of lysine malonylation in liver tissues of more db/db and ob/ob mice. Using an immunoaffinity based proteomic method, we identified a total of 573 malonylated lysine sites from 268 proteins in liver tissues of wt and db/db mice. Elevation of lysine malonylation in five proteins was confirmed by immunoprecipitation coupled with Western blot analysis. Functional analysis of the malonylated proteins showed an apparent enrichment in metabolic pathways, especially those involved in the glucose and fatty acid metabolism. Our study indicates the putative association between protein lysine malonylation and type 2 diabetes.     

Post-translational Modifications Differentially Affect IgG1 Conformation and Receptor Binding

Post-translational modifications (PTMs) can have profound effects on protein structure and protein dynamics and thereby can influence protein function. To understand and connect PTM-induced functional differences with any resulting conformational changes, the conformational changes must be detected and localized to specific parts of the protein. We illustrate these principles here with a study of the functional and conformational changes that accompany modifications to a monoclonal immunoglobulin γ1 (IgG1) antibody. IgG1s are large and heterogeneous proteins capable of incorporating a multiplicity of PTMs both in vivo and in vitro. For many IgG1s, these PTMs can play a critical role in affecting conformation, biological function, and the ability of the antibody to initiate a potential adverse biological response. We investigated the impact of differential galactosylation, methionine oxidation, and fucosylation on solution conformation using hydrogen/deuterium exchange mass spectrometry and probed the effects of IgG1 binding to the FcγRIIIa receptor. The results showed that methionine oxidation and galactosylation both impact IgG1 conformation, whereas fucosylation appears to have little or no impact to the conformation. FcγRIIIa binding was strongly influenced by both the glycan structure/composition (namely galactose and fucose) and conformational changes that were induced by some of the modifications.The structure of many proteins can be altered by post-translational modifications (1). Although the impact of post-translational modifications (PTMs)¹ on protein structure is more understood for some modifications (e.g. phosphorylation; see Ref. 2), it is less defined for other PTMs and in many cases is protein-dependent. Because there are many important downstream effects of PTMs, including changes in protein localization, protein and cellular diversification, protein functionality, protein stability, protein life cycle, and so forth, understanding how PTMs alter protein structure for as many proteins as possible in a timely manner is a highly desirable goal. Furthermore, in an age where recombinant proteins are being used to treat disease, it becomes ever more important to understand how particular modifications may alter the structure and eventually the function of therapeutic proteins. To realize these goals, methods that permit access to conformational information for modified forms of therapeutic proteins must be developed and refined. In this report, we will illustrate how MS can contribute to structural proteomics by describing our recent work with a recombinant monoclonal antibody (an IgG1), which represents an important class of therapeutic proteins.Many biopharmaceutical companies are pursuing antibody drugs (3). In particular, the IgG1 subclass of antibodies has evolved into a commonly used therapeutic option for the treatment of a wide range of diseases. IgG1s consist of a dimer of identical heavy chains and light chains that fold to form (from N to C terminus) the variable, CL, CH1, CH2, and CH3 domains (as an example, see Ref. 4). Individual domains are structurally stable and are primarily composed of antiparallel β-sheets arranged in an immunoglobulin-like β-sandwich (5). The variable, CL, and CH1 domains are collectively referred to as the Fab (fragment antigen binding) portion of IgG1, which is responsible for recognizing a specific antigen. The CH2 and CH3 domains together are referred to as the Fc (fragment crystallizable) portion, which carries out effector functions such as binding to Fcγ receptors. These effector functions are essential to many therapeutic antibodies, especially when antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity are involved in the mechanisms of action (6).As a biopharmaceutical, IgG1 monoclonal antibodies are critically monitored throughout production (7). In many cases, the impact of structural modifications in these and other formulated versions of biopharmaceuticals are not well understood at a functional level. In the case of IgG1s, with over 1300 amino acid residues and a molecular mass approaching 150 kDa, a large array of PTMs can be incorporated both in vivo (during cellular synthesis) and in vitro (as a result of handling and processing steps that occur during purification, vialing, and storage). Commonly monitored PTMs on IgG1s include methionine oxidation, asparagine and glutamine deamidation, N-terminal acetylation or cyclization, glycation of lysine, and variable glycosylation (8). Some of these modifications affect only a small percentage of the protein product, and their presence may not change overall outcome. Others, however, can have significant impact on the structure, function, and biological activities of a protein that can involve self-association as well as interactions with other proteins (9). The same PTMs can affect different IgG1 molecules in different ways or have no effect(s) at all. Therefore assessing the presence of PTMs, determining the relative level of the modifications, and understanding the structural effects of PTMs are all important during development of protein biopharmaceuticals.Two commonly studied IgG1 modifications are methionine oxidation and glycosylation, each of which has been shown to affect biological function (6, 10). Methionine oxidation has been implicated in protein stability (inducing aggregation), and increased oxidation levels have been shown to provoke an immunogenic response (11–13). Elevated levels of methionine oxidation in an IgG1 were shown to impact neonatal Fc receptor (FcRn) and protein A binding (10). Variable glycosylation (i.e. different levels of sialic acid, galactose, fucose, or high mannose structures) is known to influence thermal stability and effector functions (14–16). Previous studies have shown that removal of fucose from the glycan present on the Fc portion of an IgG1 can greatly enhance Fc binding to FcγRIIIa, but removal of the entire glycan nearly abolishes FcγRIIIa binding (17). As oxidation and changes to the glycan are both common IgG1 modifications, we were interested in determining the conformational effects of oxidation, afucosylation, and galactosylation and correlating any conformational changes that were observed with changes of FcγRIIIa binding activity.Conformational analysis of large proteins like antibodies, however, is not trivial. Traditional biophysical techniques such as circular dichroism, DSC, and fluorescence provide useful information, but these techniques look at the entire protein and provide only a global view (18). NMR and x-ray crystallography can both provide high resolution structural analysis, but each is faced with limitations that often make the study of an intact IgG1 difficult or nearly impossible (19–21). Recently we described how hydrogen/deuterium exchange (H/DX) MS could be used to study the conformation and conformational dynamics of an intact IgG1 with resolution down to stretches of several amino acid residues (22). For the present work, we used H/DX MS to study the impact of galactosylation, oxidation, and afucosylation on the conformation and dynamics of an intact IgG1. We also studied the complex of IgG1 and FcγRIIIa to map the points of interaction and probe any changes in the dynamics of the IgG1 as a result of FcγRIIIa interaction. Finally, we correlated the functional activity of all the proteins that were studied by H/DX MS with the observed conformational disturbance(s). Such correlations are important to connect structure with function and to understand whether a particular PTM is something that may affect the therapeutic value of a recombinant protein.