Byonic: advanced peptide and protein identification software

Database Search Engines: Paradigms, Challenges and Solutions

The first step in identifying proteins from mass spectrometry based shotgun proteomics data is to infer peptides from tandem mass spectra, a task generally achieved using database search engines. In this chapter, the basic principles of database search engines are introduced with a focus on open source software, and the use of database search engines is demonstrated using the freely available SearchGUI interface. This chapter also discusses how to tackle general issues related to sequence database searching and shows how to minimize their impact.

Identification and Validation of Atypical N-Glycosylation Sites

It is well-known that N-linked glycans usually attach to asparagine residues in the N-X-S/T motifs of proteins. However, accumulating evidence indicates that N-glycosylation could also possibly occur at other atypical motifs. In this study, we tried to identify atypical N-glycosylation sites using our recently developed solid-phase extraction of the N-linked Glycans And Glycosite-containing peptides (NGAG) method. Peptides with deamidation sites at asparagine residues but lacking a typical asparagine-X-serine/threonine sequons (N-X-S/T, X is any amino acid except proline) motif were identified from deglycosylated peptide data as potentially atypical glycosite-containing peptides. These atypical glycosites were verified by the presence of glycans on their intact glycopeptides and further confirmed by specific inhibition of cells with an N-linked glycosylation inhibitor, tunicamycin. From this study, two atypical N-linked glycosylation sites with N-X-C and N-X-V motifs were identified and validated from an ovarian cancer cell line (OVCAR-3).

Identification of hyaluronidase and phospholipase B in Lachesis muta rhombeata venom

Hyaluronidases contribute to local and systemic damages after envenoming, since they act as spreading factors cleaving the hyaluronan presents in the connective tissues of the victim, facilitating the diffusion of venom components. Although hyaluronidases are ubiquitous in snake venoms, they still have not been detected in transcriptomic analysis of the Lachesis venom gland and neither in the proteome of its venom performed previously. This work purified a hyaluronidase from Lachesis muta rhombeata venom whose molecular mass was estimated by SDS-PAGE to be 60 kDa. The hyaluronidase was more active at pH 6 and 37 °C when salt concentration was kept constant and more active in the presence of 0.15 M monovalent ions when the pH was kept at 6. Venom was fractionated by reversed-phase liquid chromatography (RPLC). Edman sequencing after RPLC failed to detect hyaluronidase, but identified a new serine proteinase isoform. The hyaluronidase was identified by mass spectrometry analysis of the protein bands in SDS-PAGE. Additionally, phospholipase B was identified for the first time in Lachesis genus venom. The discovery of new bioactive molecules might contribute to the design of novel drugs and biotechnology products as well as to development of more effective treatments against the envenoming.

A review of methods for interpretation of glycopeptide tandem mass spectral data

Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.

Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides

Comprehensive characterization of protein glycosylation is critical for understanding the structure and function of glycoproteins. However, due to the complexity and heterogeneity of glycoprotein conformations, current glycoprotein analyses focus mainly on either the de-glycosylated glycosylation site (glycosite)-containing peptides or the released glycans. Here, we describe a chemoenzymatic method called solid phase extraction of N-linked glycans and glycosite-containing peptides (NGAG) for the comprehensive characterization of glycoproteins that is able to determine glycan heterogeneity for individual glycosites in addition to providing information about the total N-linked glycan, glycosite-containing peptide and glycoprotein content of complex samples. The NGAG method can also be applied to quantitatively detect glycoprotein alterations in total and site-specific glycan occupancies.

Using SEQUEST with theoretically complete sequence databases

SEQUEST has long been used to identify peptides/proteins from their tandem mass spectra and protein sequence databases. The algorithm has proven to be hugely successful for its sensitivity and specificity in identifying peptides/proteins, the sequences of which are present in the protein sequence databases. In this work, we report on work that attempts a new use for the algorithm by applying it to search a complete list of theoretically possible peptides, a de novo-like sequencing. We used freely available mass spectral data and determined a number of unique peptides as identified by SEQUEST. Using masses of these peptides and the mass accuracy of 0.001 Da, we have created a database of all theoretically possible peptide sequences corresponding to the precursor masses. We used our recently developed algorithm for determining all amino acid compositions corresponding to a mass interval, and used a lexicographic ordering to generate theoretical sequences from the compositions. The newly generated theoretical database was many-fold more complex than the original protein sequence database. We used SEQUEST to search and identify the best matches to the spectra from all theoretically possible peptide sequences. We found that SEQUEST cross-correlation score ranked the correct peptide match among the top sequence matches. The results testify to the high specificity of SEQUEST when combined with the high mass accuracy for intact peptides. Graphical Abstract ᅟ.

Exploring G protein-coupled receptor signaling networks using SILAC-based phosphoproteomics

The type 1 parathyroid hormone receptor (PTH1R) is a key regulator of calcium homeostasis and bone turnover. Here, we employed SILAC-based quantitative mass spectrometry and bioinformatic pathways analysis to examine global changes in protein phosphorylation following short-term stimulation of endogenously expressed PTH1R in osteoblastic cells in vitro. Following 5min exposure to the conventional agonist, PTH(1-34), we detected significant changes in the phosphorylation of 224 distinct proteins. Kinase substrate motif enrichment demonstrated that consensus motifs for PKA and CAMK2 were the most heavily upregulated within the phosphoproteome, while consensus motifs for mitogen-activated protein kinases were strongly downregulated. Signaling pathways analysis identified ERK1/2 and AKT as important nodal kinases in the downstream network and revealed strong regulation of small GTPases involved in cytoskeletal rearrangement, cell motility, and focal adhesion complex signaling. Our data illustrate the utility of quantitative mass spectrometry in measuring dynamic changes in protein phosphorylation following GPCR activation.

Monitoring host responses to the gut microbiota

The gastrointestinal (GI) ecosystem is increasingly understood to be a fundamental component of health, and has been identified as a new focal point for diagnosing, correcting and preventing countless disorders. Shotgun DNA sequencing has emerged as the dominant technology for determining the genetic and microbial composition of the gut microbiota. This technology has linked microbiota dysbioses to numerous GI diseases including inflammatory bowel disease, obesity and allergy, and to non-GI diseases like autism and depression. The importance of establishing causality in the deterioration of the host-microbiota relationship is well appreciated; however, discovery of candidate molecules and pathways that underlie mechanisms remains a major challenge. Targeted approaches, transcriptional assays, cytokine panels and imaging analyses, applied to animals, have yielded important insight into host responses to the microbiota. However, non-invasive, hypothesis-independent means of measuring host responses in humans are necessary to keep pace with similarly unbiased sequencing efforts that monitor microbes. Mass spectrometry-based proteomics has served this purpose in many other fields, but stool proteins exist in such diversity and dynamic range as to overwhelm conventional proteomics technologies. Focused analysis of host protein secretion into the gut lumen and monitoring proteome-level dynamics in stool provides a tractable route toward non-invasively evaluating dietary, microbial, surgical or pharmacological intervention efficacies. This review is intended to guide GI biologists and clinicians through the methods currently used to elucidate host responses in the gut, with a specific focus on mass spectrometry-based shotgun proteomics applied to the study of host protein dynamics within the GI ecosystem.

Preserved Proteins from Extinct Bison latifrons Identified by Tandem Mass Spectrometry; Hydroxylysine Glycosides are a Common Feature of Ancient Collagen

Bone samples from several vertebrates were collected from the Ziegler Reservoir fossil site, in Snowmass Village, Colorado, and processed for proteomics analysis. The specimens come from Pleistocene megafauna Bison latifrons, dating back ∼ 120,000 years. Proteomics analysis using a simplified sample preparation procedure and tandem mass spectrometry (MS/MS) was applied to obtain protein identifications. Several bioinformatics resources were used to obtain peptide identifications based on sequence homology to extant species with annotated genomes. With the exception of soil sample controls, all samples resulted in confident peptide identifications that mapped to type I collagen. In addition, we analyzed a specimen from the extinct B. latifrons that yielded peptide identifications mapping to over 33 bovine proteins. Our analysis resulted in extensive fibrillar collagen sequence coverage, including the identification of posttranslational modifications. Hydroxylysine glucosylgalactosylation, a modification thought to be involved in collagen fiber formation and bone mineralization, was identified for the first time in an ancient protein dataset. Meta-analysis of data from other studies indicates that this modification may be common in well-preserved prehistoric samples. Additional peptide sequences from extracellular matrix (ECM) and non-ECM proteins have also been identified for the first time in ancient tissue samples. These data provide a framework for analyzing ancient protein signatures in well-preserved fossil specimens, while also contributing novel insights into the molecular basis of organic matter preservation. As such, this analysis has unearthed common posttranslational modifications of collagen that may assist in its preservation over time. The data are available via ProteomeXchange with identifier PXD001827.

Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. 'Systems Glycobiology' is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or 'systems-level' view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell-surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post-translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation-related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize 'Big Data' stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole-cell level has been standardized, there is a need to integrate mass spectrometry derived site-specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between 'data' generated in wet-laboratory studies with 'knowledge' that can enhance our understanding of the glycome.

An optimized approach to the rapid assessment and detection of sequence variants in recombinant protein products

The development of sensitive techniques to detect sequence variants (SVs), which naturally arise due to DNA mutations and errors in transcription/translation (amino acid misincorporations), has resulted in increased attention to their potential presence in protein-based biologic drugs in recent years. Often, these SVs may be below 0.1%, adding challenges for consistent and accurate detection. Furthermore, the presence of false-positive (FP) signals, a hallmark of SV analysis, requires time-consuming analyst inspection of the data to sort true from erroneous signal. Consequently, gaps in information about the prevalence, type, and impact of SVs in marketed and in-development products are significant. Here, we report the results of a simple, straightforward, and sensitive approach to sequence variant analysis. This strategy employs mixing of two samples of an antibody or protein with the same amino acid sequence in a dilution series followed by subsequent sequence variant analysis. Using automated peptide map analysis software, a quantitative assessment of the levels of SVs in each sample can be made based on the signal derived from the mass spectrometric data. We used this strategy to rapidly detect differences in sequence variants in a monoclonal antibody after a change in process scale, and in a comparison of three mAbs as part of a biosimilar program. This approach is powerful, as true signals can be readily distinguished from FP signal, even at a level well below 0.1%, by using a simple linear regression analysis across the data set with none to minimal inspection of the MS/MS data. Additionally, the data produced from these studies can also be used to make a quantitative assessment of relative levels of product quality attributes. The information provided here extends the published knowledge about SVs and provides context for the discussion around the potential impact of these SVs on product heterogeneity and immunogenicity.

Online two-dimensional porous graphitic carbon/reversed phase liquid chromatography platform applied to shotgun proteomics and glycoproteomics

A novel fully automatable two-dimensional liquid chromatography (2DLC) platform has been integrated into a modified commercial off-the-shelf LC instrument, incorporating porous graphitic carbon (PGC) separation and conventional low-pH reversed-phase (RP) separation for both proteomics and N-glycomics analyses; the dual-trap column configuration of this platform offers desirable high-throughput analyses with almost no idle time, in addition to a miniaturized setup and simplified operation. The total run time per analysis was only 19 h when using eight PGC fractions for unattended large-scale qualitative and quantitative proteomic analyses; the identification of 2678 nonredundant proteins and 11,984 unique peptides provided one of the most comprehensive proteome data sets for primary cerebellar granule neurons (CGNs). The effect of pH on the PGC column was investigated for the first time to improve the hydrophobic peptide coverage; the performance of the optimized system was first benchmarked using tryptic digests of Saccharomyces cerevisiae cell lysates and then evaluated through duplicate analyses of Macaca fascicularis cerebral cortex lysates using isobaric tags for relative and absolute quantitation (iTRAQ) technology. An additional plug-and-play PGC module functioned in a complementary manner to recover unretained hydrophilic solutes from the low-pH RP column; synchronization of the fractionations between the PGC-RP system and the PGC module facilitated simultaneous analyses of hydrophobic and hydrophilic compounds from a single sample injection event. This methodology was applied to perform, for the first time, detailed glycomics analyses of Macaca fascicularis plasma, resulting in the identification of a total 130 N-glycosylated plasma proteins, 705 N-glycopeptides, and 254 N-glycosylation sites.

Confident assignment of site-specific glycosylation in complex glycoproteins in a single step

A glycoprotein may contain several sites of glycosylation, each of which is heterogeneous. As a consequence of glycoform diversity and signal suppression from nonglycosylated peptides that ionize more efficiently, typical reversed-phase LC-MS and bottom-up proteomics database searching workflows do not perform well for identification of site-specific glycosylation for complex glycoproteins. We present an LC-MS system for enrichment, separation, and analysis of glycopeptides from complex glycoproteins (>4 N-glycosylation sequons) in a single step. This system uses an online HILIC enrichment trap prior to reversed-phase C18-MS analysis. We demonstrated the effectiveness of the system using a set of glycoproteins including human transferrin (2 sequons), human alpha-1-acid glycoprotein (5 sequons), and influenza A virus hemagglutinin (9 sequons). The online enrichment renders glycopeptides the most abundant ions detected, thereby facilitating the generation of high-quality data-dependent tandem mass spectra. The tandem mass spectra exhibited product ions from both glycan and peptide backbone dissociation for a majority of the glycopeptides tested using collisionally activated dissociation that served to confidently assign site-specific glycosylation. We demonstrated the value of our system to define site-specific glycosylation using a hemagglutinin containing 9 N-glycosylation sequons from a single HILIC-C18-MS acquisition.

Glycan side reaction may compromise ETD-based glycopeptide identification

Tris(hydroxymethyl)aminomethane (Tris) is one of the most frequently used buffer ingredients. Among other things, it is recommended and is usually used for lectin-based affinity enrichment of glycopeptides. Here we report that sialic acid, a common 'capping' unit in both N- and O-linked glycans may react with this chemical, and this side reaction may compromise glycopeptide identification when ETD spectra are the only MS/MS data used in the database search. We show that the modification may alter N- as well as O-linked glycans, the Tris-derivative is still prone to fragmentation both in 'beam-type' CID (HCD) and ETD experiments, at the same time--since the acidic carboxyl group was 'neutralized'--it will display a different retention time than its unmodified counterpart. We also suggest solutions that--when incorporated into existing search engines--may significantly improve the reliability of glycopeptide assignments.

Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome

Site-specific structural characterization of glycoproteins is important for understanding the exact functional relevance of protein glycosylation. Resulting partly from the multiple layers of structural complexity of the attached glycans, the system-wide site-specific characterization of protein glycosylation, defined as glycoproteomics, is still far from trivial leaving the N- and O-linked glycoproteomes significantly under-defined. However, recent years have seen significant advances in glycoproteomics driven, in part, by the developments of dedicated workflows and efficient sample preparation, including glycopeptide enrichment and prefractionation. In addition, glycoproteomics has benefitted from the continuous performance enhancement and more intelligent use of liquid chromatography and tandem mass spectrometry (LC-MS/MS) instrumentation and a wider selection of specialized software tackling the unique challenges of glycoproteomics data. Together these advances promise more streamlined N- and O-linked glycoproteome analysis. Tangible examples include system-wide glycoproteomics studies detecting thousands of intact glycopeptides from hundreds of glycoproteins from diverse biological samples. With a strict focus on the system-wide site-specific analysis of protein N- and O-linked glycosylation, we review the recent advances in LC-MS/MS based glycoproteomics. The review opens with a more general discussion of experimental designs in glycoproteomics and sample preparation prior to LC-MS/MS based data acquisition. Although many challenges still remain, it becomes clear that glycoproteomics, one of the last frontiers in proteomics, is gradually maturing enabling a wider spectrum of researchers to access this new emerging research discipline. The next milestone in analytical glycobiology is being reached allowing the glycoscientist to address the functional importance of protein glycosylation in a system-wide yet protein-specific manner.