Proteomics Analysis of the Cardiac Myofilament Subproteome Reveals Dynamic Alterations in Phosphatase Subunit Distribution

Myofilament proteins are responsible for cardiac contraction. The myofilament subproteome, however, has not been comprehensively analyzed thus far. In the present study, cardiomyocytes were isolated from rodent hearts and stimulated with endothelin-1 and isoproterenol, potent inducers of myofilament protein phosphorylation. Subsequently, cardiomyocytes were “skinned,” and the myofilament subproteome was analyzed using a high mass accuracy ion trap tandem mass spectrometer (LTQ Orbitrap XL) equipped with electron transfer dissociation. As expected, a small number of myofilament proteins constituted the majority of the total protein mass with several known phosphorylation sites confirmed by electron transfer dissociation. More than 600 additional proteins were identified in the cardiac myofilament subproteome, including kinases and phosphatase subunits. The proteomic comparison of myofilaments from control and treated cardiomyocytes suggested that isoproterenol treatment altered the subcellular localization of protein phosphatase 2A regulatory subunit B56α. Immunoblot analysis of myocyte fractions confirmed that β-adrenergic stimulation by isoproterenol decreased the B56α content of the myofilament fraction in the absence of significant changes for the myosin phosphatase target subunit isoforms 1 and 2 (MYPT1 and MYPT2). Furthermore, immunolabeling and confocal microscopy revealed the spatial redistribution of these proteins with a loss of B56α from Z-disc and M-band regions but increased association of MYPT1/2 with A-band regions of the sarcomere following β-adrenergic stimulation. In summary, we present the first comprehensive proteomics data set of skinned cardiomyocytes and demonstrate the potential of proteomics to unravel dynamic changes in protein composition that may contribute to the neurohormonal regulation of myofilament contraction.Myofilament proteins comprise the fundamental contractile apparatus of the heart, the cardiac sarcomere. They are subdivided into thin filament proteins, including actin, tropomyosin, the troponin complex (troponin C, troponin I, and troponin T), and thick filament proteins, including myosin heavy chains, myosin light chains, and myosin-binding protein C. Although calcium is the principal regulator of cardiac contraction through the excitation-contraction coupling process that culminates in calcium binding to troponin C, myofilament function is also significantly modulated by phosphorylation of constituent proteins, such as cardiac troponin I (cTnI),1 cardiac myosin-binding protein C (cMyBP-C), and myosin regulatory light chain (MLC-2). “Skinned” myocyte preparations from rodent hearts, in which the sarcolemmal envelope is disrupted through the use of detergents, have been invaluable in providing mechanistic information on the functional consequences of myofilament protein phosphorylation following exposure to neurohormonal stimuli that activate pertinent kinases prior to skinning or direct exposure to such kinases in active form after skinning (for recent examples, see studies on the phosphorylation of cTnI (1–3), cMyBP-C (4–6), and MLC-2 (7–9)). Nevertheless, to date, only a few myofilament proteins have been studied using proteomics (10–19), and a detailed proteomic characterization of the myofilament subproteome and its associated proteins from skinned myocytes has not been performed. In the present analysis, we used an LTQ Orbitrap XL equipped with ETD (20) to analyze the subproteome of skinned cardiomyocytes with or without prior stimulation. Endothelin-1 and isoproterenol were used to activate the endothelin receptor/protein kinase C and β-adrenoreceptor/protein kinase A pathway, respectively (21, 22). Importantly, the mass accuracy of the Orbitrap mass analyzer helped to distinguish true phosphorylation sites from false assignments, and the sensitivity of the ion trap provided novel insights into the translocation of phosphatase regulatory and targeting subunits following β-adrenergic stimulation.     

High-definition De Novo Sequencing of Crustacean Hyperglycemic Hormone (CHH)-family Neuropeptides

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8–9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.Neuropeptides and hormones comprise a diverse class of signaling molecules involved in numerous essential physiological processes, including analgesia, reward, food intake, learning and memory (1). Disorders of the neurosecretory and neuroendocrine systems influence many pathological processes. For example, obesity results from failure of energy homeostasis in association with endocrine alterations (2, 3). Previous work from our lab used crustaceans as model organisms found that multiple neuropeptides were implicated in control of food intake, including RFamides, tachykinin related peptides, RYamides, and pyrokinins (4–6).Crustacean hyperglycemic hormone (CHH)¹ family neuropeptides play a central role in energy homeostasis of crustaceans (7–17). Hyperglycemic response of the CHHs was first reported after injection of crude eyestalk extract in crustaceans. Based on their preprohormone organization, the CHH family can be grouped into two sub-families: subfamily-I containing CHH, and subfamily-II containing molt-inhibiting hormone (MIH) and mandibular organ-inhibiting hormone (MOIH). The preprohormones of the subfamily-I have a CHH precursor related peptide (CPRP) that is cleaved off during processing; and preprohormones of the subfamily-II lack the CPRP (9). Uncovering their physiological functions will provide new insights into neuroendocrine regulation of energy homeostasis.Characterization of CHH-family neuropeptides is challenging. They are comprised of more than 70 amino acids and often contain multiple post-translational modifications (PTMs) and complex disulfide bridge connections (7). In addition, physiological concentrations of these peptide hormones are typically below picomolar level, and most crustacean species do not have available genome and proteome databases to assist MS-based sequencing.MS-based neuropeptidomics provides a powerful tool for rapid discovery and analysis of a large number of endogenous peptides from the brain and the central nervous system. Our group and others have greatly expanded the peptidomes of many model organisms (3, 18–33). For example, we have discovered more than 200 neuropeptides with several neuropeptide families consisting of as many as 20–40 members in a simple crustacean model system (5, 6, 25–31, 34). However, a majority of these neuropeptides are small peptides with 5–15 amino acid residues long, leaving a gap of identifying larger signaling peptides from organisms without sequenced genome. The observed lack of larger size peptide hormones can be attributed to the lack of effective de novo sequencing strategies for neuropeptides larger than 4 kDa, which are inherently more difficult to fragment using conventional techniques (34–37). Although classical proteomics studies examine larger proteins, these tools are limited to identification based on database searching with one or more peptides matching without complete amino acid sequence coverage (36, 38).Large populations of neuropeptides from 4–10 kDa exist in the nervous systems of both vertebrates and invertebrates (9, 39, 40). Understanding their functional roles requires sufficient molecular knowledge and a unique analytical approach. Therefore, developing effective and reliable methods for de novo sequencing of large neuropeptides at the individual amino acid residue level is an urgent gap to fill in neurobiology. In this study, we present a multifaceted MS strategy aimed at high-definition de novo sequencing and comprehensive characterization of the CHH-family neuropeptides in crustacean central nervous system. The high-definition de novo sequencing was achieved by a combination of three methods: (1) enzymatic digestion and LC-tandem mass spectrometry (MS/MS) bottom-up analysis to generate detailed sequences of proteolytic peptides; (2) off-line LC fractionation and subsequent top-down MS/MS to obtain high-quality fragmentation maps of intact peptides; and (3) on-line LC coupled to top-down MS/MS to allow rapid sequence analysis of low abundance peptides. Combining the three methods overcomes the limitations of each, and thus offers complementary and high-confidence determination of amino acid residues. We report the complete sequence analysis of six CHH-family neuropeptides including the discovery of two novel peptides. With the accurate molecular information, MALDI imaging and ion mobility MS were conducted for the first time to explore their anatomical distribution and biochemical properties.     

The Q Exactive HF,a Benchtop Mass Spectrometer with a Pre-filter,High-performance Quadrupole and an Ultra-high-field Orbitrap Analyzer

The quadrupole Orbitrap mass spectrometer (Q Exactive) made a powerful proteomics instrument available in a benchtop format. It significantly boosted the number of proteins analyzable per hour and has now evolved into a proteomics analysis workhorse for many laboratories. Here we describe the Q Exactive Plus and Q Exactive HF mass spectrometers, which feature several innovations in comparison to the original Q Exactive instrument. A low-resolution pre-filter has been implemented within the injection flatapole, preventing unwanted ions from entering deep into the system, and thereby increasing its robustness. A new segmented quadrupole, with higher fidelity of isolation efficiency over a wide range of isolation windows, provides an almost 2-fold improvement of transmission at narrow isolation widths. Additionally, the Q Exactive HF has a compact Orbitrap analyzer, leading to higher field strength and almost doubling the resolution at the same transient times. With its very fast isolation and fragmentation capabilities, the instrument achieves overall cycle times of 1 s for a top 15 to 20 higher energy collisional dissociation method. We demonstrate the identification of 5000 proteins in standard 90-min gradients of tryptic digests of mammalian cell lysate, an increase of over 40% for detected peptides and over 20% for detected proteins. Additionally, we tested the instrument on peptide phosphorylation enriched samples, for which an improvement of up to 60% class I sites was observed.Mass spectrometry (MS)-based¹ proteomics aims at the comprehensive analysis of proteins present in a biological sample (1), and the field has expanded in many surprising directions (2). Application of the developed techniques has revealed novel insights into fundamental biology, as well as produced analysis techniques with implications for clinical applications. A major hurdle, however, is the complexity of the systems under scrutiny, as it has been shown that human cell lines, for instance, express at least 10,000 genes that are detectable as proteins (3–5). If we further consider all the peptides produced in bottom-up proteomics experiments, this hurdle is compounded, as ideally many hundreds of thousands of analytes should be characterized in order for the proteins giving rise to them to be fully reconstructed (6). In principle, issues of sample complexity and dynamic range could be addressed by a very high degree of up-front fractionation. However, this strategy faces diminishing returns and leads to unacceptably long analysis times for most purposes. Given the fact that even with optimal chromatographic resolution many peptides with abundance differences of many orders of magnitude elute within the same time frame, there remains a need to improve the mass spectrometric detection in terms of speed, resolution, and sensitivity.Nanoscale liquid chromatography coupled online to mass spectrometry is the current technique of choice for the analysis of complex peptide mixtures. In a top-N shotgun strategy, a full scan, providing a complete overview of isotope patterns resulting from ionized peptides, is followed by N fragmentation scans performed on the most abundant not-yet-sequenced isotope patterns currently visible in the full scan. During fragmentation, the goal is to cleanly isolate the intended precursor peptide ion, which today is generally done either by a linear ion trap or by a quadrupole mass filter. Fragment ions are then mass measured by an Orbitrap mass analyzer, a time-of-flight analyzer, or, less often, ion cyclotron resonance–Fourier transform or linear or three-dimensional ion traps.Apart from the MS instrumentation, recent developments in the proteomics workflow include a move toward automated online quality control systems (7, 8) and single-run analyses (9), which require very high-performance peptide chromatography (10, 11).The Orbitrap mass analyzer was introduced commercially almost 10 years ago, and hybrid instruments based on this tool have become very popular in proteomics (12). They consist of an upfront mass spectrometer coupled to a so-called C-trap, which stores and compresses the ion population (generally up to one million charges) prior to injection into the Orbitrap analyzer. Up to the Orbitrap Velos and Elite members of this family of instruments, the precursor selection (and usually the fragmentation) occurred in the linear ion trap (13), but a few years ago an instrument based on a quadrupole front end—the Q Exactive mass spectrometer—was developed (14). Compared with the linear ion trap, quadrupole mass filters have the advantage of being capable of nearly instantaneously selecting a small mass region by modulating the RF field, allowing only a select set of ions to have stable trajectories when passing through the rod assembly. As we described previously, this near-instantaneous mass selection capability and the C-trap''s capability of storing ions enable multiplexing of different ion populations (e.g. fragment ions of two or more distinct precursor ions) prior to analysis in the Orbitrap mass analyzer (14). However, that instrument did not use the highest efficiency quadrupole technology (15), and it did not use the compact high-field Orbitrap analyzer that had been introduced in the Orbitrap Elite instrument (16).Here we describe the advances incorporated into the Q Exactive Plus and the Q Exactive HF instruments. These include improved robustness effected by a low-resolution filter upstream of the quadrupole, a segmented quadrupole, and, in the case of the Q Exactive HF instrument, an ultra-high-field mass Orbitrap analyzer, doubling resolution or acquisition speed. We describe these capabilities in the context of single-shot complex mixture analysis of peptides and phosphopeptides.     

DeMix Workflow for Efficient Identification of Cofragmented Peptides in High Resolution Data-dependent Tandem Mass Spectrometry

Based on conventional data-dependent acquisition strategy of shotgun proteomics, we present a new workflow DeMix, which significantly increases the efficiency of peptide identification for in-depth shotgun analysis of complex proteomes. Capitalizing on the high resolution and mass accuracy of Orbitrap-based tandem mass spectrometry, we developed a simple deconvolution method of “cloning” chimeric tandem spectra for cofragmented peptides. Additional to a database search, a simple rescoring scheme utilizes mass accuracy and converts the unwanted cofragmenting events into a surprising advantage of multiplexing. With the combination of cloning and rescoring, we obtained on average nine peptide-spectrum matches per second on a Q-Exactive workbench, whereas the actual MS/MS acquisition rate was close to seven spectra per second. This efficiency boost to 1.24 identified peptides per MS/MS spectrum enabled analysis of over 5000 human proteins in single-dimensional LC-MS/MS shotgun experiments with an only two-hour gradient. These findings suggest a change in the dominant “one MS/MS spectrum - one peptide” paradigm for data acquisition and analysis in shotgun data-dependent proteomics. DeMix also demonstrated higher robustness than conventional approaches in terms of lower variation among the results of consecutive LC-MS/MS runs.Shotgun proteomics analysis based on a combination of high performance liquid chromatography and tandem mass spectrometry (MS/MS) (1) has achieved remarkable speed and efficiency (2–7). In a single four-hour long high performance liquid chromatography-MS/MS run, over 40,000 peptides and 5000 proteins can be identified using a high-resolution Orbitrap mass spectrometer with data-dependent acquisition (DDA)¹ (2, 3). However, in a typical LC-MS analysis of unfractionated human cell lysate, over 100,000 individual peptide isotopic patterns can be detected (4), which corresponds to simultaneous elution of hundreds of peptides. With this complexity, a mass spectrometer needs to achieve ≥25 Hz MS/MS acquisition rate to fully sample all the detectable peptides, and ≥17 Hz to cover reasonably abundant ones (4). Although this acquisition rate is reachable by modern time-of-flight (TOF) instruments, the reported DDA identification results do not encompass all expected peptides. Recently, the next-generation Orbitrap instrument, working at 20 Hz MS/MS acquisition rate, demonstrated nearly full profiling of yeast proteome using an 80 min gradient, which opened the way for comprehensive analysis of human proteome in a time efficient manner (5).During the high performance liquid chromatography-MS/MS DDA analysis of complex samples, high density of co-eluting peptides results in a high probability for two or more peptides to overlap within an MS/MS isolation window. With the commonly used ±1.0–2.0 Th isolation windows, most MS/MS spectra are chimeric (4, 8–10), with cofragmenting precursors being naturally multiplexed. However, as has been discussed previously (9, 10), the cofragmentation events are currently ignored in most of the conventional analysis workflows. According to the prevailing assumption of “one MS/MS spectrum–one peptide,” chimeric MS/MS spectra are generally unwelcome in DDA, because the product ions from different precursors may interfere with the assignment of MS/MS fragment identities, increasing the rate of false discoveries in database search (8, 9). In some studies, the precursor isolation width was set as narrow as ±0.35 Th to prevent unwanted ions from being coselected, fragmented or detected (4, 5).On the contrary, multiplexing by cofragmentation is considered to be one of the solid advantages in data-independent acquisition (DIA) (10–13). In several commonly used DIA methods, the precursor ion selection windows are set much wider than in DDA: from 25 Th as in SWATH (12), to extremely broad range as in AIF (13). In order to use the benefit of MS/MS multiplexing in DDA, several approaches have been proposed to deconvolute chimeric MS/MS spectra. In “alternative peptide identification” method implemented in Percolator (14), a machine learning algorithm reranks and rescores peptide-spectrum matches (PSMs) obtained from one or more MS/MS search engines. But the deconvolution in Percolator is limited to cofragmented peptides with masses differing from the target peptide by the tolerance of the database search, which can be as narrow as a few ppm. The “active demultiplexing” method proposed by Ledvina et al. (15) actively separates MS/MS data from several precursors using masses of complementary fragments. However, higher-energy collisional dissociation often produces MS/MS spectra with too few complementary pairs for reliable peptide identification. The “MixDB” method introduces a sophisticated new search engine, also with a machine learning algorithm (9). And the “second peptide identification” method implemented in Andromeda/MaxQuant workflow (16) submits the same dataset to the search engine several times based on the list of chromatographic peptide features, subtracting assigned MS/MS peaks after each identification round. This approach is similar to the ProbIDTree search engine that also performed iterative identification while removing assigned peaks after each round of identification (17).One important factor for spectral deconvolution that has not been fully utilized in most conventional workflows is the excellent mass accuracy achievable with modern high-resolution mass spectrometry (18). An Orbitrap Fourier-transform mass spectrometer can provide mass accuracy in the range of hundreds of ppb (parts per billion) for mass peaks with high signal-to-noise (S/N) ratio (19). However, the mass error of peaks with lower S/N ratios can be significantly higher and exceed 1 ppm. Despite this dependence of the mass accuracy from the S/N level, most MS and MS/MS search engines only allow users to set hard cut-off values for the mass error tolerances. Moreover, some search engines do not provide the option of choosing a relative error tolerance for MS/MS fragments. Such negligent treatment of mass accuracy reduces the analytical power of high accuracy experiments (18).Identification results coming from different MS/MS search engines are sometimes not consistent because of different statistical assumptions used in scoring PSMs. Introduction of tools integrating the results of different search engines (14, 20, 21) makes the data interpretation even more complex and opaque for the user. The opposite trend—simplification of MS/MS data interpretation—is therefore a welcome development. For example, an extremely straightforward algorithm recently proposed by Wenger et al. (22) demonstrated a surprisingly high performance in peptide identification, even though it is only marginally more complex than simply counting the number of matches of theoretical fragment peaks in high resolution MS/MS, without any a priori statistical assumption.In order to take advantage of natural multiplexing of MS/MS spectra in DDA, as well as properly utilize high accuracy of Orbitrap-based mass spectrometry, we developed a simple and robust data analysis workflow DeMix. It is presented in Fig. 1 as an expansion of the conventional workflow. Principles of some of the processes used by the workflow are borrowed from other approaches, including the custom-made mass peak centroiding (20), chromatographic feature detection (19, 20), and two-pass database search with the first limited pass to provide a “software lock mass” for mass scale recalibration (23).Open in a separate windowFig. 1.An overview of the DeMix workflow that expands the conventional workflow, shown by the dashed line. Processes are colored in purple for TOPP, red for search engine (Morpheus/Mascot/MS-GF+), and blue for in-house programs.In DeMix workflow, the deconvolution of chimeric MS/MS spectra consists of simply “cloning” an MS/MS spectrum if a potential cofragmented peptide is detected. The list of candidate peptide precursors is generated from chromatographic feature detection, as in the MaxQuant/Andromeda workflow (16, 19), but using The OpenMS Proteomics Pipeline (TOPP) (20, 24). During the cloning, the precursor is replaced by the new candidate, but no changes in the MS/MS fragment list are made, and therefore the cloned MS/MS spectra remain chimeric. Processing such spectra requires a search engine tolerant to the presence of unassigned peaks, as such peaks are always expected when multiple precursors cofragment. Thus, we chose Morpheus (22) as a search engine. Based on the original search algorithm, we implement a reformed scoring scheme: Morpheus-AS (advanced scoring). It inherits all the basic principles from Morpheus but deeper utilizes the high mass accuracy of the data. This kind of database search removes the necessity of spectral processing for physical separation of MS/MS data into multiple subspectra (15), or consecutive subtraction of peaks (16, 17).Despite the fact that DeMix workflow is largely a combination of known approaches, it provides remarkable improvement compared with the state-of-the-art. On our Orbitrap Q-Exactive workbench, testing on a benchmark dataset of two-hour single-dimension LC-MS/MS experiments from HeLa cell lysate, we identified on average 1.24 peptide per MS/MS spectrum, breaking the “one MS/MS spectrum–one peptide” paradigm on the level of whole data set. At 1% false discovery rate (FDR), we obtained on average nine PSMs per second (at the actual acquisition rate of ca. seven MS/MS spectra per second), and detected 40 human proteins per minute.     

From Whole-body Sections Down to Cellular Level,Multiscale Imaging of Phospholipids by MALDI Mass Spectrometry

Significant progress in instrumentation and sample preparation approaches have recently expanded the potential of MALDI imaging mass spectrometry to the analysis of phospholipids and other endogenous metabolites naturally occurring in tissue specimens. Here we explore some of the requirements necessary for the successful analysis and imaging of phospholipids from thin tissue sections of various dimensions by MALDI time-of-flight mass spectrometry. We address methodology issues relative to the imaging of whole-body sections such as those cut from model laboratory animals, sections of intermediate dimensions typically prepared from individual organs, as well as the requirements for imaging areas of interests from these sections at a cellular scale spatial resolution. We also review existing limitations of MALDI imaging MS technology relative to compound identification. Finally, we conclude with a perspective on important issues relative to data exploitation and management that need to be solved to maximize biological understanding of the tissue specimen investigated.Since its introduction in the late 90s (1), MALDI imaging mass spectrometry (MS) technology has witnessed a phenomenal expansion. Initially introduced for the mapping of intact proteins from fresh frozen tissue sections (2), imaging MS is now routinely applied to a wide range of different compounds including peptides, proteins, lipids, metabolites, and xenobiotics (3–7). Numerous compound-specific sample preparation protocols and analytical strategies have been developed. These include tissue sectioning and handling (8–14), automated matrix deposition approaches and data acquisition strategies (15–21), and the emergence of in situ tissue chemistries (22–25). Originally performed on sections cut from fresh frozen tissue specimens, methodologies incorporating an in situ enzymatic digestion step prior to matrix application have been optimized to access the proteome locked in formalin-fixed paraffin-embedded tissue biopsies (25–29). The possibility to use tissues preserved using non-cross-linking approaches has also been demonstrated (30–32). These methodologies are of high importance for the study of numerous diseases because they potentially allow the retrospective analysis for biomarker validation and discovery of the millions of tissue biopsies currently stored worldwide in tissue banks and repositories.In the past decade, instrumentation for imaging MS has also greatly evolved. Whereas the first MS images were collected with time-of-flight instruments (TOF) capable of repetition rates of a few hertz, modern systems are today capable of acquiring data in the kilohertz range and above with improved sensitivity, mass resolving power, and accuracy, significantly reducing acquisition time and improving image quality (33, 34). Beyond time-of-flight analyzers, other MALDI-based instruments have been used such as ion traps (35–37), Qq TOF instruments (38–40), and trap-TOF (16, 41). Ion mobility technology has also been used in conjunction with imaging MS (42–44). More recently, MALDI FT/ICR and Orbitrap mass spectrometers have been demonstrated to be extremely valuable instruments for the performance of imaging MS at very high mass resolving power (45–47). These non-TOF-based systems have proven to be extremely powerful for the imaging of lower molecular weight compounds such as lipids, drugs, and metabolites. Home-built instrumentation and analytical approaches to probe tissues at higher spatial resolution (1–10 μm) have also been described (48–50). In parallel to instrumentation developments, automated data acquisition, image visualization, and processing software packages have now also been developed by most manufacturers.To date, a wide range of biological systems have been studied using imaging MS as a primary methodology. Of strong interest are the organization and identification of the molecular composition of diseased tissues in direct correlation with the underlying histology and how it differs from healthy tissues. Such an approach has been used for the study of cancers (51–54), neurologic disorders (55–57), and other diseases (58, 59). The clinical potential of the imaging MS technology is enormous (7, 60, 61). Results give insights into the onset and progression of diseases, identify novel sets of disease-specific markers, and can provide a molecular confirmation of diagnosis as well as aide in outcome prediction (62–64). Imaging MS has also been extensively used to study the development, functioning, and aging of different organs such as the kidney, prostate, epididymis, and eye lens (65–70). Beyond the study of isolated tissues or organs, whole-body sections from several model animals such as leeches, mice, and rats have been investigated (71–74). For these analyses, specialized instrumentation and protocols are necessary for tissue sectioning and handling (72, 73). Whole-body imaging MS opens the door to the study of the localization and accumulation of administered pharmaceuticals and their known metabolites at the level of entire organisms as well as the monitoring of their efficacy or toxicity as a function of time or dose (72, 73, 75, 76).There is considerable interest in determining the identification and localization of small biomolecules such as lipids in tissues because they are involved in many essential biological functions including cell signaling, energy storage, and membrane structure and function. Defects in lipid metabolism play a role in many diseases such as muscular dystrophy and cardiovascular disease. Phospholipids in tissues have been intensively studied by several groups (37, 40, 77–83). In this respect, for optimal recovery of signal, several variables such as the choice of matrix for both imaging and fragmentation, solvent system, and instrument polarity have been investigated (20, 84). Particularly, the use of lithium cation adducts to facilitate phospholipid identification by tandem MS directly from tissue has also been reported (85). Of significant interest is the recent emergence of two new solvent-free matrix deposition approaches that perform exceptionally well for phospholipid imaging analyses. The first approach, described by Hankin et al. (86), consists in depositing the matrix on the sections through a sublimation process. The described sublimation system consists of sublimation glassware, a heated sand or oil bath (100–200 °C), and a primary vacuum pump (∼5 × 10⁻² torr). Within a few minutes of initiating the sublimation process, an exceptionally homogeneous film of matrix forms on the section. The thickness of the matrix may be controlled by regulating pressure, temperature, and sublimation time. The second approach, described by Puolitaival et al.(87), uses a fine mesh sieve (≤20 μm) to filter finely ground matrix on the tissue sections. Agitation of the sieve results in passage of the matrix through the mesh and the deposition of a fairly homogeneous layer of submicrometer matrix crystals of the surface of the sections. The matrix density on the sections is controlled by direct observation using a standard light microscope. This matrix deposition approach was also found to be ideal to image certain drug compounds (88, 89). Both strategies allow very rapid production of homogeneous matrix coatings on tissue sections with a fairly inexpensive setup. Signal recovery was found to be comparable with those obtained by conventional spray deposition. With the appropriate size sublimation device or sieve, larger sections with dimensions of several centimeters such as those cut from mouse or rat whole bodies can also be rapidly and homogeneously coated.Here we present several examples of MALDI imaging MS of phospholipids from tissue sections using TOF mass spectrometers over a wide range of dimensions from whole-body sections (several centimeters), to individual organs (several millimeters), down to high spatial resolution imaging of selected tissue areas (hundreds of micrometers) at 10-μm lateral resolution and below. For all of these dimension ranges, technological considerations and practical aspects are discussed. In light of the imaging MS results, we also address issues faced for compound identification by tandem MS analysis performed directly on the sections. Finally, we discuss under “Perspective” our vision of the future of the field as well as the technological improvements and analytical tools that need to be improved upon and developed.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Laserspray Ionization, a New Method for Protein Analysis Directly from Tissue at Atmospheric Pressure with Ultrahigh Mass Resolution and Electron Transfer Dissociation

Laserspray ionization (LSI) mass spectrometry (MS) allows, for the first time, the analysis of proteins directly from tissue using high performance atmospheric pressure ionization mass spectrometers. Several abundant and numerous lower abundant protein ions with molecular masses up to ∼20,000 Da were detected as highly charged ions from delipified mouse brain tissue mounted on a common microscope slide and coated with 2,5-dihydroxyacetophenone as matrix. The ability of LSI to produce multiply charged ions by laser ablation at atmospheric pressure allowed protein analysis at 100,000 mass resolution on an Orbitrap Exactive Fourier transform mass spectrometer. A single acquisition was sufficient to identify the myelin basic protein N-terminal fragment directly from tissue using electron transfer dissociation on a linear trap quadrupole (LTQ) Velos. The high mass resolution and mass accuracy, also obtained with a single acquisition, are useful in determining protein molecular weights and from the electron transfer dissociation data in confirming database-generated sequences. Furthermore, microscopy images of the ablated areas show matrix ablation of ∼15 μm-diameter spots in this study. The results suggest that LSI-MS at atmospheric pressure potentially combines speed of analysis and imaging capability common to matrix-assisted laser desorption/ionization and soft ionization, multiple charging, improved fragmentation, and cross-section analysis common to electrospray ionization.Tissue imaging by mass spectrometry (MS) is proving useful in areas such as detecting tumor margins, determining sites of high drug uptake, and mapping signaling molecules in brain tissue (1–8). Imaging using secondary ion mass spectrometry is well established but is only marginally useful with intact molecular mass measurements from biological tissue (9–11). Matrix-assisted laser desorption/ionization (MALDI)-MS operating under vacuum conditions has been used for tissue imaging with success, especially for abundant components such as membrane lipids, drug metabolites, and proteins (12–14). Spatial resolution of ∼20 μm has been achieved (15), and the MALDI-MS method has been applied in an attempt to shed light on Parkinson disease (16, 17), muscular dystrophy (18), obesity, and cancer (12, 19).Unfortunately, there are disadvantages in using vacuum-based MS for tissue imaging in relation to analysis of unadulterated tissue. Also, the mass spectrometers used in these studies frequently have much lower mass resolution and mass accuracy than are available with atmospheric pressure ionization (API)¹ instruments and are not as widely available. Because the vacuum ionization methods produce singly charged ions, mass-selected fragmentation methods provide only limited information, especially for proteins. In addition, no advanced fragmentation such as electron transfer dissociation (ETD) (20–22) is available for confident protein confirmation or identification. Atmospheric pressure (AP) MALDI can be coupled to high performance mass spectrometers but suffers from sensitivity issues for tissue imaging where high spatial resolution is desired (23). AP MALDI also primarily produces singly charged ions (24, 25). Thus, mass and cross-section analysis of intact proteins has yet to be accomplished using AP MALDI because of intrinsic mass range limitations of API instruments, which frequently have a mass-to-charge (m/z) limit of <4000. Thus, new improved methods of mass-specific tissue imaging, especially at AP, are needed.The potential of laserspray ionization (LSI) (Scheme 1) (26–33) for protein tissue analysis is reported here. LSI has advantages relative to other MS-based methods, including speed of analysis, laser ablation of small volumes, more relevant AP conditions, extended mass range and improved fragmentation through multiple charging, and the ability to obtain cross-section data for proteins on appropriate instrumentation. The applicability of LSI for high mass compounds on high performance API mass spectrometers (Orbitrap Exactive and SYNAPT G2) has been demonstrated producing ESI-like multiply protonated ions (26–28). The first experiments showing sequence analysis by ETD using the LSI method were successfully carried out on a Thermo Fisher Scientific (San Jose, CA) LTQ-ETD mass spectrometer (26). Nearly complete sequence coverage was obtained for ubiquitin, an important regulatory protein. Applying ETD fragmentation to LSI-MS analyses potentially provides a new method for studying biological processes, including the mapping of phosphorylation, glycosylation, and ubiquitination sites from intact proteins and directly from tissue.Open in a separate windowScheme 1.Overview of LSI-MS operated in transmission geometry.Furthermore, unlike ESI and related ESI-based methods such as desorption-ESI (34), the LSI method has been shown to allow analysis of lipids in tissue from ablated areas <80 μm (30). In comparison with literature reports for AP MALDI at the same stage of development (35), LSI is more than an order of magnitude more sensitive and is capable of analyzing proteins on high resolution mass spectrometers as was demonstrated by obtaining full-acquisition mass spectra at 100,000 mass resolution (FWHH, m/z 200) after application of only 20 fmol of bovine pancreas insulin in the matrix 2,5-dihydroxyacetophenone (2,5-DHAP) onto a glass microscope slide (33). The analysis speed of LSI was demonstrated by obtaining mass spectra of five samples in 8 s (32). Here, we show the utility of LSI for intact peptide and protein analyses directly from mouse brain tissue. The ability to obtain a protein mass spectrum directly from mouse brain tissue in a single laser shot at 100,000 mass resolution and with ETD fragmentation is demonstrated.     

Development of a Novel Cross-linking Strategy for Fast and Accurate Identification of Cross-linked Peptides of Protein Complexes

Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS³ analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS³) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes.Proteins form stable and dynamic multisubunit complexes under different physiological conditions to maintain cell viability and normal cell homeostasis. Detailed knowledge of protein interactions and protein complex structures is fundamental to understanding how individual proteins function within a complex and how the complex functions as a whole. However, structural elucidation of large multisubunit protein complexes has been difficult because of a lack of technologies that can effectively handle their dynamic and heterogeneous nature. Traditional methods such as nuclear magnetic resonance (NMR) analysis and x-ray crystallography can yield detailed information on protein structures; however, NMR spectroscopy requires large quantities of pure protein in a specific solvent, whereas x-ray crystallography is often limited by the crystallization process.In recent years, chemical cross-linking coupled with mass spectrometry (MS) has become a powerful method for studying protein interactions (1–3). Chemical cross-linking stabilizes protein interactions through the formation of covalent bonds and allows the detection of stable, weak, and/or transient protein-protein interactions in native cells or tissues (4–9). In addition to capturing protein interacting partners, many studies have shown that chemical cross-linking can yield low resolution structural information about the constraints within a molecule (2, 3, 10) or protein complex (11–13). The application of chemical cross-linking, enzymatic digestion, and subsequent mass spectrometric and computational analyses for the elucidation of three-dimensional protein structures offers distinct advantages over traditional methods because of its speed, sensitivity, and versatility. Identification of cross-linked peptides provides distance constraints that aid in constructing the structural topology of proteins and/or protein complexes. Although this approach has been successful, effective detection and accurate identification of cross-linked peptides as well as unambiguous assignment of cross-linked sites remain extremely challenging due to their low abundance and complicated fragmentation behavior in MS analysis (2, 3, 10, 14). Therefore, new reagents and methods are urgently needed to allow unambiguous identification of cross-linked products and to improve the speed and accuracy of data analysis to facilitate its application in structural elucidation of large protein complexes.A number of approaches have been developed to facilitate MS detection of low abundance cross-linked peptides from complex mixtures. These include selective enrichment using affinity purification with biotinylated cross-linkers (15–17) and click chemistry with alkyne-tagged (18) or azide-tagged (19, 20) cross-linkers. In addition, Staudinger ligation has recently been shown to be effective for selective enrichment of azide-tagged cross-linked peptides (21). Apart from enrichment, detection of cross-linked peptides can be achieved by isotope-labeled (22–24), fluorescently labeled (25), and mass tag-labeled cross-linking reagents (16, 26). These methods can identify cross-linked peptides with MS analysis, but interpretation of the data generated from interlinked peptides (two peptides connected with the cross-link) by automated database searching remains difficult. Several bioinformatics tools have thus been developed to interpret MS/MS data and determine interlinked peptide sequences from complex mixtures (12, 14, 27–32). Although promising, further developments are still needed to make such data analyses as robust and reliable as analyzing MS/MS data of single peptide sequences using existing database searching tools (e.g. Protein Prospector, Mascot, or SEQUEST).Various types of cleavable cross-linkers with distinct chemical properties have been developed to facilitate MS identification and characterization of cross-linked peptides. These include UV photocleavable (33), chemical cleavable (19), isotopically coded cleavable (24), and MS-cleavable reagents (16, 26, 34–38). MS-cleavable cross-linkers have received considerable attention because the resulting cross-linked products can be identified based on their characteristic fragmentation behavior observed during MS analysis. Gas-phase cleavage sites result in the detection of a “reporter” ion (26), single peptide chain fragment ions (35–38), or both reporter and fragment ions (16, 34). In each case, further structural characterization of the peptide product ions generated during the cleavage reaction can be accomplished by subsequent MSⁿ1 analysis. Among these linkers, the “fixed charge” sulfonium ion-containing cross-linker developed by Lu et al. (37) appears to be the most attractive as it allows specific and selective fragmentation of cross-linked peptides regardless of their charge and amino acid composition based on their studies with model peptides.Despite the availability of multiple types of cleavable cross-linkers, most of the applications have been limited to the study of model peptides and single proteins. Additionally, complicated synthesis and fragmentation patterns have impeded most of the known MS-cleavable cross-linkers from wide adaptation by the community. Here we describe the design and characterization of a novel and simple MS-cleavable cross-linker, DSSO, and its application to model peptides and proteins and the yeast 20 S proteasome complex. In combination with new software developed for data integration, we were able to identify DSSO-cross-linked peptides from complex peptide mixtures with speed and accuracy. Given its effectiveness and simplicity, we anticipate a broader application of this MS-cleavable cross-linker in the study of structural topology of other protein complexes using cross-linking and mass spectrometry.     

Online Peptide Fractionation Using a Multiphasic Microfluidic Liquid Chromatography Chip Improves Reproducibility and Detection Limits for Quantitation in Discovery and Targeted Proteomics

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) chip that integrates reversed phase and strong cation exchange chromatography upstream of the mass spectrometer (MS). We showed superiority of this system for standardizing discovery and targeted proteomic workflows using cancer cell lysates and nondepleted human plasma. Five-step multiphase chip LC MS/MS acquisition showed clear advantages over analyses of unfractionated samples by identifying more peptides, consuming less sample and often improving the lower limits of quantitation, all in highly reproducible, automated, online configuration. We further showed that multiphase chip LC fractionation provided a facile means to detect many N- and C-terminal peptides (including acetylated N terminus) that are challenging to identify in complex tryptic peptide matrices because of less favorable ionization characteristics. Given as much as 95% of peptides were detected in only a single salt fraction from cell lysates we exploited this high reproducibility and coupled it with multiple reaction monitoring on a high-resolution MS instrument (MRM-HR). This approach increased target analyte peak area and improved lower limits of quantitation without negatively influencing variance or bias. Further, we showed a strategy to use multiphase LC chip fractionation LC-MS/MS for ion library generation to integrate with SWATH^TM data-independent acquisition quantitative workflows. All MS data are available via ProteomeXchange with identifier PXD001464.Mass spectrometry based proteomic quantitation is an essential technique used for contemporary, integrative biological studies. Whether used in discovery experiments or for targeted biomarker applications, quantitative proteomic studies require high reproducibility at many levels. It requires reproducible run-to-run peptide detection, reproducible peptide quantitation, reproducible depth of proteome coverage, and ideally, a high degree of cross-laboratory analytical reproducibility. Mass spectrometry centered proteomics has evolved steadily over the past decade, now mature enough to derive extensive draft maps of the human proteome (1, 2). Nonetheless, a key requirement yet to be realized is to ensure that quantitative proteomics can be carried out in a timely manner while satisfying the aforementioned challenges associated with reproducibility. This is especially important for recent developments using data independent MS quantitation and multiple reaction monitoring on high-resolution MS (MRM-HR)¹ as they are both highly dependent on LC peptide retention time reproducibility and precursor detectability, while attempting to maximize proteome coverage (3). Strategies usually employed to increase the depth of proteome coverage utilize various sample fractionation methods including gel-based separation, affinity enrichment or depletion, protein or peptide chemical modification-based enrichment, and various peptide chromatography methods, particularly ion exchange chromatography (4–10). In comparison to an unfractionated “naive” sample, the trade-off in using these enrichments/fractionation approaches are higher risk of sample losses, introduction of undesired chemical modifications (e.g. oxidation, deamidation, N-terminal lactam formation), and the potential for result skewing and bias, as well as numerous time and human resources required to perform the sample preparation tasks. Online-coupled approaches aim to minimize those risks and address resource constraints. A widely practiced example of the benefits of online sample fractionation has been the decade long use of combining strong cation exchange chromatography (SCX) with C18 reversed-phase (RP) for peptide fractionation (known as MudPIT – multidimensional protein identification technology), where SCX and RP is performed under the same buffer conditions and the SCX elution performed with volatile organic cations compatible with reversed phase separation (11). This approach greatly increases analyte detection while avoiding sample handling losses. The MudPIT approach has been widely used for discovery proteomics (12–14), and we have previously shown that multiphasic separations also have utility for targeted proteomics when configured for selected reaction monitoring MS (SRM-MS). We showed substantial advantages of MudPIT-SRM-MS with reduced ion suppression, increased peak areas and lower limits of detection (LLOD) compared with conventional RP-SRM-MS (15).To improve the reproducibility of proteomic workflows, increase throughput and minimize sample loss, numerous microfluidic devices have been developed and integrated for proteomic applications (16, 17). These devices can broadly be classified into two groups: (1) microfluidic chips for peptide separation (18–25) and; (2) proteome reactors that combine enzymatic processing with peptide based fractionation (26–30). Because of the small dimension of these devices, they are readily able to integrate into nanoLC workflows. Various applications have been described including increasing proteome coverage (22, 27, 28) and targeting of phosphopeptides (24, 31, 32), glycopeptides and released glycans (29, 33, 34).In this work, we set out to take advantage of the benefits of multiphasic peptide separations and address the reproducibility needs required for high-throughput comparative proteomics using a variety of workflows. We integrated a multiphasic SCX and RP column in a “plug-and-play” microfluidic chip format for online fractionation, eliminating the need for users to make minimal dead volume connections between traps and columns. We show the flexibility of this format to provide robust peptide separation and reproducibility using conventional and topical mass spectrometry workflows. This was undertaken by coupling the multiphase liquid chromatography (LC) chip to a fast scanning Q-ToF mass spectrometer for data dependent MS/MS, data independent MS (SWATH) and for targeted proteomics using MRM-HR, showing clear advantages for repeatable analyses compared with conventional proteomic workflows.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Analysis of Intact Monoclonal Antibody IgG1 by Electron Transfer Dissociation Orbitrap FTMS

The primary structural information of proteins employed as biotherapeutics is essential if one wishes to understand their structure–function relationship, as well as in the rational design of new therapeutics and for quality control. Given both the large size (around 150 kDa) and the structural complexity of intact immunoglobulin G (IgG), which includes a variable number of disulfide bridges, its extensive fragmentation and subsequent sequence determination by means of tandem mass spectrometry (MS) are challenging. Here, we applied electron transfer dissociation (ETD), implemented on a hybrid Orbitrap Fourier transform mass spectrometer (FTMS), to analyze a commercial recombinant IgG in a liquid chromatography (LC)-tandem mass spectrometry (MS/MS) top-down experiment. The lack of sensitivity typically observed during the top-down MS of large proteins was addressed by averaging time-domain transients recorded in different LC-MS/MS experiments before performing Fourier transform signal processing. The results demonstrate that an improved signal-to-noise ratio, along with the higher resolution and mass accuracy provided by Orbitrap FTMS (relative to previous applications of top-down ETD-based proteomics on IgG), is essential for comprehensive analysis. Specifically, ETD on Orbitrap FTMS produced about 33% sequence coverage of an intact IgG, signifying an almost 2-fold increase in IgG sequence coverage relative to prior ETD-based analysis of intact monoclonal antibodies of a similar subclass. These results suggest the potential application of the developed methodology to other classes of large proteins and biomolecules.Top-down mass spectrometry (MS)¹ (1–3) has continued to demonstrate its particular advantages over traditionally employed bottom-up MS strategies (4). Specifically, top-down MS allows the characterization of specific protein isoforms originating from the alternative splicing of mRNA that code single nucleotide polymorphisms and/or post-translational modifications (PTMs) of protein species (5). Intact protein molecular weight (MW) determination and subsequent gas-phase fragmentation of selected multiply charged protein ions (referred to as tandem MS or MS/MS) theoretically might result in complete protein sequence coverage and precise assignment of the type and position of PTMs, amino acid substitutions, and C- or N-terminal truncations (6), whereas the bottom-up MS approach allows only the identification of a certain protein family when few or redundant peptides are found for a particular protein isoform. At a practical level, however, top-down MS-based proteomics struggles not only with the single- or multi-dimensional separation of undigested proteins, which demonstrates lower reproducibility and repeatability than for peptides, but also with technical limitations present in even state-of-the-art mass spectrometers. The outcome of a top-down MS experiment depends indeed on the balance between the applied resolution of the mass spectrometer and its sensitivity. The former is required for unambiguous assignment of ion isotopic clusters in both survey and MS/MS scans, whereas the latter is ultimately dependent on the scan speed of the mass analyzer, which determines the number of scans that can be accumulated for a given analyte ion on the liquid chromatography (LC) timescale to enhance the resulting signal-to-noise ratio (SNR). Until recently, the instrument of choice for top-down MS has been the Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer, primarily because of its superior resolving power and the availability of electron capture dissociation for the efficient MS/MS of large biomolecules (7, 8). However, this solution has been shown to have some limitations in the analysis of large proteins (9). The main issue, as described by Compton et al. (10), is that the SNR in Fourier transform mass spectrometry (FTMS) is inversely proportional to the width of the isotopic and charge state distributions (11), which both increase as a function of MW. Particularly, the SNR dramatically decreases with MW under standard on-line LC-MS/MS operating conditions if isotopic resolution is required. It is noteworthy that such SNR reduction can affect not only intact mass measurements, but also the subsequent MS/MS performance.The most widely employed solution for improving top-down analysis is thus a substantial reduction of the protein mixture complexity, for example, through off-line sample prefractionation (12). Furthermore, when the MW exceeds 100 kDa, proteins are often analyzed via direct infusion after off-line purification of the single isoform or species of interest (13). Overall, these strategies aim to improve the quality of mass spectra, specifically their SNR, by increasing the number of scans dedicated to each selected isoform or species. However, off-line intact protein analysis has limitations, including sample degradation and modification (e.g., oxidation during long off-line measurements and sample storage). The time required for multistep LC-based protein purification can also be substantial.Electron capture dissociation (ECD) (14, 15) and electron transfer dissociation (ETD) (16) are ion activation techniques that allow polypeptide fragmentation with reduced PTM losses (17, 18). Nevertheless, ECD and ETD generally provide larger sequence coverage for intact proteins than slow-heating activation methods such as collision induced dissociation (CID) and infrared multiple photon dissociation (19, 20). Furthermore, ECD and ETD are known to cleave disulfide bonds, a fundamental feature for the analysis of proteins in their native state (i.e., without cysteine reduction and alkylation) (21–23).The structural analysis of high MW intact proteins with MS has garnered much recent attention in the literature (24, 25), mainly because of the improved capabilities offered by rapidly developing sample preparation, protein separation, and mass spectrometric methods and techniques. Immunoglobulin G (IgG) proteins are antibodies with an MW of about 150 kDa that are composed of two identical sets of light and glycosylated heavy chains with both intra- and intermolecular disulfide bridges (Fig. 1) (26). IgGs represent an attractive target for structural analysis method development, given their high importance as biotherapeutics (27). A unit-mass resolution mass spectrum demonstrating an isotopic distribution of an isolated charge state of a 148 kDa IgG1 has been recently achieved with FT-ICR MS equipped with 9.4 T superconducting magnet and a statically harmonized ICR cell (24). However, further analytical improvements are needed to achieve routine and reproducible MS operation at the required level of resolution and sensitivity.Open in a separate windowFig. 1.Schematic representation of IgG1. Two identical light (blue) and two identical heavy (fucsia) chains form the intact IgG. The light chain is composed of a variable domain (V_L) and a constant domain (C_L), whereas the heavy chain comprises one variable domain (V_H) and three constant domains (C_H1–3). Each domain contains an intramolecular disulfide bridge (in red); intermolecular disulfide bridges link the heavy chains to each other (two bonds) and each heavy chain to one light chain (one bond). Each heavy chain includes an N-glycosylation site (located at Asn²⁹⁷; here, a G0F/G0F glycosylation is shown).Fragmentation of intact antibodies in the gas phase following the top-down MS approach has been previously attempted without precursor ion charge state isolation by means of nozzle-skimmer CID on a linear trap quadrupole (LTQ)-Orbitrap™ (28, 29) and with precursor ion isolation via ETD on a high resolution quadrupole time-of-flight (qTOF) mass spectrometer (25). Relative to the results previously obtained with slow-heating MS/MS methods, the ETD qTOF MS/MS demonstrated substantially higher sequence coverage, reaching 15% for human and 21% for murine IgGs. Important for future top-down proteomics development for complex protein mixtures, the ETD qTOF MS/MS results were obtained on the LC timescale. To increase the sequence coverage and confidence in product ion assignment, a substantial increase in SNR was achieved by averaging MS/MS data from up to 10 identical LC-MS/MS experiments. The high complexity of the product ion population reduced the effective resolution to about 30,000, presumably limiting the assignment of overlapping high charge state product ions in the 1000–2000 m/z range. Even higher peak complexity was observed in the region of charge reduced species and complementary heavy product ions, above 3000 m/z. Finally, numerous disulfide bonds drastically reduced MS/MS efficiency in the disulfide bond-protected regions.Here we demonstrate that ETD-enabled hybrid linear ion trap Orbitrap FTMS allows us to further improve the top-down ETD-based LC-MS/MS of monoclonal antibodies, introduced earlier for TOF-based MS. To fully take advantage of the high resolving power of Orbitrap MS/MS for increasing both the number of assigned product ions and the confidence of the assignments, maintaining an LC-MS/MS setup useful in a general proteomics workflow for protein desalting and separation, we averaged time-domain transients (derived from separated LC-MS/MS runs) before Fourier transform signal processing.     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer

There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein quantification methods in complex samples and address the pressing demand of systems biology or biomarker evaluation studies.Shotgun proteomics has emerged over the past decade as the most effective method for the qualitative study of complex proteomes (i.e., the identification of the protein content), as illustrated by a wealth of publications (1, 2). In this approach, after enzymatic digestion of the proteins, the generated peptides are analyzed by means of liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)¹ in a data dependent mode. However, the complexity of the digested proteomes under investigation and the wide range of protein abundances limit the reproducibility and the sensitivity of this stochastic approach (3), which is critical if one aims at the systematic quantification of the proteins. Thus, alternative MS approaches have emerged for the systematic quantitative study of complex proteomes, the MS-based targeted proteomics (4). In this hypothesis-driven approach, only specific subsets of analytes (a few targeted peptides used as surrogates for the proteins of interest) are selectively measured in predefined m/z ranges and retention time windows, which overcomes the bias toward most abundant compounds commonly observed with shotgun proteomics. When applied to complex biological samples—for example, bodily fluids such as urine or plasma—targeted proteomics requires high performance instruments allowing measurements of a wide dynamic range (many orders of magnitude), with high sensitivity in order to detect peptides in the low amol range and sufficient selectivity to cope with massive biochemical background (5). Selected reaction monitoring (SRM) on triple quadrupole (6) or triple quadrupole-linear ion trap mass spectrometers (7) has emerged as a means to conduct such analyses (8). Initially applied in the MS analysis of small molecules (9, 10), SRM has gradually emerged as the reference quantitative technique for analyzing proteins (or peptides) in biological samples. When coupled with the isotope dilution strategy (11, 12), this very effective technique allows the precise quantification of proteins (13–18). However, despite the increased selectivity provided by the two-stage mass filtering of SRM (at the precursor and fragment ion levels), the low resolution of mass selection does not allow the systematic removal of interferences (19, 20). Moreover, in proteomics, the biochemical background has a composition similar to that of the analytes of interest, which remains a major hurdle limiting the sensitivity of assays, especially in a bodily fluid matrix. High resolution/accurate mass (HR/AM) analysis represents a promising alternative approach that might more efficiently distinguish the compounds of interest from interferences in targeted proteomics. Such analyses can be conducted on orbitrap-based mass spectrometers because of their high sensitivity and high mass accuracy capabilities (21). The introduction of the benchtop standalone orbitrap mass spectrometer (Exactive) (22) further strengthened the attractiveness of the approach, especially in the field of small molecule analysis (23, 24). However, as quantification using trapping devices intrinsically suffers from a limited dynamic range because of the overall ion capacity, the complexity of biological samples remains very challenging even with the HR/AM approach (25). Targeted protein analysis with triple quadrupole mass spectrometers keeps on showing significant superiority for such samples.² The recently developed quadrupole-orbitrap mass spectrometer (Q-Exactive) can potentially address this issue.³ It is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection (26, 27). This configuration combines advantages of triple quadrupole instruments for mass filtering and orbitrap-based mass spectrometers for HR/AM measurement. The ability of the instrument to select a restricted m/z range or (sequentially) a small number of precursor ions offers new opportunities for quantification in complex samples by selectively enriching low abundant components. The resulting data, acquired in the so-called single ion monitoring (SIM) mode, fully benefit from the trapping capability while keeping a high acquisition rate as a result of the fast switching time between targeted precursor ions of the quadrupole. Although this mode of data acquisition is possible with a configuration combining a linear ion trap with the orbitrap (as in the LTQ-Orbitrap mass spectrometer), its effectiveness is far more limited in this case. The quadrupole-orbitrap configuration presents significant benefits by selectively isolating a narrow population of precursor ions. Other features of the instrument include its multiplexed trapping capability (26) using either the C-trap or the higher energy collisional dissociation (HCD) cell (28, 29), which opens new avenues in the design of innovative acquisition methods for quantification studies. For the first time, a panel of acquisition methods is designed and applied to targeted quantification at the MS and MS/MS levels. In the latter case, the simultaneous monitoring of multiple MS/MS fragmentation channels, also called parallel reaction monitoring⁴ (PRM), is particularly promising for quantifying large sets of peptides with increased selectivity.     

Conserved Peptide Fragmentation as a Benchmarking Tool for Mass Spectrometers and a Discriminating Feature for Targeted Proteomics

Quantifying the similarity of spectra is an important task in various areas of spectroscopy, for example, to identify a compound by comparing sample spectra to those of reference standards. In mass spectrometry based discovery proteomics, spectral comparisons are used to infer the amino acid sequence of peptides. In targeted proteomics by selected reaction monitoring (SRM) or SWATH MS, predetermined sets of fragment ion signals integrated over chromatographic time are used to identify target peptides in complex samples. In both cases, confidence in peptide identification is directly related to the quality of spectral matches. In this study, we used sets of simulated spectra of well-controlled dissimilarity to benchmark different spectral comparison measures and to develop a robust scoring scheme that quantifies the similarity of fragment ion spectra. We applied the normalized spectral contrast angle score to quantify the similarity of spectra to objectively assess fragment ion variability of tandem mass spectrometric datasets, to evaluate portability of peptide fragment ion spectra for targeted mass spectrometry across different types of mass spectrometers and to discriminate target assays from decoys in targeted proteomics. Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure. The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.In “bottom-up” proteomics, peptide sequences are identified by the information contained in their fragment ion spectra (1). Various methods have been developed to generate peptide fragment ion spectra and to match them to their corresponding peptide sequences. They can be broadly grouped into discovery and targeted methods. In the widely used discovery (also referred to as shotgun) proteomic approach, peptides are identified by establishing peptide to spectrum matches via a method referred to as database searching. Each acquired fragment ion spectrum is searched against theoretical peptide fragment ion spectra computed from the entries of a specified sequence database, whereby the database search space is constrained to a user defined precursor mass tolerance (2, 3). The quality of the match between experimental and theoretical spectra is typically expressed with multiple scores. These include the number of matching or nonmatching fragments, the number of consecutive fragment ion matches among others. With few exceptions (4–7) commonly used search engines do not use the relative intensities of the acquired fragment ion signals even though this information could be expected to strengthen the confidence of peptide identification because the relative fragment ion intensity pattern acquired under controlled fragmentation conditions can be considered as a unique “fingerprint” for a given precursor. Thanks to community efforts in acquiring and sharing large number of datasets, the proteomes of some species are now essentially mapped out and experimental fragment ion spectra covering entire proteomes are increasingly becoming accessible through spectral databases (8–16). This has catalyzed the emergence of new proteomics strategies that differ from classical database searching in that they use prior spectral information to identify peptides. Those comprise inclusion list sequencing (directed sequencing), spectral library matching, and targeted proteomics (17). These methods explicitly use the information contained in empirical fragment ion spectra, including the fragment ion signal intensity to identify the target peptide. For these methods, it is therefore of highest importance to accurately control and quantify the degree of reproducibility of the fragment ion spectra across experiments, instruments, labs, methods, and to quantitatively assess the similarity of spectra. To date, dot product (18–24), its corresponding arccosine spectral contrast angle (25–27) and (Pearson-like) spectral correlation (28–31), and other geometrical distance measures (18, 32), have been used in the literature for assessing spectral similarity. These measures have been used in different contexts including shotgun spectra clustering (19, 26), spectral library searching (18, 20, 21, 24, 25, 27–29), cross-instrument fragmentation comparisons (22, 30) and for scoring transitions in targeted proteomics analyses such as selected reaction monitoring (SRM)¹ (23, 31). However, to our knowledge, those scores have never been objectively benchmarked for their performance in discriminating well-defined levels of dissimilarities between spectra. In particular, similarity scores obtained by different methods have not yet been compared for targeted proteomics applications, where the sensitive discrimination of highly similar spectra is critical for the confident identification of targeted peptides.In this study, we have developed a method to objectively assess the similarity of fragment ion spectra. We provide an open-source toolset that supports these analyses. Using a computationally generated benchmark spectral library with increasing levels of well-controlled spectral dissimilarity, we performed a comprehensive and unbiased comparison of the performance of the main scores used to assess spectral similarity in mass spectrometry.We then exemplify how this method, in conjunction with its corresponding benchmarked perturbation spectra set, can be applied to answer several relevant questions for MS-based proteomics. As a first application, we show that it can efficiently assess the absolute levels of peptide fragmentation variability inherent to any given mass spectrometer. By comparing the instrument''s intrinsic fragmentation conservation distribution to that of the benchmarked perturbation spectra set, nominal values of spectral similarity scores can indeed be translated into a more directly understandable percentage of variability inherent to the instrument fragmentation. As a second application, we show that the method can be used to derive an absolute measure to estimate the conservation of peptide fragmentation between instruments or across proteomics methods. This allowed us to quantitatively evaluate, for example, the transferability of fragment ion spectra acquired by data dependent analysis in a first instrument into a fragment/transition assay list used for targeted proteomics applications (e.g. SRM or targeted extraction of data independent acquisition SWATH MS (33)) on another instrument. Third, we used the method to probe the fragmentation patterns of peptides carrying a post-translation modification (e.g. phosphorylation) by comparing the spectra of modified peptide with those of their unmodified counterparts. Finally, we used the method to determine the overall level of fragmentation conservation that is required to support target-decoy discrimination and peptide identification in targeted proteomics approaches such as SRM and SWATH MS.     

JUMP: A Tag-based Database Search Tool for Peptide Identification with High Sensitivity and Accuracy

Database search programs are essential tools for identifying peptides via mass spectrometry (MS) in shotgun proteomics. Simultaneously achieving high sensitivity and high specificity during a database search is crucial for improving proteome coverage. Here we present JUMP, a new hybrid database search program that generates amino acid tags and ranks peptide spectrum matches (PSMs) by an integrated score from the tags and pattern matching. In a typical run of liquid chromatography coupled with high-resolution tandem MS, more than 95% of MS/MS spectra can generate at least one tag, whereas the remaining spectra are usually too poor to derive genuine PSMs. To enhance search sensitivity, the JUMP program enables the use of tags as short as one amino acid. Using a target-decoy strategy, we compared JUMP with other programs (e.g. SEQUEST, Mascot, PEAKS DB, and InsPecT) in the analysis of multiple datasets and found that JUMP outperformed these preexisting programs. JUMP also permitted the analysis of multiple co-fragmented peptides from “mixture spectra” to further increase PSMs. In addition, JUMP-derived tags allowed partial de novo sequencing and facilitated the unambiguous assignment of modified residues. In summary, JUMP is an effective database search algorithm complementary to current search programs.Peptide identification by tandem mass spectra is a critical step in mass spectrometry (MS)-based¹ proteomics (1). Numerous computational algorithms and software tools have been developed for this purpose (2–6). These algorithms can be classified into three categories: (i) pattern-based database search, (ii) de novo sequencing, and (iii) hybrid search that combines database search and de novo sequencing. With the continuous development of high-performance liquid chromatography and high-resolution mass spectrometers, it is now possible to analyze almost all protein components in mammalian cells (7). In contrast to rapid data collection, it remains a challenge to extract accurate information from the raw data to identify peptides with low false positive rates (specificity) and minimal false negatives (sensitivity) (8).Database search methods usually assign peptide sequences by comparing MS/MS spectra to theoretical peptide spectra predicted from a protein database, as exemplified in SEQUEST (9), Mascot (10), OMSSA (11), X!Tandem (12), Spectrum Mill (13), ProteinProspector (14), MyriMatch (15), Crux (16), MS-GFDB (17), Andromeda (18), BaMS² (19), and Morpheus (20). Some other programs, such as SpectraST (21) and Pepitome (22), utilize a spectral library composed of experimentally identified and validated MS/MS spectra. These methods use a variety of scoring algorithms to rank potential peptide spectrum matches (PSMs) and select the top hit as a putative PSM. However, not all PSMs are correctly assigned. For example, false peptides may be assigned to MS/MS spectra with numerous noisy peaks and poor fragmentation patterns. If the samples contain unknown protein modifications, mutations, and contaminants, the related MS/MS spectra also result in false positives, as their corresponding peptides are not in the database. Other false positives may be generated simply by random matches. Therefore, it is of importance to remove these false PSMs to improve dataset quality. One common approach is to filter putative PSMs to achieve a final list with a predefined false discovery rate (FDR) via a target-decoy strategy, in which decoy proteins are merged with target proteins in the same database for estimating false PSMs (23–26). However, the true and false PSMs are not always distinguishable based on matching scores. It is a problem to set up an appropriate score threshold to achieve maximal sensitivity and high specificity (13, 27, 28).De novo methods, including Lutefisk (29), PEAKS (30), NovoHMM (31), PepNovo (32), pNovo (33), Vonovo (34), and UniNovo (35), identify peptide sequences directly from MS/MS spectra. These methods can be used to derive novel peptides and post-translational modifications without a database, which is useful, especially when the related genome is not sequenced. High-resolution MS/MS spectra greatly facilitate the generation of peptide sequences in these de novo methods. However, because MS/MS fragmentation cannot always produce all predicted product ions, only a portion of collected MS/MS spectra have sufficient quality to extract partial or full peptide sequences, leading to lower sensitivity than achieved with the database search methods.To improve the sensitivity of the de novo methods, a hybrid approach has been proposed to integrate peptide sequence tags into PSM scoring during database searches (36). Numerous software packages have been developed, such as GutenTag (37), InsPecT (38), Byonic (39), DirecTag (40), and PEAKS DB (41). These methods use peptide tag sequences to filter a protein database, followed by error-tolerant database searching. One restriction in most of these algorithms is the requirement of a minimum tag length of three amino acids for matching protein sequences in the database. This restriction reduces the sensitivity of the database search, because it filters out some high-quality spectra in which consecutive tags cannot be generated.In this paper, we describe JUMP, a novel tag-based hybrid algorithm for peptide identification. The program is optimized to balance sensitivity and specificity during tag derivation and MS/MS pattern matching. JUMP can use all potential sequence tags, including tags consisting of only one amino acid. When we compared its performance to that of two widely used search algorithms, SEQUEST and Mascot, JUMP identified ∼30% more PSMs at the same FDR threshold. In addition, the program provides two additional features: (i) using tag sequences to improve modification site assignment, and (ii) analyzing co-fragmented peptides from mixture MS/MS spectra.