Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring

Proteomic analysis of sperm from fertile stallions and subfertile stallions due to impaired acrosomal exocytosis

Thoroughbred stallions that carry a double-homozygous genotype A/A-A/A for SNPs rs397316122 and rs69101140 in exon 5 of the FKBP6 gene (chr13; EquCab3.0) are uniquely subfertile due to impaired acrosomal exocytosis (IAE). In this study, the sperm proteome in frozen/thawed semen from subfertile Thoroughbred stallions was studied and compared to that of frozen/thawed sperm from fertile Thoroughbred stallions. A total of 2,220 proteins was identified, of which 140 proteins were found to be differentially abundant in sperm from the subfertile stallions compared to that of fertile stallions (83 less and 57 more abundant). Proteins of differential abundance in sperm from the subfertile stallions were mainly overrepresented in the "metabolism" and the "metabolism of lipids" pathways. One of these proteins, arylsulfatase F (ARSF), was studied by immunofluorescence. A lower proportion of sperm displaying ARSF signal at the acrosome region was observed in sperm from subfertile Thoroughbred stallions. In addition, heterologous zona pellucida binding assays revealed that sperm from subfertile Thoroughbred stallions bound at a lower proportion to zonae pellucidae than sperm from fertile Thoroughbred stallions. In conclusion, a group of differential abundance proteins, including some of acrosome origin, were identified in sperm from subfertile stallions with acrosome dysfunction.

Comparative salivary proteomics analysis of children with and without early childhood caries using the DIA approach: A pilot study

OBJECTIVE

To screen differentially expressed proteins (DEPs) in the saliva of Early childhood caries (ECC) with different degrees of severity.

METHODS

The proteomic profiles of salivary of children with ECC of varying severity by data independent acquisition data independent acquisition (DIA) technique. A total of 12 preschool children aged 3-5 years were included in this study.

RESULTS

In this study, a total of 15,083 peptides and 1944 proteins were quantified; The results of DEPs screening showed that 34 DEPs were identified between the group H and the group LC, including 18 up-regulated proteins and 16 down-regulated proteins; 34 DEPs were screened between the group H and the group HC, including 17 up-regulated proteins and 17 down-regulated proteins; 42 DEPs were screened between the group LC and the group HC, including 18 up-regulated proteins and 24 down-regulated proteins. Among these DEPs, we screened several key proteins that may play a role in ECC, such as MK, histone H4, TGFβ3, ZG16B, MUC20, and SMR-3B.

CONCLUSION

Salivary proteins, as important host factors of caries, are differentially expressed between the saliva of ECC children and healthy children. Specific DEPs are expected to become potential biomarkers for the diagnosis of ECC.

Cyclic Ion Mobility for Hydrogen/Deuterium Exchange-Mass Spectrometry Applications

Hydrogen/deuterium exchange-mass spectrometry (HDX-MS) has emerged as a powerful tool to probe protein dynamics. As a bottom-up technique, HDX-MS provides information at peptide-level resolution, allowing structural localization of dynamic changes. Consequently, the HDX-MS data quality is largely determined by the number of peptides that are identified and monitored after deuteration. Integration of ion mobility (IM) into HDX-MS workflows has been shown to increase the data quality by providing an orthogonal mode of peptide ion separation in the gas phase. This is of critical importance for challenging targets such as integral membrane proteins (IMPs), which often suffer from low sequence coverage or redundancy in HDX-MS analyses. The increasing complexity of samples being investigated by HDX-MS, such as membrane mimetic reconstituted and in vivo IMPs, has generated need for instrumentation with greater resolving power. Recently, Giles et al. developed cyclic ion mobility (cIM), an IM device with racetrack geometry that enables scalable, multipass IM separations. Using one-pass and multipass cIM routines, we use the recently commercialized SELECT SERIES Cyclic IM spectrometer for HDX-MS analyses of four detergent solubilized IMP samples and report its enhanced performance. Furthermore, we develop a novel processing strategy capable of better handling multipass cIM data. Interestingly, use of one-pass and multipass cIM routines produced unique peptide populations, with their combined peptide output being 31 to 222% higher than previous generation SYNAPT G2-Si instrumentation. Thus, we propose a novel HDX-MS workflow with integrated cIM that has the potential to enable the analysis of more complex systems with greater accuracy and speed.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression

An altered proteome in lymph nodes often suggests abnormal signaling pathways that may be associated with diverse lymphatic disorders. Current clinical biomarkers for histological classification of lymphomas have encountered many discrepancies, particularly for borderline cases. Therefore, we launched a comprehensive proteomic study aimed to establish a proteomic landscape of patients with various lymphatic disorders and identify proteomic variations associated with different disease subgroups. In this study, 109 fresh-frozen lymph node tissues from patients with various lymphatic disorders (with a focus on Non-Hodgkin's Lymphoma) were analyzed by data-independent acquisition mass spectrometry. A quantitative proteomic landscape was comprehensively characterized, leading to the identification of featured protein profiles for each subgroup. Potential correlations between clinical outcomes and expression profiles of signature proteins were also probed. Two representative signature proteins, phospholipid-binding proteins Annexin A6 (ANXA6) and Phospholipase C Gamma 2 (PLCG2), were successfully validated via immunohistochemistry. We also evaluated the capability of acquired proteomic signatures to segregate multiple lymphatic abnormalities and identified several core signature proteins, such as Sialic Acid Binding Ig Like Lectin 1 (SIGLEC1) and GTPase of immunity-associated protein 5 (GIMAP5). In summary, the established lympho-specific data resource provides a comprehensive map of protein expression in lymph nodes during multiple disease states, thus extending the existing human tissue proteome atlas. Our findings will be of great value in exploring protein expression and regulation underlying lymphatic malignancies, while also providing novel protein candidates to classify various lymphomas for more precise medical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00075-w.

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)-also known as multiple reaction monitoring (MRM)-and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood

One of the cornerstones of effective cancer treatment is early diagnosis. In this context, the identification of proteins that can serve as cancer biomarkers in bodily fluids ("liquid biopsies") has gained attention over the last decade. Plasma and serum fractions of blood are the most commonly investigated sources of potential cancer liquid biopsy biomarkers. However, the high complexity and dynamic range typical of these fluids hinders the sensitivity of protein detection by the most commonly used mass spectrometry technology (data-dependent acquisition mass spectrometry (DDA-MS)). Recently, data-independent acquisition mass spectrometry (DIA-MS) techniques have overcome the limitations of DDA-MS, increasing sensitivity and proteome coverage. In addition to DIA-MS, isolating extracellular vesicles (EVs) can help to increase the depth of serum/plasma proteome coverage by improving the identification of low-abundance proteins which are a potential treasure trove of diagnostic molecules. EVs, the nano-sized membrane-enclosed vesicles present in most bodily fluids, contain proteins which may serve as potential biomarkers for various cancers. Here, we describe a detailed protocol that combines DIA-MS and EV methodologies for discovering and validating early cancer biomarkers using blood serum. The pipeline includes size exclusion chromatography methods to isolate serum-derived extracellular vesicles and subsequent EV sample preparation for liquid chromatography and mass spectrometry analysis. Procedures for spectral library generation by DDA-MS incorporate methods for off-line peptide separation by microflow HPLC with automated fraction concatenation. Analysis of the samples by DIA-MS includes recommended protocols for data processing and statistical methods. This pipeline will provide a guide to discovering and validating EV-associated proteins that can serve as sensitive and specific biomarkers for early cancer detection and other diseases.

The effect of tuina on ulcerative colitis model mice analyzed by gut microbiota and proteomics

Tuina can effectively alleviate ulcerative colitis-related symptoms, but the mechanism of action is unknown. The purpose of this research is to explore potential pathways for the treatment of tuina through gut microbiota and proteomics techniques. Thirty-two male BALB/c mice were divided into four groups, the control, model, mesalazine, and tuina groups. The ulcerative colitis model was established by freely drinking a 3% dextran sulphate sodium solution for 7 days. The mesalazine group and the tuina group, respectively, received 7 days of mesalazine and tuina treatment. Subsequently, their body weights, feces properties, colon length, histomorphological changes, gut microbiota, and colon proteomics were determined. Body weights, disease activity index score, colon histological scores, and microbiota diversity were restored in the tuina group. At the phylum level, Firmicutes was increased and Bacteroidota decreased. At the family level, Lachnospiraceae increased and Prevotellaceae decreased. At the genus level, the Lachnospiraceae_NK4A136_group was increased. Proteomics detected 370 differentially expressed proteins regulated by tuina, enriched to a total of 304 pathways, including biotin metabolism, Notch signaling pathway, linoleic acid metabolism, and autophagy. Tuina can effectively improve the symptoms of weight loss, fecal properties, and colon inflammation in ulcerative colitis mice and restore the gut microbiota diversity, adjusting the relative abundance of microbiota. The therapeutic effects of tuina may be achieved by modulating the signaling pathways of biotin metabolism, Notch signaling pathway, linoleic acid metabolism, and autophagy.

Targeted proteomics on its way to discovery

For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This changed with the recent advances in highly multiplexed analysis. While discovery proteomics still pushes higher numbers of identified and quantified proteins, the advances in targeted proteomics rose to cover large parts of less complex proteomes or proteomes with low protein detection counts due to dynamic range restrictions, like the blood proteome. These new developments will impact, especially on the field of biomarker discovery and the possibility of using targeted proteomics for diagnostic purposes. This article is protected by copyright. All rights reserved.

Systematic Characterization and Identification of Saikosaponins in Extracts From Bupleurum marginatum var. stenophyllum Using UPLC-PDA-Q/TOF-MS

Saikosaponins comprise a large group of chemical components present in the Bupleurum species that have attracted attention in the field of medicine because of their significant biological activities. Due to the high polarity, structural similarity, and the presence of several isomers of this class of components, their structural identification is extremely challenging. In this study, the mass spectrometric fragmentation pathways, UV spectral features, and chromatographic behavior of different types of saikosaponins were investigated using 24 standard substances. Saikosaponins containing carbonyl groups (C=O) in the aglycone produced fragment ions by loss of 30 Da, and in addition, type IV saikosaponins could produce [aglycone−CH₂OH−OH−H]⁻ and [aglycone−H₂O−H]⁻ fragment ions through neutral losses at positions C₁₆ and C₁₇. The above characteristic ions can be used to identify saikosaponins. More notably, the identification process of saikosaponins was systematically summarized, and using this method, 109 saikosaponins were identified or tentatively characterized from the saikosaponins extract of Bupleurum marginatum var. stenophyllum (BMS) using UPLC-PDA-Q/TOF-MS with both data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes, of which 25 were new compounds and 60 were first discovered from BMS. Further studies revealed that the saikosaponins profiles of BMS, Bupleurum chinense DC (BC), and Bupleurum marginatum Wall. ex DC (BMW) were very similar. This work is of great significance for the basic research of the Bupleurum species and provides strong technical support to solve the resource problems associated with Radix Bupleuri.

Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Advances in mass spectrometric methods for detection of hemoglobin disorders

Hemoglobin disorders are caused due to alterations in the hemoglobin molecules. These disorders are categorized in two broad classes - hemoglobin variants and thalassemias. The hemoglobin variants arise due to point mutations in the alpha (α), beta (β), gamma (γ), delta (δ), or epsilon (ε) globin chains of these proteins, while thalassemias are caused due to the under-production of α or β globin chain. Hemoglobin disorders account for 7 % of the major health issues globally. Mass Spectrometry is an extensively used analytical tool in the field of protein identification, protein-protein interaction, biomarker discovery and diagnosis of several impairments including hemoglobin related disorders. The remarkable advancements in the technology and method development have enormously augmented the clinical significance of mass spectrometry in these fields. The present review describes hemoglobin disorders and the recent advancements in mass spectrometry in the detection of such disorders, including its advantages, lacunae, and future directions. The literature evidence concludes that mass spectrometry can be potentially used as a 'First Line Screening Assay' for the detection of hemoglobin disorders in the near future.

Gene Validation and Remodelling Using Proteogenomics of Phytophthora cinnamomi, the Causal Agent of Dieback

Phytophthora cinnamomi is a pathogenic oomycete that causes plant dieback disease across a range of natural ecosystems and in many agriculturally important crops on a global scale. An annotated draft genome sequence is publicly available (JGI Mycocosm) and suggests 26,131 gene models. In this study, soluble mycelial, extracellular (secretome), and zoospore proteins of P. cinnamomi were exploited to refine the genome by correcting gene annotations and discovering novel genes. By implementing the diverse set of sub-proteomes into a generated proteogenomics pipeline, we were able to improve the P. cinnamomi genome annotation. Liquid chromatography mass spectrometry was used to obtain high confidence peptides with spectral matching to both the annotated genome and a generated 6-frame translation. Two thousand seven hundred sixty-four annotations from the draft genome were confirmed by spectral matching. Using a proteogenomic pipeline, mass spectra were used to edit the P. cinnamomi genome and allowed identification of 23 new gene models and 60 edited gene features using high confidence peptides obtained by mass spectrometry, suggesting a rate of incorrect annotations of 3% of the detectable proteome. The novel features were further validated by total peptide support, alongside functional analysis including the use of Gene Ontology and functional domain identification. We demonstrated the use of spectral data in combination with our proteogenomics pipeline can be used to improve the genome annotation of important plant diseases and identify missed genes. This study presents the first use of spectral data to edit and manually annotate an oomycete pathogen.

Fragmentation and Mobility Separation of Peptide and Protein Ions in a Trapped-Ion Mobility Device

Ion mobility separations (IMS) have increasingly been coupled with mass spectrometry to increase peak capacity and deconvolute complex mass spectra in proteomics workflows. IMS separations can be integrated prior to or following the collisional activation step. Post-activation IMS separations have demonstrated many advantages, yet few instrument platforms are capable of this feat. Here, we present the fragmentation of peptide ions within a commercially available trapped-ion mobility spectrometry device. Fragmentation is initiated prior to mobility analysis enabling the separation of generated product ions. The added separation step deconvolutes product ion spectra and permits improved annotation of product ions. Furthermore, we demonstrate the isolation and fragmentation of mobility separated product ions with the downstream quadrupole and collisional cell. When applied to melittin and ubiquitin, this ion mobility assisted pseudo-MS³ fragmentation approach generates sequence coverage ∼50% greater than that of typical MS² analyses. We envision this ion-mobility-assisted fragmentation technique as the foundation of a powerful new pseudo-MS³ workflow for application toward middle- or top-down proteomics.

Review of Methodological Approaches to Human Milk Small Extracellular Vesicle Proteomics

Proteomics can map extracellular vesicles (EVs), including exosomes, across disease states between organisms and cell types. Due to the diverse origin and cargo of EVs, tailoring methodological and analytical techniques can support the reproducibility of results. Proteomics scans are sensitive to in-sample contaminants, which can be retained during EV isolation procedures. Contaminants can also arise from the biological origin of exosomes, such as the lipid-rich environment in human milk. Human milk (HM) EVs and exosomes are emerging as a research interest in health and disease, though the experimental characterization and functional assays remain varied. Past studies of HM EV proteomes have used data-dependent acquisition methods for protein detection, however, improvements in data independent acquisition could allow for previously undetected EV proteins to be identified by mass spectrometry. Depending on the research question, only a specific population of proteins can be compared and measured using isotope and other labelling techniques. In this review, we summarize published HM EV proteomics protocols and suggest a methodological workflow with the end-goal of effective and reproducible analysis of human milk EV proteomes.

Proteomics Landscape of Alzheimer's Disease

Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.

Comparative proteomics analysis of Tibetan hull-less barley under osmotic stress via data-independent acquisition mass spectrometry

Background

Tibetan hull-less barley (Hordeum vulgare L. var. nudum) is one of the primary crops cultivated in the mountains of Tibet and encounters low temperature, high salinity, and drought. Specifically, drought is one of the major abiotic stresses that affect and limit Tibetan barley growth. Osmotic stress is often simultaneously accompanied by drought conditions. Thus, to improve crop yield, it is critical to explore the molecular mechanism governing the responses of hull-less barley to osmotic/drought stress conditions.

Findings

In this study, we used quantitative proteomics by data-independent acquisition mass spectrometry to investigate protein abundance changes in tolerant (XL) and sensitive (DQ) cultivars. A total of 6,921 proteins were identified and quantified in all samples. Two distinct strategies based on pairwise and time-course comparisons were utilized in the comprehensive analysis of differentially abundant proteins. Further functional analysis of differentially abundant proteins revealed that some hormone metabolism–associated and phytohormone abscisic acid–induced genes are primarily affected by osmotic stress. Enhanced regulation of reactive oxygen species (may promote the tolerance of hull-less barley under osmotic stress. Moreover, we found that some regulators, such as GRF, PR10, MAPK, and AMPK, were centrally positioned in the gene regulatory network, suggesting that they may have a dominant role in the osmotic stress response of Tibetan barley.

Conclusions

Our findings highlight a subset of proteins and processes that are involved in the alleviation of osmotic stress. In addition, this study provides a large-scale and multidimensional proteomic data resource for the further investigation and improvement of osmotic/drought stress tolerance in hull-less barley or other plant species.

Metaproteomics insights into traditional fermented foods and beverages

Traditional fermented foods and beverages (TFFB) are important dietary components. Multi-omics techniques have been applied to all aspects of TFFB research to clarify the composition and nutritional value of TFFB, and to reveal the microbial community, microbial interactions, fermentative kinetics, and metabolic profiles during the fermentation process of TFFB. Because of the advantages of metaproteomics in providing functional information, this technology has increasingly been used in research to assess the functional diversity of microbial communities. Metaproteomics is gradually gaining attention in the field of TFFB research because it can reveal the nature of microorganism function at the protein level. This paper reviews the common methods of metaproteomics applied in TFFB research; systematically summarizes the results of metaproteomics research on TFFB, such as sauces, wines, fermented tea, cheese, and fermented fish; and compares the differences in conclusions reached through metaproteomics versus other omics methods. Metaproteomics has great advantages in revealing the microbial functions in TFFB and the interaction between the materials and microbial community. In the future, metaproteomics should be further applied to the study of functional protein markers and protein interaction in TFFB; multi-omics technology requires further integration to reveal the molecular nature of TFFB fermentation.

A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins

Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) is a data-independent acquisition (DIA) strategy that requires a specific spectral library to generate unbiased and consistent quantitative data matrices of all peptides. SWATH-MS is a promising approach for in-depth proteomic profiling of Chinese hamster Ovary (CHO) cell lines, improving mechanistic understanding of process optimization, and real-time monitoring of process parameters in biologics R&D and manufacturing. However, no spectral library for CHO cells is publicly available. Here we present a comprehensive CHO global spectral library to measure the abundance of more than 10,000 proteins consisting of 199,102 identified peptides from a CHO-K1 cell proteome. The robustness, accuracy and consistency of the spectral library were validated for high confidence in protein identification and reproducible quantification in different CHO-derived cell lines, instrumental setups and downstream processing samples. The availability of a comprehensive SWATH CHO global spectral library will facilitate detailed characterization of upstream and downstream processes, as well as quality by design (QbD) in biomanufacturing. The data have been deposited to ProteomeXchange (PXD016047).

The Mitochondrial Proteomic Signatures of Human Skeletal Muscle Linked to Insulin Resistance

Introduction: Mitochondria are essential in energy metabolism and cellular survival, and there is growing evidence that insulin resistance in chronic metabolic disorders, such as obesity, type 2 diabetes (T2D), and aging, is linked to mitochondrial dysfunction in skeletal muscle. Protein profiling by proteomics is a powerful tool to investigate mechanisms underlying complex disorders. However, despite significant advances in proteomics within the past two decades, the technologies have not yet been fully exploited in the field of skeletal muscle proteome. Area covered: Here, we review the currently available studies characterizing the mitochondrial proteome in human skeletal muscle in insulin-resistant conditions, such as obesity, T2D, and aging, as well as exercise-mediated changes in the mitochondrial proteome. Furthermore, we outline technical challenges and limitations and methodological aspects that should be considered when planning future large-scale proteomics studies of mitochondria from human skeletal muscle. Authors’ view: At present, most proteomic studies of skeletal muscle or isolated muscle mitochondria have demonstrated a reduced abundance of proteins in several mitochondrial biological processes in obesity, T2D, and aging, whereas the beneficial effects of exercise involve an increased content of muscle proteins involved in mitochondrial metabolism. Powerful mass-spectrometry-based proteomics now provides unprecedented opportunities to perform in-depth proteomics of muscle mitochondria, which in the near future is expected to increase our understanding of the complex molecular mechanisms underlying the link between mitochondrial dysfunction and insulin resistance in chronic metabolic disorders.

DNA adducts: Formation, biological effects, and new biospecimens for mass spectrometric measurements in humans

Hazardous chemicals in the environment and diet or their electrophilic metabolites can form adducts with genomic DNA, which can lead to mutations and the initiation of cancer. In addition, reactive intermediates can be generated in the body through oxidative stress and damage the genome. The identification and measurement of DNA adducts are required for understanding exposure and the causal role of a genotoxic chemical in cancer risk. Over the past three decades, 32 P-postlabeling, immunoassays, gas chromatography/mass spectrometry, and liquid chromatography/mass spectrometry (LC/MS) methods have been established to assess exposures to chemicals through measurements of DNA adducts. It is now possible to measure some DNA adducts in human biopsy samples, by LC/MS, with as little as several milligrams of tissue. In this review article, we highlight the formation and biological effects of DNA adducts, and highlight our advances in human biomonitoring by mass spectrometric analysis of formalin-fixed paraffin-embedded tissues, untapped biospecimens for carcinogen DNA adduct biomarker research.

Exploring novel secondary metabolites from natural products using pre-processed mass spectral data

Many natural product chemists are working to identify a wide variety of novel secondary metabolites from natural materials and are eager to avoid repeatedly discovering known compounds. Here, we developed liquid chromatography/mass spectrometry (LC/MS) data-processing protocols for assessing high-throughput spectral data from natural sources and scoring the novelty of unknown metabolites from natural products. This approach automatically produces representative MS spectra (RMSs) corresponding to single secondary metabolites in natural sources. In this study, we used the RMSs of Agrimonia pilosa roots and aerial parts as models to reveal the structural similarities of their secondary metabolites and identify novel compounds, as well as isolation of three types of nine new compounds including three pilosanidin- and four pilosanol-type molecules and two 3-hydroxy-3-methylglutaryl (HMG)-conjugated chromones. Furthermore, we devised a new scoring system, the Fresh Compound Index (FCI), which grades the novelty of single secondary metabolites from a natural material using an in-house database constructed from 466 representative medicinal plants from East Asian countries. We expect that the FCIs of RMSs in a sample will help natural product chemists to discover other compounds of interest with similar chemical scaffolds or novel compounds and will provide insights relevant to the structural diversity and novelty of secondary metabolites in natural products.

A Metabolomics-Inspired Strategy for the Identification of Protein Covalent Modifications

Identification of protein covalent modifications (adducts) is a challenging task mainly due to the lack of data processing approaches for adductomics studies. Despite the huge technological advances in mass spectrometry (MS) instrumentation and bioinformatics tools for proteomics studies, these methodologies have very limited success on the identification of low abundant protein adducts. Herein we report a novel strategy inspired on the metabolomics workflows for the identification of covalently-modified peptides that consists on LC-MS data preprocessing followed by statistical analysis. The usefulness of this strategy was evaluated using experimental LC-MS data of histones isolated from HepG2 and THLE2 cells exposed to the chemical carcinogen glycidamide. LC-MS data was preprocessed using the open-source software MZmine and potential adducts were selected based on the m/z increments corresponding to glycidamide incorporation. Then, statistical analysis was applied to reveal the potential adducts as those ions are differently present in cells exposed and not exposed to glycidamide. The results were compared with the ones obtained upon the standard proteomics methodology, which relies on producing comprehensive MS/MS data by data dependent acquisition and analysis with proteomics data search engines. Our novel strategy was able to differentiate HepG2 and THLE2 and to identify adducts that were not detected by the standard methodology of adductomics. Thus, this metabolomics driven approach in adductomics will not only open new opportunities for the identification of protein epigenetic modifications, but also adducts formed by endogenous and exogenous exposure to chemical agents.

Multifaceted Stoichiometry Control of Bacterial Operons Revealed by Deep Proteome Quantification

More than half of the protein-coding genes in bacteria are organized in polycistronic operons composed of two or more genes. It remains under debate whether the operon organization maintains the stoichiometric expression of the genes within an operon. In this study, we performed a label-free data-independent acquisition hyper reaction monitoring mass-spectrometry (HRM-MS) experiment to quantify the Escherichia coli proteome in exponential phase and quantified 93.6% of the cytosolic proteins, covering 67.9% and 56.0% of the translating polycistronic operons in BW25113 and MG1655 strains, respectively. We found that the translational regulation contributes largely to the proteome complexity: the shorter operons tend to be more tightly controlled for stoichiometry than longer operons; the operons which mainly code for complexes is more tightly controlled for stoichiometry than the operons which mainly code for metabolic pathways. The gene interval (distance between adjacent genes in one operon) may serve as a regulatory factor for stoichiometry. The catalytic efficiency might be a driving force for differential expression of enzymes encoded in one operon. These results illustrated the multifaceted nature of the operon regulation: the operon unified transcriptional level and gene-specific translational level. This multi-level regulation benefits the host by optimizing the efficiency of the productivity of metabolic pathways and maintenance of different types of protein complexes.

Mass Spectrometry-Based Methodologies for Targeted and Untargeted Identification of Protein Covalent Adducts (Adductomics): Current Status and Challenges

Protein covalent adducts formed upon exposure to reactive (mainly electrophilic) chemicals may lead to the development of a wide range of deleterious health outcomes. Therefore, the identification of protein covalent adducts constitutes a huge opportunity for a better understanding of events underlying diseases and for the development of biomarkers which may constitute effective tools for disease diagnosis/prognosis, for the application of personalized medicine approaches and for accurately assessing human exposure to chemical toxicants. The currently available mass spectrometry (MS)-based methodologies, are clearly the most suitable for the analysis of protein covalent modifications, providing accuracy, sensitivity, unbiased identification of the modified residue and conjugates along with quantitative information. However, despite the huge technological advances in MS instrumentation and bioinformatics tools, the identification of low abundant protein covalent adducts is still challenging. This review is aimed at summarizing the MS-based methodologies currently used for the identification of protein covalent adducts and the strategies developed to overcome the analytical challenges, involving not only sample pre-treatment procedures but also distinct MS and data analysis approaches.

The nitrogen cost of photosynthesis

Global food security depends on three main cereal crops (wheat, rice and maize) achieving and maintaining high yields, as well as increasing their future yields. Fundamental to the production of this biomass is photosynthesis. The process of photosynthesis involves a large number of proteins that together account for the majority of the nitrogen in leaves. As large amounts of nitrogen are removed in the harvested grain, this needs to be replaced either from synthetic fertilizer or biological nitrogen fixation. Knowledge about photosynthetic properties of leaves in natural ecosystems is also important, particularly when we consider the potential impacts of climate change. While the relationship between nitrogen and photosynthetic capacity of a leaf differs between species, leaf nitrogen content provides a useful way to incorporate photosynthesis into models of ecosystems and the terrestrial biosphere. This review provides a generalized nitrogen budget for a C3 leaf cell and discusses the potential for improving photosynthesis from a nitrogen perspective.

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Mining for Microbial Gems: Integrating Proteomics in the Postgenomic Natural Product Discovery Pipeline

Natural products (NPs) are a major source of compounds for medical, agricultural, and biotechnological industries. Many of these compounds are of microbial origin, and, in particular, from Actinobacteria or filamentous fungi. To successfully identify novel compounds that correlate to a bioactivity of interest, or discover new enzymes with desired functions, systematic multiomics approaches have been developed over the years. Bioinformatics tools harness the rapidly expanding wealth of genome sequence information, revealing previously unsuspected biosynthetic diversity. Varying growth conditions or application of elicitors are applied to activate cryptic biosynthetic gene clusters, and metabolomics provide detailed insights into the NPs they specify. Combining these technologies with proteomics-based approaches to profile the biosynthetic enzymes provides scientists with insights into the full biosynthetic potential of microorganisms. The proteomics approaches include enrichment strategies such as employing activity-based probes designed by chemical biology, as well as unbiased (quantitative) proteomics methods. In this review, the opportunities and challenges in microbial NP research are discussed, and, in particular, the application of proteomics to link biosynthetic enzymes to the molecules they produce, and vice versa.

Development of a Gill Assay Library for Ecological Proteomics of Threespine Sticklebacks (Gasterosteus aculeatus)

A data-independent acquisition (DIA) assay library for quantitative analyses of proteome dynamics has been developed for gills of threespine sticklebacks (Gasterosteus aculeatus). A raw spectral library was generated by data-dependent acquisition (DDA) and annotation of tryptic peptides to MSMS spectra and protein database identifiers. The assay library was constructed from the raw spectral library by removal of low-quality, ambiguous, and low-signal peptides. Only unique proteins represented by at least two peptides are included in the assay library, which consists of 1506 proteins, 5074 peptides, 5104 precursors, and 25,322 transitions. This assay library was used with DIA data to identify biochemical differences in gill proteomes of four populations representing different eco- and morpho-types of threespine sticklebacks. The assay library revealed unique and reproducible proteome signatures. Warm-adapted, low-plated, brackish-water fish from Laguna de la Bocana del Rosario (Mexico) show elevated HSP47, extracellular matrix, and innate immunity proteins whereas several immunoglobulins, interferon-induced proteins, ubiquitins, proteolytic enzymes, and nucleic acid remodeling proteins are reduced. Fully-plated, brackish-water fish from Westchester Lagoon (Alaska) display elevated ion regulation, GTPase signaling, and contractile cytoskeleton proteins, altered abundances of many ribosomal, calcium signaling and immunity proteins, and depleted transcriptional regulators and metabolic enzymes. Low-plated freshwater fish from Lake Solano (California) have elevated inflammasomes and proteolytic proteins whereas several iron containing and ion regulatory proteins are reduced. Gills of fully-plated, marine fish from Bodega Harbor (California) have elevated oxidative metabolism enzymes and reduced transglutaminase 2, collagens, and clathrin heavy chains. These distinct proteome signatures represent targets for testing ecological and evolutionary influences on molecular mechanisms of gill function in threespine sticklebacks. Furthermore, the gill assay library represents a model for other tissues and paves the way for accurate and reproducible network analyses of environmental context-dependent proteome dynamics in complex organisms.

Proteomics in Inflammatory Bowel Disease: Approach Using Animal Models

Recently, proteomics studies have provided important information on the role of proteins in health and disease. In the domain of inflammatory bowel disease, proteomics has shed important light on the pathogenesis and pathophysiology of inflammation and has contributed to the discovery of some putative clinical biomarkers of disease activity. By being able to obtain a large number of specimens from multiple sites and control for confounding environmental, genetic, and metabolic factors, proteomics studies using animal models of colitis offered an alternative approach to human studies. Our aim is to review the information and lessons acquired so far from the use of proteomics in animal models of colitis. These studies helped understand the importance of different proteins at different stages of the disease and unraveled the different pathways that are activated or inhibited during the inflammatory process. Expressed proteins related to inflammation, cellular structure, endoplasmic reticulum stress, and energy depletion advanced the knowledge about the reaction of intestinal cells to inflammation and repair. The role of mesenteric lymphocytes, exosomes, and the intestinal mucosal barrier was emphasized in the inflammatory process. In addition, studies in animal models revealed mechanisms of the beneficial effects of some therapeutic interventions and foods or food components on intestinal inflammation by monitoring changes in protein expression and paved the way for some new possible inflammatory pathways to target in the future. Advances in proteomics technology will further clarify the interaction between intestinal microbiota and IBD pathogenesis and investigate the gene-environmental axis of IBD etiology.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Targeted Annotation of S-Sulfonylated Peptides by Selective Infrared Multiphoton Dissociation Mass Spectrometry

Protein S-sulfinylation (R-SO₂^-) and S-sulfonylation (R-SO₃^-) are irreversible oxidative post-translational modifications of cysteine residues. Greater than 5% of cysteines are reported to occupy these higher oxidation states, which effectively inactivate the corresponding thiols and alter the electronic and physical properties of modified proteins. Such higher oxidation states are reached after excessive exposure to cellular oxidants, and accumulate across different disease states. Despite widespread and functionally relevant cysteine oxidation across the proteome, there are currently no robust methods to profile higher order cysteine oxidation. Traditional data-dependent liquid chromatography/tandem mass spectrometry (LC/MS/MS) methods generally miss low-occupancy modifications in complex analyses. Here, we present a data-independent acquisition (DIA) LC/MS-based approach, leveraging the high IR absorbance of sulfoxides at 10.6 μm, for selective dissociation and discovery of S-sulfonated peptides. Across peptide standards and protein digests, we demonstrate selective infrared multiphoton dissociation (IRMPD) of S-sulfonated peptides in the background of unmodified peptides. This selective DIA IRMPD LC/MS-based approach allows identification and annotation of S-sulfonated peptides across complex mixtures while providing sufficient sequence information to localize the modification site.

Is myelin basic protein a potential biomarker of brain cancer?

Myelin basic protein is a potential biomarker for the central nervous system diseases in which the myelin sheath is destroyed. Using pseudo-selected reaction monitoring and the method of standard additions, we have measured the myelin basic protein level in the cerebrospinal fluid of patients with neurotrauma (n = 6), chronic neurodegenerative diseases (n = 2) and brain cancer (n = 5). Myelin basic protein was detected only in four out of five cerebrospinal fluid samples of patients with brain cancer. The cerebrospinal fluid myelin basic protein level ranged from 3.7 to 8.8 ng ml^-1. We suggest that monitoring of myelin basic protein in cerebrospinal fluid can serve as a diagnostic test for the brain cancer.

Comparison of fractionation proteomics for local SWATH library building

For data-independent acquisition by means of sequential window acquisition of all theoretical fragment ion spectra (SWATH), a reference library of data-dependent acquisition (DDA) runs is typically used to correlate the quantitative data from the fragment ion spectra with peptide identifications. The quality and coverage of such a reference library is therefore essential when processing SWATH data. In general, library sizes can be increased by reducing the impact of DDA precursor selection with replicate runs or fractionation. However, these strategies can affect the match between the library and SWATH measurement, and thus larger library sizes do not necessarily correspond to improved SWATH quantification. Here, three fractionation strategies to increase local library size were compared to standard library building using replicate DDA injection: protein SDS-PAGE fractionation, peptide high-pH RP-HPLC fractionation and MS-acquisition gas phase fractionation. The impact of these libraries on SWATH performance was evaluated in terms of the number of extracted peptides and proteins, the match quality of the peptides and the extraction reproducibility of the transitions. These analyses were conducted using the hydrophilic proteome of differentiating human embryonic stem cells. Our results show that SWATH quantitative results and interpretations are affected by choice of fractionation technique. Data are available via ProteomeXchange with identifier PXD006190.

Targeted mass spectrometry: An emerging powerful approach to unblock the bottleneck in phosphoproteomics

Following the rapid expansion of the proteomics field, the investigation of post translational modifications (PTM) has become extremely popular changing our perspective of how proteins constantly fine tune cellular functions. Reversible protein phosphorylation plays a pivotal role in virtually all biological processes in the cell and it is one the most characterized PTM up to date. During the last decade, the development of phosphoprotein/phosphopeptide enrichment strategies and mass spectrometry (MS) technology has revolutionized the field of phosphoproteomics discovering thousands of new site-specific phosphorylations and unveiling unprecedented evidence about their modulation under distinct cellular conditions. The field has expanded so rapidly that the use of traditional methods to validate and characterize the biological role of the phosphosites is not feasible any longer. Targeted MS holds great promise for becoming the method of choice to study with high precision and sensitivity already known site-specific phosphorylation events. This review summarizes the contribution of large-scale unbiased MS analyses and highlights the need of targeted MS-based approaches for follow-up investigation. Additionally, the article illustrates the biological relevance of protein phosphorylation by providing examples of disease-related phosphorylation events and emphasizes the benefits of applying targeted MS in clinics for disease diagnosis, prognosis and drug-response evaluation.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.

A global inter-laboratory study to assess acquisition modes for multi-compound confirmatory analysis of veterinary drugs using liquid chromatography coupled to triple quadrupole, time of flight and orbitrap mass spectrometry

According to EU legislation a confirmatory method used for residue analysis should be able to confirm the identity of a compound beyond reasonable doubt. To provide an adequate instrumental set-up, Commission Decision 2002/657/EC introduced the concept of "identification points". A second aspect to assure unequivocal confirmation, is the establishment of ion ratio and retention time criteria. Currently, the gold standard for confirmatory analysis of most veterinary drug residues is liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) in selected reaction monitoring (SRM) acquisition mode, isolating one precursor ion and monitoring two a priori selected product ions, yielding 4 identification points. We comprehensively evaluated the use of different low and high resolution LC-MS(/MS) techniques and acquisition modes with respect to the selectivity of 100 veterinary drugs in liver, muscle and urine extracts aiming to critically review the currently established identification points system. A comparison among MS/MS in SRM mode with high resolution mass spectrometry (HRMS) in full scan, all ion fragmentation and targeted MS/MS was made based on a unique inter-laboratory study, which comprises 21 laboratories from four different continents and equipment from all major vendors. In total 186 samples were analysed yielding results for 9282 analyte/matrix combinations. It was observed that the false positive rate approximately doubles if no ion ratio criterion is applied indicating that this criterion is important to prevent false positive results. Full scan HRMS analysis, only monitoring the molecular ion and allowing a ±5 ppm mass tolerance is, in general, less selective than low resolution MS/MS using SRM, and thus full scan alone is considered not sufficient for confirmatory analysis. Furthermore, even though the number of data on all ion fragmentation and targeted MS/MS at high resolution was limited, based on the data obtained, it was observed that the acquisition mode as well as the mass resolution needed, very much depend on the matrix and the compound itself. For complex matrix extracts and non-selective compounds (worst-case situation), only targeted MS/MS, monitoring the precursor ion and a single product ion in HR-MS using a maximum of ±5 ppm mass deviation, leads to comparable selectivity and false positive and negative rate as SRM monitoring two product ions in LR-MS. We conclude that the currently applied identification point system as established in commission decision 2002/657/EC should be revised with respect to the allocation of identification points.

Biomonitoring Human Albumin Adducts: The Past, the Present, and the Future

Serum albumin (Alb) is the most abundant protein in blood plasma. Alb reacts with many carcinogens and/or their electrophilic metabolites. Studies conducted over 20 years ago showed that Alb forms adducts with the human carcinogens aflatoxin B1 and benzene, which were successfully used as biomarkers in molecular epidemiology studies designed to address the role of these chemicals in cancer risk. Alb forms adducts with many therapeutic drugs or their reactive metabolites such as β-lactam antibiotics, acetylsalicylic acid, acetaminophen, nonsteroidal anti-inflammatory drugs, chemotherapeutic agents, and antiretroviral therapy drugs. The identification and characterization of the adduct structures formed with Alb have served to understand the generation of reactive metabolites and to predict idiosyncratic drug reactions and toxicities. The reaction of candidate drugs with Alb is now exploited as part of the battery of screening tools to assess the potential toxicities of drugs. The use of gas chromatography-mass spectrometry, liquid chromatography, or liquid chromatography-mass spectrometry (LC-MS) enabled the identification and quantification of multiple types of Alb xenobiotic adducts in animals and humans during the past three decades. In this perspective, we highlight the history of Alb as a target protein for adduction to environmental and dietary genotoxicants, pesticides, and herbicides, common classes of medicinal drugs, and endogenous electrophiles, and the emerging analytical mass spectrometry technologies to identify Alb-toxicant adducts in humans.