Protein analysis by shotgun/bottom-up proteomics

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Cell-cell transfer of adaptation traits benefits kin and actor in a cooperative microbe

Microbes face many physical, chemical, and biological insults from their environments. In response, cells adapt, but whether they do so cooperatively is poorly understood. Here, we use a model social bacterium, Myxococcus xanthus, to ask whether adapted traits are transferable to naïve kin. To do so we isolated cells adapted to detergent stresses and tested for trait transfer. In some cases, strain-mixing experiments increased sibling fitness by transferring adaptation traits. This cooperative behavior depended on a kin recognition system called outer membrane exchange (OME) because mutants defective in OME could not transfer adaptation traits. Strikingly, in mixed stressed populations, the transferred trait also benefited the adapted (actor) cells. This apparently occurred by alleviating a detergent-induced stress response in kin that otherwise killed actor cells. Additionally, this adaptation trait when transferred also conferred resistance against a lipoprotein toxin delivered to targeted kin. Based on these and other findings, we propose a model for stress adaptation and how OME in myxobacteria promotes cellular cooperation in response to environmental stresses.

Myoglobin as a molecular biomarker for meat authentication and traceability

The global incidence of economically motivated meat adulteration represents a crucial issue for the food industry. Undeclared addition of cheaper or low-quality species to meat products of high commercial value has become a common practice that needs to be countered with specific measures. In this framework, myoglobin (Mb) is a sarcoplasmic haemoprotein, primarily responsible for meat colour and has been successfully used in meat fraud authentication. Mb is highly soluble in water, easily monitored at 409 nm and species-specific. Knowing that various analytical DNA-based and protein-based methods, as well as spectroscopic techniques have been developed over the years for the detection of meat fraud, the aim of the present review is to take stock of the situation regarding the possible use of Mb as a molecular biomarker for the easy and rapid detection of undeclared species in meat products, avoiding the need of sophisticated or expensive equipment and specialised operators.

Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae

Mass spectrometry proteomics data are typically evaluated against publicly available annotated sequences, but the proteogenomics approach is a useful alternative. A single genome is commonly utilized in custom proteomic and proteogenomic data analysis. We pose the question of whether utilizing numerous different genome assemblies in a search database would be beneficial. We reanalyzed raw data from the exoprotein fraction of four reference Enterobacterial Repetitive Intergenic Consensus (ERIC) I-IV genotypes of the honey bee bacterial pathogen Paenibacillus larvae and evaluated them against three reference databases (from NCBI-protein, RefSeq, and UniProt) together with an array of protein sequences generated by six-frame direct translation of 15 genome assemblies from GenBank. The wide search yielded 453 protein hits/groups, which UpSet analysis categorized into 50 groups based on the success of protein identification by the 18 database components. Nine hits that were not identified by a unique peptide were not considered for marker selection, which discarded the only protein that was not identified by the reference databases. We propose that the variability in successful identifications between genome assemblies is useful for marker mining. The results suggest that various strains of P. larvae can exhibit specific traits that set them apart from the established genotypes ERIC I-V.

The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses

Mass spectrometry-based approaches to assess protein conformation have become widely utilized due to their sensitivity, low sample requirements, and broad applicability to proteins regardless of size and environment. Their wide applicability and sensitivity also make these techniques suitable for the analysis of complex mixtures of proteins, and thus, they have been applied at the cell and even the simple organism levels. These works are impressive, but they predominately employ "bottom-up" workflows and require proteolytic digestion prior to analysis. Once digested, it is not possible to distinguish the proteoform from which any single peptide is derived and therefore, one cannot associate distal-in primary structure-concurrent post-translational modifications (PTMs) or covalent labels, as they would be found on separate peptides. Thus, analyses via bottom-up proteomics report the average PTM status and higher-order structure (HOS) of all existing proteoforms. Second, these works predominately employ promiscuous reagents to probe protein HOS. While this does lead to improved conformational resolution, the formation of many products can divide the signal associated with low-copy number proteins below signal-to-noise thresholds and complicate the bioinformatic analysis of these already challenging systems. In this perspective, I further detail these limitations and discuss the positives and negatives of top-down proteomics as an alternative.

[Applications of high performance liquid chromatography-mass spectrometry in proteomics]

Proteomics profiling plays an important role in biomedical studies. Proteomics studies are much more complicated than genome research, mainly because of the complexity and diversity of proteomic samples. High performance liquid chromatography-mass spectrometry (HPLC-MS) is a fundamental tool in proteomics research owing to its high speed, resolution, and sensitivity. Proteomics research targets from the peptides and individual proteins to larger protein complexes, the molecular weight of which gradually increases, leading to sustained increases in structural and compositional complexity and alterations in molecular properties. Therefore, the selection of various separation strategies and stationary-phase parameters is crucial when dealing with the different targets in proteomics research for in-depth proteomics analysis. This article provides an overview of commonly used chromatographic-separation strategies in the laboratory, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic interaction chromatography (HIC), ion-exchange chromatography (IEC), and size-exclusion chromatography (SEC), as well as their applications and selectivity in the context of various biomacromolecules. At present, no single chromatographic or electrophoretic technology features the peak capacity required to resolve such complex mixtures into individual components. Multidimensional liquid chromatography (MDLC), which combines different orthogonal separation modes with MS, plays an important role in proteomics research. In the MDLC strategy, IEC, together with RPLC, remains the most widely used separation mode in proteomics analysis; other chromatographic methods are also frequently used for peptide/protein fractionation. MDLC technologies and their applications in a variety of proteomics analyses have undergone great development. Two strategies in MDLC separation systems are mainly used in proteomics profiling: the "bottom-up" approach and the "top-down" approach. The "shotgun" method is a typical "bottom-up" strategy that is based on the RPLC or MDLC separation of whole-protein-sample digests coupled with MS; it is an excellent technique for identifying a large number of proteins. "Top-down" analysis is based on the separation of intact proteins and provides their detailed molecular information; thus, this technique may be advantageous for analyzing the post-translational modifications (PTMs) of proteins. In this paper, the "bottom-up" "top-down" and protein-protein interaction (PPI) analyses of proteome samples are briefly reviewed. The diverse combinations of different chromatographic modes used to set up MDLC systems are described, and compatibility issues between mobile phases and analytes, between mobile phases and MS, and between mobile phases in different separation modes in multidimensional chromatography are analyzed. Novel developments in MDLC techniques, such as high-abundance protein depletion and chromatography arrays, are further discussed. In this review, the solutions proposed by researchers when encountering compatibility issues are emphasized. Moreover, the applications of HPLC-MS combined with various sample pretreatment methods in the study of exosomal and single-cell proteomics are examined. During exosome isolation, the combined use of ultracentrifugation and SEC can yield exosomes of higher purity. The use of SEC with ultra-large-pore-size packing materials (200 nm) enables the isolation of exosomal subgroups, and proteomics studies have revealed significant differences in protein composition and function between these subgroups. In the field of single-cell proteomics, researchers have addressed challenges related to reducing sample processing volumes, preventing sample loss, and avoiding contamination during sample preparation. Innovative methods and improvements, such as the utilization of capillaries for sample processing and microchips as platforms to minimize the contact area of the droplets, have been proposed. The integration of these techniques with HPLC-MS shows some progress. In summary, this article focuses on the recent advances in HPLC-MS technology for proteomics analysis and provides a comprehensive reference for future research in the field of proteomics.

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

[An enrichment strategy based on hydrophobic tagging and reversed-phase chromatographic separation for the analysis of lysine-containing peptides]

Lysine (K) is widely used in the design of lysine-targeted crosslinkers, structural elucidation of protein complexes, and analysis of protein-protein interactions. In "shotgun" proteomics, which is based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), proteins from complex samples are enzymatically digested, generating thousands of peptides and presenting significant challenges for the direct analysis of K-containing peptides. In view of the lack of effective methods for the enrichment of K-containing peptides, this work developed a method which based on a hydrophobic-tag-labeling reagent C10-S-S-NHS and reversed-phase chromatography (termed as HYTARP) to achieve the efficient enrichment and identification of K-containing peptides from complex samples. The C10-S-S-NHS synthesized in this work successfully labeled standard peptides containing various numbers of K and the labeling efficiency achieved up to 96% for HeLa cell protein tryptic digests. By investigating the retention behavior of these labeled peptides in C18 RP column, we found that most K-labeled peptides were eluted once when acetonitrile percentage reached 57.6% (v/v). Further optimization of the elution gradient enabled the efficient separation and enrichment of the K-labeled peptides in HeLa digests via a stepwise elution gradient. The K-labeled peptides accounted for 90% in the enriched peptides, representing an improvement of 35% compared with the number of peptides without the enrichment. The dynamic range of proteins quantified from the enriched K-containing peptides spans 5-6 orders of magnitude, and realized the detection of low-abundance proteins in the complex sample. In summary, the HYTARP strategy offers a straightforward and effective approach for reducing sample complexity and improving the identification coverage of K-containing peptides and low-abundance proteins.

SpecEncoder: deep metric learning for accurate peptide identification in proteomics

MOTIVATION

Tandem mass spectrometry (MS/MS) is a crucial technology for large-scale proteomic analysis. The protein database search or the spectral library search are commonly used for peptide identification from MS/MS spectra, which, however, may face challenges due to experimental variations between replicated spectra and similar fragmentation patterns among distinct peptides. To address this challenge, we present SpecEncoder, a deep metric learning approach to address these challenges by transforming MS/MS spectra into robust and sensitive embedding vectors in a latent space. The SpecEncoder model can also embed predicted MS/MS spectra of peptides, enabling a hybrid search approach that combines spectral library and protein database searches for peptide identification.

RESULTS

We evaluated SpecEncoder on three large human proteomics datasets, and the results showed a consistent improvement in peptide identification. For spectral library search, SpecEncoder identifies 1%-2% more unique peptides (and PSMs) than SpectraST. For protein database search, it identifies 6%-15% more unique peptides than MSGF+ enhanced by Percolator, Furthermore, SpecEncoder identified 6%-12% additional unique peptides when utilizing a combined library of experimental and predicted spectra. SpecEncoder can also identify more peptides when compared to deep-learning enhanced methods (MSFragger boosted by MSBooster). These results demonstrate SpecEncoder's potential to enhance peptide identification for proteomic data analyses.

AVAILABILITY AND IMPLEMENTATION

The source code and scripts for SpecEncoder and peptide identification are available on GitHub at https://github.com/lkytal/SpecEncoder. Contact: hatang@iu.edu.

Isolation, Characterization and IgE Binding of Two 2S Albumins of Pomegranate Seeds

Literature reports suggest that the presence of proteins in pomegranate seeds is responsible for sensitization and IgE-mediated allergic reactions. The objective of this study was the analysis of a pomegranate seed extract and the isolation and characterization of proteins contained in high amounts. The extract characterization showed a protein profile with main bands at about 18 kDa and below 10 kDa upon SDS-PAGE, and molecules were recognized by specific IgEs upon immunoblotting. Then, two new 2S albumins, a monomeric and a heterodimeric one, were isolated by using classical biochemical methods. They were identified via direct protein sequencing and mass spectrometry, and their primary structure was analyzed and compared with homologous allergenic proteins via bioinformatics. In an Italian population of 703 suspected allergic patients, analyzed by using the FABER® test, the frequency of sensitization to the monomeric and heterodimeric 2S albumins was 1.7% and 0.28%, respectively. This study reports for the first time the isolation and characterization of two 2S albumins from pomegranate seeds. The clinical relevance of these molecules needs further investigation, for instance in populations having different exposures and allergy profiles.

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

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

Mass Spectrometry Imaging Techniques: Non-Ambient and Ambient Ionization Approaches

Molecular information can be acquired from sample surfaces in real time using a revolutionary molecular imaging technique called mass spectrometry imaging (MSI). The technique can concurrently provide high spatial resolution information on the spatial distribution and relative proportion of many different compounds. Thus, many scientists have been drawn to the innovative capabilities of the MSI approach, leading to significant focus in various fields during the past few decades. This review describes the sampling protocol, working principle and applications of a few non-ambient and ambient ionization mass spectrometry imaging techniques. The non-ambient techniques include secondary ionization mass spectrometry and matrix-assisted laser desorption ionization, while the ambient techniques include desorption electrospray ionization, laser ablation electrospray ionization, probe electro-spray ionization, desorption atmospheric pressure photo-ionization and femtosecond laser desorption ionization. The review additionally addresses the advantages and disadvantages of ambient and non-ambient MSI techniques in relation to their suitability, particularly for biological samples used in tissue diagnostics. Last but not least, suggestions and conclusions are made regarding the challenges and future prospects of MSI.

Development of an efficient, effective, and economical technology for proteome analysis

We present an efficient, effective, and economical approach, named E3technology, for proteomics sample preparation. By immobilizing silica microparticles into the polytetrafluoroethylene matrix, we develop a robust membrane medium, which could serve as a reliable platform to generate proteomics-friendly samples in a rapid and low-cost fashion. We benchmark its performance using different formats and demonstrate them with a variety of sample types of varied complexity, quantity, and volume. Our data suggest that E3technology provides proteome-wide identification and quantitation performance equivalent or superior to many existing methods. We further propose an enhanced single-vessel approach, named E4technology, which performs on-filter in-cell digestion with minimal sample loss and high sensitivity, enabling low-input and low-cell proteomics. Lastly, we utilized the above technologies to investigate RNA-binding proteins and profile the intact bacterial cell proteome.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

A thiol-anchored solvatochromic and fluorogenic molecular rotor for covalent protein labeling in SDS-PAGE and mitochondria specific fluorescence imaging

Fluorescent labeling is a widely used method for protein detection and fluorescence imaging. A solvatochromic and fluorogenic molecular rotor DASPBCl was developed for covalent protein labeling in solution and SDS-PAGE, and also for stable mitochondria labeling and fluorescence imaging. The dye DASPBCl consisted of a 4-(N,N-dimethylamino)phenyl moiety as the electron donor and a positively charged N-benzylpyridinium moiety as the electron acceptor. A benzyl chloride group was introduced into the pyridine moiety for covalent labeling of thiol in proteins. When the fluorescent dye DASPBCl is covalently labeled to the thiol of proteins, significantly enhanced fluorescence was obtained, which is attributed to the polarity sensitivity caused solvatochromic effect from the hydrophobic protein structure and the viscosity sensitivity caused fluorogenic effect from the restriction of single bond rotation. DASPBCl exhibits high sensitivity and good linear response for protein detection in SDS-PAGE analysis with both the pre-staining method and post-staining method. DASPBCl was also successfully used for covalently protein-anchored fluorescence imaging of mitochondria in living cells.

Exploring coaggregation mechanisms involved in biofilm formation in drinking water through a proteomic-based approach

AIM

Coaggregation, a highly specific cell-cell interaction mechanism, plays a pivotal role in multispecies biofilm formation. While it has been mostly studied in oral environments, its occurrence in aquatic systems is also acknowledged. Considering biofilm formation's economic and health-related implications in engineered water systems, it is crucial to understand its mechanisms. Here, we hypothesized that traceable differences at the proteome level might determine coaggregation ability.

METHODS AND RESULTS

Two strains of Delftia acidovorans, isolated from drinking water were studied. First, in vitro motility assays indicated more swarming and twitching motility for the coaggregating strain (C+) than non-coaggregating strain (C-). By transmission electronic microscopy, we confirmed the presence of flagella for both strains. By proteomics, we detected a significantly higher expression of type IV pilus twitching motility proteins in C+, in line with the motility assays. Moreover, flagellum ring proteins were more abundant in C+, while those involved in the formation of the flagellar hook (FlE and FilG) were only detected in C-. All the results combined suggested structural and conformational differences between stains in their cell appendages.

CONCLUSION

This study presents an alternative approach for identifying protein biomarkers to detect coaggregation abilities in uncharacterized strains.

Negative-Ion Electron Capture Dissociation of MALDI-Generated Peptide Anions

Negative-ion electron capture dissociation (niECD) is an anion MS/MS technique that provides fragmentation analogous to conventional ECD, including high peptide sequence coverage and retention of labile post-translational modifications (PTMs). niECD has been proposed to be the most efficient for salt-bridged zwitterionic precursor ion structures. Several important PTMs, e.g., sulfation and phosphorylation, are acidic and can, therefore, be challenging to characterize in the positive-ion mode. Furthermore, PTM-friendly techniques, such as ECD, require multiple precursor ion-positive charges. By contrast, singly charged ions, refractory to ECD, are most compatible with niECD. Because electrospray ionization (ESI) typically yields multiply charged ions, we sought to explore matrix-assisted laser desorption/ionization (MALDI) in combination with niECD. However, the requirement for zwitterionic gaseous structures may preclude efficient niECD of MALDI-generated anions. Unexpectedly, we found that niECD of anions from MALDI is not only possible but proceeds with similar or higher efficiency compared with ESI-generated anions. Matrix selection did not appear to have a major effect. With MALDI, niECD is demonstrated up to m/z ∼4300. For such larger analytes, multiple electron captures are observed, resulting in triply charged fragments from singly charged precursor ions. Such charge-increased fragments show improved detectability. Furthermore, significantly improved (∼20-fold signal-to-noise increase) niECD spectral quality is achieved with equivalent sample amounts from MALDI vs ESI. Overall, the reported combination with MALDI significantly boosts the analytical utility of niECD.

Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins of organelles, cellular signaling, bioenergetic metabolism and molecular chaperoning

During the natural aging process, frailty is often associated with abnormal muscular performance. Although inter-individual differences exit, in most elderly the tissue mass and physiological functionality of voluntary muscles drastically decreases. In order to study age-related contractile decline, animal model research is of central importance in the field of biogerontology. Here we have analyzed wild type mouse muscle to establish a proteomic map of crude tissue extracts. Proteomics is an advanced and large-scale biochemical method that attempts to identify all accessible proteins in a given biological sample. It is a technology-driven approach that uses mass spectrometry for the characterization of individual protein species. Total protein extracts were used in this study in order to minimize the potential introduction of artefacts due to excess subcellular fractionation procedures. In this report, the proteomic survey of aged muscles has focused on organellar marker proteins, as well as proteins that are involved in cellular signaling, the regulation of ion homeostasis, bioenergetic metabolism and molecular chaperoning. Hence, this study has establish a proteomic reference map of a highly suitable model system for future aging research.

Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins located in the sarcomere, cytoskeleton and the extracellular matrix

Sarcopenia of old age is characterized by the progressive loss of skeletal muscle mass and concomitant decrease in contractile strength. Age-related skeletal muscle dysfunctions play a key pathophysiological role in the frailty syndrome and can result in a drastically diminished quality of life in the elderly. Here we have used mass spectrometric analysis of the mouse hindlimb musculature to establish the muscle protein constellation at advanced age of a widely used sarcopenic animal model. Proteomic results were further analyzed by systems bioinformatics of voluntary muscles. In this report, the proteomic survey of aged muscles has focused on the expression patterns of proteins involved in the contraction-relaxation cycle, membrane cytoskeletal maintenance and the formation of the extracellular matrix. This includes proteomic markers of the fast versus slow phenotypes of myosin-containing thick filaments and actin-containing thin filaments, as well as proteins that are associated with the non-sarcomeric cytoskeleton and various matrisomal layers. The bioanalytical usefulness of the newly established reference map was demonstrated by the comparative screening of normal versus dystrophic muscles of old age, and findings were verified by immunoblot analysis.

Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis

INTRODUCTION

The pharmaceutical industry continues to expand its search for innovative biotherapeutics. The comprehensive characterization of such therapeutics requires many analytical techniques to fully evaluate critical quality attributes, making analysis a bottleneck in discovery and development timelines. While thorough characterization is crucial for ensuring the safety and efficacy of biotherapeutics, there is a need to further streamline analytical characterization and expedite the overall timeline from discovery to market.

AREAS COVERED

This review focuses on recent developments in liquid-phase separations coupled with ion mobility-mass spectrometry (IM-MS) for the development and characterization of biotherapeutics. We cover uses of IM-MS to improve the characterization of monoclonal antibodies, antibody-drug conjugates, host cell proteins, glycans, and nucleic acids. This discussion is based on an extensive literature search using Web of Science, Google Scholar, and SciFinder.

EXPERT OPINION

IM-MS has the potential to enhance the depth and efficiency of biotherapeutic characterization by providing additional insights into conformational changes, post-translational modifications, and impurity profiles. The rapid timescale of IM-MS positions it well to enhance the information content of existing assays through its facile integration with standard liquid-phase separation techniques that are commonly used for biopharmaceutical analysis.

Mass spectrometry-based proteomic applications in dental implants research

Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.

Long-lived proteins and DNA as candidate predictive biomarkers for tissue associated diseases

Protein turnover is an important mechanism to maintain proteostasis. Long-lived proteins (LLPs) are vulnerable to lose their function due to time-accumulated damages. In this study we employed in vivo stable isotope labeling in mice from birth to postnatal day 89. Quantitative proteomics analysis of ten tissues and plasma identified 2113 LLPs, including widespread and tissue-specific ones. Interestingly, a significant percentage of LLPs was detected in plasma, implying a potential link to age-related cardiovascular diseases. LLPs identified in brains were related to neurodegenerative diseases. In addition, the relative quantification of DNA-derived deoxynucleosides from the same tissues provided information about cellular DNA renewal and showed good correlation with LLPs in the brain. The combined data reveal tissue-specific maps of mouse LLPs that may be involved in pathology due to a low renewal rate and an increased risk of damage. Tissue-derived peripheral LLPs hold promise as biomarkers for aging and age-related diseases.

Optimal conditions for carrying out trypsin digestions on complex proteomes: From bulk samples to single cells

To identify proteins by the bottom-up mass spectrometry workflow, enzymatic digestion is essential to break down proteins into smaller peptides amenable to both chromatographic separation and mass spectrometric analysis. Trypsin is the most extensively used protease due to its high cleavage specificity and generation of peptides with desirable positively charged N- and C-terminal amino acid residues that are amenable to reverse phase HPLC separation and MS/MS analyses. However, trypsin can yield variable digestion profiles and its protein cleavage activity is interdependent on trypsin source and quality, digestion time and temperature, pH, denaturant, trypsin and substrate concentrations, composition/complexity of the sample matrix, and other factors. There is therefore a need for a more standardized, general-purpose trypsin digestion protocol. Based on a review of the literature we delineate optimal conditions for carrying out trypsin digestions of complex proteomes from bulk samples to limiting amounts of protein extracts. Furthermore, we highlight recent developments and technological advances used in digestion protocols to quantify complex proteomes from single cells. SIGNIFICANCE: Currently, bottom-up MS-based proteomics is the method of choice for global proteome analysis. Since trypsin is the most utilized protease in bottom-up MS proteomics, delineating optimal conditions for carrying out trypsin digestions of complex proteomes in samples ranging from tissues to single cells should positively impact a broad range of biomedical research.

Recent advancements in disulfide bridge characterization: Insights from mass spectrometry

RATIONALE

Disulfide bridges (DSB) play an important role in stabilizing three-dimensional structures of biopharmaceuticals, single purified proteins, and various cyclic peptide drugs that contain disulfide in their structures. Incorrect cross-linking known as DSB scrambling results in misfolded structures that can be inactive, immunogenic, and susceptible to aggregation. Very few articles have been published on the experimental annotation of DSBs in proteins and cyclic peptide drugs. Accurate characterization of the disulfide bond is essential for understanding protein confirmation.

METHODS

Characterizing DSBs using mass spectrometry (MS) involves the chemical and enzymatic digestion of samples to obtain smaller peptide fragments, in both reduced and nonreduced forms. Subsequently, these samples are analyzed using MS to locate the DSB, either through interpretation or by employing various software tools.

RESULTS

The main challenge in DSB analysis methods using sample preparation is to obtain a sample solution in which nonnative DSBs are not formed due to high pH, temperature, and presence of free sulfhydryl groups. Formation of nonnative DSBs can lead to erroneous annotation of disulfide bond. Sample preparation techniques, fragmentation methods for DSB analysis, and contemporary approaches for DSB mapping using this fragmentation were discussed.

CONCLUSIONS

This review presents the latest advancement in MS-based characterization; also a critical perspective is presented for further annotation of DSBs using MS, primarily for single purified proteins or peptides that are densely connected and rich in cysteine. Despite significant breakthroughs resulting from advancements in MS, the analysis of disulfide bonds is not straightforward; it necessitates expertise in sample preparation and interpretation.

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the last decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

Chemical and linguistic considerations for encoding Chinese characters: an embodiment using chain-end degradable sequence-defined oligourethanes created by consecutive solid phase click chemistry

Sequence-defined polymers (SDPs) are currently being investigated for use as information storage media. As the number of monomers in the SDPs increases, with a corresponding increase in mathematical base, the use of tandem-MS for de novo sequencing becomes more challenging. In contrast, chain-end degradation routines are truly de novo, potentially allowing very large mathematical bases for encoding. While alphabetic scripts have a few dozen symbols, logographic scripts, such as Chinese, can have several thousand symbols. Using a new in situ consecutive click reaction approach on an oligourethane backbone for writing, and a previously reported chain-end degradation routine for reading, we encoded/decoded a confucius proverb written in Chinese characters using two encoding schemes: Unicode and Zhèng Mă. Unicode is an internationally standardized arbitrary string of hexadecimal (base-16) symbols which efficiently encodes uniquely identifiable symbols but requires complete fidelity of transmission, or context-based inferential strategies to be interpreted. The Zhèng Mă approach encodes with a base-26 system using the visual characteristics and internal composition of Chinese characters themselves, which leads to greater ambiguity of encoded strings, but more robust retrievability of information from partial or corrupted encodings. The application of information-encoded oligourethanes to two different encoding systems allowed us to establish their flexibility and versatility for data storage. We found the oligourethanes immensely adaptable to both encoding schemes for Chinese characters, and we highlight the expected tradeoff between the efficiency and uniqueness of Unicode encoding on the one hand, and the fidelity to a scripts' particular visual characteristics on the other.

Extracellular vesicles from the mycoparasitic fungus Trichoderma harzianum

Trichoderma harzianum is a filamentous fungus that can act as a mycoparasite, saprophyte, or a plant symbiotic. It is widely used as a biological control agent against phytopathogenic fungi and can also be used for plant growth promotion and biofortification. Interaction between T. harzianum and phytopathogenic fungi involves mycoparasitism, competition, and antibiosis. Extracellular vesicles (EVs) have been described as presenting a central role in mechanisms of communication and interaction among fungus and their hosts. In this study, we characterized extracellular vesicles of T. harzianum produced during growth in the presence of glucose or S. sclerotiorum mycelia. A set of vesicular proteins was identified using proteomic approach, mainly presenting predicted signal peptides.

A Top-Down Proteomic Assay to Evaluate KRAS4B-Compound Engagement

Development of new targeted inhibitors for oncogenic KRAS mutants may benefit from insight into how a given mutation influences the accessibility of protein residues and how compounds interact with mutant or wild-type KRAS proteins. Targeted proteomic analysis, a key validation step in the KRAS inhibitor development process, typically involves both intact mass- and peptide-based methods to confirm compound localization or quantify binding. However, these methods may not always provide a clear picture of the compound binding affinity for KRAS, how specific the compound is to the target KRAS residue, and how experimental conditions may impact these factors. To address this, we have developed a novel top-down proteomic assay to evaluate in vitro KRAS4B-compound engagement while assessing relative quantitation in parallel. We present two applications to demonstrate the capabilities of our assay: maleimide-biotin labeling of a KRAS4BG12D cysteine mutant panel and treatment of three KRAS4B proteins (WT, G12C, and G13C) with small molecule compounds. Our results show the time- or concentration-dependence of KRAS4B-compound engagement in context of the intact protein molecule while directly mapping the compound binding site.

Mirror-image trypsin digestion and sequencing of D-proteins

The development of mirror-image biology systems and related applications is hindered by the lack of effective methods to sequence mirror-image (D-) proteins. Although natural-chirality (L-) proteins can be sequenced by bottom-up liquid chromatography-tandem mass spectrometry (LC-MS/MS), the sequencing of long D-peptides and D-proteins with the same strategy requires digestion by a site-specific D-protease before mass analysis. Here we apply solid-phase peptide synthesis and native chemical ligation to chemically synthesize a mirror-image version of trypsin, a widely used protease for site-specific protein digestion. Using mirror-image trypsin digestion and LC-MS/MS, we sequence a mirror-image large subunit ribosomal protein (L25) and a mirror-image Sulfolobus solfataricus P2 DNA polymerase IV (Dpo4), and distinguish between different mutants of D-Dpo4. We also perform writing and reading of digital information in a long D-peptide of 50 amino acids. Thus, mirror-image trypsin digestion in conjunction with LC-MS/MS may facilitate practical applications of D-peptides and D-proteins as potential therapeutic and informational tools.

[Deciphering cellular processes responding to lethality of 17β-estradiol by quantitative phosphoproteomics]

17β-Estradiol (E2), an important endocrine hormone in the mammalian body, participates in the regulation of the physiological functions of the reproductive system, mammary glands, bone, and cardiovascular system, among others. Paradoxically, despite the physiological actions of endogenous E2 (0.2-1.0 nmol/L), numerous clinical and experimental studies have demonstrated that high-dose E2 treatment can cause tumor regression and exert pro-apoptotic actions in multiple cell types; however, the underlying mechanism remains undescribed. In particular, little information of the cellular processes responding to the lethality of E2 is available. In the present study, we attempted to characterize the cellular processes responding to high-dose (μmol/L) E2 treatment using quantitative phosphoproteomics to obtain a better understanding of the regulatory mechanism of E2-induced cell death. First, the cell phenotype induced by high-dose E2 was determined by performing Cell Counting Kit-8 assay (CCK8), cell cytotoxicity analysis by trypan blue staining, and microscopic imaging on HeLa cells treated with 1-10 μmol/L E2 or dimethyl sulfoxide (DMSO) for 1-3 d. E2 inhibited cell proliferation and induced cell death in a dose- and time-dependent manner. Compared with the DMSO-treated HeLa cells, the cells treated with 5 μmol/L E2 for 2 d demonstrated >74% growth inhibition and approximately 50% cell death. Thus, these cells were used for quantitative phosphoproteomic analysis. Next, a solid-phase extraction (SPE)-based immobilized titanium ion affinity chromatography (Ti4+-IMAC) phosphopeptide-enrichment method coupled with data-independent acquisition (DIA)-based quantitative proteomics was employed for the in-depth screening of high-dose E2-regulated phosphorylation sites to investigate the intracellular processes responding to high-dose E2 treatment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified over 10000 phosphorylation sites regulated by E2 and DMSO in HeLa cells. In comparison with the DMSO-treated cells, the cells treated with 5 μmol/L E2 showed 537 upregulated phosphorylation sites and 387 downregulated phosphorylation sites, with a threshold of p<0.01 and |log2(fold change)|≥1. A total of 924 phosphorylation sites on 599 proteins were significantly regulated by high-dose E2, and these sites were subjected to enrichment analysis. In addition, 453 differently regulated phosphorylation sites on 325 proteins were identified only in the E2- or DMSO-treated cell samples. These phosphorylation sites may be phosphorylated or dephosphorylated in response to high-dose E2 stimulation and were subjected to parallel enrichment analyses. Taken together, 1218 phosphorylation sites on 741 proteins were significantly regulated by high-dose E2 treatment. The functional phosphoproteins in these two groups were then analyzed using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) to determine the biological processes in which they participate and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Consistent with the cell-phenotype data, cell cycle-related proteins were highly enriched in the two groups of E2-regulated phosphoproteins (p<0.05), indicating that high-dose E2 treatment can regulate cell proliferation. In addition, E2-regulated phosphoproteins were highly enriched in the cellular processes of ribosome biogenesis, nucleocytoplasmic transport, and messenger ribonucleic acid (mRNA) processing/splicing (p<0.05), indicating that the activation of these processes may contribute to high-dose E2-induced cell death. These results further confirm that high-dose E2 treatment inhibits protein translation and induces cell death. Furthermore, the significant upregulation of multiple phosphorylation sites associated with epidermal growth factor receptor (EGFR) and mitogen-activated protein kinases (MAPKs) MAPK1, MAPK4, and MAPK14 by high-dose E2 indicates that the EGFR and MAPK signaling pathways are likely involved in the regulation of E2-induced cell death. These phosphorylation sites likely play vital roles in E2-induced cell death in HeLa cells. Overall, our phosphoproteomic data could be a valuable resource for uncovering the regulatory mechanisms of E2 in the micromolar range.

Hempseed protein-derived short- and medium-chain peptides and their multifunctional properties

Nowadays, the growing knowledge about the high nutritional value and potential functionality of hempseeds, the edible fruits of the Cannabis sativa L. plant, has sparked a surge in interest in exploring the worthwhile attributes of hempseed proteins and peptides. This trend aligns with the increasing popularity of hemp-based food, assuming a vital role in the global food chain. This chapter targets the nutritional and chemical composition of hempseed in terms of short- and medium-chain bioactive peptides. The analytical approaches for their characterization and multifunctional properties are summarized in detail. Moreover, the processing, functionality, and application of various hempseed protein products are discussed. In the final part of the chapter-for evaluating their propensity to be transported by intestinal cells-the transepithelial transport of peptides within hempseed protein hydrolysate is highlighted.

One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.

Gut dysbiosis and neurological modalities: An engineering approach via proteomic analysis of gut-brain axis

The human gut microbiota is a complex and dynamic community of microorganisms, that influence metabolic, neurodevelopmental, and immune pathways. Microbial dysbiosis, characterized by changes in microbial diversity and relative abundances, is implicated in the development of various chronic neurological and neurodegenerative disorders. These disorders are marked by the accumulation of pathological protein aggregates, leading to the progressive loss of neurons and behavioural functions. Dysregulations in protein-protein interaction networks and signalling complexes, critical for normal brain function, are common in neurological disorders but challenging to unravel, particularly at the neuron and synapse-specific levels. To advance therapeutic strategies, a deeper understanding of neuropathogenesis, especially during the progressive disease phase, is needed. Biomarkers play a crucial role in identifying disease pathophysiology and monitoring disease progression. Proteomics, a powerful technology, shows promise in accelerating biomarker discovery and aiding in the development of novel treatments. In this chapter, we provide an in-depth overview of how proteomic techniques, utilizing various biofluid samples from patients with neurological conditions and diverse animal models, have contributed valuable insights into the pathogenesis of numerous neurological disorders. We also discuss the current state of research, potential challenges, and future directions in proteomic approaches to unravel neuro-pathological conditions.

SeFilter-DIA: Squeeze-and-Excitation Network for Filtering High-Confidence Peptides of Data-Independent Acquisition Proteomics

Mass spectrometry is crucial in proteomics analysis, particularly using Data Independent Acquisition (DIA) for reliable and reproducible mass spectrometry data acquisition, enabling broad mass-to-charge ratio coverage and high throughput. DIA-NN, a prominent deep learning software in DIA proteome analysis, generates peptide results but may include low-confidence peptides. Conventionally, biologists have to manually screen peptide fragment ion chromatogram peaks (XIC) for identifying high-confidence peptides, a time-consuming and subjective process prone to variability. In this study, we introduce SeFilter-DIA, a deep learning algorithm, aiming at automating the identification of high-confidence peptides. Leveraging compressed excitation neural network and residual network models, SeFilter-DIA extracts XIC features and effectively discerns between high and low-confidence peptides. Evaluation of the benchmark datasets demonstrates SeFilter-DIA achieving 99.6% AUC on the test set and 97% for other performance indicators. Furthermore, SeFilter-DIA is applicable for screening peptides with phosphorylation modifications. These results demonstrate the potential of SeFilter-DIA to replace manual screening, providing an efficient and objective approach for high-confidence peptide identification while mitigating associated limitations.

IgG glycopeptide enrichment using hydrophilic interaction chromatography-based solid-phase extraction on an aminopropyl column

The sample preparation step is pivotal in glycoproteomic analysis. An effective approach in glycoprotein sample preparation involves enriching glycopeptides by solid-phase extraction (SPE) using polar stationary phases in hydrophilic interaction liquid chromatography (HILIC) mode. The aim of this work is to show how different experimental conditions influence the enrichment efficiency of glycopeptides from human immunoglobulin G (IgG) on an aminopropyl-modified SPE column. Different compositions of the elution solvent (acetonitrile, methanol, and isopropanol), along with varying concentrations of elution solvent acidifiers (formic and acetic acid), and different concentrations of acetonitrile for the conditioning and washing solvents (65%, 75%, and 85% acetonitrile) were tested to observe their effects on the glycopeptide enrichment process. Isopropanol proved less effective in enriching glycopeptides, while acetonitrile was the most efficient, with methanol in between. Higher formic acid concentrations in the elution solvent weakened the ionic interactions, particularly with sialylated glycopeptides. Substituting formic acid with acetic acid led to earlier elution of more glycopeptides. The acetonitrile concentration in conditioning and washing solutions played a key role; at 65% acetonitrile, glycopeptides were not retained on the SPE column and were detected in the flow-through fraction. Ultimately, it was proven that the enrichment method was applicable to human plasma samples, resulting in a significant decrease in the abundances of non-glycosylated peptides. To the best of our knowledge, this study represents the first systematic investigation into the impact of the mobile phase on glycopeptide enrichment using an aminopropyl-modified SPE column in HILIC mode. This study demonstrates the substantial impact of even minor variations in experimental conditions, which have not yet been considered in the literature, on SPE-HILIC glycopeptide enrichment. Consequently, meticulous optimization of these conditions is imperative to enhance the specificity and selectivity of glycoproteomic analysis, ensuring accurate and reliable quantification.

Recent progress in marine chondroitin sulfate, dermatan sulfate, and chondroitin sulfate/dermatan sulfate hybrid chains as potential functional foods and therapeutic agents

Chondroitin sulfate (CS), dermatan sulfate (DS), and CS/DS hybrid chains are natural complex glycosaminoglycans with high structural diversity and widely distributed in marine organisms, such as fish, shrimp, starfish, and sea cucumber. Numerous CS, DS, and CS/DS hybrid chains with various structures and activities have been obtained from marine animals and have received extensive attention. However, only a few of these hybrid chains have been well-characterized and commercially developed. This review presents information on the extraction, purification, structural characterization, biological activities, potential action mechanisms, and structure-activity relationships of marine CS, DS, and CS/DS hybrid chains. We also discuss the challenges and perspectives in the research of CS, DS, and CS/DS hybrid chains. This review may provide a useful reference for the further investigation, development, and application of CS, DS, and CS/DS hybrid chains in the fields of functional foods and therapeutic agents.

AuNPs/CNC Nanocomposite with A "Dual Dispersion" Effect for LDI-TOF MS Analysis of Intact Proteins in NSCLC Serum Exosomes

Detecting exosomal markers using laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS) is a novel approach for examining liquid biopsies of non-small cell lung cancer (NSCLC) samples. However, LDI-TOF MS is limited by low sensitivity and poor reproducibility when analyzing intact proteins directly. In this report, gold nanoparticles/cellulose nanocrystals (AuNPs/CNC) is introduced as the matrix for direct analysis of intact proteins in NSCLC serum exosomes. AuNPs/CNC with "dual dispersion" effects dispersed and stabilized AuNPs and improved ion inhibition effects caused by protein aggregation. These features increased the signal-to-noise ratio of [M+H]+ peaks by two orders of magnitude and lowered the detection limit of intact proteins to 0.01 mg mL-1. The coefficient of variation with or without AuNPs/CNC is measured as 10.2% and 32.5%, respectively. The excellent reproducibility yielded a linear relationship (y = 15.41x - 7.983, R2 = 0.989) over the protein concentration range of 0.01 to 20 mg mL-1. Finally, AuNPs/CNC-assisted LDI-TOF MS provides clinically relevant fingerprint information of exosomal proteins in NSCLC serum, and characteristic proteins S100 calcium-binding protein A10, Urokinase plasminogen activator surface receptor, Plasma protease C1 inhibitor, Tyrosine-protein kinase Fgr and Mannose-binding lectin associated serine protease 2 represented excellent predictive biomarkers of NSCLC risk.

Environmental proteomics as a useful methodology for early-stage detection of stress in anammox engineered systems

Anammox bacteria are widely applied worldwide for denitrification of urban wastewater. Differently, their application in the case of industrial effluents has been more limited. Those frequently present high loads of contaminants, demanding an individual evaluation of their treatability by anammox technologies. Bioreactors setting up and recovery after contaminants-derived perturbations are slow. Also, toxicity is frequently not acute but cumulative, which causes negative macroscopic effects to appear only after medium or long-term operations. All these particularities lead to relevant economic and time losses. We hypothesized that contaminants cause changes at anammox proteome level before perturbations in the engineered systems are detectable by macroscopic analyses. In this study, we explored the usefulness of short-batch tests combined with environmental proteomics for the early detection of those changes. Copper was used as a model of stressor contaminant, and anammox granules were exposed to increasing copper concentrations including previously reported IC50 values. The proteomic results revealed that specific anammox proteins involved in stress response (bacterioferritin, universal stress protein, or superoxide dismutase) were overexpressed in as short a time as 28 h at the higher copper concentrations. Consequently, EPS production was also increased, as indicated by the alginate export family protein, polysaccharide biosynthesis protein, and sulfotransferase increased expression. The described workflow can be applied to detect early-stage stress biomarkers of the negative effect of other metals, organics, or even changes in physical-chemical parameters such as pH or temperature on anammox-engineered systems. On an industrial level, it can be of great value for decision-making, especially before dealing with new effluents on facilities, deriving important economic and time savings.

Characterization of the Oxazolone and Macrocyclic Motifs in the bn (n = 2-5) Product Ions from Collision-Induced Dissociation of Protonated Oligoglycine Peptides with Isomer-Selective, Cryogenic Vibrational Spectroscopy

Collision-induced dissociation (CID) of small, protonated peptides leads to the formation of b-type fragment ions that can occur with several structural motifs driven by different covalent intramolecular bonding arrangements. Here, we characterize the so-called "oxazolone" and "macrocycle" bn ion structures that occur upon CID of oligoglycine peptides (Gn) ions (n = 2-6). This is determined by acquiring the vibrational band patterns of the cryogenically cooled, D2-tagged bn ions obtained using isomer-selective, two-color IR-IR photobleaching and analyzing them with predicted (DFT) harmonic spectra for the candidate structures. Both oxazolone and macrocyclic isomers are formed by b4, whereas only oxazolone species are created for b2 and b3 and the macrocycle is created for b5. As such, n = 4 corresponds to the minimum size where both Oxa and MC forms are present.

Test-Time Training for Deep MS/MS Spectrum Prediction Improves Peptide Identification

In bottom-up proteomics, peptide-spectrum matching is critical for peptide and protein identification. Recently, deep learning models have been used to predict tandem mass spectra of peptides, enabling the calculation of similarity scores between the predicted and experimental spectra for peptide-spectrum matching. These models follow the supervised learning paradigm, which trains a general model using paired peptides and spectra from standard data sets and directly employs the model on experimental data. However, this approach can lead to inaccurate predictions due to differences between the training data and the experimental data, such as sample types, enzyme specificity, and instrument calibration. To tackle this problem, we developed a test-time training paradigm that adapts the pretrained model to generate experimental data-specific models, namely, PepT3. PepT3 yields a 10-40% increase in peptide identification depending on the variability in training and experimental data. Intriguingly, when applied to a patient-derived immunopeptidomic sample, PepT3 increases the identification of tumor-specific immunopeptide candidates by 60%. Two-thirds of the newly identified candidates are predicted to bind to the patient's human leukocyte antigen isoforms. To facilitate access of the model and all the results, we have archived all the intermediate files in Zenodo.org with identifier 8231084.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Alzheimer proteopathic tau seeds are biochemically a forme fruste of mature paired helical filaments

Aggregation prone molecules, such as tau, form both historically well characterized fibrillar deposits (neurofibrillary tangles) and recently identified phosphate-buffered saline (PBS) extract species called proteopathic seeds. Both can cause normal endogenous tau to undergo templated misfolding. The relationship of these seeds to the fibrils that define tau-related diseases is unknown. We characterized the aqueous extractable and sarkosyl insoluble fibrillar tau species derived from human Alzheimer brain using mass spectrometry and in vitro bioassays. Post-translational modifications (PTMs) including phosphorylation, acetylation and ubiquitination are identified in both preparations. PBS extract seed competent tau can be distinguished from sarkosyl insoluble tau by the presence of overlapping, but less abundant, PTMs and an absence of some PTMs unique to the latter. The presence of ubiquitin and other PTMs on the PBS-extracted tau species correlates with the amount of tau in the seed competent size exclusion fractions, with the bioactivity and with the aggressiveness of clinical disease. These results demonstrate that the PTMs present on bioactive, seed competent PBS extract tau species are closely related to, but distinct from, the PTMs of mature paired helical filaments, consistent with the idea that they are a forme fruste of tau species that ultimately form fibrils.

102-Plex Approach for Accurate and Multiplexed Proteome Quantification

Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.

Characterizing Age-related Changes in Intact Mitochondrial Proteoforms in Murine Hearts using Quantitative Top-Down Proteomics

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational protein modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying all protein sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

METHODS

Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

RESULTS

From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation.

CONCLUSION

By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Present and future perspectives on mass spectrometry for clinical microbiology

In the last decade, MALDI-TOF Mass Spectrometry (MALDI-TOF MS) has been introduced and broadly accepted by clinical laboratory laboratories throughout the world as a powerful and efficient tool for rapid microbial identification. During the MALDI-TOF MS process, microbes are identified using either intact cells or cell extracts. The process is rapid, sensitive, and economical in terms of both labor and costs involved. Whilst MALDI-TOF MS is currently the gold-standard, it suffers from several shortcomings such as lack of direct information on antibiotic resistance, poor depth of analysis and insufficient discriminatory power for the distinction of closely related bacterial species or for reliably sub-differentiating isolates to the level of clones or strains. Thus, new approaches targeting proteins and allowing a better characterization of bacterial strains are strongly needed, if possible, on a very short time scale after sample collection in the hospital. Bottom-up proteomics (BUP) is a nice alternative to MALDI-TOF MS, offering the possibility for in-depth proteome analysis. Top-down proteomics (TDP) provides the highest molecular precision in proteomics, allowing the characterization of proteins at the proteoform level. A number of studies have already demonstrated the potential of these techniques in clinical microbiology. In this review, we will discuss the current state-of-the-art of MALDI-TOF MS for the rapid microbial identification and detection of resistance to antibiotics and describe emerging approaches, including bottom-up and top-down proteomics as well as ambient MS technologies.

Deciphering the Exact Sequence of Endogenous Soluble B Cell Maturation Antigen and Unbiased Quantitation in Multiple Myeloma Patient Samples by LC-MS

BACKGROUND

B-cell maturation antigen is a pivotal therapeutic target for multiple myeloma (MM). Membrane-bound BCMA can be cleaved by γ-secretase and shed as soluble BCMA (sBCMA). sBCMA can act as a neutralizing sink to compete with drug, as well as serve as a diagnostic/prognostic biomarker for MM. Antibody-capture based methods, such as enzyme-linked immunosorbent assay (ELISA) and immunoaffinity-liquid chromatography-multiple reaction monitoring (IA-LC-MRM), have been reported and well adopted to measure sBCMA in clinical samples. However, both methods are biased by capturing antibodies.

METHODS

We have used various LC-MS workflows to characterize and quantify endogenous sBCMA in MM patient samples, including bottom-up peptide mapping, intact analysis, IA-based, and reagent-free (RF)-LC-MRM quantitation.

RESULTS

We have confirmed that sBCMA contains a variable N-terminus and a C-terminus that extends to the transmembrane domain, ending at amino acid 61. Leveraging an in-house synthesized G-1-61 sBCMA recombinant standard, we developed a RF-LC-MRM method for unbiased sBCMA quantitation in MM patient samples. By comparing the results from RF-LC-MRM with ELISA and IA-LC-MRM, we demonstrated that RF-LC-MRM measures a more complete pool of endogenous sBCMA compared to the antibody-based methods.

CONCLUSIONS

This work fills the knowledge gap of the exact sequence of endogenous sBCMA for the first time, which differs from the current commercially available standard. Additionally, this work highlights the necessity of identifying the actual sequence of an endogenous soluble target such as sBCMA, both for bioanalytical purposes and to underpin pharmacodynamic measurements.

Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing

Unlike for DNA and RNA, accurate and high-throughput sequencing methods for proteins are lacking, hindering the utility of proteomics in applications where the sequences are unknown including variant calling, neoepitope identification, and metaproteomics. We introduce Spectralis, a de novo peptide sequencing method for tandem mass spectrometry. Spectralis leverages several innovations including a convolutional neural network layer connecting peaks in spectra spaced by amino acid masses, proposing fragment ion series classification as a pivotal task for de novo peptide sequencing, and a peptide-spectrum confidence score. On spectra for which database search provided a ground truth, Spectralis surpassed 40% sensitivity at 90% precision, nearly doubling state-of-the-art sensitivity. Application to unidentified spectra confirmed its superiority and showcased its applicability to variant calling. Altogether, these algorithmic innovations and the substantial sensitivity increase in the high-precision range constitute an important step toward broadly applicable peptide sequencing.

Recent developments in capillary and microchip electroseparations of peptides (2021-mid-2023)

This review article brings a comprehensive survey of developments and applications of high-performance capillary and microchip electromigration methods (zone electrophoresis in a free solution or in sieving media, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) for analysis, micropreparation, and physicochemical characterization of peptides in the period from 2021 up to ca. the middle of 2023. Progress in the study of electromigration properties of peptides and various aspects of their analysis, such as sample preparation, adsorption suppression, electroosmotic flow regulation, and detection, are presented. New developments in the particular capillary electromigration methods are demonstrated, and several types of their applications are reported. They cover qualitative and quantitative analysis of synthetic or isolated peptides and determination of peptides in complex biomatrices, peptide profiling of biofluids and tissues, and monitoring of chemical and enzymatic reactions and physicochemical changes of peptides. They include also amino acid and sequence analysis of peptides, peptide mapping of proteins, separation of stereoisomers of peptides, and their chiral analyses. In addition, micropreparative separations and physicochemical characterization of peptides and their interactions with other (bio)molecules by the above CE methods are described.

GreenPhos, a universal method for in-depth measurement of plant phosphoproteomes with high quantitative reproducibility

Protein phosphorylation regulates a variety of important cellular and physiological processes in plants. In-depth profiling of plant phosphoproteomes has been more technically challenging than that of animal phosphoproteomes. This is largely due to the need to improve protein extraction efficiency from plant cells, which have a dense cell wall, and to minimize sample loss resulting from the stringent sample clean-up steps required for the removal of a large amount of biomolecules interfering with phosphopeptide purification and mass spectrometry analysis. To this end, we developed a method with a streamlined workflow for highly efficient purification of phosphopeptides from tissues of various green organisms including Arabidopsis, rice, tomato, and Chlamydomonas reinhardtii, enabling in-depth identification with high quantitative reproducibility of about 11 000 phosphosites, the greatest depth achieved so far with single liquid chromatography-mass spectrometry (LC-MS) runs operated in a data-dependent acquisition (DDA) mode. The mainstay features of the method are the minimal sample loss achieved through elimination of sample clean-up before protease digestion and of desalting before phosphopeptide enrichment and hence the dramatic increases of time- and cost-effectiveness. The method, named GreenPhos, combined with single-shot LC-MS, enabled in-depth quantitative identification of Arabidopsis phosphoproteins, including differentially phosphorylated spliceosomal proteins, at multiple time points during salt stress and a number of kinase substrate motifs. GreenPhos is expected to serve as a universal method for purification of plant phosphopeptides, which, if samples are further fractionated and analyzed by multiple LC-MS runs, could enable measurement of plant phosphoproteomes with an unprecedented depth using a given mass spectrometry technology.