A Critical Review of Bottom-Up Proteomics: The Good, the Bad, and the Future of this Field

Mapping proteomic response to salinity stress tolerance in oil crops: Towards enhanced plant resilience

Exposure to saline environments significantly hampers the growth and productivity of oil crops, harmfully affecting their nutritional quality and suitability for biofuel production. This presents a critical challenge, as understanding salt tolerance mechanisms in crops is key to improving their performance in coastal and high-salinity regions. Our content might be read more properly: This review assembles current knowledge on protein-level changes related to salinity resistance in oil crops. From an extensive analysis of proteomic research, featured here are key genes and cellular pathways which react to salt stress. The literature evinces that cutting-edge proteomic approaches - such as 2D-DIGE, IF-MS/MS, and iTRAQ - have been required to reveal protein expression patterns in oil crops under salt conditions. These studies consistently uncover dramatic shifts in protein abundance associated with important physiological activities including antioxidant defence, stress-related signalling pathways, ion homeostasis, and osmotic regulation. Notably, proteins like ion channels (SOS1, NHX), osmolytes (proline, glycine betaine), antioxidant enzymes (SOD, CAT), and stress-related proteins (HSPs, LEA) play central roles in maintaining cellular balance and reducing oxidative stress. These findings underline the complex regulatory networks that govern oil crop salt tolerance. The application of this proteomic information can inform breeding and genetic engineering strategies to enhance salt resistance. Future research should aim to integrate multiple omics data to gain a comprehensive view of salinity responses and identify potential markers for crop improvement.

Proteomic interrogation of complex biomedical samples using the rapid denaturing organic digestion (DOD) method

Limitations to many current aqueous-based tryptic digestion methods include lengthy digestion times and both relatively high inter- and intra-day variability for both characteristic peptides identified and sequence coverages. This report describes results from digestion of some complex biomedical samples using the rapid Denaturing Organic Digestion method (DOD), an organic solvent-modified digestion method previously optimized for targeted protein digestion. Advantages of the DOD method included a very rapid digestion only requiring inexpensive solvents and reagents generally available in the laboratory, with no requirement for specialized equipment or expensive, specialized consumables. For this study, samples of E. coli and murine ileum protein extracts, and K562, a mass spectrometry-compatible human protein extract and reference standard routinely used to evaluate methods, were digested. Sequence coverage and characteristic peptide identification results were compared to those from 18 and 24 h conventional aqueous-based digestion methods. Across the samples tested, though the number of characteristic peptides and sequence coverages produced by the 5 min DOD method were very similar to those produced by the aqueous-based digestion methods, the specific characteristic proteins and their corresponding tryptic peptides identified following DOD method digestion included more hydrophilic and less hydrophobic species. In addition, we explored the effect of increasing digestion times with complex samples from 5 to 30 and 90 min for the DOD method. Increasing the digestion time to ≥30 min resulted in improved intra-day precision and the identification of many more peptide products than the currently used aqueous methods to which it was compared. These results suggest that the DOD organic-modified digestion method could, while markedly reducing protein digestion time, also provide more precise analysis and access to a somewhat different area of the proteome than that provided by current aqueous-based digestion methods. SIGNIFICANCE: The DOD tryptic digest method is a very simple and rapid process with no requirement for expensive equipment or consumables. The method markedly reduces tryptic digestion time and cost, and substantially improves within-batch and across-analyst precision for peptide and sequence coverage results over methods to which it was compared. Importantly, it also provides access to a somewhat different subset of the proteome with different peptide products identified as compared to aqueous solvent-based digestion providing potential for increased proteome coverage for bottom-up analysis if used in conjunction with aqueous-based methods.

Mass spectrometry-based proteomics for source-level attribution after DNA extraction

Biological traces recovered from crime scenes serve as vital evidence in forensic investigations. While DNA evidence is frequently used to address the sub-source level of the hierarchy of propositions, the biological source of the DNA can be highly probative at the source level. Current body fluid detection methods pose certain limitations, such as reports of false positive results from some of the presumptive and/or confirmatory tests in current use. These tests are also individual tests for the detection of one body fluid, meaning that if the sample is suspected to be a mixture of multiple body fluids, then different tests would need to be conducted to confirm the body fluid(s) present, which may exhaust small amounts of available biological trace. Proteomics applications for the identification of body fluids have been previously explored, and potential biomarkers indicative of body fluids discovered from liquid-chromatography tandem mass spectrometry (LC-MS/MS) methods have been reported. This work focuses on developing a mass spectrometry-based proteomics approach for the identification of body fluids by targeting discriminating peptide biomarkers from the non-DNA component left over after DNA extraction of samples. The non-DNA component is typically a waste product but with unappreciated evidential value. Our methodology for the purification of proteins from the post-DNA extraction waste includes an acetone precipitation and single-pot solid-phase-enhanced sample preparation (SP3) technique, microwave-assisted trypsin digestion, and LC-MS/MS analysis of the resultant peptides. Preliminary results from this proof-of-concept study include a list of potentially discriminating proteins and peptides for blood, saliva, and semen developed from the analysis of post-DNA extraction waste. Our method allows for multiple analytes to be targeted simultaneously from a DNA profiling waste stream and we anticipate that it could eventually be incorporated into standard forensic laboratory workflows.

Exploring Top-Down Mass Spectrometric Approaches To Probe Forest Cobra (Naja melanoleuca) Venom Proteoforms

Snake venoms are comprised of bioactive proteins and peptides that facilitate severe snakebite envenomation symptoms. A comprehensive understanding of venom compositions and the subtle heterogeneity therein is important. While bottom-up proteomics has been the well-established approach to catalogue venom compositions, top-down proteomics has emerged as a complementary strategy to characterize venom heterogeneity at the intact protein level. However, top-down proteomics has not been as widely implemented in the snake venom field as bottom-up proteomics, with various emerging top-down methods yet to be developed for venom systems. Here, we have explored three main top-down mass spectrometry methodologies in a proof-of-concept study to characterize selected three-finger toxin and phospholipase A2 proteoforms from the forest cobra (Naja melanoleuca) venom. We demonstrated the utility of a data-independent acquisition mode "MSE" for untargeted fragmentation on a chromatographic time scale and its improvement in protein sequence coverage compared to conventional targeted tandem mass spectrometry analysis. We also showed that protein identification can be further improved using a hybrid fragmentation approach, combining electron-capture dissociation and collision-induced dissociation. Lastly, we reported the promising application of multifunctional cyclic ion mobility separation and post-ion mobility fragmentation on snake venom proteins for the first time.

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.

From Proteomics to the Analysis of Single Protein Molecules

Limit of detection (LoD) is a term that is used to characterize the sensitivity of an analytical method. The existing limitation of the sensitivity of analysis using modern mass spectrometry methods has been experimentally shown to be a limiting factor in the application of proteomic technologies in medicine. This article proposes a concept of a new technology that will set a new vector of development in the development of systems for solving problems of medical diagnostics and deals with theoretical and practical aspects of creating a new technology for the detection of single biomacromolecules (in particular, proteins) in biological samples. Such technology should be based on the principle of signal registration similar to that used in a Geiger counter (also known as a Geiger-Müller counter or G-M counter), a device that automatically counts the number of ionizing particles that hit it. This counter is free from probabilistic components; it registers a signal if there is at least one target molecule in the analysis chamber. Predictive medical diagnostics require technology based on methods where sensitivity allows for the detection of single marker molecules in a biological sample volume of 1-10 µL, the smallest volume of biomaterial used in laboratory diagnostics. Creation of a detector with a sensitivity of 10-18 M would allow for the detection of one molecule in 1 µL of the sample, which fundamentally makes this approach analogous to a G-M counter for solutions. To date, bioanalytical methods are limited to a sensitivity of 10-12 M (which is approximately 1 million molecules per 1 μL), which is insufficient to capture the early stages of pathological processes.

Proteomics Studies on Extracellular Vesicles Derived from Glioblastoma: Where Do We Stand?

Like most tumors, glioblastoma multiforme (GBM), the deadliest brain tumor in human adulthood, releases extracellular vesicles (EVs). Their content, reflecting that of the tumor of origin, can be donated to nearby and distant cells which, by acquiring it, become more aggressive. Therefore, the study of EV-transported molecules has become very important. Particular attention has been paid to EV proteins to uncover new GBM biomarkers and potential druggable targets. Proteomic studies have mainly been performed by "bottom-up" mass spectrometry (MS) analysis of EVs isolated by different procedures from conditioned media of cultured GBM cells and biological fluids from GBM patients. Although a great number of dysregulated proteins have been identified, the translation of these findings into clinics remains elusive, probably due to multiple factors, including the lack of standardized procedures for isolation/characterization of EVs and analysis of their proteome. Thus, it is time to change research strategies by adopting, in addition to harmonized EV selection techniques, different MS methods aimed at identifying selected tumoral protein mutations and/or isoforms due to post-translational modifications, which more deeply influence the tumor behavior. Hopefully, these data integrated with those from other "omics" disciplines will lead to the discovery of druggable pathways for novel GBM therapies.

Unveiling the intricacy of gapmer oligonucleotides through advanced tandem mass spectrometry approaches and scan accumulation for 2DMS

Antisense oligonucleotides (ASOs) are crucial for biological applications as they bind to complementary RNA sequences, modulating protein expression. ASOs undergo synthetic modifications like phosphorothioate (PS) backbone and locked nucleic acid (LNA) to enhance stability and specificity. Tandem mass spectrometry (MS) techniques were employed to study gapmer ASOs, which feature a DNA chain within RNA segments at both termini, revealing enhanced cleavages with ultraviolet photodissociation (UVPD) and complementary fragment ions from collision-induced dissociation (CID) and electron detachment dissociation (EDD). 2DMS, a data-independent analysis technique, allowed for comprehensive coverage and identification of shared fragments across multiple precursor ions. EDD fragmentation efficiency correlated with precursor ion charge states, with higher charges facilitating dissociation due to intramolecular repulsions. An electron energy of 22.8 eV enabled electron capture and radical-based cleavage. Accumulating multiple scans and generating average spectra improved signal intensity, aided by denoising algorithms. Data analysis utilised a custom Python script capable of handling modifications and generating unique mass lists.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Cleanup Techniques

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identifications. Single-pot, solid-phase-enhanced sample preparation (SP3) is a cleanup technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. Recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer cleanup technique that employs protein aggregation to capture proteins without modified particles. We hypothesize that differences in capture mechanisms of SP3 and SP4 affect which proteins are identified by each cleanup technique. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. Ultimately, we demonstrate that protein-capture mechanisms are distinct, and the selection of a cleanup technique that yields high proteome coverage is dependent on protein-sample hydrophobicity. Data has been deposited into MassIVE (MSV000094130) and ProteomeXchange (PXD049965).

A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Proteomic approaches for protein kinase substrate identification in Apicomplexa

Apicomplexa is a phylum of protist parasites, notable for causing life-threatening diseases including malaria, toxoplasmosis, cryptosporidiosis, and babesiosis. Apicomplexan pathogenesis is generally a function of lytic replication, dissemination, persistence, host cell modification, and immune subversion. Decades of research have revealed essential roles for apicomplexan protein kinases in establishing infections and promoting pathogenesis. Protein kinases modify their substrates by phosphorylating serine, threonine, tyrosine, or other residues, resulting in rapid functional changes in the target protein. Post-translational modification by phosphorylation can activate or inhibit a substrate, alter its localization, or promote interactions with other proteins or ligands. Deciphering direct kinase substrates is crucial to understand mechanisms of kinase signaling, yet can be challenging due to the transient nature of kinase phosphorylation and potential for downstream indirect phosphorylation events. However, with recent advances in proteomic approaches, our understanding of kinase function in Apicomplexa has improved dramatically. Here, we discuss methods that have been used to identify kinase substrates in apicomplexan parasites, classifying them into three main categories: i) kinase interactome, ii) indirect phosphoproteomics and iii) direct labeling. We briefly discuss each approach, including their advantages and limitations, and highlight representative examples from the Apicomplexa literature. Finally, we conclude each main category by introducing prospective approaches from other fields that would benefit kinase substrate identification in Apicomplexa.

Multi-pass, single-molecule nanopore reading of long protein strands

The ability to sequence single protein molecules in their native, full-length form would enable a more comprehensive understanding of proteomic diversity. Current technologies, however, are limited in achieving this goal1,2. Here, we establish a method for the long-range, single-molecule reading of intact protein strands on a commercial nanopore sensor array. By using the ClpX unfoldase to ratchet proteins through a CsgG nanopore3,4, we provide single-molecule evidence that ClpX translocates substrates in two-residue steps. This mechanism achieves sensitivity to single amino acids on synthetic protein strands hundreds of amino acids in length, enabling the sequencing of combinations of single-amino-acid substitutions and the mapping of post-translational modifications, such as phosphorylation. To enhance classification accuracy further, we demonstrate the ability to reread individual protein molecules multiple times, and we explore the potential for highly accurate protein barcode sequencing. Furthermore, we develop a biophysical model that can simulate raw nanopore signals a priori on the basis of residue volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine full-length, folded protein domains for complete end-to-end analysis. These results provide proof of concept for a platform that has the potential to identify and characterize full-length proteoforms at single-molecule resolution.

Toward Fully Automated Personalized Orthopedic Treatments: Innovations and Interdisciplinary Gaps

Personalized orthopedic devices are increasingly favored for their potential to enhance long-term treatment success. Despite significant advancements across various disciplines, the seamless integration and full automation of personalized orthopedic treatments remain elusive. This paper identifies key interdisciplinary gaps in integrating and automating advanced technologies for personalized orthopedic treatment. It begins by outlining the standard clinical practices in orthopedic treatments and the extent of personalization achievable. The paper then explores recent innovations in artificial intelligence, biomaterials, genomic and proteomic analyses, lab-on-a-chip, medical imaging, image-based biomechanical finite element modeling, biomimicry, 3D printing and bioprinting, and implantable sensors, emphasizing their contributions to personalized treatments. Tentative strategies or solutions are proposed to address the interdisciplinary gaps by utilizing innovative technologies. The key findings highlight the need for the non-invasive quantitative assessment of bone quality, patient-specific biocompatibility, and device designs that address individual biological and mechanical conditions. This comprehensive review underscores the transformative potential of these technologies and the importance of multidisciplinary collaboration to integrate and automate them into a cohesive, intelligent system for personalized orthopedic treatments.

Community Resource: Large-Scale Proteogenomics to Refine Wheat Genome Annotations

Triticum aestivum is an important crop whose reference genome (International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.1) offers a valuable resource for understanding wheat genetic structure, improving agronomic traits, and developing new cultivars. A key aspect of gene model annotation is protein-level evidence of gene expression obtained from proteomics studies, followed up by proteogenomics to physically map proteins to the genome. In this research, we have retrieved the largest recent wheat proteomics datasets publicly available and applied the Basic Local Alignment Search Tool (tBLASTn) algorithm to map the 861,759 identified unique peptides against IWGSC RefSeq v2.1. Of the 92,719 hits, 83,015 unique peptides aligned along 33,612 High Confidence (HC) genes, thus validating 31.4% of all wheat HC gene models. Furthermore, 6685 unique peptides were mapped against 3702 Low Confidence (LC) gene models, and we argue that these gene models should be considered for HC status. The remaining 2934 orphan peptides can be used for novel gene discovery, as exemplified here on chromosome 4D. We demonstrated that tBLASTn could not map peptides exhibiting mid-sequence frame shift. We supply all our proteogenomics results, Galaxy workflow and Python code, as well as Browser Extensible Data (BED) files as a resource for the wheat community via the Apollo Jbrowse, and GitHub repositories. Our workflow could be applied to other proteomics datasets to expand this resource with proteins and peptides from biotically and abiotically stressed samples. This would help tease out wheat gene expression under various environmental conditions, both spatially and temporally.

Cyanobacterial Proteomics: Diversity and Dynamics

Cyanobacteria (oxygenic photoautrophs) comprise a diverse group holding significance both environmentally and for biotechnological applications. The utilization of proteomic techniques has significantly influenced investigations concerning cyanobacteria. Application of proteomics allows for large-scale analysis of protein expression and function within cyanobacterial systems. The cyanobacterial proteome exhibits tremendous functional, spatial, and temporal diversity regulated by multiple factors that continuously modify protein abundance, post-translational modifications, interactions, localization, and activity to meet the dynamic needs of these tiny blue greens. Modern mass spectrometry-based proteomics techniques enable system-wide examination of proteome complexity through global identification and high-throughput quantification of proteins. These powerful approaches have revolutionized our understanding of proteome dynamics and promise to provide novel insights into integrated cellular behavior at an unprecedented scale. In this Review, we present modern methods and cutting-edge technologies employed for unraveling the spatiotemporal diversity and dynamics of cyanobacterial proteomics with a specific focus on the methods used to analyze post-translational modifications (PTMs) and examples of dynamic changes in the cyanobacterial proteome investigated by proteomic approaches.

Recent Contributions of Proteomics to Our Understanding of Reversible Nε-Lysine Acylation in Bacteria

Post-translational modifications (PTMs) have been extensively studied in both eukaryotes and prokaryotes. Lysine acetylation, originally thought to be a rare occurrence in bacteria, is now recognized as a prevalent and important PTM in more than 50 species. This expansion in interest in bacterial PTMs became possible with the advancement of mass spectrometry technology and improved reagents such as acyl-modification specific antibodies. In this Review, we discuss how mass spectrometry-based proteomic studies of lysine acetylation and other acyl modifications have contributed to our understanding of bacterial physiology, focusing on recently published studies from 2018 to 2023. We begin with a discussion of approaches used to study bacterial PTMs. Next, we discuss newly characterized acylomes, including acetylomes, succinylomes, and malonylomes, in different bacterial species. In addition, we examine proteomic contributions to our understanding of bacterial virulence and biofilm formation. Finally, we discuss the contributions of mass spectrometry to our understanding of the mechanisms of acetylation, both enzymatic and nonenzymatic. We end with a discussion of the current state of the field and possible future research avenues to explore.

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Development of automated proteomic workflows utilizing silicon-based coupling agents

Automated methods for enzyme immobilization via 4-triethoxysilylbutyraldehyde (TESB) derived silicone-based coupling agents were developed. TESB and its oxidized derivative, 4-triethoxysilylbutanoic acid (TESBA), were determined to be the most effective. The resulting immobilized enzyme particles (IEPs) displayed robustness, rapid digestion, and immobilization efficiency of 51 ± 8%. Furthermore, we automated the IEP procedure, allowing for multiple enzymes, and/or coupling agents to be fabricated at once, in a fraction of the time via an Agilent Bravo. The automated trypsin TESB and TESBA IEPs were shown to rival a classical in-gel digestion method. Moreover, pepsin IEPs favored cleavage at leucine (>50%) over aromatic and methionine residues. The IEP method was then adapted for an in-situ immobilized enzyme microreactor (IMER) fabrication. We determined that TESBA could functionalize the silica capillary's inner wall while simultaneously acting as an enzyme coupler. The IMER digestion of bovine serum albumin (BSA), mirroring IEP digestion conditions, yielded a 33-40% primary sequence coverage per LC-MS/MS analysis in as little as 15 min. Overall, our findings underscore the potential of both IEP and IMER methods, paving the way for automated analysis and a reduction in enzyme waste through reuse, thereby contributing to a more cost-effective and timely study of the proteome. SIGNIFICANCE: This research introduces 4-triethoxysilylbutyraldehyde (TESB) and its derivatives as silicon-based enzyme coupling agents and an automated liquid handling method for bottom-up proteomics (BUP) while streamlining sample preparation for high-throughput processing. Additionally, immobilized enzyme particle (IEP) fabrication and digestion within the 96-well plate allows for flexibility in protocol where different enzyme-coupler combinations can be employed simultaneously. By enabling the digestion of entire microplates and reducing manual labor, the proposed method enhances reproducibility and offers a more efficient alternative to classical in-gel techniques. Furthermore, pepsin IEPs were noted to favor cleavage at leucine residues which represents an interesting finding when compared to the literature that warrants further study. The capability of immobilized enzyme microreactors (IMER) for rapid digestion (in as little as 15 min) demonstrated the system's efficiency and potential for rapid proteomic analysis. This advancement in BUP not only improves efficiency, but also opens avenues for a fully automated, mass spectrometry-integrated proteomics workflow, promising to expedite research and discoveries in complex biological studies.

PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling

Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial for understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy human donors and sequenced BCRs at bulk and single-cell levels, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.

Advances in proteomics methods for the analysis of exhaled breath condensate

The analysis of exhaled breath condensate (EBC) demonstrates a promising avenue of minimally invasive biopsies for diagnostics. EBC is obtained by cooling exhaled air and collecting the condensation to be utilized for downstream analysis using various analytical methods. The aqueous phase of breath contains a large variety of miscible small compounds including polar electrolytes, amino acids, cytokines, chemokines, peptides, small proteins, metabolites, nucleic acids, and lipids/eicosanoids-however, these analytes are typically present at minuscule levels in EBC, posing a considerable technical challenge. Along with recent improvements in devices for breath collection, the sensitivity and resolution of liquid chromatography coupled to online mass spectrometry-based proteomics has attained subfemtomole sensitivity, vastly enhancing the quality of EBC sample analysis. As a result, proteomics analysis of EBC has been expanding the field of breath biomarker research. We present an au courant overview of the achievements in proteomics of EBC, the advancement of EBC collection devices, and the current and future applications for EBC biomarker analysis.

[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.

Analytical approaches for assessing protein structure in protein-rich food: A comprehensive review

This review focuses on changes in nutrition and functional properties of protein-rich foods, primarily attributed to alterations in protein structures. We provide a comprehensive overview and comparison of commonly used laboratory methods for protein structure identification, aiming to offer readers a convenient understanding of these techniques. The review covers a range of detection technologies employed in food protein analysis and conducts an extensive comparison to identify the most suitable method for various proteins. While these techniques offer distinct advantages for protein structure determination, the inherent complexity of food matrices presents ongoing challenges. Further research is necessary to develop and enhance more robust detection methods to improve accuracy in protein conformation and structure analysis.

A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research

Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.

What proteomics has taught us about honey bee (Apis mellifera) health and disease

The Western honey bee, Apis mellifera, is currently navigating a gauntlet of environmental pressures, including the persistent threat of parasites, pathogens, and climate change - all of which compromise the vitality of honey bee colonies. The repercussions of their declining health extend beyond the immediate concerns of apiarists, potentially imposing economic burdens on society through diminished agricultural productivity. Hence, there is an imperative to devise innovative monitoring techniques for assessing the health of honey bee populations. Proteomics, recognized for its proficiency in biomarker identification and protein-protein interactions, is poised to play a pivotal role in this regard. It offers a promising avenue for monitoring and enhancing the resilience of honey bee colonies, thereby contributing to the stability of global food supplies. This review delves into the recent proteomic studies of A. mellifera, highlighting specific proteins of interest and envisioning the potential of proteomics to improve sustainable beekeeping practices amidst the challenges of a changing planet.

Exploring metalloproteins found in the secretion of venomous species: Biological role and therapeutical applications

Several species during evolution suffered random mutations in response to various environmental factors, which resulted in the formation of venom in phylogenetically distant species. The composition of the venom of most species is poorly known. Snake venom is well characterized while most species have poorly known composition. In contrast, snake venoms are well characterized which proteins and peptides are the main active and most abundant constituents. 42 protein families have been identified, including metalloproteins known as metalloproteinases. These macromolecules are enzymes with zinc in their active site derived from the disintegrin A and metalloproteinase (ADAM) cellular family and are categorized into three classes (PI, PII and PIII) according to their domain organization. The snake venom metalloproteinases (SVMP) are cytotoxic, neurotoxic, myotoxic and/or hematotoxic with a crucial role in the defense and restraint of prey. In this scenario envenoming represents a danger to human health and has been considered a neglected disease worldwide, particularly in tropical and subtropical countries. Nevertheless, recently advances in "omics" technologies have demonstrated interesting biological activities of SVMPs such as antimicrobial, anticancer, against cardiovascular diseases and nervous system disorders. Metalloproteins have the therapeutic potential to be converted into drugs as other components of the venom have undergone this process (e.g., captopril, tirefiban and eptifibatide). So, this chapter is focused on the metalloproteins found in the secretions of venomous species, highlight some aspects such as structure, biological activity, pharmacological therapeutic potential and on.

Multi Omics Applications in Biological Systems

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Integrating Physiological Features and Proteomic Analyses Provides New Insights in Blue/Red Light-Treated Moso Bamboo (Phyllostachys edulis)

Bamboo is one of the most important nontimber forestry products in the world. Light is not only the most critical source of energy for plant photosynthesis but also involved in regulating the biological processes of plants. However, there are few reports on how blue/red light affects Moso bamboo. This study investigated the growth status and physiological responses of Moso bamboo (Phyllostachys edulis) to blue/red light treatments. The growth status of the bamboo plants was evaluated, revealing that both blue- and red-light treatments promoted plant height and overall growth. Gas exchange parameters, chlorophyll fluorescence, and enzyme activity were measured to assess the photosystem response of Moso bamboo to light treatments. Additionally, the blue light treatment led to a higher chlorophyll content and enzyme activities compared to the red light treatment. A tandem mass tag quantitative proteomics approach identified significant changes in protein abundance under different light conditions with specific response proteins associated with distinct pathways, such as photosynthesis and starch metabolism. Overall, this study provides valuable insights into the physiological and proteomic responses of Moso bamboo to blue/red light treatments, highlighting their potential impact on growth and development.

Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP

Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.

Comprehensive Two-Dimensional Liquid Chromatography-High-Resolution Mass Spectrometry for Complex Protein Digest Analysis Using Parallel Gradients

Despite the high gain in peak capacity, online comprehensive two-dimensional liquid chromatography coupled with high-resolution mass spectrometry (LC × LC-HRMS) has not yet been widely applied to the analysis of complex protein digests. One reason is the method's reduced sensitivity which can be linked to the high flow rates of the second separation dimension (2D). This results in higher dilution factors and the need for flow splitters to couple to ESI-MS. This study reports proof-of-principle results of the development of an RPLC × RPLC-HRMS method using parallel gradients (2D flow rate of 0.7 mL min-1) and its comparison to shifted gradient methods (2D of 1.4 mL min-1) for the analysis of complex digests using HRMS (QExactive-Plus MS). Shifted and parallel gradients resulted in high surface coverage (SC) and effective peak capacity (SC of 0.6226 and 0.7439 and effective peak capacity of 779 and 757 in 60 min). When applied to a cell line digest sample, parallel gradients allowed higher sensitivity (e.g., average MS intensity increased by a factor of 3), allowing for a higher number of identifications (e.g., about 2600 vs 3900 peptides). In addition, reducing the modulation time to 10 s significantly increased the number of MS/MS events that could be performed. When compared to a 1D-RPLC method, parallel RPLC × RPLC-HRMS methods offered a higher separation performance (FHWH from 0.12 to 0.018 min) with limited sensitivity losses resulting in an increase of analyte identifications (e.g., about 6000 vs 7000 peptides and 1500 vs 1990 proteins).

Single-cell proteomics by mass spectrometry: Advances and implications in cancer research

Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively searching for information regarding the proteomics counterpart. Therefore recently, single-cell proteomics by mass spectrometry (SCP) has rapidly developed into state-of-the-art technology to cater the need. This review aims to summarize application of SCP in cancer research, while revealing current development progress of SCP technology. The review also aims to contribute ideas into research gaps and future directions, ultimately promoting the application of SCP in cancer research.

Increasing protein identifications in bottom-up proteomics of T. castaneum - Exploiting synergies of protein biochemistry and bioinformatics

Depending on the respective research question, LC-MS/MS based bottom-up proteomics poses challenges from the initial biological sample all the way to data evaluation. The focus of this study was to investigate the influence of sample preparation techniques and data analysis parameters on protein identification in Tribolium castaneum by applying free software proteomics platform Max Quant. Multidimensional protein extraction strategies in combination with electrophoretic or chromatographic off-line protein pre-fractionation were applied to enhance the spectrum of isolated proteins from T. castaneum and reduce the effect of co-elution and ion suppression effects during nano-LC-MS/MS measurements of peptides. For comprehensive data analysis, MaxQuant was used for protein identification and R for data evaluation. A wide range of parameters were evaluated to gain reproducible, reliable, and significant protein identifications. A simple phosphate buffer, pH 8, containing protease and phosphatase inhibitor cocktail and application of gentle extraction conditions were used as a first extraction step for T.castaneum proteins. Furthermore, a two-dimensional extraction procedure in combination with electrophoretic pre-fractionation of extracted proteins and subsequent in-gel digest resulted in almost 100% increase of identified proteins when compared to chromatographic fractionation as well as one-pot-analysis. The additionally identified proteins could be assigned to new molecular functions or cell compartments, emphasizing the positive effect of extended sample preparation in bottom-up proteomics. Besides the number of peptides during post-processing, MaxQuant's Match between Runs exhibited a crucial effect on the number of identified proteins. A maximum relative standard deviation of 2% must be considered for the data analysis. Our work with Tribolium castaneum larvae demonstrates that sometimes - depending on matrix and research question - more complex and time-consuming sample preparation can be advantageous for isolation and identification of additional proteins in bottom-up proteomics.

Evaluation of the effect of dimethyl fumarate on human bone marrow-derived mesenchymal stem cells using bottom-up proteomics

Mesenchymal stem cells (MSCs) have potential as a viable treatment option in the field of regenerative medicine, but MSC-based therapy needs to be more efficient. Preconditioning is a method to improve MSC-based therapy, and dimethyl fumarate (DMF) - an agent that can enhance the antioxidative capacity of cells - can be considered for preconditioning of MSCs. In this study, we treated bone marrow-derived MSCs with DMF and evaluated their proteome using bottom-up proteomics. The MSCs were exposed to 10 μM DMF for 24 h, followed by lysis with an SDS solution, digestion with trypsin using an s-trap column, and analysis using nanoLC-MS/MS, which identified 2262 proteins with confidence. Bioinformatic analysis of the identified proteins revealed 47 upregulated proteins and 81 downregulated proteins upon DMF treatment. Pathway enrichment analysis suggested a possible decrease in autophagy and a decrease in the activity of the TCA cycle, while indicating a potential increase in proliferation and antioxidant activity in DMF-treated MSCs compared to untreated MSCs. Our findings suggest that DMF can enhance the proliferation of MSCs and increase their stability, and that preconditioning could improve the therapeutic efficacy of MSCs for the treatment of regenerative diseases.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

A systematic evaluation of sample preparation and 2-D gel electrophoresis protocol for mosquito proteomic profiling

-Mosquito act as the carrier insect to transfer pathogens into hosts for various vector-borne diseases.To identify the pathogenesis causing determinant, comprehensive knowledge of the protein expression in different tissues and physiological conditions is very important. The most widely used technique is 2-D gel electrophoresis to study the protein expression in mosquitoes. 2-D gel electrophoresis is the multistep process to resolve intact protein with similar molecular weight. It is also useful to separate post-translational modified protein, which are not distinguished through shotgun proteomic analysis. Here, we optimized the protocol for 2-D gel electrophoresis that can effectively resolve the protein in mosquitoes and some other insects, to target immunogenic protein to fight against the vector borne disease. The optimized 2-D protocol helps to resolve complex proteomic data which is very difficult to analyze in mosquitoes.The updated protocol improved the protein solubility, resolution and visualization that help in comparative analysis of protein expression.

Study of metalation of thioredoxin by gold(I) therapeutic compounds using combined liquid chromatography/capillary electrophoresis with inductively coupled plasma/electrospray MS/MS detection

The reactivity of thioredoxin (Trx1) with the Au(I) drug auranofin (AF) and two therapeutic N-heterocyclic carbene (NHC)2-Au(I) complexes (bis [1-methyl-3-acridineimidazolin-2-ylidene]gold(I) tetrafluoroborate (Au3BC) and [1,3-diethyl-4,5-bis(4methoxyphenyl)imidazol-2-ylidene]gold(I) (Au4BC)) was investigated. Direct infusion (DI) electrospray ionization (ESI) mass spectrometry (MS) allowed information on the structure, stoichiometry, and kinetics of formation of Trx-Au adducts. The fragmentation of the formed adducts in the gas phase gave insights into the exact Au binding site within the protein, demonstrating the preference for Trx1 Cys32 or Cys35 of AF or the (NHC)2-Au(I) complex Au3BC, respectively. Reversed-phase HPLC suffered from the difficulty of elution of gold compounds, did not preserve the formed metal-protein adducts, and favored the loss of ligands (phosphine or NHC) from Au(I). These limitations were eliminated by capillary electrophoresis (CE) which enabled the separation of the gold compounds, Trx1, and the formed adducts. The ICP-MS/MS detection allowed the simultaneous quantitative monitoring of the gold and sulfur isotopes and the determination of the metallation extent of the protein. The hyphenation of the mentioned techniques was used for the analysis of Trx1-Au adducts for the first time.

Comprehensive characterization of protein modifications using mass spectrometry and dry blood spots

PURPOSE

The main objective of this study is to characterize and analyze modified peptides in DBS samples. This includes deciphering their specific PTMs and understanding their potential impact on the population or disease cohort under study.

EXPERIMENTAL DESIGN

Using mass spectrometry-based proteomic approaches, we performed a comprehensive analysis of DBS samples. Our focus was on the identification and quantification of modified peptides. We also took advantage of recent advances in DBS mass spectrometry to ensure accurate detection and quantification.

RESULTS

A comprehensive analysis identified 972 modified peptides in DBS samples. Of these, a subset of 211 peptides was consistently present in all samples, highlighting their potential biological importance and relevance. This indicates a diverse spectrum of PTMs in the proteome of DBS samples.

CONCLUSIONS AND CLINICAL RELEVANCE

Integration of mass spectrometry and proteomics has revealed a broad spectrum of modified peptides in DBS samples and highlighted their importance in biological processes and disease progression. Accurate detection of these PTMs may be critical for risk stratification and disease management. This study improves the understanding of molecular mechanisms underlying biological processes and disease development, providing important insights for clinical applications.

Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience

With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.

Key Proteomics Tools for Fundamental and Applied Microalgal Research

Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Clean-up Techniques

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identification. Single-pot, solid-phase-enhanced sample preparation (SP3) is a clean-up technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. However, recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Thus, solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer clean-up technique that employs protein-aggregation to capture proteins without modified particles. SP4 has previously enriched low-solubility proteins, though differences in protein capture could affect which proteins are detected and identified. We hypothesize that the mechanisms of capture for SP3 and SP4 are distinct. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. From these results, we recommend clean-up techniques based on protein-sample hydrophobicity to yield high proteome coverage in biological samples.

How do biomarkers dance? Specific moves of defense and damage biomarkers for biological interpretation of dose-response model trends

Omics studies are currently increasingly used in ecotoxicology to highlight the induction of known or novel biomarkers when organisms are exposed to contaminants. Although it is virtually impossible to identify all biomarkers from all organisms, biomarkers can be grouped as defense or damage biomarkers, exhibiting a limited number of response trends. Our working hypothesis is that defense and damage biomarkers follow different dose-response patterns. A meta-analysis of 156 articles and 2595 observations of dose-response curves of defense and damage biomarkers was carried out in order to characterize the response trends of these biological parameters in a large panel of living organisms (18 phyla) exposed to inorganic or organic contaminants (176 in total). Using multinomial logistic regression models, defense biomarkers were found to describe biphasic responses (bell- and U-shaped) to a greater extent (2.5 times) than damage biomarkers. In contrast, damage biomarkers varied mainly monotonically (decreasing or increasing), representing 85% of the observations. Neither the nature of the contaminant nor the type of organisms belonging to 4 kingdoms, influence these specific responses. This result suggests that cellular defense and damage mechanisms are not specific to stressors and are conserved throughout life. Trend analysis of dose-response models as a biological interpretation of biomarkers could thus be a valuable way to exploit large omics datasets.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Reporting and reproducibility: Proteomics of fish models in environmental toxicology and ecotoxicology

Environmental toxicology and ecotoxicology research efforts are employing proteomics with fish models as New Approach Methodologies, along with in silico, in vitro and other omics techniques to elucidate hazards of toxicants and toxins. We performed a critical review of toxicology studies with fish models using proteomics and reported fundamental parameters across experimental design, sample preparation, mass spectrometry, and bioinformatics of fish, which represent alternative vertebrate models in environmental toxicology, and routinely studied animals in ecotoxicology. We observed inconsistencies in reporting and methodologies among experimental designs, sample preparations, data acquisitions and bioinformatics, which can affect reproducibility of experimental results. We identified a distinct need to develop reporting guidelines for proteomics use in environmental toxicology and ecotoxicology, increased QA/QC throughout studies, and method optimization with an emphasis on reducing inconsistencies among studies. Several recommendations are offered as logical steps to advance development and application of this emerging research area to understand chemical hazards to public health and the environment.

Urine Albumin Measurements in Clinical Diagnostics

BACKGROUND

Measurement of urine albumin is critical for diagnosis, risk classification, and monitoring of chronic kidney disease (CKD). Guidelines recommend clinical decision cutoffs for the urine albumin-to-creatinine ratio (ACR) of 30 and 300 mg/g (3 and 30 mg/mmol). However, differences among manufacturers' routine urine albumin measurement procedures have been found to exceed 40%, suggesting CKD diagnosis and risk classification may vary depending upon the specific measurement procedure implemented in the laboratory.

CONTENT

This review discusses urine albumin pathophysiology and clinical practice guideline recommendations for CKD. The review also provides recommendations for urine specimen collection and storage, and results reporting for the ACR. Recent advances in measurement techniques and development of reference systems intended to facilitate standardization of urine albumin measurements are reviewed.

SUMMARY

Urine albumin is an important measurement procedure used for diagnosis, risk classification, and management of CKD. Urine albumin results should be reported as the ACR using quantitative measurement procedures. Random urine collections used for albuminuria screening should be followed by confirmation with first morning void collections to reduce variation and increase diagnostic accuracy for urine albumin measurement. Most measurement procedures utilize immunoturbidimetric or immunonephelometric techniques. However, results vary significantly among measurement procedures, potentially resulting in differences in classification or risk assessment for CKD. The National Institute for Standards and Technology (NIST) and other laboratories are developing reference systems, including liquid chromatography-tandem mass spectrometry candidate reference measurement procedures and reference materials, to enable standardization of routine measurement procedures.

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.

Protein biomarkers for root length and root dry mass on chromosomes 4A and 7A in wheat

Improving the wheat (Triticum aestivum L.) root system is important for enhancing grain yield and climate resilience. Total root length (RL) and root dry mass (RM) significantly contribute to water and nutrient acquisition directly impacting grain yield and stress tolerance. This study used label-free quantitative proteomics to identify proteins associated with RL and RM in wheat near-isogenic lines (NILs). NIL pair 6 had 113 and NIL pair 9 had 30 differentially abundant proteins (DAPs). Three of identified DAPs located within the targeted genomic regions (GRs) of NIL pairs 6 (qDT.4A.1) and 9 (QHtscc.ksu-7A), showed consistent gene expressions at the protein and mRNA transcription (qRT-PCR) levels for asparagine synthetase (TraesCS4A02G109900), signal recognition particle 19 kDa protein (TraesCS7A02G333600) and 3,4-dihydroxy-2-butanone 4-phosphate synthase (TraesCS7A02G415600). This study discovered, for the first time, the involvement of these proteins as candidate biomarkers for increased RL and RM in wheat. However, further functional validation is required to ascertain their practical applicability in wheat root breeding. SIGNIFICANCE OF THE STUDY: Climate change has impacted global demand for wheat (Triticum aestivum L.). Root traits such as total root length (RL) and root dry mass (RM) are crucial for water and nutrient uptake and tolerance to abiotic stresses such as drought, salinity, and nutrient imbalance in wheat. Improving RL and RM could significantly enhance wheat grain yield and climate resilience. However, breeding for these traits has been limited by lack of appropriate root phenotyping methods, advanced genotypes, and the complex nature of the wheat genome. In this study, we used a semi-hydroponic root phenotyping system to collect accurate root data, near-isogenic lines (NILs; isolines with similar genetic backgrounds but contrasting target genomic regions (GRs)) and label-free quantitative proteomics to explore the molecular mechanisms underlying high RL and RM in wheat. We identified differentially abundant proteins (DAPs) and their molecular pathways in NIL pairs 6 (GR: qDT.4A.1) and 9 (GR: QHtscc.ksu-7A), providing a foundation for further molecular investigations. Furthermore, we identified three DAPs within the target GRs of the NIL pairs with differential expression at the transcript level, as confirmed by qRT-PCR analysis which could serve as candidate protein biomarkers for RL and RM improvement.