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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Recent Advances in Metalloproteomics

Interactions between proteins and metal ions and their complexes are important in many areas of the life sciences, including physiology, medicine, and toxicology. Despite the involvement of essential elements in all major processes necessary for sustaining life, metalloproteomes remain ill-defined. This is not only owing to the complexity of metalloproteomes, but also to the non-covalent character of the complexes that most essential metals form, which complicates analysis. Similar issues may also be encountered for some toxic metals. The review discusses recently developed approaches and current challenges for the study of interactions involving entire (sub-)proteomes with such labile metal ions. In the second part, transition metals from the fourth and fifth periods are examined, most of which are xenobiotic and also tend to form more stable and/or inert complexes. A large research area in this respect concerns metallodrug-protein interactions. Particular attention is paid to separation approaches, as these need to be adapted to the reactivity of the metal under consideration.

Global Remodeling of Host Proteome in Response to Leishmania Infection

The protozoan parasite Leishmania possesses an intrinsic ability to modulate a multitude of pathways in the host, toward aiding its own proliferation. In response, the host reprograms its cellular, immunological, and metabolic machinery to evade the parasite's lethal impact. Besides inducing various antioxidant signaling pathways to counter the elevated stress response proteins like heme oxygenase-1 (HO-1), Leishmania also attempts to delay host cell apoptosis by promoting anti-apoptotic proteins like Bcl-2. The downstream modulation of apoptotic proteins is regulated by effector pathways, including the PI3K/Akt survival pathway, the mitogen-activated protein kinases (MAPKs) signaling pathway, and STAT phosphorylation. In addition, Leishmania assists in its infection in a time-dependent manner by modulating the level of various proteins of autophagic machinery. Immune effector cells, such as mast cells and neutrophils, entrap and kill the pathogen by secreting various granular proteins. In contrast, the host macrophages exert their leishmanicidal effect by secreting various cytokines, such as IL-2, IL-12, etc. An interplay of various signaling pathways occurs in an organized network that is highly specific to both pathogen and host species. This Review analyzes the modulation of expression of proteins, including the cytokines, providing a realistic approach toward understanding the pathophysiology of disease and predicting some prominent markers for disease intervention and vaccine support strategies.

A computational pipeline elucidating functions of conserved hypothetical Trypanosoma cruzi proteins based on public proteomic data

The proteome is complex, dynamic, and functionally diverse. Functional proteomics aims to characterize the functions of proteins in biological systems. However, there is a delay in annotating the function of proteins, even in model organisms. This gap is even greater in other organisms, including Trypanosoma cruzi, the causative agent of the parasitic, systemic, and sometimes fatal disease called Chagas disease. About 99.8% of Trypanosoma cruzi proteome is not manually annotated (unreviewed), among which>25% are conserved hypothetical proteins (CHPs), calling attention to the knowledge gap on the protein content of this organism. CHPs are conserved proteins among different species of various evolutionary lineages; however, they lack functional validation. This study describes a bioinformatics pipeline applied to public proteomic data to infer possible biological functions of conserved hypothetical Trypanosoma cruzi proteins. Here, the adopted strategy consisted of collecting differentially expressed proteins between the epimastigote and metacyclic trypomastigotes stages of Trypanosoma cruzi; followed by the functional characterization of these CHPs applying a manifold learning technique for dimension reduction and 3D structure homology analysis (Spalog). We found a panel of 25 and 26 upregulated proteins in the epimastigote and metacyclic trypomastigote stages, respectively; among these, 18 CHPs (8 in the epimastigote stage and 10 in the metacyclic stage) were characterized. The data generated corroborate the literature and complement the functional analyses of differentially regulated proteins at each stage, as they attribute potential functions to CHPs, which are frequently identified in Trypanosoma cruzi proteomics studies. However, it is important to point out that experimental validation is required to deepen our understanding of the CHPs.

Optimizing MS-Based Multi-Omics: Comparative Analysis of Protein, Metabolite, and Lipid Extraction Techniques

Multi-omics integrates diverse types of biological information from genomic, proteomic, and metabolomics experiments to achieve a comprehensive understanding of complex cellular mechanisms. However, this approach is also challenging due to technical issues such as limited sample quantities, the complexity of data pre-processing, and reproducibility concerns. Furthermore, existing studies have primarily focused on technical performance assessment and the presentation of modified protocols through quantitative comparisons of the identified protein counts. Nevertheless, the specific differences in these comparisons have been minimally investigated. Here, findings obtained from various omics approaches were profiled using various extraction methods (methanol extraction, the Folch method, and Matyash methods for metabolites and lipids) and two digestion methods (filter-aided sample preparation (FASP) and suspension traps (S-Trap)) for resuspended proteins. FASP was found to be more effective for the identification of membrane-related proteins, whereas S-Trap excelled in isolating nuclear-related and RNA-processing proteins. Thus, FASP may be suitable for investigating the immune response and bacterial infection pathways, whereas S-Trap may be more effective for studies focused on the mechanisms of neurodegenerative diseases. Moreover, regarding the choice of extraction method, the single-phase method identified organic compounds and compounds related to fatty acids, whereas the two-phase extraction method identified more hydrophilic compounds such as nucleotides. Lipids with strong hydrophobicity, such as ChE and TG, were identified in the two-phase extraction results. These findings highlight that significant differences among small molecules are primarily identified due to the varying polarities of extraction solvents. These results, obtained by considering variables such as human error and batch effects in the sample preparation step, offer comprehensive and detailed results not previously provided by existing studies, thereby aiding in the selection of the most suitable pre-processing approach.

Review of phage display: A jack-of-all-trades and master of most biomolecule display

Phage display was first described by George P. Smith when it was shown that virus particles were capable of presenting foreign proteins on their surface. The technology has paved the way for the evolution of various biomolecules presentation and diverse selection strategies. This unique feature has been applied as a versatile platform for numerous applications in drug discovery, protein engineering, diagnostics, and vaccine development. Over the decades, the limits of biomolecules displayed on phage particles have expanded from peptides to proteomes and even alternative scaffolds. This has allowed phage display to be viewed as a versatile display platform to accommodate various biomolecules ranging from small peptides to larger proteomes which has significantly impacted advancements in the biomedical industry. This review will explore the vast array of biomolecules that have been successfully employed in phage display technology in biomedical research.

Measurement and utilization of the proteomic reactivity by mass spectrometry

Chemical proteomics, which involves studying the covalent modifications of proteins by small molecules, has significantly contributed to our understanding of protein function and has become an essential tool in drug discovery. Mass spectrometry (MS) is the primary method for identifying and quantifying protein-small molecule adducts. In this review, we discuss various methods for measuring proteomic reactivity using MS and covalent proteomics probes that engage through reactivity-driven and proximity-driven mechanisms. We highlight the applications of these methods and probes in live-cell measurements, drug target identification and validation, and characterizing protein-small molecule interactions. We conclude the review with current developments and future opportunities in the field, providing our perspectives on analytical considerations for MS-based analysis of the proteomic reactivity landscape.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Integrated small RNA, mRNA and protein omics reveal a miRNA network orchestrating metabolic maturation of the developing human heart

BACKGROUND

As the fetal heart develops, cardiomyocyte proliferation potential decreases while fatty acid oxidative capacity increases in a highly regulated transition known as cardiac maturation. Small noncoding RNAs, such as microRNAs (miRNAs), contribute to the establishment and control of tissue-specific transcriptional programs. However, small RNA expression dynamics and genome-wide miRNA regulatory networks controlling maturation of the human fetal heart remain poorly understood.

RESULTS

Transcriptome profiling of small RNAs revealed the temporal expression patterns of miRNA, piRNA, circRNA, snoRNA, snRNA and tRNA in the developing human heart between 8 and 19 weeks of gestation. Our analysis demonstrated that miRNAs were the most dynamically expressed small RNA species throughout mid-gestation. Cross-referencing differentially expressed miRNAs and mRNAs predicted 6200 mRNA targets, 2134 of which were upregulated and 4066 downregulated as gestation progressed. Moreover, we found that downregulated targets of upregulated miRNAs, including hsa-let-7b, miR-1-3p, miR-133a-3p, miR-143-3p, miR-499a-5p, and miR-30a-5p predominantly control cell cycle progression. In contrast, upregulated targets of downregulated miRNAs, including hsa-miR-1276, miR-183-5p, miR-1229-3p, miR-615-3p, miR-421, miR-200b-3p and miR-18a-3p, are linked to energy sensing and oxidative metabolism. Furthermore, integrating miRNA and mRNA profiles with proteomes and reporter metabolites revealed that proteins encoded in mRNA targets and their associated metabolites mediate fatty acid oxidation and are enriched as the heart develops.

CONCLUSIONS

This study presents the first comprehensive analysis of the small RNAome of the maturing human fetal heart. Our findings suggest that coordinated activation and repression of miRNA expression throughout mid-gestation is essential to establish a dynamic miRNA-mRNA-protein network that decreases cardiomyocyte proliferation potential while increasing the oxidative capacity of the maturing human fetal heart. Our results provide novel insights into the molecular control of metabolic maturation of the human fetal heart.

Routine Workflow of Spatial Proteomics on Micro-formalin-Fixed Paraffin-Embedded Tissues

In the era of single-cell biology, spatial proteomics has emerged as an important frontier. However, it still faces several challenges in technology. Formalin-fixed paraffin-embedded (FFPE) tissues are an important material in spatial proteomics, in which fixed tissues are excised using laser capture microdissection (LCM), followed by protein identification with mass spectrometry. For a satisfied spatial proteomics upon FFPE tissues, the excision area is expected to be as small as possible, and the identified proteins are countered upon as much as possible. For a general laboratory for spatial proteomics, a routine workflow is required, not relying on any special device, and is easily operating. In view of these challenges in technology, we initiated a technology evaluation throughout the entire procedure of proteomic analysis with micro-FFPE tissues. In contrast to the protocols reported previously, several innovations in technology were proposed and conducted, such as removal of destaining, decross-linking with "hang-down", solution simplification for peptide generation and balancing to excision area, and capture rate of micro-FFPE tissues. After optimization of all the necessary steps, a routine workflow was established, in which the minimized area for protein identification was 0.002 mm2, while the excision area for a consistent proteomic analysis was 0.05 mm2. Using the developed workflow and collecting the micro-FFPE tissues continuously, for the first time, a spatial proteomic atlas of mouse brain was preliminarily constructed, which exhibited the typical characteristics of spatial-dependent protein abundance and functional enrichment.

A Multi-Omics Approach Revealed Common Dysregulated Pathways in Type One and Type Two Endometrial Cancers

Endometrial cancer (EC) is the most frequent gynecologic cancer in postmenopausal women. Pathogenetic mechanisms that are related to the onset and progression of the disease are largely still unknown. A multi-omics strategy can help identify altered pathways that could be targeted for improving therapeutical approaches. In this study we used a multi-omics approach on four EC cell lines for the identification of common dysregulated pathways in type 1 and 2 ECs. We analyzed proteomics and metabolomics of AN3CA, HEC1A, KLE and ISHIKAWA cell lines by mass spectrometry. The bioinformatic analysis identified 22 common pathways that are in common with both types of EC. In addition, we identified five proteins and 13 metabolites common to both types of EC. Western blotting analysis on 10 patients with type 1 and type 2 EC and 10 endometria samples confirmed the altered abundance of NPEPPS. Our multi-omics analysis identified dysregulated proteins and metabolites involved in EC tumor growth. Further studies are needed to understand the role of these molecules in EC. Our data can shed light on common pathways to better understand the mechanisms involved in the development and growth of EC, especially for the development of new therapies.

Carotenoids in Health as Studied by Omics-Related Endpoints

Carotenoids have been associated with risk reduction for several chronic diseases, including the association of their dietary intake/circulating levels with reduced incidence of obesity, type 2 diabetes, certain types of cancer, and even lower total mortality. In addition to some carotenoids constituting vitamin A precursors, they are implicated in potential antioxidant effects and pathways related to inflammation and oxidative stress, including transcription factors such as nuclear factor κB and nuclear factor erythroid 2-related factor 2. Carotenoids and metabolites may also interact with nuclear receptors, mainly retinoic acid receptor/retinoid X receptor and peroxisome proliferator-activated receptors, which play a role in the immune system and cellular differentiation. Therefore, a large number of downstream targets are likely influenced by carotenoids, including but not limited to genes and proteins implicated in oxidative stress and inflammation, antioxidation, and cellular differentiation processes. Furthermore, recent studies also propose an association between carotenoid intake and gut microbiota. While all these endpoints could be individually assessed, a more complete/integrative way to determine a multitude of health-related aspects of carotenoids includes (multi)omics-related techniques, especially transcriptomics, proteomics, lipidomics, and metabolomics, as well as metagenomics, measured in a variety of biospecimens including plasma, urine, stool, white blood cells, or other tissue cellular extracts. In this review, we highlight the use of omics technologies to assess health-related effects of carotenoids in mammalian organisms and models.

From volcanoes to the bench: Advantages of novel hyperthermoacidic archaeal proteases for proteomics workflows

Here we introduce hyperthermoacidic archaeal proteases (HTA-Proteases©) isolated from organisms that thrive in nearly boiling acidic volcanic springs and investigate their use for bottom-up proteomic experiments. We find that HTA-Proteases have novel cleavage specificities, show no autolysis, function in dilute formic acid, and store at ambient temperature for years. HTA-Proteases function optimally at 70-90 °C and pH of 2-4 with rapid digestion kinetics. The extreme HTA-Protease reaction conditions actively denature sample proteins, obviate the use of chaotropes, are largely independent of reduction and alkylation, and allow for a one-step/five-minute sample preparation protocol without sample manipulation, dilution, or additional cleanup. We find that brief one-step HTA-Protease protocols significantly increase proteome and protein sequence coverage with datasets orthogonal to trypsin. Importantly, HTA-Protease digests markedly increase coverage and identifications for ribonucleoproteins, histones, and mitochondrial membrane proteins as compared to tryptic digests alone. In addition to increased coverage in these classes, HTA-Proteases and simplified one-step protocols are expected to reduce technical variability and advance the fields of clinical and high-throughput proteomics. This work reveals significant utility of heretofore unavailable HTA-Proteases for proteomic workflows. We discuss some of the potential for these remarkable enzymes to empower new proteomics methods, approaches, and biological insights. SIGNIFICANCE: Here we introduce new capabilities for bottom-up proteomics applications with hyperthermoacidic archaeal proteases (HTA-Proteases©). HTA-Proteases have novel cleavage specificity, require no chaotropes, and allow simple one-step/five-minute sample preparations that promise to reduce variability between samples and laboratories. HTA-Proteases generate unique sets of observable peptides that are non-overlapping with tryptic peptides and significantly increase sequence coverage and available peptide targets relative to trypsin alone. HTA-Proteases show some bias for the detection and coverage of nucleic acid-binding proteins and membrane proteins relative to trypsin. These new ultra-stable enzymes function optimally in nearly boiling acidic conditions, show no autolysis, and do not require aliquoting as they are stable for years at ambient temperatures. Used independently or in conjunction with tryptic digests, HTA-Proteases offer increased proteome coverage, unique peptide targets, and brief one-step protocols amenable to automation, rapid turnaround, and high-throughput approaches.

A Bioconductor workflow for processing, evaluating, and interpreting expression proteomics data

Background: Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods: Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilizes open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results: The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions: A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

Multi-pass, single-molecule nanopore reading of long protein strands with single-amino acid sensitivity

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 goal. Here, we establish a method for 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 nanopore, we achieve single-amino acid level sensitivity, enabling sequencing of combinations of amino acid substitutions across long protein strands. For greater sequencing accuracy, we demonstrate the ability to reread individual protein molecules, spanning hundreds of amino acids in length, multiple times, and explore the potential for high accuracy protein barcode sequencing. Further, we develop a biophysical model that can simulate raw nanopore signals a priori, based on amino acid volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine intact, 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.

Urine-HILIC: Automated Sample Preparation for Bottom-Up Urinary Proteome Profiling in Clinical Proteomics

Urine provides a diverse source of information related to a patient's health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

Microbiologically influenced corrosion-more than just microorganisms

Microbiologically influenced corrosion (MIC) is a phenomenon of increasing concern that affects various materials and sectors of society. MIC describes the effects, often negative, that a material can experience due to the presence of microorganisms. Unfortunately, although several research groups and industrial actors worldwide have already addressed MIC, discussions are fragmented, while information sharing and willingness to reach out to other disciplines are limited. A truly interdisciplinary approach, which would be logical for this material/biology/chemistry-related challenge, is rarely taken. In this review, we highlight critical non-biological aspects of MIC that can sometimes be overlooked by microbiologists working on MIC but are highly relevant for an overall understanding of this phenomenon. Here, we identify gaps, methods, and approaches to help solve MIC-related challenges, with an emphasis on the MIC of metals. We also discuss the application of existing tools and approaches for managing MIC and propose ideas to promote an improved understanding of MIC. Furthermore, we highlight areas where the insights and expertise of microbiologists are needed to help progress this field.

Omics approaches for the assessment of biological responses to nanoparticles

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. While conventional methods have limitations in characterizing responses to NPs, omics approaches can analyze complete sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and analytical methods used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

Exploiting ion-mobility mass spectrometry for unraveling proteome complexity

Ion mobility spectrometry-mass spectrometry (IMS-MS) is experiencing rapid growth in proteomic studies, driven by its enhancements in dynamic range and throughput, increasing the quantitation precision, and the depth of proteome coverage. The core principle of ion mobility spectrometry is to separate ions in an inert gas under the influence of an electric field based on differences in drift time. This minireview provides an introduction to IMS operation modes and a description of advantages and limitations is presented. Moreover, the principles of trapped IMS-MS (TIMS-MS), including parallel accumulation-serial fragmentation are discussed. Finally, emerging applications linked to TIMS focusing on sample throughput (in clinical proteomics) and sensitivity (single-cell proteomics) are reviewed, and the possibilities of intact protein analysis are discussed.

Rosuvastatin effects on the HDL proteome in hyperlipidemic patients

The advancements in proteomics have provided a better understanding of the functionality of apolipoproteins and lipoprotein-associated proteins, with the HDL lipoprotein fraction being the most studied. The focus of this study was to evaluate the HDL proteome in dyslipidemic subjects without an established cardiovascular disease, as well as to test whether rosuvastatin treatment alters the HDL proteome. Patients with primary hypercholesterolemia or mixed dyslipidemia were assigned to 20 mg/day rosuvastatin and blood samples were drawn at study entry and after 12 weeks of treatment. A label-free LC-MS/MS protein profiling was conducted, coupled with bioinformatics analysis. Sixty-nine HDL proteins were identified, belonging to four main biological function clusters: lipid transport and metabolism; platelet activation, degranulation, and aggregation, wound response and wound healing; immune response; inflammatory and acute phase response. Five HDL proteins showed statistically significant differences in the abundance (Anova ≤ 0.05), before and after rosuvastatin treatment. Platelet factor 4 variant (PF4V1), Pregnancy-specific beta-1-glycoprotein 2 (PSG2), Profilin-1 (PFN1) and Keratin type II cytoskeletal 2 epidermal (KRT2) showed decreased expressions, while Integrin alpha-IIb (ITGA2B) showed an increased expression after treatment with rosuvastatin. The ELISA validation of PFN1 segregated the subjects into responders and non-responders, as PFN1 levels after rosuvastatin were shown to mostly depend on the subjects' inflammatory phenotype. Findings from this study introduce novel insights into the HDL proteome and statin pleiotropism.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

Using Proteins As Markers for Anabolic Steroid Abuse: A New Perspective in Doping Control?

Drug toxicity is a major concern and has motivated numerous studies to elucidate specific adverse mechanisms, with acetaminophen being the favorite candidate in toxicology studies. Conversely, androgenic anabolic steroids (AASs) also represent a severe public health issue in sports for elite and non-elite athletes. Supraphysiological dosages of AASs are associated with various adverse effects, from cardiovascular to neurological repercussions including liver dysfunction. Yet, few studies have addressed the toxicity of anabolic steroids, and a significant amount of work will be needed to elucidate and understand steroid toxicity properly. This Perspective suggests ideas on how proteomics and liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) can contribute to (1) pinpoint serum proteins affected by substantial doses of anabolic steroids that would represent interesting novel candidates for routine testing and (2) provide additional knowledge on androgenic anabolic steroid toxicity to help raise awareness on the harmful effects.

Mixed-mode column allows simple direct coupling with immobilized enzymatic reactor for on-line protein digestion

Liquid chromatography coupled with mass spectrometry is widely used in the field of proteomic analysis after off-line protein digestion. On-line digestion with chromatographic column connected in a series with immobilized enzymatic reactor is not often used approach. In this work we investigated the impact of chromatographic conditions on the protein digestion efficiency. The investigation of trypsin reactor activity was performed by on-line digestion of N-α-benzoyl-L-arginine 4-nitroanilide hydrochloride (BAPNA), followed by separation of the digests on the mixed-mode column. Two trypsin column reactors with the different trypsin coverage on the bridged ethylene hybrid particles were evaluated. To ensure optimal trypsin activity, the separation temperature was set at 37.0 °C and the pH of the mobile phase buffer was maintained at 8.5. The on-line digestion itself ongoing during the initial state of gradient was carried out at a low flow rate using a mobile phase that was free of organic modifiers. Proteins such as cytochrome C, enolase, and myoglobin were successfully digested on-line without prior reduction or alkylation, and the resulting peptides were separated using a mixed-mode column. Additionally, proteins that contain multiple cysteines, such as α-lactalbumin, albumin, β-lactoglobulin A, and conalbumin, were also successfully digested on-line (after reduction and alkylation). Moreover, trypsin immobilized enzymatic reactors were utilized for over 300 injections without any noticeable loss of digestion activity.

Biochemical and proteomic insights into sarcoplasmic reticulum Ca2+-ATPase complexes in skeletal muscles

INTRODUCTION

Skeletal muscles contain large numbers of high-molecular-mass protein complexes in elaborate membrane systems. Integral membrane proteins are involved in diverse cellular functions including the regulation of ion handling, membrane homeostasis, energy metabolism and force transmission.

AREAS COVERED

The proteomic profiling of membrane proteins and large protein assemblies in skeletal muscles are outlined in this article. This includes a critical overview of the main biochemical separation techniques and the mass spectrometric approaches taken to study membrane proteins. As an illustrative example of an analytically challenging large protein complex, the proteomic detection and characterization of the Ca2+-ATPase of the sarcoplasmic reticulum is discussed. The biological role of this large protein complex during normal muscle functioning, in the context of fiber type diversity and in relation to mechanisms of physiological adaptations and pathophysiological abnormalities is evaluated from a proteomics perspective.

EXPERT OPINION

Mass spectrometry-based muscle proteomics has decisively advanced the field of basic and applied myology. Although it is technically challenging to study membrane proteins, innovations in protein separation methodology in combination with sensitive mass spectrometry and improved systems bioinformatics has allowed the detailed proteomic detection and characterization of skeletal muscle membrane protein complexes, such as Ca2+-pump proteins of the sarcoplasmic reticulum.

Modern tools applied to classic structures: Approaches for mammalian male germ cell RNA granule research

First reported in the 1800s, germ cell granules are small nonmembrane bound RNA-rich regions of the cytoplasm. These sites of critical RNA processing and storage in the male germ cell are essential for proper differentiation and development and are present in a wide range of species from Caenorhabditis elegans through mammals. Initially characterized by light and electron microscopy, more modern techniques such as immunofluorescence and genetic models have played a major role in expanding our understanding of the composition of these structures. While these methods have given light to potential granule functions, much work remains to be done. The current expansion of imaging technologies and omics-scale analyses to germ cell granule research will drive the field forward considerably. Many of these methods, both current and upcoming, have considerable caveats and limitations that necessitate a holistic approach to the study of germ granules. By combining and balancing different techniques, the field is poised to elucidate the nature of these critical structures.