Label-Based and Label-Free Strategies for Protein Quantitation

Introducing dysfunctional Protein-Protein Interactome (dfPPI) - A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease

Protein-protein interactions (PPIs) play a crucial role in cellular function and disease manifestation, with dysfunctions in PPI networks providing a direct link between stressors and phenotype. The dysfunctional Protein-Protein Interactome (dfPPI) platform, formerly known as epichaperomics, is a newly developed chemoproteomic method aimed at detecting dynamic changes at the systems level in PPI networks under stressor-induced cellular perturbations within disease states. This review provides an overview of dfPPIs, emphasizing the novel methodology, data analytics, and applications in disease research. dfPPI has applications in cancer research, where it identifies dysfunctions integral to maintaining malignant phenotypes and discovers strategies to enhance the efficacy of current therapies. In neurodegenerative disorders, dfPPI uncovers critical dysfunctions in cellular processes and stressor-specific vulnerabilities. Challenges, including data complexity and the potential for integration with other omics datasets are discussed. The dfPPI platform is a potent tool for dissecting disease systems biology by directly informing on dysfunctions in PPI networks and holds promise for advancing disease identification and therapeutics.

Ionic liquid-assisted sample preparation mediates sensitive proteomic analysis of Bacillus subtilis spores

Endospore-forming bacteria are ubiquitous. Bacterial endospores are multilayered proteinaceous structures that protects the bacterial genome during stress conditions. They are also responsible for a wide range of critical clinical infections in humans. Precise analysis of spore-forming pathogens remains a major challenge in the field of proteomics because spore structures are highly resistant to conventional solubilizers and denaturing agents, such as sodium dodecyl sulfate and urea. We present an ionic liquid-assisted (i-soln) technique of sample preparation, called pTRUST, which enables shotgun analysis of Bacillus subtilis spores even when the starting materials are in the sub-microgram range. In proteomic analysis, this technique shows 50-2000-fold higher sensitivity than other conventional gel-based or gel-free methods (including one-pot sample processing). Using this technique, we identified 445 proteins with high confidence from trace amounts of highly pure spore preparations, including 52 of the 79 proteins (approximately 70%) previously demonstrated to be localized in spores in the SubtiWiki database and detected through direct protein analysis. Consequently, 393 additional proteins were identified as candidates for spore constitutive proteins. Twenty of these newly identified candidates were produced as green fluorescent protein fusion proteins, and each was evaluated for authenticity as a spore constituent using fluorescence microscopy analysis. The pTRUST method's sensitivity and reliability using the i-soln system, together with hitherto unreported proteins in spores, will enable an array of spore research for biological and clinical applications.

Proteomics of the heart

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

Protocol for affinity purification-mass spectrometry interactome profiling in larvae of Drosophila melanogaster

Many techniques exist for the identification of protein interaction networks. We present a protocol that relies on an affinity purification-mass spectrometry (AP-MS) approach to detect proteins that co-purify with a tagged bait of interest from Drosophila melanogaster larval muscles using the GAL4/upstream activating sequence (UAS) expression system. We also describe steps for the isolation and identification of protein complexes, followed by streamlined bioinformatics analysis for rapid and reproducible results. This protocol can be extended to investigate protein interactions in other tissues. For complete details on the use and execution of this protocol, please refer to Guo et al.1.

Proteomic characteristics of the aqueous humor in Uyghur patients with pseudoexfoliation syndrome and pseudoexfoliative glaucoma

Pseudoexfoliation syndrome (PEX) is characterized by the deposition of fibrous pseudoexfoliation material (PEXM) in the eye, and secondary glaucoma associated with this syndrome has a faster and more severe clinical course. The incidence of PEX and pseudoexfoliative glaucoma (PEXG) exhibits ethnic clustering; however, few proteomic studies related to PEX and PEXG have been conducted in Asian populations. Therefore, we aimed to conduct proteomic analysis on the aqueous humor (AH) obtained from Uyghur patients with cataracts, those with PEX and cataracts, and those with PEXG and cataracts to better understand the molecular mechanisms of the disease and identify its potential biomarkers. To this end, AH was collected from patients with cataracts (n = 10, control group), PEX with cataracts (n = 10, PEX group), and PEXG with cataracts (n = 10, PEXG group) during phacoemulsification. Label-free quantitative proteomic techniques combined with bioinformatics were used to identify and analyze differentially expressed proteins (DEPs) in the AH of PEX and PEXG groups. Then, independent AH samples (n = 12, each group) were collected to validate DEPs by enzyme-linked immunosorbent assay (ELISA). The PEX group exhibited 25 DEPs, while the PEXG group showed 44 DEPs, both compared to the control group. Subsequently, we found three newly identified proteins in both PEX and PEXG groups, wherein FRAS1-related extracellular matrix protein 2 (FREM2) and osteoclast-associated receptor (OSCAR) exhibited downregulation, whereas coagulation Factor IX (F9) displayed upregulation. Bioinformatics analysis suggested that extracellular matrix interactions, abnormal blood-derived proteins, and lysosomes were mainly involved in the process of PEX and PEXG, and the PPI network further revealed F9 may serve as a potential biomarker for both PEX and PEXG. In conclusion, this study provides new information for understanding the proteomics of AH in PEX and PEXG.

Delineation of renal protein profiles in aristolochic acid I-induced nephrotoxicity in mice by label-free quantitative proteomics

Introduction: Aristolochic acid nephropathy (AAN) is a kidney injury syndrome caused by aristolochic acids exposure. Our study used label-free quantitative proteomics to delineate renal protein profiles and identify key proteins after exposure to different doses of aristolochic acid I (AAI). Methods: Male C57BL/6 mice received AAI (1.25 mg/kg/d, 2.5 mg/kg/d, or 5 mg/kg/d) or vehicle for 5 days. Results and discussion: The results showed that AAI induced dose-dependent nephrotoxicity. Differences in renal protein profiles between the control and AAI groups increased with AAI dose. Comparing the control with the low-, medium-, and high-dose AAI groups, we found 58, 210, and 271 differentially expressed proteins, respectively. Furthermore, protein-protein interaction network analysis identified acyl-CoA synthetase medium-chain family member 3 (Acsm3), cytochrome P450 family 2 subfamily E member 1 (Cyp2e1), microsomal glutathione S-transferase 1 (Mgst1), and fetuin B (Fetub) as the key proteins. Proteomics revealed that AAI decreased Acsm3 and Cyp2e1 while increasing Mgst1 and Fetub expression in mice kidneys, which was further confirmed by Western blotting. Collectively, in AAI-induced nephrotoxicity, renal protein profiles were dysregulated and exacerbated with increasing AAI dose. Acsm3, Cyp2e1, Mgst1, and Fetub may be the potential therapeutic targets for AAN.

Addressing Cardiovascular Toxicity Risk of Electronic Nicotine Delivery Systems in the Twenty-First Century: "What Are the Tools Needed for the Job?" and "Do We Have Them?"

Cigarette smoking is positively and robustly associated with cardiovascular disease (CVD), including hypertension, atherosclerosis, cardiac arrhythmias, stroke, thromboembolism, myocardial infarctions, and heart failure. However, after more than a decade of ENDS presence in the U.S. marketplace, uncertainty persists regarding the long-term health consequences of ENDS use for CVD. New approach methods (NAMs) in the field of toxicology are being developed to enhance rapid prediction of human health hazards. Recent technical advances can now consider impact of biological factors such as sex and race/ethnicity, permitting application of NAMs findings to health equity and environmental justice issues. This has been the case for hazard assessments of drugs and environmental chemicals in areas such as cardiovascular, respiratory, and developmental toxicity. Despite these advances, a shortage of widely accepted methodologies to predict the impact of ENDS use on human health slows the application of regulatory oversight and the protection of public health. Minimizing the time between the emergence of risk (e.g., ENDS use) and the administration of well-founded regulatory policy requires thoughtful consideration of the currently available sources of data, their applicability to the prediction of health outcomes, and whether these available data streams are enough to support an actionable decision. This challenge forms the basis of this white paper on how best to reveal potential toxicities of ENDS use in the human cardiovascular system-a primary target of conventional tobacco smoking. We identify current approaches used to evaluate the impacts of tobacco on cardiovascular health, in particular emerging techniques that replace, reduce, and refine slower and more costly animal models with NAMs platforms that can be applied to tobacco regulatory science. The limitations of these emerging platforms are addressed, and systems biology approaches to close the knowledge gap between traditional models and NAMs are proposed. It is hoped that these suggestions and their adoption within the greater scientific community will result in fresh data streams that will support and enhance the scientific evaluation and subsequent decision-making of tobacco regulatory agencies worldwide.

The sensor applications for prostate and lung cancer biomarkers in terms of electrochemical analysis

Prostate and lung cancers are the most common types of cancer and affect a large part of the population around the world, causing deaths. Therefore, the rapid identification of cancer can profoundly impact reducing cancer-related death rates and protecting human lives. Significant resources have been dedicated to investigating new methods for early disease detection. Cancer biomarkers encompass various biochemical entities, including nucleic acids, proteins, sugars, small metabolites, cytogenetic and cytokinetic parameters, and whole tumor cells in bodily fluids. These tools can be utilized for various purposes, such as risk assessment, diagnosis, prognosis, treatment efficacy, toxicity evaluation, and predicting a return. Due to these versatile and critical purposes, there are widespread studies on the development of new, sensitive, and selective approaches for the determination of cancer biomarkers. This review illustrates the significant lung and prostate cancer biomarkers and their determination utilizing electrochemical sensors, which have the advantage of improved sensitivity, low cost, and simple analysis. Additionally, approaches such as improving sensitivity with nanomaterials and ensuring selectivity with MIPs are used to increase the performance of the sensor. This review aims to overview the most recent electrochemical biosensor applications for determining vital biomarkers of prostate and lung cancers in terms of nanobiosensors and molecularly imprinted polymer (MIP)-based biosensors.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Clinical Proteomics for Solid Organ Tissues

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

Omics and systems view of innate immune pathways

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

Osmoprotectants play a major role in the Portulaca oleracea resistance to high levels of salinity stress-insights from a metabolomics and proteomics integrated approach

Introduction

Purslane (Portulaca oleracea L.) is a non-conventional food plant used extensively in folk medicine and classified as a multipurpose plant species, serving as a source of features of direct importance to the agricultural and agri-industrial sectors. This species is considered a suitable model to study the mechanisms behind resistance to several abiotic stresses including salinity. The recently achieved technological developments in high-throughput biology opened a new window of opportunity to gain additional insights on purslane resistance to salinity stress-a complex, multigenic, and still not well-understood trait. Only a few reports on single-omics analysis (SOA) of purslane are available, and only one multi-omics integration (MOI) analysis exists so far integrating distinct omics platforms (transcriptomics and metabolomics) to characterize the response of purslane plants to salinity stress.

Methods

The present study is a second step in building a robust database on the morpho-physiological and molecular responses purslane to salinity stress and its subsequent use in attempting to decode the genetics behind its resistance to this abiotic stress. Here, the characterization of the morpho-physiological responses of adult purslane plants to salinity stress and a metabolomics and proteomics integrative approach to study the changes at the molecular level in their leaves and roots is presented.

Results and discussion

Adult plants of the B1 purslane accession lost approximately 50% of the fresh and dry weight (from shoots and roots) whensubmitted to very high salinity stress (2.0 g of NaCl/100 g of the substrate). The resistance to very high levels of salinity stress increases as the purslane plant matures, and most of the absorbed sodium remains in the roots, with only a part (~12%) reaching the shoots. Crystal-like structures, constituted mainly by Na⁺, Cl^-, and K⁺, were found in the leaf veins and intercellular space near the stoma, indicating that this species has a mechanism of salt exclusion operating on the leaves, which has its role in salt tolerance. The MOI approach showed that 41 metabolites were statistically significant on the leaves and 65 metabolites on the roots of adult purslane plants. The combination of the mummichog algorithm and metabolomics database comparison revealed that the glycine, serine, and threonine, amino sugar and nucleotide sugar, and glycolysis/gluconeogenesis pathways were the most significantly enriched pathways when considering the total number of occurrences in the leaves (with 14, 13, and 13, respectively) and roots (all with eight) of adult plants; and that purslane plants employ the adaptive mechanism of osmoprotection to mitigate the negative effect of very high levels of salinity stress; and that this mechanism is prevalent in the leaves. The multi-omics database built by our group underwent a screen for salt-responsive genes, which are now under further characterization for their potential to promote resistance to salinity stress when heterologously overexpressed in salt-sensitive plants.

Identification of Exosome-Related Genes Associated with Prognosis and Immune Infiltration Features in Head-Neck Squamous Cell Carcinoma

The highly immunosuppressive nature of head-neck squamous cell cancer (HNSCC) is not fully understood. Exosomes play crucial roles in the communication between cancer and non-cancer cells, but the clinical significance of the expression of exosome-related genes (ERGs) remains unclear in HNSCC. This study aimed to establish an HNSCC-ERGs model by using mass spectrometry (MS)-based label-free quantitative proteomics in combination with the TCGA primary HNSCC dataset. The study managed to classify the HNSCC patients into two subtypes based on the expression level of prognostic ERGs, which showed significant differences in prognosis and immune infiltration. LASSO regression algorithm was used to establish a risk prediction model based on seven risky genes (PYGL, ACTN2, TSPAN15, EXT2, PLAU, ITGA5), and the high-risk group was associated with poor survival prognosis and suppressive immune status. HPRT1 and PYGL were found to be independent prognostic factors through univariate and multivariate Cox regression analyses. Immune and ssGSEA analysis revealed that HPRT1 and PYGL were significantly related to immunosuppression, immune response, and critical signaling transduction pathways in HNSCC. Immunohistochemistry results further validated the expression level, clinical value, and immunosuppressive function of HPRT1 and PYGL in HNSCC patients. In conclusion, this study established molecular subtypes and a prediction risk model based on the ERGs. Furthermore, the findings suggested that HPRT1 and PYGL might play critical roles in reshaping the tumor microenvironment.

A Robust Purity Method for Biotherapeutics Using New Peak Detection in an LC-MS-Based Multi-Attribute Method

New peak detection (NPD), as part of the LC-MS-based multi-attribute method (MAM), allows for sensitive and unbiased detection of new or changing site-specific attributes between a sample and reference that is not possible with conventional UV or fluorescence detection-based methods. MAM with NPD can serve as a purity test that can establish whether a sample and the reference are similar. The broad implementation of NPD in the biopharmaceutical industry has been limited by the potential presence of false positives or artifacts, which increase the analysis time and can trigger unnecessary investigations of product quality. Our novel contributions to the success of NPD are the curation of false positives, use of the known peak list concept, pairwise analysis approach, and the development of a NPD system suitability control strategy. In this report, we also introduce a unique experimental design utilizing sequence variant co-mixes to measure NPD performance. We show that NPD has superior performance relative to conventional control system methods in the detection of an unexpected change as compared with the reference. NPD is a new frontier in purity testing that reduces subjectivity, need for analyst intervention, and potential for missing unexpected product quality changes.

Mass Spectrometry-Based Untargeted Approaches to Reveal Diagnostic Signatures of Male Infertility in Seminal Plasma: A New Laboratory Perspective for the Clinical Management of Infertility?

Male infertility has been recognized as a global health problem. Semen analysis, although considered the golden standard, may not provide a confident male infertility diagnosis alone. Hence, there is the urgent request for an innovative and reliable platform to detect biomarkers of infertility. The rapid expansion of mass spectrometry (MS) technology in the field of the 'omics' disciplines, has incredibly proved the great potential of MS-based diagnostic tests to revolutionize the future of pathology, microbiology and laboratory medicine. Despite the increasing success in the microbiology area, MS-biomarkers of male infertility currently remain a proteomic challenge. In order to address this issue, this review encompasses proteomics investigations by untargeted approaches with a special focus on experimental designs and strategies (bottom-up and top-down) for seminal fluid proteome profiling. The studies reported here witness the efforts of the scientific community to address these investigations aimed at the discovery of MS-biomarkers of male infertility. Proteomics untargeted approaches, depending on the study design, might provide a great plethora of biomarkers not only for a male infertility diagnosis, but also to address a new MS-biomarkers classification of infertility subtypes. From the early detection to the evaluation of infertility grade, new MS-derived biomarkers might also predict long-term outcomes and clinical management of infertility.

Analysis of milk with liquid chromatography–mass spectrometry: a review

As a widely consumed foodstuff, milk and dairy products are increasingly studied over the years. At the present time, milk profiling is used as a benchmark to assess the properties of milk. Modern biomolecular mass spectrometers have become invaluable to fully characterize the milk composition. This review reports the analysis of milk and its components using liquid chromatography coupled with mass spectrometry (LC–MS). LC–MS analysis as a whole will be discussed subdivided into the major constituents of milk, namely, lipids, proteins, sugars and the mineral fraction.

The potential of proteomics in the study of processed meat products

Proteomics is a field that has grown rapidly since its emergence in the mid-1990s, reaching many disciplines such as food technology. The application of proteomic techniques in the study of complex biological samples such as foods, specifically meat products, allows scientists to decipher the underlying cellular mechanisms behind different quality traits. Lately, much emphasis has been placed on the discovery of biomarkers that facilitate the prediction of biochemical transformations of the product and provide key information on parameters associated with traceability and food safety. This review study focuses on the contribution of proteomics in the improvement of processed meat products. Different techniques and strategies have recently been successfully carried out in the study of the proteome of these products that can help the development of foods with a higher sensory quality, while ensuring consumer safety through early detection of microbiological contamination and fraud. SIGNIFICANCE: The food industry and the academic world work together with the aim of responding to market demands, always seeking excellence. In particular, the meat industry has to face a series of challenges such as, achieving sensory attributes in accordance with the standards required by the consumer and maintaining a high level of safety and transparency, avoiding deliver adulterated and/or contaminated products. This review work exposes how the aforementioned challenges are attempted to be solved through proteomic technology, discussing the latest and most outstanding research in this regard, which undoubtedly contribute to improving the quality, in all the extension of the word, of meat products, providing relevant knowledge in the field of proteomic research.

Targeted Absolute Protein Quantification Using SILAC Internal Standard and Full-Length Protein Calibrators (TAQSI)

Mass spectrometry (MS)-based proteomics has been increasingly used for targeted absolute protein quantifications in both basic and clinical research. There is a great need to overcome some pitfalls of current MS-based targeted absolute protein quantification methods, such as high inter-assay variability and high cost associated with the use of synthesized isotopic peptides/proteins. Here we describe a targeted absolute protein quantification method utilizing SILAC internal standards and unlabeled full-length protein calibrators (TAQSI). The method has proven accurate, precise, reproducible, and cost-effective. Notably, the method is resistant to the variabilities caused by protein extraction and digestion. Moreover, it avoids measurement errors due to nonsynonymous mutations. This versatile method can be used for determining the absolute expressions of numerous proteins in various biological samples. As a proof-of-concept, this method was successfully applied to absolutely quantitate the protein expressions of carboxylesterase 1 (CES1) in human liver tissues.

Comprehensive maturity of nuclear pore complexes regulates zygotic genome activation

Nuclear pore complexes (NPCs) are channels for nucleocytoplasmic transport of proteins and RNAs. However, it remains unclear whether composition, structure, and permeability of NPCs dynamically change during the cleavage period of vertebrate embryos and affect embryonic development. Here, we report that the comprehensive NPC maturity (CNM) controls the onset of zygotic genome activation (ZGA) during zebrafish early embryogenesis. We show that more nucleoporin proteins are recruited to and assembled into NPCs with development, resulting in progressive increase of NPCs in size and complexity. Maternal transcription factors (TFs) transport into nuclei more efficiently with increasing CNM. Deficiency or dysfunction of Nup133 or Ahctf1/Elys impairs NPC assembly, maternal TFs nuclear transport, and ZGA onset, while nup133 overexpression promotes these processes. Therefore, CNM may act as a molecular timer for ZGA by controlling nuclear transport of maternal TFs that reach nuclear concentration thresholds at a given time to initiate ZGA.

Proteomics reveals that cell density could affect the efficacy of drug treatment

In vitro cell biology study plays a fundamental role in biological and drug development research, but the repeatability and accuracy of cell studies remain to be low. Various uncertainties during the cell culture process could introduce bias into drug research. In this study, we evaluate the potential effects and underlying mechanisms induced by cell number differences in the cell seeding process. Normally, drug experiments are initiated 24 h after cell seeding, and the difference in the cell number at the time of inoculation leads to the difference in cell confluence (cell density) when drug research is conducted. While cell confluence is closely related to intercellular communication, surface protein interaction, cell autocrine as well as paracrine protein expression of cells, it might have a potential impact on the effect of biological studies such as drug treatment. This study used proteomics technology to comprehensively explore the different protein expression patterns between cells with different confluences. Due to the high sensitivity and high throughput of liquid chromatography-mass spectrometry (LC-MS/MS) detection, it was hired to evaluate the protein expression differences of Hep3B cells with 3 different confluences (30%, 50%, and 70%). The differential expressed proteins were analyzed by the Reactome pathway and the Gene Ontology (GO) pathway. Significant differences were identified across three confluences in terms of the number of proteins identified, the protein expression pattern, and the expression level of certain KEGG pathways. We found that those proteins involved in the cell cycle pathway were differently expressed: the higher the cell confluence, the higher these proteins expressed. A cell cycle inhibitor palbociclib was selected to further verify this observation. Palbociclib in the same dose was applied to cells with different confluence, the results indicated that the growth inhibition effect of palbociclib increases along with the increasing trend of cell cycle protein expression. The result indicated that cell density did influence the effect of drug treatment. Furthermore, three other drugs, cisplatin, paclitaxel, and imatinib, were used to treat the three liver cancer cell lines Hep3B, SUN387, and MHCC97, and a similar observation was obtained that drug effect would be different when the cell confluences were different. Therefore, selecting an appropriate number of cells for plating is vitally important at the beginning of a drug study.

Dealing with missing values in proteomics data

Proteomics data are often plagued with missingness issues. These missing values (MVs) threaten the integrity of subsequent statistical analyses by reduction of statistical power, introduction of bias, and failure to represent the true sample. Over the years, several categories of missing value imputation (MVI) methods have been developed and adapted for proteomics data. These MVI methods perform their tasks based on different prior assumptions (e.g., data is normally or independently distributed) and operating principles (e.g., the algorithm is built to address random missingness only), resulting in varying levels of performance even when dealing with the same dataset. Thus, to achieve a satisfactory outcome, a suitable MVI method must be selected. To guide decision making on suitable MVI method, we provide a decision chart which facilitates strategic considerations on datasets presenting different characteristics. We also bring attention to other issues that can impact proper MVI such as the presence of confounders (e.g., batch effects) which can influence MVI performance. Thus, these too, should be considered during or before MVI.

Illuminating the dark protein-protein interactome

In living systems, a complex network of protein-protein interactions (PPIs) underlies most biochemical events. The human protein-protein interactome has been surveyed using yeast two-hybrid (Y2H)- and mass spectrometry (MS)-based approaches such as affinity purification coupled to MS (AP-MS). Despite decades of systematic investigations and collaborative multi-disciplinary efforts, there is no "gold standard" for documenting PPIs. A surprisingly large fraction of the human interactome remains uncharted, which we refer to as the "dark interactome." In this review, we highlight the complexity of the human interactome and discuss the current status of the human reference interactome maps. We discuss why a large proportion of the human interactome has remained refractory to traditional approaches. We propose an experimental model that can enable the identification of the dark interactome in a cell-type-specific manner. We also propose a framework to implement when embarking on studies designed to rigorously identify and characterize protein interactions.

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.

Sperm Phosphoproteome: Unraveling Male Infertility

Infertility affects approximately 15% of couples worldwide of childbearing age, and in many cases the etiology of male infertility is unknown. The current standard evaluation of semen is insufficient to establish an accurate diagnosis. Proteomics techniques, such as phosphoproteomics, applied in this field are a powerful tool to understand the mechanisms that regulate sperm functions such as motility, which is essential for successful fertilization. Among the post-translational modifications of sperm proteins, this review summarizes, from a proteomic perspective, the updated knowledge of protein phosphorylation, in human spermatozoa, as a relevant molecular mechanism involved in the regulation of sperm physiology. Specifically, the role of sperm protein phosphorylation in motility and, consequently, in sperm quality is highlighted. Additionally, through the analysis of published comparative phosphoproteomic studies, some candidate human sperm phosphoproteins associated with low sperm motility are proposed. Despite the remarkable advances in phosphoproteomics technologies, the relatively low number of studies performed in human spermatozoa suggests that phosphoproteomics has not been applied to its full potential in studying male infertility yet. Therefore, further studies will improve the application of this procedure and overcome the limitations, increasing the understanding of regulatory mechanisms underlying protein phosphorylation in sperm motility and, consequently, in male fertility.

Comparative Proteomic Analysis of Fucosylated Glycoproteins Produced by Bacteroides thetaiotaomicron Under Different Polysaccharide Nutrition Conditions

Bacteroides thetaiotaomicron, one of the most eminent representative gut commensal Bacteroides species, is able to use the L-fucose in host-derived and dietary polysaccharides to modify its capsular polysaccharides and glycoproteins through a mammalian-like salvage metabolic pathway. This process is essential for the colonization of the bacteria and for symbiosis with the host. However, despite the importance of fucosylated proteins (FGPs) in B. thetaiotaomicron, their types, distribution, and functions remain unclear. In this study, the effects of different polysaccharide (corn starch, mucin, and fucoidan) nutrition conditions on newly synthesized FGPs expressions and fucosylation are investigated using a chemical biological method based on metabolic labeling and bioorthogonal reaction. According to the results of label-free quantification, 559 FGPs (205 downregulated and 354 upregulated) are affected by the dietary conditions. Of these differentially expressed proteins, 65 proteins show extremely sensitive to polysaccharide nutrition conditions (FGPs fold change/global protein fold change ≥2.0 or ≤0.5). Specifically, the fucosylation of the chondroitin sulfate ABC enzyme, Sus proteins, and cationic efflux system proteins varies significantly upon the addition of mucin, corn starch, or fucoidan. Moreover, these polysaccharides can trigger an appreciable increase in the fucosylation level of the two-component system and ammonium transport proteins. These results highlight the efficiency of the combined metabolic glycan labeling and bio-orthogonal reaction in enriching the intestinal Bacteroides glycoproteins. Moreover, it emphasizes the sensitivity of Bacteroides fucosylation to polysaccharide nutrition conditions, which allows for the regulation of bacterial growth.

Protein phosphatase 2A catalytic subunit β suppresses PMA/ionomycin-induced T-cell activation by negatively regulating PI3K/Akt signaling

The precise regulation of the T-cell activation process is critical for overall immune homeostasis. Although protein phosphatase 2A (PP2A) is required for T-cell development and function, the role of PPP2CB, which is the catalytic subunit β isoform of PP2A, remains unknown. In the present study, using a T cell-specific knockout mouse of PPP2CB (PPP2CB^fl/fl Lck-Cre⁺ ), we demonstrated that PPP2CB was dispensable for T-cell development in the thymus and peripheral lymphoid organs. Furthermore, PPP2CB deletion did not affect T-cell receptor (TCR)-induced T-cell activation or cytokine-induced T-cell responses; however, it specifically enhanced phorbol myristate acetate (PMA) plus ionomycin-induced T-cell activation with increased cellular proliferation, elevated CD69 and CD25 expression, and enhanced cytokine production (inteferon-γ, interleukin-2 and tumor necrosis factor). Mechanistic analyses suggested that the PPP2CB deletion enhanced activation of the phosphoinositide 3-kinase/Akt signaling pathway and Ca²⁺ flux following stimulation with PMA plus ionomycin. Moreover, the specific PI3K inhibitor rescued the augmented cell activation in PPP2CB-deficient T cells. Using mass spectrometry-based phospho-peptide analysis, we identified potential substrates of PPP2CB during PMA plus ionomycin-induced T-cell activation. Collectively, our study provides evidence of the specific role of PPP2CB in controlling PMA plus ionomycin-induced T-cell activation.

Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity

Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is one of the centers for the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. Its key aim is to generate proteomic and transcriptomic signatures that can predict cardiotoxic adverse effects of kinase inhibitors approved by the Food and Drug Administration. Towards this goal, high throughput shotgun proteomics experiments (308 cell line/drug combinations +64 control lysates) have been conducted. Using computational network analyses, these proteomic data can be integrated with transcriptomic signatures, generated in tandem, to identify cellular signatures of cardiotoxicity that may predict kinase inhibitor-induced toxicity and enable possible mitigation. Both raw and processed proteomics data have passed several quality control steps and been made publicly available on the PRIDE database. This broad protein kinase inhibitor-stimulated human cardiomyocyte proteomic data and signature set is valuable for prediction of drug toxicities.

Human bronchial-pulmonary proteomics in coronavirus disease 2019 (COVID-19) pandemic: applications and implications

INTRODUCTION

The outbreak of the newly discovered human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has disrupted the normal life of almost every civilization worldwide. Studies have shown that the coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 can affect multiple human organs and physiological systems, but the respiratory system remains the primary location for viral infection.

AREAS COVERED

We summarize how omics technologies are used in SARS-CoV-2 research and specifically review the current knowledge of COVID-19 from the aspect of human bronchial-pulmonary proteomics. Also, knowledge gaps in COVID-19 that can be fulfilled by proteomics are discussed.

EXPERT OPINION

Overall, human bronchial-pulmonary proteomics plays an important role in revealing the dynamics, functions, tropism, and pathogenicity of SARS-CoV-2, which is crucial for COVID-19 biomarker and therapeutic target discoveries. To more fully understand the impact of COVID-19, research from various angles using multi-omics approaches should also be conducted on the lungs as well as other organs.

Water-Soluble Tomato Extract Fruitflow Alters the Phosphoproteomic Profile of Collagen-Stimulated Platelets

Platelet hyperactivity is a risk factor for cardiovascular disease and thrombosis. Recent studies reported that the tomato extract Fruitflow inhibited platelet function, but the molecular mechanism is still unclear. The present study used proteomics to quantitatively analyze the effect of fruitflow on the inhibition of collagen-stimulated platelets and validated the involvement of several signaling molecules. Fruitflow significantly inhibited human platelet aggregation and P-selectin expression that were induced by collagen. Proteomics analysis revealed that compared fruitflow-treated collagen-stimulated platelets with only collagen-stimulated platelets, 60 proteins were upregulated and 10 proteins were downregulated. Additionally, 66 phosphorylated peptides were upregulated, whereas 37 phosphorylated peptides were downregulated. Gene Ontology analysis indicated that fruitflow treatment downregulated phosphoinositide 3-kinase (PI3K)/protein kinase B and guanosine triphosphatase-mediated signal transduction in collagen-activated platelets. Biological validation indicated that fruitflow decreased Akt, glycogen synthase kinase 3β, p38 mitogen-activated protein kinase (MAPK), and heat shock protein (Hsp27) phosphorylation in collagen-stimulated platelets. Fruitflow recovered cyclic adenosine monophosphate levels in collagen-activated platelets and reduced protein kinase A substrate phosphorylation that was induced by collagen. These findings suggest that fruitflow is a functional food that can inhibit platelet function, conferring beneficial effects for people who are at risk for platelet hyperactivity-associated thrombosis.

Proteomes Are of Proteoforms: Embracing the Complexity

Proteomes are complex-much more so than genomes or transcriptomes. Thus, simplifying their analysis does not simplify the issue. Proteomes are of proteoforms, not canonical proteins. While having a catalogue of amino acid sequences provides invaluable information, this is the Proteome-lite. To dissect biological mechanisms and identify critical biomarkers/drug targets, we must assess the myriad of proteoforms that arise at any point before, after, and between translation and transcription (e.g., isoforms, splice variants, and post-translational modifications [PTM]), as well as newly defined species. There are numerous analytical methods currently used to address proteome depth and here we critically evaluate these in terms of the current 'state-of-the-field'. We thus discuss both pros and cons of available approaches and where improvements or refinements are needed to quantitatively characterize proteomes. To enable a next-generation approach, we suggest that advances lie in transdisciplinarity via integration of current proteomic methods to yield a unified discipline that capitalizes on the strongest qualities of each. Such a necessary (if not revolutionary) shift cannot be accomplished by a continued primary focus on proteo-genomics/-transcriptomics. We must embrace the complexity. Yes, these are the hard questions, and this will not be easy…but where is the fun in easy?

Application of Mass Spectrometry-Based Proteomics to Barley Research

Barley (Hordeum vulgare) is the fourth most cultivated crop in the world in terms of production volume, and it is also the most important raw material of the malting and brewing industries. Barley belongs to the grass (Poaceae) family and plays an important role in food security and food safety for both humans and livestock. With the global population set to reach 9.7 billion by 2050, but with less available and/or suitable land for agriculture, the use of biotechnology tools in breeding programs are of considerable importance in the quest to meet the growing food gap. Proteomics as a member of the "omics" technologies has become popular for the investigation of proteins in cereal crops and particularly barley and its related products such as malt and beer. This technology has been applied to study how proteins in barley respond to adverse environmental conditions including abiotic and/or biotic stresses, how they are impacted during food processing including malting and brewing, and the presence of proteins implicated in celiac disease. Moreover, proteomics can be used in the future to inform breeding programs that aim to enhance the nutritional value and broaden the application of this crop in new food and beverage products. Mass spectrometry analysis is a valuable tool that, along with genomics and transcriptomics, can inform plant breeding strategies that aim to produce superior barley varieties. In this review, recent studies employing both qualitative and quantitative mass spectrometry approaches are explored with a focus on their application in cultivation, manufacturing, processing, quality, and the safety of barley and its related products.

DDASSQ: an open-source, multiple peptide sequencing strategy for label free quantification based on an OpenMS pipeline in the KNIME analytics platform

In this study we investigated the performance of a computational pipeline for protein identification and label free quantification (LFQ) of LC–MS/MS data sets from experimental animal tissue samples, as well as the impact of its specific peptide search combinatorial approach. The full pipeline workflow was composed of peptide search engine adapters based on different identification algorithms, in the frame of the open‐source OpenMS software running within the KNIME analytics platform. Two different in silico tryptic digestion, database‐search assisted approaches (X!Tandem and MS‐GF+), de novo peptide sequencing based on Novor and consensus library search (SpectraST), were tested for the processing of LC‐MS/MS raw data files obtained from proteomic LC‐MS experiments done on proteolytic extracts from mouse ex vivo liver samples. The results from proteomic LFQ were compared to those based on the application of the two software tools MaxQuant and Proteome Discoverer for protein inference and label‐free data analysis in shotgun proteomics. Data are available via ProteomeXchange with identifier PXD025097.

Harnessing microbial wealth for lignocellulose biomass valorization through secretomics: a review

The recalcitrance of lignocellulosic biomass is a major constraint to its high-value use at industrial scale. In nature, microbes play a crucial role in biomass degradation, nutrient recycling and ecosystem functioning. Therefore, the use of microbes is an attractive way to transform biomass to produce clean energy and high-value compounds. The microbial degradation of lignocelluloses is a complex process which is dependent upon multiple secreted enzymes and their synergistic activities. The availability of the cutting edge proteomics and highly sensitive mass spectrometry tools make possible for researchers to probe the secretome of microbes and microbial consortia grown on different lignocelluloses for the identification of hydrolytic enzymes of industrial interest and their substrate-dependent expression. This review summarizes the role of secretomics in identifying enzymes involved in lignocelluloses deconstruction, the development of enzyme cocktails and the construction of synthetic microbial consortia for biomass valorization, providing our perspectives to address the current challenges.

Developing mass spectrometry for the quantitative analysis of neuropeptides

INTRODUCTION

Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.

AREAS COVERED

We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.

EXPERT OPINION

Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Current Methods of Post-Translational Modification Analysis and Their Applications in Blood Cancers

Post-translational modifications (PTMs) add a layer of complexity to the proteome through the addition of biochemical moieties to specific residues of proteins, altering their structure, function and/or localization. Mass spectrometry (MS)-based techniques are at the forefront of PTM analysis due to their ability to detect large numbers of modified proteins with a high level of sensitivity and specificity. The low stoichiometry of modified peptides means fractionation and enrichment techniques are often performed prior to MS to improve detection yields. Immuno-based techniques remain popular, with improvements in the quality of commercially available modification-specific antibodies facilitating the detection of modified proteins with high affinity. PTM-focused studies on blood cancers have provided information on altered cellular processes, including cell signaling, apoptosis and transcriptional regulation, that contribute to the malignant phenotype. Furthermore, the mechanism of action of many blood cancer therapies, such as kinase inhibitors, involves inhibiting or modulating protein modifications. Continued optimization of protocols and techniques for PTM analysis in blood cancer will undoubtedly lead to novel insights into mechanisms of malignant transformation, proliferation, and survival, in addition to the identification of novel biomarkers and therapeutic targets. This review discusses techniques used for PTM analysis and their applications in blood cancer research.

Low expression of GSTP1 in the aqueous humour of patients with primary open-angle glaucoma

Primary open‐angle glaucoma (POAG) is characterized by irreversible neurodegeneration accompanied by visual field defects and high intraocular pressure. Currently, an effective treatment is not available to prevent the progression of POAG, other than treatments to decrease the high intraocular pressure. We performed proteomic analysis of aqueous humour (AH) samples from patients with POAG combined with cataract and patients with cataract to obtain a better understanding of the pathogenesis of POAG and explore potential treatment targets for this condition. Samples were collected from 10 patients with POAG combined with cataract and 10 patients with cataract. Samples from each group were pooled. A high‐resolution, label‐free, liquid chromatography‐tandem mass spectrometry‐based quantitative proteomic analysis was performed. In total, 610 proteins were identified in human AH samples from the two groups. A total of 48 up‐regulated proteins and 49 down‐regulated proteins were identified in the POAG combined with cataract group compared with the control group. Gene Ontology (GO) analysis revealed key roles for these proteins in inflammation, immune responses, growth and development, cellular movement and vesicle‐mediated transport in the biological process category. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated the down‐regulated expression of glutathione S‐transferase P (GSTP1) in the glutathione metabolism signalling pathway in the POAG combined with cataract group. Additionally, certain significantly differentially expressed proteins in the proteomic profile were verified by enzyme‐linked immunosorbent assay (ELISA). GSTP1 levels were reduced in the human AH samples from the POAG combined with cataract group, based on the results of ELISA and proteomic profiling. Therefore, GSTP1, a redox‐related marker, may be involved in the pathological process of POAG and may become a treatment target in the future.

Quantitative proteomics of epigenetic histone modifications in MCF-7 cells under estradiol stimulation

Estrogen exposure has already been considered to be associated with tumorigenesis and breast cancer progression. To study the epigenetic regulation mechanism in MCF-7 cells under estrogen exposure, which normally results in cell proliferation and malignancy, a stable isotope labeling of amino acid (SILAC) based quantitative proteomics strategy was used to analyse histone post-translational modifications (PTMs) and protein differential expressions. In total, we have unambiguously identified 49 histone variants and quantified 42 of them, in which two differentially expressed proteins were found to be associated with breast cancers. Through the quantitative analysis of 470 histone peptides with a combination of different PTM types, including methylation (mono-, di-, and tri-), acetylation and phosphorylation, 150 of them were found to be differentially expressed. Through the biological analysis of the quantification results of both histone PTMs and proteins in MCF-7 cells, we found that (1) the histone variants H10 and H2AV have an effect on the adjustment of the nucleosome or chromatin structure and activate target genes; (2) after estrogen receptor (ER) activation by estrogen, the recruitment of histone acetyltransferase KAT7 might affect the acetylation at the N terminal of H4 (K5, K8 and K12) and also result in cross-talk between different acetylation sites; (3) different expression of histone deacetylase HDAC2 and its nucleo-cytoplasmic transportation process is important in the regulation of histone acetylation in MCF-7 cells under estrogen exposure.

Quantitative proteomics implicates YggT in streptomycin resistance in Salmonella enterica serovar Enteritidis

OBJECTIVES

To identify proteins that may be associated with antibiotic resistance in the multidrug-resistant Salmonella enterica D14, by constructing proteomic profiles using mass spectrometry-based label-free quantitative proteomics (LFQP).

RESULTS

D14 was cultured with four antibiotics (ampicillin, nalidixic acid, streptomycin, and tetracycline) separately. Subsequently, the findings from an equal combination of the four cultures were compared with the profile of sensitive S. enterica 104. 2255 proteins, including 149 differentially up-regulated proteins, were identified. Many of these up-regulated proteins were associated with flagellar assembly and chemotaxis, two-component system, amino acid metabolism, β-lactam resistance, and transmembrane transport. A subset of 10 genes was evaluated via quantitative real-time PCR (qPCR), followed by the construction of cheR, fliS, fliA, arnA, and yggT deletion mutants. Only the yggT-deleted D14 mutant showed decrease in streptomycin resistance, whereas the other deletions had no effect. Furthermore, complementation of yggT and the overexpression of yggT in S. enterica ATCC 14028 increased the streptomycin resistance. Additionally, spot dilution assay results confirmed that Salmonella strains, harboring yggT, exhibited an advantage in the presence of streptomycin.

CONCLUSIONS

The above proteomic and mutagenic analyses revealed that yggT is involved in streptomycin resistance in S. enterica.

The proteome of human Fallopian tube lavages during the phase of embryo transit reveals candidate proteins for the optimization of preimplantation embryo culture

STUDY QUESTION

Are there phase-specific changes in the early secretory (ES) phase human tubal lavage proteome that can inform and potentially optimize IVF culture media?

SUMMARY ANSWER

The human tubal lavage proteome during the ES phase relative to the menstrual phase reveals substantial differential protein abundance in pathways such as glycolysis, redox homeostasis and activation of 14-3-3 zeta-mediated signaling.

WHAT IS KNOWN ALREADY

The Fallopian tube is uniquely suited to the development of the preimplantation embryo as it transits the tube during the ES phase of the menstrual cycle. Euploid cleavage-stage embryo arrest may reflect incomplete recapitulation of in-vivo conditions by current media formulations.

STUDY DESIGN, SIZE, DURATION

Proteome-wide analysis of distal tubal lavage specimens collected from 26 healthy women undergoing open microtubal anastomosis surgery from January 2013 to January 2018 was performed. Specimens were grouped by menstrual cycle phase in order to analyze phase-specific differences in protein abundance. For the murine embryo assay, single-cell embryos (N = 482) were collected from superovulated wild type C57BL/6 female mice and cultured in microdrops over 5 days for the assessment of blastocyst development.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Human tubal lavage specimens were processed for label-free mass spectrometry. Reported menstrual cycle day was confirmed by measuring serum hormones. Key protein targets in the ES phase were validated via immunoblot. The ES phase-specific increase in 14-3-3 zeta protein was confirmed via ELISA of conditioned media obtained from primary human Fallopian tube epithelial cell culture. A murine embryo assay was performed to investigate the impact of graduated concentrations of 14-3-3 zeta on the blastocyst development rate.

MAIN RESULTS AND THE ROLE OF CHANCE

Comparison of the ES and menstrual phase human tubal lavage proteomes revealed 74 differentially expressed proteins with enrichment of pathways and biological processes involved in the regulation of carbohydrate metabolism, oxidative stress and cell survival. The adapter-regulator protein 14-3-3 zeta was among the most significantly increased in the ES phase. Supplementation of embryo culture media with 14-3-3 zeta at concentrations tested did not significantly improve the murine blastocyst development.

LIMITATIONS, REASONS FOR CAUTION

Although select associations were recapitulated in the conditioned media from sex steroid exposed primary human tubal epithelial cells, cell culture represents an in-vitro approximation. Changes to embryo culture media, such as protein supplementation, must undergo rigorous preclinical safety testing prior to adoption for human use.

WIDER IMPLICATIONS OF THE FINDINGS

This study represents the first description of the human Fallopian tube lavage proteome across the menstrual cycle, revealing a unique proteomic signature during the ES phase. Although supplementation of culture media with 14-3-3 zeta at appropriate concentrations showed no significant impact on the murine blastocyst development rate, other biologically plausible candidate proteins for individual or high throughput testing strategies are identified.

STUDY FUNDING/COMPETING INTEREST(S)

This work was funded in part by an Army Medical Department Advanced Medical Technology Initiative grant from the United States Army Medical Research and Materiel Command's Telemedicine and Advanced Technology Research Center. There are no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

Phosphoproteome Analysis in Immune Cell Signaling

Immune cell signaling is largely regulated by protein phosphorylation. Stimulation of toll-like receptors (TLRs) by pathogen-associated ligands drives the cascade of immune response, which can be influenced by differences in phosphoprotein abundance. Therefore, the analysis of phosphorylation signatures at a global level is central to understanding the complex and integrated signaling in macrophages upon pathogen attack. Here, we describe a mass spectrometry-based approach to identify and quantify phosphoproteome changes in response to the stimulation of TLR2, TLR4, and TLR7 with immune-response inducing ligands in cultured immune cells. This review will focus on the TLR stimulation of mouse macrophages as an example; however, the technique is applicable to any immortalized immune cell and any soluble stimuli. The methodology includes protocols for metabolic labeling of immune cells (stable isotope labeling of amino acids in cell culture, i.e., SILAC); ligand-initiated stimulation of immune receptors followed by cell lysis; in-solution trypsin digestion of proteins and enrichment of the resulting peptide mix for collecting phosphopeptides, which are then analyzed by high-resolution LC-MS/MS (liquid-chromatography tandem mass spectrometry). © 2020 Wiley Periodicals LLC. Basic Protocol 1: SILAC labeling of mouse macrophages Basic Protocol 2: Stimulation, cell lysis and Western Blotting Basic Protocol 3: Trypsin digestion, fractionation and phosphopeptide enrichment Basic Protocol 4: Quantitative mass spectrometry Alternate Protocol: Culturing SILAC-labeled cells from frozen mouse macrophages cells.

Recent advances in autophagic machinery: a proteomic perspective

INTRODUCTION

Autophagy is an evolutionarily conserved cellular clearance process, by which cytosolic components are delivered to autolysosomes for breakdown and recycling to maintain cellular homeostasis. During the past decades, autophagy has been found to be tightly implicated in various physiological and pathological progresses. Unraveling the regulatory mechanisms of the autophagy process will contribute to the development of emerging autophagy-targeting strategies for the treatment of various diseases. Recently, the rapid development of proteomics approaches has enabled the use of large-scale unbiased strategies to unravel autophagy machinery.

AREAS COVERED

In this review, we will highlight the recent contributions of proteomics strategies in clarifying the autophagy machinery, with an emphasis on the three different types of autophagy (namely macroautophagy, microautophagy, and chaperone-mediated autophagy). We will also discuss the emerging role of proteomics approaches in investigating the mechanism of the autophagy-based unconventional secretory pathway (secretory autophagy).

EXPERT OPINION

Proteomics has provided an effective strategy for the comprehensive analysis of the autophagy process, which will broaden our understanding of autophagy machinery, and holds great promise for developing clinical therapies targeting autophagy.

Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

BACKGROUND

Previous expression quantitative trait loci (eQTL) studies have identified thousands of genetic variants to be associated with gene expression at the mRNA level in the human liver. However, protein expression often correlates poorly with mRNA levels. Thus, protein quantitative trait loci (pQTL) study is required to identify genetic variants that regulate protein expression in human livers.

RESULTS

We conducted a genome-wide pQTL study in 287 normal human liver samples and identified 900 local pQTL variants and 4026 distant pQTL variants. We further discovered 53 genome hotspots of pQTL variants. Transcriptional region mapping analysis showed that 1133 pQTL variants are in transcriptional regulatory regions. Genomic region enrichment analysis of the identified pQTL variants revealed 804 potential regulatory interactions among 595 predicted regulators (e.g., non-coding RNAs) and 394 proteins. Moreover, pQTL variants and trait-variant integration analysis implied several novel mechanisms underlying the relationships between protein expression and liver diseases, such as alcohol dependence. Notably, over 2000 of the identified pQTL variants have not been reported in previous eQTL studies, suggesting extensive involvement of genetic polymorphisms in post-transcriptional regulation of protein expression in human livers.

CONCLUSIONS

We have partially established protein expression regulation networks in human livers and generated a wealth of pQTL data that could serve as a valuable resource for the scientific community.

Potential mechanisms of action of celastrol against rheumatoid arthritis: Transcriptomic and proteomic analysis

The clinical efficacy for treating of celastrol rheumatoid arthritis (RA) has been well-documented, but its mechanism of action remains unclear. Here we explored through what proteins and processes celastrol may act in activated fibroblast-like synoviocytes (FLS) from RA patients. Differential expression of genes and proteins after celastrol treatment of FLS was examined using RNA sequencing, label-free relatively quantitative proteomics and molecular docking. In this paper, expression of 26,565 genes and 3,372 proteins was analyzed. Celastrol was associated with significant changes in genes that respond to oxidative stress and oxygen levels, as well as genes that stabilize or synthesize components of the extracellular matrix. These results identify several potential mechanisms through which celastrol may inhibit inflammation in RA.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

Identification of marker proteins of muscular dystrophy in the urine proteome from the mdx-4cv model of dystrophinopathy

Since the protein constituents of urine present a dynamic proteome that can reflect a variety of disease-related alterations in the body, the mass spectrometric survey of proteome-wide changes in urine promises new insights into pathogenic mechanisms. Urine can be investigated in a completely non-invasive way and provides valuable biomedical information on body-wide changes. In this report, we have focused on the urine proteome in X-linked muscular dystrophy using the established mdx-4cv mouse model of dystrophinopathy. In order to avoid potential artefacts due to the manipulation of the biofluid proteome prior to mass spectrometry, crude urine specimens were analyzed without the prior usage of centrifugation steps or concentration procedures. Comparative proteomics revealed 21 increased and 8 decreased proteins out of 870 identified urinary proteoforms using 50 μl of biofluid per investigated sample, i.e. 14 wild type versus 14 mdx-4cv specimens. Promising marker proteins that were almost exclusively found in mdx-4cv urine included nidogen, parvalbumin and titin. Interestingly, the mass spectrometric identification of urine-associated titin revealed a wide spread of peptides over the sequence of this giant muscle protein. The newly established urinomic signature of dystrophinopathy might be helpful for the design of non-invasive assays to improve diagnosis, prognosis, therapy-monitoring and evaluation of potential harmful side effects of novel treatments in the field of muscular dystrophy research.

Recent Progress of Biomarker Detection Sensors

Early cancer diagnosis and treatment are crucial research fields of human health. One method that has proven efficient is biomarker detection which can provide real-time and accurate biological information for early diagnosis. This review presents several biomarker sensors based on electrochemistry, surface plasmon resonance (SPR), nanowires, other nanostructures, and, most recently, metamaterials which have also shown their mechanisms and prospects in application in recent years. Compared with previous reviews, electrochemistry-based biomarker sensors have been classified into three strategies according to their optimizing methods in this review. This makes it more convenient for researchers to find a specific fabrication method to improve the performance of their sensors. Besides that, as microfabrication technologies have improved and novel materials are explored, some novel biomarker sensors-such as nanowire-based and metamaterial-based biomarker sensors-have also been investigated and summarized in this review, which can exhibit ultrahigh resolution, sensitivity, and limit of detection (LoD) in a more complex detection environment. The purpose of this review is to understand the present by reviewing the past. Researchers can break through bottlenecks of existing biomarker sensors by reviewing previous works and finally meet the various complex detection needs for the early diagnosis of human cancer.

Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

Microorganisms enhance fitness by prioritizing catabolism of available carbon sources using a process known as carbon catabolite repression (CCR). Planktonically grown Pseudomonas aeruginosa is known to prioritize the consumption of organic acids including lactic acid over catabolism of glucose using a CCR strategy termed "reverse diauxie." P. aeruginosa is an opportunistic pathogen with well-documented biofilm phenotypes that are distinct from its planktonic phenotypes. Reverse diauxie has been described in planktonic cultures, but it has not been documented explicitly in P. aeruginosa biofilms. Here a combination of exometabolomics and label-free proteomics was used to analyze planktonic and biofilm phenotypes for reverse diauxie. P. aeruginosa biofilm cultures preferentially consumed lactic acid over glucose, and in addition, the cultures catabolized the substrates completely and did not exhibit the acetate secreting "overflow" metabolism that is typical of many model microorganisms. The biofilm phenotype was enabled by changes in protein abundances, including lactate dehydrogenase, fumarate hydratase, GTP cyclohydrolase, L-ornithine N(5)-monooxygenase, and superoxide dismutase. These results are noteworthy because reverse diauxie-mediated catabolism of organic acids necessitates a terminal electron acceptor like O2, which is typically in low supply in biofilms due to diffusion limitation. Label-free proteomics identified dozens of proteins associated with biofilm formation including 16 that have not been previously reported, highlighting both the advantages of the methodology utilized here and the complexity of the proteomic adaptation for P. aeruginosa biofilms. Documenting the reverse diauxic phenotype in P. aeruginosa biofilms is foundational for understanding cellular nutrient and energy fluxes, which ultimately control growth and virulence.