Expert Review of Proteomics最新文献

Introduction: Proteomics encompasses a wide and expanding range of methods to identify, characterize, and quantify thousands of proteins from a variety of biological samples, including blood samples, tumors, and tissues. Such methods are supportive of various forms of immunotherapy applied to chronic conditions such as allergies, autoimmune diseases, cancers, and infectious diseases.

Areas covered: In support of immunotherapy, proteomics based on mass spectrometry has multiple specific applications related to (i) disease modeling and patient stratification, (ii) antigen/ autoantigen/neoantigen/ allergen identification, (iii) characterization of proteins and monoclonal antibodies used for immunotherapeutic or diagnostic purposes, (iv) identification of biomarkers and companion diagnostics and (v) monitoring by immunoproteomics of immune responses elicited in the course of the disease or following immunotherapy.

Expert opinion: Proteomics contributes as an enabling technology to an evolution of immunotherapy toward a precision medicine approach aiming to better tailor treatments to patients' specificities in multiple disease areas. This trend is favored by a better understanding through multi-omics profiling of both the patient's characteristics, his/her immune status as well as of the features of the immunotherapeutic drug.

Introduction: A long-term stay of humans in space causes health problems and changes in protists and plants. Deep space exploration will increase the time humans or rodents will spend in microgravity (µg). Moreover, they are exposed to cosmic radiation, hypodynamia, and isolation. OMICS investigations will increase our knowledge of the underlying mechanisms of µg-induced alterations in vivo and in vitro.

Areas covered: We summarize the findings over the recent 3 years on µg-induced changes in the proteome of protists, plants, rodent, and human cells. Considering the thematic orientation of microgravity-related publications in that time frame, we focus on medicine-associated findings, such as the µg-induced antibiotic resistance of bacteria, the myocardial consequences of µg-induced calpain activation, and the role of MMP13 in osteoarthritis. All these point to the fact that µg is an extreme stressor that could not be evolutionarily addressed on Earth.

Expert opinion: In conclusion, when interpreting µg-experiments, the direct, mostly unspecific stress response, must be distinguished from specific µg-effects. For this reason, recent studies often do not consider single protein findings but place them in the context of protein-protein interactions. This enables an estimation of functional relationships, especially if these are supported by epigenetic and transcriptional data (multi-omics).

Introduction: Mass spectrometry-based single-cell proteomics (scMS) is experiencing rapid evolution due to the increased sensitivity of mass spectrometers as well as advances in multiplexing and sample preparation. To date, researchers have focused on two general approaches to scMS: label-free and isobaric label-based multiplexing. While label-free analysis provides straightforward sample preparation and a clear path to automation, it currently lacks the throughput necessary to practically analyze thousands of single cells. Multiplexed analysis utilizing isobaric labels requires additional sample manipulation but increases throughput such that analyzing thousands of cells is currently achievable. A key feature of multiplexed scMS experiments is a 'carrier proteome' - a sample added at 25x-500x, the single-cell sample that increases the number of proteins that can be identified in an MS analysis.

Areas covered: Here, we review early examples of carrier proteomes in quantitative proteomics before summarizing advantages and challenges of using a carrier proteome in scMS experiments.

Expert opinion: We conclude that the addition of carrier proteomes improves depth of identification for scMS, but high levels of carrier proteomes can have adverse effects on quantitative accuracy and precision.

Introduction: Ion mobility-mass spectrometry is an emerging technology in the clinical setting for high throughput and high confidence molecular characterization from complex biological samples. Ion mobility spectrometry can provide isomer separations on the basis of molecular structure, the ability of which is increasing through technological developments that afford enhanced resolving power. Integrating multiple separation dimensions, such as liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) provide dramatic enhancements in the mitigation of molecular interferences for high accuracy clinical measurements.

Areas covered: Multidimensional separations with LC-IM-MS provide better selectivity and sensitivity in molecular analysis. Mass spectrometry imaging of tissues to inform spatial molecular distribution is improved by complementary ion mobility analyses. Biomarker identification in surgical environments is enhanced by intraoperative biochemical analysis with mass spectrometry and holds promise for integration with ion mobility spectrometry. New prospects in high resolving power ion mobility are enhancing analysis capabilities, such as distinguishing isomeric compounds.

Expert opinion: Ion mobility-mass spectrometry holds many prospects for the field of isomer identification, molecular imaging, and intraoperative tumor margin delineation in clinical settings. These advantages are afforded while maintaining fast analysis times and subsequently high throughput. High resolving power ion mobility will enhance these advantages further, in particular for analyses requiring high confidence isobaric selectivity and detection.

Introduction: Acute leukemia results from a series of mutational events that alter cell growth and proliferation. Mutations result in protein changes that orchestrate growth alterations characteristic of leukemia. Proteomics is a methodology appropriate for study of protein changes found in leukemia. The high-throughput reverse phase protein array (RPPA) technology is particularly well-suited for the assessment of protein changes in samples derived from clinical trials.

Areas covered: This review discusses the technical, methodological, and analytical issues related to the successful development of acute leukemia RPPAs.

Expert commentary: To obtain representative protein sample lysates, samples should be prepared from freshly collected blood or bone marrow material. Variables such as sample shipment, transit time, and holding temperature only have minimal effects on protein expression. CellSave preservation tubes are preferred for cells collected after exposure to chemotherapy, and incorporation of standardized guidelines for antibody validation is recommended. A more systematic biological approach to analyze protein expression is desired, searching for recurrent patterns of protein expression that allow classification of patients into risk groups, or groups of patients that may be treated similarly. Comparing RPPA protein analysis between cell lines and primary samples shows that cell lines are not representative of patient proteomic patterns.

Introduction: Intrinsic disorder prediction field develops, assesses, and deploys computational predictors of disorder in protein sequences and constructs and disseminates databases of these predictions. Over 40 years of research resulted in the release of numerous resources.

Areas covered: We identify and briefly summarize the most comprehensive to date collection of over 100 disorder predictors. We focus on their predictive models, availability and predictive performance. We categorize and study them from a historical point of view to highlight informative trends.

Expert opinion: We find a consistent trend of improvements in predictive quality as newer and more advanced predictors are developed. The original focus on machine learning methods has shifted to meta-predictors in early 2010s, followed by a recent transition to deep learning. The use of deep learners will continue in foreseeable future given recent and convincing success of these methods. Moreover, a broad range of resources that facilitate convenient collection of accurate disorder predictions is available to users. They include web servers and standalone programs for disorder prediction, servers that combine prediction of disorder and disorder functions, and large databases of pre-computed predictions. We also point to the need to address the shortage of accurate methods that predict disordered binding regions.

Introduction: Data-independent acquisition (DIA) is an emerging technology for large-scale proteomic studies. DIA data analysis methods are evolving rapidly, and deep learning has cut a conspicuous figure in this field.

Areas covered: This review discusses and provides an overview of the deep learning methods that are used for DIA data analysis, including spectral library prediction, feature scoring, and statistical control in peptide-centric analysis, as well as de novo peptide sequencing. Literature searches were performed for articles, including preprints, up to December 2021 from PubMed, Scopus, and Web of Science databases.

Expert opinion: While spectral library prediction has broken through the limitation on proteome coverage of experimental libraries, the statistical burden due to the large query space is the remaining challenge of utilizing proteome-wide predicted libraries. Analysis of post-translational modifications is another promising direction of deep learning-based DIA methods.

Introduction: Arginine deimination (citrullination) is a post-translational modification catalyzed by a family of peptidyl arginine deiminase (PAD) enzymes. Cell-based functional studies and animal models have manifested the key role of PADs in various cardiovascular diseases (CVDs).

Area covered: This review summarizes the past 10 years of knowledge on the role of PADs in CVD pathogenesis. It focuses on the PAD functions and diverse citrullinated proteins in cardiovascular conditions like deep vein thrombosis, ischemia/reperfusion, and atherosclerosis. Identification of PAD isoforms and citrullinated targets are essential for directing diagnosis and clinical intervention. Finally, anti-citrullinated protein antibodies (ACPAs) are addressed as an independent risk factor for cardiovascular events.

Expert opinion: PAD is an unique family of enzymes that permanently converts amino acid arginine to amino acid citrulline in protein . Overexpression or increased activity of PAD has been observed in various CVDs with acute and chronic inflammation as the background. Importantly, far beyond being simply involved in forming neutrophil extracellular traps (NETs), accumulating evidence indicated PAD activation as a trigger for numerous processes, such as transcriptional regulation, endothelial dysfunction, and thrombus formation. In summary, the findings so far have testified the important role of deimination in cardiovascular biology, while more basic and translational studies are essential for further exploration.

Background: Ticks are obligate hematophagous arthropods that synthesize the glycan Galα1-3Galβ1-(3)4GlcNAc-R (α-Gal) associated with the alpha-gal syndrome (AGS) or allergy to mammalian meat consumption.

Research design and methods: In this study, we used a proteomics approach to characterize tick proteins in salivary glands (sialome SG), secreted saliva (sialome SA) and with α-Gal modification (alphagalactome SG and SA) in model tick species associated with the AGS in the United States (Amblyomma americanum) and Australia (Ixodes holocyclus). Selected proteins reactive to sera (IgE) from patients with AGS were identified to advance in the identification of possible proteins associated with the AGS. For comparative analysis, the α-Gal content was measured in various tick species.

Results: The results confirmed that ticks produce proteins with α-Gal modifications and secreted into saliva during feeding. Proteins identified in tick alphagalactome SA by sera from patients with severe AGS symptomatology may constitute candidate disease biomarkers.

Conclusions: The results support the presence of tick-derived proteins with α-Gal modifications in the saliva with potential implications in AGS and other disorders and protective capacity against tick infestations and pathogen infection. Future research should focus on the characterization of the function of tick glycoproteins with α-Gal in tick biology and AGS.