Next generation single-molecule techniques: Imaging, labeling, and manipulation in vitro and in cellulo.

Owing to their unique abilities to manipulate, label, and image individual molecules in vitro and in cellulo, single-molecule techniques provide previously unattainable access to elementary biological processes. In imaging, single-molecule fluorescence resonance energy transfer (smFRET) and protein-induced fluorescence enhancement in vitro can report on conformational changes and molecular interactions, single-molecule pull-down (SiMPull) can capture and analyze the composition and function of native protein complexes, and single-molecule tracking (SMT) in live cells reveals cellular structures and dynamics. In labeling, the abilities to specifically label genomic loci, mRNA, and nascent polypeptides in cells have uncovered chromosome organization and dynamics, transcription and translation dynamics, and gene expression regulation. In manipulation, optical tweezers, integration of single-molecule fluorescence with force measurements, and single-molecule force probes in live cells have transformed our mechanistic understanding of diverse biological processes, ranging from protein folding, nucleic acids-protein interactions to cell surface receptor function.

Current progress in clinical, molecular, and genetic aspects of adult fibromuscular dysplasia.

Fibromuscular dysplasia (FMD) is a non-atherosclerotic vascular disease that may involve medium-sized muscular arteries throughout the body. The majority of FMD patients are women. Although a variety of genetic, mechanical, and hormonal factors play a role in the pathogenesis of FMD, overall, its cause remains poorly understood. It is probable that the pathogenesis of FMD is linked to a combination of genetic and environmental factors. Extensive studies have correlated the arterial lesions of FMD to histopathological findings of arterial fibrosis, cellular hyperplasia, and distortion of the abnormal architecture of the arterial wall. More recently, the vascular phenotype of lesions associated with FMD has been expanded to include arterial aneurysms, dissections, and tortuosity. However, in the absence of a string-of-beads or focal stenosis, these lesions do not suffice to establish the diagnosis. While FMD most commonly involves renal and cerebrovascular arteries, involvement of most arteries throughout the body has been reported. Increasing evidence highlights that FMD is a systemic arterial disease and that subclinical alterations can be found in non-affected arterial segments. Recent significant progress in FMD-related research has led to improve our understanding of the disease's clinical manifestations, natural history, epidemiology, and genetics. Ongoing work continues to focus on FMD genetics and proteomics, physiological effects of FMD on cardiovascular structure and function, and novel imaging modalities and blood-based biomarkers that can be used to identify subclinical FMD. It is also hoped that the next decade will bring the development of multi-centred and potentially international clinical trials to provide comparative effectiveness data to inform the optimal management of patients with FMD.

Recent Advances in Developmental Hematopoiesis: Diving Deeper With New Technologies.

The journey of a hematopoietic stem cell (HSC) involves the passage through successive anatomical sites where HSCs are in direct contact with their surrounding microenvironment, also known as niche. These spatial and temporal cellular interactions throughout development are required for the acquisition of stem cell properties, and for maintaining the HSC pool through balancing self-renewal, quiescence and lineage commitment. Understanding the context and consequences of these interactions will be imperative for our understanding of HSC biology and will lead to the improvement of in vitro production of HSCs for clinical purposes. The aorta-gonad-mesonephros (AGM) region is in this light of particular interest since this is the cradle of HSC emergence during the embryonic development of all vertebrate species. In this review, we will focus on the developmental origin of HSCs and will discuss the novel technological approaches and recent progress made to identify the cellular composition of the HSC supportive niche and the underlying molecular events occurring in the AGM region.

Top Trends in Multiomics Research: Evaluation of 52 Published Studies and New Ways of Thinking Terminology and Visual Displays.

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Could protein content of Urinary Extracellular Vesicles be useful to detect Cirrhosis in Alcoholic Liver Disease?

Alcohol abuse has a high impact on the mortality and morbidity related to a great number of diseases and is responsible for the development of alcoholic liver disease (ALD). It remains challenging to detect and evaluate its severity, which is crucial for prognosis. In this work, we studied if urinary EVs (uEVs) could serve in diagnose and evaluate cirrhosis in ALD. To this purpose, uEVs characterization by cryo-electron microscopy (Cryo-EM), Nanoparticle Tracking Analysis (NTA) and Western blotting (WB) was performed in a cohort of 21 controls and 21 cirrhotic patients. Then, proteomics of uEVs was carried out in a second cohort of 6 controls and 8 patients in order to identify new putative biomarkers for cirrhosis in ALD. Interestingly, uEVs concentration, size and protein composition were altered in cirrhotic patients. From a total of 1304 proteins identified in uEVs, 90 of them were found to be altered in cirrhotic patients. The results suggest that uEVs could be considered as a tool and a supplier of new biomarkers for cirrhosis in ALD, whose application would be especially relevant in chronic patients. Yet, further research is necessary to obtain more relevant result in clinical terms.

MS-based proteomics for comprehensive investigation of protein O-GlcNAcylation.

Protein O-GlcNAcylation refers to the covalent binding of a single N-acetylglucosamine (GlcNAc) to the serine or threonine residue. This modification primarily occurs on proteins in the nucleus and the cytosol, and plays critical roles in many cellular events, including regulation of gene expression and signal transduction. Aberrant protein O-GlcNAcylation is directly related to human diseases such as cancers, diabetes and neurodegenerative diseases. In the past decades, considerable progress has been made for global and site-specific analysis of O-GlcNAcylation in complex biological samples using mass spectrometry (MS)-based proteomics. In this review, we summarized previous efforts on comprehensive investigation of protein O-GlcNAcylation by MS. Specifically, the review is focused on methods for enriching and site-specifically mapping O-GlcNAcylated peptides, and applications for quantifying protein O-GlcNAcylation in different biological systems. As O-GlcNAcylation is an important protein modification for cell survival, effective methods are essential for advancing our understanding of glycoprotein functions and cellular events.

Reimagining high-throughput profiling of reactive cysteines for cell-based screening of large electrophile libraries.

Current methods used for measuring amino acid side-chain reactivity lack the throughput needed to screen large chemical libraries for interactions across the proteome. Here we redesigned the workflow for activity-based protein profiling of reactive cysteine residues by using a smaller desthiobiotin-based probe, sample multiplexing, reduced protein starting amounts and software to boost data acquisition in real time on the mass spectrometer. Our method, streamlined cysteine activity-based protein profiling (SLC-ABPP), achieved a 42-fold improvement in sample throughput, corresponding to profiling library members at a depth of >8,000 reactive cysteine sites at 18 min per compound. We applied it to identify proteome-wide targets of covalent inhibitors to mutant Kirsten rat sarcoma (KRAS)G12C and Bruton's tyrosine kinase (BTK). In addition, we created a resource of cysteine reactivity to 285 electrophiles in three human cell lines, which includes >20,000 cysteines from >6,000 proteins per line. The goal of proteome-wide profiling of cysteine reactivity across thousand-member libraries under several cellular contexts is now within reach.

Quantitative and targeted proteomics-based identification and validation of drug efficacy biomarkers.

Proteomics refers to the large-scale study of proteins, providing comprehensive and quantitative information on proteins in tissue, blood, and cell samples. In many studies, proteomics utilizes liquid chromatography-mass spectrometry. Proteomics has developed from a qualitative methodology of protein identification to a quantitative methodology for comparing protein expression, and it is currently classified into two distinct methodologies: quantitative and targeted proteomics. Quantitative proteomics comprehensively identifies proteins in samples, providing quantitative information on large-scale comparative profiles of protein expression. Targeted proteomics simultaneously quantifies only target proteins with high sensitivity and specificity. Therefore, in biomarker research, quantitative proteomics is used for the identification of biomarker candidates, and targeted proteomics is used for the validation of biomarkers. Understanding the specific characteristics of each method is important for conducting appropriate proteomics studies. In this review, we introduced the different characteristics and applications of quantitative and targeted proteomics, and then discussed the results of our recent proteomics studies that focused on the identification and validation of biomarkers of drug efficacy. These findings may enable us to predict the outcomes of cancer therapy and drug-drug interactions with antibiotics through changes in the intestinal microbiome.

The future is now? Clinical and translational aspects of "Omics" technologies.

Big data has become a central part of medical research, as well as modern life generally. "Omics" technologies include genomics, proteomics, microbiomics and increasingly other omics. These have been driven by rapid advances in laboratory techniques and equipment. Crucially, improved information handling capabilities have allowed concepts such as artificial intelligence and machine learning to enter the research world. The COVID-19 pandemic has shown how quickly information can be generated and analyzed using such approaches, but also showed its limitations. This review will look at how "omics" has begun to be translated into clinical practice. While there appears almost limitless potential in using big data for "precision" or "personalized" medicine, the reality is that this remains largely aspirational. Oncology is the only field of medicine that is widely adopting such technologies, and even in this field uptake is irregular. There are practical and ethical reasons for this lack of translation of increasingly affordable techniques into the clinic. Undoubtedly, there will be increasing use of large data sets from traditional (e.g. tumor samples, patient genomics) and nontraditional (e.g. smartphone) sources. It is perhaps the greatest challenge of the health-care sector over the coming decade to integrate these resources in an effective, practical and ethical way.

Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy.

Advances in molecular biology, microfluidics and bioinformatics have empowered the study of thousands or even millions of individual cells from malignant tumours at the single-cell level of resolution. This high-dimensional, multi-faceted characterization of the genomic, transcriptomic, epigenomic and proteomic features of the tumour and/or the associated immune and stromal cells enables the dissection of tumour heterogeneity, the complex interactions between tumour cells and their microenvironment, and the details of the evolutionary trajectory of each tumour. Single-cell transcriptomics, the ability to track individual T cell clones through paired sequencing of the T cell receptor genes and high-dimensional single-cell spatial analysis are all areas of particular relevance to immuno-oncology. Multidimensional biomarker signatures will increasingly be crucial to guiding clinical decision-making in each patient with cancer. High-dimensional single-cell technologies are likely to provide the resolution and richness of data required to generate such clinically relevant signatures in immuno-oncology. In this Perspective, we describe advances made using transformative single-cell analysis technologies, especially in relation to clinical response and resistance to immunotherapy, and discuss the growing utility of single-cell approaches for answering important research questions.

Proteomic changes in intracranial blood during human ischemic stroke.

BACKGROUND: Since 2015, mechanical thrombectomy has been the standard treatment for emergent large vessel occlusion ischemic stroke. OBJECTIVE: To investigate, using the previously published Blood and Clot Thrombectomy Registry and Collaboration (BACTRAC) protocol (clinicaltrials.gov NCT03153683), how the protein expression of a patient's intracranial blood during ischemic stroke compares with the protein expression of their systemic arterial blood in order to better understand and treat stroke. METHODS: Plasma samples from 25 subjects underwent proteomic analysis, where intracranial protein expression was compared with systemic protein levels. Data including sex, comorbidities, infarct volume, and infarct time were included for each subject. RESULTS: A majority of important proteins had a lower expression in intracranial blood than in systemic arterial blood. Proteins with the most significant changes in expression were: endopeptidase at -0.26 (p<0.0001), phospholipid transfer protein (PLTP) at -0.26 (p=0.0005), uromodulin (UMOD) at -0.14 (p=0.002), ficolin-2 (FCN2) at -0.46 (p=0.005), C-C motif chemokine 19 (CCL19) at -0.51 (p<0.0001), C-C motif chemokine 20 (CCL20) at -0.40 (p<0.0001), fibroblast growth factor 21 at -0.37 (p=0.0002), and C-C motif chemokine (CCL23) at -0.43 (p=0.0003). CONCLUSIONS: Evaluation of proteomic changes in the intravascular space of a cerebral infarct in progress in human subjects suggested that changes in proteins such PLTP, fetuin-B (FETUB), and FCN2 may be involved in atherosclerotic changes, and chemokines such as CCL23 are known to play a role in the Th2 autoimmune response. These data provide a scientific springboard for identifying clinically relevant biomarkers for diagnosis/prognosis, and targets for much needed neuroprotective/neuroreparative pharmacotherapies.

Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis.

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer, diabetes, cardiomyopathy, and COVID-19. With a progressive interpretation of the clinical, molecular, and genomic factors at play in diseases, more effective and personalized medical treatments are anticipated for many disorders. Understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic, and predictive biomarkers and paths ultimately providing optimal and personalized care for diverse, and targeted chronic and acute diseases. In clinical settings, we need to timely model clinical and multi-omics data to find statistical patterns across millions of features to identify underlying biologic pathways, modifiable risk factors, and actionable information that support early detection and prevention of complex disorders, and development of new therapies for better patient care. It is important to calculate quantitative phenotype measurements, evaluate variants in unique genes and interpret using ACMG guidelines, find frequency of pathogenic and likely pathogenic variants without disease indicators, and observe autosomal recessive carriers with a phenotype manifestation in metabolome. Next, ensuring security to reconcile noise, we need to build and train machine-learning prognostic models to meaningfully process multisource heterogeneous data to identify high-risk rare variants and make medically relevant predictions. The goal, today, is to facilitate implementation of mainstream precision medicine to improve the traditional symptom-driven practice of medicine, and allow earlier interventions using predictive diagnostics and tailoring better-personalized treatments. We strongly recommend automated implementation of cutting-edge technologies, utilizing machine learning (ML) and artificial intelligence (AI) approaches for the multimodal data aggregation, multifactor examination, development of knowledgebase of clinical predictors for decision support, and best strategies for dealing with relevant ethical issues.

Protein amino-termini and how to identify them.

INTRODUCTION: The N-terminus of a protein can encode several protein features, including its half-live and its localization. As the proteomics field remains dominated by bottom-up approaches and as N-terminal peptides only account for a fraction of all analyzable peptides, there is a need for their enrichment prior to analysis. COFRADIC, TAILS, and the subtiligase method were among the first N-terminomics methods developed, and several variants and novel methods were introduced that often reduce processing time and/or the amount of material required. AREAS COVERED: We present an overview of how the field of N-terminomics developed, including a discussion of the founding methods, several updates made to these and introduce newer methods such as TMPP-labeling, biotin-based methods besides some necessary improvements in data analysis. EXPERT OPINION: N-terminomic methods remain being used and improved methods are published however, more efficient use of contemporary mass spectrometers, promising data-independent approaches, and mass spectrometry-free single peptide or protein sequences may threat the N-terminomics field.

The development and clinical applications of proteomics: an Indian perspective.

INTRODUCTION: Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic. AREAS COVERED: This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed. EXPERT OPINION: The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Power of proteomics and progress in precision medicine - 13th central and eastern European proteomic conference (CEEPC), Ustron, Poland.

INTRODUCTION: Central and Eastern European Proteomic Conference (CEEPC) provides a platform for researchers to discuss multi-disciplinary integrated approaches to address a range of challenges from present day viral pandemic to on-going progress in Precision Medicine. CEEPC brings together various multi-omics entwined with novel enabling technologies, thus facilitating conceptual advances from cell to society for the benefit of mankind. AREAS COVERED: Proteomic methodologies, databases and software has revolutionized our ability to assess protein interactions and cellular changes, allowing the establishment of biological connections and identification of important cellular regulatory proteins and pathways previously unknown or not fully understood. Additionally, Mass spectrometry (MS) remains a major driving force in the field of 'multi-omics' and a powerful technology for the structural characterization of biomolecules and for analysis of proteins and small molecules such as lipids, sugars and metabolites. Combination of measurements from proteomics, genomics, epigenomics, transcriptomics and metabolomics, present a powerful decision-making format allowing deeper interpretation of a disease scenario in Precision medicine. EXPERT COMMENTARY: Precision Medicine offers novel and promising ways to identify and treat a wide range of diseases. The future success of these therapies will be underpinned by novel proteo-genomic approaches linked to sophisticated databases to evaluate and predict drug-patient interactions.

OMICS insights into cancer histology; Metabolomics and proteomics approach.

Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.

Targeted and Untargeted Proteomics Approaches in Biomarker Development.

An enormous amount of research effort has been devoted to biomarker discovery and validation. With the completion of the human genome, proteomics is now playing an increasing role in this search for new and better biomarkers. Here, what leads to successful biomarker development is reviewed and how these features may be applied in the context of proteomic biomarker research is considered. The "fit-for-purpose" approach to biomarker development suggests that untargeted proteomic approaches may be better suited for early stages of biomarker discovery, while targeted approaches are preferred for validation and implementation. A systematic screening of published biomarker articles using MS-based proteomics reveals that while both targeted and untargeted technologies are used in proteomic biomarker development, most researchers do not combine these approaches. i) The reasons for this discrepancy, (ii) how proteomic technologies can overcome technical challenges that seem to limit their translation into the clinic, and (iii) how MS can improve, complement, or replace existing clinically important assays in the future are discussed.

[Analysis of metabolomics and proteomics based on capillary electrophoresis-mass spectrometry].

Capillary electrophoresis-mass spectrometry (CE-MS) has the advantages of higher sensitivity, higher efficiency, and less sample consumption. Moreover, it possesses obvious advantages during the analysis of strongly charged and highly polar samples. CE-MS has been widely applied in life sciences, medicine, and pharmacology. In the past ten years, the main factors affecting its application were system stability, reproducibility, and data accuracy. In order to solve the existing problems of CE-MS, researchers have invested significant effort in technology innovation to further expand CE-MS application. In the fields of medicine and analytical chemistry, substantial research indicates that CE-MS is superior compared to other metabolomic and proteomic approaches. This study aims at reviewing the latest methods and applications developed in the fields of medicine and analytical chemistry since 2015. Furthermore, it also aims at enhancing the technology development-related application value of CE-MS and serving as a reference for future development. Further development of the CE-MS technology is discussed from the aspects of coating-sample interaction, interface types, and data processing methods. Concerning the coating types, neutral coatings had been applied extensively in CE-MS and there should be no limitation to the charge of the analyte. The coating decreased sample adsorption on the inner wall by covering the surface charge, greatly reducing the electroosmotic flow (EOF). A charged capillary coating could modify such an EOF direction. The cationic coating could reduce the hydrophobic interaction between the sample and the capillary column, resulting in higher EOF. If it is applied to the sheathless interface, the resolution could be improved by extending the capillary length. Anionic coatings are predominant among the anionic compounds, shortening the separation time by reducing the interaction between the anionic compounds and the capillary. The coating type should be chosen relative to the analyte characteristics. Concerning the interface technology, all interfaces should be simple, practical, and non-dependent on sheath liquid and background electrolytes. As far as data processing methods are concerned, it is necessary to design and develop a practical method for span space data comparison and processing. The optimized experimental conditions have effectively improved separation efficiency and data comparison analysis. Furthermore, they established a solid foundation for its application development. CE-MS analysis of complex samples in the fields of metabolomics and proteomics (e. g., of tissues, cells, body fluids, etc.) could provide a visualization method for future clinical analysis. It contributes to the development of cancer pathological analysis, drug development, disease surveillance, etc. The characteristic analysis of small molecule metabolites and protein biomarkers directly reflects on enzymatic activity in the biological systems. It could be associated with the development of various diseases/complications. Omics analysis also has an important directive to disease detection and surveillance with obvious advantages in disease diagnosis, staged treatment, drug development, and patient treatment progress. CE-MS is useful in detecting complications and promoting personalized medicine. It provides technical support for future clinical developments. In addition to a comprehensive review of the recent advances of CE-MS research, this paper also indicates the development directions of CE-MS. In order to avoid the problem of omics analysis and obtain the optimized analysis results, future analysis should be improved from the following three aspects:(i) The analysis conditions should be optimized concerning sample preparation methods and separation techniques. (ii) The analytic techniques should be supported to adjust to capillary coating and interface technology. (iii) New ideas should be developed in the fields of clinical research and statistical analysis.