The Minimal Information about a Proteomics Experiment (MIAPE) from the Proteomics Standards Initiative

Intracellular proteomics and extracellular vesiculomics as a metric of disease recapitulation in 3D-bioprinted aortic valve arrays

In calcific aortic valve disease (CAVD), mechanosensitive valvular cells respond to fibrosis- and calcification-induced tissue stiffening, further driving pathophysiology. No pharmacotherapeutics are available to treat CAVD because of the paucity of (i) appropriate experimental models that recapitulate this complex environment and (ii) benchmarking novel engineered aortic valve (AV)-model performance. We established a biomaterial-based CAVD model mimicking the biomechanics of the human AV disease-prone fibrosa layer, three-dimensional (3D)-bioprinted into 96-well arrays. Liquid chromatography-tandem mass spectrometry analyses probed the cellular proteome and vesiculome to compare the 3D-bioprinted model versus traditional 2D monoculture, against human CAVD tissue. The 3D-bioprinted model highly recapitulated the CAVD cellular proteome (94% versus 70% of 2D proteins). Integration of cellular and vesicular datasets identified known and unknown proteins ubiquitous to AV calcification. This study explores how 2D versus 3D-bioengineered systems recapitulate unique aspects of human disease, positions multiomics as a technique for the evaluation of high throughput-based bioengineered model systems, and potentiates future drug discovery.

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

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

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

pISA-tree - a data management framework for life science research projects using a standardised directory tree

We developed pISA-tree, a straightforward and flexible data management solution for organisation of life science project-associated research data and metadata. pISA-tree was initiated by end-user requirements thus its strong points are practicality and low maintenance cost. It enables on-the-fly creation of enriched directory tree structure (project/Investigation/Study/Assay) based on the ISA model, in a standardised manner via consecutive batch files. Templates-based metadata is generated in parallel at each level enabling guided submission of experiment metadata. pISA-tree is complemented by two R packages, pisar and seekr. pisar facilitates integration of pISA-tree datasets into bioinformatic pipelines and generation of ISA-Tab exports. seekr enables synchronisation with the FAIRDOMHub repository. Applicability of pISA-tree was demonstrated in several national and international multi-partner projects. The system thus supports findable, accessible, interoperable and reusable (FAIR) research and is in accordance with the Open Science initiative. Source code and documentation of pISA-tree are available at https://github.com/NIB-SI/pISA-tree.

Enrichment of Newly Synthesized Proteins following treatment of C2C12 Myotubes with Endotoxin and Interferon-γ

Inflammation in muscle induces the synthesis of mediators that can impair protein synthesis and enhance proteolysis, and when sustained lead to muscle atrophy. Furthermore, muscle-derived mediators that are secreted may participate in disrupting the function of other peripheral organs. Selective identification of newly synthesized proteins can provide insight on biological processes that depend on the continued synthesis of specific proteins to maintain homeostasis as well as those proteins that are up- or down-regulated in response to inflammation. We used puromycin-associated nascent chain proteomics (PUNCH-P) to characterize new protein synthesis in C2C12 myotubes and changes resulting from their exposure to the inflammatory mediators lipopolysaccharide (LPS) and interferon (IFN)-γ for either a short (4 h) or prolonged (16 h) time period. We identified sequences of nascent polypeptide chains belonging to a total of 1523 proteins and report their detection from three independent samples of each condition at each time point. The identified nascent proteins correspond to approximately 15% of presently known proteins in C2C12 myotubes and are enriched in specific cellular components and pathways. A subset of these proteins was identified only in treated samples and has functional characteristics consistent with the synthesis of specific new proteins in response to LPS/IFNγ. Thus, the identification of proteins from their nascent polypeptide chains provides a resource to analyze the role of new synthesis of proteins in both protein homeostasis and in proteome responses to stimuli in C2C12 myotubes. Our results reveal a profile of actively translating proteins for specific cellular components and biological processes in normal C2C12 myotubes and a different enrichment of proteins in response to LPS/IFNγ. Collectively, our data disclose a highly interconnected network that integrates the regulation of cellular proteostasis and reveal a diverse immune response to inflammation in muscle which may underlie the concomitantly observed atrophy and be important in inter-organ communication.

Integrative omic and transgenic analyses reveal the positive effect of ultraviolet-B irradiation on salvianolic acid biosynthesis through upregulation of SmNAC1

Salvianolic acids (SalAs), a group of secondary metabolites in Salvia miltiorrhiza, are widely used for treating cerebrovascular diseases. Their biosynthesis is modulated by a variety of abiotic factors, including ultraviolet-B (UV-B) irradiation; however, the underlying mechanisms remain largely unknown. Here, an integrated metabolomic, proteomic, and transcriptomic approach coupled with transgenic analyses was employed to dissect the mechanisms underlying UV-B irradiation-induced SalA biosynthesis. Results of metabolomics showed that 28 metabolites, including 12 SalAs, were elevated in leaves of UV-B-treated S. miltiorrhiza. Meanwhile, the contents of several phytohormones, including jasmonic acid and salicylic acid, which positively modulate the biosynthesis of SalAs, also increased in UV-B-treated S. miltiorrhiza. Consistently, 20 core biosynthetic enzymes and numerous transcription factors that are involved in SalA biosynthesis were elevated in treated samples as indicated by a comprehensive proteomic analysis. Correlation and gene expression analyses demonstrated that the NAC1 gene, encoding a NAC transcriptional factor, was positively involved in UV-B-induced SalA biosynthesis. Accordingly, overexpression and RNA interference of NAC1 increased and decreased SalA contents, respectively, through regulation of key biosynthetic enzymes. Furthermore, ChIP-qPCR and Dual-LUC assays showed that NAC1 could directly bind to the CATGTG and CATGTC motifs present in the promoters of the SalA biosynthesis-related genes PAL3 and TAT3, respectively, and activate their expression. Our results collectively demonstrate that NAC1 plays a crucial role in UV-B irradiation-induced SalA biosynthesis. Taken together, our findings provide mechanistic insights into the UV-B-induced SalA biosynthesis in S. miltiorrhiza, and shed light on a great potential for the development of SalA-abundant varieties through genetic engineering.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

iProX: an integrated proteome resource

Sharing of research data in public repositories has become best practice in academia. With the accumulation of massive data, network bandwidth and storage requirements are rapidly increasing. The ProteomeXchange (PX) consortium implements a mode of centralized metadata and distributed raw data management, which promotes effective data sharing. To facilitate open access of proteome data worldwide, we have developed the integrated proteome resource iProX (http://www.iprox.org) as a public platform for collecting and sharing raw data, analysis results and metadata obtained from proteomics experiments. The iProX repository employs a web-based proteome data submission process and open sharing of mass spectrometry-based proteomics datasets. Also, it deploys extensive controlled vocabularies and ontologies to annotate proteomics datasets. Users can use a GUI to provide and access data through a fast Aspera-based transfer tool. iProX is a full member of the PX consortium; all released datasets are freely accessible to the public. iProX is based on a high availability architecture and has been deployed as part of the proteomics infrastructure of China, ensuring long-term and stable resource support. iProX will facilitate worldwide data analysis and sharing of proteomics experiments.

Crowd-Sourced Chemistry: Considerations for Building a Standardized Database to Improve Omic Analyses

Mass spectrometry (MS) is used in multiple omics disciplines to generate large collections of data. This data enables advancements in biomedical research by providing global profiles of a given system. One of the main barriers to generating these profiles is the inability to accurately annotate omics data, especially small molecules. To complement pre-existing large databases that are not quite complete, research groups devote efforts to generating personal libraries to annotate their data. Scientific progress is impeded during the generation of these personal libraries because the data contained within them is often redundant and/or incompatible with other databases. To overcome these redundancies and incompatibilities, we propose that communal, crowd-sourced databases be curated in a standardized fashion. A small number of groups have shown this model is feasible and successful. While the needs of a specific field will dictate the functionality of a communal database, we discuss some features to consider during database development. Special emphasis is made on standardization of terminology, documentation, format, reference materials, and quality assurance practices. These standardization procedures enable a field to have higher confidence in the quality of the data within a given database. We also discuss the three conceptual pillars of database design as well as how crowd-sourcing is practiced. Generating open-source databases requires front-end effort, but the result is a well curated, high quality data set that all can use. Having a resource such as this fosters collaboration and scientific advancement.

Pick a Tag and Explore the Functions of Your Pet Protein

Protein tags have been essential for advancing our knowledge of the function of proteins, their localization, and the mapping of their interaction partners. Expressing epitope-tagged proteins has become a standard practice in every life science laboratory and, thus, continues to enable new studies. In recent years, several new tagging moieties have entered the limelight, many of them bringing new functionalities, such as targeted protein degradation, accurate quantification, and proximity labeling. Other novel tags aim at tackling research questions in challenging niches. In this review, we elaborate on recently introduced tags and the opportunities they provide for future research endeavors. In addition, we highlight how the genome-engineering revolution may boost the field of protein tags.

Unveiling Human Cardiac Fibroblast Membrane Proteome

Cardiac fibroblasts (CFs) are one of the main cell populations in the heart and play important roles in tissue homeostasis and myocardial fibrosis. The study of these cells has been hampered by the lack of reliable membrane markers: none of the antigens currently used for characterization and isolation of CFs is unique for this cell type. This issue has also raised doubts regarding a distinct identity of cardiac fibroblasts when compared to other myocardium cell populations with similar morphologies. In this work, we report a comprehensive description and functional analysis of human CFs (hCFs) membraneenriched fraction proteome by advanced mass spectrometry-based proteomic tools. A total number of 1478 proteins were identified, including 774 membrane proteins (52%). We also report the identification of a subset of 30 membrane proteins that in this workflow were only identified in hCFs by comparison with the membrane-enriched proteome lists of human cardiac stem cells, human mesenchymal stem cells, and human dermal fibroblasts. The data reported in this work are a valuable source of information for further studies aiming at defining a membrane molecular signature of human cardiac fibroblasts (hCFs), and a step forward in research regarding membrane proteins with key roles in hCF function in homeostasis and disease.

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.

Methods for Optimizing CRISPR-Cas9 Genome Editing Specificity

Advances in the development of delivery, repair, and specificity strategies for the CRISPR-Cas9 genome engineering toolbox are helping researchers understand gene function with unprecedented precision and sensitivity. CRISPR-Cas9 also holds enormous therapeutic potential for the treatment of genetic disorders by directly correcting disease-causing mutations. Although the Cas9 protein has been shown to bind and cleave DNA at off-target sites, the field of Cas9 specificity is rapidly progressing, with marked improvements in guide RNA selection, protein and guide engineering, novel enzymes, and off-target detection methods. We review important challenges and breakthroughs in the field as a comprehensive practical guide to interested users of genome editing technologies, highlighting key tools and strategies for optimizing specificity. The genome editing community should now strive to standardize such methods for measuring and reporting off-target activity, while keeping in mind that the goal for specificity should be continued improvement and vigilance.

Review on proteomics for food authentication

Consumers have the right to know what is in the food they are eating. Accordingly, European and global food regulations require that the provenance of the food can be guaranteed from farm to fork. Many different instrumental techniques have been proposed for food authentication. Although traditional methods are still being used, new approaches such as genomics, proteomics, and metabolomics are helping to complement existing methodologies for verifying the claims made about certain food products. During the last decade, proteomics (the large-scale analysis of proteins in a particular biological system at a particular time) has been applied to different research areas within food technology. Since proteins can be used as markers for many properties of a food, even indicating processes to which the food has been subjected, they can provide further evidence of the foods labeling claim. This review is a comprehensive and updated overview of the applications, drawbacks, advantages, and challenges of proteomics for food authentication in the assessment of the foods compliance with labeling regulations and policies.

SIGNIFICANCE

This review paper provides a comprehensive and critical overview of the application of proteomics approaches to determine the authenticity of several food products updating the performances and current limitations of the applied techniques in both laboratory and industrial environments.

Quality control of antibodies for assay development

Antibodies are used as powerful tools in basic research, for example, in biomarker identification, and in various forms for diagnostics, for example, identification of allergies or autoimmune diseases. Due to their robustness and ease of handling, immunoassays are favourite methods for investigation of various biological or medical questions. Nevertheless in many cases, additional analyses such as mass spectrometry are used to validate or confirm the results of immunoassays. To minimize the workload and to increase confidence in immunoassays, there are urgent needs for antibodies which are both highly specific and well validated. Unfortunately many commercially available antibodies are neither well characterized nor fully tested for cross-reactivities. Adequate quality control and validation of an antibody is time-consuming and can be frustrating. Such validation needs to be performed for every assay/application. However, where an antibody validation is successful, a highly specific and stable reagent will be on hand. This article describes the validation processes of antibodies, including some often neglected factors, as well as unspecific binding to other sample compounds in a multiparameter diagnostic assay. The validation consists of different immunological methods, with important assay controls, and is performed in relation to the development of a diagnostic test.

SEEK: a systems biology data and model management platform

Background

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models.

There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them.

Results

The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data.

Conclusion

The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

Translating clinical proteomics: the importance of study design

Mass spectrometry-based clinical proteomics approaches were introduced into the biomedical field more than two decades ago. Despite recent developments both in the field of mass spectrometry and bioinformatics, the gap between proteomics results and their translation into clinical practice still needs to be closed, as implementation of proteomics results in the clinic appears to be scarce. An extra focus on the importance of the experimental design is therefore of crucial importance.

Development of data representation standards by the human proteome organization proteomics standards initiative

OBJECTIVE

To describe the goals of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization, the methods that the PSI has employed to create data standards, the resulting output of the PSI, lessons learned from the PSI's evolution, and future directions and synergies for the group.

MATERIALS AND METHODS

The PSI has 5 categories of deliverables that have guided the group. These are minimum information guidelines, data formats, controlled vocabularies, resources and software tools, and dissemination activities. These deliverables are produced via the leadership and working group organization of the initiative, driven by frequent workshops and ongoing communication within the working groups. Official standards are subjected to a rigorous document process that includes several levels of peer review prior to release.

RESULTS

We have produced and published minimum information guidelines describing what information should be provided when making data public, either via public repositories or other means. The PSI has produced a series of standard formats covering mass spectrometer input, mass spectrometer output, results of informatics analysis (both qualitative and quantitative analyses), reports of molecular interaction data, and gel electrophoresis analyses. We have produced controlled vocabularies that ensure that concepts are uniformly annotated in the formats and engaged in extensive software development and dissemination efforts so that the standards can efficiently be used by the community.Conclusion In its first dozen years of operation, the PSI has produced many standards that have accelerated the field of proteomics by facilitating data exchange and deposition to data repositories. We look to the future to continue developing standards for new proteomics technologies and workflows and mechanisms for integration with other omics data types. Our products facilitate the translation of genomics and proteomics findings to clinical and biological phenotypes. The PSI website can be accessed at http://www.psidev.info.

Quality assessment and optimization of purified protein samples: why and how?

Purified protein quality control is the final and critical check-point of any protein production process. Unfortunately, it is too often overlooked and performed hastily, resulting in irreproducible and misleading observations in downstream applications. In this review, we aim at proposing a simple-to-follow workflow based on an ensemble of widely available physico-chemical technologies, to assess sequentially the essential properties of any protein sample: purity and integrity, homogeneity and activity. Approaches are then suggested to optimize the homogeneity, time-stability and storage conditions of purified protein preparations, as well as methods to rapidly evaluate their reproducibility and lot-to-lot consistency.

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.