Targeted proteomics reveals compositional dynamics of 60S pre‐ribosomes after nuclear export

Construction and intracellular targeting of eukaryotic pre-ribosomal particles involve a multitude of diverse transiently associating trans-acting assembly factors, energy-consuming enzymes, and transport factors. The ability to rapidly and reliably measure co-enrichment of multiple factors with maturing pre-ribosomal particles presents a major biochemical bottleneck towards revealing their function and the precise contribution of >50 energy-consuming steps that drive ribosome assembly. Here, we devised a workflow that combines genetic trapping, affinity-capture, and selected reaction monitoring mass spectrometry (SRM-MS), to overcome this deficiency. We exploited this approach to interrogate the dynamic proteome of pre-60S particles after nuclear export. We uncovered assembly factors that travel with pre-60S particles to the cytoplasm, where they are released before initiating translation. Notably, we identified a novel shuttling factor that facilitates nuclear export of pre-60S particles. Capturing and quantitating protein interaction networks of trapped intermediates of macromolecular complexes by our workflow is a reliable discovery tool to unveil dynamic processes that contribute to their in vivo assembly and transport

Calreticulin mutations affect its chaperone function and perturb the glycoproteome

Calreticulin (CALR) is an endoplasmic reticulum (ER)-retained chaperone that assists glycoproteins in obtaining their structure. CALR mutations occur in patients with myeloproliferative neoplasms (MPNs), and the ER retention of CALR mutants (CALR MUT) is reduced due to a lacking KDEL sequence. Here, we investigate the impact of CALR mutations on protein structure and protein levels in MPNs by subjecting primary patient samples and CALR-mutated cell lines to limited proteolysis-coupled mass spectrometry (LiP-MS). Especially glycoproteins are differentially expressed and undergo profound structural alterations in granulocytes and cell lines with homozygous, but not with heterozygous, CALR mutations. Furthermore, homozygous CALR mutations and loss of CALR equally perturb glycoprotein integrity, suggesting that loss-of-function attributes of mutated CALR chaperones (CALR MUT) lead to glycoprotein maturation defects. Finally, by investigating the misfolding of the CALR glycoprotein client myeloperoxidase (MPO), we provide molecular proof of protein misfolding in the presence of homozygous CALR mutations. Keywords: CP: Cancer; CP: Molecular biology; calreticulin; chaperone; glycoprotein; limited proteolysis-coupled mass spectrometry; myeloperoxidase; myeloproliferative neoplasm; protein folding; proteome

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.</p> <p>Result</p> <p>We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.</p> <p>This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.</p> <p>Conclusions</p> <p>Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in <url>http://tools.proteomecenter.org/ATAQS/ATAQS.html</url></p

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Biology/Disease-Driven Initiative on Protein-Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date

The Biology/Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support specific biological or disease-related research areas. Here, we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intra- or extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson’s and Alzheimer’s disease and systemic amyloidosis. The PAD B/D working group aims for the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Because the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein-extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in the systemic and localized amyloidosis and the probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by nonspecialized laboratories, and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group support the transfer to clinical practice of the developed methods, such as assays to quantify specific disease-related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more-confident subtyping

mProphet: automated data processing and statistical validation for large-scale SRM experiments

Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model