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

A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects

Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific ‘service provision units’ is introduced together with the factors influencing them and the main underlying assumptions for these ‘value influencing factors’. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared

A standardized framing for reporting protein identifications in mzIdentML 1.2

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software

Calibration and performance of the photon sensor response of FACT -- The First G-APD Cherenkov telescope

The First G-APD Cherenkov Telescope (FACT) is the first in-operation test of the performance of silicon photo detectors in Cherenkov Astronomy. For more than two years it is operated on La Palma, Canary Islands (Spain), for the purpose of long-term monitoring of astrophysical sources. For this, the performance of the photo detectors is crucial and therefore has been studied in great detail. Special care has been taken for their temperature and voltage dependence implementing a correction method to keep their properties stable. Several measurements have been carried out to monitor the performance. The measurements and their results are shown, demonstrating the stability of the gain below the percent level. The resulting stability of the whole system is discussed, nicely demonstrating that silicon photo detectors are perfectly suited for the usage in Cherenkov telescopes, especially for long-term monitoring purpose

FACT -- Operation of the First G-APD Cherenkov Telescope

Since more than two years, the First G-APD Cherenkov Telescope (FACT) is operating successfully at the Canary Island of La Palma. Apart from its purpose to serve as a monitoring facility for the brightest TeV blazars, it was built as a major step to establish solid state photon counters as detectors in Cherenkov astronomy. The camera of the First G-APD Cherenkov Telesope comprises 1440 Geiger-mode avalanche photo diodes (G-APD aka. MPPC or SiPM) for photon detection. Since properties as the gain of G-APDs depend on temperature and the applied voltage, a real-time feedback system has been developed and implemented. To correct for the change introduced by temperature, several sensors have been placed close to the photon detectors. Their read out is used to calculate a corresponding voltage offset. In addition to temperature changes, changing current introduces a voltage drop in the supporting resistor network. To correct changes in the voltage drop introduced by varying photon flux from the night-sky background, the current is measured and the voltage drop calculated. To check the stability of the G-APD properties, dark count spectra with high statistics have been taken under different environmental conditions and been evaluated. The maximum data rate delivered by the camera is about 240 MB/s. The recorded data, which can exceed 1 TB in a moonless night, is compressed in real-time with a proprietary loss-less algorithm. The performance is better than gzip by almost a factor of two in compression ratio and speed. In total, two to three CPU cores are needed for data taking. In parallel, a quick-look analysis of the recently recorded data is executed on a second machine. Its result is publicly available within a few minutes after the data were taken. [...]Comment: 19th IEEE Real-Time Conference, Nara, Japan (2014

FACT -- The G-APD revolution in Cherenkov astronomy

Since two years, the FACT telescope is operating on the Canary Island of La Palma. Apart from its purpose to serve as a monitoring facility for the brightest TeV blazars, it was built as a major step to establish solid state photon counters as detectors in Cherenkov astronomy. The camera of the First G-APD Cherenkov Telesope comprises 1440 Geiger-mode avalanche photo diodes (G-APD), equipped with solid light guides to increase the effective light collection area of each sensor. Since no sense-line is available, a special challenge is to keep the applied voltage stable although the current drawn by the G-APD depends on the flux of night-sky background photons significantly varying with ambient light conditions. Methods have been developed to keep the temperature and voltage dependent response of the G-APDs stable during operation. As a cross-check, dark count spectra with high statistics have been taken under different environmental conditions. In this presentation, the project, the developed methods and the experience from two years of operation of the first G-APD based camera in Cherenkov astronomy under changing environmental conditions will be presented.Comment: Proceedings of the Nuclear Science Symposium and Medical Imaging Conference (IEEE-NSS/MIC), 201

FACT - The First G-APD Cherenkov Telescope: Status and Results

The First G-APD Cherenkov telescope (FACT) is the first telescope using silicon photon detectors (G-APD aka. SiPM). It is built on the mount of the HEGRA CT3 telescope, still located at the Observatorio del Roque de los Muchachos, and it is successfully in operation since Oct. 2011. The use of Silicon devices promises a higher photon detection efficiency, more robustness and higher precision than photo-multiplier tubes. The FACT collaboration is investigating with which precision these devices can be operated on the long-term. Currently, the telescope is successfully operated from remote and robotic operation is under development. During the past months of operation, the foreseen monitoring program of the brightest known TeV blazars has been carried out, and first physics results have been obtained including a strong flare of Mrk501. An instantaneous flare alert system is already in a testing phase. This presentation will give an overview of the project and summarize its goals, status and first results

New insights into the protein aggregation pathology in myotilinopathy by combined proteomic and immunolocalization analyses

Introduction: Myofibrillar myopathies are characterized by progressive muscle weakness and impressive abnormal protein aggregation in muscle fibers. In about 10 % of patients, the disease is caused by mutations in the MYOT gene encoding myotilin. The aim of our study was to decipher the composition of protein deposits in myotilinopathy to get new information about aggregate pathology. Results: Skeletal muscle samples from 15 myotilinopathy patients were included in the study. Aggregate and control samples were collected from muscle sections by laser microdissection and subsequently analyzed by a highly sensitive proteomic approach that enables a relative protein quantification. In total 1002 different proteins were detected. Seventy-six proteins showed a significant over-representation in aggregate samples including 66 newly identified aggregate proteins. Z-disc-associated proteins were the most abundant aggregate components, followed by sarcolemmal and extracellular matrix proteins, proteins involved in protein quality control and degradation, and proteins with a function in actin dynamics or cytoskeletal transport. Forty over-represented proteins were evaluated by immunolocalization studies. These analyses validated our mass spectrometric data and revealed different regions of protein accumulation in abnormal muscle fibers. Comparison of data from our proteomic analysis in myotilinopathy with findings in other myofibrillar myopathy subtypes indicates a characteristic basic pattern of aggregate composition and resulted in identification of a highly sensitive and specific diagnostic marker for myotilinopathy. Conclusions: Our findings i) indicate that main protein components of aggregates belong to a network of interacting proteins, ii) provide new insights into the complex regulation of protein degradation in myotilinopathy that may be relevant for new treatment strategies, iii) imply a combination of a toxic gain-of-function leading to myotilin-positive protein aggregates and a loss-of-function caused by a shift in subcellular distribution with a deficiency of myotilin at Z-discs that impairs the integrity of myofibrils, and iv) demonstrate that proteomic analysis can be helpful in differential diagnosis of protein aggregate myopathies

New insights into the protein aggregation pathology in myotilinopathy by combined proteomic and immunolocalization analyses

Introduction: Myofibrillar myopathies are characterized by progressive muscle weakness and impressive abnormal protein aggregation in muscle fibers. In about 10 % of patients, the disease is caused by mutations in the MYOT gene encoding myotilin. The aim of our study was to decipher the composition of protein deposits in myotilinopathy to get new information about aggregate pathology. Results: Skeletal muscle samples from 15 myotilinopathy patients were included in the study. Aggregate and control samples were collected from muscle sections by laser microdissection and subsequently analyzed by a highly sensitive proteomic approach that enables a relative protein quantification. In total 1002 different proteins were detected. Seventy-six proteins showed a significant over-representation in aggregate samples including 66 newly identified aggregate proteins. Z-disc-associated proteins were the most abundant aggregate components, followed by sarcolemmal and extracellular matrix proteins, proteins involved in protein quality control and degradation, and proteins with a function in actin dynamics or cytoskeletal transport. Forty over-represented proteins were evaluated by immunolocalization studies. These analyses validated our mass spectrometric data and revealed different regions of protein accumulation in abnormal muscle fibers. Comparison of data from our proteomic analysis in myotilinopathy with findings in other myofibrillar myopathy subtypes indicates a characteristic basic pattern of aggregate composition and resulted in identification of a highly sensitive and specific diagnostic marker for myotilinopathy. Conclusions: Our findings i) indicate that main protein components of aggregates belong to a network of interacting proteins, ii) provide new insights into the complex regulation of protein degradation in myotilinopathy that may be relevant for new treatment strategies, iii) imply a combination of a toxic gain-of-function leading to myotilin-positive protein aggregates and a loss-of-function caused by a shift in subcellular distribution with a deficiency of myotilin at Z-discs that impairs the integrity of myofibrils, and iv) demonstrate that proteomic analysis can be helpful in differential diagnosis of protein aggregate myopathies

The PRIDE database and related tools and resources in 2019: improving support for quantification data

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas