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neXtProt has announced in their February 2016 release that its metrics for assigning proteins as protein evidence 1 (PE1) as part of the Human Proteome Project now align with those proposed by PeptideAtlas in September 2015.
Our collaborators at neXtProt state:
Entries whose protein(s) existence is based on evidence at the transcript level (PE2), homology (PE3) or a prediction (gene model; PE4) were previously upgraded to evidence at the protein level (PE1) if the entry had (i) 2 proteotypic peptides 7 or 8 amino acids in length or (ii) 1 peptide at least 9 aa coming from mass spectrometry experiments in neXtProt. This rule has been made more stringent so as to be in sync with the PeptideAtlas/HPP criteria for validating proteins using mass spectrometry data (i.e., at least 2 proteotypic peptides 9 aa in length or more which differ in at least 1 amino acid and which are not overlapping) are now required for the protein evidence to be upgraded to PE1.
For more details click here.
Watch the video HERE.
This video provides a glimpse at the fascinating world of proteomics research, the study of all proteins that form the basis for life.
The video was produced for the lab of prof. dr. Albert Heck at Utrecht University and the Netherlands Proteomics Centre.
Q&A: Mike Snyder on Data-Driven Personalized Medicine for All, Stanford’s iPOP Study
Snyder’s new book, “Genomics and Personalized Medicine,” serves as a primer for patients and doctors, touching on topics from tailored cancer therapy to wearable devices.
News in Science | HUPOST Vol. 6, Q1 Feb 2016
Kay-Hooi Khoo, Academia Sinica, Taiwan
Among the post-translational modifications, mass spectrometry (MS) analysis of protein glycosylation remains the most challenging due to the diversity in glycosylation. However, the glyco-savvy proteomic community continues to report major technical advances in all aspects of glycomics and glycoproteomics, from sample preparation, data acquisition to informatics associated with data analysis. It is particularly welcoming to see an increasing awareness and readiness to tackle analysis of intact N-glycopeptides instead of only defining the occupied N-glycosylation sites by the easier route of analyzing the de-N-glycosylated peptides. In general, the few key enabling steps in any MS-based glycoproteomic attempt to map the site-specific glycosylation pattern include 1) enrichment of the glycopeptides; 2) construction of glycan and glycosite-containing peptide library or database to allow identification of the intact glycopeptides by any of the currently available search algorithm; 3) generation of sufficiently good quality glycopeptide MS/MS data in the first place, which usually requires the presence of peptide core fragment ions, peptide core+HexNAc or the Y1 ion, and high resolution/accurate mass MS1 data of the glycopeptide precursors.
The main innovation introduced by Hui Zhang’s group at Johns Hopkins University in a recent work published in the Jan 2016 issue of Nature Biotechnology is the way the N-glycan and N-glycosite containing peptide database was generated. Most other groups resorted to identifying as many of the PNGaseF-de-N-glycosylated peptides from analysis of a separate aliquot of the enriched glycopeptide fractions and use a publicly available glycan library such as the GlycomeDB, or the default library option available in commercial software such as Byonic. The authors took a different approach by modifying their long established hydrazide chemistry-based glycopeptide-specific capture method. Solid phase immobilization was accomplished non-selectively instead by conjugation to aldehyde-functionalized solid support via reaction with the N-termini of all tryptic peptides and, after de-N-glycosylation by PNGase F, Asp-N was used to selectively cleave and release only glycosite-containing peptides with Asp at at the initially N-glycosylated Asn site. Thus only peptides carrying N-glycosites will be selectively recovered and identified. This is a very clever approach although many chemistry modification steps are involved including modifying sequentially the e-amino group of Lys and free carboxylic groups of C-termini, Asp, Glu and sialic acids. The result is quite impressive and the authors showed that it led to many more N-glycosite-containing peptides identified. The authors also went on to profile the released glycans in order to construct their own sample-specific glycan library. This was performed by both MALDI- and LC-MS and facilitated by the sialic acids now being modified by aniline. For actual analysis of the intact glycopeptides, HILIC enriched glycopeptides were subjected to LC-HCD MS/MS on a Q-Exactive instrument and the resulting spectra searched against the custom derived database using the precursor mass-matching option of their in-house developed GPQuest software. With filtering based on the presence of peptide+HexNAc and/or peptide ions, as well as ≥7 observed b and y ions (1% FDR), this resulted in positive assignment of 4,562 oxonium ion-containing spectra to 1,562 unique glycopeptides containing 518 glycosites and 81 glycans from OVCAR-3 cells.
Key steps in solid phase extraction of N-glycans and N-glycosite containing peptides.Image adapted by Dr. Kay-Hooi Khoo, Academia Sinica, Taiwan
Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides (2016) Sun S, Shah P, Eshghi ST, Yang W, Trikannad N, Yang S, Chen L, Aiyetan P, Hoti N, Zhang Z, Chan DW and Zhang H. Nat Biotechnol. 34, 84-88.
Wishing you all Merry Christmas and Happy New Year-2016!
It brings us great pleasure to announce that the Targeted Proteomics Workshop and International Symposium (TPWIS-2015) followed by GIAN proteomics course ended on a high note. Overall 7 parallel events were conducted at IIT Bombay during 10th – 19th Dec 2015 for the unique set of participants in each event.
We take this opportunity to thank all the distinguished speakers and invited guests for providing their valuable perspectives to the audience. This ambitious effort of organising dedicated workshops and symposium heavily benefitted large numbers of participants. We wish to extend our appreciation to all delegates for their active participation in this multi-faceted event.
Event photographs are now available online: http://www.bio.iitb.ac.in/~sanjeeva/itpws/award-winners/
We are humbled by the support you all have provided us and made it a very stimulating, enjoyable and one of the very unique international events of 2015. We hope that TPWIS-2015 has been as memorable to you, as it has been for us. The attached “Reflections” booklet (click here: TPWIS-2015_Reflections) is a memoir of the TPWIS-2015 and we wish that these remembrances and experience would last you a lifetime.
Dr. Sanjeeva Srivastava
The HPP aims to hold participants and authors to rigorous standards for publication and dissemination of results. All data are to be submitted to a ProteomeXchange public data repository, statistical analyses are to be performed to a high standard, and extraordinary claims of detection of “missing proteins” or novel coding elements require extraordinary evidence. The first set of guidelines was approved in 2012. Version 2.0.1 of the guidelines was approved in December 1, 2015. The newest guidelines should be applied to all contributions.
HPP Data Interpretation Guidelines version 2.0.1 (approved 2015-12-1):
The current version of HPP Data Interpretation Guidelines is version 2.0.1. Please apply these guidelines to all new HPP contributions. If errors are detected or slight amendments are made, the updated guidelines will be posted here. Therefore, please check back in this location for a final version before submitting your manuscript. A filled out checklist must be submitted with the manuscript for inspection by the editors and reviewers. Any non-adherence to the guidelines must be explained in the space provided on the form.
Important Note: If your manuscript is being submitted to JPR for the HPP special issue, the JPR guidelines also apply. In cases where the JPR guidelines and these HPP guidelines conflict, the HPP guidelines are more stringent in all cases and take precedence over the JPR guidelines. See the Current JPR Guidelines.
2012 Guidelines (deprecated): The 2012 HPP Guidelines were in effect for 3 years and are still mentioned here, but are now considered obsolete. Please apply the current guidelines to efforts for new contributions.
STOCKHOLM, Sweden – 16 October, 2015
The Human Protein Atlas today launched a new version of the database. The major new additions to version 14 are a new Mouse Brain Atlas and a new approach for antibody validation.
The Human Protein Atlas, a major multinational research project supported by the Knut and Alice Wallenberg Foundation, today launched a new version of the database. Since the release of version 13 at end of 2014, new data has been added and the atlas now holds data on more than 25 000 antibodies, covering over 17 000 of the human genes (approximately 86% of the human genome). Focus for this release has been to improve validation of the antibodies used to map the human proteome and the inclusion a new atlas; the Mouse Brain Atlas, created by the Fluorescence Tissue Profiling facility at Science for Life Laboratory (SciLifeLab) in Stockholm.
The current version of the human protein atlas holds a comprehensive map of protein expression patterns in normal human tissues down to the single cell level. To assure the correct interpretation of the data, the RNA-seq data from transcriptomics has been evaluated against the gene/protein characterization data retrieved from antibody-based methods; antibody reliability, sub-optimal experimental procedures, and potential cross-reactivity has been assessed. The result of the extensive evaluation is summarized in a data reliability description. Currently, almost 7500 genes have been updated with this knowledge-based annotation. In addition to this, co-localization of a fluorescent protein with the target protein has been introduced for antibody characterization, and complements the previously introduced gene silencing (siRNA) technique. In total, 104 genes have been analyzed using co-localization, 256 genes have been silenced and analyzed using immunocytochemistry, and 190 genes have been silenced and analyzed using western blot.
Many of the mouse proteins have extensive homology with the human counterpart and this forms the basis for using the mouse brain as a model for the corresponding human brain to explore the expression and distribution of proteins in the various regions and cells of the brain. The new Mouse Brain Atlas, introduced in this version, includes additional brain regions and has additional information on cellular and sub cellular distribution of proteins in the brain. Currently, 88 genes and 129 brain regions are covered in the Mouse Brain Atlas.
“We believe this antibody-based data set is a valuable complement to our own human protein atlas and other international efforts that map the building-blocks of the brain, such as the Allen Brain Atlas and the Gensat effort.” says Dr Jan Mulder, head of the Mouse Brain Atlas effort at SciLifeLab. The atlas is interactive, with the possibility of zooming in from a full brain section to single cells in a specific region of the brain.
About the Human Protein Atlas project
The Human Protein Atlas project, funded by the Knut and Alice Wallenberg Foundation, has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified antibodies with protein profiling in a multitude of tissues and cells assembled in tissue microarrays. Confocal microscopy analysis using human cell lines is performed for more detailed protein localization. The program hosts the Human Protein Atlas portal with expression profiles of human proteins in tissues and cells. The main sites are located at AlbaNova and SciLifeLab, KTH – Royal Institute of Technology, Stockholm, Sweden, and the Rudbeck Laboratory, Uppsala University, Uppsala, Sweden. For more information on the Human Protein Atlas, visit our website at www.proteinatlas.org.
By Chia-Feng Tsai & Yasushi Ishihama, Kyoto University
Dysregulation of cellular signaling based on protein phosphorylation is closely linked to pathogenesis of human diseases and therapeutic strategies to control the phospho-signaling have been accepted to develop molecular-targeting drugs for cancer. MS-based quantitative phosphoproteomic approaches have been widely used to quantify over 10,000 phosphorylation sites by utilizing strong cation exchange chromatography, hydrophilic interaction chromatography or basic-pH reversed-phase chromatography to fractionate the complex samples. However, such extensive fractionation approaches require longer LC-MS measurement time as well as tedious pretreatment steps, resulting in reduced throughput and low reproducibility. Besides, these approaches cannot be applied to primary cells of rare tissues or clinical biopsy samples due to the limited starting materials.
To address these issues, Humphrey et al. (from Matthias Mann’s group) at Max Planck Institute of Biochemistry have developed a streamlined phosphoproteomics workflow called “EasyPhos” which has been designed as a high throughput and simplified workflow to study time-resolved phosphorylation alteration in vivo without any pre-fractionation strategy. They used trifluoroethanol for the digestion buffer which allows bypassing the peptide desalting step before phosphopeptide enrichment. This protocol can reduce the potential sample loss during the desalting process implemented in the conventional protocols. Besides, this simplified procedure can be expanded to a 96-well plate format to increase the throughput of phosphopeptide enrichment. The combination of this workflow with Q Exactive benchtop Orbitrap mass spectrometer allows monitoring of more than 10,000 phosphorylation sites from a mouse cell line by single-shot LC-MS/MS analysis with 2hr gradient. The applicability of this parallelized EasyPhos workflow has been demonstrated on the analysis of liver phosphoproteomes at different time points (early and intermediate) in fasted mice under insulin exposure. Up to 31,605 phosphopeptides (25,507 phosphorylation sites belong to class 1) from 6,138 phosphoproteins were identified from 91 biologically distinct liver tissues by the high throughput 96-well EasyPhos assay. Importantly, at least six biological replicate analyses (separate mice) per sample for each time point provide a highly statistical power to illustrate time-resolved maps of insulin signaling. Moreover, these dynamics datasets illuminate not only the insulin-mediated signaling network but also the signaling cascade from cell surface to the nucleus within 1 min in vivo. This rapid and high throughput EasyPhos workflow will facilitate to accumulate the knowledges of cellular signaling dynamics under physiological or pathological regulation.
Figure reprinted with permission of the Nature Publishing Group
This study was reported in the journal of Nature Biotechnology on August 17, 2015.
Read the full article here: Prioritizing Proteomics Assay Development for Clinical Translation
Vol. 66, No. 2, 2015
Journal of the American College of Cardiology
© 2015 by the American College of Cardiology Foundation
Published by Elsevier Inc.
Richard D. Semba, Maggie Lam, Kai Sun, Pingbo Zhang, Debra A. Schaumberg, Luigi Ferrucci, Peipei Ping, and Jennifer E. Van Eyk
Read the full article here: Priorities and trends in the study of proteins in eye research, 1924-2014
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics Clin. Appl. 2015, 00, 1-18
The Most Trusted Journal in the International Field of Proteomics
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