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Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0
Deutsch, Eric W.,Lane, Lydie,Overall, Christopher M.,Bandeira, Nuno,Baker, Mark S.,Pineau, Charles,Moritz, Robert L.,Corrales, Fernando,Orchard, Sandra,Van Eyk, Jennifer E.,Paik, Young-Ki,Weintraub, S American Chemical Society 2019 JOURNAL OF PROTEOME RESEARCH Vol.18 No.12
<P>The Human Proteome Organization’s (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.</P> [FIG OMISSION]</BR>
Yoon, Sung Ho,Turkarslan, Serdar,Reiss, David J.,Pan, Min,Burn, June A.,Costa, Kyle C.,Lie, Thomas J.,Slagel, Joseph,Moritz, Robert L.,Hackett, Murray,Leigh, John A.,Baliga, Nitin S. Cold Spring Harbor Laboratory Press 2013 Genome research Vol.23 No.11
<P>Methanogens catalyze the critical methane-producing step (called methanogenesis) in the anaerobic decomposition of organic matter. Here, we present the first predictive model of global gene regulation of methanogenesis in a hydrogenotrophic methanogen, <I>Methanococcus maripaludis</I>. We generated a comprehensive list of genes (protein-coding and noncoding) for <I>M. maripaludis</I> through integrated analysis of the transcriptome structure and a newly constructed Peptide Atlas. The environment and gene-regulatory influence network (EGRIN) model of the strain was constructed from a compendium of transcriptome data that was collected over 58 different steady-state and time-course experiments that were performed in chemostats or batch cultures under a spectrum of environmental perturbations that modulated methanogenesis. Analyses of the EGRIN model have revealed novel components of methanogenesis that included at least three additional protein-coding genes of previously unknown function as well as one noncoding RNA. We discovered that at least five regulatory mechanisms act in a combinatorial scheme to intercoordinate key steps of methanogenesis with different processes such as motility, ATP biosynthesis, and carbon assimilation. Through a combination of genetic and environmental perturbation experiments we have validated the EGRIN-predicted role of two novel transcription factors in the regulation of phosphate-dependent repression of formate dehydrogenase—a key enzyme in the methanogenesis pathway. The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions.</P>