Quantitative proteomics technology based on isobaric tags is playing an important role in proteomic investigation. In this paper, we present an automated software, named IQuant, which integrates a postprocessing tool of protein identification and advanced statistical algorithms to process the MS/MS signals generated from the peptides labeled by isobaric tags and aims at proteomics quantification. The software of IQuant, which is freely downloaded at http://sourceforge.net/projects/iquant/, can run from a graphical user interface and a command-line interface, and can work on both Windows and Linux systems.

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

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Investigations of missing proteins (MPs) are being endorsed by many bioanalytical strategies. We proposed that proteogenomics of testis tissue was a feasible approach to identify more MPs because testis tissues have higher gene expression levels. Here we combined proteomics and transcriptomics to survey gene expression in human testis tissues from three post-mortem individuals. Proteins were extracted and separated with glycine- and tricine-SDS-PAGE. A total of 9597 protein groups were identified; of these, 166 protein groups were listed as MPs, including 138 groups (83.1%) with transcriptional evidence. A total of 2948 proteins are designated as MPs, and 5.6% of these were identified in this study. The high incidence of MPs in testis tissue indicates that this is a rich resource for MPs. Functional category analysis revealed that the biological processes that testis MPs are mainly involved in are sexual reproduction and spermatogenesis. Some of the MPs are potentially involved in tumorgenesis in other tissues. Therefore, this proteogenomics analysis of individual testis tissues provides convincing evidence of the discovery of MPs. All mass spectrometry data from this study have been deposited in the ProteomeXchange (data set identifier PXD002179).

This paper summarizes the recent activities of the Chromosome-Centric Human Proteome Project (C-HPP) consortium, which develops new technologies to identify yet-to-be annotated proteins (termed "missing proteins") in biological samples that lack sufficient experimental evidence at the protein level for confident protein identification. The C-HPP also aims to identify new protein forms that may be caused by genetic variability, post-translational modifications, and alternative splicing. Proteogenomic data integration forms the basis of the C-HPP's activities; therefore, we have summarized some of the key approaches and their roles in the project. We present new analytical technologies that improve the chemical space and lower detection limits coupled to bioinformatics tools and some publicly available resources that can be used to improve data analysis or support the development of analytical assays. Most of this paper's content has been compiled from posters, slides, and discussions presented in the series of C-HPP workshops held during 2014. All data (posters, presentations) used are available at the C-HPP Wiki (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.

Isobaric tags have broad applications in both basic and translational research, as demonstrated by the widely used isobaric tag for relative and absolute quantitation (iTRAQ). Recent results from large-scale quantitative proteomics projects, however, indicate that protein quantification by iTRAQ is often biased in complex biological samples. Here, we report the application of another isobaric tag, deuterium isobaric amine reactive tag (DiART), for quantifying the proteome of Thermoanaerobacter tengcongensis (T. tengcongensis), a thermophilic bacterium first discovered in China. We compared the performance of DiART with iTRAQ from several different aspects, including their fragmentation mechanisms, the number of identified proteins, and the accuracy of quantification. Our results revealed that, as compared with iTRAQ, DiART yielded significantly stronger reporter ions, which did not reduce the number of identifiable peptides, but improved the signal-to-noise ratio (S/N) for quantification. Remarkably, we found that, under identical chromatography and mass spectrometry (MS) conditions, DiART exhibited less reporter ions ratio compression than iTRAQ, probably due to more reporter ions with higher intensities produced by DiART labeling. Taken together, we demonstrate that DiART is a valuable alternative of iTRAQ with enhanced performance for quantitative proteomics.

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Thermophiles are referred to as microorganisms with optimal growth temperatures of >60 °C. Over the past few years, a number of studies have been conducted regarding thermophiles, especially using the omics strategies. This review provides a systematic view of the survival physiology of thermophiles from an "omics" perspective, which suggests that the adaptive ability of thermophiles is based on a cooperative mode with multi-dimensional regulations integrating genomics, transcriptomics, and proteomics.