Functional Annotation of the Human Chromosome 7 “Missing” Proteins: A Bioinformatics Approach

Accelerating the search for the missing proteins in the human proteome

The Human Proteome Project (HPP) aims to discover high-stringency data for all proteins encoded by the human genome. Currently, ∼18% of the proteins in the human proteome (the missing proteins) do not have high-stringency evidence (for example, mass spectrometry) confirming their existence, while much additional information is available about many of these missing proteins. Here, we present MissingProteinPedia as a community resource to accelerate the discovery and understanding of these missing proteins.

The Human Proteome Project aims to catalogue the ∼20,000 proteins encoded by the human genome. In this review, Baker et al . focus on the missing proteins, proteins that lack high stringency proteomic evidence, and launch MissingProteinPedia, a database aimed at accelerating the search for missing proteins.

A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes

In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.

De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data

High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. Although the analysis of spectra by de novo sequences removes such biases and has been available for a long period of time, its uptake has been slow or almost nonexistent within the scientific community. In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.

Progress and pitfalls in finding the 'missing proteins' from the human proteome map

INTRODUCTION

The Human Proteome Project was launched with two main goals: the comprehensive and systematic definition of the human proteome map and the development of ready to use analytical tools to measure relevant proteins in their biological context in health and disease. Despite the great progress in this endeavour, there is still a group of reluctant proteins with no, or scarce, experimental evidence supporting their existence. These are called the 'missing proteins' and represent one of the biggest challenges to complete the human proteome map. Areas covered: This review focuses on the description of the missing proteome based on the HUPO standards, the analysis of the reasons explaining the difficulty of detecting missing proteins and the strategies currently used in the search for missing proteins. The present and future of the quest for the missing proteins is critically revised hereafter. Expert commentary: An overarching multidisciplinary effort is currently being done under the HUPO umbrella to allow completion of the human proteome map. It is expected that the detection of missing proteins will grow in the coming years since the methods and the best tissue/cell type sample for their search are already on the table.

Resolving chromosome-centric human proteome with translating mRNA analysis: a strategic demonstration

Chromosome-centric human proteome project (C-HPP) aims at differentiating chromosome-based and tissue-specific protein compositions in terms of protein expression, quantification, and modification. We previously found that the analysis of translating mRNA (mRNA attached to ribosome-nascent chain complex, RNC-mRNA) can explain over 94% of mRNA-protein abundance. Therefore, we propose here to use full-length RNC-mRNA information to illustrate protein expression both qualitatively and quantitatively. We performed RNA-seq on RNC-mRNA (RNC-seq) and detected 12,758 and 14,113 translating genes in human normal bronchial epithelial (HBE) cells and human colorectal adenocarcinoma Caco-2 cells, respectively. We found that most of these genes were mapped with >80% of coding sequence coverage. In Caco-2 cells, we provided translating evidence on 4180 significant single-nucleotide variations. While using RNC-mRNA data as a standard for proteomic data integration, both translating and protein evidence of 7876 genes can be acquired from four interlaboratory data sets with different MS platforms. In addition, we detected 1397 noncoding mRNAs that were attached to ribosomes, suggesting a potential source of new protein explorations. By comparing the two cell lines, a total of 677 differentially translated genes were found to be nonevenly distributed across chromosomes. In addition, 2105 genes in Caco-2 and 750 genes in HBE cells are expressed in a cell-specific manner. These genes are significantly and specifically clustered on multiple chromosomes, such as chromosome 19. We conclude that HPP/C-HPP investigations can be considerably improved by integrating RNC-mRNA analysis with MS, bioinformatics, and antibody-based verifications.

Unlocking the puzzling biology of the black Périgord truffle Tuber melanosporum

The black Périgord truffle (Tuber melanosporum Vittad.) is a highly prized food today, with its unique scent (i.e., perfume) and texture. Despite these attributes, it remains relatively poorly studied, lacking "omics" information to characterize its biology and biochemistry, especially changes associated with freshness and the proteins/metabolites responsible for its organoleptic properties. In this study, we have functionally annotated the truffle proteome from the 2010 T. melanosporum genome comprising 12,771 putative nonredundant proteins. Using sequential BLAST search strategies, we identified homologues for 2587 proteins with 2486 (96.0%) fungal homologues (available from http://biolinfo.org/protannotator/blacktruffle.php). A combined 1D PAGE and high-accuracy LC-MS/MS proteomic study was employed to validate the results of the functional annotation and identified 836 (6.5%) proteins, of which 47.5% (i.e., 397) were present in our bioinformatics studies. Our study, functionally annotating 6487 black Périgord truffle proteins and confirming 836 by proteomic experiments, is by far the most comprehensive study to date contributing significantly to the scientific community. This study has resulted in the functional characterization of novel proteins to increase our biological understanding of this organism and to uncover potential biomarkers of authenticity, freshness, and perfume maturation.