Why are they missing? : Bioinformatics characterization of missing human proteins

Comparative proteoinformatics revealed the essentials of SDS impact on HaCaT keratinocytes

There is no direct evidence supporting that SDS is a carcinogen, so to investigate this fact, we used HaCaT keratinocytes as a model of human epidermal cells. To reveal the candidate proteins and/or pathways characterizing the SDS impact on HaCaT, we proposed comparative proteoinformatics pipeline. For protein extraction, the performance of two sample preparation protocols was assessed: 0.2% SDS-based solubilization combined with the 1DE-gel concentration (Protocol 1) and osmotic shock (Protocol 2). As a result, in SDS-exposed HaCaT cells, Protocol 1 revealed 54 differentially expressed proteins (DEPs) involved in the disease of cellular proliferation (DOID:14566), whereas Protocol 2 found 45 DEPs of the same disease ID. The 'skin cancer' term was a single significant COSMIC term for Protocol 1 DEPs, including those involved in double-strand break repair pathway (BIR, GO:0000727). Considerable upregulation of BIR-associated proteins MCM3, MCM6, and MCM7 was detected. The eightfold increase in MCM6 level was verified by reverse transcription qPCR. Thus, Protocol 1 demonstrated high effectiveness in terms of the total number and sensitivity of MS identifications in HaCaT cell line proteomic analysis. The utility of Protocol 1 was confirmed by the revealed upregulation of cancer-associated MCM6 in HaCaT keratinocytes induced by non-toxic concentration of SDS. Data are available via ProteomeXchange with identifier PXD035202.

Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi

An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

Are Antisense Proteins in Prokaryotes Functional?

Many prokaryotic RNAs are transcribed from loci outside of annotated protein coding genes. Across bacterial species hundreds of short open reading frames antisense to annotated genes show evidence of both transcription and translation, for instance in ribosome profiling data. Determining the functional fraction of these protein products awaits further research, including insights from studies of molecular interactions and detailed evolutionary analysis. There are multiple lines of evidence, however, that many of these newly discovered proteins are of use to the organism. Condition-specific phenotypes have been characterized for a few. These proteins should be added to genome annotations, and the methods for predicting them standardized. Evolutionary analysis of these typically young sequences also may provide important insights into gene evolution. This research should be prioritized for its exciting potential to uncover large numbers of novel proteins with extremely diverse potential practical uses, including applications in synthetic biology and responding to pathogens.

Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM

The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.

Proteogenomics in the context of the Human Proteome Project (HPP)

INTRODUCTION

The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.

Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10^-4)% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

Digging More Missing Proteins Using an Enrichment Approach with ProteoMiner

Human Proteome Project (HPP) aims at mapping entire human proteins with a systematic effort upon all the emerging techniques, which would enhance understanding of human biology and lay a foundation for development of medical applications. Until now, 2563 missing proteins (MPs, PE2-4) are still undetected even using the most sensitive approach of protein detection. Herein, we propose that enrichment of low-abundance proteins benefits MPs finding. ProteoMiner is an equalizing technique by reducing high-abundance proteins and enriching low-abundance proteins in biological liquids. With triton X-100/TBS buffer extraction, ProteoMiner enrichment, and peptide fractionation, 20 MPs (at least two non-nested unique peptides with more than eight a.a. length) with 60 unique peptides were identified from four human tissues including eight membrane/secreted proteins and five nucleus proteins. Then 15 of them were confirmed with two non-nested unique peptides (≥9 a.a.) identified by matching well with their chemically synthetic peptides in PRM assay. Hence, these results demonstrated ProteoMiner as a powerful means in discovery of MPs.

Identification of Missing Proteins in the Phosphoproteome of Kidney Cancer

Identifying missing proteins (MPs) has been one of the critical missions of the Chromosome-Centric Human Proteome Project (C-HPP). Since 2012, over 30 research teams from 17 countries have been trying to search adequate and accurate evidence of MPs through various biochemical strategies. MPs mainly fall into the following classes: (1) low-molecular-weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTMs), (4) nucleic acid-associated proteins, (5) low abundance, and (6) unexpressed genes. In this study, kidney cancer and adjacent tissues were used for phosphoproteomics research, and 8962 proteins were identified, including 6415 phosphoproteins, and 44 728 phosphosites, of which 10 266 were unreported previously. In total, 75 candidate detections were found, including 45 phoshoproteins. GO analysis for these 75 candidate detections revealed that these proteins mainly clustered as membrane proteins and took part in nephron and kidney development. After rigorous screening and manual check, 9 of them were verified with the synthesized peptides. Finally, only one missing protein was confirmed. All mass spectrometry data from this study have been deposited in the PRIDE with identifier PXD006482.

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.