A semi-virtual two dimensional gel electrophoresis: IF-ESI LC-MS/MS

A database for inventory of proteoform profiles: "2DE-pattern"

The human proteome is composed of a diverse and heterogeneous range of gene products/proteoforms/protein species. Because of the growing amount of information about proteoforms generated by different methods, we need a convenient approach to make an inventory of the data. Here, we present a database of proteoforms that is based on information obtained by separation of proteoforms using 2DE followed by shotgun ESI-LC-MS/MS. The database's principles and structure are described. The database is called "2DE-pattern" as it contains multiple isoform-centric patterns of proteoforms separated according to 2DE principles. The database can be freely used at http://2de-pattern.pnpi.nrcki.ru.

Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium

This manuscript collects all the efforts of the Russian Consortium, bottlenecks revealed in the course of the C-HPP realization, and ways of their overcoming. One of the main bottlenecks in the C-HPP is the insufficient sensitivity of proteomic technologies, hampering the detection of low- and ultralow-copy number proteins forming the "dark part" of the human proteome. In the frame of MP-Challenge, to increase proteome coverage we suggest an experimental workflow based on a combination of shotgun technology and selected reaction monitoring with two-dimensional alkaline fractionation. Further, to detect proteins that cannot be identified by such technologies, nanotechnologies such as combined atomic force microscopy with molecular fishing and/or nanowire detection may be useful. These technologies provide a powerful tool for single molecule analysis, by analogy with nanopore sequencing during genome analysis. To systematically analyze the functional features of some proteins (CP50 Challenge), we created a mathematical model that predicts the number of proteins differing in amino acid sequence: proteoforms. According to our data, we should expect about 100 000 different proteoforms in the liver tissue and a little more in the HepG2 cell line. The variety of proteins forming the whole human proteome significantly exceeds these results due to post-translational modifications (PTMs). As PTMs determine the functional specificity of the protein, we propose using a combination of gene-centric transcriptome-proteomic analysis with preliminary fractionation by two-dimensional electrophoresis to identify chemically modified proteoforms. Despite the complexity of the proposed solutions, such integrative approaches could be fruitful for MP50 and CP50 Challenges in the framework of the C-HPP.

Next Steps on in Silico 2DE Analyses of Chromosome 18 Proteoforms

In the boundaries of the chromosome-centric Human Proteome Project (c-HPP) to obtain information about proteoforms coded by chromosome 18, several cell lines (HepG2, glioblastoma, LEH), normal liver, and plasma were analyzed. In our study, we have been using proteoform separation by two-dimensional electrophoresis (2DE) (a sectional analysis) and a semivirtual 2DE with following shotgun mass spectrometry using LC-ESI-MS/MS. Previously, we published a first draft of this research, where only HepG2 cells were tested. Here, we present the next step using more detailed analysis and more samples. Altogether, confident (2 significant sequences minimum) information about proteoforms of 117 isoforms coded by 104 genes of chromosome 18 was obtained. The 3D-graphs showing distribution of different proteoforms from the same gene in the 2D map were generated. Additionally, a semivirtual 2DE approach has allowed for detecting more proteoforms and estimating their pI more precisely. Data are available via ProteomeXchange with identifier PXD010142.

Variety and Dynamics of Proteoforms in the Human Proteome: Aspects of Markers for Hepatocellular Carcinoma

We have previously developed an approach, where two-dimensional gel electrophoresis (2DE) was used, followed by sectional analysis of the whole gel using high-resolution nano-liquid chromatography-mass spectrometry (ESI LC-MS/MS). In this study, we applied this approach on the panoramic analysis of proteins and their proteoforms from normal (liver) and cancer (HepG2) cells. This allowed us to detect, in a single proteome, about 20,000 proteoforms coded by more than 4000 genes. A set of 3D-graphs showing distribution of these proteoforms in 2DE maps (profiles) was generated. A comparative analysis of these profiles between normal and cancer cells showed high variability and dynamics of many proteins. Among these proteins, there are some well-known features like alpha-fetoprotein (FETA) or glypican-3 (GPC3) and potential hepatocellular carcinoma (HCC) markers. More detailed information about their proteoforms could be used for generation of panels of more specific biomarkers.