Protein identification is actively used. Mass spectrometric identification of proteins and protein complexes on atomic force microscope chips Kaisheva, Anna Leonidovna. Methods for protein separation Separation of proteins from low molecular weight impurities

The Ensembl database contains information on 20,469 coding genes, derived from the human genome assembly performed at the US National Center for Biotechnology Information (February 2009). The small number of genes allows us to conclude that the complexity of living systems is achieved at the level of regulation of transcription, translation, and post-translational modifications. Alternative splicing and modifications such as phosphorylation, glycosylation, along with proteolytic processing, lead to the formation of a variety of proteins, the number of which exceeds the number of genes by several orders of magnitude. Estimates carried out by various methods show that the human proteome may contain several million proteins differing in their chemical structure.

The traditional approach to proteome research is based on the use of immunohistochemical staining of tissue sections. The first version of the human proteomic atlas was built using antibodies. The use of biological microarrays containing antibodies coated on them makes it possible to identify and quantify up to several hundred proteins in a single sample. However, this approach has limitations that are associated with the need to develop and verify antibodies, insufficient specificity due to cross-interactions, and the relatively low affinity of antigen-antibody complexes. In this regard, a more universal method of protein identification, biological mass spectrometry, which does not require immunospecific reagents, has acquired particular importance for proteome research.

In mass spectrometric analysis of biomaterial, identification of protein molecules is carried out by comparing the measured mass-charge characteristics of proteins and/or their proteolytic fragments with theoretical values ​​calculated on the basis of amino acid sequences encoded in the genome. It must be taken into account that the genome sequence does not explicitly contain information about alternative splicing sites and possible post-translational modifications. Identification of cases of alternative splicing is possible on the basis of experimental data: the source of information about splice isoforms is DNA coding databases. Identification of post-translational modifications is carried out using high-precision mass spectrometry of proteins or using tandem mass spectrometry of peptide fragments

Along with alternative splicing and post-translational modification, the diversity of protein molecules increases due to the translation of non-synonymous Single Nucleotide Polymorphism (nsSNP). Determining the presence of nsSNP is done using genotyping, while confirming the presence of a corresponding residue substitution in the primary structure of the protein, that is, identifying single amino acid polymorphisms (SAP, Single Amino Acid Polymorphism, SAP), is a proteotyping task.

The importance of identifying and studying alternative splicing, PDA, and post-translational modifications at the protein level is due to the influence of these processes on the expression level and functional properties of proteins. It is known that changes in the activity or expression level of proteins can lead to the emergence and development of socially significant diseases, including cancer, cardiovascular and neurodegenerative diseases.

The presence of about 65 thousand nonsynonymous polymorphisms has been established in the genome, presumably translated into PDA, with more than 30% presumably leading to changes in the functional properties of proteins. Since changes in protein activity are associated with the development of diseases, studies of PDA are necessary to determine the structural reasons underlying the observed functional disorders. The tasks of proteotyping include qualitative and quantitative determination of the expression of allelic variants of genes at the proteomic level, as well as monitoring the frequency of occurrence of expressed allelic variants of proteins at the population level.

Identification of PDAs in high-throughput mode using mass spectrometry is associated with technical limitations. For the task of proteotyping, the most adequate approach is the “top-down” approach, that is, mass spectrometry of intact proteins (and not their fragments). However, the sensitivity of this approach is low, at the level of 10 h-10 5 M. As a result, the identification of tens, less often hundreds, and, only in exceptional cases, up to a thousand proteins is ensured. Most often, another approach is used in biological mass spectrometry - “bottom-up”, in which the presence of a protein in a sample is established by identifying its proteolytic fragments (peptides). In most cases, to identify a protein, a small number of peptides are sufficient, which together can constitute no more than 5% of the biopolymer sequence. For the remaining part of the amino acid sequence of the protein, it is impossible to determine the presence/absence of chemical modifications of amino acid residues or amino acid polymorphisms.

To identify single amino acid polymorphisms of human proteins using biological mass spectrometry, it is necessary to increase the degree of protein amino acid sequence coverage by identifying additional proteolytic peptides of the protein. This is possible by conducting an experiment with a large number of partially or fully replicated mass spectrometry analyses. In addition, data from proteomics experiments performed by multiple research groups can be combined into a single study. Access to an extensive collection of mass spectra is provided by various proteomic repositories, the most popular of which, PRIDE (Protein Identification Database), stores the results of more than 13 thousand proteomic experiments. The higher the degree of coverage of the amino acid sequence of a protein by identified peptides, the greater the likelihood of confirming the presence or absence of single amino acid substitutions in the protein structure.

Given the availability of a vast amount of mass spectrometric data, solving the problem of proteotyping is possible through the use of computational methods of bioinformatics. For example, analysis of mass spectrometry data can be carried out using expressed fragment databases (ESTs), which contain information about translated variants of nonsynonymous gene polymorphisms. The second method, implemented in many protein identification programs, is a comparison of mass spectra with a database of theoretical protein sequences, allowing for inaccuracies in the form of substitutions of amino acid residues.

The disadvantages of the above approaches are well known. Expressed fragment databases contain redundant information, including sequencing errors, which complicates the analysis of mass spectrometry results. When analyzing a sample in which several hundred proteins have been identified, the resulting mass spectra must be compared with hundreds of thousands of transcripts accumulated over decades, which contain more than 5% errors. When analyzing mass spectra with the assumption of possible inaccuracies in the database, information about actually existing non-synonymous substitutions that were established by genotyping is ignored. Artificial assumptions introduced into the database or protein identification algorithm reduce the reliability of the results. These shortcomings of existing proteotyping methods necessitate the improvement of computational approaches to PDA identification.

The goal of the work was to develop a method for analyzing mass spectrometric data to identify single amino acid polymorphisms resulting from the translation of nonsynonymous nucleotide substitutions in the corresponding genes, and to use the developed method to identify amino acid substitutions in human proteins. To achieve the goal, the following tasks were solved:

1. Process the mass spectra of peptide fragments to increase the degree of coverage of amino acid sequences of proteins by identified peptides.

2. Using a model set of mass spectrometric data that provides a high degree of sequence coverage, develop a method for identifying single-amino acid substitutions in human proteins.

3. Summarize the method for identifying single-amino acid substitutions in the form of a universal algorithm for processing tandem mass spectra; evaluate the sensitivity and specificity of the created algorithm.

4. Apply the created algorithm to process a repository of mass spectrometric data, identify single-amino acid polymorphisms and characterize human proteins containing the identified polymorphisms.

2 LITERATURE REVIEW

The term “proteome” - the complete set of proteins expressed in the body - was first proposed by Mark Wilkins in connection with the emerging need to supplement knowledge about genomes with relevant information about the proteins encoded in them. The object of study when analyzing the proteome can be either a whole organism or a cellular component, tissue, subcellular structure, for example, the nucleus, microsomal fraction, etc.

The results of a large-scale inventory of proteins using mass spectrometry were published in the work of Shevchenko et al in 1996. The advent of biological mass spectrometry marked the advent of the era of high-throughput post-genomic technologies, which make it possible to obtain information about genes and proteins on the scale of the entire organism as a result of a single experiment. Postgenomic technologies, in addition to proteomics, also include genomics and transcriptomics. When analyzing genetic material, postgenomic technologies make it possible to determine the presence of gene polymorphism using whole-genome re-sequencing or high-density mapping of single nucleotide substitutions (SNPs).

Existing approaches to studying protein diversity can be divided into two directions. In the first case, before setting up the experiment, it is predetermined which protein molecules are planned to be identified. In this approach, protein identification is carried out using antibodies, which are used for histochemical staining of tissue sections followed by obtaining micrographs of cells. In a microphotograph of a section, fluorescent areas correspond to the localization sites of the detected antigen protein, and the intensity of fluorescence allows one to obtain a quantitative assessment of the content of this protein.

As part of the large international project ProteinAtlas, large-scale production of antibodies to proteins of all human genes is being carried out. This project produced and made available for public use more than 400,000 micrographs of immunohistochemically stained sections for virtually all human tissues. A comparative analysis of the distribution of specific protein staining made it possible, in particular, to identify characteristic protein expression profiles for cancer tissues. However, staining tissue sections using fluorescently labeled antibodies is a rather crude method for studying the proteome. Firstly, as the developers of the ProteinAtlas project themselves point out, the quality of many commercially available antibodies is extremely low. When verified, approximately half of the purchased antibodies show low specificity for the antigen under study, and antibody preparations are often characterized by low purity. Secondly, a large number of antigen-antibody complexes are characterized by a dissociation constant (107-108 M), which limits the sensitivity when measuring protein concentrations.

In addition to histochemical analysis, proteome research is carried out using biological microarrays. Protein microarrays are a powerful tool for translational medicine, but are limited in their ability to be used for large-scale proteome research. The use of microarray technologies in proteomics rarely makes it possible to identify more than ten proteins at a time: with an increase in the number of analyzed proteins, standardization of the conditions for antigen-antibody interaction is difficult. Thus, the use of microchips leads to false-negative results in the case when the differences in dissociation constants for antigen-antibody complexes are several orders of magnitude. In addition, the stability of antibodies very much depends on their storage conditions, so the use of protein microarrays is limited to the time immediately after their manufacture, which does not allow this type of analysis to become widespread.

The second direction of proteome research is associated with setting up an experiment in the so-called “panoramic” (survey) mode, when it is not known in advance which proteins can be identified. Potentially, as a result of a panoramic experiment, any proteins encoded in the genome of the organism under study can be identified, including even products from regions of the genome considered to be non-coding. Technical and methodological tools for genome-wide proteome research are provided by biological mass spectrometry.

1. Proteomic mapping of mass spectrometric data was carried out, including identification of proteins using the peptide mass fingerprint method, followed by analysis aimed at identifying protein-specific proteotypic peptides. Using the example of proteins of the cytochrome P450 superfamily, it was shown that by mapping protein localization zones in the gel, the degree of sequence coverage by identified peptide fragments increases by 27%.

2. Proteolytic peptides specific for the forms of cytochromes P450 CYP3A4 and CYP3A5 have been identified, the sequence identity of which is 82%. Allelic variants of translation of cytochromes CYP3A4 and CYP3A5 were identified, containing single-amino acid polymorphisms M445N (ZA4), K96E (ZA4), L82R (ZA5) and D277E (ZA5).

3. An iterative algorithm has been developed to identify single-amino acid polymorphisms of proteins using tandem mass spectra of proteolytic peptides. When tested on the Aurum Dataset control set, the polymorphism detection algorithm showed a specificity of more than 95%. The sensitivity of the algorithm was 30%, which corresponds to the average coverage of the sequences included in the control set.

4. As a result of the analysis of mass spectrometric experiments deposited in the PRIDE repository, a total of 270 single-amino acid polymorphisms in 156 human proteins were identified, including 51 PDAs (45 proteins) associated with diseases, including disorders of the blood coagulation system and systemic amyloidosis.

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