Proteome

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General schema showing the relationships of the genome, transcriptome, proteome, and metabolome (lipidome). Metabolomics schema.png
General schema showing the relationships of the genome, transcriptome, proteome, and metabolome (lipidome).

The proteome is the entire set of proteins that is, or can be, expressed by a genome, cell, tissue, or organism at a certain time. It is the set of expressed proteins in a given type of cell or organism, at a given time, under defined conditions. Proteomics is the study of the proteome.

Contents

Types of proteomes

While proteome generally refers to the proteome of an organism, multicellular organisms may have very different proteomes in different cells, hence it is important to distinguish proteomes in cells and organisms.

A cellular proteome is the collection of proteins found in a particular cell type under a particular set of environmental conditions such as exposure to hormone stimulation.

It can also be useful to consider an organism's complete proteome, which can be conceptualized as the complete set of proteins from all of the various cellular proteomes. This is very roughly the protein equivalent of the genome.

The term proteome has also been used to refer to the collection of proteins in certain sub-cellular systems, such as organelles. For instance, the mitochondrial proteome may consist of more than 3000 distinct proteins. [1] [2] [3]

The proteins in a virus can be called a viral proteome . Usually viral proteomes are predicted from the viral genome [4] but some attempts have been made to determine all the proteins expressed from a virus genome, i.e. the viral proteome. [5] More often, however, virus proteomics analyzes the changes of host proteins upon virus infection, so that in effect two proteomes (of virus and its host) are studied. [6]

Importance in cancer

The proteome can be used to determine the presence of different types of cancers. Protein Patterns and Diagnosis.jpg
The proteome can be used to determine the presence of different types of cancers.

The proteome can be used in order to comparatively analyze different cancer cell lines. Proteomic studies have been used in order to identify the likelihood of metastasis in bladder cancer cell lines KK47 and YTS1 and were found to have 36 unregulated and 74 down regulated proteins. [7] The differences in protein expression can help identify novel cancer signaling mechanisms.

Biomarkers of cancer have been found by mass spectrometry based proteomic analyses. The use of proteomics or the study of the proteome is a step forward in personalized medicine to tailor drug cocktails to the patient's specific proteomic and genomic profile. [8] The analysis of ovarian cancer cell lines showed that putative biomarkers for ovarian cancer include "α-enolase (ENOA), elongation factor Tu, mitochondrial (EFTU), glyceraldehyde-3-phosphate dehydrogenase (G3P), stress-70 protein, mitochondrial (GRP75), apolipoprotein A-1 (APOA1), peroxiredoxin (PRDX2) and annexin A (ANXA)". [9]

Comparative proteomic analyses of 11 cell lines demonstrated the similarity between the metabolic processes of each cell line; 11,731 proteins were completely identified from this study. Housekeeping proteins tend to show greater variability between cell lines. [10]

Resistance to certain cancer drugs is still not well understood. Proteomic analysis has been used in order to identify proteins that may have anti-cancer drug properties, specifically for the colon cancer drug irinotecan. [11] Studies of adenocarcinoma cell line LoVo demonstrated that 8 proteins were unregulated and 7 proteins were down-regulated. Proteins that showed a differential expression were involved in processes such as transcription, apoptosis and cell proliferation/differentiation among others.

The proteome in bacterial systems

Proteomic analyses have been performed in different kinds of bacteria to assess their metabolic reactions to different conditions. For example, in bacteria such as Clostridium and Bacillus , proteomic analyses were used in order to investigate how different proteins help each of these bacteria spores germinate after a prolonged period of dormancy. [12] In order to better understand how to properly eliminate spores, proteomic analysis must be performed.

History

Marc Wilkins coined the term proteome [13] in 1994 in a symposium on "2D Electrophoresis: from protein maps to genomes" held in Siena in Italy. It appeared in print in 1995, [14] with the publication of part of his PhD thesis. Wilkins used the term to describe the entire complement of proteins expressed by a genome, cell, tissue or organism.

Size and contents

The genomes of viruses and prokaryotes encode a relatively well-defined proteome as each protein can be predicted with high confidence, based on its open reading frame (in viruses ranging from ~3 to ~1000, in bacteria ranging from about 500 proteins to about 10,000). [15] However, most protein prediction algorithms use certain cut-offs, such as 50 or 100 amino acids, so small proteins are often missed by such predictions. [16] In eukaryotes this becomes much more complicated as more than one protein can be produced from most genes due to alternative splicing (e.g. human proteome encodes about 20,000 proteins, but some estimates predicted 92,179 proteins[ citation needed ] out of which 71,173 are splicing variants[ citation needed ]). [17]

Association of proteome size with DNA repair capability

The concept of “proteomic constraint” is that DNA repair capacity is positively correlated with the information content of a genome, which, in turn, is approximately related to the size of the proteome. [18] In bacteria, archaea and DNA viruses, DNA repair capability is positively related to genome information content and to genome size. [18] “Proteomic constraint” proposes that modulators of mutation rates such as DNA repair genes are subject to selection pressure proportional to the amount of information in a genome. [18]

Proteoforms. There are different factors that can add variability to proteins. SAPs (single amino acid polymorphisms) and non-synonymous single nucleotide polymorphisms (nsSNPs) can lead to different "proteoforms" [19] or "proteomorphs". Recent estimates have found ~135,000 validated nonsynonymous cSNPs currently housed within SwissProt. In dbSNP, there are 4.7 million candidate cSNPs, yet only ~670,000 cSNPs have been validated in the 1,000-genomes set as nonsynonymous cSNPs that change the identity of an amino acid in a protein. [19]

Dark proteome. The term dark proteome coined by Perdigão and colleagues, defines regions of proteins that have no detectable sequence homology to other proteins of known three-dimensional structure and therefore cannot be modeled by homology. For 546,000 Swiss-Prot proteins, 44–54% of the proteome in eukaryotes and viruses was found to be "dark", compared with only ~14% in archaea and bacteria. [20]

Human proteome. Currently, several projects aim to map the human proteome, including the Human Proteome Map, ProteomicsDB, isoform.io, and The Human Proteome Project (HPP). Much like the human genome project, these projects seek to find and collect evidence for all predicted protein coding genes in the human genome. The Human Proteome Map currently (October 2020) claims 17,294 proteins and ProteomicsDB 15,479, using different criteria. On October 16, 2020, the HPP published a high-stringency blueprint [21] covering more than 90% of the predicted protein coding genes. Proteins are identified from a wide range of fetal and adult tissues and cell types, including hematopoietic cells.

Methods to study the proteome

This image shows a two-dimensional gel with color-coded proteins. This is a way to visualize proteins based on their mass and isoelectric point. 2D gel color coding.jpg
This image shows a two-dimensional gel with color-coded proteins. This is a way to visualize proteins based on their mass and isoelectric point.

Analyzing proteins proves to be more difficult than analyzing nucleic acid sequences. While there are only 4 nucleotides that make up DNA, there are at least 20 different amino acids that can make up a protein. Additionally, there is currently no known high throughput technology to make copies of a single protein. Numerous methods are available to study proteins, sets of proteins, or the whole proteome. In fact, proteins are often studied indirectly, e.g. using computational methods and analyses of genomes. Only a few examples are given below.

Separation techniques and electrophoresis

Proteomics, the study of the proteome, has largely been practiced through the separation of proteins by two dimensional gel electrophoresis. In the first dimension, the proteins are separated by isoelectric focusing, which resolves proteins on the basis of charge. In the second dimension, proteins are separated by molecular weight using SDS-PAGE. The gel is stained with Coomassie brilliant blue or silver to visualize the proteins. Spots on the gel are proteins that have migrated to specific locations.

Mass spectrometry

An Orbitrap mass spectrometer commonly used in proteomics ThermoScientificOrbitrapElite.JPG
An Orbitrap mass spectrometer commonly used in proteomics

Mass spectrometry is one of the key methods to study the proteome. [22] Some important mass spectrometry methods include Orbitrap Mass Spectrometry, MALDI (Matrix Assisted Laser Desorption/Ionization), and ESI (Electrospray Ionization). Peptide mass fingerprinting identifies a protein by cleaving it into short peptides and then deduces the protein's identity by matching the observed peptide masses against a sequence database. Tandem mass spectrometry, on the other hand, can get sequence information from individual peptides by isolating them, colliding them with a non-reactive gas, and then cataloguing the fragment ions produced. [23]

In May 2014, a draft map of the human proteome was published in Nature . [24] This map was generated using high-resolution Fourier-transform mass spectrometry. This study profiled 30 histologically normal human samples resulting in the identification of proteins coded by 17,294 genes. This accounts for around 84% of the total annotated protein-coding genes.

Chromatography

Liquid chromatography is an important tool in the study of the proteome. It allows for very sensitive separation of different kinds of proteins based on their affinity for a matrix. Some newer methods for the separation and identification of proteins include the use of monolithic capillary columns, high temperature chromatography and capillary electrochromatography. [25]

Blotting

Western blotting can be used in order to quantify the abundance of certain proteins. By using antibodies specific to the protein of interest, it is possible to probe for the presence of specific proteins from a mixture of proteins.

Protein complementation assays and interaction screens

Protein-fragment complementation assays are often used to detect protein–protein interactions. The yeast two-hybrid assay is the most popular of them but there are numerous variations, both used in vitro and in vivo . Pull-down assays are a method to determine the protein binding partners of a given protein. [26]

Protein structure prediction

Protein structure prediction can be used to provide three-dimensional protein structure predictions of whole proteomes. In 2022, a large-scale collaboration between EMBL-EBI and DeepMind provided predicted structures for over 200 million proteins from across the tree of life. [27] Smaller projects have also used protein structure prediction to help map the proteome of individual organisms, for example isoform.io provides coverage of multiple protein isoforms for over 20,000 genes in the human genome. [28]

Protein databases

The Human Protein Atlas contains information about the human proteins in cells, tissues, and organs. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome. The organization ELIXIR has selected the protein atlas as a core resource due to its fundamental importance for a wider life science community.

The Plasma Proteome database contains information on 10,500 blood plasma proteins. Because the range in protein contents in plasma is very large, it is difficult to detect proteins that tend to be scarce when compared to abundant proteins. This is an analytical limit that may possibly be a barrier for the detections of proteins with ultra low concentrations. [29]

Databases such as neXtprot and UniProt are central resources for human proteomic data.

See also

Related Research Articles

<span class="mw-page-title-main">Mutation</span> Alteration in the nucleotide sequence of a genome

In biology, a mutation is an alteration in the nucleic acid sequence of the genome of an organism, virus, or extrachromosomal DNA. Viral genomes contain either DNA or RNA. Mutations result from errors during DNA or viral replication, mitosis, or meiosis or other types of damage to DNA, which then may undergo error-prone repair, cause an error during other forms of repair, or cause an error during replication. Mutations may also result from insertion or deletion of segments of DNA due to mobile genetic elements.

<span class="mw-page-title-main">Stop codon</span> Codon that marks the end of a protein-coding sequence

In molecular biology, a stop codon is a codon that signals the termination of the translation process of the current protein. Most codons in messenger RNA correspond to the addition of an amino acid to a growing polypeptide chain, which may ultimately become a protein; stop codons signal the termination of this process by binding release factors, which cause the ribosomal subunits to disassociate, releasing the amino acid chain.

<span class="mw-page-title-main">Proteomics</span> Large-scale study of proteins

Proteomics is the large-scale study of proteins. Proteins are vital parts of living organisms, with many functions such as the formation of structural fibers of muscle tissue, enzymatic digestion of food, or synthesis and replication of DNA. In addition, other kinds of proteins include antibodies that protect an organism from infection, and hormones that send important signals throughout the body.

<span class="mw-page-title-main">Gene expression</span> Conversion of a genes sequence into a mature gene product or products

Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product that enables it to produce end products, proteins or non-coding RNA, and ultimately affect a phenotype. These products are often proteins, but in non-protein-coding genes such as transfer RNA (tRNA) and small nuclear RNA (snRNA), the product is a functional non-coding RNA. The process of gene expression is used by all known life—eukaryotes, prokaryotes, and utilized by viruses—to generate the macromolecular machinery for life.

<span class="mw-page-title-main">Molecular genetics</span> Scientific study of genes at the molecular level

Molecular genetics is a branch of biology that addresses how differences in the structures or expression of DNA molecules manifests as variation among organisms. Molecular genetics often applies an "investigative approach" to determine the structure and/or function of genes in an organism's genome using genetic screens. 

<span class="mw-page-title-main">Omics</span> Suffix in biology

The branches of science known informally as omics are various disciplines in biology whose names end in the suffix -omics, such as genomics, proteomics, metabolomics, metagenomics, phenomics and transcriptomics. Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms.

<span class="mw-page-title-main">Protein isoform</span> Forms of a protein produced from different genes

A protein isoform, or "protein variant", is a member of a set of highly similar proteins that originate from a single gene or gene family and are the result of genetic differences. While many perform the same or similar biological roles, some isoforms have unique functions. A set of protein isoforms may be formed from alternative splicings, variable promoter usage, or other post-transcriptional modifications of a single gene; post-translational modifications are generally not considered. Through RNA splicing mechanisms, mRNA has the ability to select different protein-coding segments (exons) of a gene, or even different parts of exons from RNA to form different mRNA sequences. Each unique sequence produces a specific form of a protein.

<span class="mw-page-title-main">Single-nucleotide polymorphism</span> Single nucleotide in genomic DNA at which different sequence alternatives exist

In genetics and bioinformatics, a single-nucleotide polymorphism is a germline substitution of a single nucleotide at a specific position in the genome that is present in a sufficiently large fraction of considered population.

<span class="mw-page-title-main">Interactome</span> Complete set of molecular interactions in a biological cell

In molecular biology, an interactome is the whole set of molecular interactions in a particular cell. The term specifically refers to physical interactions among molecules but can also describe sets of indirect interactions among genes.

Protein subcellular localization prediction involves the prediction of where a protein resides in a cell, its subcellular localization.

Extrachromosomal DNA is any DNA that is found off the chromosomes, either inside or outside the nucleus of a cell. Most DNA in an individual genome is found in chromosomes contained in the nucleus. Multiple forms of extrachromosomal DNA exist, and, while some of these serve important biological functions, they can also play a role in diseases such as cancer.

<span class="mw-page-title-main">40S ribosomal protein S16</span> Protein-coding gene in the species Homo sapiens

40S ribosomal protein S16' is a protein that in humans is encoded by the RPS16 gene.

<span class="mw-page-title-main">60S ribosomal protein L36</span> Protein found in humans

60S ribosomal protein L36 is a protein that in humans is encoded by the RPL36 gene.

<span class="mw-page-title-main">60S ribosomal protein L8</span> Protein found in humans

60S ribosomal protein L8 is a protein that in humans is encoded by the RPL8 gene.

<span class="mw-page-title-main">40S ribosomal protein S18</span> Protein-coding gene in the species Homo sapiens

40S ribosomal protein S18 is a protein that in humans is encoded by the RPS18 gene.

<span class="mw-page-title-main">60S ribosomal protein L17</span> Protein found in humans

Large ribosomal subunit protein uL22 is a protein that in humans is encoded by the RPL17 gene.

<span class="mw-page-title-main">Proteogenomics</span>

Proteogenomics is a field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of peptides. Proteogenomics is used to identify new peptides by comparing MS/MS spectra against a protein database that has been derived from genomic and transcriptomic information. Proteogenomics often refers to studies that use proteomic information, often derived from mass spectrometry, to improve gene annotations. The utilization of both proteomics and genomics data alongside advances in the availability and power of spectrographic and chromatographic technology led to the emergence of proteogenomics as its own field in 2004.

Secretomics is a type of proteomics which involves the analysis of the secretome—all the secreted proteins of a cell, tissue or organism. Secreted proteins are involved in a variety of physiological processes, including cell signaling and matrix remodeling, but are also integral to invasion and metastasis of malignant cells. Secretomics has thus been especially important in the discovery of biomarkers for cancer and understanding molecular basis of pathogenesis. The analysis of the insoluble fraction of the secretome has been termed matrisomics.

The minimal genome is a concept which can be defined as the set of genes sufficient for life to exist and propagate under nutrient-rich and stress-free conditions. Alternatively, it can also be defined as the gene set supporting life on an axenic cell culture in rich media, and it is thought what makes up the minimal genome will depend on the environmental conditions that the organism inhabits. By one early investigation, the minimal genome of a bacterium should include a virtually complete set of proteins for replication and translation, a transcription apparatus including four subunits of RNA polymerase including the sigma factor rudimentary proteins sufficient for recombination and repair, several chaperone proteins, the capacity for anaerobic metabolism through glycolysis and substrate-level phosphorylation, transamination of glutamyl-tRNA to glutaminyl-tRNA, lipid biosynthesis, eight cofactor enzymes, protein export machinery, and a limited metabolite transport network including membrane ATPases. Proteins involved in the minimum bacterial genome tend to be substantially more related to proteins found in archaea and eukaryotes compared to the average gene in the bacterial genome more generally indicating a substantial number of universally conserved proteins. The minimal genomes reconstructed on the basis of existing genes does not preclude simpler systems in more primitive cells, such as an RNA world genome which does not have the need for DNA replication machinery, which is otherwise part of the minimal genome of current cells.

<span class="mw-page-title-main">Single-cell analysis</span> Testbg biochemical processes and reactions in an individual cell

In the field of cellular biology, single-cell analysis and subcellular analysis is the study of genomics, transcriptomics, proteomics, metabolomics and cell–cell interactions at the single cell level. The concept of single-cell analysis originated in the 1970s. Before the discovery of heterogeneity, single-cell analysis mainly referred to the analysis or manipulation of an individual cell in a bulk population of cells at a particular condition using optical or electronic microscope. To date, due to the heterogeneity seen in both eukaryotic and prokaryotic cell populations, analyzing a single cell makes it possible to discover mechanisms not seen when studying a bulk population of cells. Technologies such as fluorescence-activated cell sorting (FACS) allow the precise isolation of selected single cells from complex samples, while high throughput single cell partitioning technologies, enable the simultaneous molecular analysis of hundreds or thousands of single unsorted cells; this is particularly useful for the analysis of transcriptome variation in genotypically identical cells, allowing the definition of otherwise undetectable cell subtypes. The development of new technologies is increasing our ability to analyze the genome and transcriptome of single cells, as well as to quantify their proteome and metabolome. Mass spectrometry techniques have become important analytical tools for proteomic and metabolomic analysis of single cells. Recent advances have enabled quantifying thousands of protein across hundreds of single cells, and thus make possible new types of analysis. In situ sequencing and fluorescence in situ hybridization (FISH) do not require that cells be isolated and are increasingly being used for analysis of tissues.

References

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