Biology论文模板 – Proteomic Analysis, Its Contributions, Challenges and Technological Advances


 Proteomics, also referred to as proteomic analysis, is a methodical quantification and establishment of the comprehensive proteins complement of genetic systems at a given period. The most popular method that has been applied to carry out proteomic analysis is the mass spectrometry (Dua and Chowriappa, 2013). The proteins or proteomes are featured by post-translational adjustments, time-dependent patterns of expression, and large proteome-abundance variations. All these characteristics transmit biological messages which cannot be accessed by either transcriptomics or genomics (Hoffmann and Stroobant, 2007). Proteomic analysis can be applicable in the identification and localization of different post-translational adjustments, protein profiling and a comparative analysis of different samples of proteomes (Kondo, 2008).

Branches of Proteomics

        Proteomic is sub-divided into different branches including the branch of protein sequence analysis, protein modification branch, structural proteomics branch, protein quantification branch, experimental bioinformatics branch, interaction proteomics branch among other branches. These branches are discussed in details in this segment (Li, n.d.).

       Protein separation branch is mainly dependent on technologies which are capable of separating long and complicated proteomes mixtures to enable easy processing using other methods.

      Protein identification branch employs the use of a more advanced proteomic technique which is dependent on mass spectrometry, to enable accurate proteome identification.  Some of the most common examples of protein identification include fingerprinting on basic instruments.

       In the protein quantification branch, different Gel-based techniques like the differential use of fluorescent dyes to stain gels. Other techniques which are independent of gels include different chemical modification techniques like the MeCATs, COFRADIC, and ICATs. In this branch, the quantification of tools majorly indicates the separation of different proteome spots. Moreover, these tools are capable of matching different gel spots to indicate the different in the proteins in different stages of a disease (Sanchez, Corthals and Hochstrasser, 2004).

       The protein sequence analysis is a bioinformatics division which is focused on analyzing databases to find out any peptide match, their evolutionary associations, and their domains’ functional assignment and finally forecast their functions from the patterns.

       Structural and interaction proteomics branches are concerned with the establishment of a peptide or a proteome structure in a 3D space using techniques like NMR spectroscopy and X-ray Crystallography, while the interaction proteomic branch is concerned with establishing the interaction of proteomes within the cellular, atomic and even the molecular levels (Vékey, Telekes and Vertes, 2008).

       The branch of protein modification is concerned with the post-translational modification, for instance, from their original amino-acid sequence. Specialized techniques have been established to study glycosylation and phosphorylation (Piętka and Kawa, 2012).

 Cellular Proteomics branch has the main objective of establishing the protein-protein interaction and their locations, in cells especially during main cell events. Cellular Proteomics branch is based on techniques like optical fluorescence microscopy and x-ray tomography.

       Finally is the experimental bioinformatics branch which involves design techniques like bioinformatics and experimental, to facilitate the extraction and creation of new information derived from different proteomics investigations.

Proteomic Challenges

       The main constraint which is mostly encountered in proteomics is accurately establishing the role of particular isoform in each proteome. There are numerous proteins which are identified through proteomics which lack specified functions. Also, the present understanding regarding the biochemical and cellular functions are limited on these proteins (Steuble, 2008). The main aim of establishing a proteome’s subcellular location is to provide useful information regarding cellular specialty of these proteins. This challenge has therefore resulted to the many suggestions which are aimed at finding the best way in which the cellular functions can be identified (Twyman, 2014). One of the methods includes the identification of proteomes which are known to associate with the proteomes that are of interest at that particular time. However, such methodologies are more likely to offer reliable results when carried out in organisms with relatively limited genomes.

       Additionally, the main challenge in the development of protein array comes in three dimensions. The main challenge which has been encountered in trying to come up with protein microarrays is the establishment of complete clone libraries which can supply huge amounts of protein samples (Peirce and Wait, 2009). Moreover, the materials linked to protein assays are mostly incompatible with different arrays, are unable to provide the expected variations from experiments and finally do not demonstrate the desired sensitivity.

With the arrival of microarrays which are protein based, it is now possible to carry out mass analysis of proteomes which can, therefore, be randomly screened to establish the interactions, the  identification and quantification of the proteomes among other significant aspects.

Contribution to the Field Of Diseases

The proteome is one of the busiest operations sites for most biological functions; its presence and interactions are accurately regulated, and it also provides the link between phenotypes and genome. The presence of proteins varies in different proportions of shapes, sizes, and charges. Proteome has over twenty amino acids compared to the four nucleotides for the genome. The proteome undergoes active changes within the different cells, tissues and organs in its development due to disease processes and environmental stimuli. Understanding the processes of proteome interactions with metabolites, nucleic acids, and other proteins is important is differentiating the various biological mechanisms and gathering insights about other diseases like cancer. For decades, the center of attention has been Genomic sequencing which has generated a lot of valuable information. Nonetheless, DNA level variation and protein abundance do not correlate well. Thus, proteomics serves to bridge the gap between functional proteins, information translation and genomic information (Keedwell and Narayanan, 2005).

  • Cancer

Proteomics play an integral role in identifying biomarkers that detect the early stage tumor in patients, monitor drug response to tumors, define the mechanisms that predispose patients to cancer and generate new therapeutics in cancer research. The proteome can systematically quantify protein concentration positions, monitor the mechanisms for malignant prototype and monitor alterations in the heterogeneous multiple pathways. Oncologists, therefore, use proteomic tools, experimental designs, and proteomic interpretations to evaluate the causative mechanisms, develop cancer treatment and guide prognostication.

  • Neurotrauma

In the study of cancer, Proteomics is considered a crucial aspect which provides useful approach to enable the assessment of post trauma. Despite the fact that it is almost impossible to offer a comprehensive evaluation of different proteomes, numerous reports covering neurotraumia summarize the most recent innovations which are accessed by responsible researchers to enable them offer more light regarding the same. The technical approaches are two-dimensional gel electrophoresis, mass spectrometry direct analysis that includes a two-dimensional chromatography with isotope-coded tags and mass spectrometry, and antibody technologies. In the case of spinal cord and brain trauma, proteomics is used in the development of diagnostic predictors that follow a central nervous system injury and in the mapping of changes in the injured proteins to identify the next therapeutic targets. Neurotrauma experience leads to severe alterations of the biological systems involving the nervous system which evolve with time. The exploration of the nervous system following an injury requires methods for assessments and for simplifying the complexities.

  • Renal disease diagnosis

Proteomics is highly prospected to play a critical role in the conversion of genomics into clinically significant uses particularly in prognostics and diagnostics context. For instance, the confirmation, management and even the treatment of renal disorders have a main goal of identifying the biomarkers which are linked to the disorder. The application of proteomics unbiased and with high throughput approach in the analysis of protein pattern variations provides one of the most appropriate notions for the discovery of biomarkers. The combination of these analytical methodologies such as the two-dimensional gel electrophoresis with some sophisticated techniques like the MS has facilitated a promising development in cataloging and quantification of protein components in the urine and other kidney parts in the normal and diseased states.

  • Neurology

The rapidly advancing proteomic techniques have been extensively applied the major areas of medicine and biology. In the fields of neuroscience and neurology, the applications of proteomics have been widely applicable in neurometabolic and neurotoxicology beside the determination of specific areas of individual brain parts and body fluids neurodegeneration (Sanchez, Corthals, & Hochstrasser, 2004). The investigation involving the protein groups of the brain such as cytoskeleton proteins, enzymes, chaperones, antioxidant proteins and synaptosomal proteins are in the process similar to phenotype related proteomics. The connected detection of hundreds of proteins on a gel provides a database of sufficiently comprehensive repository for the determination of a pathophysiological network of proteins and their peripheral representatives.

  • Maternal and fetal medicine

Proteomics activities involve the functional analysis and characterization of proteins as expressed by genomes at specific circumstances and period. The degree of expressions of different proteins is completely dependent of the dynamic well balanced and complicated systems. The variation, however, is dependent on the cell’s biological function and from the signals within its environment.

In biomedical research, it is apparent that the cellular processes, especially during a disease, are dependent on multiple proteins, thus not significant to direct focus on a single gene product that is one protein but to work with a complete proteome set. This ensures that the underlying multifactorial relations that are factored in certain diseases may be discovered by identifying the potential therapeutic targets (Pietka & Kawa, 2012). The characterization of functional proteome for many diseases is useful for determining alterations in the protein modifications and expression

Technologies Applied In Proteomics

Some of the most important technologies applied in proteomics include nuclear magnetic resonance and x-ray crystallography which are employed to illustrate the proteins’ and peptides’ 3D make up. Additionally, to study the proteins’ secondary arrangements, less complicated technologies including the x-ray scattering, and infrared spectroscopy (Divan and Royds, 2013).

       2D electrophoresis (reverse phase chromatography) coupled up with tandem mass spectrometry are technologies which facilitate the appropriate identification of cell proteins and their respective quantifications by applying methods such as the de novo peptide sequencing.

Mass spectrometer applies peptide mass fingerprinting and is beneficial when identifying the proteins. This approach is less commonly used especially with high resolution mass spectrometry and chromatography. The technique is rapidly being rendered outdated since protein identification which is based on data from peptide mass fingerprints is no longer permitted. A combination of tandem mass spectrometry with two dimensional electrophoresis or reverse phase chromatography is used to identify and quantify the proteins and their levels as found in cells (Lang, 2009).

Yeast two-hybrid technique, affinity chromatography, Plasmon resonance and florescence resonance energy transfer are applied for correct identification of protein –DNA and protein-protein binding reactions. On the other hand, X-ray tomography is applied to identify the location of protein complexes and labeled proteins in an intact cell (Lipton and Paša-Tolić, 2009). The process is frequently comparative to the cell images obtained from light microscopes.

Another technology is software image analysis which is useful in an authenticated quantification and identification of proteome spots in different samples. The expertise may be widely utilized, but the intelligence is yet to be adjusted to perfection.


Proteomics is, therefore, a very important research topic which has immensely contributed to the field of medicine and agriculture as well. The analysis has enabled breakthrough especially in the diagnosis of fatal diseases like cancer, neurological disorders, and kidney diseases. Despite the challenges facing this field, there have been improvements due to technological advances.


Daoud, S. (2008). Cancer proteomics. Totowa, N.J.: Humana Press.

Divan, A. and Royds, J. (2013). Tools and techniques in biomolecular science. Oxford: Oxford University Press.

Dua, S. and Chowriappa, P. (2013). Data mining for bioinformatics. Boca Raton, FL: CRC Press.

García, A. and Senis, Y. (2011). Platelet proteomics. Hoboken, N.J.: John Wiley & Sons.

Hoffmann, E. and Stroobant, V. (2007). Mass spectrometry. Chichester, West Sussex, England: J. Wiley.

Keedwell, E. and Narayanan, A. (2005). Intelligent bioinformatics. Hoboken, NJ: Wiley.

Kondo, T. (2008). Cancer Proteomics for Biomarker Development. Journal of Proteomics & Bioinformatics, 01(09).

Kondo, T. (2008). Cancer Proteomics for Personalized Medicine. Journal of Proteomics & Bioinformatics, S2(01), pp.086-086.

Lang, J. (2009). Handbook on mass spectrometry. New York: Nova Science Publishers.

Li, M. (n.d.). Recent advances in proteomics research.

Lipton, M. and Paša-Tolić, L. (2009). Mass spectrometry of proteins and peptides. New York: Humana.

Peirce, M. and Wait, R. (2009). Membrane proteomics. New York, NY: Humana Press.

Piętka, E. and Kawa, J. (2012). Information technologies in biomedicine. Berlin: Springer.

Sanchez, J., Corthals, G. and Hochstrasser, D. (2004). Biomedical applications of proteomics. Weinheim: Wiley-VCH.

Steuble, M. (2008). Proteomic analysis of calsyntenin-1 organelles and their functional and structural characterization.

Twyman, R. (2014). Principles of proteomics. New York: Garland Science.

Vékey, K., Telekes, A. and Vertes, A. (2008). Medical applications of mass spectrometry. Amsterdam: Elsevier.

Scroll to Top