Systemic vitamin intake impacting tissue proteomes
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Abstract:
The kinetics and localization of the reactions of metabolism are coordinated by the enzymes that catalyze them. These enzymes are controlled via a myriad of mechanisms including inhibition/activation by metabolites, compartmentalization, thermodynamics, and nutrient sensing-based transcriptional or post-translational regulation; all of which are influenced as a network by the activities of metabolic enzymes and have downstream potential to exert direct or indirect control over protein abundances. Considering many of these enzymes are active only when one or more vitamin cofactors are present; the availability of vitamin cofactors likely yields a systems-influence over tissue proteomes. Furthermore, vitamins may influence protein abundances as nuclear receptor agonists, antioxidants, substrates for post-translational modifications, molecular signal transducers, and regulators of electrolyte homeostasis. Herein, studies of vitamin intake are explored for their contribution to unraveling vitamin influence over protein expression. As a body of work, these studies establish vitamin intake as a regulator of protein abundance; with the most powerful demonstrations reporting regulation of proteins directly related to the vitamin of interest. However, as a whole, the field has not kept pace with advances in proteomic platforms and analytical methodologies, and has not moved to validate mechanisms of regulation or potential for clinical application.Keywords:
Clinical nutrition
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Reference proteomes are generated by increasingly sophisticated annotation pipelines as part of regular genome build releases; yet, the corresponding changes in reference proteomes' content are dramatic. In the history of the NCBI-curated human proteome, the total number of entries has remained roughly constant but approximately half of the proteins from the 2003 build 33 are no longer represented by entries in current releases, while about the same number of new proteins have been added (for sequence identity thresholds 50-90%). Although mostly hypothetical proteins are affected, there are also spectacular cases of entry removal/addition of well studied proteins. The changes between the 2003 and recent human proteomes are in a similar order of magnitude as the differences between recent human and chimpanzee proteome releases. As an application example, we show that the proteome fluctuations affect the interpretation (about 74% of hits) of organelle-specific mass-spectrometry data. Although proteome quality tends to improve with more recent releases as, for example, the fraction of proteins with functional annotation has increased over time, existing evidence implies that, apparently, the proteome content still remains incomplete, not just pertaining to isoforms/sequence variants but also to proteins and their families that are clearly distinct.
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Abstract Motivation: The SWISS-PROT group at the EBI has developed the Proteome Analysis Database utilizing existing resources and providing comprehensive and integrated comparative analysis of the predicted protein coding sequencesof the complete genomes of bacteria, archaea and eukaryotes. The Proteome Analysis Database is accompanied by a program that has been designed to carry out interactive InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database. Availability: http://www.ebi.ac.uk/proteome/comparisons.html Contact: alex@ebi.ac.uk; proteome@ebi.ac.uk * To whom all correspondence should be addressed.
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The physical characteristics of proteins are fundamentally important in organismal function. We used the complete predicted proteomes of >100 organisms spanning the three domains of life to investigate the comparative biology and evolution of proteomes. Theoretical 2D gels were constructed with axes of protein mass and charge (pI) and converted to density estimates comparable across all types and sizes of proteome. We asked whether we could detect general patterns of proteome conservation and variation. The overall pattern of theoretical 2D gels was strongly conserved across all life forms. Nevertheless, coevolved replicons from the same organism (different chromosomes or plasmid and host chromosomes) encode proteomes more similar to each other than those from different organisms. Furthermore, there was disparity between the membrane and nonmembrane subproteomes within organisms (proteins of membrane proteomes are on the average more basic and heavier) and their variation across organisms, suggesting that membrane proteomes evolve most rapidly. Experimentally, a significant positive relationship independent of phylogeny was found between the predicted proteome and Biolog profile, a measure associated with the ecological niche. Finally, we show that, for the smallest and most alkaline proteomes, there is a negative relationship between proteome size and basicity. This relationship is not adequately explained by AT bias at the DNA sequence level. Together, these data provide evidence of functional adaptation in the properties of complete proteomes.
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Proteome analysis is usually performed by separating complex cellular protein extracts by two‐dimensional‐electrophoresis followed by protein identification using mass spectrometry. In this way proteins are compared from normal and diseased tissue in order to detect disease related protein changes. In a strict sense, however, this procedure cannot be called proteome analysis: the tools of proteomics are used just to detect some interesting proteins which are then investigated by protein chemistry as usual. Real proteome research would be studying the cellular proteome as a whole, its composition, organization and its kind of action. At present however, we have no idea how a proteome works as a whole; we have not even a theory about that. If we would know how the proteome of a cell type is arranged, we probably would alter our strategy to detect and analyze disease‐related proteins. I will present a theory of proteomics and show some results from our laboratory which support this theory. The results come from investigations of the mouse brain proteome and include mouse models for neurodegenerative diseases.
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The Proteome Analysis Databases (PAD) (http://www.ebi.ac.uk/proteome/) is a very useful tool for giving simultaneously the key representative proteomes of archean and bacterium as well as three eukaryotic kingdoms, i.e., animal, plant and fungus. Moreover, it integrates the information of higher structures of proteins interested. This paper introduces the structure and function of Proteome Analysis, then our study on the erythrocruorin with the Proteome Analysis, finally, a few interested results obtained even though it is rather preliminary.
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In this study,Dongnong 46 was chosen as the experimental material.During its growth period,four kinds of plant growth regulators(TIBA,RE,SBS and DTA- 6) were used to spray the leaves of Dongnong 46.Through the observation of the submicroscopic structure of the soybean storage cells,it could be found that at R6stage,TIBA took a part in the proteome aggregating process.Under the SBS treatment,the proteome were turned to out of shape and there were more starch grains in the storage cells.RE and DTA-6 increased the number of proteome and lipid bodies obviously.At R7stage,the effects of TIBA on the aggregation of proteome were not evident,while it increased the number of lipid bodies and made them arranged more closely.In the samples with RE treatment,there were still more proteome and lipid bodies in the storage cells.In the SBS treated samples,there were more starch grains and proteome.The number of proteome in the storage cells was increased and their shape and size were heterogeneity after DTA-6 treated,the average diameters of proteome were larger than the control groups.At R8stage,the substances were rich in the storage cells and the sizes of proteome were larger.In the RE,SBS and DTA-6 treated samples,more proteome existed in the storage cells.In RE groups,the proteome were arranged more closely.In DTA-6 groups,the size of proteome increased,however,there were still unconverted starch grains in the storage cells,indicating that DTA-6 had slowed the degradation and conversion speed of the starch grains.In SBS treated groups,the lipid bodies were arranged loosely in the storage cells,but in RE and TIBA groups,the lipid bodies were full and arranged closely.This experiment showed that the plant growth regulators had a significant effect on the growth on soybean storage cells.In some certain stages of soybean growth,the purpose of increasing production and improving the quality could be achieved through spraying the four selected regulators.More specifically,in RE and DTA-6 treated samples,the production can be increased by 17% and 21.83%,respectively.The plants spraying with TIBA showed obvious influence on plant dwarf and stem strong,the height of the plants decreased from 28% to 30%,the capability of lodging-resistance were improved significantly.
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Identification of intrinsic disorder in proteins and proteomes has revealed important novel aspects of protein function and interactions. However, it has been pointed out that several oligomeric fibrillar protein motifs such as coiled coils and collagen triple helical segments can also identified as intrinsically disordered. This feature has not yet been investigated in more detail at the proteome level. The present work aims at the identification and quantification of such overlaps in full proteomes to assess their significance in large-scale studies of protein disorder. It was found that the percentage of cross-predicted residues is around 5% in the human proteome and is generally near that value in other metazoan ones but shows remarkable variation in different organisms. In particular, smaller proteomes are increasingly prone to such cross-predictions, thus, especially the analysis of viral proteomes requires the use of specific prediction tools.
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