518 resultados para PROTEOME
Resumo:
Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.
Resumo:
Since the development and prognosis of alcohol-induced liver disease (ALD) vary significantly with genetic background, identification of a genetic background-independent noninvasive ALD biomarker would significantly improve screening and diagnosis. This study explored the effect of genetic background on the ALD-associated urinary metabolome using the Ppara-null mouse model on two different backgrounds, C57BL/6 (B6) and 129/SvJ (129S), along with their wild-type counterparts. Reversed-phase gradient UPLC-ESI-QTOF-MS analysis revealed that urinary excretion of a number of metabolites, such as ethylsulfate, 4-hydroxyphenylacetic acid, 4-hydroxyphenylacetic acid sulfate, adipic acid, pimelic acid, xanthurenic acid, and taurine, were background-dependent. Elevation of ethyl-β-d-glucuronide and N-acetylglycine was found to be a common signature of the metabolomic response to alcohol exposure in wild-type as well as in Ppara-null mice of both strains. However, increased excretion of indole-3-lactic acid and phenyllactic acid was found to be a conserved feature exclusively associated with the alcohol-treated Ppara-null mouse on both backgrounds that develop liver pathologies similar to the early stages of human ALD. These markers reflected the biochemical events associated with early stages of ALD pathogenesis. The results suggest that indole-3-lactic acid and phenyllactic acid are potential candidates for conserved and pathology-specific high-throughput noninvasive biomarkers for early stages of ALD.
Resumo:
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.
Resumo:
Abstract Purpose: To further evaluate the use of microbeam irradiation (MBI) as a potential means of non-invasive brain tumor treatment by investigating the induction of a bystander effect in non-irradiated tissue. Methods: Adult rats were irradiated with 35 or 350 Gy at the European Synchotron Research Facility (ESRF), using homogenous (broad beam) irradiation (HI) or a high energy microbeam delivered to the right brain hemisphere only. The proteome of the frontal lobes were then analyzed using two-dimensional electrophoresis (2-DE) and mass spectrometry. Results: HI resulted in proteomic responses indicative of tumourigenesis; increased albumin, aconitase and triosphosphate isomerase (TPI), and decreased dihydrolipoyldehydrogenase (DLD). The MBI bystander effect proteomic changes were indicative of reactive oxygen species mediated apoptosis; reduced TPI, prohibitin and tubulin and increased glial fibrillary acidic protein (GFAP). These potentially anti-tumourigenic apoptotic proteomic changes are also associated with neurodegeneration. However the bystander effect also increased heat shock protein (HSP) 71 turnover. HSP 71 is known to protect against all of the neurological disorders characterized by the bystander effect proteome changes. Conclusions: These results indicate that the collective interaction of these MBI-induced bystander effect proteins and their mediation by HSP 71, may confer a protective effect which now warrants additional experimental attention.
Resumo:
The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology. We present a graph theoretic approach to test the significance of the association between multiple disparate sources of functional genomics data by proposing two statistical tests, namely edge permutation and node label permutation tests. We demonstrate the use of the proposed tests by finding significant association between a Gene Ontology-derived "predictome" and data obtained from mRNA expression and phenotypic experiments for Saccharomyces cerevisiae. Moreover, we employ the graph theoretic framework to recast a surprising discrepancy presented in Giaever et al. (2002) between gene expression and knockout phenotype, using expression data from a different set of experiments.
Resumo:
BACKGROUND: The quality of platelet concentrates (PCs) is primarily determined in vitro by selective methods (e.g., pH, aggregometry), which provide only limited information on certain platelet (PLT) characteristics. In contrast, proteomic technologies provide a comprehensive overview of the PLT proteome. High interassay variability, however, limits meaningful assessment of samples taken from the same product over time or before and after processing. STUDY DESIGN AND METHODS: Differential in-gel electrophoresis (DIGE) and mass spectrometry were applied to analyze changes in the PLT proteome during storage of PCs. RESULTS: DIGE provides a comprehensive and reproducible overview of the cytoplasmic PLT proteome (median standard deviation of protein spot intensities, 5%-9%). Although 97 percent of cytosolic PLT proteins remained unchanged over a 9-day storage period, septin 2 showed characteristic alterations that preceded by several days more widespread alterations affecting numerous other proteins. Also beta-actin and gelsolin are potential marker proteins for changes in the PLT proteome. Interestingly septin 2 and gelsolin are affected during apoptosis, indicating that apoptosis in PCs may have an impact on PLT storage. CONCLUSION: DIGE is a tool for comprehensively assessing the impact of storage on the global proteome profile of therapeutic PCs. Most of the changes detected are in high-abundance PLT proteins.
Resumo:
BACKGROUND ; AIMS: Pancreatic and bile duct carcinomas represent highly aggressive malignancies that evolve from secretin receptor-rich ductular cells. With premessenger RNA splicing abnormalities common in cancer, we evaluated whether an abnormal secretin receptor spliceoform were present, characterized it, and developed a serum assay for it. METHODS: Cancer cell lines and healthy and neoplastic tissue were studied by nested reverse-transcription polymerase chain reaction and sequencing. A promising spliceoform was isolated and characterized, and monoclonal antibodies were raised to 2 distinct regions. A dual antibody enzyme-linked immunosorbent assay was developed and applied to blinded serum samples from 26 patients with pancreatic carcinoma, 10 patients with chronic pancreatitis, and 14 controls. RESULTS: Each of 9 pancreatic cancer specimens and no normal tissue expressed a secretin receptor variant with exons 3 and 4 deleted. This encoded a 111-residue peptide with its first 43 residues identical to wild-type receptor, but, subsequent to a shift in coding frame and early truncation, the next 68 residues were unique in the transcriptome/proteome. This nonfunctional soluble protein did not bind or signal in response to secretin and was secreted from transfected MiaPaCa-2 cells. Elevated serum levels of this variant were present in 69% of pancreatic cancer patients, 60% of chronic pancreatitis patients, and 1 of 14 controls. CONCLUSIONS: We identified a novel abnormal spliceoform of the secretin receptor in pancreatic and bile duct cancers and developed a dual antibody sandwich enzyme-linked immunosorbent assay to measure it in the circulation. Initial application of this assay in patients with pancreatic cancer and chronic pancreatitis was promising, but additional validation will be required to evaluate its clinical utility.
Resumo:
Cu is an essential nutrient for man, but can be toxic if intakes are too high. In sensitive populations, marginal over- or under-exposure can have detrimental effects. Malnourished children, the elderly, and pregnant or lactating females may be susceptible for Cu deficiency. Cu status and exposure in the population can currently not be easily measured, as neither plasma Cu nor plasma cuproenzymes reflect Cu status precisely. Some blood markers (such as ceruloplasmin) indicate severe Cu depletion, but do not inversely respond to Cu excess, and are not suitable to indicate marginal states. A biomarker of Cu is needed that is sensitive to small changes in Cu status, and that responds to Cu excess as well as deficiency. Such a marker will aid in monitoring Cu status in large populations, and will help to avoid chronic health effects (for example, liver damage in chronic toxicity, osteoporosis, loss of collagen stability, or increased susceptibility to infections in deficiency). The advent of high-throughput technologies has enabled us to screen for potential biomarkers in the whole proteome of a cell, not excluding markers that have no direct link to Cu. Further, this screening allows us to search for a whole group of proteins that, in combination, reflect Cu status. The present review emphasises the need to find sensitive biomarkers for Cu, examines potential markers of Cu status already available, and discusses methods to identify a novel suite of biomarkers.
Resumo:
Proteomics describes, analogous to the term genomics, the study of the complete set of proteins present in a cell, organ, or organism at a given time. The genome tells us what could theoretically happen, whereas the proteome tells us what does happen. Therefore, a genomic-centered view of biologic processes is incomplete and does not describe what happens at the protein level. Proteomics is a relatively new methodology and is rapidly changing because of extensive advances in the underlying techniques. The core technologies of proteomics are 2-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry. Proteomic approaches might help to close the gap between traditional pathophysiologic and more recent genomic studies, assisting our basic understanding of cardiovascular disease. The application of proteomics in cardiovascular medicine holds great promise. The analysis of tissue and plasma/serum specimens has the potential to provide unique information on the patient. Proteomics might therefore influence daily clinical practice, providing tools for diagnosis, defining the disease state, assessing of individual risk profiles, examining and/or screening of healthy relatives of patients, monitoring the course of the disease, determining the outcome, and setting up individual therapeutic strategies. Currently available clinical applications of proteomics are limited and focus mainly on cardiovascular biomarkers of chronic heart failure and myocardial ischemia. Larger clinical studies are required to test whether proteomics may have promising applications for clinical medicine. Cardiovascular surgeons should be aware of this increasingly pertinent and challenging field of science.
Resumo:
Therapeutic intravenous immunoglobulin (IVIg) preparations contain antibodies reflecting the cumulative antigen experience of the donor population. IVIg contains variable amounts of monomeric and dimeric IgG, but there is little information available on their comparative antibody specificities. We have isolated highly purified fractions of monomeric and dimeric IgG by size-exclusion chromatography. Following treatment of all fractions at pH4, analyses by immunodot and immunocytology on human cell lines showed a preferential recognition of autoantigens in the dimeric IgG fraction. Investigation of the HEp-2 cytoplasmic proteome by 2D-PAGE, Western blot, and subsequent identification of IVIg reactive spots by mass spectrometry (LC-MS/MS) showed that IVIg recognized only a restricted set of the total proteins. Similar experiments showed that more antigens were recognized by the dimeric IgG fraction, especially when the dissociated dimer fraction was used, as compared to its monomeric counterpart. These observations are consistent with idiotype-anti-idiotype masking of auto-specific Abs in the dimeric fraction of IVIg.
Resumo:
Flagellar-mediated motility is an indispensable function for cell types as evolutionarily distant as mammalian sperm and kinetoplastid parasites, a large group of flagellated protozoa that includes several important human pathogens. Despite the obvious importance of flagellar motility, little is known about the signalling processes that direct the frequency and wave shape of the flagellar beat, or those that provide the motile cell with the necessary environmental cues that enable it to aim its movement. Similarly, the energetics of the flagellar beat and the problem of a sufficient ATP supply along the entire length of the beating flagellum remain to be explored. Recent proteome projects studying the flagella of mammalian sperm and kinetoplastid parasites have provided important information and have indicated a surprising degree of similarities between the flagella of these two cell types.
Resumo:
ABSTRACT: BACKGROUND: Many parasitic organisms, eukaryotes as well as bacteria, possess surface antigens with amino acid repeats. Making up the interface between host and pathogen such repetitive proteins may be virulence factors involved in immune evasion or cytoadherence. They find immunological applications in serodiagnostics and vaccine development. Here we use proteins which contain perfect repeats as a basis for comparative genomics between parasitic and free-living organisms. RESULTS: We have developed Reptile http://reptile.unibe.ch, a program for proteome-wide probabilistic description of perfect repeats in proteins. Parasite proteomes exhibited a large variance regarding the proportion of repeat-containing proteins. Interestingly, there was a good correlation between the percentage of highly repetitive proteins and mean protein length in parasite proteomes, but not at all in the proteomes of free-living eukaryotes. Reptile combined with programs for the prediction of transmembrane domains and GPI-anchoring resulted in an effective tool for in silico identification of potential surface antigens and virulence factors from parasites. CONCLUSION: Systemic surveys for perfect amino acid repeats allowed basic comparisons between free-living and parasitic organisms that were directly applicable to predict proteins of serological and parasitological importance. An on-line tool is available at http://genomics.unibe.ch/dora.
Resumo:
Trypanosoma brucei rhodesiense and T. b. gambiense are the causative agents of sleeping sickness, a fatal disease that affects 36 countries in sub-Saharan Africa. Nevertheless, only a handful of clinically useful drugs are available. These drugs suffer from severe side-effects. The situation is further aggravated by the alarming incidence of treatment failures in several sleeping sickness foci, apparently indicating the occurrence of drug-resistant trypanosomes. Because of these reasons, and since vaccination does not appear to be feasible due to the trypanosomes' ever changing coat of variable surface glycoproteins (VSGs), new drugs are needed urgently. The entry of Trypanosoma brucei into the post-genomic age raises hopes for the identification of novel kinds of drug targets and in turn new treatments for sleeping sickness. The pragmatic definition of a drug target is, a protein that is essential for the parasite and does not have homologues in the host. Such proteins are identified by comparing the predicted proteomes of T. brucei and Homo sapiens, then validated by large-scale gene disruption or gene silencing experiments in trypanosomes. Once all proteins that are essential and unique to the parasite are identified, inhibitors may be found by high-throughput screening. However powerful, this functional genomics approach is going to miss a number of attractive targets. Several current, successful parasiticides attack proteins that have close homologues in the human proteome. Drugs like DFMO or pyrimethamine inhibit parasite and host enzymes alike--a therapeutic window is opened only by subtle differences in the regulation of the targets, which cannot be recognized in silico. Working against the post-genomic approach is also the fact that essential proteins tend to be more highly conserved between species than non-essential ones. Here we advocate drug targeting, i.e. uptake or activation of a drug via parasite-specific pathways, as a chemotherapeutic strategy to selectively inhibit enzymes that have equally sensitive counterparts in the host. The T. brucei purine salvage machinery offers opportunities for both metabolic and transport-based targeting: unusual nucleoside and nucleobase permeases may be exploited for selective import, salvage enzymes for selective activation of purine antimetabolites.
Resumo:
To identify components of the copper homeostatic mechanism of Lactococcus lactis, we employed two-dimensional gel electrophoresis to detect changes in the proteome in response to copper. Three proteins upregulated by copper were identified: glyoxylase I (YaiA), a nitroreductase (YtjD), and lactate oxidase (LctO). The promoter regions of these genes feature cop boxes of consensus TACAnnTGTA, which are the binding site of CopY-type copper-responsive repressors. A genome-wide search for cop boxes revealed 28 such sequence motifs. They were tested by electrophoretic mobility shift assays for the interaction with purified CopR, the CopY-type repressor of L. lactis. Seven of the cop boxes interacted with CopR in a copper-sensitive manner. They were present in the promoter region of five genes, lctO, ytjD, copB, ydiD, and yahC; and two polycistronic operons, yahCD-yaiAB and copRZA. Induction of these genes by copper was confirmed by real-time quantitative PCR. The copRZA operon encodes the CopR repressor of the regulon; a copper chaperone, CopZ; and a putative copper ATPase, CopA. When expressed in Escherichia coli, the copRZA operon conferred copper resistance, suggesting that it functions in copper export from the cytoplasm. Other member genes of the CopR regulon may similarly be involved in copper metabolism.
Resumo:
In this study, we isolated eight copper-resistant bacteria from Torch Lake sediment contaminated by copper mine tailings (stamp sand). Sequence analysis of gyrB and rpoD genes revealed that these organisms are closer to various Pseudomonas species. These eight bacterial isolates were also resistant to zinc, cesium, lead, arsenate and mercury. Further characterization showed that all the strains produced plant growth promoting indole-3-acetic acid (IAA), iron chelating siderophore and solubilized mineral phosphate and metals. The effect of bacterial inoculation on plant growth and copper uptake by maize (Zea mays) and sunflower (Helianthus annuus) was investigated using one of the isolates (Pseudomonas sp. TLC 6-6.5-4) with higher IAA production and phosphate and metal soubilization, which resulted in a significant increase in copper accumulation in maize and sunflower, and an increase in the total biomass of maize. Genes involved in copper resistance of Pseudomonas sp. TLC 6-6.5-4 was analyzed by transposon mutational analysis. Two copper sensitive mutants with significant reduction in copper resistance were identified: CSM1, a mutant disrupted in trp A gene (tryptophan synthase alpha subunit); CSM2, a mutant disrupted in clpA gene (ATP-dependent Clp protease). Proteomic and metabolomic analysis were performed to identify biochemical and molecular mechanisms involved in copper resistance using CSM2 due to its lower minimum inhibitory concentration compared with CSM1 and the wild type. The effect of different bacterial inoculation methods on plant growth, copper uptake and soil enzyme activities was investigated. Four different delivery methods were used including soil inoculation (before or after plant emergence), seed coating and root dipping. Soil inoculation before sowing seeds and coating seeds with PGPB led to better growth of maize, higher copper uptake and an increase in soil invertase and dehydrogenase activities. Proteomic and metabolomic analyses were performed to investigate the effect of bacterial inoculation on maize grown in normal soil and stamp sand. Our results revealed that bacterial inoculation led to environment-dependent effects on maize proteome and metabolome.